Neurobiology of mental illness [3e edition] 9780199798261, 9780199398461, 0199398461, 0199798265, 9780199857548, 0199857547, 9780199934966, 0199934967, 9781283098335, 1283098334

Table of contents :
Sect. I. Introduction to basic neuroscience --
sect. II. New methods and new technologies for preclinical and clinical neurobiology --
sect. III. Psychotic disorders --
sect. IV. Mood disorders --
sect. V. Anxiety disorders --
sect. VI. Substance use disorders --
sect. VII. Dementia --
sect. VIII. Psychiatric disorders of childhood onset --
sect. IX. Special topic areas.

Citation preview

Neurobiology of Mental Illness

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NEUROBIOLOGY OF MENTAL ILLNESS Third Edition Edited by

DENNIS S. CHARNEY, M.D. Dean, Mount Sinai School of Medicine Executive Vice President for Academic Affairs The Mount Sinai Medical Center Anne and Joel Ehrenkranz Professor Departments of Psychiatry, Neuroscience, and Pharmacology & Systems Therapeutics Mount Sinai School of Medicine New York, New York

ERIC J. NESTLER, M.D., Ph.D. Chair of Neuroscience Director of the Mount Sinai Brain Institute Nash Family Professor of Neuroscience Mount Sinai School of Medicine New York, New York

SECTION EDITORS Eric J. Nestler, M.D., Ph.D. Carol A. Tamminga, M.D. Jeffrey A. Lieberman, M.D. Charles B. Nemeroff, M.D., Ph.D. Antonia S. New, M.D. Steven E. Hyman, M.D. Mary Sano, Ph.D. Daniel S. Pine, M.D.

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1 Oxford University Press, Inc., publishes works that further Oxford University’s objective of excellence in research, scholarship, and education. Oxford New York Auckland Cape Town Dar es Salaam Hong Kong Karachi Kuala Lumpur Madrid Melbourne Mexico City Nairobi New Delhi Shanghai Taipei Toronto With offices in Argentina Austria Brazil Chile Czech Republic France Greece Guatemala Hungary Italy Japan Poland Portugal Singapore South Korea Switzerland Thailand Turkey Ukraine Vietnam

Copyright © 2009 by Oxford University Press, Inc. Published by Oxford University Press, Inc. 198 Madison Avenue, New York, New York 10016 www.oup.com First issued as an Oxford University Press paperback, 2011 Oxford is a registered trademark of Oxford University Press All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Oxford University Press. Library of Congress Cataloging-in-Publication Data Neurobiology of mental illness / edited by Dennis S. Charney, Eric J. Nestler. — 3rd ed. p. ; cm. Includes bibliographical references and index. ISBN 978-0-19-979826-1 1. Neuropsychiatry. 2. Mental illness—Physiological aspects. I. Charney, Dennis S. II. Nestler, Eric J. (Eric Jonathan), 1954[DNLM: 1. Mental Disorders—etiology. 2. Mental Disorders—physiopathology. 3. Mental Disorders—therapy. 4. Neurobiology. WM 140 N9495 2009] RC341.N393 2009 616.8—dc22 2008025739

987654321 Printed in the United States of America on acid-free paper

Preface

Psychiatry stands poised to make dramatic advances in defining disease pathogenesis, developing diagnostic methods capable of identifying specific and valid disease entities, discovering novel and more effective treatments, and ultimately preventing psychiatric disorders. Publishing the third edition of Neurobiology of Mental Illness within 5 years of publication of the second edition is a testament to the progress that has been made in our field. For this third edition, all the chapters have been thoroughly updated and new chapters have been added in areas where significant advances have been made. As before, Part I provides an overview of basic neuroscience that is relevant to clinical psychiatry or to expanding its foundations. Molecular neurobiology and molecular genetics are emphasized in the context of brain development, neuronal function, and neural networks and their contribution to complex behaviors. A chapter has been added on epigenetic mechanisms in psychiatry based on recent advances in understanding the influence of chromatin regulation on normal behavior as well as abnormalities in behavior seen in major psychiatric disorders. Part II reviews and evaluates the methods used to examine the neurobiological basis of mental illness in humans. This part has been expanded to reflect critically important advances in the techniques of cognitive neuroscience, procedures for the postmortem investigation of the human brain, and current approaches to drug discovery. The chapters in this part provide a context for recent findings from neuroimaging studies that have related specific genes to the regulation of emotion. Further, an understanding of the methods underlying drug discovery will facilitate the translation of preclinical

and clinical neuroscience research into badly needed breakthroughs in our therapeutic toolkit. The remaining parts of the book cover the neurobiology of psychiatric disorders: psychoses, mood disorders, anxiety disorders, substance abuse disorders, dementias, disorders of childhood onset, and special topic areas. These parts have been augmented in several different areas as a reflection of research progress. New chapters have been added on epidemiology, animal models, different forms of dementia, mental retardation, neuropsychiatry, and developmental therapeutics. Current diagnostic classification systems are limited because they are based primarily on phenomenology rather than etiology and pathophysiology. We predict that the research advances reviewed in the parts on psychiatric disorders will ultimately lead to diagnostic systems in which genetic and neurobiological abnormalities have a primary role. This edition of Neurobiology of Mental Illness reflects the continuing reintegration of psychiatry into the mainstream of biomedical science. The research tools that are transforming other branches of medicine— epidemiology, genetics, molecular biology, imaging, and medicinal chemistry—are also transforming psychiatry. It is our hope that, like us, the reader is optimistic that the progress in molecular, cellular, and behavioral neuroscience described in this textbook will eventually break new ground in the diagnosis, treatment, and prevention of disabling psychiatric disorders. D.S.C. New York, New York E.J.N. New York, New York

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Contents

Contributors, xi

PART I

INTRODUCTION TO BASIC NEUROSCIENCE

Section Editor: Eric J. Nestler Introduction: Eric J. Nestler 1. Overview of Brain Development, 3 John L.R. Rubenstein and Stewart A. Anderson 2. Neurochemical Systems in the Central Nervous System, 12 Ariel Y. Deutch and Robert H. Roth 3. Using Basic Electrophysiology to Understand the Neurobiology of Mental Illness, 29 Evelyn K. Lambe and George K. Aghajanian 4. Principles of Signal Transduction, 41 Jean-Antoine Girault and Paul Greengard 5. Mechanisms of Neural Plasticity, 66 Eric J. Nestler and Steven E. Hyman 6. Principles of Molecular Biology, 76 Steven E. Hyman and Eric J. Nestler 7. Functional Genomics and Models of Mental Illness, 88 Lisa M. Monteggia, William A. Carlezon Jr., and Ralph J. DiLeone 8. Epigenetics of Psychiatric Diseases, 104 Bryan E. McGill and Huda Y. Zoghbi

PART II

METHODS OF CLINICAL NEUROBIOLOGICAL RESEARCH

Section Editor: Carol A. Tamminga Introduction: Carol A. Tamminga 9. Contributions of Epidemiology to the Neurobiology of Mental Illness, 131 Kathleen R. Merikangas and Amanda Kalaydjian

10. Basic Methods for Clinical Molecular Genetics of Psychiatric Illness, 144 Joel Gelernter and Jaakko Lappalainen 11. Neurocognitive Assessment for Psychiatric Disorders, 158 Michael F. Green, Junghee Lee, and Robert S. Kern 12. Cognitive Neuroscience: Bridging Thinking and Feeling to the Brain, and its Implications for Psychiatry, 168 Cameron S. Carter, John G. Kerns, and Jonathan D. Cohen 13. Neuroimaging Methods using Nuclear Magnetic Resonance, 179 Hanzhang Lu and Yihong Yang 14. Molecular Brain Imaging Research in Mental Illness, 192 Jong-Hoon Kim, Diana Martinez, Mark Slifstein, and Anissa Abi-Dargham 15. Human Postmortem Brain Research in Mental Illness Syndromes, 202 Monica Beneyto, Etienne Sibille, and David A. Lewis 16. Neuroimmunology, 215 John M. Petitto, Dean G. Cruess, Martin J. Repetto, David R. Gettes, Tami D. Benton, and Dwight L. Evans 17. Drug Discovery and Development Methods for Mental Illness, 225 Gary D. Tollefson

PART III

PSYCHOSES

Section Editor: Jeffrey A. Lieberman Introduction: Jeffrey A. Lieberman 18. Diagnosis of Schizophrenia, 241 Michael B. First 19. Genetics of Schizophrenia, 252 Xiangning Chen, Brien Riley, and Kenneth S. Kendler

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20. Neurobiological Theories of Schizophrenia, 266 David A. Lewis and David W. Volk 21. Postmortem and In Vivo Structural Pathology in Schizophrenia, 281 Andrew J. Dwork, John F. Smiley, Tiziano Colibazzi, and Matthew J. Hoptman 22. Cognitive Neuroscience and Neuroimaging in Schizophrenia, 303 Aysenil Belger and Deanna M. Barch 23. The Neurochemistry of Schizophrenia: A Focus on Dopamine and Glutamate, 321 Anissa Abi-Dargham 24. Principles of the Pharmacotherapy of Schizophrenia, 329 Carol A. Tamminga

33. Abnormalities of Brain Structure and Function in Mood Disorders, 515 Victoria Arango and J. John Mann 34. Novel Targets for Antidepressant Treatments, 530 Olivier Berton and Eric J. Nestler 35. The Neurobiology of Menstrual CycleRelated Mood Disorders, 544 David R. Rubinow, Peter J. Schmidt, Samantha Meltzer-Brody, and Veronica Harsh 36. Depression and Medical Illness, 556 Tami D. Benton, Paul Crits-Christoph, Benoit Dubé, and Dwight L. Evans

PART V PART IV

MOOD DISORDERS

Section Editor: Charles B. Nemeroff Introduction: Charles B. Nemeroff 25. Diagnostic Classifications of Mood Disorders: Historical Context and Implications for Neurobiology, 351 S. Nassir Ghaemi and Frederick K. Goodwin 26. Genetics of Mood Disorders, 360 Falk W. Lohoff and Wade H. Berrettini 27. Animal Models of Mood Disorders, 378 Inge Sillaber, Florian Holsboer, and Carsten T. Wotjak 28. Cellular Plasticity Cascades: Genes to Behavior Pathways in the Pathophysiology and Treatment of Bipolar Disorder, 392 Lisa A. Catapano, Guang Chen, Jing Du, Carlos A. Zarate, Jr., and Husseini K. Manji 29. Neurochemical Theories of Depression: Preclinical Studies, 413 Ronald S. Duman 30. The Neurochemistry of Depressive Disorders: Clinical Studies, 435 Boadie W. Dunlop, Steven J. Garlow, and Charles B. Nemeroff 31. Neuroimaging Studies of Mood Disorders, 461 Wayne C. Drevets, Kishore M. Gadde, and K. Ranga R. Krishnan 32. Principles of the Pharmacotherapy of Depression, 491 Robert M. Berman, Jonathan Sporn, Dennis S. Charney, and Sanjay J. Mathew

ANXIETY DISORDERS

Section Editor: Antonia S. New Introduction: Antonia S. New and Dennis S. Charney 37. Diagnostic Classification of Anxiety Disorders: DSM-V and Beyond, 575 Murray B. Stein and O. Joseph Bienvenu 38. The Molecular Genetics of Anxiety Disorders, 585 Steven P. Hamilton and Abby J. Fyer 39. The Neurobiology of Fear and Anxiety: Contributions of Animal Models to Current Understanding, 603 Gregory M. Sullivan, Jacek Debiec, David E.A. Bush, David M. Lyons, and Joseph E. LeDoux 40. Stress-Induced Structural and Functional Plasticity in the Brain: Protection, Damage, and Brain–Body Communication, 627 Bruce S. McEwen 41. The Neurobiology of Anxiety Disorders, 655 Amir Garakani, James W. Murrough, Dennis S. Charney, and J. Douglas Bremner 42. The Neurobiology and Treatment of Obsessive-Compulsive Disorder, 691 Susan E. Swedo and Paul Grant 43. Neuroimaging Studies of Anxiety Disorders, 703 Justine M. Kent and Scott L. Rauch 44. Pharmacotherapy of Anxiety Disorders, 731 Sanjay J. Mathew, Ellen J. Hoffman, and Dennis S. Charney

CONTENTS

PART VI

SUBSTANCE ABUSE DISORDERS

Section Editor: Steven E. Hyman Introduction: Steven E. Hyman

58. Abnormalities in Brain Structure on Postmortem Analysis of Dementia, 958 Daniel P. Perl

45. Animal Models of Addiction, 757 Eliot L. Gardner and Roy A. Wise

59. Functional Brain Imaging Studies in Dementia, 971 Monte S. Buchsbaum, Adam Brickman, Jing Zhang, and Erin A. Hazlett

46. Cellular and Molecular Mechanisms of Drug Addiction, 775 Eric J. Nestler

60. Principles of the Pharmacotherapy of Dementia, 987 Christine Bergmann and Mary Sano

47. Genetic Epidemiology of Substance Use Disorders, 786 Kathleen R. Merikangas and Kevin P. Conway

61. Cognitive Impairment in Demyelinating Disease, 1001 Thomas M. Hyde

48. Effects of Drugs of Abuse on Brain Development, 801 Barry M. Lester and Barry E. Kosofsky 49. PET and SPECT Imaging in Substance Abuse Research, 828 Joanna S. Fowler and Nora D. Volkow 50. Brain Reward and fMRI, 846 P. Read Montague and Pearl H. Chiu 51. Principles of the Pharmacotherapy of Addictive Disorders, 867 Charles P. O’Brien and Charles Dackis

62. Dementia with Lewy Bodies, 1010 David J. Burn, Elaine K. Perry, John T. O’Brien, Neil Archibald, Elizabeta B. Mukaetova-Ladinska, Joaquim Cerejeira, Daniel Collerton, Evelyn Jaros, Robert Perry, Margaret A. Piggott, Chris M. Morris, Andrew McLaren, Clive G.Ballard, and Ian G. McKeith 63. Dementia in Parkinson’s Disease, 1032 Martin Goldstein and C. Warren Olanow 64. Mild Cognitive Impairment, 1066 Brendan J. Kelley and Ronald C. Petersen

PART VII

DEMENTIA

Section Editor: Mary Sano Introduction: Mary Sano 52. The Genetics and Pathogenesis of Alzheimer’s Disease and Related Dementia, 883 John A. Hardy

65. Frontotemporal Dementia, 1082 Steven Z. Chao, Indre Viskontas, and Bruce L. Miller 66. Vascular Dementia, 1090 Nancy Nielsen-Brown and Helena C. Chui

53. Diagnostic Classifications: Relationship to the Neurobiology of Dementia, 895 Daniel I. Kaufer and Steven T. DeKosky

PART VIII

54. Transgenic Models of Dementias, 908 Gregory A. Elder

Section Editor: Daniel S. Pine Introduction: Daniel S. Pine

PSYCHIATRIC DISORDERS OF CHILDHOOD ONSET

55. Functional Neuroanatomy of Learning and Memory, 920 Gary L. Wenk

67. The Neurobiology of Intellectual Disabilities, 1105 Antonio Y. Hardan and Allan L. Reiss

56. Neurochemical Systems Involved in Learning and Memory, 927 Joanne Berger-Sweeney, Laura R. Schaevitz, and Karyn M. Frick

68. Cognitive Neuroscience Approaches to Typical and Atypical Development, 1120 B.J. Casey and Sarah Durston

57. Neuropathological and Neuroimaging Studies of the Hippocampus in Normal Aging and in Alzheimer’s Disease, 936 Effie M. Mitsis, Matthew Bobinski, Miroslaw Brys, Lidia Glodzik-Sobanska, Susan DeSanti, Yi Li, Byeong-Chae Kim, Lisa Mosconi, and Money J. de Leon

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69. The Neurobiology of Impulsivity and Self-Regulatory Control in Children with Attention-Deficit/Hyperactivity Disorder, 1129 Kerstin J. Plessen and Bradley S. Peterson 70. Childhood Anxiety Disorders: A Cognitive Neurobiological Perspective, 1153 Christopher S. Monk and Daniel S. Pine

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71. Molecular Genetics of Childhood and Adolescent Onset Psychiatric Disorders, 1173 Jeremy M. Veenstra-VanderWeele, Randy D. Blakely, and Edwin H. Cook, Jr. 72. Pediatric Bipolar Disorder, 1187 Ellen Leibenluft 73. Neurobiology of Child and Adolescent Depression, 1197 Joan Kaufman, Andrés Martin, and Hilary Blumberg 74. Structural Magnetic Resonance Imaging of Typical Pediatric Brain Development, 1209 Jay N. Giedd, Samantha L. White, and Mark Celano 75. Tourette’s Syndrome and Tic-Related Disorders in Children, 1218 Paul J. Lombroso, Michael H. Bloch, and James F. Leckman 76. The Neurobiology of Childhood Psychotic Disorders, 1230 Nitin Gogtay and Judith Rapoport 77. Developmental Perspectives on Psychopathology, 1239 Michael Rutter 78. Neurobiology of Autism and the Pervasive Developmental Disorders, 1251 Sarah Spence, Paul Grant, Audrey Thurm, and Susan E. Swedo

PART IX

SPECIAL TOPIC AREAS

Section Editor: Antonia S. New 79. Neuropsychiatry: The Border Between Neurology and Psychiatry, 1273 William M. McDonald and Michael S. Okun 80. The Neurobiology of Personality Disorders, 1286 Antonia S. New, Joseph Triebwasser, and Marianne Goodman 81. The Neurobiology of Aggression, 1307 R. J. R. Blair 82. Sexual Dysfunction and Pharmacological Treatments: Biological Interactions, 1321 Stuart N. Seidman, Steven P. Roose, and

Raymond C. Rosen 83. The Neurobiology of Social Attachment, 1337 Thomas R. Insel and James T. Winslow 84. The Neurobiology of Eating Disorders, 1349 Walter Kaye, Michael Strober, and David Jimerson 85. The Neurobiology of Sleep, 1370 Giulio Tononi and Chiara Cirelli 86. The Neurobiology of Resilience, 1387 Margaret Haglund, Paul Nestadt, Nicole S. Cooper, Steven Southwick, and Dennis S. Charney 87. A Brief History of Neural Evolution, 1410 Daniel R. Wilson Index, 1429

Contributors*

Anissa Abi-Dargham, M.D.

Tami D. Benton, M.D.

Departments of Psychiatry and Radiology Columbia University College of Physicians and Surgeons New York, NY

Department of Psychiatry University of Pennsylvania Philadelphia, PA

George K. Aghajanian, M.D.

Joanne Berger-Sweeney, Ph.D.

Departments of Psychiatry and Pharmacology Yale School of Medicine New Haven, CT

Department of Neuroscience Wellesley College Wellesley, MA

Stewart A. Anderson, M.D.

Christine Bergmann, M.D., Ph.D.

Departments of Psychiatry and Neuroscience Weill Cornell Medical College Cornell University Ithaca, NY

Victoria Arango, Ph.D. Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Robert M. Berman, M.D. Department of Psychiatry Columbia University New York, NY

Neil Archibald, M.A., B.M.B.Ch., MRCP

Wade H. Berrettini, M.D., Ph.D.

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Department of Psychiatry University of Pennsylvania School of Medicine Philadelphia, PA

Clive G. Ballard, M.D.

Olivier Berton, Ph.D.

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Department of Psychiatry University of Texas Southwestern Medical Center at Dallas Dallas, TX

Deanna M. Barch, Ph.D.

O. Joseph Bienvenu, M.D., Ph.D.

Departments of Psychiatry and Psychology Washington University in St. Louis St. Louis, MO

Department of Psychiatry and Behavioral Science Johns Hopkins University School of Medicine Baltimore, MD

Aysenil Belger, Ph.D.

R.J.R. Blair, Ph.D.

Department of Psychiatry University of North Carolina at Chapel Hill Chapel Hill, NC

National Institute of Mental Health National Institutes of Health Bethesda, MD

Monica Beneyto, Ph.D.

Randy D. Blakely, Ph.D.

Department of Psychiatry University of Pittsburgh School of Medicine Pittsburgh, PA

Departments of Pharmacology and Psychiatry Vanderbilt University Nashville, TN

* Visit www.NMI3_disclosures.com for details of contributors’ disclosures.

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CONTRIBUTORS

Michael H. Bloch, M.D.

Cameron S. Carter, M.D.

Department of Psychiatry Yale School of Medicine New Haven, CT

Department of Psychiatry and Behavioral Sciences University of California, Davis Sacramento, CA

Hilary Blumberg, M.D.

B.J. Casey, Ph.D.

Departments of Psychiatry and Diagnostic Radiology Yale School of Medicine New Haven, CT

Department of Psychiatry Weill Cornell Medical College New York, NY

Matthew Bobinski, M.D., Ph.D.

Lisa A. Catapano, Ph.D.

Department of Radiology University of California Davis Health System Sacramento, CA

National Institute of Mental Health National Institutes of Health Bethesda, MD

J. Douglas Bremner, M.D.

Mark Celano

Departments of Psychiatry and Radiology Emory University School of Medicine Atlanta, GA

National Institute of Mental Health National Institutes of Health Bethesda, MD

Adam Brickman, Ph.D.

Joaquim Cerejeira

Department of Neurology Columbia University College of Physicians and Surgeons New York, NY

Miroslaw Brys, M.D., Ph.D. Department of Research New York University School of Medicine New York, NY

Monte S. Buchsbaum, M.D. Department of Psychiatry Mount Sinai School of Medicine New York, NY

David J. Burn, M.D. Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

David E. A. Bush Center for Neural Science New York University New York, NY

President Associação Portuguesa de Internos de Psiquiatria Coimbra, Portugal

Steven Z. Chao, M.D., Ph.D. Department of Neurology University of California, San Francisco San Francisco, CA

Dennis S. Charney, M.D. Department of Psychiatry, Neuroscience, and Pharmacology & Systems Therapeutics Mount Sinai School of Medicine New York, NY

Guang Chen, M.D., Ph.D. National Institute of Mental Health National Institutes of Health Bethesda, MD

Xiangning Chen, Ph.D. Department of Psychiatry Virginia Commonwealth University Richmond, VA

Tiziano Colibazzi, M.D.

Pearl H. Chiu, Ph.D.

Department of Psychiatry Columbia University New York, NY

Department of Neuroscience Baylor College of Medicine Houston, TX

William A. Carlezon, Jr., Ph.D.

Helena C. Chui, M.D.

Departments of Psychiatry and Neuroscience Harvard Medical School Belmont, MA

Department of Neurology School of Medicine of University of Southern California Los Angeles, CA

CONTRIBUTORS

Chiara Cirelli, M.D., Ph.D.

Steven T. DeKosky, M.D.

Department of Psychiatry University of Wisconsin, Madison Madison, WI

Department of Neurology University of Pittsburgh School of Medicine Pittsburgh, PA

Jonathan D. Cohen, M.D., Ph.D.

Mony J. de Leon, Ed.D

Princeton Neuroscience Institute Princeton University Princeton, NJ

Department of Psychiatry New York University School of Medicine New York, NY

Tiziano Colibazzi, M.D.

Susan DeSanti, Ph.D.

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

Department of Psychiatry New York University School of Medicine New York, NY

Daniel Collerton, M.Sc.

Ariel Y. Deutch, Ph.D.

Newcastle Biomedicine Newcastle University Newcastle upon Tyne, UK

Departments of Psychiatry and Pharmacology Vanderbilt University Medical Center Nashville, TN

Kevin P. Conway, Ph.D.

Ralph J. DiLeone, Ph.D.

National Institute of Drug Abuse National Institute of Mental Health Bethesda, MD

Department of Psychiatry Yale School of Medicine New Haven, CT

Edwin H. Cook, Jr., M.D.

Wayne C. Drevets, M.D.

Department of Psychiatry University of Illinois at Chicago Chicago, IL

National Institute of Mental Health National Institutes of Health Bethesda, MD

Nicole S. Cooper, Ph.D.

Jing Du, M.D., Ph.D.

Department of Psychiatry Mount Sinai School of Medicine New York, NY

National Institute of Mental Health National Institutes of Health Bethesda, MD

Paul Crits-Christoph, Ph.D.

Benoit Dube, M.D.

Department of Psychiatry University of Pennsylvania Medical School Philadelphia, PA

Department of Psychiatry University of Pennsylvania Philadelphia, PA

Dean G. Cruess, Ph.D.

Ronald S. Duman, Ph.D.

Department of Psychology University of Connecticut Storrs, CT

Departments of Psychiatry and Pharmacology Yale School of Medicine New Haven, CT

Charles Dackis, M.D.

Boadie W. Dunlop, M.D.

Department of Psychiatry University of Pennsylvania Philadelphia, PA

Department of Psychiatry & Behavioral Sciences Emory University School of Medicine Atlanta, GA

Jacek Debiec, M.D., Ph.D.

Sarah Durston, Ph.D.

Center for Neural Science New York University New York, NY

Department of Child and Adolescent Psychiatry University Medical Center Utrecht Utrecht, The Netherlands

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CONTRIBUTORS

Andrew J. Dwork, M.D.

Joel Gelernter, M.D.

Departments of Pathology and Psychiatry Columbia University New York, NY

Department of Psychiatry Yale School of Medicine New Haven, CT

Gregory A. Elder, M.D.

David R. Gettes

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Department of Psychiatry University of Pennsylvania Philadelphia, PA

Dwight L. Evans, M.D.

S. Nassir Ghaemi, M.D.

Departments of Psychiatry, Medicine, and Neuroscience University of Pennsylvania Philadelphia, PA

Department of Psychiatry Emory University Atlanta, GA

Michael B. First, M.D.

Jay N. Giedd, M.D.

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

National Institute of Mental Health National Institutes of Health Bethesda, MD

Joanna S. Fowler, Ph.D.

Jean-Antoine Girault, M.D., Ph.D.

Chemistry Department Brookhaven National Laboratory Upton, NY

Inserm and Pierre & Marie Curie University Institut du Fer a Moulin Paris, France

Karyn M. Frick, Ph.D.

Lidia Glodzik-Sobanska, M.D., Ph.D.

Department of Psychology Yale University New Haven, CT

Department of Psychiatry NYU Center for Brain Health New York, NY

Abby J. Fyer, M.D.

Nitin Gogtay, M.D.

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

National Institute of Mental Health National Institutes of Health Bethesda, MD

Kishore M. Gadde, M.D.

Martin Goldstein, M.D.

Department of Psychiatry Duke University Medical Center Durham, NC

Department of Neurology Mount Sinai School of Medicine New York, NY

Amir Garakani, M.D.

Marianne Goodman, M.D.

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Eliot L. Gardner, M.D.

Frederick K. Goodwin, M.D.

National Institute on Drug Abuse National Institutes of Health Bethesda, MD

Department of Psychiatry George Washington University Washington, DC

Steven J. Garlow, M.D., Ph.D.

Paul Grant, M.D.

Department of Psychiatry & Behavioral Sciences Emory University School of Medicine Atlanta, GA

National Institute of Mental Health National Institutes of Health Bethesda, MD

CONTRIBUTORS

Michael F. Green, Ph.D.

Steven E. Hyman, M.D.

Department of Psychiatry and Biobehavioral Sciences University of California, Los Angeles Los Angeles, CA

Office of the Provost Harvard University Cambridge, MA

Paul Greengard, Ph.D.

Thomas R. Insel, M.D.

Laboratory of Molecular and Cellular Neuroscience The Rockefeller University New York, NY

National Institute of Mental Health National Institutes of Health Bethesda, MD

Margaret Haglund, M.D.

Evelyn Jaros, Ph.D.

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Steven P. Hamilton, M.D., Ph.D.

David Jimerson, M.D.

Department of Psychiatry University of California, San Francisco San Francisco, CA

Department of Psychiatry Harvard Medical School Boston, MA

Antonio Y. Hardan, M.D. Department of Psychiatry and Behavioral Science Stanford University School of Medicine Stanford, CA

John A. Hardy, Ph.D. National Institute on Aging National Institutes of Health Bethesda, MD

Veronica Harsh, M.D. National Institute of Mental Health National Institutes of Health Bethesda, MD

Erin A. Hazlett, Ph.D. Department of Psychiatry Mount Sinai School of Medicine New York, NY

Ellen J. Hoffman, M.D. Department of Psychiatry Mount Sinai School of Medicine New York, NY

Amanda Kalaydjian, Ph.D. Department of Mental Health at the Bloomberg School of Public Health Johns Hopkins University Baltimore, MD

Daniel I. Kaufer, M.D. Department of Neurology University of North Carolina, Chapel Hill Chapel Hill, NC

Joan Kaufman, Ph.D. Department of Psychiatry Yale University School of Medicine New Haven, CT

Walter Kaye, M.D. Department of Psychiatry University of Pittsburgh Medical School Pittsburgh, PA

Brendan J. Kelley, M.D.

Florian Holsboer, M.D., Ph.D.

Department of Neurology May Medical School Rochester, MN

Max Planck Institute of Psychiatry Munich, Germany

Kenneth S. Kendler, M.D.

Matthew J. Hoptman, Ph.D. Department of Psychiatry New York University New York, NY

Departments of Psychiatry and Human and Molecular Genetics Virginia Commonwealth University Richmond, VA

Justine M. Kent, M.D. Thomas M. Hyde, M.D., Ph.D. National Institute of Mental Health National Institutes of Health Bethesda, MD

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

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CONTRIBUTORS

Robert S. Kern, Ph.D.

Ellen Leibenluft, M.D.

Department of Psychiatry and Biobehavioral Sciences University of California, Los Angeles Los Angeles, CA

National Institute of Mental Health National Institutes of Health Bethesda, MD

John G. Kerns, Ph.D.

Yi Li, M.D.

Department of Psychological Sciences University of Missouri-Columbia Columbia, MO

Department of Psychiatry New York University School of Medicine New York, NY Department of Radiology Qi Lu Hospital Shandog University China

Byeong-Chae Kim, M.D., Ph.D. Department of Neurology Chonnam National University Medical School Korea

Jong-Hoon Kim, M.D. Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

Jeffrey A. Lieberman, M.D. Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

Barry M. Lester, Ph.D. Barry E. Kosofsky, M.D., Ph.D. Department of Pediatrics Weill Cornell Medical College New York, NY

Department of Psychiatry Brown University Providence, RI

David A. Lewis, M.D. K. Ranga R. Krishnan, M.D. Department of Psychiatry and Behavioral Sciences Duke University School of Medicine Durham, NC

Departments of Psychiatry and Neuroscience University of Pittsburgh School of Medicine Pittsburgh, PA

Falk W. Lohoff, M.D. Evelyn K. Lambe, Ph.D. Departments of Physiology and Obstetrics and Gynaecology University of Toronto Toronto, Canada

Department of Psychiatry University of Pennsylvania Philadelphia, PA

Paul J. Lombroso, M.D. Jaakko Lappalainen, M.D., Ph.D. Pharmacogenetics and Clinical Research, Discovery Medicine AstraZeneca Pharmaceuticals Wilmington, DE

Departments of Psychiatry and Neurobiology Yale School of Medicine New Haven, CT

Hanzhang Lu, Ph.D. James F. Leckman, M.D. Department of Psychiatry Yale School of Medicine New Haven, CT

Advance Imaging Research Center University of Texas Southwestern Medical Center Dallas, TX

Joseph E. LeDoux, Ph.D.

David M. Lyons, Ph.D.

Center for Neural Science New York University New York, NY

Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA

Junghee Lee, Ph.D.

Husseini K. Manji, M.D.

Department of Psychology Vanderbilt University Nashville, TN

National Institute of Mental Health National Institutes of Health Bethesda, MD

CONTRIBUTORS

J. John Mann, M.D.

Bruce L. Miller, M.D.

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

Departments of Neurology and Psychiatry University of California, San Francisco San Francisco, CA

Andrés Martin, M.D., M.P.H.

Effie M. Mitsis

Department of Psychiatry Yale School of Medicine New Haven, CT

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Diana Martinez, M.D.

Christopher S. Monk, Ph.D.

Department of Psychiatry Columbia University Medical Center New York, NY

Department of Psychology University of Michigan Ann Arbor, MI

Sanjay J. Mathew, M.D.

P. Read Montague, Ph.D.

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Departments of Neuroscience and Psychiatry Baylor College of Medicine Houston, TX

William M. McDonald, M.D.

Lisa M. Monteggia, Ph.D.

Department of Psychiatry and Behavioral Sciences Emory University Atlanta, GA

Department of Psychiatry The University of Texas Southwestern Medical Center Dallas, TX

Bruce S. McEwen, Ph.D. Harold and Margaret Milliken Hatch Laboratory of Neuroendocrinology The Rockefeller University New York, NY

Chris M. Morris, Ph.D.

Bryan E. McGill, M.D., Ph.D.

Lisa Mosconi, Ph.D.

Department of Pediatrics Washington University St. Louis School of Medicine St. Louis, MO

Department of Psychiatry New York School of Medicine New York, NY

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Elizabeta B. Mukaetova-Ladinska, M.D., Ph.D. Ian G. McKeith, M.D. Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

James W. Murrough, M.D. Andrew McLaren, MRCP Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Charles B. Nemeroff, M.D., Ph.D. Samantha Meltzer-Brody, M.D. Department of Psychiatry University of North Carolina at Chapel Hill School of Medicine Chapel Hill, NC

Department of Psychiatry and Behavioral Sciences Emory University School of Medicine Atlanta, GA

Kathleen R. Merikangas, Ph.D.

Paul Nestadt, B.S.

National Institute of Mental Health National Institutes of Health Bethesda, MD

School of Medicine New York Medical College New York, NY

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CONTRIBUTORS

Eric J. Nestler, M.D., Ph.D.

Bradley S. Peterson, M.D.

Department of Neuroscience Mount Sinai School of Medicine New York, NY

Department of Psychiatry Columbia College of Physicians and Surgeons New York, NY

Antonia S. New, M.D.

John M. Petitto, M.D.

Department of Psychiatry Mount Sinai School of Medicine New York, NY

Departments of Psychiatry, Nueroscience and Pharmacology University of Florida College of Medicine Gainesville, FL

Nancy Nielsen-Brown, M.S., PA-C

Margaret A. Piggott, Ph.D.

College of Allied Health Professions Western University of Health Sciences Pomona, CA

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Charles P. O’Brien, M.D., Ph.D.

Daniel S. Pine, M.D.

Department of Psychiatry University of Pennsylvania Philadelphia, PA

National Institute of Mental Health National Institutes of Health Bethesda, MD

John T. O’Brien, M.D.

Kerstin J. Plessen, M.D., Ph.D.

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Center for Child and Adolescent Mental Health University of Bergen Bergen, Norway

Michael S. Okun, M.D.

Judith Rapoport, M.D.

Departments of Neurology and Neurosurgery University of Florida Gainesville, FL

National Institute of Mental Health National Institutes of Health Bethesda, MD

C. Warren Olanow, M.D.

Scott L. Rauch, M.D.

Department of Neurology Mount Sinai School of Medicine New York, NY

Department of Psychiatry Harvard Medical School Boston, MA

Daniel P. Perl, M.D.

Allan L. Reiss, M.D.

Department of Neuropathology Mount Sinai School of Medicine New York, NY

Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford, CA

Elaine K. Perry, BSc, Ph.D., DSc

Martin J. Repetto, M.D., Ph.D.

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Department of Psychiatry University of Florida College of Medicine Gainesville, FL

Robert Perry, PRCP, FRCPath

Brien Riley, Ph.D.

Institute for Ageing and Health Newcastle University Newcastle upon Tyne, UK

Department of Psychiatry Virginia Commonwealth University Richmond, VA

Ronald C. Petersen, M.D., Ph.D.

Steven P. Roose, M.D.

Department of Neurology Mayo Medical School Rochester, MN

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

CONTRIBUTORS

Raymond C. Rosen, Ph.D.

Mark Slifstein, Ph.D.

Department of Psychiatry University of Medicine and Dentistry of New Jersey Piscataway, NJ

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

Robert H. Roth, Ph.D.

John F. Smiley, Ph.D.

Departments of Psychiatry and Pharmacology Yale School of Medicine New Haven, CT

Nathan S. Kline Institute for Psychiatric Research Orangeburg, NY

Steven Southwick, M.D. John L.R. Rubenstein, M.D., Ph.D. Langley Porter Psychiatric Institute University of California, San Francisco San Francisco, CA

Department of Psychiatry Yale School of Medicine New Haven, CT

Sarah Spence, M.D. David R. Rubinow, M.D. Department of Psychiatry University of North Carolina at Chapel Hill School of Medicine Chapel Hill, NC

National Institute of Mental Health National Institutes of Health Bethesda, MD

Jonathan Sporn, M.D. Michael Rutter, M.D. Institute of Psychiatry King’s College, London London, UK

Department of Psychiatry Massachusetts General Hospital Boston, MA

Murray B. Stein, M.D., M.P.H. Mary Sano, Ph.D. Department of Psychiatry Mount Sinai School of Medicine New York, NY

Department of Psychiatry University of California, San Diego La Jolla, CA

Michael Strober, Ph.D. Laura R. Schaevitz, Ph.D. Department of Biological Sciences Wellesley College Wellesley, MA

Department of Psychiatry David Geffen School of Medicine at UCLA Los Angeles, CA

Gregory M. Sullivan, M.D. Peter J. Schmidt, M.D. National Institute of Mental Health National Institutes of Health Bethesda, MD

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

Stuart N. Seidman, M.D.

Susan E. Swedo, M.D.

Department of Psychiatry Columbia University College of Physicians and Surgeons New York, NY

National Institute of Mental Health National Institutes of Health Bethesda, MD

Etienne Sibille, Ph.D.

Carol A. Tamminga, M.D.

Department of Psychiatry University of Pittsburgh Pittsburgh, PA

Department of Psychiatry The University of Texas Southwestern Medical Center Dallas, TX

Inge Sillaber, Ph.D.

Audrey Thurm, Ph.D.

Behavioural Pharmacology Affectis Pharmaceuticals Munich, Germany

National Institute of Mental Health National Institutes of Health Bethesda, MD

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CONTRIBUTORS

Gary D. Tollefson, M.D., Ph.D.

Daniel R. Wilson, M.D., Ph.D.

Department of Psychiatry Indiana School of Medicine Indianapolis, IN

Department of Psychiatry Creighton University Omaha, NE

Giulio Tononi, M.D., Ph.D. Department of Psychiatry University of Wisconsin, Madison Madison, WI

James T. Winslow, M.D. National Institute of Mental Health National Institutes of Health Bethesda, MD

Joseph Triebwasser, M.D. Bronx Veterans Administration Medical Center Bronx, NY

Roy A. Wise, M.D.

Jeremy M. Veenstra-VanderWeele, M.D.

National Institute on Drug Abuse National Institutes of Health Bethesda, MD

Department of Psychiatry Vanderbilt University Nashville, TN

Carsten T. Wotjak, Ph.D.

Indre Viskontas, Ph.D. Department of Neurology University of California, San Francisco San Francisco, CA

David W. Volk, M.D., Ph.D. Department of Psychiatry University of Pittsburgh School of Medicine Pittsburgh, PA

Neuronal Plasticity Max Planck Institute of Psychiatry Munich, Germany

Yihong Yang, Ph.D. National Institute on Drug Abuse National Institutes of Health Bethesda, MD

Carlos A. Zarate, Jr., M.D. Nora D. Volkow, M.D. National Institute on Drug Abuse National Institutes of Health Bethesda, MD

Gary L. Wenk, Ph.D. Department of Psychology and Neuroscience The Ohio State University Columbus, OH

National Institute of Mental Health National Institutes of Health Bethesda, MD

Jing Zhang, M.D. National Institute on Aging National Institutes of Health Bethesda, MD

Samantha L. White, M.D.

Huda Y. Zoghbi, M.D.

National Institute of Mental Health National Institutes of Health Bethesda, MD

Department of Neuroscience Baylor College of Medicine Houston, TX

I

INTRODUCTION TO BASIC NEUROSCIENCE ERIC J. NESTLER

T

HE first part of this book provides an overview of basic neuroscience and molecular biology. Each chapter represents an enormous body of material that could itself be the subject of an entire textbook. Accordingly, these chapters are not intended to be comprehensive reviews, but rather concise summaries of the fields that lay the foundation of basic biological principles required for the clinical material that is the main focus of the book. Chapter 1 provides an overview of brain development. There is increasing evidence that certain neuropsychiatric disorders may involve abnormalities in the formation of the nervous system. Although the details of such abnormalities remain obscure, the chapter provides insights into the cellular and molecular processes that may be involved and the ways in which such processes can be influenced by genetic and external factors. Chapter 2 describes the neurochemical organization of the brain. It summarizes the diverse types of molecules that neurons in the brain use as neurotransmitters and neurotrophic factors, and how these molecules are synthesized and metabolized. The chapter also presents the array of receptor proteins through which these molecules regulate target neuron functioning and the reuptake proteins that generally terminate the neurotransmitter signal. Today a large majority of all drugs used to treat psychiatric disorders, as well as most drugs of abuse, still have as their initial targets proteins involved directly in neurotransmitter function. Chapter 3 summarizes the electrophysiological basis of neuronal function. Ultimately, brain function is mediated by interactions between nerve cells, and the readout of such interactions is an alteration in the electrical properties of the cells. The chapter reviews the several types of recording techniques that are commonly used to measure neuronal activity, followed by a presentation of the many types of ion channels and receptors that control a neuron’s electrophysiological responses. Chapter 4 covers postreceptor intracellular messenger cascades through which neurotransmitters and neurotrophic factors, and their receptors, produce their diverse

physiological effects. A major advance over the past generation of research has been an appreciation of the complex webs of intracellular signaling pathways that control every aspect of a neuron’s functioning, from neurotransmitter signaling to cell shape and motility to gene expression. Although only a small number of medications used in psychiatry today have as their initial target intracellular signaling proteins, it is likely that drug development efforts will look increasingly to such proteins for the discovery of novel medications with fundamentally new mechanisms of action. Chapter 5 describes prominent mechanisms of neural plasticity, that is, ways in which neurons adapt over time in response to environmental perturbations. It is this capacity for adaptation (or maladaptation) that makes it possible for the brain to not only learn and think but also for the brain to get sick. The chapter focuses on protein phosphorylation as a prominent molecular basis of neural plasticity. The ways in which protein phosphorylation mechanisms contribute to adaptive and maladaptive changes in the brain are discussed. Chapter 6 provides an overview of the genetic basis of the nervous system. The chapter covers the structure of DNA and chromatin in the nucleus, how genes encode messenger RNAs and proteins, and the mechanisms (for example, alternative splicing and posttranslational processing) by which numerous proteins can be generated from individual genes. The chapter also describes how this process of gene expression is under dynamic regulation throughout the adult life of an organism via the regulation of transcription factors and other nuclear proteins, and how such mechanisms contribute in important ways to long-lived neural plasticity. Chapter 7 offers a progress report on new tools developed by molecular biologists to manipulate the expression of genes in the nervous system. Through the use of tools such as viral-mediated gene transfer and inducible mutations in mice, scientists are able to manipulate genes in the brain with increasing spatial and temporal precision. Such tools are essential as we strive to better understand the contribution of individual genes to complex behavior.

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INTRODUCTION TO BASIC NEUROSCIENCE

Chapter 8, new to this third edition, covers epigenetic mechanisms in psychiatry. Epigenetic regulation in neurons describes a process in which the activity of a particular gene is controlled by the structure of chromatin in that gene’s proximity. Recent work has demonstrated the dynamic nature of chromatin remodeling in the nervous system and its importance for the normal development of the nervous system as well as the brain’s capacity to adapt over time to environmental challenges. Abnormalities in chromatin remodeling have also been implicated in several neurological and psychiatric disorders. A great deal has been written recently about the need for translational research in psychiatry. Yet we all know how uniquely difficult translational research is in our field. This is due to several factors, including the unique complexity of the brain, the lack of ready access to the brains of our patients, and the apparent complexity of at

least some psychiatric disorders with respect to etiology and pathophysiology. As a result, it is currently difficult, if not impossible, to relate most of the material covered in this first part of the book to studies of the clinical disorders. How does one study, for example, the transcription factor cyclic adenosine monophosphate response element binding protein (CREB) or changes in dendritic spine density implicated in animal models of several psychiatric conditions, in living patients? We view this difficulty, though very real today, as a time-limited obstacle. As advances in human genetics and brain imaging progress, it will become possible to analyze diverse neurotransmitter and neurotrophic factor systems, intracellular signaling proteins, and even gene expression profiles in our patients and ultimately within discrete brain regions implicated in disease pathophysiology. Such methodologies will complete psychiatry’s transformation into a field of modern molecular medicine.

1 Overview of Brain Development JOHN L.R. RUBENSTEIN

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There is increasing evidence that abnormalities in the development of the brain either predispose or directly cause certain psychiatric disorders. Although it is not surprising that childhood disorders, such as autism, are caused by neurodevelopmental abnormalities, disorders that display their most characteristic symptoms during or after adolescence also may be influenced by developmental abnormalities that occurred in utero. For instance, numerous lines of evidence suggest that some cases of schizophrenia are the result of abnormal neurodevelopment. Thus, there is a compelling rationale for behavioral scientists and clinicians to understand the basic mechanisms that regulate assembly of the brain, as this information may be key to understanding the etiology and perhaps even the prevention and treatment of major psychiatric disorders. This chapter highlights the major processes involved in development of the brain to provide the reader with a foundation for understanding developmental neuroscience. The chapter briefly surveys neurodevelopment, from induction of the central nervous system (CNS) to patterning of the primordia of major brain regions, proliferation of neuroepithelial cells, differentiation and migration of immature neurons and glia, formation of axon tracts and synapses, and concludes with the establishment and plasticity of neuronal networks. Although most of the information described in this chapter is based upon studies in nonprimate mammals, it is likely that these findings are also true in the developing human brain. INDUCTION AND PATTERNING OF THE EMBRYONIC CNS Early CNS development involves an ordered sequence of inductive processes that begin with the formation of the neural plate followed by a hierarchical series of inductions that lead to regionally distinct developmental programs (for a more extensive review on this subject, see Rubenstein and Puelles, 2003). Inductive processes generally involve two tissues. One tissue is the target of the induction; the other, called the organizer, produces the molecular signals that carry out the induction. These molecular signals, which generally are proteins, induce

STEWART A. ANDERSON

in the target tissues a new pattern of gene expression that dictates their subsequent developmental program. Development of the CNS begins during gastrulation by a process called neural induction. Proteins produced by organizer tissues cause the embryonic ectoderm to differentiate into a neural fate. This process involves activation of receptor tyrosine kinases, perhaps through fibroblast growth factors (FGFs) and /or insulin-like growth factors (IGFs) (Streit et al., 2000; Wilson and Rubenstein, 2000; Pera et al., 2001) and inhibition of transforming growth factor-b (TGF-b) signaling through the noggin and chordin proteins that bind to bone morphogenetic proteins (BMPs) (de Robertis et al., 2000; Wilson and Edlund, 2001). In addition, wingless (WNT) signaling is implicated in inhibiting neural induction in some species (Wilson and Edlund, 2001). Induction of the neural ectoderm leads to the formation of the neural plate, which will give rise to the entire CNS (Fig. 1.1); its lateral edges will give rise to the neural crest, which gives rise to most of the peripheral nervous system (PNS) and contributes to the head skeleton. Beginning during neural induction, inductive processes subdivide the neural plate into molecularly distinct domains that are the primordia of the major subdivisions of the CNS. One can distinguish three types of inductive processes during CNS regionalization: (1) anteriorposterior or A-P, (2) mediolateral or M-L, and (3) local. The A-P regionalization subdivides the neural plate into transverse domains. The principal transverse subdivisions of the brain are the prosencephalon (forebrain), mesencephalon (midbrain), and rhombencephalon (hindbrain) (Fig. 1.2). Further refinements of A-P regionalization subdivide the rhombencephalon into segment-like domains called neuromeres (rhombomeres). The forebrain may also have neuromeric subdivisions called prosomeres. The inductive mechanisms underlying A-P regionalization are poorly understood but probably include vertical inductions (from underlying tissues) from mesoderm and endoderm (via substances such as the protein cereberus) and planar inductions (from substances that transmit their effects in the plane of the neural plate), perhaps from the node (via substances such as retinoids). The M-L regionalization produces distinct tissues that are longitudinally aligned along the long axis of the CNS (Fig. 1.1). Medial inductions are regulated by 3

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INTRODUCTION TO BASIC NEUROSCIENCE

FIGURE 1.1 Schemes of the longitudinal organization of the forebrain proposed in Shimamura et al. (1995; see Rubenstein and Shimamura, 1997). (A) Model of the longitudinal domains in the neural plate, including the primordia of the floor, basal, alar, and roof plates (fp, bp, ap). Beneath the medial neural plate are the notochord and the prechordal plate. (B) Medial view of the neural tube. (C) Rostrolateral view of the neural tube. lt, lamina terminalis; os, optic stalk.

substances produced by axial mesodermal organizers: the notochord and prechordal plate. These organizers are midline structures that lie underneath the middle of the neural plate and produce substances, such as sonic hedgehog, that induce the medial neural plate to form the primordia of the floor plate and basal plate (Fig. 1.1). Lateral inductions are believed to be mediated by substances such as TGF-bs that include the BMPs that are produced along the rim of the neural plate by the nonneural ectoderm. Lateral inductions are likely to be essential for development of the neural crest, roof plate, and alar plate (Fig. 1.1). The combination of A-P and M-L patterning generates a checkerboard organization of brain subdivisions (Fig. 1.2), each of which expresses a distinct combination of regulatory genes. Superimposed on this pattern are the local inductive signals that are essential for the formation of the vesicles that evaginate from the brain such as the telencephalon, eyes, and posterior pituitary. Evidence suggests that signals originating from ectodermal tissues (lens placode, anterior neural ridge, and anterior pituitary, respectively) adjacent to these structures produce signals that induce their formation. Although the process of regionalization subdivides the neural plate into the primordia of the major brain regions, the process of morphogenesis transforms the shape of the neural plate into a tube that additionally has flexures and evaginations. Note that the folding of the neural plate into the neural tube converts the lateromedial

dimension of the neural plate into the dorsoventral (D-V) dimension of the neural tube (Fig. 1.1). A cross section through the D-V axis of the neural tube transects its four primary longitudinal subdivisions (Fig. 1.3). From ventral to dorsal, these longitudinal

FIGURE 1.2 Schemes of the embryonic 12.5-day mouse brain, in which

the primordia of some forebrain structures are labeled. In addition, longitudinal and transverse subdivisions are indicated. The paired telencephalic vesicles make up the majority of the forebrain and can be subdivided into the cortical and subcortical areas. The cortical region includes the neocortex, archicortex (hippocampus), and paleocortex (olfactory bulb and olfactory cortex). The subcortical areas include the striatum, globus pallidus, septum, and parts of the amygdala (not shown). Ventral to the telencephalon are the eyes and hypothalamic areas. Neuromeric (transverse) components are labeled in their basal plate: r1–r7: rhombomeres; p1–p6 are the theoretical prosomeres. This drawing is a modified version of the prosomeric model (e.g., see Rubenstein and Shimamura, 1997). is, isthmus; m, midbrain.

1: OVERVIEW OF BRAIN DEVELOPMENT

5

HISTOGENESIS OF BRAIN REGIONS: PROLIFERATION, CELL FATE DETERMINATION, MIGRATION, AND DIFFERENTIATION

FIGURE 1.3 Cross section of the D-V organization of the neural tube at the level of the spinal cord. The floor plate is induced by the notochord; together they produce sonic hedgehog protein, which induces motor neurons in the basal plate. Neural crest cells from the most dorsal alar plate form the spinal ganglia, including the dorsal root ganglia, which contain the primary sensory neurons. Secondary sensory neurons are in the alar plate. v, ventricle.

columns are the floor, basal, alar, and roof plates. Each of these longitudinal columns may extend along the entire A-P axis of the CNS and contribute to distinct functional elements of the nervous system. The basal plate is the primordia for the motor neurons. The alar plate is the primordia for the secondary sensory neurons. The floor plate, which does not produce any neurons, has several functions that are required during development. Like the notochord, the floor plate produces sonic hedgehog and is believed to serve as a secondary ventral (medial) organizer where it also, in combination with chemotropic molecules such as netrins, guides the growth of axon tracts (Okada et al., 2006). Most of the roof plate forms the nonneuronal dorsal midline, which in some regions gives rise to specialized structures such as the choroid plexus and the pineal gland. The roof plate is marked by its high expression of BMPs and WNTs. The regionalization process continues after neurulation (neural tube formation) to further subdivide large primordial regions into their constituent domains. These aspects of regionalization are probably carried out by planar inductive mechanisms via organizers that are within the neural tube. For example, secondary D-V patterning can be regulated by the floor plate (see the next section), whereas secondary A-P patterning can be regulated by the isthmus. The isthmus is a region between the mid- and hindbrain that produces inductive substances such as FGFs and WNT that regulate development of the midbrain and cerebellum.

The process of regionalization subdivides the CNS into the primordia of its major structures (for example, cerebral cortex, striatum, thalamus, cerebellum) and initiates within these primordia their genetic programs of histogenesis. Histogenesis is a complex process that can be subdivided into two general parts: proliferation and differentiation (for more extensive reviews of this subject, see Rakic, 1995; Alvarez-Buylla et al., 2001; Marin and Rubenstein, 2001; Kriegstein et al., 2006). In general, each of these processes takes place in distinct zones within the wall of the neural tube. Proliferation takes place in the ventricular zone (VZ), which lines the inner surface of the neural tube and is adjacent to the ventricular cavity, whereas differentiation takes place largely in the mantle, which surrounds the VZ (see Fig. 1.4). The VZ cells are undifferentiated and mitotically active. Each brain region has a distinct proliferation program that regulates the rate of cell division, the number of times VZ cells divide, and the character of the cell division. Cell division can be symmetrical, producing daughter cells that are identical, or asymmetrical, producing daughter cells that are nonidentical. Symmetrical divisions produce daughter cells that, like their mother, continue to proliferate or, unlike their mother, differentiate or die. Asymmetric division can produce one daughter cell that differentiates and one daughter cell that continues to proliferate. The regulation of these processes is integral to controlling how many cells are produced in each region

FIGURE 1.4 Organization of proliferative and differentiation zones

within the wall of the neural tube. This scheme shows developing cerebral neocortex. The proliferative zones (ventricular zone [VZ] and subventricular zone [SVZ]) are adjacent to the ventricle. Postmitotic cells migrate from the proliferation zones, through the intermediate zone (IZ), and stop migrating in the mantle, where differentiation is completed. The cerebral cortex is a laminar structure (six major layers); cells in the deeper layers (for example, layer 6) are generally born before cells in the superficial layers.

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INTRODUCTION TO BASIC NEUROSCIENCE

and when these cells are made. For example, the expansion of the cerebral cortex in primates may relate to increased numbers of symmetrical divisions of neuronproducing progenitors in the cortical subventricular zone (Kriegstein et al., 2006). There are many types of cells that make up the CNS. The two major classes are neurons and glia (Lemke, 2001). There are two major types of neurons: projection neurons, whose axons migrate to distant territories, and local circuit neurons (interneurons), whose processes ramify nearby. Within these general categories, there are many distinct types of projection and local circuit neurons that differ by neurochemistry, firing characteristics, and connectivity (Wonders and Anderson, 2006). There are two types of CNS-derived glia, astrocytes and oligodendrocytes, whereas the other major glial type, the microglia, is mesodermally derived (Colognato and French-Constant, 2004). Astrocytes regulate the local chemical milieu and appear to play a role in synaptogenesis (Allen and Barres, 2005). Oligodendrocytes produce the myelin sheaths that surround many axons; these sheaths function as insulators that increase the velocity of action potentials. Microglia are related to macrophages and subserve a phagocytic role in removing dead cells from the CNS. Early in development, the VZ contains proliferative cells that have the potential to produce neurons and glia. In general, neurogenesis precedes gliogenesis. Whereas most regions of the CNS can produce neurons and astrocytic glia, some regions are specialized for producing oligodendroglia. For instance, a small region of the ventral spinal cord that initially generates motor neurons later converts to producing oligodendrocytes (Richardson et al., 2006). Different types of neurons are generated at distinct D-V positions in the CNS. For instance, within the spinal cord, motor neurons are generated by ventral progenitors, whereas sensory neurons are generated by dorsal progenitors (Shirasaki and Pfaff, 2002). Likewise, in the telencephalon, ventral progenitors produce neurons of the basal ganglia, whereas dorsal progenitors produce cortical neurons. This arrangement is the result of the D-V patterning mechanisms described earlier in this chapter. Although patterning of the nervous system produces separate primordia of major brain regions (for example, cerebral cortex and basal ganglia), cell migration processes “mix” certain cell types between these primordia. The mechanisms underlying cell fate decisions in the nervous system involve molecules within the cells (intrinsic signals controlled by proteins such as transcription factors; see Chapter 6) as well as molecules outside of the cells (extrinsic signals controlled by proteins such as growth/differentiation factors and their receptors). These proteins have integral roles in regulating whether a cell continues to divide, whether it undergoes symmetrical

or asymmetrical division, whether the daughter cells go on to differentiate, and what lineage they will differentiate along. Notch signaling is an example of extrinsic control of differentiation and is mediated by Notch receptors and their ligands (for example, Delta) (Justice and Jan, 2002). Activation of Notch by its ligand biases a cell not to differentiate; thus neurogenesis requires inhibition of Notch signaling (Gaiano and Fishell, 2002). Thus, Notch signaling can control the rate and timing of neuron production. Furthermore, high levels of Notch signaling bias progenitors toward an astrocytic fate. Notch signaling activates a cascade of molecular switches that culminates in the induction of transcription factors that change gene expression in the differentiating cell (Bertrand et al., 2002). Although Notch signaling largely operates through basic helix-loop-helix transcription factors, many other types of transcription factors have central roles in brain development. These include Homeobox, Sox, T-box, Winged-Helix, and HMG-box families. Each family consists of subfamilies; for instance, key homeobox genes include Dlx, Emx, Nkx, Otx, Pax, and POU, which control such processes as regional fate, cell type identity, neuronal maturation, and cell migration (Briscoe et al., 2000; Wilson and Rubenstein, 2000). Once neurons are generated, the next step in their differentiation is migration to the appropriate destination (Ayala et al., 2007). Each brain region has a specific migration program. In cortical structures (for example, cerebral cortex and superior colliculus), migrations are orchestrated to form layered or laminar structures. In most subcortical regions, migrations form nuclear structures that generally are not laminar. There are two general types of migration: radial and tangential. Radial migration is movement perpendicular to the plane of the ventricle toward the pial surface; tangential migration is movement parallel to the plane of the ventricle. Radial migration involves the interaction between the elongated processes of radial glial cells and the migrating immature neurons. The immature neurons migrate to a specified location within the wall of the neural tube where they disengage from the radial glial cell and continue to differentiate. One of the key molecules regulating this process was identified through analysis of the reeler mutant mouse (Rice and Curran, 2001). In the cerebral cortex of reeler mice, later-born neurons fail to migrate past their earlier-born siblings, leading to partial inversion of the usual inside-out lamination. The reeler gene encodes a large, secreted molecule named reelin that appears to promote dissociation of neuroblasts from radial glia. Further mouse genetic studies have implicated two low-density lipoprotein receptors (VLDLR and ApoER2) as the receptors for the reelin molecule. In addition to radial migration of neurons, it is now clear that nervous system development also depends on

1: OVERVIEW OF BRAIN DEVELOPMENT

tangential migration. Tangential migration of neurons has long been known to occur in the cerebellum and in the rostral migratory stream (RMS) of the olfactory bulb, where adult neurogenesis is best characterized. Now it appears that many GABAergic local circuit neurons of the telencephalon are generated in the basal ganglia primordia and then tangentially migrate to the cerebral cortex and hippocampus (Marin and Rubenstein, 2001). This process results in mixing of gamma-aminobutyric acid (GABA)ergic neurons from the basal ganglia anlage with glutamatergic projection neurons of the cerebral cortex, thus allowing inhibitory regulation of excitatory transmission. Neuregulin1, a candidate gene for contributing risk of schizophrenia, has been identified as providing critical guidance cues for tangenially migrating interneurons (Flames et al., 2004). Progress has also been made in identifying genes that control cytoskeletal processes that are essential for migration. Several of these genes were first identified as causing neuronal migration defects in humans, including Lisencephaly-1, Doublecortin, and Filamin (Mochida and Walsh, 2004). The time when a neuron is born (the cell is no longer mitotically active and migrates away from the VZ) has an important influence on its fate (the type of neuron it becomes and its location within the brain). For instance, in the cerebral cortex, there are seven layers: layers 1, 2, 3, 4, 5, 6, and the subplate. Layer 1 is the most superficial, and the subplate is closest to the VZ. In the cerebral cortex, cells that are born first populate the deepest layers; this produces the so-called inside-out pattern of histogenesis. Each layer has distinct functions. For instance, the subplate is believed to provide signals that direct the incoming thalamic axons to their appropriate cortical target zone; layers 5 and 6 contain neurons that project out of the cortex; neurons in layer 4 receive input from the thalamus; neurons in layers 2 and 3 have intracortical projections; reelin-secreting layer 1 neurons participate in regulating cortical histogenesis by modulating the radial migration process (Tissir and Goffinet, 2003). WIRING OF THE BRAIN: FORMATION OF AXON PATHWAYS AND SYNAPSES As the immature neurons and glia migrate from the proliferative zone to the differentiation zone (the mantle), they elaborate more complex cellular structures. Neurons extend several thin processes away from their cell body; these include multiple dendrites and a single axon. Perhaps the most distinctive feature of the nervous system is how axon processes navigate long distances to find their targets (for a more extensive review of this subject see Tessier-Lavigne and Goodman, 1996; Grunwald and Klein, 2002; Charron and Tessier-Lavigne, 2005). The growing tip of the axon is called the growth cone.

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This dynamic web-like structure extends filopodia that appear to explore their environment, searching for cues that either attract or repel them. Molecules and their receptors have been identified that serve as chemoattractants or repellents for growing axons. Some of these molecules are long-range signals that instruct growing axons from a distance where to project. Other signals have local effects and provide more specific information to the axon concerning the path it should take. Some of these signals are found on the surface of glial cells that serve as guideposts for the axons. The first axon pathways that develop create a scaffold for later-arriving axons. Through a process called fasciculation, later-arriving axons can adhere to axons that are already in an axon pathway. Molecules on the surface of the axons, some of which are related to immunoglobulins, can regulate selective fasciculation to generate axon bundles with common properties. When an axon has reached its target, a process called defasciculation enables the axon to separate from the axon bundle. As axons grow and navigate, they express receptors for guidance molecules expressed by neighboring cells (Tessier-Lavigne and Goodman, 1996; Brose and Tessier-Lavigne, 2000; Yu and Bargmann, 2001). These processes operate as growth cones grow along specific pathways that in many cases involve crossing midline structures (commissures), such as the optic chiasm and corpus callosum. Activation of these receptors determines whether an axon grows toward or away from a target cell. At least four conserved families of guidance molecules have been identified. The semaphorins comprise a large 20-member family of soluble and membrane-bound molecules that elicit repulsive signals through two receptor families, neuropilins and plexins. The slit family of proteins consists of three members in mammals and acts through Robo receptors in commissural axons to prevent these axons from recrossing the midline. Whereas the slits and semaphorins are repulsive, members of the netrin family can be repulsive or attractive for a growth cone, depending upon the types of receptors expressed by the axon (receptor complexes containing either the colorectal cancer [DCC] or the neogenin protein lead to attraction; UNC-5-related protein leads to repulsion). Members of the ephrin family of ligands are membrane-bound and interact with two families of receptors, EphA and EphB (Kullander and Klein, 2002). EphrinB ligands, when bound to EphB receptors, are capable of bidirectional signaling whereby the cytoplasmic domain of the ephrin ligand transmits a phosphorylation signal. In addition to regulating axon pathfinding, semaphorins, slits, netrins, and ephrins control neuronal migrations. Upon reaching its target, the growth cone is further modified as it forms a part of the synapse (Sanes and Lichtman, 2001). Reciprocal signals between the growth

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INTRODUCTION TO BASIC NEUROSCIENCE

cone and the postsynaptic target cell induce the production of molecules and membranous specializations found in synapses (Benson et al., 2001). For instance, the presynaptic cells produce synaptic vesicles filled with neurotransmitters, and the postsynaptic cells form dendrites with specialized domains containing neurotransmitter receptors (Jan and Jan, 2001). Both cells express the channels and other components required for the initiation and propagation of action potentials. In the 1950s, Levi Montalcini discovered nerve growth factor (NGF), the first of four so-called neurotrophins that provide signals that control such processes as neuronal survival and synapse strength (Huang and Reichardt, 2001). By the end of the 1980s the neurotrophic hypothesis was firmly entrenched, and it suggested that postsynaptic cells are responsible for releasing neurotrophins that the presynaptic neuronal process was attracted to via its expression of a so-called Trk receptor. The amount of neurotrophin released by a given cell determined whether a cell reached a given target and formed a synapse or otherwise was destined for “programmed death.” The mechanisms underlying programmed cell death, or apoptosis, have recently been elucidated (Kuan et al., 2000). The biochemical nature of apoptosis was first discovered by studying the nematode Caenorhabditis elegans. A genetic analysis identified a cascade of proteases, known as caspases, that control programmed cell death in all animals. Subsequently, mitochondrial-associated proteins have also emerged as important regulators of apoptosis including the Bcl-2 family, APAF, and cytochrome C. Apoptosis is recognized as a fundamental process that, together with progenitor cell proliferation, controls neuronal numbers during development. Presently, researchers are investigating whether some neurodegenerative disorders may be the result of aberrant apoptosis or neurotrophin signaling and whether neurotrophins or apoptosis inhibitors can be used clinically to treat neurodegenerative abnormalities. The wiring of complex CNS systems requires the connection of multiple cell types that are located in different positions. The wiring diagram of the visual system is an instructive example of this process. The neural retina contains primary sensory receptor neurons (rods and cones), interneurons (for example, amacrine, bipolar, and horizontal cells), glia (Müller cells), and projection neurons called retinal ganglion cells. The retinal ganglion cells extend axons that must make several choices on the path to their targets. First, they exit the eye through the optic nerve and confront the optic chiasmatic plate, a structure at the front of the hypothalamus. Axons from the temporal retina do not cross at the chiasm, whereas axons from the nasal retina do cross. Intrinsic signals that distinguish nasal and temporal cells (for example, the brain factor-1 and -2 transcription factors) permit the growing axons to sort themselves out to follow the correct pathway. There appear to be signals

that the axons detect in the chiasmatic plate that direct the axon traffic. Upon exiting the chiasm, the optic axons grow posteriorly toward their two main targets: the thalamus and the superior colliculus. The optic tracts grow along the surface of the hypothalamic mantle zone, passing many nuclei, until they reach the thalamus. Branches perpendicular to the trajectory of the optic tracts grow out from the axons. These branches then specifically enter the visual centers of the thalamus, principally the lateral geniculate nucleus (LGN), where they form synapses with the LGN neurons. Before describing the LGN in greater detail, it is important to point out that some optic axons continue to grow more posteriorly into the midbrain, where they form branches into the superior colliculus (or optic tectum). Here, the optic axons synapse in specific locations; axons from the temporal retina synapse in the anterior tectum, whereas axons from the nasal retina synapse in the posterior tectum. Molecules that may regulate this retinotopic map on the optic tectum are membrane-bound Eph-type receptors (found on the axons) and their membrane-bound protein ligands (found on the target cells). The Eph proteins probably make up part of the molecular system that orchestrates the precise mapping of axonal projections onto the target tissues in all CNS regions. In the LGN, the optic axons also form a retinotopic map. In higher mammals, the LGN is a laminar structure; each layer in the adult is connected with only one eye. However, during development, axons from both eyes have processes that extend into many LGN layers. Experimental evidence suggests that neuronal activity is required for the sorting-out process that eliminates branches in some layers and strengthens the synapses in others. Neuronal activity–dependent processes appear to have an essential role in many steps that refine the patterns of connections in the CNS; this is addressed further below. The projection neurons in the LGN send axons anteriorly into the telencephalon, where they traverse the striatum in the internal capsule and enter their target: the cerebral neocortex. The thalamocortical fibers enter the cortex while neurogenesis is still actively occurring and grow into a layer called the intermediate zone that is interposed between the proliferative (VZ and subventricular zone [SVZ]) and mantle (cortical plate) zones. The thalamocortical fibers’ next task is to innervate the correct region of the neocortex. The neocortex is subdivided into functionally distinct areas, each with a distinctive set of inputs. The LGN axons must innervate the primary visual cortex. Evidence suggests that some of the positional information that regulates this process is found in a transient layer of cortical neurons called the subplate cells. These are among the first cortical neurons to differentiate, and they are located in the deepest layer of the cortical plate, adjacent to the intermediate zone. The axons

1: OVERVIEW OF BRAIN DEVELOPMENT

from different thalamic nuclei form transient synapses with the subplate cells in distinct cortical domains. The LGN fibers grow to a caudal position in the cortex, which will become the primary visual cortex. There the LGN axons form synapses with the subplate cells and wait in this location until the cerebral cortex has further matured. Then the LGN fibers leave the subplate, grow into the cortex, and form synapses with neurons in layer 4. After the axons leave the subplate, most of these cells die, leaving no trace of this important step in neurodevelopment. Initially, inputs from both eyes converge within the same areas in layer 4 of the primary visual cortex. Then the axons from each eye segregate into distinct alternating domains called the ocular dominance columns. Evidence suggests that formation of these columns requires neuronal activity and that correlated activity from subregions of each eye plays a role in this process (see Katz and Shatz, 1996, for a review of this subject). Because ocular dominance formation occurs in utero, the neuronal activity is not induced by visual experience but is probably regulated by intrinsic neuronal discharges within the retina. As the thalamocortical circuit is maturing, local connections between cortical layers 1–6 form a columnar intracortical circuit that is the basic unit of cortical function. Each region of visual space is represented in these cortical columns, and the ensemble of these columns becomes the primary visual cortex. Through processes that are beyond the scope of this chapter, the primary visual cortex regulates the development of secondary visual centers that are concerned with more complex aspects of processing and integrating visual information. These areas project to cortical association areas that integrate visual and other information, which then influences motor output areas of the cortex. Forming and refining of these more complex intracortical circuits continues into postnatal life. These postnatal aspects of CNS development are greatly influenced by visual experience. POSTNATAL DEVELOPMENTAL PROCESSES Many aspects of neuronal development continue during postnatal life. As noted above, there is the continued elaboration and refinement of neuronal connections. Indeed, neocortical connectivity remains plastic into adulthood. For instance, in adult animals, when peripheral sensory inputs are eliminated, such as through amputation of a finger, the cortical regions that previously received input from the now-removed finger now receive sensory inputs from the adjacent fingers. There is evidence that this alteration in the neocortical sensory map results from changes in the sizes and shapes of axonal processes and the distribution of synapses. Thus, the synaptic

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connectivity of the adult neocortex is capable of a significant level of reorganization. In addition to the ability of neuronal processes to continue to grow and change in shape in postnatal animals, there are several brain regions that postnatally continue to produce new cells, probably neurons and glia. For instance, the SVZ of the lateral ventricles produces interneurons of the olfactory bulb, and the subgranular zone of the dentate gyrus in the hippocampus continues to make new granular neurons postnatally. Recent studies suggest that adult neurogenesis in the hippocampal dentate gyrus mediates aspects of spatial memory as well as aspects of antidepressant response and is negatively affected by certain forms of stress (Dranovsky and Hen, 2006; Perera et al., 2007). Gliogenesis is also active in many brain regions, including the cerebral cortex, where the cells differentiate into oligodendrocytes that actively continue to myelinate axons postnatally. In primates, some central circuits are not fully myelinated (and hence are not fully functional) until late adolescence or young adulthood. Thus, brain development does not end following birth, and several aspects of development are perhaps maintained throughout life. As newborns become exposed to sensory information, experience-driven influences gain increasing importance in molding the structure and function of the CNS. Although experience-based learning involves alterations in the structure of the brain (through physical changes that affect the number and distribution of synapses), it is likely that other mechanisms also have important roles. For instance, there are models that suggest that learning may include changes in the strength of synaptic signaling (via processes called long-term potentiation and long-term depression) accomplished at the molecular level (Chapter 5). It will not be surprising if such a complex process as learning turns out to involve multiple mechanisms. In sum, CNS development is probably a lifelong process requiring a precise order of events to occur at particular times. When a genetic or other influence eliminates, alters, or postpones (during a critical period) a specific developmental step, it is likely that optimal function of the CNS may be forever impaired. This may lead either to overt psychopathology or to a predisposition for later psychopathological problems. Postnatal development involves the melding of genetically driven events with those influenced by experience. How abnormalities in the developmental program lead to psychiatric disorders remains a mystery, probably due to the staggering complexity of the problem. Progress will, however, result eventually from further investigation, and the potential benefits of further study are many. Establishing the mechanisms underlying psychiatric disorders offers the potential of more rational diagnoses through genetic, molecular, histological, neuroimaging,

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INTRODUCTION TO BASIC NEUROSCIENCE

and other methods. If we can identify individuals who are carriers of genes, or gene combinations, that predispose to neuropsychiatric disorders, we can offer genetic counseling and intervene early in the cases of their children who may be at risk for psychopathology. Finally, through an understanding of disease mechanisms, there is hope for the development of better therapies. Although most developmental abnormalities probably cannot be precisely repaired, one can be optimistic that rational molecular, cellular, and psychotherapeutic interventions will ameliorate CNS dysfunction—in part due to the plasticity of the mature brain.

REFERENCES Allen, N.J., and Barres, B.A. (2005) Signaling between glia and neurons: focus on synaptic plasticity. Curr. Opin. Neurobiol. 15:542–548 Alvarez-Buylla, A., Garcia-Verdugo, J.M., and Tramontin, A.D. (2001) A unified hypothesis on the lineage of neural stem cells. Nat. Rev. Neurosci. 2:287–293. Ayala, R., Shu, T., and Tsai, L.H. (2007) Trekking across the brain: the journey of neuronal migration. Cell 128:29– 43. Benson, D.L., Colman, D.R., and Huntley, G.W. (2001) Molecules, maps and synapse specificity. Nat. Rev. Neurosci. 2:899–909. Bertrand, N., Castro, D.S., and Guillemot, F. (2002) Proneural genes and the specification of neural cell types. Nat. Rev. Neurosci. 7:517–530. Briscoe, J., Pierani, A., Jessell, T.M., and Ericson, J. (2000) A homeodomain protein code specifies progenitor cell identity and neuronal fate in the ventral neural tube. Cell 101:435– 445. Brose, K., and Tessier-Lavigne, M. (2000) Slit proteins: key regulators of axon guidance, axonal branching, and cell migration. Curr. Opin. Neurobiol. 10:95–102. Charron, F., and Tessier-Lavigne, M. (2005) Novel brain wiring functions for classical morphogens: a role as graded positional cues in axon guidance. Development 132:2251–2262. Colognato, H., and French-Constant, C. (2004) Mechanisms of glial development. Curr. Opin. Neurobiol. 14:37– 44. De Robertis, E.M., Larrin, J., Oelgeschläger, M., and Wessely, O. (2000) The establishment of Spemann’s organizer and patterning of the vertebrate embryo. Nat. Genet. 3:171–181. Dranovsky, A., and Hen, R. (2006) Hippocampal neurogenesis: regulation by stress and antidepressants. Biol. Psychiatry 59(12): 1136–1143. Flames, N., Long, J.E., Garratt, A.N., Fischer, T.M., Gassmann, M., Birchmeier, C., Lai, C., Rubenstein, J.L., and Marin, O. (2004) Short- and long-range attraction of cortical GABAergic interneurons by neuregulin-1. Neuron 44(2):251–261. Gaiano, N., and Fishell, G. (2002) The role of notch in promoting glial and neural stem cell fates. Annu. Rev. Neurosci. 25:471– 490. Gleeson, J.G., and Walsh, C.A. (2000) Neuronal migration disorders: from genetic diseases to developmental mechanisms. Trends Neurosci. 23:352–359. Greer, J.M., and Capecchi, M.R. (2002) Hoxb8 is required for normal grooming behavior in mice. Neuron 33:23–34. Grunwald, I.C., and Klein, R. (2002) Axon guidance: receptor complexes and signaling mechanisms. Curr. Opin. Neurobiol. 12:250 –259. Harrison, P.J., and Law, A.J. (2006) Neuregulin 1 and schizophrenia: genetics, gene expression, and neurobiology. Biol. Psychiatry 60(2):131–140. Hoogenraad, C.C., Koekkoek, B., Akhmanova, A., Krugers, H., Dortland, B., Miedema, M., van Alphen, A., Kistler, W.M., Jaegle, M.,

Koutsourakis, M., Van Camp, N., Verhoye, M., van der Linden, A., Kaverina, I., Grosveld, F., De Zeeuw, C.I., and Galjart, N. (2002) Targeted mutation of Cyln2 in the Williams syndrome critical region links CLIP-115 haploinsufficiency to neurodevelopmental abnormalities in mice. Nat. Genet. 32:116–127. Huang, E.J., and Reichardt, L.F. (2001) Neurotrophins: roles in neuronal development and function. Annu. Rev. Neurosci. 24: 677–736. Jan, Y.N., and Jan, L.Y. (2001) Dendrites. Genes Dev. 15:2627–2641. Jessell, T.M. (2000) Neuronal specification in the spinal cord: inductive signals and transcriptional codes. Nat. Rev. Genet. 1:20–29. Jessell, T.M., and Sanes, J.R. (2000) Development. The decade of the developing brain. Curr. Opin. Neurobiol. 10:599–611. Justice, N.J., and Jan, Y.N. (2002) Variations on the Notch pathway in neural development. Curr. Opin. Neurobiol. 2:64–70. Katz, L.C., and Shatz, C.J. (1996) Synaptic activity and the construction of cortical circuits. Science 274:1133–1138. Kriegstein, A., Noctor, S., and Martinez-Cerdeno, V. (2006) Patterns of neural stem and progenitor cell division may underlie evolutionary cortical expansion. Nat. Rev. Neurosci. 7:883–890. Kuan, C.Y., Roth, K.A., Flavell, R.A., and Rakic, P. (2000) Mechanisms of programmed cell death in the developing brain. Trends Neurosci. 23:291–297. Kullander, K., and Klein, R. (2002) Mechanisms and functions of Eph and ephrin signalling. Nat. Rev. Mol. Cell Biol. 7:475– 486. Lemke, G. (2001) Glial control of neuronal development. Annu. Rev. Neurosci. 24:87–105. Lumsden, A., and Krumlauf, R. (1996) Patterning the vertebrate neur-axis. Science 274:1109–1114. Marin, O., and Rubenstein, J.L.R. (2001) A long remarkable journey: tangential migration in the telencephalon. Nat. Rev. Neurosci. 2:780–790. Meng, Y., Zhang, Y., Tregoubov, V., Janus, C., Cruz, L., Jackson, M., Lu, W.Y., MacDonald, J.F., Wang, J.Y., Falls, D.L., and Jia, Z. (2002) Abnormal spine morphology and enhanced LTP in LIMK-1 knockout mice. Neuron 35:121–133. Mochida, G.H., and Walsh, C.A (2004) Genetic basis of developmental malformations of the cerebral cortex. Arch. Neurol. 61:637–640. Okada, A., Charron, F., Morin, S., Shin, D.S., Wong, K., Fabre, P.J, Tessier-Lavigne, M., and McConnell, S.K. (2006) Boc is a receptor for sonic hedgehog in the guidance of commissural axons. Nature 444:369–373. Pera, E.M., Wessely, O., Li, S.Y., and De Robertis, E.M. (2001) Neural and head induction by insulin-like growth factor signals. Cell 5:655–665. Perera, T.D., Coplan, J.D., Lisanby, S.H., Lipira, C.M., Arif, M., Carpio, C., Spitzer, G., Santarelli, L., Scharf, B., Hen, R., Rosoklija, G., Sackeim, H.A., and Dwork, A.J. (2007) Antidepressant-induced neurogenesis in the hippocampus of adult nonhuman primates. J. Neurosci. 27:4894 – 4901. Rakic, P. (1995) A small step for the cell, a giant leap for mankind: a hypothesis of neocortical expansion during evolution. Trends Neurosci. 18:383–388. Rice, D.S., and Curran, T. (2001) Role of the reelin signaling pathway in central nervous system development. Annu. Rev. Neurosci. 24: 1005–1039. Richardson, W.D., Kessaris, N., and Pringle, N. (2006) Oligodendrocyte wars. Nat. Rev. Neurosci. 7(1):11–18. Rubenstein, J.L.R., and Puelles, L. (2003) Development of the nervous system. In: Epstein, C.J., Erikson, R.P., and WynshawBoris, A., eds. Inborn Errors of Development. New York: Oxford University Press, pp. 75–88. Rubenstein, J.L.R., and Shimamura, K. (1997) Regulation of patterning and differentiation in the embryonic vertebrate forebrain. In: Cowan, W.M., Jessel, T.M., and Zipursky, S.L., eds. Molecular and Cellular Approaches to Neural Development. Oxford, UK: Oxford University Press, pp. 356–390.

1: OVERVIEW OF BRAIN DEVELOPMENT Sanes, J.R., and Lichtman, J.W. (2001) Development, induction, assembly, maturation and maintenance of a postsynaptic apparatus. Nat. Rev. Neurosci. 2:791–805. Shahbazian, M., Young, J., Yuva-Paylor, L., Spencer, C., Antalffy, B., Noebels, J., Armstrong, D., Paylor, R., and Zoghbi, H. (2002) Mice with truncated MeCP2 recapitulate many Rett syndrome features and display hyperacetylation of histone H3. Neuron 35:243–254. Shimamura, K., Hartigan, D.J., Martinez, S., Puelles, L., and Rubenstein, J.L.R. (1995) Longitudinal organization of the anterior neural plate and neural tube. Development 121:3923–3933. Shirasaki, R., and Pfaff, S.L. (2002) Transcriptional codes and the control of neuronal identity. Annu. Rev. Neurosci. 25:251–281. Streit, A., Berliner, A.J., Papanayotou, C., Sirulnik, A., and Stern, C.D. (2000) Initiation of neural induction by FGF signalling. Nature 406(6791):74–78.

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Tessier-Lavigne, M., and Goodman, C. (1996) The molecular biology of axon guidance. Science 274:1123–1131. Tissir, F., and Goffinet, A.M. (2003) Reelin and brain development. Nat. Rev. Neurosci. 4:496–505. Wilson, S.I., and Edlund, T. (2001) Neural induction: toward a unifying mechanism. Nat. Neurosci. 4(Suppl):1161–1168. Wilson, S.W., and Rubenstein, J.L.R. (2000) Induction and dorsoventral patterning of the telencephalon. Neuron 28:641–651. Wonders, C.P., and Anderson, S.A. (2006) The origin and specification of cortical interneurons. Nat. Rev. Neurosci. 7:687–696. Yu, T.W., and Bargmann, C.I. (2001) Dynamic regulation of axon guidance. Nat. Neurosci. 4(Suppl):1169–1176.

2 Neurochemical Systems in the Central Nervous System ARIEL Y. DEUTCH

A N D

ROBERT H. ROTH

More than a century ago the introduction of the neuron doctrine by Santiago Ramon y Cajal marked the beginning of modern neuroscience and positioned the neuron as the individual unit of the brain. The modes of communication between neurons have occupied the subsequent century. Although battles on the nature of the primary mode of communication, electrical or chemical, raged on for more than 50 years, by the mid20th century there was widespread acceptance that chemical signals were the primary means of interaction between two neurons (see Valenstein, 2005). The “classic” view of transmission of signals between neurons was that transmitter molecules that are synthesized by the presynaptic neurons are released into the synaptic cleft when the neuronal membrane is depolarized, with the transmitter subsequently binding to specific postsynaptic receptors that are coupled to intracellular second messengers. Although many thought the defining principles of neural transmission had been worked out by the beginning of the 21st century, the past decade has been as scientifically tumultuous as any of the last 100 years, with several findings challenging certain long-held and cherished beliefs about neurotransmitters. We examine the basic underpinnings of classical neurotransmitters and then explore new notions of chemical transmission brought about by the discovery of several decidedly unclassical chemical messengers. WHAT DEFINES A NEUROTRANSMITTER? Several criteria have been established that define a neurotransmitter (Cooper et al., 2002). These include the following: (1) a neurotransmitter should be synthesized in the neuron from which it is released; (2) the substance released from neurons should be present in a chemically or pharmacologically identifiable form, that is, should be capable of being measured and identified; (3) exogenous application of the neurotransmitter in physiologically relevant concentrations should cause changes in the postsynaptic neuron that mimic the 12

effects of stimulation of the presynaptic neuron; (4) the effects of the neurotransmitter should act on specific receptor sites on neurons and should therefore be blocked by administration of specific antagonists; and (5) there should be appropriate active mechanisms to terminate the actions of the neurotransmitter; these can include high-affinity reuptake processes or enzymatic degradation. These criteria are based largely on studies of acetylcholine (ACh), the first neurotransmitter identified. The experimental steps required to advance a transmitter role for ACh were relatively simple because ACh was initially studied at the neuromuscular junction rather than in the brain. The ability to expose and maintain preparations of the neuromuscular junction, a peripheral site, permitted electrophysiological and biochemical studies of synaptic transmission. Physiological studies revealed fast excitatory responses of muscle fibers in response to stimulation of the nerve innervating the muscle, similar to the effects of ACh. Moreover, miniature end-plate potentials were observed, which Fatt and Katz (1952) demonstrated to be due to the slow “leakage” of individual vesicles’ contents of ACh from the presynaptic terminal. In contrast, overt depolarization is due to an increased number of quanta released over a set period of time. Finally, studies of the neuromuscular junction and another peripheral site, the superior cervical ganglion, allowed detailed analyses of the enzymatic inactivation of ACh. These studies of ACh established the standard to which subsequent studies of neurotransmitters would be held. Many of the rules that were uncovered in studies of ACh apply to other transmitters. For example, the concept of the quantal nature of neurotransmission is central to current ideas of transmitter release. However, in the past generation, our ideas about the defining characteristics and functions of neurotransmitters have been eroded by the discovery of a number of chemical messengers that do not meet the criteria established for classical transmitters but have been clearly demonstrated to convey information from one neuron to another.

2: NEUROCHEMICAL SYSTEMS

FUNCTIONAL ASPECTS OF MULTIPLE NEUROTRANSMITTER Why are there so many neurotransmitters? In early years it seemed as if simple excitatory or inhibitory transmission would suffice, thus requiring two, or at least few, transmitters. More careful consideration reveals that several factors may contribute to the need for multiple chemical messengers (Deutch and Roth, 2008). The simplest explanation is that many afferents terminate on a single postsynaptic neuron, which must be able to distinguish between these multiple inputs. Although multiple inputs terminate on different parts of the postsynaptic neuron (such as different dendritic spines), many inputs to a neuron arrive in such close apposition that spatial segregation of inputs using the same transmitter will not allow accurate discrimination between incoming signals. Multiple transmitters allow the postsynaptic cell to distinguish differences in inputs by chemically coding the information, with the receptive neurons having distinct receptors and intracellular signaling pathways. A second reason for multiple transmitters may be related to the number of chemical messengers found in a single neuron. Thirty years ago, it was commonly thought that each neuron had but a single neurotransmitter; it is now clear that most if not all neurons have two or more chemical messengers (Deutch and Bean, 1995). Multiple transmitters in a single neuron permit the information transmitted by a neuron to a postsynaptic target to be encoded by different chemical messengers for different functional states. For example, the firing rates of neurons differ widely, and thus it may be useful for a neuron to encode a high-frequency discharge by one transmitter and a lower-frequency discharge by another transmitter. Similarly, differences in firing pattern convey different information; for example, classical and peptide transmitters are differentially released by different patterns of discharge. A third reason for multiple transmitters is that different types of transmitters are depleted at different rates. Classical transmitters are synthesized in the nerve terminal by enzymatic processing of a precursor; this process allows these transmitters to be released over extended periods of time while simultaneously being replenished at the terminal. In contrast, peptide transmitters are synthesized in the cell body and transported long distances to the axon terminal. Peptides can therefore be depleted by repetitive firing of neurons before new stores of the peptide are synthesized and transported to the nerve terminal for use. Still another reason for multiple transmitters is that transmitters are released from different parts of a neuron. The prototypic site of release is the axon terminal. However, transmitters are also released from dendrites,

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or at least escape from dendrites to function as chemical messengers, and can also be released from varicosities present on the axon. It has been suggested that these different sites of release may be occupied by different transmitters. The types of spatial arrangements between neurons may dictate yet another reason for multiple transmitters. We generally consider synapses to be the structural specializations for intercellular communication. However, transmitters may also be released from nonjunctional appositions between two neurons. Multiple transmitters may allow the postsynaptic cell to distinguish between transmitters released from nonjunctional appositions and areas of synaptic specializations. Another factor that may contribute to the need for multiple transmitters is that postsynaptic responses to transmitters occur over different time frames. Such temporal differences allow the postsynaptic cell to respond in a manner that takes into account antecedent activity in the presynaptic neuron. Thus, one transmitter can set the stage for the response of a particular cell to subsequent stimuli, which can occur on the order of seconds, or even minutes, independent of changes in gene expression. So many substances are now commonly accepted as neurotransmitters that one cannot discuss them all, much less new transmitter candidates. We therefore review in some detail the principles of neurotransmission for one group of classical neurotransmitters. A representative peptide transmitter is then discussed, emphasizing similarities and differences between neuropeptide and classical transmitters. Finally, we briefly touch on unconventional transmitters, a growing group that includes such unexpected members as soluble gases (for example, nitric oxide and carbon monoxide). CLASSICAL TRANSMITTERS Classical is a relative term in science, and particularly in neuroscience, where it can refer to a year, a decade, or a century. Despite the use of the term classical to define certain neurotransmitters, some of these were unknown 50 years ago. Nonetheless, there is a wealth of information concerning virtually every step in the biosynthetic and catabolic processes of the classical transmitters. One characteristic of classical transmitters, shared only by some of the more recently defined transmitters, is that the final synthesis of classical transmitters occurs in the axon terminal. Another defining characteristic of classical transmitters is that they (or their metabolic products) are accumulated by the presynaptic cell via an active process; there is no energy-dependent, highaffinity reuptake process for nonclassical transmitters. The catecholamines are a group of three related classical transmitters that are synthesized in certain

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central neurons, as well as the peripheral nervous system, where they can have hormonal functions. Because of the involvement of the catecholamines in several neuropsychiatric disorders, ranging from schizophrenia and depression to Parkinson’s disease and dystonias, these transmitters have been the focus of extensive investigation. A detailed description of the life cycle of catecholamine transmitters offers an excellent appreciation of the basic characteristics of classical transmitters. Catecholamines Catecholamines are organic compounds with a catechol nucleus (a benzene ring with two adjacent hydroxyl substitutions) and an amine group (Fig. 2.1). The term catecholamine is used more loosely to describe dopamine (DA; dihydroxyphenylethylamine) and its metabolic products norepinephrine and epinephrine. These three transmitters are generated by successive enzymatic modification of the amino acid tyrosine, each step requiring a different enzyme. The three catecholamines are found as transmitters in distinct dopamine-, norepinephrine-, and epinephrine-containing neurons because the biosynthetic enzymes that sequentially form these transmitters are localized to different cells.

FIGURE 2.1 Synthetic pathway for catecholamines. From Hyman and

Nestler (1993).

Catecholamine synthesis The amino acids phenylalanine and tyrosine are present in high concentration in plasma and brain and are precursors for catecholamine synthesis. Under most conditions the starting point of catecholamine synthesis is tyrosine, which is derived from dietary phenylalanine by the hepatic enzyme phenylalanine hydroxylase. Decreased levels of this enzyme cause phenylketonuria, a disorder that results in severe intellectual deficits if not treated. The amino acid tyrosine is accumulated by catecholamine neurons and then hydroxylated by the enzyme tyrosine hydroxylase (TH) to 3,4-dihydroxyphenylalanine (L-DOPA); this intermediary is immediately metabolized to DA by L-aromatic amino acid decarboxylase (AADC). In DA-containing neurons, this is the final synthetic step. However, neurons that use norepinephrine (NE) or epinephrine as transmitters contain the enzymes dopamine-b -hydroxylase (DBH) as well as TH, and DBH acts on DA to yield NE. Finally, brain stem neurons that use epinephrine as a transmitter, and adrenal medullary chromaffin cells that release epinephrine, contain phenylethanolamine-N-methyltransferase (PNMT), which is responsible for the formation of epinephrine from norepinephrine (Fig. 2.1). The entry of tyrosine into the brain depends on an energy-dependent uptake process for large neutral amino acids; tyrosine competes with other large neutral amino acids at this transporter. Under normal conditions, brain levels of tyrosine are high enough to saturate TH, and thus changes in precursor availability do not affect catecholamine synthesis. As a result, TH is considered the rate-limiting step in catecholamine synthesis. There are, however, certain exceptions to this rule, including in poorly controlled diabetes, in which the size of the large neutral amino acid pool is altered. Tyrosine hydroxylase. A single TH gene in humans gives rise to four TH messenger ribonucleic acids (mRNAs) through alternative splicing. In most non-human primates, two mRNA species are present, whereas in the rat there is but a single transcript. The functional significance of multiple transcripts is unknown, although it has been speculated that there may be subtle differences in enzyme activity in the different protein species. The amount of TH protein and the activity of the enzyme determine TH function. Enzyme activity is dependent upon phosphorylation of the enzyme at four distinct serine residues by different protein kinases. This provides remarkably specific control over TH activity. In addition to regulation of the enzyme by phosphorylation, TH activity can be regulated by end product (DA in the case of dopaminergic neurons)

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inhibition. Catecholamines inhibit the activity of TH through competition for tetrahydrobiopterin, a required cofactor for TH. Levels of reduced tetrahydrobiopterin are not saturated under basal conditions and thus play an important role in regulating TH activity. This is best illustrated by DOPA-responsive dystonia, which is due to mutations in the gene encoding GTP-cyclohydrolase I, which is the rate-limiting enzyme in the synthesis of tetrahydrobiopterin (Ichinose et al., 1994). The two means by which catecholamine neurons can cope with an increased demand for synthesis are by inducing TH protein or by activating (phosphorylating) existing enzyme (Kumer and Vrana, 1996). The degree to which catecholamine synthesis depends on de novo synthesis of enzyme protein or changes in enzymatic activity differ in various catecholamine neurons. Noradrenergic neurons of the brainstem nucleus locus coeruleus respond to increased demands for synthesis primarily by increasing TH gene expression, ultimately leading to an increase in TH protein levels. However, in midbrain DA neurons changes in TH mRNA levels are rarely seen; synthesis in these DA cells is thought to occur primarily by altering the activity of TH, that is, by posttranslational events such as phosphorylation. L-Aromatic amino acid decarboxylase. The product of tyrosine hydroxylation is the formation of L-DOPA, which in turn is immediately decarboxylated to form DA. This latter step requires the enzyme AADC (also referred to as DOPA decarboxylase). AADC has low substrate specificity: because the enzyme decarboxylates tryptophan as well as tyrosine, it is a key step in the synthesis of serotonin and catecholamines. The activity of AADC is so high that L-DOPA is almost instantaneously converted to DA. A single AADC gene encodes multiple transcripts that are differentially expressed in the central nervous system (CNS) and peripheral tissues. L-Aromatic amino acid decarboxylase mRNA is enriched in catecholamineand indoleamine-containing neurons in the CNS but is also found at low levels in other cell types. Dopamine has very poor blood-brain barrier penetrability. In contrast, the DA precursor L-DOPA readily enters the brain and has therefore become the mainstay in the treatment of Parkinson’s disease, the proximate cause of which is striatal DA insufficiency. Administration of L-DOPA to parkinsonian patients quickly increases brain DA levels and improves symptomatology. Dopamine-b-hydroxylase. Noradrenergic and adrenergic neurons, but not dopaminergic neurons, contain DBH, the enzyme that converts DA to norepinephrine. In noradrenergic neurons this is the final step of catecholamine synthesis. Two different human DBH mRNAs are generated from a single gene.

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Dopamine-b -hydroxylase has relatively poor substrate specificity and can oxidize in vitro almost any phenylethylamine to its corresponding phenylethanolamine. Thus, in addition to the oxidation of DA to form NE, DBH promotes the conversion of tyramine to octopamine and a-methyldopamine to a-methylnorepinephrine. This lack of substrate specificity has been exploited in the laboratory: several structurally analogous compounds can replace NE function as “false transmitters,” providing useful experimental tools. Specific receptors have now been identified for the trace amines, including octopamine (Zucchi et al., 2006). These receptors are expressed in brain and gut and may in part be responsible for the “cheese” effect seen in patients treated with monoamine oxidase inhibitors (see below). Contrary to the usual situation in which TH is the rate-limiting step in catecholamine synthesis, when the activity of locus coeruleus noradrenergic neurons is increased, DBH is saturated and becomes the rate-limiting step. Because DBH is localized to the vesicle, if DBH is saturated then DA can accumulate, and thus when the vesicles dock with the plasma membrane NE and DA and DA metabolites are released, that is, the noradrenergic cell becomes a source of DA. Under sustained periods of activation, there is a compensatory increase in DBH expression in these cells. Phenylethanolamine-N-methyltransferase. The enzyme phenylethanolamine-N-methyltransferase methylates NE to epinephrine. Epinephrine neurons are clustered into two groups of brainstem cells. In addition, high levels of PNMT are present in the adrenal medulla. The enzyme has relatively poor substrate specificity and will transfer methyl groups to the nitrogen atom on a variety of b -hydroxylated amines. Nonspecific N-methyltransferases are also found in the lung and will methylate many indoleamines. The high levels of PNMT in the adrenal gland, coupled with relatively easy access to the adrenal, have led to an extensive characterization of the enzyme in this gland, where enzyme activity and expression are tightly regulated by glucocorticoids and nerve growth factor. Storage of catecholamines: Synaptic vesicles and vesicular transporters Catecholamine transmitters are stored in small vesicles located near the synapse and poised for fusion with the neuronal membrane and subsequent exocytosis. In addition to serving as a storage depot for catecholamines, vesicles sequester catecholamines from cytosolic enzymes and from some toxins that enter the neuron. Dopamine-b -hydroxylase differs from other catecholamine-synthesizing enzymes by being localized to the vesicle, rather than neuronal cytosol. Thus, DA

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must be accumulated by noradrenergic vesicles through an active uptake process prior to being converted to norepinephrine. The vesicular storage of DBH also means that the enzyme is released from neurons when norepinephrine is released. Moreover, because DBH is the rate-limiting enzyme for activated noradrenergic neurons, DA accumulates in the vesicles when catecholamine neurons are activated, culminating in release of DA along with norepinephrine. The accumulation of DA by vesicles depends on a vesicular monoamine transporter protein (VMAT). Two VMAT genes have been cloned: one is in the adrenal medulla, and the other (called VMAT2) is found in catecholamine and serotonin neurons of the CNS. VMAT2 broadly accumulates monoamines, including catecholamines and indoleamines. The VMATs are targets of some psychotropic drugs. Reserpine, a blocker of VMAT, has been used for decades to treat hypertension and psychosis. Studies of reserpine shed light on how this drug can reduce psychotic symptoms (by decreasing DA accumulation into vesicles and thereby decreasing DA availability) and hypertension (by disrupting catecholamine synthesis in the adrenal medulla and thereby decreasing circulating catecholamine levels). Regulation of catecholamine synthesis and release by autoreceptors We have shown how catecholamines are synthesized, and some of the regulatory features that govern synthesis of these transmitters. Another way in which the synthesis of catecholamines can be regulated is by the catecholamine transmitter that is released from the neuron. Once released, the transmitter (for example, DA) interacts with a receptor located on the catecholamine axon that binds the transmitter (for example, a DA D2 receptor). This nerve terminal “autoreceptor” provides a feedback loop that controls release of the transmitter. This feedback can be a negative feedback, in which released transmitter shuts down further transmitter release; drugs that are antagonists of the autoreceptor can promote transmitter release. There are several types of autoreceptors. In addition to autoreceptors that regulate transmitter release, there are autoreceptors that regulate transmitter synthesis, and still another type that regulates the firing rate of the neuron. Thus, the transmitter regulates its own synthesis and release and determines the firing rate of the neuron from which it is released. Dopamine autoreceptors, which are among the bestcharacterized autoreceptors, are found on the cell bodies, dendrites, and nerve terminals of dopaminergic neurons. The different sites correspond to the different end points of autoreceptor tone. Release- and synthesis-modulating autoreceptors are present on axon terminals and

somatodendritic regions of DA neurons. In addition, impulse-modulating autoreceptors that govern the firing rate of the neuron are present on somatodendritic regions of the neuron. All three types of DA autoreceptors are D2-like receptors. Although once suspected that different types of DA receptors subserve the different autoreceptor functions, it appears that there may be, to some degree, distinct transduction mechanisms, all operating through a D2 receptor. Release-modulating autoreceptors are present on all DA neurons. However, synthesis-modulating autoreceptors are not. For example, DA neurons that innervate the prefrontal cortex and hypothalamic tuberoinfundibular DA neurons do not have functional synthesis-modulating autoreceptors. Impulse-modulating autoreceptors are also present on most but not all DA neurons. Such differences in the localization of autoreceptors to different types of neurons are thought to confer regional specificity on the function of DA neurons. Autoreceptors for norepinephrine are also well characterized. Although noradrenergic autoreceptors that regulate release of NE are well known, and are important targets for drugs used to treat cardiovascular and neuropsychiatric disorders, the presence of synthesismodulating autoreceptors on NE neurons is not well established. Norepinephrine autoreceptors in brain are a 2-adrenergic receptors, the activation of which serves to inhibit norepinephrine release. In contrast, autoreceptors on peripheral nerves are b -adrenergic receptors and facilitate norepinephrine release. There is almost no information concerning autoreceptor-mediated release function of central epinephrine neurons. Inactivation of released catecholamine neurotransmitters Continuous (as opposed to discrete pulsatile) release of a transmitter does not provide target neurons with appropriate information about the dynamic state of the presynaptic neuron. Accordingly, there is a need for mechanisms to inactivate the released transmitter. The importance of this process can be easily appreciated by considering the consequences of unrestrained stimulation of ion channel-forming receptors that allow calcium entry into the neuron: if intracellular Ca2+ levels increase too much, excitotoxic cell death results. There are several specific mechanisms for terminating transmitter actions. Diffusion contributes to inactivation of a transmitter. However, functional receptors are often present on the axon as well as in the immediate synaptic region, making diffusion a poor means for terminating transmitter action. The primary mode of inactivation appears to be uptake by neurons of the released transmitter by a plasma membrane-associated transporter protein. Inactivation by means of transporter-mediated reuptake is efficient, and often allows for recycling of

2: NEUROCHEMICAL SYSTEMS

the transmitter or metabolites to lower energy demands on the neuron. A second way for transmitter actions to be terminated is by catabolic enzymes located either extra- or intracellularly. Enzymatic inactivation of catecholamines. Two enzymes sequentially metabolize catecholamines. Monoamine oxidases (MAO) deaminate catecholamines to yield aldehyde derivatives; these are further catabolized by dehydrogenases and reductases. Catechol-O-methyltransferase (COMT) methylates the meta-hydroxy group on catechols, and these methylated intermediaries are further oxidized by MAO. Enzymatic inactivation, particularly by COMT, is the primary mode of terminating the actions of catecholamines circulating in the blood. In the brain, termination of catecholamine actions by reuptake mechanisms appears to be more important. Nevertheless, drugs that target the enzymatic inactivation of catecholamines have been very useful therapeutic strategies for several disorders, including depression. Two MAO genes have been cloned, and two isoforms of the enzyme can be distinguished by substrate specificities. Both isoforms are present in the CNS and peripheral tissues. MAOA displays high affinities for NE and serotonin, whereas MAOB has a higher affinity for b -phenylethylamines. Drugs that inhibit MAOA (clorgyline, tranylcypromine) are among the most effective antidepressant drugs. However, these agents have serious side effects, including development of hypertensive crisis. Thus, patients treated with MAOA inhibitors who eat foods high in tyramine content (for example, aged cheeses and Chianti, a particularly appetizing combination) do not effectively metabolize tyramine, which releases catecholamines from nerve endings and thereby sharply and dangerously increases blood pressure. Recently, novel receptors for which tyramine and other trace amines have high affinity have been identified and may be targets for drugs that prevent or treat the side effects of MAOA inhibitors (Zucchi et al., 2006). Interestingly, amphetamine and lysergic acid diethylamide (LSD) are also agonists at one of these receptors. Deprenyl is a specific inhibitor of MAOB and is sometimes used in the treatment of early-stage Parkinson’s disease (PD). The use of deprenyl in PD derived from studies of the neurotoxin 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine (MPTP), which causes a parkinsonian syndrome. 1-Methyl-4-phenyl-1,2,3,6tetrahydropyridine itself is not toxic, but the active metabolite MPP+ that is generated by the actions of MAOB is highly toxic. Because the MAOB inhibitor deprenyl blocks the formation of MPP+ from MPTP, pretreatment with deprenyl prevents MPTP-induced parkinsonism. Genetic defects that cause PD account for a small percentage of the total cases of PD, leading to the suggestion that an environmental toxin similar to MPTP might cause parkinsonism. Studies of the ability

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of deprenyl to slow progression of PD in newly diagnosed patients ensued. Early analysis of these studies suggested that the drug did slow disease progression, but longer term analyses failed to sustain the early enthusiasm, although it does appear that deprenyl may offer some symptomatic relief. This probably occurs by increasing DA levels secondary to the inhibition of MAOB-mediated catabolism of DA. In addition, small amounts of amphetamine and methamphetamine, potent DA releasers, are generated by the metabolism of deprenyl and may contribute to symptomatic improvement in parkinsonian symptoms. Catecholamine reuptake: Membrane transporter. The reuptake of transmitters released into the extracellular space via specific cell membrane proteins is thought to be the major mode of inactivation of classical transmitters. The accumulation of transmitters in the presynaptic neuron may also permit intracellular degradative enzymes to act and further contribute to transmitter inactivation, particularly if the transmitter is not rapidly accumulated by vesicles. Neuronal reuptake of catecholamines and other classical transmitters has several characteristics: the process is energy dependent, saturable, involves Na+ cotransport, and requires extracellular Cl– (Zahniser and Doolen, 2001). It is worthwhile to note that transporters can operate bidirectionally and under certain conditions may paradoxically transport in the “wrong” direction, thereby “releasing” a transmitter. Catecholamine transporters are found in catecholamine but not other neurons. There appears to be some catecholamine uptake by glial cells, but this is not a high-affinity reuptake process and the functional significance of this process remains obscure. However, extracellular levels of amino acid transmitters such as g -aminobutyric acid (GABA) and glutamate are strongly regulated by glial (astrocytic) uptake. In mammals, two different catecholamine transporters, the DA (DAT) and NE (NET) transporters, have been identified. An amphibian epinephrine transporter has been cloned, but a mammalian homologue of this gene has not been identified. Both DAT and NET transporters have significant sequence homology. They also share relatively poor substrate specificity; in fact, NET has a higher affinity for DA than for NE. Anatomical studies have revealed that DAT and NET are restricted to DA- and norepinephrine-containing cells, respectively. However, DAT is not present in measurable levels in all DA neurons. For example, the hypothalamic neurons that release DA into the pituitary portal blood supply do not express detectable levels of DAT mRNA or protein. Because DA released from these neurons is rapidly carried away in the portal vasculature, there is probably no need for inactivation of DA by reuptake into tuberoinfundibular neurons.

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Immunohistochemical studies have revealed that under basal conditions, DAT, as well as other transmitter transporters, is localized to the extrasynaptic region of the axon terminal (Hoffman et al., 1998), suggesting that the transporter may be important in clearing DA that has diffused from the synaptic region. When one considers that DA receptors are also found adjacent to the synapse rather than at the synaptic junction, extrasynaptic (socalled paracrine) transmission may be of greater importance than was previously realized for catecholaminergic transmission (Wickens and Arbuthnott, 2005). Just as there is a tight process of regulation over enzyme activity, there are regulatory controls for neurotransmitter transporters. Chronic administration of catecholamine reuptake inhibitors decreases the number of transporter sites, consistent with a decrease in gene expression. In addition, the activity of catecholamine transporters appears to be regulated acutely by several mechanisms (Zahniser and Doolen, 2001). The recognition that transporter expression is dynamically regulated has broad implications for in vivo imaging studies of transporters (such as studies of DAT in PD) because drug treatments that patients receive may alter the apparent density of the transporter. The generation of mice lacking DAT has revealed that a remarkably broad array of DA neuron functions is disrupted by loss of the transporter (Sotnikova et al., 2006). It is therefore not surprising that transporters are key targets of psychoactive drugs. Cocaine increases extracellular monoamine levels by blocking the transporters for DA, NE, and serotonin. The tricyclic antidepressants potently inhibit NE and serotonin reuptake, with significantly weaker effects on DAT, and are one of the major means of treating certain types of depression. The newer serotonin-selective reuptake blockers, such as fluoxetine, are now the most widely prescribed antidepressant medications.

nucleus and putamen (striatum), limbic sites such as the amygdala, septum, and hippocampus, and certain cortical sites (Fig. 2.2). The cortical DA innervation in primates is much broader than that seen in rodents. In addition to the midbrain DA neurons, several clusters of DA neurons are found in the diencephalon, including hypothalamic cells with long axons that innervate the spinal cord as well as intrahypothalamic projections. Still another set of DA neurons is found in the olfactory bulb. The reader is referred to the review by Moore and Bloom (1978) for a more comprehensive discussion of the anatomy of DA neurons. Norepinephrine-containing cells are located in the medulla and pons (Fig. 2.3). In the rostral pons, a small but important group of cells is found in the nucleus locus coeruleus. These neurons give rise to most of the noradrenergic innervation of the forebrain, as well as of the brain stem and spinal cord. Pontine and lower brain stem NE-containing cells project to ventral forebrain and diencephalic sites, including certain nuclei in the hypothalamus and thalamus, and limbic areas such as the amygdala, hippocampus, and septum. Epinephrine-containing cells are found in two nuclei in the medulla and provide descending projections as well as an important projection to the pons that regulates the activity of the locus coeruleus NE-containing cells.

Anatomy of catecholamine neurons Neurons expressing DA, NE, and epinephrine are found in a wide variety of species, although there are some major differences in the anatomical organization of these neurons between species. For example, midbrain DA neurons are present in all vertebrates except bony fish (teleosts), and dopaminergic cells (although few in number) are present in flies and worms. There are some differences in the anatomy of the catecholaminergic neurons between primate and lower mammalian species, but these differences are mainly quantitative rather than qualitative, and the general organization of the catecholamine systems of primates and lower mammalian species is quite similar. Dopamine neurons in the ventral midbrain cells project to several forebrain sites, including the caudate

FIGURE 2.2 Dopaminergic projection systems in the brain. The

major dopaminergic nuclei in the brain are the substantia nigra pars compacta (hatched), shown projecting to the striatum (also hatched); the ventral tegmental area (fine stipple), shown projecting to the frontal and cingulate cortex, nucleus accumbens, and other limbic structures (fine stipple); and the arcuate nucleus of the hypothalamus (coarse stipple), which provides dopaminergic regulation to the pituitary. From Hyman and Nestler (1993).

2: NEUROCHEMICAL SYSTEMS

FIGURE 2.3 Noradrenergic projection systems in the brain. Shown

are the major noradrenergic nuclei of the brain, the locus coeruleus (hatched), and the lateral tegmental nuclei (fine stipple). Epinephrinecontaining nuclei are shown in black. The projections from the locus coeruleus (as described in the text) are markedly simplified. Projections from the other noradrenergic nuclei are not shown. From Hyman and Nestler (1993).

Serotonin The major processes that regulate catecholamine synthesis and degradation are common to all classical transmitters, including serotonin. Nonetheless, there are some relatively minor differences among the classical transmitters. The following discussion focuses on the differences between serotonin and catecholamine neurotransmitters. Synthesis of serotonin The synthesis of serotonin (5-hydroxytryptamine) follows the basic scheme laid out for catecholamine transmitters: the uptake of a precursor amino acid (tryptophan) into the neuron, the sequential enzymatic formation of serotonin from tryptophan, the accumulation of serotonin by VMAT2 and its storage by vesicles, and active reuptake of extracellular serotonin as the primary mode of inactivation of the transmitter. The precursor amino acid tryptophan enters the CNS on a large neutral amino acid transporter, where it competes with other amino acids (including phenylalanine and tyrosine). In serotonergic neurons, tryptophan is a substrate for tryptophan hydroxylase, which results in the formation of 5-hydroxytryptophan (5-HTP), the immediate serotonin precursor (Fig. 2.4). Tryptophan hydroxylase is not saturated; therefore, peripheral, including dietary, sources of tryptophan have a major influence on central serotonin synthesis. Tryptophan hydroxylase is found in the CNS and the periphery. There are some biochemical differences

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between the central and peripheral forms, which appear to be due to posttranslational modifications. Situations requiring increased synthesis of serotonin are dealt with mainly by increasing the activity of the enzyme through phosphorylation; some long-term changes in demand may lead to increases in tryptophan hydroxylase gene expression. 5-Hydroxytryptophan is metabolized to serotonin by L-aromatic amino acid decarboxylase, the same enzyme that converts L-DOPA to DA. With one prominent exception, serotonin is the end point of indoleamine synthesis in the brain. That exception is in the pineal gland, where serotonin is metabolized to form the hormone melatonin. There is also a kynurenic acid shunt from tryptophan metabolism that results in the formation of several compounds, including quinolinic acid and kynurenic acid. Quinolinic acid is a potent N-methyl-D-aspartate (NMDA) receptor agonist and can cause convulsions and neurotoxicity. In contrast, kynurenine is an NMDA antagonist (Schwarcz, 2004). It has been suggested that the ratio of the two substances may be of significance in clinical conditions such as stroke, where cell death is mediated in part by NMDA receptors. Storage and release of serotonin Serotonin is stored intraneuronally in vesicles. The accumulation of serotonin by vesicles is accomplished by VMAT2. There is one major difference between serotonin and catecholamine neurons: serotonin synthesis is not regulated by end product inhibition in vivo. Otherwise, the regulatory features are quite similar, including serotonin autoreceptors that regulate serotonin release and synthesis, acting through functionally distinct somatodendritic and terminal autoreceptors. The release and impulse-modulating autoreceptor in

FIGURE 2.4 Synthetic pathway for serotonin. From Hyman and

Nestler (1993).

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serotonin neurons is a 5-HT1 receptor. The 5-HT1A receptor is an autoreceptor present on the somatodendritic region of the serotonin neurons, whereas the 5-HT1B receptor is an autoreceptor found on serotonin nerve terminals. In addition, the 5-HT1A receptor is also found on some nonserotonergic neurons. Inactivation of released serotonin Reuptake of released serotonin by a specific serotonin transporter (SERT) is the major means of terminating serotonin’s actions. The SERT is a member of the same molecular family as the catecholamine transporters and has the same requirements for action (Zahniser and Doolen, 2001). The SERT, like DAT and NET, is a major target for psychotropic drugs, including the most commonly used antidepressants, which are serotoninselective reuptake inhibitors (Blakely, 2001). Like the catecholamines, serotonin can be inactivated enzymatically by MAO. Anatomy of serotonin-containing neurons Serotonergic cells are present in distinct groups of brain stem neurons, which are found from the caudal medulla to the caudal midbrain level (Fig. 2.5). Pontine serotonin cells in the dorsal and median raphe nuclei are the source of diencephalic and telencephalic sites; cells in the medulla provide important descending serotonin projections to the spinal cord. Amino Acid Transmitters The excitatory and inhibitor amino acid transmitters glutamate and GABA, respectively, are the most

FIGURE 2.5 Serotonergic projection systems in the brain. The major

serotonergic nuclei in the brain are the brain stem raphe nuclei (hatched). The nuclei are shown slightly enlarged, and their diffuse projections (as described in the text) are markedly simplified. From Hyman and Nestler (1993).

abundant transmitters in the brain. Monoamine-containing neurons are discretely localized in the brain, but glutamatergic and GABAergic neurons are found in virtually all areas of the brain. Although there are some significant differences between amino acid and monoamine transmitters, most of the major principles discussed in the section on catecholamine transmitters are applicable to amino acid transmitters. The amino acid transmitters are derived from intermediary glucose metabolism. This dual role for GABA and glutamate as transmitters and metabolic intermediaries requires some mechanisms for segregating the transmitter and metabolic pools (Hassel and Dingledine, 2006; Olsen and Betz, 2006). The other major difference between amino acid and monoamine transmitters is that the former are subject to uptake by high-affinity transporters expressed by glial cells as well as by transporters localized to neurons. This discussion focuses on those aspects of amino acid transmitters that differ from monoamine transmitters, as enumerated above. Although glycine is also an inhibitory transmitter, particularly in the spinal cord, GABA is discussed as the major inhibitory transmitter. Glutamate is discussed as the major excitatory transmitter, although other excitatory amino acids, including aspartate, N-acetylaspartylglutamate, and sulfurcontaining amino acids such as homocysteic acid, also have key roles. Amino acid transmitter synthesis g -Aminobutyric acid is derived from glucose metabolism, with a-ketoglutarate from the Krebs (tricarboxylic acid) cycle being transaminated to glutamate by GABA a-oxoglutarate transaminase (GABA-T). The key step for the generation of the transmitter pool of GABA is the action of the enzyme glutamic acid decarboxylase (GAD), which converts glutamate to GABA. Glutamic acid decarboxylase is found almost exclusively in neurons that use GABA as a transmitter and thus serves as a marker for GABAergic neurons. Two isoforms of GAD are encoded by two different genes. The two GAD species (designated GAD65 and GAD67 on the basis of their mass) have somewhat different intracellular distributions and are differently regulated; thus, the processes that govern GABA synthesis may be specialized to some degree in different parts of the neuron. Glutamic acid decarboxylase requires a pyridoxal phosphate cofactor for activity. The lower-mass enzyme, GAD65, has a high affinity for the cofactor, but GAD67 does not. The high affinity of GAD65 for cofactor provides a way in which enzyme activity can be quickly and efficiently regulated. However, GAD67 activity is not as readily regulated, although the amount of enzyme can be regulated at the transcriptional level.

2: NEUROCHEMICAL SYSTEMS

As noted above, GAD is an excellent marker for cells in which GABA is a transmitter. Glutamic acid decarboxylase is a cytosolic protein. However, GABA-T, which synthesizes the GABA precursor glutamate from a-ketoglutarate, is a mitochondrial enzyme. Thus, there is a metabolic pool of GABA that is mitochondrial. The process by which glutamate destined for the transmitter pool is exported from the mitochondria is not well understood. Glutamate is the immediate precursor to the inhibitory transmitter GABA, but it has a major independent role as an excitatory transmitter in different neurons. Neurons must therefore have some mechanisms to prevent GABA neurons from using glutamate as a transmitter. Glutamic acid decarboxylase is not found in neurons that use glutamate as a transmitter, thus ensuring that GABAergic neurons use GABA but not glutamate as a transmitter. The process that sequesters glutamate from the transmitter pathway in GABA neurons is less clear. It has been proposed that synthesis of glutamate destined for the transmitter pool may require a special form of glutaminase. Although GABA and glutamate are not cotransmitters, it is interesting to note that a recent report suggested that some reports indicate that single neurons may contain an excitatory and an inhibitory transmitter (Salter and De Koninck, 1999). Glutamate can also be formed directly from glutamine, which is synthesized in glial cells. The glutamine that is formed in glia can be transported into nerve terminals and then locally converted by glutaminase into glutamate. Thus, glial cells may in part regulate glutamate synthesis. This underscores the complex functions of glia, which are now recognized to play several critical roles in brain fuction in addition to the support role previously envisioned (Volterra and Meldolesi, 2005). Storage of amino acid transmitters: Vesicular transporters Although vesicular storage of amino acid transmitters has been known for some time, only very recently were the vesicular transporters cloned. A vesicular transporter that accumulates GABA and glycine has been cloned and characterized (McIntire et al., 1997). This vesicular transporter is expressed in GABA and glycine neurons, where it is enriched in axon terminals. In contrast to the monoamine vesicular transporters, which use a pH gradient to transport monoamines into the cell, the vesicular GABA transporter uses electrochemical and pH gradients to drive transport. Three vesicular glutamate transporters have recently been identified and cloned (Fremeau et al., 2004). These proteins also transport inorganic phosphate, on which basis they were first identified, and accumulate glutamate by an electrochemical gradient. The expression of these transporters is the definitive marker for a neuron that uses glutamate as a transmitter.

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Regulation of amino acid transmitter release by autoreceptors Autoreceptor-mediated regulation of GABA neurons occurs through GABAB receptors, which in contrast to the postsynaptic ionotropic GABAA receptors are G protein–coupled. GABAB receptors are also found on non-GABA cells, where they may regulate the release of glutamate and other transmitters. The release of glutamate from nerve terminals is also subject to autoreceptor regulation, a function subserved by G protein–coupled metabotropic glutamate receptors (mGluR). There are three groups of mGluR receptors that include eight different receptors; one group of mGluRs are autoreceptors. In addition to the well-characterized release-modulating mGluRs, electrophysiological studies have suggested the presence of a glutamate impulse–modulating autoreceptor. Drugs that target metabotropic glutamate receptors are a target for the development of new drugs to treat a variety of neuropsychiatric disorders, including schizophrenia and Parkinson’s disease Inactivation of released GABA and glutamate The uptake of released GABA and glutamate is the primary means of terminating the actions of these transmitters. High-affinity GABA and glutamate uptake by neurons and glia has long been known and distinguishes these transmitters from the monoamines, which are not accumulated by high-affinity glial transporters (Zahniser and Doolen, 2001). In contrast to monoamine transporters, which include a single transporter for each of the monoamines, at least three transporters accumulate GABA (Kanner, 2006); other transporters present in the brain, such as a betaine transporter, can also accumulate GABA. The three types of GABA transporters (GATs) do not readily correspond to different subtypes in glia and neurons. Early pharmacological studies defined two GATs that could be distinguished in part on the basis of glial and neuronal uptake. However, the cloning of GAT genes and subsequent generation of specific probes to mark these transporters revealed that a cloned GAT, which on pharmacological grounds corresponded to the classical glial transporter, was present mainly on neurons. Other GATs are expressed in neurons and glia. Although it is possible to distinguish glial from neuronal uptake of GABA pharmacologically, the inability to ascribe glial and neuronal transporters to specific cell types suggests that still other GATs may be present. Glial and neuronal expression of glutamate transporters also occurs. Two glutamate transporters are primarily expressed in glia, with a third glutamate transporter being predominantly neuronal. The glutamate transporters accumulate L-glutamate and D- and L-aspartate; all three of these transporters have similar

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INTRODUCTION TO BASIC NEUROSCIENCE

affinities for glutamate, but there are substantial differences in affinities for other amino acids. Anatomy of amino acid transmitters GABA- and glutamate-containing neuronal elements can be found in almost every area of the brain. Nonetheless, certain discrete projections for excitatory and inhibitory neurons have been identified. For example, inhibitory GABAergic cells are often found as local circuit neurons. However, some GABA neurons are projection neurons; among these are cells that project from the basal forebrain to the cortex and striatal GABAergic neurons that innervate the globus pallidus and substantia nigra. Among the many glutamatergic neurons are the pyramidal cells of the cortex, as well as a variety of long-axoned projection neurons in subcortical sites. Diversity of amino acid transmitters More so than other classical transmitters, GABA and glutamate as transmitters are marked by a complexity and diversity of function. There are multiple membrane transporters for GABA and glutamate, and multiple vesicular glutamate transporters. GABA and glutamate play transmitter and metabolic roles in neurons. There are a diverse group of receptors for GABA and glutamate, including ionotropic and metabotropic receptors. GABA and glutamate involve more than just neurons but critically bring into play glial cells. We focused this brief discussion of the amino acid transmitters on GABA and glutamate, but there are other amino acids that are transmitters or have been proposed to be neurotransmitters; these include N-acetylaspartylglutamate, glycine, and sulfur-containing amino acids. Among the most surprising of the amino acids transmitter candidates are D-amino acids (Snyder and Ferris, 2000; Martineau et al., 2006). Conventional wisdom has held that L- but not D-enantiomers of amino acids are active; D-amino acids were relegated to their functions in bacteria and invertebrates. However, D-serine and D-aspartate are present in relatively high concentrations in the human brain. D-Serine is heterogeneously distributed, with the highest concentrations in regions with a high density of NMDA glutamate receptors. An enzyme, serine racemase, which converts L-serine to D-serine, has been found in glia but not neurons, suggesting that glia may synthesize and release D-serine. However, classical considerations of transmitters hold that neurons but not glia communicate via release of transmitters. This conundrum has been resolved by noting that certain types of glia express a-amino-3-hydroxy-5-methyl-4-isoxasolepropionic acid (AMPA)-type glutamate receptors and respond to glutamate stimulation by releasing D-serine onto NMDA-receptor-bearing neurons. Thus, in this case, glia serve as intermediate functional links

between two neurons, and D-amino acids may be neurotransmitters, albeit uncoventional ones (see below). PEPTIDE TRANSMITTERS Peptides have become firmly established as neurotransmitters only over the past 30 years. The notion that there are peptide transmitters initially met with resistance because peptides did not appear to meet some of the criteria developed for classical transmitters. Some of these missing steps were subsequently shown to be due to methodological issues, including sensitivity of assay techniques. There are two major differences between classical and peptide transmitters. The first is the intraneuronal site(s) of synthesis of the transmitter. Synthetic enzymes for classical transmitters are present in axon terminals as well as cell body regions, allowing a rapid response to increased demand for transmitter release from axon terminals. In contrast, peptide transmitters are typically synthesized in the cell body but not in axons. As such, increased demand for the peptide transmitter requires de novo protein synthesis and transport of the peptide to the terminal. The second major difference is that peptides are inactivated almost exclusively by enzymatic means; there are no high-affinity transporters that accumulate neuropeptides. Despite the failure of peptide transmitters to meet all of the classical criteria for transmitters, neuropeptides clearly convey information between neurons. Such information is not simply generalized information about the milieu, but temporally and spatially coded information transfer. Table 2.1 lists some of the peptide transmitters in the brain. The general principles of the peptide transmitters are discussed below. The discussion focuses on specific examples drawn from one widely distributed peptide, neurotensin. Synthesis and Storage of Peptide Transmitters Classical transmitters are typically synthesized by enzymatic processing of precursor(s) in the vicinity of the release site, often the axon terminal. In contrast, peptide transmitters are formed from a prohormone precursor that is transcribed and translated in the cell body of the neuron, where it is then incorporated into vesicles. Thus, most peptide transmitters are formed from a single precursor from which active peptides are cleaved, in contrast to the successive enzymatic modifications of a precursor amino acid that give rise to most classical transmitters. The general process can be easily understood by examining the case of the peptide transmitter neurotensin (NT). A large (170 amino acid) prohormone precursor of NT and a related peptide, neuromedin N (NMN), are encoded by a single gene that is transcribed

2: NEUROCHEMICAL SYSTEMS TABLE

2.1. Examples of Peptide Transmitters

Opioid and related peptides Dynorphin Endorphin Enkephalin Nociceptin (orphanin FQ) Gut-brain peptidesa Cholecystokinin (CCK) Gastrin Secretin Somatostatin Vasoactive intestinal polypeptide (VIP) Tachykinin peptides Substance K Substance P Neuromedin N

23

processes that subserve vesicular release of peptides and classical transmitters (Bean et al., 1995); recent data have begun to untangle the mechanisms responsible (Sieburth et al., 2007). Release of Peptides The depolarization-elicited release of peptides from dense-core vesicular stores is calcium dependent. The amount of peptide transmitter that is released from neurons varies as a function of the firing rate and firing pattern of the neuron. For example, studies of neurons that use both DA and NT as transmitters have found that higher firing frequencies are required to elicit release of the peptide. The temporal pattern of impulses arriving at the nerve terminal also determines release characteristics: The release of many peptides is most prominent under conditions of burst firing, where neurons fire in very rapid succession (Bean and Roth, 1992).

Pituitary peptidesb Adrenal corticotropic hormone (ACTH) Melanocyte stimulating hormone (MSH) Oxytocin Vasopressin Hypothalamic releasing factorsc Corticotropin releasing hormone (CRH) Growth hormone releasing factor (GHRF) Luteinizing hormone releasing hormone (LHRH) Thyrotropin releasing hormone (TRH) Others Angiotensin Calcitonin gene-related peptide (CGRP) Cocaine- and amphetamine-related transcript (CART) Melanocyte concentration hormone (MCH) Neurotensin Hypocretin /Orexin a Peptides first found in the gut and later shown to serve as neurotransmitters in the brain. b Peptides first discovered as pituitary hormones and later shown to serve as neurotransmitters in the brain. c Peptides first discovered for their role as hypothalamic release hormones and later shown to serve as neurotransmitters in the brain.

to yield two mRNAs. The two transcripts are present in equal abundance in most brain areas. Different molar ratios of NT and NMN are found in some tissues because of differential processing of the prohormone (Kitabgi et al., 1992). Classical neurotransmitters are usually packaged in small (10,000

720

0.5

5-HT2C

>10,000

10

11

5,100

25

1

5-HT1D

>10,000

1,900

800

6,200

170

2

5-HT reuptake

1,700

5,000

ND

ND

1,300

50

NE reuptake

210

0.4 3

4,700

500

ND

ND

>10,000

50

a1

6

7

19

7

1

10

a2

360

8

230

90

1

200

H1

440

1

3

11

20

50

5-HT6

9,600

14

10

33

2,200

130

5-HT7

1,200

100

150

130

2

23

Muscarinic

5,500

2

2

>1,000

>1,000

>1,000

Source: The data in this table were taken from the following references and compiled by Dr. Robert A. Lahti (Leysen et al., 1994; Bymaster et al., 1996; Lahti et al., 1996). 5-HT: 5-hydroxytryptamine; NE: norepinephrine.

has been documented in all patient groups evaluated, even in treatment-resistant persons with schizophrenia. The high D2 occupancy of haloperidol has suggested this as a mechanism not only for its antipsychotic action but also for its parkinsonism and akathisia side effects. Haloperidol occupancy of the striatal D2 receptor in schizophrenic patients is dose-dependent; measurable occupancy of the D2 receptor with chronic treatment remains extends approximately 1 week after drug withdrawal and is not detectable in vivo at 2 weeks (Tamminga et al., 1993). Haloperidol lacks measurable occupancy at the cortical 5-HT2 receptor using PET with 11C-N-methylspiperone (11C-NMSP). Functional imaging studies have addressed the question of where in the central nervous system (CNS) haloperidol exerts its therapeutic actions (Holcomb et al., 1996). Our own work in this area has shown that haloperidol increases neuronal activity as measured by regional cerebral blood flow (rCBF) in the human striatum, in dorsal and ventral regions. In addition, haloperidol increases neuronal activity in the thalamus and decreases glucose metabolism in the frontal cortex and anterior cingulate with minimal regional alterations in other CNS areas (Holcomb et al., 1996). We have speculated that haloperidol reduces psychosis by exerting its initial action in the striatum at the D2 DA receptors and than by transmitting this action to thalamus and fron-

tal and limbic cortex using the well-described neuronal circuits connecting the basal ganglia, thalamus, and cortex (Alexander and Crutcher, 1990). Although actions of other antipsychotics at other receptor sites (for example, serotonin receptors) may be exerted primarily in neocortex, we speculate that the antidopaminergic actions of antipsychotics are initiated in the striatum and then transmitted in a secondary and tertiary manner to cortex through the brain’s own neural pathways (Alexander and Crutcher, 1990). In addition, haloperidol could have primary actions in multiple different brain regions to deliver its clinical effect. Efficacy The antipsychotic efficacy of haloperidol was initially established in controlled trials in the early 1960s (Davis, 1969); it is a highly effective antipsychotic, useful at low doses. But it was not until recently that a dose-response study was conducted across the apparent dose-sensitive range for haloperidol. Three doses of haloperidol (4, 8, and 16 mg/day) were tested against placebo in a multicenter controlled trial (Zimbroff et al., 1997). The study results showed haloperidol to be highly effective in schizophrenia. There was no linear dose-response relationship with any symptom or symptom cluster across this dose range, as has been previously suggested for APDs.

24: PHARMACOTHERAPY OF SCHIZOPHRENIA

Side effects and safety In the above dose study, haloperidol produced significant parkinsonism on the Simpson–Angus Scale (SAS) and akathisia on the Barnes Akathisia Scale (BAS) across all the doses used, even at the lowest dose of 4 mg/day. There were no relationships between drug dose and motor side effects in the 4 –16 mg/day range. Other side effects of haloperidol were low, including cardiovascular, anticholinergic, and hematological. No QTc prolongation occurs with haloperidol. Hepatotoxicity is a rare side effect. These safety results are consistent with years of clinical experience using haloperidol. SECOND-GENERATION ANTIPSYCHOTICS: BROAD PROFILE RECEPTOR ANTAGONISTS Some second-generation APDs block many monoamine and other G protein–coupled receptors in brain and have a broad receptor affinity profile (Table 24.2). Their spectrum of receptor antagonist activity is extensive, and their overall clinical action is neurochemically complex. The APDs described here are available for prescription in the United States; additional compounds may be available in other countries (for example, amisulpride), even though not described in detail here.

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Clozapine was the first antipsychotic shown to have anatomically restricted electrophysiological actions on DA neurons; clozapine induces depolarization blockade in the mesolimbic (A10) DA neurons but not in the nigrostriatal (A9) cells (Grace et al., 1997). The association of this distinctive preclinical characteristic with the drug’s low motor side-effect profile in humans is broadly consistent with the idea that antipsychotic actions are generally mediated through the A10 dopaminergic neurons and motor side effects through the A9 group. Consistent with clozapine’s action in the depolarization inactivation model has been its selective functional anatomy using cFos in situ hybridization autoradiography and Fos protein immunohistochemistry (Robertson et al., 1994). These studies show that clozapine stimulates immediate early gene (IEG) expression in rats in mesolimbic projection fields of the DA cell bodies (nucleus accumbens, ventral striatum, anterior cingulate, and medial prefrontal cortex) but not in the nigrostriatal projections to the dorsal striatum (A9). The mechanism subserving this anatomical selectivity of clozapine’s action remains unknown. Nonetheless, the principle that limited regional drug action in CNS is important to schizophrenia pharmacology has been repeatedly demonstrated. Moreover, the failure of clozapine to induce dyskinesias in the neuroleptic-sensitized monkey (Casey, 1996) or to cause oral dyskinesias in chronically treated rats (Gunne et al., 1982) is consistent with these observations.

Clozapine (Clozaril) Clozapine is an APD that, although it has led the “second-generation drug” era, is not itself new. Its demonstration of superior efficacy over chlorpromazine in treatment-resistant patients with schizophrenia spurred subsequent research in this area (Kane et al., 1988). It is the only antipsychotic shown so far to have superior antipsychotic action in schizophrenia compared with the traditional and the new compounds. Its mechanism in this regard remains unknown. Pharmacology Clozapine has a broad affinity for many receptors in brain. Not only the DA receptors (D1, D5, D2, D3, D4) but also serotonin (5-HT2A, 5-HT2C, 5-HT6, 5-HT7), noradrenergic (a1 and a2), cholinergic (nicotine and muscarinic), and histamine (H1) receptors are blocked by clozapine. Clozapine affinities are generally low at all sites (Table 24.2). Consistent with this profile, clozapine blocks not only DA agonist–stimulated behaviors but also cholinergic-, serotonergic-, and noradrenergicstimulated neurochemical and behavioral actions in animals. Clozapine inhibits conditioned-avoidance behavior but does not produce catalepsy. Clozapine does not measurably alter DA metabolite concentrations in striatum but does increase metabolites (DOPAC) in the rat nucleus accumbens (Coward, 1992).

Metabolism and pharmacokinetics Clozapine has several metabolites, the two most abundant of which are norclozapine and N-desmethylclozapine. Too little data are available concerning clozapine catabolism and the activity of its metabolites. N-desmethylclozapine has been identified as an active clozapine metabolite with a clozapine-like affinity profile, except for showing muscarinic cholinergic agonist activity instead of anticholinergic activity (Weiner et al., 2004). This compound, known as ACP104, is being developed for psychosis and for cognitive dysfunction in schizophrenia. For clozapine, single-dose kinetic analysis with a 200 mg oral dose found the Tmax to be 3 +/– 1.5 hours and the Cmax to be 386 +/– 249 ng/ml. The distribution half-life (Ta1/2) is 0.1 +/–.12 hours, and the elimination half-life (TB1/2) is 10.3 +/– 2.9 hours. Plasma concentrations show a linear relationship to dose with multiple dose kinetics. Interindividual variability in metabolism is high. Terminal elimination is linear. In vivo imaging Clozapine occupies measurably fewer striatal DA receptors at clinically effective doses than do traditional neuroleptics (Farde et al., 1992). Using 11C-Rac and positron emission tomography (PET), occupancy is 40%–60%; with 11C-NMSP, occupancy is 15%–30%. At the same

334

PSYCHOSES

doses, clozapine occupies 80%–90% of serotonin receptors in cortex, consistent with its in vitro affinity profile. The profile of reduced DA receptor occupancy in striatum and increased serotonin receptor occupancy in cortex is characteristic of second-generation antipsychotics (Kapur et al., 1999). Functional imaging data show that clozapine, like haloperidol, increases rCBF in striatum, but clozapine does this only in the ventral striatum and to a lesser degree. Moreover, clozapine differs from haloperidol in that it increases (not decreases) neuronal activation in the anterior cingulate cortex and in the middle frontal gyrus, areas that are important to core cognitive functions such as attention and working memory. During task performance, clozapine “normalizes” rCBF in several areas of frontal cortex, especially in the anterior cingulate cortex (Lahti et al., 2003). These broad differences in cerebral activation patterns between clozapine and haloperidol likely represent in some way the unique clinical action of clozapine in schizophrenia and could, with further study, be developed as a surrogate marker of that action. Efficacy The general antipsychotic efficacy of clozapine was established more than 20 years ago. However, because of clozapine’s higher side-effect burden, including agranulocytosis, the Food and Drug Administration (FDA) required Sandoz to demonstrate its superiority to traditional antipsychotics. Kane and colleagues (1988) demonstrated clozapine to be superior to chlorpromazine in treating treatment-refractory inpatients with schizophrenia. Subsequently, several additional studies confirmed this unique action (Conley, Carpenter, and Tamminga, 1997). Moreover, its superior efficacy in treating partial nonresponding populations was also demonstrated (Kane et al., 2001). Arguably the most convincing demonstration recently of clozapine superiority was in Phase 2 of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) trial where the time to treatment discontinuation and the decrease in Positive and Negative Syndrome Scale (PANSS) scores was greatest by a substantial margin for clozapine compared with three other second-generation antipsychotics (SGAs) (McEvoy et al., 2006). Whether clozapine has superior efficacy in treating primary negative symptoms has been widely debated; the answer is suggested but is still not clear (Davis et al., 2003). Optimal studies where drug action on negative symptoms can be clearly differentiated from secondary effects or lack of drug side effects have not yet been reported. Some cognitive dysfunctions are improved by clozapine, and others are worsened. In clinical populations with drug abuse comorbidity, clozapine is also more effective. Although the final composite outcomes remain to be demonstrated, the longterm psychosocial improvement with clozapine suggests

cognitive improvement. There is no doubt that clozapine increases discharge rates from hospital care and improves community function after discharge (Rosenheck et al., 1997; Love et al., 1999). Side effects and safety Acute motor side effects with clozapine are very low, if detectable at all, including parkinsonism and akathisia. In addition, clozapine appears by all estimates to have an extremely low (if any) incidence of tardive dyskinesia. Moreover, clozapine treatment of tardive dyskinesia allows dyskinetic symptoms to fade gradually over 6–12 months (Tamminga et al., 1994). With respect to other side effects, clozapine is at the top of any list. It causes agranulocytosis with an incidence of 0.5%–1%, a condition that has 3%–15% mortality. The risk of agranulocytosis is highest in the 2nd and 3rd months after beginning treatment; the risk is reduced after the first 6 months and remains flat and relatively low (comparable to other APDs) after the first 12 months of treatment. In addition, the drug can induce seizures, increase heart rate, and stimulate cardiac arrhythmias. It causes weight gain, substantial in some instances, and alters carbohydrate metabolism and plasma lipid levels producing the metabolic syndrome (Allison et al., 1999; Wirshing et al., 1999; Henderson et al., 2000; McEvoy et al., 2006). It also causes other, less medically significant but bothersome side effects like sedation and drooling. It is surprising that, with this serious side-effect profile, clozapine is used at all. Its superior efficacy is the reason, in those situations where efficacy is needed, that the drug’s substantial side-effect profile is tolerated. Moreover, many clinicians contend that the drug is underused. Olanzapine (Zyprexa) Olanzapine is a structural congener of clozapine. It is the third of the new antipsychotics available in the United States, preceded to market by clozapine and risperidone. As would be predicted from its pharmacology, olanzapine has many of the same pharmacological characteristics as clozapine (for example, its affinity at multiple receptors) with several significant exceptions in terms of pharmacology (for example, high not low receptor affinities), side effects (for example, no agranulocytosis) and efficacy (equal, but not superior). Pharmacology Olanzapine has a high affinity for a broad range of CNS receptors at clinically relevant concentrations, including DA (D1–D5), serotonin (5-HT2A, 5-HT2C, 5-HT6), noradrenalin (a1), acetylcholine (muscarinic, particularly M1), and histamine (H1) receptors. It is a potent ligand

24: PHARMACOTHERAPY OF SCHIZOPHRENIA

at all of these receptors, with a high affinity at each site (Table 24.2). Different from clozapine, it lacks high affinity for the 5-HT7, a2, and other cholinergic receptors (Bymaster et al., 1996). Olanzapine blocks conditioned avoidance responding in rats but causes catalepsy only at high doses. Olanzapine increases DA and norepinephrine metabolite levels in nucleus accumbens and reduces acetylcholine levels in striatum. Moreover, unlike haloperidol, olanzapine also increases DA and norepinephrine release in frontal cortex (Bymaster et al., 1996). Olanzapine blocks DA and serotonin-stimulated biochemical changes and animal behaviors; its antiserotonin actions are more potent than its antidopaminergic actions. With chronic treatment, olanzapine significantly but minimally upregulates D2 receptors in striatum (Sakai, Gao, Hashimoto, and Tamminga, 2001); in addition, olanzapine, like clozapine, exerts a regional action on DA-containing neurons. With chronic treatment, olanzapine produces depolarization blockade in A10 DA neurons but not in the A9 cells (Skarsfeldt, 1995). Olanzapine also shows selective activation of the c-Fos IEG gene in ventral striatum and in medial prefrontal cortex without inducing c-Fos messenger ribonucleic acid (mRNA) in the dorsal striatum (Robertson and Fibiger, 1996). Consistent with this regional action, olanzapine produces dystonias in neuroleptic-sensitized monkeys only at high doses, above its clinically effective dose ranges (Casey, 1996) and fails to produce a high rate of oral dyskinesias (purposeless chewing) in chronically treated rats (Sakai Gao, and Tamminga 2001). Metabolism and pharmacokinetics Olanzapine has two primary metabolites, 4-N-desmethyl olanzapine and 10-N-glucuronide olanzapine, both of which are inactive as antipsychotics. The parent drug has weak affinity for several different hepatic isoenzyme systems, including CYP-2D6, –1A2, –34A, and – 2C19; thus, significant drug–drug interactions on this basis are minimal. Tmax for olanzapine is 5 hours, and the drug has a mean plasma elimination half-life (TB1/2) of 31 hours (range: 21–54 hours). Plasma kinetic studies suggest linear dose proportionality. Female participants show slower metabolism and consequently higher plasma levels than male participants. Concurrent cigarette smoking and carbamezapine use accelerate metabolism and lower olanzapine levels modestly. In vivo imaging In preliminary human PET studies, olanzapine shows approximately 60% occupancy at the striatal D2 receptors when evaluated with 11C-Rac/PET after an acute 10 mg dose (Farde et al., 1997), a lower striatal DA receptor occupancy than that of the traditional antipsychotics. The low motor side effects seen with olanzapine

335

are consistent with the Farde et al. (1992) proposition that it takes a D2 occupancy greater than 70% to induce acute motor side effects. More recent occupancy studies with olanzapine are consistent with these early data (Kapur et al., 1998). In preliminary studies comparing the functional activation properties of olanzapine to those of haloperidol, it is easy to see that olanzapine is associated with reduced rCBF activation in basal ganglia and thalamus, like clozapine, and increased rCBF activation in anterior cingulate and temporal cortex, also like clozapine. Efficacy Olanzapine’s efficacy is based on four large placeboand haloperidol-controlled multicenter registration trials (Beasley et al., 1997; Tamminga and Kane, 1997). Consistently in all of these trials, olanzapine showed a substantial antipsychotic response in patients with actively psychotic schizophrenia, significantly greater than that of placebo on positive and negative symptoms, and equivalent to that of haloperidol on positive symptoms. There was an indication that olanzapine is more effective than haloperidol in treating negative symptoms. Whether the antinegative symptom response to olanzapine involves primary or secondary negative symptoms has been debated, although the results of a path analysis are consistent with a drug action on primary negative symptoms (Tollefson et al., 1997). Further work in this area is needed to distinguish the primary from the secondary nature of its negative symptom action. In treatment-resistant inpatients with schizophrenia, olanzapine has been compared to chlorpromazine in a trial design mimicking the clozapine-chlorpromazine trial (Kane et al., 1988). At a fixed dose of 25 mg/day, the action of olanzapine on psychotic symptoms was found to be similar to the action of chlorpromazine; no significant differences in efficacy on psychosis emerged between the two drugs in this population, except that olanzapine imparted a significant antianxiety effect (Conley, Tamminga and Beasley, 1997). In addition to schizophrenia, olanzapine currently has an indication in the treatment of mania (Tohen and Zarate, 1998). Several non-industry-sponsored, naturalistic studies have been conducted to answer the question of comparative efficacy across the SGA compared with FGA. CATIE found that olanzapine, in modal daily doses of 20.1 mg, showed the greatest improvement in effectiveness, including a low rate of discontinuation, a greater initial reduction in psychopathology, a longer duration of successful treatment, and a lower rate of hospitalization for relapse among SGAs (Lieberman et al., 2005). The Cost Utility of the Latest Antipsychotic Drugs in Schizophrenia Study (CUtLASS) study contrasted a group of FGAs with SGAs (including olanzapine) and showed no difference between the two groups of drugs on Quality of Life or on any of their secondary outcome measures;

336

PSYCHOSES

individual analyses were not done for each drug (Jones et al., 2006). A meta-analysis of FGA and SGA efficacy studies reports that olanzapine shows a modest but significant overall advantage over FGAs with an effect size of 0.21 but is not significantly different from the other SGAs (Davis et al., 2003). Leucht found that, as a group, the SGAs were modestly but significantly better on rate of relapse and failure to respond than the FGAs (Leucht et al., 2003). Rosenheck has found no advantage of olanzapine on overall cost effectiveness in treating chronic schziophrenia (Rosenheck et al., 2003; Rosenheck et al., 2006). Side effects and safety Motor side effects with olanzapine are remarkably and significantly diminished from those seen with haloperidol (Beasley et al., 1996; Tamminga and Kane, 1997). This finding is consistent across studies, thus providing confidence from replication. On average in the controlled trials, parkinsonism (SAS) and akathisia (BAS) were equivalent to placebo and lower than with haloperidol use. At the highest olanzapine dose, mild akathisia was evident, along with a low rate of anticholinergic drug use to treat motor side effects. Some evidence exists that this will translate into lower rates of tardive dyskinesia (Tollefson et al., 1997) Weight gain and other metabolic side effects occur with olanzapine treatment; these changes pose a substantial risk factor for diabetes and heart disease. The metabolic side effects (weight gain, increases in cholesterol, triglycerides, and glycosylated hemoglobin) have been widely documented (Osser et al., 1999; Bettinger et al., 2000; Lieberman et al., 2005; McEvoy et al., 2006). Relative to other SGAs, olanzapine shows the greatest metabolic syndrome burden along with clozapine, followed by quetiapine and then risperidone. In addition, mild anticholinergic actions are evident with olanzapine treatment, including dry mouth and constipation. Few cardiac side effects have been noted with olanzapine, including no blood pressure elevations, tachycardia, electrocardiographic changes, or significant QTc prolongation (Glassman and Bigger, 2001). In addition, no blood dyscrasias have been associated with olanzapine use, a side effect closely evaluated because of the structural similarity between olanzapine and clozapine. Transient dose-sensitive increases in hepatic transaminanses have been noted, but these occur infrequently and attenuate with continued treatment. Initial prolactin elevations occur but are lower than those seen with haloperidol and showed almost complete tolerance over time. Quetiapine (Seroquel) Although from a different chemical class, quetiapine displays many biochemical and behavioral similarities to clozapine. Quetiapine has broad and low receptor

affinity characteristics and many of the behavioral actions of clozapine. Quetiapine is the fourth antipsychotic marketed in the United States and has become widely prescribed. Its sleep-enhancing properties probably deriving from its potent 5-HT2A activity determine some portion of its prescription base. Pharmacology Quetiapine comes from the chemical class of dibenzothiazapine drugs. The drug binds to the D1, D5, D2, D3, D4, 5-HT2, 5-HT1A, a1, and a2 receptors, as does clozapine, but lacks clozapine-like affinity for the muscarinic cholinergic receptors. Its affinity to all of these receptors is low, similar to clozapine (Table 24.2). Quetiapine fails to potently upregulate D2 DA receptors in striatum with chronic treatment, suggesting its low affinity as a DA antagonist. But it increases DA metabolites in striatum as well as in nucleus accumbens with acute administration; it shows an acute but short-lived action on increasing plasma prolactin in rats. The anatomical selectivity of quetiapine in the depolarization block model is not yet clear (conflicting study findings have been reported). However, it shows selective action on regional c-Fos activation, similar to that of clozapine, in that it fails to activate Fos proteins in the dorsal striatum. Quetiapine inhibits conditional avoidance responding at high concentrations; it blocks DA agonist– induced behaviors in rats such as eye blink, climbing, and locomotor activity. Quetiapine induces catalepsy only at very high doses that are no longer clinically relevant (Saller and Salama, 1993). In neuroleptic sensitized Cebus monkeys, quetiapine induces mild dystonias only in a high dose range, which is probably not clinically significant (Casey, 1996). Metabolism and pharmacokinetics Acute kinetics are linear; the drug shows good oral bioavailability. The elimination half-life (TB1/2) is approximately 6 hours. Plasma concentrations at steady state are linear up to a dose of 600 mg/day; for example, daily doses of 75, 300, and 600 mg produce steadystate (trough) plasma levels of 13.9, 43.9, and 91.1 ng/ml, respectively. Drug clearance is reduced in elderly persons with schizophrenia, perhaps by 50%; therefore, in elderly patients, the dose should be reduced. In vivo imaging Preliminary imaging studies of quetiapine using 11C-Rac/ PET show occupancy in striatum at 2 hours of 44% and at 12 hours of 27% at the DA receptor. With 11CNMSP/PET, quetiapine shows occupancy in cortex at the serotonin receptor of 72% (2 hours), and 50% (at 24 hours). More recent imaging studies are consistent but show short-lived occupancy (Kapur et al., 2000).

24: PHARMACOTHERAPY OF SCHIZOPHRENIA

Efficacy Quetiapine demonstrates antipsychotic action significantly greater than that of placebo in several placebocontrolled trials at doses of 150–750 mg/day and action equivalent to that of haloperidol. Although this drug was initially recommended for use in schizophrenia at 300 mg/day, many clinicians suspect that a much higher dose is optimal, closer to or above 750 mg/day. Therapeutic action on positive and negative symptoms of psychosis has been demonstrated, with the magnitude of its antipsychotic effect significantly greater than that of placebo in each domain and equivalent to that of haloperidol (Arvanitis and Miller, 1997). The CATIE1 study showed that quetiapine, in a modal dose of 543.4 mg/day, showed effectiveness outcomes similar to the other SGAs (except clozapine and olanzapine) but had the largest percentage of volunteers who dropped the study before its 18-month end (82%) (Lieberman et al., 2005). In CATIE-2, quetiapine was modestly but significantly less effective than olanzapine or risperidone (Stroup et al., 2006). Studies show that quetiapine has actions on promoting sleep quality and efficacy in Bipolar-2 Disorder depression. Side effects and safety Routine safety parameters show a relatively benign safety profile for quetiapine in many respects. Almost no motor side effects accompany its use; no episodes of extrapyramidal adverse events beyond placebo levels have been reported. No anticholinergic medication use beyond that of placebo has been necessary in any dose group. No akathisia is apparent. The most frequently observed side effects are sedation, somnolence, and headache. Significant weight gains occur accompanied by hyper-cholesterolemia and -triglyceridemia, although to a lesser degree than with olanzapine or clozapine (Lieberman et al., 2005). Alterations in cholesterol metabolism are being studied. Transient and reversible increases in hepatic transaminase levels can be seen. No prolactin elevations are apparent in the 6–8-week parallel group studies comparing any dose group to placebo use. Although cataracts have been observed in some animal studies, no evidence to support the onset of cataracats has been found in humans. No significant QTc prolongtion occurs with quetiapine (Glassman and Bigger, 2001). NEW ANTIPSYCHOTICS: SELECTIVE DOPAMINE AND SEROTONIN RECEPTOR ANTAGONISTS Selective DA and serotonin receptor blockers show effective antipsychotic action and preserve advantageous motor side-effect profiles. These second-generation drugs

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show greater serotonin than DA blockade, pharmacologically and in occupancy studies. Risperidone (Risperdol) Risperidone was the first second-generation drug presented to the FDA and reviewed by them in approximately 15 years. This long hiatus without new drug products for treating psychosis made clinicians and consumers eager to use this first new drug. Risperidone has been well received and widely prescribed for schizophrenia. It is approved for bipolar disorder with psychosis as well. Pharmacology Risperidone is a benzisoxazol derivative with high affinity for the 5-HT2A and D2 receptors. Its in vitro affinity for 5-HT2A is 20 times higher than for D2 receptors; its affinity for other serotonin receptor subtypes is lower by two or more orders of magnitude (Table 24.2). Risperidone has moderate affinity for a1 noradrenergic and H1 histamine receptors and even lower affinity for a2 sites. It lacks significant affinity for cholinergic receptors, for the sigma site, and for the D1 receptor family. The major metabolite of risperidone, 9-hydroxyrisperidone, is active and has a receptor affinity profile similar to that of its parent compound (Leysen et al., 1994). The pharmacology of 9-OH risperidone accounts for many of the actions of risperidone itself given its extensive metabolism and the long half-life of the metabolite. Risperidone blocks serotonin and DA agonist–induced behaviors in animal paradigms, with greater serotonergic than dopaminergic potency. It has no anticholinergic activity in behavioral or neurochemical tests. Risperidone increases DA turnover in frontal cortex and in the olfactory area but is less active in striatum (Fink-Jensen and Kristensen, 1994). It induces catalepsy in rats only at relatively high doses, but it induces dystonias in sensitized Cebus monkeys at clinically relevant concentrations (Casey, 1996). Risperidone has a similar effect on A9 and A10 DA neurons in the depolarization inactivation model, but its actions on both cell groups are atypical. At low dose levels, risperidone fails to stimulate c-Fos expression in the dorsal striatum, whereas it activates the IEG briskly in the nucleus accumbens. Preclinically, the profile for anatomical selectivity is mixed and leaves questions about predictions for human motor side effects. Metabolism and pharmacokinetics Risperidone is metabolized by the liver isoenzyme CYP2D6. Its major metabolite is 9-hydroxyrisperidone (9-OH-R) and is pharmacologically active. Because the

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metabolite is renally excreted, hepatic and renal metabolism is important to overall risperidone clearance. Individual genetic variation of the CYP2D6 isoenzyme and other concomitant 2D6-metabolized medications (for example, fluoxetine) significantly alter drug clearance and plasma concentrations. After a single 1 mg dose of risperidone, Tmax is 1 hour for risperidone and 3 hours for 9-OH-R; TB1/2 for risperidone is 3.6 hours, and for 9-OH-R it is 22 hours. Kinetics are dose proportional up to 10 mg. In extensive metabolizers, TB1/2 is 2.8 hours, whereas for poor metabolizers it is 21.0 hours. The TB1/2 of 9-OH-R remains 20–22 hours in both groups of metabolizers because its excretion is renally dependent. Also, in individuals who are renally impaired and in the elderly, overall risperidone metabolism and excretion are reduced (Ereshefsky and Lacombe, 1993).

clozapine (McEvoy et al., 2006). In the Davis (Davis et al., 2003) meta-analysis, comparing SGAs to efficacy of FGAs, risperidone showed a modest but significant positive difference from FGAs with an effect size of 0.25. The 9-OH metabolite of risperidone (developed as paliperidone; marketed as Invega) has pharmacological effects that largely match those of risperidone, as expected (Kane et al., 2007; Kramer et al., 2007; Marder et al., 2007). Side effects and safety

With a 1 mg oral dose of risperidone, D2 occupancy measured in striatum with 11C-Rac/PET was 50% (range: 40%–64%). The 5-HT2A occupancy measured in cortex using 11C-NMSP/PET was 60% (range: 45%–68%). Occupancy is dose proportional; thus, risperidone shows high occupancy with high doses (Kapur et al., 1999). Chronic risperidone treatment at low but clinically effective doses results in D2 occupancy in striatum of less than 70% (Nyberg et al., 1993).

Motor side effects with risperidone are at placebo levels at doses below 6 mg/day. At doses above 10 mg/day, parkinsonism and akathisia are significant and probably similar to those with haloperidol. Anticholinergic drug use is also at placebo levels below 6 mg/day but progressively approaches the haloperidol use rate above 10 mg/day. Thus, below 6 mg/day of risperidone, parkinsonian motor side effects are minimal but rise thereafter. Agitation, anxiety, sedation, and insomnia have been reported with risperidone, but at rates similar to those of haloperidol. Hypotension was noted in normal volunteer studies but was not selectively noted in volunteers with schizophrenia. The QTc is not affected by risperidone. Hyperprolactinemia is common, and frank galactorrhea can occur with risperidone. Mild weight gain occurs; alterations in carbohydrate or lipid metabolism should be monitored.

Efficacy

Ziprasidone (Geodon)

Risperidone has been studied worldwide in patients who are actively psychotic with schizophrenia. Its actions have been evaluated on positive and negative psychotic symptoms across a broad dose range (2–16 mg/day) in several large multicenter trials, with largely consistent findings. Risperidone treatment results in a significant reduction in positive and negative symptoms compared to placebo; positive symptoms respond to risperidone to a similar extent as haloperidol; the negative symptom response may be greater (Marder and Meibach, 1994). A risperidone dose of 3–6 mg/day produces the best overall outcome of the doses tested, including its effects on positive and negative symptoms. These results are consistent across several risperidone efficacy studies, suggesting a U-shaped dose-response curve, with the greatest psychosis response occurring at a daily dose of 3–6 mg/day. Moreover, population survey data confirm physician use of lower doses of risperidone preferentially, with a good outcome (Love et al., 1999). In the CATIE-1 study, risperidone showed a modest but significantly lower effectiveness than olanzapine (Lieberman et al., 2005), whereas in CATIE-2, it showed equivalent effectiveness (Stroup et al., 2006); in treatment nonresponders, risperidone was less effective than

Ziprasidone was the fifth new antipsychotic to come to market. It was developed on the basis not only of its aminergic receptor binding profile (5-HT2.DA2) but also its unique reuptake blockade property with the serotonin and noradrenergic reuptake proteins. This has encouraged the speculation that ziprasidone will treat schizophrenia with depression and/or anxiety, a question still not fully answered. The side-effect profile of ziprasidone has received considerable attention: on the negative side, due to the QTc prolongation, and on the positive side, due to the lack of any significant weight gain or alterations of cholesterol or lipid metabolism.

In vivo imaging

Pharmacology The receptor binding profile of ziprasidone is distinctive in several respects. Its affinity for the D2 family of receptors is high; 10-fold higher is its affinity for the 5-HT2A receptor. Thus, the 5-HT2A/DA ratio is the highest among the second-generation drugs. Moreover, it has significant affinity for several additional serotonin receptors, including 5-HT1A, 5-HT2C, and 5-HT1D (Table 24.2). Ziprasidone is a partial agonist at the 5-HT1A receptor and thereby increases extracellular DA levels

24: PHARMACOTHERAPY OF SCHIZOPHRENIA

in medial frontal cortex (Sharma and Shapiro, 1996; Daniel et al., 1999). It also acts as an antagonist at its other receptors. It is unique among the new antipsychotics in showing moderate affinity for and inhibition of the 5-HT and norepinephrine receptor proteins, comparable to the action of amitriptyline (Seeger et al., 1995). Moreover, it lacks significant affinity for the muscarinic M1 receptor (Seeger et al., 1995). Behaviorally, ziprasidone is a potent inhibitor of DAand serotonin-mediated behaviors; it is sixfold more potent in inhibiting serotonergic than dopaminergic behaviors. It inhibits conditioned avoidance responding in rats. It decreases spontaneous locomotor activity and causes catalepsy, but the latter only at relatively high doses, thought to be no longer clinically relevant. Ziprasidone appears to affect equally DA cell firing in A9 and A10 neurons with chronic administration; therefore, it lacks the clozapine-like anatomical selectivity on dopaminergic function.

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across a dose range of 40–160 mg/day to placebo and haloperidol at 15 mg/day. Ziprasidone demonstrated significant antipsychotic actions over the dose range of 80–160 mg/day (40–80 mg bid). Therapeutic action on positive symptoms was equivalent to that of haloperidol and comparable to that of other second-generation antipsychotics; significant antinegative effects occurred compared to those of placebo (O’Connor et al., personal communication, 1997; Daniel et al., 2001). In patients with clinically significant depressive symptomatology at baseline, ziprasidone produced an antidepressant effect (Daniel et al., 2001). In the CATIE-1 study, ziprasidone at a modal dose of 112.8 mg/day showed modestly but significantly lower effectiveness than olanzapine (Lieberman et al., 2005), and in CATIE-2, when contrasted with olanzapine, risperidone, and quetiapine in a similar dose range, showed a similar level of low effectiveness (Stroup et al., 2006). Side effects and safety

Metabolism and pharmacokinetics Ziprasidone is metabolized by several hepatic and extrahepatic enzyme systems; hence, its plasma levels are relatively unaffected by other concomitant medications. In metabolic inhibition studies with ketoconasole, the P450 enzyme inhibitor of CYP3A4, ziprasidone plasma levels were unaffected. Additional safety is imparted by ziprasidone’s multiple degratory drug routes. There appear to be no active metabolites of ziprasidone. The kinetics of ziprasidone are dose proportional at steadystate kinetics. At therapeutic doses, the Tmax is 4.7 +/– 1.5 hours and the elimination half-life (TB1/2) is 10 hours. In vivo imaging Full assessment of ziprasidone occupancy at the D2 receptor using PET (with 11C-Rac in striatum) and at the 5-HT2 receptor (with 18F-septoperone in cortex) was carried out in normal human volunteers prior to patient studies to allow rational dose selection. Participants received 40 mg of oral ziprasidone, and neurochemical scans were obtained at regular intervals over the next 36 hours, beginning at Tmax. At 4 hours, D2 occupancy in striatum was 79.4% and 5-HT occupancy in cortex was 98.5%. At 12 hours, D2 occupancy was 52.8% and 5-HT2 occupancy was 73.1%. Calculations from the model based on all the data predicted that at steady state with 40 mg ziprasidone administered bid, 5-HT2 occupancy would remain at 90% and D2 occupancy would average 75% (Bench et al., 1993; Bench et al., 1996). Efficacy Results from Phase II and III efficacy studies have been published. In these studies, ziprasidone was compared

Ziprasidone has been associated with a low rate of motor side effects at all of the doses tested, indistinguishable from placebo on SAS and BAS rating scales. The drug produced significantly lower levels of parkinsonism and akathisia than haloperidol. Moreover, anticholinergic drug prescriptions for motor side effects were at placebo levels (10%–15%) across the range of ziprasidone doses and were lower than with haloperidol at any dose (Daniel et al., 2001). Moreover, in contrast to several other new antipsychotics, ziprasidone causes no significant weight gain, either in the short term (Daniel et al., 2001) or in extended (12-month) trials. This advantage in avoiding weight gain is substantial relative to the other new antipsychotics in terms of cardiovascular health (Allison et al., 1999; Bettinger et al., 2000) and compliance (Silverstone et al., 1988). The advantage of ziprasidone on metabolic side effects and weight gain was also documented in the CATIE trials (Lieberman et al., 2005; Stroup et al., 2006). The most significant ziprasidone side effect is its mild but unequivocal effect on the QTc interval (Glassman and Bigger, 2001). In a rigorously conducted study to evaluate the extent of this drug side effect, the average QTc prolongation time with ziprasidone at peak plasma levels, at its highest recommended dose, was 20.3 ms (95% Confidence Interval [CI]: 14.2–26.4), and this was not increased with a specific metabolic inhibitor (with ketoconazole: QTc520.0 ms; 95% CI: 13.7–26.2). However, in its registration safety database of 7876 electrocardiograms from 3095 patients, only 2 individuals had a QTc interval of over 500 ms (a lower rate than with placebo). Last, the all-cause mortality for ziprasidone in its registration safety database was 1.6 deaths per 100 patient treatment years, well within the range of 1.0– 2.0 for all antipsychotics. Of additional and critical

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relevance is that ziprasidone has multiple routes of metabolic degradation, providing patients with a protection against a drug–drug interactions increasing ziprasidone plasma levels. Ziprasidone is currently marketed with the warning that it not be used in individuals with preexisting heart disease. Ziprasidone use should not be restricted further than the FDA guidelines recommend, especially because its other effects and side-effect advantages are substantial. Aripiprazole (Abilify) Aripiprazole was developed as a partial DA agonist with a high affinity for the D2 DA receptor (>90%) and low intrinsic activity ( 3 Episodes; Onset < age 30 (Kraepelin’s manic-depressive illness)

Bipolar

BP-I

BP-II

BPNOS

Unipolar

Cyclothymia

Psychotic

Nonpsychotic

Depressive Disorders < 3 Episodes; Onset < age 30

Major Depression

Psychotic

Dysthymia

Depressive Disorder-NOS

Nonpsychotic

The Bipolar Spectrum

FIGURE

25.2 Affective disorders in DSM-V: A proposal. BP: bipolar; NOS: not otherwise specified.

All of this research tends to invalidate the phenomenology, genetic, and treatment basis for the BP/UP dichotomy (Koukopoulos et al., 2005), yet such findings have not had much impact on changing that nosology to date. OUR CURRENT NOSOLOGY: PROMOTING MISDIAGNOSIS? Bipolar disorder is frequently misdiagnosed, and common reasons cited include lack of insight into mania by patients (Ghaemi, 1997), poor clinical assessment of mania (Sprock, 1988), and stigma (Johnson and Orrell, 1995), among others. But a key issue is also that because our current polarity-based nosology requires the presence of mania to diagnose bipolar disorder even though depression is the main morbidity of this illness (Judd et al., 2002), our nosology almost guarantees a notable amount of misdiagnosis of bipolar disorder (F. Goodwin and Jamison, 2007). Many clinicians and patients tend to think of “depression” as being equivalent to unipolar depression, something fundamentally different from bipolar disorder (Ghaemi et al., 2000). Whether or not this proves to be the case biologically, certainly one can say that it is not the case clinically: both conditions are characterized by depression as their most common and prominent feature (Mitchell et al., 2001). It has now been well-established that depressive symptoms tend to last longer than manic symptoms (F. Goodwin and Jamison, 2007), and that patients with bipolar disorder spend about one-half of their lives depressed, versus only about one-tenth of their lives manic or hypomanic (Ghaemi et al., 2000; Judd et al., 2002). Un-

fortunately, many clinicians and patients jump from the recognition of a major depressive syndrome directly to a diagnosis of unipolar depression without carefully ruling out bipolar conditions (Ghaemi et al., 2000). NEUROBIOLOGY OR CLINICAL DIAGNOSIS: WHICH COMES FIRST? As future neurobiological research evolves, the complementary nature of clinical research and neurobiological research needs to be carefully appreciated: the historical example of the debate between Sydenham and Harvey should not be forgotten (Osler, 1921). It would be a mistake, in our view, for neurobiological studies to be seen as a sufficient basis for nosological judgments. For example, in a neurobiologically driven nosology the diagnostic distinction between schizophrenia and bipolar psychosis would be undermined by observations of extensive neurobiological overlap between the two illnesses (Dutta et al., 2007). This view reflects what philosophers call a category error; it is important to differentiate between pathophysiology and etiology. Most neurobiological research involves pathophysiology—we can say that certain neurotransmitter systems, or other chemical changes in the brain or body, are involved when a person is acutely depressed, for example. This does not mean that those changes are the cause, or etiology, of the illness of major depressive disorder. The etiologies can be an environmental insult in pregnancy, or involve an infectious agent, or involve having certain genes, or some combination of these. These etiologies may eventually lead to depression through a mechanism that later entails changes in

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a neurotransmitter system. Varying etiologies can lead to the same clinical presentation via similar pathophysiological mechanisms called “final common pathways.” The category mistake is this: to conclude, based on final common pathways of pathophysiology, that all the etiologies are the same is a mistake. If one further concludes that all those illnesses are the same, one is further mistaken (Ghaemi, 2003). This need not be the case. In fact, sometimes the reverse is the case: multiple diagnostic etiologies can produce a single pathophysiological mechanism, as with varied infectious causes of the same clinical syndrome (Nahmias et al., 2006). In a nutshell, the neurobiology of pathogenesis is quite distinct from the neurobiology of ultimate etiology, and researchers should be aware of this distinction when considering nosological definitions (Ghaemi, 2003). Further, diagnostic validity is not dependent on therapeutic specificity (Murray and Murphy, 1978). A disease is a disease, whether or not there is a treatment for it, and whether or not there are one or many treatments for it. For instance, coronary artery disease can be treated by a variety of different medications as well as different surgical interventions. Similarly, psychotropic medications may affect many different symptom complexes, possibly mediated by common neurobiological mechanisms (van Praag et al., 1990). It does not follow, logically or biologically, that such symptom complexes should replace our clinical diagnoses (van Praag et al., 1990), nor that the biological similarities of drug effects invalidate clinical diagnoses based on observation of symptoms, correlated with course of illness and genetic evidence (Stahl, 2005). Clinical diagnosis should aid us in identifying etiologies of disease; as such work progresses, we may find that a single etiology leads to a single clinical syndrome, or that multiple etiologies lead to a single clinical syndrome, or that a single etiology leads to multiple clinical syndromes. The matter cannot be prejudged. And, those who would wish to replace clinical diagnoses, based on millennia of careful observation, with our neurobiological knowledge of today would do well to pay attention to the retardation of scientific progress when theory replaced observation in the Galenic era (Osler, 1921). It would be harmful to the progress of neurobiology if the early state of our knowledge today led to premature theorization in place of continued careful contact with the reality of unbiased clinical observation (Jaspers, 1998). Otherwise, even the most up-to-date current neurobiologically based nosology is bound to be, sooner or later, as outdated as 19th-century brain-based models are today (Jaspers, 1998). NEUROBIOLOGICAL IMPLICATIONS The above discussion is relevant to future trends in neurobiology because the direction that neurobiologi-

cal research takes partly depends on what kind of nosology we accept. In the case of contemporary nosology, which has been polarity based, neurobiological research has tended to focus on studies of the acute phases of mood disorders. Thus we have a large literature on the neurobiology of acute depression (Licinio and Wong, 2005), and a somewhat smaller literature on the neurobiology of acute mania (Soares and Gershon, 2000). These studies began by focusing on neurotransmitter systems and have extended to studies of abnormalities in other aspects of physiology, such as the hypothalamic pituitary adrenal (Gillespie and Nemeroff, 2005) or thyroid (Bauer et al., 2002) axes. Recent studies have further extended such studies into secondmessenger and genetic changes in acute depression or mania (Gould et al., 2007). Although immensely useful, this is only one of two major approaches that could have been taken. Neurobiological research could go in a completely different direction based on the other main perspective on the nosology of mood disorders: a recurrence-based nosology would direct research into the biology of recurrence (F.K. Goodwin, 1989), not the nature of acute phases. Mood cycling into and out of episodes would be the phenotype of interest, not the specific clinical features of the episodes. Such studies have begun to happen and have tended to occur mainly in the context of studies of circadian rhythms, sleep research, genetic studies, or long-term changes in neuroplasticity and neuronal circuits. THE NEUROBIOLOGY OF RECURRENCE: THE KINDLING PARADIGM As with all neurobiological research, theoretical models are needed to generate hypotheses for testing. These models include the kindling paradigm (Post et al., 1988), which builds on the physiological finding that intermittent subthreshold electrical or chemical stimuli produce increasingly strong neuronal depolarization in the brain, a process of sensitization that may possess temporal similarities to the episodic behavioral disturbances of recurrent mood disorders, with an emphasis on the bipolar subgroup (Post et al., 1988). As an explanatory model for these clinical phenomena, the kindling paradigm predicts that psychosocial stressors would be more frequent earlier in the course of illness, and that frequency of episodes would increase later in the course of illness (F. Goodwin and Jamison, 2007; Post, 2007). Post hypothesized that this process applies to at least a subgroup of patients with recurrent mood disorders (Post, 2007), though not necessarily all patients (S.R. Weiss and Post, 1994). This literature has been reviewed in detail elsewhere (F. Goodwin and Jamison, 2007). In sum, the majority, but not all, of the studies that have examined the kin-

25: DIAGNOSTIC CLASSIFICATIONS

dling hypothesis provide data that are consistent with the hypothesis. Although the issue is not settled, the accumulating empirical evidence suggests that the kindling hypothesis has had at least heuristic value in advancing our knowledge of the course of some forms of recurrent mood disorders, perhaps especially bipolar illness. The kindling hypothesis dovetails with neurobiological research that demonstrates that stress can activate a cascade of changes in the brain that play out over progressively longer time frames. In animal studies of kindling, investigators have reported changes in genetic expression (of c-Fos and thyroid-releasing hormone genes), as well as effects on glucocorticoid receptor expression, as a result of repeated intermittent electrical and chemical stimulation (Clark et al., 1994; Kim et al., 1996). These genetic changes are mediated by intermediary processes: the second-messenger systems that transmit information from the synapse to the cell nucleus. Many studies on the mechanisms of action of mood-altering drugs are now focusing on these postsynaptic changes (Manji, 1992; Manji et al., 1995; Bachmann et al., 2005; Gould and Manji, 2005; Gould et al., 2006; Gould et al., 2007) because it has long been noted that though the effects of treatments for mood disorders on neurotransmitters at the synaptic junction are immediate, the clinical effects on mood symptoms are delayed by weeks to months. In the investigation of these longer-acting and longer-lasting mechanisms, researchers have established a central role for G proteins and other secondmessenger systems in mediating the effects of drugs, the most extensively studied of which is lithium (Bachmann et al., 2005; Gould and Manji, 2005; Gould et al., 2006; Gould et al., 2007). THE NEUROBIOLOGY OF RECURRENCE: OTHER APPROACHES The neurobiology of recurrence can also be approached through other fields such as circadian rhythm, genetic, and animal behavior studies. Circadian rhythm research can be connected to some recent second-messenger research related to mechanisms of lithium action. Lithium has been shown to be a direct inhibitor of glycogen synthase kinase 3 (GSK3) (Gould and Manji, 2005), which has also been shown to be an essential component to the Drosophila circadian clock. Glycogen synthase kinase 3 knockout mice have a marked phase delay in their circadian rhythms, and an experimental study found that lithium produced a similar effect (Kaladchibachi et al., 2007). Genetic studies have also tended to find that recurrence is a major predictor of increased genetic loading for mood disorders (Levinson, 2006). An example of genetic studies relevant to recurrence is a study in

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which a polymorphism in the human CLOCK gene, associated with diurnal preferences of human healthy participants, was observed at a significantly higher recurrence rate in homozygotes for the C variant (Benedetti et al., 2003). Another approach would involve selective breeding for models of animal behavior that would reflect cycling into and out of animal models of depression and mania, rather than simply seeking to identify models of mania separately from models of depression. An example of potential for this kind of work has been published based on selective breeding of low as well as high motor activity in a swim test for rats (J.M. Weiss et al., 1998). FUTURE NEEDS Clinical work in the nosology of mood disorders needs to continue, and the profession needs to be open to incorporating this research into DSM-V and beyond. F. Goodwin and Jamison (2007) explicitly recommended that in DSM-V mood disorders should first be divided into those characterized by a significant degree of recurrence and those not so characterized. The UP/BP distinction would then be made among those with recurrent mood disorder (as was done in the original research supporting the UP–BP dichotomy). That is, the original meaning of unipolar was a type of recurrent mood disorder without mania/hypomania. In DSM IV (APA, 1994) unipolar has come to mean everything that is not bipolar. They also point out that the current DSM-IV definition of recurrent unipolar depression (more than one episode) is so broad as to be almost meaningless. Further, neurobiological research needs to be more flexible than our current nosology, with greater extension into a study of the neurobiology of recurrence. Also, premature theories based on the rapidly moving neurosciences should be avoided, and we should remain true to the Hippocratic tradition of the primacy of careful clinical observation for medical diagnosis. The two lines of research should go hand in hand: clinical and neurobiological work, independent of each other but connected, need to progress together, or not at all. REFERENCES Abraham, K. (1927) Notes on the psychoanalytical investigation and treatment of manic-depressive insanity and allied conditions. In: Bryan, D., and Strachey, A., eds. Selected Papers of Karl Abraham, M.D. London: Hogarth, pp. 137–156. Akiskal, H. (2000) Temperament and mood disorders. Harv. Ment. Health Lett. 16:5–6. Akiskal, H. (2002) Classification, diagnosis and boundaries of bipolar disorders. In Maj, M., Akiskal, H., Lopez-Ibor, J., and Sartorius, N., eds. Bipolar Disorder. London: Wiley, pp. 1–52. American Psychiatric Association. (1980) Diagnostic and Statistical Manual of Mental Disorders, 3rd ed. Washington, DC: Author.

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American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Andreasen, N.C. (2007) DSM and the death of phenomenology in America: an example of unintended consequences. Schizophr. Bull. 33:108–112. Angst, J. (1966) [On the etiology and nosology of endogenous depressive psychoses: A genetic, sociologic, and clinical study]. Monogr. Gesamtgeb. Neurol. Psychiatr. 112:1–118. Angst, J., and Marneros, A. (2001) Bipolarity from ancient to modern times: conception, birth and rebirth. J. Affect. Disord. 67:3–19. Bachmann, R.F., Schloesser, R.J., Gould, T.D., and Manji, H.K. (2005) Mood stabilizers target cellular plasticity and resilience cascades: implications for the development of novel therapeutics. Mol. Neurobiol. 32:173–202. Bauer, M., Heinz, A., and Whybrow, P.C. (2002) Thyroid hormones, serotonin and mood: of synergy and significance in the adult brain. Mol. Psychiatry 7:140–156. Benazzi, F. (2001) Depressive mixed state: testing different definitions. Psychiatry Clin. Neurosci. 55:647–652. Benedetti, F., Serretti, A., Colombo, C., Barbini, B., Lorenzi, C., Campori, E., et al. (2003) Influence of CLOCK gene polymorphism on circadian mood fluctuation and illness recurrence in bipolar depression. Am. J. Med. Genet. B Neuropsychiatr. Genet. 123:23–26. Berrios, G., and Porter, R. (Eds.). (1999) A history of clinical psychiatry. London: Athlone Press. Calabrese, J.R., Keck, P.E., Jr., Macfadden, W., Minkwitz, M., Ketter, T.A., Weisler, R.H., et al. (2005) A randomized, double-blind, placebo-controlled trial of quetiapine in the treatment of bipolar I or II depression. Am. J. Psychiatry 162:1351–1360. Cassidy, F., Murry, E., Forest, K., and Carroll, B.J. (1998) Signs and symptoms of mania in pure and mixed episodes. J. Affect. Disord. 50:187–201. Clark, M., Smith, M.A., Weiss, S.R., and Post, R.M. (1994) Modulation of hippocampal glucocorticoid and mineralocorticoid receptor mRNA expression by amygdaloid kindling. Neuroendocrinology 59:451– 456. Davis, L.L., Bartolucci, A., and Petty, F. (2005) Divalproex in the treatment of bipolar depression: a placebo-controlled study. J. Affect. Disord. 85:259–266. Dewhurst, K. (1962) Thomas Sydenham (1624-1689) reformer of clinical medicine. Med. Hist. 6:101–118. Dutta, R., Greene, T., Addington, J., McKenzie, K., Phillips, M., and Murray, R.M. (2007) Biological, life course, and cross-cultural studies all point toward the value of dimensional and developmental ratings in the classification of psychosis. Schizophr. Bull. 33(4):868–876. Engstrom, E. (2004) Clinical Psychiatry in Imperial Germany. Ithaca, NY: Cornell University Press. Evans, L., Akiskal, H.S., Keck, P.E., Jr., McElroy, S.L., Sadovnick, A.D., Remick, R.A., et al. (2005) Familiality of temperament in bipolar disorder: support for a genetic spectrum. J. Affect. Disord. 85:153–168. Franzek, E. (1990) Influence of Carl Wernicke on Karl Leonhard’s nosology. Psychopathology 23:277–281. Freud, S. (1917) Mourning and Melancholia. London: Hogarth. Ghaemi, S. (1997) Insight and psychiatric disorders: a review of the literature, with a focus on its clinical relevance for bipolar disorder. Psychiatric Annals 27:782–790. Ghaemi, S.N. (2003) The Concepts of Psychiatry. Baltimore: Johns Hopkins University Press. Ghaemi, S.N., Boiman, E.E., and Goodwin, F.K. (2000) Diagnosing bipolar disorder and the effect of antidepressants: a naturalistic study. J. Clin. Psychiatry 61:804–808. Gillespie, C.F., and Nemeroff, C.B. (2005) Hypercortisolemia and depression. Psychosom. Med. 67(Suppl 1):S26–S28.

Goldstein, S. (2002) Console and Classify: The French Psychiatric Profession in the 19th Century. Chicago: University of Chicago Press. Goodwin, F.K. (1989) The biology of recurrence: new directions for the pharmacologic bridge. J. Clin. Psychiatry 50(Suppl):40– 44; discussion 45–47. Goodwin, F., and Jamison, K. (2007) Manic Depressive Illness, 2nd ed. New York: Oxford University Press. Goodwin, G.M., Bowden, C.L., Calabrese, J.R., Grunze, H., Kasper, S., White, R., et al. (2004) A pooled analysis of 2 placebo controlled 18-month trials of lamotrigine and lithium maintenance in bipolar I disorder. J. Clin. Psychiatry 65:432– 441. Gould, T.D., Dow, E.R., O’Donnell, K.C., Chen, G., and Manji, H.K. (2007) Targeting signal transduction pathways in the treatment of mood disorders: recent insights into the relevance of the WNT pathway. CNS Neurol. Disord. Drug Targets 6:193–204. Gould, T.D., and Manji, H.K. (2005) Glycogen synthase kinase-3: a putative molecular target for lithium mimetic drugs. Neuropsychopharmacology 30:1223–1237. Gould, T.D., Picchini, A.M., Einat, H., and Manji, H.K. (2006) Targeting glycogen synthase kinase-3 in the CNS: implications for the development of new treatments for mood disorders. Curr. Drug Targets 7:1399–1409. Healy, D. (2001) The Creation of Psychopharmacology. Cambridge, MA: Harvard University Press. Hippocrates. (1952) On the sacred disease. In: Hutchins, R/M. ed. Hippocratic Writings: Great Books of the Western World, Volume 10. Chicago: Encyclopaedia Britanica, Inc, p. 159. Jackson, S. (1986) Melancholia and Depression: From Hippocratic Times to Modern Times. New Haven, CT: Yale University Press. Jaspers, K. (1986) An autobiographical account. In Ehrlich, E. L., and Pepper, G.B., eds. Karl Jaspers: Basic Philosophical Writings. Atlantic Highland, NJ: Humanities Press, p. 5. Jaspers, K. (1998) General Psychopathology. Baltimore: Johns Hopkins University Press. Johnson, S., and Orrell, M. (1995) Insight and psychosis: a social perspective. Psychol. Med. 25:515–520. Jouanna, J. (1999) Hippocrates. Baltimore: Johns Hopkins University Press. Judd, L.L., Akiskal, H.S., Schettler, P.J., Endicott, J., Maser, J., Solomon, D.A., et al. (2002) The long-term natural history of the weekly symptomatic status of bipolar I disorder. Arch. Gen. Psychiatry 59: 530–537. Kaladchibachi, S.A., Doble, B., Anthopoulos, N., Woodgett, J.R., and Manoukian, A.S. (2007) Glycogen synthase kinase 3, circadian rhythms, and bipolar disorder: a molecular link in the therapeutic action of lithium. J. Circadian Rhythms 5:3. Kant, I. (1998) Critique of Pure Reason. Cambridge, UK: Cambridge University Press. (Original work published 1781) Kendler, K.S., Karkowski, L.M., and Walsh, D. (1998) The structure of psychosis. Arch. Gen. Psychiatry 55:492– 499. Kim, S.Y., Post, R.M., and Rosen, J.B. (1996) Differential regulation of basal and kindling-induced TRH mRNA expression by thyroid hormone in the hypothalamic and limbic structures. Neuroendocrinology 63:297–304. Klerman, G. (1986) Historical perspectives on contemporary schools of psychopathology. In: Millon, T., and Klerman, G.L., eds. Contemporary Directions in Psychopathology: Toward the DSM-IV. New York: Guilford Press, pp. 3–28. Klerman, G.L., Vaillant, G.E., Spitzer, R.L., and Michels, R. (1984) A debate on DSM-III. Am. J. Psychiatry 141:539–553. Koukopoulos, A., Albert, M.J., Sani, G., Koukopoulos, A.E., and Girardi, P. (2005) Mixed depressive states: nosologic and therapeutic issues. Int. Rev. Psychiatry 17:21–37. Kraepelin, E. (1921) Manic-Depressive Insanity and Paranoia (G. M. Robertson, Ed.). Edinburgh, UK: E and S Livingstone.

25: DIAGNOSTIC CLASSIFICATIONS Leonhard, K. (1966) [Psychiatry on the clinical basis of Wernicke. In memory of Wernicke as a clinician on the occasion of the 60th anniversary of his death (June 15, 1905)]. Psychiatr. Neurol. Med. Psychol. (Leipz) 18:165–171. Levinson, D. F. (2006) The genetics of depression: a review. Biol. Psychiatry 60:84–92. Licinio, J., and Wong, M.-L. (Eds.). (2005) Biology of Depression. New York: John Wiley. Manji, H.K. (1992) G proteins: implications for psychiatry. Am. J. Psychiatry 149:746–760. Manji, H.K., Potter, W.Z., and Lenox, R.H. (1995) Signal transduction pathways: molecular targets for lithium’s actions. Arch. Gen. Psychiatry 52:531–543. Marx, O.M. (1970) Nineteenth-century medical psychology. Theoretical problems in the work of Griesinger, Meynert, and Wernicke. Isis 61:355–370. Menninger, K. (1963) The Vital Balance. New York: Viking. Mitchell, P.B., Wilhelm, K., Parker, G., Austin, M., Rutgers, P., and Malhi, G.S. (2001) The clinical features of bipolar depression: a comparison with matched major depressive disorder patients. J. Clin. Psychiatry 62:212–216. Murray, R.M., and Murphy, D.L. (1978) Drug response and psychiatric nosology. Psychol. Med. 8:667– 681. Nahmias, A.J., Nahmias, S.B., and Danielsson, D. (2006) The possible role of transplacentally-acquired antibodies to infectious agents, with molecular mimicry to nervous system sialic acid epitopes, as causes of neuromental disorders: prevention and vaccine implications. Clin. Dev. Immunol. 13:167–183. Neumarker, K.J., and Bartsch, A.J. (2003) Karl Kleist (1879-1960) a pioneer of neuropsychiatry. Hist. Psychiatry 14:411– 458. Osler, W. (1921) The Evolution of Modern Medicine. New Haven, CT: Yale University Press. Perris, C. (1966) A study of bipolar (manic-depressive) and unipolar recurrent depressive psychoses. Acta Psychiatr. Scand. 42(Suppl 194):58–67. Post, R.M. (2007) Kindling and sensitization as models for affective episode recurrence, cyclicity, and tolerance phenomena. Neurosci. Biobehav. Rev. 31(6):858–873. Post, R.M., Weiss, S.R., and Pert, A. (1988) Cocaine-induced behavioral sensitization and kindling: implications for the emergence of psychopathology and seizures. Ann. N.Y. Acad. Sci. 537:292–308. Roazen, P. (1969) Brother Animal: The Story of Freud and Tausk. New York: Knopf. Roazen, P. (2002) The Trauma of Freud: Controversies in Psychoanalysis. New Brunswick, NJ: Transaction Publishers. Sachs, G., Chengappa, K., Suppes, T., Mullen, J., Brecher, M., Devine, N.,

359

et al. (2004) Quetiapine with lithium or divalproex for the treatment of bipolar mania: a randomized, double-blind, placebocontrolled study. Bipolar Disord. 6:213–223. Sachs, G., Sanchez, R., Marcus, R., Stock, E., McQuade, R., Carson, W., et al. (2006) Aripiprazole in the treatment of acute manic or mixed episodes in patients with bipolar I disorder: a 3-week placebocontrolled study. J. Psychopharmacol. 20:536–546. Shorter, E. (1997) A History of Psychiatry. New York: John Wiley and Sons. Soares, J., and Gershon, S. (Eds.). (2000) Bipolar Disorders: Basic Mechanisms and Therapeutic Implications. Washington, DC: American Psychiatric Press. Spitzer, M. (1994) The basis of psychiatric diagnosis. In: Sadler, J., Wiggins, O., and Schwartz, M., eds. Philosophical Perspectives on Psychiatric Diagnostic Classification. Baltimore: Johns Hopkins University Press, pp. 163–177. Sprock, J. (1988) Classification of schizoaffective disorder. Compr. Psychiatry 29:55–71. Stahl, S.M. (2005) Essential Psychopharmacology. Cambridge, UK: Cambridge University Press. Trede, K., Salvatore, P., Baethge, C., Gerhard, A., Maggini, C., and Baldessarini, R. J. (2005) Manic-depressive illness: evolution in Kraepelin’s textbook, 1883-1926. Harv. Rev. Psychiatry 13:155–178. Ungvari, G. S. (1993) The Wernicke-Kleist-Leonhard school of psychiatry. Biol. Psychiatry 34:749–752. Vakili, N., and Gorji, A. (2006) Psychiatry and psychology in medieval Persia. J. Clin. Psychiatry 67:1862–1869. van Praag, H.M., Asnis, G.M., Kahn, R.S., Brown, S.L., Korn, M., Friedman, J.M., et al. (1990) Nosological tunnel vision in biological psychiatry. A plea for a functional psychopathology. Ann. N.Y. Acad. Sci. 600:501–510. van Praag, H.M., Asnis, G.M., Kahn, R.S., Brown, S.L., Korn, M., Harkavy-Friedman, J.M., et al. (1990) Monamines and abnormal behavior: a multi-aminergic perspective. Br. J. Psychiatry 157: 723–734. Vieta, E., and Barcia, D. (2000) El Trastorno Bipolar en el Siglo XVIII [Bipolar disorder in the eighteenth century]. Burdeos, Spain: Mra ediciones. Weiss, J.M., Cierpial, M.A., and West, C.H. (1998) Selective breeding of rats for high and low motor activity in a swim test: toward a new animal model of depression. Pharmacol. Biochem. Behav. 61:49–66. Weiss, S.R., and Post, R.M. (1994) Caveats in the use of the kindling model of affective disorders. Toxicol. Ind. Health 10:421– 447. Wernicke, C. (1906) Grundriss der Psychiatrie in klinischen Vorlesungen [Basic Lectures in Clinical Psychiatry]. Leipzig, Germany: Georg Thieme.

26 Genetics of Mood Disorders FALK W. LOHOFF

A N D

WADE H. BERRETTINI

The search for susceptibility genes for bipolar disorders (BPD) and recurrent unipolar disorders (RUP) is the subject of this chapter. Genetic factors play important roles for the development of BPD and to a lesser extend for RUP, as indicated by family, twin, and adoption studies. According to monozygotic and dizygotic twin studies of BPD, ∼65%–80% of the risk for developing BPD is attributable to genetic factors (Berrettini, 2002). Bipolar disorder family studies reflect a degree of familial aggregation that is congruous with the twin studies: children of parents with BPD have approximately a ninefold increase in lifetime BPD risk, compared to the ∼1% general population risk (Helzer and Winokur, 1974; James and Chapman, 1975; Johnson and Leeman, 1977; Angst et al., 1980; Baron et al., 1982; Gershon et al., 1982; Winokur et al., 1982; Weissman et al., 1984; Maier et al., 1993). For RUP, the lifetime prevalence is at least 10% (Moldin et al., 1991; Weissman et al., 1996; Tsuang et al., 2004) and twin studies suggest a heritability of 40%–50% (Torgersen, 1986; Kendler, Neale, et al., 1993; McGuffin et al., 1996; Bierut et al., 1999; Sullivan et al., 2000; Kendler et al., 2001). Family studies indicated a two- to threefold increase in lifetime risk to develop RUP for first-degree relatives (Gershon et al., 1982; Weissman et al., 1984; Maier et al., 1992). This degree of familial aggregation, coupled with the high heritability from twin studies, generated optimism that genetic linkage techniques (which have been so successful in identifying genes for Mendelian disorders) would reveal genes of substantial influence on BPD and RUP risks. Unfortunately, gene localization and identification has been a slow and labor intensive process. Genetic investigators have encountered similar frustrations with other common complex traits (such as asthma, hypertension, and diabetes mellitus). The major impediments to mood disorders gene localization and identification are: (1) no single gene is necessary and sufficient for BPD or RUP; (2) each susceptibility gene contributes a small fraction of the total genetic risk; and (3) complex genetic heterogeneity, meaning that multiple, partially overlapping sets of susceptibility genes (which interact with the environment) can predispose to similar syndromes that are indistinguishable on clinical grounds. 360

Given that the inherited susceptibilities for BPD and RUP are explained by multiple genes of small effect, simulations indicate that universal confirmation of vulnerability genes cannot be expected due to power issues, sampling variation, and genetic heterogeneity. With this background, several valid linkages of BPD to genomic regions are reviewed, including some that may be shared with schizophrenia. These results suggest that nosology must be changed to reflect the genetic origins of the multiple disorders that are collectively described by the term BPD. The briefer history of RUP molecular linkage and linkage disequilibrium (LD) studies is reviewed. GENETIC EPIDEMIOLOGY OF MOOD DISORDERS Twin Studies Evidence for a genetic component to mood disorders has been documented consistently using family, twin, and adoptions studies and is summarized in Table 26.1. The first genetic studies of mood disorders were conducted over 70 years ago and included assessment of concordance rates for monozygotic and dizygotic twins with mood disorders (Luxenberger, 1930; Rosanoff et al., 1935; Slater, 1936; Kallman, 1954; Allen et al., 1974; Harvald and Hauge, 1975; Bertelsen et al., 1977). The early studies did not distinguish between BPD and RUP; however, in nearly all these reports, RUP illness in the cotwin of a BPD index case was grounds for categorizing the twin pair as concordant. Bertelsen et al. (1977)

TABLE

26.1 Genetic Epidemiology of Mood Disorders Bipolar Disorder

Unipolar Depression

Lifetime prevalence (%)

2–3

10–15

Lifetime risk for first degree relatives (fold increase)

9–10

2–3

Proband-wise MZ twin concordance (%)

45–70

40–50

Heritability estimate (%)

65–80

33–42

26: GENETICS

and Allen et al. (1974) reported that ∼20% of concordant monozygotic twin pairs were constituted by a BPD index twin and a RUP cotwin. These older results are quite consistent with the more recent studies of BPD (Kendler, Neale, et al., 1993; McGuffin et al., 2003) reporting significantly higher monozygotic twins’ concordance rates, compared to those for dizygotic twins. A recent review of twin studies in RUP disorder estimated heritability at 37%, with a substantial component of unique individual environmental risk, but little shared environmental risk (Sullivan et al., 2000). These twin studies included four communityascertained samples (Kendler, Pedersen, et al., 1995; Lyons et al., 1998; Bierut et al., 1999; Kendler and Prescott, 1999) and two clinically ascertained samples, one from the United Kingdom (McGuffin et al., 1996) and one from Sweden (Kendler, Pedersen, et al., 1995). The results are quite consistent in concluding that genetic influence is a significant factor in risk for RUP, independent of ascertainment and country or origin. Family Studies Family studies of BPD show that a spectrum of mood disorders is found among the first-degree relatives of BPD probands: BPI, BPII with major depression (hypomania and RUP illness in the same person), schizoaffective disorders, and RUP illness (Helzer and Winokur, 1974; James and Chapman, 1975; Johnson and Leeman, 1977; Angst et al., 1980; Tsuang et al., 1980; Baron et al., 1982; Gershon et al., 1982; Weissman et al., 1984; Maier et al., 1993; Taylor et al., 1993). The family studies suggest shared liability for BPD and RUP disorders. No BPD family study, conducted in an optimal manner, reports increased risk for schizophrenia (SZ) among relatives of BPD probands. Similarly, no SZ family study reports increased risk for BPD among relatives of SZ probands. However, several SZ family studies report increased risk for RUP and schizoaffective disorders among relatives of SZ probands (Gershon et al., 1988; Kendler, McGuire, et al., 1993; Maier et al., 1993; Taylor et al., 1993). These family studies are consistent with some degree of overlap in susceptibility to RUP and schizoaffective disorders for relatives of BPD probands and relatives of SZ probands. Kendler, McGuire, et al. (1993) specifically note an increase in risk for psychotic affective disorders among the relatives of SZ probands. Potash et al. reported that psychotic affective disorders cluster in families (Potash, Chiu, et al., 2003; Potash et al., 2001). Risk for psychotic affective disorders was significantly higher among the relatives of psychotic BPD probands, compared to the risk for relatives of nonpsychotic BPD probands. This raises the possibility that the partial overlap in risk for BPD and SZ nosological categories is due to a subset of

361

BPD characterized by psychotic symptoms. This subset of BPD is probably quite common, as the majority of BPD probands from the Potash, Chiu, et al. (2003) study were psychotic. Family studies of RUP show that first-degree relatives of RUP probands were at increased risk for RUP disorders, compared to first-degree relatives of control probands (Tsuang et al., 1980; Gershon et al., 1982; Weissman et al., 1984; Maier et al., 1993; Weissman et al., 1993). There was a two- to fourfold increased risk for RUP among the first-degree relatives of RUP probands. Characteristics of RUP disorders that yield a more heritable phenotype include early onset, for example, before age 30 (Cadoret et al., 1977; Mendlewicz and Baron, 1981; Bland et al., 1986; Weissman et al., 1986; Stancer et al., 1987; Kupfer et al., 1989; Weissman et al., 1993) and a high degree of recurrence (Bland et al., 1986; Gershon et al., 1986; Reich et al., 1987; Kendler et al., 1994; Kendler et al., 1999). A third characteristic that may identify a separate group of disorders is the presence of psychosis (Kendler, McGuire, et al., 1993). Additional genetic subtypes of RUP may be identified through examination of comorbidities with panic disorder and other anxiety disorders and with alcoholism (Winokur et al., 1971; Merikangas et al., 1994; Nurnberger et al., 2002). Adoption Studies Mendlewicz and Rainer (1977) reported a controlled adoption study of BPD probands, including a control group of probands with poliomyelitis (Mendlewicz and Rainer, 1977). The biological relatives of the BPD probands had a 31% risk for BPD or UP disorders, as opposed to 2% in the relatives of the control probands. The risk for affective disorder in biological relatives of adopted patients with BPD was similar to the risk in relatives of patients with BPD who were not adopted (26%). Adoptive relatives do not show increased risk compared to relatives of control probands. Wender et al. (1986) and Cadoret (1978) studied RUP and BPD probands. Although evidence for genetic susceptibility was found, adoptive relatives of affective probands had a tendency to more affective illness themselves, compared with the adoptive relatives of controls (Cadoret, 1978; Wender et al., 1986). Von Knorring et al. (1983) did not find concordance in psychopathology between adoptees and biological relatives when examining the records of 56 adoptees with RUP disorders. LINKAGE STUDIES OF BIPOLAR DISORDERS Because of the strong epidemiological evidence for a genetic component in particular for BPD, the field has hoped that the identification of genetic risk factors would

362

MOOD DISORDERS

have been straightforward. However, the search for susceptibility genes has been difficult and frustrating due to the complex mode of inheritance, multiple genes with small effects, and clinical sample heterogeneity. Although linkage studies have suggested several regions in the genome that might harbor risk alleles, there has been inconsistency in findings, and so far no established universal genetic risk factor or causative gene for mood disorders has been identified. The term linkage refers to the observation that two genetic loci, found near one another on the same chromosome, tend to be inherited together more often than expected by chance within families. Two such loci are said to be linked. The key concept of linkage is that chromosomal fragments that might harbor vulnerability genes are inherited with an illness more often then expected by chance in families. LOD (the logarithm of the odds ratio) scores refer to the probability that observed cosegregation of alleles at two loci within a family has occurred because the two loci are linked. A LOD score > 3 is evidence (not proof) that two DNA sequences are linked. The numerical value of the LOD score is dependent on the proposed mode of inheritance (dominant, recessive, sex-linked) and penetrance. Because the LOD score is dependent on these parameters (mode of inheritance and penetrance), it is sometimes termed a parametric statistic. This dependence on inheritance mode and penetrance distinguishes the LOD score from nonparametric statistics (including affected sibling pair and affected pedigree member methods) because such statistics are not dependent on mode of inheritance or penetrance. What level of statistical significance should be required for declaring linkage? A recommended level of statistical significance for an initial report (p < ∼0.00002) is a stringent criterion, based on simulations that indicate that this level of significance would occur less than 5 times randomly in 100 genome scans for linkage (Lander and Kruglyak, 1995). This statistical criterion assumes that all the genetic information within the pedigrees studied would be extracted, an assumption that is not true in practice. Typically, no more than ∼80% of the genetic information in a pedigree series is extracted through genotyping. As in any other area of science, however, no single report of linkage should be accepted as valid without independent confirmation. The requirement for independent confirmations (at p ≤ 0.01) is not waived, no matter what level of statistical significance has been achieved in a single report. This confirmation requirement should be seen within the context that valid linkages will not be confirmed in some studies. Indeed, nonconfirmations should be expected, intuitively, because of population (ethnic) differences, sampling procedures, and genetic heterogeneity. Suarez et al. (1994) have examined the probability of confirmation in simulations. Suarez et al. (1994) simulated a disorder caused by any one of six loci and determined that a large sample

size and substantial time will be required for an initial linkage to be confirmed in a second sample. From his simulations, it is clear that consistent detection of a locus of moderate effect cannot be expected. Nonconfirmatory studies will always occur when an initially detected linkage is valid (Suarez et al., 1994). One of the most critical issues in confirmation of reported linkages is power. Attempts at confirmation of a reported susceptibility locus should state what power has been achieved to detect the locus initially described. For example, if a locus increases risk for BPD by a factor of two, it may be necessary to study ∼200 affected sibling pairs to have adequate (90%) power to detect such a locus (Hauser et al., 1996). Unfortunately, few studies address this key issue. If 200 affected sibling pairs are required to achieve adequate (90%) power to detect a previously described locus, then a publication with fewer than 150 sibling pairs does not address the central issue of confirmation. However, such powerlimited publications may have an important role in meta-analyses, in that they identify invaluable sources of additional data. Comprehensive scans of the human genome have been completed with sufficient numbers (for example, > 100) of individuals with BPD (Rice et al., 1997; Detera-Wadleigh et al., 1999; Cichon et al., 2001; Kelsoe et al., 2001; Bennett et al., 2002; Dick et al., 2003; Ekholm et al., 2003; J. Liu et al., 2003; McInnis et al., 2003). If a major locus (explaining > 50% of the risk in > 50% of persons with BPD) existed, it would have been detected in many of these studies. Thus, no such major locus exists for BPD. There are several confirmed reports of loci of smaller effect, which can be termed susceptibility loci. These loci are neither necessary nor sufficient for disease but increase risk for the disorder in a non-Mendelian manner. Confirmed linkage loci are summarized in Table 26.2. From these genome scans and from additional, smaller studies, a picture has emerged in which there are several confirmed BPD linkage regions across the genome. It is highly probable that additional confirmed BPD linkages will be identified through future linkage studies. These BPD linkage regions are confirmed by virtue of at least one study with strong statistical significance (p < 0.0001) and at least two confirmatory studies (p < 0.01). As noted elsewhere (Berrettini, 2003), in some cases, these confirmed BPD linkage regions overlap with schizophrenia linkage reports, suggesting that the same loci may be involved in some aspects of both disorders. In an attempt to further elucidate possible BPD linkage regions, two meta-analyses of BPD genome scans have been conducted (Badner and Gershon, 2002; Segurado et al., 2003). Badner and Gershon (2002) analyzed linkage results using a multiple scan probability approach, in which p values are combined across studies, after adjusting for the size of the linkage region. These authors concluded that two genomic regions, 13q32 and

26: GENETICS TABLE

363

26.2 Linkage Studies of Bipolar Disorder Evidence from Meta-analyses for Genome-wide Significance

Location

Primary Report

Independent Confirmations/Supportive Evidence

4q32

Ekholm et al., 2003

Adams et al., 1998; J. Liu et al., 2003; McInnis et al., 2003; Schumacher, Kaneva, et al., 2005

4p15

Blackwood et al., 1996

Cichon et al., 2001; Detera-Wadleigh et al., 1999; Ewald et al., 2002; Ginns et al., 1998; Morissette et al., 1999

6q16-24

Middleton et al., 2004

Dick et al., 2003; Ewald et al., 2002; Lambert et al., 2005; Pato et al., 2004; Rice et al., 1997; Schumacher, Kaneva, et al., 2005; Venken et al., 2005

McQueen et al., 2005

8q24

Cichon et al., 2001

Dick et al., 2003; Friddle et al., 2000; McInnis et al., 2003; Park et al., 2004; Segurado et al., 2003

McQueen et al., 2005

12q23

Morissette et al., 1999

Cassidy et al., 2007; Curtis et al., 2003; Dawson et al., 1995; Ekholm et al., 2003; Ewald et al., 2002; Maziade et al., 2001; Shink et al., 2005

13q21-32

Detera-Wadleigh et al., 1999

Badenhop et al., 2001; Goes et al., 2007; Kelsoe et al., 2001; Liu et al., 2003; Potash, Zandi, et al., 2003

16p12

Ewald et al., 2002

Dick et al., 2003; Ekholm et al., 2003; Savitz et al., 2007

18p11.2

Berrettini et al., 1997

Bennett et al., 2002; M.W. Lin et al., 1997; Mukherjee et al., 2006; Nothen et al., 1999; Stine et al., 1995; Turecki et al., 1999a

18q22

Stine et al., 1995

De bruyn et al., 1996; Fallin et al., 2004; Freimer et al., 1996; Lambert et al., 2005; McInnes et al., 1996; McInnis et al., 2003; McMahon et al., 1997

21q22

Straub et al., 1994

Aita et al., 1999; Detera-Wadleigh et al., 1996; Kwok et al., 1999; Morissette et al., 1999; Smyth et al., 1996

22q11-13

Kelsoe et al., 2001

Detera-Wadleigh et al., 1997; Detera-Wadleigh et al., 1999; Lachman et al., 1997

Badner and Gershon, 2002

Badner and Gershon, 2002

Only primary linkage studies are shown with genome-wide significance according to Lander and Kruglyak (1995). Negative studies are not shown.

22q11-13, were the most promising loci for BPD. Segurado et al. (2003) used the method of Levinson et al. (2003), which ranks the p values across the genome of each study, then sums the rankings for each genomic “bin.” In this approach, no genomic region reached genome-wide significance, although the regions which seemed most promising were 9p, 10q, 14q, and the pericentromeric region of chromosome 18 (Segurado et al, 2003). A combined analysis of 11 previous linkage scans was carried out by McQueen et al. (2005). In contrast to the two previous meta-analyses, the authors used original genotyping data and showed genome-wide significant linkage for BPD on chromosomes 6q and 8q (McQueen et al., 2005). It is likely that several additional linkage loci will be identified in the future; in particular, when large enough sample sizes will allow the analyses of clinical subtypes like psychotic BPD, early onset of illness, or BPD with comorbid panic disorder. These subtypes have been suggested to have a strong heritable component to them (Potash et al., 2001; MacKinnon et al., 2002; Potash et al., 2003; P.I. Lin et al., 2005). Recent genome scans of psychotic BPD, for example, showed promising results to chromosome 9q31 and 8p21 (N. Park et al., 2004; Cheng et al.,

2006) and 13q21-33 and 2p11-q14 (Goes et al., 2007). Interestingly, 8p21 and 13q overlap with SZ, further substantiating the concept of shared genomic regions that harbor shared susceptibility factors between BPD and SZ (Berrettini, 2004). CANDIDATE GENE STUDIES OF BIPOLAR DISORDER The human genome consists of ∼3 billion base pairs of DNA (Venter et al., 2001). The recent completion of draft genomic sequences of the human genome (Venter et al., 2001) is consistent with ∼35,000–40,000 genes. Physical distance along the linear sequence of DNA can be expressed in terms of base pairs of DNA. The most common sequence variation in the human genome is a single nucleotide polymorphism (SNP), where there are two different nucleotides (from the possible four, adenine [A], guanine [G], thymidine [T], and cytosine [C]) found among homo sapiens at the same position on different chromosomes. Single nucleotide polymorphisms (SNP) with a common minor allele (frequency of ∼20%) occur every ∼1000 base pairs of DNA (Venter et al., 2001). Analysis of closely spaced SNPs in outbred populations suggests a complex pattern of inheri-

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tance in which recombination is inhibited in a small region of DNA, such that blocks of DNA (containing multiple SNPs) tend to be inherited intact over many generations (Gabriel et al., 2002). Thus, blocks of DNA are shared among present-day individuals who may have had a common ancestor 10,000 generations ago. These blocks are variable in length and often contain multiple SNPs, but among outbred human populations, the block length rarely exceeds ∼100,000 base pairs. Alleles of SNPs within a block form a haplotype (a set of alleles) that are usually inherited together across many generations. Such SNPs are said to be in strong linkage disequilibrium (LD) with each other. LD refers to the fact that two (or more) alleles can be found together in unrelated individuals more often than predicted by chance. The interested reader is referred to primary reports concerning LD (Gabriel et al., 2002). LD is a useful tool to investigate the relatively small genomic regions that have been implicated in the genetic origins of BPD through linkage studies (see Table 26.2). In this process, SNPs spaced across genes in the linkage region are assessed in large groups (ideally several hundred at least) of ethnically matched cases and controls. Investigators compare allele and genotype frequencies among groups of cases and controls. If nominally significant differences in allele or genotype frequencies are found between groups, the investigators might conclude that the tested SNP or a variant in close proximity influences risk for BPD.

FIGURE

There have been a multitude of association studies in BPD over the past decade. Most studies have focused on neurotransmitter, neuroendocrine, neurotrophic, and cellular signaling systems. Unfortunately, the nearly complete absence of pathophysiologic data in BPD makes the process of rational candidate gene selection difficult. Additionally, these studies have typically involved smaller numbers of patients with BPD than is optimal, given that the effect size of individual alleles on risk must be small. Although the lack of adequate power of some studies might explain the high degree of nonreplication, other factors such as genetic heterogeneity and population differences further complicate matters. As indicated by the findings of multiple linkage loci, it is likely that there are several candidate genes that in combination contribute to the clinical phenotype of BPD. This paradigm is illustrated in Figure 26.1. Assume that there are 20 risk alleles, each only contributing a small fraction to the overall risk. To develop BPD, let’s suppose one needs five risk alleles. As shown, individual A and B have BPD but share only one risk allele. Individual C has also five risk alleles but shares one risk allele with individual A and one risk allele with individual B. Individual D has also BPD risk alleles but falls in the SZ continuum. This genetic heterogeneity can explain why it is difficult to find universal risk alleles. It is more likely that several sets of risk alleles will contribute to the clinical phenotype. The degree and amount of risk alleles might explain why we

26.1 Model of risk and protective alleles involved in psychiatric disorders.

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observe a continuum or spectrum of the bipolar disorders, or psychiatric disorders in general. As shown for the unaffected group, there are several scenarios that could explain unaffected status. One simple explanation is the lack of risk alleles (individual E), but another possibility includes the presence of protective alleles (as shown for individual F and G in green). Although the majority of past studies have investigated risk alleles, it is becoming increasing clear that complex interactions of genetic risk and protective factors in concert with environmental stimuli contribute to the development of BPD. This observation has been made for example in cancer genetics, with the identification of oncogenes and tumor suppressor genes (Pierotti et al., 2000; B.H. Park and Vogelstein, 2003). Investigation of interaction of protective and susceptibility factors, in addition to complex gene–gene (epistatic) and gene–environment interactions, will be necessary to elucidate the genetic basis of complex behaviors (Feinberg, 2007). Furthermore, epigenetic regulation and mechanisms might influence gene expression without altering the genetic code and could mediate stable changes in brain function (Tsankova et al., 2007). Despite these difficulties and complexities, there are several candidate genes that deserve mention. On a general note, many candidate genes discussed here show also positive results for other psychiatric illnesses such as anxiety disorders, attention-deficit/ hyperactivity disorder, psychotic disorders, and substance use disorders, supporting the concept of shared susceptibility factors and comorbidities across diagnostic categories (Fig. 26.1). D-Amino Acid Oxidase Activator DAOA (G72)/G30 One promising candidate gene is the G72/G30 locus on 13q32, the site of a confirmed linkage in BPD (see Table 26.2) and SZ (M.W. Lin et al., 1997; Blouin et al., 1998; Shaw et al., 1998; Brzustowicz et al., 1999; Camp et al., 2001; Cardno et al., 2001; Badner and Gershon, 2002; Faraone et al., 2002; Wijsman et al., 2003; Abecasis et al., 2004). G72 is a primate-specific brain-expressed gene that activates D-amino acid oxidase (Chumakov et al., 2002) and was recently renamed D-amino acid oxidase activator (DAOA) (UCSC genome browser; Ensembl genome browser; National Center for Biotechnology Information, http://www.ncbi.nlm.nih .gov). D-amino acid oxidase may control levels of Dserine, which regulates glutamatergic receptors (Stevens et al., 2003), implicated in the pathophysiology of SZ and BPD. Chumakov et al. (2002) identified a haplotype from G72 SNPs (without obvious functional significance) that were in LD with SZ in a French Canadian sample. This has been confirmed in distinct SZ populations (Chumakov et al., 2002; Schumacher et al., 2004; Fallin et al., 2005;

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Williams et al., 2006), although different haplotypes have been associated in different ethnic populations. Similarly, in BPD there have been several positive findings with distinct haplotypes in different populations (Hattori et al., 2003; Chen et al., 2004; Schumacher et al., 2004; Fallin et al., 2005; Williams et al., 2006). A recent metaanalysis combined the published results at this locus and further substantiated the association of G72/G30 with BPD and SZ (Detera-Wadleigh and McMahon, 2006). Although the G72/G30 locus is arguably among the best replicated association findings in psychiatric genetics, no clear functional variants have been yet defined at this locus, and the biological relevance of this susceptibility locus remains elusive. Brain-Derived Neurotrophic Factor (BDNF) A second promising candidate gene is the brain-derived neurotrophic factor (BDNF). The BDNF gene is located on chromosome 11p13, a region of suggestive linkage for BPD (McInnes et al., 1996; Detera-Wadleigh et al., 1999). Two family-based association studies showed an overtransmission of Val-allele of the functional Val66Met polymorphism (Neves-Pereira et al., 2002; Sklar et al., 2002). This finding was confirmed in a large case-control association study of unrelated participants with BPD from the National Institute of Mental Health (NIMH) Genetics Initiative (Lohoff et al., 2005). Additional evidence for an association of the Val66Met polymorphism was reported in three small childhoodonset samples: two using a family-based design (Geller et al., 2004; Strauss et al., 2005) and one employing a case-control approach (Strauss et al., 2004). Furthermore, two studies implicate the Val66Met polymorphism to be associated with rapid cycling (Green et al., 2006; Muller et al., 2006). However, there are also several negative findings (Hong et al., 2003; Nakata et al., 2003; Kunugi et al., 2004; Oswald et al., 2004; Skibinska et al., 2004; Neves-Pereira et al., 2005; Green et al., 2006; Surtees et al., 2007). Although some of these studies were likely underpowered, another explanation would be ethnic and clinical differences between samples. It should be also noted that most of the mentioned studies only investigated the Val66Met polymorphism. The BDNF gene structure is complex and might harbor several risk alleles in addition to haplotypes conferring risk as shown by Okada et al. (2006). These positive reports are promising because they involve a genetic variant with functional consequences. Egan et al. (2003) demonstrated allele-specific effects on intracellular trafficking and activity-dependent secretion of BDNF protein. Recent studies demonstrate a role of the BDNF Val66Met polymorphism in cognition (Egan et al., 2003; Hariri et al., 2003; Rybakowski et al., 2003; Rybakowski, Borkowska, Skibinska, and Hauser, 2006;

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Rybakowski, Borkowska, Skibinska, Szczepankiewicz, et al., 2006), brain structures (Bueller et al., 2006), and BDNF serum levels (Tramontina et al., 2007). Growing evidence suggests that BDNF is involved in the etiology of mood disorders (K. Hashimoto et al., 2004; Post, 2007) and depressive personality traits (Lang et al., 2004). Serum levels of BDNF were decreased in patients who were depressed when compared to controls (Karege et al., 2002; Shimizu et al., 2003; Aydemir et al., 2005; Gonul et al., 2005) and postmortem brain studies in patients with BPD show decreased BDNF protein when compared to controls (Knable et al., 2004). The use of antidepressants, electroconvulsive therapy, and mood stabilizers such as lithium increase BDNF gene transcription (Nibuya et al., 1995; Fukumoto et al., 2001; R. Hashimoto et al., 2002), and infusion of BDNF into rat brain has a direct antidepressant effect in animal models of depression (Siuciak et al., 1997; Shirayama et al., 2002). Taken together, the convergent evidence from genetic, preclinical, and clinical studies makes BDNF a strong candidate for mood disorder. Monoamine Oxidase A (MAO-A) There have been numerous independent association studies of BPD and RUP and a Monoamine Oxidase A MAO-A (CA)n repeat polymorphism in European (Craddock et al., 1995; Lim et al., 1995; Nothen et al., 1995; Parsian and Todd, 1997; Furlong et al., 1999; Turecki et al., 1999b; Preisig et al., 2000; Syagailo et al., 2001; Serretti et al., 2002; Muller et al., 2007) and Asian populations (Kawada et al., 1995; Muramatsu et al., 1997; Kunugi et al., 1999). Those studies reporting a positive association (Kawada et al., 1995; Lim et al., 1995; Furlong et al., 1999; Preisig et al., 2000; Muller et al., 2007) generally detect an overrepresentation of allele 5 or 6 of the MAO-A (CA)n repeat among patients with BPD, compared to controls, an observation that may be particularly evident among women (Deckert et al., 1999; S. Lin et al., 2000; Preisig et al., 2000; Schulze et al., 2000; Gutierrez et al., 2004). The effect size is small, the odds ratio being 1.49 (Preisig et al., 2000), and the sample size required for adequate power to detect is larger than most of the negative studies (Craddock et al., 1995; Lim et al., 1995; Nothen et al., 1995; Parsian and Todd, 1997; Furlong et al., 1999; Turecki et al., 1999b; Preisig et al., 2000; Syagailo et al., 2001; Serretti et al., 2002; Muller et al., 2007). There is also an MAO-A promoter polymorphism (Kunugi et al., 1999). These studies involve multiple ethnic groups, case-control methods, and family-based designs, with some studies having limited power to detect a small effect size. Thus, it is understandable that conflicting studies are reported.

Serotonin Transporter (5HTT) Another intensively studied candidate gene is the serotonin transporter (5HTT/SLC6A4), a functional candidate gene for which multiple BPD LD studies have been published. The 5HTT represents a logical candidate gene, as many antidepressants act through binding to the 5HTT protein (Ramamoorthy et al., 1993). There are two variants of the 5HTT that have been studied in BPD, and both have functional significance, based on in vitro analysis of these noncoding polymorphisms. The first variant is an insertion/deletion polymorphism in the promoter region (5HTTLPR). The shorter allele has much less transcriptional activity than the longer allele (Collier, Stober, et al., 1996; Heils et al., 1996). Moreover, the shorter allele has been associated with anxiety-related personality traits in humans (Lesch et al., 1996). The second variant is a variable number of tandem repeats (VNTR) polymorphism in intron 2. The two most common alleles are the 10 and 12 repeats, which confer differential transcriptional activity in an embryonic stem cell line (Fiskerstrand et al., 1999). Collier et al. first reported that the 5HTT intron 2 VNTR allele 12 was in LD with BPD among patients from the United Kingdom (Collier, Arranz, et al., 1996). Collier et al. also reported that the short allele of the 5HTT promoter variant was more common among 454 European patients with BPD and patients with RUP, compared to 570 European controls, although the statistical significance was marginal (p = 0.03), emphasizing the small effect size involved (Collier, Stober, et al., 1996). Analysis by genotype suggested that homozygosity for the short allele was associated with BPD (p < 0.05) and RUP (p < 0.01). Since this initial report there have been numerous replication studies with positive (Kunugi et al., 1997; Rees et al., 1997; Bellivier et al., 1998; Vincent et al., 1999; Mynett-Johnson et al., 2000) and negative results (Kunugi et al., 1996; Bellivier et al., 1997; Gutierrez et al., 1998; Hoehe et al., 1998; Bocchetta et al., 1999; Kirov et al., 1999; Oliveira et al., 2000; Ospina-Duque et al., 2000; Saleem et al., 2000; Mendlewicz et al., 2004; Ikeda et al., 2006). Sampling variation and the small effect size coupled with limited power of this sample size are probable explanations for these mixed results. Furlong et al. (1998) reported results of a meta-analysis for ∼1400 individuals of European origin, including 772 controls, 375 patients with BPD, and 299 patients with UP. Although there was no evidence for LD with affective disorders for the VNTR, a marginally significant result was found for the short allele of the 5HTT promoter polymorphism. This result is important because it suggests that samples in the thousands will be necessary to draw firm conclusions, due to the small effect sizes involved. In another large European study, Mendlewicz

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et al. (2004) examined the genetic contribution of the 5HTT promoter polymorphism in a case-control sample, including 539 patients with RUP, 572 patients with BPD, and 821 controls. No evidence of LD was found for RUP or BPD, and subdividing the sample according to family history, suicidal attempts, or psychotic features did not reveal any role of the promoter variant in the genetic susceptibilities to these disorders. A recent meta-analysis of published population-based and family-based association studies in BPD investigating the 5HTTLPR and the VNTR polymorphism showed a small effect (odds ratio [OR] = 1.12) of both SNPs (Cho et al., 2005). Lasky-Su et al. (2005) performed a meta-analysis of these SNPs for BPD and RUP and could only document a small effect (OR = 1.13) of the insertion/deletion polymorphism with BPD (Lasky-Su et al., 2005). A recent large scale study of the 5HTTLPR promoter polymorphism failed to show an association for neuroticism, major depression, or recurrent major depression (Willis-Owen et al., 2005). Taken together, these data suggest a small but significant effect of the 44-bp insertion/deletion polymorphism (5HTTLPR) in BPD, whereas the role in major depression remains unclear. Other Genes and Whole-Genome Association Studies Several other candidate genes have been investigated in BPD with some positive results for COMT, DAT, HTR4, DRD4, DRD2, HTR2A, DISC1, P2RX7 (Craddock and Forty, 2006; Hayden and Nurnberger, 2006). Most of these candidate genes were selected based on a priori hypotheses regarding their neurobiological function. This approach of candidate gene selection has obvious limitations given our lack of understanding of the pathophysiology of mood disorders. With the rapid development of technological advances in genomics, it is now possible to genotype 500,000– 1,000,000 SNPs across the genome in cases and normal controls. This “whole-genome association” (WGA) study design has the advantage that no genes are preselected and robust findings might identify new pathways involved in mood disorders. Limitations of this approach are the immense large amount of data, costs, and issues regarding multiple testing. The stringent statistical correction for multiple testing might mask true signals from genes that confer only modest risk of disease (Clark et al., 2005; Jorgenson and Witte, 2006). The first WGA study in BPD using the DNA samples collected through the NIMH Genetic Initiative of Bipolar Disorder (www .nimhgenetics.org) and Germany was recently completed (Baum et al., 2007). The authors studied over 550,000 SNPs in two independent case-control samples of European origin. A total of 88 SNPs located in 80 different genes met criteria for association and replication in both samples. This large number of genes might still

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be an underestimation of the total number of genes involved in BPD, given the overall small effect size and stringent replication criteria. The strongest association signal was detected in an intron of the diacylglycerol kinase eta gene that encodes a key protein in the lithiumsensitive phosphatidyl inositol pathway. The results of the first WGA study in BPD confirm the polygenic nature of this complex trait and furthermore provide evidence for new genes and pathways involved in mood disorders. The recent completion of a WGA study by the Wellcome Trust Case Control Consortium using 14,000 participants with different diseases, including about 2,000 patients with BPD and 3,000 control subjects, confirmed the polygenic nature of a complex disease like BPD (Wellcome Trust Case Control Consortium, 2007). The strongest association signal was observed for an SNP on chromosome 16p12. With further advances in technology and larger sample sizes, it appears likely that some key genetic mechanism and pathways will be identified quite soon. Future studies will have to replicate findings and proof biological consequences, with ultimately improved drug development and patient care. LINKAGE STUDIES OF RECURRENT UNIPOLAR DISORDERS There have been relatively few RUP genome scans with > ∼100 affected individuals, in contrast to BPD. Holmans et al. (2004) reported on the first phase of a multisite collaborative effort (Recurrent Early-Onset Depression [GenRED] sample). The sample consisted of 297 informative multiplex families (containing 685 informative affected relative pairs, 555 sibling pairs, and 130 other pair types). Affected cases had RUP with onset before age 31 for probands or 41 for other affected relatives; the mean age at onset was 18.5 and the mean number of depressive episodes was 7.3, indicating a highly recurrent form of illness. Families were excluded if there was a BPD first-degree or second-degree relative (Holmans et al., 2004). Linkage was observed on chromosome 15q25.3-26.2 (empirical genome-wide p = 0.023). The linkage was not sex specific. This was the sole significant linkage peak observed by this group. In the complete sample of 656 families, genome-wide suggestive linkage was confirmed on chromosome 15q and also observed on chromosomes 17p and 8p in a planned second analysis accounting for the sex of each pair of relatives (Holmans et al., 2007). Fine mapping of the 15q region demonstrated further evidence for linkage (Levinson et al., 2007). Abkevich et al. (2003) reported a genome scan on 110 Utah pedigrees (each with at least four affected individuals), in which there were 784 individuals with

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RUP, 161 persons with single-episode major depressive disorder, and 162 individuals with BPD, who were also considered affected. They observed a highly significant linkage signal at 12q23 (Abkevich et al., 2003), confirming a previously identified BPD locus (see Table 26.2). There were no other linkage peaks approaching statistical significance. It is probable that this study has detected the same BPD 12q23 locus, even though their families were ascertained from a RUP proband, because most kindreds probably did have at least one individual with BPD. These results confirm family and twin studies, suggesting genetic overlap between BPD and RUP disorders, and this study identifies the 12q23 region as a locus that increases risk for BPD and RUP disorders. Camp et al. (2005) reanalyzed the large Utah pedigrees and excluded relatives with BPD. They considered three alternative phenotypes (major depressive disorder [MDD] age at onset before 31; MDD or anxiety; MDD and anxiety) and identified regions with at least suggestive genome-wide evidence for linkage on chromosomes 3centr, 7p, and 18q (Camp et al., 2005). Interestingly the region identified on 18q with MDD and anxiety is also a well-replicated linkage finding in BPD (see Table 26.2). Zubenko et al. reported on a genome scan of 81 families ascertained through a proband with early-onset nonpsychotic RUP disorder (Zubenko, Maher, et al., 2003). They described a highly significant linkage (p < 0.0001) of this phenotype to 2q35 near marker D2321, which is near a candidate gene, CREB1 (cyclic AMPresponse element binding protein 1). Sequence variants in the CREB gene were found to segregate with RUP disorder among women in 2 of these 81 extended kindreds (Zubenko, Hughes, et al., 2003), thus nominating CREB as a RUP susceptibility gene. These intriguing results await independent confirmation. Another recent genome-wide linkage scan was carried out using 497 sib pairs concordant for recurrent depression excluding BPD. The advantage of affected sib pair design is that it does not require knowledge of mode of inheritance and increased power under certain conditions. Suggestive evidence for linkage was observed on chromosome 1p36, 12q23.3-q24.11, and 13q31.1-q31.3 (McGuffin et al., 2005). The 12q locus has been previously implicated in linkage studies of UP (Abkevich et al., 2003) and BPDs (see Table 26.2 above) whereas the 13q peak lies within a region previously linked strongly to panic disorder (Hamilton et al., 2003). CANDIDATE GENE STUDIES OF RECURRENT UNIPOLAR DISORDERS Candidate gene studies of UP depression have received traditionally less attention in the past compared to BPD and SZ. Likely reasons for this discrepancy might be

practical limitations given the much smaller expected effect size and a more heterogeneous clinical phenotype. However, with increasing sample sizes, the literature is developing rapidly. As with BPD, there is no universal susceptibility gene for RUP. It can be expected that multiple genes with small effect sizes contribute to RUP. Some of the candidate genes for BPD are also promising genes in RUP, including BDNF and 5HTT. Similar to the search for BPD and SZ genes, whole genome scans for RUP are currently under way. Results are expected in the near future. Several candidate genes show promising preliminary results and are worthwhile mentioning. Serotonin Transporter (5HT T )/Serotonin Receptor 2A (HTR2A) The serotonin transporter gene and genes involved in the serotonergic system are logical candidate genes for susceptibility to depression, given that many antidepressant medications act on these systems. Several studies reported positive associations between variants in the 5HTT gene and MDD (Collier, Stober, et al., 1996; Rees et al., 1997; W. Liu et al., 1999; Anguelova et al., 2003) whereas others could not confirm results (Kunugi et al., 1997; Bellivier et al., 1998; Furlong et al., 1998; Gutierrez et al., 1998; Hoehe et al., 1998; Oliveira et al., 2000; Minov et al., 2001; Anguelova et al., 2003). Case-control association studies of the HTR2A gene and major depression have yielded similar mixed results as for the 5HTT gene (Anguelova et al., 2003). Because the 5HTT gene encodes a direct target for antidepressant medications, there has been a great interest in correlating genetic variation to pharmacological treatment response (Malhotra et al., 2004; Serretti et al., 2005; Serretti et al., 2006; Smeraldi et al., 2006). A recent large scale study utilizing DNA samples from 1953 patients with MDD who were treated with citalopram in the Sequenced Treatment Alternatives for Depression (STAR*D) trial investigated genetic predictors for treatment response (McMahon et al., 2006). The authors could not find evidence for 5HTT variation influencing treatment response; however, they report a significant effect with a marker in the serotonin receptor gene HTR2A and treatment outcome. As expected for a single gene, the clinical impact of HTR2A on treatment outcome is modest. Although these studies face similar complexities and obstacles as disease candidate gene studies and await replication, this pharmacogenetic approach will likely yield robust results in the near future. Gene–environment interaction studies have received increasing attention in particular for MDD, given the robust correlation between stressful life events and risk for developing depressive symptoms (Kendler, Kessler, et al., 1995; Repetti et al., 2002; Leckman et al., 2004). In a recent population-based study, Caspi and colleagues

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noted that individuals with one or more copies of the short allele of the 5HTT promoter variants were at increased risk for depression depending on the occurrence of adverse life events (Caspi et al., 2003). This article describes a plausible gene–environment interaction that may help explain the conflicting results for the 5HTT promoter variant noted above. There have been positive (Kendler et al., 2005) and negative (Gillespie et al., 2005; Surtees et al., 2006) replication studies demonstrating the complexity of detecting these effects. Similar gene–environmental interactions have been demonstrated for variants in the HTR2A gene and childhood maternal nurturance and depressive symptoms in adulthood (Jokela et al., 2007). Future genetic studies of depression will have to pay close attention to these gene– environmental interactions. BDNF There is growing evidence suggesting an important role of BDNF in affective disorder (Nestler et al., 2002; Duman and Monteggia, 2006; Post, 2007). Preclinical animal studies have consistently documented a role of BNDF on neurogenesis (Duman, 2004), and animal models of depression further substantiate a role of BNDF in mood disorders. Decreased BDNF levels in hippocampus have been reported in animals exposed to chronic stress (Roceri et al., 2002; Zhang et al., 2002; Kuma et al., 2004; Roceri et al., 2004). Interestingly, administration of antidepressants increased hippocampal BDNF, preventing the stress-induced decrease (Nibuya et al., 1995). These findings are intriguing given the hippocampal volume loss observed in mood disorders (Bertolino et al., 2003; Blumberg et al., 2003; Monkul et al., 2003; Videbech and Ravnkilde, 2004). Several recent studies have shown that BDNF serum levels are decreased in individuals with mood disorders or depressive personality traits (Karege et al., 2002; Shimizu et al., 2003; Lang et al., 2004; Aydemir et al., 2005; Gonul et al., 2005). Based on these convergent preclinical and clinical data, the BDNF gene represents a logical target for genetic investigations of mood disorders. Although there is stronger literature support for a genetic association between the Val66Met polymorphism in the BDNF gene and BPD (see above), several studies have also investigated this SNP in RUP. Results have been similarly mixed as with most other candidate genes for depression. Schumacher et al. (2005) examined 465 individuals with MDD but did not find a significant association with the Val66Met polymorphism. However, there was evidence for a haplotypic association. Surtees et al. (2007) failed to detect an association of the Val66Met polymorphism in 1214 individuals with a history of MDD, whereas studies of this polymorphism in Asian populations showed inconsistent results (Tsai et al., 2003; Hwang et al., 2006; Iga et al., 2007). Despite

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these mixed and negative results, interpretation of these data should be carried out with caution, given the complex structure of the gene (Okada et al., 2006) and the fact that most studies have only investigated the Val66Met SNP. It is likely that other variation in the BDNF gene might influence susceptibility to depression. Tryptophan Hydroxylase (TPH2) Tryptophan hydroxylase is the rate-limiting enzyme in brain serotonin synthesis. The discovery of a new brainspecific isoform of the tryptophan hydroxylase (TPH2) (Walther and Bader, 2003) has generated new interest in the connection between serotonergic systems and depression. The TPH2 gene is located on chromosome 12q, a region implicated previously in linkage studies of BPD (Dawson et al., 1995; Ewald et al., 1998; Morissette et al., 1999). Zill et al. (2004) reported first evidence for an association of variants in the TPH2 gene and major depression. X. Zhang et al. (2005) identified a functional polymorphism (Arg441His) that results in approximately 80% loss of function in serotonin production when expressed in a cell system. The authors also reported that this rare mutation was not seen in 219 healthy controls but in 9 of 87 individuals with major depression (X. Zhang et al., 2005). However, subsequent replication attempts by other groups for this rare variant were negative (Garriock et al., 2005; Glatt et al., 2005; Van Den Bogaert et al., 2005; X. Zhang et al., 2005; Zhou, Peters, et al., 2005; Bicalho et al., 2006; Delorme et al., 2006). Haplotypic associations of sets of markers across the TPH2 gene have yielded positive results (Van Den Bogaert et al., 2006), and interestingly variants were associated with suicidal behavior (De Luca et al., 2004; Zhou, Roy, et al., 2005; Ke et al., 2006; de Lara et al., 2007; Lopez et al., 2007). Deficits in brain serotonin synthesis secondary to genetic variation in the TPH2 gene might represent an important risk factor for UP major depression. CONCLUSIONS AND FUTURE DIRECTIONS Family, twin, and adoption studies of BPD and RUP disorders were reviewed. They are, in general, consistent with substantial heritable components to risk, with the BPDs having higher heritability than the RUP disorders. Multiple regions of the genome (including 18p11, 18q22, 12q24, 21q21, 13q32, 4p15, 4q32, 16p12, 8q24, and 22q11) have been implicated by several independent groups in the genetic origins of BPD. It is likely that most of these regions will yield susceptibility genes within the near future, through the application of LD mapping methods and WGA studies to large sample sizes. LD approaches to candidate genes

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have yielded several promising candidate genes, including G72 and BDNF for BPD. In addition, molecular genetic studies of various psychiatric phenotypes document shared genomic regions between disorders, indicating a continuum between diagnostic categories rather than dichotomy. Although the field of psychiatric genetics has been plagued by positive and negative replications, promising robust findings are now emerging with potential implications for future clinical practice.

REFERENCES Abecasis, G.R., Burt, R.A., Hall, D., et al. (2004) Genomewide scan in families with schizophrenia from the founder population of Afrikaners reveals evidence for linkage and uniparental disomy on chromosome 1. Am. J. Hum. Genet. 74:403– 417. Abkevich, V., Camp, N.J., Hensel, C.H., et al. (2003) Predisposition locus for major depression at chromosome 12q22-12q23.2. Am. J. Hum. Genet. 73:1271–1281. Adams, L.J., Mitchell, P.B., Fielder, S.L., Rosso, A., Donald, J.A., and Schofield, P.R. (1998) A susceptibility locus for bipolar affective disorder on chromosome 4q35. Am. J. Hum. Genet. 62:1084 –1091. Aita, V.M., Liu, J., Knowles, J.A., et al. (1999) A comprehensive linkage analysis of chromosome 21q22 supports prior evidence for a putative bipolar affective disorder locus. Am. J. Hum. Genet. 64:210–217. Allen, M.G., Cohen, S., Pollin, W., and Greenspan, S.I. (1974) Affective illness in veteran twins: a diagnostic review. Am. J. Psychiatry 131:1234 –1239. Angst, J., Frey, R., Lohmeyer, B., and Zerbin-Rudin, E. (1980) Bipolar manic-depressive psychoses: results of a genetic investigation. Hum. Genet. 55:237–254. Anguelova, M., Benkelfat, C., and Turecki, G. (2003) A systematic review of association studies investigating genes coding for serotonin receptors and the serotonin transporter: I. Affective disorders. Mol. Psychiatry 8:574 –591. Aydemir, O., Deveci, A., and Taneli, F. (2005) The effect of chronic antidepressant treatment on serum brain-derived neurotrophic factor levels in depressed patients: a preliminary study. Prog. Neuropsychopharmacol. Biol. Psychiatry 29:261–265. Badenhop, R.F., Moses, M.J., Scimone, A., et al. (2001) A genome screen of a large bipolar affective disorder pedigree supports evidence for a susceptibility locus on chromosome 13q. Mol. Psychiatry 6:396 – 403. Badner, J.A., and Gershon, E.S. (2002) Meta-analysis of whole-genome linkage scans of bipolar disorder and schizophrenia. Mol. Psychiatry 7:405– 411. Baron, M., Gruen, R., Asnis, L., and Kane, J. (1982) Schizoaffective illness, schizophrenia and affective disorders: morbidity risk and genetic transmission. Acta Psychiatr. Scand. 65:253–262. Baum, A.E., Akula, N., Cabanero, M., et al. (2007) A genome-wide association study implicates diacylglycerol kinase eta (DGKH) and several other genes in the etiology of bipolar disorder. Mol. Psychiatry 13(2):197–207. Bellivier, F., Henry, C., Szoke, A., et al. (1998) Serotonin transporter gene polymorphisms in patients with unipolar or bipolar depression. Neurosci. Lett. 255:143–146. Bellivier, F., Laplanche, J.L., Leboyer, M., et al. (1997) Serotonin transporter gene and manic depressive illness: an association study. Biol. Psychiatry 41:750–752. Bennett, P., Segurado, R., Jones, I., et al. (2002) The Wellcome Trust UK-Irish bipolar affective disorder sibling-pair genome screen: first stage report. Mol. Psychiatry 7:189–200. Berrettini, W. (2002) Review of bipolar molecular linkage and association studies. Curr. Psychiatry Rep. 4:124 –129.

Berrettini, W. (2003) Evidence for shared susceptibility in bipolar disorder and schizophrenia. Am. J. Med. Genet. 123C:59–64. Berrettini, W. (2004) Bipolar disorder and schizophrenia: convergent molecular data. Neuromolecular Med. 5:109–117. Berrettini, W.H., Ferraro, T.N., Goldin, L.R., et al. (1997) A linkage study of bipolar illness. Arch. Gen. Psychiatry 54:27–35. Bertelsen, A., Harvald, B., and Hauge, M. (1977) A Danish twin study of manic-depressive disorders. Br. J. Psychiatry 130:330–351. Bertolino, A., Frye, M., Callicott, J.H., Mattay, V.S., Rakow, R., Shelton-Repella, J., et al. (2003) Neuronal pathology in the hippocampal area of patients with bipolar disorder: a study with proton magnetic resonance spectroscopic imaging. Biol. Psychiatry 53:906–913. Bicalho, M.A., Pimenta, G.J., Neves, F.S., et al. (2006) Genotyping of the G1463A (Arg441His) TPH2 polymorphism in a geriatric population of patients with major depression. Mol. Psychiatry 11:799–800. Bierut, L.J., Heath, A.C., Bucholz, K.K., et al. (1999) Major depressive disorder in a community-based twin sample: are there different genetic and environmental contributions for men and women? Arch. Gen. Psychiatry 56:557–563. Blackwood, D.H., He, L., Morris, S.W., et al. (1996) A locus for bipolar affective disorder on chromosome 4p. Nat. Genet. 12:427– 430. Bland, R.C., Newman, S.C., and Orn, H. (1986) Recurrent and nonrecurrent depression. A family study. Arch. Gen. Psychiatry 43: 1085–1089. Blouin, J.L., Dombroski, B.A., Nath, S.K., et al. (1998) Schizophrenia susceptibility loci on chromosomes 13q32 and 8p21. Nat. Genet. 20:70–73. Blumberg, H.P., Kaugman, J., Martin, A., Whiteman, R., Zhang, J.H., Gore, J.C., et al. (2003) Amygdala and hippocampal volumes in adolescents and adults with bipolar disorder. Arch. Gen. Psychiatry 60:1201–1208. Bocchetta, A., Piccardi, M.P., Palmas, M.A., Chillotti, C., Oi, A., and Del Zompo, M. (1999) Family-based association study between bipolar disorder and DRD2, DRD4, DAT, and SERT in Sardinia. Am. J. Med. Genet. 88:522–526. Brzustowicz, L.M., Honer, W.G., Chow, E.W., et al. (1999) Linkage of familial schizophrenia to chromosome 13q32. Am. J. Hum. Genet. 65:1096–1103. Bueller, J.A., Aftab, M., Sen, S., Gomez-Hassan, D., Burmeister, M., and Zubieta, J.K. (2006) BDNF Val66Met allele is associated with reduced hippocampal volume in healthy subjects. Biol. Psychiatry 59:812–815. Cadoret, R.J. (1978) Evidence for genetic inheritance of primary affective disorder in adoptees. Am. J. Psychiatry 135:463– 466. Cadoret, R.J., Woolson, R., and Winokur, G. (1977) The relationship of age of onset in unipolar affective disorder to risk of alcoholism and depression in parents. J. Psychiatr. Res. 13:137–142. Camp, N.J., Lowry, M.R., Richards, R.L., et al. (2005) Genomewide linkage analyses of extended Utah pedigrees identifies loci that influence recurrent, early-onset major depression and anxiety disorders. Am. J. Med. Genet. B Neuropsychiatr. Genet. 135:85–93. Camp, N.J., Neuhausen, S.L., Tiobech, J., Polloi, A., Coon, H., and Myles-Worsley, M. (2001) Genomewide multipoint linkage analysis of seven extended Palauan pedigrees with schizophrenia, by a Markov-chain Monte Carlo method. Am. J. Hum. Genet. 69: 1278–1289. Cardno, A.G., Holmans, P.A., Rees, M.I., et al. (2001) A genomewide linkage study of age at onset in schizophrenia. Am. J. Med. Genet. 105:439– 445. Caspi, A., Sugden, K., Moffitt, T.E., et al. (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301:386–389. Cassidy, F., Zhao, C., Badger, J., et al. (2007) Genome-wide scan of bipolar disorder and investigation of population stratification effects on linkage: Support for susceptibility loci at 4q21, 7q36, 9p21, 12q24, 14q24, and 16p13. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144:791–801.

26: GENETICS Chen, Y.S., Akula, N., Detera-Wadleigh, S.D., et al. (2004) Findings in an independent sample support an association between bipolar affective disorder and the G72/G30 locus on chromosome 13q33. Mol. Psychiatry 9:87–92; image 5. Cheng, R., Juo, S.H., Loth, J.E., et al. (2006) Genome-wide linkage scan in a large bipolar disorder sample from the National Institute of Mental Health genetics initiative suggests putative loci for bipolar disorder, psychosis, suicide, and panic disorder. Mol. Psychiatry 11:252–260. Cho, H.J., Meira-Lima, I., Cordeiro, Q., et al. (2005) Populationbased and family-based studies on the serotonin transporter gene polymorphisms and bipolar disorder: a systematic review and metaanalysis. Mol. Psychiatry 10:771–781. Chumakov, I., Blumenfeld, M., Guerassimenko, O., et al. (2002) Genetic and physiological data implicating the new human gene G72 and the gene for D-amino acid oxidase in schizophrenia. Proc. Natl. Acad. Sci. USA 99:13675–13680. Cichon, S., Schumacher, J., Muller, D.J., et al. (2001) A genome screen for genes predisposing to bipolar affective disorder detects a new susceptibility locus on 8q. Hum. Mol. Genet. 10:2933–2944. Clark, A.G., Boerwinkle, E., Hixson, J., and Sing, C.F. (2005) Determinants of the success of whole-genome association testing. Genome Res. 15:1463–1467. Collier, D.A., Arranz, M.J., Sham, P., et al. (1996) The serotonin transporter is a potential susceptibility factor for bipolar affective disorder. Neuroreport 7:1675–1679. Collier, D.A., Stober, G., Li, T., et al. (1996) A novel functional polymorphism within the promoter of the serotonin transporter gene: possible role in susceptibility to affective disorders. Mol. Psychiatry 1:453– 460. Craddock, N., Daniels, J., Roberts, E., Rees, M., McGuffin, P., and Owen, M.J. (1995) No evidence for allelic association between bipolar disorder and monoamine oxidase A gene polymorphisms. Am. J. Med. Genet. 60:322–324. Craddock, N., and Forty, L. (2006) Genetics of affective (mood) disorders. Eur. J. Hum. Genet. 14:660–668. Curtis, D., Kalsi, G., Brynjolfsson, J., et al. (2003) Genome scan of pedigrees multiply affected with bipolar disorder provides further support for the presence of a susceptibility locus on chromosome 12q23-q24, and suggests the presence of additional loci on 1p and 1q. Psychiatr. Genet. 13:77–84. Dawson, E., Parfitt, E., Roberts, Q., et al. (1995) Linkage studies of bipolar disorder in the region of the Darier‘s disease gene on chromosome 12q23-24.1. Am. J. Med. Genet. 60:94–102. De bruyn, A., Souery, D., Mendelbaum, K., Mendlewicz, J., and Van Broeckhoven, C. (1996) Linkage analysis of families with bipolar illness and chromosome 18 markers. Biol. Psychiatry 39:679–688. de Lara, C.L., Brezo, J., Rouleau, G., et al. (2007) Effect of tryptophan hydroxylase-2 gene variants on suicide risk in major depression. Biol. Psychiatry 62(1):72–80. De Luca, V., Mueller, D.J., Tharmalingam, S., King, N., and Kennedy, J.L. (2004) Analysis of the novel TPH2 gene in bipolar disorder and suicidality. Mol. Psychiatry 9:896–897. Deckert, J., Catalano, M., Syagailo, Y.V., et al. (1999) Excess of high activity monoamine oxidase A gene promoter alleles in female patients with panic disorder. Hum. Mol. Genet. 8:621–624. Delorme, R., Durand, C.M., Betancur, C., et al. (2006) No human tryptophan hydroxylase-2 gene R441H mutation in a large cohort of psychiatric patients and control subjects. Biol. Psychiatry 60:202–203. Detera-Wadleigh, S.D., Badner, J.A., Berrettini, W.H., et al. (1999) A high-density genome scan detects evidence for a bipolar-disorder susceptibility locus on 13q32 and other potential loci on 1q32 and 18p11.2. Proc. Natl. Acad. Sci. USA 96:5604–5609. Detera-Wadleigh, S.D., Badner, J.A., Goldin, L.R., et al. (1996) Affectedsib-pair analyses reveal support of prior evidence for a susceptibility locus for bipolar disorder, on 21q. Am. J. Hum. Genet. 58:1279–1285.

371

Detera-Wadleigh, S.D., Badner, J.A., Yoshikawa, T., et al. (1997) Initial genome scan of the NIMH genetics initiative bipolar pedigrees: chromosomes 4, 7, 9, 18, 19, 20, and 21q. Am. J. Med. Genet. 74:254–262. Detera-Wadleigh, S.D., and McMahon, F.J. (2006) G72/G30 in schizophrenia and bipolar disorder: review and meta-analysis. Biol. Psychiatry 60:106–114. Dick, D.M., Foroud, T., Flury, L., et al. (2003) Genomewide linkage analyses of bipolar disorder: a new sample of 250 pedigrees from the National Institute of Mental Health Genetics Initiative. Am. J. Hum. Genet. 73:107–114. Duman, R.S. (2004) Role of neurotrophic factors in the etiology and treatment of mood disorders. Neuromolecular Med. 5:11–25. Duman, R.S., and Monteggia, L.M. (2006) A neurotrophic model for stress-related mood disorders. Biol. Psychiatry 59:1116–1127. Egan, M.F., Kojima, M., Callicott, J.H., et al. (2003) The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell 112:257–269. Ekholm, J.M., Kieseppa, T., Hiekkalinna, T., et al. (2003) Evidence of susceptibility loci on 4q32 and 16p12 for bipolar disorder. Hum. Mol. Genet.12:1907–1915. Ewald, H., Degn, B., Mors, O., and Kruse, T.A. (1998) Significant linkage between bipolar affective disorder and chromosome 12q24. Psychiatr. Genet. 8:131–140. Ewald, H., Flint, T., Kruse, T.A., and Mors, O. (2002) A genome-wide scan shows significant linkage between bipolar disorder and chromosome 12q24.3 and suggestive linkage to chromosomes 1p22-21, 4p16, 6q14-22, 10q26 and 16p13.3. Mol. Psychiatry 7:734–744. Fallin, M.D., Lasseter, V.K., Avramopoulos, D., et al. (2005) Bipolar I disorder and schizophrenia: a 440-single-nucleotide polymorphism screen of 64 candidate genes among Ashkenazi Jewish caseparent trios. Am. J. Hum. Genet. 77:918–936. Fallin, M.D., Lasseter, V.K., Wolyniec, P.S., et al. (2004) Genomewide linkage scan for bipolar-disorder susceptibility loci among Ashkenazi Jewish families. Am. J. Hum. Genet. 75:204–219. Faraone, S.V., Skol, A.D., Tsuang, D.W., et al. (2002) Linkage of chromosome 13q32 to schizophrenia in a large veterans affairs cooperative study sample. Am. J. Med. Genet. 114:598–604. Feinberg, A.P. (2007) Phenotypic plasticity and the epigenetics of human disease. Nature 447:433– 440. Fiskerstrand, C.E., Lovejoy, E.A., and Quinn, J.P. (1999) An intronic polymorphic domain often associated with susceptibility to affective disorders has allele dependent differential enhancer activity in embryonic stem cells. FEBS Lett. 458:171–174. Freimer, N.B., Reus, V.I., Escamilla, M.A., et al. (1996) Genetic mapping using haplotype, association and linkage methods suggests a locus for severe bipolar disorder (BPI) at 18q22-q23. Nat. Genet. 12:436– 441. Friddle, C., Koskela, R., Ranade, K., et al. (2000) Full-genome scan for linkage in 50 families segregating the bipolar affective disease phenotype. Am. J. Hum. Genet. 66:205–215. Fukumoto, T., Morinobu, S., Okamoto, Y., Kagaya, A., and Yamawaki, S. (2001) Chronic lithium treatment increases the expression of brain-derived neurotrophic factor in the rat brain. Psychopharmacology (Berl) 158:100–106. Furlong, R.A., Ho, L., Rubinsztein, J.S., Walsh, C., Paykel, E.S., and Rubinsztein, D.C. (1999) Analysis of the monoamine oxidase A (MAOA) gene in bipolar affective disorder by association studies, meta-analyses, and sequencing of the promoter. Am. J. Med. Genet. 88:398– 406. Furlong, R.A., Ho, L., Walsh, C., et al. (1998) Analysis and meta-analysis of two serotonin transporter gene polymorphisms in bipolar and unipolar affective disorders. Am. J. Med. Genet. 81:58–63. Gabriel, S.B., Schaffner, S.F., Nguyen, H., et al. (2002) The structure of haplotype blocks in the human genome. Science 296:2225–2229. Garriock, H.A., Allen, J.J., Delgado, P., et al. (2005) Lack of association of TPH2 exon XI polymorphisms with major depression and treatment resistance. Mol. Psychiatry 10:976–977.

372

MOOD DISORDERS

Geller, B., Badner, J.A., Tillman, R., Christian, S.L., Bolhofner, K., and Cook, E.H., Jr. (2004) Linkage disequilibrium of the brainderived neurotrophic factor Val66Met polymorphism in children with a prepubertal and early adolescent bipolar disorder phenotype. Am. J. Psychiatry 161:1698–1700. Gershon, E.S., DeLisi, L.E., Hamovit, J., et al. (1988) A controlled family study of chronic psychoses. Schizophrenia and schizoaffective disorder. Arch. Gen. Psychiatry 45:328–336. Gershon, E.S., Hamovit, J., Guroff, J.J., et al. (1982) A family study of schizoaffective, bipolar I, bipolar II, unipolar, and normal control probands. Arch. Gen. Psychiatry 39:1157–1167. Gershon, E.S., Weissman, M.M., Guroff, J.J., Prusoff, B.A., and Leckman, J.F. (1986) Validation of criteria for major depression through controlled family study. J. Affect. Disord. 11:125–131. Gillespie, N.A., Whitfield, J.B., Williams, B., Heath, A.C., and Martin, N.G. (2005) The relationship between stressful life events, the serotonin transporter (5-HTTLPR) genotype and major depression. Psychol. Med. 35:101–111. Ginns, E.I., St. Jean, P., Philibert, R.A., et al. (1998) A genome-wide search for chromosomal loci linked to mental health wellness in relatives at high risk for bipolar affective disorder among the Old Order Amish. Proc. Natl. Acad. Sci. USA 95:15531–15536. Glatt, C.E., Carlson, E., Taylor, T.R., Risch, N., Reus, V.I., and Schaefer, C.A. (2005) Response to Zhang et al. (2005) loss-of-function mutation in tryptophan hydroxylase-2 identified in unipolar major depression. Neuron 45:11–16. Neuron 48:704–705; author reply 705–706. Goes, F.S., Zandi, P.P., Miao, K., et al. (2007) Mood-incongruent psychotic features in bipolar disorder: familial aggregation and suggestive linkage to 2p11-q14 and 13q21-33. Am. J. Psychiatry 164:236–247. Gonul, A.S., Akdeniz, F., Taneli, F., Donat, O., Eker, C., and Vahip, S. (2005) Effect of treatment on serum brain-derived neurotrophic factor levels in depressed patients. Eur. Arch. Psychiatry Clin. Neurosci. 255:381–386. Green, E.K., Raybould, R., Macgregor, S., et al. (2006) Genetic variation of brain-derived neurotrophic factor (BDNF) in bipolar disorder: case-control study of over 3000 individuals from the UK. Br. J. Psychiatry 188:21–25. Gutierrez, B., Arias, B., Gasto, C., et al. (2004) Association analysis between a functional polymorphism in the monoamine oxidase A gene promoter and severe mood disorders. Psychiatr. Genet. 14: 203–208. Gutierrez, B., Arranz, M.J., Collier, D.A., et al. (1998) Serotonin transporter gene and risk for bipolar affective disorder: an association study in Spanish population. Biol. Psychiatry 43:843– 847. Hamilton, S.P., Fyer, A.J., Durner, M., et al. (2003) Further genetic evidence for a panic disorder syndrome mapping to chromosome 13q. Proc. Natl. Acad. Sci. USA 100:2550–2555. Hariri, A.R., Goldberg, T.E., Mattay, V.S., et al. (2003) Brain-derived neurotrophic factor val66met polymorphism affects human memoryrelated hippocampal activity and predicts memory performance. J. Neurosci. 23:6690–6694. Harvald, B., and Hauge, M. (1975) Genetics and the Epidemiology of Chronic Diseases, Vol. No. 1163. Washington, DC: PHS Publication. Hashimoto, K., Shimizu, E., and Iyo, M. (2004) Critical role of brainderived neurotrophic factor in mood disorders. Brain Res. Brain Res. Rev. 45:104 –114. Hashimoto, R., Takei, N., Shimazu, K., Christ, L., Lu, B., and Chuang, D.M. (2002) Lithium induces brain-derived neurotrophic factor and activates TrkB in rodent cortical neurons: an essential step for neuroprotection against glutamate excitotoxicity. Neuropharmacology 43:1173–1179. Hattori, E., Liu, C., Badner, J.A., et al. (2003) Polymorphisms at the G72/G30 gene locus, on 13q33, are associated with bipolar dis-

order in two independent pedigree series. Am. J. Hum. Genet. 72:1131–1140. Hauser, E.R., Boehnke, M., Guo, S.W., and Risch, N. (1996) Affectedsib-pair interval mapping and exclusion for complex genetic traits: sampling considerations. Genet. Epidemiol. 13:117–137. Hayden, E.P., and Nurnberger, J.I. (2006) Molecular genetics of bipolar disorder. Genes, Brain Behav. 5:85–95. Heils, A., Teufel, A., Petri, S., et al. (1996) Allelic variation of human serotonin transporter gene expression. J. Neurochem. 66:2621–2624. Helzer, J.E., and Winokur, G. (1974) A family interview study of male manic depressives. Arch. Gen. Psychiatry 31:73–77. Hoehe, M.R., Wendel, B., Grunewald, I., et al. (1998) Serotonin transporter (5-HTT) gene polymorphisms are not associated with susceptibility to mood disorders. Am. J. Med. Genet. 81:1–3. Holmans, P., Weissman, M.M., Zubenko, G.S., et al. (2007) Genetics of recurrent early-onset major depression (GenRED) final genome scan report. Am. J. Psychiatry 164:248–258. Holmans, P., Zubenko, G.S., Crowe, R.R., et al. (2004) Genomewide significant linkage to recurrent, early-onset major depressive disorder on chromosome 15q. Am. J. Hum. Genet. 74:1154–1167. Hong, C.J., Huo, S.J., Yen, F.C., Tung, C.L., Pan, G.M., and Tsai, S.J. (2003) Association study of a brain-derived neurotrophicfactor genetic polymorphism and mood disorders, age of onset and suicidal behavior. Neuropsychobiology 48:186–189. Hwang, J.P., Tsai, S.J., Hong, C.J., Yang, C.H., Lirng, J.F., and Yang, Y.M. (2006) The val66met polymorphism of the brain-derived neurotrophic-factor gene is associated with geriatric depression. Neurobiol. Aging 27:1834–1837. Iga, J.I., Ueno, S.I., Yamauchi, K., et al. (2007) The val66met polymorphism of the brain-derived neurotrophic factor gene is associated with psychotic feature and suicidal behavior in Japanese major depressive patients. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144(8):1003–1006. Ikeda, M., Iwata, N., Suzuki, T., et al. (2006) No association of serotonin transporter gene (SLC6A4) with schizophrenia and bipolar disorder in Japanese patients: association analysis based on linkage disequilibrium. J. Neural Transm. 113:899–905. James, N.M., and Chapman, C.J. (1975) A genetic study of bipolar affective disorder. Br. J. Psychiatry 126:449– 456. Johnson, G.F., and Leeman, M.M. (1977) Analysis of familial factors in bipolar affective illness. Arch. Gen. Psychiatry 34:1074 –1083. Jokela, M., Keltikangas-Jarvinen, L., Kivimaki, M., et al. (2007) Serotonin receptor 2a gene and the influence of childhood maternal nurturance on adulthood depressive symptoms. Arch. Gen. Psychiatry 64:356–360. Jorgenson, E., and Witte, J.S. (2006) A gene-centric approach to genome-wide association studies. Nat. Rev. Genet. 7:885–891. Kallman, F. (1954) Depression. New York: Grune and Stratton Karege, F., Perret, G., Bondolfi, G., Schwald, M., Bertschy, G., and Aubry, J.M. (2002) Decreased serum brain-derived neurotrophic factor levels in major depressed patients. Psychiatry Res. 109:143–148. Kawada, Y., Hattori, M., Dai, X.Y., and Nanko, S. (1995) Possible association between monoamine oxidase A gene and bipolar affective disorder. Am. J. Hum. Genet. 56:335–336. Ke, L., Qi, Z.Y., Ping, Y., and Ren, C.Y. (2006) Effect of SNP at position 40237 in exon 7 of the TPH2 gene on susceptibility to suicide. Brain Res. 1122:24–26. Kelsoe, J.R., Spence, M.A., Loetscher, E., et al. (2001) A genome survey indicates a possible susceptibility locus for bipolar disorder on chromosome 22. Proc. Natl. Acad. Sci. USA 98:585–590. Kendler, K.S., Gardner, C.O., Neale, M.C., and Prescott, C.A. (2001) Genetic risk factors for major depression in men and women: similar or different heritabilities and same or partly distinct genes? Psychol. Med. 31:605–616. Kendler, K.S., Gardner, C.O., and Prescott, C.A. (1999) Clinical characteristics of major depression that predict risk of depression in relatives. Arch. Gen. Psychiatry 56:322–327.

26: GENETICS Kendler, K.S., Kessler, R.C., Walters, E.E., et al. (1995) Stressful life events, genetic liability, and onset of an episode of major depression in women. Am. J. Psychiatry 152:833–842. Kendler, K.S., Kuhn, J.W., Vittum, J., Prescott, C.A., and Riley, B. (2005) The interaction of stressful life events and a serotonin transporter polymorphism in the prediction of episodes of major depression: a replication. Arch. Gen. Psychiatry 62:529–535. Kendler, K.S., McGuire, M., Gruenberg, A.M., O’Hare, A., Spellman, M., and Walsh, D. (1993) The Roscommon Family Study. I. Methods, diagnosis of probands, and risk of schizophrenia in relatives. Arch. Gen. Psychiatry 50:527–540. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1993) The lifetime history of major depression in women. Reliability of diagnosis and heritability. Arch. Gen. Psychiatry 50: 863–870. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1994) The clinical characteristics of major depression as indices of the familial risk to illness. Br. J. Psychiatry 165:66–72. Kendler, K.S., Pedersen, N.L., Neale, M.C., and Mathe, A.A. (1995) A pilot Swedish twin study of affective illness including hospitaland population-ascertained subsamples: results of model fitting. Behav. Genet. 25:217–232. Kendler, K.S., and Prescott, C.A. (1999) A population-based twin study of lifetime major depression in men and women. Arch. Gen. Psychiatry 56:39– 44. Kirov, G., Rees, M., Jones, I., MacCandless, F., Owen, M.J., and Craddock, N. (1999) Bipolar disorder and the serotonin transporter gene: a family-based association study. Psychol. Med. 29: 1249–1254. Knable, M.B., Barci, B.M., Webster, M.J., Meador-Woodruff, J., and Torrey, E.F. (2004) Molecular abnormalities of the hippocampus in severe psychiatric illness: postmortem findings from the Stanley Neuropathology Consortium. Mol. Psychiatry 9:609–620, 544. Kuma, H., Miki, T., Matsumoto, Y., Gu, H., Li, H.P., Kusaka, T., et al. (2004) Early maternal deprivation induces alterations in brainderived neurotrophic factor expression in the developing rat hippocampus. Neurosci. Lett. 372:68–73. Kunugi, H., Hattori, M., Kato, T., et al. (1997) Serotonin transporter gene polymorphisms: ethnic difference and possible association with bipolar affective disorder. Mol. Psychiatry 2:457– 462. Kunugi, H., Iijima, Y., Tatsumi, M., et al. (2004) No association between the Val66Met polymorphism of the brain-derived neurotrophic factor gene and bipolar disorder in a Japanese population: a multicenter study. Biol. Psychiatry 56:376–378. Kunugi, H., Ishida, S., Kato, T., et al. (1999) A functional polymorphism in the promoter region of monoamine oxidase-A gene and mood disorders. Mol. Psychiatry 4:393–395. Kunugi, H., Tatsumi, M., Sakai, T., Hattori, M., and Nanko, S. (1996) Serotonin transporter gene polymorphism and affective disorder. Lancet 347:1340–1341. Kupfer, D.J., Frank, E., Carpenter, L.L., and Neiswanger, K. (1989) Family history in recurrent depression. J. Affect. Disord. 17:113–119. Kwok, J.B., Adams, L.J., Salmon, J.A., Donald, J.A., Mitchell, P.B., and Schofield, P.R. (1999) Nonparametric simulation-based statistical analyses for bipolar affective disorder locus on chromosome 21q22.3. Am. J. Med. Genet. 88:99–102. Lachman, H.M., Kelsoe, J.R., Remick, R.A., et al. (1997) Linkage studies suggest a possible locus for bipolar disorder near the velocardio-facial syndrome region on chromosome 22. Am. J. Med. Genet. 74:121–128. Lambert, D., Middle, F., Hamshere, M.L., et al. (2005) Stage 2 of the Wellcome Trust UK-Irish bipolar affective disorder sibling-pair genome screen: evidence for linkage on chromosomes 6q16-q21, 4q12q21, 9p21, 10p14-p12 and 18q22. Mol. Psychiatry 10:831–841. Lander, E., and Kruglyak, L. (1995) Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nat. Genet. 11:241–247.

373

Lang, U.E., Hellweg, R., and Gallinat, J. (2004) BDNF serum concentrations in healthy volunteers are associated with depressionrelated personality traits. Neuropsychopharmacology 29:795–798. Lasky-Su, J.A., Faraone, S.V., Glatt, S.J., and Tsuang, M.T. (2005) Meta-analysis of the association between two polymorphisms in the serotonin transporter gene and affective disorders. Am. J. Med. Genet. B Neuropsychiatr. Genet. 133:110–115. Leckman, J.F., Feldman, R., Swain, J.E., Eicher, V., Thompson, N., and Mayes, L.C. (2004) Primary parental preoccupation: circuits, genes, and the crucial role of the environment. J. Neural Transm. 111:753–771. Lesch, K.P., Bengel, D., Heils, A., et al. (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274:1527–1531. Levinson, D.F., Evgrafov, O.V., Knowles, J.A., et al. (2007) Genetics of recurrent early-onset major depression (GenRED) significant linkage on chromosome 15q25-q26 after fine mapping with single nucleotide polymorphism markers. Am. J. Psychiatry 164: 259–264. Levinson, D.F., Levinson, M.D., Segurado, R., and Lewis, C.M. (2003) Genome scan meta-analysis of schizophrenia and bipolar disorder, part I: Methods and power analysis. Am. J. Hum. Genet. 73:17–33. Lim, L.C., Powell, J., Sham, P., et al. (1995) Evidence for a genetic association between alleles of monoamine oxidase A gene and bipolar affective disorder. Am. J. Med. Genet. 60:325–331. Lin, M.W., Sham, P., Hwu, H.G., Collier, D., Murray, R., and Powell, J.F. (1997) Suggestive evidence for linkage of schizophrenia to markers on chromosome 13 in Caucasian but not Oriental populations. Hum. Genet. 99:417– 420. Lin, P.I., McInnis, M.G., Potash, J.B., et al. (2005) Assessment of the effect of age at onset on linkage to bipolar disorder: evidence on chromosomes 18p and 21q. Am. J. Hum. Genet. 77:545–555. Lin, S., Jiang, S., Wu, X., et al. (2000) Association analysis between mood disorder and monoamine oxidase gene. Am. J. Med. Genet. 96:12–14. Liu, J., Juo, S.H., Dewan, A., et al. (2003) Evidence for a putative bipolar disorder locus on 2p13-16 and other potential loci on 4q31, 7q34, 8q13, 9q31, 10q21-24, 13q32, 14q21 and 17q11-12. Mol. Psychiatry 8:333–342. Liu, W., Gu, N., Feng, G., et al. (1999) Tentative association of the serotonin transporter with schizophrenia and unipolar depression but not with bipolar disorder in Han Chinese. Pharmacogenetics 9:491– 495. Lohoff, F.W., Sander, T., Ferraro, T.N., Dahl, J.P., Gallinat, J., and Berrettini, W.H. (2005) Confirmation of association between the Val66Met polymorphism in the brain-derived neurotrophic factor (BDNF) gene and bipolar I disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. 139:51–53. Lopez, V.A., Detera-Wadleigh, S., Cardona, I., Kassem, L., and McMahon, F.J. (2007) Nested association between genetic variation in tryptophan hydroxylase II, bipolar affective disorder, and suicide attempts. Biol. Psychiatry 61:181–186. Luxenberger, H. (1930) Psychiatrisch-neurologische Zwillings pathologie. Zentralblatt fur diagesamte Neurologie and Psychiatrie 14: 145–180. Lyons, M.J., Eisen, S.A., Goldberg, J., et al. (1998) A registry-based twin study of depression in men. Arch. Gen. Psychiatry 55:468 – 472. MacKinnon, D.F., Zandi, P.P., Cooper, J., et al. (2002) Comorbid bipolar disorder and panic disorder in families with a high prevalence of bipolar disorder. Am. J. Psychiatry 159:30–35. Maier, W., Lichtermann, D., Minges, J., et al. (1993) Continuity and discontinuity of affective disorders and schizophrenia. Results of a controlled family study. Arch. Gen. Psychiatry 50:871–883. Maier, W., Lichtermann, D., Minges, J., Heun, R., Hallmayer, J., and Benkert, O. (1992) Schizoaffective disorder and affective disorders with mood-incongruent psychotic features: keep separate or

374

MOOD DISORDERS

combine? Evidence from a family study. Am. J. Psychiatry 149: 1666–1673. Malhotra, A.K., Murphy, G.M., Jr., and Kennedy, J.L. (2004) Pharmacogenetics of Psychotropic Drug Response. Am. J. Psychiatry 161:780–796. Maziade, M., Roy, M.A., Rouillard, E., et al. (2001) A search for specific and common susceptibility loci for schizophrenia and bipolar disorder: a linkage study in 13 target chromosomes. Mol. Psychiatry 6:684 – 693. McGuffin, P., Katz, R., Watkins, S., and Rutherford, J. (1996) A hospital-based twin register of the heritability of DSM-IV unipolar depression. Arch. Gen. Psychiatry 53:129–136. McGuffin, P., Knight, J., Breen, G., et al. (2005) Whole genome linkage scan of recurrent depressive disorder from the depression network study. Hum. Mol. Genet. 14:3337–3345. McGuffin, P., Rijsdijk, F., Andrew, M., Sham, P., Katz, R., and Cardno, A. (2003) The heritability of bipolar affective disorder and the genetic relationship to unipolar depression. Arch. Gen. Psychiatry 60:497–502. McInnes, L.A., Escamilla, M.A., Service, S.K., et al. (1996) A complete genome screen for genes predisposing to severe bipolar disorder in two Costa Rican pedigrees. Proc. Natl. Acad. Sci. USA 93:13060–13065. McInnis, M.G., Lan, T.H., Willour, V.L., et al. (2003) Genome-wide scan of bipolar disorder in 65 pedigrees: supportive evidence for linkage at 8q24, 18q22, 4q32, 2p12, and 13q12. Mol. Psychiatry 8:288–298. McMahon, F.J., Buervenich, S., Charney, D., et al. (2006) Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am. J. Hum. Genet. 78:804 – 814. McMahon, F.J., Hopkins, P.J., Xu, J., et al. (1997) Linkage of bipolar affective disorder to chromosome 18 markers in a new pedigree series. Am. J. Hum. Genet. 61:1397–1404. McQueen, M.B., Devlin, B., Faraone, S.V., et al. (2005) Combined analysis from eleven linkage studies of bipolar disorder provides strong evidence of susceptibility loci on chromosomes 6q and 8q. Am. J. Hum. Genet. 77:582–595. Mendlewicz, J., and Baron, M. (1981) Morbidity risks in subtypes of unipolar depressive illness: differences between early and late onset forms. Br. J. Psychiatry 139:463– 466. Mendlewicz, J., Massat, I., Souery, D., et al. (2004) Serotonin transporter 5HTTLPR polymorphism and affective disorders: no evidence of association in a large European multicenter study. Eur. J. Hum. Genet. 12:377–382. Mendlewicz, J., and Rainer, J.D. (1977) Adoption study supporting genetic transmission in manic--depressive illness. Nature 268: 327–329. Merikangas, K.R., Risch, N.J., and Weissman, M.M. (1994) Comorbidity and co-transmission of alcoholism, anxiety and depression. Psychol. Med. 24:69–80. Middleton, F.A., Pato, M.T., Gentile, K.L., et al. (2004) Genomewide linkage analysis of bipolar disorder by use of a high-density single-nucleotide-polymorphism (SNP) genotyping assay: a comparison with microsatellite marker assays and finding of significant linkage to chromosome 6q22. Am. J. Hum. Genet. 74:886–897. Minov, C., Baghai, T.C., Schule, C., et al. (2001) Serotonin-2Areceptor and -transporter polymorphisms: lack of association in patients with major depression. Neurosci. Lett. 303:119–122. Moldin, S.O., Reich, T., and Rice, J.P. (1991) Current perspectives on the genetics of unipolar depression. Behav. Genet. 21:211–242. Monkul, E.S., Malhi, G.S., and Soares, J.C. (2003) Mood disorder— review of structural MRI studies. Acta Neuropsychiatrica 15: 368–380. Morissette, J., Villeneuve, A., Bordeleau, L., et al. (1999) Genomewide search for linkage of bipolar affective disorders in a very large pedigree derived from a homogeneous population in Quebec

points to a locus of major effect on chromosome 12q23-q24. Am. J. Med. Genet. 88:567–587. Mukherjee, O., Meera, P., Ghosh, S., et al. (2006) Evidence of linkage and association on 18p11.2 for psychosis. Am. J. Med. Genet. B Neuropsychiatr. Genet. 141B:868–873. Muller, D.J., de Luca, V., Sicard, T., King, N., Strauss, J., and Kennedy, J.L. (2006) Brain-derived neurotrophic factor (BDNF) gene and rapid-cycling bipolar disorder: family-based association study. Br. J. Psychiatry 189:317–323. Muller, D.J., Serretti, A., Sicard, T., et al. (2007) Further evidence of MAO-A gene variants associated with bipolar disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144:37– 40. Muramatsu, T., Matsushita, S., Kanba, S., et al. (1997) Monoamine oxidase genes polymorphisms and mood disorder. Am. J. Med. Genet. 74:494 – 496. Mynett-Johnson, L., Kealey, C., Claffey, E., et al. (2000) Multimarkerhaplotypes within the serotonin transporter gene suggest evidence of an association with bipolar disorder. Am. J. Med. Genet. 96:845–849. Nakata, K., Ujike, H., Sakai, A., et al. (2003) Association study of the brain-derived neurotrophic factor (BDNF) gene with bipolar disorder. Neurosci. Lett. 337:17–20. Nestler, E.J., Barrot, M., DiLeone, R.J., Eisch, A.J., Gold, S.J., and Monteggia, L.M. (2002) Neurobiology of depression. Neuron 34:13–25. Neves-Pereira, M., Cheung, J.K., Pasdar, A., et al. (2005) BDNF gene is a risk factor for schizophrenia in a Scottish population. Mol. Psychiatry 10:208–212. Neves-Pereira, M., Mundo, E., Muglia, P., King, N., Macciardi, F., and Kennedy, J.L. (2002) The brain-derived neurotrophic factor gene confers susceptibility to bipolar disorder: evidence from a family-based association study. Am. J. Hum. Genet. 71:651– 655. Nibuya, M., Morinobu, S., and Duman, R.S. (1995) Regulation of BDNF and trkB mRNA in rat brain by chronic electroconvulsive seizure and antidepressant drug treatments. J. Neurosci. 15: 7539–7547. Nothen, M.M., Cichon, S., Rohleder, H., et al. (1999) Evaluation of linkage of bipolar affective disorder to chromosome 18 in a sample of 57 German families. Mol. Psychiatry 4:76–84. Nothen, M.M., Eggermann, K., Albus, M., et al. (1995) Association analysis of the monoamine oxidase A gene in bipolar affective disorder by using family-based internal controls. Am. J. Hum. Genet. 57:975–978. Nurnberger, J.I., Jr., Foroud, T., Flury, L., Meyer, E.T., and Wiegand, R. (2002) Is there a genetic relationship between alcoholism and depression? Alcohol Res. Health 26:233–240. Okada, T., Hashimoto, R., Numakawa, T., et al. (2006) A complex polymorphic region in the brain-derived neurotrophic factor (BDNF) gene confers susceptibility to bipolar disorder and affects transcriptional activity. Mol. Psychiatry 11:695–703. Oliveira, J.R., Carvalho, D.R., Pontual, D., et al. (2000) Analysis of the serotonin transporter polymorphism (5-HTTLPR) in Brazilian patients affected by dysthymia, major depression and bipolar disorder. Mol. Psychiatry 5:348–349. Ospina-Duque, J., Duque, C., Carvajal-Carmona, L., et al. (2000) An association study of bipolar mood disorder (type I) with the 5-HTTLPR serotonin transporter polymorphism in a human population isolate from Colombia. Neurosci. Lett. 292:199–202. Oswald, P., Del-Favero, J., Massat, I., et al. (2004) Non-replication of the brain-derived neurotrophic factor (BDNF) association in bipolar affective disorder: a Belgian patient-control study. Am. J. Med. Genet. 129B:34–35. Park, B.H., and Vogelstein, B. (2003) Tumor-suppressor genes. In: Kufe, D.W., Pollock, R.E., Weichselbaum, R.R., Bast, R.C., Jr., Gansler, T. S. eds. Cancer Medicine, 6th ed. Lewiston, NY: BC Decker, pp. 87–106.

26: GENETICS Park, N., Juo, S.H., Cheng, R., et al. (2004) Linkage analysis of psychosis in bipolar pedigrees suggests novel putative loci for bipolar disorder and shared susceptibility with schizophrenia. Mol. Psychiatry 9:1091–1099. Parsian, A., and Todd, R.D. (1997) Genetic association between monoamine oxidase and manic-depressive illness: comparison of relative risk and haplotype relative risk data. Am. J. Med. Genet. 74: 475– 479. Pato, C.N., Pato, M.T., Kirby, A., et al. (2004) Genome-wide scan in Portuguese Island families implicates multiple loci in bipolar disorder: fine mapping adds support on chromosomes 6 and 11. Am. J. Med. Genet. B Neuropsychiatr. Genet. 127:30–34. Pierotti, N.S., Schichman, S.A., Sozzi, G., and Croce, C.M. (2000) Oncogenes. Hamilton, Canada: BC Decker Inc. Post, R.M. (2007) Role of BDNF in bipolar and unipolar disorder: clinical and theoretical implications. J. Psychiatr. Res. 41(12): 979–990. Potash, J.B., Chiu, Y.F., MacKinnon, D.F., et al. (2003) Familial aggregation of psychotic symptoms in a replication set of 69 bipolar disorder pedigrees. Am. J. Med. Genet. B Neuropsychiatr. Genet. 116:90–97. Potash, J.B., Willour, V.L., Chiu, Y.F., et al. (2001) The familial aggregation of psychotic symptoms in bipolar disorder pedigrees. Am. J. Psychiatry 158:1258–1264. Potash, J.B., Zandi, P.P., Willour, V.L., et al. (2003) Suggestive linkage to chromosomal regions 13q31 and 22q12 in families with psychotic bipolar disorder. Am. J. Psychiatry 160:680–686. Preisig, M., Bellivier, F., Fenton, B.T., et al. (2000) Association between bipolar disorder and monoamine oxidase A gene polymorphisms: results of a multicenter study. Am. J. Psychiatry 157:948–955. Ramamoorthy, S., Bauman, A.L., Moore, K.R., et al. (1993) Antidepressant- and cocaine-sensitive human serotonin transporter: molecular cloning, expression, and chromosomal localization. Proc. Natl. Acad. Sci. USA 90:2542–2546. Rees, M., Norton, N., Jones, I., et al. (1997) Association studies of bipolar disorder at the human serotonin transporter gene (hSERT; 5HTT). Mol. Psychiatry 2:398– 402. Reich, T., Van Eerdewegh, P., Rice, J., Mullaney, J., Endicott, J., and Klerman, G.L. (1987) The familial transmission of primary major depressive disorder. J. Psychiatr. Res. 21:613–624. Repetti, R.L., Taylor, S.E., and Seeman, T.E. (2002) Risky families: family social environments and the mental and physical health of offspring. Psychol. Bull. 128:330–366. Rice, J.P., Goate, A., Williams, J.T., et al. (1997) Initial genome scan of the NIMH genetics initiative bipolar pedigrees: chromosomes 1, 6, 8, 10, and 12. Am. J. Med. Genet. 74:247–253. Roceri, M., Cirulli, F., Pessina, C., Peretto, P., Racagni, G., and Riva, M.A. (2004) Postnatal repeated maternal deprivation produces age-dependent changes of brain-derived neurotrophic factor expression in selected rat brain regions. Biol. Psychiatry 55:708–714. Roceri, M., Hendriks, W., Racagni, G., Ellenbroek, B.A., and Riva, M.A. (2002) Early maternal deprivation reduces the expression of BDNF and NMDA receptor subunits in rat hippoampus. Mol. Psychiatry 7:609–616. Rosanoff, A.J., Handy, L., and Plesset, I.R. (1935) The etiology of manic-depressive syndromes with special reference to their occurrence in twins. Am. J. Psychiatry 91:725–762. Rybakowski, J.K., Borkowska, A., Czerski, P.M., Skibinska, M., and Hauser, J. (2003) Polymorphism of the brain-derived neurotrophic factor gene and performance on a cognitive prefrontal test in bipolar patients. Bipolar Disord. 5:468– 472. Rybakowski, J.K., Borkowska, A., Skibinska, M., and Hauser, J. (2006) Illness-specific association of val66met BDNF polymorphism with performance on Wisconsin Card Sorting Test in bipolar mood disorder. Mol. Psychiatry 11:122–124. Rybakowski, J.K., Borkowska, A., Skibinska, M., Szczepankiewicz, A., et al. (2006) Prefrontal cognition in schizophrenia and bipolar

375

illness in relation to Val66Met polymorphism of the brain-derived neurotrophic factor gene. Psychiatry Clin. Neurosci. 60:70–76. Saleem, Q., Ganesh, S., Vijaykumar, M., Reddy, Y.C., Brahmachari, S.K., and Jain, S. (2000) Association analysis of 5HT transporter gene in bipolar disorder in the Indian population. Am. J. Med. Genet. 96:170–172. Savitz, J., Cupido, C.L., and Ramesar, R.K. (2007) Preliminary evidence for linkage to chromosome 1q31-32, 10q23.3, and 16p13.3 in a South African cohort with bipolar disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144:383–387. Schulze, T.G., Muller, D.J., Krauss, H., et al. (2000) Association between a functional polymorphism in the monoamine oxidase A gene promoter and major depressive disorder. Am. J. Med. Genet. 96:801–803. Schumacher, J., Jamra, R.A., Becker, T., et al. (2005) Evidence for a relationship between genetic variants at the brain-derived neurotrophic factor (BDNF) locus and major depression. Biol. Psychiatry 58:307–314. Schumacher, J., Jamra, R.A., Freudenberg, J., et al. (2004) Examination of G72 and D-amino-acid oxidase as genetic risk factors for schizophrenia and bipolar affective disorder. Mol. Psychiatry 9:203–207. Schumacher, J., Kaneva, R., Jamra, R.A., et al. (2005) Genomewide scan and fine-mapping linkage studies in four European samples with bipolar affective disorder suggest a new susceptibility locus on chromosome 1p35-p36 and provides further evidence of loci on chromosome 4q31 and 6q24. Am. J. Hum. Genet. 77:1102–1111. Segurado, R., Detera-Wadleigh, S.D., Levinson, D.F., et al. (2003) Genome scan meta-analysis of schizophrenia and bipolar disorder, part III: Bipolar disorder. Am. J. Hum. Genet. 73:49–62. Serretti, A., Benedetti, F., Zanardi, R., and Smeraldi, E. (2005) The influence of Serotonin Transporter Promoter Polymorphism (SERTPR) and other polymorphisms of the serotonin pathway on the efficacy of antidepressant treatments. Prog. Neuropsychopharmacol. Biol. Psychiatry 29:1074 –1084. Serretti, A., Cristina, S., Lilli, R., et al. (2002) Family-based association study of 5-HTTLPR, TPH, MAO-A, and DRD4 polymorphisms in mood disorders. Am. J. Med. Genet. 114:361–369. Serretti, A., Cusin, C., Rausch, J.L., Bondy, B., and Smeraldi, E. (2006) Pooling pharmacogenetic studies on the serotonin transporter: a mega-analysis. Psychiatry Res. 145:61–65. Shaw, S.H., Kelly, M., Smith, A.B., et al. (1998) A genome-wide search for schizophrenia susceptibility genes. Am. J. Med. Genet. 81:364 –376. Shimizu, E., Hashimoto, K., Okamura, N., et al. (2003) Alterations of serum levels of brain-derived neurotrophic factor (BDNF) in depressed patients with or without antidepressants. Biol. Psychiatry 54:70–75. Shink, E., Morissette, J., Sherrington, R., and Barden, N. (2005) A genome-wide scan points to a susceptibility locus for bipolar disorder on chromosome 12. Mol. Psychiatry 10:545–552. Shirayama, Y., Chen, A.C., Nakagawa, S., Russell, D.S., and Duman, R.S. (2002) Brain-derived neurotrophic factor produces antidepressant effects in behavioral models of depression. J. Neurosci. 22:3251–3261. Siuciak, J.A., Lewis, D.R., Wiegand, S.J., and Lindsay, R.M. (1997) Antidepressant-like effect of brain-derived neurotrophic factor (BDNF). Pharmacol. Biochem. Behav. 56:131–137. Skibinska, M., Hauser, J., Czerski, P.M., et al. (2004) Association analysis of brain-derived neurotrophic factor (BDNF) gene Val66Met polymorphism in schizophrenia and bipolar affective disorder. World J. Biol. Psychiatry 5:215–220. Sklar, P., Gabriel, S.B., McInnis, M.G., et al. (2002) Family-based association study of 76 candidate genes in bipolar disorder: BDNF is a potential risk locus. Brain-derived neutrophic factor. Mol. Psychiatry 7:579–593. Slater, E. (1936) The inheritance of manic-depressive insanity. Proc. R. Soc. Med. 29:981–990.

376

MOOD DISORDERS

Smeraldi, E., Serretti, A., Artioli, P., Lorenzi, C., and Catalano, M. (2006) Serotonin transporter gene-linked polymorphic region: possible pharmacogenetic implications of rare variants. Psychiatr. Genet. 16:153–158. Smith, M.A., Makino, S., Kvetnansky, R., and Post, R.M. (1995) Effects of stress on neurotrophic factor expression in the rat brain. Ann. N.Y. Acad. Sci. 771:234–239. Smyth, C., Kalsi, G., Brynjolfsson, J., et al. (1996) Further tests for linkage of bipolar affective disorder to the tyrosine hydroxylase gene locus on chromosome 11p15 in a new series of multiplex British affective disorder pedigrees. Am. J. Psychiatry 153:271– 274. Stancer, H.C., Persad, E., Wagener, D.K., and Jorna, T. (1987) Evidence for homogeneity of major depression and bipolar affective disorder. J. Psychiatr. Res. 21:37–53. Stevens, E.R., Esguerra, M., Kim, P.M., et al. (2003) D-serine and serine racemase are present in the vertebrate retina and contribute to the physiological activation of NMDA receptors. Proc. Natl. Acad. Sci. USA 100:6789–6794. Stine, O.C., Xu, J., Koskela, R., et al. (1995) Evidence for linkage of bipolar disorder to chromosome 18 with a parent-of-origin effect. Am. J. Hum. Genet. 57:1384–1394. Straub, R.E., Lehner, T., Luo, Y., et al. (1994) A possible vulnerability locus for bipolar affective disorder on chromosome 21q22.3. Nat. Genet. 8:291–296. Strauss, J., Barr, C.L., George, C.J., et al. (2004) Association study of brain-derived neurotrophic factor in adults with a history of childhood onset mood disorder. Am. J. Med. Genet. 131B(1): 16–19. Strauss, J., Barr, C.L., George, C.J., et al. (2005) Brain-derived neurotrophic factor variants are associated with childhood-onset mood disorder: confirmation in a Hungarian sample. Mol. Psychiatry 10:861–867. Suarez, B.H., Hampe, C.L., and Van Eerdewegh, P. (1994) Problems of replicating linkage claims in psychiatry. Washington, DC: American Psychiatric Press. Sullivan, P.F., Neale, M.C., and Kendler, K.S. (2000) Genetic epidemiology of major depression: review and meta-analysis. Am. J. Psychiatry 157:1552–1562. Surtees, P.G., Wainwright, N.W., Willis-Owen, S.A., et al. (2007) No association between the BDNF Val66Met polymorphism and mood status in a non-clinical community sample of 7389 older adults. J. Psychiatr. Res. 41:404 – 409. Surtees, P.G., Wainwright, N.W., Willis-Owen, S.A., Luben, R., Day, N.E., and Flint, J. (2006) Social adversity, the serotonin transporter (5-HTTLPR) polymorphism and major depressive disorder. Biol. Psychiatry 59:224 –229. Syagailo, Y.V., Stober, G., Grassle, M., et al. (2001) Association analysis of the functional monoamine oxidase A gene promoter polymorphism in psychiatric disorders. Am. J. Med. Genet. 105: 168–171. Taylor, M.A., Berenbaum, S.A., Jampala, V.C., and Cloninger, C.R. (1993) Are schizophrenia and affective disorder related? preliminary data from a family study. Am. J. Psychiatry 150:278–285. Torgersen, S. (1986) Genetic factors in moderately severe and mild affective disorders. Arch. Gen. Psychiatry 43:222–226. Tramontina, J., Frey, B.N., Andreazza, A.C., Zandona, M., Santin, A., and Kapczinski, F. (2007) Val66met polymorphism and serum brain-derived neurotrophic factor levels in bipolar disorder. Mol. Psychiatry 12:230–231. Tsai, S.J., Cheng, C.Y., Yu, Y.W., Chen, T.J., and Hong, C.J. (2003) Association study of a brain-derived neurotrophic-factor genetic polymorphism and major depressive disorders, symptomatology, and antidepressant response. Am. J. Med. Genet. B Neuropsychiatr. Genet. 123:19–22. Tsankova, N., Renthal, W., Kumar, A., and Nestler, E.J. (2007) Epigenetic regulation in psychiatric disorders. Nat. Rev. Neurosci. 8:355–367.

Tsuang, M.T., Taylor, L., and Faraone, S.V. (2004) An overview of the genetics of psychotic mood disorders. J. Psychiatr. Res. 38:3–15. Tsuang, M.T., Winokur, G., and Crowe, R.R. (1980) Morbidity risks of schizophrenia and affective disorders among first degree relatives of patients with schizophrenia, mania, depression and surgical conditions. Br. J. Psychiatry 137:497–504. Turecki, G., Grof, P., Cavazzoni, P., et al. (1999a) Lithium responsive bipolar disorder, unilineality, and chromosome 18: A linkage study. Am. J. Med. Genet. 88:411– 415. Turecki, G., Grof, P., Cavazzoni, P., et al. (1999b) MAOA: association and linkage studies with lithium responsive bipolar disorder. Psychiatr. Genet. 9:13–16. Van Den Bogaert, A., De Zutter, S., Heyrman, L., et al. (2005) Response to Zhang et al. (2005): loss-of-function mutation in tryptophan hydroxylase-2 identified in unipolar major depression. Neuron 48:704; author reply 705–706. Van Den Bogaert, A., Sleegers, K., De Zutter, S., et al. (2006) Association of brain-specific tryptophan hydroxylase, TPH2, with unipolar and bipolar disorder in a Northern Swedish, isolated population. Arch. Gen. Psychiatry 63:1103–1110. Venken, T., Claes, S., Sluijs, S., et al. (2005) Genomewide scan for affective disorder susceptibility Loci in families of a northern Swedish isolated population. Am. J. Hum. Genet. 76:237–248. Venter, J.C., Adams, M.D., Myers, E.W., et al. (2001) The sequence of the human genome. Science 291:1304 –1351. Videbech, P., and Ravnkilde, B. (2004) Hippocampal volume and depression: a meta-analysis of MRI studies. Am. J. Psychiatry 161: 1957–1966. Vincent, J.B., Masellis, M., Lawrence, J., et al. (1999) Genetic association analysis of serotonin system genes in bipolar affective disorder. Am. J. Psychiatry 156:136–138. von Knorring, A.L., Cloninger, C.R., Bohman, M., and Sigvardsson, S. (1983) An adoption study of depressive disorders and substance abuse. Arch. Gen. Psychiatry 40:943–950. Walther, D.J., and Bader, M. (2003) A unique central tryptophan hydroxylase isoform. Biochem. Pharmacol. 66:1673–1680. Weissman, M.M., Bland, R.C., Canino, G.J., et al. (1996) Crossnational epidemiology of major depression and bipolar disorder. JAMA 276:293–299. Weissman, M.M., Gershon, E.S., Kidd, K.K., et al. (1984) Psychiatric disorders in the relatives of probands with affective disorders. The Yale University—National Institute of Mental Health Collaborative Study. Arch. Gen. Psychiatry 41:13–21. Weissman, M.M., Merikangas, K.R., Wickramaratne, P., et al. (1986) Understanding the clinical heterogeneity of major depression using family data. Arch. Gen. Psychiatry 43:430 – 434. Weissman, M.M., Wickramaratne, P., Adams, P.B., et al. (1993) The relationship between panic disorder and major depression. A new family study. Arch. Gen. Psychiatry 50:767–780. Wellcome Trust Case Control Consortium. (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447:661–678. Wender, P.H., Kety, S.S., Rosenthal, D., Schulsinger, F., Ortmann, J., and Lunde, I. (1986) Psychiatric disorders in the biological and adoptive families of adopted individuals with affective disorders. Arch. Gen. Psychiatry 43:923–929. Wijsman, E.M., Rosenthal, E.A., Hall, D., et al. (2003) Genomewide scan in a large complex pedigree with predominantly male schizophrenics from the island of Kosrae: evidence for linkage to chromosome 2q. Mol. Psychiatry 8:695–705, 643. Williams, N.M., Green, E.K., Macgregor, S., et al. (2006) Variation at the DAOA/G30 locus influences susceptibility to major mood episodes but not psychosis in schizophrenia and bipolar disorder. Arch. Gen. Psychiatry 63:366–373. Willis-Owen, S.A., Turri, M.G., Munafo, M.R., et al. (2005) The serotonin transporter length polymorphism, neuroticism, and depression: a comprehensive assessment of association. Biol. Psychiatry 58:451–456.

26: GENETICS Winokur, G., Cadoret, R., Dorzab, J., and Baker, M. (1971) Depressive disease: a genetic study. Arch. Gen. Psychiatry 24:135– 144. Winokur, G., Tsuang, M.T., and Crowe, R.R. (1982) The Iowa 500: affective disorder in relatives of manic and depressed patients. Am. J. Psychiatry 139:209–212. Zhang, L.X., Levine, S., Dent, G., Zhan, Y., Xing, G., Okimoto, D., et al. (2002) Maternal deprivation increases cell death in the infant rat brain. Brain Res. 133:1–11 Zhang, X., Gainetdinov, R.R., Beaulieu, J.M., et al. (2005) Loss-offunction mutation in tryptophan hydroxylase-2 identified in unipolar major depression. Neuron 45:11–16. Zhou, Z., Peters, E.J., Hamilton, S.P., et al. (2005) Response to Zhang et al. (2005) loss-of-function mutation in tryptophan hydroxylase-2 identified in unipolar major depression. Neuron 48:702–703; author reply 705–706.

377

Zhou, Z., Roy, A., Lipsky, R., et al. (2005) Haplotype-based linkage of tryptophan hydroxylase 2 to suicide attempt, major depression, and cerebrospinal fluid 5-hydroxyindoleacetic acid in 4 populations. Arch. Gen. Psychiatry 62:1109–1118. Zill, P., Baghai, T.C., Zwanzger, P., et al. (2004) SNP and haplotype analysis of a novel tryptophan hydroxylase isoform (TPH2) gene provide evidence for association with major depression. Mol. Psychiatry 9:1030–1036. Zubenko, G.S., Hughes, H.B., 3rd, Stiffler, J.S., et al. (2003) Sequence variations in CREB1 cosegregate with depressive disorders in women. Mol. Psychiatry 8:611–618. Zubenko, G.S., Maher, B., Hughes, H.B., 3rd, et al. (2003) Genomewide linkage survey for genetic loci that influence the development of depressive disorders in families with recurrent, early-onset, major depression. Am. J. Med. Genet. B Neuropsychiatr. Genet. 123:1–18.

27 Animal Models of Mood Disorders INGE SILLABER, FLORIAN HOLSBOER, A N D

CARSTEN T. WOTJAK

Animal models have proven to be indispensable tools for the advancement of medicine as a whole, and they are playing an increasingly important role as research tools in psychiatry. Ideally, the animal model created should mimic the human condition of interest with respect to its etiology (etiological validity), symptomatology (face validity), pharmacological treatment (predictive validity), and biological basis (construct validity; Fig. 27.1) (McKinney and Bunney, 1969). Clearly, meeting such requirements is difficult. This is particularly true for depression, where the presence of some of the cardinal features (for example, feelings of worthlessness and guilt and suicidal ideation) is defined by a subjective verbal report, something that can never be modelled in an animal. The presence of other features of depression can be defined operationally (for example, loss of appetite and weight, sleep disturbances, and psychomotor changes). However, a model that is limited to a decrease in appetite and psychomotor activity, for example, would be a very superficial reflection of the clinical condition of depression. Another difficulty in the development of animal models of depression stems from the way by which such models are generated. Most models using nonhuman primates or rodents are based on exposing healthy animals to adverse experience, in most cases a stressor, for prolonged periods of time. The resulting phenotype accounts only for experience-related behavioral changes bearing the resemblance to depression (Kalueff et al., 2007). In such models, the fact that the development of depression is strongly influenced by genetic factors is ignored. In light of these difficulties, the development of a perfectly homologous model, reproducing as closely as possible all aspects of depression, seems out of reach. Instead, more pragmatic approaches are now being pursued, in which animal models are developed for distinct purposes: (1) as behavioral tests to screen for potential antidepressant effects of new pharmaceutical drugs and (2) as tools to investigate specific pathogenetic aspects of cardinal symptoms of depression. The traditional routes to animal models of depression have recently been expanded by the possibility of studying mice that have behavioral changes that are not experience

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related but rather are secondary to the insertion of a transgene or to a targeted disruption of a single gene. This chapter starts with a brief overview of potential model organisms, followed by a description of depression-like symptoms that can be addressed in animal models and an introduction to stress paradigms used for inducing depression-like symptoms. A few representative examples of successfully established animal models are given, ending with an outlook on future requirements for animal models of depression. MODEL ORGANISMS Invertebrate model organisms such as fruit flies (Drosophila melanogaster) and maritime snails (Aplysia californica) turned out to be of inestimable value for our understanding of molecular mechanisms underlying synaptic plasticity and memory formation (Kandel, 2001; Margulies et al., 2005). However, they have their clear limitations if complex interactions between neuronal circuits, transmitter systems, hormones, and behavior have to be considered. Therefore, animal studies on mood disorders have to be performed in higher vertebrates with close homologies to humans in brain anatomy and physiology. Accordingly, most animal models of depression have been established with rodents and nonhuman primates. Among rodents, the rat (Rattus norvegicus familiaris) has been the preferred species for decades. With the advent of modern mouse genetics, however, a rapidly increasing number of studies employed mice (Mus musculus) (Cryan and Holmes, 2005). Today, there is a huge number of different rat and mouse strains available from commercial breeders. These strains can be roughly assigned to outbred or inbred strains. The former bear high genetic variability, whereas the latter are genetically homogeneous, as they are derived from brother–sister matings for more than 20 generations. Importantly, single strains not only display a characteristic behavioral phenotype under basal conditions, but also differ in their responsiveness to several manipulations, for example, stress or antidepressant treatment. Therefore, it is indispensable to distinguish between the

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27.1 Criteria for an animal model of depression. Animal models cannot keep the balance with the complexity of human psychopathology (here illustrated with the balance used by Alois Alzheimer in Munich). However, different aspects of depression can be addressed in animals, and the validity of an animal model can be judged by a set of criteria, whereby it is not essential that all criteria are met at the same time.

FIGURE

different strains by strictly adhering to international recommendations of nomenclature (Wotjak, 2003). In recent years a number of methods (for details, see Chapter 7 “Functional Genomics and Models of Mental Illness”) have been established by which the mouse genome can be altered in a direct or reverse genetic manner, which opens up a new molecular approach to behavior. Reverse genetics refers to a set of techniques such as transgenesis and gene targeting in which a single cloned gene is used to generate a line of mice with an alteration specifically in that gene (Picciotto and Wickman, 1998). Genetically engineered mice were not originally generated to produce animal models with face validity for depression but rather to delineate the role of a specific gene product in bringing about the behavioral phenotype. DEPRESSION-LIKE SYMPTOMS As mentioned above, no animal model can reflect the complexity of depression, but certain key symptoms might be mimicked, including behavioral despair, anhedonia, sleep disturbances, dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, comorbidity with anxiety, altered brain morphology, and impaired cognitive performance (Fig. 27.1, Table 27.1). The following paragraphs illustrate how some of these symptoms might be addressed in animal experiments.

27.1 Experimental Access to Key Symptoms of Depression TABLE

Symptoms

Experimental Measures in Animal Models

Despair

Increased immobility in forced swim and tail suspension tests “Learned helplessness”

Anhedonia

Decrease in intracranial self-stimulation Decreased sucrose preference Reduced sexual interest

Increased anxiety

Unconditioned and conditioned avoidance Suppression of punished responding Conditioned freezing Ultrasonic vocalization

Impaired cognition Activity changes

Impairments in hippocampus-dependent learning tasks Decreased home cage activity Decreased locomotion in novel environments

Sleep changes

Flattening of circadian rhythm (sleep/ wakefulness) Increased rapid-eye-movement density

Changes in appetite

Hyperphagia / Hypophagia-anorexia Carbohydrate preference

Metabolic syndrome

Increased ratio of visceral and subcutaneous fat Altered glucose metabolism

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Behavioral Despair In rats and mice, behavioral despair is typically assessed by alterations in escape-oriented behavior in aversive situations, such as during exposure to water (Forced Swim Test), capture by the tail (Tail Suspension Test), and exposure to electric foot shocks (shuttle box avoidance). Forced Swim Test (FST) and Tail Suspension Test (TST) Both paradigms measure escape approaches and immobility responses in an unavoidable test situation (for comprehensive reviews, see Cryan and Mombereau, 2004; Cryan, Mombereau, and Vassout, 2005). In temporary versions of the FST (alias Porsolt’s Test; Porsolt et al., 1977), mice or rats are forced to swim in a glass cylinder that is half-filled with water so that the animal cannot touch the bottom with its hind paws. The animal swims around attempting to escape, which is impossible, and eventually assumes an immobile posture called “floating.” Over the course of the exposure and, in particular, in subsequent tests, the time spent immobile increases, indicating that the animals have learned that they cannot escape. This phenomenon was originally termed “behavioral despair,” resembling the situation of “learned helplessness” (see below). More recent interpretations favor the view that immobility may also reflect a successful strategy, which involves memory processes aimed at conserving energy (West, 1990). Behavioral stress coping in the FST is affected by a variety of test modifications and biological parameters (Cryan and Mombereau, 2004; Petit-Demouliere et al., 2005), including single housing versus group housing and water temperature. In particular, the latter parameter gains importance if one considers that the test is typically performed at 21°C (rats) or 25°C (mice) water temperature, which causes a significant drop in core body temperature and brain temperature, which may partially account for the increase in floating time. The TST is conceptually similar to the FST as both tests share a common theoretical basis and behavioral measure (Steru et al., 1985; Cryan, Valentino, and Lucki, 2005). In this test, mice are suspended by the tail to a bar, and as a consequence the animals engage in agitation-or escape-like behaviors, interrupted by periods of immobility. The immobile posture and its duration within a 5- or 6-minute test session are used as the measure of depression-like behavior, that is, behavioral despair or passive coping. Compared with the FST, the TST avoids confounding effects of hypothermia. Of disadvantage is that in particular the broadly used C57BL/6 strains fail to produce valid data in the TST as the animals climb their tail up to the bar (Mayorga and Lucki, 2001). Many studies on effects of antidepressants of all major classes on behavioral performance in FST and TST

reported an increase in escape-oriented behavior, resulting in a reduction of immobility. Specifically, inhibition of serotonin uptake reduces floating by promoting swimming behavior, whereas inhibition of noradrenaline uptake reduces immobility by promoting more vigorous escape attempts (that is, climbing and struggling; Cryan, Mombereau, and Vassout, 2005). One has to stress that in FST and TST drug effects are typically assessed after acute treatment, which is in contrast to the situation in human patients, where prolonged treatment with antidepressants is necessary to ameliorate depressive symptoms. It is conceivable that the acute drug effects relate to increased arousal in the animals due to acutely potentiated serotonergic and noradrenergic transmission. Anhedonia Another key symptom of depression is the inability to experience bliss and pleasure. In animal experiments, this symptom is assessed as a decrease in the value of otherwise rewarding stimuli by measuring voluntary consumption of saccharine or sucrose or by applying intracranial self-stimulation. Saccharine or sucrose consumption is typically assessed in a two-bottle choice test in the home cage, with one bottle containing tap water and the other saccharine or sucrose in concentrations from 1% to 10%. The amount of sweetened solution consumed will be set into relation to water consumption and serves as a measure of hedonic behavior. For intracranial self-stimulation, an electrode is chronically implanted into brain structures belonging to the reward system of the brain (that is, primarily in the mesocorticolimbic dopaminergic system, which originates from the ventral tegmental area and projects to the nucleus accumbens and the prefrontal cortex). Animals can control electrical stimulation of the respective pathway by turning a wheel, nose-poking into a hole, or pressing a lever. A reduction in the respective behavioral parameter serves as a measure of anhedonia. Hypothalamic-Pituitary-Adrenal (HPA) Axis Dysregulation Changes in stress hormones and an aberrant regulation of the HPA axis functioning are often reported for patients with major depression: basal levels of cortisol are elevated and accompanied by a flattened diurnal variation in its secretion, cerebrospinal fluid (CSF) levels of corticotropin-releasing hormone (CRH, alias CRF) are increased, the response of adrenocorticotropic hormone (ACTH) to a challenge with exogenous CRH is blunted, and the negative feedback response to a synthetic glucocorticoid (dexamethasone [DEX]) is less effective (Holsboer, 1995; Plotsky et al., 1998; Holsboer, 2000; de Kloet et al., 2005). Bearing in mind that rats

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and mice are nocturnal animals, the regulation of the HPA axis under basal and stressful conditions is quite similar to the human situation. Importantly, in laboratory animals, molecular changes within the brain and pituitary and adrenal cortex can be determined in addition to measuring stress hormone levels in plasma. Anxiety-Related Behavior Depression is frequently associated with anxiety. Therefore, animal models of depression are typically tested for alterations in anxiety-related behavior as well. In humans as well as in laboratory animals, anxiety is not a unitary phenomenon as it includes innate (trait) anxiety and situation-evoked (state) or experience-related expression of anxiety, which are not separable from each other. Various test paradigms, often termed “animal models of anxiety,” have been developed to assess behavioral parameters indicating anxiety (see Part V, Anxiety Disorders). Altered Brain Morphology Patients who are depressed often show a reduced size and neuronal integrity of hippocampus formation and prefrontal cortex, as assessed by magnetic resonance imaging (MRI) in combination with morphometry and/ or magnetic resonance spectroscopy. These changes have been ascribed to long-lasting elevations of glucocorticoid levels. With the refinement of scanning methods, potentiation of the magnetic field and the adjustment of the setup for the use of small laboratory animals, MRI has only recently been adopted to animal models of depression (Czéh et al., 2001). The advantage of this method would be the possibility to perform longitudinal studies within the same experimental subject. So far, snapshots of morphological changes are obtained by Golgi impregnation of neurons in brain slices, followed by detailed analysis of dendritic profiles (for example, number of dendritic branches, maximal length of the dendrites, and number of dendritic spines). By means of this method, several studies compared the consequences of chronic stress on anxiety-like behavior and neuron morphology. For instance, rats showed a sustained increase in anxiety-like behavior following chronic immobilization stress that coincided with atrophy and debranching in pyramidal neurons in the CA3 region of the hippocampus (a brain structure likely to be involved in cognition and inhibitory control of hormonal stress responses), whereas pyramidal and stellate neurons exhibited enhanced dendritic arborization in the basolateral amygdala (a brain structure implicated in control of negative affects) (Vyas et al., 2002). Hence, it is conceivable that, if similar morphological changes occur in patients who are depressed, atrophy and hypotrophy of neurons in the hippocampus account

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for impairments in cognition, whereas hypertrophy in the amygdala would support the development of mood disturbances. Impaired Neurogenesis Neurogenesis exists in the mature brain of adult rats, mice, nonhuman primates, and even in humans, not only in the subventricular zone but also in the subgranular layer of the dentate gyrus (Lindsey and Tropepe, 2006). Today the molecular cascades underlying proliferation of progenitor cells and their differentiation into neurons start to emerge. However, our knowledge about the biological significance of these processes is still in its infancy. Surprisingly, a considerable number of animal models of depression displayed a reduction in neurogenesis in the dentate gyrus, whereas most of the antidepressants and antidepressive treatments turned out to increase neurogenesis (Duman, 2004). First evidence for a direct relationship between neurogenesis and depression-like symptoms came from a study on experimental inhibition of neurogenesis in mice by X-ray irradiation (Santarelli et al., 2003), which rendered the animals insensitive to anxiolytic effects of long-term antidepressant treatment. However, the exact nature of this relationship is far from being clear and its causality is questioned (Henn and Vollmayr, 2004). Impaired Cognition Severe human depressions are often accompanied by impaired cognitive functioning, primarily in hippocampusor prefrontal cortex–dependent tasks. Accordingly, the behavioral analyses of animal models of depression often include tests of hippocampus-dependent learning, such as spatial learning along distal landmarks in dry mazes (for example, Barnes maze or radial maze) and wet mazes (for example, Morris water maze), passive avoidance tasks, and contextual fear conditioning (Sousa et al., 2006). To decide whether impairments in learning result from changes in synaptic plasticity rather than in performance and stress coping (see below), studies might include analyses of long-term potentiation or long-term depression preferably in the pathway to the CA1 region of the hippocampus. ANIMAL MODELS OF DEPRESSION In an attempt to understand the neurobiological basis of human depression and to predict successful treatment strategies, animal models for depression have been developed, whose depression-like symptoms have been assessed as described before. Existing models include pharmacological models (for example, depression-like

382 TABLE

MOOD DISORDERS

27.2 Animal Models of Depression (Selection)

Strategy

Description

Lesions

Olfactory bulbectomy in rats (and mice)

Social stress

Tree shrews (Tupaia belangeri) exposed to a dominant conspecific undergo social defeat and subsequently develop depression-like symptoms

Selective breeding

Rats and mice have been selectively bred for extremes in depression-like symptoms • Learned helplessness-susceptible rats • Flinders Sensitive Line (FSL) • Wistar–Kyoto rats (WKY) • High anxiety (HAB) rats and mice • H/Rouen mice Several inbred and outbred mouse strains are commercially available that differ in their susceptibility for developing depression-like symptoms and in their responsiveness to antidepressants

Transgenic mice

Gain-of-function and loss-of-function mouse mutants, which, however, do not always fulfill the expectations in terms of depression-like symptoms (for details see text)

symptoms induced by withdrawal from psychostimulants or by monoamine depletion), the olfactory bulbectomy model, developmental models, and genetic models (Table 27.2). The following section exemplarily highlights a few of them. Olfactory Bulbectomized Rats and Mice Olfaction is the primary sensory system of rodents. Volatile odorants and pheromones are acquired and processed by the main and the accessory olfactory system, respectively. Bulbectomy in rats and mice leads to permanent destruction of these systems and, in consequence, to disinhibition of the amygdala, structural changes in hippocampus and prefrontal cortex, alterations in transmitter systems including serotonergic and noradrenergic transmission, and changes in a distinct set of behaviors (Song and Leonard, 2005). The latter includes increased exploratory behavior (likely because of impaired habituation) and impaired cognition. Although face and etiological validity of this model can be questioned, bulbectomized animals responded to the chronic administration of all types of therapeutically active antidepressants. They also responded to compounds not directly related to monoamine systems but with a different mechanism of action and potential antidepressant activity, for example, methyrapone or yohimbine (Song and Leonard, 2005) and might thus be useful for the screening of antidepressant drugs.

Developmental Animal Models of Depression Stressful experiences have been reported to favor the evolution of depression (for review see Anisman and Matheson, 2005). Therefore most animal models of depression include stress paradigms for the induction of depression-like symptoms. In this context, various factors have been identified that influence the stress response of the animals. All in all, a stressor turns out to be particularly suitable for the induction of depressionlike symptoms, if it is (1) long-lasting and/or intense, (2) uncontrollable, (3) unpredictable, and/or (4) uncertain in its occurrence (Anisman and Matheson, 2005). The efficiency of stress exposure depends on the genetic makeup of the individual. Moreover, there seem to be sensitive phases during development (for example, pre- and early postnatally, puberty/adolescence), during which stressors have a particular impact on the individual susceptibility for developing depression-like symptoms in later life. Uncontrollable shock and learned helplessness models The model using uncontrollable shock was introduced by Overmier and Seligman (1967). It is based on the observation that animals exposed to uncontrollable electric shocks developed behavioral deficits that were different from those seen in animals that were able to exert control over the shock. In a prototypic experiment, animals were tested in dyads with one animal being able to control the shock and the other not. To achieve this, the two animals were placed into two different shock chambers, which were connected to the same shock generator. Both chambers were equipped with a wheel, a nose-poke detector, or a lever. However, only the device from one of the chambers was connected with the shock generator. Accordingly, only the animal from that chamber could get operational control over the shock by turning the wheel, nose-poking into the hole, or pressing the lever, which switched off the shock. Importantly, the animal from the other chamber also had benefit from this, however, without the possibility to control the shock by itself. In other words, both animals received the same number of shocks, however, in a controllable or uncontrollable manner. Animals exposed to uncontrollable shock had decreased food and water intake and subsequent weight loss (Weiss, 1968, 1980), were more passive in the FST, and showed alterations in sleep patterns and a weakened response to previously rewarding brain stimulation (Anisman and Matheson, 2005). In addition, animals that had been exposed to uncontrollable shock were strongly impaired in an active avoidance task in a shuttle box compared to animals exposed to controllable stress. In this task, a foot shock is presented in a two-compartment chamber.

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A tone or light signal precedes the foot shock, and the animals can avoid the foot shock if they move to the other compartment during presentation of the tone/light signal (pre-emptive response). Seligman and Beagley (1975) linked the behavioral consequences of uncontrollable shock in rats to the clinical condition of depression, and because patients with depression also have feelings of helplessness, the term “learned helplessness” was coined for this response in animals. Learned helplessness paradigms are limited by the fact that only a small proportion of the animals develop depression-like symptoms and that these symptoms persist for one or two days after induction only (Anisman and Matheson, 2005). Chronic mild stress (CMS) models Mice and rats rapidly habituate to a distinct stressor. To avoid this, complex protocols with exposure to different kinds of stressors have been established. For example, the chronic mild stress (CMS) model is generated by sequential applications of different unpredictable stressful conditions such as mild uncontrollable foot shock, forced swimming in cold water, changes in housing conditions, food and water deprivation, reversal of light/dark periods, and exposure to noise and bright light. After exposure to these stressors for 2 to 3 weeks, animals show a number of behavioral changes that are maintained for days (mice) or even weeks (rats) and that are reminiscent of depression-like symptoms. These changes include not only alterations in psychomotor behavior and sleep architecture, as evidenced by reduced open field activity and altered rapid eye movement sleep (REM sleep), but also a reduced sensitivity to rewards, such as a decrease in sucrose consumption, reduced intracranial self-stimulation, and the inability to associate rewards with a distinctive environment in a place conditioning. The stress protocol and the choice of rat or mouse strain might be very critical as some groups report failure to replicate the findings (for example, Nielsen et al., 2000). One strength of the CMS model is its predictive validity because only long-term treatment with various antidepressants causes a return to initial levels of sucrose intake (for comprehensive review see Willner, 2005). Social and predator stress models Acute or repeated exposures to dominant conspecifics (for example, to resident animals in social defeat paradigms) or to predators (for example, ferret or cat) have long-lasting consequences on vegetative, hormonal, and behavioral parameters in the test animals. For instance, exposure to predator stress in sensitive phases during development “primes” the individual susceptibility of

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rats to subsequent aversive encounters in terms of developing symptoms of posttraumatic depression or posttraumatic stress disorder (Tsoory et al., 2007). Of note, maternal influence (see next paragraph) and social hierarchies among cage mates can be regarded as special cases of social factors determining the individual susceptibility for developing depression-like symptoms. Submissive animals are prone to develop a depression-like phenotype (that is, anhedonia, passive stress coping, and anxiety-like behavior) following chronic stress, whereas dominant animals turn out to be resistant or even to display mania-like phenotypes (Malatynska and Knapp, 2005). Applying a social stress paradigm to male tree shrews (Tupaia belangeri), Fuchs and colleagues collected an array of data showing a number of depression-like symptoms in the subordinate animal, which lives in visual and olfactory contact to a conspecific by which it has been defeated (Fuchs, 2005). The subordinate male showed not only behavioral changes and a reduction in body weight, but also changes in sleeping pattern, increased concentration of stress hormones, and structural changes in the hippocampus. The validity of this model is further supported by the finding that chronic treatment with antidepressants exerts a time-dependent restorative influence on most parameters affected by the stress paradigm including cell proliferation in the hippocampus (Fuchs et al., 1996, 2002; Czéh et al., 2006). The chronic psychosocial conflict in tree shrews may represent a natural and valid paradigm for studying behavioral, endocrine, and neurobiological changes underlying stress-related disorders such as depression in a species phylogenetically close to humans. Early life stressors Adverse experiences during development turned out to provide a fundamental factor for determining susceptibility to psychiatric disorders in adulthood. Many investigators have administered stressors to pregnant rats (prenatal stress) or newborn rats or mice (early postnatal stress) and studied their impact on behavior and hormonal stress coping in the offspring throughout adulthood. In a prototypical experiment employing postnatal stress, the litter will be separated from their mother for a certain amount of time, starting 2 days after birth. Duration and frequency of separations critically determine the success of the experiment (Macrì and Würbel, 2006; Millstein and Holmes, 2007). In fact, separation may just attract the interest of the mothers in their replaced litter, thus leading to intensive active grooming and licking. Such forms of maternal behavior, which can be seen also spontaneously without separation of the dams from their litter, influence the individual susceptibility of the offspring to stressors in later life. It

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could be shown that active nursing (that is, arched-back posture with frequent licking and grooming, Fig. 27.2) results in a “stress resistant” phenotype, whereas passive nursing behavior renders the offspring vulnerable for stress-induced depression-like symptoms (Champagne et al., 2003). These differences in stress susceptibility are accompanied by a variety of changes at the molecular level, including altered expression of neurotransmitter and hormone receptors (Champagne et al., 2003), at least in part due to epigenetic modifications at the level of the deoxyribonucleic acid (DNA) (Weaver et al., 2004). A particular striking example for the role of pre- and postnatal factors is provided by the behavioral phenotype of two inbred mouse strains, C57BL/6J and BALB/c. Whereas C57BL/6J mice are good learners in the water

maze task, BALB/c fail to do so, likely because of altered stress coping. In a cross-fostering experiment, however, BALB/c mice performed equally well as C57BL/6J mice, if reared by C57BL/6J mothers. Hence, the strain differences do not primarily relate to differences in the genetic makeup, but to strain-specific postnatal maternal factors. Interestingly, the good learning capabilities of C57BL/6J mice were unaffected if the animals had been reared by BALB/c mothers (Zaharia et al., 1996). As confirmed in an elegant embryo transfer and crossfostering study (Francis et al., 2003), mice from this strain showed altered behavioral performance only if their development was influenced by BALB/c mothers pre- and postnatally (Fig. 27.2). These data demonstrate how epigenetic (that is, pre- and postnatal) factors during development on the basis of a distinct genetic

27.2 Developmental factors influencing the individual stress susceptibility in mice and rats. (A) Strain differences between two inbred mouse strains in terms of stress susceptibility can be overcome if offspring of mothers from the stress-susceptible strain (BALB/c) are reared by mothers from the stress-resistant strain (C57BL/6J). The same postnatal cross-fostering failed to affect stress resistance of C57BL/6J offspring, if reared by BALB/c mothers (Zaharia et al., 1996). (B) C57BL/6J offspring show increased stress susceptibility only following pre- (embryo transfer) and postnatal cross-fostering (Francis et al., 2003). (C) Maternal care has a strong impact on stress coping, cognition, and anxiety of the offspring of Long–Evans rats (Champagne et al., 2003).

FIGURE

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385

makeup determine the stress susceptibility and most likely also the development of depression-like symptoms in adulthood. Separation models are also used in nonhuman primates, species that due to the evolutionary proximity to humans seem to be particularly suited to providing insights into the biobehavioral underpinnings of depression. Infant monkeys respond to maternal separation with agitation, sleep disturbances, and screaming. After 1–2 days they become “despaired,” a condition characterized in monkeys by a decrease in activity, appetite, and weight; play and social interaction; and the assumption of a hunched posture and “sad” facial expression (McKinney and Bunney, 1969; Hinde et al., 1978). Studies by many laboratories have also suggested that “depressive” responses during “despair” can be predicted by the amount of cortisol released immediately following separation. The link between the HPA system and depression-like behavior has been studied extensively by Kalin et al. (1989), who injected CRH into the central nervous system (CNS) of infant monkeys. The animals developed a phenotype similar to the “behavioral despair” produced by maternal separation. Furthermore, monkeys reared by mothers foraging under unpredictable conditions had a persistently elevated CSF concentration of CRH (Coplan et al., 1996). These findings lend support to the neuroendocrine hypothesis of depression, according to which depression can develop if the balance between stressrelated elevation of CRH and corticosteroid-induced suppression is continously disturbed (Holsboer, 2000). If these animal models are applicable to humans, the conclusion can be drawn that early stressors such as neglect or abuse lead to persistent elevations of CRH, rendering an individual vulnerable to depression or anxiety, or both. The predictive value of “behavioral despair”

in the context of drug treatment is not yet clear, but the few existing studies suggest that antidepressants can reduce at least some of the separation-induced deficits.

27.3 Gene-environment interaction. This cartoon illustrates that true masterpieces of art require outstanding quality of the artist (vulgo: life, environment or nurture) and of the raw material (vulgo:

genetic makeup or nature; here sandstone for the left sculpture and marble for the middle and the right sculpture).

FIGURE

Genetic Animal Models of Depression The previous sections of this chapter described the choice of the experimental models, how distinct symptoms of human depression can be studied in these animals, and how developmental and environmental factors contribute to the manifestation of depression-like symptoms. However, not the isolated entities by themselves, but their integration eventually results in an animal model of depression. In other words, genetic predisposition of the animals, environmental factors, and careful analysis of behavioral, hormonal, and morphological characteristics provide the basis for the study of depressionlike symptoms in animals. The focus of interest dictates whether the animal model is used for studying molecular correlates and etiology of the behavioral alterations or for testing of novel pharmacotherapeutic strategies. Genetic factors have been estimated to account for 40%–70% of the individual risk for developing major depression (Lesch, 2004). However, it is the interaction between genetic predisposition and environmental factors (Fig. 27.3) that results in a fully manifested disorder (Caspi et al., 2003). In recent years a rich methodological portfolio has been established that allows dissecting the genetic basis of behavior in animals (Fig. 27.4). Top-down or forward genetic approaches start with a certain behavioral phenotype. Natural variance in its expression due to strain differences, selective breeding, or spontaneous or randomly induced mutations (for example, by mutagenic compounds such as N-ethyl-Nnitroso-urea; Hotz Vitaterna et al., 2006) enable the characterization of candidate genes. This can be achieved

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FIGURE 27.4 Strategic considerations for studying the genetic basis of behavior. Forward genetics tries to characterize candidate genes for a certain behavioral phenotype by starting with the respective animal model and ending with molecular biology. Reverse genetics, in turn, tries to demonstrate the causal involvement of a certain gene in the behavioral phenotype under study, thus starting with molecular

in a hypothesis-driven as well as in a hypothesis-free manner. In the latter case, methods such as quantitative trait loci analyses (QTL; Peters et al., 2007) or high-throughput approaches (for example, microarray analyses) are employed to identify genes or gene arrays that are associated with extremes in behavioral performance. The ultimate goal is to establish a causality between the candidate genes identified and the behavioral phenotype under study. This bottom-up approach or reverse route of behavioral genetics includes alterations in gene expression (gain-of-function or loss-offunction), which can be achieved by genetic modifications that will be germline transmitted (for example, transgenic or knockout mice) or by somatic recombinations (for example, by viral vectors that will be injected into a certain brain region, where they lead to expression of transgenes, short-interference ribonucleic acids [RNAs], or antisense oligonucleotides), and by subsequent behavioral phenotyping. The following examples illustrate the potential of some of these approaches.

biology and ending with behavioral analyses (modified from Wotjak, 2004). (ENU: N-ethyl-N-nitroso urea; RNAi: RNA interference; RT-PCR: reverse transcriptase polymerase chain reaction; QTL: quantitative trait loci analysis; SNP: single-nucleotide polymorphism; for further details, see text).

Selective breeding for susceptibility to learned helplessness Henn and colleagues (1985) selectively bred rats for susceptibility and resistance to behavioral deficits produced by uncontrollable shock. The “failure to escape” of susceptible rats can be attributed to psychomotor retardation and may thus reflect a depression-like symptom. After repeated testing and subsequent breeding of animals that showed “failure to escape” from uncontrollable shock for four generations, about one half of the animals showed the phenomenon, whereas none of the animals bred for rapid escape showed poor escape performance. The utility of this attractive model for studies of the neurobiological basis of depression can be assessed only if neuropathological and neurochemical characteristics of depression are better specified than is currently the case. Whereas this model has only limited construct validity (that is, it is not homologous to depression), it has considerable predictive validity,

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as both animals subjected to uncontrollable shock and those bred for susceptibility to the behavioral deficit (“failure to escape”) respond to a variety of antidepressants. The Flinders sensitive line (FSL) Another model, based on genetic selection, makes use of two lines of rats that were bred to be either sensitive or resistant to pharmacological manipulation of cholinergic activity (Overstreet et al., 2005). This model was developed at Flinders University in Australia by selective breeding for differences in the effects of the cholinesterase inhibitor diisopropylfluorophosphate on body temperature, fluid intake, and body weight. Flinders sensitive line (FSL) rats are hypersensitive to cholinergic agonists and were proposed as an animal model of depression with good face validity because these rats exhibit (1) reduced locomotor activity, (2) reduced body weight, (3) increased REM sleep (a phenomenon frequently observed in patients who are depressed), and (4) a greater degree of anhedonic behavior after stress (Overstreet, 1993). However, the evidence that cholinergic hypersensitivity is the leading cause of depression is limited, and this hypothesis is further called into question by the therapeutic efficacy of new antidepressants lacking anticholinergic properties. In light of the behavioral phenomena observed following foot shocks and in the FST, it is of note that FSL rats show exaggerated immobility and that this behavior returns to normal after administration of antidepressants, including those without anticholinergic effects, which in turn is of interest in connection with reported changes in serotonergic activity in these animals (Zangen et al., 1997). More recently, this genetic animal model, together with the Wistar Kyoto rat line, has been proposed as putative genetic animal model of childhood depression (Malkesman et al., 2006). Hyperanxious rat model Increased anxiety is one cardinal symptom accompanying depression. According to current diagnostic standards, anxiety disorders and depression are classified as separate disorders; however, at some points they share a common pathophysiology. Animal models of high innate anxiety, gained by selective breeding, are valuable tools as those animals would exhibit pathological anxiety not because of the presentation of a stressor, but because it is an enduring feature of a strain or an individual, probably involving multiple genetic and environmental factors. One animal model meeting this criterion is the rat model of high (HAB) and low (LAB) anxiety-related behavior, developed by Landgraf and colleagues (Liebsch et al., 1998). These two rat lines differ not only in their inborn emotionality, but also in their stress-coping strategies and hormonal stress re-

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sponses (Frank et al., 2006). Rats with high anxietyrelated behavior seem to display deregulations of the HPA axis that are consistent with the neuroendocrine status of depressed patients. Importantly, the exaggerated corticosterone response in the dexamethasone/CRH test observed in these animals (Keck et al., 2002) disappeared following antidepressant treatment (Keck et al., 2003), similar to the situation in patients who were depressed. Using this rat model, the CRH type 1 receptor antagonist R121919—as a representative of a potential new class of antidepressants and which exerted antidepressive effects in human patients (Zobel et al., 2000)—was tested. Only in HAB rats was a significant dose-related reduction of anxiety-like behavior noted, while LAB rats showed no behavioral response (Keck, Welt, Wigger, et al., 2001). The two rat lines also differ in their reactivity to benzodiazepines (Liebsch et al., 1998), repetitive transcranial magnetic stimulation treatment (Keck, Welt, Post, et al., 2001), and chronic paroxetine treatment (Muigg et al., 2007). These results illustrate the predictive validity of this rat model. The consistency and stability of the observed high level of innate anxiety has been partially proven by studies in different laboratories. Recent data indicate that increased expression of vasopressin due to a single-nucleotide polymorphism (SNP) in regulatory structures of the vasopressin gene at least partially accounts for hyperanxiety and depression-like symptoms in these animals (for review see Landgraf et al., 2007). Inbred and outbred mice The high number of commercially available inbred and outbred strains provides an excellent tool for studying genetic differences in development and maintenance of depression-like symptoms. Such strain differences eventually resulted from genetic drift and accumulation of mutations (for example, absence of the gene encoding for α-synuclein specifically in C57BL/6JOlaHsd mice; Specht and Schoepfer, 2001; SNP in the tryptophan hydroxylase 2 gene in BALB/c and DBA/2 mice compared to C57BL/6 strains; Zhang et al., 2004). Strains may considerably differ in their FST and TST behavior, in their responsiveness to antidepressant treatment, and in stress-induced development of depression-like symptoms (for comprehensive review see Anisman and Matheson, 2005; Jacobson and Cryan, 2007). So far, only a few studies have tried to characterize the genetic basis of these differences using QTL analyses (Turri et al., 2001; Yoshikawa et al., 2002). HAB and H/Rouen mice Selective breeding of mice displaying specific behavioral traits is one starting point to develop genetic mouse models for depression. This concept was the basis for

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the development of the mouse version of the HAB rats mentioned above (Kromer et al., 2005). In a similar way the H/Rouen mice had been established (Vaugeois et al., 1997) by selective breeding of CD-1 mice for high and low immobility on the TST. After 10 generations, helpless (H/Rouen) and nonhelpless mice (NH/ Rouen) were clearly distinguishable on the behavioral level. H/Rouen mice showed not only increased immobility in the TST and FST, but also reduced consumption of palatable sucrose solution, higher basal corticosterone levels, changes in the serotonin system, and alterations in sleep-wakefulness patterns that resemble those observed in patients who were depressed. Further characterization of this mouse line (Popa et al., 2006) validates the H/Rouen mice as a mouse model of particular interest for studying neurobiological mechanisms and, possibly, genetic substrates involved in sleep alterations in depression. Mouse mutants A different starting point for the generation of genetic mouse models is to target a specific gene putatively implicated in etiology and expression of depression. Today, there are three main hypotheses on the molecular and biochemical mechanisms underlying depression: the monoamine hypothesis, the HPA axis hypothesis, and the neurotrophin/neurogenesis hypothesis. Further, genetic studies in humans and animals come up with new candidate genes that might be involved in determining the vulnerability to develop depression or in mediating the effects of antidepressant action (e.g., Charney and Manji, 2004; Berton and Nestler, 2006; Ising and Holsboer, 2006; Lucae et al., 2006; Wong et al., 2006). Targeting different components (for example, genes encoding transmitters, receptors, or transporters) of the systems involved in the above-mentioned hypotheses led to the generation of a number of mutant mouse lines, which have been systematically analyzed for alterations in depression-like symptoms (for comprehensive review see Urani et al., 2005). These mouse models do not only serve to validate a working hypothesis but also are of high value in terms of disentangling the role of single genes in highly complex frameworks such as, for example, the regulation of the HPA axis and the modulation of anxiety behavior by the CRH receptors 1 and 2 (Bale and Vale, 2004; Müller and Holsboer, 2006). In terms of representing animal models of depression, however, mutant mouse lines generated so far display clear limitations, and only few of them show depression-like behavior. In line with the neurotrophin/ neurogenesis hypothesis of depression, a reduction of brain-derived neurotrophic factor (BDNF) should convey a depression-like phenotype. However, experiments with heterozygous BDNF knockout (BDNF+/−) mice, which display a 50% reduction of BDNF, failed to reveal

depression-like symptoms (Montkowski and Holsboer, 1997; Chourbaji et al., 2004). Moreover, in some mouse mutants the behavioral phenotype did not always meet the expectations, but rather the opposite was observed: serotonin transporter knockout mice (SERT KO), for instance, were supposed to show reduced anxiety but exhibited a more anxious phenotype (Holmes et al., 2003). To explain this one has to consider the strong influence of the genetic background and also that gene deletion eventually results in compensatory processes. Moreover, human studies imply that variants in many genes confer an individual’s risk for mood disorders, and mutations found result in rather subtle changes in protein expression and function, which become overt under certain conditions only. The ambition to develop new pharmacological treatments for patients who are depressed goes hand in hand with the attempt to learn more about the neurobiological basis of depression. Mouse mutants bearing a deficiency in gene products, which were so far not considered in the context of depression, represent an additional source for potential targets for new antidepressants. For instance, analyses of the behavioral phenotype of Kcnk2-knockout mice, which are deficient for the background potassium channel TREK-1, show a depressionresistant phenotype (Heurteaux et al., 2006). Compared to the wild-type, TREK-1 deficient mice showed reduced immobility in FST and TST, reduced conditioned suppression of motility, no increase in escape latencies after inescapable foot shocks, reduced latency in the novelty-suppressed feeding test, and no behavioral response to chronic treatment with the antidepressant paroxetine. This example illustrates the importance of including tests of depression-like behavior into standard screens for behavioral phenotyping of mouse mutants without apparent link to human depression.

FUTURE REQUIREMENTS Despite the enormous progress in recent years, animal models of depression still bear limitations, which have to be overcome in the future: 1. Most tests of depression-like behavior (for example, FST, TST, anxiety tests) activate memory processes, which preclude their repeated application to one and the same animal. This renders it impossible to follow the progress of chronic antidepressant treatment and to study animal models with repeated depression-like episodes, for instance in the context of development of pharmacotolerance to antidepressants. Therefore, more attention has to be paid to read-outs, which can be repeatedly assessed (for example, by refined measurements of anhedonia).

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2. Chronic antidepressant treatment should be initiated after, but not during, the induction of depressionlike symptoms (for example, during chronic stress), if the therapeutic rather than preventive potential of the antidepressant is under study. 3. Depression-like episodes are often limited to a few days even after severe stress, which is in striking contrast to the situation in human patients. It appears to be necessary that animal models include developmental and genetic factors, for instance, by exposing animals with a certain genetic makeup (inbred strains, selectively bred animals, genetically modified mice) to uncontrollable, unpredictable and severe stressors, if possible during sensitive phases of development. 4. Even groups of inbred (that is, genetically identical) animals show considerable variability in their behavioral responses (Cohen and Zohar, 2004). Tests should be established that allow the identification of vulnerable and resilient individuals before induction of depression-like symptoms. Subsequent focusing on susceptible animals increases the power of pharmacological studies and enables, in comparison to resilient animals, the characterization of pathogenic versus salutogenic processes. 5. Results of behavioral studies need to be corroborated in complementary test paradigms. For instance, reduced consumption of sucrose solution not necessarily indicates anhedonia, because it might result from increased neophobia. Only a sustained reduction in sucrose intake over longer periods of time serves as a valid measure of anhedonia. 6. Animal models of depression too often lack reproducibility in other laboratories. This can be largely ascribed to differences in animal husbandry and in experimental conditions (Crabbe et al., 1999). Consequently, more effort has to be invested in the establishment of standard operating procedures, including the use of defined reference strains.

CONCLUSION Depressive syndromes constitute a heterogeneous combination of symptoms, and these symptoms may vary considerably in type and severity. Thus, development of a “perfect” animal model of depression that meets all criteria is highly unlikely. A more pragmatic approach is to identify those behaviors and changes that frequently occur in the clinical condition and that can be confidently studied in animals. Such behaviors include anxiety, anhedonia, learning and memory retrieval, food consumption, sleep patterns, and the response to neuropsychopharmacological interventions. Models designed to simulate signs and symptoms prevalent in depression may be useful in detecting certain underlying pathologies, for example, aberrant HPA axis regulation as a causative factor for cognitive deficits. Until recently,

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available animal models of depression almost exclusively employed various stressors, and too little attention was paid to genetic and epigenetic factors. Although several neuroendocrine and behavioral phenomena that are characteristic for depression are consistent with the view that depression and inappropriate coping with stress have much in common, it must be noted that stressful life events per se are frequent, but not necessary, precipitators of depressive episodes in individuals that carry the genetic risk. Also, psychopathology following chronic stress does not mimic depression. To overcome the limitations associated with purely stressderived animal models, more attention has to be paid to the increasing knowledge about genetic susceptibility. Future efforts will integrate molecular genetics, developmental factors, and behavioral research in such a way that animal models emerge that have a high overall validity for studies of complex clinical conditions such as mood disorders. REFERENCES Anisman, H., and Matheson, K. (2005) Stress, depression, and anhedonia: caveats concerning animal models. Neurosci. Biobehav. Rev. 29:525–546. Bale, T.L., and Vale, W.W. (2004) CRF and CRF receptors: role in stress responsivity and other behaviors. Annu. Rev. Pharmacol. Toxicol. 44:525–557. Berton, O., and Nestler, E.J. (2006) New approaches to antidepressant drug discovery: beyond monoamines. Nat. Rev. Neurosci. 7:137–151. Caspi, A., Sugden, K., Moffitt, T.E., Taylor, A., Craig, I.W., Harrington, H., McClay, J., Mill, J., Martin, J., Braithwaite, A., and Poulton, R. (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301:386–389. Champagne, F.A., Francis, D.D., Mar, A., and Meaney, M.J. (2003) Variations in maternal care in the rat as a mediating influence for the effects of environment on development. Physiol. Behav. 79: 359–371. Charney, D.S., and Manji, H.K. (2004) Life stress, genes, and depression: multiple pathways lead to increased risk and new opportunities for intervention. Sci. STKE. 2004(225):re5. Chourbaji, S., Hellweg, R., Brandis, D., Zorner, B., Zacher, C., Lang, U.E., Henn, F.A., Hortnagl, H., and Gass, P. (2004) Mice with reduced brain-derived neurotrophic factor expression show decreased choline acetyltransferase activity, but regular brain monoamine levels and unaltered emotional behavior. Brain Res. Mol. Brain Res. 121:28–36. Cohen, H., and Zohar, J. (2004) An animal model of posttraumatic stress disorder: the use of cut-off behavioral criteria. Ann. N. Y. Acad. Sci. 1032:167–178. Coplan, J.D., Andrewa, M.W., Rosenblum, L.A., Owens, M.J., Freidman, S., Gorman, J.M., and Nemeroff, C.B. (1996) Persistent elevations of cerebrospinal fluid concentrations of corticotropinreleasing factor in adult nonhuman primates exposed to earlylife stressors: implications for the pathophysiology of mood and anxiety disorders. Proc. Natl. Acad. Sci. USA 93:1619–1623. Crabbe, J.C., Wahlsten, D., and Dudek, B.C. (1999) Genetics of mouse behavior: interactions with laboratory environment [see comments]. Science 284:1670–1672. Cryan, J.F., and Holmes, A. (2005) The ascent of mouse: advances in modelling human depression and anxiety. Nat. Rev. Drug Discov. 4:775–790.

390

MOOD DISORDERS

Cryan, J.F., and Mombereau, C. (2004) In search of a depressed mouse: utility of models for studying depression-related behavior in genetically modified mice. Mol. Psychiatry 9:326–357. Cryan, J.F., Mombereau, C., and Vassout, A. (2005) The tail suspension test as a model for assessing antidepressant activity: review of pharmacological and genetic studies in mice. Neurosci. Biobehav. Rev. 29:571– 625. Cryan, J.F., Valentino, R.J., and Lucki, I. (2005) Assessing substrates underlying the behavioral effects of antidepressants using the modified rat forced swimming test. Neurosci. Biobehav. Rev. 29:547– 569. Czéh, B., Michaelis, T., Watanabe, T., Frahm, J., de Biurrun, G., van Kampen, M., Bartolomucci, A., and Fuchs, E. (2001) Stressinduced changes in cerebral metabolites, hippocampal volume, and cell proliferation are prevented by antidepressant treatment with tianeptine. Proc. Natl. Acad. Sci. USA 98:12796–12801. Czéh, B., Simon, M., Schmelting, B., Hiemke, C., and Fuchs, E. (2006) Astroglial plasticity in the hippocampus is affected by chronic psychosocial stress and concomitant fluoxetine treatment. Neuropsychopharmacology 31:1616–1626. de Kloet, E.R., Joels, M., and Holsboer, F. (2005) Stress and the brain: from adaptation to disease. Nat. Rev. Neurosci. 6:463– 475. Duman, R.S. (2004) Depression: a case of neuronal life and death? Biol. Psychiatry 56:140–145. Francis, D.D., Szegda, K., Campbell, G., Martin, W.D., and Insel, T.R. (2003) Epigenetic sources of behavioral differences in mice. Nat. Neurosci. 6:445– 446. Frank, E., Salchner, P., Aldag, J.M., Salome, N., Singewald, N., Landgraf, R., and Wigger, A. (2006) Genetic predisposition to anxiety-related behavior determines coping style, neuroendocrine responses, and neuronal activation during social defeat. Behav. Neurosci. 120:60–71. Fuchs, E. (2005) Social stress in tree shrews as an animal model of depression: an example of a behavioral model of a CNS disorder. CNS Spectr. 10:182–190. Fuchs, E., Czeh, B., Michaelis, T., de Biurrun, G., Watanabe, T., and Frahm, J. (2002) Synaptic plasticity and tianeptine: structural regulation. Eur. Psychiatry. 17:311–317. Fuchs, E., Kramer, M., Hermes, B., Netter, P., and Hiemke, C. (1996) Psychosocial stress in tree shrews: clomipramine counteracts behavioral and endocrine changes. Pharmacol. Biochem. Behav. 54: 219–228. Henn, F.A., Johnson, J., Edwards, E., and Anderson, D. (1985) Melancholia in rodents: neurobiology and pharmacology. Psychopharm. Bull. 21:443– 446. Henn, F.A., and Vollmayr, B. (2004) Neurogenesis and depression: etiology or epiphenomenon? Biol. Psychiatry 56:146–150. Heurteaux, C., Lucas, G., Guy, N., El Yacoubi, M., Thummler, S., Peng, X.D., Noble, F., Blondeau, N., Widmann, C., Borsotto, M., Gobbi, G., Vaugeois, J.M., Debonnel, G., and Lazdunski, M. (2006) Deletion of the background potassium channel TREK1 results in a depression-resistant phenotype. Nat. Neurosci. 9:1134 –1141. Hinde, R.A., Leighton-Shapiro, M.E., and McGinnis, L. (1978) Effects of various types of separation experience on rhesus monkeys 5 months later. J. Child Psychol. Psychiatry All. Disc. 19: 199–211. Holmes, A., Murphy, D.L., and Crawley, J.N. (2003) Abnormal behavioral phenotypes of serotonin transporter knockout mice: parallels with human anxiety and depression. Biol. Psychiatry 54: 953–959. Holsboer, F. (1995) Neuroendocrinology of mood disorders. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 957–969. Holsboer, F. (2000) The corticosteroid receptor hypothesis of depression. Neuropsychopharmacology 23:477–501. Hotz Vitaterna, M., Pinto, L.H., and Takahashi, J.S. (2006) Largescale mutagenesis and phenotypic screens for the nervous system and behavior in mice. Trends Neurosci. 29:233–240.

Ising, M., and Holsboer, F. (2006) Genetics of stress response and stress-related disorders. Dialogues Clin. Neurosci. 8:433– 444. Jacobson, L.H., and Cryan, J.F. (2007) Feeling strained? Influence of genetic background on depression-related behavior in mice: a review. Behav. Genet. 37:171–213. Kalin, N.H., Shelton, S.E., and Barksdale, C.M. (1989) Behavioral and physiologic effects of CRH administration to infant primates undergoing maternal separation. Neuropsychopharmacology 2:97–104. Kalueff, A.V., Wheaton, M., and Murphy, D.L. (2007) What’s wrong with my mouse model? Advances and strategies in animal modeling of anxiety and depression. Behav. Brain Res. 179:1–18. Kandel, E.R. (2001) The molecular biology of memory storage: a dialogue between genes and synapses. Science 294:1030–1038. Keck, M.E., Welt, T., Müller, M.B., Uhr, M., Ohl, F., Wigger, A., Toschi, N., Holsboer, F., and Landgraf, R. (2003) Reduction of hypothalamic vasopressinergic hyperdrive contributes to clinically relevant behavioral and neuroendocrine effects of the antidepressant paroxetine in a psychopathological rat model. Neuropsychopharmacology 28:235–243. Keck, M.E., Welt, T., Post, A., Müller, M.B., Toschi, N., Wigger, A., Landgraf, R., Holsboer, F., and Engelmann, M. (2001) Neuroendocrine and behavioral effects of repetitive transcranial magnetic stimulation in a psychopathological animal model are suggestive of antidepressant-like effects. Neuropsychopharmacology 24: 337–349. Keck, M.E., Welt, T., Wigger, A., Renner, U., Engelmann, M., Holsboer, F., and Landgraf, R. (2001) The anxiolytic effect of the CRH1 receptor antagonist R121919 depends on innate emotionality in rats. Eur. J. Neurosci. 13:373–380. Keck, M.E., Wigger, A., Welt, T., Muller, M.B., Gesing, A., Reul, J.M., Holsboer, F., Landgraf, R., and Neumann, I.D. (2002) Vasopressin mediates the response of the combined dexamethasone/ CRH test in hyper-anxious rats: implications for pathogenesis of affective disorders. Neuropsychopharmacology 26:94 –105. Kromer, S.A., Kessler, M.S., Milfay, D., Birg, I.N., Bunck, M., Czibere, L., Panhuysen, M., Putz, B., Deussing, J.M., Holsboer, F., Landgraf, R., and Turck, C.W. (2005) Identification of glyoxalase-I as a protein marker in a mouse model of extremes in trait anxiety. J. Neurosci. 25:4375– 4384. Landgraf, R., Kessler, M.S., Bunck, M., Murgatroyd, C., Spengler, D., Zimbelmann, M., Nussbaumer, M., Czibere, L., Turck, C.W., Singewald, N., Rujescu, D., and Frank, E. (2007) Candidate genes of anxiety-related behavior in HAB/LAB rats and mice: focus on vasopressin and glyoxalase-I. Neurosci. Biobehav. Rev. 31:89–102. Lesch, K.P. (2004) Gene-environment interaction and the genetics of depression. J. Psychiatry Neurosci. 29:174 –184. Liebsch, G., Linthorst, A.C.E., Neumann, I.D., Reul, J.M.H.M., Holsboer, F., and Landgraf, R. (1998) Behavioral, physiological, and neuroendocrine stress responses and differential sensitivity to diazepam in two Wistar rat lines selectively bred for high and low anxiety-related behavior. Neuropsychopharmacology 19:381–396. Lindsey, B.W., and Tropepe, V. (2006) A comparative framework for understanding the biological principles of adult neurogenesis. Prog. Neurobiol. 80:281–307. Lucae, S., Salyakina, D., Barden, N., Harvey, M., Gagne, B., Labbe, M., Binder, E.B., Uhr, M., Paez-Pereda, M., Sillaber, I., Ising, M., Bruckl, T., Lieb, R., Holsboer, F., and Muller-Myhsok, B. (2006) P2RX7, a gene coding for a purinergic ligand-gated ion channel, is associated with major depressive disorder. Hum. Mol. Genet. 15:2438–2445. Macri, S., and Wurbel, H. (2006) Developmental plasticity of HPA and fear responses in rats: a critical review of the maternal mediation hypothesis. Horm. Behav. 50:667– 680. Malatynska, E., and Knapp, R.J. (2005) Dominant-submissive behavior as models of mania and depression. Neurosci. Biobehav. Rev. 29:715–737. Malkesman, O., Braw, Y., Maayan, R., Weizman, A., Overstreet, D.H., Shabat-Simon, M., Kesner, Y., Touati-Werner, D., Yadid, G.,

27: ANIMAL MODELS and Weller, A. (2006) Two different putative genetic animal models of childhood depression. Biol. Psychiatry. 59:17–23. Margulies, C., Tully, T., and Dubnau, J. (2005) Deconstructing memory in Drosophila. Curr. Biol. 15:R700–R713. Mayorga, A.J., and Lucki, I. (2001) Limitations on the use of the C57BL/6 mouse in the tail suspension test. Psychopharmacology 155:110–112. McKinney, W.T., Jr., and Bunney, W.E., Jr. (1969) Animal model of depression: I. Review of evidence: implications for research. Arch. Gen. Psychiatry 21:240–248. Millstein, R.A., and Holmes, A. (2007) Effects of repeated maternal separation on anxiety- and depression-related phenotypes in different mouse strains. Neurosci. Biobehav. Rev. 31:3–17. Montkowski, A., and Holsboer, F. (1997) Intact spatial learning and memory in transgenic mice with reduced BDNF. Neuroreport 8: 779–782. Muigg, P., Hoelzl, U., Palfrader, K., Neumann, I., Wigger, A., Landgraf, R., and Singewald, N. (2007) Altered brain activation pattern associated with drug-induced attenuation of enhanced depressionlike behavior in rats bred for high anxiety. Biol. Psychiatry 61: 782–796. Müller, M.B., and Holsboer, F. (2006) Mice with mutations in the HPA-system as models for symptoms of depression. Biol. Psychiatry 59:1104 –1115. Nielsen, C.K., Arnt, J., and Sanchez, C. (2000) Intracranial selfstimulation and sucrose intake differ as hedonic measures following chronic mild stress: interstrain and interindividual differences. Behav. Brain Res. 107:21–33. Overmier, J.B., and Seligman, M.E.P. (1967) Effects of inescapable shock upon subsequent escape and avoidance learning. J. Comp. Physiol. Psychol. 63:28–33. Overstreet, D.H. (1993) The Flinders Sensitive Line rats: a genetic animal model of depression. Neurosci. Biobehav. Rev. 17:51–68. Overstreet, D.H., Friedman, E., Mathe, A.A., and Yadid, G. (2005) The Flinders Sensitive Line rat: a selectively bred putative animal model of depression. Neurosci. Biobehav. Rev. 29:739–759. Peters, L.L., Robledo, R.F., Bult, C.J., Churchill, G.A., Paigen, B.J., and Svenson, K.L. (2007) The mouse as a model for human biology: a resource guide for complex trait analysis. Nat. Rev. Genet. 8:58–69. Petit-Demouliere, B., Chenu, F., and Bourin, M. (2005) Forced swimming test in mice: a review of antidepressant activity. Psychopharmacology 177:245–255. Picciotto, M.R., and Wickman, K. (1998) Using knockout and transgenic mice to study neurophysiology and behavior. Physiol. Rev. 78:1131–1163. Plotsky, P.M., Owens, M.J., and Nemeroff, C.B. (1998) Psychoneuroendocrinology of depression. Hypothalamic-pituitary-adrenal axis. Psychiatr. Clin. North Am. 21:293–307. Popa, D., El Yacoubi, M., Vaugeois, J.M., Hamon, M., and Adrien, J. (2006) Homeostatic regulation of sleep in a genetic model of depression in the mouse: effects of muscarinic and 5-HT1A receptor activation. Neuropsychopharmacology 31:1637–1646. Porsolt, R.D., Bertin, A., and Jalfre, M. (1977) Behavioral despair in mice: a primary screening test for antidepressants. Arch. Int. Pharmacodyn. Ther. 229:327–336. Santarelli, L., Saxe, M., Gross, C., Surget, A., Battaglia, F., Dulawa, S., Weisstaubs, N., Lee, J., Duman, R., Arancio, O., Belzung, C., and Hen, R. (2003) Requirement of hippocampal neurogenesis for the behavioral effects of antidepressants. Science 301:805–809. Seligman, M.E.P., and Beagley, G. (1975) Learned helplessness in the rat. J. Comp. Physiol. Psychol. 88:534–541. Song, C., and Leonard, B.E. (2005) The olfactory bulbectomised rat as a model of depression. Neurosci. Biobehav. Rev. 29:627– 647. Sousa, N., Almeida, O.F., and Wotjak, C.T. (2006) A hitchhiker’s guide to behavioral analysis in laboratory rodents. Genes Brain Behav. 5(Suppl 2):5–24.

391

Specht, C.G. and Schoepfer, R. (2001) Deletion of the alpha-synuclein locus in a subpopulation of C57BL/6J inbred mice. BMC. Neurosci. 2:11. Steru, L., Chermat, R., Thierry, B., and Simon, P. (1985) The tail suspension test: a new method for screening antidepressants in mice. Psychopharmacology 85:367–370. Tsoory, M., Cohen, H., and Richter-Levin, G. (2007) Juvenile stress induces a predisposition to either anxiety or depressive-like symptoms following stress in adulthood. Eur. Neuropsychopharmacol. 17:245–256. Turri, M.G., Datta, S.R., DeFries, J., Henderson, N.D., and Flint, J. (2001) QTL analysis identifies multiple behavioral dimensions in ethological tests of anxiety in laboratory mice. Curr. Biol. 11: 725–734. Urani, A., Chourbaji, S., and Gass, P. (2005) Mutant mouse models of depression: candidate genes and current mouse lines. Neurosci. Biobehav. Rev. 29:805–828. Vaugeois, J.M., Passera, G., Zuccaro, F., and Costentin, J. (1997) Individual differences in response to imipramine in the mouse tail suspension test. Psychopharmacology 134:387–391. Vyas, A., Mitra, R., Shankaranarayana Rao, B.S., and Chattarji, S. (2002) Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons. J. Neurosci. 22:6810–6818. Weaver, I.C., Cervoni, N., Champagne, F.A., D’Alessio, A.C., Sharma, S., Seckl, J.R., Dymov, S., Szyf, M., and Meaney, M.J. (2004) Epigenetic programming by maternal behavior. Nat. Neurosci. 7:847– 854. Weiss, J.M. (1968) Effects of coping responses on stress. J. Comp. Physiol. Psychiol. 65:251–260. Weiss, J.M. (1980) Coping behavior: explaining behavioral depression following uncontrollable stressful events. Behav. Res. Ther. 18:485–504. West, P.A. (1990) Neurobehavioral studies of forced swimming. The role of learning and memory in the forced swim test. Progr. Neuropsychopharmacol. Biol. Psychiatry 14:863–875. Willner, P. (2005) Chronic mild stress (CMS) revisited: consistency and behavioural-neurobiological concordance in the effects of CMS. Neuropsychobiology 52:90–110. Wong, M.L., Whelan, F., Deloukas, P., Whittaker, P., Delgado, M., Cantor, R.M., McCann, S.M., and Licinio J. (2006) Phosphodiesterase genes are associated with susceptibility to major depression and antidepressant treatment response. Proc. Natl. Acad. Sci. USA 103:15124–15129. Wotjak, C.T. (2003) C57BLack/BOX? The importance of exact mouse strain nomenclature. Trends Genet. 19:183–184. Wotjak, C.T. (2004) Of mice and men: potentials and caveats of behavioural experiments with mice. B.I.F. FUTURA 19:158–169. Yoshikawa, T., Watanabe, A., Ishitsuka, Y., Nakaya, A., and Nakatani, N. (2002) Identification of multiple genetic loci linked to the propensity for “behavioral despair” in mice. Genome Res. 12: 357– 366. Zaharia, M.D., Kulczycki, J., Shanks, N., Meaney, M.J., and Anisman, H. (1996) The effects of early postnatal stimulation on Morris water-maze acquisition in adult mice: genetic and maternal factors. Psychopharmacology 128:227–239. Zangen, A., Overstreet, D.H., and Yadid, G. (1997) High serotonin and 5-hydroxyindoleacetic acid levels in limbic brain regions in a rat model of depression: normalization by chronic antidepressant treatment. J. Neurochem. 69:2477–2483. Zhang, X., Beaulieu, J.M., Sotnikova, T.D., Gainetdinov, R.R., and Caron, M.G. (2004) Tryptophan hydroxylase-2 controls brain serotonin synthesis. Science 305:217. Zobel, A.W., Nickel, T., Kunzel, H.E., Ackl, N., Sonntag, A., Ising, M., and Holsboer, F. (2000) Effects of the high-affinity corticotropinreleasing hormone receptor 1 antagonist R121919 in major depression: the first 20 patients treated. J. Psychiatr. Res. 34:171–181.

28 Cellular Plasticity Cascades: Genes to Behavior Pathways in the Pathophysiology and Treatment of Bipolar Disorder LISA A. CATAPANO, GUANG CHEN, JING DU, CARLOS A. ZARATE, JR.,

Bipolar disorder (BPD) is a complex illness, involving the dysregulation of mood, sleep, cognition, endocrine, and motor systems. A true understanding of the pathophysiology of this disorder must encompass these different systems, and the different physiologic levels at which the disease manifests: molecular, cellular, systems, and behavioral (Fig. 28.1). Building upon decades of research that has identified abnormalities in neurotransmitter systems in this disorder, there is a growing appreciation that signal transduction pathways play a pivotal role in mediating the dysfunction of multiple neurotransmitter systems and physiologic processes in bipolar illness. Complex signaling networks are undoubtedly involved in regulating such diverse functions as n)

rs tio to riva c a p lF e ta ep d es n n e m sle Ge on rs, ing ting r i v so fy in En res odi mpr t M I s ., .g e (

Cellular

Molecular Susceptibility genes Protective Genes

392

* Synaptic connectivity * Neuroplasticity * Cytoskeletal remodeling * Cell growth/ survival

* PKC & MARCKS * GSK-3␤ & substrates * CREB & BDNF * ERK MAP kinases * G proteins * G protein-coupled receptor kinases * Bcl-2 family * Neuronal cytoskeleton

* Transcription Factors * mRNA stability * Nuclear Import/Export

HUSSEINI K. MANJI

mood, appetite, and wakefulness and are therefore thought to be involved in the pathophysiology of mood and vegetative symptoms. Furthermore, there is clear evidence that signaling pathways are targets of the most effective pharmacologic treatments for BPD. Neurobiological studies of mood disorders over the last 40 years have focused primarily on abnormalities of the monoaminergic neurotransmitter systems, characterizing alterations of individual neurotransmitters in disease states, and in response to mood stabilizer and antidepressant medications. The monoaminergic systems are extensively distributed throughout the network of limbic, striatal, and prefrontal cortical neuronal circuits thought to support the behavioral and visceral

Cognitive Affective Sensorimotor

Behavior

Systems

A N D

Critical Neuronal Circuitry

Proteome

Transcriptome

FIGURE 28.1 The pathophysiology of bipolar disorder. A complete understanding of the pathophysiology of bipolar disorder must address its neurobiology at different physiological levels: molecular, cellular, systems, and behavioral. PKC: protein kinase C; MARCKS: myristoylated alanine-rich C kinase substrate; GSK-3: glycogen synthase kinase-3; CREB: cyclic AMP response binding protein; BDNF: brain-derived neurotrophic factor; ERK MAP kinase: extracellular response kinase/mitogen-activated protein kinase; Bcl-2: B-cell leukemia/lymphoma; transcriptome refers to the population of cellular mRNA species and their expression level; proteome refers to the population of cellular protein species and their expression level. Modified and reproduced with (pending) permission from Manji and Lenox (2000a).

28: GENES TO BEHAVIOR PATHWAYS OF BIPOLAR DISORDER

manifestations of mood disorders (Drevets, 2000). Assessments of cerebrospinal fluid (CSF) chemistry, neuroendocrine responses to pharmacological challenge, and neuroreceptor and transporter binding have demonstrated a number of abnormalities in monoaminergic neurotransTABLE

393

mitter and neuropeptide systems in mood disorders (Table 28.1) (Goodwin and Jamison, 2007). Unfortunately, these observations have not yet greatly advanced our understanding of the underlying biology of recurrent mood disorders, which must include an

28.1 Summary of Major Findings Implicating Multiple Systems in Bipolar Disorder

Serotonergic system

Glutamatergic system

• Reduced CSF 5-HIAA • Blunted neuroendocrine and temperature responses to 5-HT agonists

• Key role of glutamate signaling in stress-induced atrophy • Alterations of CSF, plasma, and platelet glutamate/glutamine levels • Altered regional glutamate metabolism by positron emission tomography • Facilitated glutamate reuptake, and protection against excitotoxicity, by lithium • Regulation of hippocampal glutamate uptake capacity by valproate • Attentuation of excess glutamate release by the mood stabilizer lamotrigine • Downregulation of AMPA GluR1 synaptic expression by lithium and valproate • Upregulation of AMPA GluR1 synaptic expression by antidepressants • Regulation of NMDA receptor mRNA and binding by antidepressants • Antidepressant effects of NMDA antagonists, including ketamine • Attenuation of manic-like behavior in animals by AMPA antagonists

• Reduced 5-HT1A receptor binding in living brain and postmortem brain tissue • Antidepressant efficacy of agents that increase intrasynaptic 5-HT • Triggering of manic episodes by agents that increase intrasynaptic 5-HT • Depressogenic effects of tryptophan depletion in patients treated with antidepressants • Decrease 5-HT1A and 5-HT2 density and 5-HT turnover by antidepressants Noradrenergic system • Reduced CSF and urinary MHPG • Elevated plasma NE • Correlation between CSF NE levels and dysphoric symptoms and severity of illness • Blunted neuroendocrine responses to clonidine • Triggering of mania by agents that increase NE release or block reuptake • Altered α 2 -AR and β-AR density and responsivity in peripheral circulating cells • Altered densities of α 2 -AR and β-AR in areas of postmortem brain • Antidepressant efficacy of agents that increase NE • Reduction in NE turnover by most antidepressants • Reduction β -AR density and/or function in limbic areas in response to antidepressants Dopaminergic system • Reduced CSF HVA • Blunted neuroendocrine and temperature responses to DA agonists • Antidepressant efficacy of agents whose biochemical effects include increasing DA • Enhanced DA function by ECT • Depressogenic effects of AMPT and reserpine in susceptible individuals • Antimanic efficacy of antipsychotic medications (D2 receptor blockers) • Reduced internal jugular venoarterial DA metabolite concentration gradients • Increased risk of depression in Parkinson’s disease • Prominent anhedonia and amotivation given role of DA in reward and motivation circuits Cholinergic system • Depressogenic and antimanic effects of cholinomimetics • Enhanced cholinergic sensitivity • Role in sleep EEG abnormalities

GABAergic system • Altered CSF and plasma GABA in depressed and manic subjects • Reduced occipital cortex GABA in unipolar (but not bipolar) depressed individuals • Region-specific decrease in reelin (secreted by GABAergic interneurons) • Region-specific decrease in GABA synthetic enzymes GAD65 and GAD67 • Decreased GABA turnover in frontal cortex in response to mood stabilizers • Increased GABA(B) receptors in hippocampus in response to mood stabilizers • Genetic association of genes for GABA receptor α3 and α5 subunits with BPD CRF and HPA axis • Hypercortisolemia and resistance to feedback inhibition • Adrenal and pituitary hypertrophy • Increased CSF CRF, and reduced CRF receptors, in postmortem brain • Depressogenic/anxiogenic effects of CRF agonists in preclinical models • Hypercortisolemia normalized by successful antidepressant treatment Peptides • Anxiolytic/antidepressant properties of substance P receptor (NK-1) antagonists • Reduced CSF NPY in depression, and increased NPY with lithium, antidepressants, and ECT • Reduced somatostatin in CSF of patients with depression • Abnormalities of vasopressin expression and receptor activity in depression

CSF: cerebrospinal fluid; 5-HIAA: 5-Hydroxyindoleacetic acid; MHPG: methoxy-hydroxy-phenyl-glycol; NE: norepinephrine; AR: adrenergic receptor; HVA: homovanillic acid; DA: dopamine; AMPT: alpha-methyl-p-tyrosine; EEG: electroencephalography; NMDA: N-methyl-D-aspartate; CRF: cortisol releasing factor; HPA: hypothalamic-pituitary axis; ECT: electroconvulsive therapy; NPY: Neuropeptide Y; AMPA: a-amino-3-hydroxy-5-methyl-4-isoxasdepropionic acid; mRNA: messenger ribonucleic acid; GABA: g -aminobutyric acid; BPD: bipolar disorder.

394

MOOD DISORDERS

explanation for the predilection to episodic and often profound mood disturbance that can become progressive over time. Bipolar disorder likely arises from the complex interaction of multiple susceptibility (and protective) genes and environmental factors, and the phenotypic expression of the disease includes not only mood disturbance, but also a constellation of cognitive, motoric, autonomic, endocrine, and sleep/wake abnormalities. Furthermore, though most antidepressants exert their initial effects by increasing intrasynaptic levels of serotonin and/or norepinephrine, their clinical antidepressant effects are observed only after chronic administration (over days to weeks), suggesting that a cascade of downstream events is ultimately responsible for their therapeutic effects. These observations have led to the idea that though dysfunction within the monoaminergic neurotransmitter systems is likely to play an important role in mediating some facets of the pathophysiology of BPD, it likely represents the downstream effects of other, more primary abnormalities in signaling pathways (Table 28.2) (Manji and Lenox, 2000a). It is our hypothesis that BPD arises from abnormalities in cellular plasticity cascades, leading to aberrant information processing in synapses and circuits mediating affective, cognitive, motoric, and neurovegetative functions. Thus, these illnesses can be best conceptualized as genetically influenced disorders of synapses and circuits—rather than simply as deficits or excesses in individual neurotransmitters. Furthermore, many of these pathways play critical roles not only in synaptic (and therefore behavioral) plasticity, but also in long-term atrophic processes. Targeting these cascades in treatment may stabilize the underlying disease process by reducing the frequency and severity of the profound mood cycling that contributes to morbidity and mortality. In this chapter, we focus upon the role of signaling cascades in the pathophysiology and treatment of BPD. The role of neurotransmitter and neuropeptide systems has been extensively covered elsewhere in recent publications (Goodwin and Jamison, 2007; Soares and Young, 2007) and is not covered here.

28.2 Putative Roles for Signaling Pathways in Mood Disorders

TABLE

• Amplify, attenuate, and integrate multiple signals that form the basis for intracellular circuits and cellular modules • Regulate multiple neurotransmitter and peptide systems • Play critical role in cellular memory and long-term neuroplasticity • Regulate complex signaling networks that form the basis for higher-order brain function, mood, and cognition • Act as major targets for many hormones implicated in mood disorders, including gonadal steroids, thyroid hormones, and glucocorticoids • Act as targets for medications that are most effective in the treatment of mood disorders

SIGNALING NETWORKS: THE CELLULAR MACHINERY UNDERLYING INFORMATION PROCESSING AND LONG-TERM NEUROPLASTIC EVENTS It is hardly surprising that abnormalities in multiple neurotransmitter systems and physiological processes have been found in a disorder as complex as BPD. Signal transduction pathways are in a pivotal position in the central nervous system (CNS), affecting the functional balance between multiple neurotransmitter systems, and therefore playing a role in mediating the more downstream abnormalities that likely underlie the pathophysiology of affective disorders (Fig. 28.2). Moreover, as we discuss below, recent research has clearly identified signaling pathways as therapeutically relevant targets for our most effective pharmacological treatments. Multicomponent cellular signaling pathways interact at various levels, forming complex signaling networks that allow the cell to receive, process, and respond to information (Bhalla and Iyengar, 1999). Given their widespread and crucial role in the integration, regulation, amplification, and fine-tuning of physiological processes, it is not surprising that abnormalities in signaling pathways have now been identified in a variety of human diseases (Spiegel, 1998). Importantly, these diseases manifest relatively circumscribed symptomatology, despite widespread expression of the affected signaling proteins. Although complex signaling networks are likely present in all eukaryotic cells and control various metabolic, humoral, and developmental functions, they may be especially important in the CNS, where they serve the critical roles of first amplifying and “weighting”

The Role of Synaptic & Cellular Plasticity Cascades in the Neurobiology of Bipolar Disorder Serotonin Norepinephrine Dopamine Neuropeptides GABA

?? Responsible for “Comorbidities”

Synaptic & Cellular Plasticity Cascades Cell Loss & Atrophy Impairments of Cellular Resilience

Targets for the Most Effective Treatments

AMPA/NMDAmediated Synaptic Plasticity in Critical Circuits

Cell Growth and Cell Survival Pathways to Mediate Affective Resilience

28.2 Signal transduction pathways provide good explanatory power for understanding the complex neurobiology of bipolar disorder. GABA: g-aminobutyric acid; AMPA: AMPA-type glutamate receptor; NMDA: NMDA-type glutamate receptor.

FIGURE

28: GENES TO BEHAVIOR PATHWAYS OF BIPOLAR DISORDER

numerous extracellularly generated signals, and then transmitting these integrated signals to effectors, thereby forming the basis for complex information processing. The high degree of complexity generated by these signaling networks may be one mechanism by which neurons acquire the flexibility for generating the wide range of responses observed in the nervous system. Recent studies provide evidence that impairments of signaling pathways play a role in the pathophysiology of BPD, and that mood stabilizers exert major effects on the signaling pathways that regulate neuroplasticity and cell survival. These data are reshaping views about the neurobiological underpinnings of BPD and generating exciting possibilities for the development of novel therapeutics. ABNORMALITIES OF PLASTICITY AT THE SYNAPTIC AND/OR CELLULAR LEVEL IN MOOD DISORDERS Evidence for Abnormalities of Synaptic/Cellular Plasticity in the Pathophysiology of Mood Disorders

395

28.3 Postmortem Morphometric Brain Studies in Mood Disorders Demonstrating Cellular Atrophy and/or Loss TABLE

Reduced volume Cortical thickness of rostral orbitofrontal cortex in MDD Laminar cortical thickness in layers III, V, and VI in subgenual anterior cingulate cortex in BPD Volume of subgenual prefrontal cortex in MDD and BPD Volumes of nucleus accumbens and basal ganglia in MDD and BPD Parahippocampal cortex size in suicide Reduced neuronal size and/or density Neuronal size in layer V and VI in prefrontal cortex in MDD and BPD Pyramidal neuronal density, layers III and V in dorsolateral prefrontal cortex in BPD and MDD Neuronal density and size in layers II–VI in orbitofrontal cortex in MDD Neuronal density in layers III, V, and VI in subgenual anterior cingulate cortex in BPD Neuronal size in layer VI in anterior cingulate cortex in MDD Layer-specific interneurons in anterior cingulate cortex in BPD and MDD Nonpyramidal neuronal density in layer II in anterior cingulate cortex in BPD Nonpyramidal neuronal density in the CA2 region in BPD

Atrophic changes in recurrent mood disorders

Reduced glia

Bipolar disorder is increasingly recognized as involving dysregulation of intracellular signaling cascades that produce not only functional but also morphological impairments. Several morphometric imaging and postmortem investigations have demonstrated abnormalities of brain structure that persist independent of mood state and may contribute to corresponding abnormalities in metabolic activity (Table 28.3) (Manji et al., 2001). Structural imaging studies have demonstrated reduced gray matter volumes in areas of the orbital and medial prefrontal cortex, ventral striatum, and hippocampus in patients with mood disorders (Drevets, 2001; Beyer and Krishnan, 2002; Strakowski et al., 2002). Also consistent is the presence of white matter hyperintensities in the brains of elderly depressed patients and patients with BPD, which may be associated with poor treatment response (Goodwin and Jamison, 2007). Complementary to this neuroimaging evidence, postmortem brain studies have demonstrated reductions in regional CNS volume, cell number, and cell body size. Baumann et al. (1999) reported reduced volumes of the left nucleus accumbens, right putamen, and bilateral pallidum externum in postmortem brain samples from patients with major depressive disorder (MDD) or BPD. A number of morphometric analyses have revealed abnormal size and density of pyramidal and nonpyramidal neurons in dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex, anterior cingulate cortex, and hippocampus in patients with mood disorders, although not all studies have observed these findings (Goodwin and Jamison, 2007). Detailed studies from the Rajkowska laboratory have measured the density and size of

Density/size of glia in dorsolateral prefrontal cortex and caudal orbitofrontal cortex in MDD and BPD Glial cell density in layer V in prefrontal cortex in MDD Glial number in subgenual prefrontal cortex in familial MDD and BPD Glial cell density in layer VI in anterior cingulate cortex in MDD Glial cell counts, glial density, and glia:neuron ratio in amygdala in MDD MDD: major depressive disorder; BPD: bipolar disorder.

calbindin-immunoreactive neurons (presumed to be γ -aminobutyric acid [GABA]-ergic) in layers II and III of the DLPFC, revealing a 43% reduction in the density of these neurons in MDD compared with controls (Rajkowska, 2002). Of particular note, in the rostral orbitofrontal cortex, there was a trend toward a negative correlation between the duration of depression and the size of neuronal cell bodies, suggesting changes associated with disease progression (Rajkowska et al., 1999). In general, findings of decreased neuronal size have been more subtle in patients with BPD than in those with MDD. This difference may represent the longterm protective effects of mood stabilizers, as discussed below. In addition to neuronal pathology, unexpected reductions in glial cell number and density have been found in postmortem brains of patients with MDD and BPD. In fact, observed glial changes have often been more dramatic than those of neurons. Layer-specific reductions in glial densities have been reported in prefrontal cortex in BPD and MDD (Öngür et al., 1998;

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MOOD DISORDERS

Rajkowska et al., 1999; Miguel-Hidalgo et al., 2000). Although the most prominent findings thus far have been from the frontal cortex, studies have also provided evidence for glial pathology in the hippocampus (Stockmeier et al., 2004), consistent with decreases in hippocampal volume noted by neuroimaging studies. Studies implicate astrocytic (Johnston-Wilson et al., 2000) and oligodendrocytic (Uranova et al., 2001; Tkachev et al., 2003; Aston et al., 2005) glial subtypes. These data are particularly intriguing in view of the growing appreciation of glia’s roles in regulating synaptic glutamate concentrations and releasing trophic factors that participate in the development and maintenance of synaptic networks. Increasing recent evidence supports the association between impaired neurogenesis and depression (Vollmayr et al., 2007). Several studies support the hypothesis that stress, which plays a major role in depression, reduces neurogenesis in the dentate gyrus, consistent with findings of reduced hippocampal volume in patients who are depressed. Studies suggest that altered neurogenesis is not necessary for depression-like states in animals (Vollmayr et al., 2007) but is nevertheless reversed by mood stabilizers and antidepressants, as discussed below. The precise nature of the relationship between neurogenesis and mood is still to be determined. It must be acknowledged that it is not currently known if these impairments of structural plasticity (cell loss, cell atrophy, white matter changes) constitute developmental abnormalities conferring vulnerability to severe mood episodes, compensatory changes to other pathogenic processes, or the sequelae of recurrent affective episodes (Carlson et al., 2006). Indeed, data suggest that multiple factors may be operative. In support of a potential etiologic role of cellular plasticity cascades, some studies have observed reduced gray matter volumes and white matter hyperintensities in patients with mood disorders at first onset, and in children (Frazier et al., 2005). Reduced levels of N-acetylaspartate (NAA), generally regarded as a measure of neuronal viability and function (Tsai and Coyle, 1995), have also been found to be significantly reduced in the DLPFC of children with BPD (Sassi et al., 2005). Although these studies do not demonstrate that the changes precede illness onset, they are inconsistent with the theory that the changes represent the toxic sequelae of decades of illness. Consistent with these findings, a meta-analysis of imaging studies concluded that volumetric abnormalities in the subgenual prefrontal cortex, striatum, hippocampus, and amygdala are seen in first-episode patients with BPD, children with BPD, and unaffected siblings, raising the possibility that this endophenotype may constitute a heritable vulnerability factor in these patients (Hajek et al., 2005). There are, however, also data to suggest that some brain changes may be associated with duration of ill-

ness and are the consequences of affective episodes per se. Sheline and colleagues measured hippocampal volumes of patients with a history of major depressive episodes and found that the degree of hippocampal volume reduction correlated with total duration of depression, and with duration of untreated depressive episodes (Sheline et al., 1996; Sheline et al., 2003). Another study found hippocampal volume reduction in patients with multiple depressive episodes, but not in first-episode patients (MacQueen et al., 2003). It is noteworthy that similar changes have not been reported in patients with BPD. This difference may reflect distinct pathophysiologies, or the neuroprotective effects of mood stabilizers (see below). Overall, it seems likely that cell loss and atrophy represent both etiologic factors and the consequence of disease progression. There is almost no doubt that these atrophic brain changes contribute to illness pathophysiology by disrupting the circuits that mediate normal affective, cognitive, motoric and neurovegetative functioning. These findings suggest that neurotrophic effects of mood stabilizers—if they occur in humans— may be very relevant for the treatment of BPD. Targeting Synaptic/Cellular Plasticity in the Treatment of Mood Disorders Neurotrophic and neuroprotective actions of mood stabilizers Numerous studies at the anatomic, cellular, and molecular levels, provide evidence for the neurotrophic and neuroprotective actions of mood stabilizers. As a complement to the findings of region-specific brain atrophy in BPD, many studies have found evidence that mood stabilizers promote neural viability in multiple preclinical paradigms. Moore and colleagues quantitated levels of NAA in a longitudinal clinical study using proton magnetic resonance spectroscopy (MRS) and found that chronic administration of the mood stabilizer lithium, at therapeutic doses, increases NAA (Moore, Bebchuk, Hasanat, et al., 2000). In follow-up studies, the authors examined brain tissue volumes using high-resolution three-dimensional magnetic resonance imaging (MRI) and demonstrated that chronic lithium administration significantly, and specifically, increased total gray matter content in the brains of patients with BPD (Moore, Bebchuk, Wilds, et al., 2000). A more recent MRI study reported increased hippocampal volume in patients who were treated with lithium (Yucel et al., 2007). Providing evidence for the clinical significance of these findings, a longitudinal study using high-resolution volumetric MRI demonstrated significant regional volumetric differences between lithium responders and nonresponders (Moore et al., 2006). Only responders showed increases in gray matter in the prefrontal cortex

28: GENES TO BEHAVIOR PATHWAYS OF BIPOLAR DISORDER

and left subgenual prefrontal cortex, areas that are specifically implicated in the neuropathophysiology of BPD in various neuroimaging and postmortem neuropathology investigations. At the cellular level, lithium has been shown to exert neuroprotective effects in a variety of preclinical paradigms (see Table 28.4). At therapeutically relevant concentrations, lithium has been demonstrated to protect against the deleterious effects of glutamate, N-methylD-aspartate (NMDA) receptor activation, aging, serum or growth factor deprivation, and other toxins in vitro (Manji and Lenox, 2000b). Lithium’s neurotrophic and cytoprotective effects have also been demonstrated in rodent brain in vivo, in response to kainic acid infusion, forebrain cholinergic system lesions, middle cerebral artery occlusion, and cranial irradiation (Manji and Lenox, 2000b; Yazlovitskaya et al., 2006). Lithium prevents injury-induced degeneration and also promotes axon regeneration in retinal ganglion cells (Huang et al., 2003), presumably via up-regulation of Bcl-2 (discussed below). A more direct recent study of synaptic plasticity has demonstrated that subchronic lithium, applied to hippocampal slices, resulted in increases in excitatory post-

28.4 Neurotrophic and Neuroprotective Effects of Lithium

TABLE

Protects (human and rodent) brain cells in vitro from glutamate and NMDA toxicity calcium toxicity thapsigargin (which mobilizes MPP+ and Ca2+) toxicity β-amyloid toxicity aging-induced cell death growth factor and serum deprivation glucose deprivation low K+ C2-ceramide Ouabain aluminum toxicity HIV regulatory protein, Tat Demonstrates following effects in rodent brain (in vivo) enhanced hippocampal neurogenesis protection against cholinergic lesions protection against radiation injury protection against medial cerebral artery occlusion (stroke model) protection against quinolinic acid (Huntington’s model) Demonstrates following effects in human brain increased gray matter volumes in lithium-treated bipolar patients increased N-acetylaspartate (NAA) levels in lithium-treated bipolar patients protection against reduced subgenual prefrontal cortex volumes larger anterior cingulate volumes in lithium-treated bipolar patients protection against reduced glial numbers or glia: neuron ratio in the amygdale NMDA: N-methyl-D-asparate; HIV: human immuno-deficiency virus; MPP+: 1-methyl-4-phenylpyridium.

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synaptic responses, synaptic strength, and cell firing in dentate gyrus granule cells (Shim et al., 2007). Although the mood stabilizer valproate has not been as extensively studied as lithium, a number of studies have found that it does indeed exert neuroprotective effects in injury paradigms such as thapsigargin and 1methyl-4-phenylpyridinium (MPP+) toxicity (Lai et al., 2006), excitotoxicity (Bruno et al., 1995), low K+-induced apoptosis (Mora et al., 1999), and middle cerebral artery occlusion (Ren et al., 2004). Neurotrophic and neuroprotective actions of antidepressants Several studies demonstrate the neurotrophic-like effects of various classes of antidepressant medications (Goodwin and Jamison, 2007). One early study found that antidepressant treatment induced regeneration of catecholamine axon terminals in the cerebral cortex (Nakamura, 1990). Another study demonstrated that treatment with the atypical antidepressant tianeptine blocked the stress-induced atrophy of CA3 pyramidal neurons, measured as a blockade of the decrease in the number and length of apical dendrite branch points (Watanabe et al., 1992). In tree shrews subjected to chronic psychosocial stress, tianeptine was shown to reverse the stressinduced decreases in NAA, granule cell proliferation, and hippocampal volume (Czeh et al., 2001). Regulation of hippocampal neurogenesis by mood stabilizers Given lithium’s neurotrophic and neuroprotective effects, the ability of lithium to promote neurogenesis has been of considerable interest. In the normal process of neurogenesis, a significant fraction of neural progenitor cells undergo programmed cell death, and the overexpression of anti-apoptotic Bcl-2 rescues these progenitors (Kuhn et al., 2005). As lithium has been shown to up-regulate Bcl-2 (as discussed below), the intriguing possibility that lithium might promote the survival of neural precursors has been investigated in a number of studies. In an early study, mice treated chronically with lithium were found to have an increase in recently dividing cells in the dentate gyrus (Chen et al., 2000), as identified with BrdU, a thymidine analog that is incorporated into deoxyribonucleic acid (DNA). Approximately two thirds of these BrdU-positive cells also stained with the neuronal marker NeuN, demonstrating their neuronal identity. These results have been replicated by others, in vitro and in vivo (Kim et al., 2004). Valproate has also been shown to have neurogenic effects in at least one study. In cultured embryonic rat cortical cells and striatal primordial stem cells, valproate markedly increased the number and percentage of

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primarily GABAergic neurons, and increased neurite outgrowth (Laeng et al., 2004). Regulation of hippocampal neurogenesis by antidepressants Several studies have shown that antidepressant treatment increases neurogenesis of dentate gyrus granule cells (Vollmayr et al., 2007). These studies have found that chronic administration of different classes of antidepressants, including norepinephrine- and serotoninselective reuptake inhibitors (SSRIs), and electroconvulsive shock (ECS; the animal model of electroconvulsive therapy, or ECT, which is an effective nonpharmacologic treatment for depression) increases the proliferation and survival of new neurons. Studies demonstrating that neurogenesis is increased by conditions that stimulate neuronal activity (for example, enriched environment, learning, exercise) suggest that this process is also positively regulated by, and may even be dependent on, neuronal plasticity (Kempermann, 2002). In view of the opposite effects of stress and antidepressants on hippocampal neurogenesis, it is hypothesized that alterations in this process are fundamental to the clinical syndrome of depression. To investigate this, Hen and colleagues (Santarelli et al., 2003) conducted an important series of experiments in which mice were administered antidepressants and their responses on a novelty-suppressed feeding test measured. Antidepressant treatment was associated with an improvement in the speed of retrieving food or water, and a 60% increase in BrdU-positive cells in the dentate gyrus. To test whether hippocampal neurogenesis was necessary for the antidepressants’ behavioral effects, mice were exposed to X-rays directed at the hippocampus, eliminating >80% of the BrdU-positive cells in the subgranular zone. In these mice, the previously noted antidepressant effects on the novelty-suppressed feeding test were not observed. These results suggest that the behavioral effects of chronic antidepressants may be mediated by new neuronal growth in the hippocampus, although further confirmation, using different behavioral paradigms, is necessary. A problem to be addressed with the neurotrophic hypothesis of antidepressant drug action is the “tryptophan depletion conundrum.” It is now well-established that patients successfully treated with SSRIs show a rapid depressive relapse following experimental procedures that deplete tryptophan and serotonin (Delgado et al., 1991; Aberg-Wistedt et al., 1998; Delgado et al., 1999). How are such rapid effects to be reconciled with the postulated neurotrophic actions of antidepressants? It is our contention that treatment of depression is attained by providing trophic and neurochemical support, such that the trophic support restores normal synaptic connectivity, allowing the chemical signal to reinstate

the optimal functioning of critical circuits necessary for normal affective regulation. Furthermore, what is sometimes less well appreciated is the fact that the major function of brain-derived neurotrophic factor (BDNF), a major neurotrophin in the CNS, is its regulation of synaptic excitability/plasticity, not its cell growth/survival effects (Manji et al., 2003). Thus an antidepressant-induced neurotrophin increase would have effects on long-term cell trophic/survival pathways and also neurotransmitter function. The latter would, of course, be susceptible to rapid perturbations (for example, with tryptophan depletion). AMPA- AND NMDA-TYPE GLUTAMATE RECEPTORS AND MOOD DISORDERS Glutamate Receptors in the Pathophysiology of Mood Disorders It is surprising that the glutamatergic system has only recently undergone extensive investigation with regard to its possible involvement in the pathophysiology of mood disorders, because it is the major excitatory neurotransmitter in the CNS and known to play a role in regulating the threshold for excitation of most other neurotransmitter systems. Although direct evidence for glutamatergic excitotoxicity in BPD is lacking, and the precise mechanisms underlying the cell atrophy and death that occur in recurrent mood disorders are unknown, considerable data have shown that impairments of the glutamatergic system play a major role in the morphometric changes observed with severe stresses (McEwen, 1999; Sapolsky, 2000). It is now clear that modification of the levels of synaptic α-amino-3-hydroxy-5-methyl-4-isoxasolepropionic acid (AMPA)-type glutamate receptors, in particular by receptor subunit trafficking, insertion, and internalization, is a critically important mechanism for regulating various forms of synaptic plasticity and behavior. Recent studies have identified region-specific alterations in expression levels of AMPA and NMDA glutamate receptor subunits in patients with mood disorders (Beneyto et al., 2007). Supporting the suggestion that abnormalities in glutamate signaling may be involved in mood pathophysiology, AMPA receptors have been shown to regulate affective-like behaviors in rodents. Antagonists at the AMPA receptor have been demonstrated to attenuate amphetamine- and cocaine-induced hyperactivity, and psychostimulant-induced sensitization and hedonic behavior (Goodwin and Jamison, 2007). Glutamate Receptors in the Treatment of Mood Disorders Further evidence for the role of glutamate receptors in mood disorders comes from investigations of the mech-

28: GENES TO BEHAVIOR PATHWAYS OF BIPOLAR DISORDER

anism of action of mood stabilizers and antidepressants. In postmortem human brain tissue, Künig et al. (1998) found that therapeutic levels of valproate decreased binding of AMPA to AMPA receptors, thus effectively blocking them. Chronic lithium and valproate (two structurally dissimilar mood stabilizers) have been shown to down-regulate synaptic expression of the AMPA receptor subunit GluR1 in hippocampus, in vitro and in vivo (Du et al., 2003). In cultured hippocampal neurons, lithium and valproate were found to attenuate surface GluR1 expression after long-term treatment. Furthermore, our group and the Greengard laboratory have found that antidepressants have the opposite effect of up-regulating AMPA synaptic strength in hippocampus (Svenningsson et al., 2002; Du et al., 2003). In addition to effects on AMPA receptor trafficking, valproate appears to block synaptic responses mediated by NMDA glutamate receptors (Loscher, 1999). Two independent studies (Ueda and Willmore, 2000; Hassel et al., 2001) showed that chronic valproate selectively altered glutamate transporter expression in hippocampus. Thus overall, chronic valproate likely decreases intrasynaptic glutamate levels through a variety of mechanisms. A growing body of data demonstrates that antidepressants also attenuate expression and/or function of NMDA receptor subunits (Goodwin and Jamison, 2007). Building upon these preclinical data, recent clinical trials have investigated the clinical effects of glutamatergic agents in patients with mood disorders. Recent clinical studies have demonstrated effective and rapid antidepressant action of glutamatergic agents, including ketamine, an NMDA receptor antagonist, and riluzole, a glutamate release inhibitor (Zarate, Singh, and Manji, 2006; Sanacora et al., 2007). These and other data have led to the hypothesis that alterations in neural plasticity in critical limbic and reward circuits, mediated by increasing the postsynaptic AMPA to NMDA throughput, may represent a convergent mechanism for antidepressant action (Zarate, Singh, Carlson, et al., 2006). This line of research holds considerable promise for developing new treatments for depression and BPD.

THE GS/CYCLIC ADENOSINE MONOPHOSPHATE (cAMP)-GENERATING SIGNALING PATHWAY IN THE PATHOPHYSIOLOGY AND TREATMENT OF MOOD DISORDERS Evidence for the Role of the Gs/cAMP Pathway in the Pathophysiology of Mood Disorders Several independent laboratories have now reported abnormalities in the G protein signaling cascade in mood disorders (Schreiber et al., 1991; Young et al., 1993; Manji et al., 1995; Garcia-Sevilla et al., 1997; Spleiss

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et al., 1998; Warsh et al., 2000). Postmortem brain studies have consistently reported increased levels of the stimulatory G protein (Gαs) accompanied by increases in stimulated adenylate cyclase (AC) activity in BPD (Young et al., 1993; Warsh et al., 2000). These observations of elevated Gαs levels and/or function are further supported by the demonstration of increased agonist-activated [35S]GTPγ S binding to Gα subunits in the frontal cortex of patients with BPD (Wang and Friedman, 1996). Several studies have also found elevated Gαs messenger ribonucleic acid (mRNA) and protein levels in peripheral circulating cells in BPD, although the dependency on clinical state remains unclear (Schreiber et al., 1991; Young et al., 1994; Manji et al., 1995; Spleiss et al., 1998). Gαolf, which is highly homologous to Gαs, is located in an area of chromosome 18 that has been identified as a potential site of BPD susceptibility loci. Heterozygous Gαolf knockout mice show a markedly abnormal behavioral response to psychostimulants (Corvol et al., 2001). It should be emphasized that there is at present no evidence of mutations in the Gαs or Gαolf genes in mood disorders (Ram et al., 1997; Zill et al., 2003). There are numerous transcriptional and posttranscriptional mechanisms that regulate the levels of Gα subunits, and elevated levels of Gαs could potentially represent the indirect sequelae of alterations in any one of these biochemical pathways (Manji and Chen, 2000). Overall, elevation of levels of the predominant subspecies of Gαs is a very consistent finding. Although it may appear unintuitive that disruption of such a ubiquitously expressed protein may lead to the relatively subtle abnormalities in brain function in mood disorders, there is precedent for clinical disorders with circumscribed clinical manifestations arising as a result of abnormalities in Gαs levels (Spiegel, 1998). Considerable clinical research has focused on the activity of the cyclic adenosine monophosphate (cAMP)generating system in readily accessible blood elements in patients with BPD. Overall, the preponderance of evidence demonstrates altered receptor and/or postreceptor sensitivity of the cAMP-generating system in the absence of consistent alterations in the number of receptors themselves (J.F. Wang et al., 1997; Warsh et al., 2000). Peripheral cell studies in patients with BPD have demonstrated increased protein kinase A (PKA) catalytic subunit levels, and increased cAMP-stimulated PKA activity (Perez et al., 1999; Tardito et al., 2003; Karege et al., 2004). Similarly, in a series of postmortem studies, Warsh and colleagues have found increased basal and stimulated PKA activity, and corresponding alterations in PKA regulatory and catalytic subunits in various brain areas in patients with BPD (Rahman et al., 1997; Fields et al., 1999; Chang et al., 2003). In addition, other studies have shown increased basal and stimulated AC activity in postmortem brain tissue of patients with BPD (Gould and Manji, 2002b).

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Interestingly, quite distinct abnormalities have been observed in this signaling pathway in MDD compared to BPD. Peripheral cell studies have shown decreased cAMP levels and PKA activity in MDD (Mizrahi et al., 2004; Akin et al., 2005). Postmortem brain studies have shown increased levels of the inhibitory G protein (Gαi) in the frontal cortex of antidepressant-free patients with MDD (Garcia-Sevilla et al., 1999), and decreased stimulated AC activity in the frontal cortex of victims of suicide (Cowburn et al., 1994; Lowther et al., 1996). These data suggest that MDD is associated with downregulation of the cAMP pathway. This is consistent with data from studies investigating the mechanism of action of antidepressants and antimanic mood stabilizers, as discussed below. A critical downstream target of the Gs /cAMP pathway, cAMP-response element binding protein (CREB), has also been implicated in mood disorders and suicide (Dwivedi et al., 2003; Yamada et al., 2003; Zubenko et al., 2003; Young et al., 2004). Markers near the CREB1 locus have been reported to cosegregate with MDD in women (Zubenko et al., 2003). By microarray analysis, CREB1 gene expression was found to be significantly reduced in postmortem orbitofrontal cortex from patients with BPD (Ryan et al., 2006). Induced CREB overexpression in the dentate gyrus resulted in an antidepressant-like effect in the learned helplessness paradigm and the Forced Swim Test in rats (A.C. Chen et al., 2001). Initial results suggesting an association between polymorphisms in CREB-regulated BDNF and BPD have not been confirmed (Kato, 2007). The effects of mood stabilizers and antidepressants on CREB and BDNF have generated much interest, as discussed below. Evidence for the Role of the Gs/cAMP Pathway in the Treatment of Mood Disorders Lithium Although it appears that lithium, at therapeutic concentrations, does not directly affect G proteins, there is considerable evidence that chronic lithium administration indirectly affects G protein function (Risby et al., 1991; Mork et al., 1992; J.F. Wang et al., 1999). For Gs and Gi, lithium’s major effects in humans and rodents are most compatible with stabilization of the heterotrimeric, undissociated, inactive αβγ conformation of the G protein (Manji et al., 1995; Li and El-Mallahk, 2000; Warsh et al., 2000). Lithium has been recently shown to promote membrane localization of G protein receptor kinase-3 (GRK-3), a serine-threonine kinase that regulates G protein–coupled receptor sensitivity (Ertley et al., 2007). Lithium also exerts complex effects on the activity of AC, with the preponderance of the data demonstrating an elevation of basal AC activity but an attenuation

of receptor-stimulated response in preclinical and clinical studies (Mork et al., 1992; J.F. Wang et al., 1997; Jope, 1999; Manji et al., 2000; Hahn et al., 2005). It has been postulated that these elevations of basal cAMP and dampening of receptor-mediated stimulated response play an important role in lithium’s ability to prevent “excessive excursions from the norm” (Manji et al., 1995; Jope, 1999). These complex actions likely represent the net effects of direct inhibition of AC, up-regulation of certain AC subtypes, and effects on stimulatory and inhibitory G proteins (Manji and Lenox, 2000b). Lithium’s effects on the phosphorylation and activity of CREB have been examined in numerous preclinical studies, with conflicting results (Ozaki and Chuang, 1997; Einat et al., 2003; Tardito, Tiraboschi, et al., 2006). Postmortem studies have demonstrated decreased phosphorylated CREB in patients with BPD treated with lithium (Stewart et al., 2001; Young et al., 2004). As discussed below, CREB is also regulated by the mitogen-activated protein kinase (MAPK) signaling cascade, another target of lithium’s actions. Thus, lithium’s effects on CREB may be temporally and spatially specific, reflecting the relative contributions of these two major signaling pathways. Valproate Valproate is another major antimanic agent, but structurally dissimilar to lithium. Chronic valproate treatment has been shown to induce a significant reduction of β -adrenergic receptors (β -ARs), and even greater decrease in receptor- and postreceptor-mediated cAMP accumulation (G. Chen, Manji, et al., 1996), consistent with recent studies that show that valproate decreases receptor/G protein coupling (Hahn et al., 2005). In a recent microarray analysis, valproate treatment resulted in altered levels of several G protein subunits, a PKA catalytic subunit, and CREB (Bosetti et al., 2005). Carbamazepine Carbamazepine, an atypical anticonvulsant, is widely used in BPD as an alternative or adjunctive treatment to lithium. Carbamazepine exerts effects on G proteins that are largely, although not completely, in common with those of lithium. Like lithium, however, it has been recently found to regulate GRK-3, a regulator of G protein–coupled receptors (Ertley et al., 2007). Carbamazepine has been demonstrated in numerous studies to have significant effects on the cAMP signaling pathway. Carbamazepine has been shown to decrease basal concentrations of cAMP in mouse cerebral cortex and cerebellum and reduce pharmacologically induced cAMP production (Lewin and Bleck, 1977; Ferrendelli and Kinscherf, 1979; Palmer et al., 1979; van Calker et al., 1991). In patients, who were manic, car-

28: GENES TO BEHAVIOR PATHWAYS OF BIPOLAR DISORDER

bamazepine decreased elevated CSF levels of cAMP (Post et al., 1982). At therapeutically relevant concentrations, carbamazepine was found to inhibit basal and stimulated cAMP production, an effect found also in AC extracts, suggesting that lithium acts directly on AC, or on closely associated factors that copurify with AC (G. Chen, Pan, et al., 1996). Antidepressants The cAMP signaling cascade appears to be a major target for the actions of chronic antidepressant treatments. Multiple lines of evidence support the up-regulation of the cAMP/PKA cascade by antidepressants (Fig. 28.3) (Tardito, Perez, et al., 2006). Duman and colleagues (2000) performed an elegant series of studies that first demonstrated antidepressant effects on CREB, an important downstream target of this cascade. Work from this group demonstrated increases in CREB mRNA, CREB protein, and CRE DNA binding activity in hip-

Antidepressant Treatment

Neural Plasticity

5-HT or NE

Glutamate

␤AR Gs 5-HT7

NMDA

AC

cAMP Ca2⫹⫺dependent kinases PKA Neuronal Plasticity and Cell Survival nucleus

CREB BDNF Gene Expression FIGURE 28.3 Influence of antidepressant treatment on the cAMP-CREB cascade. Antidepressant treatment increases synaptic levels of norepinephrine (NE) and serotonin (5-HT) by blocking the reuptake or breakdown of these monoamines, resulting in activation of intracellular signal transduction cascades, including the cAMP-CREB cascade. Chronic antidepressant treatment increases Gs coupling to adenylyl cyclase (AC), levels of cAMP-dependent PKA, and CREB. CREB is also phosphorylated by Ca2+-dependent protein kinases, which can be activated by the phosphatidylinositol pathway (not shown) or by glutamate ionotropic receptors (for example, NMDA). Glutamate receptors and Ca2+-dependent protein kinases are also involved in neural plasticity. One gene target of antidepressant treatment and the cAMP-CREB cascade is BDNF, which contributes to the cellular processes underlying neuronal plasticity and cell survival. AR: adrenergic receptor. cAMP: cyclic adenosine monophosphate; CREB: cAMPresponse element binding; PKA: protein kinease A; BDNF: brainderived neurotrophic factor; NMDA: N-methyl-D-aspartate. Reproduced with permission from Duman et al., (2000).

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pocampus in response to several different classes of antidepressants (Nibuya et al., 1996; Thome et al., 2000), as well as increases in the expression of two CREBregulated genes that have been implicated in the pathophysiology of mood disorders: BDNF and its receptor, trkB (Nibuya et al., 1996), discussed further below. THE PI/PKC SIGNALING PATHWAY IN THE PATHOPHYSIOLOGY AND TREATMENT OF MOOD DISORDERS Evidence for the Role of the Phosphoinositide (PI) Signaling Cascade in the Pathophysiology of Mood Disorders Interest in the phosphoinositide (PI) signaling system in BPD was first generated by the seminal observation that lithium reduces brain levels of inositol (Allison and Stewart, 1971). The implication of this major secondmessenger cascade was intriguing, given that several subtypes of adrenergic, cholinergic, and serotonergic receptors are coupled to this system. Further studies have supported the inositol signaling pathway (Fig. 28.4) as a target of lithium (see below), but evidence that disruptions in the PI/PKC (protein kinase C) signaling system play a role in the pathophysiology of mood disorders is less definitive. Some evidence is provided by peripheral cell studies. Patients who were manic were found to have a significantly higher percentage of platelet membrane phosphoinositide 4,5-biphosphate (PIP2) (Brown et al., 1993), a finding that was replicated in a follow-up study of medication-free patients with BPD who were depressed (Soares et al., 2001). Postmortem studies of patients with BPD have revealed lower free inositol levels in prefrontal cortex (Shimon et al., 1997) and reduced agonist-induced PI turnover in occipital cortex (Jope et al., 1996). Importantly, a recent whole-genome association study of BPD has further implicated this pathway. Of the risk genes identified, that demonstrating by far the strongest association with BPD was diacylglycerol kinase eta (DGKH), an immediate regulator of PKC (Baum et al., 2008). PKC in the Pathophysiology of Mood Disorders There have been a limited number of studies directly examining PKC in BPD. In postmortem brain tissue from patients with BPD, there have been observations of an increase in PKC activity, PKC translocation, and cortical levels of specific PKC isozymes (H.Y. Wang and Friedman, 1996). Postmortem brains from patients with BPD were found to have increased association of PKC isozymes with the receptor for activated C kinase-1 (RACK1), which anchors PKC to the membrane (H.Y. Wang and

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MOOD DISORDERS Serotonin, norepinephrine, dopamine, glutamate

Myo-inositol

Wnt

G protein

WntR PIP2

Li VPA

PLC-␤

Dishevelled

Myo-inositol

DAG

IP3 Li

PKC

GSK-3␤

Li VPA

ERK/MAPK cascade

Cytoskeletal proteins underlying longterm neuroplasticity

MARCKS

Li VPA

c-FOS c-Jun Jun-D ⌬ FosB AP-1

Li VPA

P ␤-catenin

P LEF

CREB

P P

Li ?VPA

Long term alterations in synaptic plasticity and neuronal morphology FIGURE 28.4 Intracellular signaling cascades involved in long-term stabilization of mood by Li and VPA. Activation of receptors coupled to PI hydrolysis results in the breakdown of PIP2 into two second messengers: IP3 and DAG, which is an endogenous activator of PKC. Li is an uncompetitive inhibitor of inositol monophosphatases, whereas Li and VPA, upon chronic administration, decrease myoinositol uptake. These perturbations by mood stabilizers likely contribute to the reduction in PKC activity and the reduced levels of PKC-α, PKC-ε and MARCKS, a major PKC substrate in the CNS. In the Wnt signaling pathway, binding of the Wnt signal to the Wnt receptor (WntR) activates an intermediary protein, Dishevelled, which regulates GSK-3β. GSK-3β regulates cytoskeletal proteins and also has an important role in determining cell survival and cell death. Li (and possibly VPA) directly inhibit GSK-3β, which may underlie, at least in part, the increases in β -catenin that occur after

chronic treatment with these agents. The ERK-MAP kinase cascade regulates several important transcription factors, most notably CREB and activator protein-1 (AP-1). Recent studies have demonstrated that Li and VPA activate the ERK MAP kinase cascade, which may contribute to the long-term changes in synaptic plasticity and morphology that follow chronic treatment. Together, the regulation of these signaling pathways brings about an enhancement of synaptic connectivity potentially necessary for long-term stabilization of mood. Li: lithium; VPA: valproic acid; PIP2: phosphoinositide 4,5-biphosphate; DAG: diacylglycerol; PKC: protein kinease C; MARCKS: myristoylated alanine-rich C kinase substrate; CNS: central nervous system; ERK: extracellular signal regulated kinases; MAP: mitogenactivated protein; CREB: cyclic adenosine monophosphate [AMP]response element binding. Reproduced with permission from Coyle and Manji (2002).

Friedman, 2001). The same group also found elevated PKC activity in platelets from patients who were manic (Friedman et al., 1993). In contrast to these findings, other studies have reported evidence consistent with reduced PKC function in BPD from postmortem studies using [3H]PDBu, a radioligand that binds to PKC, and one peripheral cell study using platelets from pediatric patients (Pandey et al., 1997; Coull et al., 2000; Pandey et al., 2007). Resolution of these apparent inconsistencies requires further study. In animal models of mania, several studies have demonstrated that acute and chronic amphetamine produces an alteration in PKC activity, its relative cytosol to mem-

brane distribution, and the phosphorylation of a major PKC substrate, GAP-43, which has been implicated in long-term alterations of neurotransmitter release (Giambalvo, 1992a, 1992b). Increased hedonistic drive and increased tendency to abuse drugs are well-known facets of manic behavior; notably, PKC inhibitors attenuate these important aspects of the manic-like syndrome in rodents (Einat and Manji, 2006; Einat et al., 2007). Importantly, recent preclinical studies have specifically investigated the antimanic effects of tamoxifen per se (because this is the only CNS-penetrant PKC inhibitor available for humans). These studies showed that tamoxifen significantly reduced amphetamine-induced

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hyperactivity and risk-taking behavior (Einat et al., 2007). Finally, with respect to cognitive dysfunction associated with mania, Birnbaum et al. (2004) demonstrated that excessive activation of PKC dramatically impaired the cognitive functions of the prefrontal cortex, and that inhibition of PKC protected cognitive function. In summary, preclinical biochemical and behavioral data support the notion that PKC activation may result in manic-like behaviors whereas PKC inhibition may be antimanic. These data have prompted clinical trials of tamoxifen for the treatment of mania (see below). Abnormalities of Calcium Signaling in Mood Disorders In response to the fact that calcium ions have been shown to regulate the synthesis and release of neurotransmitters, neuronal excitability, cytoskeletal remodeling, and long-term neuroplastic events, a large number of studies have investigated intracellular calcium in peripheral cells in BPD (Dubovsky et al., 1992; Emamghoreishi et al., 1997; J.F. Wang et al., 1997). Given the many caveats associated with studies of peripheral circulating cells, the consistency of the findings is remarkable. Studies have repeatedly revealed elevations in resting and stimulated intracellular calcium levels in platelets, lymphocytes, and neutrophils of patients with BPD. Whether these abnormalities are state- or trait-dependent is debated (Dubovsky et al., 1992; Emamghoreishi et al., 1997). The regulation of free intracellular calcium is a complex multifaceted process involving extracellular entry, release from intracellular stores, uptake into organelles, and binding to specific proteins. Thus, the abnormalities observed in BPD could arise from dysfunction at a variety of levels, and studies suggest that the abnormality lies beyond the receptor (Hough et al., 1999). Recent evidence suggests altered regulation of calcium by PKC in patients with BPD (Akimoto et al., 2007). Linking abnormalities in the PI cascade to alterations in intracellular calcium, Warsh and colleagues (2000) demonstrated a correlation between altered IMPA2 (myo-inositol monophosphatase 2) mRNA levels and calcium levels in B lymphoblast cell lines from patients with BPD (Yoon et al., 2001). The PI Signaling Cascade in the Treatment of Mood Disorders The inositol depletion hypothesis posits that lithium, an uncompetitive inhibitor of inositol-monophosphatase (IMP), produces its therapeutic effects via a depletion of neuronal myo-inositol levels. Through this uncompetitive inhibition, lithium is proposed to selectively inhibit overactive components of the PI system without interfering with basal functioning (Berridge, 1989).

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Although this hypothesis has been of great heuristic value, studies that support this theory have often been small, inconsistent, and subject to numerous methodological differences (Jope and Williams, 1994). Recent studies have investigated the possibility that lithium and other mood stabilizers regulate the PI system independently of IMPase. One interesting potential target is SMIT (sodium-dependent myo-inositol transporter). In an in vitro study, SMIT expression and activity were down-regulated in response to chronic lithium, valproate, or carbamazepine treatment (van Calker and Belmaker, 2000). In a follow-up in vivo study, neutrophils from untreated patients with BPD were found to have elevated SMIT levels, which were reduced by lithium or valproate treatment (Willmroth et al., 2007). The effects of lithium on myo-inositol levels have also been documented by imaging studies. A number of studies have demonstrated lithium-induced reductions in myo-inositol levels in child and adult patients with BPD, in brain regions previously implicated in BPD (Moore et al., 1999; Davanzo et al., 2001; Yildiz et al., 2001). However, the time course of lithium’s effect on inositol did not correlate with that of its therapeutic action, suggesting that the reduction of myo-inositol is not directly responsible for lithium’s mood-stabilizing effects, but may instead initiate a cascade of secondary changes in the PKC signaling pathway and downstream gene expression. PKC in the Treatment of Mood Disorders Evidence from various laboratories has clearly demonstrated that lithium, at therapeutically relevant concentrations, exerts major effects on the PKC signaling cascade (Fig. 28.4) (Goodwin and Jamison, 2007). Data suggest that acute lithium exposure facilitates a number of PKC-mediated responses, whereas longer-term exposure results in an attenuation of phorbol estermediated responses accompanied by a down-regulation of specific PKC isozymes (Manji and Lenox, 1999). Studies in rodents have demonstrated that chronic lithium administration produces an isozyme-selective reduction in PKC α and ε in frontal cortex and hippocampus, and in immortalized hippocampal cells (Manji et al., 1993; G. Chen, Masana, and Manji, 2000). Chronic lithium administration has been demonstrated to dramatically reduce the hippocampal levels of MARCKS (myristoylated alanine–rich C kinase substrate), a major PKC substrate that has been implicated in the regulation of long-term neuroplastic events (Lenox et al., 1992). Further supporting the therapeutic relevance of these findings, studies have shown that the structurally dissimilar mood stabilizer valproate produces very similar effects on PKC α and ε isozymes and MARCKS (G. Chen et al., 1994; Watson et al., 1998). Interestingly, lithium and valproate appear to bring about their effects on the

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PKC signaling pathway by distinct mechanisms (Manji and Lenox, 1999). These biochemical observations are consistent with the clinical observation that some patients show a preferential response to one of the two agents and that additive therapeutic effects are often observed when the two agents are coadministered. These preclinical data, along with animal studies discussed above, have prompted clinical studies of PKC inhibitors and mood dysregulation. A number of small studies have found that tamoxifen, a nonsteroidal antiestrogen and a PKC inhibitor at high concentrations, possesses antimanic efficacy (Bebchuk et al., 2000; Kulkarni et al., 2006). Most recently, a double-blind, placebo controlled trial of tamoxifen in the treatment of acute mania was undertaken (Zarate et al., 2007). Patients on tamoxifen showed significant improvement in mania compared to placebo as early as 5 days, and the effect size for the drug difference was very large after 3 weeks. Significant interest has been generated recently in the potential mood-stabilizing properties of another class of PKC inhibitors, omega-3 fatty acids (ω -3 FA). The predominant naturally occurring ω -3 FAs, docosahexaenoic acid (DHA) and eicosapentanoic acid (EPA), have been shown to inhibit PKC (Seung Kim et al., 2001), and a number of clinical trials have investigated these agents as monotherapy or adjunctive treatment for depression or BPD. Although many of these trials have demonstrated efficacy (Stoll et al., 1999; Nemets et al., 2002; Peet and Horrobin, 2002; Wozniak et al., 2007), others have not (Post et al., 2003; Keck et al., 2006). Thus, further evaluation of the efficacy of w -3 FAs as monotherapy or adjunctive treatment in BPD or depression is warranted. Together with the emerging genetic evidence, these data suggest that PKC may play an important role in the pathophysiology and treatment of BPD. GSK-3 AS A TARGET FOR TREATMENT IN BPD Recently, considerable excitement has been generated by the identification of an unexpected and novel target for lithium: glycogen synthase kinase-3 (GSK-3). Glycogen synthase kinase-3 is a kinase that functions as an intermediary in numerous intracellular signaling pathways (Fig. 28.4) and is regulated by serotonin, dopamine, psychostimulants, and antidepressants (Gould and Manji, 2005). It is a major regulator of apoptosis and cellular plasticity/resilience, and this role has been postulated to be the target of lithium and valproate (Gould and Manji, 2002a; Li et al., 2002). Lithium is a direct inhibitor of GSK-3, via competition with magnesium for a binding site (Klein and Melton, 1996; Ryves and Harwood, 2001). In mice, GSK-3 has also been shown to be inhibited by valproate (G. Chen et al., 1999),

and electroconvulsive therapy (ECT), a nonpharmacologic therapy for mood disorders (Roh et al., 2003). Animal behavioral data from pharmacologic and genetic models have shown that manipulation of GSK-3 produces antidepressant and antimanic effects (Gould and Manji, 2005; Jope and Roh, 2006). To our knowledge, this is the only manipulation, other than that of lithium, that has been demonstrated to exert both such effects. Further studies have been carried out to identify the GSK-3 target most relevant to lithium’s behavioral effects. Glycogen synthase kinase-3 inhibition results in a decrease in phosphorylation and degradation of its target β -catenin, and at therapeutically relevant concentrations, lithium increases β -catenin and Wntmediated gene expression in rodent brain. It was therefore hypothesized that transgenic mice that overexpress a constitutively active form of β -catenin would phenocopy lithium’s behavioral effects. It was found that lithium-induced behaviors in wild-type mice are phenocopied by overexpression of β -catenin. Notably, lithium and β -catenin overexpression have moodstabilizing-like actions in prototypical animal models of mania (D-amphetamine hyperlocomotion) and depression (Forced Swim Test) (Gould et al., 2007). Interestingly, GSK-3 has been found to play a role in regulating circadian rhythm, in Drosophila (Martinek et al., 2001), and mice (Kaladchibachi et al., 2007). Patients with BPD often demonstrate circadian disturbances, and lithium has been shown to increase circadian period in many organisms including humans (Johnsson et al., 1979; Iwahana et al., 2004; Jolma et al., 2006), consistent with a decrease in GSK-3 activity. Direct evidence for the role of GSK-3 in the etiology of BPD has not been reported, and genetic studies have not reproducibly found GSK-3 polymorphisms to be associated with the disease (reviewed in Kato, 2007). Therefore, it remains to be determined if bipolar pathophysiology involves abnormalities of GSK-3 itself, or of other signaling molecules regulated by GSK-3. Nevertheless, in view of the role of GSK-3 in neural plasticity, survival, and circadian rhythms, and its involvement in the action of mood stabilizers, development of GSK-3 inhibitors is actively under way by numerous pharmaceutical companies. CELL SURVIVAL AND RESILIENCE PATHWAYS IN THE TREATMENT OF MOOD DISORDERS Regulation of Cell Survival and Resilience Pathways by Mood Stabilizers In conjunction with the body of data supporting mood stabilizers’ effects on cell survival and plasticity at the cellular level, relevant intracellular signaling cascades have been shown to be regulated by these agents. The extracellular signal regulated kinases (ERK) MAPK-signaling

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cascade plays an important role in mediating neurotrophic and neuroplastic events (Segal and Greenberg, 1996). A series of studies investigating the effects of mood stabilizers on this signaling cascade showed that lithium and valproate, at therapeutically relevant concentrations, robustly activated the ERK MAPK cascade and promoted neurite outgrowth and growth cone formation in human neuroblastoma SH-SY5Y cells (Yuan et al., 2001). Furthermore, in vivo, chronic lithium and valproate robustly increased the levels of activated ERK in the frontal cortex and hippocampus, areas of brain that have been implicated in the pathophysiology and treatment of BPD (Einat et al., 2003). Neurotrophic factors are known to promote cell survival by activating MAPKs to suppress intrinsic cellular

5HT

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apoptotic machinery (Thoenen, 1995; Pettmann and Henderson, 1998). A downstream target of the MAPK cascade, ribosomal S-6 kinase (Rsk), phosphorylates CREB, leading to expression of antiapoptotic Bcl-2 (Fig. 28.5). Studies by our group demonstrated that chronic treatment with lithium or valproate in rats produced a doubling of Bcl-2 levels in the frontal cortex, due primarily to a marked increase in the number of Bcl-2immunoreactive cells in layers II and III of the frontal cortex (Manji et al., 2000). Chronic lithium also markedly increased the number of Bcl-2-immunoreactive cells in the dentate gyrus and striatum, and in cultured cells (R.W. Chen and Chuang, 1999; Manji et al., 2000). Lithium and valproate have also been shown to increase the expression of the Bcl-2-associated gene BAG-1. BAG-1

Stress Depression

NE BDNF

Glutamate

BDNF

P

Cortisol

NMDA

trk trk B B P

Antidepressants

Lithium Ca⫹⫹

Akt

GSK-3

GR

ROS Energy Capacity

BAD

Neuroplasticity and Cellular Resilience

Bcl-x

P trk B trk B

BDNF

P ROS Ca⫹⫹ (⫺) Cytochrome C Bcl-2 Lithium VPA

Failure of Neuroplasticity Signal

Ras GTP

Bcl-2

Repeated Episodes Illness Progression

28.5 The multiple influences on neuroplasticity and cellular resilience in mood disorders. Genetic and neurodevelopmental factors, repeated affective episodes, and illness progression might all contribute to the impairments of cellular resilience, volumetric reductions, and cell death and atrophy observed in mood disorders. Stress and depression likely contribute to impairments of cellular resilience by a variety of mechanisms, including reductions in the levels of BDNF, facilitating glutamatergic transmission via NMDA and non-NMDA receptors, and reducing energy capacity of cells. Neurotrophic factors such as BDNF enhance cell survival by activating two distinct signaling pathways: the PI3-kinase pathway, and the ERK MAP kinase pathway. One of the major mechanisms by which BDNF promotes cell survival is by increasing the expression of the major cytoprotective protein, Bcl-2. Bcl-2 attenuates cell death through a variety of mechanisms, including impairment of the release of calcium and cytochrome c, sequestering of proforms of death-inducing

FIGURE

MEK

RSK-2 ERK Lithium

Genetic and Developmental Factors

Raf

CREB

VPA

Cerebrovascular Insufficiency caspase enzymes, and enhancement of mitochondrial calcium uptake. The chronic administration of a variety of antidepressants increases the expression of BDNF and its receptor TrkB. Lithium and valproic acid robustly upregulate the cytoprotective protein Bcl-2 and inhibit GSK-3β, both of which have neuroprotective results. Valproic acid also activates the ERK-MAP kinase pathway, which may play a major role in producing neurotrophic effects and neurite outgrowth. 5HT: serotonin; BAD and Bax: pro-apoptotic members of the Bcl-2 family; Bcl-2 and Bcl-x: anti-apoptotic members of the Bcl-2 family; BDNF: brain-derived neurotrophic receptor; NMDA: N-methyl-D-aspartate; ERK: extracellular signal regulated kinases; MAP: mitogen-activated protein; CREB: cyclic AMP-responsive element-binding protein; GR: glucocorticoid receptor; GSK-3: glycogen synthase kinase-3; NE: norepinephrine; NGF: nerve growth factor; ROS: reactive oxygen species; RSK-2: ribosomal S-6 kinase; VPA: valproic acid. Reprinted with permission from Manji et al. (2001).

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attenuates glucocorticoid receptor (GR) nuclear translocation, activates MAPKs, and potentiates the anti-apoptotic functions of Bcl-2 (Zhou et al., 2005). Thus, lithium regulates a number of components of survival cascades, through which it may exert its neuroprotective effects. Regulation of Cell Survival and Resilience Pathways by Antidepressants As discussed above, many studies have demonstrated that antidepressant treatment up-regulates a key pathway involved in cell survival and plasticity, the cAMP– CREB cascade (Duman et al., 2000; Tardito, Perez, et al., 2006). A critical target of CREB gene regulation is the neurotrophic factor BDNF, and the effect of several different classes of antidepressants on BDNF expression has been demonstrated in a number of animal and human postmortem studies. ECT, a nonpharmacologic treatment for depression, has been consistently found to upregulate BDNF expression (Tardito, Perez, et al., 2006). In an elegant study from the Nestler laboratory, mice subjected to chronic social defeat stress exhibited adaptations in gene expression and chromatin remodeling of five BDNF splice variant mRNAs (I–V), including down-regulation of BDNF transcripts III and IV, and robustly increased repressive histone methylation at their corresponding promoters. Chronic imipramine (a tricyclic antidepressant) reversed this down-regulation and increased histone acetylation at these promoters (Tsankova et al., 2006). Other studies, however, have not shown antidepressant-induced BDNF expression; this lack of consistency may depend on experimental paradigm (Tardito, Perez, et al., 2006). Further evidence to support the role of the cAMP– CREB cascade and BDNF in antidepressant action comes from studies using animal models of depression, in which up-regulation of these pathways results in an antidepressant-like effect (Duman et al., 2000; A.C. Chen, Shirayama, et al., 2001). Indirect human evidence comes from studies showing increased hippocampal BDNF expression in postmortem brain from patients treated with antidepressants at the time of death compared with untreated patients (B. Chen, Dowlatshahi, et al., 2001). In summary, there is strong evidence that the cAMP–CREB pathway, including CREB-regulated BDNF expression, is a major target of antidepressant action, but the precise nature of these actions is yet to be determined. It is important to note that CREB is regulated by multiple upstream cascades. Although antidepressant induction of CREB activity has been primarily shown to be via the cAMP–PKA pathway, other signaling cascades, such as the calcium/calmodulin-dependent kinase (CaMK) and MAPK cascades, have been implicated in recent studies as possibly involved in the mechanism of antidepressant action (Tiraboschi et al., 2004; Tardito, Tiraboschi, et al., 2006).

NEUROTROPHIC SIGNALING-MEDIATED MITOCHONDRIAL FUNCTION IN BPD Kato and Kato (2000) anticipated recent developments in the field when they first proposed that mitochondrial dysfunction plays an important role in the pathophysiology of BPD. In addition to critical roles in regulation of energy production via oxidative phosphorylation, regulation of intracellular Ca2+, and mediation of apoptosis, increasing evidence suggests that mitochondrial calcium sequestration is integrally involved in regulating synaptic plasticity. Consistent with the growing appreciation of this role, a number of human neuroimaging and postmortem brain studies, as well as preclinical molecular and cellular biology studies, have implicated mitochondria in the impairments of plasticity and cellular resilience manifest in BPD. As a point of clarification, it is not our contention that BPD is a classic mitochondrial disorder. Although individuals with mitochondrial dysfunction often manifest psychiatric symptoms, the vast majority of patients with BPD do not show the symptoms of classic mitochondrial disorders (Fadic and Johns, 1996). Nevertheless, these disorders may have a partially shared etiology: impaired regulation of Ca2+ cascades, and consequent toxic cell injury, is an essential component of the pathophysiology of classic mitochondriopathies, and has been the most reproducible biological measure of abnormalities described in research on BPD. In view of the growing body of evidence demonstrating the toxic effects of elevated intracellular Ca2+ on neurons and glia, Ca2+ dysregulation has been postulated to underlie aspects of the pathophysiology of BPD (Goodwin and Jamison, 2007). Results from Kato’s group (Kato et al., 2003) implicate the mitochondrial–endoplasmic reticulum (ER) calcium regulation system in the Ca2+ abnormalities seen in BPD. Building upon Kato’s findings, a subsequent study (Kakiuchi et al., 2003) identified XBP1, a pivotal gene in the ER stress response, as contributing to the genetic risk for BPD. They identified a polymorphism (-116G/C) in the promoter region of XBP1 that was associated with an increased risk for BPD. They showed that the polymorphism was associated with impaired induction of XBP1 expression after ER stress, and that valproate rescued the impaired response by inducing ATF6, the gene upstream of XBP1. An elegant series of postmortem brain microarray studies (Konradi et al., 2004) provided additional evidence for mitochondrial dysregulation in BPD. They found that nuclear mRNA coding for mitochondrial proteins that regulate oxidative phosphorylation and proteasome degradation was decreased in BPD. More recently, Benes et al. (2006) performed a post hoc analysis of an extant gene expression–profiling database obtained

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from the hippocampus. Postmortem brain tissue from patients with BPD showed a marked upregulation of several apoptosis genes, and a downregulation of antioxidant genes, suggesting that accumulation of free radicals might occur in the setting of a previously reported decrease of the electron transport chain in this disorder (Benes et al., 2006). We outlined evidence to support the contention that neurotrophic signaling and its downstream effects on mitochondrial function are integral to many facets of BPD. This theory leads to the intriguing possibility that enhancing mitochondrial vigor may represent an important adjunctive strategy for the optimal long-term treatment of BPD. CONCLUDING REMARKS As we have demonstrated, there is a considerable body of evidence conceptually and experimentally to support abnormalities in the regulation of signaling as integral to the underlying neurobiology of BPD. Indeed, all of the highly significant associations in the recent bipolar whole-genome association study implicate signaling cascades (Baum et al., 2008). In fact, the contribution of these pathways to the pathophysiology of this illness must be reasonably robust, given the variability that might be expected in assessing such dynamic systems under the constraints in experimental design imposed upon such research. Figure 28.5 integrates many of the signaling pathways, and actions upon them by medications, presented in this chapter. The role of cellular signaling cascades offers much explanatory power for understanding the complex neurobiology of BPD (Goodwin and Jamison, 2007). Signaling cascades regulate the multiple neurotransmitter and neuropeptide systems implicated in the disorder and are targets for the most effective treatments. Signaling pathways are also targets for hormones that have been implicated in the pathophysiology of BPD. The highly integrated monoamine and prominent neuropeptide pathways are known to originate and project heavily to limbic-related regions such as the hippocampus, hypothalamus, and brain stem that are likely associated with neurovegetative symptoms. Abnormalities in cellular signaling cascades that regulate diverse physiologic functions likely explain the tremendous medical comorbidity associated with the disorder. Evidence also suggests that, somewhat akin to the treatment of conditions such as hypertension and diabetes, early and sustained treatment may be necessary to adequately prevent the deleterious long-term sequelae associated with mood disorders. Furthermore, for patients who are depressed and refractory to treatment, there may be a limited benefit to drugs that sim-

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ply directly or indirectly alter neurotransmitter levels or bind to cell surface receptors. Such strategies implicitly assume that the target circuits are functionally intact and that altered synaptic activity will thus be transduced to modify the postsynaptic throughput of the system. However, the evidence presented here suggests that, in addition to neurochemical changes, many patients also have pronounced structural alterations (for example, neuropil reductions, reduced spine densities, neurite retraction) in critical neuronal circuits. Thus, optimal treatment may require more direct trophic support to enhance and maintain normal synaptic connectivity, thereby allowing the chemical signal to reinstate the optimal functioning of critical circuits necessary for normal affective regulation. There are a number of pharmacologic “plasticityenhancing” strategies that may be effective in the treatment of BPD. Indeed, this next generation of drugs, in addition to treating core mood symptoms, might be able to target other important aspects of the illness such as impaired cognition, epigenetic factors that may have a long-term negative impact of the course of illness (for example, histone deacetylase inhibitors), and medical comorbidities (for example, GSK inhibitors). The development of novel therapeutics holds much promise for the long-term treatment of severe mood disorders and for improving the lives of the many who suffer from them. REFERENCES Aberg-Wistedt, A., Hasselmark, L., Stain-Malmgren, R., Aperia, B., Kjellman, B.F., and Mathe, A.A. (1998) Serotonergic “vulnerability” in affective disorder: a study of the tryptophan depletion test and relationships between peripheral and central serotonin indexes in citalopram-responders. Acta Psychiatr. Scand. 97: 374–380. Akimoto, T., Kusumi, I., Suzuki, K., and Koyama, T. (2007) Effects of calmodulin and protein kinase C modulators on transient Ca2+ increase and capacitative Ca2+ entry in human platelets: relevant to pathophysiology of bipolar disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 31:136–141. Akin, D., Manier, D H., Sanders-Bush, E., and Shelton, R.C. (2005) Signal transduction abnormalities in melancholic depression. Int. J. Neuropsychopharmacol. 8:5–16. Allison, J.H., and Stewart, M.A. (1971) Reduced brain inositol in lithium-treated rats. Nat. New Biol. 233:267–268. Aston, C., Jiang, L., and Sokolov, B.P. (2005) Transcriptional profiling reveals evidence for signaling and oligodendroglial abnormalities in the temporal cortex from patients with major depressive disorder. Mol. Psychiatry 10:309–322. Baum, A., Akula, N., Cabenero, M., Cardona, I., Corona, W., Klemens, B., Schulze, T.G., et al. (2008) A genome-wide association study implicates diacylglycerol kinase eta (DGKH) and several other genes in the etiology of bipolar disorder. Mol. Psychiatry 13(2):197–207. Baumann, B., Danos, P., Krell, D., Diekmann, S., Wurthmann, C., Bielau, H., Bernstein, H.G., et al. (1999) Unipolar-bipolar dichotomy of mood disorders is supported by noradrenergic brainstem system morphology. J. Affect. Disord. 54:217–224. Bebchuk, J.M., Arfken, C.L., Dolan-Manji, S., Murphy, J., Hasanat, K., and Manji, H.K. (2000) A preliminary investigation of a protein

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MOOD DISORDERS

kinase C inhibitor in the treatment of acute mania. Arch. Gen. Psychiatry 57:95–97. Benes, F.M., Matzilevich, D., Burke, R.E., and Walsh, J. (2006) The expression of proapoptosis genes is increased in bipolar disorder, but not in schizophrenia. Mol. Psychiatry 11:241–251. Beneyto, M., Kristiansen, L.V., Oni-Orisan, A., McCullumsmith, R.E., and Meador-Woodruff, J H. (2007) Abnormal glutamate receptor expression in the medial temporal lobe in schizophrenia and mood disorders. Neuropsychopharmacology 32(9):1888–1902. Berridge, M.J. (1989) The Albert Lasker Medical Awards. Inositol trisphosphate, calcium, lithium, and cell signaling. JAMA 262: 1834–1841. Beyer, J.L., and Krishnan, K.R. (2002) Volumetric brain imaging findings in mood disorders. Bipolar Disord. 4:89–104. Bhalla, U.S., and Iyengar, R. (1999) Emergent properties of networks of biological signaling pathways. Science 283:381–387. Birnbaum, S.G., Yuan, P.X., Wang, M., Vijayraghavan, S., Bloom, A.K., Davis, D.J., Gobeske, K.T., et al. (2004) Protein kinase C overactivity impairs prefrontal cortical regulation of working memory. Science 306:882–884. Bosetti, F., Bell, J.M., and Manickam, P. (2005) Microarray analysis of rat brain gene expression after chronic administration of sodium valproate. Brain Res. Bull. 65:331–338. Brown, A.S., Mallinger, A.G., and Renbaum, L.C. (1993) Elevated platelet membrane phosphatidylinositol-4,5-bisphosphate in bipolar mania. Am. J. Psychiatry 150:1252–1254. Bruno, V., Sortino, M.A., Scapagnini, U., Nicoletti, F., and Canonico, P.L. (1995) Antidegenerative effects of Mg(2+)-valproate in cultured cerebellar neurons. Funct. Neurol. 10:121–130. Carlson, P.J., Singh, J.B., Zarate, C.A., Jr., Drevets, W.C., and Manji, H.K. (2006) Neural circuitry and neuroplasticity in mood disorders: insights for novel therapeutic targets. NeuroRx 3:22–41. Chang, A., Li, P.P., and Warsh, J.J. (2003) Altered cAMP-dependent protein kinase subunit immunolabeling in post-mortem brain from patients with bipolar affective disorder. J. Neurochem. 84:781–791. Chen, A.C., Shirayama, Y., Shin, K.H., Neve, R.L., and Duman, R.S. (2001) Expression of the cAMP response element binding protein (CREB) in hippocampus produces an antidepressant effect. Biol. Psychiatry 49:753–762. Chen, B., Dowlatshahi, D., MacQueen, G.M., Wang, J.F., and Young, L.T. (2001) Increased hippocampal BDNF immunoreactivity in subjects treated with antidepressant medication. Biol. Psychiatry 50:260–265. Chen, G., Huang, L.D., Jiang, Y.M., and Manji, H.K. (1999) The mood-stabilizing agent valproate inhibits the activity of glycogen synthase kinase-3. J. Neurochem. 72:1327–1330. Chen, G., Manji, H.K., Hawver, D.B., Wright, C.B., and Potter, W.Z. (1994) Chronic sodium valproate selectively decreases protein kinase C alpha and epsilon in vitro. J. Neurochem. 63:2361–2364. Chen, G., Manji, H.K., Wright, C.B., Hawver, D.B., and Potter, W.Z. (1996) Effects of valproic acid on beta-adrenergic receptors, G-proteins, and adenylyl cyclase in rat C6 glioma cells. Neuropsychopharmacology 15:271–280. Chen, G., Masana, M.I., and Manji, H.K. (2000) Lithium regulates PKC-mediated intracellular cross-talk and gene expression in the CNS in vivo. Bipolar Disord. 2:217–236. Chen, G., Pan, B., Hawver, D.B., Wright, C.B., Potter, W.Z., and Manji, H.K. (1996) Attenuation of cyclic AMP production by carbamazepine. J. Neurochem. 67:2079–2086. Chen, G., Rajkowska, G., Du, F., Seraji-Bozorgzad, N., and Manji, H.K. (2000) Enhancement of hippocampal neurogenesis by lithium. J. Neurochem. 75:1729–1734. Chen, R.W., and Chuang, D.M. (1999) Long term lithium treatment suppresses p53 and Bax expression but increases Bcl-2 expression. A prominent role in neuroprotection against excitotoxicity. J. Biol. Chem. 274:6039–6042. Corvol, J.C., Studler, J.M., Schonn, J.S., Girault, J.A., and Herve, D. (2001) Galpha(olf) is necessary for coupling D1 and A2a receptors

to adenylyl cyclase in the striatum. J. Neurochem. 76:1585–1588. Coull, M.A., Lowther, S., Katona, C.L., and Horton, R.W. (2000) Altered brain protein kinase C in depression: a post-mortem study. Eur. Neuropsychopharmacol. 10:283–288. Cowburn, R.F., Marcusson, J.O., Eriksson, A., Wiehager, B., and O’Neill, C. (1994) Adenylyl cyclase activity and G-protein subunit levels in postmortem frontal cortex of suicide victims. Brain Res. 633:297–304. Coyle, J.T., and Manji, H.K. (2002) Getting balance: drugs for bipolar disorder share target. Nat. Med. 8:557–558. Czeh, B., Michaelis, T., Watanabe, T., Frahm, J., de Biurrun, G., van Kampen, M., Bartolomucci, A., et al. (2001) Stress-induced changes in cerebral metabolites, hippocampal volume, and cell proliferation are prevented by antidepressant treatment with tianeptine. Proc. Natl. Acad. Sci. USA 98:12796–12801. Davanzo, P., Thomas, M.A., Yue, K., Oshiro, T., Belin, T., Strober, M., and McCracken, J. (2001) Decreased anterior cingulate myoinositol/creatine spectroscopy resonance with lithium treatment in children with bipolar disorder. Neuropsychopharmacology 24: 359–369. Delgado, P.L., Miller, H.L., Salomon, R.M., Licinio, J., Krystal, J.H., Moreno, F.A., Heninger, G.R., et al. (1999) Tryptophandepletion challenge in depressed patients treated with desipramine or fluoxetine: implications for the role of serotonin in the mechanism of antidepressant action. Biol. Psychiatry 46:212–220. Delgado, P.L., Price, L.H., Miller, H.L., Salomon, R.M., Licinio, J., Krystal, J.H., Heninger, G.R., et al. (1991) Rapid serotonin depletion as a provocative challenge test for patients with major depression: relevance to antidepressant action and the neurobiology of depression. Psychopharmacol. Bull. 27:321–330. Drevets, W.C. (2000) Neuroimaging studies of mood disorders. Biol. Psychiatry 48:813–829. Drevets, W.C. (2001) Neuroimaging and neuropathological studies of depression: implications for the cognitive-emotional features of mood disorders. Curr. Opin. Neurobiol. 11:240–249. Du, J., Gray, N.A., Falke, C., Yuan, P., Szabo, S., and Manji, H.K. (2003) Structurally dissimilar antimanic agents modulate synaptic plasticity by regulating AMPA glutamate receptor subunit GluR1 synaptic expression. Ann. N.Y. Acad. Sci. 1003:378–380. Dubovsky, S.L., Murphy, J., Thomas, M., and Rademacher, J. (1992) Abnormal intracellular calcium ion concentration in platelets and lymphocytes of bipolar patients. Am. J. Psychiatry 149:118– 120. Duman, R.S., Malberg, J., Nakagawa, S., and D’Sa, C. (2000) Neuronal plasticity and survival in mood disorders. Biol. Psychiatry 48:732–739. Dwivedi, Y., Rao, J.S., Rizavi, H.S., Kotowski, J., Conley, R.R., Roberts, R.C., Tamminga, C.A., et al. (2003) Abnormal expression and functional characteristics of cyclic adenosine monophosphate response element binding protein in postmortem brain of suicide subjects. Arch. Gen. Psychiatry 60:273–282. Einat, H., and Manji, H.K. (2006) Cellular plasticity cascades: genesto-behavior pathways in animal models of bipolar disorder. Biol. Psychiatry 59:1160–1171. Einat, H., Yuan, P., Gould, T.D., Li, J., Du, J., Zhang, L., Manji, H.K., et al. (2003) The role of the extracellular signal-regulated kinase signaling pathway in mood modulation. J. Neurosci. 23:7311–7316. Einat, H., Yuan, P., Szabo, S.T., Dogra, S., and Manji, H.K. (2007) Protein kinase C inhibition by tamoxifen antagonizes manic-like behavior in rats: implications for the development of novel therapeutics for bipolar disorder. Neuropsychobiology 55(3/4):123–131. Emamghoreishi, M., Schlichter, L., Li, P.P., Parikh, S., Sen, J., Kamble, A., and Warsh, J.J. (1997) High intracellular calcium concentrations in transformed lymphoblasts from subjects with bipolar I disorder. Am. J. Psychiatry 154:976–982. Ertley, R.N., Bazinet, R.P., Lee, H.J., Rapoport, S.I., and Rao, J.S. (2007) Chronic treatment with mood stabilizers increases membrane GRK3 in rat frontal cortex. Biol. Psychiatry 61:246–249.

28: GENES TO BEHAVIOR PATHWAYS OF BIPOLAR DISORDER Fadic, R., and Johns, D.R. (1996) Clinical spectrum of mitochondrial diseases. Semin. Neurol. 16:11–20. Ferrendelli, J.A., and Kinscherf, D.A. (1979) Inhibitory effects of anticonvulsant drugs on cyclic nucleotide accumulation in brain. Ann. Neurol. 5:533–538. Fields, A., Li, P.P., Kish, S.J., and Warsh, J.J. (1999) Increased cyclic AMP-dependent protein kinase activity in postmortem brain from patients with bipolar affective disorder. J. Neurochem. 73: 1704– 1710. Frazier, J.A., Ahn, M.S., DeJong, S., Bent, E.K., Breeze, J.L., and Giuliano, A.J. (2005) Magnetic resonance imaging studies in early-onset bipolar disorder: a critical review. Harv. Rev. Psychiatry 13:125–140. Friedman, E., Hoau Yan, W., Levinson, D., Connell, T.A., and Singh, H. (1993) Altered platelet protein kinase C activity in bipolar affective disorder, manic episode. Biol. Psychiatry 33:520–525. Garcia-Sevilla, J.A., Escriba, P.V., Ozaita, A., La Harpe, R., Walzer, C., Eytan, A., and Guimon, J. (1999) Up-regulation of immunolabeled alpha2A-adrenoceptors, Gi coupling proteins, and regulatory receptor kinases in the prefrontal cortex of depressed suicides. J. Neurochem. 72:282–291. Garcia-Sevilla, J.A., Walzer, C., Busquets, X., Escriba, P.V., Balant, L., and Guimon, J. (1997) Density of guanine nucleotide-binding proteins in platelets of patients with major depression: increased abundance of the G alpha i2 subunit and down-regulation by antidepressant drug treatment. Biol. Psychiatry 42:704–712. Giambalvo, C.T. (1992a) Protein kinase C and dopamine transport—1. Effects of amphetamine in vivo. Neuropharmacology 31:1201– 1210. Giambalvo, C.T. (1992b) Protein kinase C and dopamine transport—2. Effects of amphetamine in vitro. Neuropharmacology 31:1211– 1222. Goodwin, F.K., and Jamison, K.R. (2007) Manic-Depressive Illness: Bipolar Disorders and Recurrent Depression. New York: Oxford University Press. Gould, T.D., Einat, H., O’Donnell, K.C., Picchini, A.M., Schloesser, R.J., and Manji, H.K. (2007) B-catenin overexpression in the mouse brain phenocopies lithium-sensitive behaviors. Neuropsychopharmacology 32:2173–83. Gould, T.D., and Manji, H.K. (2002a) Signaling networks in the pathophysiology and treatment of mood disorders. J. Psychosom. Res. 53:687–697. Gould, T.D., and Manji, H.K. (2002b) The WNT signaling pathway in bipolar disorder. Neuroscientist 8:497–511. Gould, T.D., and Manji, H.K. (2005) Glycogen synthase kinase-3: a putative molecular target for lithium mimetic drugs. Neuropsychopharmacology 30:1223–1237. Hahn, C.G., Umapathy, Wang, H.Y., Koneru, R., Levinson, D.F., and Friedman, E. (2005) Lithium and valproic acid treatments reduce PKC activation and receptor-G protein coupling in platelets of bipolar manic patients. J. Psychiatr. Res. 39:355–363. Hajek, T., Carrey, N., and Alda, M. (2005) Neuroanatomical abnormalities as risk factors for bipolar disorder. Bipolar Disord. 7:393– 403. Hassel, B., Iversen, E.G., Gjerstad, L., and Tauboll, E. (2001) Upregulation of hippocampal glutamate transport during chronic treatment with sodium valproate. J. Neurochem. 77:1285–1292. Hough, C., Lu, S.J., Davis, C.L., Chuang, D.M., and Post, R.M. (1999) Elevated basal and thapsigargin-stimulated intracellular calcium of platelets and lymphocytes from bipolar affective disorder patients measured by a fluorometric microassay. Biol. Psychiatry 46:247–255. Huang, X., Wu, D.Y., Chen, G., Manji, H., and Chen, D.F. (2003) Support of retinal ganglion cell survival and axon regeneration by lithium through a Bcl-2-dependent mechanism. Invest. Ophthalmol. Vis. Sci. 44:347–354. Iwahana, E., Akiyama, M., Miyakawa, K., Uchida, A., Kasahara, J., Fukunaga, K., Hamada, T., et al. (2004) Effect of lithium on the circadian rhythms of locomotor activity and glycogen synthase

409

kinase-3 protein expression in the mouse suprachiasmatic nuclei. Eur. J. Neurosci. 19:2281–2287. Johnsson, A., Pflug, B., Engelmann, W., and Klemke, W. (1979) Effect of lithium carbonate on circadian periodicity in humans. Pharmakopsychiatr. Neuropsychopharmakol. 12:423 – 425. Johnston-Wilson, N.L., Sims, C.D., Hofmann, J.P., Anderson, L., Shore, A.D., Torrey, E.F., and Yolken, R.H. (2000) Diseasespecific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder. The Stanley Neuropathology Consortium. Mol. Psychiatry 5:142–149. Jolma, I.W., Falkeid, G., Bamerni, M., and Ruoff, P. (2006) Lithium leads to an increased FRQ protein stability and to a partial loss of temperature compensation in the Neurospora circadian clock. J. Biol. Rhythms 21:327–334. Jope, R.S. (1999) A bimodal model of the mechanism of action of lithium. Mol. Psychiatry 4:21–25. Jope, R.S., and Roh, M.S. (2006) Glycogen synthase kinase-3 (GSK3) in psychiatric diseases and therapeutic interventions. Curr. Drug Targets 7:1421–1434. Jope, R.S., Song, L., Li, P.P., Young, L.T., Kish, S.J., Pacheco, M.A., and Warsh, J.J. (1996) The phosphoinositide signal transduction system is impaired in bipolar affective disorder brain. J. Neurochem. 66:2402–2409. Jope, R.S., and Williams, M.B. (1994) Lithium and brain signal transduction systems. Biochem. Pharmacol. 47:429–441. Kakiuchi, C., Iwamoto, K., Ishiwata, M., Bundo, M., Kasahara, T., Kusumi, I., Tsujita, T., et al. (2003) Impaired feedback regulation of XBP1 as a genetic risk factor for bipolar disorder. Nat. Genet. 35:171–175. Kaladchibachi, S.A., Doble, B., Anthopoulos, N., Woodgett, J.R., and Manoukian, A.S. (2007) Glycogen synthase kinase 3, circadian rhythms, and bipolar disorder: a molecular link in the therapeutic action of lithium. J. Circadian Rhythms 5:3. Karege, F., Schwald, M., Papadimitriou, P., Lachausse, C., and Cisse, M. (2004) The cAMP-dependent protein kinase A and brainderived neurotrophic factor expression in lymphoblast cells of bipolar affective disorder. J. Affect. Disord. 79:187–192. Kato, T. (2007) Molecular genetics of bipolar disorder and depression. Psychiatry Clin. Neurosci. 61:3–19. Kato, T., Ishiwata, M., Mori, K., Washizuka, S., Tajima, O., Akiyama, T., and Kato, N. (2003) Mechanisms of altered Ca2+ signalling in transformed lymphoblastoid cells from patients with bipolar disorder. Int. J. Neuropsychopharmacol 6:379–389. Kato, T., and Kato, N. (2000) Mitochondrial dysfunction in bipolar disorder. Bipolar Disord. 2:180–190. Keck, P.E., Jr., Mintz, J., McElroy, S.L., Freeman, M.P., Suppes, T., Frye, M.A., Altshuler, L.L., et al. (2006) Double-blind, randomized, placebo-controlled trials of ethyl-eicosapentanoate in the treatment of bipolar depression and rapid cycling bipolar disorder. Biol. Psychiatry 60:1020–1022. Kempermann, G. (2002) Why new neurons? Possible functions for adult hippocampal neurogenesis. J. Neurosci. 22:635–638. Kim, J.S., Chang, M.Y., Yu, I.T., Kim, J.H., Lee, S.H., Lee, Y.S., and Son, H. (2004) Lithium selectively increases neuronal differentiation of hippocampal neural progenitor cells both in vitro and in vivo. J. Neurochem. 89:324–336. Klein, P.S., and Melton, D.A. (1996) A molecular mechanism for the effect of lithium on development. Proc. Natl. Acad. Sci. USA 93: 8455–8459. Konradi, C., Eaton, M., MacDonald, M.L., Walsh, J., Benes, F.M., and Heckers, S. (2004) Molecular evidence for mitochondrial dysfunction in bipolar disorder. Arch. Gen. Psychiatry 61:300–308. Kuhn, H.G., Biebl, M., Wilhelm, D., Li, M., Friedlander, R.M., and Winkler, J. (2005) Increased generation of granule cells in adult Bcl-2-overexpressing mice: a role for cell death during continued hippocampal neurogenesis. Eur. J. Neurosci. 22:1907–1915. Kulkarni, J., Garland, K.A., Scaffidi, A., Headey, B., Anderson, R., de Castella, A., Fitzgerald, P., et al. (2006) A pilot study of hormone

410

MOOD DISORDERS

modulation as a new treatment for mania in women with bipolar affective disorder. Psychoneuroendocrinology 31:543–547. Künig, G., Niedermeyer, B., Deckert, J., Gsell, W., Ransmayr, G., and Riederer, P. (1998) Inhibition of [3H]alpha-amino-3-hydroxy5-methyl-4-isoxazole-propionic acid [AMPA] binding by the anticonvulsant valproate in clinically relevant concentrations: an autoradiographic investigation in human hippocampus. Epilepsy Res. 31:153–157. Laeng, P., Pitts, R.L., Lemire, A.L., Drabik, C.E., Weiner, A., Tang, H., Thyagarajan, R., et al. (2004) The mood stabilizer valproic acid stimulates GABA neurogenesis from rat forebrain stem cells. J. Neurochem. 91:238–251. Lai, J.S., Zhao, C., Warsh, J.J., and Li, P.P. (2006) Cytoprotection by lithium and valproate varies between cell types and cellular stresses. Eur. J. Pharmacol. 539:18–26. Lenox, R.H., Watson, D.G., Patel, J., and Ellis, J. (1992) Chronic lithium administration alters a prominent PKC substrate in rat hippocampus. Brain Res. 570:333–340. Lewin, E., and Bleck, V. (1977) Cyclic AMP accumulation in cerebral cortical slices: effect of carbamazepine, phenobarbital, and phenytoin. Epilepsia 18:237–242. Li, R., and El-Mallahk, R.S. (2000) A novel evidence of different mechanisms of lithium and valproate neuroprotective action on human SY5Y neuroblastoma cells: caspase-3 dependency. Neurosci. Lett. 294:147–150. Li, X., Bijur, G.N., and Jope, R.S. (2002) Glycogen synthase kinase3beta, mood stabilizers, and neuroprotection. Bipolar Disord. 4: 137–144. Loscher, W. (1999) Valproate: a reappraisal of its pharmacodynamic properties and mechanisms of action. Prog. Neurobiol. 58:31–59. Lowther, S., Crompton, M.R., Katona, C.L., and Horton, R.W. (1996) GTP gamma S and forskolin-stimulated adenylyl cyclase activity in post-mortem brain from depressed suicides and controls. Mol. Psychiatry 1:470– 477. MacQueen, G.M., Campbell, S., McEwen, B.S., Macdonald, K., Amano, S., Joffe, R. T., Nahmias, C., et al. (2003) Course of illness, hippocampal function, and hippocampal volume in major depression. Proc. Natl. Acad. Sci. USA 100:1387–1392. Manji, H.K., and Chen, G. (2000) Post-receptor signaling pathways in the pathophysiology and treatment of mood disorders. Curr. Psychiatry Rep. 2:479–489. Manji, H.K., Chen, G., Shimon, H., Hsiao, J.K., Potter, W.Z., and Belmaker, R.H. (1995) Guanine nucleotide-binding proteins in bipolar affective disorder. Effects of long-term lithium treatment. Arch. Gen. Psychiatry 52:135–144. Manji, H.K., Drevets, W.C., and Charney, D.S. (2001) The cellular neurobiology of depression. Nat. Med. 7:541–547. Manji, H.K., Etcheberrigaray, R., Chen, G., and Olds, J.L. (1993) Lithium decreases membrane-associated protein kinase C in hippocampus: selectivity for the alpha isozyme. J. Neurochem. 61: 2303–2310. Manji, H.K., and Lenox, R.H. (1999) Ziskind-Somerfeld Research Award. Protein kinase C signaling in the brain: molecular transduction of mood stabilization in the treatment of manic-depressive illness. Biol. Psychiatry 46:1328–1351. Manji, H. K., and Lenox, R.H. (2000a) The nature of bipolar disorder. J. Clin. Psychiatry 61(Supp 13):42–57. Manji, H.K., and Lenox, R.H. (2000b) Signaling: cellular insights into the pathophysiology of bipolar disorder. Biol. Psychiatry 48: 518–530. Manji, H.K., Moore, G.J., and Chen, G. (2000) Lithium up-regulates the cytoprotective protein Bcl-2 in the CNS in vivo: a role for neurotrophic and neuroprotective effects in manic depressive illness. J. Clin. Psychiatry 61(Suppl 9):82–96. Manji, H.K., Quiroz, J.A., Sporn, J., Payne, J.L., Denicoff, K., Gray, A., Zarate, C. A., Jr., et al. (2003) Enhancing neuronal plasticity and cellular resilience to develop novel, improved therapeutics for difficult-to-treat depression. Biol. Psychiatry 53:707–742.

Martinek, S., Inonog, S., Manoukian, A.S., and Young, M.W. (2001) A role for the segment polarity gene shaggy/GSK-3 in the Drosophila circadian clock. Cell 105:769–779. McEwen, B.S. (1999) Stress and hippocampal plasticity. Annu. Rev. Neurosci. 22:105–122. Miguel-Hidalgo, J.J., Baucom, C., Dilley, G., Overholser, J.C., Meltzer, H.Y., Stockmeier, C.A., and Rajkowska, G. (2000) Glial fibrillary acidic protein immunoreactivity in the prefrontal cortex distinguishes younger from older adults in major depressive disorder. Biol. Psychiatry 48:861–873. Mizrahi, C., Stojanovic, A., Urbina, M., Carreira, I., and Lima, L. (2004) Differential cAMP levels and serotonin effects in blood peripheral mononuclear cells and lymphocytes from major depression patients. Int. Immunopharmacol. 4:1125–1133. Moore, C.M., Biederman, J., Wozniak, J., Mick, E., Aleardi, M., Wardrop, M., Dougherty, M., et al. (2006) Differences in brain chemistry in children and adolescents with attention deficit hyperactivity disorder with and without comorbid bipolar disorder: a proton magnetic resonance spectroscopy study. Am. J. Psychiatry 163:316–318. Moore, G.J., Bebchuk, J.M., Hasanat, K., Chen, G., Seraji-Bozorgzad, N., Wilds, I.B., Faulk, M.W., et al. (2000) Lithium increases Nacetyl-aspartate in the human brain: in vivo evidence in support of bcl-2’s neurotrophic effects? Biol. Psychiatry 48:1–8. Moore, G.J., Bebchuk, J.M., Parrish, J.K., Faulk, M.W., Arfken, C.L., Strahl-Bevacqua, J., and Manji, H.K. (1999) Temporal dissociation between lithium-induced changes in frontal lobe myo-inositol and clinical response in manic-depressive illness. Am. J. Psychiatry 156:1902–1908. Moore, G.J., Bebchuk, J.M., Wilds, I.B., Chen, G., and Manji, H.K. (2000) Lithium-induced increase in human brain grey matter. Lancet 356:1241–1242. Mora, A., Gonzalez-Polo, R.A., Fuentes, J.M., Soler, G., and Centeno, F. (1999) Different mechanisms of protection against apoptosis by valproate and Li+. Eur. J. Biochem. 266:886–891. Mork, A., Geisler, A., and Hollund, P. (1992) Effects of lithium on second messenger systems in the brain. Pharmacol. Toxicol. 71 (Suppl 1):4 –17. Nakamura, S. (1990) Antidepressants induce regeneration of catecholaminergic axon terminals in the rat cerebral cortex. Neurosci. Lett. 111:64–68. Nemets, B., Stahl, Z., and Belmaker, R. H. (2002) Addition of omega3 fatty acid to maintenance medication treatment for recurrent unipolar depressive disorder. Am. J. Psychiatry 159:477– 479. Nibuya, M., Nestler, E.J., and Duman, R.S. (1996) Chronic antidepressant administration increases the expression of cAMP response element binding protein (CREB) in rat hippocampus. J. Neurosci. 16:2365–2372. Öngür, D., Drevets, W.C., and Price, J.L. (1998) Glial reduction in the subgenual prefrontal cortex in mood disorders. Proc. Natl. Acad. Sci. USA 95:13290–13295. Ozaki, N., and Chuang, D.M. (1997) Lithium increases transcription factor binding to AP-1 and cyclic AMP-responsive element in cultured neurons and rat brain. J. Neurochem. 69:2336–2344. Palmer, G.C., Jones, D.J., Medina, M.A., and Stavinoha, W.B. (1979) Anticonvulsant drug actions on in vitro and in vivo levels of cyclic AMP in the mouse brain. Epilepsia 20:95–104. Pandey, G.N., Dwivedi, Y., Pandey, S.C., Conley, R.R., Roberts, R.C., and Tamminga, C.A. (1997) Protein kinase C in the postmortem brain of teenage suicide victims. Neurosci. Lett. 228:111–114. Pandey, G.N., Ren, X., Dwivedi, Y., and Pavuluri, M.N. (2007) Decreased protein kinase C (PKC) in platelets of pediatric bipolar patients: Effect of treatment with mood stabilizing drugs. J. Psychiatr. Res. 42(2):106–116. Peet, M., and Horrobin, D.F. (2002) A dose-ranging study of the effects of ethyl-eicosapentaenoate in patients with ongoing depression despite apparently adequate treatment with standard drugs. Arch. Gen. Psychiatry 59:913–919.

28: GENES TO BEHAVIOR PATHWAYS OF BIPOLAR DISORDER Perez, J., Tardito, D., Mori, S., Racagni, G., Smeraldi, E., and Zanardi, R. (1999) Abnormalities of cyclic adenosine monophosphate signaling in platelets from untreated patients with bipolar disorder. Arch. Gen. Psychiatry 56:248–253. Pettmann, B., and Henderson, C.E. (1998) Neuronal cell death. Neuron 20:633–647. Post, R.M., Ballenger, J.C., Uhde, T.W., Smith, C., Rubinow, D.R., and Bunney, W.E., Jr. (1982) Effect of carbamazepine on cyclic nucleotides in CSF of patients with affective illness. Biol. Psychiatry 17:1037–1045. Post, R.M., Leverich, G.S., Altshuler, L.L., Frye, M.A., Suppes, T.M., Keck, P.E., Jr., McElroy, S.L., et al. (2003) An overview of recent findings of the Stanley Foundation Bipolar Network (Part I). Bipolar Disord. 5:310–319. Rahman, S., Li, P.P., Young, L.T., Kofman, O., Kish, S.J., and Warsh, J.J. (1997) Reduced [3H]cyclic AMP binding in postmortem brain from subjects with bipolar affective disorder. J. Neurochem. 68: 297–304. Rajkowska, G. (2002) Cell pathology in mood disorders. Semin. Clin. Neuropsychiatry 7:281–292. Rajkowska, G., Miguel-Hidalgo, J.J., Wei, J., Dilley, G., Pittman, S.D., Meltzer, H.Y., Overholser, J.C., et al. (1999) Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression. Biol. Psychiatry 45:1085–1098. Ram, A., Guedj, F., Cravchik, A., Weinstein, L., Cao, Q., Badner, J.A., Goldin, L.R., et al. (1997) No abnormality in the gene for the G protein stimulatory alpha subunit in patients with bipolar disorder. Arch. Gen. Psychiatry 54:44 – 48. Ren, M., Leng, Y., Jeong, M., Leeds, P.R., and Chuang, D.M. (2004) Valproic acid reduces brain damage induced by transient focal cerebral ischemia in rats: potential roles of histone deacetylase inhibition and heat shock protein induction. J. Neurochem. 89: 1358–1367. Risby, E.D., Hsiao, J.K., Manji, H.K., Bitran, J., Moses, F., Zhou, D.F., and Potter, W.Z. (1991) The mechanisms of action of lithium. II. Effects on adenylate cyclase activity and beta-adrenergic receptor binding in normal subjects. Arch. Gen. Psychiatry 48:513–524. Roh, M.S., Kang, U.G., Shin, S.Y., Lee, Y.H., Jung, H.Y., Juhnn, Y.S., and Kim, Y.S. (2003) Biphasic changes in the Ser-9 phosphorylation of glycogen synthase kinase-3beta after electroconvulsive shock in the rat brain. Prog. Neuropsychopharmacol. Biol. Psychiatry 27:1–5. Ryan, M.M., Lockstone, H.E., Huffaker, S.J., Wayland, M.T., Webster, M.J., and Bahn, S. (2006) Gene expression analysis of bipolar disorder reveals downregulation of the ubiquitin cycle and alterations in synaptic genes. Mol. Psychiatry 11:965–978. Ryves, W.J., and Harwood, A.J. (2001) Lithium inhibits glycogen synthase kinase-3 by competition for magnesium. Biochem. Biophys. Res. Commun. 280:720–725. Sanacora, G., Kendell, S.F., Levin, Y., Simen, A.A., Fenton, L.R., Coric, V., and Krystal, J.H. (2007) Preliminary evidence of riluzole efficacy in antidepressant-treated patients with residual depressive symptoms. Biol. Psychiatry 61:822–825. Santarelli, L., Saxe, M., Gross, C., Surget, A., Battaglia, F., Dulawa, S., Weisstaub, N., et al. (2003) Requirement of hippocampal neurogenesis for the behavioral effects of antidepressants. Science 301:805–809. Sapolsky, R.M. (2000) Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Arch. Gen. Psychiatry 57:925–935. Sassi, R.B., Stanley, J.A., Axelson, D., Brambilla, P., Nicoletti, M.A., Keshavan, M.S., Ramos, R.T., et al. (2005) Reduced NAA levels in the dorsolateral prefrontal cortex of young bipolar patients. Am. J. Psychiatry 162:2109–2115. Schreiber, G., Avissar, S., Danon, A., and Belmaker, R.H. (1991) Hyperfunctional G proteins in mononuclear leukocytes of patients with mania. Biol. Psychiatry 29:273–280. Segal, R.A., and Greenberg, M.E. (1996) Intracellular signaling pathways activated by neurotrophic factors. Annu. Rev. Neurosci. 19:463– 489.

411

Seung Kim, H.F., Weeber, E.J., Sweatt, J.D., Stoll, A.L., and Marangell, L.B. (2001) Inhibitory effects of omega-3 fatty acids on protein kinase C activity in vitro. Mol. Psychiatry 6:246–248. Sheline, Y.I., Gado, M.H., and Kraemer, H.C. (2003) Untreated depression and hippocampal volume loss. Am. J. Psychiatry 160: 1516–1518. Sheline, Y.I., Wang, P.W., Gado, M.H., Csernansky, J.G., and Vannier, M.W. (1996) Hippocampal atrophy in recurrent major depression. Proc. Natl. Acad. Sci. USA 93:3908–3913. Shim, S.S., Hammonds, M.D., Ganocy, S.J., and Calabrese, J.R. (2007) Effects of sub-chronic lithium treatment on synaptic plasticity in the dentate gyrus of rat hippocampal slices. Prog. Neuropsychopharmacol. Biol. Psychiatry 31:343–347. Shimon, H., Agam, G., Belmaker, R.H., Hyde, T.M., and Kleinman, J.E. (1997) Reduced frontal cortex inositol levels in postmortem brain of suicide victims and patients with bipolar disorder. Am. J. Psychiatry 154:1148–1150. Soares, J.C., Dippold, C.S., Wells, K.F., Frank, E., Kupfer, D.J., and Mallinger, A.G. (2001) Increased platelet membrane phosphatidylinositol-4,5-bisphosphate in drug-free depressed bipolar patients. Neurosci. Lett. 299:150–152. Soares, J.C., and Young, A. (2007) Bipolar Disorder: Basic Mechanisms and Therapeutic Implications, 2nd edition.. New York: Informa Healthcare. Spiegel, A. (1998) G Proteins, Receptors, and Disease. Totowa, NJ: Humana Press. Spleiss, O., van Calker, D., Scharer, L., Adamovic, K., Berger, M., and Gebicke-Haerter, P.J. (1998) Abnormal G protein alpha(s) and alpha(i2)-subunit mRNA expression in bipolar affective disorder. Mol. Psychiatry 3:512–520. Stewart, R.J., Chen, B., Dowlatshahi, D., MacQueen, G.M., and Young, L.T. (2001) Abnormalities in the cAMP signaling pathway in post-mortem brain tissue from the Stanley Neuropathology Consortium. Brain Res. Bull. 55:625–629. Stockmeier, C.A., Mahajan, G.J., Konick, L.C., Overholser, J.C., Jurjus, G.J., Meltzer, H.Y., Uylings, H.B., et al. (2004) Cellular changes in the postmortem hippocampus in major depression. Biol. Psychiatry 56:640–650. Stoll, A.L., Severus, W.E., Freeman, M.P., Rueter, S., Zboyan, H.A., Diamond, E., Cress, K.K., et al. (1999) Omega 3 fatty acids in bipolar disorder: a preliminary double-blind, placebo-controlled trial. Arch. Gen. Psychiatry 56:407– 412. Strakowski, S.M., Adler, C.M., and DelBello, M.P. (2002) Volumetric MRI studies of mood disorders: do they distinguish unipolar and bipolar disorder? Bipolar Disord. 4:80–88. Svenningsson, P., Tzavara, E.T., Witkin, J.M., Fienberg, A.A., Nomikos, G.G., and Greengard, P. (2002) Involvement of striatal and extrastriatal DARPP-32 in biochemical and behavioral effects of fluoxetine (Prozac). Proc. Natl. Acad. Sci. USA 99:3182–3187. Tardito, D., Mori, S., Racagni, G., Smeraldi, E., Zanardi, R., and Perez, J. (2003) Protein kinase A activity in platelets from patients with bipolar disorder. J. Affect. Disord. 76:249–253. Tardito, D., Perez, J., Tiraboschi, E., Musazzi, L., Racagni, G., and Popoli, M. (2006) Signaling pathways regulating gene expression, neuroplasticity, and neurotrophic mechanisms in the action of antidepressants: a critical overview. Pharmacol. Rev. 58:115–134. Tardito, D., Tiraboschi, E., Kasahara, J., Racagni, G., and Popoli, M. (2006) Reduced CREB phosphorylation after chronic lithium treatment is associated with down-regulation of CaM kinase IV in rat hippocampus. Int. J. Neuropsychopharmacol. 10(4):491– 496. Thoenen, H. (1995) Neurotrophins and neuronal plasticity. Science 270:593–598. Thome, J., Sakai, N., Shin, K., Steffen, C., Zhang, Y.J., Impey, S., Storm, D., et al. (2000) cAMP response element-mediated gene transcription is upregulated by chronic antidepressant treatment. J. Neurosci. 20:4030– 4036. Tiraboschi, E., Tardito, D., Kasahara, J., Moraschi, S., Pruneri, P., Gennarelli, M., Racagni, G., et al. (2004) Selective phosphorylation

412

MOOD DISORDERS

of nuclear CREB by fluoxetine is linked to activation of CaM kinase IV and MAP kinase cascades. Neuropsychopharmacology 29:1831–1840. Tkachev, D., Mimmack, M.L., Ryan, M.M., Wayland, M., Freeman, T., Jones, P.B., Starkey, M., et al. (2003) Oligodendrocyte dysfunction in schizophrenia and bipolar disorder. Lancet 362:798–805. Tsai, G., and Coyle, J.T. (1995) N-acetylaspartate in neuropsychiatric disorders. Prog. Neurobiol. 46:531–540. Tsankova, N.M., Berton, O., Renthal, W., Kumar, A., Neve, R.L., and Nestler, E.J. (2006) Sustained hippocampal chromatin regulation in a mouse model of depression and antidepressant action. Nat. Neurosci. 9:519–525. Ueda, Y., and Willmore, L.J. (2000) Molecular regulation of glutamate and GABA transporter proteins by valproic acid in rat hippocampus during epileptogenesis. Exp. Brain Res. 133:334 –339. Uranova, N., Orlovskaya, D., Vikhreva, O., Zimina, I., Kolomeets, N., Vostrikov, V., and Rachmanova, V. (2001) Electron microscopy of oligodendroglia in severe mental illness. Brain Res. Bull. 55:597–610. van Calker, D., and Belmaker, R.H. (2000) The high affinity inositol transport system--implications for the pathophysiology and treatment of bipolar disorder. Bipolar Disord. 2:102–107. van Calker, D., Steber, R., Klotz, K.N., and Greil, W. (1991) Carbamazepine distinguishes between adenosine receptors that mediate different second messenger responses. Eur. J. Pharmacol. 206: 285–290. Vollmayr, B., Mahlstedt, M.M., and Henn, F.A. (2007) Neurogenesis and depression: what animal models tell us about the link. Eur. Arch. Psychiatry Clin. Neurosci. 257(5):300 –303. Wang, H.Y., and Friedman, E. (1996) Enhanced protein kinase C activity and translocation in bipolar affective disorder brains. Biol. Psychiatry 40:568–575. Wang, H.Y., and Friedman, E. (2001) Increased association of brain protein kinase C with the receptor for activated C kinase-1 (RACK1) in bipolar affective disorder. Biol. Psychiatry 50:364–370. Wang, J.F., Asghari, V., Rockel, C., and Young, L.T. (1999) Cyclic AMP responsive element binding protein phosphorylation and DNA binding is decreased by chronic lithium but not valproate treatment of SH-SY5Y neuroblastoma cells. Neuroscience 91: 771–776. Wang, J.-F., Young, L.T., Li, P.P., and Warsh, J.J. (1997) Signal transduction abnormalities in bipolar disorder. In: Joffe, R. T., ed. Bipolar Disorder: Biological Models and Their Clinical Application. New York: Dekker, pp. 41–79. Warsh, J., Young, L., and Li, P. (2000) Guanine nucleotide binding (G) protein disturbances. In: Belmaker, R., ed. Bipolar Affective Disorder in Bipolar Medications: Mechanisms of Action. Washington, DC: American Psychiatric Press, pp. 299–329. Watanabe, Y., Gould, E., Daniels, D.C., Cameron, H., and McEwen, B.S. (1992) Tianeptine attenuates stress-induced morphological changes in the hippocampus. Eur. J. Pharmacol. 222:157–162. Watson, D.G., Watterson, J.M., and Lenox, R.H. (1998) Sodium valproate down-regulates the myristoylated alanine-rich C kinase substrate (MARCKS) in immortalized hippocampal cells: a property of protein kinase C-mediated mood stabilizers. J. Pharmacol. Exp. Ther. 285:307–316. Willmroth, F., Drieling, T., Lamla, U., Marcushen, M., Wark, H.J., and van Calker, D. (2007) Sodium-myo-inositol co-transporter (SMIT-1) mRNA is increased in neutrophils of patients with bipolar 1 disorder and down-regulated under treatment with mood stabilizers. Int. J. Neuropsychopharmacol. 10:63–71. Wozniak, J., Biederman, J., Mick, E., Waxmonsky, J., Hantsoo, L., Best, C., Cluette-Brown, J.E., et al. (2007) Omega-3 fatty acid

monotherapy for pediatric bipolar disorder: A prospective openlabel trial. Eur. Neuropsychopharmacol. 17:440– 447. Yamada, S., Yamamoto, M., Ozawa, H., Riederer, P., and Saito, T. (2003) Reduced phosphorylation of cyclic AMP-responsive element binding protein in the postmortem orbitofrontal cortex of patients with major depressive disorder. J. Neural. Transm. 110:671–680. Yazlovitskaya, E.M., Edwards, E., Thotala, D., Fu, A., Osusky, K.L., Whetsell, W.O., Jr., Boone, B., et al. (2006) Lithium treatment prevents neurocognitive deficit resulting from cranial irradiation. Cancer Res. 66:11179–11186. Yildiz, A., Demopulos, C.M., Moore, C.M., Renshaw, P.F., and Sachs, G.S. (2001) Effect of lithium on phosphoinositide metabolism in human brain: a proton decoupled (31)P magnetic resonance spectroscopy study. Biol. Psychiatry 50:3–7. Yoon, I.S., Li, P.P., Siu, K.P., Kennedy, J.L., Cooke, R.G., Parikh, S. V., and Warsh, J.J. (2001) Altered IMPA2 gene expression and calcium homeostasis in bipolar disorder. Mol. Psychiatry 6:678– 683. Young, L.T., Bezchlibnyk, Y.B., Chen, B., Wang, J.F., and MacQueen, G.M. (2004) Amygdala cyclic adenosine monophosphate response element binding protein phosphorylation in patients with mood disorders: effects of diagnosis, suicide, and drug treatment. Biol. Psychiatry 55:570 –577. Young, L.T., Li, P.P., Kamble, A., Siu, K.P., and Warsh, J.J. (1994) Mononuclear leukocyte levels of G proteins in depressed patients with bipolar disorder or major depressive disorder. Am. J. Psychiatry 151:594 –596. Young, L.T., Li, P.P., Kish, S.J., Siu, K.P., Kamble, A., Hornykiewicz, O., and Warsh, J.J. (1993) Cerebral cortex Gs alpha protein levels and forskolin-stimulated cyclic AMP formation are increased in bipolar affective disorder. J. Neurochem. 61:890–898. Yuan, P.X., Huang, L.D., Jiang, Y.M., Gutkind, J.S., Manji, H.K., and Chen, G. (2001) The mood stabilizer valproic acid activates mitogen-activated protein kinases and promotes neurite growth. J. Biol. Chem. 276:31674 –31683. Yucel, K., Taylor, V.H., McKinnon, M.C., Macdonald, K., Alda, M., Young, L.T., and Macqueen, G.M. (2007) Bilateral hippocampal volume increase in patients with bipolar disorder and short-term lithium treatment. Neuropsychopharmacology 33(2):361–367. Zarate, C.A., Jr., Singh, J.B., Carlson, P.J., Brutsche, N.E., Ameli, R., Luckenbaugh, D.A., Charney, D.S., et al. (2006) A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch. Gen. Psychiatry 63:856–864. Zarate, C.A., Jr., Singh, J.B., Carlson, P.J., Quiroz, J., Jolkovsky, L., Luckenbuagh, D., and Manji, H.K. (2007) Efficacy of a protein kinase c inhibitor (tamoxifen) in the treatment of acute mania: a pilot study. Bipolar Disord. 9(6):561–570. Zarate, C.A., Jr., Singh, J., and Manji, H.K. (2006) Cellular plasticity cascades: targets for the development of novel therapeutics for bipolar disorder. Biol. Psychiatry 59:1006–1020. Zhou, R., Gray, N.A., Yuan, P., Li, X., Chen, J., Chen, G., Damschroder-Williams, P., et al. (2005) The anti-apoptotic, glucocorticoid receptor cochaperone protein BAG-1 is a long-term target for the actions of mood stabilizers. J. Neurosci. 25:4493– 4502. Zill, P., Malitas, P.N., Bondy, B., Engel, R., Boufidou, F., Behrens, S., Alevizos, B.E., et al. (2003) Analysis of polymorphisms in the alpha-subunit of the olfactory G-protein Golf in lithium-treated bipolar patients. Psychiatr. Genet. 13:65–69. Zubenko, G.S., Hughes, H.B., 3rd, Stiffler, J.S., Brechbiel, A., Zubenko, W.N., Maher, B.S., and Marazita, M.L. (2003) Sequence variations in CREB1 cosegregate with depressive disorders in women. Mol. Psychiatry 8:611–618.

29 Neurochemical Theories of Depression: Preclinical Studies RONALD S. DUMAN

Preclinical and clinical studies suggest that the serotonin (5-HT) and norepinephrine (NE) neurotransmitter systems are involved in the treatment of depression. These studies have focused largely on levels of monoamines and their receptors and have led to several theories of depression, including the monoamine depletion and receptor sensitivity hypotheses. However, this work has not led to a unifying theory of antidepressant action. In addition, the pathophysiology of depression cannot be explained by simple dysregulation of 5-HT and/or NE neurotransmission. Recent advances in molecular and cellular neurobiology have provided new insights into the longterm adaptations that underlie the therapeutic actions of antidepressant treatments (Duman and Monteggia, 2006; Manji et al., 2001; Berton and Nestler, 2006). These studies have demonstrated that chronic antidepressant treatment regulates intracellular signal transduction pathways and expression of specific target genes. In combination with advances in our understanding of the neurobiology of stress, a primary cause of depression, this work is beginning to reveal potential molecular and anatomical sites that could contribute to the pathophysiology and treatment of depression. This chapter provides a short review of basic and clinical work regarding the role of 5-HT and NE neurotransmission in depression. Then advances in molecular and cellular neurobiology that demonstrate a role for the cyclic adenosine monophosphate (cAMP) intracellular signal transduction pathway and regulation of specific target genes, particularly brain-derived neurotrophic factor (BDNF) in the actions of antidepressant treatment, as well as stress, are discussed. There are many other neurotransmitters and signal molecules that have been studied, as well as others not yet identified, for their role in mood disorders, and there is not sufficient space to cover all of this work in this chapter. However, taken together these studies support an emerging hypothesis of how stress and other environmental insults can induce neuronal atrophy and how antidepressant treatment can reverse or block these damaging effects.

MONOAMINES AND DEPRESSION Monoamine Depletion and Depression A role for 5-HT and NE in depression was first suggested by the observation that pharmacological manipulation of monoamine levels could either induce or alleviate the symptoms of depression. For example, early clinical studies demonstrated that treatment with reserpine, which interferes with storage and thereby depletes monoamine levels (Fig. 29.1), can cause depression in a small percentage of individuals. This led to the hypothesis that depression results from reduced availability of 5-HT and/or NE (Bunney and Davis, 1965; Schildkraut, 1965; Coppen, 1967). The monoamine depletion hypothesis was further supported by the discovery that the prototypical antidepressant drugs, the tricyclic and MAO inhibitor antidepressants, acutely increase synaptic levels of monoamines (Fig. 29.1). The tricyclic antidepressant drugs inhibit the transporter-mediated reuptake of 5-HT and NE, one of the primary mechanisms for removal and inactivation of monoamines. Selective 5-HT reuptake inhibitors, including fluoxetine and sertraline, have been developed that lack many of the side effects of the early tricyclic antidepressants. The MAO inhibitor antidepressants block one of the primary enzymes responsible for the degradation of 5-HT and NE and thereby increase levels of monoamines. Although these observations suggest that monoamine levels are closely related to the cause and treatment of depression, additional paradigms for the depletion of 5-HT or NE suggest a more complex relationship (Shopsin et al., 1975; Delgado et al., 1994; Miller et al., 1996). Levels of 5-HT can be safely and significantly reduced by administration of an amino acid cocktail containing all essential amino acids except tryptophan, the precursor for 5-HT. Levels of NE can be reduced by administration of low doses of α-methyl-p-tyrosine (AMPT), a competitive inhibitor of tyrosine hydroxylase, the rate-limiting enzyme for the synthesis of NE. These paradigms have

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FIGURE 29.1 A model of the pre- and postsynaptic components of monoamine neurotransmission. 5-HT and NE neurotransmission is regulated at several levels, including the synthesis, storage, release, reuptake, and degradation of monoamines. Drugs that influence these sites can either decrease or increase synaptic levels of 5-HT and NE and can lead to depression, under certain conditions, or have antidepressant effects, respectively. The synthesis of 5-HT and NE can be inhibited by PCPA or AMPT, respectively. These agents act as competitive inhibitors of the 5-HT and NE rate limiting synthetic enzymes, tryptophan hydroxylase and tyrosine hydroxylase, respectively. The storage of monoamines in synaptic vesicles is disrupted by reserpine. Monoamines released into the synapse activate pre-and postsynaptic receptor binding sites. Postsynaptic 5-HT receptors include 5-HT1A, 5-HT2A, and 5-HT4,6,7, and NE receptors include β1AR, β2AR, and α1AR; this represents a partial list of the many 5-HT and NE receptor subtypes. Presynaptic autoreceptors, including 5-HT1A and 5-HT1B

(5-HT1A is localized to cell bodies and 5-HT1B to terminals) and α2AR, inhibit the firing rate of monoamine neurons. The human homologue of rodent 5-HT1B is the 5-HT1D receptor. Pindolol is an antagonist that has some selectivity for 5-HT1A receptors located on 5-HT cell bodies. Yohimbine is an antagonist for the presynaptic α2AR. Monoamine function is terminated by reuptake into neurons and glia and enzymatic neurotransmitter degradation. Reuptake is mediated by high affinity transporters for 5-HT (SERT) and NE (NET) that are inhibited by the antidepressants fluoxetine and desipramine, respectively. MAO, localized to mitochondrial membranes, catalyzes the degradation of 5-HT and NE, and is the site of action for the MAOI antidepressants. Degradation of monoamines is also catalyzed by COMT that has an extracellular location (not shown). 5HT: serontonin; NE: norepinephrine; PCPA: p-chlorophenylalanine; AMPT: α-methyl-para-tyrosine; MAO: Monoamine oxidase; MAOI: monoamine oxidase inhibitor; COMT: catechol-O-methyltransferase.

been used to examine the role of 5-HT and NE in normal patients and drug-remitted individuals who are depressed. The results are summarized as follows:

Time Lag for the Therapeutic Action of Antidepressant Treatments

• Depression is not induced in normal patients upon depletion of either 5-HT and/or NE with these paradigms, including normal patients receiving antidepressant treatment. • Patients who are depressed and being treated with 5-HT selective reuptake inhibitors (SSRIs), but not NE selective reuptake inhibitors (NSRIs), suffer a brief relapse upon depletion of 5-HT. • Conversely, patients who are depressed being treated with NSRIs, but not SSRIs, suffer a brief relapse upon depletion of NE. • Patients who are depressed, who are not medicated, are not made worse by depletion of either 5-HT or NE. These studies indicate that monoamine depletion alone is not sufficient to cause depression in normal patients. However, when patients are successfully treated with either 5-HT or NE selective reuptake inhibitors they become vulnerable to depletion of the corresponding monoamine, suggesting that 5-HT and NE are involved in the maintenance of the antidepressant response.

In addition to the depletion studies, the time course for the therapeutic action of antidepressant treatments provides additional evidence that there is a complex relationship between monoamines and depression. Although antidepressant drugs rapidly increase the levels of monoamines (that is, within days) the therapeutic action of these treatments is dependent on chronic administration (that is, several weeks or even months). One hypothesis to explain this delay is that the firing rate of monoamine neurons is reduced by inhibitory autoreceptors that become activated when levels of monoamines are increased by an antidepressant treatment. Electrophysiological studies in rodents support this possibility, demonstrating that the firing rate of 5-HT neurons is reduced by administration of certain antidepressants (Blier and de Montigny, 1994). In addition, inhibition of cell firing gradually diminishes with time, consistent with the time lag for the onset of the therapeutic actions of antidepressant treatment. Clinical studies suggest that treatment with a 5-HT1A antagonist (for example, pindolol), which blocks the autoreceptor inhibition of cell firing, may hasten the response time to a 5-HT selective reuptake inhibitor (Artigas et al., 1994). How-

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ever, inhibition of cell firing may only account for a fraction of the time lag. In addition, administration of tryptophan with a MAO inhibitor, a treatment known to rapidly elevate levels of 5-HT and induce a 5-HT behavioral syndrome, does not alleviate depressive symptoms (Price et al., 1985). Finally, administration of an α 2-adrenergic antagonist, which blocks NE autoreceptor inhibition of cell firing, has not proven effective in reducing the time lag for antidepressant drugs that influence this monoamine system (Heninger and Charney, 1987). Neuroplasticity and Antidepressant Treatment Another hypothesis to explain the delayed time course is that neuronal adaptations to the elevation of monoamines, which occurs over time, are required for the therapeutic action of antidepressants. Adaptation or neuroplasticity could also explain why the maintenance of antidepressant treatment, discussed above, is dependent on the presence of monoamines (for example, the antidepressant-induced neuronal adaptation could also mediate monoamine neurotransmission). Neuroplasticity has been studied in cellular and behavioral models of learning and memory but can also be viewed as a fundamental process that allows neuronal systems to respond to the constant influx of all types of stimuli, including environmental and endocrine, as well as pharmacological treatment (see Chapter 5). The mechanisms underlying neuroplasticity involve receptor-coupled intracellular signal transduction pathways and neuronal gene expression. Studies of these pathways have led to alternative theories of the mechanism of action of antidepressant treatment, as well as the pathophysiology of depression and are discussed in some detail below. MONOAMINE RECEPTOR SENSITIVITY AND DEPRESSION Release of 5-HT and NE into the synapse leads to activation of pre- and postsynaptic receptor subtypes (Fig. 29.1). Sustained release and/or elevation of monoamines by antidepressant treatment results in continued activation of these receptor sites. One proximal adaptive response to sustained activation is down-regulation of monoamine receptors. Indeed, antidepressant treatment is reported to down-regulate levels of several 5-HT and NE receptor subtypes. Listed below is a brief overview of the major monoamine receptor systems that are regulated by antidepressant treatment.

β-adrenergic receptor (βAR) Sensitivity and Depression Chronic antidepressant treatment is known to downregulate β -adrenergic receptor (β1AR) ligand binding sites

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in limbic brain regions, such as cerebral cortex and hippocampus (Vetulani and Sulser, 1975; Banerjee et al., 1977). This led to the hypothesis that the therapeutic action of antidepressant treatment is mediated by downregulation of βAR sites and that up-regulation of these receptors may lead to depression (Sulser et al., 1978; Charney et al., 1981). However, there are several problems with this hypothesis. First, levels of βAR ligand binding sites are not down-regulated by all antidepressants (Charney et al., 1981). This could mean that the action of different antidepressants is mediated by different receptors, or that other receptor sites are more relevant to the action of antidepressant treatments. Second, the time delay for down-regulation of βAR binding sites is more rapid than the therapeutic onset of these treatments (Riva and Creese, 1989). Third, inhibition of βARs by treatment with a selective antagonist is not an effective treatment for depression: in fact βAR antagonists are reported to produce depression in some individuals (Paykel et al., 1982; Avorn et al., 1986), and βAR agonists have antidepressant effects in behavioral models of depression (O’Donnell, 1993). Moreover, activation or facilitation of βAR function by administration of thyroid hormone or a specific receptor agonist can have antidepressant efficacy in some patients (Goodwin et al., 1982). Taken together, these findings indicate that βAR downregulation does not mediate the therapeutic action of antidepressants. In fact, the results are more consistent with the possibility that inhibition or down-regulation of βAR may actually contribute to a depressive phenotype. 5-HT2A Receptor-Sensitivity and Depression Another monoamine receptor that is influenced by antidepressant treatment is the 5-HT2 receptor (Peroutka and Snyder, 1980). There are two 5-HT2 receptor subtypes expressed in brain, 5-HT2A and 5-HT2C. The 5-HT2A receptor subtype is more widely distributed and is expressed at relatively higher levels in most limbic brain regions. The 5-HT2A receptor subtype is also the primary receptor site for hallucinogenic compounds. Antidepressant treatments are reported to down-regulate the expression of 5-HT2A receptors in rat brain, and brainimaging studies demonstrate that levels of this receptor are altered in patients who are depressed (Heninger and Charney, 1987). In addition, several antidepressant drugs, including tricyclic antidepressants and the atypical antidepressant, mianserin, bind with relatively high affinity to 5-HT2A receptor receptors. However, the 5-HT2A receptor sensitivity hypothesis has many of the same problems as the βAR hypothesis: not all antidepressants decrease 5-HT2A receptor binding; in fact, electroconvulsive seizures increase receptor levels; 5-HT2A receptor binding is rapidly decreased after a few days of antidepressant treatment; and 5-HT2A receptor antago-

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nists when administered alone are not effective antidepressants (Heninger and Charney, 1987; Butler et al., 1993). However, recent studies demonstrate that administration of a 5-HT2A antagonist, such as risperidone or the atypical antipsychotics clozapine or olanzapine, to patients who are not responding to an SSRI can result in treatment response. Taken together these findings suggest that 5-HT2A receptor antagonism alone is not sufficient to produce an antidepressant response but can improve treatment response to a SSRI. In addition, a polymorphism in the 5-HT2A gene was associated with treatment outcome in the STAR*D study (McMahon et al., 2006).

One problem with the 5-HT1A receptor hypothesis is that direct acting 5-HT1A receptor agonists are not very effective antidepressants. However, the drugs tested thus far are partial agonists (for example, buspirone), and it is possible that a full 5-HT1A receptor agonist would have better clinical efficacy. This hypothesis will require the testing of full 5-HT1A agonists. Another possibility is that increased 5-HT1A neurotransmission is necessary, but not sufficient, for antidepressant efficacy, and that activation of an additional 5-HT receptor(s) or other signaling factors are required.

5-HT1A Receptor Sensitivity and Depression

An Alternative Hypothesis for Adaptation of Receptor Sensitivity

Studies of the 5-HT1A receptor have provided evidence that this receptor subtype also plays a role in the action of antidepressant treatments (Heninger and Charney, 1987; Butler et al., 1993). Results from electrophysiological studies indicate that chronic antidepressant treatment increases postsynaptic 5-HT1A receptor neurotransmission in the hippocampus. The proposed mechanisms for increased 5-HT1A receptor transmission differ for different classes of antidepressant drugs. For agents that inhibit MAO or selectively block 5-HT reuptake, the mechanism is thought to involve desensitization of presynaptic autoreceptors present on 5-HT neurons, leading to elevation of synaptic levels of 5-HT. The significance of presynaptic autoreceptor inhibition is supported by reports that administration of an autoreceptor antagonist can hasten the response to a SSRI. In contrast, chronic administration of a tricyclic antidepressant or electroconvulsive seizure increases the sensitivity of postsynaptic 5-HT1A receptors in hippocampus. A role for 5-HT1A receptors is also supported by studies of adult neurogenesis, which demonstrate that induction of adult neurogenesis by a 5HT selective reuptake inhibitor is blocked in 5-HT1A null mice (Santarelli et al., 2003).

There are additional monoamine receptor subtypes that are regulated by antidepressant treatment. However, regulation of these receptors, as with the β1AR, 5-HT1A, and 5-HT2A receptors, cannot explain the therapeutic action of antidepressants. An alternative interpretation is that receptor regulation is an adaptation to elevated monoamine levels that is a cellular response to maintain homeostatic control of monoamine neurotransmission. In fact, down-regulation of receptors supports the possibility that these receptors remain activated during chronic antidepressant treatment. Indeed, levels of these receptors are reduced, not completely eliminated, by chronic antidepressant treatment, suggesting that there is a sufficient level of receptor remaining to respond to the elevated levels of 5-HT and NE (Fig. 29.2). In fact, in the presence of elevated monoamines, the functional output of a receptor may be increased, not decreased, during long-term treatment. This would suggest that there is a sustained activation of the intracellular signal transduction cascades regulated by these monoamine receptors. Intracellular pathways regulate the function and expression of many cellular proteins that may be targets of antidepressant treatment.

29.2 A model for regulation of the βAR-coupled cAMP system by acute and chronic antidepressant treatment. In the absence of antidepressant treatment, synaptic levels of NE stimulate βARs and thereby increase the formation of cAMP. Acute antidepressant treatment increases synaptic levels of NE and increases βAR-stimulation of cAMP formation. Chronic antidepressant treatment results in downregulation of the number of βAR sites, and a reduction of cAMP

formation relative to acute antidepressant treatment. However, because the level of NE remains elevated, the level of cAMP formation is greater than that in the absence of drug treatment. Although this hypothetical model requires testing, it is supported by studies demonstrating that antidepressant treatment increases the cAMP cascade and target genes of this second messenger pathway. cAMP: cyclic adenosine monophosphate; NE: norepinephrine.

FIGURE

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NEUROPEPTIDE RECEPTORS AND DEPRESSION In addition to the monoamine receptors, there are several neuropeptide receptors that have become the subject of intense investigation and interest as potential targets for antidepressant treatment. These include the corticortrophin releasing factor (CRF) and neurokinin (NK) receptors. CRF Receptor System Corticortrophin releasing factor was first characterized as a critical mediator of the stress response in the central nervous system. This neuropeptide is expressed prominently in the paraventricular nucleus of the hypothalamus and coordinates the stress-induced release of adrenocorticotrophin hormone (ACTH) from the anterior pituitary (Chalmers et al., 1996). Corticortrophin releasing factor is also found throughout the brain, and expression in several limbic structures, such as the amygdala, suggesting a role in anxiety and mood disorders. Support for this hypothesis was provided by studies demonstrating that levels of CRF are increased in the cerebrospinal fluid (CSF) of patients who are depressed or postmortem tissue of victims of suicide (Nemeroff et al., 1984). A large volume of work over several years has provided evidence that an antagonist of the CRF receptor could be efficacious for the treatment of psychiatric illnesses associated with stress (Holsboer, 1999; Owens and Nemeroff, 1999). Two CRF receptor subtypes, CRF-R1 and CRF-R2, have been identified and characterized in the brain. Although the CRF-R1 receptor is more widely distributed in the brain, both receptor subtypes have been implicated in the response to stress. Preliminary clinical studies have been encouraging, but larger clinical trials have not been conducted due to toxicology problems. Development of safer agents will be required to confirm the therapeutic efficacy of CRF-R1 antagonists. One of the concerns with these compounds is that they will also block the pituitary CRF receptor (R1 subtype) and thereby interfere with the fine control of the hypothalamic-pituitary-adrenal (HPA) axis. However, preliminary studies in humans indicate that this may not be a problem. NK1 Receptor System Early studies focused on the potential role of neurokinins (NKs), including substance P, in the control of pain, although subsequent work has not supported this hypothesis. However, recent studies have taken a broad overview of the possible function of NKs, resulting in clinical trials of a NK antagonist in depression. The first major clinical study demonstrated that treatment with a neurokinin-1 (NK1) receptor antagonist was effective for the treatment of depression at a level that

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was comparable to a prototypical antidepressant agent (Kramer et al., 1998). Subsequent studies have not been as straightforward to interpret, highlighting a major problem in the development of novel antidepressant agents (that is, many clinical trials fail because of high placebo response rate or insufficient separation from comparator drugs). In the meantime, basic research studies in experimental animals indicate that NK1 receptors are located on 5-HT terminals and can depress the activity of 5-HT neurons. Conversely, antagonist treatment blocks these receptors and thereby enhances 5-HT neurotransmission, suggesting that this may be the mechanism by which blockade of the NK1 receptor produces an antidepressant response. Further studies will be necessary to test this hypothesis and to determine the possible role of other NK receptor subtypes in the treatment of mood disorders. There are several other neuropeptide-receptor systems that have received attention, including 5-HT4, vasopressin-1b, dynorphin, δ-opiate, and galanin receptor subtypes, to name a few. Preclinical studies provide evidence that drugs acting at these receptors can produce antidepressant responses in behavioral models and warrant the development and testing of agents in clinical trials. INTRACELLULAR SIGNAL TRANSDUCTION PATHWAYS AND DEPRESSION The intracellular signal transduction cascades that mediate the actions of monoamine receptors have been studied in some detail (see Chapters 4 and 5, and Nestler and Duman, 2006), making it possible to study the role of these pathways in the action of antidepressant treatment. The second-messenger signal transduction pathways (for example, cAMP, inositol triphosphate, Ca2+, and diacyl glycerol) mediate the actions of many monoamine receptors, as well as many neuropeptide and amino acid receptors (Fig. 29.3). Receptor regulation of these pathways occurs via G proteins that couple neurotransmitter receptors to effectors, such as adenylyl cyclase and phospholipase C, that catalyze the formation of cAMP and inositol triphosphate, respectively. These second messengers, in turn, regulate the activity of second messenger–dependent protein kinases (Fig. 29.3). In addition to the second-messenger dependent pathways, neurotrophic factors influence cell function via another type of signal transduction cascade. Receptors for these factors contain a tyrosine kinase domain that is activated upon agonist binding to the receptor. This leads to the phosphorylation of tyrosine residues on other cellular proteins. The mitogen-associated protein kinase (MAPK) cascade is one pathway regulated by these receptors. There is also evidence for cross talk between the second messenger and neurotrophic factor–regulated tyrosine kinase pathways.

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can be viewed as prototypical ways in which the brain adapts to environmental stimuli. It is likely that similar types of molecular and cellular adaptations occur in response to antidepressant treatment, and that dysfunction of this adaptive plasticity is involved in the pathophysiology of depression and other mood disorders. Although such adaptations are complicated and can be difficult to identify, their potential importance has stimulated a large number of studies to investigate the role of intracellular pathways and cellular adaptations in the pathophysiology and treatment of depression. Cyclic AMP Signal Transduction and Depression

FIGURE 29.3 A model for monoamine and neurotrophic factor regulated intracellular signal transduction pathways. The actions of monoamines are mediated largely by activation of receptors (R) coupled to effectors (E) via G proteins (G). This leads to the formation of second messengers (for example, cAMP, IP3, DAG, and Ca2+) and then activation of second-messenger-dependent protein kinases (for example, Ca2+/CAMK, PKA, and PKC). Neurotrophic factor signal transduction occurs via a different type of intracellular cascade. Binding of a neurotrophic factor to its receptor (Trk) results in activation of an intrinsic tyrosine kinase domain and autophosphorylation of intracellular receptor sites. This leads to binding to an adaptor protein in the Shc family. Shc becomes phosphorylated and binds to a Grb protein, such as Grb2. This complex of Shc and Grb2 then binds to Sos, a guanine nucleotide exchange factor. Sos then activates a small GTP binding protein, Ras, by enhancing the exchange of GDP for GTP. Ras then leads to activation of Raf, the first protein kinase in the MAP kinase cascade. The second-messenger-dependent protein kinases and the MAP kinase cascade result in phosphorylation and regulation of diverse cellular proteins that control all aspects of neuronal function. This includes the short- and long-term responses to psychotropic drugs, as well as neuroendocrine and environmental stimuli. cAMP: cyclic adenosine monophosphate; IP3: inositol triphosphate; DAG: diacylglycerol; GDP: guanosine 5'-diphosphate; GTP: guanosine-5′ triphosphate; CAMK: calmodulin-dependent protein kinase; MAP: mitogen-activated protein; PKA: protein kinase A; PKC: protein kinase C.

These pathways control all aspects of neuronal function and ultimately underlie the ability of the brain to adapt and respond to pharmacological and environmental inputs. Some examples include increased or decreased synaptic efficacy in cellular models of learning and memory (Madison et al., 1991; Bliss and Collingridge, 1993; Kang and Schuman, 1995; Levine et al., 1995) and atrophy and growth of neurons in adults, as well as during development (Lindsay et al., 1994; Lindvall et al., 1994; Thoenen, 1995). These types of responses

The cAMP cascade is one pathway that has been implicated in the action of antidepressant treatment (Fig. 29.2). Formation of cAMP can be regulated by direct coupling of receptors to adenylyl cyclase or indirectly by other second-messenger pathways. Receptors directly coupled to this pathway interact with either stimulatory (Gs) or inhibitory (Gi) G protein subtypes. This results in release of the α subunits of Gs or Gi and stimulation or inhibition, respectively, of adenylyl cyclase and cAMP formation. Indirect activation of certain forms of adenylyl cyclase occurs via elevation of Ca2+ and calmodulin, and is independent of Gs (Nestler and Duman, 2006). Elevation of cAMP leads to activation of protein kinase A (PKA), which in turn leads to regulation of cellular function by phosphorylation of specific proteins, including receptors, ion channels, G proteins, enzymes, and transcription factors. The cAMP-response element binding (CREB) protein is one transcription factor that can mediate the actions of the cAMP system (Meyer and Habener, 1993; Ghosh and Greenberg, 1995). The transcriptional activity of CREB is regulated primarily by phosphorylation of specific amino acid residues, although CREB function can also be influenced by increasing or decreasing the total amount of CREB protein (Widnell et al., 1994; Walker et al., 1995; Nibuya et al., 1996). In addition to PKA, other types of protein kinases are known to phosphorylate and activate CREB, including Ca2+/calmodulin-dependent protein kinase and ribosomal S6 kinase, which is activated by the MAPK cascade (Russell and Duman, 2002). The cAMP cascade and CREB could represent common downstream targets for 5-HT and NE neurotransmitter systems, as well as antidepressant treatment. There are several 5-HT and NE receptor subtypes that directly stimulate cAMP production (Fig. 29.4). β1AR and β2AR subtypes mediate NE-stimulated cAMP formation, and there are at least three 5-HT receptor subtypes that stimulate this second messenger system (that is, 5-HT4, 5-HT6, and 5-HT7). A role for the β1AR and 5-HT7 receptor coupled regulation of the cAMP system is supported by reports that chronic antidepressant treatment down-regulates levels of βAR-stimulated cAMP forma-

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419

FIGURE 29.4 A model of the molecular actions of antidepressant treatment: adaptations of the cAMP-CREB cascade. Antidepressant treatment increases synaptic levels of 5-HT and NE via blockade of monoamine reuptake and degradation. This can lead to down-regulation of certain monoamine receptors (for example, β1-AR, 5-HT7, 5-HT2A). However, chronic antidepressant treatment results in up-regulation of the postreceptor components of the cAMP cascade, including levels of adenylyl cyclase enzyme activity, particulate levels of PKA, and expression of CREB. CREB is a common target for both 5-HT and NE and different types of antidepressants, because it is regulated by receptors coupled to the cAMP pathway (for example, β-AR, 5-HT4,6,7) and receptors that activate Ca2+-dependent protein kinases

(for example, 5-HT2A, α 1-AR). In addition, the NMDA glutamate receptor complex can also influence CREB via activation of Ca2+dependent protein kinases, and chronic antidepressant treatment is reported to decrease the affinity of a modulatory glycine site on the NMDA receptor. Up-regulation of CREB increases the expression of target genes, such as BDNF and TrkB. BDNF and TrkB exert trophic actions on target neurons and thereby increase cell survival and function. 5-HT: serotonin: NE: norepinephrine; cAMP: cyclic adenosine monophosphate; PKA: protein kinase A; CREB: cAMP-response element binding; NMDA: N-methyl-D-aspartate; BDNF: brain-derived neurotrophic factor.

tion and decreases the level of 5-HT7 receptor binding sites (Sleight et al., 1995). These findings indicate that there may be a sustained activation of the cAMP secondmessenger system via these receptors (see Fig. 29.4). Recent studies also demonstrate that 5-HT4 and 5-HT6 receptors may be involved in the action of antidepressants. For example, activation of 5-HT4 receptors located on 5-HT dorsal raphé nucleus neurons can increase the firing rate of these cells (Lucas and Debonnel, 2002). Moreover, this effect is maximal after only 3 days of treatment and is sustained with repeated treatment for up to 3 weeks (Lucas et al., 2005). Additional studies demonstrate antidepressant activity in cellular and behavioral models (Lucas et al., 2007). These studies suggest that 5-HT4 receptor agonists may have a rapid response rate in patients who are depressed. Studies of dopamine and cAMP-regulated phosphoprotein of 32 Kd molecular weight (DARPP-32) have implicated the 5-HT6 receptor subtype in the actions

of selective serotonin reuptake inhibitor (SSRI) antidepressants. The behavioral actions of fluoxetine in the forced swim test are mediated in part by phosphorylation of Thr34-DARPP-32 and Ser845-GluR1 (Svenningsson, Tzavara, Liu, et al., 2002). In vitro slice experiments have demonstrated that 5-HT-stimulated phosphorylation of Thr34-DARPP-32 and Ser845-GluR1 is mediated by 5HT4 and 5-HT6 receptors, both of which are positively coupled to the cAMP–PKA pathway (Svenningsson, Tzavara, Witkin, et al., 2002). The distribution of 5-HT6 receptors is localized to limbic structures that could influence various aspects of depression and antidepressant response (Hamon et al., 1999; Ballaz et al., 2007). Another potential site of convergence for antidepressant treatments is CREB. In addition to regulation by the cAMP cascade, CREB can be activated by 5-HT or NE receptors that stimulate Ca2+-dependent protein kinases (for example, 5-HT2A, 5-HT2C, α1-adrenergic receptors) (Meyer and Habener, 1993; Ghosh and Greenberg,

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1995). cAMP-response element binding can also be influenced by α-amino-3-hydroxy-5-methyl-4-isoxasolepropionic acid (AMPA) or N-methyl-D-aspartate (NMDA) type glutamate receptors, which form a ligand gated Ca2+ channel (Fig. 29.4) (Ghosh and Greenberg, 1995). N-methyl-D-aspartate receptor gating of Ca2+ is enhanced by a glycine modulatory site, and the affinity of glycine for this site is reduced by chronic antidepressant treatment (Paul et al., 1994). One interpretation of these results is that NMDA receptor function is reduced by antidepressant treatment. An alternative possibility is that this is an adaptive down-regulation of receptor affinity in response to sustained activation of receptor function, similar to that observed for the βAR (see Fig. 29.2). N-methyl-D-aspartate receptor activation alone can regulate cell function, but interaction of NMDA receptors with other neurotransmitters (for example, monoamines) and neurotrophic factors may be critical for maintaining the normal function and plasticity of neurons (A. McAllister et al., 1996). Additional studies are needed to determine the role of NMDA receptors in monoamine receptor function and the action of antidepressant treatment. Adaptations of the cAMP Cascade by Antidepressant Treatment The possibility that antidepressant treatment results in sustained activation of the cAMP second-messenger cascade is supported by studies of the postreceptor components of this system (Fig. 29.4). The level of adenylyl cyclase enzyme activity is increased by chronic administration of several different types of antidepressants (Menkes et al., 1983; Ozawa and Rasenick, 1991). This effect appears to result from enhanced coupling of Gs to the adenylyl cyclase catalytic subunit. In addition, chronic lithium treatment increases the expression of adenylyl cyclase types I and II in rat neocortex (Colin et al., 1991). Antidepressant treatment is also reported to increase levels of PKA enzyme activity in particulate fractions of rat neocortex (Fig. 29.4) (Nestler et al., 1989; Perez et al., 1989). Levels of PKA are increased in the nuclear fraction but decreased in the cytosolic fraction, suggesting that PKA is translocated to the nucleus in response to antidepressant treatments (Nestler et al., 1989; Tiraboschi et al., 2004). Although additional studies are required to confirm the cellular localization of this effect, the results indicate that PKA can be regulated by antidepressant treatments. However, nuclear localization analysis of several protein kinases indicates that PKA is less likely to account for the induction of gene transcriptin by CREB phosphorylation than CAMKIV and MAPK, although a role for PKA cannot be completely excluded (Tiraboschi et al., 2004).

Regulation of CREB by Antidepressant Treatment Up-regulation of adenylyl cyclase and increased levels of PKA in the nucleus suggest that the function of CREB, as well as other transcription factors, is also regulated by antidepressant treatment. Regulation of CREB and expression of target genes may be particularly relevant to the action of antidepressant treatment because of the therapeutic time delay: altered expression of target genes and the cellular proteins they encode, as well as the transport and incorporation of these newly synthesized proteins into the cellular architecture, would be expected to require a time delay. In support of this possibility, the expression of CREB messenger ribonucleic acid (mRNA) and protein in rat hippocampus is increased by chronic antidepressant treatment (Nibuya et al., 1996; Conti et al., 2002). This could occur via regulation of a cAMP response element (CRE) in the promoter of the CREB gene (Walker et al., 1995; Nibuya et al., 1996). Up-regulation of CREB is observed with 5-HT or NE selective reuptake inhibitors, indicating that CREB is a target for both monoamine systems. Chronic antidepressant administration also increases the phosphorylation of CREB and CRE-mediated gene expression, demonstrating that CREB function is also increased by antidepressant treatment (Thome et al., 2000; Tiraboschi et al., 2004). Increased levels of CaMKIV and MAPK in nuclear fractions suggest that these kinases mediate the induction of CREB transcription activity (Tiraboschi et al., 2004). Up-regulation of CREB suggests that genes containing CRE elements may be targets for antidepressant treatment. However, gene expression is regulated in a complex, region-specific manner, and not all CRE-regulated genes can be considered targets of antidepressant treatments. For example, in the locus coeruleus chronic antidepressant treatment decreases PKA activity and expression of tyrosine hydroxylase, which contains a CRE, suggesting that antidepressant treatment down-regulates CREB in this brain region (Melia et al., 1992). In addition, expression of a particular gene is dependent on the function and interaction of multiple transcription factors that either enhance or inhibit transcriptional activity. This indicates that even though antidepressant treatment regulates the cAMP cascade, the functional consequences of this regulation are region specific and are limited to a subset of target genes. Identification of the specific target genes will provide new insights into the therapeutic action of antidepressant treatments. Behavioral Studies of CREB A possible role for CREB in depression has gained additional support from behavioral studies in rodent models. One report demonstrates that overexpression of CREB

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in hippocampus produces an antidepressant-like effect in behavioral models of depression (Chen et al., 2001). In this study viral-mediated gene transfer was used to increase levels of CREB in the hippocampus, and animals were then tested in the forced swim and learned helplessness paradigms. In both paradigms, viral expression of CREB produced an effect similar to that observed with chemical antidepressant agents. These studies indicate that up-regulation of CREB in hippocampus is sufficient to produce an antidepressant response. However, studies of altered CREB expression in other brain regions and tests of CREB null mutant mice have reported different effects (that is, CREB is prodepressive) indicating that the actions of CREB are region specific (Pliakas et al., 2001; Newton et al., 2002). In particular, studies of the mesolimbic dopamine system demonstrate that in the nucleus accumbens, CREB serves a gating function between emotional stimuli and behavioral responding, such that increased CREB reduces and decreased CREB increases responding (Barrot et al., 2002). In addition, it is likely that the function of CREB is dependent on the timing and context in which the effect of overexpression on behavior is studied, as has been observed in models of learning and memory (that is, CREB is necessary for long-term memory, but not for short-term memory). Additional studies will be needed to fully understand the role of this transcription factor in the action of antidepressant treatment. Clinical Studies of the cAMP-CREB Cascade Studies of postmortem brain also provide evidence of altered CREB expression in patients who are depressed. cAMP-response element binding immunoreactivity is reported to be decreased in the temporal cortex of patients who are depressed relative to matched controls (Dowlatshahi et al., 1998; Odagaki et al., 2001; Dwivedi et al., 2003), and CREB phosphorylation is reduced in postmortem patients who are depressed (Yamada et al, 2003). Moreover, levels of CREB were significantly increased in patients who were depressed and who were being medicated with antidepressants at the time of death. Although these findings must be replicated, the results are consistent with the hypothesis that up-regulation of CREB could contribute to the action of antidepressant treatment and that decreased levels could play a role in the pathophysiology of depression. Dysfunction of other components of the cAMP cascade, including G proteins, adenylyl cyclase, and PKA subunits, have also been conducted in postmortem tissue (Dowlatshahi and Young, 2000). One of the most consistent findings in these studies is that levels of stimulated adenylyl cyclase enzyme activity are decreased in patients with depression. Studies of blood elements or fibroblasts also demonstrate a reduction in levels of PKA subunit im-

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munoreactivity or enzyme activity (Manier et al., 1996; Perez et al., 2001). Taken together, these different lines of evidence suggest that the cAMP–CREB cascade is down-regulated in patients who are depressed. Additional Signal Transduction Sites and Depression Although studies of the cAMP–CREB cascade are highlighted in this chapter, it is likely that there are many other intracellular signaling cascades that also play a role in depression. For example, antidepressant treatment regulates monoamine receptors, including 5-HT2A and β1-AR, coupled to the phosphatidylinositol pathway and protein kinase C (PKC) (Charney et al., 1981; Heninger and Charney, 1987). Lithium also regulates PKC, and recent studies have identified glycogen-synthase kinase-3β as a novel target of this bipolar medication (Manji and Duman, 2001; Zarate et al., 2006). In addition to CREB, PKC could regulate distinct transcription factors, as well as other phosphoproteins. Another study has found that P11, a member of the S100 family of small acidic proteins, is up-regulated by antidepressant treatment, is decreased by a behavioral model of stress and depression, and decreased in postmortem tissue of patients who are depressed (Svenningsson et al., 2006). P11 interacts with a variety of proteins, including 5-HT1B receptors; notably, P11 increases the surface expression and function of 5-HT1B, and P11 transgenic mice display an antidepressant phenotype in the tail suspension test. The MAPK pathway, which is regulated by neurotrophic factors as well as other signaling pathways, has also been implicated in the actions of antidepressant treatment (Shirayama et al., 2002; Duman et al., 2007) (see also section on neurotrophic factors in this chapter). A role for glucocorticoid receptors, which regulate gene expression via binding to a glucocorticoid response element, in the treatment and etiology of depression has also been suggested (Barden et al., 1995). This most likely represents a partial listing of the signal transduction pathways and transcription factors that are involved in depression, and future studies will be necessary to fully characterize the relevant cellular adaptations. NEURONAL ATROPHY AND LOSS IN ANIMAL MODELS OF DEPRESSION Experimental studies have demonstrated that stress causes a loss of neurotrophic support in animal models. Moreover, several lines of evidence demonstrate that stress can lead to structural alterations in limbic brain regions. This includes atrophy of neurons and a reduction of neurogenesis in adult hippocampus. These deleterious effects of stress could contribute to the pathophysiology

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of depression. A brief overview of neurotrophic factors and the effects of stress on the hippocampus are reviewed in this section. Neurotrophic Factors There are several different families of neurotrophic factors that control the survival and growth of neurons during development but that also play a critical role in the survival and function of adult neurons. One of the best-characterized subgroups is the nerve growth factor (NGF) family, which includes nerve growth factor, brainderived neurotrophic factor (BDNF), neurotrophin-3, and neurotrophin-4/5. The members of this family are expressed throughout the central nervous system and are known to have a wide range of effects on neuronal function (Thoenen, 1995; K. McAllister et al., 1999; Arancio and Chao, 2007). These neurotrophic factors produce cellular actions by binding to receptors, referred to as Trks A, B, and C for NGF, BDNF, and NT3, respectively. The Trk receptors have intrinsic tyrosine kinase activity, and activation results in autophosphorylation and subsequent coupling to one of three effector systems: the MAPK cascade, phosphotidylinositol3 kinase, and phospholipase Cγ (Russell and Duman, 2002; Tanis and Duman, 2007). Within this family of neurotrophic factors, BDNF is the most widely distributed and most abundant in brain. Preclinical studies of neurotrophic factors in the actions of stress and antidepressants have been conducted at the molecular, cellular, and behavioral levels. Taken together the results indicate that BDNF may be involved in the action of antidepressants, and that dysfunction of this or other neurotrophic factors could contribute to the pathophysiology of depression. Stress Down-Regulates BDNF Expression in Hippocampus Exposure to stressful conditions causes a rapid and longlasting down-regulation of BDNF in rodent hippocampus (Nibuya et al., 1995; Smith et al., 1995). This effect is observed after short- (2 hours) and long-term (7 days) immobilization stress and is observed in the major subfields of the hippocampus (that is, the dentate gyrus granule cell layer, and CA1 and CA3 pyramidal cell layers). Down-regulation of BDNF is one of the most consistently reported effects of stress and is observed with many different paradigms, including unpredictable stress, foot shock, social isolation, social defeat, swim stress, and maternal deprivation (see Duman and Monteggia, 2006, for review). Glucocorticoid treatment causes a smaller, but significant, down-regulation of BDNF expression in hippocampus, indicating that adrenal steroids may contribute to this effect of stress. BDNF is also decreased upon reexposing animals to cues

previously associated with foot shock (that is, conditioned response) (Rasmussen et al., 2002). This suggests that the recurrent memory of stressful or traumatic experiences could continue to result in down-regulation of BDNF long after the experience and thereby influence behavior. In addition to BDNF, there is also evidence that other neurotrophic/growth factors are decreased by stress. One of the most interesting factors is vascular endothelial growth factor (VEGF). Vascular endothelial growth factor was first identified as an angiogenic factor and endothelial cell mitogen but has also been shown to increase the proliferation of neural progenitor cells in the hippocampus (Jin et al., 2004). Exposure to stress down-regulates the expression of VEGF in the hippocampus (Heine et al., 2005), and studies are currently under way to determine if decreased VEGF contributes to the reduction in neurogenesis resulting from stress (Heine et al., 2005). Stress Induces Atrophy of Hippocampal Neurons in Experimental Animals Chronic exposure of rodents to physical stress or exposure of nonhuman primates to psychosocial stress is reported to cause atrophy of CA3 pyramidal neurons in the hippocampus (Sapolsky et al., 1985; Uno et al., 1989; Sapolsky et al., 1990; Margarinos et al., 1996; also see Chapter 40 by McEwen). Chronic exposure to immobilization stress decreases the number and length of the CA3 pyramidal neuron apical dendrites. Atrophy of CA3 pyramidal neurons is also observed after chronic glucocorticoid treatment, indicating that activation of the HPA axis is sufficient to cause CA3 pyramidal cell atrophy (Wooley et al., 1990). It is also possible that down-regulation of BDNF could contribute to the stress-induced atrophy of CA3 neurons, and further studies are needed to test this hypothesis. In addition, atrophy may result from glucocorticoid enhancement of excitotoxicity, as well as reduced metabolic capacity of these neurons (Stein-Behrens et al., 1994). These effects of stress and elevated glucocorticoid levels could also make the CA3 pyramidal neurons more vulnerable to different types of neuronal insults, such as hypoxia and ischemia. The atrophy of neurons in response to corticosterone or stress has also been extended to pyramidal neurons of the prefrontal cortex (PFC) (Wellman, 2001; Radley et al., 2004), effects that could contribute to the atrophy observed in this brain region of patients who are depressed (see below). In contrast, stress is reported to cause hypertrophy of the pyramidal neurons of the amygdala, measured by an increase in spine density of pyramidal neurons in the basolateral nucleus of the amygdala, effects that could contribute to increased anxiety observed in response to stress (Mitra et al., 2005).

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Stress Decreases Neurogenesis in Adult Hippocampus In addition to causing atrophy of CA3 pyramidal neurons, stress also has profound effects on the dentate gyrus granule neurons in the hippocampus. The hippocampal dentate gyrus is one of the few brain structures (the other region is the subventricular zone) that retain the ability to generate new neurons throughout adult life (Gould et al., 1999; Gage, 2000). Adult neurogenesis has been observed in a variety of different animals, including humans, and occurs into old age. Progenitor cells located in the subgranular zone of the hippocampus proliferate, and many of the new cells migrate into the granule cell layer where they mature and make connections that are typical of adult granule cells. Moreover, the rate of proliferation and the survival of newborn cells are highly regulated by environmental and endocrine factors (Warner-Schmidt and Duman, 2006). For example, running, enriched environment, and hippocampal-dependent learning all increase proliferation and/or survival of newborn neurons. In contrast, stress, aging, and drugs of abuse decrease the proliferation of neurons in adult hippocampus (Gould et al., 1998; Warner-Schmidt and Duman, 2006). Decreased neurogenesis is observed after exposure to different types of stress, including predator odor, social stress, acute and chronic restraint, foot shock, and chronic mild stress (Duman, 2004). In addition, decreased neurogenesis is also associated with a depressive-like phenotype in an animal model of depression (Malberg and Duman, 2003). Administration of glucocorticoids also decreases adult neurogenesis, indicating that activation of the HPA axis is responsible for the down-regulation of neurogenesis by stress. Decreased neurogenesis could contribute to the reduction in hippocampal volume that is observed in patients who are depressed (see below). EVIDENCE OF NEURONAL ATROPHY AND LOSS IN HUMAN BRAIN Preclinical evidence demonstrating that stress decreases neurotrophic factor expression and causes the structural alterations in the brain has led to clinical investigations of morphological changes in patients who are depressed. A series of studies conducted in living patients (brain imaging) and in postmortem tissue demonstrates that there is also structural remodeling in patients with depression (also see Chapter 31). Atrophy of Limbic Brain Regions in Depression and PTSD: Brain Imaging The possibility that the morphology of hippocampal neurons is altered in depression is supported by clinical brain imaging reports. These studies demonstrate that

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the volume of hippocampus is reduced in patients with depression or posttraumatic disorder, suggesting that atrophy of hippocampus may be associated with these disorders (Bremner et al., 1995; Sapolsky, 1996; Sheline et al., 1996), although not all studies report a decrease in patients who are depressed (see Vythilingam et al., 2004). The magnitude of the change in hippocampal volume is directly proportional to the length of illness, suggesting that the reduction in hippocampal volume is a result, not cause, of depression (Sheline et al., 1999). However, it is possible that small structural changes occur prior to or coincident with onset of illness and could thereby contribute to the symptoms of depression. There is also a report that antidepressant treatment can reverse the reduced hippocampal volume in patients with post-traumatic stress disorder (PTSD) (Vermetten et al., 2003). Evidence that the function of the hippocampus is altered in depression is also provided by studies of the feedback inhibition of the HPA axis. Glucocorticoids activate a fast feedback inhibitory pathway from the hippocampus to hypothalamus, and this pathway is downregulated in patients who are depressed (Young et al., 1997). Atrophy and dysfunction of hippocampal neurons could also mediate other abnormalities observed in depression, including memory or cognitive deficits, which are controlled by this brain region. In addition, hippocampus has reciprocal connections with other brain structures that regulate mood and emotion (for example, amygdala and PFC) and could indirectly influence other symptoms of depression. Dysfunction of the hippocampus is also supported by studies demonstrating that patients who are depressed display deficits of declarative memory, a hippocampal-dependent behavior, and that antidepressant treatment improves memory (Vythilingham et al., 2004; Vermetten et al., 2003). Neuronal Atrophy and Loss in Depression: Postmortem Analysis Preclinical studies suggest that the reduction of hippocampal volume observed in patients who are depressed could result from atrophy or decreased neurogenesis of hippocampal neurons. There have been a few studies conducted to address this issue. There is one report that the number of nonpyramidal cells in the hippocampal CA2 region is decreased in patients with bipolar disorder (Benes et al., 1998). There was no difference in the number of pyramidal neurons, and analysis of granule neurons was not conducted in this study. Another study found no evidence for a reduction in the number of neurons or synaptic contacts in patients who are depressed or individuals treated with glucocorticoids (Muller et al., 2001). However, this was a semiquantitative study, and all of the patients in the depressed group were on antidepressant medication at the time of death, which could reverse or oppose neu-

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ronal atrophy (see below). A more recent study found that there is an increase in packing density in the granule cell layer, suggesting that there is a decrease in neuropil in patients who were depressed, but not a decrease in cell number (Stockmeier et al., 2004). Additional postmortem studies of the hippocampus will be necessary to determine the cellular mechanisms underlying the reduction in hippocampal volume reported in brain imaging studies. Postmortem investigations of structural alterations have also been conducted in cortical brain regions implicated in depression. These studies report a reduction in the size of neurons and the number of glia in the orbital frontal cortex, subgenual PFC, and cingulate cortex (Ongur et al., 1998; Rajkowska et al., 1999; Cotter et al., 2001). Preclinical studies have also demonstrated that stress decreases the proliferation of glia in the PFC, which could underlie in part the decreases observed in patients who are depressed (Banasr et al., 2007). These results are consistent with brain imaging studies showing altered blood flow or metabolism in these cortical structures of patients who are depressed (Manji and Duman, 2001). Moreover, the alterations in cerebral cortex indicate that imbalances in the expression of neurotrophic factors and neuronal atrophy are not limited to the hippocampus.

studies that have not reported an up-regulation of BDNF in response to chronic antidepressant treatment (see Duman and Monteggia, 2006). Expression of BDNF is activity dependent and can therefore be influenced by a variety of external stimuli. This, as well as differences in drug treatment schedules (dose and length of treatment, as well as time after the last drug administration), could all contribute to the discrepancy in reports of antidepressant regulation of BDNF expression. The time course and regional distribution of BDNF up-regulation is consistent with that for up-regulation of CREB by antidepressant treatment. In addition, chronic administration of a phosphodiesterase inhibitor increases the expression of BDNF and hastens the up-regulation of BDNF in response to a tricyclic antidepressant drug (Nibuya et al., 1996). The expression of BDNF in cultured cells is also up-regulated by activation of cAMP or Ca2+-activated pathways (Condorelli et al., 1994; Ghosh et al., 1994), and a Ca2+/CRE response element has been identified in the exon III promoter of the BDNF gene (Tao et al., 1998). A recent study also demonstrated that the regulation of BDNF by antidepressant treatment is mediated in part via regulation of histone remodeling (Tsankova et al., 2006). Taken together, these findings support the hypothesis that upregulation of BDNF is mediated by activation of the cAMP cascade and chromatin remodeling and that BDNF is a target of antidepressant treatment.

NEUROTROPHIC ACTIONS OF ANTIDEPRESSANTS In contrast to the atrophy and neuronal loss caused by stress, studies in rodents demonstrate that antidepressants produce effects that block or reverse the effects of stress. The clinical relevance of these findings is supported by studies of BDNF in patients who are depressed. A review of this literature is discussed in this section. Antidepressant Treatment Increases BDNF Expression The possibility that neurotrophic factors are involved in the action of antidepressants is supported by studies demonstrating that chronic antidepressant treatment increases the expression of BDNF in rat hippocampus (Nibuya et al., 1995; Nibuya et al., 1996; see Duman and Monteggia, 2006, for review). In addition, antidepressant pretreatment blocks the down-regulation of BDNF in response to stress (Nibuya et al., 1995). The antidepressants tested included 5-HT and NE selective reuptake inhibitors, MAO inhibitors, atypical antidepressants, and electroconvulsive seizures. In contrast, acute administration of antidepressant drugs or chronic administration of nonantidepressant psychotropic drugs, including morphine, cocaine, and haloperidol, does not increase the expression of BDNF in hippocampus. Although most studies have been positive, there are also

BDNF and Antidepressant Treatment Enhance Neuronal Arborization and Survival BDNF is reported to enhance the growth and survival of cortical neurons (Ghosh et al., 1994), as well as 5-HT and NE neurons (Mamounas et al., 1995; Sklair-Tavron and Nestler, 1995). This suggests that loss of BDNF support could adversely influence monoamine neurotransmission at pre- and postsynaptic sites. Antidepressant treatment is also reported to enhance the regeneration of catecholamine neurons in the cerebral cortex (Nakagawa et al., 2000), and chronic electroconvulsive shock (ECS) is reported to induce sprouting of dentate gyrus granule neurons in hippocampus (Vaidya et al., 1997). One study has demonstrated that administration of an atypical antidepressant, tianeptine, blocks the stressinduced atrophy of CA3 apical dendrites (Watanabe et al., 1992; McEwen, 2002). A more recent study has reported that antidepressant treatment increases the number of synapses, determined by electron microscopy (Hajszan et al., 2005). Studies of other antidepressants and additional stress paradigms (for example, psychosocial stress) are needed to determine if blockade of neuronal atrophy or enhanced neuronal growth are common actions of antidepressant treatments, and to determine if these effects are mediated by induction of BDNF.

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BDNF Increases Synaptic Strength of Hippocampal Neurons Antidepressant treatment and increased BDNF expression may also influence the strength of neuronal synapses, as well as the cognitive function of animals. The influence of BDNF and antidepressant treatment on synaptic strength has been assessed using a cellular model of learning and memory, long-term potentiation (LTP). Incubation with BDNF is reported to increase the synaptic efficacy of hippocampal neurons, and LTP is reduced in BDNF knockout mice expressing reduced levels of this neurotrophic factor (Kang and Schuman, 1995; Levine et al., 1995). Studies of antidepressant drugs have been mixed, with reports of enhanced and reduced LTP in hippocampus. However, these apparent discrepancies may be explained by the hippocampal circuits examined. Studies of granule cell LTP (stimulation of the perforant path) have reported that antidepressants enhance LTP (Stewart and Reid, 2000; Levkovitz et al., 2001), while studies of CA1 pyramidal cells (stimulation of the Schaffer collateral) report that LTP is suppressed (Massicotte et al., 1993; O’Connor et al., 1993; Von Frijtag et al., 2001). There are also behavioral studies demonstrating that antidepressant treatment enhances learning and memory. There are reports that memory and cognitive function are enhanced in rodent models and in patients who are depressed by chronic antidepressant treatments (Allain et al., 1992; Yau et al., 1995). More recent studies have confirmed these effects, demonstrating that chronic administration of fluoxetine or venlafaxine, a mixed action reuptake inhibitor, improves performance in the Morris water maze, a spatial learning and memory model (Nowakowska et al., 2000, 2003; Nowakowska et al., 2006). There are also clinical studies reporting improvement in cognition and memory in response to chronic antidepressant treatment (Spring et al., 1992; Vermetten et al., 2003; Vythilingam et al., 2004). Together with the cellular LTP studies, these findings indicate that antidepressant treatment results in neuroplasticity-like responses. However, the actions of antidepressants are dependent on the type of drug tested, with reports that certain antidepressants worsen performance in learning and memory models (Yau et al., 2002; Naudon et al., 2007). Additional preclinical and clinical studies are needed to further examine the influence of antidepressants on behavioral models of memory and cognitive performance tasks in animals and humans.

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BDNF in behavioral models of depression have been examined. These studies are consistent with the hypothesis that BDNF is sufficient to produce an antidepressant response and is required for the actions of antidepressants. Infusions of BDNF into the midbrain for 7 days produced an antidepressant-like effect in the forced swim and learned helplessness paradigms (Siuciak et al., 1997). The antidepressant effect of BDNF in this brain region could result from increased 5-HT neurotransmission, as indicated by increased levels of 5-HT and its metabolites in forebrain regions (Siuciak et al., 1994). The influence of BDNF applied in forebrain regions, where it is regulated by antidepressant treatment, has also been studied. Infusions of BDNF into the dentate gyrus or CA3 pyramidal cell layer, but not the CA1 layer, of hippocampus also produce antidepressant effects in the forced swim and learned helplessness paradigms (Shirayama et al., 2002). The effect of BDNF in hippocampus was notable because a single, local infusion into the hippocampal subfields was sufficient to produce an effect similar to that observed with repeated systemic administration of a chemical antidepressant. The actions of hippocampal BDNF are blocked by coadministration of a tyrosine kinase antagonist or by inhibition of the MAPK cascade, indicating that these pathways mediate the antidepressant effects of BDNF. More recent studies also demonstrate that blockade of the MAPK cascade results in a depressive phenotype in different models of depression (Duman et al., 2007). Infusion of BDNF into the lateral ventricle also produces an antidepressant response in the forced swim test (Hoshaw et al., 2005). Studies of mutant mice have confirmed a role for BDNF and demonstrate that the actions of antidepressant treatment are dependent on BDNF-TrkB signaling. In transgenic mice that express a dominant negative form of TrkB (Saarelainen et al., 2003) or in BDNF conditional null mutant mice (Monteggia et al., 2004), the behavioral response to antidepressant treatment is blocked (see Duman and Monteggia, 2006, for review). Surprisingly, BDNF mutant mice do not have a depressive-like phenotype, although there is one report that female, but not male, conditional BDNF null mutant mice display behavioral despair and anhedonia (Monteggia et al., 2007). This suggests that reduction of BDNF is not always sufficient to produce a behavioral response, and that other environmental factors such as stress may be needed. This type of Gene × Environment interaction has been demonstrated in basic and clinical research studies (Kaufman et al., 2006; Duman et al., 2007).

BDNF Produces Antidepressant Effects in Behavioral Models of Depression

Antidepressant Treatment Increases Neurogenesis

To determine if the induction of BDNF contributes to the actions of antidepressant treatment, the effects of

Interestingly, antidepressant treatment increases adult neurogenesis in the hippocampus (Malberg et al., 2000a;

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FIGURE 29.5 Neurotrophic actions of stress and antidepressants in the hippocampus. This model demonstrates the influence of stress and antidepressant treatments on subsets of neurons in the hippocampus. The major cell groups in the hippocampus include the dentate gyrus granule cells and CA3 and CA1 pyramidal cells. The mossy fiber (mf) pathway carries projections from the granule cell layer to CA3 neurons, which in turn project to CA1 neurons via the Schaffer collateral (sc) pathway. Chronic stress increases glucocorticoid levels and decreases BDNF and thereby causes atrophy of CA3 pyramidal neurons. CA3 neurons are also vulnerable to damage by other types of neuronal insult (for example, hypoxia-ischemia, hypoglycemia,

neurotoxins, and viral infections). Genetic factors could also contribute to such selective vulnerability. Stress or glucocorticoid treatments also decrease neurogenesis of granule cells in adult hippocampus. In contrast, chronic antidepressant treatment increases the expression of BDNF and adult neurogenesis, and prevents the downregulation of BDNF and neurogenesis in response to stress. These effects could reverse the atrophy of hippocampal neurons, as well as protect these neurons from further damage. Up-regulation of BDNF occurs via increased 5-HT and NE neurotransmission and up-regulation of the cAMP-CREB cascade. BDNF: brain-derived neurotrophic factor.

see Duman, 2004; Warner-Schmidt and Duman, 2006). The time course for induction of adult neurogenesis is consistent with the time course for the therapeutic response to antidepressants. Up-regulation of neurogenesis is observed with several different classes of antidepressants, indicating that this effect may be a common cellular mechanism of antidepressant action. Moreover, the down-regulation of adult neurogenesis caused by stress is blocked by antidepressant treatment (Malberg et al., 2000b; Czeh et al., 2001). Pharmacological and transgenic approaches also demonstrate that activation of the cAMP–CREB cascade increases adult neurogenesis (Nakagawa et al., 2002). Moreover, the induction of neurogenesis is required for the behavioral actions of antidepressant treatment (Santarelli et al., 2003). Blockade of neurogenesis by irradiation or in a mutant mouse model blocks the effects of chronic antidepressant treatment in two long-term behavioral models, chronic unpredictable stress and novelty suppressed feeding. These findings provide the first evidence that induction of neurogenesis has functional consequences related to the actions of antidepressants. However, it is likely that antidepressants also lead to additional effects (for

example, altered plasticity, neuroprotection) in hippocampus as well as other brain regions that contribute to behavioral responding and the therapeutic actions of these agents. A NEUROTROPHIC HYPOTHESIS OF DEPRESSION The preclinical and clinical studies reviewed in this chapter form the basis of a neurotrophic theory of depression and antidepressant action (Fig. 29.5). Depression, particularly stress-associated cases, may result from atrophy, damage, or death of vulnerable neurons (that is, the CA3 pyramidal cells) or down-regulation of adult neurogenesis in the hippocampus. The atrophy, vulnerability, and reduced neurogenesis could result, at least in part, from the down-regulation of BDNF, as well as other trophic factors, in response to stress. In addition, sustained elevation of adrenal-glucocorticoids, often observed in patients who are depressed, could contribute to the atrophy of CA3 pyramidal neurons and down-regulation of neurogenesis. Antidepressant treatment could reverse the atrophy and reduced neurogenesis by up-regulating the

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cAMP-CREB cascade and expression of neurotrophic factors. This could lead to enhanced growth and function of hippocampal neurons, in conjunction with the antidepressant-induced increase in monoamine neurotransmission. The formation of new synaptic elements that are dependent on monoamine transmission could explain why patients who are depressed get worse upon the depletion of monoamines. The neurotrophic hypothesis could also explain why stress leads to depression in some, but not all, individuals. Selective vulnerability of hippocampal neurons may be increased by prior exposure to neuronal insults, such as hypoxia-ischemia, hypoglycemia, neurotoxins, and viral infections, or there may be a genetic vulnerability. In these individuals the damage resulting from prior insult may not be sufficient to cause the behavioral abnormalities associated with depression. However, when exposed to a subsequent insult or stress, the atrophy or reduction in neurogenesis becomes sufficient to cause the hippocampal-dependent symptoms of depression. One example of this is the high incidence of depression in patients of stroke (Reding et al., 1986; Federoff et al., 1992; Stern and Bachmann, 1992). Another possibility is that genetic factors increase neuronal vulnerability to stress or other insults, a hypothesis also supported by recent studies of BDNF and stress or trauma (Kaufman et al., 2006; Duman et al., 2007). Subtle damage or genetic vulnerability could also reduce the fast feedback inhibition of the HPA axis. This would lead to increased levels of glucocorticoids and further damage to hippocampal neurons. This cycle of disinhibition and damage could have significant consequences on vulnerable hippocampal neurons. This neurotrophic hypothesis provides a framework for future studies to characterize the pathophysiology and genetic basis of depression and other stress-related disorders. However, this model may be limited to certain types of depression associated with stress. Moreover, additional studies are required to determine if antidepressant treatment is neuroprotective and if it influences the atrophy or size of hippocampal neurons. Additional postmortem studies are also needed to determine if neuronal survival and dendritic arborization are associated with depression and reversed by antidepressant treatment. NEUROANATOMICAL SUBSTRATES OF DEPRESSION One of the major questions in depression research is what brain region underlies the endocrine, emotional, cognitive, and vegetative abnormalities associated with this disorder. The hippocampus, which has been the focus of many of the studies discussed in this review, is one of several regions that could contribute to many of these abnormalities. The hippocampus has been associated with learning and memory and therefore could

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also be involved in cognitive abnormalities of depression. Hippocampus is involved in feedback regulation of the HPA axis, and depression is associated with dysfunction of this neuroendocrine axis (Young et al., 1997). The hippocampus could also influence mood and emotion via indirect pathways to cortical brain regions. The results demonstrating atrophy and remodeling of hippocampal neurons in response to stress and in patients who are depressed indicate that altered function of this brain structure could contribute to certain symptoms of depression. However, there are several other limbic brain structures that also play a critical role in emotion and mood, including the PFC, amygdala, and nucleus accumbens, that are likely to be equally or even more important than hippocampus in understanding the neurobiological abnormalities that underlie mood disorders (Manji et al., 2001; Wong and Licinio, 2001; Nestler et al., 2002). In the frontal cortex, glucose metabolism, blood flow, and electroencephalogram (EEG) activity are altered in unipolar and bipolar depression (Buchsbaum et al., 1986; Baxter et al., 1989; Drevets et al., 1992; Manji and Duman, 2001). Frontal cortex has been implicated in short-term, representational memory. Recent clinical and preclinical studies provide evidence of atrophy and cell loss of PFC, which extends the neurotrophic hypothesis (Ongur et al., 1998; Rajkowska et al., 1999; Cotter et al., 2001; Radley et al., 2004; Banasr et al., 2007). Based on these findings, it has been suggested that frontal cortex could mediate the ruminative ideation observed in depression. The amygdala has been studied primarily in the regulation of fear and anxiety. This structure is associated with positive and aversive emotional stimuli. The amygdala appears to play a role in assigning affective significance to psychological and sensory stimuli (Nishijo et al., 1988; see Chapter 39). Evidence of increased blood flow and volume of the amygdala of patients who are depressive indicates a possible role of this structure in mood disorders (Drevets et al., 1992; Sheline et al., 1998; Manji and Duman, 2001). Experimental studies in animals also indicate a role for the amygdala in the pharmacological actions of antidepressant treatments (Gorka et al., 1979; Duncan et al., 1986; Ordway et al., 1991; Thome et al., 2000). Amygdala also sends and receives projections from the PFC, ventral striatum, and hippocampus, and interactions between these brain regions could underlie certain aspects of depressive behavior. Dopaminergic brain reward regions have been implicated in certain aspects of depression, including anhedonia and anergy (Nestler et al., 2002). The mesolimbic dopamine system comprises dopamine cell bodies located in the ventral tegmental area and its major projection region, the nucleus accumbens. The anhedonia associated with depression can be studied in a behav-

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ioral model of depression that is based on the consumption of sweetened water (Muscat et al., 1990). Chronic stress is reported to reduce the consumption of sweetened water, and antidepressant treatment reverses this effect. Antidepressant treatment also enhances several aspects of dopamine neurotransmission in the nucleus accumbens (Serra et al., 1992). Interestingly, studies of the regional actions of CREB have provided evidence that this transcription factor produces opposite effects in the nucleus accumbens (that is, depressive-like behavior) compared to its actions in the hippocampus in behavioral models of depression (Pliakas et al., 2001; Newton et al., 2002; Conti et al., 2002). Further studies are required to characterize the molecular and cellular adaptations in the mesolimbic dopamine system that mediate the anhedonia and loss of motivation that are often seen as symptoms of depression. Although it is possible that abnormal function of a single brain region underlies depression, it is more likely that dysfunction of multiple brain regions contribute to this disorder. Dysfunction of multiple brain regions could occur via independent mechanisms, or one region could lead to altered function of other brain regions connected to the first. Studies to further characterize the neuronal circuitry of the frontal cortex, hippocampus, amygdala, and nucleus accumbens, as well as other brain regions, will help elucidate the neuroanatomical substrates of depression. NOVEL TARGETS FOR THERAPEUTIC INTERVENTION The identification of intracellular signal transduction pathways and genes that mediate the action of antidepressant treatment will lead to novel targets for the development of faster acting and more efficacious therapeutic agents. Several possible targets that have been identified through these studies are discussed in this section. Activation of Monoamine Receptors Directly Coupled to the cAMP Cascade The hypothesis that the action of antidepressant treatment is mediated by up-regulation of the cAMP signal transduction cascade and increased expression of BDNF suggests several possible sites for intervention. First, agonist stimulation of 5-HT and NE receptors that are positively coupled to the cAMP system would lead to activation of CREB and increased expression of BDNF. Potential candidate receptors are the βAR and 5-HT4, 6, 7 receptor subtypes, as well as other neurotransmitter or neuropeptide receptors coupled to cAMP or Ca2+activated cascades. One concern with direct-acting receptor agonists is that they may cause rapid desensitization of receptors and may not be more efficacious

than currently available treatments. However, an advantage is that receptor agonists could have relatively specific effects in the hippocampus, depending on the distribution of the receptors targeted. Activation of the cAMP Cascade Another possibility would be to develop agents that directly influence the intracellular components of the cAMP pathway, for example, drugs that directly stimulate cAMP or Ca2+-activated kinases, or that directly activate CREB. Blockade of cAMP metabolism, via inhibition of cAMP-specific phosphodiesterase type IV (PDE4) isozymes, is an additional possibility to consider. A concern with drugs acting at these intracellular targets is that they would influence cell systems in many brain regions, as well as tissues throughout the body. However, such agents have the promise of being more efficacious and faster acting than treatments that act on monoamine transporter systems as their primary site of action. It is difficult to predict the specificity and effectiveness of agents acting at intracellular sites. However, there are several currently used therapeutic agents that act in this manner. The best example of such an agent that is currently used for psychiatric illness is lithium, which inhibits several enzymatic steps in the phosphatidylinositol pathway and also inhibits glycogen synthase kinase-3β. Lithium is an effective treatment of bipolar disorder, although it does have side effects. The possibility that PDE4 inhibitors may be effective for the treatment of depression is supported by basic research studies demonstrating that these agents increase the expression of CREB and BDNF and hasten the response time to other antidepressant drugs (Nibuya et al., 1996). Inhibitors of PDE4 have also been shown to be effective in animal models that predict antidepressant activity (Wachtel and Schneider, 1986; O’Donnell, 1993), and studies demonstrating an induction of adult neurogenesis (Nakagawa et al., 2002). The clinical utility of PDE inhibitors for the treatment of depression has been examined previously (Wachtel, 1983; Horowski and Sastre-Y-Hernandez, 1985). These early studies reported that rolipram, a relatively specific inhibitor of PDE4, had antidepressant effects in approximately two thirds of patients tested, similar to monoamine reuptake inhibitor antidepressants. However, rolipram also produced side effects, most notably nausea. Another possibility is that PDE4 inhibitors, at lower doses, may enhance or hasten the response to a typical antidepressant that blocks the reuptake or breakdown of 5-HT and NE. There is a preliminary report that cotreatment with a nonselective PDE inhibitor and an antidepressant drug resulted in a significant improvement of a drug resistant patient (Malison et al., 1997). Additional studies are needed to determine if PDE inhibitors may

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have general usefulness for enhancing the actions of antidepressant drugs. It may also be possible to develop inhibitors that are selective for specific PDE isozymes. The PDE4 family includes four separate genes, each of which has multiple splice variants (Conti et al., 1995). Given this heterogeneity, it may be possible to identify a single PDE isozyme or splice variant, the inhibition of which may have antidepressant actions without unwanted side effects. Recent evidence suggests a possible role of the PDE4A and PDE4B isoforms (Takahashi et al., 1999), although PDE4D mutant mice also display an antidepressant-like behavioral phenotype, as would be predicted if this were a relevant isoform (Zhang et al., 2004). Further studies at the basic research level are needed to characterize the regional distribution and antidepressant regulation of the PDE isozymes, as well as isozymes for other intracellular signal transduction proteins, that may be targets for the development of antidepressant treatments. CONCLUSIONS The results and strategies discussed provide a framework for future studies, at the basic and clinical levels, to further characterize the pathophysiology and treatment of depression. Studies of intracellular signal transduction pathways provide new information about the action of antidepressant treatment that could not be determined from studies of monoamines or their receptors. Importantly, this work indicates that the cAMP system is increased, not decreased, by antidepressant treatments. In addition, identification of intracellular cascades provides new strategies for identification of target genes that are regulated by, and contribute to, the therapeutic action of antidepressant treatments. For example, the results of preclinical studies indicate that up-regulation of BDNF could serve to reverse the atrophy or damage of vulnerable neurons, or protect these neurons from further damage. Identification of these pathways and target genes will provide novel targets for the development of therapeutic agents. Moreover, dysfunction of intracellular signal transduction proteins and target genes could be closely related to the molecular determinants that underlie the pathophysiology of depression. In this case, decreased expression of BDNF could contribute to neuronal atrophy and depressed mood, especially when combined with stress or neuronal insult. This hypothesis could be tested at the basic research level using BDNF mutant mice that express altered levels of this neurotrophic factor. At the clinical level, additional postmortem studies will be needed to determine if there is a reduction in the size or number of hippocampal neurons in the brains of patients who are depressed, and if there is a relationship of

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these effects with the amount or function of CREB. Finally, a more complete understanding of depression will be dependent on critical, future studies to identify the additional intracellular pathways and target genes, and genetic polymorphisms that are involved in the etiology and treatment of this complex psychiatric disorder.

ACKNOWLEDGMENTS This work is supported by U.S. Public Health Service grants MH45481, MH53199, and 2 PO1 MH25642 and by a Veterans Administration National Center Grant for PTSD at the West Haven Connecticut VA Medical Center.

REFERENCES Allain, H., Lieury, A., Brunet-Bourgin, F., Mirabaud, C., Trebon, P., Le Coz, F., and Gandon, J.M. (1992) Antidepressants and cognition: comparative effects of moclobemide, viloxazine and maprotiline. Psychopharmacology 106:S56–S61. Arancio, O., and Chao, M.V. (2007) Neurotrophins, synaptic plasticity and dementia. Curr. Opin. Neurobiol. 17:325–330. Artigas, F., Perez, V., and Alvarez, E. (1994) Pindolol induces a rapid improvement of depressed patients treated with serotonin reuptake inhibitors. Arch. Gen. Psychiatry 51:248–251. Avorn, J., Everitt, D.E., and Weiss, S (1986) Increased antidepressant use in patients prescribed b-blockers. JAMA 255:357–360. Ballaz, S.J., Akil, H., and Watson, S.J. (2007) Analysis of 5-HT6 and 5-HT7 receptor gene expression in rats showing differences in novelty-seeing behavior. Neurosci. 247:428– 438. Banasr, M., Valentine, G.W., Li, X.Y., Gourley, S., Taylor, J., and Duman, R.S. (2007) Chronic stress decreases cell proliferation in adult cerebral cortex of rat: reversal by antidepressant treatment. Biol. Psychiatry 62:495–504. Banerjee, S.P., Kung, L.S., Riggi, S.J., and Chanda, S.K. (1977) Development of b-adrenergic receptor subsensitivity by antidepressants. Nature 268:455–456. Barden, N.R.J., Reul, J.M., and Holsboer, F. (1995) Do antidepressants stabilize mood through actions on the hypothalamic-pituitaryadrenocorticalo system? Trends Neurosci. 18(1):6–11. Barrot, M., Olivier, J.D., Perrotti, L.I., DiLeone, R.J., Berton, O., Eisch, A.J., Impey, S., Storm, D.R., Neve, R.L., Yin, J.C., Zachariou, V., and Nestler, E.J. (2002) CREB activity in the nucleus accumbens shell controls gating of behavioral responses to emotional stimuli. Proc. Natl. Acad. Sci. USA 99:11435–11440. Baxter, L., Schwartz, J.M., Phelps, M.E., Mazziota, J.C., Guze, B.H., Selin, C.R., Gerner, R.H., and Sumida, R.M. (1989) Reduction of prefrontal cortex glucose metabolism common to three types of depression. Arch. Gen. Psychiatry 46:243–250. Benes, F., Kwok, E.W., Vincent, S.L., and Todtenkopf, M.S. (1998) A reduction of nonpyramidal cells in sector CA2 of schizophrenics and manic depressives. Biol. Psychiatry 15:88–97. Berton, O., and Nestler, E. (2006) New approaches to antidepressant drug discovery: beyond monoamines. Nat. Rev. Neurosci. 7: 137–151. Blier, P., and de Montigny, C. (1994) Current advances and trends in the treatment of depression. Trends Pharmacol. Sci. 15(7):220–226. Bliss, T., and Collingridge, G. (1993) A synaptic model of memory: long-term potentiation in the hippocampus. Nature 361:31–39. Bremner, J.D., Randall, P., Scott, T.M., Bronen, R.A., Seibyl, J.P., Southwick, S.M., Delaney, R.C., McCarthy, G., Charney, D.S., and Innis, R.B. (1995) MRI-based measurement of hippocampal volume in patients with combat-related posttraumatic stress disorder. Am. J. Psychiatry 152:973–981.

430

MOOD DISORDERS

Buchsbaum, M., Wu, J., DeLisi, L.E., Holcomb, H., Kessler, R., Johnson, J., King, A.C., Hazlett, E., Langston, K., and Post, R.M. (1986) Frontal cortex and basal ganglia metabolic rates assisted by positron emission tomography with [18F]2-deoxyglucose in affective illness. J. Affect. Disord. 10:137–152. Bunney, W., and Davis, J. (1965) Norepinephrine in depressive reactions: a review. Arch. Gen. Psychiatry 13:483– 494. Butler, M., Morinobu, S., and Duman, R.S. (1993) Chronic electrocovulsive seizures increase the expression of serotonin2 receptor mRNA in rat frontal cortex. J. Neurochem. 61:1270–1276. Chalmers, D., Lovenberg, T.W., Grigoriadis, D.E., Behan, D.P., and DeSouza, E.B. (1996) Corticotrophin-releasing factor receptors: from molecular biology to drug design. Trends Pharmacol. Sci 17:166–172. Charney, D.S., Menkes, D.B., and Heninger, G.R. (1981) Receptor sensitivity and the mechanism of action of antidepressant treatment. Arch. Gen. Psychiatry 38:1160–1173. Chen, B., Dowlatshahi, D., MacQueen, G.M., Wang. J.-F., and Young, L.T. (2001) Increased hippocampal BDNF immunoreactivity in subjects treated with antidepressant medication. Biol. Psychiatry 50:260–265. Colin, S., Chang, H.-C., Mollner, S., Pfeuffer, T., Reed, R.R., Duman, R.S., and Nestler, E.J. (1991) Chronic lithium regulates the expression of adenylate cyclase and Gi-protein alpha subunit in rat cerebral cortex. Proc. Natl. Acad. Sci. USA 88:10634 –10637. Condorelli, D., Dell’Albani, P., Mudo, G., Timmusk, T., and Belluardo, N. (1994) Expression of neurotrophins and their receptors in primary astroglial cultures: induction by cAMP elevating agents. J. Neurochem. 63:509–516. Conti, A., Cryan, J.F., Dalvi, A., Lucki, L., and Blendy, J.A. (2002) CREB is essential for the upregulation of BDNF transcription, but not the behavioral or endocrine responses to antidepressant drugs. J. Neurosci. 22(8):3262–3268. Conti, M., Nemoz, G., Sette, C., and Vicini, E. (1995) Recent progress in understanding the hormonal regulation of phosphodiesterases. Endocr. Rev. 16:370–389. Coppen, A. (1967) The biochemistry of affective disorders. Br. J. Psychiatry 113:1237–1264. Cotter, D., Mackay, D., Landau, S., Kerwin, R., and Everall, I. (2001) Reduced glial cell density and neuronal size in the anterior cingulate cortex in major depressive disorder. Arch. Gen. Psychiatry 58:545–553. Czeh, B., Michaelis, T., Watanabe, T., Frahm, J., de Biurrun, G., van Kampen, M., Bartololomucci, A., and Fuchs, E. (2001) Stressinduced changes in cerebral metabolites, hippocampal volume, and cell proliferation are prevented by antidepressant treatment with tianeptine. Proc. Natl. Acad. Sci. USA 98(22):12796–12801. Delgado, P., Price, L.H., Miller, H.L., Salomon, R.M., Aghajanian, G., Heninger, G.R., and Charney, D. (1994) Serotonin and the neurobiology of depression. Arch. Gen. Psychiatry 51:865–874. Dowlatshahi, D., MacQueen, G.M., Wang, J.F., and Young, L.T. (1998) Increased temporal cortex CREB concentrations and antidepressant treatment in major depression. Lancet 352:1754 –1755. Dowlatshahi, D., and Young, L.T. (2000) Molecular abnormalities in brains of depressed patients. Neuroscientist 6:401– 410. Drevets, W., Videen, T.O., Price, J.L., Preskorn, S.H., Carmichael, S.T., and Raichle, M.E. (1992) A functional anatomical study of unipolar depression. J. Neurosci. 12:3628–3641. Duman, C., Schlesinger, L., Kodama, M., Russell, D.S., and Duman, R.S. (2007) A role for MAPK signaling in behavioral models of depression and antidepressant treatment. Biol. Psychiatry 61(5): 660–670. Duman, R. (2004) Depression: a case of neuronal life and death? Biol. Psychiatry 56:140–145. Duman, R., Malberg, J., Nakagawa, S., and D’Sa, C. (2000) Neuronal plasticity and survival in mood disorders. Biol. Psychiatry 48: 732–739.

Duman, R., and Monteggia, L.M. (2006) A neurotrophic model for stress-related mood disorders. Biol. Psychiatry 59:1116–1127. Duncan, G., Breese, G.R., Criswell, H., Stumpf, W.E., Mueller, R.A., and Covey, J.B. (1986) Effects of antidepressant drugs injected into the amygdala on behavioral responses of rats in the forced swim test. J. Pharmacol. Exp. Ther. 238:758–762. Dwivedi, Y., Rao, J.S., Hooriyah, S.R., Kotowski, J., Conley, R.R., Roberts, R.C., Tamminga, C.A., and Pandey, G.N. (2003) Abnormal expression and functional characteristics of cyclic adenosine monophosphate response element binding protein in postmortem brain of suicide subjects. Arch Gen. Psychiatry 60: 273–282. Federoff, J., Starkstein, S., and Forrester, A. (1992) Depression in patients with acute traumatic brain injury. Am. J. Psychiatry 149: 918–923. Gage, F. (2000) Mammalian neural stem cells. Science 287:1433–1438. Ghosh, A., Carnahan, J., and Greenberg, M.E. (1994) Requirement for BDNF in activity-dependent survival of cortical neurons. Science 263:1618–1623. Ghosh, A., and Greenberg, M.E. (1995) Calcium signaling in neurons: molecular mechanisms and cellular consequences. Science 268:239–247. Goodwin, F.K., Prange, A.J., Post, R.M., Muscettola, G., and Lipton, M.A (1982) Potentiation of antidepressant effect by triiodothyronine in tricyclic nonresponders. Am. J. Psychiatry 139:34–38. Gorka, Z., Ossowska, K., and Stach, R. (1979) The effect of unilateral amygdala lesion on the imipramine action in behavioural despair in rats. J. Pharm. Pharmacol. 31:647–648. Gould, E., Reeves, A.J., Graziano, M.S.A., and Gross, C.G. (1999) Neurogenesis in the neocortex of adult primates. Science 286:548–552. Gould, E., Tanapat, P., McEwen, B.S., Flugge, G., and Fuchs, E. (1998) Proliferation of granule cell precursors in the dentate gyrus of adult monkeys is diminished by stress. Proc. Natl. Acad. Sci. USA 95:3168–3171. Hajszan, T., Maclusky, N.J., and Leranth, C. (2005) Short-term treatment with the antidepressant fluoxetine triggers pyramidal dendritic spine synapse formation in rat hippocampus. Eur. J. Neurosci. 21:1299–1303. Hamon, M., Doucet, E., Lefevre, K., Miquel, M.C., Lanfumey, L., Insausti, R., Frechilla, D., Del Rio, J., and Verge, D. (1999) Antibodies and antisense oligonucleotide for probing the distribution and putative functions of central 5-HT6 receptors. Neuropsychopharmacology 21:68S –76S. Heine, V., Zareno, J., Maslam, S., Joels, M., and Lucassen, P.J. (2005) Chronic stress in the adult dentate gyrus reduces cell proliferation near the vasculature and VEGF and Flk-1 protein expression. Eur. J. Neurosci. 21:1304 –1314. Heninger, G.R., and Charney, D.S. (1987) Mechanisms of Action of Antidepressant Treatments: Implications for the Etiology and Treatment of Depressive Disorders. New York: Raven Press. Holsboer, F. (1999) The rationale for corticotropoin-releasing hormone receptor (CRH-R) antagonists to treat depression and anxiety. J. Psychiatric Res. 33:181–214. Horowski, R., and Sastre-Y-Hernandez, M. (1985) Clinical effects of the neurotrophic selective cAMP phosphodiesterase inhibitor rolipram in depressed patients: global evaluation of the preliminary reports. Curr. Ther. Res. 38:23–29. Hoshaw, B., Malberg, J.E., and Lucki, I. (2005) Central administration of IGF-I and BDNF leads to long-lasting antidepressant-like effects. Brain Res. 1037:204 –208. Jin, K., Xie, L., Kim, S.H., Parmentier-Batteur, S., Sun, Y., Mao, X.O., Childs, J., and Greenberg, D.A. (2004) Defective adult neurogenesis in CB1 cannabinoid receptor knockout mice. Mol. Pharmacol. 66:204 –208. Kang, H., and Schuman, E.M. (1995) Long-lasting neurotrophininduced enhancement of synaptic transmission in the adult hippocampus. Science 267:1658–1662.

29: NEUROCHEMICAL THEORIES OF DEPRESSION Kaufman, J., Yang, B.Z., Douglas-Palumberi, H., Grasso, D., Lipschitz, D., Houshyar, S., Krystal, J.H., and Gelernter, J. (2006) Brainderived neurotrophic factor-5-HTTLPR gene interactions and environmental modifiers of depression in children. Biol. Psychiatry 59:673–680. Kramer, M., Cutler, N., Feighner, J., Shrivastava, R., Carman, J., Sramek, J.J., Reines, S.A., Liu, G., Snavely, D., Wyatt-Knowles, E., et al. (1998) Distinct mechanism for antidepressant activity by blockade of central substance P receptors. Science 281:1640–1645. Levine, E., Dreyfus, C.F., Black, I.B., and Plummer, M.R. (1995) Brain-derived neuroprophic factor rapidly enhances synaptic transmission in hippocampal neurons via postsynaptic tyrosine kinase receptors. Proc. Natl. Acad. Sci. USA 92:8074 –8077. Levkovitz, Y., Grisaru, N., and Segal, N. (2001) Transcranial magnetic stimulation and antidepressive drugs share similar cellular effects in rat hippocampus. Neuropsychopharmacology 24: 608 – 616. Lindsay, R.M., Wiegand, S.J., Altar, A., and DiStefano, P.S. (1994) Neurotrophic factors: from molecule to man. Trends Neurosci. 17:182–190. Lindvall, O., Kokaia, Z., Bengzon, J., Elmer, E., and Kokaia, M. (1994) Neurotrophins and brain insults. Trends Neurosci. 17:490 – 496. Lucas, G., Compran, V., Charnay, Y., Neve, R.L., Nestler, E.J., Bockaert, J., Barrot, M., and Debonnel, G. (2005) Frontocortical 5-HT4 receptors exert positive feedback on serotonergic activity: viral transfactions, subacute and chronic treatments with 5-HT4 agonists. Biol. Psychiatry 15:918–925. Lucas, G., and Debonnel, G. (2002) 5-HT4 receptors exert a frenquency-related facilitatory control on dorsal raphe nucleus 5-HT neuronal activity. Eur. J. Neurosci. 16:817–822. Lucas, G., Rymar, V.V., Du, J., Mnie-Filali, O., Bisgaard, C., Manta, S., Lambas-Senas, L., Wiborg, O., Haddjeri, N., Pineyro, G., Sadikot, A.F., and Debonnel, G. (2007) Serotonin (4) (5-HT (4)) receptor agonists are putative antidepressants with a rapid onset of action. Neuron 55:712–134. Madison, D., Malenka, R.C., and Nicoll, R.A. (1991) Mechanisms underlying long-term potentiation of synaptic transmission. Ann. Rev. Neurosci. 14:379–399. Malberg, J., and Duman, R.S. (2003) Cell proliferation in adult hippocmpus is decreased by inescapable stress: reversal by fluoxetine treatment. Neuropsychopharmacology 28:1562–1571. Malberg, J., Eisch, A.J., Nestler, E.J., and Duman, R.S. (2000a) Chronic antidepressant treatment increases neurogenesis in adult hippocampus. J. Neurosci. 20:9104 –9110. Malberg, J., Eisch, A.J., Nestler, E.J., and Duman, R.S. (2000b) Effects of antidepressant treatment and learned helplessness training on hippocampal neurogenesis in adult rat. Soc. Neurosci. Abstr. 26:1044. Malison, R., Price, L.H., Nestler, E.J., Heninger, G.R., and Duman, R.S. (1997) Efficacy of papaverine addition in treatment-refractory major depression. Am. J. Psychiatry 154:579–580. Mamounas, L., Blue, M.E., Siuciak, J.A., and Anthony, A.C. (1995) BDNF promotes the survival and sprouting of serotonergic axons in the rat brain. J. Neurosci. 15:7929–7939. Manier, D., Eiring, A., Shelton, R.C., and Sulser, F. (1996) bAdrenoceptor-linked protein kinase A (PKA) activity in human fibroblasts from normal subjects and from patients with major depression. Neuropsychopharmacology 15:556–561. Manji, H., Drevets, W.C., and Charney, D.S. (2001) The cellular neurobiology of depression. Nat. Med. 7:541–547. Manji, H., and Duman, R.S. (2001) Impairments of neuroplasticity and cellular resilience in severe mood disorders: implications for the development of novel therapeutics. Psychopharmacol. Bull. 35:5– 49. Manji, H.K., Etcheberrigaray, R., Chen, G., and Olds, J.L. (1993) Lithium decreases membrane-associated protein kinase hippocampus selectivity for the alpha isozyme. J. Neurosci. 61:2303–2310.

431

Margarinos, A., McEwen, B.S., Flugge, G., and Fuchs, E. (1996) Chronic psychosocial stress causes apical dendritic atrophy of hippocampal CA3 pyramidal neurons in subordinate tree shrews. J. Neurosci. 16:3534–3540. Massicotte, G., Bernard, J., and Ohayon, M. (1993) Chronic effects of trimipramine, an antidepressant, on hippocampal synaptic plasticity. Behav. Neural Biol. 59:100–106. McAllister, A., Katz, L.C., and Lo, D.C. (1996) Neurotrophin regulation of cortical dendritic growth requires activity. Neuron 17: 1057–1064. McAllister, K., Katz, L.C., and Lo, D.C. (1999) Neurotrophins and synaptic plasticity. Ann. Rev. Neurosci. 22:295–318. McEwen, B. (2002) Sex, stress and the hippocampus: allostatic load and the aging process. Neurobiol. Aging 23:921–939. McMahon, F., Buervenich, S., Charney, D., Lipsky, R., Rush, A.J., Wilson, A.F., Sorant, A.J., Papanicolaou, G.J., Laje, G., Fava, M., Trivedi, M.H., Wisniewski, S.R., and Manji, H. (2006) Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am. J. Hum. Genet. 78:804–814. Melia, K., Rasmussen, K., Haycock, J., Terwilliger, R.Z., Nestler, E.J., and Duman, R.S. (1992) Coordinate regulation of firing rate, tyrosine hydroxylase, and the cAMP system in rat locus coeruleus: effects of chronic stress and norepinephrine depleting agents. J. Neurochem. 58:494–502. Menkes, D.B., Rasenick, M.M., Wheeler, M.A., and Bitensky, M.W. (1983) Guanosine triphosphate activation of brain adenylate cyclase: enhancement by long-term antidepressant treatment. Science 129:65–67. Meyer, T., and Habener, J.F. (1993) Cyclic adenosine 3′,5′monophosphate response element-binding protein (CREB) and related transcription-activating deoxyribonucleic acid-binding proteins. Endocr. Rev. 14:269–290. Miller, H., Delgado, P.L., Salomon, R.M., Berman, R., Krystal, J.H., Heninger, G.R., and Charney, D.S. (1996) Clinical and biochemical effects of catecholamine depletion on antidepressant induced remission of depression: implications for monoamine hypothesis of antidepressant action. Arch. Gen. Psychiatry 53: 117–128. Mitra, R., Jadhav, S., McEwen, B.S., Vyas, A., and Chattarji, S. (2005) Stress duration modulates the spatiotemporal patterns of spine formation in the basolateral amygdala. Proc. Natl. Acad. Sci. USA 102:9371–9376. Monteggia, L., Barrot, M., Powell, C.M., Berton, O., Galanis, V., Gemelli, T., Meuth, S., Nagy, A., Greene, R.W., and Nestler, E.J. (2004) Essential role of brain-derived neurotrophic factor in adult hippocampal function. Proc. Natl. Acad. Sci. USA 101: 10827–10832. Monteggia, L., Luikart, B., Barrot, M., Theobold, D., Malkovska, I., Nef, S., Parada, L.F., and Nestler, E.J. (2007) Brain-derived neurotrophic factor conditional knockouts show gender differences in depression-related behaviors. Biol. Psychiatry 61(2): 187–197. Morinobu, S., Nibuya, M., and Duman, R.S. (1995) Chronic antidepressant treatment down-regulates the induction of c-fos mRNA in response to acute stress in rat frontal cortex. Neuropsychopharmacology 12:221–228. Muller, M., Lucassen, P.J., Yassouridis, A., Hoogendijk, J.G., Holsboer, F., and Swabb, D.F. (2001) Neither major depression nor glucocorticoid treatment affects the cellular integrity of the human hippocampus. Eur. J. Neurosci. 14:1603–1612. Muscat, R., Sampson, D., and Willner, P. (1990) Dopaminergic mechanism of imipramine action in an animal model of depression. Biol. Psychiatry 28:223–230. Nakagawa, S., Kim, J.-E., Lee, R., Chen, J., and Duman, R.S. (2000) CREB plays a critical role in the survival of newborn cells in the adult hippocampus. Soc. Neurosci. Abstr. 26:2317.

432

MOOD DISORDERS

Nakagawa, S., Kim, J.-E., Lee, R., Malberg, J.E., Chen, J., Steffen, C., Zhang, Y.-J., Nestler, E.J., and Duman, R.S. (2002) Regulation of neurogenesis in adult mouse hippocampus by cAMP and cAMP response element-binding protein. J. Neurosci. 22(9): 3673–3682. Naudon, L., Hotte, M., and Jay, T.M. (2007) Effects of acute and chronic antidepressant treatment on memory performance: a comparison between paroxetine and imipramine. Psychopharmacology (Berl) 191:353–364. Nemeroff, C., Widerlov, E., Bissette, G., Walleus, H., Karlsson, I., Eklund, K., Kilts, C.D., Loosen, P.T., and Vale, W. (1984) Elevated concentrations of CSF corticotropin-releasing factor-like immunoreactivity in depressed patients. Science 226:1342–1344. Nestler, E., Barrot, M., DiLeone, R.J., Eisch, A.J., Gold, S.J., and Monteggia, L.M. (2002) Neurobiology of depression. Neuron 34:13–25. Nestler, E., and Duman, R.S. (2006) G Proteins. New York: Elsevier. Nestler, E., Terwilliger, R.Z., and Duman, R.S. (1989) Chronic antidepressant administration alters the subcellular distribution of cAMP-dependent protein kinase in rat frontal cortex. J. Neurochem. 53:1644–1647. Newton, S., Thome, J., Wallace, T.L., Shirayama, Y., Schlesinger, L., Sakai, N., Chen, N., Neve, R., Nestler, E.J., and Duman, R.S. (2002) Inhibition of cAMP response element-binding protein or dynorphin in the nucleus accumbens produces an antidepressantlike effect. J. Neurosci. 24:10883–10890. Nibuya, M., Morinobu,, S., and Duman, R.S. (1995) Regulation of BDNF and trkB mRNA in rat brain by chronic electroconvulsive seizure and antidepressant drug treatments. J. Neurosci. 15: 7539– 7547. Nibuya, M., Nestler, E.J., and Duman, R.S. (1996) Chronic antidepressant administration increases the expression of cAMP response element binding protein (CREB) in rat hippocampus. J. Neurosci. 16:2365–2372. Nishijo, H., Ono, T., and Nishino, H. (1988) Single neuron responses in amygdala of alert monkey during complex sensory stimulation with affective significance. J. Neurosci. 8:3570–3583. Nowakowska, E., Kus, K., Chodera, A., and Rybakowski, J. (2000) Behavioural effects of fluoxetine and tianeptine, two antidepressants with opposite action mechanisms, in rats. Arzneimittelforschung 50:5–10. Nowakowska, E., Kus, K., Chodera, A., and Rybakowski, J. (2003) Comparison of behavioural effects of venlafaxine and imipramine in rats. Arzneimittelforschung 53:237–242. Nowakowska, E., Kus, K., Florek, E., Czubak, A., and JodynisLiebert, J. (2006) The influence of tobacco smoke and nicotine on antidepressant and memory-improving effects of venlafaxine. Hum. Exp. Toxicol. 25:199–209. O’Connor, J., Rowan, M.J., and Anwyl, R. (1993) Use-dependent effects of acute and chronic treatment with imipramine and buspirone on excitatory synaptic transmission in the rat hippocampus in vivo. Naunyn Schmiedeberg’s Arch. Pharmacol. 348:158–163. Odagaki, Y., Garcia-Sevilla, J.A., Huguelet, P., La Harpe, R., Koyama, T., Guimon, L (2001) Cyclic AMP-mediated signaling components are upregulated in the prefrontal cortex of depressed suicide cictims. Brain Research 898:224–231. O’Donnell, J. (1993) Involvement of beta-1 and beta-2 adrenergic receptors in the antidepressant-like effects of centrally administered isoproterenol. J. Pharm. Exp. Ther. 271:246–254. Ongur, D., Drevets, W.C., and Price, J.L. (1998) Glial reduction in the subgenual prefrontal cortex in mood disorders. Proc. Natl. Acad. Sci. USA 95:13290–13295. Ordway, G., Gambarana, C., Tejani-Butt, S.M., Areso, P., Hauptmann, M., and Frazer, A. (1991) Preferential reduction of binding of 125IIodopindolol to beta-1-adrenoceptors in the amygdala of rat after antidepressant treatments. J. Pharm. Exp. Ther. 257:681–690.

Owens, M., and Nemeroff, C.B. (1999) Corticotropin-releasing factor antagonists in affective disorders. Expert Opin. Invest. Drugs 8:1849–1858. Ozawa, H., and Rasenick, M.M. (1991) Chronic electroconvulsive treatment augments coupling of the GTP-binding protein Gs to the catalytic moiety of adenylyl cyclase in a manner similar to that seen with chronic antidepressant drugs. J. Neurochem. 56:330–338. Paul, I., Nowak, G., Layer, R.T., Popik, P., and Skolnick, P. (1994) Adaptation of N-methyl-D-aspartate receptor complex following chronic antidepressant treatments. J. Pharm. Exp. Ther. 269:95–102. Paykel, E.S., Fleminger, R., and Watson, J.P. (1982) Psychiatric side effects of antihypertensive drugs other than reserpine. J. Clin. Psychopharmacol. 2:14–39. Perez, J., Tardito, D., Racagni, G., Smeraldi, E., and Zanardi, R. (2001) Protein kinase A and Rap1 levels in platelets of untreated patients with major depression. Mol. Psychiatry 6:44 – 49. Perez, J., Tinelli, D., Brunello, N., and Racagni, G. (1989) cAMPdependent phosphorylation of soluble and crude microtubule fractions of rat cerebral cortex after prolonged desmethylimipramine treatment. Eur. J. Pharmacol. 172:305–316. Peroutka, S., and Snyder, S.H. (1980) Long-term antidepressant treatment decreases spiroperidol labeled serotonin receptor binding. Science 210:88–90. Pliakas, A., Carlson, R.R., Neve, R.L., Konraki, C., Nestler, E.J., and Carlezon, W.A. (2001) Altered responsiveness to cocaine and increased immobility in the forced swim test associated with elevated CREB expression in the nucleus accumbens. J. Neurosci. 21:7397–7403. Price, L., Charney, D.S., and Heninger, G.R. (1985) Effects of tranylcypromine treatment on neuroendocrine, behavioral, and autonomic responses to tryptophan in depressed patients. Life Sci. 37: 809–818. Radley, J., Sisti, H.M., Hao, J., Rocher, A.B., McCall, T., Hof, P.R., McEwen, B.S., and Morrison, J.H. (2004) Chronic behavioral stress induces apical dendritic reorganization in pyramidal neurons of the medial prefrontal cortex. Neurosci. 125:1–6. Rajkowska, G., Miguel-Hidalgo, J.J., Wei, J., Dilley, G., Pittman, S.D., Meltzer, H.Y., Overholser, J.C., Roth, B.L., and Stockmeier, C.A. (1999) Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression. Biol. Psychiatry 45: 1085–1098. Rasmussen, A., Shi, L., and Duman, R.S. (2002) Down-regulation of BDNF mRNA in the hippocampal dentate gyrus after reexposure to cues previously associated with footshock. Neuropsychopharmacology 27(2):133–142. Reding, M., Orto, L.A., Winter, S.W., Firtuna, I.M., DiPoonte, P., and McDowell, F.H. (1986) Antidepressant therapy after stroke. Arch. Neurol. 43:763–765. Riva, M., and Creese, I. (1989) Reevaluation of the regulation of b-adrenergic receptor binding by desipramine treatment. Mol. Pharmacol. 36:211–218. Russell, D., and Duman, R.S. (2002) Neurotrophic Factors and Intracellular Signal Transduction Pathways. Philadelphia: Lippincott Williams and Wilkins. Saarelainen, T., Hendolin, P., Lucas, G., Koponen, E., Sairanen, M., MacDonald, E., Agerman, K., Haapasalo, A., Nawa, H., Aloyz, R., Ernfors, P., and Castren, E. (2003) Activation of the trkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects. J. Neurosci. 23:349–357. Santarelli, L., Saxe, M., Gross, C., Surget, A., Battaglia, F., Dulawa, S., Weisstaub, N., Lee, J., Duman, R., Aranico, O., Belzung, C., and Hen, R. (2003) Requirement of hippocampal neurogenisis for the behavioral effects of antidepressants. Science 301:805–809. Sapolsky, R. (1996) Glucocorticoids and atrophy of the human hippocampus. Science 273:749–750.

29: NEUROCHEMICAL THEORIES OF DEPRESSION Sapolsky, R., Krey, L.C., and McEwen, B.S. (1985) Prolonged glucocorticoid exposure reduces hippocampal neuron number: implications for aging. J. Neurosci. 5:1222–1227. Sapolsky, R.M., Uno, H., Robert, C.S., and Finsh, C.E. (1990) Hippocampal damage associated with prolonged glucocorticoid exposure in primates. J. Neurosci. 10:2897–2902. Schildkraut, J. (1965) The catecholamine hypothesis of affective disorders: a review of supporting evidence. Am. J. Psychiatry 122: 509–522. Serra, G., Collu, M., D’Aquila, P.S., and Gessa, G.L. (1992) Role of the mesolimbic dopamine system in the mechanism of action of antidepressants. Pharmol. Toxicol. 71:72–85. Sheline, Y., Gado, M.H., and Price, J.L. (1998) Amygdala core nuclei volumes are decreased in recurrent major depression. Neuroreport 9:2023–2028. Sheline, Y., Sanghavi, M., Mintun, M.A., and Gado, M.H. (1999) Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. J. Neurosci. 19:5034–5043. Sheline, Y., Wany, P., Gado, M.H., Csernansky, J.G., and Vannier, M.W. (1996) Hippocampal atrophy in recurrent major depression. Proc. Natl. Acad. Sci. USA 93:3908–3913. Shirayama, Y., Chen, A.C.-H., Nakagawa, S., Russell, R.S., and Duman, R.S. (2002) Brain derived neurotrophic factor produces antidepressant effects in behavioral models of depression. J. Neurosci. 22:3251–3261. Shopsin, B., Gershon, S., Goldstein, M., Friedman, E., and Wilk, S. (1975) Use of synthesis inhibitors in defining a role for biogenic amines during imipramine treatment in depressed patients. Psychopharmacol. Comm. 1:239–249. Siuciak. J., Altar, C.A., Wiegand, S.J., and Lindsay, R.M. (1994) Antinociceptive effect of brain-derived neurotrophic factor and neurotrophin-3. Brain Res. 633:326–330. Siuciak, J.A., Lewis, D.R., Wiegand, S.J., and Lindsay, R. (1997) Antidepressant-like effect of brain derived neurotrophic factor (BDNF). Pharmacol. Biochem. Beh. 56:131–137. Sklair-Tavron, L., and Nestler, E.J. (1995) Opposing effects of morphine and the neurotrophins, NT-3, NT-4, and BDNF, on locus coeruleus neurons in vitro. Brain Res. 702:117–125. Sleight, A., Carolo, C., Petit, N., Zwingelstein, C., and Bourson, A. (1995) Identification of 5-hydroxytryptamine 7 receptor binding sites in rat hypothalamus: sensitivity to chronic antidepressant treatments. Mol. Pharmacol. 47:99–103. Smith, M.A., Makino, S., Kvetnansky, R., and Post, R.M. (1995) Stress alters the express of brain-derived neurotrophic factor and neurotrophin-3 mRNAs in the hippocampus. J. Neurosci. 15:1768–1777. Spring, B., Gelenberg, A.J., Garvin, R., and Thompson, S. (1992) Amitriptyline, clovoxamine and cognitive function: a placebo-controlled comparison in depressed outpatients. Psychopharmacology 108: 327–332. Stein-Behrens, B., Mattson, M.P., Chang, I., Yeh, M., and Sapolsky, R. (1994) Stress exacerates neuron loss and cytoskeletal pathology in the hippocampus. J. Neurosci. 14:5373–5380. Stern, R., and Bachmann, D.L. (1992) Depressive symptoms following stroke. Am. J. Psychiatry 148:351–356. Stewart, C.A., and Reid, J.C. (2000) Repeated ECS and fluoxetine administration have equivalent effects on hippocampal synaptic plasticity. Psychopharmacology 48(3):217–123. Stockmeier, C., Mahajan, G.J., Konick, L.C., Overholser, J.C., Jurjus, G.J., Meltzer, H.Y., Uylings, H.B.M., Friedman, L., and Rajkowska, G. (2004) Cellular changes in the postmortem hippocampus in major depression. Biol. Psychiatry 56:640–650. Sulser, F., Vetulani, J., and Mobley, P. (1978) Mode of action of antidepressant drugs. Biochem. Pharmacol. 27:257–261. Svenningsson, P., Chergui, K., Rachleff, I., Flajolet, M., Zhang, X., Le Jacobi, M., Vaugeois, J.M. Nomikos, G.G., and Greengard, P.

433

(2006) Alterations in 5-HT1B receptor function by p11 in depression-like states. Science 311:77–80. Svenningsson, P., Tzavara, E.T., Liu, F., Fienberg, A.A., Nomikos, G.G., and Greengard, P. (2002) DARPP-32 mediates serotonergic neurotransmission in the forebrain. Proc. Natl. Acad. Sci. USA 99:3188–3193. Svenningsson, P., Tzavara, E.T., Witkin, J.M., Fienberg, A.A., Nomikos, G.G., and Greengard, P. (2002) Involvement of striatal and extrastriatal DARPP-32 in biochemical and behavioral effects of fluoxetine (Prozac). Proc. Natl. Acad. Sci. USA 99:3182–3187. Takahashi, M., Terwilliger, R., Lane, S., Mezes, P.S., Conti, M., and Duman, R.S. (1999) Chronic antidepressant administration increases the expression of cAMP phosphodiesterase 4A and 4B isoforms. J. Neurosci. 19:610–618. Tanis, K., and Duman, R.S. (2007) Intracellular signaling pathways pave roads to recovery for mood disorders. Annals of Medicine 39:531–544. Tao, X., Finkbeiner, S., Arnold, D.B., Shaywitz, A.J., Greenberg, M.E. (1998) Ca2+ influx regulates BDNF transcription by a CREB family transcription factor-dependent mechanism. Neuron 20:709–726. Tardito, D., Perez, J., Tiraboschhi, E., Musazzi, L., Racagni, G., Popoli, M. (2006) Signaling pathways regulating gene expression, neuroplasticity, and neurotrophic mechanisms in the action of antidepressants: a critical overview. Pharmacol. Rev. 58:115–134. Thoenen, H. (1995) Neurotrophins and neuronal plasticity. Science 270:593–598. Thome, J., Sakai, N., Shin, K.H., Steffen, C., Zhang, Y.-J., Impey, S., Storm, D.R., and Duman, R.S. (2000) cAMP response elementmediated gene transcription is upregulated by chronic antidepressant treatment. J. Neurosci. 20:4030 – 4036. Tiraboschi, E., Tardito, D., Kasahara, J., Moraschi, S., Pruneri, P., Gennarelli, M., Racagni, G., and Popoli, M. (2004) Selective phosphorylation of nuclear CREB by fluoxetine is linked to activation of CaM kinase IV and MAP kinase cascades. Neuropsychopharmacology 29:1831–1840. Tsankova, N., Berton, O., Renthal, W., Kumar, A., Neve, R., and Nestler, E.J. (2006) Sustained hippocampal chromatin regulation in a mouse model of depression and antidepressant action. Nat. Neurosci. 9:465– 466. Uno, H., Tarara,, R., Else, J.G., Suleman, M.A., and Sapolsky, R.M. (1989) Hippocampal damage associated with prolonged and fatal stress in primates. J. Neurosci. 9:1705–1711. Vaidya, V., Marek, G.J., Aghajanian, G.A., and Duman, R.S. (1997) 5-HT2A receptor-mediated regulation of BDNF mRNA in the hippocampus and the neocortex. J. Neurosci. 17:2785–2795. Vermetten, E., Vythilingam, M., Southwick, S.M., Charney, D.S., and Bremner, J.D. (2003) Long-term treatment with paroxetine increases verbal declarative memory and hippocampal volume in posttraumatic stress disorder. Biol. Psychiatry 54:693–702. Vetulani, J., and Sulser, F. (1975) Action of various antidepressant treatments reduces reactivity of noradrenergic cAMP generating system in limbic forebrain. Nature 257:495– 496. Von Fritag, J., Kamal, A., Reijmers, L.G., Schrama, L.H., van den Bos, R., and Spruijt, B.M. (2001) Chronic imipramine treatment partially reverses the long-term changes of hippocampal synaptic plasticity in socially stressed rats. Neurosci. Lett. 309:153–156. Vythilingam, M., Vermetten, E., Anderson, G.M., Luckenbaugh, D., Anderson, E.R., Snow, J., Staib, L.H., Charney, D.S., and Bremner, J.D. (2004) Hippocampal volume, memory, and cortisol status in major depressive disorder: effects of treatment. Biol. Psychiatry 56:101–112. Wachtel, H. (1983) Potential antidepressant activity of rolipram and other selective cyclic adenosine 3′,5′-monophosphate phosphodiesterase inhibitors. Neuropharmacology 22:267–272. Wachtel, T., and Schneider, H.D. (1986) Rolipram, a novel antidepressant drug, reverses the hypothermia and hypokinesia of mono-

434

MOOD DISORDERS

amine-depleted mice by an action beyond postsynaptic monoamine receptors. Neuropharmacology 25:1119–1126. Walker, W., Fucci, L., and Habener, J.F. (1995) Expression of the gene encoding transcription factor cAMP response element-binding protein (CREB): regulation by follicle stimulating hormone induced cAMP signaling in primary rat Sertoli cells. Endocrinology 136: 3534–3545. Warner-Schmidt, J., and Duman, R.S. (2006) Hippocampal neurogenesis: opposing effects of stress and antidepressant treatment. Hippocampus 16:239–249. Watanabe, Y., Gould, E., Daniels, D.C., Cameron, H., and McEwen, B.S (1992) Tianeptine attenuates stress-induced morphological changes in the hippocampus. Eur. J. Pharmacol. 222:157–162. Wellman, C. (2001) Dendritic reorganization in pyramidal neurons in medial prefrontal cortex after chronic corticosterone administration. J. Neurobiol. 49:245–253. Widnell, K., Russell, D., and Nestler, E.J. (1994) Regulation of cAMP response element binding protein in the locus coeruleus in vivo and in a locus coeruleus-like (CATH.a) cell line in vitro. Proc. Natl. Acad. Sci. USA 91:10947–10951. Wong, M.-L., and Licinio, J. (2001) Research and treatment approaches to depression. Nat. Rev./Neurosci. 2:343–351. Wooley, C.S., Gould, E., and McEwen, B.S. (1990) Exposure to excess glucocorticoids alters dendritic morphology of adult hippocampal pyramidal neurons. Brain Res. 531:225–231.

Yamada, S., Yamamoto, M., Ozawa, H., Riederer, P., and Saito, T. (2003) Reduced phosphorylation of cyclic AMP-responsive element binding protein in the postmortem orbitofrontal cortex of patients with major depressive disorder. J. Neural Trans. 110:671– 680. Yau, J., Noble, J., Hibberd, C., Rowe, W.B., Meaney, M.J., Morris, R.G.M., and Secki, J.R. (2002) Chronic treatment with the antidepressant amitriptyline prevents impairments in water maze learning in aging rats. J. Neurosci. 22:1436–1442. Yau, J.L.W., Olsson, T., Morris, R.G.M., Meaney, M.J., and Seckl, J.R. (1995) Glucocorticoids, hippocampal corticosteroid receptor gene expression and antidepressant treatment: relationship with spatial learning in young and aged rats. Neurosci. 66:571–581. Young, E., Haskett, R.F., Murphy-Weinberg, V., Watson, S.J., and Akil, H. (1997) Loss of glucocorticoid fast feedback in depression. Arch. Gen. Psychiatry 48:693–699. Zarate, C., Singh, J., and Manji, H.K. (2006) Cellular plasticity cascades: targets for the development of novel therapeutics for bipolar disorder. Biol. Psychiatry 59:1006–1020. Zhang, H.-T., Zhao, Y., Huang, Y., Dorairaj, N.R., Chandler, L.J., and O’Donnell, J.M. (2004) Inhibition of the phosphodiesterase 4 (PDE4) enzyme reverses memory deficits produced by infusion of the MEK inhibitor U0126 into the CAI subregion of the rat hippocampus. Neuropsychopharmacology 29:1432–1439.

30 The Neurochemistry of Depressive Disorders: Clinical Studies BOADIE W. DUNLOP, STEVEN J. GARLOW, A N D

CHARLES B. NEMEROFF

Investigations into the neurochemical basis of psychiatric diseases began in the mid-1950s. This interest was largely stimulated by the identification of effective psychotherapeutic drugs, first chlorpromazine for the treatment of psychosis, followed later in the decade by the tricyclic antidepressants (TCAs) and monoamine oxidase inhibitors (MAOIs) for the treatment of depression. The earliest modern theories of the pathogenesis of psychiatric disorders were based in large part on the observable mechanisms of actions of these first effective psychopharmacological agents. The in vitro description of the mechanism of action of imipramine was one of the key observations in the development of the monoamine hypothesis of depression. A series of simple yet elegant experiments demonstrated that imipramine blocked the reuptake of norepinephrine (NE) into presynaptic neurons, and this action was considered to be the basis of its antidepressant activity (Glowinski et al., 1964; Glowinski and Axelrod, 1966; Glowinski and Iverson, 1966; Glowinski et al., 1966). The hypothesis that developed from these observations is that depression is due to a state of decreased NE availability in the synapse, a condition that is reversed by the actions of imipramine (Prange, 1964; Bunney and Davis, 1965; Schildkraut, 1965). This set the stage for a recurrent theme in the study of depression: to base theories of pathophysiology on the observed actions of antidepressants. In many ways, the introduction of efficacious noradrenergic (TCAs) and serotonergic (TCAs and selective serotonin reuptake inhibitors [SSRIs]) drugs has driven research and theory on the pathophysiology of depression. In particular, it has supported the idea that depression results from a relative deficiency of a particular neurotransmitter and that prolonging the transmitter’s residence and/or concentration in the synapse, with reuptake inhibiting antidepressants, functionally reverses this deficiency.

METHODOLOGICAL CONSIDERATIONS Studies seeking to elucidate the neurochemical pathology of depression have focused on the pre- and postsynaptic levels of neuronal functioning. Neurotransmitter release and availability are dependent on the functional state of the presynaptic neurons, and concentrations of neurotransmitters and their metabolites are considered to be reflective of presynaptic neuronal activity. Quantification of neurotransmitter and metabolite concentrations has been carried out in cerebrospinal fluid (CSF), blood, urine, and saliva. The underlying assumption of these studies is that the concentration of the transmitter or metabolite in the particular body fluid is directly proportional to its concentration in the synapse. Another approach to the study of presynaptic activity is neurotransmitter depletion studies. In these experiments, the central nervous system (CNS) availability of a particular transmitter is drastically and transiently depleted through either dietary or pharmacological manipulations. The impact of this depletion on mood (or anxiety) is then measured (Delgado et al., 1990; Delgado et al., 1994; Delgado et al., 1999). Various measurements of neurotransmitter receptor and effector system activation are considered to reflect primarily postsynaptic neuronal activity. Postsynaptic mechanisms have been studied by direct postmortem measurement of particular receptors or effector systems in brains of patients who were depressed at the time of death. Often these studies are of victims of suicide in comparison to some nonpsychiatric control group. These experiments are frequently confounded by differences in postmortem interval prior to analysis and by agonal state, differences in handling and processing of tissues, and diagnostic uncertainties for the affected and control groups. With the development of positron emission tomography (PET) and other high-resolution neuroimag-

435

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ing techniques, studies previously possible only through postmortem analyses, such as neurotransmitter receptorbinding assays, can now be performed in living patients. Another method used to study neurotransmitter systems in depression is neuroendocrine challenge assays, which use the neuroendocrine window strategy. This technique can measure pre- and postsynaptic mechanisms, depending on the assay employed. In these experiments, patients receive a pharmacological agent known to alter the secretion of an anterior pituitary or target gland hormone by an action on a particular neurotransmitter system. The underlying assumption is that the secretory response to the challenge agent is related to the functional state of that neurotransmitter system. Table 30.1 lists some of the commonly used agents, the systems they test, and the actual measurements (readout) made (Siever et al., 1982; Siever, Murphy, et al., 1984; Anand et al., 1994; Pitchot et al., 1995; Yatham et al., 1997; Whale et al., 2001). A number of peripheral measures have been proposed as surrogates for their cognate systems in the CNS. The expression of neurotransmitter system components on blood cells has been posited to reflect these same systems in the CNS. In particular, platelets have been studied extensively in depression. The rationale for these studies is that the precursor cells from which platelets are derived, megakaryocytes, share embryological origins with 5-hydroxytryptamine (5-HT) neurons, and platelets contain serotonergic and adrenergic receptors, the serotonin transporter, and the inositol trisphosphate and adenylate cyclase second-messenger systems. Platelets concentrate 5-HT in and secrete it from secretory granules that resemble synaptic vesicles (Stahl, 1977; McBride et al., 1983; Da Prada et al., 1988; Wirz-Justice, 1988). Blood lymphocytes and skin fibroblasts are other

peripheral cells that have also been studied in depression. Both of these cell types express a number of neurotransmitter receptors, glucocorticoid receptors, and second-messenger systems. The neurotransmitter receptors expressed on peripheral cells are indeed identical to those expressed in the CNS. The assumption that underlies the study of peripheral cell types is that the receptors, transporters, and second-messenger systems are subject to the same molecular regulation in the periphery as in the CNS and that peripheral alterations directly reflect changes in the CNS that occur in depression. There are a large number of observations in major depression that have either not been replicated at all, have been replicated only in a minority of studies, or have yielded the opposite result from that initially reported. This could be due to a number of factors; the most prominent one is diagnostic heterogeneity. The diagnosis of major depression has evolved over the past 40 years, with progressively more precise definitions with each iteration of the Diagnostic and Statistical Manual (DSM); however, the interpretation of the DSM (and other diagnostic criteria) for depression is not standardized among all investigators and is quite broad in disease severity. The result is that it may not be possible to compare one study cohort to another, despite the efforts of investigators to employ standardized assessment and documentation instruments with their particular sample. Given the potential confounds, it is remarkable that changes in the serotonergic and noradrenergic systems have been so consistently documented in patients who are depressed, across many studies, from different investigators, with many different analytic techniques. This argues convincingly that these two systems play a central role in the pathophysiology of major depression.

TABLE 30.1 Neuroendocrine Challenge Agents, Neurotransmitter System Tested, Specific Target, Synaptic Level, and Assay Readout

Agent

System

Target

Synaptic Level

Readout

Intravenous tryptophan

5-HT

5-HT synthesis

Pre

Serum prolactin

Fenfluramine

5-HT

5-HT nerve terminals

Pre

Serum prolactin CNS metabolism by PET

Sumitriptan

5-HT

5-HT1D-R

Pre

Serum growth hormone

Zolmitriptan

5-HT

5-HT1D-R

Pre

Serum growth hormone

Citalopram

5-HT

SERT

Pre

Serum prolactin, cortisol

m-CPP

5-HT

5-HT2 family

Post

Serum prolactin, growth hormone, cortisol

Clonidine

NE

A2-AR

Post

Serum growth hormone

Apomorphine

DA

DA-2-R

Post

Serum growth hormone

A2-AR: a2 adrenergic receptor; DA: dopamine; 5-HT: 5-hydroxytryptamine; 5-HTID-R: 5-HTID receptor; M-CPP: m-chlorophenylpiperidine; NE: norepinephrine; PET: positron emission tomography; SERT: serotonin transporter; CNS:central nervous system.

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS

NEUROTRANSMITTER SYSTEMS All of the major neurotransmitter systems, serotonin, NE, dopamine (DA), g -aminobutyric acid (GABA), glutamate, many of the peptidergic systems, and many other systems have been scrutinized for a role in the pathogenesis of depressive disorders. A preponderance of evidence accumulated over four decades has consistently revealed alterations in the noradrenergic and serotonergic systems. Both of these systems appear to be central to the pathophysiology of depression, and one, the other, or both appear to be involved in the mechanism of action of most antidepressants. There are many other interesting yet less well studied findings in other neurotransmitter systems in depression, including the DA and corticotropin-releasing factor (CRF) circuits, that hint at the complexity and interrelatedness of these systems in the CNS and at the widespread impact that major depression has on the neurochemistry of the CNS. Norepinephrine The noradrenergic system was the first to be studied intensively in major depression. Early theories of the pathogenesis of depression focused on a relative deficiency of norepinephrine (NE) as the cause of depression (Prange, 1964; Bunney and Davis, 1965; Schildkraut, 1965). This was due in large part to the observed mechanisms of action of imipramine and other drugs. Theo-

437

ries of the mechanisms of action of antidepressants and of the pathophysiology of depression converged around the ability of TCAs to block uptake of NE into synaptic vesicles and the ability of the catecholamine-depleting agent reserpine to provoke symptoms of depression. The original catecholamine hypothesis of affective disorders proposed that depression was due to a relative deficiency of catecholamines, particularly NE, at important sites in the brain and that mania was due to relative NE excess. Key findings implicating dysfunction of the noradrenergic system in depression are summarized in Table 30.2. The biochemical pathways that lead to production of catecholamines were described in exquisite detail as part of the effort to validate the catecholamine hypothesis. Norepinephrine, DA, and epinephrine contain the catechol ring structure or 1,2-dihydroxybenzene. The concentration of NE in bodily fluids is difficult to measure because the transmitter is rapidly catabolized, but the principal metabolite, 3-methoxy-4-hydroxyphenylglycol (MHPG), is stable, and its concentration has been proposed as a surrogate measure of NE levels. This metabolite can be measured in urine, and approximately 20% of urinary MHPG is derived from the CNS pool (Potter et al., 1984). The underlying assumption is that changes in urinary levels of MHPG are reflective of changes in the activity of NE neurons in the CNS. In early reports, urinary levels of MHPG were found to be significantly lower in patients who were depressed

TABLE 30.2 Findings Implicating Noradrenergic Dysfunction in the Pathophysiology of Depression at Various Neuropharmacologic Levels of Action

Level of Action

Finding

Replicability

Neurotransmitter synthesis

AMPT, inhibitor of tyrosine hydroxylase, results in depressive relapse in antidepressant-treated patients

++

Neurotransmitter storage

Long-term treatment with reserpine, which depletes monoamine stores, results in depressive symptoms in patients with a history of depression

++

Neurotransmitter reuptake

NE reuptake inhibitors are effective antidepressants TCAs block NE reuptake in vitro

+++

Neurotransmitter metabolism

MAOIs are effective antidepressants

+++

Low NE metabolites in bipolar depression

++

MAO-A levels elevated in depressed patients

+

Postsynaptic neurotransmitter receptors

a 2-Adrenergic receptor • Increased Bmax on platelets of depressed patients • Increased Bmax in brains of suicide victims • Blunted GH response to clonidine challenge

++ + +++

β -Adrenergic receptor • Increased Bmax in brains of suicide victims • Down-regulation in response to antidepressant treatment (patients) • Down-regulation in experimental animals systems

+++ + +++

AMPT: alpha-methyl-paratyrosine; MAOI: monoamine oxidase inhibitor; NE: norepinephrine; TCA: tricyclic antidepressant; GH: growth hormone; Replication key: +: one or no replication studies; + +: several replication studies; + + +: highly replicated by more than two research groups.

438

MOOD DISORDERS

compared to controls (Maas et al., 1972; Schildkraut, 1973). This finding has not, however, been consistently replicated, especially in patients with unipolar depression. Overall, urinary MHPG levels do not distinguish patients with unipolar depression from controls (Schildkraut et al., 1978; Schatzberg et al., 1982). Subsequent research has attempted to classify subtypes of depression based on urinary catecholamine excretion. Because patients with unipolar depression display a wide range of urinary MHPG concentrations, attempts have been made to stratify these patients based on MHPG values as a means of analyzing symptom content and treatment response. Patients with unipolar depression have been classified as having low, intermediate, or high urinary MHPG values (Schatzberg et al., 1982; Schatzberg et al., 1989). Those patients in the low category are considered to have diminished activity of noradrenergic neurons resulting in low NE output and release, consistent with the original catecholamine hypothesis. These patients have been reported to respond to treatment with tricyclic and tetracyclic antidepressants and to fluoxetine, a specific serotonin reuptake inhibitor (Hollister et al., 1980; Schatzberg et al., 1981; Maas et al., 1984; Schatzberg, 1998). The nature of patients with unipolar depression with intermediate MHPG values remains obscure. Patients with unipolar depression and high urinary MHPG are believed to have increased activity of presynaptic noradrenergic neurons. This may reflect dysfunction of one or more of the adrenergic receptors or an interaction with other transmitter systems. Patients in the high urinary MHPG group also tend to have high circulating plasma cortisol concentrations, to be nonsuppressors on the dexamethasone suppression test, and to be resistant to treatment with conventional antidepressants. These patients have been reported to respond poorly to TCAs and SSRIs. Initial reports indicated that patients suffering from bipolar disorder (BPD) had the lowest urinary MHPG values during the depressed phase of the illness, lower than those of patients with unipolar depression and healthy controls. As the distinctions between bipolar types I and II have been realized, patients with type I bipolar disorder have been reported to have the lowest urinary MHPG values during the depressed phase. Patients with type II BPD have urinary MHPG values similar to those of patients with unipolar depression, which as a group are higher than those of patients who are depressed with type I BPD (Schatzberg et al., 1989). Some patients with unipolar depression also have low urinary MHPG values, similar to those with type I BPD. These patients may in fact have incipient type I BPD and have simply not yet suffered their first manic episode. One obvious prediction from the reports that patients with type I BPD have the lowest concentrations

of urinary MHPG during the depressed phase is that these same patients would have increased levels of MHPG during the manic phase. This prediction has been confirmed in several studies (Halaris, 1978). Patients with BPD during manic episodes have significantly higher plasma NE and epinephrine levels than when they are depressed or euthymic (Maj et al., 1984). Other investigators have reported that urinary MHPG and CSF NE levels are significantly higher in patients who are manic than in patients who are depressed or controls (Swann et al., 1987). Measurement of NE and MHPG concentrations in blood and CSF has yielded equally confounding results. In a study that compared CSF MHPG levels between 99 hospitalized patients who were depressed, 14 patients who were manic, and 61 healthy controls, elevated CSF MHPG was observed in patients who were depressed with high levels of anxiety, agitation, somatization, and sleep disturbance (Redmond et al., 1986). This observation did not correlate to global severity of symptoms or to other symptom domains. In another study in which CSF was sampled hourly for 30 consecutive hours in patients with melancholic depression, patients had significantly elevated NE levels, across the entire circadian cycle, compared to controls (Wong et al., 2000). In a study of patients with nonbipolar, medication-refractory unipolar depression, venoarterial neurotransmitter gradients were determined by means of cannulas inserted into the internal jugular vein (Lambert et al., 2000). Venoarterial NE and DA gradients were reduced in the patients compared to the controls. Not only was the venoarterial NE gradient markedly reduced in the medication-refractory patients who were depressed, but similar results were also observed with the two major NE metabolites, MHPG and dihydroxyphenylglycol (DHPG). This is presumptive evidence of decreased activity of NE circuits in this sample of refractory patients who are depressed. In a different study comparing patients with posttraumatic stress disorder (PTSD), PTSD plus depression, depression, and normal controls, the group with PTSD alone had significantly elevated serum NE concentrations, while there were no differences in serum NE levels between the other three diagnostic groups (Yehuda et al., 1998). A recent PET study using [11C]harmine, a radioligand specific for the measurement of monoamine oxidase A (MAO-A) activity, demonstrated a dramatic 34% elevation in MAO-A in numerous brain regions of patients who were currently depressed versus controls (Meyer et al., 2006). MAO-A is responsible for catabolizing NE, serotonin. and, to a lesser extent, DA in the CNS, and elevated MAO-A levels may explain the reduced monoamine concentrations in major depression. The cold-pressor test is one functional assay of NE system reactivity. In a comparison of patients with mel-

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS

ancholic or psychotic depression, nonmelancholic depression, generalized anxiety disorder, and normal controls, the patients with melancholic/psychotic depression exhibited a significant decrease in NE response to coldpressor compared with all of the other groups (Kelly and Cooper, 1998). This appears to be evidence for NE system under reactivity in melancholic/psychotic depression. Clearly, the measurement of NE and its metabolites in peripheral samples has been invaluable historically in developing the disease concept of major depression. However, given the wide variance in levels of serum, CSF, and urinary NE and MHPG in unipolar depression, the original hypothesis that depression results from a deficiency of NE has not been validated by these methods. One of the original goals of these research efforts was to develop laboratory tests that would aid in the diagnosis of depression; however, measurement of peripheral NE or MHPG has never been validated as such a test. With the emergence of high-resolution functional neuroimaging methods with which to study catecholaminergic systems in the CNS, the peripheral measurement of catecholamine levels as an index of CNS function has now been superseded (Schatzberg and Schildkraut, 1995). Even though the direct measurement of NE or MHPG has not yielded definitive evidence of catecholamine system dysfunction in depression, functional manipulation of the NE system does implicate this system in the pathophysiology of depression. Brief inhibition of tyrosine hydroxylase (TH) with a-methyl-para-tyrosine (AMPT) transiently depletes CNS NE and other catecholamine (DA and epinephrine) pools. Administration of AMPT to normal healthy patients with no history of depression does not produce mood symptoms (Salomon et al., 1997). Moreover, administration of AMPT to untreated patients who are depressed does not cause worsening of core symptoms of depression, but it does exacerbate some neurovegetative symptoms such as anergia (Miller et al., 1996b). In contrast, patients who are depressed treated with desipramine or mazindol, which are specific NE reuptake inhibitors, suffer a significant return of depressive symptoms when challenged with AMPT (Miller et al., 1996a; Berman et al., 1999). The AMPT-induced return of depressive symptoms in patients remitted from major depression during treatment with NE reuptake inhibitors is correlated with reduced brain metabolism in the dorsolateral prefrontal cortex (PFC), orbitofrontal cortex, and thalamus assessed by PET (Bremner et al., 2003). In contrast, patients treated with specific serotonin reuptake inhibitors (fluoxetine, sertraline) do not relapse when treated with AMPT. This implies parallel treatment response pathways that involve either NE or 5-HT systems and that manipulation of one or the other system is often adequate to cause resolution of depression (Heninger et al., 1996).

439

A number of different noradrenergic neurotransmitter receptors have been implicated in the pathophysiology of depression and in the mechanism of action of antidepressants (Duman and Nestler, 1995). The a 2adrenergic and b -adrenergic receptors have been the focus of considerable research in the biology of depression. The expression and function of a 2 receptors on platelets have been studied on the assumption that the function of these receptors in platelets reflects that of those in the CNS. Increased density of a 2 receptors on platelets has been repeatedly reported in drug-free patients who were depressed (Garcia-Sevilla et al., 1987; Garcia-Sevilla et al., 1990; Piletz et al, 1990; Gurguis et al., 1999). The platelet a 2 receptor mediates platelet aggregation, and this response is exaggerated in patients who are depressed (Musselman et al., 1996). Platelet a 2 receptor density has been correlated with severity of depressive symptoms, as measured with the Hamilton Rating Scale for Depression (HRSD) (Marazziti et al., 2001). However, there are also reports that platelet a2 receptor density is decreased in depression (Maes et al., 1999). Postmortem measurement of a 2 binding in the locus ceruleus in patients with major depression has been found to be elevated compared to controls (Ordway et al., 2003). Locus ceruleus a 2 receptors likely function as autoreceptors and act to inhibit noradrenergic cell firing. Although some investigators report increased postmortem Bmax (maximum binding capacity) of a 2 receptors in the cerebral cortex of patients who were depressed versus controls (Meana et al., 1992), others have found no difference (Arango et al., 1993; Klimek et al., 1999). The findings of increased a 2 receptors in depression have been interpreted as reflecting increased sensitivity of this receptor, perhaps resulting in decreased activity of noradrenergic neurons and hence decreased CNS NE release in patients who are depressed, consistent with the original catecholamine hypothesis. The clonidine challenge test is an indirect means of assessing the functional state of CNS a 2 receptors. Clonidine is an a 2 agonist that increases growth hormone (GH) release from the anterior pituitary gland, presumably through a postsynaptic mechanism. A blunted GH response to clonidine has been reported in patients who were depressed in several studies (Siever, Uhde, et al., 1984; Amsterdam et al., 1989). A blunted GH response to clonidine has been reported in patients who were acutely symptomatic depressed, in patients treated with antidepressants, and in those in remission (Mitchell et al., 1988; Siever et al., 1992). This suggests that the alteration in a 2 receptor function revealed by the clonidine challenge test might be a trait characteristic of some patients who are depressed. The clonidine challenge test does not discriminate between patients who are depressed and nonsuicidal and patients who are depressed and highly suicidal, which suggests that NE

440

MOOD DISORDERS

dysregulation is involved in the pathology of depression and not in suicide (Pitchot et al., 2001b). However, earlier studies did not adequately control for the presence of anxiety comorbid with depression. When patients who are depressed without anxiety were compared with patients who were not depressed and anxious or patients with mixed anxiety/depression, only those patients with some level of anxiety demonstrated reduced GH response to clonidine; those with depression without anxiety showed GH responses similar to healthy controls (Cameron et al., 2004). Nevertheless, drawing firm mechanistic conclusions from these results is difficult because many of the findings of increased a2 receptor density in depression have not been consistently replicated or because the exact opposite has been observed. b -Adrenergic receptors have also been postulated to contribute to the pathophysiology of depression and to the response to antidepressants. As with the a-adrenergic receptors, results with b -adrenergic receptors have been variable, contradictory, and difficult to interpret. There are reports of increased Bmax for the b adrenergic receptor in postmortem brain tissue of victims of suicide, but there are equally credible discrepant reports (Crow et al., 1984; Mann et al., 1986; De Paermentier et al., 1990, 1991). A number of different variables could account for the failure to replicate this finding, including diagnostic heterogeneity between studies, differences in antemortem antidepressant treatment, differences in processing of the postmortem tissue, and differences in analytical techniques. Similarly contradictory results have been reported for studies in which the Bmax for b receptors on leukocytes was determined. There are reports of decreased Bmax values for peripheral b receptors in patients who are depressed and studies that report no difference between patients who are depressed and healthy controls (Extein et al., 1979; Healy et al., 1985). Certainly, treatment with antidepressants can affect the Bmax of b receptors, and much of the variability in these studies could be accounted for by differences in the type, duration, and intensity of antidepressant treatment. Down-regulation of b receptors has been postulated to be integral to antidepressant action (Banarjee et al., 1977). In animal models, one consistent action of many antidepressants is to decrease the numbers of b receptors and uncouple the receptors from their second-messenger systems. These effects occur after chronic but not acute treatment, corresponding to the temporal response to these agents in clinical practice. However, studies with primarily serotonergic agents have found no effect on b adrenoreceptors (Ordway et al., 1991). Serotonin There is considerable evidence for dysfunction of the serotonergic system in major depression, which has culmi-

nated in the serotonin hypothesis of depression (Meltzer and Lowy, 1987; Maes and Meltzer, 1995). Alterations in serotonergic function have been observed at pre- and postsynaptic levels in patients who are depressed. There are voluminous treatment response data implicating the serotonergic system as a principal target for the action of antidepressants (Owens, 1997). Whether serotonergic dysfunction is sufficient to cause depression or is a necessary risk factor remains an open question. Key findings implicating dysfunction of serotonergic circuits in depression are summarized in Table 30.3. All of the serotonin in the CNS is synthesized in raphé nuclei neurons. Serotonin synthesized in the periphery does not enter the CNS. Disruption of 5-HT synthesis in the CNS has been hypothesized as a major pathophysiological mechanism leading to major depression. Serotonin is synthesized from the essential amino acid l-tryptophan (l-TRP), and the availability of l-TRP determines the amount of serotonin synthesized (Maes et al., 1990). Plasma l-TRP concentrations determine the amount of l-TRP that crosses the blood-brain barrier, and hence the amount of 5-HT synthesized and available in the CNS. There is evidence that the concentration of plasma l-TRP is lower in patients who are depressed than in controls. This may be due at least partly to increased clearance of l-TRP via hepatic biotransformation. Peak plasma concentrations of l-TRP are lower in patients who are depressed than in controls after oral or intravenous l-TRP loading doses, perhaps due to induction of the hepatic metabolic pathway responsible for the processing of l-TRP (Maes et al., 1987). Dietary depletion of l-TRP decreases the serum concentration of l-TRP, which in turn results in a transient fall in CNS 5-HT availability. In normal controls, lowering plasma l-TRP via dietary manipulation can produce a transient depressed mood (S.N. Young et al., 1985); this may represent a trait vulnerability factor for depression. The occurrence of depression and dysphoria following l-TRP depletion occurs much more prominently in normal patients with first-degree relatives who suffer from depression than in healthy patients with no family history of depression (Benkelfat et al., 1994; Ellenbogen et al., 1996). The mood-altering effect of l-TRP depletion is dramatically demonstrated in patients who are depressed with recent remission (Heninger et al., 1992; Smith et al., 1997). These patients display a remarkably rapid return of depressed mood, and the attendant cognitive and neurovegetative symptoms, with l-TRP depletion. Patients treated with SSRIs are much more sensitive to this manipulation than patients treated with antidepressants that act on noradrenergic neurons. This response has not been universally replicated, but the failure to replicate may be due to differences in severity of depression, intensity of treatment, or the presence of suicidal ideation between different study cohorts. In at least one study that did not find an effect of l-TRP de-

30.3 Findings Implicating Serotonergic Dysfunction in the Pathophysiology of Depression at Various Neuropharmacologic Levels of Action

TABLE

Level of Action

Finding

Replicability

Plasma TRP is lower in subgroups of depressed patients

+/−

Depletion of plasma TRP results in depressive relapse in antidepressant-treated patients

++

Depletion of plasma TRP causes dysphoria in first-degree relatives of depressed patients

++

Neurotransmitter synthesis

PCPA, inhibitor of TRP hydroxylase, results in depressive relapse in antidepressant-treated patients

+

Neurotransmitter storage

Long-term treatment with reserpine, which depletes monoamine stores, results in depressive symptoms in patients with a history of depression

++

Neurotransmitter release

Fenfluramine and MDMA, which increase synaptic 5-HT, cause mild euphoria and a sense of well-being

+

Lithium, which enhances 5-HT release, augments antidepressant action

+++

Prolactin release in response to intravenous TRP blunted in depressed patients

++

Prolactin release in response to fenfluramine challenge blunted in depressed patients

+++

Cerebral glucose use reaction blunted in response to fenfluramine challenge in depressed patients

+

Prolactin release in response to citalopram challenge blunted

+

5-HT1A agonists (gepirone, buspirone) may have antidepressant properties

++

Precursor availability

Presynaptic autoreceptor function Neurotransmitter reuptake

Neurotransmitter metabolism

Postsynaptic neurotransmitter receptors

+++ 5-HT reuptake inhibitors are effective antidepressants Decreased platelet 5-HT reuptake sites in depressed patients

+++

Decreased 5-HT reuptake sites in postmortem brains of depressed patients

+/−

5-HT reuptake site down-regulated in response to antidepressants (patients)

+/−

5-HT reuptake sites down-regulated in response to antidepressants (experimental animals)

++ +++

MAOIs are effective antidepressants Low 5-HT metabolites in subgroups of depressed patients

+/−

Low 5-HT metabolites in CSF of patients prone to violent suicide

+++

MAO-A levels elevated in depressed patients

+

5-HT1A receptor Increased Bmax in brains of suicide victims

+/−

5-HT1D receptor Blunted GH response to sumatriptan/zolmitriptan

++

5-HT2 receptor Increased Bmax in brains of suicide victims

++/−

Increased Bmax on platelets of depressed patients

+++

Antagonists (trazodone, nefazodone, mianserin) are antidepressants

+++

Down-regulation in response to antidepressant treatment (patients)

+

Down-regulation in experimental animal systems

+++

CSF: cerebral spinal fluid; 5-HT: serotonin; MAOI: monoamine oxidase inhibitor; MDMA: 3,4-methlenedioxymethamphetamine; PCPA: parachlorophenylalanine; TCA: tricyclic antidepressant; TRP: tryptophan; GH; growth hormone. Replication key: +: one or no replication studies; + +: several replication studies; + + +: highly replicated by more than two research groups; + / −: mixed or inconsistent results.

441

442

MOOD DISORDERS

pletion, patients who were considered at risk for suicide or self-destructive behavior were excluded (Leyton et al., 1997). A study of patients who were depressed and subsequently treated with antidepressants to the point of remission suggests there is a threshold effect, wherein insufficient tryptophan depletion does not provoke depressive relapse but more thorough depletion does (Spillmann et al., 2001). Such “low dose” depletion can produce changes in emotion processing and cognitive functioning without detectable reduction in mood (Hayward et al., 2005). This finding is consistent with findings from patients with Alzheimer’s dementia, in which l-TRP depletion can worsen the cognitive performance without causing symptoms of depression (Porter et al., 2000). Interestingly, untreated patients who were depressed do not worsen in response to l-TRP depletion. Patients who were depressed and without thoughts of suicide who had been successfully treated with antidepressants, to the point of euthymia and discontinuation of medication, were more resistant to the mood-altering effects of l-TRP depletion than patients with recent remission (Leyton et al., 1997). Tryptophan depletion has been shown, with [15O]H2O PET, to cause diminished neural activity in the ventral anterior cingulate, orbitofrontal cortex, and caudate nucleus in recently remitted patients who were depressed (Smith et al., 1999). A subsequent PET study using [18F]fluorodeoxyglucose (FDG) found similar reductions in metabolism in orbital frontal cortex, ventral striatum, cingulate cortex, and thalamus (Neumeister et al., 2004). However, this study did not identify differences in cerebral metabolism between those patients who did or did not have a return of depressive symptoms, suggesting that the abnormal metabolism may reflect a trait abnormality associated with major depression. More recently, serum concentrations of brain-derived neurotrophic factor (BDNF) have been shown to differ between patients who were depressed and controls exposed to l-TRP depletion, with normal controls demonstrating an increase in BDNF, but patients who were depressed showing no such change (Neumeister et al., 2005). Brainderived neurotrophic factor has been shown to be crucial for the normal function of serotonergic and neurotrophic systems. Taken together, these findings suggest that l-TRP availability may be decreased in some patients who are depressed, leading to decreased serotonin synthesis in the CNS. Moreover, available l-TRP and, by extension, CNS serotonin likely plays a role in the treatment response to antidepressants, in particular for the SSRIs. Additional evidence for dysfunction of presynaptic serotonergic neurons in major depression is provided by a number of different neuroendocrine challenge paradigms. Prolactin is released from the anterior pitu-

itary gland upon activation of 5HT-2a and -2c receptors (Coccaro et al., 1996). Intravenous infusion of tryptophan causes an acute increase in serotonergic transmission associated with an increase in serum prolactin levels (Price et al., 1991). Patients who were depressed demonstrate a blunted prolactin response to lTRP infusion compared to controls (Cappiello et al., 1996). The appetite suppressant fenfluramine causes a rapid release of serotonin from presynaptic neurons and increases serum prolactin levels. Patients who were depressed have been shown repeatedly to exhibit a blunted prolactin response to fenfluramine challenge (Mitchell and Smythe, 1990; O’Keane and Dinan, 1991; Malone et al., 1993; Shapira et al., 1993), though discrepant reports have appeared (Kavoussi et al., 1998). There is evidence that the blunted prolactin response may be a marker of suicidality or impulsivity and not depression (Correa et al., 2000). Studies of the effect of antidepressant treatment on prolactin response to fenfluramine challenge are highly conflicting, with increases, decreases, and no changes reported in the literature (Kavoussi et al., 1999; Dulchin et al., 2001). A novel variation of the fenfluramine challenge test measures cerebral glucose utilization with PET imaging instead of prolactin release in response to the fenfluramine challenge (Mann et al., 1996). Consistent with the prolactin results obtained, patients who were depressed displayed reduced cerebral glucose use in response to fenfluramine challenge. Interestingly, prolactin responses to fenfluramine challenge are also blunted in bipolar patients who are acutely manic (Thakore et al., 1996). This has been interpreted as indicative of a general serotonergic dysfunction in mood disorders, in BPD and in unipolar depression. Another neuroendocrine assay of presynaptic serotonergic function uses sumatriptan as the challenge agent. This antimigraine compound is an agonist at the 5-HT1D receptor, the nerve terminal autoreceptor on serotonergic neurons. Sumatriptan administration results in an increase in plasma GH concentrations. The GH response to sumatriptan in patients who are depressed is blunted compared to that of normal controls or patients with bipolar mania (Yatham et al., 1997; Cleare et al., 1998). A similar result has been reported for patients with melancholic depression challenged with the related compound zolmitriptan (Whale et al., 2001). Citalopram, an SSRI, which is a specific serotonin transporter antagonist, has also been used as a challenge agent to study presynaptic serotonergic function. Patients who were depressed had a significantly blunted prolactin response to a challenge dose of citalopram compared with controls (Kapitany et al., 1999). That the abnormalities in response to the neuroendocrine challenge tests observed in patients who are depressed are caused by dysfunction of presynaptic serotonergic neurons is suggested by the results of the

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS

m-chlorophenylpiperazine (m-CPP) challenge test (Anand et al., 1994). This agent has mixed pharmacodynamic actions at postsynaptic serotonin receptors, principally the 5-HT2 receptor family. There are no differences in neuroendocrine measures between patients who were depressed and controls in response to intravenous infusion of m-CPP (Anand et al., 1994; Price et al., 1997). Concatenation of the results of these many neuroendocrine challenge assays is consistent with and very supportive of the hypothesis that major depression is characterized by significant dysfunction of presynaptic serotonergic neurons. Synaptic activity of serotonergic neurons frequently has been estimated by measuring the CSF concentration of the major serotonin metabolite 5-hydroxyindoleacetic acid (5-HIAA). Although consistent evidence for serotonergic hypofunction in depression in general has not emerged from these studies, the most reproducible finding is of reduced CSF 5-HIAA concentrations, presumably a measure of reduced CNS serotonergic function, in patients who attempted or committed suicide. The finding of low CSF 5-HIAA concentrations is particularly robust in patients who used violent means to commit suicide (Asberg et al., 1976; Gibbons and Davis, 1986; Roy et al., 1989), independent of psychiatric diagnosis (Traskman et al., 1981; Van Praag, 1982). There are also reports linking low CSF 5-HIAA concentrations with poor impulse control in violent criminal offenders and arsonists (Virkkunen et al., 1994; Virkkunen et al., 1995; Virkkunen et al., 1996). In all of these patient samples, the strongest relationship appears to be between low CSF 5-HIAA concentrations and violent, impulsive behavior (Linnoila and Virkkunen, 1992). This behavioral spectrum is quite distinct from the constellation of symptoms that constitute major depression, but it does appear to intersect with the depressive syndrome. One hypothesis is that depression in combination with low CNS serotonin availability, as demonstrated by low CSF 5-HIAA concentrations, is a prominent risk factor for impulsive and highly lethal suicide attempts. A corollary to this hypothesis is that there may be separate pathological processes that distinguish depression and suicide, and that suicide may be associated with a distinct pathophysiology. Another measure of presynaptic serotonergic function that has received a great deal of research attention is serotonin transporter (SERT) binding. In the CNS, the SERT is expressed exclusively in serotonergic perikarya and subsequently transported to and localized on the 5HT-containing nerve terminals. Serotonergic neurotransmission is terminated by the SERT, which clears 5-HT from the synapse, pumping it back into the presynaptic terminal. The efficiency or availability of this transporter directly controls the concentration of 5-HT in the synapse. The hypothesis that has emerged

443

is that changes in the activity state or number of SERT sites may play a preeminent role in major depression (Owens and Nemeroff, 1994, 1997). The SERT is also expressed on platelets, where it concentrates 5-HT from plasma, eventually in secretory granules. The SERT is transcribed from a single copy gene, and therefore the transporters expressed on platelets and in the CNS are identical. Because the SERT is identical in both cell types, and because blood platelets are much easier to study than CNS neurons, platelet SERT indices have been exploited as surrogate measures of CNS SERT function. The transport kinetics of serotonin in human cortical brain synaptosomes and platelets have been shown to be highly correlated, suggesting that studies of platelet SERT do reflect CNS SERT function (Rausch et al., 2005). The underlying (and not yet proven) assumption is that the SERT gene is subject to identical regulation in both tissues so that changes measured in platelets mirror changes in the CNS (Lesch et al., 1993). The concentration of the SERT on platelets has been measured with [3H]-imipramine binding and [3H]paroxetine binding. Although there have been some discrepant reports that failed to detect differences in the Bmax for the platelet SERT between patients who are depressed and controls, the vast majority report a decrease in the platelet SERT Bmax between patients who were depressed and a variety of comparison groups (Briley et al., 1979; Briley et al., 1980). A comprehensive meta-analysis of the worldwide platelet [3H]-imipramine binding data identified 70 independent studies that included data on approximately 1900 patients who were depressed and slightly fewer controls (Ellis and Salmond, 1994). The meta-analysis revealed that the lower Bmax value for platelet [3H]-imipramine binding is a highly significant finding in major depression. This appears to be a state marker for depression because the Bmax tends to normalize with treatment and syndrome resolution. The Bmax of the SERT has also been measured in postmortem brain tissue of victims of suicide. These studies are not nearly as consistent as the platelet studies; some reported decreased Bmax for the SERT in the frontal cortices of victims of suicide when compared to controls, and others reported no such differences (Perry et al., 1983; Gross-Isseroff et al., 1989; Lawrence et al., 1990; Leake et al., 1991; Bligh-Glover et al., 2000). There are methodological issues related to these postmortem studies. The first is that the number of patients is low, especially compared to the platelet data; the second is that the postmortem processing of the tissue varies between different centers and studies; and the third is that different analytical techniques were employed by the different research groups. PET and single photon emission computed tomography (SPECT) ligands relatively specific for the SERT

444

MOOD DISORDERS

have been used to assess SERT binding in patients with major depression. In one study, drug-free patients who were depressed were compared to healthy controls using the SERT ligand [123I]-b -CIT, imaged with SPECT (Malison et al., 1998). This study revealed a significant reduction in SERT binding in the raphé nuclei in the patients who were depressed compared to the controls. This is interpreted as indicating fewer SERT sites in the brain stem of the patients who were depressed. Interestingly, there were no differences in platelet [3H]paroxetine binding between the depressed and control groups, suggesting that central and peripheral regulation of the SERT may in fact be different. A tri-allelic functional genetic polymorphism has been described in the promoter of the SERT gene (Heils et al., 1996; Hu et al., 2004). Initially only two alleles, the short (S) and long (L) forms, were described, though subsequent work identified two functional variants of the long form: LA, which results in greater SERT experession than the S form, and LG, which expresses the SERT comparably to the S form. Differences in promoter strength could be one molecular mechanism that causes differences in the SERT Bmax. Association and linkage studies have produced contradictory results, with some reporting an overrepresentation of the S allele in patients who are depressed and others finding no association between SERT promoter alleles and depression. This inconsistency may stem partly from variations in ethnicity between sampled populations, as the effects of SERT promoter polymorphism on measures of CNS serotonin function have been shown to vary by race in healthy patients (Williams et al., 2003). Positron emission tomography studies of SERT density have found a lower binding potential in patients who were depressed versus controls (Malison et al., 1998; Parsey, Hastings, et al., 2006) though correlations with SERT promoter polymorphisms have not been made, and one study found no difference (Meyer et al., 2004). Similarly, postmortem analyses have found that the SERT Bmax in the CNS is decreased in depression, but independently from promoter genotype (Mann et al., 2000; Ordway, 2000). The most consistent finding from studies of the SERT polymorphisms is that the S and LG forms convey increased risk for the development of major depression following stressful life events (Caspi et al., 2003; Kendler et al., 2005; Zalsman et al., 2006). In fact of 20 studies identified, 17 confirmed the finding (Zammit and Owen, 2006). Healthy S-allele carriers have been found by functional magnetic resonance imaging (MRI) to have increased amygdala reactivity to fearful or angry facial expressions, and to have impaired functional connectivity between the amygdala and anterior cingulate regulatory regions, which may represent a risk factor for depression in the face of stress (Hariri et al., 2005; Pezawas et al., 2005). Patients in remission from major

depression who carry at least one copy of the LA allele have greater worsening of depressive symptoms, and increased cortical metabolism as assessed by PET in the amygdala, subgenual cingulate cortex, and hippocampus, than do patients with two copies of the S allele when undergoing tryptophan depletion (Neumeister et al., 2006). There are at least 14 distinct 5-HT receptor subtypes (Glennon and Dukat, 1995; Saxena, 1995). The advent of low-stringency polymerase chain reaction (PCR) cloning strategies has revealed the existence of a large number of previously unknown and unpredicted 5-HT receptors. These receptors are grouped into seven different families based on their molecular structure, which also determines their other characteristics such as ligand affinities, second-messenger coupling, and so on. The 5-HT3 receptor is a ligand-gated ion channel, whereas all of the others are seven-transmembrane, G protein–coupled receptors. Prior to the discovery of the “new” serotonin receptors, the 5-HT1A and 5-HT2A receptors were the subject of the majority of 5-HT receptor research in depression. The contribution of the newly discovered 5HT receptors to the pathophysiology of depression and the mechanism of action of antidepressants have yet to be determined. The 5-HT2A receptor is positively coupled to phospholipase C and the mobilization of intracellular calcium, whereas the 5-HT1A receptor is negatively coupled to adenylate cyclase (AC) activity. The 5-HT1A and 5-HT2A receptors are postsynaptic in location, though the 5-HT1A receptor is the predominant 5-HT receptor on the serotonergic perikarya in the raphé nuclei, therefore controlling the firing rate of the serotonergic neurons. The 5-HT2A receptor is located on a number of different cell types in the CNS, on platelets, smooth muscle cells, cells in the immune system, skin fibroblasts, and a number of other peripheral cell types. The 5-HT1A receptor is found predominantly in the CNS but also on lymphocytes in the periphery. The promoter region of the gene for the 5-HT1A receptor has a functional single nucleotide polymorphism (SNP) (C[-1019]G 5-HT1A), in which a guanine (G) is substituted for a cytosine (C) residue. The G allele results in greater 5HT1A autoreceptor expression and consequently greater inhibition of basal raphé neuronal activity (Lemonde et al., 2003). The G allele has been reported to be twice as frequent in patients who were depressed versus controls, and 4 times more common in persons who completed suicide. Individuals with a G/G genotype at this polymorphism have been shown to exhibit increased expression of 5-HT1A autoreceptors (Parsey, Oquendo, et al., 2006) The platelet 5-HT2A receptor has been the focus of considerable scrutiny in depression, with at least 12 independent studies published in which the Bmax for the platelet 5-HT2A receptor in major depression was mea-

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS

sured (Biegon et al., 1987; Cowen et al., 1987; Arora and Meltzer, 1989a; Biegon, Essar, et al., 1990; Biegon, Grinspoon, et al., 1990; Pandey et al., 1990, 1995; Mann et al., 1992; Arora and Meltzer, 1993; McBride et al., 1994; Hrdina et al., 1995, 1997; Sheline et al., 1995). One of these studies reported no difference between patients who were depressed and controls. The others all reported a significant increase in the Bmax for the platelet 5-HT2A receptor for patients who were depressed or suicidal. Several of the studies reported that the increased Bmax is related to suicidality, while others suggested that it is related to the syndromal diagnosis of depression. Initially, this finding was considered a state marker of depression because the Bmax was reported to normalize with recovery from depression. One group has, however, reported that the increased Bmax does not normalize with successful treatment, raising the question of whether this may be a trait marker for vulnerability to depression (Bakish et al., 1997). There are several other studies that have inferred changes in the Bmax for the platelet 5-HT2A receptor by a number of secondary measures of receptor function including platelet shape change, phosphatidyl inositol (PI) hydrolysis, and calcium mobilization. There are at least 10 publications in which the Bmax for the 5-HT2A receptor has been measured in the CNS of victims of suicide (Owen et al., 1983; Stanley and Mann, 1983; Crow et al., 1984; Mann et al., 1986; Owen et al., 1986; McKeith et al., 1987; Cheetham et al., 1988; Arora and Meltzer, 1989b; Arango et al., 1990; Hrdina et al., 1993; Lowther et al., 1994). The results of these analyses are considerably more variable than those of the platelet studies. Approximately half of the publications report an increase in the Bmax for the 5-HT2A receptor in the brains of victims of suicide, and the other half report no difference. As in other postmortem studies, the variability in these results could be due to a number of technical and artifactual factors. Based on postmortem analysis, it is not clear whether the Bmax for the 5-HT2A receptor is altered in the CNS of individuals who were depressed. The 5-HT1A receptor controls the rate of firing of the serotonergic neurons and hence the availability of 5-HT in the synapse. Changes in the numbers or responsiveness of the 5-HT1A receptor might affect the firing rate of the serotonergic neurons, which in turn could lead to symptoms of depression. There is at least one report of increased Bmax of the 5-HT1A receptor in the frontal cortex of patients who committed suicide via nonviolent means versus those who used violent means or nonsuicidal controls (Matsubara et al., 1991). Discordant reports have also appeared (Cheetham et al., 1990). In one postmortem study of victims of suicide with a “firm” retrospective diagnosis of depression, no differences in 5-HT1A Bmax were detected in all brain regions analyzed, and there was no relationship

445

between Bmax and method of suicide or antidepressant exposure (Lowther et al., 1997). The development of PET ligands specific to the 5HT1A and 5-HT2A receptors has allowed these receptors to be studied in vivo (Fujita et al., 2000). The ligand [11C] WAY100635 has been consistently used to image the 5-HT1A receptor in PET studies. Two studies comparing patients with familial depression versus controls have reported reduced 5-HT1A receptor binding in midbrain raphé, frontal cortex, and mesiotemporal cortex (Drevets et al., 1999; Sargent et al., 2000). More recently, patients with temporal lobe epilepsy (TLE) and major depression were found to have a greater reduction in 5-HT1A receptor binding in limbic regions than patients with TLE without depression (Hasler et al., 2007). However, another study found significantly greater 5-HT1A binding in antidepressant naïve patients who were depressed versus controls, but previously treated patients who were depressed did not differ from controls (Parsey, Oquendo, et al., 2006). Previously treated men remitted from major depression were found to have a persistent 17% decrease in cortical 5-HT1A receptor binding potential compared to controls in another study (Bhagwagar et al., 2004). Taken together, these findings leave unresolved the question of whether reduced 5-HT1A expression is a trait marker for major depression but do provide some support for the theory that antidepressant use may have long-term effects on the 5-HT1A receptor. The results with 5-HT2A specific ligands are also variable, likely due to methodological variability in the specific radioligand employed and use of psychotropic medications in temporal proximity to the scanning. One study compared 14 patients who were depressed to 19 healthy controls and found no differences in ligand binding between the two groups (Meyer et al., 1999). These investigators attempted to study the 5-HT2A receptor in depression, independent of suicidality, by excluding patients with a history of suicide attempt within 5 years of the study. In another study of 8 drug-free patients who were depressed compared to 22 healthy controls, there was a significant reduction in the 5-HT2A binding in the right posterolateral orbitofrontal cortex and anterior cingulate cortex of the patients who were depressed (Biver et al., 1997). A study of 20 unmedicated patients who were depressed compared to 20 healthy controls yielded a similar result, that is, reduced 5-HT2A binding in frontal, temporal, parietal, and occipital cortex (Yatham et al., 2000). In a PET study of patients with late-life depression, there was no difference between those who were depressed and controls in 5-HT2A labeling, but there was a dramatic decrease in 5-HT2A signal in patients with dementia (Meltzer et al., 1999). The largest study to date, comparing 46 patients who were depressed with 29 controls, found patients who were depressed to have 29% lower 5-HT2A receptor

446

MOOD DISORDERS

binding in the hippocampus, and nonsignificantly reduced binding in several other brain regions (Mintun et al., 2004). Recently, increased 5-HT2A receptor binding in frontal, parietal, and occipital cortical regions was demonstrated using PET in 20 unmedicated patients remitted from a major depressive episode compared to 20 controls (Bhagwagar et al., 2006). Results of PET studies of 5-HT2A binding in patients who were depressed who had been treated with antidepressants have been even more variable. In a study of patients who were depressed treated with the TCA clomipramine, there was a significant reduction in cortical 5-HT2A binding density (Attar-Levy et al., 1999). These authors reported no relationship between measures of depression severity and the intensity of labeling of the 5-HT2A receptor in the treated group. A similar result was reported in a study of 10 patients who were depressed treated with desipramine (Yatham et al., 1999). In this study, 8 of the 10 patients exhibited a significant antidepressant response, as revealed by a 50% reduction in the Hamilton Depression Rating Scale (HDRS), but all of the patients demonstrated a reduction in 5-HT2A binding bilaterally throughout the cortex, regardless of the antidepressant response. However, as in the previous study, there was no relationship between measures of depression severity and change in 5-HT2A labeling. The opposite result has also been reported (Massou et al., 1997). In this study of six patients who were depressed treated with SSRIs, there was an increase in cortical 5-HT2A labeling compared to untreated patients who were depressed. Clearly, no firm conclusions can be drawn from these results about the impact of antidepressants on CNS 5-HT2A binding kinetics. There is an abundance of data implicating the serotonergic system in the pathophysiology of major depression. Although one specific causal pathological change has not been found, multiple perturbations of the serotonergic system, pre- and postsynaptic, have been documented in major depression. Many different antidepressants have pharmacodynamic targets within the serotonergic system, and many, if not all, act in part by modifying the activity of serotonergic circuits. Future research into the function of 5-HT systems will surely address the molecular mechanisms that result in the observed changes in depression and in response to antidepressants. Dopamine Historically, dopamine (DA) has not received the attention accorded 5-HT and NE in theories of the pathophysiology of depression. The DA systems were largely considered to have little or no importance in the biology of mood disorders, with the exception of a central role in psychotic depression (Schatzberg et al., 1985). Several lines of evidence are consistent with a role for

DA systems in the pathophysiology of depression, including evidence of altered DA function in patients who are depressed, pathological mood symptoms in patients suffering from other diseases that affect DA systems (principally Parkinson’s disease), and the effects on mood of psychopharmacological agents that alter DA neurotransmission (Dunlop and Nemeroff, 2007). Moreover, some antidepressants appear to enhance and may even predominantly act via a dopaminergic action. Key findings implicating dysfunction of the dopaminergic system in depression are summarized in Table 30.4. Dopamine neurotransmission is frequently estimated by measuring its major metabolite, homovanillic acid (HVA), in bodily fluids. The concentration of HVA is directly related to the extracellular concentration of DA, and therefore the concentration of HVA is thought to reflect the activity state of presynaptic DA neurons. The majority of studies examining CSF HVA concentrations in major depression have found lower concentrations in patients who are depressed compared to controls, particularly in patients with psychomotor retardation (Kapur and Mann, 1992). Careful matching for age between patients who are depressed and controls is necessary as there is a functionally significant and progressive loss of DA activity with advancing age, largely due to a loss of DA neurons. In a unique study employing internal jugular venous sampling, medication-free treatment-resistant patients with unipolar depression were found to exhibit reduced concentrations of NE and its metabolites, and HVA, but not 5-HIAA, compared to healthy controls (Lambert et al., 2000). In this study, estimates of brain DA turnover were inversely correlated with the severity of depressive illness. Low CSF HVA concentrations are not specific to major depression because this finding has also been reported in Parkinson’s and Alzheimer’s diseases (Van Praag et al., 1975; Wolfe et al., 1990). There are also reports of increased CSF HVA in patients who are agitated and manic (Willner, 1983), providing further evidence that CSF HVA levels and hence DA neurotransmission may be more a marker for psychomotor activity than for mood state. Dopamine metabolites are detectable in urine and have been measured in cohorts of patients who are depressed compared to various control groups. In one study of 28 patients who were depressed and 25 controls, the urinary concentration of 3,4-dihydroxyphenyl acetic acid (DOPAC), another DA metabolite, was significantly lower in the patients who were depressed compared to the controls (Roy et al., 1986). In another study in which the 24-hour urinary excretion of a number of DA metabolites was measured, patients with depression and a suicide attempt had lower DA metabolite concentrations than patients with depression and no suicide attempts (Roy et al., 1992).

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS

447

TABLE 30.4 Findings Implicating Dopaminergic Dysfunction in the Pathophysiology of Depression at Various Neuropharmacologic Levels of Action

Level of Action Neurotransmitter storage

Finding

Replicability

Long-term treatment with reserpine, which depletes monoamine stores, results in depressive symptoms in patients with a history of depression

++

Depression comorbid with Parkinson’s disease

+++

Neurotransmitter release

L-DOPA

++

Neurotransmitter reuptake

Stimulants (amphetamine, methylphenidate) elevate mood in depressed and nondepressed individuals

+++

“Novel” antidepressants block dopamine reuptake; for example, nomifensine, amineptine

++

Neurotransmitter metabolism

Postsynaptic neurotransmitter receptors

relieves mood symptoms in Parkinson’s disease patients

MAOIs are effective antidepressants

+++

Low CSF HVA in subgroups of depressed patients

+

Increased CSF HVA in manic patients

++

MAO-A levels elevated in depressed patients

+

Typical antipsychotics (D2 antagonists) induce apathy, anhedonia, and avolition

++

CSF: cerebrospinal fluid; L-DOPA: L-dihydroxyphenylalanine; MAOI: monoamine oxidase inhibitor; HVA: homovanillic acid (dopamine metabolite). Replication key: +: one or no replication studies; + +: several replication studies, + + +: highly replicated by more than two research groups.

Another line of evidence that supports a role for DA system dysfunction in depressive syndromes is suggested by the mood symptoms that occur in patients with Parkinson’s disease. The incidence of major depression in community samples of Parkinson’s disease patients is 5%–10%, with an additional 10%–30% experiencing subsyndromal depressive symptoms (Tandberg et al., 1996). Depressive symptoms in these patients often precede the development of the physical manifestations of the disorder (Van Praag et al., 1975; Guze and Barrio, 1991). The symptoms of depression in patients with Parkinson’s disease do not appear to be related to the severity of disability resulting from the disease itself (Murray, 1996). Treatment of patients with Parkinson’s disease with L-dihydroxyphenylalanine (L-DOPA) is often associated with antidepressant effects that can precede the improvement in the physical symptoms of the disease (Murphy, 1972). Results of functional neuroimaging studies of DA function in patients who are depressed have been informative, though the D2 receptor binding studies in major depressive disorder (MDD) have been inconsistent (Table 30.2). Early studies examining striatal D2 binding found elevated levels in inpatients who were depressed, either in whole group samples (D’haenen and Bossuyt, 1994; Shah et al., 1997), or when limited to a psychomotor retarded group (Ebert et al., 1996). Elevated D2 receptor binding may reflect increased numbers of D2 receptors in depression (possibly reflecting presynaptic hypofunction), an increase in affinity of the receptor for the ligand, or a decrease in availability of synaptic

DA (which competes with the radiolabeled ligand, albeit weakly, for D2 binding). Two later studies failed to confirm these findings, though one study used a nonhealthy control group and the other studied outpatients (Klimke et al., 1999; Parsey et al., 2001). A major confound across the studies was the medication status of the patients, as most were either on antidepressant therapy or had only a 7-day washout prior to the imaging procedure. Variability in the level of anxiety may also confound the results, as anxiety has been associated with reduced D2 receptor expression (Schneier et al., 2000). In the two studies comparing D2 binding pre- and postantidepressant treatment for depression, clinical improvement was noted with either an increase or decrease in D2 receptor binding, perhaps due to the differing mechanism of action of the drugs employed (Ebert et al., 1996; Klimke et al., 1999). Studies of dopamine transporter (DAT) expression have also found conflicting results, though the most comprehensive PET study observed reduced DAT binding in depression (Meyer et al., 2001). In a PET study assessing DA neuronal function by measuring [18F]-fluoro-DOPA uptake in the striatum, patients who were depressed with psychomotor retardation exhibited reduced striatal uptake of the radioligand compared to inpatients who were anxious and depressed and healthy volunteers (Martinot et al., 2001). Anhedonia is a core symptom of depression that has been posited to be particularly related to DA transmission because DA neurotransmission has long been known

448

MOOD DISORDERS

to be critical to a wide variety of pleasurable experiences and reward. Severity of depression has been found to correlate highly with the magnitude of reward experienced after oral d-amphetamine, which increases DA availability by a variety of mechanisms (Tremblay et al., 2002). In particular, medication-free patients who were severely depressed experienced greater reward than controls, while those with milder forms of depression did not differ from the control group. In an fMRI study extending these findings, patients who were severely depressed demonstrated a markedly greater behavioral response to the rewarding effects of the psychostimulant than controls, and had altered brain activation of the ventrolateral prefrontal cortex, orbitofrontal cortex, caudate, and putamen (Tremblay et al., 2005). Glucocorticoids selectively facilitate DA transmission in the nucleus accumbens, thereby providing a potential link between the findings of hypercortisolemia and altered reward experience in severe depression (Marinelli and Piazza, 2002). Another important link between glucocorticoids and DA function may be present in psychotic depression. Increased DA neurotransmission is considered to be central to the production of psychotic symptoms in schizophrenia, stimulant-induced psychoses, and major depression with psychotic features. Patients with psychotic depression have increased serum levels of DA and HVA compared to patients with nonpsychotic depression (Devanand et al., 1985; Schatzberg et al., 1985). The increased levels of glucocorticoids routinely observed in psychotic depression may drive the increase in DA activity (Rothschild et al., 1984). This has led to the hypothesis that increased glucocorticoid secretion in patients who are depressed produces increased DA neurotransmission, which in turn leads to the development of psychotic symptoms (Schatzberg and Rothschild, 1992; Posener et al., 1999). Results of neuroendocrine challenge tests have been used to explore DA dysfunction in depression. Apomorphine is an agonist at D2/D3 DA receptors and causes increased secretion of GH via binding to postsynaptic DA receptors in the arcuate nucleus of the hypothalamus. The majority of studies have found no difference in GH response to apomorphine between patients who were depressed and healthy controls (McPherson et al., 2003). Results from this paradigm in patients who were actively manic were equivocal and did not directly support the hypothesis of excessive DA activity in mania (Ansseau et al., 1987). The GH response to apomorphine also does not differ between subjects with panic disorder and controls. The apomorphine challenge test may be a marker for suicidality in patients who are depressed because there are reported differences in GH response between patients who are depressed who make suicide attempts or commit suicide and those with no history of suicide attempts (Pitchot et al., 2001a, 2001b).

Postmortem studies of the DA system in patients who are depressed are relatively few and have provided conflicting results. Dopamine concentrations in the brains of victims of suicide are unchanged compared to controls (Moses and Robins, 1975; Bowden, Cheetham, et al., 1997). In victims of suicide, HVA concentrations in the frontal cortex have been found to be elevated (Beskow et al., 1976; Ohmori et al., 1992), or unaltered (Crow et al., 1984), and unaltered in the basal ganglia (Beskow et al., 1976; Bowden, Cheetham, et al., 1997). Cerebrospinal fluid HVA concentrations from those who attempted suicide have been found to be lower than those of controls (Engstrom et al., 1999), but not different between those who were high- versus low-lethality attempters (Mann and Malone, 1997). Concentrations of DA metabolites in the caudate, putamen, and nucleus accumbens were reduced in antidepressantfree patients who were depressed who died by suicide compared to controls (Bowden, Theodorou, et al., 1997). A postmortem study comparing psychiatrically normal controls with patients who were depressed using immunohistochemical and autoradiographic methods found reduced DAT density and elevated D2/D3 receptor binding in the central and basal nuclei of the amygdala in the patients who were depressed (Klimek et al., 2002). A second study using different methods and larger brain regions found no difference in D2 receptor number or affinity (Bowden, Theodorou, et al., 1997). No studies have reported a difference in D1 receptor binding between patients who were depressed who died by suicide and controls. The actions of a number of different drugs suggest that increasing DA transmission is associated with improvement in depressive symptoms. The psychostimulants d-amphetamine and methylphenidate increase DA release, with resultant increased energy, activation, and elevated mood. Although these drugs cause transient mood elevations in individuals who are depressed and euthymic (Jacobs and Silverstone, 1988; Little, 1988), they are ineffective as antidepressants, at least as monotherapy. They may be effective as adjuncts to SSRIs and other antidepressants in nonresponders (Fawcett and Busch, 1998). Several individual studies have found an inverse association between CSF HVA concentrations and the magnitude of clinical response to agents with relatively specific effects on DA, including L-DOPA, piribedil, and nomifensine (van Praag et al., 1975; Post et al., 1978; van Scheyen et al., 1977). The atypical antidepressants bupropion (Ascher et al., 1995) and amineptine (Garattini, 1997) have been suggested to be antagonists of the DA transporter, but in vitro and in vivo data on the former are not persuasive. Remarkably, the high potency of sertraline as a DA transporter antagonist has been largely overlooked (Owens et al., 1997a, 1997b). Pramipexole, a nonergot DA agonist used in the treatment of Parkinson’s disease and restless

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS

legs syndrome, exhibits marked selectivity for D2-like receptors, particularly the D3 receptor. In a neuroimaging study of baboons, pramipexole reduced cerebral blood flow in the orbitofrontal cortex, subgenual anterior cingulate cortex, and insula, all regions thought to contribute significantly to mood regulation (Black et al., 2002). Pramipexole has demonstrated efficacy for depressive symptoms in two double-blind, placebo-controlled studies of patients with bipolar depression on mood stabilizer therapy (Goldberg et al., 2004; Zarate et al., 2004), and in a monotherapy study in unipolar major depression (Corrigan et al., 2000). Ropinirole, another D2/D3 agonist, has also demonstrated antidepressant efficacy (Cassano et al., 2005). In contrast, typical antipsychotic drugs are potent antagonists of multiple DA receptors. A syndrome that resembles depression often results from treatment with these agents, with symptoms that include anhedonia, anergia, and dysphoria (Belmaker and Wald, 1977). GABA Gamma (g)-aminobutyric acid (GABA) is the predominant inhibitory neurotransmitter in the CNS, with GABAergic neurons constituting 20%–40% of all neurons in the cortex and more than three fourths of all striatal neurons (Hendry et al., 1987; Tepper et al., 2004). Most GABAergic cells in the brain are interneurons, with short axons that form synapses within a few hundred microns of their cell body, connecting different neurons together and coordinating neuronal activity within local brain regions. GABA neurons provide tonic inhibition of raphé nuclei neurons, and 5HT-containing neurons from the raphé project to the cortex and preferentially synapse on GABA interneurons (more so than pyramidal neurons), increasing their firing rate. Cerebrospinal fluid and plasma GABA concentrations have been demonstrated to be lower in patients who were depressed than controls, with persistence of low plasma GABA levels up to 4 years after remission, suggesting that low plasma GABA levels may be a trait marker for depression (Gold et al., 1980). Support for this hypothesis emerged from the finding that plasma GABA levels are lower in individuals who were not depressed who have a first-degree relative with a history of major depression than in those without such a family history (Bjork et al., 2001). The source of plasma GABA remains obscure and may not be the CNS. Moreover, recent studies employing magnetic resonance spectroscopy found that reduced cortical GABA concentrations present in the acutely depressed state resolved after successful treatment with medication or electro-convulsive therapy (ECT) (Sanacora et al., 2002, 2003; Hasler et al., 2005). Reductions in GABA concentrations are not specific to depression, having also been demonstrated in alcohol dependence and mania (Petty, 1994). Further

449

evidence of reduced GABAergic tone in patients who are depressed is suggested by lower resting-state levels of cortical inhibition as assessed by transcranial magnetic stimulation (Bajbouj et al., 2006). Neuropeptides Many different peptide neurotransmitter systems have been scrutinized in major depression. In particular, those peptides that regulate the hypothalamic-pituitary-adrenal (HPA) and the hypothalamic-pituitary-thyroid (HPT) axes have been hypothesized to play a significant role in the pathophysiology of mood disorders (Plotsky et al., 1995). The changes in neuroendocrine function that have been repeatedly documented in major depression support the proposition that the peptide systems that regulate the neuroendocrine axes are intimately involved in depression and may even be one of the primary substrates in the pathophysiology of depression. Corticotropin-releasing factor (CRF), which regulates the activity of the HPA axis; somatostatin, which regulates the secretion of GH from somatotrophs; and thyrotropin-releasing hormone (TRH), which regulates the HPT axis, have all been intensively studied in mood disorders. Key findings implicating dysfunction of these three neuropeptide systems in depression are summarized in Table 30.5. Corticotropin-releasing Factor Corticotropin-releasing factor (CRF) is the major secretogogue controlling the release of adrenocorticotropic hormone (ACTH) from the corticotrophs in the anterior pituitary and is also a neurotransmitter in extrahypothalamic brain regions. There is considerable evidence that the extrahypothalamic CRF system orchestrates the stress responses, coordinating endocrine, autonomic, immune, and behavioral outputs. Given the global role of CRF in coordinating stress responsivity, hyperactivity of this system has been hypothesized to be central to the pathophysiology of depression (Nemeroff, 1996; Arborelius et al., 1999). The CSF concentration of CRF in untreated patients who are depressed has been demonstrated to be increased compared to healthy controls in several studies (Hartline et al., 1996). Intracisternally collected CSF concentrations of CRF have been found to be elevated in victims of suicide, who presumably were suffering from depression at the time of death (Arato et al., 1989). Higher plasma concentrations of CRF have been reported in patients who were depressed compared to controls (Catalan et al., 1998). The increase in CRF in major depression appears to be due to up-regulated production and release because there is increased expression of the messenger ribonucleic acid (mRNA) that encodes CRF in the hypothalamus of victims of suicide

450 TABLE

MOOD DISORDERS

30.5 Findings Implicating Three Neuropeptide Systems in the Pathophysiology of Depression

Neuropeptide Corticotrophin releasing factor (CRF)

CRF receptors

Somatostatin

Thyrotropin-releasing hormone (TRH)

Finding

Replicability

Increased concentration in CSF of depressed patients

+++

CSF level normalizes with treatment

++

Increased CRF mRNA in postmortem brains of suicides

+

Decreased Bmax in postmortem brains of suicides

+

Blunted ACTH release in response to CRF challenge

+++

ACTH response normalizes with treatment

+

Decreased CSF concentration in unipolar and bipolar depression

+++

“State” marker, normalizes with treatment

++

Not specific to depression; also decreased in Alzheimer’s disease, Parkinson’s disease, multiple sclerosis

++

Increased CSF concentration in depressed patients

++

25%–30% of euthyroid depressed patients have blunted TSH response to TRH challenge

+++

25%–30% of euthyroid depressed patients have abnormal T3/T4 levels

+

ACTH: adrenocorticotropic hormone; CSF: cerebral spinal fluid; TSH: thyroid stimulating hormone; T3/T4: thyroid hormones; mRNA: messenger ribonucleic acid. Replication key: +: one or no replication studies; + +: several replication studies; + + +: highly replicated by more than two research groups.

who were depressed (Raadsheer et al., 1995) and an increase in the number of CRF immunopositive neurons. Similar findings have been observed in other brain regions including the cerebral cortex and locus ceruleus (Bissette et al., 2003; Merali et al., 2004). The CSF concentration of CRF has also been shown to be elevated in patients with anorexia nervosa (Kaye et al., 1987). In these patients, CSF CRF levels normalize with restoration of normal weight. The relationship, if any, between the regulation of CRF expression in depression and anorexia nervosa remains obscure. Two studies have reported elevated CSF CRF concentrations in patients with PTSD (Bremner et al., 1997; Baker et al., 1999). The increased CSF CRF levels appear to be relatively specific for depression, PTSD, and anorexia nervosa because they have not been observed in patients with schizophrenia, neurological disorders, dementia, or in those with mania, panic disorder, or other psychiatric diagnoses, unless they also suffered from comorbid depression. The CSF CRF concentration in depression appears to be a state-dependent measure because the levels normalize after treatment with ECT, fluoxetine, and other antidepressants (Nemeroff et al., 1991; DeBellis et al., 1993). In a cohort of elderly individuals who were depressed and treated with amitriptyline, CSF CRF concentrations decreased in those who responded to treatment (Heuser et al., 1998). In a control cohort, also treated with amitriptyline, there was a nonsignificant decrease in CSF CRF concentrations. This suggests a general reduction of CRF secretion in response to anti-

depressant treatment. Normalization of the CSF CRF concentration may be predictive of long-term remission, while failure to normalize may predict early relapse (Banki et al., 1992). In two studies, we observed decreased Bmax values for CRF receptors in the frontal cortex of victims of suicide who were depressed (Nemeroff et al., 1988). This finding has been confirmed in an elegant study using sensitive polymerase chain reaction (PCR) methods to assess CRF-1 mRNA expression (Merali et al., 2006). However, there is one discrepant report of no differences in CRF receptor Bmax values in depression (Hucks et al., 1997). In this study of victims of suicide with a “firm” antemortem diagnosis of depression, there were no differences in CRF receptor density, nor did exposure to antidepressants or method of suicide correlate with CRF receptor Bmax. One interpretation of the finding of decreased CRF receptor Bmax is down-regulation of CRF receptors in response to the chronic hypersecretion of CRF in depression. Concordant with this are results of the CRF stimulation test, in which the ACTH response to a standard intravenous dose of CRF is measured. In patients who are depressed, there is blunting of the ACTH response to intravenously administered CRF compared to controls (Holsboer et al., 1987; E.A. Young et al., 1990). The ACTH response to CRF challenge in patients who are depressed has been reported to normalize with treatment and syndrome resolution (Amsterdam et al., 1988). More recently a combination of the dexamethasone suppression test (DST) and the CRF stimu-

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lation test, the so-called Dex-CRF test, has been developed and is arguably the most sensitive measure of the HPA axis activity (von Bardeleben and Holsboer, 1989). It is markedly abnormal in many patients who are depressed. Based on the CRF hypersecretion model, antagonists of the CRF1 receptor subtype have been scrutinized as potential antidepressants. Proof-of-concept studies suggest that blocking this receptor does relieve symptoms of depression (Zobel et al., 2001). These agents do demonstrate an antidepressant profile in animal models. A confluence of data, neurochemical, postmortem, and pharmacological, is concordant with the CRF hypersecretion hypothesis of major depression. What remains obscure is whether the CRF system is subject to a higher level of regulation that is also altered in depression, by 5-HT or NE systems, for example, or whether the dysfunction of the CRF system is the primary pathophysiological alteration in major depression. Somatostatin and the Growth Hormone Axis Somatostatin is a tetradecapeptide that inhibits the secretion of GH from the anterior pituitary. This peptide is also referred to as GH-release inhibiting hormone (GHRF) or somatotropin release-inhibiting factor (SRIF). Like CRF, SRIF has been clearly demonstrated to be a neurotransmitter, with a heterogeneous distribution outside of the hypothalamus. At least four different SRIF receptor subtypes have been cloned, with overlapping affinities and effector couplings. Somatostatin has been shown to affect sleep, ingestive behaviors, activity state, memory and cognition, and nociception. Growth hormone secretion is blunted in major depression in the clonidine, sumatriptan/zolmitriptan, and apomorphine challenge assays. These are probes of the NE, 5-HT, and DA systems, respectively, which suggests possible dysfunction of the somatostatin–GH axis in major depression, revealed by each of these neuroendocrine challenge assays. The GH response to SRIF is also blunted in patients who are depressed in most but not all studies. The GH response to SRIF is blunted in children who are depressed and in children at high risk for depression due to familial loading, suggestive of a trait marker (Birmaher et al., 2000; Dahl et al., 2000). The CSF concentration of SRIF is decreased in major depression (Gerner and Yamada, 1982; Rubinow et al., 1983; Bissette et al., 1986; Rubinow, 1986). Levels of CSF SRIF are decreased in unipolar depression and in BPD during the depressed phase of the illness. Levels of CSF SRIF appear to be a state marker of depression because they normalize with successful treatment and symptom resolution. This has been observed in patients with unipolar and bipolar depression. Concentrations of CSF SRIF are not altered in schizophrenia, anorexia nervosa, euthymic BPD, or remitted depression. Remarkably, CSF

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SRIF levels are also increased in patients with obsessivecompulsive disorder (Altemus et al., 1993). The finding of decreased CSF somatostatin concentrations is not specific to major depression. The same finding has been reported in a number of neurological diseases without prominent comorbid psychiatric symptoms. Thus, decreased CSF SRIF levels have been reported in dementing diseases including Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. In contrast, increased levels of CSF SRIF have been reported in traumatic or inflammatory neurological processes including compression injuries, meningitis, and encephalopathies. Although a decreased CSF SRIF concentration represents a state-dependent marker of depression, it appears to be relatively nonspecific, as it occurs in a number of unrelated nonpsychiatric conditions. Whether the decreased somatostatin level plays a role in the pathophysiology of depression, or is an epiphenomenon of the generalized HPA dysfunction that has been hypothesized by some investigators to occur in depression, remains to be determined. Hypothalamic-Pituitary-Thyroid Axis The manifestations of hypothyroidism can appear indistinguishable from those of major depression, with symptoms of depressed mood, impaired cognition, and multiple neurovegetative symptoms in both conditions. For this reason, the HPT axis has been intensively scrutinized in major depression. Approximately 20%–30% of patients with major depression have discernible HPT dysfunction. Secretion of thyroid-stimulating hormone (TSH) from the anterior pituitary gland is primarily regulated by thyrotropin-releasing hormone (TRH), a tripeptide that is released into the hypothalamic-hypophyseal portal system from hypothalamic neurons that project to the median eminence. Thyroid-stimulating hormone induces the secretion of l-triiodothyronine (T3) and thyroxine (T4) from the thyroid gland. As with other peptide neurotransmitters, the CSF concentration of TRH has been measured in patients with major depression. Two studies reported that the concentration of TRH was increased in patients who were depressed compared to neurological and nondepressed controls (Kirkegaard et al., 1979; Banki et al., 1988). A negative study has also appeared (Roy et al., 1994). The CSF concentration of TRH has been reported to be unaltered in Alzheimer’s disease, anxiety disorders, and alcoholism. The CSF concentration of transthyretin has been reported to be decreased in major depression (Sullivan et al., 1999), and a recent replication of this finding found a strong inverse correlation between transthyretin levels and suicidal ideation (Sullivan et al., 2006). Transthyretin transports and distributes thyroid hormones in the CNS. Decreased availability of this molecule in the CNS could result in a hypometabolic state in

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the neurons of individuals who are affected. This finding could account for observations of “normal” concentrations of thyroid hormones in depression, as well as the utility of thyroid hormone augmentation in nonresponders to antidepressants. Decreased transthyretin would functionally result in hypothyroidism within the CNS. A number of peripheral thyroid indices have been measured in major depression. Red blood cell T3 uptake is increased in major depression, and changes in this marker in response to antidepressants may predict a further treatment response (Moreau et al., 2000). In another study, pretreatment plasma T3 and T4 levels did not correlate to Rush / Thase stage of treatment resistance (Joffe, 1999). In a naturalistic study of patients with unipolar depression treated by “clinician choice” to the point of remission, serum T3 levels were inversely related to time to relapse after initial remission (Joffe and Marriott, 2000). Higher T3 levels appear to be protective against relapse. Interestingly, treatment of patients who are severely depressed with the SSRI paroxetine was noted to cause an 11.2% reduction in circulating T4, whereas 24 weeks of sertraline treatment in 15 inpatient women who were depressed increased T3 levels by 24% but did not affect T4 levels (Konig et al., 2000; Sagud et al., 2002). The TRH stimulation test is generally considered to be one of the most sensitive measures of HPT axis function. In this test, plasma TSH concentrations are measured at baseline and at 30-minute intervals for at least 2 hours after a challenge dose of TRH. This test has been administered to a large number of patients who were depressed and controls in many independent studies (Kastin et al., 1972; Prange et al., 1972). Across all of these studies, 25%–30% of the patients who were depressed exhibit a blunted TSH response to TRH challenge. This is apparently not due to primary hyperthyroidism because these patients who were depressed were euthyroid at the time of assessment. In one study, patients were specifically identified as being depressed but having “high-normal” baseline circulating TSH levels (Kraus et al., 1997). In this particular cohort of patients who were depressed, 38% demonstrated exaggerated TSH secretion in response to TRH challenge. The magnitude of the TSH response was not related to the baseline TSH value. The authors of this study suggest that there may be a subset of patients who are depressed who are in fact hypothyroid, a condition that is revealed only by the TRH challenge assay. In a related study, 26% of patients who were depressed were reported to have abnormal concentrations of circulating thyroid hormones (T3 and / or T4), which normalized with treatment and syndrome resolution (Shelton et al., 1993). One possible explanation for the blunted TSH response to TRH challenge is down-regulation of TRH receptors in the pituitary in response to increased secretion of TRH into the hypophyseal-portal circulation. This has been tested in a cohort of 15 patients

who were depressed who had pretreatment measurement of CSF TRH followed by a TRH stimulation test (Frye et al., 1999). There was no relationship between CSF TRH levels and TSH response to TRH in these patients. These authors also reported no correlation between CSF TRH concentrations and severity of depression. However these results are in contrast to those of Adinoff et al. (1991), who found a very significant correlation between CSF TRH concentrations and the TSH response to TRH in patients who were alcoholic. The significance of alteration of the HPT axis in the pathogenesis of depression remains to be elucidated. Certainly, one could postulate a subtype of depression (or hypothyroidism) in which there was disruption of the HPT axis revealed only by the TRH challenge test. Whether this represents a distinct disease entity has not been determined, nor is it clear that the patients with depression and altered TRH challenge respond preferentially to any particular treatment regimen. Potentially relevant to these findings are studies that have demonstrated the efficacy of T3 in accelerating the response to older antidepressants and in converting antidepressant partial responders into full responders (Altshuler et al., 2001; Aronson et al., 1996). Whether addition of T3 improves the speed and rate of response with SSRIs remains uncertain. A placebo-controlled study with paroxetine found no benefit on outcome with T3 supplementation (Appelhof et al., 2004), but a similar study combining sertraline with T3 did show improved response and remission rates (Cooper-Kazaz et al., 2007). Thyroid hormones may contribute to the biology of major depression through the effects of T3 on serotonin function. T3, alone and in combination with fluoxetine, reduces transcription of the 5-HT1A and 5-HT1B receptors (Lifschytz et al., 2006). Down-regulation of the 5HT1A autoreceptor may be an important mechanism of action of antidepressants. The ability of T3 augmentation to enhance this down-regulation may provide benefits, in the speed and overall response, when used to augment an antidepressant. One intriguing observation that suggests a role for HPT system dysfunction in major depression comes from the antidepressant actions of TRH. In two small studies reported by the same research group, TRH appeared to have antidepressant actions in patients with treatmentrefractory depression (Callahan et al., 1997; Marangell et al., 1997). In one report, two patients responded to intravenous and intrathecal administration of TRH, though tolerance developed to the intravenous route. In a second study by the same group, eight patients with treatment-refractory depression were treated with intrathecal TRH in a double-blind trial. Five of the eight patients had a 50% or greater reduction in HDRS, but the responses were transient. These results are clearly preliminary, but they further support a role for the TRH system in the biology of major depression and may point the way to a novel treatment strategy.

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CONCLUSIONS Despite 40 years of concerted research, the primary neurochemical pathology of major depression has not been identified. Dysfunction of many different neurotransmitter systems has been documented in depression, yet no one system or one perturbation has clearly emerged as the fundamental pathology in major depression. Reconciling the clinical manifestations of depression with the described neurochemical manifestations of depressed patients is one of the great challenges facing psychiatric researchers in the future. There is clearly a great deal of redundancy and functional reserve within the CNS, such that pathological changes that result in depression would be quickly and diffusely compensated for by other neurochemical systems. In fact, many of the neurochemical changes documented above could be manifestations of adaptive responses to depression and not at all related to the primary pathological process. Thus, it is not surprising that the primary defect in depression has not been identified. A disease such as major depression that manifests symptoms in many different neurobehavioral domains, including mood and emotion, cognition, perception, autonomic function, homeostatic function, and stress responsiveness, would be expected to cause disruption of the neurochemical systems that regulate these diverse processes. There are many avenues for future research into the pathophysiology of major depression. With the emergence of functional neuroimaging modalities, the opportunity to study patients across the course of their illness is now available. The development of well-characterized and consistently acquired banks of postmortem tissues will further allow the study of the changes that major depression causes in the CNS. The other major intellectual resource that will illuminate the search for the etiopathology of depression is the rapidly evolving human genome initiative. As knowledge of the molecular genetics of the nervous system advances and new technologies such as high-density microarray systems become available, new insights into the function and dysfunction of the brain will increase our knowledge of the pathophysiology of major depression. ACKNOWLEDGMENTS Boadie W. Dunlop is supported by a K-12 grant from the National Institutes of Health (NIH) Center for Research Resources, K12 RR 017643. Charles B. Nemeroff is supported by NIH Grants MH-42088, MH-39415, MH–77083 and MH-69056, and MH-58922, an American Foundation for Suicide Prevention Distinguished Investigator Award, and a National Alliance for Research on Schizophrenia and Depression (NARSAD) Established Investigator Award. REFERENCES Adinoff, B., Nemeroff, C.B., et al. (1991) Inverse relationship between CSF TRH concentrations and the TSH response to TRH in abstinent alcohol-dependent patients. Am. J. Psychiatry 148: 1586–1588.

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Altemus, M., Pigott, T., et al. (1993) CSF somatostatin in obsessivecompulsive disorder. Am. J. Psychiatry 150(3):460– 464. Altshuler, L.L., Bauer, M., et al. (2001) Does thyroid supplementation accelerate tricyclic antidepressant response? A review and meta-analysis of the literature. Am. J. Psychiatry 158:1617–1622. Amsterdam, J.D., Maislin, G., et al. (1988) The oCRH test before and after clinical recovery from depression. J. Affect. Disord. 14: 213–222. Amsterdam, J.D., Maislin, G., et al. (1989) Multiple hormone responses to clonidine administration in depressed patients and healthy volunteers. Biol. Psychiatry 26(3):265–278. Anand, A., Charney, D.S., et al. (1994) Neuroendocrine and behavioral responses to intravenous m-chlorophenylpiperazine (m-CPP) in depressed patients and healthy comparison subjects. Am. J. Psychiatry 151(11):1626–1630. Ansseau, M., von Frenckell, R., et al. (1987) Neuroendocrine evaluation of catecholamine neurotransmission in mania. Psychiatry Res. 22(3):193–206. Appelhof, B.C., Brouwer, J.P., et al. (2004) Triiodothyronine addition to paroxetine in the treatment of major depressive disorder. J. Clin. Endocrinol. Metab. 89(12):6271–6276. Arango, V., Ernsberger, P., et al. (1990) Autoradiographic demonstration of increased serotonin 5-HT2 and b-adrenergic receptor binding sites in the brain of suicide victims. Arch. Gen. Psychiatry 47:1038–1047. Arango, V., Ernsberger, P., et al. (1993) Quantitative autoradiography of a1 and a2 adrenergic receptors in the cerebral cortex of controls and suicide victims. Brain Res. 630:271–282. Arato, M., Banki, C.M., et al. (1989) Elevated CSF CRF in suicide victims. Biol. Psychiatry 25:355–359. Arborelius, L., Owens, M.J., et al. (1999) The role of corticotropinreleasing factor in depression and anxiety disorders. J. Endocrinol. 160(1):1–12. Aronson, R., Offman, H.J., et al. (1996) Triiodothyronine augmentation in the treatment of refractory depression. A meta-analysis. Arch. Gen. Psychiatry 53(9):842–848. Arora, R.C., and Meltzer, H.Y. (1989a) Increased serotonin2 (5-HT2) receptor binding as measured by 3H-lysergic diethylamide (3HLSD) in the blood platelets of depressed patients. Life Sci. 44: 725–734. Arora, R.C., and Meltzer, H.Y. (1989b) Serotonergic measures in the brains of suicide victims: 5-HT2 binding sites in the frontal cortex of suicide victims and control subjects. Am. J. Psychiatry 146(6):730–736. Arora, R.C., and Meltzer, H.Y. (1993) Serotonin2 receptor binding in blood platelets of schizophrenic patients. Psychol. Res. 47: 111–119. Asberg, M., Traskman, L., et al. (1976) 5-HIAA in the cerebrospinal fluid: a biochemical suicide predictor? Arch. Gen. Psychiatry 33: 1193–1197. Ascher, J.A., Cole, J.O., et al. (1995) Bupropion: a review of its mechanism of antidepressant activity. J. Clin. Psychiatry 56(9):395– 401. Attar-Levy, D., Martinot, J.L., et al. (1999) The cortical serotonin2 receptors studied with positron-emission tomography and [18F]setoperone during depressive illness and antidepressant treatment with clomipramine. Biol. Psychiatry 45(2):180–186. Bajbouj, M., Lisanby, S.H., et al. (2006) Evidence for impaired cortical inhibition in patients with unipolar major depression. Biol. Psychiatry 59:395– 400. Baker, D.G., West, S.A., et al. (1999) Serial CSF corticotropin-releasing hormone levels and adrenocortical activity in combat veterans with posttraumatic stress disorder. Am. J. Psychiatry 156(4):585–588. Bakish, D., Cavazzoni, P., et al. (1997) Effects of selective serotonin reuptake inhibitors on platelet serotonin parameters in major depressive disorders. Biol. Psychiatry 41(2):184 –190. Banarjee, S.P., Kung, L.S., et al. (1977) Development of ß adrenergic receptor subsensitivity by antidepressants. Nature 268:455– 456.

454

MOOD DISORDERS

Banki, C.M., Bissette, G., et al. (1988) Elevation of immunoreactive CSF TRH in depressed patients. Am. J. Psychiatry 145:1526–1531. Banki, C.M., Karmacsi, L., et al. (1992) CSF corticotropin-releasing hormone and somatostatin in major depression: response to antidepressant treatment and relapse. Eur. Neuropsychopharmacol. 2: 107–113. Belmaker, R.H., and Wald, D. (1977) Haloperidol in normals. Br. J. Psychiatry 131:222–223. Benkelfat, C., Ellenbogen, M.A., et al. (1994) Mood-lowering effect of tryptophan depletion. Enhanced susceptibility in young men at genetic risk for major affective disorders. Arch. Gen. Psychiatry 51(9):687–697. Berman, R.M., Narasimhan, M., et al. (1999) Transient depressive relapse induced by catecholamine depletion: potential phenotypic vulnerability marker? Arch. Gen. Psychiatry 56(5):395– 403. Beskow, J., Gotffries, C.G., et al. (1976) Determination of monoamine and monoamine metabolites in the human brain: postmortem studies in a group of suicides and in a control group. Acta Psychiatr. Scand. 53:7–20. Bhagwagar, Z., Hinz, R., et al. (2006) Increased 5-HT2A receptor binding in euthymic medication-free patients recovered from depression: a positron emission study with [11C] MDL 100,907. Am. J. Psychiatry 163:1580–1587. Bhagwagar, Z., Rabiner, E.A., et al. (2004) Persistent reduction in brain serotonin1A receptor binding in recovered depressed men measured by positron emission tomography with [11C]WAY-100635. Mol. Psychiatry 9:386–392. Biegon, A., Essar, N., et al. (1990) Serotonin 5-HT2 receptor binding on blood platelets as a state dependant marker in major affective disorder. Psychopharmacology 102:73–75. Biegon, A., Grinspoon, A., et al. (1990) Increased serotonin 5-HT2 receptor binding on blood platelets of suicidal men. Psychopharmacology 100:165–167. Biegon, A., Weizman, A., et al. (1987) Serotonin 5-HT2 receptor binding on blood platelets—a peripheral marker for depression? Life Sci. 41:2485–2492. Birmaher, B., Dahl, R.E., et al. (2000) Growth hormone secretion in children and adolescents at high risk for major depressive disorder. Arch. Gen. Psychiatry 57(9):867–872. Bissette, G., Klimek, V., et al. (2003) Elevated concentrations of CRF in the locus coeruleus of depressed subjects. Neuropsychopharmacology 28:1328–1335. Bissette, G., Widerlov, E., et al. (1986) Alterations in cerebrospinal fluid somatostatin-like immunoreactivity in neuropsychiatric disorders. Arch. Gen. Psychiatry 43(12):1148–1151. Biver, F., Wikler, D., et al. (1997) Serotonin 5-HT2 receptor imaging in major depression: focal changes in orbito-insular cortex. Br. J. Psychiatry 171:444 – 448. Bjork, J.M., Moeller, F.G., et al. (2001) Plasma GABA levels correlate with aggressiveness in relatives of patients with unipolar depressive disorder. Psychiatry Res. 101:131–136. Black, K.J., Hershey, T., et al. (2002) A possible substrate for dopamine-related changes in mood and behavior: prefrontal and limbic effects of a D3-preferring dopamine agonist. Proc. Natl. Acad. Sci. USA 99:17113–17118. Bligh-Glover, W., Kolli, T.N., et al. (2000) The serotonin transporter in midbrain suicide victims with major depression. Biol. Psychiatry 47(12):1015–1024. Bowden, C., Cheetham, S.C., et al. (1997) Reduced dopamine turnover in the basal ganglia of depressed suicides. Brain Res. 769:135–140. Bowden, C., Theodorou, A.E., et al. (1997) Dopamine D1 and D2 receptor binding sites in brain samples form depressed suicides and controls. Brain Res. 752:227–233. Bremner, J.D., Licinio, J., et al. (1997) Elevated CSF corticotropinreleasing factor concentrations in posttraumatic stress disorder. Am. J. Psychiatry 154(5):624–629. Bremner, J.D., Vythilingam, M., et al. (2003) Regional brain metabolic correlates of alpha-methylparatyrosine-induced depressive

symptoms: Implications for the neural circuitry of depression. JAMA 289:3125–3134. Briley, M.S., Langer, S.Z., et al. (1980) Tritiated imipramine binding sites are decreased in platelets of untreated depressed patients. Science 209:303–305. Briley, M.S., Raisman, R., et al. (1979) Human platelets possess high affinity binding sites for 3H-imipramine. Eur. J. Pharmacol. 58: 347–348. Bunney, W.E., and Davis, M. (1965) Norepinephrine in depressive reactions. Arch. Gen. Psychiatry 13:137–152. Callahan, A.M., Frye, M.A., et al. (1997) Comparative antidepressant effects of intravenous and intrathecal thyrotropin-releasing hormone: confounding effects of tolerance and implications for therapeutics. Biol. Psychiatry 41(3):264–272. Cameron, O.G., Abelson, J.L., et al., (2004) Anxious and depressive disorders and their comorbidity: effect on central nervous system noradrenergic function. Biol. Psychiatry 56:875–883. Cappiello, A., Malison, R.T., et al. (1996) Seasonal variation in neuroendocrine and mood response to iv L-tryptophan in depressed patients and healthy subjects. Neuropsychopharmacology 15(5): 475– 483. Caspi, A., Sugden, K., et al. (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301:386–389. Cassano, P., Lattanzi, L., et al. (2005) Ropinirole in treatment-resistant depression: a 16-week pilot study. Can. J. Psychiatry 50:357–360. Catalan, R., Gallart, J.M., et al. (1998) Plasma corticotropin-releasing factor in depressive disorders. Biol. Psychiatry 44(1):15–20. Cheetham, S.C., Crompton, M., et al. (1988) Brain 5-HT2 receptor binding sites in depressed suicide victims. Brain Res. 443:272–280. Cheetham, S.C., Crompton, M.R., et al. (1990) Brain 5-HT1 binding sites in depressed suicides. Psychopharmacology 102:544 –548. Cleare, A.J., Murray, R.M., et al. (1998) Abnormal 5-HT1D receptor function in major depression: a neuropharmacological challenge study using sumatriptan. Psychol. Med. 28(2):295–300. Coccaro, E.F., Kavoussi, R.J., et al. (1996) 5-HT2a/2c receptor blockade by amesergide fully attenuates prolactin response to d-fenfluramine challenge in physically healthy human subjects. Psychopharmacology (Berl) 126:24–30. Cooper-Kazaz, R., Apter, J.T., et al. (2007) Combined treatment with sertraline and liothyronine in major depression. Arch. Gen. Psychiatry 64:679–688. Correa, H., Duval, F., et al. (2000) Prolactin response to D-fenfluramine and suicidal behavior in depressed patients. Psychiatry Res. 93(3):189–199. Corrigan M.H., Denahan, A.Q., et al. (2000) Comparison of pramipexole, fluoxetine, and placebo in patients with major depression. Depress. Anxiety 11:58–65. Cowen, P., Charig, E., et al. (1987) Platelet 5-HT receptor binding during depressive illness and tricyclic antidepressant treatment. J. Affect. Disord. 13:45–50. Crow, T., Cross, A., et al. (1984) Neurotransmitter receptors and monoamine metabolites in the brains of patients with Alzheimertype dementia and depression, and suicides. Neuropharmacology 23(12B):1561–1569. D’haenen, H.A., and Bossuyt, A. (1994) Dopamine D2 receptors in depression measured with single photon emission computed tomography. Biol. Psychiatry 35(2):128–132. Da Prada, M., Cesura, A.M., et al. (1988) Platelets as model for neurones. Experentia 44:115–126. Dahl, R.E., Birmaher, B., et al. (2000) Low growth hormone response to growth hormone-releasing hormone in child depression. Biol. Psychiatry 48(10):981–988. DeBellis, M.D., Gold, P.W., et al. (1993) Fluoxetine significantly reduces CSF CRH and AVP concentrations in patients with major depression. Am. J. Psychiatry 150:656–657. Delgado, P.L., Charney, D.S., et al. (1990) Neuroendocrine and behavioral effects of dietary tryptophan restriction in healthy subjects. Life Sci. 45:2323–2332.

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS Delgado, P.L., Miller, H.L., et al. (1999) Tryptophan-depletion challenge in depressed patients treated with desipramine or fluoxetine: implications for the role of serotonin in the mechanism of antidepressant action. Biol. Psychiatry 46(2):212–220. Delgado, P.L., Price, L.H., et al. (1994) Serotonin and the neurobiology of depression. Effects of tryptophan depletion in drug-free depressed patients. Arch. Gen. Psychiatry 51(11):865–874. De Paermentier, F., Cheetham, S.C., et al. (1990) Brain beta-adrenoceptor binding sites in antidepressant-free depressed suicide victims. Brain Res. 525(1):71–77. De Paermentier, F., Cheetham, S.C., et al. (1991) Brain beta-adrenoceptor binding sites in depressed suicide victims: effects of antidepressant treatment. Psychopharmacology 105(2):283–288. Devanand, D.P., Bowers, M.B., et al. (1985) Elevated plasma homovanillic acid in depressed females with melancholia and psychosis. Psychiatry Res. 15(1):1– 4. Drevets, W.C., Frank, E., et al. (1999) PET imaging of serotonin 1A receptor binding in depression. Biol. Psychiatry 46(10):1375–1387. Dulchin, M.C., Oquendo, M.A., et al. (2001) Prolactin response to dl-fenfluramine challenge before and after treatment with paroxetine. Neuropsychopharmacology 25:395– 401. Duman, R.S., and Nestler, E.J. (1995) Signal transduction pathways for catecholamine receptors. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 303–320. Dunlop, B.W., and Nemeroff, C.B. (2007) The role of dopamine in the pathophysiology of depression. Arch. Gen. Psychiatry 64:327–337. Ebert, D., Feistel, H., et al. (1996) Dopamine and depression – Striatal dopamine D2 receptor SPECT before and after antidepressant therapy. Psychopharmacology 126:91–94. Ellenbogen, M.A., Young, S.N., et al. (1996) Mood response to acute tryptophan depletion in healthy volunteers: sex differences and temporal stability. Neuropsychopharmacology 15(5):465– 474. Ellis, P.M., and Salmond, C. (1994) Is platelet imipramine binding reduced in depression? A meta-analysis. Biol. Psychiatry 36:292–299. Engstrom, G., Alling, C., et al. (1999) Reduced cerebrospinal HVA concentration and HVA/5-HIAA ratios in suicide attempters. Eur. Neuropsychopharmacol. 9:399– 405. Extein, I., Tallman, J., et al. (1979) Changes in lymphocyte beta-adrenergic receptors in depression and mania. Psychiatry Res. 1(2):191–197. Fawcett, J., and Busch, K.A. (1998) Stimulants in psychiatry. In: Schatzberg, A.F., and Nemeroff, C.B., eds. Textbook of Psychopharmacology, 2nd ed. Washington, DC: American Psychiatric Press, pp. 503–522. Frye, M.A., Dunn, R.T., et al. (1999) Lack of correlation between cerebrospinal fluid thyrotropin-releasing hormone (TRH) and TRH stimulated thyroid-stimulating hormone in patients with depression. Biol. Psychiatry 45(8):1049–1052. Fujita, M., Charney, D.S., et al. (2000) Imaging serotonergic neurotransmission in depression: hippocampal pathophysiology may mirror global brain alterations. Biol. Psychiatry 48(8):801–812. Garattini, S. (1997) Pharmacology of amineptine, an antidepressant agent acting on the dopaminergic system: a review. Int. Clin. Psychopharmacol. 12(Suppl 3):S15–S19. Garcia-Sevilla, J.A., Padro, D., et al. (1990) Alpha 2-adrenoceptormediated inhibition of platelet adenylate cyclase and induction of aggregation in major depression. Effect of long-term cyclic antidepressant drug treatment. Arch. Gen. Psychiatry 47(2):125–132. Garcia-Sevilla, J.A., Udina, C., et al. (1987) Enhanced binding of [3H]-adrenaline to platelets of depressed patients with melacholia: effect of long-term clomipramine treatment. Acta Psychiatr. Scand. 75(2):150–157. Gerner, R.H., and Yamada, T. (1982) Altered neuropeptide concentrations in cerebrospinal fluid of psychiatric patients. Brain Res. 238:298–302. Gibbons, R.D., and Davis, J.M. (1986) Consistent evidence for a biological subtype of depression characterized by low CSF monoamine levels. Acta Psychiatr. Scand. 74:8–12.

455

Glennon, R.A., and Dukat, M. (1995) Serotonin receptor subtypes. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 415– 429. Glowinski, J., and Axelrod, J. (1966) Effects of drugs on the disposition of H-3-norepinephrine in the rat brain. Pharmacol. Rev. 18(1): 775–785. Glowinski, J., Axelrod, J., et al. (1964) Physiological disposition of 3H-norepinephrine in the developing rat. J. Pharmacol. Exp. Ther. 146:48–53. Glowinski, J., and Iverson, L.L. (1966) Regional studies of catecholamines in the rat brain. J. Neurochem. 13:665–669. Glowinski, J., Snyder, S., et al. (1966) Subcellular localization of H3-norepinephrine in the rat brain and the effect of drugs. J. Pharmacol. Exp. Ther. 152(2):282–292. Gold, B.I., Bowers, M.B., et al. (1980) GABA levels in CSF of patients with psychiatric disorders. Am. J. Psychiatry 137:362– 364. Goldberg. J.F., Burdick, K.E., et al. (2004) Preliminary randomized, double-blind, placebo-controlled trial of pramipexole added to mood stabilizers for treatment-resistant bipolar depression. Am. J. Psychiatry 161:564–566. Gross-Isseroff, R., Israeli, M., et al. (1989) Autoradiographic analysis of tritiated imipramine binding in the human brain postmortem: effects of suicide. Arch. Gen. Psychiatry 46:237–241. Gurguis, G.N., Vo, S.P., et al. (1999) Platelet alpha2A-adrenoceptor function in major depression: Gi coupling, effects of imipramine and relationship to treatment outcome. Psychiatry Res. 89(2): 73–95. Guze, B.H., and Barrio, J.C. (1991) The etiology of depression in Parkinson’s disease patients. Psychosomatics 32:390–394. Halaris, A. (1978) 3-Methoxy-4-hydroxyphenyl-glycol in manic psychosis. Am. J. Psychiatry 135:493– 494. Hariri, A.R., Drabant, E.M., et al. (2005) A susceptibility gene for affective disorders and the response of the human amygdala. Arch. Gen. Psychiatry 62:146–152. Hartline, K.M., Owens, M.J., et al. (1996) Postmortem and cerebrospinal fluid studies of corticotropin-releasing factor in humans. Ann. N. Y. Acad. Sci. 780:96–105. Hasler, G., Bonwetsch, R., et al. (2007) 5-HT1A receptor binding in temporal lobe epilepsy patients with and without major depression. Biol. Psychiatry 62(11):1258–1264.. Hasler, G., Neumeister A., et al. (2005) Normal prefrontal gammaaminobutryric acid levels in remitted depressed subjects determined by proton magnetic resonance spectroscopy. Biol. Psychiatry 58:969–973. Hayward, G., Goodwin, G.M., et al. (2005) Low-dose tryptophan depletion in recovered depressed patients induces changes in cognitive processing without depressive symptoms. Biol. Psychiatry 57:517–552. Healy, D., Carney, P.A., et al. (1985) Peripheral adrenoceptors and serotonin receptors in depression. Changes associated with response to treatment with trazodone or amitriptyline. J. Affect. Disord. 9(3):285–296. Heils, A., Teufel, A., et al. (1996) Allelic variation of human serotonin transporter gene expression. J. Neurochem. 66:2621–2624. Hendry, S.H., Schwark, H.D., et al. (1987) Numbers and proportions of GABA-immunoreactive neurons in different areas of monkey cerebral cortex. J. Neurosci. 7:1503–1509. Heninger, G.R., Delgado, P.L., et al. (1992) Tryptophan-deficient diet and amino acid drink deplete plasma tryptophan and induce a relapse of depression in susceptible patients. J. Chem. Neuroanat. 5:347–348. Heninger, G.R., Delgado, P.L., et al. (1996) The revised monoamine theory of depression: a modulatory role for monoamines, based on new findings from monoamine depletion experiments in humans. Pharmacopsychiatry 29(1):2–11. Heuser, I., Bissette, G., et al. (1998) Cerebrospinal fluid concentrations of corticotropin-releasing hormone, vasopressin, and soma-

456

MOOD DISORDERS

tostatin in depressed patients and healthy controls: response to amitriptyline treatment. Depress. Anxiety 8(2):71–79. Hollister, L.E., David, K.L., et al. (1980) Subtypes of depression based on excretion of MHPG and response to nortriptyline. Arch. Gen. Psychiatry 37:1107–1110. Holsboer, F., Gerken, A., et al. (1987) Blunted aldosterone and ACTH release after human corticotropin-releasing factor administration in depressed patients. Am. J. Psychiatry 144:229–231. Hrdina, P.D., Bakish, M.D., et al. (1995) Serotonergic markers in platelets of patients with major depression: upregulation of 5HT2 receptors. J. Psychiatr. Neurosci. 20(1):11–19. Hrdina, P.D., Bakish, D., et al. (1997) Platelet serotonergic indices in major depression: up-regulation of 5-HT2A receptors unchanged by antidepressant treatment. Psychiatry Res. 66:73–85. Hrdina, P.D., Demeter, E., et al. (1993) 5-HT uptake sites and 5HT2 receptors in brain of antidepressant-free suicide victims/depressives: increase in 5-HT2 sites in cortex and amygdala. Brain Res. 614:37– 44. Hu, X., Zhu, G., et al. (2004) HTTLPR allele expression is codominant, correlating with gene effects on fMRI and SPECT imaging intermediate phenotypes, and behavior (abstract). Biol. Psychiatry 55 (Suppl 1):191S. Hucks, D., Lowther, S., et al. (1997) Corticotropin-releasing factor binding sites in cortex of depressed suicides. Psychopharmacology 134(2):174 –178. Jacobs, D., and Silverstone, T. (1988) Dextroamphetamine arousal in human subjects as a model for mania. Psychol. Med. 16:323–329. Joffe, R.T. (1999) Peripheral thyroid hormone levels in treatment resistant depression. Biol. Psychiatry 45(8):1053–1055. Joffe, R.T., and Marriott, M. (2000) Thyroid hormone levels and recurrence of major depression. Am. J. Psychiatry 157:1689–1691. Kapitany, T., Schindl, M., et al. (1999) The citalopram challenge test in patients with major depression and in healthy controls. Psychiatry Res. 88(2):75–88. Kapur, S., and Mann, J.J. (1992) Role of the dopaminergic system in depression. Biol. Psychiatry 32:1–17. Kastin, A.J., Ehrensing, R.H., et al. (1972) Improvement in mental depression with decreased thyrotropin response after administration of thyrotropin-releasing hormone. Lancet 2(780):740–742. Kavoussi, R.J., Hauger, R.L., et al. (1999) Prolactin response to dfenfluramine in major depression before and after treatment with serotonin reuptake inhibitors. Biol. Psychiatry 45(3):295–299. Kavoussi, R.J., Kramer, J., et al. (1998) Prolactin response to Dfenfluramine in outpatients with major depression. Psychiatry Res. 79(3):199–205. Kaye, W.H., Gwirtsman, H.E., et al. (1987) Elevated cerebrospinal fluid levels of immunoreactive corticotropin-releasing hormone in anorexia nervosa: relation to state of nutrition, adrenal function, and intensity of depression. J. Clin. Endocrinol. Metab. 64(2): 203–208. Kelly, C.B., and Cooper, S.J. (1998) Plasma norepinephrine response to a cold pressor test in subtypes of depressive illness. Psychiatry Res. 81(1):39–50. Kendler, K.S., Kuhn, J.W., et al. (2005) The interaction of stressful life events and a serotonin transporter polymorphism in the prediction of episodes of major depression. Arch. Gen. Psychiatry 62:529–535. Kirkegaard, C., Faber, J., et al. (1979) Increased levels of TRH in cerebrospinal fluid from patients with endogenous depression. Psychoneuroendocrinology 4:227–235. Klimek, V., Rajkowska, G., et al. (1999) Brain noradrenergic receptors in major depression and schizophrenia. Neuropsychopharmacology 21:69–81. Klimek, V., Schenck, J.E., et al. (2002) Dopaminergic abnormalities in amygdaloid nucleus in major depression: a postmortem study. Biol. Psychiatry 52:740–748.

Klimke, A., Larisch, R., et al. (1999) Dopamine D2 receptor binding before and after treatment of major depression measured by [123I]IZBM SPECT. Psychiatry Res. 90:91–101. Konig, F., Hauger, B., et al. (2000) Effect of paroxetine on thyroid hormone levels in severely depressed patients. Neuropsychobiology 42(3):135–138. Kraus, R.P., Phoenix, E., et al. (1997) Exaggerated TSH responses to TRH in depressed patients with normal baseline. J. Clin. Psychiatry 58(6):266–270. Lambert, G., Johansson, M., et al. (2000) Reduced brain norepinephrine and dopamine release in treatment-refractory depressive illness: evidence in support of the catecholamine hypothesis of mood disorders. Arch. Gen. Psychiatry 57(8):787–793. Lawrence, K.M., DePaermentier, F., et al. (1990) Brain 5-HT uptake sites, labelled with [3H]paroxetine, in antidepressant-free depressed suicides. Brain Res. 526:17–22. Leake, A., Fairbairn, A.F., et al. (1991) Studies on the serotonin uptake binding site in major depressive disorder and control postmortem brain: neurochemical and clinical correlates. Psychiatry Res. 39:155–165. Lemonde, S., Turecki, G., et al. (2003) Impaired repression at a 5hydroxytryptamine 1A receptor gene polymorphism associated with major depression and suicide. J. Neurosci. 23:8788–8799. Lesch, K.P., Wolozin, B.L., et al. (1993) Primary structure of the human platelet serotonin uptake site: identity with the brain serotonin transporter. J. Neurochem. 60:2319–2322. Leyton, M., Young, S.N., et al. (1997) The effect of tryptophan depletion on mood in medication-free, former patients with major affective disorder. Neuropsychopharmacology 16(4):294 –297. Lifschytz, T., Segman, R., et al. (2006) Basic mechanisms of augmentation of antidepressant effects with thyroid hormone. Curr. Drug Targets 7:203–210. Linnoila, M., and Virkkunen, M. (1992) Aggression, suicidality and serotonin. J. Clin. Psychiatry 53(Suppl):46–51. Little, K.Y. (1988) Amphetamine, but not methylphenidate, predicts antidepressant response. J. Clin. Psychopharmacol. 8:177–183. Lowther, S., De Paermentier, F., et al. (1994) Brain 5-HT2 receptors in suicide victims: violence of death, depression and effects of antidepressant treatment. Brain Res. 642:281–289. Lowther, S., De Paermentier, F., et al. (1997) 5-HT1A receptor binding sites in post-mortem brain samples from depressed suicides and controls. J. Affect. Disord. 42(2–3):199–207. Maas, J.W., Fawcett, J.A., et al. (1972) Catecholamine metabolism, depressive illness and drug response. Arch. Gen. Psychiatry 26: 252–262. Maas, J.W., Koslow, S.H., et al. (1984) Pretreatment neurotransmitter metabolite levels and response to tricyclic antidepressant drugs. Am. J. Psychiatry 141(10):1159–1171. Maes, M., De Ruyter, M., et al. (1987) The renal excretion of xanthurenic acid following L-tryptophan loading in depressed patients. Hum. Psychopharmacol. 2:231–235. Maes, M., Jacobs, M.-P., et al. (1990) Suppressant effects of dexamethasone on the availability of plasma L-tryptophan and tyrosine in healthy controls and depressed patients. Acta Psychiatr. Scand. 81:19–23. Maes, M., and Meltzer, H.Y. (1995) The serotonin hypothesis of major depression. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 933–944. Maes, M., Van Gastel, A., et al. (1999) Decreased platelet alpha-2 adrenoceptor density in major depression: effects of tricyclic antidepressants and fluoxetine. Biol. Psychiatry 45(3):278–284. Maj, M., Ariano, M.G., et al. (1984) Plasma cortisol, catecholamine and cyclic AMP levels, response to dexamethasone suppression test and platelet MAO activity in manic-depressive patients. A longitudinal study. Neuropsychobiology 11(3):168–173.

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS Malison, R.T., Price, L.H., et al. (1998) Reduced brain serotonin transporter availability in major depression as measured by [123I]-2beta-carbomethoxy-3 beta-(4-iodophenyl)tropane and single photon emission computed tomography. Biol. Psychiatry 44(11): 1090–1098. Malone, K.M., Thase, M.E., et al. (1993) Fenfluramine challenge test as predictor of outcome in major depression. Psychopharmacol. Bull. 29(2):155–161. Mann, J., McBride, P., et al. (1992) Relationship between central and peripheral serotonin indexes in depressed and suicidal psychiatric inpatients. Arch. Gen. Psychiatry 49:442– 446. Mann, J., Stanley, M., et al. (1986) Increased serotonin2 and badrenergic receptor binding in the frontal cortices of suicide victims. Arch. Gen. Psychiatry 43:954–959. Mann, J.J., Huang, Y., et al. (2000) A serotonin transporter gene promoter polymorphism (5-HTTLPR) and prefrontal cortical binding in major depression and suicide. Arch. Gen. Psychiatry 57: 729–738. Mann, J.J., and Malone, K.M. (1997) Cerebrospinal fluid amines and higher-lethality suicide attempts in depressed inpatients. Biol. Psychiatry 41:162–171. Mann, J.J., Malone, K.M., et al. (1996) Demonstration in vivo of reduced serotonin responsivity in the brain of untreated depressed patients. Am. J. Psychiatry 153(2):174 –182. Marangell, L.B., George, M.S., et al. (1997) Effects of intrathecal thyrotropin-releasing hormone (protirelin) in refractory depressed patients. Arch. Gen. Psychiatry 54(3):214–222. Marazziti, D., Baroni, S., et al. (2001) Correlation between platelet alpha (2)-adrenoceptors and symptom severity in major depression. Neuropsychobiology 44(3):122–125. Marinelli, M., and Piazza, P.V. (2002) Interaction between glucocorticoid hormones, stress and psychostimulant drugs. Eur. J. Neurosci. 16:387–394. Martinot, M., Bragulat, V., et al. (2001) Decreased presynaptic dopaminergic function in the left caudate of depressed patients with affective flattening and psychomotor retardation. Am. J. Psychiatry 158(2):314–316. Massou, J.M., Trichard, C., et al. (1997) Frontal 5-HT2A receptors studied in depressive patients during chronic treatment by selective serotonin reuptake inhibitors. Psychopharmacology 133(1): 99–101. Matsubara, S., Arora, R.C., et al. (1991) Serotonergic measures in suicide brain: 5-HT1A binding sites in frontal cortex of suicide victims. J. Neural Transm. 85:181–194. McBride, P.A., Brown, R., et al. (1994) The relationship of platelet 5-HT2 receptor indices to major depressive disorder, personality traits, and suicidal behavior. Biol. Psychiatry 35:295–308. McBride, P.A., Mann, J.J., et al. (1983) Characterization of serotonin binding sites on human platelets. Life Sci. 33:2033–2041. McKeith, I., Marshall, E., et al. (1987) 5-HT receptor binding in post-mortem brain from patients with affective disorder. J. Affect. Disord. 13:67–74. McPherson, H., Walsh, A., et al. (2003) Growth hormone and prolactin response to apomorphine in bipolar and unipolar depression. J. Affect. Disord. 76:121–125. Meana, J.J., Barturen, F., et al. (1992) Alpha 2-adrenoceptors in the brain of suicide victims: increased receptor density associated with major depression. Biol. Psychiatry 31(5):471– 490. Meltzer, C.C., Price, J.C., et al. (1999) PET imaging of serotonin type 2 receptors in late-life neuropsychiatric disorders. Am. J. Psychiatry 156(12):1871–1878. Meltzer, H.Y., and Lowy, M.T. (1987) The serotonin hypothesis of depression. In: Meltzer, H.Y., ed. Psychopharmacology: The Third Generation of Progress. New York: Raven Press, pp. 513–526. Merali, Z., Du, L., et al. (2004) Dysregulation in the suicide brain: mRNA expression of corticotropin-releasing hormone receptors

457

and GABA(A) receptor subunits in frontal cortical brain region. J. Neurosci. 24:1478–1485. Merali, Z., Kent, P., et al. (2006) Corticotropin-releasing hormone, arginine vasopressin, gastrin-releasing peptide, and neuromedin B alterations in stress-relevant brain regions of suicides and control subjects. Biol. Psychiatry 59:594 – 602. Meyer, J.H, Ginovart, N., et al. (2006) Elevated monoamine oxidase A levels in the brain. Arch. Gen. Psychiatry 63:1209–1216. Meyer, J.H., Houle, S., et al. (2004) Brain serotonin transporter binding potential measured with carbon 11-labeled DASB positron emission tomography. Arch. Gen. Psychiatry 61:1271–1279. Meyer, J.H., Kapur, S., et al. (1999) Prefrontal cortex 5-HT2 receptors in depression: an [18F]setoperone PET imaging study. Am. J. Psychiatry 156(7):1029–1034. Meyer, J.H., Kruger, S., et al. (2001) Lower dopamine transporter binding potential in striatum during depression. Neuroreport 12: 4121– 4125. Miller, H.L., Delgado, P.L., et al. (1996a) Clinical and biochemical effects of catecholamine depletion on antidepressant-induced remission of depression. Arch. Gen. Psychiatry 53(2):117–128. Miller, H.L., Delgado, P.L., et al. (1996b) Effects of alpha-methylparatyrosine (AMPT) in drug-free depressed patients. Neuropsychopharmacology 14(3):151–157. Mintun, M.A., Sheline, Y.I., et al. (2004) Decreased hippocampal 5HT2A receptor binding in major depressive disorder: in vivo measurement with [18F]altanserin positron emission tomography. Biol. Psychiatry 55:217–224. Mitchell, P.B., Bearn, J.A., et al. (1988) Growth hormone response to clonidine after recovery in patients with endogenous depression. Br. J. Psychiatry 152:34–38. Mitchell, P.B., and Smythe, G. (1990) Hormonal responses to fenfluramine in depressed and control subjects. J. Affect. Disord. 19(1): 43–51. Moreau, X., Azorin, J.M., et al. (2000) Red blood cell triiodothyronine uptake in unipolar major depression: effect of a chronic antidepressant treatment. Prog. Neuro-Psychopharm. Biol. Psychiatry 24(1):23–35. Moses, S.G., and Robins, E. (1975) Regional distribution of norepinephrine and dopamine in brains of depressive suicides and alcoholic suicides. Psychopharmacol. Commun. 1:327–337. Murphy, D.L. (1972) L-DOPA, behavioral activation and psychopathology. Res. Publ. Ass. Res. Nerv. Ment. Dis. 50:430–437. Murray, J.B. (1996) Depression in Parkinson’s disease. J. Psychol. 130(6):659–667. Musselman, D.L., Tomer, A., et al. (1996) Exaggerated platelet reactivity in major depression. Am. J. Psychiatry 153(10):1313–1317. Nemeroff, C.B. (1996) The corticotropin-releasing factor (CRF) hypothesis of depression: new findings and new directions. Mol. Psychiatry 1(4):336–342. Nemeroff, C.B., Bissette, G., et al. (1991) Neuropeptide concentrations in cerebrospinal fluid of depressed patients treated with electroconvulsive therapy: corticotropin-releasing factor, B-endorphin and somatostatin. Br. J. Psychiatry 158:59–63. Nemeroff, C.B., Owens, M.J., et al. (1988) Reduced corticotropin releasing factor binding sites in the frontal cortex of suicide victims. Arch. Gen. Psychiatry 45(6):577–579. Neumeister, A., Hu, X.Z., et al. (2006) Differential effects of 5HTTLPR genotypes on the behavioral and neural responses to tryptophan depletion in patients with major depression and controls. Arch. Gen. Psychiatry 63:978–986. Neumeister, A., Nugent, A.C., et al. (2004) Neural and behavioral responses to tryptophan depletion in unmedicated patients with remitted major depressive disorder and controls. Arch. Gen. Psychiatry 61:765–773. Neumeister, A., Yuan, P., et al. (2005) Effects of tryptophan depletion on serum levels of brain-derived neurotrophic factor in un-

458

MOOD DISORDERS

medicated patients with remitted depression and healthy subjects. Am. J. Psychiatry 162:805–807. O’Keane, V., and Dinan, T.G. (1991) Prolactin and cortisol responses to d-fenfluramine in major depression: evidence of diminished responsivity of central serotonergic function. Am. J. Psychiatry 148(8): 1009–1015. Ohmori, T., Arora, R.C., et al. (1992) Serotonergic measures in suicide brain: the concentration of 5-HIAA, HVA and tryptophan in frontal cortex of suicide victims. Biol. Psychiatry 32:57–71. Ordway, G. (2000) Searching for the chicken’s egg in transporter gene polymorphisms. Arch. Gen. Psychiatry 57(8):739–740. Ordway, G., Schenk, J., et al., (2003) Elevated agonist binding to a2-adrenoreceptors in the locus ceruleus in major depression. Biol. Psychiatry 53:315–323. Ordway, G.A., Gambarana, C., et al. (1991) Preferential reduction of binding of 125I-iodopindolol to beta-1 adrenoceptors in the amygdala of rat after antidepressant treatments. J. Pharmacol. Exp. Ther. 257:681–690 Owen, F., Chambers, D., et al. (1986) Serotonergic mechanisms in brains of suicide victims. Brain Res. 362:185–188. Owen, F., Cross, A.J., et al. (1983) Brain 5-HT2 receptors and suicide. Lancet 2(8361):1256. Owens, M.J. (1997) Molecular and cellular mechanisms of antidepressant drugs. Depress. Anxiety 4:153–159. Owens, M.J., Morgan, W.N., et al. (1997a) Neurotransmitter receptor binding profile of antidepressants. J. Pharm. Exp. Ther. 283(3): 1305–1322. Owens, M.J., Morgan, W.N., et al. (1997b) Receptor binding profile of monoamine transporter antagonist antidepressants and their metabolites. J. Pharm. Exp. Ther. 283(3):1305–1322. Owens, M.J., and Nemeroff, C.B. (1994) Role of serotonin in the pathophysiology of depression: focus on the serotonin transporter. Clin. Chem. 40:288–295. Owens, M.J., and Nemeroff, C.B. (1997) The serotonin transporter and depression. Depress. Anxiety 8(Suppl 1):5–12. Pandey, G.N., Pandey, S.C., et al. (1990) Platelet serotonin-2 receptor binding sites in depression and suicide. Biol. Psychiatry 28: 215–222. Pandey, G.N., Pandey, S.C., et al. (1995) Platelet serotonin-2A receptors: a potential biological marker for suicidal behavior. Am. J. Psychiatry 152(6):850–855. Parsey, R.V., Hastings, R.S., et al. (2006) Lower serotonin transporter binding potential in the human brain during major depressive episodes. Am. J. Psychiatry 163:52–58. Parsey, R.V., Oquendo, M.A., et al. (2001) Dopamine D2 receptor availability and amephetamine-induced dopamine release in unipolar depression. Biol. Psychiatry 50:313-322. Parsey, R.V., Oquendo, M.A., et al. (2006) Altered serotonin 1A binding in major depression: a [carbonyl-C-11]WAY100635 positron emission tomography study. Biol. Psychiatry 59:106-113. Perry, E.K., Marshall, E.F., et al. (1983) Decreased imipramine binding in the brains of patients with depressive illness. Br. J. Psychiatry 142:188–192. Petty, F. (1994) Plasma concentrations of GABA and mood disorders: a blood test for manic depressive disease? Clin. Chem. 40:296–302. Pezawas, L., Meyer-Lindenberg, A., et al. (2005) 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nat. Neurosci. 8: 828–834. Piletz, J.E., Halaris, A.S., et al. (1990) Elevated -3H-para-aminoclonidine binding to platelet purified plasma membranes from depressed patients. Neuropsychopharmacology 3(3):201-210. Pitchot, W., Hansenne, M., et al. (1995) Growth hormone response to apomorphine in panic disorder: comparison to major depression and normal controls. Eur. Arch. Psych. Clin. Neurosci. 245(6): 306–308.

Pitchot, W., Hansenne, M., et al. (2001a) Alpha-2-adrenoceptors in depressed suicide attempters: relationship to medical lethality of the attempt. Neuropsychobiology 44(2):91–94. Pitchot, W., Hansenne, M., et al. (2001b) Reduced dopamine function in depressed patients is related to suicidal behavior but not its lethality. Psychoneuroendocrinology 26(7):689–696. Plotsky, P.M., Owens, M.J., et al. (1995) Neuropeptide alterations in mood disorders. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 971–981. Porter, R.J., Lunn, B.S., et al. (2000) Cognitive deficit induced by acute tryptophan depletion in patients with Alzheimer’s disease. Am. J. Psychiatry 157(4):638–640. Posener, J.A., Schatzberg, A.F., et al. (1999) Hypothalamic-pituitaryadrenal axis effects on plasma homovanillic acid in man. Biol. Psychiatry 45(2):222–228. Post, R.M., Gerner, R.H., et al. (1978) Effects of a dopamine agonist piribedil in depressed patients. Arch. Gen. Psychiatry 35: 609–615. Potter, W.Z., Karoum, F., et al. (1984) Common mechanisms of action of biochemically specific antidepressants. Prog. Neuropsychopharmacol. Biol. Psychiatry 8:153–161. Prange, A.J. (1964) The pharmacology and biochemistry of depression. Dis. Central Nerv. Syst. 25:217–221. Prange, A.J., Lara, P.P., et al. (1972) Effects of thyrotropin-releasing hormone in depression. Lancet 2(785):999–1002. Price, L.H., Charney, D.S., et al. (1991) Serotonin function and depression: neuroendocrine and mood responses to intravenous Ltryptophan in depressed patients and healthy comparison subjects. Am. J. Psychiatry 148(11):1518–1525. Price, L.H., Malison, R.T., et al. (1997) Neurobiology of tryptophan depletion in depression: effects of m-chlorophenypiperazine (mCPP). Neuropsychopharmacology 17(5):342–350. Raadsheer, F.C., van Heerikhuize, J.J., et al. (1995) Corticotropinreleasing hormone mRNA levels in paraventricular nucleus of patients with Alzheimer’s disease and depression. Am. J. Psychiatry 152(9):1372–1379. Rausch, J.L., Johnson, M.E., et al. (2005) Serotonin transport kinetics correlated between human platelets and brain synaptosomes. Psychopharmacology 180:391–398. Redmond, D.E., Kratz, M.M., et al. (1986) Cerebrospinal fluid amine metabolites. Relationships with behavioral measurements in depressed, manic and healthy control subjects. Arch. Gen. Psychiatry 43(10):938–947. Rothschild, A.J., Langlais, P.J., et al. (1984) Dexamethasone increases plasma free dopamine in man. J. Psychiatr. Res. 18(3):217–223. Roy, A., DeJong, J., et al. (1989) Cerebrospinal fluid monoamine metabolites and suicidal behavior in depressed patients. A 5-year follow-up study. Arch. Gen. Psychiatry 46(7):609–612. Roy, A., Karoum, F., et al. (1992) Marked reduction in indexes of dopamine transmission among patients with depression who attempted suicide. Arch. Gen. Psychiatry 49:447– 450. Roy, A., Pickar, D., et al. (1986) Urinary monoamines and monoamine metabolites in subtypes of unipolar depressive disorder and normal controls. Psychol. Med. 16(3):541–546. Roy, A., Wolkowitz, O.M., et al. (1994) Differences in CSF concentrations of thyrotropin-releasing hormone in depressed patients and normal subjects: negative findings. Am. J. Psychiatry 151(4): 600–602. Rubinow, D.R. (1986) Cerebrospinal fluid somatostatin and psychiatric illness. Biol. Psychiatry 21:341–365. Rubinow, D.R., Gold, P.W., et al. (1983) CSF somatostatin in affective illness. Arch. Gen. Psychiatry 40:409– 412. Sagud, M., Pivac, N., et al. (2002) Effects of sertraline treatment on plasma cortisol, prolactin and thyroid hormones in female depressed patients. Neuropsychobiology 45:139–143.

30: NEUROCHEMISTRY OF DEPRESSIVE DISORDERS Salomon, R.M., Miller, H.L., et al. (1997) Lack of behavioral effects of monoamine depletion in healthy subjects. Biol. Psychiatry 41(1): 58–64. Sanacora, G., Mason, G.F., et al (2003) Increased cortical GABA concentrations in depressed patients receiving ECT. Am. J. Psychiatry 160:577–579. Sanacora, G., Mason, G.F., et al. (2002) Increased occipital cortex GABA concentrations in depressed patients after therapy with selective serotonin reuptake inhibitors. Am. J. Psychiatry 159:663–665. Sargent, P.A., Kjaer, K.H., et al. (2000) Brain serotonin 1A receptor binding measured by positron emission tomography with [11C]WAY100635: effects of depression and antidepressant treatment. Arch. Gen. Psychiatry 57(2):174–180. Saxena, P.R. (1995) Serotonin receptors: subtypes, functional responses, and therapeutic relevance. Pharmacol. Ther. 66:339–368. Schatzberg, A.F. (1998) Noradrenergic versus serotonergic antidepressants: Predictors of treatment response. J. Clin Psychiatry 59 (Suppl 14):15–18. Schatzberg, A.F., Orsulak, P.J., et al. (1982) Toward a biochemical classification of depressive disorders, V: heterogeneity of unipolar depressions. Am. J. Psychiatry 139(4):471– 475. Schatzberg, A.F., Rosenbaum, A.H., et al. (1981) Toward a biochemical classification of depressive disorders, III: pretreatment urinary MHPG levels as predictors of response to treatment with maprotiline. Psychopharmacology 75:34 –38. Schatzberg, A.F., and Rothschild, A.J. (1992) Psychotic (delusional) major depression: should it be included as a distinct syndrome in DSM-IV? Am. J. Psychiatry 149:733–745. Schatzberg, A.F., Rothschild, A.J., et al. (1985) A corticosteroid/dopamine hypothesis for psychotic depression and related states. J. Psychiatr. Res. 19(1):57–64. Schatzberg, A.F., Samson, J.A., et al. (1989) Toward a biochemical classification of depressive disorders, X: urinary catecholamines, their metabolites, and D-type scores in subgroups of depressive disorders. Arch. Gen. Psychiatry 46(3):260–268. Schatzberg, A.F., and Schildkraut, J.J. (1995) Recent studies on norepinephrine systems in mood disorders. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 911–920. Schildkraut, J.J. (1965) The catecholamine hypothesis of affective disorders: a review of supporting evidence. Am. J. Psychiatry 122: 509–522. Schildkraut, J.J. (1973) Norepinephrine metabolites as biochemical criteria for classifying depressive disorders and predicting response to treatment. Preliminary findings. Am. J. Psychiatry 130:695– 699. Schildkraut, J.J., Orsulak, P.J., et al. (1978) Toward a biochemical classification of depressive disorders, I: differences in urinary excretion of MHPG and other catecholamine metabolites in clinically defined subtypes of depression. Arch. Gen. Psychiatry 35(12): 1427–1433. Schneier, F.R.,, Liebowitz, M.R., et al. (2000) Low dopamine D(2) receptor binding potential in social phobia. Am. J. Psychiatry 157:457– 459. Shah, P.J., Ogilvie, A.D., et al. (1997) Clinical and psychometric correlates of dopamine D2 binding in depression. Psychol. Med. 27(6):1247–1256. Shapira, B., Cohen, J., et al. (1993) Prolactin response to fenfluramine and placebo challenge following maintenance pharmacotherapy withdrawal in remitted depressed patients. Biol. Psychiatry 33(7):531–535. Sheline, Y., Bargett, M., et al. (1995) Platelet serotonin markers and depressive symptomatology. Biol. Psychiatry 37:442– 447. Shelton, R.C., Winn, S., et al. (1993) The effects of antidepressants on the thyroid axis in depression. Biol. Psychiatry 33:120–126. Siever, L.J., Murphy, D.L., et al. (1984) Plasma prolactin changes following fenfluramine in depressed patients compared to con-

459

trols: an evaluation of central serotonergic responsivity in depression. Life Sci. 34(11):1029–1039. Siever, L.J., Trestmen, R.L., et al. (1992) The growth hormone response to clonidine in acute and remitted depressed male patients. Neuropsychopharmacology 6(3):165–177. Siever, L.J., Uhde, T.W., et al. (1982) Growth hormone response to clonidine as a probe of noradrenergic receptor responsiveness in affective disorder patients and controls. Psychiatry Res. 7(2): 139–144. Siever, L.J., Uhde, T.W., et al. (1984) Differential inhibitory noradrenergic responses to clonidine in 25 depressed patients and 25 normal control subjects. Am. J. Psychiatry 141(6):733–741. Smith, K.A., Fairburn, C.G., et al. (1997) Relapse of depression after rapid depletion of tryptophan. Lancet 349:915–919. Smith, K.A., Morris, J.S., et al. (1999) Brain mechanisms associated with depressive relapse and associated cognitive impairment following acute tryptophan depletion. Br. J. Psychiatry 174:525–529. Spillmann, M.K., Van der Does, A.J., et al. (2001) Tryptophan depletion in SSRI-recovered depressed outpatients. Psychopharmacologia 155(2):123–127. Stahl, S. (1977) The human platelet. Arch. Gen. Psychiatry 34: 509–516. Stanley, M., and Mann, J.J. (1983) Increased serotonin-2 binding sites in frontal cortex of suicide victims. Lancet 1:214–216. Sullivan, G.M., Hatterer, J.A., et al. (1999) Low levels of transthyretin in CSF of depressed patients. Am. J. Psychiatry 156(5):710–715. Sullivan, M., Mann, J.J., et al. (2006) Low cerebral spinal fluid transthyretin levels in depression: correlations with suicidal ideation and low serotonin function. Biol. Psychiatry 60:500–506. Swann, A.C., Koslow, S.H., et al. (1987) Lithium carbonate treatment of mania. Arch. Gen. Psychiatry 44(4):345–354. Tandberg, E., Larsen J.P., et al. (1996) The occurrence of depression in Parkinson’s disease. Arch. Neurol. 53:175–179. Tepper, J.M., Koos, T., et al. (2004) GABAergic microcircuits in the neostriatum. Trends Neurosci. 11:662–669. Thakore, J.H., O’Keane, V., et al. (1996) d-Fenfluramine-induced prolactin responses in mania: evidence for serotonergic subsensitivity. Am. J. Psychiatry 153(11):1460–1463. Traskman, L., Asberg, M., et al. (1981) Monoamine metabolites in CSF and suicidal behavior. Arch. Gen. Psychiatry 38(6):631–636. Tremblay, L.K., Naranjo, C.A., et al. (2002) Probing brain reward system function in major depressive disorder: altered response to dextroamphetamine. Arch. Gen. Psychiatry 59:409– 416. Tremblay, L.K., Naranjo, C.A., et al. (2005) Functional neuroanatomical substrates of altered reward processing in major depressive disorder revealed by a dopaminergic probe. Arch. Gen. Psychiatry 62:1228–1236. Van Praag, H.M. (1982) Depression, suicide, and the metabolites of serotonin in the brain. J. Affect. Disord. 4:21–29. Van Praag, H.M., Korf, J., et al. (1975) Dopamine metabolism in depressions, psychoses and Parkinson’s disease: the problem of the specificity of biological variables in behavior disorders. Psychol. Med. 5:138–146. Van Scheyen, J.D., Van Praag, H.M., et al. (1977) Controlled study comparing nomifensine and clomipramine in unipolar depression, using the probenecid technique. Br. J. Clin. Pharmacol. 4:179S –184S. Virkkunen, M., Eggert, M., et al. (1996) A prospective follow-up study of violent offenders and fire setters. Arch. Gen. Psychiatry 53(6):523–529. Virkkunen, M., Goldman, D., et al. (1995) Low brain serotonin turnover rate (low CSF 5-HIAA) and impulsive violence. J. Psychiatry Neurosci. 20(4):271–275. Virkkunen, M., Rawlings, R., et al. (1994) CSF biochemistries, glucose metabolism, and diurnal activity rhythms in alcoholic, violent offenders, fire setters, and healthy volunteers. Arch. Gen. Psychiatry 51(1):20–27.

460

MOOD DISORDERS

Von Bardeleben, U., and Holsboer, F. (1989) Cortisol response to a combined dexamethasone-human corticotropin-releasing hormone (CRH) challenge in patients with major depression. J. Neuroendocrinol. 1:485– 488. Whale, R., Clifford, E.M., et al. (2001) Decreased sensitivity of 5HT1D receptors in melancholic depression. Br. J. Psychiatry 178: 454 – 457. Williams, R.B., Marchuk, D.A., et al. (2003) Serotonin-related gene polymorphisms and central nervous system function. Neuropsychopharmacology 28:533–541. Willner, P. (1983) Dopamine and depression: a review of recent evidence. Brain Res. Rev. 6:211–246. Wirz-Justice, A. (1988) Platelet research in psychiatry. Experientia 44:145–152. Wolfe, N., Katz, D.I., et al. (1990) Neuropsychological profile linked to low dopamine: in Alzheimer’s disease, major depression, and Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 53(10): 915–917. Wong, M.L., Kling, M.A., et al. (2000) Pronounced and sustained central hypernoradrenergic function in major depression with melacholic features: relation to hypercortisolism and corticotropinreleasing hormone. Proc. Natl. Acad. Sci. USA 97(1):325–330. Yatham, L.N., Liddle, P.F., et al. (1999) Decrease in brain serotonin 2 receptor binding in patients with major depression following desipramine treatment. Arch. Gen. Psychiatry 56:705–711. Yatham, L.N., Liddle, P.F., et al. (2000) Brain serotonin2 receptors in major depression: a positron emission tomography study. Arch. Gen. Psychiatry 57(9):850–858.

Yatham, L.N., Zis, A.P., et al. (1997) Sumatriptan-induced growth hormone release in patients with major depression, mania, and normal controls. Neuropsychopharmacology 17(4):258–263. Yehuda, R., Siever, L.J., et al. (1998) Plasma norepinephrine and 3methoxy-4-hydroxylglycol concentrations and severity of depression in combat posttraumatic stress disorder and major depressive disorder. Biol. Psychiatry 44(1):56–63. Young, E.A., Watson, S.J., et al. (1990) Beta-lipotropin-beta-endorphin response to low-dose ovine corticotropin releasing factor in endogenous depression. Arch. Gen. Psychiatry 47(5):449– 457. Young, S.N., Smith, S.E., et al. (1985) Tryptophan depletion causes a rapid lowering of mood in normal males. Psychopharmacology 87:173–177. Zalsman, G., Yung-yu, H., et al. (2006) Association of a triallelic serotonin transporter gene promoter region (5-HTTLPR) polymorphism with stressful life events and severity of depression. Am. J. Psychiatry 163:1588–1593. Zammit, S., and Owen M.J. (2006) Stressful life events, 5-HTT genotype and risk of depression. Br. J. Psychiatry 188:199–201. Zarate, C.A., Payne, J.L., et al. (2004) Pramipexole for bipolar II depression: a placebo-controlled proof of concept study. Biol. Psychiatry 56:54–60. Zobel, A.W., Nickel, T., et al. (2001) Effects of high-affinity corticotropin-releasing hormone receptor 1 antagonist R121919 in major depression: the first 20 patients. J. Psychiatric Res. 34(3): 171–181.

31 Neuroimaging Studies of Mood Disorders WAYNE C. DREVETS, KISHORE M. GADDE, A N D

K. RANGA R. KRISHNAN

The application of neuroimaging technology in clinical neuroscience research holds the potential to transport psychiatry into an era in which pathophysiology, rather than signs and symptoms, guides the nosology of psychiatric disorders. The past two decades of imaging technology development have produced a variety of techniques that make possible noninvasive examination of brain structure, function, and chemistry. These tools are being applied to elucidate the anatomical correlates of normal and pathological emotional states and the physiological correlates of antidepressant and mood stabilizing treatments in humans. The results of such studies are guiding the clinical neuroscience field toward models of depression in which functional and structural factors play roles in the pathogenesis of mood disorders. STRUCTURAL NEUROIMAGING STUDIES OF MOOD DISORDERS Structural imaging technologies for evaluating morphology and elements of tissue composition in vivo became available in the late 1970s with the advent of computed tomography (CT), and shortly thereafter, magnetic resonance imaging (MRI). These techniques revolutionized clinical diagnostic evaluation by affording the ability to visualize gross neuropathology in vivo. They also enabled noninvasive investigation of brain structure without the limitations of postmortem studies, such as the requirement for excised brain tissue and the uncertain adjustment for the variable changes in brain volume occurring with tissue fixation. In the evaluation of mood disorders, structural imaging technology is used clinically to facilitate differential diagnosis in cases where depressive or manic syndromes are suspected of arising secondary to lesions or degenerative processes. However, structural imaging has played more direct and pivotal roles in quantitative neuromorphological and neuromorphometric studies of depression (assessment of the appearance and volume of brain

structure, respectively), where such research has demonstrated the existence of white matter pathology and abnormalities of brain structure volume in some mood disorder subtypes. This chapter reviews these findings in mood-disordered samples and discusses their specificity with respect to diagnostic subtype and other neuropsychiatric conditions. Technical Issues Relevant to the Interpretation of Structural Brain Images The sensitivity of structural imaging assessments depends upon a variety of technical factors related to the imaging modality, the spatial resolution of the images, and the tissue contrast resolution (that is, discrimination between lesions, grey matter, white matter, and cerebrospinal fluid [CSF]). Although CT and MRI permit detection of neuromorphological abnormalities and assessment of cerebral volumes, MRI is superior for these purposes in psychiatric research. Relative to CT, MRI provides greater spatial resolution (0.5 mm for newer scanners) and higher contrast resolution for delimiting neuroanatomical structures and depicting white matter pathology. Magnetic resonance imaging also allows greater flexibility of acquisition parameters for varying tissue contrast and image plane orientation. In contrast, CT images have low-contrast resolution between gray and white matter, are susceptible to artifacts near bony surfaces (obscuring visualization of the brain stem, basotemporal cortex, and posterior fossa), and are limited to acquisition in the axial orientation. Finally, though CT involves exposure to ionizing radiation, there are no known biological risks associated with the magnetic field strengths currently employed for MRI studies (unless metallic objects or pacemaker devices are present inside the body). Neuromorphometric assessments generally are performed by segmenting MRI images using manual or semiautomated techniques. The reliability of such measures has progressively increased with improvements in MR signal homogeneity and reductions in image-slice thickness. 461

462

MOOD DISORDERS

However, the reliability and validity of such measures are also influenced by the reproducibility of anatomical rules for delimiting target structures, the tissue contrast resolution, and the effects of partial volume averaging (which diminish as either spatial resolution or structure size increase). These issues limit the structures that can be reliably assessed by volumetric MRI (vMRI). For example, of regions that participate in emotional processing, cerebral cortical regions, mesiotemporal lobe structures such as the amygdala and hippocampus, and basal ganglia structures such as the caudate and putamen have been examined in vMRI studies. In contrast, structures such as the hypothalamus, the periaqueductal gray (PAG) matter, and brainstem monoaminergic nuclei, which have also been implicated in depression, are less tractable to neuroimaging approaches because of their small size and lack of clear demarcation from adjacent grey matter structures in MRI images. Clinical differences between depressive samples related to current age, age at illness-onset, and capacity for developing mania or psychosis also affect structural imaging measures. Differences in control samples may also influence study results, as some groups selected controls who were not depressed who underwent MRI as part of an evaluation for headaches or seizures, whereas others limited controls to participants who are healthy. Finally, because the magnitude of the differences between participants who are depressed and controls is subtle relative to the variability of structural imaging measures, vMRI abnormalities are not evident in individual participants, and relatively large samples are needed to ensure adequate statistical sensitivity. Neuromorphological Imaging Studies of Mood Disorders The most robust finding from structural imaging studies of mood disorders has been the elevated prevalence of MR signal hyperintensities in the deep and periventricular white matter of elderly participants with major depressive disorder (MDD; that is, “unipolar depression”) (Table 31.1). These abnormalities are predominantly seen in subjects who experienced their initial major depressive episode (MDE) in late life. As discussed below, the implications of these structural imaging findings with respect to the pathogenesis of late-life-onset depression is beginning to set this mood disorder subtype apart phenomenologically as a type of depression that may arise secondarily to cerebrovascular disease (Krishnan et al, 1993). MR Signal Hyperintensities: Clinical and Neuropathological Correlates The improved sensitivity of MRI technology to tissue contrasts and white matter pathology led to the obser-

FIGURE 31.1 Brain MRI, axial view through base of lateral ventricles showing large, confluent, deep white matter hyperintensities (open arrows) and hyperintensity in the right caudate head (closed arrow) in an elderly depressed subject. MRI: magnetic resonance imaging. Reproduced with permission from Drevets (1993).

vation that many individuals who otherwise appear neurologically healthy have lesions, seen as hyperintense foci of the MR signal, in the deep white matter, periventricular white matter, basal ganglia, and pons (Fig. 31.1). Although the correlates of such signal abnormalities occasionally were evident in CT scans (initially termed leukoaraiosis), their extent and frequency are more clearly visualized using MRI. In MRI images, white matter hyperintensities (WMH) were initially referred to as “unidentified bright objects” or “leukoencephalopathy,” but these lesions now are descriptively classified as either WMH or lacunae, and graded by their size and location in T2-weighted MRI scans. In elderly participants without known white matter disease such as multiple sclerosis (which presents with transient, focal areas of WMH that reflect a distinct neuropathological process), postmortem assessment of brain tissue where WMH were evident in MRI images antemortem indicate that “patches” and “caps” of signal hyperintensity in the deep and periventricular white matter generally correspond to areas affected by cerebrovascular disease (Awad, Johnson, et al., 1986; Chimowitz et al., 1992). Histopathological characterization of such patches demonstrates myelin pallor, gliosis, dilated perivascular spaces, white matter necrosis, and/ or axonal loss within the cap- or patch-like areas of signal hyperintensity, and these findings are absent in

31: NEUROIMAGING STUDIES

the surrounding tissue where the MRI signal appeared normal (Chimowitz et al., 1992). Consistent with the interpretation that these histopathological changes reflect cerebrovascular disease, functional imaging studies find local reductions in blood flow in the areas where WMH are apparent in MRI scans from the same participants (Fazekas, 1989; Herholz et al., 1990; Kobari et al., 1990). Lacunae also are more prevalent in MRI images from participants with late-onset depression than in agematched controls without depression, a finding that further supports the hypothesis that cerebrovascular disease increases the risk for depression. Lacunae appear in MRI images within grey matter as irregularly shaped, signal hyperintensities >5 mm in T2-weighted images, and as signal hypointensities in T1-weighted images. Such lesions reflect areas where infarcted tissue has been replaced by CSF. Lacunae are distinguished from Virchow–Robin spaces, which are small, punctate foci evident on T2-weighted MR images that reflect dilated perivascular spaces. The hypothesis that the pathogenesis of late-life depression involves cerebrovascular disease also is supported by epidemiological evidence. The risk factors for developing WMH also constitute risk factors for atherosclerotic cerebrovascular disease, namely advancing age, hypertension, diabetes, and ischemic stroke

(Awad, Johnson, et al., 1986; Awad, Spetzler, et al., 1986; Gerard and Weisberg, 1986; Fazekas, 1989; Coffey et al., 1990; Chimowitz et al., 1992). For example, Fazekas (1989) reported that the proportion of participants having subcortical or deep WMH ranged from 11% of participants scanned between age 40 and 49 to 83% of participants age 70 and older, and was highest in participants with known risk factors for cerebrovascular disease. Incidence of MR Signal Hyperintensities in Late-Life Depression The elevated prevalence of signal hyperintensities in T2weighted MRI scans from elderly participants with depression was initially observed in uncontrolled studies. Krishnan et al. (1988) reported patchy white matter lesions in 72% of a depressive sample (n = 35) with illness-onset after age 45, and Coffey et al. (1988) noted “moderate-to-severe” WMH in 66% of a sample of predominantly elderly participants with depression (n = 67) referred for electroconvulsive therapy. That these prevalence rates are higher than the corresponding rates in age-matched, healthy controls was subsequently established in controlled studies (Table 31.1). Coffey et al. (1990) reported that the incidence of moderate-to-severe signal hyperintensities (graded by size) is increased in

TABLE 31.1 Deep White Matter (DWMH) and Periventricular (PVH) Hyperintensities on MRI Scans in Patients with Affective Disorders - Controlled Studies

Year

Investigators

463

Patients

Controls

Results

51 elderly

22

More DWMHs and PVHs in patients over controls

Studies in unipolar depression 1990

Coffey et al.

1990

Zubenko et al.

67

44

More cortical and white matter hyperintensities in patients

1991

Lesser et al.

14 (psychotic)

72

More DWMHs and PVHs in patients over controls

1991

Rabins et al.

21 elderly

14

More cortical and white matter hyperintensities in patients

1993

Krishnan et al.

25 elderly

20

More DWMHs and PVHs in patients over controls

1995

Dupont et al.

30

26

No difference in abnormal white matter

1996

O’Brien, Desmond, et al.

60

39

More DWMHs in patients

1998

Greenwald et al.

35 elderly

31

More left frontal DWMHs in patients

Studies in bipolar disorder 1987

Dupont et al.

14

8

More DWMHs and PVHs in patients over controls

1990

Dupont et al.

19

10

More DWMHs and PVHs in patients over controls

1990

Swayze et al.

48

47

More DWMHs and PVHs in patients over controls

1991

McDonald et al.

1991

Figiel, Krishnan, Rao, et al.

1992

Brown et al.

1993

Strakowski et al.

1994 1995

12 late-onset

12

More large subcortical hyperintensities in patients

18

18

More DWMHs and PVHs in patients over controls

22

154

No differences

17 first mania

16

No differences

Aylward et al.

30

30

More DWMHs in patients (mostly frontal) in patients

Dupont et al.

36

26

More abnormal white matter in patients

464

MOOD DISORDERS

elderly participants who are depressed relative to agematched controls in the periventricular (62% vs. 23%, respectively) and deep white matter (55% vs. 14%) and in the thalamus/ basal ganglia (51% vs. 5%). Similarly, Iidaka et al. (1996) found hyperintensities in the putamen and the globus pallidus in 57% of elderly participants with depression versus 27% of controls. Greenwald et al. (1996; Greenwald et al., 1998) localized the areas where such lesions predominate in participants with depression versus controls to the left frontal lobe and left striatum—the same areas where cerebral infarctions increased risk for poststroke MDE (Starkstein and Robinson, 1989). In an extension of these findings, MacFall et al. (2001) found that within the left orbitofrontal cortex (OFC) was the specific cortical area where WMH were associated with an increased risk for MDE. These data converge with evidence from functional imaging studies of early- and mid-life depression indicating that the left OFC plays a modulatory role over depressive symptoms, and that dysfunction of this region from various etiologies increases risk for depression (reviewed below). The increased prevalence of MR signal hyperintensities in elderly depression appears to be largely attributable to participants with a late-life-onset of MDD. Figiel, Krisnan, Doraiswamy, et al. (1991) initially observed that 6 of 10 participants with late-onset depression (first MDE after age 60) but only 1 of 9 age-matched, earlyonset cases (first MDE before age 60) had WMH larger than 1 cm in diameter, and that the same proportions of each subsample had basal ganglia lesions. Krishnan et al. (1993) later demonstrated that elderly participants with depression (n = 25) had an increased frequency of subcortical hyperintensities, smaller caudate nuclei, and smaller putamenal complexes than age-matched controls and noted that these findings were all more pronounced in the late-onset subset. This association between the extent of MR signal hyperintensities and the age at which participants suffer their first MDE has been confirmed in several studies. Hickie et al. (1995) showed that in hospitalized participants with depression (n = 39, ages 28–86), the occurrence of WMH correlated with onset of MDD after age 50. Lesser et al. (1996) reported that the frequency of more severe WMH was higher in participants with depression whose first MDE occurred after age 50 (n = 60) relative to participants with depression with a first MDE before age 35 (n = 35) and to controls with other neuropsychiatric disorders (n = 165). Lesser et al. (1991) also observed that 50% of participants with depression who developed psychotic features after age 45 (n = 14) had combined periventricular and deep WMH volume of greater than 3 cm3 compared with less than 10% of healthy controls (n = 72). Finally, Fujikawa et al. (1993), showed that of depressives studied in mid- to late life (n = 205), participants

aged 50–65 years who had their first MDE after age 50 had a higher incidence of WMH meeting criteria for “silent cerebral infarction” (see below) than participants with earlier-onset depression. This study also showed that among participants with depression aged 65 or older, 94% of participants with their first MDE occurring after age 65 had such lesions compared with 66% of participants whose first MDE occurred between ages 50 and 65. These findings suggest that cerebrovascular disease plays a major role in the pathogenesis of MDE arising in late life, extending evidence from studies of poststroke depression (Starkstein and Robinson, 1989; Krishnan et al., 1993). Consistent with this hypothesis, elderly participants with depression with WMH meeting criteria for putative cerebral infarction were less likely to have a family history of a mood disorder (the major risk factor for early-onset depression) but more likely to have a family history of hypertension (Fujikawa et al., 1994). One group argued that the term silent cerebral ischemia should be applied to areas of MR signal hyperintensity greater than 5 mm in size (in T2-weighted images) in participants without a history of neurological signs of cerebrovascular infarction (Fujikawa et al., 1993). Nevertheless, though such lesions may not be associated with motor, sensory, or cognitive impairment, their association with depression implies that they are not clinically “silent.” In participants with late-onset depression with MRI evidence of cerebrovascular lesions, the depressive syndrome itself may reflect a neuropsychiatric sequela of cerebral dysfunction involving the brain structures that modulate emotional processing (Krishnan et al., 1993; Drevets and Todd, 1997). The clinical impact of such lesions is evidenced further by the poorer clinical response to treatment, the higher likelihood of treatment-related adverse reactions (for example, delirium), and the more prominent cognitive impairment found in elderly participants with depression with moderate-to-severe WMH and/or lacunae relative to elderly participants with depression without such lesions (Figiel et al., 1989; Figiel et al., 1990; Fujikawa et al., 1996; Lesser et al., 1996). MR Signal Hyperintensities in Bipolar Disorder The incidence of MR signal hyperintensities also appears elevated in bipolar disorder (BPD). Dupont et al. (1987; Dupont et al., 1990) reported deep or periventricular WMH in 8 of 14 participants with BPD and subcortical hyperintensities in 9 of 19 participants with BPD compared with none of the controls. In bipolar cases with subcortical WMH reimaged one year later, the lesions persisted. Dupont et al. (1995) later compared 30 participants with MDD, 36 participants with BPD, and 26 controls with no depression and found that the mean volume of abnormal white matter was

31: NEUROIMAGING STUDIES

larger in the participants with BPD than the participants with MDD and participants who were healthy (who did not differ from each other). However, in similar or larger samples sizes of participants with BPD, other investigators found much smaller rates of participants with MR signal hyperintensities that did not differ significantly from controls in incidence or size (Swayze et al., 1990; Brown et al., 1992; Strakowski et al., 1993). The age-at-onset of BPD may prove relevant for studies assessing MR signal hyperintensities in BPD, as McDonald et al. (1991) observed that participants with BPD with an age-of illness-onset after age 50 were more likely to have large subcortical hyperintensities. Incidence of MR Signal Hyperintensities in Dementia Magnetic resonance imaging evidence of WMH is not specific to mood disorders and also is common in multiinfarct and Alzheimer’s-type dementia (O’Brien, Ames, and Schwietzer, 1996). Zubenko et al. (1990) found that the incidence of lacunae, cortical infarction, and deep or periventricular WMH were similar in participants with dementia (n = 61) and age-matched, participants with depression (n = 67), although cortical atrophy was more prominent in dementia (all of these abnormalities were more common in the participants with depression and dementia relative to an age-matched, healthy sample: n = 44). Similarly, Rabins et al. (1991) found no differences in the rates of WMH and lacunae between participants with dementia of the Alzheimer type (n = 16) and elderly patients with depression (n = 21), both of whom had a greater size and frequency of basal ganglia lesions than age-matched, healthy controls (n = 14). Finally, in a study comparing MRI scans of 61 participants with Alzheimer’s-type dementia, 60 participants with MDD and 39 controls, O’Brien, Desmond, et al. (1996) found that deep WMH were more common in the participants with depression (especially in those with late-life onset) whereas periventricular WMH were more common in the participants with dementia. Neuromorphometric Studies of Mood Disorders Cerebral ventricles More than 30 studies have examined ventricular size in depression using CT or MRI. The methods for measuring ventricle-to-brain ratio (VBR) vary across studies, with most groups obtaining linear or areal measures from the axial slice where the ventricles appear largest and others using dimensional measures of ventricular volume (Coffey et al., 1993; Drevets and Botteron, 1997). Enlargement of the lateral ventricles was consistently found in participants with MDD who were elderly, particular in those with late-life-onset MDD (in whom ventricular enlargement likely signify ex vacuo changes

465

associated with ischemic neuropathology), and less consistently found in participants with delusional depression (reviewed in Elkis et al., 1995; Drevets and Botteron, 1997). In contrast, enlargement of the lateral ventricles has generally not been present in MRI studies of samples limited to midlife, nondelusional, participants with MDD, and to older participants with MDD with an early age-onset of MDD. In some studies, the increased VBR in participants with depression samples was shown to correlate with cognitive impairment, cortisol hypersecretion, hypothyroidism, or reduced CSF concentrations of the serotonin metabolite 5-HIAA. Enlargement of the third ventricle has been found in most studies of BPD (reviewed in Drevets and Botteron, 1997; Pearlson et al., 1997). In contrast, third ventricle enlargement was less consistently found in MDD (Drevets and Botteron, 1997). The brain structures where tissue loss may result in third ventricle enlargement in BPD have not been identified but may involve structures that line the third ventricle, such as the medial thalamus, hypothalamus, or habenula. The magnitude of ventricular enlargement in BPD generally is similar to that found in schizophrenia. Frontal lobe structures Although total cerebral volume generally has not differed between participants with depression and healthy samples, neuromorphometric abnormalities have been reported in specific frontal lobe, temporal lobe, and basal ganglia structures. Krishnan et al. (1992) reported decreased width of the frontal lobe, and Coffey et al. (1993) reported decreased frontal lobe volume (by 7%) in MRI studies of participants with mid- and late-life depression relative to age-matched, healthy controls. Similarly, Kumar et al. (1997) found the prefrontal cortex (PFC) volume smaller in participants with late-life “minor depression” compared with age-matched controls. More pronounced reductions of grey matter volume were found in MDD and BPD in specific subregions of the PFC. In the anterior cingulate cortex (ACC) ventral to the genu of the corpus callosum (that is, subgenual), left-lateralized reductions (20%– 40%) of grey matter volume were evident in participants with familial MDD, participants with familial BPD, and participants with MDD with psychotic features (Drevets et al., 1997, Hirayasu et al., 1999; Botteron et al., 2002; Coryell et al. 2005; Fig. 31.2; see also COLOR FIGURE 31.2 in separate insert). This finding has been confirmed by postmortem studies of clinically similar samples (Öngür et al., 1998). This reduction in volume exists early in the illness in familial BPD (Hirayasu et al., 1999) and MDD (Botteron et al., 2002). Although effective treatment with selective serotonin reuptake inhibitors (SSRIs) did not alter the subgenual PFC volume in MDD (Drevets et al., 1997), this cortex appeared larger in participants

466

MOOD DISORDERS

A

B

with BPD medicated with lithium compared to participants with BPD who were unmedicated, compatible with evidence that chronic administration of these mood stabilizers increases expression of the neuroprotective protein, Bcl-2, in the frontal cortex of experimental animals (Moore et al., 2004). In the lateral orbital cortex, volume has also been found reduced in vMRI studies of MDD (Lai et al., 2000) and BPD (Lyoo et al., 2004; Nugent et al. 2006), as well as in postmortem neuropathological studies of MDD (Rajkowska et al., 1999). Temporal lobe structures The volume of the entire temporal lobe was reportedly decreased in participants with BPD versus healthy controls by Hauser et al. (1989) and Altschuler et al. (1991). However, this finding was not replicated by Johnstone

FIGURE 31.2 (A-B) Areas of abnormally increased blood flow in patients with major depressive disorder. The image sections shown are from an image of t-values, produced by a voxel-byvoxel computation of the unpaired t-statistic to compare regional CBF between a depressed sample selected according to criteria for familial pure depressive disease (n = 13) and a healthy control sample (n = 33) (Drevets et al., 1992). The positive t-values shown correspond to areas where flow is increased in the depressives relative to the controls. The abnormal activity in these regions was replicated using glucose metabolism imaging in independent subject samples (Drevets, Spitznagel, and Raichle, 1995; Drevets, Bogers and Raichle, 2002; Drevets, Price, et al., 2002). (A) Sagittal section at 17 mm left of midline illustrating areas of increased CBF in depression in the amygdala and orbital cortex. (B) This area of increased flow extended through the lateral orbital cortex (C) to the ventrolateral prefrontal cortex (VLPFC) and anterior (Ant) insula (Drevets et al., 1992; Drevets, Bogers and Raichle, 2002). The x coordinate locates sagittal sections in mm to the left of midline. (A-B) The PET images from which the t-image was generated have been stereotaxically transformed to the coordinate system of Talairach and Tournoux (Co-Planar Stereotaxic Atlas of the Human Brain, Stuttgart, Thieme, 1988), from which the corresponding atlas outline is shown. Anterior is left. Illustration A is modified from Price et al. (1996) and B is reproduced from Drevets (1994) with permission. CBF: cerebral blood flow; PET: positron emission tomography

et al. (1989), Swayze et al. (1992), or Pearlson et al. (1997) in BPD, or by Coffey et al. (1993) in a predominantly MDD sample. An abnormal degree of temporal lobe asymmetry (right larger than left) was noted in four studies of MDD and one study of BPD. Another study found reduced grey matter in the superior temporal gyrus in participants with BPD versus controls (Nugent et al., 2006). Morphometric MRI studies of medial temporal lobe structures have reported significant reductions in hippocampal volume in MDD, with the magnitudes of difference ranging from 8% to 19% versus healthy controls (Bremner et al., 2000; Mervaala et al., 2000; Steffens et al., 2000). The reduction in hippocampal volume in MDD persists into remission (Neumeister et al., 2005). Sheline et al. (1996) reported that the hippocampal volume correlated inversely with the estimated total time spent depressed in MDD. Nevertheless, many groups

31: NEUROIMAGING STUDIES

found no significant differences between MDD and control samples (Hauser et al., 1989; Axelson et al., 1993; Pantel et al., 1997; P.J. Shah et al., 1998; Ashtari et al., 1999; Vakili et al., 2000; von Gunten et al., 2000), possibly reflecting biological heterogeneity across MDD samples. For example, Vythilingam et al. (2002) reported that the hippocampal volume was abnormally decreased in women with depression who also had suffered earlylife trauma, but not in women with depression without early-life trauma. In BPD, reduced hippocampal volume was reported by Noga et al. (2001) and Swayze et al. (1992) relative to healthy controls, but Pearlson et al. (1997) found no differences between BPD and control samples. Notably, postmortem studies of BPD found histopathological changes in the hippocampus may be more limited to the subiculum (e.g., Eastwood and Harrison, 2000). Two studies reported abnormalities of the hippocampal T1 MR signal in MDD. Krishnan, Doraiswamy, Figiel, et al. (1991) observed that the T1 relaxation time was reduced in the hippocampus, but not in the entire temporal lobe, in participants with MDD relative to healthy controls, and Sheline et al. (1996) observed that elderly participants with MDD had a higher number of areas showing low MR signal than age-matched controls in T1-weighted images. The significance of such abnormalities remains unclear. Finally, the volume of the amygdala has been reported to be decreased, increased (e.g., Frodl et al., 2004), or not different (e.g., Mervaala et al., 2000) in participants with MDD relative to healthy controls. Similarly in BPD amygdala volume was reported to be increased

TABLE

Year

(e.g., Altshuler et al., 1998; Strakowski et al., 1999), decreased (Pearlson et al., 1997; Blumberg et al., 2003; DelBello et al., 2004), or not different (Swayze et al., 1992) relative to healthy controls. The disagreements in the results across studies may be attributable to technical factors, as the amygdala’s small size and proximity to other grey matter structures limits the validity and reliability for delimiting amygdala boundaries in images acquired using MRI scanners of ≤1.5 Tesla field strength. Basal ganglia Some MRI studies reported that volumes of basal ganglia structures also are abnormal in MDD (Table 31.2). Husain et al. (1991) reported that the putamen was smaller in depressives (mean age = 55) versus controls, and Krishnan et al. (1992) found a smaller caudate volume in participants with depression (mean age = 48) than controls. In elderly participants with depression, Krishnan et al. (1993) reported smaller volumes of putamen and caudate relative to age-matched controls. These findings were consistent with the postmortem study of Baumann et al. (1999), which found that smaller caudate and accumbens area volumes in participants with MDD than controls. However, Dupont et al. (1995) and Lenz et al. (2000) found no significant differences in caudate or lenticular nucleus (putamen plus globus pallidus) volumes between younger participants with MDD (mean age = 39) and controls. Volumetric MRI studies of BPD have not found significant differences in the volumes of basal ganglia structures

31.2 Basal Ganglia Pathology in Affective Disorders—Controlled MRI Studies Investigators

Patients

Controls

22

467

Results

Studies in unipolar depression 1990

Coffey et al.

51 elderly

More basal ganglia lesions in patients

1991

Rabins et al.

21 elderly

14

More basal ganglia lesions in patients

1991

Husain et al.

41

44

Smaller putamen in patients

1992

Krishnan et al.

50

50

Smaller caudate in patients

1993

Krishnan et al.

25 elderly

20

Smaller caudate and putamen in patients

1995

Dupont et al.

30

26

No significant differences in caudate and lenticular volumes (decreased thalamic volume in patients)

1996

Greenwald et al.

48 elderly

39

More severe hyperintensities in the subcortical gray matter in patients

1996

Iidaka et al.

30 elderly

30

More hyperintensities in the putamen and globus pallidus in patients

1998

Greenwald et al.

35

31

More left putaminal hyperintensities in patients

Studies in bipolar disorder 1992

Swayze et al.

48

47

No significant differences

1994

Aylward et al.

30

30

Larger caudate volume in patients

1994

Harvey et al.

26

34

Subcortical tissue volume estimated; no differences

1995

Dupont et al.

36

26

No significant differences in caudate and lenticular volumes (larger thalamic volume in patients)

468

MOOD DISORDERS

relative to controls (reviewed in Drevets and Botteron, 1997). However, one postmortem study reported reduced caudate and accumbens area volumes in participants with BPD versus controls (Baumann et al., 1999). It remains unclear whether the discrepant results across studies may be accounted for by differences in the age or age at depression onset of their participants. Other cerebral structures Other brain structures have been less often studied in mood disorders. Of vMRI studies of the thalamus, Dupont et al. (1995) found reduced thalamic volume in participants with MDD versus controls, whereas Krishnan et al. (Krishnan, Doraiswamy, Figiel, et al., 1991; Krishnan et al., 1993) found no difference between participants with depression and controls. Studies of thalamic volume in BPD also reported conflicting results. In the posterior cingulate cortex, Nugent et al. (2006) reported reduced grey matter in BPD. In the cerebellum, some studies found reduced vermal volume in participants with depression versus controls (S.A. Shah et al., 1992; Escalona et al., 1993) whereas others did not. Endocrine glands Consistent with evidence that cortisol hypersecretion and hypothalamic-pituitary-adrenal (HPA) axis dysfunction exists in some participants with depression, a substantial proportion of participants with MDD showed enlargement of the adrenal and pituitary glands. Amsterdam et al. (1987) reported that 8 of 16 participants with depression who underwent abdominal CT were judged by radiologist’s clinical reading to have enlarged adrenal glands. Similarly, Nemeroff et al. (1992) found that the abdominal CT films of 11 of 38 participants with depression but 0 of 11 healthy controls were clinically reported as showing adrenal enlargement, with the mean adrenal volume of the participants with depression exceeding that of the controls by 57%. Rubin et al. (1995) similarly reported that the median adrenal volume was increased 68% in participants with depression (n = 11) versus controls (n = 11) using abdominal MRI, but that the median adrenal volume of the participants with depression decreased approximately to that of controls following remission. In a subsequent study, Rubin et al. (1996) showed that the mean adrenal volume was 38% larger in participants with depression (n = 35) than controls (n = 35), and that the magnitude of the enlargement did not correlate with the severity or duration of the index MDE or the lifetime number of episodes. The results of these imaging studies are consistent with the finding that the mean adrenal gland weight is abnormally increased in victims of suicide (Zis and Zis, 1987). The cause of adrenal enlargement is putatively related to the hypersecretion of

corticotrophin-releasing hormone and/or other adrenocorticotropic hormone (ACTH) secretagogues in depression, as chronic stimulation by ACTH results in hypertrophy of the adrenal cortex. Pituitary size is also enlarged in MRI studies of depression. Krishnan, Doraiswamy, Lurie, et al. (1991) showed that MRI-based measures of the cross-sectional area and the volume of the pituitary were increased (by 34% and 41%, respectively) in participants with depression (n = 19) relative to controls (n =19). Diffusion Tensor Imaging Magnetic resonance diffusion tensor imaging (DTI) is a noninvasive in vivo method for characterizing the integrity of anatomical connections and white matter circuitry and provides a quantitative assessment of the brain’s white matter microstructure. Hyperintensities showed more abnormalities than normal regions thus suggesting that hyperintensities reflect a pathophysiological process that damages the structure of brain tissue (Taylor et al., 2001). Microstructural changes in the frontal lobe also are associated with late-life depression (Taylor et al., 2004). This has been shown in young and elderly participants with depression (Li et al., 2007). Microstructural changes in the white matter of the OFC appear to be associated with BPD using DTI (Beyer et al., 2005). FUNCTIONAL NEUROIMAGING: APPLICATIONS IN MOOD DISORDERS RESEARCH Functional imaging research also holds great promise for elucidating the pathophysiology of mood disorders because neurochemical and neuroendocrine data indicate that these conditions are associated with disruptions of brain function, yet with the exception of lateonset MDD, structural imaging and postmortem studies have shown that the corresponding brain morphology largely is intact. The episodic nature and responsiveness to treatment of mood disorders permit imaging in symptomatic and asymptomatic states so that the physiological correlates of depressive symptoms can be distinguished from the pathophysiological changes underlying the tendency to develop depressive episodes. Moreover, because depressive symptoms reflect distortions of emotional states that can be expressed by participants without depression, the nature of neurophysiological changes related to the depressed state can be explored by imaging hemodynamic changes in participants who are healthy during experimentally induced states of sadness or anxiety, or during the processing of emotionally valenced stimuli. Finally, imaging techniques for quantifying neuroreceptor binding and neurotransmitter function enable in vivo characterization of the neurochemical abnormalities

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in mood disorders. The data offered from such studies are being used to localize specific brain regions for histopathological assessment, to investigate treatment mechanisms, and to guide genetic and treatment-outcome studies. In contrast to their utility in research, the clinical capabilities of functional imaging techniques for determining diagnosis or guiding treatment selection have not been established. The abnormalities identified thus far in depression have had relatively small effect sizes, and the sensitivity and specificity have not been characterized sufficiently to support clinical application. Significance of Cerebral Blood Flow and Glucose Metabolism Local cerebral blood flow (CBF) and glucose metabolism predominantly reflect a summation of the metabolic activity associated with terminal field synaptic transmission within each image volume element, or voxel (Raichle, 1987; DiRocco et al., 1989). Altered regional CBF and metabolism thus may signify corresponding changes in neurotransmission from afferent projections arising from within the same structure or from a distal structure (Raichle, 1987; DiRocco et al., 1989). Dynamic brain images thus provide maps of regional neural function associated with ongoing mental activity. Metabolic and CBF images also are affected by the integrity of the cerebrovascular system, the amount of viable grey matter within an image voxel, and other factors that may be abnormal in mood disorders. Differences in CBF or metabolism between participants with depression and controls thus may reflect neurophysiological correlates of emotional, behavioral, or cognitive symptoms of MDE, mood-congruent biases on neural processing in depression, pathophysiological changes that predispose to or result from affective disease, or compensatory mechanisms invoked to modulate or inhibit pathological processes. The physiological correlates of depressive symptoms and behaviors putatively appear as baseline abnormalities of local CBF or metabolism that normalize following effective treatment and that may, to some extent, be reproduced in participants who are healthy imaged while performing tasks that mimic the corresponding depressive manifestation. In contrast, neuroimaging abnormalities that reflect pathophysiological changes in synaptic transmission associated with altered neurotransmitter function, receptor sensitivity/density, or neuronal arborization (e.g., Wooten and Collins, 1981; Ågren et al., 1993) may persist whether participants are symptomatic or asymptomatic (Drevets et al., 1992). Irreversible abnormalities in CBF and metabolism also may be associated with grey matter volume reductions in familial mood disorders, or cerebrovascular disease in elderly participants with depression with a late-age of depression-onset (see below; Fig. 31.1; Drevets et al., 1997; Krishnan et al., 1993.

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Technical Issues Relevant to the Interpretation of Functional Brain Images The functional imaging literature reflects some disagreement in the results across studies. Many inconsistencies within this literature likely reflect limitations of statistical power for replicating findings across studies because the sample sizes employed have been small and the effect sizes of the abnormalities found to date also are small. Other apparent discrepancies across studies may be resolved by considering issues related to participant selection, image acquisition, and image analysis. Nevertheless, some of the variability within the literature is likely accounted for by the biological heterogeneity encompassed within the Diagnostic and Statistical Manual of Mental Disorders–4th ed. (DSM-IV: American Psychiatric Association, 1994) diagnostic categories for mood disorders. Issues related to image acquisition and analysis Understanding the neuroimaging literature requires critical assessment of a few key aspects of experimental design and analysis. The precision of anatomical localization in functional images has benefited from progressive improvements in spatial resolution (to 4 mm for the newest generation of positron emission tomography [PET] camera and < 1mm for high resolution functional MRI [fMRI]) and development of PET-MRI image coregistration techniques and of voxel-wise analysis approaches capable of identifying inherent differences between groups (Drevets and Botteron, 1997; Figs. 31.2 and 31.3; see also COLOR FIGURE 31.3 in separate insert). However, older studies applied techniques that were more severely constrained with respect to sensitivity and spatial resolution (Drevets and Botteron, 1997; Raichle, 1987). For example, images acquired using single photon emission computed tomography (SPECT) or nontomographic systems during 133Xe administration provided CBF measures limited to the cortical grey matter lying near the scalp, precluding measures from limbic, basal ganglia, and ventral and medial frontal and temporal lobe structures (Raichle, 1987). Moreover, perfusion measures obtained using SPECT and either 99mTcHMPAO or 133I-iodoamphetamine, agents that are not freely diffusable across the blood-brain-barrier, were relatively insensitive to CBF increases within the physiological range. Moreover, though PET affords relatively higher spatial resolution and sensitivity for deep structures, in most PET studies the images have been blurred to much lower spatial resolutions prior to analysis to reduce the effects of anatomical variability across participants. Another image processing issue that influences specificity and sensitivity involves “normalization” of regional data by dividing local-by-global measures. Because of the small sample sizes involved in imaging studies,

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FIGURE 31.3 Altered metabolism in PFC ventral to the genu of the corpus callosum (that is, subgenual PFC) in mood disorders. The top panel shows negative voxel t-values where glucose metabolism is decreased in depressives relative to controls in coronal (31 mm anterior to the anterior commissure, or y = 31) and sagittal (3 mm left of midline, or x = –3) planes of a statistical parametric image that compares depressives to controls (Drevets et al., 1997). This image localized an abnormality in the subgenual portion of the ACC (subgenual ACC; Drevets et al., 1997), which was subsequently shown to be accounted for by a corresponding reduction in cortex volume on the left side (see text). Anterior or left is to left. The bar histogram in the lower panel shows mean, normalized, glucose metabolic values for the left subgenual ACC measured using MRI-based region-of-interest analysis. Metabolism is decreased in depressed patients with either BD or MDD relative to healthy controls. In contrast, subjects scanned in the manic phase of BD have higher metabolism than either depressed or control patients in this region. Asterisk: difference between controls and bipolar depressives significant at p < 0.025; cross: difference between depressed and manic significant at p < 0.01; double cross: difference between control and manic significant at p < 0.05. Although none of these patients were involved in the study that generated the images shown in Figure 31.2, the mean glucose metabolism in this independent sample of depressed patients and controls also confirmed the areas of abnormally increased activity in the depressed patients in the amygdala, lateral orbital cortex, ventrolateral PFC, and medial thalamus (not shown in the t-image section in the figure, which only illustrates negative t-values corresponding to hypometabolic areas in the patients who were depressed). Reproduced with permission from Drevets et al. (1997) (upper panel) and Drevets (2001) (lower panel). PFC: prefrontal cortex; ACC: anterior cingulate cortex; MRI: magnetic resonance imaging; BD: bipolar depressed; MDD: unipolar depressed.

normalization is usually required to reduce the variability of regional values so that intergroup differences can be detected. In most studies of unmedicated, midlife participants with depression the whole-brain CBF and glucose metabolism have not differed significantly

between participants with depression and controls, so whole-brain activity serves as a useful denominator for factoring out nonspecific global effects (e.g., Baxter et al., 1985; Silfverskiöld and Risberg, 1989; Bench et al., 1993; Drevets et al., 1997, Kimbrell et al., 2002). In contrast, normalization of regional values by measurements confined to another region can prove more difficult to interpret. For example, early SPECT studies of depression normalized regional perfusion by flow in the cerebellum, a practice that confounded results because PET studies showed that medial cerebellar flow was abnormally increased in MDD (normalization to cerebellar flow thus artifactually decreased ratios obtained for other brain regions; Philpot et al., 1993). Nevertheless, whole-brain CBF and metabolism can be reduced by benzodiazepines, antipsychotic drugs, or cerebrovascular disease (Silfverskiöld and Risberg, 1989; Maes et al., 1993; Lesser et al., 1994), potentially confounding the interpretation of absolute and normalized values, so such issues merit specific consideration in experimental design. Image analysis approaches for detecting differences in regional physiology between participants with depression and controls also influence the sensitivity for detecting differences. The most anatomically precise technique involves MRI-based region-of-interest (ROI) analysis in which ROI is predefined on each participant’s own anatomical MRI scan and then transferred to coregistered, lower resolution functional images. This approach can nevertheless mislocalize the peak difference or excessively dilute differences if the ROI defined is too large (Mazziotta et al., 1981; Drevets, Price, et al., 2002). Voxel-wise approaches (for example, Statistical Parametric Mapping, or SPM) thus were developed to survey entire data sets and localize peak, inherent differences between conditions. These approaches nevertheless reduce sensitivity for detecting abnormalities in structures that are either small or characterized by a high degree of anatomical variability (e.g., Drevets, Bogers, et al., 2002) because they depend upon spatial transformation of the primary tomographs into a standardized stereotaxic space using algorithms that do not precisely align small structures or variable anatomy across participants. To reduce the effects of this misalignment error, images are blurred (“filtered”) to lower spatial resolutions. One approach that has proven useful is to iteratively apply MRI-based ROI analysis and voxelwise analysis to exploit the strengths and address the limitations inherent in each method (e.g., Drevets et al., 1997). To increase sensitivity for detecting abnormalities (that is, reduce Type II error), most studies compared image data between participants with depression and controls either in large numbers of predefined ROI or using voxelwise approaches. Voxel-wise approaches compute tens of thousands of independent statistical comparisons per

31: NEUROIMAGING STUDIES

image set, however, so the probability that an apparent difference between groups reflects multiple comparison artifact is high. Studies applying such approaches must therefore establish the significance of findings by replication in independent samples or by applying appropriate corrections of p values for multiple comparisons (Drevets et al., 1992; Drevets et al., 1997; Poline et al., 1997). Clinical sources of variability in image data from depressed samples Medication effects comprise an important source of variability in functional imaging studies, as regional physiology and chemistry of the brain areas of interest in depression can be altered by antidepressant, antipsychotic, and antianxiety drugs (e.g., Silfverskiöld and Risberg, 1989; Maes et al., 1993; Drevets and Botteron, 1997). These agents also affect the behavioral and hemodynamic responses to emotionally valenced sensory stimuli employed as neurocognitive probes in fMRI studies. Image data acquired in participants medicated with these drugs thus are difficult to interpret unless scans in the unmedicated condition also are available. Nevertheless, most published studies of depression report data confounded by medication effects, potentially introducing artifactual differences or obscuring true biological differences between participants with depression and controls. Notably, studies of participants with depression confounded by medication effects generally fail to detect the areas of abnormally elevated metabolism seen in unmedicated participants and instead often report regional reductions in flow or metabolism that cannot be replicated in unmedicated samples (reviewed in Drevets and Botteron, 1997). The clinical heterogeneity reflected within mood disorders introduces another source of variability, as diverse signs and symptoms may have distinct neurophysiological correlates (Drevets and Todd, 1997). For example, clinical features such as psychomotor slowing have been reported to influence neurophysiological and receptor pharmacological measures (see below). Few studies have had sufficiently large samples to characterize the imaging correlates of distinct clinical features, however, so the extent to which differing symptom profiles across depressed samples have contributed to differences in the results across studies remains unclear. A related challenge for imaging studies is the likelihood that the diagnostic criteria for MDD and BPD encompass groups of disorders that are heterogenous with respect to pathophysiology and etiology. Biological heterogeneity is evidenced by the variety of antecedents to MDE (genetic, medical, psychosocial), the diversity of responses to somatic or psychological therapies, and the variable presence of neuroendocrine, neurochemical, and circadian rhythm disturbances in depressive samples (Drevets and Todd, 1997). If depression is

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associated with multiple pathophysiologic states, it also may be characterized by an assortment of distinct functional imaging abnormalities. Consistent with this hypothesis, the reproducibility of some imaging findings in depression depends upon subtyping participants with depression. For example, participants with MDD with familial pure depressive disease (FPDD) were more likely to show imaging abnormalities such as elevated CBF and metabolism in the amygdala (see below). This subgroup also was more likely to show neuroendocrine and other types of biological abnormalities relative to other depressive subtypes (reviewed in Drevets, Price, et al., 2002). This MDD subtype thus may be more often associated with pathophysiologically linked abnormalities (for example, through interactions between the amygdala and CRF/glucocorticoid secretion). Nevertheless, it remains unclear whether subtyping strategies that increase sensitivity for detecting regional abnormalities in depression identify pathophysiologically distinct phenotypes of MDD or more generally “enrich” samples with participants likely to have biological markers for depression. Effects of structural abnormalities in functional brain images The vMRI abnormalities seen in some regions in depression can profoundly influence functional imaging measures. Tissue reductions decrease the magnitude of functional or receptor imaging measures from the corresponding regions via “partial volume averaging” effects (Mazziotta et al., 1981). Because of the low spatial resolution of PET and SPECT images, reductions in the proportion of grey matter relative to CSF and/or white matter within corresponding image voxels reduces the measured CBF or metabolism via the partial volume effect of averaging in more CSF, which is metabolically inactive, and white matter, which is one fourth as metabolically active as grey matter, relative to the diminished contribution of grey matter (Mazziotta et al., 1981). Because the ventricular and sulcal enlargement evident in late-onset depression is not apparent in participants with nondelusional MDD with a young age-of-onset, image data from these latter groups constitute a benchmark against which physiological imaging measures in other depressive subtypes are compared (Drevets and Botteron, 1997). Nevertheless, evidence that focal areas of reduced grey matter volume exist even in young participants with nondelusional MDD emphasizes the importance of evaluating areas where CBF and metabolism are irreversibly decreased in participants with depression relative to controls using vMRI and postmortem histopathological studies (Fig. 31.3; Drevets et al., 1997; Öngür et al., 1998. The WMH patches and lacunae evident in MRI images from participants with late-onset depression present

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an even greater problem for functional imaging studies because these abnormalities putatively reflect arteriosclerotic or ischemic disease. In vivo imaging studies demonstrate that elderly participants with depression with WMH have decreased CBF and metabolism in the frontal cortex and other areas where WMH are seen relative to age-matched participants with depression without WMH (Lesser et al., 1994). Moreover, because the relationship between regional BF, metabolism, and local synaptic transmission are altered by cerebrovascular disease, functional imaging studies of elderly participants with depression are difficult to interpret unless participants with prominent or diffuse MRI signal hyperintensities have not been excluded. Effect of behavioral state on flow and metabolism Because of the sensitivity of CBF and metabolism to changes in neural activity, the behavioral state in which participants are imaged profoundly influences neurophysiological image data. The pattern of physiological imaging abnormalities seen in depression thus depends on the behavioral state under which image data are acquired. For example, limbic and paralimbic areas such as the amygdala, ventral ACC, ventrolateral PFC/lateral orbital cortex, and posterior cingulate cortices normally deactivate during the performance of attentionally demanding tasks (Drevets and Raichle, 1998; Drevets, Bogers, and Raichle, 2002). Presumably because of this phenomenon, the elevations of CBF and metabolism seen in these areas in participants who are depressed scanned while resting with eyes closed have usually not been evident in images acquired as participants are engaged in attentionally demanding tasks. NEUROPHYSIOLOGICAL IMAGING ABNORMALITIES IN DEPRESSION Functional imaging studies have begun to characterize the neuroanatomical correlates of MDE, the neurophysiological effects of antidepressant treatments, and the trait-like abnormalities that persist into remission. These studies have identified CBF and metabolic differences between participants with depression and healthy controls in multiple regions, consistent with the expectation that the emotional, cognitive, psychomotor, neurovegetative, neuroendocrine, and neurochemical disturbances associated with depression implicate extended anatomical networks. The ensuing review highlights major findings from studies of unmedicated depressed samples. Abnormalities within the Prefrontal Cortex (PFC) Within the PFC, depression is associated with decreased physiological activity in some regions, together with in-

creased activity in others (Drevets and Raichle, 1998). Interpreting this complex pattern requires consideration both of the reductions in tissue volume described above, and also of the principles derived from brain-mapping and lesion analysis studies. Brain-mapping studies show that regional hemodynamic activity increases in patterns specific to the mental operations demanded by a particular cognitive-behavioral state, and that simultaneously hemodynamic activity decreases in some other regions, presumably to facilitate task performance via suppression of unattended, potentially competing background processes (Drevets, Burton et al., 1995; Drevets and Raichle, 1998). For example, the functional image data converge with evidence from anatomical, electrophysiological, and lesion analysis studies to implicate areas within the orbital and medial PFC (OMPFC) in the integration of sensory processing and emotional salience, decision-making pertaining to reward contingencies, modulation of emotional experience and expression, and experience of internally generated emotion and thought (reviewed in Drevets and Raichle, 1998; Öngür et al., 2003). Ventral anterior cingulate cortex (ACC) The ACC situated ventral and anterior to the genu of the corpus callosum (termed subgenual and pregenual, respectively) has been consistently implicated in the pathophysiology of MDD and BPD. In the subgenual PFC, a complex relationship between CBF, metabolism, and illness state exists that appears accounted for by the volumetric reduction of the corresponding cortex described above. In recurrent BPD and MDD, the baseline subgenual ACC CBF and metabolism appear abnormally decreased in PET images during MDE (Drevets et al., 1997), and correlated inversely with the number of lifetime depressive episodes (Kimbrell et al., 2002). However, computer simulations that correct PET data for the partial volume effect of reduced grey matter volume conclude the “actual” metabolic activity in the remaining subgenual PFC tissue is increased in participants with depression relative to controls. This hypothesis appears compatible with the observation that effective antidepressant pharmacotherapy results in a decrease in metabolic activity in this region in MDD (Buchsbaum et al., 1997; Mayberg et al., 1999; Drevets, Bogers, and Raichle, 2002; Drevets, Thase, et al., 2002). Computer simulations that correct posttreatment image data from MDD samples for spatial resolution (partial volume) effects find that actual metabolism (that is, corrected for the effect of the volumetric reduction in this region on PET measures) decreases to normative levels during effective treatment. Furthermore, these data are consistent with indications that during depressive episodes, metabolism shows a positive relationship with depression severity (Osuch et al., 2000; Drevets,

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Bogers, and Raichle, 2002). This mood state-dependency of subgenual ACC metabolism thus appears consistent with PET studies showing that flow increases in this region in healthy humans who are not depressed during sadness internally induced via contemplation of sad thoughts or memories (M.S. George et al., 1995; Mayberg et al., 1999). Notably, Mayberg et al. (2005) showed that deep brain stimulation within the subgenual ACC at frequencies expected to inhibit local neuronal function exerts antidepressant effects in treatment refractory cases. Neuroimaging measures obtained from the subgenual ACC have been associated with treatment outcome. Siegle et al. (2006) reported that decreased pretreatment reactivity to negative words in the subgenual ACC and increased pretreatment reactivity in the amygdala predicted stronger recovery with cognitive-behavioral therapy in participants who had depression. In addition, Chen et al. (2007) reported that the rate of clinical improvement after 8 weeks of fluoxetine treatment was positively predicted by the grey matter volume and the hemodymanic responsiveness to sad faces in the subgenual and pregenual ACC. In the pregenual ACC, Drevets et al. (1992) initially found increased CBF in MDD. Although other laboratories also reported abnormalities of CBF and metabolism in this area during depression, these data have been inconsistent (Table 31.3). The variability of these results may have clinical relevance, as several studies report relationships between pregenual ACC activity and subsequent antidepressant treatment outcome. Wu et al. (1992) reported that participants who are depressed whose mood improved during sleep deprivation showed elevated metabolism in the pregenual ACC and amygdala in their pretreatment scans. Mayberg et al. (1997) reported that though metabolism in the pregenual ACC was abnormally increased in participants with depression who subsequently responded to antidepressant drugs, metabolism was decreased in participants with depression who later had poor treatment response. Finally, in a tomographic electroencephalogram (EEG) analysis, Pizzagalli et al. (2001) reported that participants with depression who ultimately showed the best response to nortriptyline showed hyperactivity (higher theta activity) in the pregenual ACC at baseline, as compared to participants showing the poorer response. The effects of treatment on pregenual ACC flow and metabolism also have differed across studies, with activity decreasing in some but increasing in others in post- relative to pretreatment scans (Table 31.4). Positron emission tomography studies of chronic SSRI treatment have been more consistent, showing reductions in pregenual ACC metabolism in post- relative to pretreatment scans in all but one study (Table 31.4).The extent to which these discrepant findings are explained by differential effects across subregions of this area

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remains unclear. The pregenual ACC shows elevated CBF during a greater variety of emotional conditions elicited in healthy humans or humans with anxiety disorders (reviewed in Drevets and Raichle, 1998). Electrical stimulation of this region elicits fear, panic, or a sense of foreboding in humans, and vocalization in experimental animals (reviewed in Price et al., 1996). Postmortem assessment of the subgenual ACC (part of BA 24) demonstrated this abnormal reduction in grey matter was associated with a reduction in glia, no equivalent loss of neurons, and increased neuronal density in MDD and BPD relative to control samples (Öngür et al., 1998). In a tissue section that appeared to correspond to Brodmann area 24 cortex of the pregenual ACC, Cotter et al. (2002) found that glial density was significantly reduced in layer VI from participants with MDD or schizophrenia, but not in participants with BPD (most of whom were receiving mood stabilizers that appear to exert neurotrophic/neuroprotective effects). The mean size of neurons was also reported to be reduced in the deep layers of participants with MDD. In BPD, Benes et al. (2001) found reductions in nonpyramidal cells in the pregenual ACC. The volumetric abnormality in the subgenual PFC most likely reflects a reduction of neuropil rather than in the number of cell bodies. The neuropil (the fibrous layers comprising dendrites and axons) occupies most of the cortex volume and can be remodeled by dendritic atrophy during repeated stress (McEwen, 1999). In rodents and nonhuman primates the cortex that appears homologous to human subgenual and pregenual ACC has extensive reciprocal connections with areas implicated in the expression of behavioral, autonomic, and endocrine responses to stressors, aversive stimuli and rewarding stimuli, such as the hypothalamus, amygdala, accumbens, subiculum, ventral tegmental area, raphé, locus coeruleus, PAG, and nucleus tractus solitarius (NTS) (reviewed in Drevets et al., 1998, Öngür et al, 2003). Humans with lesions that include the ventral ACC show abnormal autonomic responses to emotionally provocative stimuli, inability to experience emotion related to concepts that ordinarily evoke emotion, and inability to use information regarding the likelihood of punishment and reward in guiding social behavior (Damasio, 1994). In rats, bilateral or right-lateralized lesions of the infralimbic, prelimbic and ventral ACC cortex attenuate sympathetic autonomic responses, stress-induced corticosterone secretion, and gastric stress pathology during restraint stress or exposure to fear-conditioned stimuli (reviewed in Drevets et al., 1998). In contrast, leftsided lesions of this area increase sympathetic autonomic arousal and corticosterone responses to restraint stress (Sullivan and Gratton, 1999). These data suggest the hypothesis that the right subgenual PFC facilitates expression of visceral responses during emotional processing, while the left subgenual PFC modulates such responses

31.3 Functional Imaging Results in Prefrontal Cortex (PFC) for Studies Limited to Unmedicated, Primary, Unipolar Depressivesa Imaged in the Resting Condition

TABLE

Blood Flow or Glucose Metabolism in DEP Relative to CON

Sample Size Authors

DEP CON

Ventral PFC

Dorsal PFC

Baxter et al., 1987

14

14

PET, 18FDG

↑ medial orbital C (BL)b

N/A

18

Imaging Technique

Baxter et al., 1989

10

12

PET, FDG

N/A

↓ dorsal anterolateral(BL)

Bench et al., 1992

33c

23

PET, H215O

N/Ad

↓ dorsolateral (L)

Biver et al., 1994

12

12

PET, FDG

↑ medial and lateral orbital(BL)

↓ dorsolateral (L)

Brody et al., 2001

24

16

PET, FDG

↑ ventrolateral PFC, lateral orbital C

n.s. dorsolateral

Buchsbaum et al., 1997

39

28

PET, 18FDG

↑ pregenual ACC

↓ dorsal medial

↓ subgenual ACC/ ventromedial PFCe

n.s. dorsolateral

↑ L. ventrolateral PFC, lateral orbital

n.s.

↓ dorsal ant. cingulate

Drevets et al., 1992

13

33

18 18

PET, H2 O 15

↑ pregenual ACC 17

PET, 18FDG

↑ ventrolateral PFC, lat. orbital (BL)g

Drevets, Spitznagel, & Raichle, 1995

31

Drevets, Bogers, & Raichle, 2002

27

14

PET, 18FDG

↑ lateral orbital C,

Ebert et al., 1991

10

8

SPET,99mTcHMPAO

↑ orbital C (BL)g

↓ dorsal anterolateral (L)

Kennedy et al., 2001

13

24

PET, FDG

↑ pregenual ACC

↓ dorsolateral (L)

Mayberg et al., 1997

18i

15

PET, 18FDG

↑ pregenual ACC in treatment-

↓ dorsolateral (BL)

N/A

↓ subgenual ACCf ↓ dorsomedial/ dorsal anterolateral (BL)

↓ ventrolateral PFC (BL) 18

responsive but ↓ in treatmentresistant; n.s. orbitali Nofzinger et al., 1999

6

10

PET, 18FDG

↑ L. medial orbital C ↑ R. lateral orbital C

↓ dorsolateral (L)

Postalache et al., 2002

15

15

PET, 18FDG

↑ ventrolateral PFC, lateral orbital C

n.s.

Saxena et al., 2002

27

17

PET, FDG

n.s. (trend to↑ ventrolateral PFC, BL)

n.s.

Silfverskiöld & Risberg, 1989

31

31

Multidetector

n.s. (trend to↑ L ventrolateral PFC)

n.s.

Uytdenhoef et al., 1983

16

↑ left “frontal ratio” (which included ventrolateral PFC)

↑ superior frontal g (L)

↑ ACCg; orbital C N/A

N/A

18

Probes,133Xej 20

Multidetector Probes,

133

Wu et al., 1992

15

15

Xe

PET, 18FDG

j

ACC: anterior cingulate cortex; BL: bilateral; C: cortex; CON: controls; DEP: depressed patients; 18FDG: 18F-fluorodeoxyglucose; g: gyrus; H215O; oxygen-15 water; L: left; PFC: prefrontal cortex; R: right; 99mTc-HMPAO: technetium-99 HMPAO; 133Xe (xenon-133) used to measure blood flow; n.s: difference assessed and not significant; N/A: region not assessed; ↑ and ↓ indicate increases and decreases, respectively, in the depressed patients; relative to the controls. a. Image data from studies that are uninterpretable due to confounding medication effects are not reviewed unless data were separately assessed for the unmedicated subsample. Data from studies of “secondary” depression and bipolar depression are addressed separately (see text). Some of these studies included bipolar patients in their depressed samples, but only the results from the unipolar subsample are reported here (unless data were not presented separately for bipolar and unipolar patients). The descriptive terms used to locate regions vary across study, and in some cases distinct terms may be used to describe the same area. Conversely, studies using the same term may be describing different cortical areas (e.g., the “dorsolateral PFC” spans several cm2 and encompasses thousands of independent resolution elements). b. This paper compared regional metabolism between patients with obsessive-compulsive disorder and patients with either primary unipolar depression or healthy controls. While the difference between depressed patients and controls was not statistically assessed in this paper, the published values for the orbital-to-hemisphere ratio in the depressives (n = 14; right: 1.17 ± 0.06, left: 1.14 ± 0.05) and the controls (n = 13; right: 1.11 ± 0.08, left: 1.09 ± 0.06) showed differences that were similar in magnitude and variability to the differences found in other studies using images of similar resolution, and would be significant by t test (right: p < 0.05, left: p < 0.02) (from Table 3 of Baxter et al., 1987). c. Nineteen of the depressed patients were imaged while receiving various medications. The reported abnormalities were initially identified using image data from the entire depressed sample (n = 33), but the difference between DEP and CON was also confirmed in the unmedicated subsample (n = 14) post hoc. d. This study identified abnormalities using a statistical image that excluded pixels in the orbital cortex, because the images acquired did not extend into this ventral structure for all subjects (Dolan, personal communication). e. Abnormally reduced metabolism was found in predefined regions-of-interest in ventral ACC and “rectal gyrus” lying within the same horizontal image plane, implying these ventromedial PFC areas were likely located in subgenual ACC. f. Abnormalities significant in subgroup meeting criteria for familial pure depressive disease, but not for subgroup with familial loading for alcoholism. g. Abnormality found only in subgroup who proved responsive to sleep deprivation. h. Reflects the sample size for the unmedicated patients only, who were independently compared to controls and to another 13 benzodiazepine-treated patients. i. Five of these patients had been subchronically treated with antidepressant drugs prior to scanning. It is unclear whether subchronic antidepressant drug therapy has the same effect of decreasing orbital metabolism as does chronic treatment (Table 31.4). j. Blood flow is only measured near the scalp using this technique, so results are unavailable for the orbital or cingulate cortices (see text).

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31.4 Antidepressant Treatment Effects Upon Ventral Prefrontal Cortical Blood Flow and Metabolism in Major Depressiona

TABLE

Authors Bonne et al., 1996 Brody et al., 2001

Change in CBF or Glucose Metabolism Post- vs. Pretreatment Scans

Treatment Modality ECT

↑ pregenual ACC in responders

paroxetine

↓ pregenual ACC and ventrolateral PFC

interpersonal therapy

↓ pregenual ACC, ↑ left anterior insula

Buchsbaum et al., 1997

sertraline

↓ pregenual ACC,

Cohen et al., 1992

phototherapy

↓ medial orbital Cb

Drevets & Raichle, 1992

desipramine

↓ left ventrolateral PFC/ lateral orbital C

↓ ventromedial PFC (see Table 31.3, note e)

Drevets, Bogers, & Raichle, 2002

sertraline

↓ subgenual ACC

Drevets, Thase, et al., 2002

citalopram

↓ ventrolateral PFC/ lateral orbital C (BL) ↓ subgenual and pregenual ACC, ↓ anterior insula (BL)

Ebert et al., 1991

sleep deprivation

↓ orbital C in respondersb

Goodwin et al., 1993

various drug treatments

↑ anterior cingulate, n.s. ventral anterolateral

Kennedy et al., 2001

paroxetine

↓ anterior insula (BL)

Mayberg et al., 1999, Mayberg et al., 2000

fluoxetine

↓ anterior insula

Nobler et al., 1994

ECT

↓ left ventrolateral PFC in respondersc

Nobler et al., 2000

nortriptyline or sertraline

↓ left ventrolateral PFC in respondersc

Nobler et al., 2001

ECT

↓ left ventrolateral PFC

Saxena et al., 2002

paroxetine

↓ left ventrolateral PFC

Smith et al., 1999

sleep deprivation

↓ right ventrolateral PFC

↑ pregenual ACC ↓ subgenual ACC ↑ left ventrolateral PFC

↓ subgenual PFC ↓ orbital C (BL) ↓ pregenual ACC, Wu et al., 1992

sleep deprivation

↓ ACC in responders

ACC, anterior cingulate cortex; BL, bilateral; C, cortex; CBF: cerebral blood flow; ECT, electroconvulsive therapy; PFC, prefrontal cortex; RTMS, repeated transcranial magnetic stimulation; ↑, ↓, and n.s. indicate increases, decreases, or no significant changes, respectively, in the treated relative to the untreated state for regions assessed. Not all studies examined the same regions, and the absence of a listed result for a specific region indicates that no image data were provided for that region. a. The changes in these ventral PFC regions show similar results to studies of antidepressant drug treatment in obsessive compulsive disordered samples. In contrast to these ventral prefrontal changes in depression, CBF and metabolism in the dorsal anterior cingulate and the dorsolateral PFC have been shown to increase in some studies of depression (e.g., Baxter et al., 1989; Bonne et al., 1996), but to decrease in others (Nobler et al., 1994; Nobler et al., 2001) following effective treatment. b. The treatment-associated change reported in this study was not shown by paired statistical tests but rather by the observation that in the treatment responders, the abnormal increase that was evident pretreatment was not present posttreatment. c. These studies were performed using the radiotracer xenon-133, which only provides CBF measures near the scalp. Thus results were not available for the orbital or the cingulate cortices (see text).

(Sullivan and Gratton, 1999). If so, then the left-lateralized grey matter reduction of the ventral ACC in MDD and BPD may contribute to dysregulation of neuroendocrine and autonomic function in depression. The subgenual ACC and adjacent ventromedial PFC also participates in evaluating the reward-related significance of stimuli (Elliott et al., 2000). These areas

send efferent projections to the ventral tegmental area (VTA) and substantia nigra and receive dense dopaminergic innervation from VTA (reviewed in Drevets et al., 1998). In rats, electrical or glutamatergic stimulation of the medial PFC areas elicits burst firing patterns from DA cells in the VTA and increases DA release in the accumbens (reviewed in Drevets et al., 1998).

31: NEUROIMAGING STUDIES

Because these phasic, burst-firing patterns of DA neurons are thought to encode information regarding stimuli that predict reward and deviations between such predictions and occurrence of reward, ventral ACC dysfunction may conceivably contribute to disturbances of hedonic perception and motivated behavior in mood disorders. In this regard, the magnitude of abnormal metabolic activity in the subgenual PFC may relate to switches between depression and mania, as even in the presence of reduced volume, apparent subgenual PFC activity appears abnormally increased in small samples of participants with mania (e.g., Drevets et al., 1997). Dorsomedial/dorsal anterolateral PFC Many studies reported decreased CBF and metabolism in areas of the dorsolateral and dorsomedial PFC in participants with MDD and BPD relative to controls (Table 31.3). The dorsomedial region where flow and metabolism are decreased in MDD appears to include the dorsal ACC (Bench et al., 1992) and an area rostral to the dorsal ACC involving cortex on the medial and lateral surface of the superior frontal gyrus (approximately corresponding to Brodmann area 9) (Baxter et al., 1989; Drevets, Bogers, and Raichle, 2002). Postmortem studies of MDD and BPD have found abnormal reductions in the size of neurons and/or the density of glia in this portion of BA 9 (Rajkowska et al., 1999; Cotter et al., 2002). The reduction in metabolism in this region in the unmedicated depressed condition may thus reflect these histopathological changes and account for the failure of antidepressant drug treatment to alter metabolism in these areas (Drevets, Bogers, and Raichle, 2002). Nevertheless, currently remitted participants with MDD who experience depressive relapse during tryptophan depletion show increased metabolic activity within these areas in the depressed versus the remitted conditions (Neumeister et al., 2004), similar to other structures where histopathological and grey matter volume changes exist in MDD. Flow normally increases in the vicinity of this dorsomedial/dorsal anterolateral PFC in healthy humans as they perform tasks that elicit emotional responses or require emotional evaluations (Dolan et al., 1996; Reiman et al., 1997). In primates the BA 9 cortex sends efferent projections to the lateral PAG and the dorsal hypothalamus through which it may modulate cardiovascular responses associated with emotional behavior (Öngür et al, 2003). Dysfunction of the dorsomedial/dorsal anterolateral PFC may also impair the ability to modulate emotional responses in mood disorders. In contrast, the reduction in CBF in the dorsal ACC has been associated with impaired mnemonic and attentional processing derived from neuropsychological test scores obtained near the time of scanning (Dolan et al., 1994). This area has been implicated in selective

477

attentional processing during cognitive tasks, and Drevets and Raichle (1998) demonstrated that hemodynamic activity decreases in the same area in participants who are healthy in whom anxiety is induced via fear of electrical shock. The reciprocal pattern of activation/deactivation in this region during cognitive versus emotional processing may conceivably relate to the neuropsychological manifestations of depression (Drevets and Raichle, 1998). In other areas of the dorsolateral PFC the spatial locations of reported differences between participants with depression and controls have varied widely across studies, and new studies performed in independent participant samples have had difficulty replicating the originally described abnormalities (e.g., see Brody et al., 2001; Saxena et al. 2002). In a more posterior area of the dorsolateral PFC, Bench et al. (1992) also reported an area where flow was abnormally reduced in MDD. Dolan et al. (1993) subsequently observed that the reductions in CBF in this area correlated with ratings of impoverished speech in participants with depression and schizophrenia and proposed that this abnormality reflected a correlate of slowed cognitive processing. Lateral orbital/ventrolateral PFC In the lateral orbital cortex, ventrolateral PFC, and anterior insula, CBF and metabolism have been abnormally increased in most studies of unmedicated participants with primary MDD scanned while resting with eyes closed (Table 31.3). In contrast, image data acquired as participants who are either medicated or are engaging in attentionally demanding tasks during scanning (Kimbrell et al., 2002) have usually not detected this abnormality. The elevated activity in these areas in MDD appears mood-state dependent (Drevets et al., 1992). Flow and metabolism also increase in these areas during induced sadness and anxiety in participants who are healthy and induced anxiety and obsessional states in participants with anxiety disorders (reviewed in Drevets and Raichle, 1998; Charney and Drevets, 2002). Many studies also report that flow or metabolism decrease during antidepressant treatment in the orbital cortex, ventrolateral PFC, and/or anterior insula (Table 31.4). A complex relationship exists between depression severity and physiological activity in the orbital cortex and ventrolateral PFC. Although CBF and metabolism increase in these areas in participants who are depressed relative to the remitted phase of MDD, the magnitude of these measures correlates inversely with ratings of depressive ideation and severity (Drevets et al., 1992; Drevets, Spitznagel, and Raichle, 1995). Moreover, though metabolic activity is abnormally increased in these areas in treatment-responsive participants with MDD and BPD, more severely ill or treatment refractory samples show CBF and metabolic values that were lower than

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MOOD DISORDERS

or not different from those of controls (Mayberg et al., 1997). This inverse relationship between orbital cortex/ventrolateral PFC activity and depression severity appears compatible with similar assessments in other conditions. Posterior orbital cortex flow also increases in participants with obsessive-compulsive disorder (OCD) and animal phobias during exposure to phobic stimuli and in participants who are healthy during induced sadness (Rauch, et al., 1994; Drevets, Simpson, and Raichle, 1995; Schneider et al., 1995), and the change in posterior orbital CBF correlated inversely with changes in obsessive thinking, anxiety, and sadness, respectively. Some OFC regions modulate the behavioral, endocrine, and autonomic responses associated with defensive, fear, and reward-directed behavior via anatomical projections to the amygdala, striatum, hypothalamus, PAG, hippocampal subiculum, and other limbic and brainstem structures (Rolls, 1995; Öngür et al., 2003). The orbital cortex and amygdala send overlapping projections to each of these structures as well as to each other through which they appear to modulate each other’s neural transmission (Timms, 1977; Öngür et al., 2003). Activation of the orbital cortex during depression may thus reflect endogenous attempts to attenuate emotional expression or interrupt unreinforced aversive thought and emotion. Consistent with this hypothesis, cerebrovascular lesions and tumors involving the frontal lobe increase the risk for developing major depression (e.g., Starkstein and Robinson, 1989), with the orbital cortex having been more specifically implicated as the area where such lesions induce depression (MacFall et al., 2001). Finally, serotonin depletion (Bremner et al., 1997; Hasler et al. 2008) and Parkinson’s disease appear to impair orbital cortex function (Mayberg et al., 1990; Ring et al., 1994), suggesting other mechanisms through which deficits in orbital cortex function may increase risk for depression. These observations further suggest that the abnormal reduction in grey matter in the lateral OFC (Rajkowska et al., 1999) contributes to the perseverative or persistent nature of depressive mood and ideation. The reduction of CBF and metabolism in the orbital cortex and ventrolateral PFC seen during antidepressant drugs treatment (Table 31.4) may, therefore, not be a primary mechanism through which such agents ameliorate depressive symptoms. Instead, direct inhibition of pathological limbic activity in areas such as the amygdala and ventral ACC may be more essential for correcting the pathophysiology associated with the production of mood symptoms (Drevets, Bogers, and Raichle, 2002). The orbital cortex neurons may thus be able to “relax,” as reflected by the reduction of metabolism to normal levels, as antidepressant drug therapy attenuates the pathological limbic activity to which these neurons respond. Notably, other OFC regions participate in integrating experiential stimuli with emotional salience and in

associating reward-directed behavioral responses with the outcome of such responses, allowing redirection of behavior as reinforcement contingencies change (Rolls, 1995). Thus OFC dysfunction in mood disorders also may contribute to the attenuation of motivated behavior and reward salience during depression. The Amygdala In the amygdala, neurophysiological activity at rest and during exposure to emotionally valenced stimuli is altered in some depressive subgroups. Resting CBF and metabolism are elevated in subgroups with mood disorders who meet criteria for either FPDD (Fig. 31.2; Drevets et al., 1992; Drevets, Spitznagel, and Raichle, 1995; Drevets, Bogers, and Raichle, 2002; Drevets, Price, et al., 2002), MDD-melancholic subtype (Nofzinger et al., 1999), Type II BPD or nonpsychotic, Type I BPD (Ketter et al., 2001; Drevets, Price, et al., 2002), or who prove responsive to sleep deprivation (Wu et al., 1992). In contrast, metabolism has not been found to be abnormal in participants with MDD meeting criteria for depression spectrum disease (Drevets, Spitznagel, and Raichle, 1995; Drevets, Price, et al., 2002), or in depressed samples who meet DSM criteria for MDD as the only entrance criterion (Abercrombie et al., 1998; Brody et al., 2001; Saxena et al., 2002). Nevertheless, the extent to which such nonreplications reflect technical limitations related to the small size of the amygdala remains unclear (discussed in Drevets, Price, et al., 2002). In FPDD the magnitude of the abnormal elevation of flow and metabolism ranges averages about 6% with state-of-the-art PET cameras (Fig. 31.4). When corrected for spatial resolution effects, this difference would reflect an increase in the actual CBF and metabolism of about 70% (Drevets et al., 1992). These magnitudes are in the physiological range. The elevation of resting amygdala CBF/metabolism appears relatively specific for primary mood disorders, insofar as this abnormality has not been reported in OCD, panic disorder, phobic disorders, or schizophrenia (Charney and Drevets, 2002). In participants with these conditions and in healthy humans, the amygdala CBF generally increases during exposure to emotionally salient sensory stimuli, but not during anxiety or sadness states elicited by internally generated thoughts (reviewed in Charney and Drevets, 2002. In contrast, amygdala metabolism is abnormally elevated in MDD during resting wakefulness and during sleep, as Nofzinger et al. (1999) reported that though amygdala metabolism was increased in participants with depression versus controls during wakefulness, the increase in metabolism occurring in the amygdaloid complex during rapid-eyemovement (REM) sleep also was greater in participants with depression than controls. These data imply that amygdala hypermetabolism exists in MDD even when stressors are not being consciously processed.

31: NEUROIMAGING STUDIES

479

FIGURE

31.4 Elevation of mean normalized physiological activity (± SEM) in the left amygdala, measured in terms of CBF or glucose metabolism, in mid-life depressed subjects relative to healthy controls. The five consecutive studies obtained using different PET cameras (PETT VI, HR+ and 953B are PET scanner model numbers—the latter two manufactured by Siemens/CTI; 2D and 3D refer to distinct image acquisition modes) in different laboratories in independent subject samples are summarized in Drevets et al. (1992; Drevets, Spitznagel, and Raichle, 1995; Drevets et al., 1999; Drevets, Bogers,

and Raichle, 2002; Drevets, Price, et al., 2002). Because the first glucose metabolism study (center) showed that FPDD and BD-D samples significantly differed from controls, but not from each other, patients from these categories were combined for two subsequent studies (panels 2 and 4). SEM: standard error of mean; CBF: cerebral blood flow; PET: positron emission tomography; rCBF/gCBF: regional-toglobal CBF ratio; rMRglu/gMRglu: ratio of regional-to-global metabolic rates for glucose; CON: healthy controls; FPDD: familial pure depressive disease; BD-D: depressed phase of bipolar disorder.

During antidepressant treatment that ameliorates depressive symptoms and prophylaxes against relapse, amygdala metabolism decreases toward normal in MDD (Drevets, Bogers, and Raichle, 2002). Similarly, a preliminary study of BPD showed that mean amygdala metabolism in remitted participants taking mood stabilizers was lower than in remitted participants taking mood-stabilizing drugs and not different from healthy controls (Drevets, Price, et al., 2002). Compatible with these observations, antidepressant-medicated, remitted participants with MDD who did not relapse during tryptophan depletion (which putatively decreases CNS serotonin concentrations) had a lower baseline amygdala metabolism (that is, prior to depletion) than remitted participants with MDD who did relapse (Bremner et al., 1997). Finally, Sheline et al. (2001) showed that the left amygdala’s hemodynamic response to emotionally valenced stimuli was attenuated in participants with MDD following chronic sertraline treatment. Functional imaging data acquired as participants view emotionally valenced stimuli that normally activate the amygdala also demonstrate altered physiological responses in MDD. In the left amygdala, the hemodynamic response to viewing fearful faces (relative to viewing either smiling or neutral faces) was blunted in children with depression (Thomas et al., 2001). This finding was consistent with the elevation of basal CBF and metabolism in the left amygdala in such cases because tissue that is physiologically activated is expected to show an attenuation of further rises in the hemodynamic/metabolic signal in response to tasks that normally engage the same

tissue. Nevertheless, Sheline et al. (2001) reported that hemodynamic responses were exaggerated in participants with MDD exposed to fearful or smiling faces that were displayed briefly (40 msec) and then masked by faces with “neutral” expressions, so that participants were unaware of having seen the emotional faces. Similarly, the hemodynamic response of the amygdala to happy or fearful faces was increased in participants with depression with BPD relative to healthy controls (YurgelunTodd et al., 2000; Lawrence et al., 2004; Blumberg et al., 2005). The duration of the amygdala response to emotionally valenced stimuli also is abnormal in depression. Drevets et al. (2001) observed that although the initial amydgala blood-flow response to sad faces was similar to that of controls, the response habituated during repeated exposures to the same stimuli in controls, but not in participants with depression. Moreover, Siegle et al. (2002) reported that the increase in hemodynamic activity occurring in the amygdala during exposure to negatively valenced words in participants with depression and controls was sustained for a longer time in the participants with depression. The observation of Siegle et al. (2002) is particularly noteworthy in light of neuroimaging, electrophysiological, and lesion analysis studies in humans and experimental animals that demonstrate the amygdala is involved in the acquisition and recall of emotional or arousing memories (Ferry et al., 1999; Canli et al., 2000). In humans, bursts of EEG activity occur in the amygdala during recollection of specific emotional events, and electrical

480

MOOD DISORDERS

stimulation of the amygdala can evoke emotional experiences (fear, anxiety, dysphoria) and recall of emotionally charged, life events from remote memory (reviewed in Drevets, 2003). Taken together with the finding of elevated amygdala metabolism in MDD, these observations suggest the hypothesis that excessive amygdala stimulation of cortical structures involved in declarative memory may account for the tendency of participants with depression to ruminate about memories of emotionally aversive or guilt-provoking life events. Amygdala dysfunction also may conceivably alter the initial evaluation and memory consolidation related to social or sensory stimuli with respect to their emotional significance in mood disorders (Drevets, 2003). The amygdala is involved in recognizing sadness and fear in facial expression and fear and anger in spoken language (reviewed in Drevets, 2003). Norepinephrine (NE) release in the amygdala plays a critical role in at least some types of emotional learning, and the activation of NE release is facilitated by glucocorticoid secretion (Ferry et al., 1999). At least some participants with depression have abnormally elevated secretion of NE and cortisol, which in the presence of amygdala activation may conceivably increase the likelihood that sensory or social stimuli are perceived or remembered as emotionally arousing or aversive (reviewed in Drevets, 2003). The amygdala also plays an important role in organizing other emotional, behavioral, neuroendocrine, and autonomic aspects of emotional/ stress responses as well, potentially compatible with reports that amygdala CBF and metabolism correlate positively with ratings of depression severity that score emotional and neurovegetative aspects of the major depressive syndrome (Drevets et al., 1992; Drevets, Spitsnagel, and Raichle, 1995; Abercrombie et al., 1998; Drevets, Price, et al., 2002). For example, the amygdala facilitates stress-related corticotropin-releasing hormone (CRH) release (Herman and Cullinan, 1997) and electrical stimulation of the amygdala in humans increases cortisol secretion (Rubin et al., 1966), suggesting a mechanism via which excessive amygdala activity may play a role in inducing CRH hypersecretion in MDD (see Chapter 30 by Dunlop, Garlow, and Nemeroff). In PET studies of MDD and BPD, CBF and glucose metabolism in the left amygdala correlated positively with stressed plasma cortisol secretion, which may conceivably reflect either the effect of amygdala activity on CRH secretion or the effect of cortisol on amygdala function (Drevets, Price, et al., 2002). Abnormalities in Anatomically Related Limbic and Subcortical Structures The ventrolateral PFC, ACC, and OFC areas where metabolism is abnormal in depression share extensive interconnections with the amygdala, mediodorsal nucleus of the thalamus, and the ventromedial striatum (Öngür et al,

2003; Price et al., 1996). In the medial thalamus and ventral striatum, CBF and metabolism are abnormally increased in MDD and BPD depression and decrease during antidepressant drug treatment (Drevets et al., 1992; Drevets, Spitznagel, and Raichle, 1995; Videbech et al., 2001; Drevets, Thase, et al., 2002; Saxena et al., 2002; Wilson et al., 2002). In the dorsal caudate, in contrast, some depressed samples have shown abnormally decreased resting activity (Baxter et al., 1985; Schwartz et al., 1987; Drevets et al., 1992), while others showed abnormally increased activity (Brody et al., 2001). Finally, during exposure to positive or rewarding stimuli, participants with depression have shown blunted hemodynamic responses relative to controls in the ventral striatum (Tremblay et al., 2005; Epstein et al., 2006). Other Brain Areas Several groups reported abnormally increased CBF in the posterior cingulate cortex in MDD (e.g., Bench et al., 1993; Buchsbaum et al., 1997; Drevets, Bogers, and Raichle, 2002), and some showed that posterior cingulate flow and metabolism decreased during antidepressant treatment (Buchsbaum et al., 1997). Bench et al. (1993) specifically reported that the posterior cingulate flow in participants with depression correlated positively with anxiety ratings. Exposure to aversive stimuli of various types results in increased physiological activity in the posterior cingulate cortex (reviewed in Charney and Drevets, 2002). Nevertheless, Mayberg et al. (1999) reported that script-driven sadness resulted in decreased activity in participants who are healthy in the dorsal posterior cingulate cortex, and that flow also was decreased in the depressed relative to the remitted phase of MDD, raising the possibility that this large region is functionally heterogenous with respect to emotional processing. The posterior cingulate cortex appears to serve as a sensory association cortex and may participate in processing the affective salience of sensory stimuli. The posterior cingulate cortex sends major anatomical projections to the ACC, through which it may relay such information into the limbic circuitry (Öngür et al., 2003). Abnormally increased CBF has also been consistently reported in the medial cerebellum in MDD (e.g., Bench et al., 1992; Videbech et al., 2001). Flow increases in this region in experimentally induced anxiety or sadness in participants who are healthy and in participants with anxiety disorders (reviewed in George et al., 1995; Charney and Drevets, 2002). Activation of this structure during depression and anxiety may conceivably reflect either the activation of established anatomical loops between the cortex and cerebellum or the role of the paleocerebellum in modulating autonomic function. Regional CBF and metabolic abnormalities in other structures have been less consistently replicated. In the lateral temporal and inferior parietal cortex, some studies

31: NEUROIMAGING STUDIES

found reduced regional CBF and metabolism (e.g., Cohen et al., 1992; Drevets et al., 1992; Philpot et al., 1993; Biver et al., 1994). Some of these areas have been implicated in processing sensory information. Although the significance of reduced activity in such areas in depression remains unclear, it may conceivably relate to neuropsychological impairments associated with depression (Drevets and Raichle, 1998). Implications for Anatomical Circuits Related to Depression Because alterations in regional CBF and metabolism primarily reflect changes in local synaptic activity, interpreting the regional abnormalities in depression requires consideration of anatomical connectivity (Raichle, 1987; Drevets et al., 1992). The functional and structural imaging data in primary depression converge with evidence from lesion analysis studies to implicate circuits involving parts of the frontal and temporal lobes along with related parts of the striatum, pallidum, and thalamus in the pathophysiology of depression. For example, the findings in participants with MDD of abnormally increased CBF and metabolism in the ventrolateral and orbital PFC, ventral ACC, amygdala, ventral striatum, and medial thalamus implicate two interconnected circuits in the pathophysiology of depression: a limbicthalamo-cortical circuit involving the amygdala, mediodorsal nucleus of the thalamus (in the medial thalamus), and OMPFC; and a limbic-striatal-pallidal-thalamic (LCSPT) circuit involving related parts of the striatum and ventral pallidum as well as the components of the other circuit (Drevets et al., 1992). The amygdala and OMPFC are connected by excitatory projections with each other and with the mediodorsal nucleus of the thalamus, so increased metabolic activity in these structures would presumably reflect increased synaptic transmission through the limbic-thalamo-cortical circuit. It is noteworthy that neurosurgical procedures and deep brain stimulation that ameliorate treatment-resistant depression interrupt projections within these circuits (reviewed in Drevets et al., 1992; Mayberg et al., 2005). Within the LCSPT circuitry, the volumetric and histopathological changes found in the subgenual and pregenual ACC, lateral OFC, hippocampal subiculum, amygdala, and ventral striatum in MDD and BPD include a reduction in glial cells with no equivalent loss of neurons, loss of synaptic markers or proteins, elevated neuronal density, and reduced neuronal size, findings that would be consistent with a reduction in neuropil (Öngür et al., 1998; Baumann et al., 1999; Rajkowska et al., 1999; Cotter et al., 2002; Eastwood and Harrison, 2000; Bowley et al., 2002). Although the pathogenesis of these changes has not been established, notably the dendritic arbors that form the neuropil can, in some limbic and medial PFC structures, undergo atrophy or “remodel-

481

ing” during exposure to stress-induced elevations in excitatory amino acid (EAA) neurotransmitters and glucocorticoid secretion (McEwen, 1999). The targeted nature of the grey matter volume reductions to specific areas of the limbic-thalamo-cortical (LTC) and LCSPT circuits that show increased glucose metabolism is noteworthy because the glucose metabolic signal is dominated by glutamatergic transmission (Shulman et al., 2004). The reduction in metabolism in these regions during chronic antidepressant drug treatment may thus signal the attenuation of elevated glutamatergic transmission through this circuit. Notably, chronic antidepressant drug administration and repeated electroconvulsive shocks also desensitize N-methyl-D-aspartate (NMDA)glutamatergic receptors in the rat frontal cortex (Paul and Skolnick, 2003) and increase expression of neurotrophic and neuroprotective factors that may protect the cortex from continuing loss of neuropil (Manji et al., 2001). Functional Imaging Studies of Secondary Depression Transmission through these circuits may differ across depressive subtypes because the lesions involving the PFC (that is, tumors or infarctions) and the diseases of the basal ganglia (for example, Parkinson’s or Huntington’s disease) that are associated with increased risk for depression result in dysfunction at distinct points within these circuits that affect synaptic transmission in diverse ways (Table 31.5; reviewed in Starkstein and Robinson, 1989; Drevets and Todd, 1997). Consistent with this hypothesis, imaging studies of depressive syndromes arising secondary to neurological disorders have generally shown results that differ from those reported for primary mood disorders. For example, in contrast to the findings of increased CBF or metabolism in parts of the orbital cortex in primary participants with depression (Table 31.3), orbital cortex flow is reportedly decreased or not significantly different in participants with depressive syndromes arising secondary to Parkinson’s disease, Huntington’s disease, or basal ganglia infarction relative to participants with no depressive syndromes with the same illnesses (Table 31.5). Moreover, CBF and metabolism in the dorsolateral PFC generally have not differed between participants who are depressed with the above mentioned neurological conditions and nondepressed controls with the same conditions. Studies of the physiological correlates of depressive symptoms in participants who have primary psychiatric disorders other than mood disorders have generally reported abnormalities resembling those found in primary participants with depression. In bulimia nervosa, Andreason et al. (1992) reported a negative correlation between metabolism in the dorsolateral PFC and depression ratings (as reported in primary MDD by Baxter et al., 1989) while metabolism in the orbital

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31.5 Regional Blood Flow and Metabolic Abnormalities in the Ventral Prefrontal Cortex in Primary and Secondary Neuropsychiatric Syndromesa

TABLE

Primary

Secondary ⇓

Unipolar major depression

Authors (and Primary Diagnosis) Mayberg et al., 1990 (Parkinson’s D)c Mayberg et al., 1992 (Huntington’s D)c Ring et al., 1994 (Parkinson’s D)c

⇑b n.s.

Obsessive-compulsive disorder

Mayberg et al., 1991 (basal ganglia infarction)c

⇓

LaPlane et al., 1989 (basal ganglia lesions)e

n.s.

George et al., 1992 (Tourette’s syndrome)f

⇑d

D: disease; n.s: difference not significant. a. Additional studies of patients who had depressive symptoms but did not meet criteria for the major depressive syndrome are reviewed in the text. b. Cerebral blood flow (CBF) and metabolism generally increased in unmedicated, primary depressed patients vs. controls (Table 31.3). c. Comparison between depressed and nondepressed patients with the same illness. d. CBF and metabolism generally increased in unmedicated patients with primary obsessive-compulsive disorder relative to controls (Baxter et al., 1987; chap. 44). e. Patients with secondary obsessive-compulsive syndrome compared to healthy controls. f. Comparison between Tourette’s patients who manifest obsessions and compulsions vs. Tourette’s patients without such features.

cortex was abnormally elevated and inversely correlated with obsessive-compulsive ratings (similar to the relationships between posterior orbital CBF and obsession ratings in primary OCD; Rauch et al., 1994) and between orbital metabolism and depressive ideation ratings in primary MDD (Drevets, Spitznagel, and Raichle, 1995). In participants who were cocaine dependent and scanned within the first week of cocaine withdrawal as they experienced depressive symptoms and cocaine craving, glucose metabolism was elevated in the medial orbital cortex and basal ganglia relative to healthy controls (Volkow et al., 1991). Primary and secondary depressive syndromes may thus involve the same neural network, although the direction of the physiological abnormalities within individual structures may differ across conditions. This observation supports a circuitry-based model in which mood disorders are associated with dysfunctional interactions within limbic-cortical-striatal-pallidal-thalamic circuits, rather than increased or decreased activity within a single structure (Drevets and Todd, 1997). A common substrate in these cases may be the dysfunction of frontalstriatal modulation of limbic and visceral functions. The idiopathic, neuropathological changes evident in the OMPFC and ventral striatum in primary mood disorders (see above) and the degenerative processes found in conditions that can induce depressive syndromes (see above) have in common the disturbance of function within the OMPFC and striatum. This model also has relevance for considering the pathophysiology of neuropsychiatric syndromes that occur comorbidly with major depression. For example, neuroimaging studies implicate the same neural circuits in the pathophysiology of OCD, providing insights into the common coincidence of depressive and obsessional

syndromes (Drevets and Todd, 1997). Notably the differences found in the OFC between primary and secondary depression parallel the findings in primary and secondary obsessive-compulsive syndromes, in which OFC metabolism is increased in the former but decreased or unchanged in the latter (Table 31.5). NEURORECEPTOR IMAGING STUDIES OF DEPRESSION The development of neuroreceptor radioligands is providing expanding capabilities for noninvasive quantitation of in vivo receptor binding and dynamic neurotransmitter function. Such data complement neuropharmacological assessments performed postmortem. Although this area is expected to become an increasingly common application for PET and SPECT technology, studies conducted in mood disorders largely remain limited to assessments of monoaminergic receptor systems. Dopamine Receptor Imaging Neuroimaging studies have discovered abnormalities involving multiple aspects of the central dopaminergic system in depression, which converge with other types of evidence to implicate this system in the pathophysiology of mood disorders. With respect to dopamine (DA) D1 receptors, Suhara et al. (1992) reported that the binding of [11C]SCH-23990 was decreased in the frontal cortex of participants with BPD. In participants with MDD with anger attacks, Dougherty et al. (2006) found decreased striatal D1 receptor binding to [11C]SCH 23390. Both findings await replication using D1 receptor ligands that are more amenable to quantitation.

31: NEUROIMAGING STUDIES

483

FIGURE

31.5 Summary of neuroimaging abnormalities in early-onset, primary MDD. Regions where physiological imaging abnormalities have been replicated in unmedicated MDD samples are listed and approximately shown on this midsagittal brain diagram in which subcortical structures are highlighted onto the medial surface. Because only the medial wall of the cortex is shown, the location of the lateral orbital/ventrolateral PFC/anterior insular region is better illustrated in Figure 31.2B. The “ventral anterior cingulate” region refers to pregenual and subgenual portions (see text and Figure 31.3).

The arrows in front of each region name indicate the direction of resting state abnormalities in glucose metabolism in unmedicated, depressed MDD samples relative to healthy control samples. In some cases abnormalities in both directions have been reported that may depend either on the specific region involved or on the clinical state (for example, treatment responsive vs. nonresponsive—see text). The shaded regions have been shown to have histopathological and/or grey matter volumetric abnormalities in postmortem studies of primary mood disorders. PFC: prefrontal cortex; MDD: major depressive disorder.

Abnormal DA D2/D3 receptor binding also was reported in depression. Pearlson et al. (1995) showed that psychotic participants with BPD had increased striatal uptake of the DA D2/D3 receptor ligand, [11C]-N-methylspiperone, relative to healthy controls and nonpsychotic participants with BPD. In MDD, SPECT studies performed using 123I-iodobenzamide (IBZM), a DA D2/ D3 receptor ligand that is sensitive to endogenous DA concentrations, found increased striatal uptake during the depressed phase (D’haenen and Bossuyt, 1994; P.J. Shah et al., 1997), which potentially may reflect a reduction in endogenous DA release. Ebert et al. (1996) also found increased striatal DA D2/D3 receptor availability in participants with depression with psychomotor slowing, and Shah et al. (1997) reported that striatal [123I]-IBZM binding correlated inversely with movement speed and verbal fluency measures. Other preliminary PET data appear compatible with the hypothesis that DA release is reduced in MDD. Meyer et al. (2001) found decreased DA transporter binding in participants with MDD versus controls, which may reflect a compensatory response to reduced DA release. Moreover, Ågren et al. (1993) found abnormally reduced brain uptake of the catecholamine precursor [11C]L-DOPA in MDD, suggesting that DA

synthesis is reduced in depression, consistent with observations that CSF homovanillic acid concentrations are reduced in MDD (Fig. 31.5). Serotonin Receptor Imaging Within the serotonin system, the pre- and postsynaptic serotonin type 1A (5-HT1A) receptor binding is abnormally decreased in most, but not all, studies of MDD and BPD, and in participants with depression with temporal lobe epilepsy (Drevets et al., 2007). The reduction in 5-HT1A receptor binding was demonstrated using PET and [carbonyl-11C]WAY-100635 in the raphé, hippocampus, amygdala, temporopolar cortex, insula, anterior and posterior cingulate cortex, and left OFC (Drevets et al., 1999; Drevets et al., 2007) (Fig. 31.6). The magnitudes of these differences have been similar to those found postmortem in studies of primary MDD samples or depressed, nonalcoholic victims of suicides. These data also were compatible with evidence that unmedicated participants with MDD show blunted thermic and endocrine responses to 5-HT1A receptor agonist challenge (reviewed in Drevets et al., 1999). Treatment with SSRI did not alter the changes in 5-HT1A receptor BP in any area (reviewed in Drevets et al., 2007).

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FIGURE 31.6 Transverse images of 5-HT type 1A receptor binding potential obtained using PET and [carbonyl-11C]WAY100635 in a young male with bipolar disorder and a healthy control male (see text). The full study for which these images were obtained demonstrated reduced 5-HT1A receptor binding in depressed patients versus

controls in brain regions where these receptors are expressed postsynaptically (for example, mesiotemporal cortex) and presynaptically (for example, raphé) (Drevets et al., 1999). PET: positron emission tomography. Reproduced from Journal of the American Medical Association 287(14):1787–1788.

Neuroimaging studies of other 5-HT binding sites found less consistent differences in depression. One study reported reduced 5-HT2A receptor binding in the hippocampus in depressed participants with MDD versus controls (Sheline et al., 2004), although other studies found no significant difference between participants with depression and controls when age effects were controlled (Meltzer et al., 1999; Meyer et al., 1999). In contrast, several studies conducted postmortem in victims of suicide reported increases in 5-HT2A receptor binding relative to nonsuicide controls (reviewed in Stockmeier, 2003). Neuroreceptor imaging and postmortem histochemical studies also reported abnormalities of 5-HTT binding in mood disorders (Stockmeier, 2003). Studies performed using 5-HTT radioligands with high selectivity for 5-HTT sites, such as [11C]DASB, reported abnormally increased 5-HTT binding in the striatum, thalamus, insula, and ACC in participants with early-onset MDD (Cannon et al., 2007) and/or in participants with MDD with negativistic attitudes (Meyer et al., 2004).

Similarly depressed participants with BPD showed elevated 5-HTT binding in the striatum, thalamus, and insula, along with reduced binding in the vicinity of the pontine raphé. Of studies that used the less selective 5HTT radioligands, [11C](+)McN5652 or [123I]βCIT, some also found abnormally increased 5-HTT binding in the thalamus (Ichimiya et al., 2002), PFC, and ACC (Reivich et al., 2004), but others found reduced 5-HTT binding in the amygdala and/or midbrain in MDD (Malison et al., 1998; Parsey et al., 2006), or reduced binding in thalamus, midbrain, putamen, amygdala, hippocampus, and ACC in BPD (Oquendo et al., 2007). Whether differences in the selectivity of these radiotracers accounts for the discrepant findings across studies remains unclear. CONCLUDING REMARKS The convergent results from studies of mood disorders conducted using neuroimaging, lesion analysis, and postmortem techniques support a model in which the signs

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and symptoms of major depression emanate from dysfunction within circuits involving the OMPFC, temporal lobe, striatum, and brain stem that normally modulate emotional behavior. Antidepressant therapies may compensate for this dysfunction by attenuating the pathological limbic activity that mediates such symptoms (Drevets, Bogers, and Raichle, 2002; Drevets, Thase, et al., 2002), and by increasing genetic transmission of neurotrophic factors that exert neuroplastic effects within the pathways modulating emotional expression (Manji et al., 2001).

REFERENCES Abercrombie, H.C., Schaefer, S.M., Larson, C.L., Oakes, T.R., Lindgren, K.A., Holden, J.E., Perlman, S.B., Turski, P.A., Krahn, D.D., Benca, R.M., and Davidson, R.J. (1998) Metabolic rate in the right amygdala predicts negative affect in depressed patients. Neuroreport 9(14):3301–3307. Ågren, H., Reibring, L., Hartvig, P., Tedroff, J., Bjurling, P., Lundqvist, H., and Långström, B. (1993) Monoamine metabolism in human prefrontal cortex and basal ganglia. PET studies using [11C]L-hydroxytryptophan and [11C]L-DOPA in healthy volunteers and patients with unipolar depression. Depression 1:71–81. Altschuler, L.L., Bartzokis, G., Thomas, G., Curran, J., and Mintz, J. (1998) Amygdala enlargement in bipolar disorder and hippocampal reduction in schizophrenia: an MRI study demonstrating neuroanatomic specificity. Arch. Gen. Psychiatry 55:663–664. Altschuler, L.L., Conrad, A., Hauser, P., et al. (1991) Reduction of temporal lobe volume in bipolar disorder: a preliminary report of magnetic resonance imaging. Arch. Gen. Psychiatry 48:482– 483. American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Amsterdam, J.D., Marinelli, D.L., Arger, P., et al. (1987) Assessment of adrenal gland volume by computed tomography in depressed patients and healthy volunteers: a pilot study. Psychiatry Res. 21:3 84–387. Andreason, P.J., Altemus, M.S., Zametkin, A.J., King, A.C., Lucinio, J., and Cohen, R.M. (1992) Regional cerebral glucose metabolism in bulimia nervosa. Am. J. Psychiatry 149:1506–1513. Ashtari, M., Greenwald, B.S., Kramer-Ginsberg, E., Hu, J., Wu, H., Patel, M., Aupperle, P., and Pollack, S. (1999) Hippocampal/ amygdala volumes in geriatric depression. Psychol. Med. 29: 629–638. Awad, I.A., Johnson, P.C., Spetzler, R.J., et al. (1986) Incidental subcortical lesions identified on magnetic resonance imaging in the elderly, II: Postmortem pathological correlations. Stroke 17:1090–1097. Awad, I.A., Spetzler, R.F., Hodak, J.A., et al. (1986) Incidental subcortical lesion identified on magnetic resonance imaging in the elderly: I. Correlation with age and cerebrovascular risk factor. Stroke 17:1084 –1089. Axelson, D., Doraiswamy, P.M., McDonald, W.M., et al. (1993) Hypercortisolemia and amygdala hippocampal changes in depression. Psychiatry Res. 47:167–173. Aylward, E.H., Roberts-Twillie, J.V., Barta, P.E., et al. (1994) Basal ganglia volumes and white matter hyperintensities in patients with bipolar disorder. Am. J. Psychiatry 151:687–693. Baumann, B., Danos, P., Krell, D., Diekmann, S., Leschinger, A., Stauch, R., Wurthman, C., Bernstein, H.-G., and Bogerts, B. (1999) Reduced volume of limbic system-affiliated basal ganglia in mood disorders: preliminary data from a post mortem study. J. Neuropsych. Clin. Neurosci. 11(1):71–78. Baxter, L.R., Phelps, M.E., Mazziotta, J.C., Guze, B.H., Schwartz, J.M., and Selin, C.E. (1987) Local cerebral glucose metabolic

485

rates in obsessive-compulsive disorder. Arch. Gen. Psychiatry 44: 211–218. Baxter, L.R., Phelps, M.E., Mazziotta, J.C., Schwartz, J.M., Gerner, R.H., Selin, C.E., and Sumida, R.M. (1985) Cerebral metabolic rates for glucose in mood disorders. Arch. Gen. Psychiatry 42: 441– 447. Baxter, L.R., Schwartz, J.M., Phelps, M.E., Mazziota, J.C., Guze, B.H., Selin, C.E., Gerner, R.H., and Sumida, R.M. (1989) Reduction of prefrontal cortex glucose metabolism common to three types of depression. Arch. Gen. Psychiatry 46:243–250. Bench, C.J., Friston, K.J., Brown, R.G., Frackowiak, R.S., and Dolan, R.J. (1993) Regional cerebral blood flow in depression measured by positron emission tomography: the relationship with clinical dimensions. Psychol. Med. 23:579–590. Bench, C.J., Friston, K.J., Brown, R.G., Scott, L.C., Frackowiak, S.J., and Dolan, R.J. (1992) The anatomy of melancholia - focal abnormalities of cerebral blood flow in major depression. Psychol. Med. 22:607– 615. Benes, F.M., Vincent, S.L., and Todtenkopf, M. (2001) The density of pyramidal and nonpyramidal neurons in anterior cingulate cortex of schizophrenic and bipolar subjects. Biol. Psychiatry 50(6): 395– 406. Beyer, J.L., Taylor, W.D., MacFall, J.R., Kuchibhatla, M., Payne, M.E., Provenzale, J.M., Cassidy, F., and Krishnan, K.R. (2005) Cortical white matter microstructural abnormalities in bipolar disorder. Neuropsychopharmacology 30(12):2225–2229. Biver, F., Goldman, S., Delvenne, V., Luxen, A., DeMaertelaer, V., Hubain, P., Mendlewicz, J., and Lotstra, F. (1994) Frontal and parietal metabolic disturbances in unipolar depression. Biol. Psychiatry 36:381–388. Blumberg, H.P., Donegan, N.H., et al. (2005) Preliminary evidence for medication effects on functional abnormalities in the amygdala and anterior cingulate in bipolar disorder. Psychopharmacology (Berl) 183(3):308–313. Blumberg, H.P., Kaufman, J., Martin, A., Whiteman, R., Zhang, J.H., Gore, J.C., Charney, D.S., Krystal, J.H., and Peterson, B.S. (2003) Amygdala and hippocampal volumes in adolescents and adults with bipolar disorder. Arch. Gen. Psychiatry 60(12):1201– 1208. Bonne, O., Krausz, Y., Shapira, B., Bocher, M., Karger, H., Gorfine, M., Chisin, R., and Lerer, B. (1996) Increased cerebral blood flow in depressed patients responding to electroconvulsive therapy. J. Nucl. Med. 37:1075–1080. Botteron, K.N., Raichle, M.E., Drevets, W.C., Heath, A.C., and Todd, R.D. (2002) Volumetric reduction in left subgenual prefrontal cortex in early onset depression. Biol. Psychiatry 51(4):342–344. Bowley, M.P., Drevets, W.C., Öngür, D., and Price, J.L. (2002) Low glial numbers in the amygdala in mood disorders. Biol. Psychiatry 52(5): 404 – 41. Bremner, J.D., Innis, R.B., Salomon, R.M., Staib, L.H., Ng, C.K., Miller, H.L., et al. (1997) Positron emission tomography measurement of cerebral metabolic correlates of tryptophan depletioninduced depressive relapse. Arch. Gen. Psychiatry 54:364 –374. Bremner, J.D., Narayan, M., Anderson, E.R., Staib, L.H., Miller, H.L., and Charney, D.S. (2000) Hippocampal volume reduction in major depression. Am. J. Psychiatry 157:115–118. Brody, A.L., Saxena, S., Stoessel, P., Gillies, L.A., Fairbanks, L.A., Alborzian, S., Phelps, M.E., Huang, S.C., Wu, H.M., Ho, M.L., Ho, M.K., Au, S.C., Maidment, K., and Baxter, L.R. (2001) Regional brain metabolic changes in patients major depressive disorder from pre- to post-treatment with paroxetine. Arch. Gen. Psychiatry 58:631–640. Brown, F.W., Lewine, R.J., Hudgins, P.A., et al. (1992) White matter hyperintensity signals in psychiatric and nonpsychiatric subjects. Am. J. Psychiatry 149:620–625. Buchsbaum, M.S., Wu, J., Siegel, B.V., Hackett, E., Trenary, M., Abel, L., and Reynolds, C. (1997) Effect of sertraline on regional meta-

486

MOOD DISORDERS

bolic rate in patients with affective disorder. Biol. Psychiatry 41: 15–22. Canli, T., Zhao, Z., Brewer, J., Gabrieli, J.D., and Cahill, L. (2000) Event-related activation in the human amygdala associates with later memory for individual emotional experience. J. Neurosci. 20:RC99. Cannon, D.M., Ichise, M., Rollis, D., Klaver, J.M., Gandhi, S.K., Charney, D.S., Manji, H.K., and Drevets, W.C. (2007) Elevated serotonin transporter binding in major depressive disorder assessed using [11C]DASB and positron emission tomography: comparison with bipolar disorder. Biol. Psychiatry 62(8):870–877. Charney, D.S., and Drevets, W.C. (2002) The neurobiological basis of anxiety disorders. In: Davis, K., Charney, D.S., Coyle, J., Nemeroff, C.B. eds. The Fifth Generation of Progress. Psychopharmacology. New York: Lippencott, Williams and Wilkins, pp. 901–930. Chen, C.H., Ridler, K., et al. (2007) Brain imaging correlates of depressive symptom severity and predictors of symptom improvement after antidepressant treatment. Biol. Psychiatry 62(5):407– 414. Chimowitz, M.I., Estes, M.L., Furlan, A.J., et al. (1992) Further observations on the pathology, 1992 of subcortical lesions identified on magnetic resonance imaging. Arch. Neurol. 49:747–752. Coffey, C.E., Figiel, G.S., Djang, W.T., et al. (1988) Leukoencephalopathy in elderly depressed patients referred for ECT. Biol. Psychiatry 24:143–161. Coffey, C.E., Figiel, G.S., Djang, W.T., et al. (1990) Subcortical hyperintensity on magnetic resonance imaging: a comparison of normal and depressed elderly subjects. Am. J. Psychiatry 147:187– 189. Coffey, C.E., Wilkinson, W.E., Weiner, R.D., et al. (1993) Quantitative cerebral anatomy in depression. A controlled magnetic resonance imaging study. Arch. Gen. Psychiatry 50:7–16. Cohen, R.M., Gross, M., Nordahl, T.E., Semple, W.E., Oren, D.A., and Rosenthal, N. (1992) Preliminary data on the metabolic brain pattern of patients with winter seasonal affective disorder. Arch. Gen. Psychiatry 49:545–552. Coryell, W., Nopoulos, P., Drevets, W.C., and Andreasen, N.C. (2005) Subgenual PFC volumes in MDD and schizophrenia: diagnostic specificity and prognostic implications. Am. J. Psychiatry 162:1706–1712. Cotter, D., Mackay, D., Chana, G., Beasley, C., Landau, S., and Everall, I. (2002) Reduced neuronal size and glial cell density in Area 9 of the dorsolateral prefrontal cortex in subjects with major depressive disorder. Cereb. Cortex 12:386–394. Damasio, A.R. (1994) Descarte’s Error: Emotion, Reason, and the Human Brain. New York: G.P. Putnam. DelBello, M.P., Zimmerman, M.E., Mills, N.P., Getz, G.E., and Strakowski, S.M. (2004) Magnetic resonance imaging analysis of amygdala and other subcortical brain regions in adolescents with bipolar disorder. Bipolar Disord. 6:43–52. D’haenen, H.A., and Bossuyt, A. (1994) Dopamine D2 receptors in depression measured with single photon emission computed tomography. Biol. Psychiatry 35:128–132. DiRocco, R.J., et al. (1989) The relationship between CNS metabolism and cytoarchitecture: a review of 14C-deoxyglucose studies with correlation to cytochrome oxidase histochemistry. Comput. Med. Imaging Graph. 13:81–92. Dolan, R.J., Bench, C.J., Brown, R.G., Scott, L.C., and Frackowiak, R.S.J. (1994) Neuropsychological dysfunction in depression: the relationship to regional cerebral BF. Psychol. Med. 24:849–857. Dolan, R.J., Bench, C.J., Liddle, P.F., et al. (1993) Dorsolateral prefrontal cortex dysfunction in the major psychoses: symptom or disease specificity? J. Neurol. Neurosurg. Psychiatry 56:1290–1294. Dolan, R.J., Fletcher, P., Morris, J., Kapur, N., Deakin, J.F., and Frith, C.D. (1996) Neural activation during covert processing of positive emotional facial expressions. Neuroimage. 4(3 Pt 1):194 –200. Dougherty, D.D., et al. (2006) Decreased striatal D1 binding as measured using PET and [11C]SCH 23,390 in patients with major depression with anger attacks. Depress. Anxiety 23(3):175–177.

Drevets, W.C. (1993) Brain imaging in psychiatry. In: Sierles, F.S., ed. Behavioral Science for Medical Students. Baltimore: Williams and Wilkins, pp. 212–235. Drevets, W.C. (1994) Geriatric depression: brain imaging correlates and pharmacologic considerations. J. Clin. Psychiatry 55:71–81. Drevets, W.C. (2001) Neuroimaging and neuropathologial studies of depression: implications for the cognitive emotional manifestations of mood disorders. Curr. Opin. Neurobiol. 11:240–249. Drevets, W.C. (2003) Neuroimaging abnormalities in the amygdala in mood disorders. In: The Amygdala in Brain Function: Basic and Clinical Approaches. Annals of the New York Academy of Sciences. New York: New York Academy of Sciences, pp. 959–967. Drevets, W.C., Bogers, W., and Raichle, M.E. (2002) Functional anatomical correlates of antidepressant drug treatment assessed using PET measures of regional glucose metabolism. Eur. J. Neuropharmacol. 12(6):527–544. Drevets, W.C., and Botteron, K. (1997) Neuroimaging in psychiatry. In: Guze, S.B., ed.. Adult Psychiatry. St. Louis, MO: Mosby Press, pp. 53–81. Drevets, W.C., Burton, H., Simpson, J.R., Videen, T.O., Snyder, A.Z., and Raichle, M.E. (1995) Blood flow changes in human somatosensory cortex during anticipated stimulation. Nature 373:249–252. Drevets, W.C., Frank, E., Price, J.C., Kupfer, D.J., Holt, D., Greer, P.J., Huang, H., Gautier, C., and Mathis, C. (1999) PET imaging of serotonin 1A receptor binding in depression. Biol. Psychiatry 46(10):1375–1387. Drevets, W.C., Gautier, C., Lowry, T., Bogers, W., Greer, P., and Kupfer, D.J. (2001) Abnormal hemodynamic responses to facially expressed emotion in major depression. Soc. Neurosci. Abstr. 31. Drevets, W.C., Öngür, D., and Price, J.L. (1998) Neuroimaging abnormalities in the subgenual prefrontal cortex: implications for pathophysiology of familial mood disorders. Mol. Psychiatry 3(3):220–226. Drevets, W.C., Price, J.L., Bardgett, M.E., Reich, T., Todd, R., and Raichle, M.E. (2002) Glucose metabolism in the amygdala in depression: relationship to diagnostic subtype and stressed plasma cortisol levels. Pharmacol. Biochem. Behav. 71:431–447. Drevets, W.C., Price, J.L., Simpson, J.R., Todd, R.D., Reich, T., Vannier, M., and Raichle, M.E. (1997) Subgenual prefrontal cortex abnormalities in mood disorders. Nature 386:824–827. Drevets, W.C., and Raichle, M.E. (1992) Neuroanatomical circuits in depression: implications for treatment mechanisms. Psychopharm. Bull. 28:26l–274. Drevets, W.C., and Raichle, M.E. (1998) Reciprocal suppression of regional cerebral blood flow during emotional versus higher cognitive processes: implications for interactions between emotion and cognition. Cognition and Emotion 12(3):353–385. Drevets, W.C., Simpson, J.R., and Raichle, M.E. (1995) Regional blood flow changes in response to phobic anxiety and habituation. J. Cereb. Blood Flow Metab. 15(1):S856. Drevets, W.C., Spitznagel, E., and Raichle, M.E. (1995) Functional anatomical differences between major depressive subtypes. J. Cereb. Blood Flow Metab. 15(1):S93. Drevets, W.C., Thase, M., Moses-Kolko, E., Price, J.C., Frank, E., Kupfer, D.J., and Mathis, C.A. (2007) Serotonin-1A receptor imaging in recurrent depression: replication and literature review. Nuc. Med. Biol. 34(7):865–878. Drevets, W.C., Thase, M., Price, J.C., Bogers, W., Greer, P.J., and Kupfer, D.K. (2002) Antidepressant drug effects on regional glucose metabolism in major depression. Soc. Neurosci. Abstr. 32. Drevets, W.C., and Todd, R.D. (1997) Depression, mania and related disorders. In: Guze, S.B., ed. Adult Psychiatry. St. Louis, MO: Mosby Press, pp. 99–141. Drevets, W.C., Videen, T.O., Price, J.L., Preskorn, S.H., Carmichael, S.T., and Raichle, M.E. (1992) A functional anatomical study of unipolar depression. J. Neuroscience 12:3628–3641.

31: NEUROIMAGING STUDIES Dupont, R.M., Jernigan, T.L., Butters, N., et al. (1990) Subcortical abnormalities detected in bipolar affective disorder using magnetic resonance imaging: clinical and neuropsychological significance. Arch. Gen. Psychiatry 47:55–59. Dupont, R.M., Jernigan, T.L., Gillin, J.C., et al. (1987) Subcortical signal hyperintensities in bipolar patients detected by MRI. Psychiatry Res. 21:357–358. Dupont, R.M., Jernigan, T.L., Heindel, W., et al. (1995) Magnetic resonance imaging and mood disorders - Localization of white matter and other subcortical abnormalities. Arch. Gen. Psychiatry 52:747–755. Eastwood, S.L., and Harrison, P.J. (2000): Hippocampal synaptic pathology in schizophrenia, bipolar disorder, and major depression: a study of complexin mRNAs. Mol. Psychiatry 5:425– 432. Ebert, D., Feistel, H., and Barocka, A. (1991) Effects of sleep deprivation on the limbic system and the frontal lobes in affective disorders: a study with Pc-99m-HMPAO SPECT. Psychiatry Res. Neuroimaging 40:247–251. Ebert, D., Feistel, H., Loew, T., and Pirner, A. (1996): Dopamine and depression-striatal dopamine D2 receptor SPECT before and after antidepressant therapy. Psychopharmacology 126:91–94. Elkis, H., Friedman, L., Wise, A., et al. (1995) Meta-analyses of studies of ventricular enlargement and cortical sulcal prominence in mood disorders - Comparisons with controls or patients with schizophrenia. Arch. Gen. Psychiatry 52:735–746. Elliott, R., Friston, K. J., et al. (2000) Dissociable neural responses in human reward systems. J. Neurosci. 20(16):6159–6165. Epstein, J., Pan, H., et al. (2006) Lack of ventral striatal response to positive stimuli in depressed versus normal subjects. Am. J. Psychiatry 163(10):1784–1790. Escalona, P.R., McDonald, W.M., Doraiswamy, P.M., et al. (1993) Reduction of cerebellar volume in major depression: a controlled MRI study. Depression 1:156–158. Fazekas, F. (1989) Magnetic resonance signal abnormalities in asymptomatic individuals: their incidence and functional correlates. Eur. Neurol. 29:164–168. Ferry, B., Roozendaal, B., and McGaugh, J.L. (1999) Role of norepinephrine in mediating stress hormone regulation of long- term memory storage: a critical involvement of the amygdala. Biol. Psychiatry 46:1140–1152. Figiel, G.S., Coffey, C.E., Djang, W.T., et al. (1990) Brain magnetic resonance imaging findings in ECT induced delirium. J. Neuropsychiatry 2:53–58. Figiel, G.S., Krishnan, K.R.R., Breitner, J.C., et al. (1989) Radiologic correlates of antidepressant induced delirium: the possible significance of basal ganglia lesion. J. Neuropsychiatry 1:188–190. Figiel, G.S., Krishnan, K.R.R., Doraiswamy, P.M., et al. (1991) Subcortical hyperintensities on brain magnetic resonance imaging: a comparison between late age onset and early onset elderly depressed subjects. Neurobiol. of Aging 26:245–247. Frodl, T., Meisenzahl, E.M., Zetzsche, T., Hohne, T., Banac, S., Schorr, C., et al. (2004) Hippocampal and amygdala changes in patients with major depressive disorder and healthy controls during a 1year follow-up. J. Clin. Psychiatry 65:492– 499. Fujikawa, T., Yamawaki, S., and Touhouda, Y. (1993) Incidence of silent cerebral infarction in patients with major depression. Stroke 24:1631–1634. Fujikawa, T., Yamawaki, S., and Touhouda, Y. (1994) Background factors and clinical symptoms of major depression with silent cerebral infarction. Stroke 25:798–801. Fujikawa, T., Yokota, N., Muraoka, M., et al. (1996) Response of patients with major depression and silent cerebral infarction to antidepressant drug therapy, with emphasis on central nervous system adverse effects. Stroke 27:2040–2042. George, M.S., Ketter, T.A., Parekh, P.I., Horwitz, B., Herscovitch, P., and Post, R.M. (1995) Brain activity during transient sadness and happiness in healthy women. Am. J. Psychiatry 152:341–351.

487

George, M.S., Trimble, M.R., Costa, D.C., Robertson, M.M., Ring, H.A., and Ell, P.J. (1992) Elevated frontal CBF in Gilles de la Tourette syndrome: a 99Tcm-HMPAO SPECT study. Psychiatry Res. 45:143–151. Gerard, G., and Weisberg, L.A. (1986) MRI periventricular lesions in adults. Neurology 36:998–1001. Goodwin, G.M., Austin, M.P., Dougall, N., Ross, M., Murray, C., O’Carroll, R.E., Moffoot, A., Prentice, N., and Ebmeier, K.P. (1993) State changes in brain activity shown by the uptake of 99mTcexametazine with SPET in major depression before and after treatment. J. Affect. Disord. 29:243–253. Greenwald, B.S., et al. (1998) Neuroanatomic localization of magnetic resonance imaging signal hyperintensities in geriatric depression. Stroke 29(3):613–617. Greenwald, B.S., Kramerginsberg, E., Krishnan, K.R.R., et al. (1996) MRI signal hyperintensities in geriatric depression. Am. J. Psychiatry 153:1212–1215. Harvey, I., Persaud, R., Ron, M.A., and Murray, R.M. (1994) Volumetric MRI measurements in bipolars compared with schizophrenics and healthy controls. Psychol. Med. 24(3):689–699. Hasler, G., Fromm, S., Carlson, P.J., Luckenbaugh, D.A., Waldeck, T., Geraci, M., Roiser, J.P., Neumeister, A., Meyers, N., Charney, D.S., and Drevets, W.C. (2008) Neural response to catecholamine depletion in unmedicated, remitted subjects with major depressive disorder and healthy subjects. Archives of General Psychiatry, in press. Hauser, P., Altschuler, L.L., Berrettini, W., et al. (1989) Temporal lobe measurement in primary affective disorder by magnetic resonance imaging. J. Neuropsychiatry Clin. Neurosci. 1:128–134. Herholz, K., Heindel, W., Rackl, A., et al. (1990) Regional cerebral blood in patients with leuko-araiosis and atherosclerotic carotid artery disease. Arch. Neurol. 47:392–396. Herman, J.P., and Cullinan, W.E. (1997) Neurocircuitry of stress: central control of the hypothalamo-pituitary-adrenocortical axis. Trends Neurosci. 20(2):78–84. Hickie, I., Scott, E., Mitchell, P., et al. (1995) Subcortical hyperintensities on magnetic resonance imaging: clinical correlates and prognostic significance in patients with severe depression. Biol. Psychiatry 37:151–160. Hirayasu, Y., Shenton, M.E., Salisbury, D.F., Kwon, J.S., Wible, C.G., Fischer, I.A., Yurgelun-Todd, D., Zarate, C., Kikinis, R., Jolesz, F.A., and McCarley, R.W. (1999) Subgenual cingulate cortex volume in first-episode psychosis. Am. J. Psychiatry 156:1091–1093. Husain, M.M., McDonald, W.M., Doraiswamy, P.M., et al. (1991) A magnetic resonance imaging study of putamen nuclei in major depression. Psychiatry Res. 40:95–99. Ichimiya, T., Suhara, T., Sudo, Y., Okubo, Y., Nakayama, K., Nankai, M., et al. (2002) Serotonin transporter binding in patients with mood disorders: a PET study with [11C](+)McN5652. Biol. Psychiatry 51:715–722. Iidaka, T., Nakajima, T., Kawamoto, K., et al. (1996) Signal hyperintensities on brain magnetic resonance imaging in elderly depressed patients. Eur. Neurol. 36:293–299. Johnstone, E.C., Owens, D.G., Crow, T.J., et al. (1989) Temporal lobe structure as determined by nuclear magnetic resonance in schizophrenia and bipolar affective disorder. J. Neurol. Neurosurg. Psychiatry 52:736–741. Kennedy, S.H., Evans, K.R., Kruger, S., Mayberg, H.S., Meyer, J.H., McCann, S., Arifuzzman, A.I., Houle, S., and Vaccarino, F.J. (2001) Changes in regional brain glucose metabolism measured with PET after paroxetine treatment of major depression. Am. J. Psychiatry 158:899–905. Ketter, T.A., Kimbrell, T.A., George, M.S., Dunn, R.T., Speer, A.M., Benson, B.E., et al. (2001) Effects of mood and subtype on cerebral glucose metabolism in treatment-resistant bipolar disorder. Biol. Psychiatry 49:97–109. Kimbrell, T.A., Ketter, T.A., George, M.S., Little, J.T., Benson, B.E., Willis, M.W., Herscovitch, P., and Post, R.M. (2002) Regional

488

MOOD DISORDERS

cerebral glucose utilization in patients with a range of severities of unipolar depression. Biol. Psychiatry 51:237–252. Kobari, M., Meyer, J.S., and Ichijo, M. (1990) Leuko-araiosis, cerebral atrophy, and cerebral perfusion in normal aging. Arch. Neurol. 47:161–165. Krishnan, K.R.R., Doraiswamy, P.M., Figiel, G.S., et al. (1991) Hippocampal abnormalities in depression. J. Neuropsychiatry Clin. Neurosci. 3:387–391. Krishnan, K.R.R., Doraiswamy, P.M., Lurie, S.N., et al. (1991) Pituitary size in depression. J. Clin. Endocrinol. Metab. 72:256–259. Krishnan, K.R.R., Goli, V., Ellinwood, E.H., et al. (1988) Leukoencephalopathy in patients diagnosed as major depressive. Biol. Psychiatry 23:519–522. Krishnan, K.R.R., McDonald, W.M., Doraiswamy, P.M., et al. (1993) Neuroanatomical substrates of depression in the elderly. Eur. Arch. Psychiatry Neurosci. 243:41–46. Krishnan, K.R.R., McDonald, W.M., Escalona, P.R., et al. (1992) Magnetic resonanace imaging of the caudate nuclei in depression: Preliminary observations Arch. Gen. Psychiatry 49:553–557. Kumar, A., Schweizer, E., Jin, Z.S., et al. (1997) Neuroanatomical substrates of late-life minor depression - A quantitative magnetic resonance imaging study. Arch. Neurology 54:613–617. Lai, T., Payne, M.E., Byrum, C.E., Steffens, D.C., and Krishnan, K.R. (2000) Reduction of orbital frontal cortex volume in geriatric depression. Biol. Psychiatry 48(10):971–975. LaPlane, D., Levasseur, M., Pillon, B., Dubois, B., Baulac, M., Mazoyer, B., Tran Dinh, S., Sette, G., Danze, F., and Baron, J.C. (1989) Obsessive-compulsive and other behavioral changes with bilateral basal ganglia lesions. Brain 112:699–725. Lawrence, N.S., Williams, A. M., et al. (2004) Subcortical and ventral prefrontal cortical neural responses to facial expressions distinguish patients with bipolar disorder and major depression. Biol. Psychiatry 55(6):578–587. Lesser, I.M., Boone, K.B., Mehringer, C.M., et al. (1996) Cognition and white matter hyperintensities in older depressed patients. Am. J. Psychiatry 153:1280–1287. Lesser, I.M., Mena, I., Boone, K.B., Miller, B.L., Mehringer, C.M., and Mohl, M. (1994) Reduction of cerebral blood flow in older depressed patients. Arch. Gen. Psychiatry 51:677–686. Lesser, I.M., Miller, B.L., Boone, K.B., et al. (1991) Brain injury and cognitive function in late-onset psychotic depression. J. Neuropsychiatry Clin. Neurosci. 3:33– 40. Li, L., Ma, N., Li, Z., Tan, L., Liu, J., Gong, G., Shu, N., He, Z., Jiang, T., and Xu, L. (2007) Prefrontal white matter abnormalities in young adult with major depressive disorder: A diffusion tensor imaging study. Brain Res. 1168:124 –128. Lyoo, I. K., et al. (2004) Frontal lobe gray matter density decreases in bipolar I disorder. Biol. Psychiatry 55:648–651. MacFall, J.R., Payne, M.E., Provenzale, J.E., and Krishnan, K.R.R. (2001) Medial orbital frontal lesions in late onset depression. Biol. Psychiatry 49:803–806. Maes, M., Dierckx, R., Meltzer, H., Ingels, M., Schotte, C., Vandewoude, M., Calabrese, J., and Cosyns, P. (1993) Regional cerebral blood flow in unipolar depression measured with Tc-99m-HMPAO SPECT: negative findings. Psychiatry Res./Neuroimaging 50:77–88. Malison, R.T., Price, L.H., Berman, R., van Dyck, C.H., Pelton, G.H., Carpenter, L., et al. (1998) Reduced brain serotonin transporter availability in major depression as measured by [123I]-2 betacarbomethoxy-3 beta-(4-iodophenyl)tropane and single photon emission computed tomography. Biol. Psychiatry 44:1090–1098. Manji, H., Drevets, W.C., and Charney, D. (2001) The cellular neurobiology of depression. Nat. Medi. 7(5):541–547. Mayberg, H.S., Brannan, S.K., Mahurin, R.K., Jerabek, P.A., Brickman, J.S., Tekell, J.L., Silva, J.A., McGinnis, S., Glass, T.G., Martin, C.C., and Fox, P.T. (1997) Cingulate function in depression: a potential predictor of treatment response. Neuroreport 8:1057–1061. Mayberg, H.S., Brannan, S.K., Tekell, J.L., Silva, J.A., Mahurin, R.K., McGinnis, S., and Jerabek, P.A. (2000) Regional metabolic

effects of fluoxetine in major depression: serial changes and relationship to clinical response. Biol. Psychiatry 48:830–843. Mayberg, H.S., Liotti, M., Brannan, S.K., McGinnis, B.S., Mahurin, R.K., Jerabek, P.A., et al. (1999) Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am. J. Psychiatry 156:675–682. Mayberg, H.S., Lozano, A.M., Voon, V., McNeeley, H.E., Seminowicz, D., Hamani, C., Schwalb, J. M., and Kennedy, S.H. (2005) Deep brain stimulation for treatment-resistant depression. Neuron 45: 651–660. Mayberg, H.S., Starkstein, S.E., Morris, P.L., et al. (1991) Remote cortical hypometabolism following focal basal ganglia injury: relationship to secondary changes in mood. Neurology 41(Suppl): 266. Mayberg, H.S., Starkstein, S.E., Peyser, C.E., Brandt, J., Dannals, R.F., and Folstein, S.E. (1992) Paralimbic frontal lobe hypometabolism in depression associated with Huntington’s disease. Neurology 42:1791–1797. Mayberg, H.S., Starkstein, S.E., Sadzot, B., Preziosi, T., Andrezejewski, P.L., Dannals, R.F., Wanger, H.N., Jr., and Robinson, R.G. (1990) Selective hypometabolism in the inferior frontal lobe in depressed patients with Parkinson’s disease. Ann. Neurol. 28:57–64. Mazziotta, J.C., Phelps, M.E., Plummer, D., and Kuhl, D.E. (1981) Quantitation in positron emission computed tomography. 5. Physical-anatomical effects. J. Comput. Assist. Tomogr. 5:734 –743. McDonald, W.M., Krishnan, K.R.R., Doraiswamy, P.M., et al. (1991) Occurrence of subcortical hyperintensities in elderly subjects with mania. Psychiatry Res. 40:211–220. McEwen, B.S. (1999) Stress and hippocampal plasticity. Ann. Rev. Neurosci. 22:105–122. Meltzer, C.C., Price, J.C., Mathis, C.A., Greer, P.J., Cantwell, M.N., Houck, P.R., Mulsant, B.H., Ben-Eliezer, D., Lopresti, B., DeKosky S.T., and Reynolds, C.F. III. (1999) PET imaging of serotonin type 2A receptors in late-life neuropsychiatric disorders. Am. J. Psychiatry 156:1871–1878. Mervaala, E., Fohr, J., Kononen, M., Valkonen-Korhonen, M., Vainio, P., Partanen, K., et al. (2000) Quantitative MRI of the hippocampus and amygdala in severe depression. Psychol. Med. 30:117–125. Meyer, J.H., Houle, S., Sagrati, S., Carella, A., Hussey, D.F., Ginovart, N., et al. (2004) Brain serotonin transporter binding potential measured with carbon 11-labeled DASB positron emission tomography: effects of major depressive episodes and severity of dysfunctional attitudes. Arch. Gen. Psychiatry 61:1271–1279. Meyer, J.H., Kapur, S., Houle, S., DaSilva, J., Owczarek, B., Brown, G.M., Wilson, A.A., and Kennedy, S.H. (1999) Prefrontal cortex 5-HT2 receptors in depression: An [18F] Setoperone PET imaging study. Am. J. Psychiatry 156(7):1029–1034. Meyer, J.H., Kruger, S., Wilson, A.A., Christensen, B.K., Goulding, V.S., Schaffer, A., Minifie, C., Houle, S., and Kennedy, S.H. (2001) Lower dopamine transporter binding potential in striatum during depression. Neuroreport 12(18):4121–4125. Moore, G., Cortese, B., Glitz, D., Zajac-Benitez, C., Keenan, P., Drevets, W.C., and Manji, H.K. (2004) Chronic lithium increases prefrontal and subgenual prefrontal gray matter in patients with bipolar disorder: a longitudinal high resolution volumetric MRI study. Soc. Neurosci. Abstr. Nemeroff, C.B., Krishnan, K.R.R., Reed, D., et al. (1992) Adrenal gland enlargement in major depression: a computed tomographic study. Arch. Gen. Psychiatry 49:384–387. Neumeister, A., Nugent, A.C., Waldeck, T., Geraci, M., Schwarz, M., Bonne, O., Luckenbaugh, D., Herscovitch, P., Charney, D.S., and Drevets, W.C. (2004) Behavioral and neural responses to tryptophan depletion in unmedicated remitted patients with major depressive disorder and controls. Arch. Gen. Psychiatry 61: 765–773. Neumeister, A., Wood, S., Bonne, O., Nugent, A.C., Luckenbaugh, D.A., Young, T., Bain, E.E., Charney, D.S., and Drevets, W.C. (2005) Reduced hippocampal volume in unmedicated, remitted

31: NEUROIMAGING STUDIES patients with major depressive disorder versus control subjects. Biol. Psychiatry 58(8):935–937. Nobler, M.S., Oquendo, M.A., Kegeles, L.S., Malone, K.M., Campbell, C., Sackeim, H.A., and Mann, J.J. (2001) Decreased regional brain metabolism after ECT. Am. J. Psychiatry 158:305–308. Nobler, M.S., Roose, S., Prohovnik, I., Moeller, J.R., Louie, J., Van Heertum, R.L., and Sackeim, H.A. (2000) Regional cerebral blood flow in mood disorders, V. Effects of antidepressant medication in late-life depression. Am. J. Geriatr. Psychiatry 8:289–296. Nobler, M.S., Sackeim, H.A., Prohovnik, I., Moeller, J.R., Mukherjee, S., Schnur, D.B., Prudic, J., and Devanand, D.P. (1994) Regional cerebral BF in mood disorders, III. Treatment and clinical response. Arch. Gen. Psychiatry 51:884–897. Nofzinger, E.F., Nichols, T.E., Meltzer, C.C., Price, J., Steppe, D.A., Miewald, J.M., Kupfer, D.J., and Moore, R.Y. (1999) Changes in forebrain function from waking to REM sleep in depression: preliminary analyses of [18F]FDG PET studies. Psychiatry Res. Neuroimaging 91:59–78. Noga, J.T., Vladar, K., Torrey, E.F. (2001) A volumetric magnetic resonance imaging study of monozygotic twins discordant for bipolar disorder. Psychiatry Res 106:25–34. Nugent, A. C., et al. (2006) Cortical abnormalities in bipolar disorder investigated with MRI and voxel-based morphometry. Neuroimage 30(2):485– 497. O’Brien, J.T., Ames, D., and Schwietzer, I. (1996) White matter changes in depression and Alzheimer’s disease: a review of magnetic resonance imaging studies. Int. J. Geriatric Psychiatry 11:681–694. O’Brien, J.T., Desmond, P., Ames, D., et al. (1996) Magnetic resonance imaging study of white matter lesions in depression and Alzheimer’s disease. Br. J. Psychiatry 168:477–485. Öngür, D., Drevets, W.C., and Price, J.L. (1998) Glial reduction in the subgenual prefrontal cortex in mood disorders. Proceedings of the National Academy of Science 95:13290–13295. Öngür, D., Ferry, A. T., and Price, J.L. (2003) Architectonic subdivision of the human orbital and medial prefrontal cortex. J. Comp. Neurol. 460:425– 449. Oquendo, M.A., Hastings, R.S., Huang, Y.Y., Simpson, N., Ogden, R.T., Hu, X.Z., et al. (2007) Brain serotonin transporter binding in depressed patients with bipolar disorder using positron emission tomography. Arch. Gen. Psychiatry 64:201–208. Osuch, E.A., Ketter, T.A., Kimbrell, T.A., George, M.S., Benson, B.E., Willis, M.W., Herscovitch, P., and Post, R.M. (2000) Regional cerebral metabolism associated with anxiety symptoms in affective disorder patients. Biol. Psychiatry 48(10):1020 –1023. Pantel, J., Schroder, J., Essig, M., et al. (1997) Quantitative magnetic resonance imaging in geriatric depression and primary degenerative dementia. J. Affect. Disord. 42:69–83. Parsey, R.V., Hastings, R.S., Oquendo, M.A., Huang, Y.Y., Simpson, N., Arcement, J., et al. (2006) Lower serotonin transporter binding potential in the human brain during major depressive episodes. Am. J. Psychiatry 163:52–58. Paul, I. A., and Skolnick, P. (2003) Glutamate and depression: clinical and preclinical studies. Ann. N. Y. Acad. Sci. 1003:250–272. Pearlson, G.D., Barta, P.E., Powers, R.E., Menon, R.R., Richards, S.S., Aylward, E.H., Federman, E.B., Chase, G.A., Petty, R.G., and Tien, A.Y. (1997) Medial and superior temporal gyral volumes and cerebral asymmetry in schizophrenia versus bipolar disorder. Biol. Psychiatry 41:1–14. Pearlson, G.D., Wong, D.F., Tune, L.E., et al. (1995) In vivo D2 dopamine receptor density in psychotic and nonpsychotic patients with bipolar disorder. Arch. Gen. Psychiatry 52:471– 477. Philpot, M.P., Banerjee, S., Needham-Bennett, H., Costa, D.C., and Ell, P.J. (1993) 99mmTc-HMPAO single photon emission tomography in late life depression: a pilot study of regional cerebral blood flow at rest and during a verbal fluency task. J. Affect. Disord. 28:233–240. Pizzagalli, D., Pascual-Marqui, R.D., Nitschke, J.B., Oakes, T.R., Larson, C.L., Abercrombie, H.C., Schaefer, S.M., Koger, J.V., Benca, R.M., and Davidson, R.J. (2001) Anterior cingulate activity

489

as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. Am. J. Psychiatry 158(3):405– 415. Poline, J.B., Holmes, A., Worsley, K., and Friston, K.J. (1997) Making statistical inferences. In: Frackowiak, R., Friston, K.J., Frith, C.D., Dolan, R.J., and Mazziotta J.C., eds. Human Brain Function. London: Academic Press, pp. 85–106. Postalache, T.T., Matthews, J.R., Turner, E.H., Benson, B.E., Guzman, A., Rosenthal, N.E., and Drevets, W.C. (2002, June 13-15) Cerebral blood flow in depressed individuals with seasonal affective disorder as compared to matched controls. Soc. Light Treatment Bio Rhythms Abstracts, 14:23. Price, J.L., Carmichael, S.T., and Drevets, W.C. (1996) Networks related to the orbital and medial prefrontal cortex: a substrate for emotional behavior? Prog. Brain Res. 107:523–536. Rabins, P.V., Pearlson, G.D., Aylward, E., et al. (1991) Cortical magnetic imaging changes in elderly inpatients with major depression. Am. J. Psychiatry 148:617–620. Raichle, M.E. (1987) Circulatory and metabolic correlates of brain function in normal humans. In: Brookhart, J.M., and Mountcastle, V.B., ed. Handbook of Physiology - the Nervous System V. Baltimore: Williams and Wilkins, pp. 643–674. Rajkowska, G., Miguel-Hidalgo, J.J., Wei, J., Dilley, G., Pittman, S.D., Meltzer, H.Y., Overholser, J.C., Roth, B.L., and Stockmeier, C.A. (1999) Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression. Biol. Psychiatry 45(9): 1085–1098 Rauch, S.L., Jenike, M.A., Alpert, N.M., Baer, L., Breiter, H., Savage, C.R., and Fischman, A.J. (1994) Regional cerebral blood flow measured during symptom provocation in obsessive-compulsive disorder using oxygen 15-labeled carbon dioxide and positron emission tomography. Arch. Gen. Psychiatry 51:62–70 Reiman, E.M., Lane, R.D., Ahern, G.L., Schwartz, G.E., Davidson, R.J., Friston, K.J., Yun, L.S., and Chen, K. (1997) Neuroanatomical correlates of externally and internally generated human emotion. Am. J. Psychiatry 154(7):918–925 Reivich, M., Amsterdam, J.D., Brunswick, D.J., and Shiue, C.Y. (2004) PET brain imaging with [11C](+)McN5652 shows increased serotonin transporter availability in major depression. J. Affect. Disord. 82:321–327. Ring, H.A., Bench, C.J., Trimble, M.R., Brooks, D.J., Frackowiak, R.S.J., and Dolan, R.J. (1994) Depression in Parkinson’s disease: a positron emission study. Br. J. Psychiatry 165:333–339. Rolls, E.T. (1995) A theory of emotion and consciousness, and its application to understanding the neural basis of emotion. In: Gazzaniga M, ed. The Cognitive Neurosciences. Cambridge, MA: MIT Press, pp. 1091–1106. Rubin, R.T., Mandell, A.J., and Crandall, P.H. (1966) Corticosteroid responses to limbic stimulation in man: localization of stimulus sites. Science 153:767–768. Rubin, R.T., Phillips, J.J., McCracken, J.T., Sadow, T.F. (1996) Adrenal gland volume in major depression: relationship to basal and stimulated pituitary-adrenal cortical axis function. Biol. Psychiatry 40(2):89–97 Rubin, R.T., Phillips, J.J., Sadow, T.F., et al. (1995) Adrenal gland volume in major depression: increase during the depressive episode and decrease with successful treatment. Arch. Gen. Psychiatry 52:213–218. Saxena, S., Brody, A.L., Ho, M.L., Alborzian, S., Maidment, K., Zohrabi, N., Ho, M.K., Huang, S.C., Wu, H.M., and Baxter, L.R. (2002) Differential cerebral metabolic changes with paroxetine treatment of obsessive-compulsive disorder vs major depression. Arch. Gen. Psychiatry 59:250–261. Schneider, F., Gur, R.E., Alavi, A., Mozley, L.H., Smith, R.J., Mozley, P.D., Censits, D.M., and Gur, R.C. (1995) Mood effects on limbic blood flow correlate with emotion self-rating: a PET study with oxygen-15 labeled water. Psychiatry Res. Neuroimaging 61: 265–283.

490

MOOD DISORDERS

Schwartz, J.M., Baxter, L.R., Mazziota, J.C., Gerner, R.H., and Phelps, M.E. (1987) The differential diagnosis of depression: Relevance of positron emission tomography studies of cerebral glucose metabolism to the bipolar-unipolar dichotomy. JAMA 258:1368–1373. Shah, P.J., Ebmeier, K.P., Glabus, M.F., and Goodwin, G.M. (1998) Cortical grey matter reductions associated with treatment-resistant chronic unipolar depression. Controlled magnetic resonance imaging study. Br. J. Psychiatry 172:527–532. Shah, P.J., Ogilvie, A.D., Goodwin, G.M., and Ebmeier, K.P. (1997) Clinical and psychometric correlates of dopamine D2 binding in depression. Psychol. Med. 27:1247–1256 Shah, S.A., Doraiswamy, P.M., Husain, M.M., et al. (1992) Posterior fossa abnormalities in major depression: a controlled magnetic resonance imaging study. Acta Psychiatr. Scand. 85:474– 479. Sheline, Y.I., Barch, D.M., Donnelly, J.M., Ollinger, J.M., Snyder, A.Z., and Mintun, M.A. (2001) Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol. Psychiatry 50:651–658. Sheline, Y.I., Gado, M.H., and Price, J.L. (1998) Amygdala core nuclei volumes are decreased in recurrent major depression. Neuroreport 9(9):2023–2028. Sheline, Y.I., Mintun, M.A., Barch, D.M., Wilkins, C., Snyder, A.Z., and Moerlein, S.M. (2004) Decreased hippocampal 5-HT(2A) receptor binding in older depressed patients using [18F]altanserin positron emission tomography. Neuropsychopharmacology 29(12): 2235–2241. Sheline, Y.I., Wang, P.W., Gado, M.H., Csernansky, J.G., and Vannier, M.W. (1996) Hippocampal atrophy in recurrent major depression. Proc. Natl. Acad. Sci. USA 93:3908–3913. Shulman, R.G., Rothman, D.L., Behar, K.L. and Hyder, F. (2004) Energetic basis of brain activity: implications for neuroimaging. Trends Neurosci. 27:489– 495. Siegle, G.J., Carter, C. S., et al. (2006) Use of FMRI to predict recovery from unipolar depression with cognitive behavior therapy. Am. J. Psychiatry 163(4):735–738. Siegle, G.J., Steinhauer, S.R., Thase, M.E., Stenger, V.A., and Carter, C.C. (2002) Can’t shake that feeling: event-related fMRI assessment of sustained amygdala activity in response to emotional information in depressed individuals. Biol. Psychiatry 51:693–707. Silfverskiöld, P., and Risberg, J. (1989) Regional blood flow in depression and mania. Arch. Gen. Psychiatry 46:253–259. Smith, G.S., Reynolds, C.F., Pollock, B., Derbyshire, S., Nofzinger, E., Dew, M.A., Houck, P.A., Milko, D., Meltzer, C.C., and Kupfer, D.J. (1999) Cerebral glucose metabolic response to combined total sleep deprivation and antidepressant treatment in geriatric depression. Am. J. Psychiatry 156:683–689. Starkstein, S.E., and Robinson, R.G. (1989) Affective disorders and cerebral vascular disease. Br. J. Psychiatry 154:170–182. Steffens, D.C., Byrum, C.E., McQuoid, D.R., Greenberg, D.L., Payne, M.E., Blitchington, T.F., MacFall, J.R., and Krishnan, K.R. (2000) Hippocampal volume in geriatric depression. Biol. Psychiatry 48:301–309. Stockmeier, C.A. (2003) Involvement of serotonin in depression: evidence from postmortem and imaging studies of serotonin receptors and the serotonin transporter. J. Psychiatry Res. 37:357–373. Strakowski, S.M., DelBello, M.P., Sax, K.W., Zimmerman, M.E., Shear, P.K., Hawkins, J.M., and Larson, E.R. (1999) Brain magnetic resonance imaging of structural abnormalities in bipolar disorder. Arch. Gen. Psychiatry 56:254–260. Strakowski, S.M., Wilson, D.R., Tohen, M., et al. (1993) Structural brain abnormalities in first-episode mania. Biol. Psychiatry 33: 602–609. Suhara, T., Nakayama, K., Inoue, O., Fukuda, H., Shimizu, M., Mori, A., and Tateno, Y. (1992) D1 dopamine receptor binding in mood disorders measured by PET. Psychopharmacology 106:14–18. Sullivan, R.M., and Gratton, A. (1999) Lateralized effects of medial prefrontal cortex lesions on neuroendocrine and autonomic stress responses in rats. J. Neurosci. 19:2834–2840

Swayze, V.W., Andreasen, N.C., Alliger, R.J., et al. (1990) Structural brain abnormalties in bipolar affective disorder. Ventricular enlargement and focal signal hyperintensities. Arch. Gen. Psychiatry 47:1054–1059. Swayze, V.W., 2nd, Andreasen, N.C., Alliger, R.J., Yuh, W.T., and Ehrhardt, J.C. (1992) Subcortical and temporal structures in affective disorder and schizophrenia: a magnetic resonance imaging study. Biol. Psychiatry 31(3):221– 240 Taylor, W.D., MacFall, J.R., Payne, M.E., McQuoid, D.R., Provenzale, J.M., Steffens, D.C., and Krishnan, K.R. (2004) Late-life depression and microstructural abnormalities in dorsolateral prefrontal cortex. Am. J. Psychiatry 161(7):1293–1296. Taylor, W.D., Payne, M.E., Krishnan, K.R., Wagner, H.R., Provenzale, J.M., Steffens, D.C., and MacFall, J.R. (2001) Evidence of white matter tract disruption in MRI hyperintensities. Biol. Psychiatry 50(3):179–183. Thomas, K.M., Drevets, W.C., Dahl, R.E., Ryan, N.D., Birmaher, B., Eccard, C.H., Axelson, D., Whalen, P.J., and Casey, B.J. (2001) Abnormal amygdala response to faces in anxious and depressed children. Arch. Gen. Psychiatry 58:1057–1063. Timms, R.J. (1977) Cortical inhibition and facilitation of the defence reaction. J. Physiol. Lond. 266:98P–99P. Tremblay, L.K., Naranjo, C.A., et al. (2005) Functional neuroanatomical substrates of altered reward processing in major depressive disorder revealed by a dopaminergic probe. Arch. Gen. Psychiatry 62(11):1228–1236. Uytdenhoef, P., Portelange, P., Jacquy, J., Charles, G., Linkowski, P., and Mendlewicz, J. (1983) Regional cerebral blood flow and lateralized hemispheric dysfunction in depression. Br. J. Psychiatry 143:128–132. Vakili, K., Pillay, S.S., Lafer, B., Fava, M., Renshaw, P.F., and BonelloCintron, C.M. (2000) Hippocampal volume in primary unipolar major depression: a magnetic resonance imaging study. Biol. Psychiatry 47:1087–1090. Videbech, P., Ravnkilde, B., Pedersen, A.R., Egander, A., Landbo, B., Rasmussen, N.A., Andersen, F., Stodkilde-Jorgensen, H., Gjedde, A., and Rosenberg, R. (2001) The Danish PET/depression project: PET findings in patients with major depression. Psychol. Med. 31: 1147–1158. Volkow, N.D., Fowler, J.S., Wolf, A.P., Hitzemann, R., Dewey, S., Bendriem, B., Alpert, R., and Hoff, A. (1991) Changes in brain glucose metabolism in cocaine dependence and withdrawal. Am. J. Psychiatry 148:621–626. von Gunten, A., Fox, N.C., Cipolotti, L., and Ron, M.A. (2000) A volumetric study of hippocampus and amygdala in depressed patients with subjective memory problems. J. Neuropsychiatry Clin. Neurosci. 12:493– 498. Vythilingam, M., Heim, C., Newport, J., Miller, A.H., Anderson, E., Bronen, R., et al. (2002) Childhood trauma associated with smaller hippocampal volume in women with major depression. Am. J. Psychiatry 159:2072–2080. Wilson, J., Kupfer, D.J., Thase, M., Bogers, W., Greer, P., and Drevets, W.C. (2002) Ventral striatal metabolism is increased in depression, and decreases with treatment. Biol. Psychiatry 51:122S. Wooten, G.F., and Collins, R.C. (1981) Metabolic effects of unilateral lesion of the substantia nigra. J. Neurosci. 1:285–291. Wu, J.C., Gillin, J.C., Buchsbaum, M.S., Hershey, T., Johnson, J.C., Bunney, W.E. (1992) Effect of sleep deprivation on brain metabolism of depressed patients. Am. J. Psychiatry 149:538–543. Yurgelun-Todd, D.A., Gruber, S.A., Kanayama, G., Killgore, W.D., Baird, A.A., and Young, A.D. (2000) fMRI during affect discrimination in bipolar affective disorder. Bipolar Disord. 2: 237–248. Zis, K.D., and Zis, A.P. (1987) Increased adrenal weight in victims of violent suicide. Am. J. Psychiatry 144:1214–1215. Zubenko, G.S., Sullivan, P., Nelson, J.P., et al. (1990) Brain imaging abnormalities in mental disorders of late life. Arch. Neurol. 47: 1107–1113.

32 Principles of the Pharmacotherapy of Depression ROBERT M. BERMAN,* JONATHAN SPORN*, DENNIS S. CHARNEY,

AN D

Serendipitous discoveries in the 1950s led to the development of the first antidepressant agents, iproniazid (Crane, 1956; Kline, 1970) and imipramine (Kuhn, 1958). These agents were strategically developed as potential treatments for tuberculosis and psychosis, respectively. The observations that these agents improved mood and boosted psychomotoric activity led to their testing in clinical trials for the treatment of depression. Further investigation revealed their pharmacological activity on monoamine systems, subsequently leading to the development of over two dozen medications with demonstrated antidepressant properties. In the 1960s, knowledge that tricyclic antidepressants inhibited uptake of not only the catecholamine norepinephrine but also serotonin led to a search for specific serotonin reuptake inhibitors (SSRIs). This culminated in the derivation of the first SSRI, zimelidine, which was withdrawn due to an idiosyncratic side effect. In addition, observation of decreased serotonin levels in postmortem and cerebrospinal fluid (CSF) studies of depression provided further stimulus for a search for specific SSRIs, culminating in the discovery of the landmark SSRI, fluoxetine (Blardi et al., 2002). Clinical development of new agents has been limited by the lack of homogeneity within diagnostically defined entities and by the limited validity and sensitivity of rating instruments for testing change. As well, patients treated in antidepressant trials represent only a subset of individuals, and results may not be fully generalizable with regard to effectiveness in the field (Zimmerman et al., 2002). Rational use of these medications requires an understanding of their pharmacological properties and clinical effects in varied patient populations. Despite appropriate use of medications, for a long time it has been thought only 40%–50% of patients with depression can expect timely remission with antidepressant treatment

* Contributed equally to the writing of this chapter.

SANJAY J. MATHEW

(Frank et al., 1993). However, the recent large-scale STAR*D study noted even lower remission rates (circa 30%) with acute citalopram treatment (Trivedi, Rush, et al., 2006). Some 10%–20% of care-seeking patients with depression remain significantly symptomatic after 2 years (Keller et al., 1982). THE ANTIDEPRESSANTS For clinical purposes, a useful classification system for antidepressants is based on known receptor affinities— specifically, affinities thought to be related to their mechanism of action. Such a categorization belies the structural diversity of the members of each class; hence, the members of each category may not resemble each other in terms of pharmacokinetics, metabolism, or toxicity (Table 32.1). However, most antidepressants have pharmacological action on the metabolism and at the receptors for the monoamine neurotransmitters norepinephrine (NE), serotonin, and dopamine (DA). In addition, multiple classes of antidepressant agents augment intracellular cyclic adenosine monophosphate (cAMP) and levels of neurotrophic and transcription factors such as cAMP-response element binding protein (CREB) and brain-derived neurotrophic factor (BDNF). Antidepressants may also modulate excitatory transmission by decreasing binding at N-methyl-D-aspartate (NMDA) receptors or by inducing changes at other excitatory receptors such as the α-amino-3-hydroxy-5-methyl-4-isoxasolepropionic acid (AMPA) receptor. Last, there are novel antidepressants that in part may exert effects on melatonin receptors. Tricyclic Antidepressants The standard tricyclic antidepressant, imipramine, a dibenzazepine drug, is similar in structure to the phenothiazines. Kuhn (1958) determined that it lacked the capacity to 491

492 TABLE

MOOD DISORDERS

32.1 Functionally Relevant Receptor Antagonism and Associated Side Effectsa

Antidepressant

Histamine-1 (Sedation, Weight Gain, Hypotension, Potentiation of CNS Depressants)

Muscarinic (Tachycardia, Memory Impairment, Constipation, Urinary Retention, Blurred Vision, Dry Mouth)

α1-Adrenergic (Hypotension, Tachycardia)

Tricyclic agents Amitriptyline

1111

111

Doxepine

1111

111

1111 1111

Imipramine

111

11

1111

Protripyline

111

111

1111

Trimipramine

1111

11

1111

Desipramine

11/111

11

111

Nortripyline

111

11

111

Fluoxetine

1

1

1

Sertraline

1

1

11

Paroxetine

1

1

1

Fluvoxamine

1

1

1

Citalopram

1

1

1

Mirtazapine

1111

1

11

Venlafaxine

1

1

1

Duloxetine

1

1

1

Nefazodone

1

1

111

Trazodone

1

1

1111

Bupropion

1

1

1

SSRIs

Other agents

CNS: central nervous system; SSRI: specific serotonin reuptake inhibitor. a. Negligible (1), mild (11), moderate (111), and high (1111) affinities. Receptor-mediated side effects are more likely with higher-affinity agents. Source: Adapted from Richelson (1991).

calm patients who were agitated but observed robust positive effects in patients who were depressed. Tricyclic antidepressants (TCAs)—so labeled because of a core structure consisting of three rings—also include imipramine, amitriptyline, trimipramine, doxepin, desipramine, nortriptyline, and protriptyline. Tricyclics antidepressants that are either secondary amines or the N-demethylated (nor) metabolites of tertiaryamine structures (for example, amoxapine, desipramine, and nortriptyline) have relative selectivity for the inhibition of noradrenaline uptake, whereas the older tertiary-amine tricyclics additionally inhibit the reuptake and inactivation of serotonin while maintaining NE reuptake inhibition vis-à-vis their metabolites. Amoxapine additionally is a DA2 antagonist and thus has neuroleptic properties that are important in the treatment of psychotic depression; however, it may lead to extrapyramidal side effects, especially in patients with Parkinson’s disease (Richelson, 1991). Within a narrow dose range, and typically at therapeutic doses, these antidepressants are active at multiple nonmonoamine receptors, resulting in a complex set of adaptive processes from

the level of the receptor to that of genomic regulatory factors. Augmentation of α1-receptor activity, desensitization of α 2-receptors, and possibly desensitization of D2 autoreceptors may facilitate serotonin, NE, and DA signaling. Subsequently, 5-HT1 autoreceptors and 5HT2 receptors postsynaptically may be down-regulated and involved in generating an antidepressant signal. As indicated in Table 32.1, such high affinity for other receptors leads to bothersome side effects. Blockade of muscarinic acetylcholine receptors may cause dry mouth, blurred vision, constipation, urinary retention, memory impairment, and tachycardia. Blockade of histamine-1 receptors may cause sedation, weight gain, hypotension, and the potentiation of other central nervous system (CNS) depressants. Blockade of α 1-adrenergic receptors may cause postural hypotension, reflex tachycardia, and perhaps sedation. Via unclear mechanisms, TCAs, especially clomipramine and amoxapine, are associated with a 0.1%–0.5% rate of seizures (Skowron and Stimmel, 1992), likely occurring early in treatment or during periods of acute dose escalation. After its release, maprotiline—a tetracyclic compound—was

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION

associated with higher rates of seizures probably due to too rapid a dosage escalation (Dessain et al., 1986). Revision of the recommended dosing schedule appeared to decrease the risk substantially. When given in doses up to one order of magnitude greater than typical therapeutic doses, TCAs may be lethal, causing fatal arrhythmias. At these doses, conduction abnormalities may emerge, such as prolonged PR, QRS, or QTc intervals, as well as flattening or inversion of T waves. Also, slowing of depolarization may lead to atrioventricular or bundle branch block, as well as premature ventricular contractions. Some TCAs may also decrease heart rate variability, which is a risk factor for sudden cardiac death. Nevertheless, at standard doses, clinically significant cardiac abnormalities are not common (Nelson, 1997a). An important consideration is that drugs that inhibit the cytochrome CYP2D6 isozyme may lead to potentially dangerous increases in TCA blood levels that can be problematic for patients who are elderly. Once the mainstay of antidepressant treatment, TCAs have been replaced by newer agents with more favorable side-effect and safety profiles. Despite their resulting diminished popularity, the tolerability of TCAs may well be underestimated by most clinicians (Nelson, 1997a). They are still commonly used for patients with chronic pain. Monoamine Oxidase Inhibitors Monoamine oxidase inhibitors (MAOIs) used to treat depression can be irreversible inhibitors (for example, phenelzine and tranylcypromine) or short acting and reversible, such as the MAOI-A, moclobemide. They are either of the hydrazine class, such as phenalzine and isocarboxazide, or unrelated to the hydrazines and related to the CNS stimulants such as tranylcypromine. Reversible MAOIs such as moclobemide have a moderate degree of antidepressant activity (Davidson, 1992). The older agents in this class irreversibly inhibit the MAO isozymes A and B, whereas moclobemide competitively inhibits MAO-A. Increased MAO-A activity in brain has recently been reported using positron emission tomography (PET) imaging (Meyer et al, 2006). Antidepressant activity of these agents has been attributed to their ability to inhibit MAO-A, which metabolizes noradrenaline and serotonin because oral agents that specifically inhibit MAO-B, such as deprenyl, have limited antidepressant efficacy (Mann et al., 1989). However, transdermal deprenyl does appear effective (Feighner et al., 2006) and is safer than other orally available MAOIs. It is now on the U.S. market. Preclinical data indicate that when administered transdermally the agent is a potent inhibitor of central MAO-A and MAO-B activity (Wecker et al., 2003). The older MAOIs became unpopular in clinical practice because of side effects and potential toxicity. The

493

MAOIs may cause acute, severe elevations in blood pressure (that is, hypertensive crises) with ingestion of tyramine-containing foods and sympathomimetic medications. Other symptoms of this syndrome include headache, nausea, sweating, pallor, and vomiting. Fatalities secondary to intracranial hemorrhage have been reported. Patients must adhere to dietary restrictions aimed at eliminating foods rich in tyramine, such as aged cheeses, soy sauce, sauerkraut, air-dried sausage, pickled herring, concentrated yeast extract, and fava beans. Tyramine, ordinarily metabolized by gastrointestinal MAO, acts as a direct and/or indirect pressor agent when absorbed by patients on MAOIs. Rare cases of hypertensive crisis without demonstrable dietary indiscretions have also been reported. However, clinicians should be aware that recent studies of food tyramine content indicate that a simple, limited list of absolutely restricted foods can be developed and that a user-friendly MAOI diet may enhance patient compliance and physician comfort with this important class of agents (Gardner et al., 1996; Walker et al., 1996). Patients must also be diligent about avoiding dangerous medication interactions with MAOIs. Drugs that increase synaptic monoamine effects should be eliminated, such as tricyclics, SSRIs, cocaine, stimulants, and many over-the-counter flu medications. Furthermore, idiosyncratic hyperthermic reactions with certain medications such as pethidine and meperidine, as well as other opiates, can be lethal. Due to such dramatic toxic effects, irreversible MAOIs are best reserved for cases when multiple previous treatment trials have been unsuccessful. Moclobemide and brofaromine represented a newer generation of MAOIs that were distinguished by their reversible inhibition of MAO. Consequently, these agents had less interaction with dietary tyramine to cause hypertensive crises. Nevertheless, drug interactions with SSRIs or SNRIs could cause a serotonin syndrome. U.S. trials with these agents were not as robust as European studies, and their development has been on hold in the United States. Selective Serotonin Reuptake Inhibitors The SSRIs generally have affinity for the serotonin transporter that is one to two orders of magnitude greater than their affinity for the noradrenergic transporter (Table 32.2) (Richelson, 1991). At typical therapeutic doses, they generally inhibit about 80% of serotonin transporter activity (Meyer et al., 2001). Increased serotonin levels at the synapse stimulate a large number of serotonin receptor subtypes and are putatively related to the antidepressant effect and many of the side effects of these agents. Increased serotonin availability occurs following desensitization of dendritic 5-HT1A receptors and terminal 5-HT1D receptors. Down-regulation of postsynaptic 5-HT2A receptors may also be impor-

494

MOOD DISORDERS

32.2 Potency of Selected Antidepressants to Inhibit Monoamine Reuptake a

TABLE

IC50 Values (nM) Antidepressant

Norepinephrine

Serotonin

Tricyclic agents Amitriptyline Doxepine

25

100

150

2,000

Imipramine

25

50

Protriptyline

10

250

Trimipramine

5,000

10,000

Desipramine

2

300

Nortriptyline

6

200

Fluoxetine

200

15

Sertraline

300

4

Paroxetine

70

1

SSRIs

Fluvoxamine

500

5

3,900

3

Mirtazapine

2,000

5,000

Venlafaxine

300

50

9

3

Citalopram Other agents

Duloxetine Nefazodone

600

150

Trazodone

20,000

750

Bupropion

2,500

15,000

Reboxetine

8

1,070

SSRI: specific serotonin reuptake inhibitor. a. The depicted inhibitory constants reflect the concentration of antidepressant that blocks one half of the reuptake of monoamines, serotonin, and norepinephrine by their respective transporters. Source: Frazer (1997).

tant in generating an antidepressant signal. Beyond the receptor, fluoxetine, via the cAMP-dependent protein kinase A (PKA) pathway in frontal cortex and hippocampus, has been observed to regulate the phosphorylation state of DA- and cAMP-regulated phosophoprotein of Mr 32,000 (DARPP-32) (Svenningsson et al., 2002). DARPP-32 mediates changes in the phosphorylation state and activity of AMPA, a glutamate receptor that is a therapeutic target in depression. Ease of use made the SSRIs the standard first-line treatment for major depression by most practitioners. Available SSRIs worldwide include fluoxetine, paroxetine, sertraline, fluvoxamine, citalopram, and escitalopram (the enantiomer of citalopram). The agents in this class may be distinguished by their half-lives. Fluoxetine and its metabolite have respective half-lives of approximately 2 and 7 days. Plasma levels for fluoxetine

reach their peak 30 days after starting the drug. Platelet serotonin level decreases and increases in plasma serotonin are also greatest after 30 days (Blardi et al., 2002). Nevertheless, common practice is once-daily dosing of fluoxetine as well as most other SSRIs. Fluvoxamine, approved in the United States for obsessive compulsive disorder but not major depression, is distinguished by having the shortest half-life (approximately 16 hours), which requires twice daily dosing, and by being the least protein bound. The SSRIs are very rarely associated with fatalities when large doses are ingested unless other agents are also taken. The SSRIs may be safe in pregnancy if absolutely necessary, with the most observational retrospective data available for fluoxetine and sertraline. There are reports of possible subtle motoric effects with late pregnancy exposure to SSRIs (Casper et al., 2003). Proliferation and increased use of SSRIs has necessitated a keen awareness of potentially lethal interactions involving drug metabolism (Nemeroff et al., 1996). The cytochrome P450 enzymes are a superfamily of heme-thiolate proteins, and blockade or polymorphisms of these enzymes result in altered drug metabolism. Inhibition of the hepatic isozyme CYP-2D6 can lead to significant elevations in blood levels of TCAs and neuroleptics. Although fluoxetine and paroxetine most potently inhibit this isozyme and are, therefore, more commonly associated with related interactions, sertraline can also cause clinically relevant isozyme inhibition. About 70 single-nucleotide polymorphisms have been found for CYP-2D6, and a relatively common genetic polymorphism may profoundly reduce the activity of this isozyme in up to 10% of Caucasians as well as 2% of Asians and Blacks (Kroemer and Eichelbaum, 1995). Given the prevalence of such poor metabolizers, the clinician should be aware of potential interactions involving CYP-2D6 isozymes even when using agents such as sertraline. However, a recent pharmacogenetic study of paroxetine in geriatric patients with depression did not observe increased dropouts due to adverse events in slow metabolizers (Murphy et al., 2003). Fluvoxamine is a potent inhibitor of CYP-3A4 and hence may lead to dangerous cardiotoxic elevations related to the metabolism of terfenadine, astemizole, and cisapride. The prudent clinician must take heed of potentially expectable interactions, and careful monitoring is necessary when a patient is concurrently taking medications with a narrow therapeutic index (Nemeroff et al., 1996). The newer antidepressants have less inhibition of clinically important CYPs with the exception of nefazadone, a potent inhibitor of CYP-3A4. A possible lethal interaction involves the use of SSRIs with MAOIs or other agents that may potentiate serotonergic transmission. A resultant serotonin syndrome may emerge, consisting of hyperpyrexia, cardio-

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION

genic shock, abdominal pain, agitation, delirium, myoclonus, and/or hypertension (Lane and Baldwin, 1997). The SSRIs, as a class, have been associated with a common set of side effects; consequently, these effects may potentially be mediated via serotonin receptors. Sexual dysfunction consisting of anorgasmia and impotence may be present in one-third or more of patients. Specific receptors associated with this phenomenon have yet to be elucidated but may involve 5-HT2 receptors. Sildenafil may be effective in some patients for as-needed treatment of SSRI-induced erectile dysfunction (Nurnberg et al., 2001), and bupropion may modestly be helpful for increasing drive or interest even though a small controlled trial failed to show an effect (DeBattista et al., 2005). Nausea may be mediated via 5HT3 receptor stimulation and may be blocked by agents with 5-HT3 antagonists such as mirtazapine. Nefazodone and Trazodone Nefazodone and trazodone are potent inhibitors of 5HT2A receptors. They may have weak affinity for serotonin reuptake sites; however, this activity may have little clinical significance. Nefazadone and trazodone improve sleep continuity, and 5-HT2 antagonists increase delta or slow-wave sleep. Significant histaminergic and α1-adrenergic antagonist activities are responsible for the common side effects of sedation and orthostatic hypotension—less problematic for nefazodone than trazodone. Additionally, arrhythmias have been reported with trazodone in patients with preexisting premature ventricular contractions or mitral valve prolapse (Lippman et al., 1983). Although these agents do not cause impotence or anorgasmia, trazodone is associated with priapism, a rare emergency requiring immediate attention. Nefazadone was associated with hepatic toxicity and liver failure in a very small percentage of patients, and this led the original manufacturer to cease production. It is available as a generic. Hepatic toxicity has been observed with trazodone as well. Mirtazapine Mirtazapine has potent affinity for the 5-HT2A (Ki of about 10 nM) and α 2-adrenoceptors (Ki of about 100 nm) (Frazer, 1997). Adrenergic blockade may lead to enhanced noradrenergic neurotransmission, via autoreceptor blockade, and enhanced serotonergic neurotransmission, via release of heterologous α 2-mediated inhibition and potentiation of the α 1-mediated serotonin cell firing rate. Additionally, significant histaminergic antagonism may contribute to this medication’s potential side effects of sedation, dry mouth, weight gain, and constipation. Cardiac side effects have not been reported. Rare idiosyncratic cases of agranulocytosis or neutro-

495

penia have been reported. Furthermore, preliminary experience with this drug worldwide suggests that it has a high therapeutic index, and no known deaths due to overdose have been cited to date (Preskorn, 1997, Waring et al., 2007). Mirtazapine is effective in acute treatment of major depression as well as in relapse prevention with continuation therapy. In the United States, it has become commonly used for geriatric patients. Bupropion The mechanism of action of bupropion remains unclear but likely acts via effects on NE neurons and augmentation of NE release (Dong and Blier, 2001). In preclinical studies, bupropion is a potent inhibitor of DA, but the lack of decrease in CSF levels of homovanillic acid after bupropion use suggests that its efficacy in vivo is not related to changes in DA reuptake; however, clinical studies suggest that it has more potent activity on noradrenergic function, as evidenced by its effects on monoamine metabolite levels (Golden et al., 1988). It is approved in smoking cessation. Bupropion rarely causes orthostatic hypotension, sexual dysfunction, daytime drowsiness, or weight gain. Common side effects include headache, insomnia, nausea, and restlessness. At daily doses below 450 mg, there is a 0.4% incidence of seizures. At daily doses between 450 and 600 mg, a 2.4% seizure rate was observed (Johnston et al., 1991), but this side effect is less problematic with more slowly released formulations. An extended release formulation of bupropion received regulatory approval in 2006 in the U.S. for the prevention of recurrence of major depressive episodes in patients with seasonal affective disorder. Fourth-Generation Antidepressants: Selective Serotonin and Noradrenaline Reuptake Inhibitors (SNRIs): Venlafaxine, Duloxetine, and Milnacipran Venlafaxine Venlafaxine is a newly introduced antidepressant agent with selectively high affinity for the noradrenergic and serotonergic reuptake sites in vitro. However, its NE reuptake inhibition becomes evident only at higher doses, usually above 150–200 mg/day. Low affinity for histaminergic, cholinergic, and adrenergic receptors is corroborated by venlafaxine’s side-effect profile. Furthermore, venlafaxine is only 30% protein bound and thus does not displace highly protein-bound drugs, and because it does not block hepatic cytochrome P450 activity, it is not likely to interfere with hepatic metabolism of other drugs (Holliday and Benfield, 1995). Venlafaxine’s dual mechanism of action is likely responsible for the high rates of remission of depression

496

MOOD DISORDERS

compared to SSRIs (Thase, Entsuah, et al., 2001) and may contribute to its efficacy in generalized anxiety disorder as well (Allgulander et al., 2001). This agent is generally well tolerated when prescribed in its extended-release form and shares a side-effect profile similar to that of SSRIs in that both can be associated with increased sweating and sedation. In patients treated with over 200 mg daily, 5.5% were observed to have clinically significant blood pressure elevations. Such increases were defined as a diastolic blood pressure greater than 105 mmHg and a minimum 15 mmHg increase that was sustained on recordings over three consecutive visits. Nevertheless, this incidence does not differ from that of TCAs, as seen in comparator trials (Feighner , 1995). At doses of over 300 mg daily of immediate release venlafaxine, the incidence of hypertension increases to 13%. Infrequently, increases in serum lipids are observed. Also, rapid discontinuation of venlafaxine, or even missed doses, may result in rebound hypotension, nausea, dizziness, and other withdrawal symptoms. Venlafaxine may be associated with a higher incidence of toxicity in overdose than the SSRIs. Desvenlafaxine, the major active metabolite of venlafaxine, was approved in 2008 for major depressive disorder at a dose of 50mg/day. Duloxetine Duloxetine, in contrast to venlafaxine, has a relatively balanced ratio of serotonergic to noradrenergic reuptake inhibition. Its SNRI profile may account for its perceived robust efficacy. The agent is approved for the treatment of diabetic peripheral neuropathy and has been reported to be effective in fibromyalgia. In addition to major depressive disorder, the agent is approved for generalized anxiety disorder, diabetic peripheral neuropathy, and fibromyalgia. Milnacipran Milnacipran is an SNRI not available in the United States that is equal in efficacy to TCAs and may be superior to SSRIs, especially in patients who are severely ill and agitated with insomnia. Urological side effects can occur (Fukuchi and Kanemoto, 2002). The drug is being developed in the United States for treatment of fibromyalgia. Reboxetine Reboxetine is an NRI approved in Europe and other regions, but it is not approved by the U.S. Food and Drug Administration (FDA) for the treatment of major depression due to equivocal Phase III efficacy results. Reboxetine alters noradrenergic neuronal activity by blocking NE transporters. It appears to increase ventral tegmental neuronal activity and consequently increases

prefrontal cortex (PFC) DA levels as well (Linner et al., 2001). It has observed efficacy in some short- and longterm studies and may have advantages in improving social function over SSRIs (Kasper et al., 2000). Reboxetine is effective on the Hamilton Depression Rating Scale (HAM-D) psychomotor retardation, anxiety, and cognitive clusters of symptoms, with possibly less efficacy for insomnia (Ferguson et al., 2002). It may also be effective in panic disorder and possibly in attention deficit disorder. Urinary hesitancy, sedation, and noradrenergic/anticholinergic side effects such as dry mouth and tachycardia can occur. Reboxetine does not cause prominent sexual side effects in doses below 8 mg and has limited potential for pharmacokinetic interactions, but levels can be effected by inhibitors of CYP-3A4 (Herman et al., 1999). CHOICE OF ANTIDEPRESSANT Given the wide variety of antidepressants, how does the clinician rationally choose a treatment option? Although most patients will eventually respond to treatment, there are no (or only nominally useful) predictors for the initial selection of a specific agent, although there are some budding pharmacogenetic leads. Initial treatment is typically chosen on the basis of side effects, safety, cost, and convenience; differential efficacy plays little role in selecting an antidepressant (Table 32.3). INITIAL CLINICAL ASSESSMENT: ESTABLISHING DIAGNOSIS INITIATING ACUTE THERAPY Assessment of the patient with depression must include a thorough medical as well as psychiatric evaluation. The presence and severity of functional impairment should be carefully evaluated, including interpersonal relationships and work. Patients should be encouraged not to make drastic or irreversible decisions while in a major depression and may require problem-solving assistance and support to adjust their responsibilities and schedules until improvement in functioning occurs. A medical evaluation will be useful to exclude underlying medical conditions that are associated with depressive symptoms and conditions that should be the focus of intervention. In one study, approximately one half of tertiary care patients were found to have previously undiagnosed general medical illnesses upon thorough medical assessment (Hall et al., 1981). Treating these illnesses significantly alleviated their depressive symptoms. Furthermore, occult general medical illness may diminish responsiveness to treatment (Akiskal, 1982). Drugs of abuse or even prescription medications may generate or exacerbate depressive symptoms. Clinicians need to inquire about their patients’ use of recreational substances of abuse, noting

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION

32.3 Clinical and Medical Guides to Treatment Choice

TABLE

Characteristic Uncomplicated unipolar

Comment All antidepressants have similar efficacy More severe depression or depression with agitation may respond better to SNRIs Choice based on side effects, tolerability, cost, convenience

Psychotic

Requires concurrent antipsychotic and antidepressant therapy or ECT

Melancholic/endogenous

Requires somatic treatment; poor response to placebo treatment

Atypical

Moderately increased responsiveness to MAOIs and perhaps SSRIs

Seasonal

Responsive to phototherapy

Anxiety

Increased risk of suicide; consider agents with high therapeutic index

Panic

Use agents known to be effective for panic (e.g., SSRIs, MAOIs, TCAs) Modestly reduced response rate

Bipolar

Observe for induction of “manic switch”; need to consider lithium, anticonvulsants, and atypical antipsychotics, especially for bipolar I disorder

Dysthymia

Responsive to treatment

Geriatric

Avoid agents with anticholinergic side effects if possible Start at low doses and increase dose gradually as needed Consider complicating medical illnesses (see text)

ECT: electroconvulsive therapy; MAOI: monoamine oxidase inhibitor; SNRI: selective serotonin and norepinephrine reuptake inhibitor; SSRI: selective serotonin reuptake inhibitors; TCA: tricyclic antidepressants. Source: Bymaster et al. (2001).

that even modest use may diminish treatment responsiveness—as may be the case for alcohol. Few studies have adequately examined the impact of subsyndromal substance use on depression. During treatment, it is important to carefully monitor the patient’s mental status for the presence of self-destructive thoughts or other dangerous impulses, and for the emergence of mania as well as drug-induced side effects characteristic of the prescribed agent. The risk of converting from a unipolar course to a bipolar course of illness should be considered. Overall, 5%–10% of patients initially characterized as unipolar will eventually develop mania, and subsyndromal levels of hypomania are common. In a young cohort of patients who were hospitalized and thus severely depressed (especially with psychotic features), almost one half will eventually experience a manic or hypomanic episode if followed longitudinally (Goldberg

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et al., 2001). A high suspicion of bipolar disorder (BPD) is also important in women presenting with postpartum depression. Education of the patient and family about depression and treatment options may alleviate guilt, hopelessness, and criticism by emphasizing that depression is a real illness with effective treatments. A family history of psychiatric illness and suicide should be acquired, and corroborative information from intimates is often helpful. The importance of adherence to treatment should be emphasized from the start of therapy, and frequent visits early on may combat demoralization and allow for dose adjustment for efficacy and side effects. Adjunctive psychotherapy may be helpful in ensuring compliance and may be more effective than medication alone; in one study, patients with chronic depression had a significantly better outcome with nefazadone plus cognitive-behavioral psychotherapy than with either treatment alone (Keller et al., 2000). If at least moderate improvement is not observed by 4 weeks of treatment, reassessment for adjustment of therapy should occur (patients with more chronic depression may respond more slowly to therapy). Maximizing therapy, switching therapy, and adjunctive therapy are options discussed below under “Treatment-Resistant Depression.” Clinical Factors Influencing Choice of Treatment Despite decades of vigorous research, there remains a lack of consensus on useful predictors of response to specific treatments in depressed populations. Nevertheless, some clinical factors merit consideration. Psychotic Depression Psychotic depression has been thought to respond poorly to monotherapy with either antidepressants (particularly in the early TCA studies) or antipsychotics, with response rates ranging from 20%–40% (Chan et al., 1987). Additionally, mood-incongruent psychosis may confer a poorer prognosis than mood-congruent psychosis (Coryell et al., 1982). Italian investigators have argued that some SSRIs can be effective in monotherapy (Zanardi et al., 1996), an observation questioned by others. Electro-convulsive therapy (ECT) studies point to high response rates (Prudic et al., 2004), but to a relatively rapid and moderate loss of response (Prudic et al., 2004). Antidepressant-refractory patients with depression with psychotic features were found to respond readily when antipsychotic medication was added to the treatment regimen (Spiker et al., 1985). Typical antipsychotics as well as atypical agents such as olanzapine are effective in combination with antidepressants (Rothschild et al., 2004). Patients with “near”-psychotic symptoms (for example, highly overvalued ideas focusing on depressive themes) may also respond preferentially to combination treatment (Nelson et al., 1994).

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Melancholic/Endogenous Severe Major Depression Historically, patients with melancholic or endogenous depression have been thought to be particularly unresponsive to placebo treatment (Peselow et al., 1992) and, hence, to have a significantly greater differential response (that is, response rate to medication compared to placebo) to medication treatment. Although some controversy exists as to whether SSRIs are as effective as TCAs in the treatment of melancholic depression, multiple studies have shown equivalent effectiveness in varied depressed populations, including severely depressed, inpatient, and melancholic samples. Furthermore, TCArefractory melancholia may respond to subsequent SSRI treatment (e.g., Amsterdam et al., 1994). Nevertheless, in the subgroup of melancholic in-patients with depression, European studies suggested that one TCA, clomipramine, was more efficacious than were SSRIs and coupled with U.S. experience this has led some to argue SSRIs are less effective in this subgroup (Danish University Antidepressant Study Group, 1990; Roose et al., 1994). The significance of this subgroup remains unclear. Some evidence suggests that venlafaxine and escitalopram have differential efficacy in a severely ill population (Clerc et al., 1994; Montgomery et al., 2007). Further work is necessary to clarify the role of newer antidepressants in the treatment of melancholic or severe major depression. Atypical Depression Definitions of atypical depression (now predominantly characterized by mood reactivity, hypersomnia, hyperphagia, leaden paralysis, and rejection sensitivity) have evolved over the past four decades (West and Dally, 1959), although the correlation among the atypical symptoms is modest (Posternak and Zimmerman, 2002). Patients with atypical depression may respond better to MAOIs than to TCAs or placebo, as demonstrated in one series (e.g., Quitkin et al., 1991); however, the advantage may have modest clinical relevance (Joyce and Paykel, 1989). The SSRIs may be preferable first-line agents in these patients (Roose, 1994). Patients with atypical depression may be more likely to have a history of symptoms of hypomania than patients with a typical pattern of symptoms. In contrast with melancholic and psychotic depression, preliminary data have suggested that atypical depression may be associated with exaggerated negative feedback control of the hypothalamic-pituitary-adrenal (HPA) axis (Levitan et al., 2002). Seasonal Depression Seasonal or “winter” depression (SAD) is distinguished among depressive subpopulations by its differential response to treatment. Decreased levels of DA transporter

in the striatum have been reported in SAD, and remitted patients relapse when challenged with the catecholamine depleter α-methyl-para-tyrosine (AMPT) (Lam et al., 2001). Genetic polymorphism variation in the 5HT2A receptor gene may be associated with SAD (Arias et al., 2001). Specifically, several studies support the rapid efficacy of phototherapy for this depressive subtype. Furthermore, hypersomnia and carbohydrate cravings may predict responsiveness to light therapy (Berman et al., 1997). Antidepressants can also be a very effective treatment. Comorbid Anxiety Symptoms and Panic Disorder Common neuropathological and neuroendocrine features may lead to anxiety and depressive disorders, and comorbidity is common. Nonspecific anxiety symptoms in depression do not suggest differential antidepressant efficacy or nonresponsiveness (Nelson et al., 1994). Metaanalysis suggests, however, that addition of a benzodiazepine may improve the outcome and decrease dropout rates in patients with depression with anxiety compared to administration of an antidepressant alone. The benefit of adjunctive benzodiazepine treatment must be balanced against the risks of dependence and accident proneness (Furukawa et al., 2001). Approximately one third of patients with depression may experience concurrent panic attacks (Clayton, 1990). Because comorbid panic attacks are associated with a worse acute and long-term prognosis (Coryell et al., 1988), such dually diagnosed patients should be prescribed agents with known antipanic efficacy—such as MAOIs, TCAs, SSRIs, or venlafaxine. In patients with comorbid anxiety disorder and major depression, the SSRIs and venlafaxine are generally considered first-line therapies. A history of panic attacks may predict a poor treatment outcome and a greater number of treatments and side effects in the acute treatment of BPD (Feske et al., 2000). In STAR*D, patients who were anxious and depressed who failed to respond in Phase I to citalopram did very poorly in subsequent phases (Fava et al., 2008). Optimal strategies for refractory depressives with anxiety are needed. Bipolar Depression Patients with bipolar depression may respond less consistently to standard antidepressants and commonly develop treatment-resistant depression. They also may have a higher rate of psychotic depression, and early-onset psychotic depression may be a form fruste of BPD. High depression scores during mania predict subsequent depression, and 16% of patients treated for a first episode of mania will cycle into depression over the following 2 years (Zarate et al., 2001). The efficacy of standard marketed antidepressants in BPD is, surpris-

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION

ingly, not well established (reviewed in Thase and Sachs, 2000). None of the available antidepressants have demonstrated efficacy in two well-powered and controlled trials, and the FDA has never approved an antidepressant specifically for depression BPD, although lamotrigine was recently approved for the long-term maintenance treatment of bipolar I to delay the onset of recurrent mood episodes, and olanzapine–fluoxetine combination (Tohen et al., 2003) is now approved for bipolar depression. Bipolar disorder is associated with autoimmune thyroiditis, and low or low-normal thyroid function may be a marker of a poor response to antidepressants in BPD (Cole et al., 2002). The appropriate duration of antidepressant therapy in bipolar depression has not been established. Especially for individuals with bipolar I, mood stabilizers are necessary to protect against dangerous manic switching, and addition of a second mood stabilizer is often as effective as addition of marketed antidepressants, though prone to induce intolerable side effects in some patients. Quetiapine (300–600 mg/day) has been reported to be significantly more effective than placebo in patients with bipolar I and II depression (Thase et al., 2006) and is now FDA approved for that use. Lithium has proven efficacy in bipolar depression and protective properties against suicide, and carbamazepine (and, by extension, possibly oxcarbazepine) has modest antidepressant properties. The SSRIs are considered first-rank antidepressants for episodes of bipolar depression and can be robustly effective in some patients with limited mania induction if patients are maintained on mood stabilizers (this may not always be necessary in patients with bipolar II). The SSRIs are generally favored in terms of efficacy over tricyclics (Bauer et al., 1999), which also have a high propensity to induce mania; however, a recent randomized study failed to find a difference between placebo and imipramine or paroxetine, except post hoc in the low lithium-level subgroup (Nemeroff et al., 2001). The SSRIs are generally safe in combination with lithium, but several cases of serotonin syndrome have been reported. Metabolic effects are of concern for atypical antipsychotics. Bupropion is favored by experts in BPD, and its noradrenergic properties may be helpful in treating the severe anergy, reversed vegetative symptoms, and psychomotor retardation often seen in bipolar depression. It also is not prone to cause the weight gain and sexual side effects that can be induced by concomitant medications and may have a lower rate of manic switch than TCAs (Sachs et al., 1994). Venlafaxine was associated with a much higher switch rate into hypomanic or mania than bupropion in a recent multicenter study (Leverich et al., 2006). Nefazadone and mirtazapine, by virtue of their sleep-enhancing properties, may also have a place in the treatment of bipolar depression. Limited evidence suggests that some patients with bipolar (especially those with depressions characterized

499

by anergia, psychomotor retardation, and hypersomnia) may be more responsive to MAOIs (in particular tranylcypromine) than TCAs (Himmelhoch et al., 1972; Thase et al., 1992) Response rates to MAOIs in bipolar depression are estimated overall to be 50%–60% (Malinger et al., 1999), and MAOIs may be an alternative to ECT for refractory patients. Lamotrigine is an antiglutamatergic agent that decreases presynatic release of excitatory neurotransmitters and is the most promising new treatment for BPD based on a large, uncontrolled database and published double-blind study (Calabrese et al., 1999). It has putative efficacy in bipolar depression and decreases the subsequent relapse rate in rapidly cycling bipolar patients. Several studies suggest that the anticonvulsant carbamazepine also has antidepressant properties (Post et al., 1997). Controlled trials do not support the efficacy of gabapentin, though its sleep-promoting and anxiolytic properties may be useful in selected individuals. Electroconvulsive therapy is highly effective in unipolar and bipolar depression and may be particularly effective in patients who are delusional. Patients characterized as bipolar may have more rapid improvement and require fewer treatments than patients characterized as unipolar (Daly et al., 2001). Although almost all antidepressants have been associated with induction of a manic switch in patients who were bipolar depressed, evidence suggests that bupropion and the SSRIs may be less likely to cause this phenomenon than TCAs or MAOIs (Peet, 1994; Leverich et al., 2006). Antidepressant medication in the patient with bipolar may lead to cycle acceleration (Post and Weiss, 1995) or mania induction, but the risk of mania or hypomania induction in patients maintained on mood stabilizer therapy is probably less than 10% during the acute phase of treatment (Thase and Sachs, 2000). Given the severe morbidity of bipolar illness and the striking paucity of clinical trials, this subtype of affective illness should become a prime agenda for future research and drug development. Geriatric Depression Depression that recurs or first emerges late in life may be underappreciated and undertreated (Lebowitz et al., 1997). Relatively few controlled trials of antidepressants have been conducted in depressed populations older than age 65 years (Roose and Schatzberg, 2005). Available evidence suggests that TCAs and SSRIs are likely equivalent in efficacy (Schneider, 1996). However, there is a paucity of positive data on SSRIs or SNRIs being more effective than placebo. Large-scale trials have at times been needed to demonstrate statistical superiority over placebo (Tollefson et al., 1995). In one recent trial, venlafaxine, fluoxetine, and placebo all produced high response rates (Schatzberg and Roose, 2006).

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Too few studies in the very old who are depressed (that is, older than age 85 years) have been conducted to draw conclusions concerning antidepressant efficacy. In one recent trial, Roose and colleagues (2004) failed to observe statistical superiority of citalopram over placebo. Infirmity may reduce responsiveness in the elderly and make them more prone to side effects. The effects of TCAs on cardiac conduction, cognition, and blood pressure may limit their use in geriatric populations with cardiac disease, cognitive decline, and/or proneness to falling. Nevertheless, given that TCAs can be quite effective in the elderly (Roose, Glassman, et al., 1994), occasions may arise to prescribe such agents. Desipramine and nortriptyline may be the preferred tricyclic agents because they have fewer anticholinergic, sedative, and cardiovascular effects than the other agents. The clinician must be aware that SSRIs may alter metabolism of other drugs, such as β -adrenergic blockers, and displace highly protein-bound drugs, such as coumadin. Among the least protein-bound antidepressants, venlafaxine may be an advantageous choice for patients who are taking coumadin. Bupropion may also be efficacious in elderly patients (Branconnier et al., 1983). Additionally, stimulants may be effective in geriatric patients who are medically ill with depressive symptoms characterized by apathy (Satel and Nelson, 1989). Further considerations on how medical illnesses may influence treatment choice are reviewed below.

tify biological predictors of response to antidepressants have been largely unsuccessful. Biological assays have had limited clinical utility in the pharmacotherapy of depression (Joyce and Paykel, 1989), although pharmacogenetics offer great promise. Monoamine Markers Many groups have examined the correlation of varied monoamine markers with antidepressant response. Several have reported that low urinary levels of 3-methoxy-4-hydroxyphenylglycol (MHPG), a noradrenaline metabolite, predict responsiveness to noradrenergic TCAs—imipramine, nortryptiline, maprotiline treatment; however, some findings contradict this. The significance of this association is questionable, as MHPG levels may not reliably predict the response to other antidepressant treatments. Consistency of results may be confounded by variance in circadian rhythm, diet, stress, psychomotor activity, and activation of neurotransmitter systems that indirectly influence catecholamine activity. In a unique invasive small-n study of NE and DA release via internal jugular sampling in refractory unipolar depression, deficits in brain NE and DA levels were observed compared to healthy controls (Lambert et al., 2000). Although multiple clinical markers of serotonergic alteration exist in drug-free patients with depression, the ability to correlate treatment response to these biological markers reliably also does not exist.

Dysthymia Dysthymia is responsive to a variety of antidepressants, including TCAs, MAOIs, and SSRIs (e.g., Thase et al., 1996). The reversible inhibitor of MAO-A, moclobemide, at high doses has efficacy comparable to that of imipramine and is superior to placebo (Versiani et al., 1997). Interpretation of studies in this area is limited by the variability of diagnostic criteria and the use of heterogeneous patient populations (inclusion of patients with comorbid major depression). The relationship of dysthymia to major depression remains unclear; however, it is well established that patients who are dysthymic are at significantly greater risk for development of major depression. In elderly males, dysthymia may relate to a hypogonadal state with low testosterone levels (Seidman et al., 2002). Fluoxetine has been reported to be of limited efficacy in geriatric dysthymic patients (Devanand et al., 2005). Biological Predictors of Response Considerable research over the past three decades has focused on elucidating the pathophysiology of depression and the mechanism of antidepressant action. Despite clear-cut advances in this endeavor, efforts to iden-

Dexamethasone Suppression Test as a Marker An abnormal response to the dexamethasone suppression test (DST) is found in less than one half of patients with depression and is most frequent in individuals who are psychotically depressed or very severely depressed (Nelson and Davis, 1997) and least frequent in outpatients who are mildly ill. Nonsuppression does not correlate with response to medication treatment; however, nonsuppression was associated with a much lower rate of response to placebo treatment. In a metaanalysis of 412 patients, DST nonsuppressers responded much more poorly to placebo treatment than did DST suppressers (that is, 14% vs. 36%, respectively) (Ribeiro et al., 1993). These findings underscore the increased relative benefit of antidepressant medication in DST nonsuppressers. Some studies suggest that pretreatment DST nonsuppression may be associated with a poor longterm outcome, specifically an increased risk of significant suicidal behaviors (e.g., Coryell, 1990). Nonsuppression appears to increase the risk of subsequent suicide tenfold (Coryell and Schlesser, 2001). Also, nonsupression after a course of treatment has been associated with higher rates of recurrence on longer term follow-up (Ribeiro et al., 1993). Despite early hopes, the DST has not proven

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501

clinically useful in predicting the differential response to treatment. However, an exaggerated cortisol response using the dexamethasone/corticotpropin-releasing hormone (CRH) test may be predictive of subsequent relapse in treatment responders (Zobel et al., 2001). One study found a reduced skin vasoconstrictor response to the corticosteroid beclamethasone in depression compared with controls, suggesting subsensitivity of skin glucocorticoid receptor (GR) signal transduction, that was not correlated with DST results (Cotter et al., 2002). Thus, pituitary-level GR function may not reflect other tissue-specific changes in depression.

that s/s patients actually experience greater dropout rates due to adverse events, and that may explain the poorer responses observed by others (Perlis et al., 2003; Murphy et al., 2004). In addition, genetic variants for the serotonin 2A receptor have been reported to predict positive responses or side effects with SSRIs (Murphy et al., 2003; McMahon et al., 2006). A recent report (Perlis et al., 2007) suggests alleles for CREB protein may predict those male patients who experience suicidal ideation with SSRIs.

Sleep Studies

Careful medical assessment remains crucial in guiding the safe selection of antidepressant treatment.

Patients with depression commonly manifest sleep abnormalities, many of which have been assessed for the ability to predict responsiveness to treatment. These include decreased sleep continuity, decreased slow-wave sleep, and reduced rapid-eye-movement (REM) latency and may be more prominent in patients with recurrent and hence more virulent depressive illness (Jindal et al., 2002). Agents that block 5-HT2 receptors, such as nefazadone and mirtazapine, may increase slow-wave sleep toward normal in depression (Sharpley et al., 1994). Reduced REM latency reliably correlates with a favorable response to acute treatment with TCAs and ECT (Joyce, 1992). Subsequently, reduced REM latency did not predict responsiveness to fluoxetine but did predict a poor response to placebo (Heiligenstein et al., 1994). Pretreatment-reduced REM latency may also be associated with higher rates of relapse (Giles et al., 1987). Overall, these findings underscore the value of medication treatment in patients with reduced REM latency but do not provide a rationale for predicting specific responses. In sum, biological markers do not suggest specific antidepressant choice. However, abnormalities on the DST and shortened REM latency reliably indicate better response with antidepressant medications than placebo treatment. Furthermore, these markers may have relevance to long-term prognosis. Although these tests are not used in common practice, it remains to be tested whether they can be exploited to effectively guide longterm clinical management. Pharmacogenetics Pharmacogenetics offer an opportunity to develop customized therapies for patients with depression. Data indicate that Caucasian patients with the short/short (s/s) form of the serotonin transporter respond poorly to SSRIs (Smeraldi et al., 1998; Zanardi et al., 2000; Hu et al., 2007). In contrast, Asians with the s/s genotype respond better to SSRIs than do those with the long form (Kim et al., 2006). Others have reported

Medical Factors in Antidepressant Selection

Cardiovascular disease Depression is associated with reduced heart rate variability that may reflect abnormal autonomic nervous system modulation. Furthermore, clinical depression is a risk factor for coronary artery disease and diabetes and is associated with higher rates of mortality after a myocardial infarction (MI). Most SSRIs (for example, sertraline, paroxetine, and fluoxetine) and bupropion have minimal effects on heart rate, cardiac conduction, and blood pressure. Hence, they are good first choices for patients with cardiovascular disease. The SSRIs have been associated with a rare incidence of severe sinus node slowing (Glassman et al., 1993). Further experience with these drugs in cardiac patients is warranted before their safety is firmly established, but observational data suggest that SSRIs may have a protective effect against MI (Sauer et al., 2001). Although TCAs have been safely employed in patients with cardiovascular disease, their effects on blood pressure and cardiac conduction should limit their common use as a first-line agent. The TCAs have conduction effects similar to those of class I anti-arrhythmic agents. In large-scale clinical trials, these latter agents have been associated with increased mortality when administered chronically to patients with ventricular arrhythmias following MI and with atrial fibrillation. Potentially, TCAs confer similar risks in this cardiac population (Glassman et al., 1993). More studies are required to assess the safety of antidepressant medications in patients with underlying conduction abnormalities and ischemic heart disease. Caution regarding hypertension needed to be exercised particularly when administering high doses of immediate release (i.r.) venlafaxine. Approximately one in eight patients experienced blood pressure elevation when prescribed 300 mg or more daily of the i.r. compound. The extended release formulation appears to be less problematic in part because of the prolonged release as well as lower doses used. Duloxetine has not

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produced a significant increase in blood pressure. Conversely, trazodone and nefazodone have been associated with significant decreases in blood pressure.

be less effective against vegetative symptoms such as fatigue. Targeting Response and Duration of Treatment

Neurological diseases Seizures due to antidepressants are generally dosedependent and can occur in patients with a genetically or environmentally reduced seizure threshold. Medications to be potentially avoided in patients with a history of seizure disorder include maprotiline, clomipramine, and bupropion (in head injury patients in particular); phenelzine, tranylcypromine, fluoxetine, paroxetine, sertraline, venlafaxine, and trazadone have a relatively low risk of seizure (Rosenstein et al., 1993; Charney et al., 1998; Pisani et al., 2002). Poststroke depression occurs in about one third of patients and affects cognition and survival at 1 and 2 years. Recent review of the literature indicates that poststroke depression is not specific to patients with specific neuroanatomical lesions (that is, left frontal lesions). Fluoxetine has been found to effectively treat poststroke depression, and the SSRIs as a class may be safer and induce fewer side effects than older agents, although according to Robinson et al. (2001), nortriptyline may have superior efficacy than fluoxetine and may be a noradrenergic alternative to the SSRI class in this population (Gainotti and Marra, 2002). Head injury is associated with increased risk of major depression for decades afterward (Holsinger et al., 2002). Patients with Parkinson’s disease have a high rate of depression as well as treatment-induced psychotic symptoms. Other illnesses The pharmacological effects of some antidepressants that lead to bothersome side effects may be exploited positively. For example, the antihistaminergic activity of mirtazapine and many TCAs may be useful for increasing weight gain in anorectic patients (for example, secondary to cancer or other systemic illnesses) or for patients with common allergies. Conversely, these agents may best be avoided in patients who are morbidly obese. For patients with premorbid sexual dysfunction, bupropion, nefazodone, and trazodone may be the most benign agents. Most others classes of drugs are associated with impotence or anorgasmia. Anticholinergic properties of the TCAs may complicate prostatic hypertrophy or narrow-angle glaucoma. Treatment of chronic active hepatitis and malignancies with interferona immunotherapy induces depression via putative activation of proinflammatory cytokine networks that may affect serotonin metabolism and can be effectively treated with SSRIs (Dieperink et al., 2000; Bonaccorso et al., 2002) or even prevented with them (Musselman et al., 2001). However, the SSRIs tend to treat the mood symptoms (such as suicidal ideation) but may

Little attention has been given to developing a clinically useful definition of an adequate treatment response. Definitions abound in the literature (Prien et al., 1991). Most studies have defined response as a 50% decrease in the HAM-D score or some other measure of the symptom state. Limits on maximum absolute scores may also be employed. Although the use of standardized scales is essential to the study of depression, the vast majority of clinicians have not found such instruments useful. Rating instruments, upon which most of what we know about depression is based, may not characterize key dimensions of patients’ depression: overall severity, social/occupational adjustment, and quality of life. Social adjustment improves with greater responses or remission (Miller et al., 1998). Furthermore, patients fulfilling categorical definitions of response may still have residual symptoms that are significant. For example, partial responders may have an increased risk for suicide, impaired occupational function, and markedly greater rates of relapse (Fawcett, 1994; Paykel et al., 1995). These phenomena underscore the fact that depression is a chronic illness, typified by periods of full and partial remission alternating with depressive episodes. Further work is needed to assess whether more aggressive antidepressant therapy is warranted in patients with minor residual symptoms. Although depression is an enduring illness, little direct evidence is available to guide the clinician as to how long a patient should be medicated. Ten to 15 years after an index first depressive episode, approximately 80%– 90% of patients can be expected to experience a recurrence (e.g., Kiloh et al., 1988; Lee and Murray, 1988). Studies of maintenance treatment have typically lasted up to 1 year, reliably suggesting that continued treatment reduces the risk of relapse. In one 3-year maintenance study, 20% of patients relapsed on full-dose imipramine, whereas 80% relapsed on placebo (Frank et al., 1990). The most well established predictor of a recurrence or relapse of major depression is a history of multiple previous episodes (Lee and Murray, 1988; Winokur et al., 1993). Keller and colleagues (1982) found that patients with a history of three or more prior depressive episodes had approximately a 1.5-fold greater risk of relapse after 1 year than patients with two or fewer prior episodes. Given these considerations, the duration of treatment is a clinical decision that should be based on individual patient factors: presence of continued depressive symptoms, number of previous episodes, potential impairment predicted from a recurrence, and medication tolerance (Charney et al., 1998).

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32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION

Treatment-resistant depression Historically, 40%–50% of patients with depression who are prescribed antidepressants do not experience a full response in a timely manner (Frank et al., 1993). Treatment resistance is defined by failure to respond for an adequate period (6–8 weeks) to a maximal dosage (or blood level) with an adequate decrease in depression ratings to one antidepressant or two antidepressants from different classes. Augmentation strategies may be preferable in patients labeled as partial responders to treatment. Management of this apparently treatmentrefractory group must be methodical (Berman et al., 1997). Potential factors contributing to nonresponse must be considered: inadequacy of the trial, medication intolerance, noncompliance, underlying medical illness, and comorbid psychiatric conditions or substance use. Once true treatment resistance has been established, there are multiple treatment options that fall into four main categories: optimization/maximization, switching, combination, and augmentation (Table 32.4). Treatment with antidepressants that have a dual mechanism of action via inhibition of serotonin and NE uptake (SNRIs) may have an advantage in terms of improved rate of remission over SSRIs (Thase, Entsuah et al., 2001). Thus, venlafaxine and possibly duloxetine or milnacipran may be of value in treating patients nonresponsive to SSRI therapy. This may be due in part to increasing activity in the PKA-related second-messenger system pathway. As well, SSRIs decrease burst firing in the locus coeruleus and agents that block NE reuptake increase burst firing and may thus increase alertness and decrease depression through this mechanism (Szabo and Blier, 2001). Optimization/maximization When a patient does not respond fully to an initial dose of an antidepressant, the clinician may improve the response by 20%–30% simply by increasing the dose and/or duration of the trial. However, it is important to first consider whether the patient has fully complied with treatment because poor adherence to therapy may account for as many as 20% of treatment-resistant cases. Discrepancy exists in defining an optimal dose. For nortriptyline, desipramine, and imipramine, blood levels of these agents and metabolites may best guide the clinician. As tolerated, gradual dose escalation up to the highest recommended doses (for example, as indicated in the Physicians Desk Reference [PDR]) may ensure that therapeutic drug levels are attained. Conversely, there have been reports on the effective use of “megadoses” of TCAs (Garvey et al., 1991) and MAOIs (Amsterdam, 1991), doses higher than those maximally suggested by the PDR. The unclear medical risks of using such doses should limit their use to highly refractory

32.4 Management of Treatment-Resistant Depression TABLE

Efficacy a

Replicability b

Lithium augmentation

111

111

ECT (bilateral or high-intensity unilateral)

111

111

lnterclass switching

11/111

111

Thyroid augmentation

11/111

11

Stimulant augmentation

1/11

11

SSRI/TCA combination

11

1

Buspirone augmentation

11

1

High-dose MAOI

11

1

Estrogen in postmenopausal women

11

1

Antiglucocorticoid therapy

1/11

1

1

1

Pindolol augmentation Bupropion/SSRI combination

1/11

1

Intraclass switching

11

1

Transcranial magnetic stimulation

1

1

SSRI/mirtazapine combination

11

1

Pramipexole augmentation

1

1

Olanzapine augmentation of fluoxetine

11

11

Reboxetine augmentation of SSRI

1

1

SSRI/nefazodone combination

1

1

Adjunctive gabapentin

1

1

Adjunctive aripiprazole

11

11

ECT: electroconvulsive therapy; MAOI: monoamine oxidase inhibitor; SSRI: selective serotonin reuptake inhibitor; TCA: tricyclic antidepressant. a. Efficacy was rated as modest (1), moderate (11), or very (111) effective. b. Replicability was rated as follows: (1) open studies; (11) controlled studies and/or multiple open studies; (111) multiple controlled studies. Source: Charney et al. (1998).

patients. Although most trials are recommended to last at least up to 6 weeks—as supported by available research—a subset of patients may respond especially slowly (Georgotas and McCue, 1989; Thase and Rush, 1995); therefore, extending a trial beyond 6 weeks may be useful in some patients. It is recommended that this strategy be reserved for patients demonstrating at least a mild to moderate response to an ongoing treatment regimen by 5 or 6 weeks. Switching Monotherapy offers the advantages of improved compliance, lower cost, and fewer side effects. For these practical reasons, many clinicians choose to discontinue one medicine and initiate another when a patient fails to respond. Switching response rates generally range from 40%–60% over various classes of antidepressants.

504

MOOD DISORDERS

Interclass switching. Interclass switching has been the logical first choice, as it represents a shifting of pharmacological strategies. Thus, although overall response rates with SSRIs and SNRIs are similar, different subgroups of patients may respond preferentially to one drug versus another. Although limited empirical work has assessed which class of antidepressant should best follow a failed trial, a pharmacological rationale could be made to use agents with significantly differing mechanisms of action (for example, move from SSRIs to agents with significant noradrenergic activity such as TCAs, venlafaxine, bupropion, MAOIs, or mirtazapine). Multiple studies suggest a range of response rates to interclass switching—with approximately one half of the patients adequately responding (Nelson, 1997b; Thase and Rush, 1995). Thus, approximately 50% of patients with chronic depression responded when switched from imipramine to sertraline or vice versa (Thase et al., 2002). STAR*D assessed switching from citalopram to one of three agents—venlafaxine, bupropion, or sertraline. The three yielded similar response rates (Rush et al., 2006). Intraclass switching. Intraclass switching has been only modestly successful with the TCAs (Nelson, 1997b). Available studies on intraclass switching with the SSRIs are generally limited by the use of mixed patient populations consisting of patients who exhibited resistance and intolerance. Although preliminary open data suggest that response rates, for instance in switching from fluoxetine to citalopram or from sertraline to fluoxetine, may be substantial (Thase et al., 1997; Thase, Feighner, et al., 2001), the response rate of switching from citalopram to either venlafaxine or sertraline was not impressive (Rush et al., 2006). Electroconvulsive therapy For patients who are severely or psychotically depressed, and for patients with prominent suicidality or who are refusing food and hydration, a switch from pharmacological management to ECT should be considered. Approximately one half of TCA-resistant patients with depression may be expected to demonstrate a response (Prudic et al., 1990). Although the likelihood of response is diminished in patients who have failed multiple medication trials, are female, and have severe depression, an ECT trial merits strong consideration. Highdosage right unilateral and bilateral ECT appears to produce equivalent response rates and is twice as effective as low- or moderate-dose unilateral ECT (Sackeim et al., 2000). However, bilateral ECT results in greater cognitive impairment. Indeed, a recent community-based trial pointed to considerable memory effects (Sackeim et al., 2007). Without maintenance therapy, the majority of patients will relapse 6 months after an ECT response (Sackeim et al., 2001). At 2 years, one half of patients

relapse after ECT plus maintenance antidepressant therapy, whereas over 90% are relapse free if they receive maintenance ECT treatment over the same period (Gagne et al., 2000). Combination therapy Combination strategies involve the use of multiple antidepressant medications from different classes. This approach represents a broadening of pharmacological targets, an approach that may be particularly attractive when a patient has already demonstrated a modest response and the clinician wants to minimize the risk of losing these gains. The large permutations of such possible combinations have prevented systematic study of many newer medication combinations. Favorable anecdotal reports need to be followed up with controlled trials. Combinations supported by a preclinical rationale should also be pursued. For example, the a2-adrenergic antagonism of mirtazapine may potentiate SSRImediated serotonergic neurotransmission via blockade of heterologous autoreceptors. Tricyclic antidepressant–monoamine oxidase inhibitor combinations. Initial successes with TCA-MAOI combinations in case series with over 200 patients suggest that over one half of TCA nonresponders may respond to the addition of MAOIs (Charney et al., 1998). The abundance of safer treatment options that do not risk hypertensive crises should make this strategy avoidable. Tricyclic antidepressant–selective serotonin reuptake inhibitor combinations. TCA-SSRI combinations may be a useful strategy. A case series of 30 refractory patients, predominantly on TCAs, demonstrated an 87% response rate when fluoxetine was added (Weilburg et al., 1989). Such combinations have also been used successfully in geriatric populations (Seth et al., 1992). Furthermore, preliminary evidence suggests that a desipramine–fluoxetine combination may hasten the treatment response in newly treated patients (Nelson et al., 1991). Case reports suggest that reboxetine plus citalopram may also be effective in refractory depression (Dursun and Devarajan, 2001). Bupropion–selective serotonin reuptake inhibitor combinations. Bupropion-SSRI combinations were described early on in approximately 50 refractory patients with depression in two case series (Boyer and Feighner, 1995; Bodkin et al., 1997). Twenty seven, or approximately one half, demonstrated improvement. Twelve patients discontinued therapy because of side effects. The recent STAR*D indicated approximately 30% of patients who had failed to respond to citalopram remitted when bupropion was added (Trivedi, Fava, et al., 2006).

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION

Augmentation Augmentation involves the addition of an agent that is not intrinsically a full antidepressant to an ongoing antidepressant treatment for the purposes of potentiating the activity of the antidepressant. Lithium augmentation. Lithium augmentation is a strategy based on preclinical observations that lithium potentiates TCA-mediated serotonergic neurotransmission (De Montigny et al., 1981). Numerous case series and seven of nine placebo-controlled trials established the efficacy of lithium in the treatment of refractory depression (Charney et al., 1998), with response rates typically between 30% and 70%. This support made lithium augmentation the most proven treatment strategy in refractory depression. Although a fraction of patients will demonstrate dramatic responses within 1 week of adding lithium, more commonly the response is gradual, evident after 3 weeks. Unclear issues in the management of these patients include how long lithium should be continued. Lithium augmentation is probably effective in patients treated with SSRIs, but the data are not as compelling as those related to TCAs. Indeed in STAR*D, lithium augmentation resulted in remission in less than 20% of patients (Nierenberg et al., 2006). Mirtazapine augmentation. Open and randomized pilot data suggest that mirtazapine augmentation of SSRIs and possibly other antidepressants may result in about a 60% response rate in refractory patients (Carpenter et al., 2002). Atypical antipsychotic augmentation. Combining atypical antipsychotic medications with SSRIs may increase levels of DA and/or NE in the PFC, resulting in an improved antidepressant response. Apathy has also been observed as a side effect of SSRIs and may be reduced by addition of an atypical antipsychotic such as olanzapine. Blockade of 5-HT2A and 5-HT2C receptors may also decrease some SSRI-induced side effects, but blockade of 5-HT2C receptors may also be responsible for some of the weight gain potential of this class of drug. Pilot test data suggested that addition of olanzapine to SSRIs was effective and rapidly acting (Shelton et al., 2001), particularly in more severely refractory patients. Olanzapine–fluoxetine combination has been demonstrated to be effective in refractory depressives (Thase et al., 2007). The atypical agent quetiapine has been shown to attenuate the stress-induced decrease in BDNF expression in the hippocampus (Xu et al., 2002), which could protect against stress-related neuroplastic changes in affective and anxiety disorders. Aripiprazole augmentation appears to convert SSRI nonresponders to responders and is now approved by the FDA. There are also positive data for risperidone augmentation.

505

Thyroid hormone augmentation. Initial open-label reports on the addition of thyroid hormone (specifically triiodothyronine) to antidepressant regimens suggested that it may hasten and potentiate the response. Systematic studies have yielded mixed results, both supporting (Goodwin et al., 1982; Joffe et al., 1993) and refuting (Gitlin et al., 1987; Thase et al., 1989) its efficacy. In one placebo-controlled study (Joffe et al., 1993), 59% (10/17) versus 19% (3/19) of triiodothyronineand placebo-treated patients, respectively, demonstrated a response. In STAR*D, triiodothyronine appeared if anything more effective than lithium (Nierenberg et al., 2006). The safety and tolerability of thyroid augmentation make it an alternative to consider. Stimulant augmentation. Addition of stimulants to an ongoing antidepressant regimen would expectably enhance monoamine neurotransmission. The use of stimulant augmentation in over 60 patients in combination with TCAs, MAOIs, and SSRIs has been described in published case series (Nelson, 1997b). Stimulant augmentation was moderately effective and not associated with tolerance problems. These agents have been found to be relatively safe, with a low incidence of dangerous cardiac side effects (Satel and Nelson, 1989). Abuse potential has limited the popularity of this combination. Furthermore, controlled studies have not been reported. Serotonin-1A augmentation. Prevailing theories of antidepressant action suggest that efficacy derives from enhanced postsynaptic 5-HT1A-mediated neurotransmission and that the delay in efficacy may be due to the timing of presynaptic 5-HT1A receptor desensitization. Stimulation of 5HT1A receptors increases levels of BDNF, which may be associated with antidepressant activity, and knocking out the gene for the 5-HT1A receptor decreases the responses to antidepressants in animal models of depression such as the Forced Swim Test. Augmentation with buspirone, a partial agonist at this receptor, has been tested in an open-label manner in treatment-resistant depression (Nelson, 1997b). Up to two thirds of patients remitted. In STAR*D, buspirone was about as efficacious as bupropion as an augmentator (Trivedi, Fava, et al., 2006). Pindolol is a β -adrenergic antagonist and a 5-HT1A antagonist putatively selective for presynaptic sites. In two openlabel studies with a total of 25 medication-refractory patients with depression, pindolol augmentation (2.5 mg thrice daily) was associated with a complete remission in approximately two thirds of the sample, achieved within 1 week (Artigas et al., 1994; Blier and Bergeron, 1995). A subsequent controlled trial in 10 SSRI-refractory patients failed to demonstrate its efficacy over placebo augmentation (Moreno et al., 1997). Most investigators currently believe pindolol is a better facilitator of response—particularly in patients who are more mildly ill in primary care settings—than it is an augmentation.

506

MOOD DISORDERS

Estrogen augmentation. Despite a half-century’s investigation of the role of estrogen in the treatment of depression, a clear understanding has not emerged. Discovery of a second estrogen receptor with high concentrations in the CNS (the β -estrogen receptor) has led to speculation that with stimulation, complex interactions between the canonical α -estrogen receptor and the β -estrogen receptor may give rise to observed hormonal effects on cognition and mood. Evidence suggests that the recently discovered β -estrogen receptor may stimulate increased serotonin levels via transcriptional effects in the raphé nucleus, and estrogen may increase BDNF levels and inhibit MAO-A activity (Gibbs, 1999; Bethea et al., 2000; Gundlah et al., 2001, 2002). Mixed results were found in treatment trials using estrogen as monotherapy in pre- and postmenopausal women, and estrogen does not appear to be useful in preventing postpartum depression. Observations in the literature suggest that estrogen may be an effective augmenting agent (Shapira et al., 1985; Charney et al., 1998; Schneider et al., 1997). For example, postmenopausal women were more than twice as likely to respond to fluoxetine (that is, 40% vs. 17% response rates) if they were concurrently undergoing estrogen replacement therapy (Schneider et al., 1997). In a short 2-week controlled trial, estrogen augmentation of 11 patients who were imipramine resistant was associated with one case of clinical remission and another case of a manic switch. These observations suggest that longer controlled trials of estrogen augmentation in treatment-refractory postmenopausal women are warranted. Recent studies suggest that perimenopausal depression is effectively treated with transdermal estrogen (Schmidt et al., 2000; Soares et al., 2001). This treatment option should be explored only with gynecological consultation, as the effects of long-term estrogen replacement therapy have not been definitively determined. Novel tissue-specific and estrogen β -receptor-specific agents such as raloxifene may be tested in the future as augmentation agents for SSRIs because they affect serotonin neuron function in the raphé. NEW DIRECTIONS Over the past three decades, a proliferation of antidepressant drugs has made the pharmacotherapy of depression effective and well tolerated. Nevertheless, several important limitations remain. 1. Forty to 50% of patients with depression do not experience a timely remission upon initial medication treatment. 2. Although patients may respond to subsequent treatment options, there are no useful clinical or biological predictors of these subsequent treatments. 3. Furthermore, the antidepressant response typically lags weeks behind the institution of treatment.

4. Some patients cannot tolerate therapeutic doses of many medications, and many patients choose to discontinue effective regimens because of significant side effects. 5. Few studies are available to guide the clinician in the long-term pharmacotherapy of depression, the choice of pharmacological strategies in cases of treatment resistant depression, or the management of bipolar depressions. Much remains to be understood about the mechanism of antidepressant action and the pathophysiology of depression. Effort focused beyond the monoamine systems may lead to new classes of agents that will effectively treat depression and, ideally, prevent its emergence. Major depression may be associated with blunted cAMP signaling, and studies have demonstrated that antidepressant treatment results in increased activation of the cAMP second-messenger system. In turn, this increased activation would be expected to set in motion a cascade of intracellular events that would regulate specific target genes, genes that are known to include the transcription factor CREB and BDNF, along with its receptor, trkB. Staining of BDNF in postmortem samples is greater in the hippocampus of psychiatric patients treated with antidepressants compared with those not treated with antidepressants prior to death (Chen et al., 2001). Enhanced levels of BDNF may modify the function of neuronal elements crucial in mood regulation (Duman et al., 1997). Levels of BDNF may be increased by exercise, dietary restriction, estrogen, glutamate AMPA receptor agonists, and cAMP phosphodiesterase-4 inhibitors, as well as by antidepressants. Agents that increase cAMP levels (that is, rolipram and papaverine) have modest antidepressant efficacy when given alone or when added to an ongoing antidepressant regimen (Malison et al., 1997). Compelling preclinical evidence combined with somewhat favorable efficacy studies warrants the development of specific phosphodiesterase-4 inhibitors with potential antidepressant properties for augmentation therapy. Other pharmacological strategies could target other sites along this hypothesized intracellular cascade of events (for example, BDNF agonists and agents that stimulate transcription factors or directly stimulate cAMP or Ca21-activated kinases). Modulation of Neuropeptide and Glucocorticoid Receptors The potential importance of neuropeptides and glucocorticoid signaling for the regulation of behavior and cognition is the result of many decades of research. However, only now are small molecules for neuropeptide receptors and safe antiglucocorticoids becoming available for clinical trials. Substance P, also known as neurokinin, was discovered in 1931. Initial evidence on the successful use of a substance P antagonist in the treatment of major depression (Kramer et al., 1998) was followed by five failed or negative trials (Keller et al., 2006).

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION

Substance P antagonists, similar to imipramine, increased locus coeruleus firing rates, and knockout of the neurokinin-1 receptor for substance P produces adapative changes in 5-HT1A receptors that mimicked antidepressant-induced desensitization (Froger et al., 2001; Maubach et al., 2002). Two trials with substance P antagonists have been positive, but negative trials have also been reported. Further side effects and other neuropeptide-related antidepressant strategies may be developed. Well-established abnormalities in the HPA axis in patients with depression may reflect underlying abnormalities in CRH function. Supporting evidence, summarized elsewhere (Musselman and Nemeroff, 1993), includes findings that CRH causes depressive-like symptoms in animals when injected intracerebroventricularly. As well, early-life administration of CRH reduces memory function, as well as progressive loss of hippocampal neurons and up-regulation of CRH production in the hippocampus (Brunson et al., 2001). Chronic antidepressant treatment appears to reduce stress-induced release and synthesis of CRH but not basal levels (Stout et al., 2002). Furthermore, patients with depression have been found to have elevated levels of CSF CRH. Compelling findings such as these have motivated the development of nonpeptide small-molecule CRH antagonists for testing as antidepressants and anxiolytics. Data indicate that the CRH system may be intricately involved in regulating serotonin output and raphé nucleus firing rate such that antagonists of CRH could have antidepressant effects by augmenting serotonin levels (Penalva et al., 2002). Zobel et al. (2000) and Kunzel et al. (2003) reported on use of CRH antagonist in an open-label inpatient trial although a recent negative placebo-controlled trial was published (Binneman et al., 2008). In a related strategy, the use of steroid synthesis inhibitors or steroid antagonists has been shown to have modest efficacy in lowering depressive symptoms (Murphy, 1997). Data with the antiglucocorticoid mifepristone (RU-486) indicate that it may be rapidly effective in treating psychotic symptoms in delusional forms of depression, which has the highest rate of HPA axis hyperactivity (Belanoff et al., 2001; DeBattista et al., 2006), although there are failed trials as well. Young et al. (2004) have reported positive benefit of mifepristone on cognition in bipolar depression. Agomelatine—a melatonin receptor, 1 and 2 agonist, and a 5HT2 antagonist— appears effective in major depression (Kennedy and Emsley, 2006). Last, there are efforts to develop compounds with novel effects—β3 agonism, NK-2 antagonism, and so on. Modulation of Excitatory Neurotransmitter Activity Glutamate and aspartate signal through a variety of receptors. The NMDA receptor is a ligand-gated ion channel critically involved in excitatory neurotransmission. Aberrant NMDA activity may be of pathophysi-

507

ological importance in neurodegenerative diseases and depression, where decreased neuronal size and loss of glial cells have been observed postmortem. Long-term exposure to antidepressants may alter NMDA receptor subunit expression and function. The efficacy of lamotrigine in bipolar depression and the known effects of many antidepressants on NMDA glutamate receptor binding have led to increased interest in the importance of the excitatory and inhibitory neurotransmitter balance in depression. Ketamine has been reported to have a rapid antidepressant effect in at least two studies (Berman et al., 2000; Zarate, Singh, Carlson, et al., 2006) although memantine had little antidepressant effect (Zarate, Singh, Quiroz, et al., 2006). This is also supported by some evidence of a decrease in CNS γ aminobutyric acid (GABA)ergic activity in depression. Agents that inhibit glutamatergic activity may also be neuroprotective and affect neurotrophic activity. Preliminary evidence indicates that lamotrigine has substantial efficacy in bipolar depression but not in unipolar depression. However, this may be a function of the greater heterogeneity of unipolar disorder, and a subset of patients characterized as unipolar may be identified as responsive with future research. Other agents with antiglutamatergic mechanisms of action are under investigation. Drugs that affect the activity or membrane cycling of AMPA glutamate receptors may also be good candidates for antidepressant trials, and “AMPAkines” are in early testing in affective illness, as well as for cognitive enhancement in patients with mild cognitive impairment and against negative symptoms in schizophrenia. Tianeptine is a French antidepressant that, in contrast to SSRIs, may increase serotonin uptake. In preclinical studies, it has been found to be neuroprotective against stress-induced limbic damage to the hippocampus. It is just as effective as fluoxetine, imipramine, and paroxetine and has demonstrated efficacy compared to placebo (Waintraub et al., 2002). Its mechanism of action may be related to decreasing NMDA glutamate receptor signaling. Dopamine agonists such as the D3 agonist pramipexole have observed efficacy that, in one large trial, was equivalent to that of an SSRI, and pilot data suggest its efficacy in bipolar depression (Zarate et al., 2004) and in treatment-resistant depression. Pramipexole may also be protective against activation of apoptotic cell death pathways and may be neuroprotective. Agents with a similar profile may see further development for depression (Sporn et al., 2000). Alternative or complementary strategies have also been explored in pilot add-on studies using omega-3 fatty acids in treatment-resistant and breakthrough unipolar and BPD. Epidemiological data suggest that high consumption of fish oils is protective against depression and heart disease. In recurrent unipolar disorder, eicosapentaenoic acid was effective compared to placebo after 2 weeks, with improvement in core depressive symptoms (Nemets et al.,

508

MOOD DISORDERS

2002). In a bipolar study, time to relapse was longer in the omega-3-treated group compared to the placebo group (Stoll et al., 1999). Other complementary agents such as chromium, trace minerals, and isoflavones may be tested in the future for their anxiolytic and antidepressant activity. Until recently, there has been almost no capacity to exploit clinically our emerging understanding of the neuroanatomy of major depression. Developed over the past decade, the technique of transcranial magnetic stimulation (TMS) can now be used to affect brain circuitry directly. In this technique, a rapidly generated magnetic field is applied over specific scalp and brain regions. The magnetic field, if of sufficient strength, can alter neuronal firing patterns over a quarter-sized area of cortex. In controlled studies of patients who were treatment resistant, TMS, when applied over the left dorsolateral PFC, has been associated with significant reductions in depressive symptoms compared to sham TMS treatment (Pascual-Leone et al., 1996; George et al., 1997). This innovative modality represents a radical frameshift in the treatment of depression, based on directly altering underlying neurocircuitry, but it may only produce transient improvement and does not appear to approach the efficacy of ECT. Transcranial magnetic stimulation is only able to affect cortical tissue, whereas depression may involve deeper limbic structures not directly accessible via TMS. A recent controlled trial pointed to efficacy in mildly refractory patients (O’Reardon et al., 2007). In sum, advances in neuroscience over the past three decades have led to the development of dozens of antidepressant agents, almost all of which target monoamine systems. A significant number of new and novel agents are in either early clinical development or are under study preclinically for depression. Our present understanding of the pathophysiology of depressive illness suggests many other biological treatment strategies. The next three decades promise radically novel approaches to the current treatment armamentarium. Targeting neuropeptide receptors may lead to effective antidepressants with fewer adverse effects. Targeting DA receptors, signal transduction pathways (for example with phoshodiesterase inhibitors), immunoreceptors, and glutamate and GABA receptors are also future strategies of interest. Neuroprotective strategies and approaches that improve neuroplasticity are also actively being pursued. UPDATES Paroxetine and Pregnancy In 2005, the U.S. Food and Drug Administration (FDA) issued a public health advisory regarding the risks of paroxetine and pregnancy, based on preliminary analyses of two epidemiological studies (http://www.fda.gov/cder/

drug/advisory/paroxetine). A U.S. epidemiologic study of major malformations following first trimester maternal exposure to antidepressants showed a trend towards a 1.5-fold increased risk for cardiovascular malformations for paroxetine specifically. There was also a statistically significant increased overall risk of major congenital malformations in infants exposed to paroxetine compared to other antidepressants. A second, independent retrospective epidemiological analysis utilizing the Swedish national registry database reported a twofold increased risk of cardiac defects in infants exposed to paroxetine, compared with the general population (Källén et al., 2007). These reports resulted in a change of paroxetine’s classification from Pregnancy Category C to D. Bipolar Depression A large NIH-funded effectiveness study of bipolar depression found that adjunctive antidepressant medication did not show increased efficacy relative to mood stabilizer alone, but also was not associated with an increased risk of treatment-emergent affective switch (Sachs et al., 2007). REFERENCES Akiskal, H. (1982) Factors associated with incomplete recovery in primary depressive illness. J. Clin. Psychiatry 43:266–271. Allgulander, C., Hackett, D., et al. (2001) Venlafaxine extended release (ER) in the treatment of generalised anxiety disorder: twentyfour-week placebo-controlled dose-ranging study. Br. J. Psychiatry 179:15–22. Amsterdam, I. (1991) Use of high dose tranylcypromine in resistant depression. In: Amsterdam, J.E., ed. Advances in Neuropsychiatry and Psychopharmacology. New York: Raven Press, pp. 123–129. Amsterdam, I., Maislin, G., and Potter, L. (1994) Fluoxetine efficacy in treatment resistant depression. Prog. Neuropsychopharmacol. Biol. Psychiatry 18:243–261. Arias, B., Gutierrez, B., et al. (2001) Variability in the 5-HT(2A) receptor gene is associated with seasonal pattern in major depression. Mol. Psychiatry 6(2):239–242. Arnold, L.M., Pritchett, Y.L., D’Souza, D.N., Kajdasz, D.K., Ivengar, S., and Wernicke, J.F. (2007) Duloxetine for the treatment of fibromyalgia in women: pooled results from two randomized, placebo-controlled clinical trials. J. Women’s Health (Larchmt) 16(8):1145–1156. Artigas, F., Perez, V., and Alvarez, E. (1994) Pindolol induces a rapid improvement of depressed patients treated with serotonin reuptake inhibitors. Arch. Gen. Psychiatry 51:248–251. Bauer, M., Zaninelli, R., et al. (1999) Paroxetine and amitriptyline augmentation of lithium in the treatment of major depression: a double-blind study. J. Clin. Psychopharmacol. 19(2):164–171. Belanoff, J.K., Flores, B.H., et al. (2001) Rapid reversal of psychotic depression using mifepristone. J. Clin. Psychopharmacol. 21(5): 516–521. Berman, R.M., Cappiello, A., Anand, A., Oren, D.A., Heninger, G.R., Charney, D.S., and Krystal, J.H. (2000) Antidepressant effects of ketamine in depressed patients. Biol. Psychiatry 47(4):351–354. Berman, R.M., Narasimhan, M., and Charney, D.S. (1997) Treatment-refractory depression: definitions and characteristics. Depress. Anxiety 5(4):154–164.

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION Bethea, C.L., Gundlah, C., et al. (2000) Ovarian steroid action in the serotonin neural system of macaques. Novartis Found. Symp. 230:112–130; discussion:130–133. Binneman, B., Feltner, D., et al. (2008) A 6-week randomized, placebo-controlled trial of CP-316,311 (a selective CRH1 antagonist) in the treatment of major depression. Am. J. Psychiatry 165(5):617–620. Blardi, P., De Lalla, A., et al. (2002) Serotonin and fluoxetine levels in plasma and platelets after fluoxetine treatment in depressive patients. J. Clin. Psychopharmacol. 22(2):131–136. Blier, P., and Bergeron, P. (1995) Effectiveness of pindolol with selected antidepressant drugs in the treatment of major depression. J. Clin. Psychopharmacol. 15:217–222. Bodkin, I.A., Lasser, R.A., Wines, I.D., Gardner, D.M., and Baldessarini, R.I. (1997) Combining serotonin reuptake inhibitors and bupropion in partial responders to antidepressant monotherapy. J. Clin. Psychiatry 58:137–145. Bonaccorso, S., Marino, V., et al. (2002) Increased depressive ratings in patients with hepatitis C receiving interferon-alpha-based immunotherapy are related to interferon-alpha-induced changes in the serotonergic system. J. Clin. Psychopharmacol. 22(1):86–90. Boyer, W.F., and Feighner, I.P. (1995, May 27) The combined use of fluoxetine and bupropion. Presented at the annual meeting of the American Psychiatric Association, Miami, FL. Branconnier, R.J., Cole, J.O., Ghazvinian, S., Spera, K.F., Oxenkrug, G.F., and Bass, I.L. (1983) Clinical pharmacology of bupropion and imipramine in elderly depressives. J. Clin. Psychiatry 44(5, Sec. 2):130–133. Brunson, K.L., Eghbal-Ahmadi, M., et al. (2001) Long-term, progressive hippocampal cell loss and dysfunction induced by early-life administration of corticotropin-releasing hormone reproduce the effects of early-life stress. Proc. Natl. Acad. Sci. USA 98(15):8856–8861. Bymaster, F.P., Dreshfield-Ahmad, L.J., Threlkeld, P.G., Shaw, J.L., Thompson, L., Nelson, D.L., Hemrick-Luecke, S.K., and Wong, D.T. (2001) Comparative affinity of duloxetine and venlafaxine for serotonin and norepinephrine transporters in vitro and in vivo, human serotonin receptor subtypes, and other neuronal receptors. Neuropsychopharmacology 25(6):871–880. Calabrese, J.R., Bowden, C.L., et al. (1999) A double-blind placebocontrolled study of lamotrigine monotherapy in outpatients with bipolar I depression. Lamictal 602 Study Group. J. Clin. Psychiatry 60(2):79–88. Carpenter, L.L., Yasmin, S., et al. (2002) A double-blind, placebocontrolled study of antidepressant augmentation with mirtazapine. Biol. Psychiatry 51(2):183–188. Casper, R.C., Fleisher, B.E., Lee-Ancajas, J.C., Gilles, A., Gaylor, E., DeBattista, A., and Hoyme, H.E. (2003) Follow-up of children of depressed mothers exposed or not exposed to antidepressant drugs during pregnancy. J. Pediatr. 142(4):402– 408. Chan, C.H., Janicak, P.G., Davis, J.M., Altman, E., Andriukaitis, S., and Hedecker, D. (1987) Response of psychotic and nonpsychotic depressed patients to tricyclic antidepressants. J. Clin. Psychiatry 47:197–200. Charney, D.S., Berman, R.M., and Miller, H.L. (1998). Treatment of depression. In: Schatzberg, A., and Nemeroff, A.C., eds. The American Psychiatric Association Textbook of Psychiatry, 2nd ed. Washington, DC: American Psychiatric Press, pp. 705–733. Chen, B., Dowlatshahi, D., et al. (2001) Increased hippocampal BDNF immunoreactivity in subjects treated with antidepressant medication. Biol. Psychiatry 50(4):260–265. Clayton, P.J. (1990) The comorbidity factor: establishing the primary diagnosis in patients with mixed symptoms of anxiety and depression. J. Clin. Psychiatry 51(11, Suppl):35–39. Clerc, G., Ruimy, P., and Verdeau-Pailles, J. (1994) A double-blind comparison of venlafaxine and fluoxetine in patients hospitalized for major depression and melancholia. Int. Clin. Psychopharmacol. 9:139–143.

509

Cole, D.P., Thase, M.E., et al. (2002) Slower treatment response in bipolar depression predicted by lower pretreatment thyroid function. Am. J. Psychiatry 159(1):116–121. Coryell, W. (1990) DST abnormality as a predictor of course in major depression. J. Affect. Disord. 19:163–169. Coryell, W., Endicott, I., Andreasen, N., Keller, M., Clayton, P., Hirschfeld, R., Scheftner, W., and Winokur, G. (1988) Depression and panic attacks: the significance of overlap as reflected in follow-up and family study data. Am. J. Psychiatry 145:293–300. Coryell, W., and Schlesser, M. (2001) The dexamethasone suppression test and suicide prediction. Am. J. Psychiatry 158(5):748–753. Coryell, W., Tsuang, M., and McDaniel, J. (1982) Psychotic features in major depression: is mood congruence important? J. Affect. Disord. 4:227–236. Cotter, P.A., Mulligan, O.F., et al. (2002) Vasoconstrictor response to topical beclomethasone in major depression. Psychoneuroendocrinology 27(4):475–487. Crane, G.E. (1956) The psychiatric side-effects of iproniazid. Am. J. Psychiatry 112:494–501. Daly, J.J., Prudic, J., et al. (2001) ECT in bipolar and unipolar depression: differences in speed of response. Bipolar Disord. 3(2): 95–104. Danish University Antidepressant Study Group. (1990) Paroxetine: a selective serotonin reuptake inhibitor showing better tolerance, but weaker antidepressant effect than clomipramine in a controlled multicenter study. J. Affect. Disord. 18:289–299. Davidson, R.T. (1992). Monoamine oxidase inhibitors. In: Paykel, E.S., ed. Handbook of Affective Disorders. New York: Churchill Livingstone, pp. 345–358. De Montigny, C., Grunberg, F., Mayer, A., and Deschenes, J.P. (1981) Lithium induces rapid relief of depression in tricyclic antidepressant drug non-responders. Br. J. Psychiatry 138:252–256. DeBattista, C., Belanoff, J., Glass, S., Khan, A., Horne, R.L., Blasey, C., Carpenter, L.L., and Alva, G. (2006) Mifepristone versus placebo in the treatment of psychosis in patients with psychotic major depression. Biol. Psychiatry 60(12):1343–1349. DeBattista, C., Solvason, B., Poirier, J., Kendrick, E., and Loraas, E. (2005) A placebo-controlled, randomized, double-blind study of adjunctive bupropion sustained release in the treatment of SSRIinduced sexual dysfunction. J. Clin. Psychiatry 66(7):844–848. Dessain, E.C., Schatzberg, A.F., Woods, B.T., and Cole, J.O. (1986) Maprotiline treatment in depression. A perspective on seizures. Arch. Gen. Psychiatry 43(1):86–90. Devanand, D.P., Nobler, M.S., Cheng, J., Turret, N., Pelton, G.H., Roose, S.P., and Sackeim, H.A. (2005) Randomized, double-blind, placebo-controlled trial of fluoxetine treatment for elderly patients with dysthymic disorder. Am. J. Geriatr. Psychiatry 13(1):59–68. Dieperink, E., Willenbring, M., et al. (2000) Neuropsychiatric symptoms associated with hepatitis C and interferon alpha: a review. Am. J. Psychiatry 157(6):867–876. Dong, J., and Blier, P. (2001) Modification of norepinephrine and serotonin, but not dopamine, neuron firing by sustained bupropion treatment. Psychopharmacology (Berl.) 155(1):52–57. Duman, R., Heninger, G., and Nestler, E. (1997) A molecular and cellular theory of depression. Arch. Gen. Psychiatry 54:597–606. Dursun, S.M., and Devarajan, S. (2001) Reboxetine plus citalopram for refractory depression not responding to venlafaxine: possible mechanisms. Psychopharmacology (Berl.) 153(4):497–498. Fava, M., Rush, A.J., Alpert, J.E., Alasubramani, G.K., Wisniewski, S.R., Carmin, C.N., Biggs, M.M., Zisook, S., Leuchter, A., Howland, R., Warden, D., and Trivedi, M.H. (2008) Difference in treatment outcome in outpatients with anxious versus nonanxious depression: a STAR*D report. Am. J. Psychiatry 165:342–351. Fawcett, I. (1994) Antidepressants: partial response in chronic depression. Br. J. Psychiatry 165:37–41. Feighner, A.D., Rickels, K., Rynn, M.A., Zimbroff, D.L., and Robinson, D.S. (2006) Selegiline transdermal system for the

510

MOOD DISORDERS

treatment of major depression disorder: an 8-week, double-blind, placebo-controlled, flexible-dose titration trial. J. Clin. Psychiatry 67(9):1354–1361. Feighner, J. (1995) Cardiovascular safety in depressed patients: focus on venlafaxine. J. Clin. Psychiatry 56:574–579. Ferguson, J.M., Mendels, J., et al. (2002) Effects of reboxetine on Hamilton Depression Rating Scale factors from randomized, placebo-controlled trials in major depression. Int. Clin. Psychopharmacol. 17(2):45–51. Feske, U., Frank, E., et al. (2000) Anxiety as a correlate of response to the acute treatment of bipolar I disorder. Am. J. Psychiatry 157(6):956–962. Frank, E., Karp, I., and Rush, A. (1993) Efficacy of treatments for major depression. Psychopharmacol. Bull. 29:457– 475. Frank, E., Kupfer, D., Perel, I., Comes, C., Jarret, D., Mallinger, A., Thase, M., McEachran, A., and Grochocinski, V. (1990) Threeyear outcomes for maintenance therapies in recurrent depression. Arch. Gen. Psychiatry 47:1093–1099. Frazer, A. (1997) Antidepressants. J. Clin. Psychiatry 58(Suppl. 6):9–25. Froger, N., Gardier, A.M., et al. (2001) 5-Hydroxytryptamine (5HT)1A autoreceptor adaptive changes in substance P (neurokinin 1) receptor knock-out mice mimic antidepressant-induced desensitization. J. Neurosci. 21(20):8188–8197. Fukuchi, T., and Kanemoto, K. (2002) Differential effects of milnacipran and fluvoxamine, especially in patients with severe depression and agitated depression: a case-control study. Int. Clin. Psychopharmacol. 17(2):53–58. Furukawa, T.A., Streiner, D.L., et al. (2001) Is antidepressantbenzodiazepine combination therapy clinically more useful? A meta-analytic study. J. Affect. Disord. 65(2):173–177. Gagne, G.G., Jr., Furman, M.J., et al. (2000) Efficacy of continuation ECT and antidepressant drugs compared to long-term antidepressants alone in depressed patients. Am. J. Psychiatry 157(12): 1960–1965. Gainotti, G., and Marra, C. (2002) Determinants and consequences of post-stroke depression. Curr. Opin. Neurol. 15(1):85–89. Gardner, D.M., Shulman, K.I., et al. (1996) The making of a user friendly MAOI diet. J. Clin. Psychiatry 57(3):99–104. Garvey, M., DeRubeis, R., Hollon, S., Evans, M., and Tuason, V. (1991) Response of depression to very high plasma levels of imipramine plus desipramine. Biol. Psychiatry 30:57–62. George, M.S., Wassermann, E.M., Kimbrell, T.A., and Little, I.T. (1997) Mood improvement following daily left prefrontal repetitive transcranial magnetic stimulation in patients with depression—a placebo-controlled crossover trial. Am. J. Psychiatry 154: 1752–1756. Georgotas, A., and McCue, A. (1989) Factors affecting the delay of antidepressant effect in responders to nortriptyline and phenelzine. Psychiatry Res. 28:1–9. Gibbs, R.B. (1999) Treatment with estrogen and progesterone affects relative levels of brain-derived neurotrophic factor mRNA and protein in different regions of the adult rat brain. Brain Res. 844(1/2):20–27. Giles, D.E., Jarrett, R.B., Roffwarg, H.P., and Rush, A.I. (1987) Reduced rapid eye movement latency. A predictor of recurrence in depression. Neuropsychopharmacology 1:33–39. Gitlin, M.I., Weiner, H., Fairbanks, L., Hershman, I.M., and Friedfeld, N. (1987) Failure of T3 to potentiate tricyclic antidepressant response. J. Affect. Disord. 13:267–272. Glassman, A.H., Roose, S.P., and Bigger, I.T., Jr. (1993) The safety of tricyclic antidepressants in cardiac patients: risk-benefit reconsidered. JAMA 269:2673–2675. Goldberg, J.F., Harrow, M., et al. (2001) Risk for bipolar illness in patients initially hospitalized for unipolar depression. Am. J. Psychiatry 158(8):1265–1270. Golden, R.N., DeVane, C.L., Laizure, S.C., Rudorfer, M.V., Sherer M.A., and Potter, W.Z. (1988) Bupropion in depression, II: the

role of metabolites in clinical outcome. Arch. Gen. Psychiatry 45:145–149. Goodwin, F.K., Prange, A.I., Jr., Post, R.M., Muscettola, G., and Lipton, M.A. (1982) Potentiation of antidepressant effects by 1triiodothyronine in tricyclic nonresponders. Am. J. Psychiatry 139: 34–38. Gundlah, C., Lu, N.Z., et al. (2001) Estrogen receptor beta (ERbeta) mRNA and protein in serotonin neurons of macaques. Brain Res. Mol. Brain Res. 91(1/2):14–22. Gundlah, C., Lu, N.Z., et al. (2002) Ovarian steroid regulation of monoamine oxidase-A and B mRNAs in the macaque dorsal raphe and hypothalamic nuclei. Psychopharmacology (Berl.) 160(3): 271–282. Hall, C., Gardner, E., Popkin, M., Lecann, A., and Stickney, S. (1981) Unrecognized physical illness prompting psychiatric admission: a prospective study. Am. J. Psychiatry 138:629–635. Heiligenstein, I., Raries, D., Rush, I., Andersen, I., Pande, A., RoffWarg, H., Dunner, D., Gillin, I., James, S., Lahmeyer, H., Zajecka, I., Tollefson, G., and Gardner, D. (1994) Latency to rapid eye movement sleep as a predictor of treatment response to fluoxetine and placebo in nonpsychotic depressed outpatients. Psychiatry Res. 52:327–339. Herman, B.D., Fleishaker, J.C., et al. (1999) Ketoconazole inhibits the clearance of the enantiomers of the antidepressant reboxetine in humans. Clin. Pharmacol. Ther. 66(4):374–379. Himmelhoch, J.M., Detre, T., Kupfer, D.J., Swartzburg, M., and Byck, R. (1972) Treatment of previously intractable depressions with tranylcypromine and lithium. J. Nerv. Ment. Dis. 155:216–220. Holliday, S.M., and Benfield, P. (1995) Venlafaxine. A review of its pharmacology and therapeutic potential in depression. Drugs 49(2): 280–294. Holsinger, T., Steffens, D.C., et al. (2002) Head injury in early adulthood and the lifetime risk of depression. Arch. Gen. Psychiatry 59(1):17–22. Hu, X.Z., Rush, A.J., Charney, D., Wilson, A.F., Sorant, A.J., Papanicolaou, G.J., Fava, M., Trivedi, M.H., Wisniewski, S.R., Laje, G., Paddock, S., McMahon, F.J., Manji, H., and Lipsky, R.H. (2007) Association between a functional serotonin transporter promoter polymorphism and citalopram treatment in adult outpatients with major depression. Arch. Gen. Psychiatry 65(7):783–792. Jindal, R.D., Thase, M.E., et al. (2002) Electroencephalographic sleep profiles in single-episode and recurrent unipolar forms of major depression: II. comparison during remission. Biol. Psychiatry 51(3): 230–236. Joffe, R.T., Singer, W., Levitt, A.J., and MacDonald, C. (1993) A placebo-controlled comparison of lithium and triiodothyronine augmentation of tricyclic antidepressants in unipolar refractory depression. Arch. Gen. Psychiatry 50:387–393. Johnston, J.A., Lineberry, C.G., Ascher, I.A., Davidson, I., Khayrallah, M.A., Feighner, I.P., and Stark, P. (1991) A 102-center prospective study of seizure in association with bupropion. J. Clin. Psychiatry 52:450 – 456. Joyce, P.R. (1992). Prediction of treatment response. In: Paykel, E. S., ed. Handbook of Affective Disorders. New York: Churchill Livingston, pp. 453– 462. Joyce, P.R., and Paykel, E.S. (1989) Predictors of drug response in depression (review). Arch. Gen. Psychiatry 46:89–99. Källén, B.A., Otterblad Olausson, P. (2007) Maternal use of selective serotonin re-uptake inhibitors in early pregnancy and infant congenital malformations. Birth Defects Res. A. Clin. Mol. Teratol. 79(4):301–308. Kasper, S., el Giamal, N., et al. (2000) Reboxetine: the first selective noradrenaline re-uptake inhibitor. Expert Opin. Pharmacother. 1(4):771–782. Keller, M., Montgomery, S., Ball, W., Morrison, M., Snavely, D., Liu, G., Hargreaves, R., Hietala, J., Lines, C., Beebe, K., and Reines, S. (2006) Lack of efficacy of the substance ρ (neirokinin1

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION receptor) antagonist aprepitant in the treatment of major depressive disorder. Biol. Psychiatry 59(3):216–223. Keller, M.B., McCullough, J.P., et al. (2000) A comparison of nefazodone, the cognitive behavioral-analysis system of psychotherapy, and their combination for the treatment of chronic depression. N. Engl. J. Med. 342(20):1462–1470. Keller, M.B., Shapiro, R.W., Lavori, P.W., and Wolfe, N. (1982) Recovery in major depressive disorder: analysis with the life table and regression models. Arch. Gen. Psychiatry 39:905–910. Kennedy, S.H., and Emsley, R. (2006) Placebo-controlled trial of agomelatine in the treatment of major depressive disorder. Eur. Neuropsychopharmacol. 16(2):93–100. Kiloh, L., Andrews, G., and Neilson, M. (1988) The long-term outcome of depressive illness. Br. J. Psychiatry 153:752–757. Kim, H., Lim, S.W., Kim, S., Kim, J.W., Chang, Y.H., Carroll, B.J., and Kim, D.K. (2006) Monoamine transporter gene polymorphisms and antidepressant response in Koreans with late-life depression. JAMA 296(13):1609–1618. Kline, N.S. (1970). Monoamine oxidase inhibitors: an unfinished picaresque tale. In: Ayd, F.J., and Blackwell, B., eds. Discoveries in Biological Psychiatry. Philadelphia: J.B. Lippincott, pp. 194–204. Kramer, M.S., Cutler, N., Feighner, J., Shrivastava, R., Carman, J., Sramek, J.J., Reines, S.A., Liu, G., Snavely, D., Wyatt-Knowles, E., Hale, J.J., Mills, S.G., MacCoss, M., Swain, C.J., Harrison, T., Hill, R.G., Hefti, F., Scolnick, E.M., Casciéri, M.A., Chichi, C.G., Sadowski, S., Williams, A.R., Hewson, L., Smith, D., Carlson, E.J. Hargreaves, R.J., and Rupniak, N.M.J. (1998) Distinct mechanism for antidepressant activity by blockade of central substance p receptors. Science 281:1640–1645. Kroemer, H.K., and Eichelbaum, M. (1995) “It’s the genes, stupid”: molecular basis and clinical consequences of genetic cytochrome P450 2D6 polymorphism. Life Sci. 56:2285–2298. Kuhn, R. (1958) The treatment of depressive states with G22355 (imipramine) hydrochloride. Am. J. Psychiatry 115:459– 464. Künzel, H.E., Zobel, A.W., Nickel, T., Ackl, N., Uhr, M., Sonntag, A., Ising, M., and Holsboer, F. (2003) Treatment of depression with the CRH-1-receptor antagonist R121919: endocrine changes and side effects. J. Psychiatry Res. 37(6):525–533. Lam, R.W., Tam, E.M., et al. (2001) Effects of alpha-methyl-paratyrosine-induced catecholamine depletion in patients with seasonal affective disorder in summer remission. Neuropsychopharmacology 25(5 Suppl):S97–S101. Lambert, G., Johansson, M., et al. (2000) Reduced brain norepinephrine and dopamine release in treatment-refractory depressive illness: evidence in support of the catecholamine hypothesis of mood disorders. Arch. Gen. Psychiatry 57(8):787–793. Lane, R., and Baldwin, D. (1997) Serotonin syndrome and drug combinations: selective serotonin reuptake. Eur. Arch. Psychiatry Clin. Neurosci. 247:113–119. Lebowitz, B.D., Pearson, I.L., Schneider, L.S., Reynolds, C.F. III, Alexopoulos, G.S., Bruce, M.L., Conwell, Y., Katz, I.R., Meyers, B.S., Morrison, M.F., Mossey, I., Niederehe, G., and Parmelee, P. (1997) Diagnosis and treatment of depression in late life. Consensus statement update. JAMA 278:1186–1190. Lee, A., and Murray, R. (1988) The long-term outcome of Maudsley Depressives. Br. J. Psychiatry 153:741–753. Leverich, G.S., Atshuler, L.L., Frye, M.A., Suppes, T., McElroy, S.L., Keck, P.E., Jr., Kupka, R.W., Denicoff, K.D., Nolen, W.A., Grunze, H., Marinez, M.I, and Post, R.M. (2006) Risk of switch in mood polarity to hypomania or mania in patients with bipolar depression during acute and continuation trials of venlafaxine, sertraline, and bupropion as adjuncts to mood stabilizers. Am. J. Psychiatry 163(2):232–239. Levitan, R.D., Vaccarino, F.J., et al. (2002) Low-dose dexamethasone challenge in women with atypical major depression: pilot study. J. Psychiatry Neurosci. 27(1):47–51.

511

Linner, L., Endersz, H., et al. (2001) Reboxetine modulates the firing pattern of dopamine cells in the ventral tegmental area and selectively increases dopamine availability in the prefrontal cortex. J. Pharmacol. Exp. Ther. 297(2):540–546. Lippman, S., Bedford, P., Manshadi, M., and Mather, S. (1983) Trazodone cardiotoxicity. Am. J. Psychiatry 140:1383. Malinger, A.G., Frank, E., et al. (1999). Effectiveness of Traditional Antidepressants Is Suboptimal in the Depressed Phase of Bipolar Disorder. Boca Raton, FL: New Clinical Drug Evaluation Unit Program. Malison, R., Price, L., Nestler, E., Heninger, G., and Duman, R. (1997) Efficacy of papaverine addition for treatment-refractory major depression. Am. J. Psychiatry 154:579–580. Mann, J.J., Aarons, S.F., Wilner, P.J., Keilp, J.G., Sweeney, J.A., Pearlstein, T., Frances, A.J., Kocsis, J.H., and Brown, R.P. (1989) A controlled study of the antidepressant efficacy and side-effects of (2)-deprenyl: a selective monoamine oxidase inhibitor. Arch. Gen. Psychiatry 46:45–50. Maubach, K.A., Martin, K., et al. (2002) Chronic substance P (NK1) receptor antagonist and conventional antidepressant treatment increases burst firing of monoamine neurones in the locus coeruleus. Neuroscience 109(3):609–617. McMahon, F.J., Buervenich, S., Charney, D., Lipsky, R., Rush, A.J., Wilson, A.F., Sorant, A.J., Papanicolaou, G.J., Laje, G., Fava, M., Trivedi, M.H., Wisniewski, S.R., and Manji, H. (2006) Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am. J. Hum. Genet. 78(3):804–814. Meyer, J.H., Ginovart, N., Boovariwala, A., Sagrati, S., Hussey, D., Garcia, A., Young, T., Praschak-Rieder, N., Wilson, A.A., and Houle, S. (2006) Elevated monoamine oxidase a levels in the brain: an explanation for the monoamine imbalance of major depression. Arch. Gen. Psychiatry 63(11):1209–1213. Meyer, J.H., Wilson, A.A., et al. (2001) Occupancy of serotonin transporters by paroxetine and citalopram during treatment of depression: a [(11)C]DASB PET imaging study. Am. J. Psychiatry 158(11):1843–1849. Miller, I.W., Keitner, G.I., Schatzberg, A.F., Klein, D.N., Thase, M.E., Rush, A.J., Markowitz, J.C., Schlager, D.S., Kornstein, S.G., Davis, S.M., Harrison, W.M., and Keller, M.B. (1998) The treatment of chronic depression, part 3: psychosocial functioning before and after treatment with sertraline or imipramine. J. Clin. Psychiatry 59(11):608–619. Montgomery, S.A., Baldwin, D.S., Blier, P., Fineberg, N.A., Kasper, S., Lader, M., Lam, R.W., Lépine, J.P., Möller, H.J., Nutt, D.J., Rouillon, F., Schatzberg, A.F., and Thase, M.E. (2007) Which antidepressants have demonstrated superior efficacy? A review of the evidence. Int. Clin. Psychopharmacol. 22(6):323–329. Moreno, F.A., Gelenberg, A.J., Bachar, K., and Delgado, P.L. (1997) Pindolol augmentation of treatment-resistant depressed patients. J. Clin. Psychiatry 58:437– 439. Murphy, B. (1997) Antiglucocorticoid therapies in major depression— a review. Psychoneuroendocrinology 22(Suppl 1):125–132. Murphy, G.M., Jr., Hollander, S.B., Rodrigues, H.E., Kremer, C, and Schatzberg, A.F. (2004) Effects of the serotonin transporter gene promoter polymorphism on mirtazapine and paroxetine efficacy and adverse events in geriatric major depression. Arch. Gen. Psychiatry 61(11):1163–1169. Murphy, G.M., Jr., Kemer, C., Rodrigues, H.E., and Schatzberg, A.F. (2003) Pharmacogenetics of antidepressant medication intolerance. Am. J. Psychiatry 160(10):1830-1835. Musselman, D., and Nemeroff, C. (1993) The role of corticotropinreleasing factor in the pathophysiology of psychiatric disorders. Psychiatr. Ann. 23:676–681. Musselman, D.L., Lawson, D.H., Gumnick, J.F., Manatunga, A.K., Penna, S., Goodkin, R.S., Greiner, K., Nemeroff, C.B., and Miller,

512

MOOD DISORDERS

A.H. (2001) Paroxetine for the prevention of depression induced by high-dose interferon alfa. N. Engl. J. Med. 344(13):961–966. Nelson, J.C. (1997a) Safety and tolerability of the new antidepressants (review). J. Clin. Psychiatry 6:26–31. Nelson, J.C. (1997b) Treatment of refractory depression. Depress. Anxiety 5(4):165–174. Nelson, J.C., and Davis, J.M. (1997) DST studies in psychotic depression: a meta-analysis. Am. J. Psychiatry 154(11):1497–1503. Nelson, J.C., Mazure, C.M., Bowers, M.B., Jr., and Jatlow, P.I. (1991) A preliminary, open study of the combination of fluoxetine and desipramine for rapid treatment of major depression. Arch. Gen. Psychiatry 48:303–307. Nelson, J.C., Mazure, C.M., and Jatlow, P.I. (1994) Characteristics of desipramine refractory depression. J. Clin. Psychiatry 55:12–19. Nemeroff, C.B., DeVane, C.L., Pollock, B.G., Hilton, S.E., Maradit, H., and Moller, H.I. (1996) Newer antidepressants and the cytochrome P450 system (see comments). Am. J. Psychiatry 153: 311–320. Nemeroff, C.B., Evans, D.L., Gyulai, L., Sachs, G.S., Bowden, C.L., Gergel, I.P., Oakes, R., and Pitts, C.D. (2001). Double-blind, placebo-controlled comparison of imipramine and paroxetine in the treatment of bipolar depression. Am. J. Psychiatry 158(6): 906–912. Nemets, B., Stahl, Z., et al. (2002) Addition of omega-3 fatty acid to maintenance medication treatment for recurrent unipolar depressive disorder. Am. J. Psychiatry 159(3):477– 479. Nierenberg, A.A., Fava, M., Trivedi, M.H., Wisniewski, S.R., Thase, M.E., McGrath, P.J., Alpert, J.E., Warden, D., Luther, J.F., Niederehe, G., Lebowitz, B., Shores-Wilson, K., and Rush, A.J. (2006) A comparison of lithium and T(3) augmentation following two failed medication treatments for depression: a STAR*D report. Am. J. Psychiatry 163(9):1519–1530. Nurnberg, H.G., Gelenberg, A., et al. (2001) Efficacy of sildenafil citrate for the treatment of erectile dysfunction in men taking serotonin reuptake inhibitors. Am. J. Psychiatry 158(11):1926–1928. O’Reardon, J.P., Solvason, H.B., Janicak, P.G., Sampson, S., Isenberg, K.E., Nahas, Z., McDonald, W.M., Avery, D., Fitzgerald, P.B., Loo, C., Demitrack, M.A., George, M.S., and Sackeim, H.A. (2007) Efficacy and safety of transcranial magnetic stimulation in the acute treatment of major depression: a multisite randomized controlled trial. Biol. Psychiatry 62(11):1208–1216. Pascual-Leone, A., Rubio, B., Pallardo, F., Catala, M.D., George, M.S., Wassermann, E.M., Williams, W.A., Callahan, A., Ketter, T.A., and Basser, P. (1996) Rapid-rate transcranial magnetic stimulation of left dorsolateral prefrontal cortex in drug-resistant depression (see comments). Lancet 348:233–237. Paykel, E., Ramana, R., Cooper, Z., Hayhurst, H., Kerr, I., and Barocka, A. (1995) Residual symptoms after partial remission: an important outcome in depression. Psychol. Med. 25:1171–1180. Peet, M. (1994) Induction of mania with selective serotonin reuptake inhibitors. Int. Clin. Psychopharmacol. 1:49–53. Penalva, R.G., Flachskamm, C., et al. (2002) Corticotropin-releasing hormone receptor type 1-deficiency enhances hippocampal serotonergic neurotransmission: an in vivo microdialysis study in mutant mice. Neuroscience 109(2):253–266. Perlis, R.H., Purcell, S., Fava, M., Fagerness, J., Rush, A.J., Trivedi, M.H., and Smoller, J.W. (2007) Association between treatmentemergent suicidal ideation with citalopram and polymorphisms near cyclic adenosine monophosphate response element binding protein in the STAR*D study. Arch. Gen. Psychiatry 64(6):689–697. Perlis, R.H., Mischoulon, D., Smoller, J.W., Wan, Y.J., Lamon-Fava, S., Lin, K.M., Rosenbaum, J.F., and Fava, M. (2003) Serotonin transporter polymorphisms and adverse effects with fluoxetine treatment. Biol. Psychiatry 54(9):879-883. Peselow, E., Sanfilipo, M., Difiglia, C., and Fieve, R. (1992) Melancholic/endogenous depression and response to somatic treatment and placebo. Am. J. Psychiatry 149:1324–1334.

Pisani, F., Oteri, G., et al. (2002) Effects of psychotropic drugs on seizure threshold. Drug Saf. 25(2):91–110. Post, R., and Weiss, S. (1995). The neurobiology of treatment-resistant mood disorders. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 1155–1170. Post, R.M., Leverich, G.S., Denicoff, K.D., Frye, M.A., Kimbrell, T.A., and Dunn, R. (1997) Alternative approaches to refractory depression in bipolar illness. Depress. Anxiety 5(4):175–189. Posternak, M.A., and Zimmerman, M. (2002) Partial validation of the atypical features subtype of major depressive disorder. Arch. Gen. Psychiatry 59(1):70–76. Preskorn, S.H. (1997) Selection of an antidepressant: mirtazapine (review). J. Clin. Psychiatry 6(17):3–8. Prien, R., Carpenter, L., and Kupfer, D. (1991) The definition and operational criteria for treatment outcome of major depressive disorder: a review of the current research literature. Arch. Gen. Psychiatry 48:796–800. Prudic, I., Sackeim, H.A., and Devanand, D.P. (1990) Medication resistance and clinical response to electroconvulsive therapy. Psychiatry Res. 31:287–296. Prudic, J., Olfson, M., Marcus, S.C., Fuller, R.B., and Sackeim, H.A. (2004) Effectiveness of electroconvulsive therapy in community settings. Biol. Psychiatry 55(3):301–312. Quitkin, F.M., Harrison, W., Stewart, J.W., McGrath, P.J., Tricamo, E., Ocepek-Welikson, K., Rabkin, J.G., Wager, S.G., Nunes, E., and Klein, D.F. (1991) Response to pheneizine and imipramine in placebo nonresponders with atypical depression. Arch. Gen. Psychiatry 48:319–323. Ribeiro, S., Tandon, R., Grunhaus, L., and Greden, I. (1993) The DST as a predictor of outcome in depression: a meta-analysis. Am. J. Psychiatry 150:1618–1629. Richelson, E. (1991) Biological basis of depression and therapeutic relevance J. Clin. Psychiatry 52(6, Suppl):4 –10. Robinson, R.G., Schultz, S.K., Castillo, C., Koppel, T., Kosier, J.T., Newman, R.M., Curdue, K., Petracca, G., and Starkstein, S.E. (2001) Nortriptyline versus fluoxetine in the treatment of depression and in short-term recovery after stroke: a placebo-controlled, double-blind study. Am J. Psychiatry 158(4):351-359. Roose, S. (1994). Selective serotonin reuptake inhibitors in refractory depression. In: Nolen, W.A., Zohar, J., Roose, S.I., and Amsterdam, J.D., eds. Refractory Depression: Current Strategies and Future Directions. New York: Wiley, pp. 37– 46. Roose, S., Glassman, A., Attia, E., and Woodring, S. (1994) Comparative efficacy of selective serotonin reuptake inhibitors and tricyclics in the treatment of melancholia. Am. J. Psychiatry 151: 1735–1739. Roose, S.P., Sackeim, H.A., Krishnan, K.R., Pollock, B.G., Alexopoulos, G., Lavretsky, H., Katz, I.R., Hakkarainen, H., Old-Old Depression Study Group. (2004) Antidepressant pharmacotherapy in the treatment of depression in the very old: a randomized, placebo-controlled trial. Am. J. Psychiatry 161(11):2050–2059. Roose, S.P., and Schatzberg, A.F. (2005) The efficacy of antidepressants in the treatment of late-life depression. J. Clin. Psychopharmacol. 25(4 Suppl 1):S1–S7. Rosenstein, D., Nelson, I., and Jacobs, S. (1993) Seizures associated with antidepressants: a review. J. Clin. Psychiatry 54:289–299. Rothschild, A.J., Williamson, D.J., Tohen, M.F., Schatzberg, A.F., Anderson, S.W., Van Campen, L.E., Sanger, T.M., and Tollefson, G.D. (2004) A double-blind, randomized study of olanzapine and olanzapine/fluoxetine combination for major depression with psychotic features. J. Clin. Psychopharmacol. 24(4):365–373. Rush, A.J., Trivedi, M.H., Wisniewski, S.R., Stewart, J.W., Nierenberg, A.A., Thase, M.E., Ritz, L., Biggs, M.M., Warden, D., Luther, J. F., Shores-Wilson, K., Niederehe, G., Fava, M.; STAR*D Study Team. (2006) Bupropion-SR, sertraline, or venlafaxine-XR after failure of SSRIs for depression. N. Engl. J. Med. 354(12):1231–1242.

32: PRINCIPLES OF THE PHARMACOTHERAPY OF DEPRESSION Sachs, G.S., Lafer, B., et al. (1994) A double-blind trial of bupropion versus desipramine for bipolar depression. J. Clin. Psychiatry 55(9): 391–393. Sachs, G.S., Nierenberg, A.A., et al. (2007) Effectiveness of adjuntive antidepressant treatment for bipolar depression. N. Engl. J. Med. 356(17):1711–1722. Sackeim, H.A., Haskett, R.F., et al. (2001) Continuation pharmacotherapy in the prevention of relapse following electroconvulsive therapy: a randomized controlled trial. JAMA 285(10):1299–1307. Sackeim, H.A., Prudic, J., Devanand, D.P., et al. (2000) A prospective, randomized, double-blind comparison of bilateral and right unilateral electroconvulsive therapy at different stimulus intensities. Arch. Gen. Psychiatry 57(5):425– 434. Sackeim, H.A., Prudic, J., Fuller, R., Keilp, J., Lavor, P.W., and Olfson, M. (2007) The cognitive effects of electroconvulsive therapy in community settings. Neuropsychopharmacology 32(1):244 –254. Satel, S., and Nelson, J. (1989) Stimulants in the treatment of depression: a critical overview. J. Clin. Psychiatry 50:241–249. Sauer, W.H., Berlin, J.A., et al. (2001) Selective serotonin reuptake inhibitors and myocardial infarction. Circulation 104(16): 1894 –1898. Schatzberg, A.F., and Roose, S. (2006) A double-blind, placebocontrolled study of venlafaxine and fluoxetine in geriatric outpatients with major depression. Am. J. Geriatr. Psychiatry 14(4): 361–370. Schmidt, P.J., Nieman, L., et al. (2000) Estrogen replacement in perimenopause-related depression: a preliminary report. Am. J. Obstet. Gynecol. 183(2):414 – 420. Schneider, L.S. (1996) Pharmacological considerations in the treatment of late life depression. Am. J. Geriatr. Psychiatry 4(Suppl 1):S51–S65. Schneider, L.S., Small, G.W., Hamilton, S.H., Bystritsky, A., Nemeroff, C.B., and Meyers, A.B. (1997) Estrogen replacement and response to fluoxetine in a multicenter geriatric depression trial. Fluoxetine Collaborative Study Group. Am. J. Geriatr. Psychiatry 5:97–106. Seidman, S.N., Araujo, A.B., et al. (2002) Low testosterone levels in elderly men with dysthymic disorder. Am. J. Psychiatry 159(3): 456– 449. Seth, R., Jennings, A.L., Bindman, I., Phillips, I., and Bergmann, K. (1992) Combination treatment with noradrenaline and serotonin reuptake inhibitors in resistant depression. Br. J. Psychiatry 161: 562–565. Shapira, B., Oppenheim, G., Zohar, I., Segal, M., Malach, D., and Belmaker, R.H. (1985) Lack of efficacy of estrogen supplementation to imipramine in resistant female depressives. Biol. Psychiatry 20:576–579. Sharpley, A.L., Elliott, J.M., et al. (1994) Slow wave sleep in humans: role of 5-HT2A and 5-HT2C receptors. Neuropharmacology 33(3/4):467– 471. Shelton, R.C., Tollefson, G.D., et al. (2001) A novel augmentation strategy for treating resistant major depression. Am. J. Psychiatry 158(1):131–134. Skowron, D.M., and Stimmel, G.L. (1992) Antidepressant and the risk of seizures. Pharmacotherapy 12:18–22. Smeraldi, E., Zanardi, R., Benedetti, F., Di Bella, D., Perez, J., and Catalano, M. (1998) Polymorphism within the promoter of the serotonin transporter gene and antidepressant efficacy of fluvoxamine. Mol. Psychiatry 3(6):508–511. Soares, C.N., Almeida, O.P., et al. (2001) Efficacy of estradiol for the treatment of depressive disorders in perimenopausal women: a double-blind, randomized, placebo-controlled trial. Arch. Gen. Psychiatry 58(6):529–534. Spiker, D.G., Weiss, J.C., Dealy, R.S., Griffin, S.J., Hanin, I., Neil, J. F., Perel, J.M., Rossi, A.J., and Soloff, P.H. (1985) The pharmacologic treatment of delusional depression. Am. J. Psychiatry 142: 430 – 436.

513

Sporn, J., Ghaemi, S.N., et al. (2000) Pramipexole augmentation in the treatment of unipolar and bipolar depression: a retrospective chart review. Ann. Clin. Psychiatry 12(3):137–140. Stoll, A.L., Severus, W.E., et al. (1999) Omega 3 fatty acids in bipolar disorder: a preliminary double-blind, placebo-controlled trial [see comments]. Arch. Gen. Psychiatry 56(5):407– 412. Stout, S.C., Owens, M.J., et al. (2002) Regulation of corticotropinreleasing factor neuronal systems and hypothalamic-pituitaryadrenal axis activity by stress and chronic antidepressant treatment. J. Pharmacol. Exp. Ther. 300(3):1085–1092. Svenningsson, P., Tzavara, E.T., et al. (2002) Involvement of striatal and extrastriatal DARPP-32 in biochemical and behavioral effects of fluoxetine (Prozac). Proc. Natl. Acad. Sci. USA 99(5): 3182–3187. Szabo, S.T., and Blier, P. (2001) Functional and pharmacological characterization of the modulatory role of serotonin on the firing activity of locus coeruleus norepinephrine neurons. Brain Res. 922(1): 9–20. Thase, M.E., Blomgren, S.L., et al. (1997) Fluoxetine treatment of patients with major depressive disorder who failed initial treatment with sertraline. J. Clin. Psychiatry 58(1):16–21. Thase, M.E., Corya, S.A., Osuntokun, O., Case, M., Henley, D.B., Sanger, T.M., Watson, S.B., and Dubé, S. (2007) A randomized, double-blind comparison of olanzapine/fluoxetine combination, olanzapine, and fluoxetine in treatment-resistant major depressive disorder. J. Clin. Psychiatry 68(2):224–236. Thase, M.E., Entsuah, A.R., et al. (2001) Remission rates during treatment with venlafaxine or selective serotonin reuptake inhibitors. Br. J. Psychiatry 178:234–241. Thase, M.E., Fava, M., Halbreich, U., Kocsis, I., Koran, L., Davidson, I., Rosenbaum, I., and Harrison, W. (1996) A placebocontrolled, randomized clinical trial comparing sertraline and imipramine for the treatment of dysthymia. Arch. Gen. Psychiatry 53:777–784. Thase, M.E., Feighner, J.P., et al. (2001) Citalopram treatment of fluoxetine nonresponders. J. Clin. Psychiatry 62(9):683–687. Thase, M.E., Kupfer, D.J., and Jarrett, D.B. (1989) Treatment of imipramine-resistant recurrent depression: I. An open clinical trial of adjunctive 1-triiodothyronine. J. Clin. Psychiatry 50:385–388. Thase, M.E., Macfadden, W., Weisler, R.H., Chang, W., Paulsson, B., Khan, A., Calabrese, J.R.; Bolder II Study Group. (2006) Efficacy of quetiapine monotherapy in bipolar I and II depression: a double-blind, placebo-controlled study (the BOLDER II study). J. Clin. Psychopharmacol. 26(6):600–609. Thase, M.E., Mallinger, A.G., et al. (1992) Treatment of imipramine-resistant recurrent depression, IV: A double-blind crossover study of tranylcypromine for anergic bipolar depression. Am. J. Psychiatry 149(2):195–198. Thase, M.E., and Rush, A. (1995). Treatment-resistant depression. In: Bloom, F.E., and Kupfer, D.F., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 1081–1097. Thase, M.E., Rush, A.J., et al. (2002) Double-blind switch study of imipramine or sertraline treatment of antidepressant-resistant chronic depression. Arch. Gen. Psychiatry 59(3):233–239. Thase, M.E., and Sachs, G.S. (2000) Bipolar depression: pharmacotherapy and related therapeutic strategies. Biol. Psychiatry 48(6): 558–572. Tohen, M., Vieta, E., Calabrese, J., Ketter, T.A., Sachs, G., Bowden, C., Mitchell, P.B., Centorrino, F., Risser, R., Baker, R.W., Evans, A.R., Beymer, K., Dube, S., Tollefson, G.D., and Breier, A. (2003) Efficacy of olanzapine and olanzapine-fluoxetine combination in the treatment of bipolar I depression. Arch. Gen. Psychiatry 60(11): 1079–1088. Tollefson, G.D., Bosomworth, J.C., Heiligenstein, J.H., Potvin, J.H., and Holman, S. (1995) A double-blind, placebo-controlled clinical trial of fluoxetine in geriatric patients with major depression.

514

MOOD DISORDERS

The Fluoxetine Collaborative Study Group. Int. Psychogeriatr. 7(1):89–104. Trivedi, M.H., Fava, M., Wisniewski, S.R., Thase, M.E., Quitkin, F., Warden, D., Ritz, L., Nierenberg, A.A., Lebowitz, B.D., Biggs, M.M., Luther, J.F., Shores-Wilson, K., Rush, A.J.; STAR*D Study Team. (2006) Medication augmentation after the failure of SSRIs for depression. N. Engl. J. Med. 354(12):1243–1252. Trivedi, M.H., Rush, A.J., Wisniewski, S.R., Nierenberg, A.A., Warden, D., Ritz, L., Norquist, G., Howland, R.H., Lebowitz, B.D., McGrath, P.J., Shores-Wilson, K., Biggs, M.M., Balasubramani, G.K., Fava, M.; STAR*D Study Team. (2006) Evaluation of outcomes with citalopram for depression using measurementbased care in STAR*D: implications for clinical practice. Am. J. Psychiatry 163(1):28–40. Versiani, M., Amrein, R., et al. (1997) Moclobemide and imipramine in chronic depression (dysthymia): an international doubleblind, placebo-controlled trial. International Collaborative Study Group. Int. Clin. Psychopharmacol. 12(4):183–193. Waintraub, L., Septien, L., et al. (2002) Efficacy and safety of tianeptine in major depression: evidence from a 3-month controlled clinical trial versus paroxetine. CNS Drugs 16(1):65–75. Walker, S.E., Shulman, K.I., et al. (1996) Tyramine content of previously restricted foods in monoamine oxidase inhibitor diets. J. Clin. Psychopharmacol. 16(5):383–388. Waring, W.S., Good, A.M., Bateman, D.N. (2007) Lack of significant toxicity after mirtazapine overdose: a five-year review of cases admitted to a regional toxicology unit. Clin. Toxicol. (Phila) 45(1):45–50. Wecker, L., James, S., Copeland, N., and Pacheco, M.A. (2003) Transdermal selegiline: targeted effects on monoamine oxidases in the brain. Biol. Psychiatry 54(10):1099–1104. Weilburg, J.B., Rosenbaum, J.F., Biederman, I., Sachs, G.S., Pollack, M.H., and Kelly, K. (1989) Fluoxetine added to non-MAOI antidepressants converts nonresponders to responders: a preliminary report. J. Clin. Psychiatry 50:447– 449. Wernicke, J.F., Pritchett, Y.L., D’Souza, D.N., Waninger, A., Tran, P., Ivengar, S., and Raskin, J. (2006) A randomized controlled trial of duloxetine in diabetic peripheral neuropathic pain. Neurology 67(8):1411–1420. West, D., and Dally, P. (1959) Effect of iproniazid in depressive syndromes. Br. Med. J. 1:1491–1494. Winokur, G., Coryell, W., Keller, M., Endicott, I., and Akiskal, H. (1993) A prospective follow-up of patients with bipolar and primary unipolar affective disorder. Arch. Gen. Psychiatry 50:457– 465.

Xu, H., Qing, H., et al. (2002) Quetiapine attenuates the immobilization stress-induced decrease of brain-derived neurotrophic factor expression in rat hippocampus. Neurosci. Lett. 321(1/2): 65–68. Young, A.H., Gallagher, P., Watson, S., Del-Estal, D., Owen, B.M., and Ferrer, I.N. (2004) Improvements in neurocognitive function and mood following adjunctive treatment with mifepristone (RU486) in bipolar disorder. Neuropsychopharmacology 29(8): 1538–1545. Zanardi, R., Benedetti, F., De Bella, D., Catalano, M., and Smeraldi, E. (2000) Efficacy of paroxetine in depression is influenced by a functional polymorphism within the promoter of the serotonin transporter gene. J. Clin. Psychopharmacol. 20(1):105–107. Zanardi, R., Franchini, L., Gasperini, M., Perez, J., and Smeraldi, E. (1996) Double-blind controlled trial of sertraline versus paroxetine in the treatment of delusional depression. Am. J. Psychiatry 153(12):1631–1633. Zarate, C.A., Jr., Payne, J.L., Singh, J., Quiroz, J.A., Luckenbaugh, D.A., Denicoff, K.D., Charney, D.S., and Manji, H.K. (2004) Pramipexole for bipolar II depression: a placebo-controlled proof of concept study. Biol. Psychiatry 56(1):54–60. Zarate, C.A., Jr., Singh, J., Carlson, P.J., Brutsche, N.E., Ameli, R., Luckenbaugh, D.A., Charney, D.S., and Manji, H.K. (2006) A randomized trial of N-methy-D-asparate antagonist in treatmentresistant major depression. Arch. Gen. Psychiatry 63(8):856–864. Zarate, C.A., Jr., Singh, J., Quiroz, J.A., DeJesus, G., Denicoff, K.K., Luckenbaugh, D.A., Manji, H.K. and Charney, D.S. (2006) A double-blind, placebo-controlled study of memantine in the treatment of major depression. Am. J. Psychiatry 163(1):153–155. Zarate, C.A., Jr., Tohen, M., et al. (2001) Cycling into depression from a first episode of mania: a case-comparison study. Am. J. Psychiatry 158(9):1524–1526. Zimmerman, M., Mattia, J.I., et al. (2002) Are subjects in pharmacological treatment trials of depression representative of patients in routine clinical practice? Am. J. Psychiatry 159(3):469– 473. Zobel, A.W., Nickel, T., Künzel, H.E., Ackl, N., Sonntag, A., Ising, M., and Holsboer, F. (2000) Effects of the high-affinity corticotrophin-releasing hormone receptor 1 antagonist R121919 in major depression: the first 20 patients treated. J. Psychiatr. Res. 34(3):171–181. Zobel, A.W., Nickel, T., Sonntag, A., et al. (2001) Cortisol response in the combined dexamethasone/CRH test as predictor of relapse in patients with remitted depression. a prospective study. J. Psychiatr. Res. 35(2):83–94.

33 Abnormalities of Brain Structure and Function in Mood Disorders VICTORIA ARANGO

A N D

J. JOHN MANN

This chapter describes our current knowledge of brain structure and function in mood disorders based on postmortem brain studies and should be read in conjunction with other chapters on in vivo imaging and neurochemistry studies. A confluence of structural and functional imaging studies have suggested that the prefrontal cortex (PFC) is reduced in size and/or function in major depression. Altered indices of noradrenergic (NA) and serotonergic function have been found in major depression, and their molecular components and the anatomical location have been identified. In addition, associated second-messenger systems in cortical target regions are affected, raising questions over whether the primary abnormalities are in the monoamine source neurons or in target cortical or subcortical neurons. It is important to determine which abnormalities detected in postmortem studies are related specifically to the pathogenesis of mood disorders and which changes are related to nonspecific effects of stress, the most common cause of death in such studies of persons with depression, namely suicide, homeostatic mechanisms, or other comorbid psychopathology. We discuss these alternative possibilities throughout this chapter. POSTMORTEM STUDIES OF THE SEROTONERGIC SYSTEM IN DEPRESSION Of all the neurotransmitter systems altered in mood disorders and suicide, the serotonergic system is most consistently affected (Stanley et al., 1982; Arango and Mann, 1992; Arango et al., 1995; Pandey et al., 2002; Stockmeier, 2003). Major depressive disorder (MDD; Coccaro et al., 1989; Delgado et al., 1990; O’Keane and Dinan, 1991; Price et al., 1991; Mann et al., 1992; Mann et al., 1995; Flory et al., 1998; Arango et al., 2002; Stockmeier, 2003) and suicidal behavior (Arango and Mann, 1992; Arango et al., 1995; Arango and Underwood, 1997; Mann et al., 2000; Arango et al., 2002; Mann, 2002; Pandey et al., 2002; Mann, 2003) are independently correlated with direct indicators of altered

serotonergic function in the brain and indirectly through measures in the cerebrospinal fluid (CSF; Mann, 1998; Mann et al., 2000). This dysfunction of the serotonergic system appears to be a trait as patients with remitted mood disorder continue to demonstrate an impairment of serotonergic function (Delgado et al., 1990; Delgado et al., 1994; Flory et al., 1998). Moreover, individuals with major depression who have died by suicide or made more lethal suicide attempts have an additional deficiency in serotonergic function over and above the abnormality associated with depression (Shaw et al., 1967; Bourne et al., 1968; Pare et al., 1969; Lloyd et al., 1974; Åsberg et al., 1976; Beskow et al., 1976; Agren, 1980; Brown et al., 1982; Malone et al., 1996; Mann, Malone, et al., 1996; Mann and Malone, 1997), consistent with the hypothesis that reduced serotonergic activity is associated with suicide risk. In individuals who attempt suicide, there appears to be a biological trait involving impaired serotonergic function that can predict risk of future suicide (Nordström et al., 1994; Mann et al., 2006). Genetics and early-life environment can both influence serotonergic function in a manner that can affect adult behavior and that may explain such traits as impulsive aggressive behaviors in adulthood as well as the development of recurrent mood disorders. Given evidence that serotonergic function is under substantial genetic regulation (Higley et al., 1993; Fairbanks et al., 2004; Rogers et al., 2004), we have proposed that the genetic factors causing recurrent mood disorders and regulating the risk of suicidal behavior may be at least partly mediated by the serotonergic system and its impact on development of mood disorders and on impulse regulation via executive function (Mann et al., 2001; Arango, Huang, et al., 2003; Mann et al., 2005). It is in this context that studies of the serotonergic system in major depression and violent suicides and controls are best understood. We emphasize suicide because many individuals with major depression that come to autopsy have died by suicide, and thus most postmortem studies of patients with depression include a very high proportion of suicides. There are fewer post515

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mortem studies of patients with depression dying of natural causes or accidents, and it is difficult to obtain suitable cases of patients with major depression dying from causes other than suicide. For example, some studies of individuals with mood disorder who died from natural causes may be compromised by inclusion of patients in remission at the time of death, and/or receiving antidepressant medications that down-regulate 5-hydroxytryptophan (5-HT; serotonin)1A or 5-HT2A receptors and thereby reverse any potential increase in these receptors due to depression. Ferrier et al. (1986) found lower cortical 5-hydroxyindole acetic acid (5-HIAA) and a trend for more 5HT2A binding in patients who were depressed but not on antidepressants in the month prior to death. A subsequent study by the same group reported higher 5HT2A binding (Yates et al., 1990). A study by McKeith et al. (1987) found greater 3H-ketanserin (3H-KET) binding to 5-HT2A receptors in the cortex of the frontal pole (Brodmann area [BA] 10) of patients with depression dying from causes other than suicide compared to controls, despite the fact that only four of the nine patients with major depression were off antidepressants for at least one month prior to death. Owen et al. (1986) reported on patients with depression, not all of whom were depressed at time of death, and some of whom were on antidepressants, and found no differences in frontal cortical or hypothalamic levels of 5-HIAA; however, the postmortem delay was over 40 hours, which can lead to degradation of this metabolite. In addition, they reported no change in 5-HT2A binding in the same brain samples. Yates and Ferrier (1990) found less 5HT1A binding in frontal cortex of medicated patients with depression compared with euthymic unmedicated patients and suggested down-regulation by antidepressants as an explanation for less binding. Perry et al. (1983) found lower imipramine binding in occipital cortex. Imipramine binds to the serotonin transporter (SERT), but also to nontransporter sites. Thus, this study suggests there are fewer SERT sites but cannot rule out a contribution by nontransporter sites. We published the largest postmortem study to date, assaying PFC tissue samples from 159 individuals for SERT binding (3Hcyanoimipramine; Arango et al., 1995), by quantitative receptor autoradiography (Mann et al., 2000). Clinical information, including Diagnostic and Statistical Manual of Mental Disorders-3rd ed. revised (DSM-III-R; American Psychiatric Association, 1987) axis I and axis II diagnoses, was obtained by psychological autopsy (Kelly and Mann, 1996). Serotonin transporter binding in individuals with a history of major depression was lower throughout all prefrontal cortical areas studied. This contrasted with the finding that suicide was associated with less SERT binding only in the ventral prefrontal and anterior cingulate cortex (Arango et al., 2002).

In summary, studies in patients with depression dying from causes other than suicide have found more 5-HT2A binding and less SERT binding, changes that are in the same direction as those seen in individuals who die by suicide regardless of diagnosis. Mapping studies of SERT binding suggest that mood disorders involve a widespread alteration in the PFC, whereas suicide involves a localized change in serotonin function confined to the ventral PFC. Clearly, more data are required on the serotonergic system in the brain of patients with depression to determine the qualitative or quantitative differences in the serotonergic system associated with mood disorders as distinct from suicide. POSTMORTEM STUDIES OF THE SEROTONERGIC SYSTEM IN SUICIDES An association between serotonin and suicidal behavior is one of the most consistent findings in biological psychiatry (Mann, 2003; Mann and Currier, 2007). Numerous studies have reported less postmortem SERT binding in ventromedial PFC related to suicide independent of psychiatric diagnosis, and an independent deficiency in transporter binding across most of the PFC related to major depression (Mann et al., 2000; Arango et al., 2002). Similarly, we have reported higher postmortem postsynaptic 5-HT1A binding in ventral PFC related to suicide but not to major depression (Arango et al., 1995). Therefore, serotonin-related factors may hold important clues to the etiology of suicidal behavior, particularly that aspect that cannot be explained by the presence of psychiatric illness alone. Early neurochemical studies of 5-HT or 5-HIAA in the brainstem of suicides found small differences of 10%– 20% in brain stem, but not in cortex, in suicides compared to controls (reviewed in Mann et al., 1989; Arango and Mann, 1992; Mann, Underwood, and Arango, 1996). Korpi et al. (1986) found lower hypothalamic 5-HT in suicides without schizophrenia, but not in suicides with schizophrenia. The brain stem differences were of similar magnitude in suicides with a depressive illness (about 60% of all suicides in most studies have a major depression at the time of suicide; Mann et al., 1989), compared with suicides with other psychiatric diagnoses, suggesting that lower brain stem 5-HT and 5-HIAA levels are primarily associated with suicidal behavior rather than with major depression (Mann et al., 1989). Levels of 5-HT or 5-HIAA postmortem are only a crude index of presynaptic serotonergic function because 5-HT and 5-HIAA concentrations decline rapidly after death and the removal of the brain from the calvarium, and also because 5-HT is found in a fast and in a slow turnover pool that cannot be distinguished by tissue assay even though the pools have different func-

33: ABNORMALITIES OF BRAIN STRUCTURE AND FUNCTION

tions. Postsynaptic receptors and transporter sites, and membrane-bound proteins, are more stable postmortem indicators of altered function and have proven valuable in the localization of abnormalities in the brain. We and others reviewed elsewhere postmortem brain serotonin receptor studies in suicides (Arango and Mann, 1992; Mann, Underwood, and Arango, 1996; Stockmeier, 2003). In summary, 9 of 18 studies found an increase in 5-HT2A binding. The discrepant results appear to be due to a combination of ligand specificity, agonist versus antagonist, and region-specific or agonal effects (Lewis, 2002). A separate body of studies (Biegon et al., 1990; Pandey et al., 1990; McBride et al., 1994; Pandey et al., 1995; Hrdina and Du, 2001) have found more platelet 5-HT2A receptors in association with suicidal behavior, lending further support to the conclusion that 5-HT2A receptor binding may be altered in suicide. Our original finding in dorsolateral PFC, where specific 5-HT2A binding was defined by mianserin (Mann et al., 1986), may have included binding to non-5-HT2A receptor populations. The majority of earlier studies of 5-HT2A receptors, including ours, used 3H-spiroperidol or 125I-LSD in membrane preparations from dorsolateral PFC. Six of 11 studies found more 5-HT2A binding sites. Using the agonist 125I-LSD and ketanserin as a displacer for autoradiography (Arango et al., 1990), we found more 5HT2A sites in dorsolateral PFC, a finding replicated in homogenates using the same ligand (Pandey et al., 2001). Moreover, Pandey et al. (2002) found more 5-HT2A protein and gene expression in PFC of adolescent suicides, suggesting that at least part of the explanation of more binding lay in more gene expression. Our most recent autoradiography study using the selective 5-HT2A antagonist ligand 3H-ketanserin throughout the pregenual PFC indicates an increase in 5-HT2A binding that appears most pronounced in ventral PFC (Fig. 33.1A), although using the same ligand, a study in homogenates revealed higher Bmax in dorsal PFC (Turecki et al., 1999). A recent study by our group (Underwood et al., 2004) showed that adult suicides (> 25 years) who were alcoholic had higher binding than controls in ventrolateral PFC (BA 45 and 46). In the younger age group (≤ 25 years), nonalcoholic suicides had more binding than controls in orbital cortex (BA 47, 11 and 12). A shift in the ratio of high- and low-affinity binding sites can explain some discrepancies in the literature because only agonists detect the difference in binding affinity. We also reported higher 5-HT1A binding localized to the ventrolateral PFC (Arango et al., 1995, Fig. 33.1B). The 5-HT1A receptor appears to be involved in the actions of anxiolytic and antidepressant drugs. Overall, three (Matsubara et al., 1991; Joyce et al., 1993; Arango et al., 1995) of seven studies have found increased 5HT1A binding in localized brain regions in suicides. Negative studies (Dillon et al., 1991; Arranz et al., 1994;

517

Lowther et al., 1997; Stockmeier et al., 1997) did not study multiple areas by autoradiography and may have missed regions of change or included tissue from patients on medications at the time of death. Using quantitative autoradiography we studied 5-HT1A binding in nine pregenual cortical Brodmann areas (11, 12, 32, 24, 8, 9, 46, 45, and 47) in large coronal sections of the PFC of suicides and controls. The suicide group had higher 5-HT1A binding compared with the control group in ventral PFC (BA 45 and 46) with differences ranging from 17%–30% (Fig. 33.2; Arango et al., 1995), a finding we replicated with almost double the sample size (Arango et al., 1998; Arango et al., 2004, Figs. 33.1B and 33.2). Females have higher 5-HT1A binding than males in some of the PFC areas studied (Arango et al., 1995). Some studies of 5-HT1A receptors in the hippocampus report an increase in suicides (Joyce et al., 1993), but most do not (Dillon et al., 1991; Lowther et al., 1997; Stockmeier et al., 1997). Conflicting reports exist in the literature as to whether binding to the SERT on serotonin nerve terminals is lower in cortical regions of suicides (Arango and Mann, 1992; Stockmeier, 2003). Serotonin transporter binding is an index of serotonin nerve terminals. Early studies used ligands that did not distinguish high-affinity SERT binding from a very similar non-SERT binding site that has no known functional role (Mann, Henteleff, et al., 1996). Presynaptic imipramine binding density in the frontal cortex and hypothalamus of suicides was lower compared to controls (Stanley et al., 1982; Paul et al., 1984). Other later studies failed to find fewer imipramine or paroxetine binding sites in PFC (Meyerson et al., 1982; Crow et al., 1984; Owen et al., 1986; Gross-Isseroff et al., 1989; Lawrence et al., 1990; Arora and Meltzer, 1991). In summary, 7 of 17 studies report less SERT binding associated with suicide. In our autoradiography studies (Arango et al., 1995; Mann et al., 2000; Arango et al., 2002, Fig. 33.1C), SERT binding was 15%–27% lower in the ventral PFC of suicides compared with controls. We found no difference in dorsolateral PFC in suicides where most other investigators focused, but we did find binding to be lower in that brain region in major depression, suggesting brain region and diagnosis associated with suicide are crucial (Lewis, 2002). We also reported that nontransporter (non-SERT), defined by independence from sodium concentration, paroxetine binding is lower in dorsolateral PFC (Mann, Henteleff, et al., 1996). Because 3H-imipramine binds with high affinity to the SERT and non-SERT sites, the finding of lower 3H-imipramine binding in dorsolateral PFC is probably due to non-SERT sites. In contrast to suicides, SERT binding in individuals with a history of major depression who died by natural causes or accident was lower throughout all prefrontal

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FIGURE 33.1 Upper panel: Serotonin receptors. Pseudocolor images of subtracted autoradiograms representing total specific 5-HT2A (A), 5-HT1A (B), and serotonin transporter (C) binding sites in adjacent coronal sections of the prefrontal cortex of the human. Lower panel: Adrenergic receptors. Pseudocolor images of subtracted autoradio-

grams representing total specific β1-adrenergic (high-affinity) (D), α 1adrenergic (E), and α 2-adrenergic (F) binding. Note that each receptor has a different lamination within the cortex and varies dorso-ventrally with ventral cortical areas having more binding.

cortical areas studied (Mann et al., 2000; Arango et al., 2002). Thus, SERT binding revealed what appear to be regionally distinct neurobiological correlates of major depression and suicide. Levels of 5-HT and 5-HIAA did not correlate with SERT binding, but 5-HT1A binding and SERT binding correlated negatively in controls and suicides in the same brain region.

caudal mesencephalon and rostral pons. Based on topographic and cytoarchitectonic characteristics in Nisslstained material, the DRN has been subdivided into distinct subnuclei (Baker et al., 1990). These subdivisions correspond to those observed in tissue immunoreacted with antiphenylalanine hydroxylase sera (Törk, 1990; Törk and Hornung, 1990), which also revealed an additional component (the ventral subnucleus) not recognized in Nissl material. The subnuclei are median (or interfascicular), ventrolateral, dorsal, lateral, and caudal. At present it is not possible to verify the cortical targets of the various DRN nuclear subdivisions in the human. The projection from the DRN to cortical targets in the monkey exhibits a coarse rostrocaudal topographic relationship, as opposed to the MRN projections that are not separated rostrocaudally (Wilson and Molliver, 1991). The serotonergic projection to the PFC

THE DORSAL RAPHÉ NUCLEUS In nonhuman primates, serotonergic innervation of the cerebral cortex and much of the forebrain is derived from serotonin-synthesizing neurons in the dorsal (DRN) and median raphé nucleus (MRN; Törk, 1990). In the human, the DRN is a large group of neurons embedded in the ventral part of the central gray matter of

33: ABNORMALITIES OF BRAIN STRUCTURE AND FUNCTION

519

Controls (n=42) Suicides (n=29)

3

H-8-OH-DPAT Binding (fmol/mg tissue)

25

* *

20

*

*

15

p < 0.05

*

*

10

5

0

8

9

46

45

47

11

12

32

24

White Matter

Brodmann Area FIGURE

33.2 Binding to the 5-HT1A receptor in sulci of the prefrontal cortex in controls and suicides. The coronal section was taken at a level just anterior to the genu of the corpus callosum and includes dorsal Brodmann areas (BA) 8 and 9, lateral (BA 46) orbital (BA 45,

47, and 11) and medial (BA 12, 32, and 24). Note that binding is higher in orbital regions and that suicides had more binding than controls in dorsolateral and orbital regions.

has a substantial component arising from cells in the rostral part of the DRN. Regarding cortical innervation by serotonin projections in the primate, density is highest in layer I, except in sensory areas where the highest density is in layer IV. The serotonergic target cells in the cortex are mostly GAD-IR, indicating that they are γ-aminobutyric acid (GABA)ergic inhibitory neurons, but in some brain regions, such as in the pyriform cortex, the target neurons are pyramidal cells (Sheldon and Aghajanian, 1990). One possible simple explanation for impaired serotonergic neurotransmission in depression and/or suicide may be that there are fewer serotonergic neurons in the DRN resulting in a compensatory increase in 5HT2A and 5-HT1A postsynaptic receptors in the PFC, and associated with fewer presynaptic SERT sites. Using a specific tryptophan hydroxylase antibody to identify only serotonergic neurons, we ruled out the possibility that the serotonergic deficiency is due to fewer serotonin-synthesizing neurons in the DRN where we found more rather than fewer 5-HT neurons in suicides with depression (Underwood et al., 1999, Fig. 33.3). A replication of this study by the Gundersen group (Dorph-Petersen et al., 2001) also found that suicides did not have fewer cell numbers in the DRN. We then counted the number of Nissl-stained neurons in suicides and controls and found no differences. How-

ever, when the TPH-IR neurons were expressed as a percent of the total number of DRN neurons, approximately 54% of DRN neurons in controls were serotonergic compared to 78% of the neurons in suicides, indicating a change in the phenotype (Arango, Underwood, et al., 2003, Fig. 33.4). Thus, not only are there more serotonergic neurons in the suicides, there is evidence of more TPH2 protein (Underwood et al., 1999; Boldrini et al., 2005), and more TPH2 messenger ribonucleic acids (mRNA) (Bach-Mizrachi et al., 2006) in the DRN of suicides, a condition predicting more, not less, 5-HT transmitter synthesis. However, not all groups find these differences in the DRN of suicides (Bonkale et al., 2004), but they report higher levels of TPH protein in the DRN of alcohol dependent individuals with depression (Bonkale et al., 2006). The presence of TPH does not necessarily indicate functional capacity. Such superfluous expression of TPH may explain our observation of increased enzyme, presumably with reduced 5-HT synthesis, release, and turnover. However, it remains unclear whether it is at the transcriptional level or at the translational level that TPH is aberrantly regulated. Studies using quantitative reverse transcription polymerase chain reaction (RT-PCR) report low levels of TPH2 transcript in the terminal fields of 5-HT neurons in human postmortem tissue (De Luca et al., 2005; Zill et al., 2007), with the level of TPH2 mRNA in the

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A

C

B

D

Control

Suicide

DRN being tenfold higher than in the cortex (Zill et al., 2007). One study examined TPH2 mRNA levels in the PFC of suicides (De Luca et al., 2006) and found no significant differences between groups. TPH mRNA was reported to be higher in PFC of patients with bipolar

Percentage TPH-IR Cells

100

* 80

*

p = 0.002

60 40 20 0 Control (n = 8)

Suicide (n = 7)

FIGURE 33.4 The percentage of DRN neurons that are tryptophan hydroxylase-immunoreactive in controls (left, light gray) and suicides (right, dark gray). Note that, while the number of neurons (stained for Nissl substance) is not different between groups, the number of serotonergic neurons is higher in the DRN of suicide victims. DRN: dorsal raphé nucleus.

FIGURE 33.3 TPH immunoreactivity in the DRN in a representative control (A & B) and suicide (C & D) at medium (400X, A & C) and high (1000X, B & D) magnification. TPH was labeled using an antibody to phenylalanine hydroxylase, as described in the text. The photomicrographs were taken from the ventrolateral subnucleus. Note that the intensity of staining is greater in the DRN of the suicide victim. The increase in staining extends to neuronal processes. TPH: tryptophan hydroxylase; DRN: dorsal raphé nucleus.

disorder, but not in patients with schizophrenia, compared to controls (De Luca et al., 2005), an alteration not present in the parietal cortex (Shamir et al., 2005). TPH2 protein is very abundant in cortex as measured with Western Blots, but no differences were detected between suicides and controls (Ono et al., 2002). Within the raphé nuclei, serotonin neuron firing and therefore serotonin release are negatively regulated by 5-HT1A somatodendritic inhibitory autoreceptors (see review by Sibille and Hen, 2001). Altered autoinhibition at the 5-HT1A receptor in the brain-stem raphé nuclei might be a contributing mechanism to reduced serotonergic neurotransmission in PFC in suicides and patients with depression. Initial in vivo positron emission tomography (PET) studies report lower brainstem 5-HT1A receptor binding in depression (Drevets et al., 1999; Sargent et al., 2000), an effect that is likely to enhance serotonergic activity through reduced autoinhibition, perhaps as a homeostatic mechanism. Using PET, our group recently demonstrated that there is no difference in the binding potential of patients with MDD versus controls, although patients that were medication naïve had higher 5-HT1A receptor binding potential than those exposed to antidepressants and normal controls (Parsey et al., 2006) in cortical regions and in the brain stem. The patients with MDD were more likely to possess the higher expressing G allele of the C-1019G 5-HT1A receptor gene promoter polymorphism than controls, which may have contributed to higher levels

33: ABNORMALITIES OF BRAIN STRUCTURE AND FUNCTION

of 5-HT1A receptor BP. Although we studied suicides with MDD, not MDD per se, the in vivo findings in the brain stem appear to counter our postmortem findings, as suicides have fourfold higher GG genotypes compared to controls (Lemonde et al., 2003), yet we report a reduction in total binding in the DRN of suicides (Arango, Underwood, Boldrini, et al., 2001; Boldrini et al., 2007). In contrast to our findings, 5-HT1A autoreceptor levels were reported to be elevated in the midbrain of suicides (Stockmeier et al., 1998). These discrepant findings were reconciled in our recent work (Boldrini et al., 2007) showing more 5-HT1A receptors in the rostral part of the DRN in suicides and lower binding in the remaining caudal 15 mm (~75% of the DRN), for a net decrease in binding throughout the DRN. Stockmeier et al. (1998) examined the most rostral 5 mm of the DRN and, like our study (Boldrini et al., 2007), found an increase in binding. Another determining factor may be found in the sex composition of the study cohorts. We find that females have significantly higher 5-HT1A binding than males (Arango, Underwood, Boldrini, et al., 2001), a finding replicated by our group in vivo with PET (Parsey et al., 2002). POSTMORTEM NORADRENERGIC CORRELATES OF SUICIDE AND DEPRESSION The catecholamine hypothesis of depression proposes impaired NA transmission as the basic neurochemical defect. There is a paucity of data on the NA system in brain of patients with depression (Birkmayer and Riederer, 1975). We have reported higher β -adrenergic binding (without distinguishing β1 and β2 subtypes) in the frontal cortex of violent suicides (Arango et al., 1990). Based on psychological autopsy, approximately 60% of suicides in our sample have a major depression around the time of suicide. Biegon and Israeli (1988) also found higher Bmax and no change in KD in β -adrenergic binding in multiple brain regions of suicides, whereas De Paermentier et al. (1990) and others (Stockmeier and Meltzer, 1991) did not find higher β1-adrenergic binding. Little et al. (1993) found less 125I-pindolol binding in suicides. More recently we found less high-affinity β1-adrenoreceptor binding in localized areas of the PFC (Fig. 33.1D), and hypothesize that the previously reported increase in nonselective β -adrenergic binding may be due to the β2-subtype, although this remains to be directly tested. As most studies do not separately report on patients with major depression, it is not clear whether observed changes in β -adrenergic binding are associated with major depression or suicide. However, less high-affinity β1-adrenergic receptor binding could contribute to reduced NA transmission if the receptor change is primary and would be consistent with the catecholamine hypothesis of depression. An alternative

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formulation is that β1-adrenergic binding is reduced because of down-regulation due to NA overactivity, a potential consequence of increased norepinephrine (NE) release in response to stress. Animal studies report that maternal deprivation can heighten stress responses in adulthood as evidenced by higher cortisol and NE release (Barr et al., 2004; Pryce et al., 2004; Levine, 2005). We found elevated α 1-adrenergic binding (Fig. 33.1E) in a layer of dorsolateral PFC (Arango, Ernsberger, et al., 1993). Consistent with Gross-Isseroff et al. (1990), who found less binding in presumably other cortical areas in suicides, we also found that binding appears lower in ventral PFC. In contrast, we previously found less α 2-binding by autoradiography of the dorsolateral PFC (Fig. 33.1F), but this requires confirmation in a larger series of cases (Arango, Ernsberger, et al., 1993). However, others (Klimek et al., 1999) found no differences, whereas García-Sevilla’s group (Meana and García-Sevilla, 1987) reported greater α 2-adrenergic homogenate binding from an unspecified area of frontal cortex, emphasizing the need for comparing results from similar brain regions using the same ligands. They also examined α 2-adrenoreceptor protein immunolabeling and mRNA expression in suicides and showed that the immunolabeling of α 2-receptor in the PFC was higher in suicides (Garcia-Sevilla et al., 1999). A subsequent publication (Escriba et al., 2004) reported higher mRNA levels for α 2-receptors in the PFC of suicides and found a correlation between α 2-receptor mRNA and the protein measured by immunolabeling, suggesting that higher protein is related to increased transcription. Ordway et al. (Ordway, Widdowson, et al., 1994) found elevated α 2adrenergic agonist binding to autoreceptors in the locus coeruleus (LC) of suicides. This may be secondary up-regulation due to deficient NE release from the LC because less autoreceptor binding would favor higher firing rates and more NE release. Studies, largely confined to nonviolent suicides, have reported no change in NE levels (Bourne et al., 1968; Pare et al., 1969), but we found increased NE levels in the PFC of violent suicides (Arango et al., 1990). This finding must be considered in the context of reports of more tyrosine hydroxylase (TH) immunoreactivity and more α 2-binding in the LC of suicides with depression (Ordway, Smith, et al., 1994) and less NE transporter (NET; Ordway, Widdowson, et al., 1994; Klimek et al., 1997; Ordway et al., 1997). The Ordway group also reported higher TH-immunoreactivity along the rostro-caudal axis of the LC of suicides compared to controls (Zhu et al., 1999). Others report less TH immunoreactivity in the LC neurons in suicides, as measured by optical density (Biegon and Fieldust, 1992) and in depressed, nonsuicide cases (Baumann, Danos, Diekmann, et al., 1999). When comparing suicides with bipolar and unipolar depression, we find less TH-IR in the bipolar group, compared to unipolar suicides and controls (Wiste et al.,

MOOD DISORDERS

2008). All bipolar suicides in this study, except one, died during the depressed phase of the illness, and the patients who were manic at the time of death had much higher TH-IR than any other patient (Wiste et al., in press). Contrary reports notwithstanding, the possible scenario of greater TH enzyme activity and fewer NET sites suggests increased NA activity and may be a consequence of an excess NE release leading to deficiency or depletion. A deficiency in NA activity may be the consequence of previous excessive NA output, as seen in stress models in adult rodent studies, particularly after adverse childhood-rearing experiences. Other cortical measures are consistent with a recent increase in NA activity, such as secondary cortical β1-adrenoreceptor and perhaps α 2-adrenoreceptor down-regulation. However, the attribution of changes in the NA system to suicide versus a depressive illness remains to be determined. The studies by Ordway and colleagues (Ordway, Smith, and Haycock, 1994) have largely been in suicides with major depression. Most other studies have not distinguished between suicides with and without a recent episode of major depression. Hence, it is not possible to distinguish biochemical changes associated with major depression from those associated with suicide. In summary, there is evidence of NA overactivity, based on higher cortical NE levels and less high affinity β -adrenergic receptor binding. More α1- and less α 2-adrenergic binding will also affect NA transmission in the cortex. Depletion of LC stores of NE may trigger a compensatory increase in NE synthesis and reduction in LC NET sites. The presence of fewer NA neurons may mean that the functional reserve of the NA system is lower in suicide and/or major depression; therefore, there is greater likelihood of NA depletion in the face of severe or prolonged stress. The cause of this increase in NA activity is unknown, but it could be a response to the stress of the depressive illness. Moreover, in the case of suicides with depression there is the additional stress of feeling suicidal. The NA response to stress may be greater in those with an adverse experience in childhood who are then at greater risk in adulthood for major depression (Heim and Nemeroff, 2001) and suicidal acts (Brodsky et al., 2001). MORPHOMETRIC STUDIES OF THE LOCUS COERULEUS We found 23% fewer LC neurons and 38% lower density of pigmented LC neurons in suicides with depression (Arango et al., 1996) compared with controls (Fig. 33.5). The difference in neuron number was localized to the rostral two thirds of the LC. Neither the LC length nor the LC volume in suicides with depression differed from controls. Altered brain NA neurotransmission in suicides with depression appears associated

30000

Left LC Right LC

Estimated Neuron Number

522

p < 0.05 from control † p < 0.05 left vs. right

* 20000

*

†

10000

0 Controls (N = 11)

Suicides (N = 6)

FIGURE 33.5 Estimated total number of pigmented neurons in the left and right locus coeruleus (LC) in controls and suicide victims. Note that the total number of pigmented neurons was significantly reduced in the suicide group. The number of LC neurons was symmetrical in the left and right LC of controls. In suicides, however, there were significantly fewer pigmented neurons in the left than right LC.

with fewer NA neurons in the LC. These neurons may be hyperactive in response to the stress of major depression or suicidal feelings (Ordway, Smith, and Haycock, 1994; Ordway, Widdowson, et al., 1994; Ordway, 1997). Further studies are needed to determine whether this NA neuron deficit is associated with an underlying major depression or specifically with suicidal behavior. Subtype of mood disorder may be relevant. For example, Baumann, Danos, Krell, et al. (1999) found that patients with bipolar disorder had significantly more LC neurons, compared with patients with unipolar depression, suggesting that polarity of affective illness may have an impact on brain-stem morphology. Morphometric studies should be combined with receptor and biochemical assays (Ordway, Smith, and Haycock, 1994) as the latter greatly enhance the available information regarding functional status. Morphological Studies of the Cerebral Cortex Reports indicate that there is an increased density of neurons and reduced neuropil in the PFC of individuals with schizophrenia (Selemon et al., 1995; Rajkowska et al., 1998). Before examining the integrity of cortical neurons and glia in mood disorders, Dr. Goldman-Rakic and colleagues pioneered morphometric studies in normal cortex (Rajkowska and Goldman-Rakic, 1995a, 1995b), providing a guide for structural and functional in vivo imaging studies by producing a detailed mapping

33: ABNORMALITIES OF BRAIN STRUCTURE AND FUNCTION

of PFC (BA 9 and 46) in Talairach space (Talairach and Tournoux, 1988). Rajkowska’s group (Rajkowska et al., 1999) reported neuronal and glial alterations in the orbitofrontal cortex of individuals with MDD, mostly restricted to the rostral aspect (BA10). They found a 12% reduction in cortical thickness, accompanied by an overall reduction in glial density and a 20%–60% reduction in the density of “large” cortical neurons (reviewed in Rajkowska, 2002). The same group reported a 30% reduction in packing density of pyramidal neurons in the orbital cortex of elderly depressed (Rajkowska et al., 2005). To investigate possible cytoarchitectonic alterations that may explain the changes in receptor binding in the ventral PFC observed in suicide, we used three-dimensional unbiased stereology to estimate the density of neurons in the same areas where the receptor binding was measured (Arango, Underwood, Le, et al., 2001; Arango et al., 2002). Combining receptor binding and neuron density, we calculated an index of receptor binding per neuron: (fmol/mg tissue)/(neurons/mm3). Ventral PFC (right hemisphere) was analyzed in 15 pairs of matched suicides and controls, all psychiatrically characterized. We found neuron density to be lower in suicides with depression. A review of structural imaging data found that results suggest smaller volume of the PFC in major depression (Soares and Mann, 1997a). Functional imaging data are even more convincing regarding hypofunction of the PFC (Rubin et al., 1995; Drevets et al., 1997; Mayberg, 1997; Drevets, 2000; Milak et al., 2005). Therefore, it is of particular importance to pursue the morphometric studies of the PFC. No functional imaging method can match the image resolution of postmortem light microscopy, electron microscopy and film-based autoradiography of receptor binding, and in situ hybridization histochemistry. Studies of this kind should include individuals with major depression dying from causes other than suicide to clearly distinguish the neurochemistry of major depression. Such studies are rarely performed and are a priority. Hypothalamic-Pituitary-Adrenal Axis A great deal of work on depression and suicide has focused on the hypothalamic-pituitary-adrenal (HPA) axis (Bunney et al., 1969; Carroll et al., 1981; Nemeroff et al., 1988; Mann and Currier, 2006). Hypercortisolism is a well-documented abnormality in mood disorders (Carroll, Curtis, Davies, et al., 1976; Carroll, Curtis, and Mendels, 1976; Coryell et al., 2006). Suicides have heavier adrenal glands than individuals who die by other causes (Szigethy et al., 1994), higher levels of corticotropin-releasing hormone (CRH) in the CSF (Arato et al., 1989) and fewer CRH receptors in the cortex (Nemeroff et al., 1988; Nemeroff et al., 1992). Patients with major depression also show adrenal gland hypertrophy by

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computerized tomography (Nemeroff et al., 1992) and more CRH-synthesizing neurons and mRNA in the paraventricular hypothalamic nucleus (Raadsheer et al., 1994; Raadsheer et al., 1995). A hypothesized breakdown in cortisol feedback on CRH secretion at the level of the hypothalamus, perhaps due to hippocampal damage, has little direct experimental data support. Structural magnetic resonance imaging (MRI) studies of reduced hippocampal volume in individuals with major depression are suggestive (Sheline et al., 1996; Sheline et al., 1999; Bremner et al., 2000; Sheline, 2000), especially following traumatic brain injury (Jorge et al., 2007), but not conclusive (see Soares and Mann, 1997b; Sala et al., 2004). Studies in elderly individuals with depression showed that the hippocampal volume reduction seen in this population was not associated with increased cortisol level, but correlated with memory deficits (O’Brien et al., 2004). Lyons and colleagues (2001) examined the effects of early life stressors and inherited variation in hippocampal volume of monkeys. They concluded that small hippocami were more the result of an inherited characteristic than the result of cortisol-induced volume loss. Postmortem studies in individuals with depression have demonstrated atrophy of the PFC and hippocampus, as indicated by fewer neurons and glia, smaller size and/or lower cell density and dendritic length (Sheline et al., 1996; Benes et al., 1998; Öngür et al., 1998; Rajkowska et al., 1999; Sheline et al., 1999; Rajkowska, 2000; Sapolsky, 2000; Arango et al., 2002). Extra Hypothalamic CRH System Corticotropin-releasing hormone neurons are localized in brain areas other than the hypothalamus in several species (Fischman and Moldow, 1982; Cote et al., 1983), including nonhuman primates (Foote and Cha, 1988; Lewis et al., 1989), and humans (Pammer et al., 1990; Austin et al., 1995). We were the first to describe a group of CRH immunoreactive neurons in the peduculo pontine tegmental nucleus and laterodorsal complex in the brain stem of the human that also expressed CRH mRNA (Arango, Rice, et al., 1993; Austin et al., 1995). These neurons are in a position close to the LC, the DRN and MRN, and the substantia nigra, all monoaminergic nuclei that are differentially innervated by CRH axons (Austin et al., 1995; Austin et al., 1997; Ruggiero et al., 1999). The specificity of this anatomical localization may dictate the differential influence that CRH may exert on a specific neurotransmitter system. No studies have quantified these brain-stem CRH neurons. Light microscopy immunocytochemical studies suggest that CRH neuronal processes terminate on DRN serotonergic neurons and on NA neurons (Arango, Rice, et al., 1993; Austin et al., 1997; Ruggiero et al., 1999) and, if so, are uniquely situated to modulate monoaminergic function. These

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studies will help complete the picture in terms of this major neurohumoral stress–response system.

CONCLUSIONS Considerable new information has emerged from postmortem brain studies implicating altered serotonergic, NA, and HPA function in major depression and suicide. These findings should be considered in the context of in vivo studies of these systems in patients who are depressed and remitted. In vivo studies suggest that serotonergic abnormalities may be a stable trait reflecting the vulnerability to recurrent episodes of major depression, whereas NA changes are at least partly mood state-dependent. HPA axis dysfunction is also partly state-dependent, although enlargement of the pituitary and adrenal glands, and hippocampal atrophy, may persist between episodes and originate in childhood adversity. Functional and structural imaging studies will be able to bridge postmortem brain studies and in vivo studies involving cerebrospinal fluid and neuroendocrine challenge techniques by allowing quantitative imaging of neurotransmitter systems in vivo. This kind of approach will allow determination of state- and traitdependent changes related to the pathogenesis of mood disorders. Monitoring of effects of antidepressant treatments will permit identification of actions critical for a clinical response, and thereby aid the clinician, as well as assist in the design of better treatments. Because the data generated by postmortem studies evaluate the brain at one point in time (namely at death), the data offer a high-resolution picture of brain structure and function that cannot distinguish between state and trait, pathogenesis, or treatment effects. Hence, these studies must be interpreted in the context of data from in vivo longitudinal studies that can make these distinctions.

ACKNOWLEDGMENTS This work was supported by NIMH grants MH40210, MH62185 and NIAAA grant AA09004.

REFERENCES Agren, H. (1980) Symptom patterns in unipolar and bipolar depression correlating with monoamine metabolites in the cerebrospinal fluid: II. Suicide. Psychiatry Res. 3:225–236. American Psychiatric Association. (1987) Diagnostic and Statistical Manual of Mental Disorders, 3rd ed., rev. Washington, DC: American Psychiatric Association. Arango, V., Ernsberger, P., Marzuk, P.M., Chen, J.S., Tierney, H., Stanley, M., Reis, D.J., and Mann, J.J. (1990) Autoradiographic demonstration of increased serotonin 5-HT2 and beta-adrenergic receptor binding sites in the brain of suicide victims. Arch. Gen. Psychiatry 47:1038–1047. Arango, V., Ernsberger, P., Sved, A.F., and Mann, J.J. (1993) Quantitative autoradiography of alpha 1- and alpha 2-adrenergic recep-

tors in the cerebral cortex of controls and suicide victims. Brain Res. 630:271–282. Arango, V., Huang, Y.Y., Underwood, M.D., and Mann, J.J. (2003) Genetics of the serotonergic system in suicidal behavior. J. Psychiatry Res. 37:375–386. Arango, V., and Mann, J.J. (1992) Relevance of serotonergic postmortem studies to suicidal behavior. Int. Rev. Psychiatry 4:131–140. Arango, V., Rice, P.M., Smith, R.W., Austin, M.C., and Mann, J.J. (1993) Immunocytochemical localization of corticotropin-releasing factor in the human brainstem. Society for Neuroscience Abstracts 19:1148. Arango, V., and Underwood, M.D. (1997) Serotonin chemistry in the brain of suicide victims. In: Maris, R., Silverman, M., Canetto, S., eds. Review of Suicidology. New York: Guilford Press, pp. 237–250. Arango, V., Underwood, M.D., Bakalian, M.J., Kassir, S.A., Ellis, S.P., and Mann, J.J. (2004) Widespread 5-HT1A binding increase in suicide but not in major depression or alcoholism. Society for Neuroscience Abstracts. Arango, V., Underwood, M.D., Boldrini, M., Tamir, H., Kassir, S.A., Hsiung, S., Chen, J.J.X., and Mann, J.J. (2001) Serotonin 1A receptors, serotonin transporter binding and serotonin transporter mRNA expression in the brainstem of depressed suicide victims. Neuropsychopharmacology 25:892–903. Arango, V., Underwood, M.D., Gubbi, A.V., and Mann, J.J. (1995) Localized alterations in pre- and postsynaptic serotonin binding sites in the ventrolateral prefrontal cortex of suicide victims. Brain Res. 688:121–133. Arango, V., Underwood, M.D., Kassir, S.A., Bakalian, M.J., Ellis, S.P., Oppenheim, S., and Mann, J.J. (1998, Dec 14–18) Revisiting serotonin 5-HT1A binding in prefrontal cortex of suicide victims. Paper presented at the ACNP 37th Annual Meeting, Las Croabas, Puerto Rico. Arango, V., Underwood, M.D., Le, E., Johnson, V.L., Kassir, S.A., and Mann, J.J. (2001, Dec 9–13) Suicide victims have lower neuronal density, decreased 5-HT innervation and higher 5-HT1A and 5-HT2A receptor binding per neuron than controls in orbital prefrontal cortex. Paper presented at the ACNP 40th Annual Meeting, Waikoloa, Hawaii. Arango, V., Underwood, M.D., and Mann, J.J. (1996) Fewer pigmented locus coeruleus neurons in suicide victims: preliminary results. Biol. Psychiatry 39:112–120. Arango, V., Underwood, M.D., and Mann, J.J. (2002) Serotonin brain circuits involved in major depression and suicide. In: Azmitia, E.C., DeFelipe, J., Jones, E.G., Rakic, P., Ribak, C.E., ed. Changing Views of Cajal’s Neuron. Amsterdam: Elsevier, pp. 443– 453. Arango, V., Underwood, M.D., and Mann, J.J. (2003, Dec 7–11) Serotonin and neuropeptide circuitry in depression and suicide. Paper presented at the ACNP 42nd Annual Meeting, San Juan, Puerto Rico. Arato, M., Banki, C.M., Bissette, G., and Nemeroff, C.B. (1989) Elevated CSF CRF in suicide victims. Biol. Psychiatry 25:355–359. Arora, R.C., and Meltzer, H.Y. (1991) Laterality and 3H-imipramine binding: studies in the frontal cortex of normal controls and suicide victims. Biol. Psychiatry 29:1016–1022. Arranz, B., Eriksson, A., Mellerup, E., Plenge, P., and Marcusson, J. (1994) Brain 5-HT1A, 5-HT1D, and 5-HT2 receptors in suicide victims. Biol. Psychiatry 35:457– 463. Åsberg, M., Träskman, L., and Thorén, P. (1976) 5-HIAA in the cerebrospinal fluid. A biochemical suicide predictor? Arch. Gen. Psychiatry 33:1193–1197. Austin, M.C., Rhodes, J.L., and Lewis, D.A. (1997) Differential distribution of corticotropin-releasing hormone immunoreactive axons in monoaminergic nuclei of the human brainstem. Neuropsychopharmacology 17:326–341. Austin, M.C., Rice, P.M., Mann, J.J., and Arango, V. (1995) Localization of corticotropin-releasing hormone in the human locus

33: ABNORMALITIES OF BRAIN STRUCTURE AND FUNCTION coeruleus and pedunculopontine tegmental nucleus: an immunocytochemical and in situ hybridization study. Neuroscience 64: 713–727. Bach-Mizrachi, H., Underwood, M.D., Kassir, S.A., Bakalian, M.J., Sibille, E., Tamir, H., Mann, J.J., and Arango, V. (2006) Neuronal tryptophan hydroxylase mRNA expression in the human dorsal and median raphe nuclei: major depression and suicide. Neuropsychopharmacology 31:814 –824. Baker, K.G., Halliday, G.M., and Tork, I. (1990) Cytoarchitecture of the human dorsal raphe nucleus. J. Comp. Neurol. 301:147–161. Barr, C.S., Newman, T.K., Lindell, S., Becker, M.L., Shannon, C., Champoux, M., Suomi, S.J., and Higley, J.D. (2004) Early experience and sex interact to influence limbic-hypothalamic-pituitary-adrenal-axis function after acute alcohol administration in rhesus macaques (Macaca mulatta). Alcohol Clin. Exp. Res. 28: 1114 –1119. Baumann, B., Danos, P., Diekmann, S., Krell, D., Bielau, H., Geretsegger, C., Wurthmann, C., Bernstein, H.-G., and Bogerts, B. (1999) Tyrosine hydroxylase immunoreactivity in the locus coeruleus is reduced in depressed non-suicidal patients but normal in depressed suicide patients. Eur. Arch. Psychiatry Clin. Neurosci. 249:212–219. Baumann, B., Danos, P., Krell, D., Diekmann, S., Wurthmann, C., Bielau, H., Bernstein, H.G., and Bogerts, B. (1999) Unipolarbipolar dichotomy of mood disorders is supported by noradrenergic brainstem system morphology. J. Affect. Disord. 54:217–224. Benes, F.M., Kwok, E.W., Vincent, S.L., and Todtenkopf, M.S. (1998) A reduction of nonpyramidal cells in sector CA2 of schizophrenics and manic depressives. Biol. Psychiatry 44:88–97. Beskow, J., Gottfries, C.G., Roos, B.E., and Winblad, B. (1976) Determination of monoamine and monoamine metabolites in the human brain: post mortem studies in a group of suicides and in a control group. Acta Psychiatr. Scand. 53:7–20. Biegon, A., and Fieldust, S. (1992) Reduced tyrosine hydroxylase immunoreactivity in locus coeruleus of suicide victims. Synapse 10:79–82. Biegon, A., Grinspoon, A., Blumenfeld, B., Bleich, A., Apter, A., and Mester, R. (1990) Increased serotonin 5-HT2 receptor binding on blood platelets of suicidal men. Psychopharmacology (Berl) 100:165–167. Biegon, A., and Israeli, M. (1988) Regionally selective increases in beta-adrenergic receptor density in the brains of suicide victims. Brain Res. 442:199–203. Birkmayer, W., and Riederer, P. (1975) Biochemical postmortem findings in depressed patients. J. Neural Transm. 37:95–109. Boldrini, M., Underwood, M.D., Mann, J.J., and Arango, V. (2005) More tryptophan hydroxylase in the brainstem dorsal raphe nucleus in depressed suicides. Brain Res. 1041:19–28. Boldrini, M., Underwood, M.D., Mann, J.J., and Arango, V. (2007) Serotonin-1A autoreceptor binding in the dorsal raphe nucleus of depressed suicides. Psychiatry Res. 42(6):433– 442. Bonkale, W.L., Murdock, S., Janosky, J.E., and Austin, M.C. (2004) Normal levels of tryptophan hydroxylase immunoreactivity in the dorsal raphe of depressed suicide victims. J. Neurochem. 88: 958–964. Bonkale, W.L., Turecki, G., and Austin, M.C. (2006) Increased tryptophan hydroxylase immunoreactivity in the dorsal raphe nucleus of alcohol-dependent, depressed suicide subjects is restricted to the dorsal subnucleus. Synapse 60:81–85. Bourne, H.R., Bunney, W.E., Jr., Colburn, R.W., Davis, J.M., Shaw, D.M., and Coppen, A.J. (1968) Noradrenaline, 5-hydroxytryptamine, and 5-hydroxyindoleacetic acid in hindbrains of suicidal patients. Lancet 2(7572):805–808. Bremner, J.D., Narayan, M., Anderson, E.R., Staib, L.H., Miller, H.L., and Charney, D.S. (2000) Hippocampal volume reduction in major depression. Am. J. Psychiatry 157:115–118. Brodsky, B.S., Oquendo, M.A., Ellis, S.P., Haas, G.L., Malone, K.M., and Mann, J.J. (2001) The relationship of childhood abuse to

525

impulsivity and suicidal behavior in adults with major depression. Am. J. Psychiatry 158:1871–1877. Brown, G.L., Goodwin, F.K., and Bunney, W.E., Jr. (1982) Human aggression and suicide: their relationship to neuropsychiatric diagnoses and serotonin metabolism. Adv. Biochem. Psychopharmacol. 34:287–307. Bunney, W.E., Jr., Fawcett, J.A., Davis, J.M., and Gifford, S. (1969) Further evaluation of urinary 17-hydroxycorticosteroids in suicidal patients. Arch. Gen. Psychiatry 21:138–150. Carroll, B.J., Curtis, G.C., Davies, B.M., Mendels, J., and Sugerman, A.A. (1976) Urinary free cortisol excretion in depression. Psychol. Med. 6:43–50. Carroll, B.J., Curtis, G.C., and Mendels, J. (1976) Cerebrospinal fluid and plasma free cortisol concentrations in depression. Psychol. Med. 6:235–244. Carroll, B.J., Greden, J.F., and Feinberg, M. (1981) Suicide, neuroendocrine dysfunction and CSF 5-H1AA concentrations in depression. In: Angris, B., ed. Recent Advances in Neuropsychopharmacology: Selected Papers from the 12th Congress of the Collegium Internationale Neuro-Psychopharmacologicum, Ghoteborg, Sweden, 22-26 June 1980. New York: Pergamon Press Oxford, pp. 307–313. Coccaro, E.F., Siever, L.J., Klar, H.M., Maurer, G., Cochrane, K., Cooper, T.B., Mohs, R.C., and Davis, K.L. (1989) Serotonergic studies in patients with affective and personality disorders. Correlates with suicidal and impulsive aggressive behavior. Arch. Gen. Psychiatry 46:587–599. Coryell, W., Young, E., and Carroll, B. (2006) Hyperactivity of the hypothalamic-pituitary-adrenal axis and mortality in major depressive disorder. Psychiatry Res. 142:99–104. Cote, J., Lefevre, G., Labrie, F., and Barden, N. (1983) Distribution of corticotropin-releasing factor in ovine brain determined by radioimmunoassay. Regl. Pept. 5:189–195. Crow, T.J., Cross, A.J., Cooper, S.J., Deakin, J.F.W., Ferrier, I.N., Johnson, J.A., Joseph, M.H., Owen, F., Poulter, M., Lofthouse, R., Corsellis, J.A.N., Chambers, D.R., Blessed, G., Perry, E.K., Perry, R.H., and Tomlinson, B.E. (1984) Neurotransmitter receptors and monoamine metabolites in the brains of patients with Alzheimer-type dementia and depression, and suicides. Neuropharmacology 23:1561–1569. De Luca, V., Likhodi, O., Van Tol, H.H., Kennedy, J.L., and Wong, A.H. (2005) Tryptophan hydroxylase 2 gene expression and promoter polymorphisms in bipolar disorder and schizophrenia. Psychopharmacology (Berl) 183(3):378–382. De Luca, V., Likhodi, O., Van Tol, H.H., Kennedy, J.L., and Wong, A.H. (2006) Gene expression of tryptophan hydroxylase 2 in postmortem brain of suicide subjects. Int. J. Neuropsychopharmacol. 9(1):21–25. De Paermentier, F., Cheetham, S.C., Crompton, M.R., Katona, C.L.E., and Horton, R.W. (1990) Brain b-adrenoceptor binding sites in antidepressant-free depressed suicide victims. Brain Res. 525: 71–77. Delgado, P.L., Charney, D.S., Price, L.H., Aghajanian, G.K., Landis, H., and Heninger, G.R. (1990) Serotonin function and the mechanism of antidepressant action. Reversal of antidepressant-induced remission by rapid depletion of plasma tryptophan. Arch. Gen. Psychiatry 47:411– 418. Delgado, P.L., Price, L.H., Miller, H.L., Salomon, R.M., Aghajanian, G.K., Heninger, G.R., and Charney, D.S. (1994) Serotonin and the neurobiology of depression. Effects of tryptophan depletion in drugfree depressed patients. Arch. Gen. Psychiatry 51:865–874. Dillon, K.A., Gross-Isseroff, R., Israeli, M., and Biegon, A. (1991) Autoradiographic analysis of serotonin 5-HT1A receptor binding in the human brain postmortem: Effects of age and alcohol. Brain Res. 554:56–64. Dorph-Petersen, K.-A., Nyengaard, J.R., Rosenberg, R., and Gundersen, H.J.G. (2001) No change in serotonergic neuron number and

526

MOOD DISORDERS

volume in the human dorsal raphe in depression but observation of a pronounced sexual dismorphism - A stereological study using unbiased principles. Society for Neuroscience Abstracts. 27. Drevets, W.C. (2000) Neuroimaging studies of mood disorders. Biol. Psychiatry 48:813–829. Drevets, W.C., Frank, E., Price, J.C., Kupfer, D.J., Holt, D., Greer, P.J., Huang, Y., Gautier, C., and Mathis, C. (1999) PET imaging of serotonin 1A receptor binding in depression. Biol. Psychiatry 46:1375–1387. Drevets, W.C., Price, J.L., Simpson, J.R., Jr., Todd, R.D., Reich, T., Vannier. M., and Raichle, M.E. (1997) Subgenual prefrontal cortex abnormalities in mood disorders. Nature 386:824–827. Escriba, P.V., Ozaita, A., and Garcia-Sevilla, J.A. (2004) Increased mRNA expression of alpha2A-adrenoceptors, serotonin receptors and mu-opioid receptors in the brains of suicide victims. Neuropsychopharmacology 29:1512–1521. Fairbanks, L.A., Jorgensen, M.J., Huff, A., Blau, K., Hung, Y.Y., and Mann, J.J. (2004) Adolescent impulsivity predicts adult dominance attainment in male vervet monkeys. Am. J. Primatol. 64: 1–17. Ferrier, I.N., McKeith, I.G., Cross, A.J., Perry, E.K., Candy, J.M., and Perry, R.H. (1986) Postmortem neurochemical studies in depression. Ann. N. Y. Acad. Sci. 487:128–142. Fischman, A.J., and Moldow, R.L. (1982) Extrahypothalamic distribution of CRF-like immunoreactivity in the rat brain. Peptides 1:149–153. Flory, J.D., Mann, J.J., Manuck, S.B., and Muldoon, M.F. (1998) Recovery from major depression is not associated with normalization of serotonergic function. Biol. Psychiatry 43:320–326. Foote, S.L., and Cha, C.I. (1988) Distribution of corticotropinreleasing-factor-like immunoreactivity in brainstem of two monkey species (Saimiri sciureus and Macaca fascicularis): An immunohistochemical study. J. Comp. Neurol. 276:239–264. Garcia-Sevilla, J.A., Escriba, P.V., Ozaita, A., La Harpe, R., Walzer, C., Eytan, A., and Guimon, J. (1999) Up-regulation of immunolabeled alpha2A-adrenoceptors, Gi coupling proteins, and regulatory receptor kinases in the prefrontal cortex of depressed suicides. J. Neurochem. 72:282–291. Gross-Isseroff, R., Dillon, K.A., Fieldust, S.J., and Biegon. A. (1990) Autoradiographic analysis of a1-noradrenergic receptors in the human brain postmortem. Arch. Gen. Psychiatry 47:1049–1053. Gross-Isseroff, R., Israeli, M., and Biegon, A. (1989) Autoradiographic analysis of tritiated imipramine binding in the human brain post mortem: effects of suicide. Arch. Gen. Psychiatry 46:237–241. Heim, C., and Nemeroff, C.B. (2001) The role of childhood trauma in the neurobiology of mood and anxiety disorders: preclinical and clinical studies. Biol. Psychiatry 49:1023–1039. Higley, J.D., Thompson, W.W., Champoux, M., Goldman, D., Hasert, M.F., Kraemer, G.W., Scanlan, J.M., Suomi, S.J., and Linnoila, M. (1993) Paternal and maternal genetic and environmental contributions to cerebrospinal fluid monoamine metabolites in Rhesus monkeys (Macaca mulatta). Arch. Gen. Psychiatry 50:615– 623. Hrdina, P.D., and Du, L. (2001) Levels of serotonin receptor 2A higher in suicide victims? Am. J. Psychiatry 158:147–148. Jorge, R.E., Acion, L., Starkstein, S.E., and Magnotta, V. (2007) Hippocampal volume and mood disorders after traumatic brain injury. Biol. Psychiatry 62:332–338. Joyce, J.N., Shane, A., Lexow, N., Winokur, A., Casanova, M.F., and Kleinman, J.E. (1993) Serotonin uptake sites and serotonin receptors are altered in the limbic system of schizophrenics. Neuropsychopharmacology 8:315–336. Kelly, T.M., and Mann, J.J. (1996) Validity of DSM-III-R diagnosis by psychological autopsy: a comparison with clinician ante-mortem diagnosis. Acta Psychiatr. Scand. 94:337–343. Klimek, V., Rajkowska, G., Luker, S.N., Dilley, G., Meltzer, H.Y., Overholser, J.C., Stockmeier, C.A., and Ordway, G.A. (1999) Brain noradrenergic receptors in major depression and schizophrenia. Neuropsychopharmacology 21:69–81.

Klimek, V., Stockmeier, C.A., Overholser, J., Meltzer, H.Y., Kalka, S., Dilley, G., and Ordway, G.A. (1997) Reduced levels of norepinephrine transporters in the locus coeruleus in major depression. J. Neurosci. 17:8451–8458. Korpi, E.R., Kleinman, J., Goodman, S.I., Phillips, I., DeLisi, L.E., Linnoila, M., and Wyatt, R.J. (1986) Serotonin and 5-hydroxyindoleacetic acid in brains of suicide victims. Comparison in chronic schizophrenic patients with suicide as cause of death. Arch. Gen. Psychiatry 43:594–600. Lawrence, K.M., De Paermentier, F., Cheetham, S.C., Crompton, M.R., Katona, C.L.E., and Horton, R.W. (1990) Symmetrical hemispheric distribution of 3H-paroxetine binding sites in postmortem human brain from controls and suicides. Biol. Psychiatry 28: 544–546. Lemonde, S., Turecki, G., Bakish, D., Du, L., Hrdina, P.D., Bown, C.D., Sequeira, A., Kushwaha, N., Morris, S.J., Basak, A., Ou, X.M., and Albert, P.R. (2003) Impaired repression at a 5hydroxytryptamine 1A receptor gene polymorphism associated with major depression and suicide. J. Neurosci. 23:8788–8799. Levine, S. (2005) Developmental determinants of sensitivity and resistance to stress. Psychoneuroendocrinology 30:939–946. Lewis, D.A. (2002) The human brain revisited. Opportunities and challenges in postmortem studies of psychiatric disorders. Neuropsychopharmacology 26:143–154. Lewis, D.A., Foote, S.L., and Cha, C.I. (1989) Corticotropin-releasing factor immunoreactivity in monkey neocortex: An immunohistochemical analysis. J. Comp. Neurol. 290:599–613. Little, K.Y., Clark, T.B., Ranc, J., and Duncan, G.E. (1993) b-Adrenergic receptor binding in frontal cortex from suicide victims. Biol. Psychiatry 34:596–605. Lloyd, K.G., Farley, I.J., Deck, J.H.N., and Hornykiewicz, O. (1974) Serotonin and 5-hydroxyindoleacetic acid in discrete areas of the brainstem of suicide victims and control patients. Adv. Biochem. Psychopharmacol. 11:387–397. Lowther, S., De Paermentier, F., Cheetham, S.C., Crompton, M.R., Katona, C.L., and Horton, R.W. (1997) 5-HT1A receptor binding sites in post-mortem brain samples from depressed suicides and controls. J. Affect. Disord. 42:199–207. Lyons, D.M., Yang, C., Sawyer-Glover, A.M., Moseley, M.E., and Schatzberg, A.F. (2001) Early life stress and inherited variation in monkey hippocampal volumes. Arch. Gen. Psychiatry 58: 1145–1151. Malone, K.M., Corbitt, E.M., Li, S, and Mann, J.J. (1996) Prolactin response to fenfluramine and suicide attempt lethality in major depression. Br. J. Psychiatry 168:324 –329. Mann, J.J. (1998) The neurobiology of suicide. Nat. Med. 4:25–30. Mann, J.J. (2002) A current perspective of suicide and attempted suicide. Ann. Intern. Med. 136:302–311. Mann, J.J. (2003) Neurobiology of suicidal behaviour. Nat. Rev. Neurosci. 4:819–828. Mann, J.J., Arango, V., Marzuk, P.M., Theccanat, S., and Reis, D.J. (1989) Evidence for the 5-HT hypothesis of suicide. A review of post-mortem studies. Br. J. Psychiatry Suppl 155 (Suppl 8):7–14. Mann, J.J., Bortinger, J., Oquendo, M.A., Currier, D., Li, S., and Brent, D.A. (2005) Family history of suicidal behavior and mood disorders in probands with mood disorders. Am. J. Psychiatry 162:1672–1679. Mann, J.J., Brent, D.A., and Arango, V. (2001) The neurobiology and genetics of suicide and attempted suicide: a focus on the serotonergic system. Neuropsychopharmacology 24:467– 477. Mann, J.J., and Currier, D. (2006) Effects of genes and stress on the neurobiology of depression. Int. Rev. Neurobiol. 73:153–189. Mann, J.J., and Currier, D. (2007) A review of prospective studies of biologic predictors of suicidal behavior in mood disorders. Arch. Suicide Res. 11:3–16. Mann, J.J., Currier, D., Stanley, B., Oquendo, M.A., Amsel, L.V., and Ellis, S.P. (2006) Can biological tests assist prediction of suicide in mood disorders? Int. J. Neuropsychopharmacol. 9:465– 474.

33: ABNORMALITIES OF BRAIN STRUCTURE AND FUNCTION Mann, J.J., Henteleff, R.A., Lagattuta, T.F., Perper, J.A., Li, S., and Arango, V. (1996) Lower 3H-paroxetine binding in cerebral cortex of suicide victims is partly due to fewer high affinity, nontransporter sites. J. Neural Transm. 103:1337–1350. Mann, J.J., Huang, Y.Y., Underwood, M.D., Kassir, S.A., Oppenheim, S., Kelly, T.M., Dwork, A.J., and Arango, V. (2000) A serotonin transporter gene promoter polymorphism (5-HTTLPR) and prefrontal cortical binding in major depression and suicide. Arch. Gen. Psychiatry 57:729–738. Mann, J.J., and Malone, K.M. (1997) Cerebrospinal fluid amines and higher-lethality suicide attempts in depressed inpatients. Biol. Psychiatry 41:162–171. Mann, J.J., Malone, K.M., Sweeney, J.A., Brown, R.P., Linnoila, M., Stanley, B., and Stanley, M. (1996) Attempted suicide characteristics and cerebrospinal fluid amine metabolites in depressed inpatients. Neuropsychopharmacology 15:576–586. Mann, J.J., McBride, P.A., Brown, R.P., Linnoila, M., Leon, A.C., DeMeo, M., Mieczkowski, T., Myers, J.E., and Stanley, M. (1992) Relationship between central and peripheral serotonin indexes in depressed and suicidal psychiatric inpatients. Arch. Gen. Psychiatry 49:442– 446. Mann, J.J., McBride, P.A., Malone, K.M., DeMeo, M.D., and Keilp, J.G. (1995) Blunted serotonergic responsivity in depressed patients. Neuropsychopharmacology 13:53–64. Mann, J.J., Stanley, M., McBride, P.A., and McEwen, B.S. (1986) Increased serotonin2 and beta-adrenergic receptor binding in the frontal cortices of suicide victims. Arch. Gen. Psychiatry 43:954 –959. Mann, J.J., Underwood, M.D., and Arango, V. (1996) Postmortem studies of suicide victims. In: Watson, S.J., ed. Biology of Schizophrenia and Affective Disease. Washington, DC: American Psychiatric Press, pp. 197–220. Matsubara, S., Arora, R.C., and Meltzer, H.Y. (1991) Serotonergic measures in suicide brain: 5-HT1A binding sites in frontal cortex of suicide victims. J. Neural Transm. Gen. Sect. 85:181–194. Mayberg, H.S. (1997) Limbic-cortical dysregulation: a proposed model of depression. J. Neuropsychiatry Clin. Neurosci. 9:471– 481. McBride, P.A., Brown, R.P., DeMeo, M., Keilp, J., Mieczkowski, T., and Mann, J.J. (1994) The relationship of platelet 5-HT2 receptor indices to major depressive disorder, personality traits, and suicidal behavior. Biol. Psychiatry 35:295–308. McKeith, I.G., Marshall, E.F., Ferrier, I.N., Armstrong, M.M., Kennedy, W.N., Perry, E.K., and Eccleston, D. (1987) 5-HT receptor binding in post-mortem brain from patients with affective disorder. J. Affect. Disord. 13:67–74. Meana, J.J., and García-Sevilla, J.A. (1987) Increased a2-adrenoceptor density in the frontal cortex of depressed suicide victims. J. Neural Transm. 70:377–381. Meyerson, L.R., Wennogle, L.P., Abel, M.S., Coupet, J., Lippa, A.S., Rauh, C.E., and Beer, B. (1982) Human brain receptor alterations in suicide victims. Pharmacol. Biochem. Behav. 17:159–163. Milak, M.S., Parsey, R.V., Keilp, J., Oquendo, M.A., Malone, K.M, and Mann, J.J. (2005) Neuroanatomic correlates of psychopathologic components of major depressive disorder. Arch. Gen. Psychiatry 62:397– 408. Nemeroff, C.B., Krishnan, K.R., Reed, D., Leder, R., Beam, C., and Dunnick, N.R. (1992) Adrenal gland enlargement in major depression. A computed tomographic study. Arch. Gen. Psychiatry 49:384 –387. Nemeroff, C.B., Owens, M.J., Bissette, G., Andorn, A.C., and Stanley, M. (1988) Reduced corticotropin releasing factor binding sites in the frontal cortex of suicide victims. Arch. Gen. Psychiatry 45: 577–579. Nordström, P., Samuelsson, M., Åsberg, M., Träskman-Bendz, L., Aberg-Wistedt, A., Nordin, C., and Bertilsson, L. (1994) CSF 5HIAA predicts suicide risk after attempted suicide. Suicide Life Threat. Behav. 24:1–9. O’Brien, J.T., Lloyd, A., McKeith, I., Gholkar, A., and Ferrier, N. (2004) A longitudinal study of hippocampal volume, cortisol lev-

527

els, and cognition in older depressed subjects. Am. J. Psychiatry 161:2081–2090. O’Keane, V., and Dinan, T.G. (1991) Prolactin and cortisol responses to d-fenfluramine in major depression: Evidence for diminished responsivity of central serotonergic function. Am. J. Psychiatry 148:1009–1015. Öngür, D., Drevets, W.C., and Price, J.L. (1998) Glial reduction in the subgenual prefrontal cortex in mood disorders. Proc. Natl. Acad. Sci. USA 95:13290–13295. Ono, H., Shirakawa, O., Kitamura, N., Hashimoto, T., Nishiguchi, N., Nishimura, A., Nushida, H., Ueno, Y., and Maeda, K. (2002) Tryptophan hydroxylase immunoreactivity is altered by the genetic variation in postmortem brain samples of both suicide victims and controls. Mol. Psychiatry 7:1127–1132. Ordway, G.A. (1997) Pathophysiology of the locus coeruleus in suicide. Ann. N. Y. Acad. Sci. 836:233–252. Ordway, G.A., Smith, K.S., and Haycock, J.W. (1994) Elevated tyrosine hydroxylase in the locus coeruleus of suicide victims. J. Neurochem 62:680–685. Ordway, G.A., Stockmeier, C.A., Cason, G.W., and Klimek, V. (1997) Pharmacology and distribution of norepinephrine transporters in the human locus coeruleus and raphe nuclei. J. Neurosci. 17: 1710–1719. Ordway, G.A., Widdowson, P.S., Smith, K.S., and Halaris, A. (1994) Agonist binding to a2-adrenoceptors is elevated in the locus coeruleus from victims of suicide. J. Neurochem. 63:617–624. Owen, F., Chambers, D.R., Cooper, S.J., Crow, T.J., Johnson, J.A., Lofthouse, R., and Poulter, M. (1986) Serotonergic mechanisms in brains of suicide victims. Brain Res. 362:185–188. Pammer, C., Gorcs, T.J., and Palkovits, M. (1990) Peptidergic innervation of the locus coeruleus cells in the human brain. Brain Res. 515:247–255. Pandey, G.N., Dwivedi, Y., Ren, X., Robert, R.C., Conley, R., and Tamminga, C. (2001) Increased 5HT2A receptors and impaired phosphoinositide siginaling in the postmortem brain of suicide victims. In: Miyoshi, K., Shapiro, C.M., Gaviria, M., Morita, Y., eds. Contemporary Neuropsychiatry. Tokyo: Springer-Verlag, pp. 314 –321. Pandey, G.N., Dwivedi, Y., Rizavi, H.S., Ren, X., Pandey, S.C., Pesold, C., Roberts, R.C., Conley, R.R., and Tamminga, C.A. (2002) Higher expression of serotonin 5-HT(2A) receptors in the postmortem brains of teenage suicide victims. Am. J. Psychiatry 159:419– 429. Pandey, G.N., Pandey, S.C., Dwivedi, Y., Sharma, R.P., Janicak, P.G., and Davis, J.M. (1995) Platelet serotonin-2A receptors: a potential biological marker for suicidal behavior. Am. J. Psychiatry 152:850–855. Pandey, G.N., Pandey, S.C., Janicak, P.G., Marks, R.C., and Davis, J.M. (1990) Platelet serotonin-2 receptor binding sites in depression and suicide. Biol. Psychiatry 28:215–222. Pare, C.M.B., Yeung, D.P.H., Price, K., and Stacey, R.S. (1969) 5Hydroxytryptamine, noradrenaline, and dopamine in brainstem, hypothalamus, and caudate nucleus of controls and of patients committing suicide by coal-gas poisoning. Lancet 2(7612): 133–135. Parsey, R.V., Oquendo, M.A., Ogden, R.T., Olvet, D.M., Simpson, N., Huang, Y.Y., Van Heertum, R.L., Arango, V., and Mann, J.J. (2006) Altered serotonin 1A binding in major depression: a [carbonyl-C-11]WAY100635 positron emission tomography study. Biol. Psychiatry 59:106–113. Parsey, R.V., Oquendo, M.A., Simpson, N.R., Ogden, R.T., Van Heertum, R., Arango, V., and Mann, J.J. (2002) Effects of sex, age, and aggressive traits in man on brain serotonin 5- HT(1A) receptor binding potential measured by PET using [C-11]WAY100635. Brain Res. 954:173–182. Paul, S.M., Rehavi, M., Skolnick, P., and Goodwin, F.K. (1984) High affinity binding of antidepressants to a biogenic amine transport site in human brain and platelet; studies in depression. In: Post,

528

MOOD DISORDERS

R.M., Bellinger, C.J., eds. Neurobiology of Mood Disorders. Baltimore: Williams and Wilkins, pp. 846–853. Perry, E.K., Marshall, E.F., Blessed, G., Tomlinson, B.E., and Perry, R.H. (1983) Decreased imipramine binding in the brains of patients with depressive illness. Br. J. Psychiatry 142:188–192. Price, L.H., Charney, D.S., Delgado, P.L., and Heninger, G.R. (1991) Serotonin function and depression: neuroendocrine and mood responses to intravenous L-tryptophan in depressed patients and healthy comparison subjects. Am. J. Psychiatry 148:1518–1525. Pryce, C.R., Dettling, A., Spengler, M., Spaete, C., and Feldon, J. (2004) Evidence for altered monoamine activity and emotional and cognitive disturbance in marmoset monkeys exposed to early life stress. Ann. N. Y. Acad. Sci. 1032:245–249. Raadsheer, F.C., Hoogendijk, W.J.G., Stam, F.C., Tilders, F.J.H., and Swaab, D.F. (1994) Increased numbers of corticotropin-releasing hormone expressing neurons in the hypothalamic paraventricular nucleus of depressed patients. Neuroendocrinology 60:436– 444. Raadsheer, F.C., Van Heerikhuize, J.J., Lucassen, P.J., Hoogendijk, W.J.G., Tilders, F.J.H., and Swaab, D.F. (1995) Corticotropinreleasing hormone mRNA levels in the paraventricular nucleus of patients with Alzheimer’s disease and depression. Am. J. Psychiatry 152:1372–1376. Rajkowska, G. (2000) Postmortem studies in mood disorders indicate altered numbers of neurons and glial cells [Dysfunction in neural circuits involved in the pathophysiology of mood disorders]. Biol. Psychiatry 48:766–777. Rajkowska, G. (2002) Cell pathology in mood disorders. Semin. Clin. Neuropsychiatry 7:281–292. Rajkowska, G., and Goldman-Rakic, P.S. (1995a) Cytoarchitectonic definition of prefrontal areas in the normal human cortex: I. Remapping of areas 9 and 46 using quantitative criteria. Cereb. Cortex 5:307–322. Rajkowska, G., and Goldman-Rakic, P.S. (1995b) Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System. Cereb. Cortex 5:323–337. Rajkowska, G., Miguel-Hidalgo, J.J., Dubey, P., Stockmeier, C.A., and Krishnan, K.R. (2005) Prominent reduction in pyramidal neurons density in the orbitofrontal cortex of elderly depressed patients. Biol. Psychiatry 58:297–306. Rajkowska, G., Miguel-Hidalgo, J.J., Wei, J., Dilley, G., Pittman, S.D., Meltzer, H.Y., Overholser, J.C., Roth, B.L., and Stockmeier, C.A. (1999) Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression. Biol. Psychiatry 45:1085–1098. Rajkowska, G., Selemon, L.D., and Goldman-Rakic, P.S. (1998) Neuronal and glial somal size in the prefrontal cortex. A postmortem morphometric study of schizophrenia and Huntington disease. Arch. Gen. Psychiatry 55:215–224. Rogers, J., Martin, L.J., Comuzzie, A.G., Mann, J.J., Manuck, S.B., Leland, M., and Kaplan, J.R. (2004) Genetics of monoamine metabolites in baboons: overlapping sets of genes influence levels of 5-hydroxyindolacetic acid, 3-hydroxy-4-methoxyphenylglycol, and homovanillic acid. Biol. Psychiatry 55:739–744. Rubin, E., Sackeim, H.A., Prohovnik, I., Moeller, J.R., Schnur, D.B., and Mukherjee, S. (1995) Regional cerebral blood flow in mood disorders: IV. Comparison of mania and depression. Psychiatry Res. 61:1–10. Ruggiero, D.A., Underwood, M.D., Rice, P.M., Mann, J.J., and Arango, V. (1999) Corticotropic-releasing hormone and serotonin interact in the human brainstem: behavioral implications. Neuroscience 91:1343–1354. Sala, M., Perez, J., Soloff, P., Ucelli di Nemi, S., Caverzasi, E., Soares, J.C., and Brambilla, P. (2004) Stress and hippocampal abnormalities in psychiatric disorders. Eur. Neuropsychopharmacol. 14: 393– 405. Sapolsky, R.M. (2000) The possibility of neurotoxicity in the hippocampus in major depression: a primer on neuron death. Biol. Psychiatry 48:755–765.

Sargent, P.A., Kjaer, K.H., Bench, C.J., Rabiner, E.A., Messa, C., Meyer, J., Gunn, R.N., Grasby, P.M., and Cowen, P.J. (2000) Brain serotonin 1A receptor binding measured by positron emission tomography with [11C]WAY-100635: effects of depression and antidepressant treatment. Arch. Gen. Psychiatry 57:174–180. Selemon, L.D., Rajkowska, G., and Goldman-Rakic, P.S. (1995) Abnormally high neuronal density in the schizophrenic cortex - A morphometric analysis of prefrontal area 9 and occipital area 17. Arch. Gen. Psychiatry 52:805–818. Shamir, A., Shaltiel, G., Levi, I., Belmaker, R.H., and Agam, G. (2005) Postmortem parietal cortex TPH2 expression is not altered in schizophrenic, unipolar-depressed, and bipolar patients vs control subjects. J. Mol. Neurosci. 26:33–37. Shaw, D.M., Camps, F.E., and Eccleston, E.G. (1967) 5-Hydroxytryptamine in the hind-brain of depressive suicides. Br. J. Psychiatry 113:1407–1411. Sheldon, P.W., and Aghajanian, G.K. (1990) Serotonin (5-HT) induces IPSPs in pyramidal layer cells of rat piriform cortex: evidence for the involvement of a 5-HT2-activated interneuron. Brain Res. 506: 62–69. Sheline, Y.I. (2000) 3D MRI studies of neuroanatomic changes in unipolar major depression: the role of stress and medical comorbidity. Biol. Psychiatry 48:791–800. Sheline, Y.I., Sanghavi, M., Mintun, M.A., and Gado, M.H. (1999) Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. J. Neurosci. 19:5034–5043. Sheline, Y.I., Wang, P.W., Gado, M.H., Csernansky, J.G., and Vannier, M.W. (1996) Hippocampal atrophy in recurrent major depression. Proc. Natl. Acad. Sci. USA 93:3908–3913. Sibille, E., and Hen, R. (2001) Serotonin(1A) receptors in mood disorders: a combined genetic and genomic approach. Behav. Pharmacol. 12:429– 438. Soares, J.C., and Mann, J.J. (1997a) The anatomy of mood disorders—review of structural neuroimaging studies. Biol. Psychiatry 41:86–106. Soares, J.C., and Mann, J.J. (1997b) The functional neuroanatomy of mood disorders. J. Psychiatr. Res. 31:393 – 432. Stanley, M., Virgilio, J., and Gershon, S. (1982) Tritiated imipramine binding sites are decreased in the frontal cortex of suicides. Science 216:1337–1339. Stockmeier, C.A. (2003) Involvement of serotonin in depression: evidence from postmortem and imaging studies of serotonin receptors and the serotonin transporter. J. Psychiat. Res. 37:357–373. Stockmeier, C.A., Dilley, G.E., Shapiro, L.A., Overholser, J.C., Thompson, P.A., and Meltzer, H.Y. (1997) Serotonin receptors in suicide victims with major depression. Neuropsychopharmacology 16:162–173. Stockmeier, C.A., and Meltzer, H.Y. (1991) b-Adrenergic receptor binding in frontal cortex of suicide victims. Biol. Psychiatry 29: 183–191. Stockmeier, C.A., Shapiro, L.A., Dilley, G.E., Kolli, T.N., Friedman, L., and Rajkowska, G. (1998) Increase in serotonin-1A autoreceptors in the midbrain of suicide victims with major depressionpostmortem evidence for decreased serotonin activity. J. Neurosci. 18:7394–7401. Szigethy, E., Conwell, Y., Forbes, N.T., Cox, C., and Caine, E.D. (1994) Adrenal weight and morphology in victims of completed suicide. Biol. Psychiatry 36:374–380. Talairach, J., and Tournoux, P. (1988) Co-Planar Stereotaxic Atlas of the Human Brain. Dimensional Proportional System: An Approach to Cerebral Imaging. New York: Thieme Medical Publishers, Inc. Törk, I. (1990) Anatomy of the serotonergic system. Ann. N. Y. Acad. Sci. 600:9–35. Törk, I., and Hornung, J.-P. (1990) Raphe nuclei and the serotonergic system. In: Paxinos, G., edr. The Human Nervous System. San Diego: Academic Press, pp. 1001–1022.

33: ABNORMALITIES OF BRAIN STRUCTURE AND FUNCTION Turecki, G., Briere, R., Dewar, K., Antonetti, T., Lesage, A.D., Seguin, M., Chawky, N., Vanier, C., Alda, M., Joober, R., Benkelfat, C., and Rouleau, G.A. (1999) Prediction of level of serotonin 2A receptor binding by serotonin receptor 2A genetic variation in postmortem brain samples from subjects who did or did not commit suicide. Am. J. Psychiatry 156:1456–1458. Underwood, M.D., Khaibulina, A.A., Ellis, S.P., Moran, A., Rice, P.M., Mann, J.J., and Arango, V. (1999) Morphometry of the dorsal raphe nucleus serotonergic neurons in suicide victims. Biol. Psychiatry 46:473– 483. Underwood, M.D., Mann, J.J., and Arango, V. (2004) Serotonergic and noradrenergic neurobiology of alcoholic suicide. Alcohol Clin. Exp. Res. 28:57S–69S. Wilson, M.A., and Molliver, M.E. (1991) The organization of serotonergic projections to cerebral cortex in primates: retrograde transport studies. Neuroscience 44:555–570.

529

Wiste, A.K., Arango, V., Ellis, S.P., Mann, J.J., and Underwood, M.D. (2008) Norepinephrine and serotonin imbalance in the locus coeruleus in bipolar disorder. Bipolar Disord. 10:349–359. Yates, M., and Ferrier, I.N. (1990) 5-HT1A receptors in major depression. J. Psychopharmacol. 4:69–74. Yates, M., Leake, A., Candy, J.M., Fairbairn, A.F., McKeith, I.G., and Ferrier, I.N. (1990) 5HT2 receptor changes in major depression. Biol. Psychiatry 27:489– 496. Zhu, M.Y., Klimek, V., Dilley, G.E., Haycock, J.W., Stockmeier, C.A., Overholser, J.C., Meltzer, H.Y., and Ordway, G.A. (1999) Elevated levels of tyrosine hydroxylase in the locus coeruleus in major depression. Biol. Psychiatry 46:1275–1286. Zill, P., Buttner, A., Eisenmenger, W., Moller, H.J., Ackenheil, M., and Bondy, B. (2007) Analysis of tryptophan hydroxylase I and II mRNA expression in the human brain: A post-mortem study. J. Psychiat. Res. 41:168–173.

34 Novel Targets for Antidepressant Treatments OLIVIER BERTON

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Despite our still limited knowledge of the etiology and pathophysiology of depression, there are many effective treatments for depressive disorders. These are described in other chapters of this text (Nestler et al., 2002; Berton and Nestler, 2006). However, there is still substantial room for faster acting, safer, and more effective treatments (Agid et al., 2007). All currently available treatments must be administered for weeks or months to see maximum clinical benefits, and side effects are still a major problem, even with newer medications. Moreover, roughly one half of all patients with depression never show full remission with optimized treatment. From the point of view of market analysts, antidepressants have always been profitable, even though the market has consistently been one of the most crowded, since around 1960, when antidepressants were first commercialized. The successive generations of drugs that have emerged since the 1960s have been more “new” than “novel.” Virtually all such drugs are based on a version of the same mechanistic template: increasing the synaptic levels of monoamines (Wermuth, 2006). Tricyclic antidepressants are believed to act by inhibiting the plasma membrane transporters for serotonin and/or norepinephrine (NE), whereas monoamine oxidase inhibitors (MAOIs) reduce the enzymatic breakdown of serotonin, NE, or dopamine (DA) (depending on which MAO isoform—A or B—they target). The serotonin-selective reuptake inhibitors (SSRIs) and norepinephrine reuptake inhibitors (NRIs) developed since the 1980s work by selectively inhibiting the reuptake of their respective monoaminergic targets, whereas serotonin and norepinephrine reuptake inhibitors (SNRIs) and the triple reuptake inhibitors (TRIs) now in development purposely target multiple monoamine transporters (Shaw et al., 2007). Although there have been claims that TRIs may offer advantages in efficacy, such as addressing a broader array of symptoms, this remains highly speculative. Despite an impressive accumulation of knowledge about nonmonoamine systems that might contribute to the pathophysiology of depression (Manji et al., 2001; Duman and Monteggia, 2006), none of these relatively recent discoveries has yet been translated into a new 530

bona fide treatment for depression. There are several reasons. First, it is not known whether the preclinical screens (essentially behavioral models in rodents), which have been designed to accurately predict antidepressant action for monoamine-based drugs, efficiently detect antidepressants with different mechanisms. Indeed, there is so far no non-monoamine-based compound adequately validated in humans to be used as a reference drug in these animal models (Pacher and Kecskemeti, 2004; Agid et al., 2007). Second, antidepressant efficacy studies are extremely expensive (they involve chronic treatment of large numbers of patients) and notoriously risky (large placebo responses cause many trials to fail). This increases the threshold for a pharmaceutical or biotech company to embark on a trial of any antidepressant, especially one with a non-monoamine-based (and hence riskier) mechanism. Third, to increase their confidence level in a non-monoamine-based drug, many groups have looked for effects of such drugs on serotonin and NE systems. According to this view, if one can show that a non-monoamine-based drug enhances, for example, serotonergic neurotransmission, this would increase the cache of that drug. But this approach destines us to not develop drugs with truly novel mechanisms of action. Finally, profits from monoamine-based drugs are still extremely strong, and small alterations added upon existing scaffolds have been sufficient to keep them growing. However, most experts agree that antidepressant drug discovery is now at a crossroads. With the large majority of today’s monoaminergic-based drugs facing loss of patent around 2010, molecules with mechanisms truly distinct from the compounds available as generics may gain stronger appeal for the pharmaceutical industry. The $16 billion/year antidepressant market should provide a strong enough incentive for the industry to take the risks involved in developing drugs with non-monoaminebased actions. A search of the database maintained by the International Federation of Pharmaceutical Manufacturers and Associations (http://clinicaltrials.ifpma.org), which keeps a worldwide inventory of active clinical trials, indicates that in May 2007 approximately two thirds

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of the current phase 2 and 3 trials for depression are being conducted with non-monoamine-based drugs. This is an interesting trend, which suggests that the tide may be turning. Although some efforts to find better monoaminergic agents are still under way with some promising leads, these are addressed in other chapters of this text and are not discussed here. Rather, we focus on some of the best hopes for non-monoamine-based drugs for the treatment of depression. Given space limitations, this review is not comprehensive. We only highlight some examples of current nonmonoamine approaches to antidepressant drug discovery, with some additional, more preliminary examples given in Table 34.1.

TABLE

531

STRESS HORMONES AND NEUROPEPTIDES A prominent line of antidepressant targets comprises a variety of ligands for stress hormone and neuropeptide receptors. The physiological systems targeted with this approach are directly involved in the neuroendocrine and behavioral components of stress responses. The rationale for the development of such molecules, which often block acute stress responses, is the assumption that depression results from an overactivation of these stress systems. Although the characterization of these systems started in some cases more than 50 years ago, the first leads with therapeutic potential are just coming out of pharmaceutical pipelines. Results of the first

34.1 Example of Other Antidepressant Drug Discovery Strategies

Mechanism

Brief Summary of Evidence

k opioid antagonists

Stress causes a CREB-mediated induction of the opioid peptide dynorphin in the nucleus accumbens. Dynorphin induction in this region causes certain depression-like behaviors (e.g., anhedonia). Accordingly, administration of k antagonists, which block dynorphin action, either systemically or into the nucleus accumbens, have been shown to decrease depression-like behavior in rodents.

CB1 agonists or antagonists

Manipulation of the CB1 receptor, the major target for cannabinoids in brain, causes potent effects on anxiety and stress-related behaviors in rodents. This suggests that ligands for the CB1 receptor, or drugs that affect the production of endogenous ligands for the receptor, may be antidepressant. However, results to date are inconsistent, with agents that promote and attenuate CB1 activity reported to be beneficial in animal models.

Cytokines

Sickness behavior, which is mediated by proinflammatory cytokines (e.g., interleukins IL1 and IL6, tumor necrosis factor-a, or interferon-g), resembles symptoms of depression (e.g., anhedonia, reduced social interactions, and fatigue). Moreover, interferon-g, when used to treat hepatitis C, causes a high incidence of depression, and several cytokines are regulated in brain by stress and antidepressant treatments. This has raised the potential of exploiting cytokine-regulated pathways in the development of novel antidepressants.

HDAC inhibitors

Histone deacetylation by HDACs represses gene transcription. HDAC inhibitors reportedly promote synaptic plasticity and enhance memory, addiction, and other forms of behavioral adaptation. The potential utility of HDAC inhibitors in the treatment of mood disorders comes from the observations that: (1) valproic acid (an antimanic agent), among many other actions, is a weak HDAC inhibitor, (2) antidepressant treatments regulate histone acetylation in brain, and (3) imipramine selectively decreases levels of one form of HDAC (HDAC5) in hippocampus, and this effect is required for its antidepressant efficacy in a social defeat model of depression. The brain regions involved in these actions are not known with certainty. Histone and DNA methylation may also be involved in stress and antidepressant responses. Although clearly in very early stages of development, drugs that affect chromatin structure deserve further consideration in depression research.

Par-4

This protein, initially described in apoptotic prostate cancer cells, was recently identified as a partner, and an important endogenous modulator, of dopamine D2 receptor signal transduction. Genetic impairment of Par-4 mediated modulation of D2 function, at dopaminergic synapses in the striatum, results in a depression-like syndrome in mice.

p11

p11 (also named S100A10) interacts with the serotonin 5-HT1B receptor and increases localization of the receptor at the cell surface. p11 is increased in rodent brains by antidepressants or electroconvulsive seizures, and decreased in an animal model of depression and in brain tissue from depressed patients. Overexpression of p11 increases 5-HT1B receptor function in cells and recapitulates certain behaviors seen after antidepressant treatment in mice. p11 knockout mice exhibit a depression-like phenotype and have reduced responsiveness to 5-HT1B receptor agonists and to an antidepressant.

TREK-1

TREK-1 is a two-pore-domain K+ channel important in shaping the overall excitability of individual neurons. Its genetic disruption produces animals with an increased efficacy of 5-HT neurotransmission, reduced stress reactivity, and a resistance to depression in several behavioral models, suggesting that a blocker of this particular K+ channel may be a potential target for new antidepressants.

CREB: cyclic adenosine monophosphate (cAMP)-response element binding; NPY: neuropeptide Y; HDAC: histone deacetylase; DNA: deoxyribonucleic acid. See: Berton and Nestler (2006), Tsankova et al. (2007), Park et al. (2005), Svenningsson et al. (2006), and Heurteaux et al. (2006).

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phase 2 and 3 trials for some of the best neuropeptide and neuroendocrine targets are now available and should keep coming over the next several years. These results are highly anticipated. In addition to being among the best hopes for patients and clinicians, these trials also will constitute a test for the generally accepted theoretical framework in which mood disorder research is currently conducted. The Hypothalamic-Pituitary-Adrenal (HPA) Axis Glucocorticoid release is controlled by the hypothalamicpituitary-adrenal (HPA) axis, where corticotropin releasing factor (CRF) released by the paraventricular nucleus of the hypothalamus stimulates the release of adrenocorticotropic hormone (ACTH) from the anterior pituitary, which in turn stimulates glucocorticoid secretion from the adrenal cortex. The HPA axis is an essential component of an individual’s capacity to cope with stress. However, excessive stimulation of the axis has been implicated in depression. Hyperactivity of the HPA axis is observed in a majority of patients with depression, as manifested by increased expression of CRF in hypothalamus, increased levels of CRF in cerebrospinal fluid (CSF), and reduced feedback inhibition of the axis by CRF and glucocorticoids (Sapolsky, 2000; Pariante and Miller, 2001; Barden, 2004; de Kloet et al., 2005; Gillespie and Nemeroff, 2005; Korte et al., 2005). Although the molecular basis of these derangements in the HPA axis remains unknown, numerous clinical studies suggest that normalization of the axis may be a necessary step for stable remission of depressive symptoms. In animal models, hypercortisolemia can potentiate excitotoxicity of hippocampal pyramidal neurons, as evidenced by dendritic atrophy and spine loss, and possibly cell death, as well as inhibit the birth of new granule cell neurons in the hippocampal dendate gyrus, and many of these changes can be prevented by antidepressant treatment (Drew and Hen, 2007; Tanis et al., 2007). Excessive glucocorticoids could, therefore, be a causative factor for the small reductions in hippocampal volume seen in patients with depression or post-traumatic stress disorder, although this finding remains controversial (Manji et al., 2001). Besides its role in the HPA axis, CRF also serves as a neurotransmitter in several brain areas outside the hypothalamus, in particular, the central nucleus of the amygdala (Pare et al., 2004; Charmandari et al., 2005). These amygdala neurons send wide projections to forebrain and brain stem and have a crucial role in negative emotional memory (for example, as measured by fear conditioning), as well as in the generation of anxietylike behavior and in mediating negative emotional symptoms of drug withdrawal states (Heinrichs and Koob, 2004). Elevated levels of CRF have been found in some

of these target regions (for example, locus coeruleus) of patients with depression. This impressive literature has directed intense interest in the CRF and glucocorticoid systems as targets for the development of novel antidepressants. CRF antagonists Overexpression of CRF in transgenic mice, or CRF administration into the central nervous system (CNS), causes several depression-like symptoms, including hypercortisolemia, increased anxiety and arousal, decreased appetite and weight loss, and decreased sexual behavior (Bale and Vale, 2004; de Kloet et al., 2005; Keck et al., 2005; Keck, 2006). These symptoms are presumably induced via increased CRF function in the HPA axis and amygdala and related circuits. Physiological actions of CRF are mediated through two receptors, CRF1 and CRF2, both of which are coupled to the Gs subunit of G proteins—the subunit that can stimulate adenylyl cylcase to increase cyclic adenosine monophosphate (cAMP) synthesis. CRF1 receptors are the predominant subtype: they are enriched in pituitary where they regulate the HPA axis and are also highly expressed throughout limbic brain regions where their selective deletion attenuates behavioral responses to stress (Keck, 2006). These data have supported a massive effort to develop CRF1 antagonists as anxiolytic and antidepressant medications. Such compounds dramatically reduce anxietylike behavior and fear conditioning in rodents (Li et al., 2005; Kehne, 2007) and also antagonize a range of depression-like symptoms seen during withdrawal from several drugs of abuse (Heinrichs and Koob, 2004). On the other hand, CRF1 antagonists have not demonstrated consistent activity in standard antidepressant screens (Kehne, 2007). Open-label clinical trials found that a nonpeptidic CRF1 antagonist is effective in reducing psychosocial stress and depressive symptoms and in improving sleep in patients suffering from major depression (Ising et al., 2007). No serious side effects and no significant disruption of endocrine systems, including the HPA axis, thyroid hormone, gonadal steriods, prolactin, and vasopressin, were found. However, no well controlled study has yet verified these findings. Unfortunately, pharmacokinetic and hepatoxicity issues have led to the discontinuation of numerous CRF1 antagonists, an all-too-common occurrence for drugs aimed at neuropeptide receptors. The failure to obtain clear proof of concept of the CRF1 antagonist mechanism as anxiolytic or antidepressant in humans, despite decades of research, is a major disappointment and frustration for the field. CRF2 receptors show more restricted expression in brain, and their role in regulating complex behavior is still under investigation (Hillhouse and Grammatopoulos,

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2006; Fekete and Zorrilla, 2007). CRF2 knockout mice show normal anxiety-like behavior, but CRF2 antagonists show anxiolytic properties in animal models, and some, but not all, show significant efficacy in the learned helplessness and chronic mild stress depression paradigms as well (Bale and Vale, 2004). Recent results indicate that the endogenous ligands for CRF2 receptors, in addition to CRF, may be the urocortin peptides, which promote adaptive responses to stress (Hillhouse and Grammatopoulos, 2006; Fekete and Zorrilla, 2007). There remains considerable interest in the clinical development of CRF2 antagonists, particularly because they are less likely than CRF1 antagonists to cause side effects via the HPA axis. Vasopressin antagonists The neuropeptide vasopressin, synthesized in the paraventricular and supraoptic hypothalamic nuclei, is well known for its role in fluid metabolism. It also regulates the HPA axis: stress stimulates the release of vasopressin that then potentiates the effects of CRF on ACTH release. Vasopressin is found outside the hypothalamus as well, notably in the amygdala and bed nucleus of the stria terminalis, and is believed to exert effects throughout the limbic system via activation of V1a and V1b receptors. Vasopressin levels are reportedly increased in some patients with depression (Bao et al., 2007). Nonpeptide V1b antagonists exhibit antidepressant-like effects in rodents partly via amygdala-dependent mechanisms (Keck et al., 2003). This is in contrast to V1b knockout mice, which display normal stress responses (Lolait et al., 2007). Vasopressin antagonists have yet to be evaluated in humans. Glucocorticoids: agonists or antagonists? Glucocorticoids diffuse passively through cellular membranes and bind to intracellular glucocorticoid receptors (GR) causing their translocation into the nucleus. Within the nucleus, these ligand-activated transcription factors bind to specific DNA response elements, or to other transcription factors, and alter gene expression. In the brain, glucocorticoid-regulated genes affect many aspects of neuronal function, including metabolism, structure, and synaptic transmission. Glucocorticoids also promote the termination of stress reactions through complex feedback loops, in part mediated through the hippocampus, ultimately leading to the repression of target genes implicated in stress responses, such as CRF (Hillhouse and Grammatopoulos, 2006). As mentioned earlier, insufficient feedback suppression of the HPA axis by CRF and glucocorticoids is seen in a large subset of patients with depression (de Kloet et al., 2005). This neuroendocrine abnormality was repro-

533

duced recently in adult mice with selective deletion of GR in forebrain (Boyle et al., 2004; Boyle et al., 2005). Interestingly, this mutation also resulted in a robust depression-like phenotype normalized after chronic treatment with tricyclic antidepressants. Conversely, transgenic mice overexpressing GR in the forebrain are more sensitive to the acute effects of antidepressants (Wei et al., 2004). These findings raise the possibility that enhanced GR activity in the forebrain might be antidepressant. Most antidepressant treatments can restore efficient negative feedback of the HPA axis and increase the expression of GR in forebrain regions such as the hippocampus (de Kloet et al., 2005). Some patients with depression carry a polymorphism in the FKBP5 gene (which encodes a cochaperone of heat shock protein 90) that results in higher affinity of GR for cortisol (Binder et al., 2004; Gillespie and Nemeroff, 2005). These individuals reportedly respond much faster to antidepressants than a group without this mutation. These findings are paradoxical, given the evidence, cited above, that hypercortisolemia may contribute to the pathophysiology of depression, but the two sets of results could be reconciled in the following way. Deficient inhibitory feedback of the HPA axis might result from excessive activation of GR in the hippocampus and subsequent damage to this region (Sapolsky, 2000; Korte et al., 2005). Recently, viral vectors have been used to deliver chimeric GR receptors into the hippocampus that combined the ligand-binding domain of GR with the DNA-binding domain of estrogen receptors, thereby converting the glucocorticoid signal into an estrogenlike effect (Kaufer et al., 2004; Akama and McEwen, 2005). The expression of the chimeric receptor potently reduced hippocampal damage and rendered excess glucocorticoids protective rather than destructive. The behavioral effects of such genetically altered GR receptors have not yet been reported in animal models of depression. In the clinic, preliminary evidence indicates that some symptoms of psychotic depression might be rapidly ameliorated by GR antagonists (Flores et al., 2006). The GR antagonist mifepristone, which is also a progesterone receptor antagonist and approved as a “morning after” pill, is currently in phase 3 clinical trials for psychotic major depression. In March 2007, the results of the third phase 3 trial (443 patients randomized, double-blind, placebo-controlled study) were communicated by Corcept Therapeutics. Although the effect of the treatment did not achieve overall statistical significance, the company reported a statistically significant correlation between plasma drug levels and clinical outcome achieved during treatment. At higher plasma levels, patients did respond to the treatment when compared to placebo. This result confirmed a similar finding obtained in a previous phase 3 trial completed in 2006,

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suggesting that the drug can produce desired clinical effects within a week when dosages are tailored to achieve an optimal plasma level. A point to emphasize here is that the primary endpoint set in the study was a 50% improvement in the severity of positive symptoms, which are the psychotic rather than the depressive features of the disease. Several other large multicenter trials are currently under way and will confirm whether the medication is useful for the treatment of psychotic depression. Galanin The discovery of the neuropeptide galanin was first reported in the early 1980s after its extraction from the intestine. Galanin has attracted interest in the field in view of its anatomical distribution and the physiological functions it mediates (Lu, Mazarati, et al., 2005; Karlsson and Holmes, 2006; Ogren et al., 2006; Lu et al., 2007). Despite a wide distribution in rodent brain, the neuropeptide has a particularly high level of expression in the brain stem, where it is strongly colocalized with NE and serotonin. Galanin acts through three G protein–coupled receptors, Gal1, Gal2, and Gal3, which are also enriched in brain regions containing monoaminergic cell bodies and terminals (Hawes and Picciotto, 2004; Lu, Mazarati, et al., 2005). The Gal1 and Gal3 receptors are coupled to Gi and exert an inhibitory influence on cell excitability and adenylyl cyclase, whereas Gal2 receptors are Gq coupled and lead to the activation of phospholipase C (PLC) (Lu, Lundstrom, et al., 2005). Upon intracerebroventricular (ICV) administration, galanin exerts potent neurobehavioral effects, including modulation of seizure activity, pain-processing, feeding, sexual behavior, fear-related behaviors, and cognitive functions. The contribution of each receptor subtype to this complex profile remains unclear, due to the unavailability, until recently, of selective galanin receptor ligands (Holmes and Picciotto, 2006). In depression models, synthetic galanin receptor agonists, galnon and galmic (which act on Gal1 and Gal2), were found to reduce immobility time in the rat Forced Swim Test (FST) when given systemically, indicating an antidepressant-like effect, likely mediated through Gal2 receptor. Galanin transcripts were found to increase almost twofold in the dorsal raphé and locus coeruleus after subchronic fluoxetine treatment, whereas Galanin (2-11) binding (which reflects primarily Gal2 binding capacity) also showed a 50% increase in dorsal raphé (Yoshitake et al., 2003; Lu, Barr, et al., 2005). Interestingly, M40, a peptidic nonselective Gal1/ Gal2 receptor antagonist, has been shown to attenuate the antidepressant-like effects of fluoxetine in the FST. Together, these results suggest that acute galanin signaling through Gal2 receptors may mediate an antidepressant-like response and may provide one mechanism through which fluoxetine acts in rodent models. These

results are reinforced by a recent clinical study, which demonstrated a potent antidepressant effect of galanin upon acute intravenous administration in patients with depression (Murck et al., 2004). In 2005, the characterization of the first nonpeptide antagonists for the Gal3 receptor (SNAP37889 and SNAP398299) was published by Lundbeck (Swanson et al., 2005). This report demonstrated potent anxiolyticand antidepressant-like properties of Gal3 antagonists in several social behavior–based models in rats and guinea pigs, as well as more classical tests such as the forced swimming and stress induced-hyperthermia in mice. Interestingly, like with Gal2 receptor agonist, these antidepressant-like effects were observed after acute administration of the drug and did not desensitize after chronic administration. Electrophysiological and microdialysis studies indicate that these anxiolytic- and antidepressant-like effects of Gal3 antagonists could possibly result from an attenuation of the inhibitory influence of galanin, released during stress, on serotonergic transmission at the level of the dorsal raphé. Another interesting property of galanin is its action as a trophic factor during development and in adult brain after injury. Galanin and galanin receptor expression have been identified in the proliferative zones of adult and postnatal brain. In cultured neurospheres, galanin decreases cell proliferation, an effect blocked by the nonselective antagonist M35. Nevertheless, much further work is needed to validate galanin-based drugs as effective agents in humans. Neurokinins The neuropeptides known as neurokinins were discovered over 70 years ago, but compounds that antagonize their action at specific receptors were only developed during the past decade. They are products of two genes that code for substance P (SP), the most abundant in the CNS, neurokinin A, and neurokinin B. Three subtypes of neurokinin receptors have been identified and designated as NK1, NK2, and NK3. Substance P is the preferred endogenous agonist for NK1 receptors, which are coupled to Gq and stimulate phospholipase C, whereas neurokinin A exhibits the highest affinity for the NK2 receptor and neurokinin B for the NK3 receptor (Pennefather et al., 2004). Substance P has been studied primarily for its role as a central mediator of pain, an indication for which nonpeptidic NK1 antagonists were initially developed. The rationale for considering NK1 antagonists in depression was based on the expression of SP and NK1 receptors in fear- and anxiety-related circuits, the release of SP in animals in response to fearful stimuli, and the strong colocalization of SP with serotonin and NE or their receptors in human brain. Reciprocally, local application of SP agonists was shown to induce a range

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of neural, behavioral, and cardiovascular changes characteristic of defensive responses, including increased firing of the locus coeruleus, place aversion, distress vocalizations, escape behavior, and cardiovascular activation. Moreover, some effects of stress can be blocked by systemic administration of NK1 receptor antagonists. These effects have since been confirmed by the anxiolytic- and antidepressant-like phenotype of SP and NK1 receptor knockout mice (Rupniak et al., 2001). Kramer et al. published in 1998 the first evidence that chronic treatment with a nonpeptidic NK1 receptor antagonist might be antidepressant in humans. This report was greeted with great enthusiasm, but it has been difficult to replicate its findings, such that the validity of NK1 antagonism as an effective antidepressant strategy is now questioned (Chahl, 2006). Indeed, several pharmaceutical companies have discontinued their NK1 antagonist programs in yet another major disappointment for the field. Although NK1 antagonists were initially claimed to act through a completely novel mechanism of action, subsequent studies have suggested that their therapeutic action, if any, could be secondary to changes in monoaminergic systems. NK1 antagonists have a delayed onset of action similar to monoamine-based antidepressants, and their chronic administration causes increased firing of serotonergic neurons—a change also observed in NK1 knockout mice (Blier et al., 2004). In addition, genetic or pharmacological blockade of NK1 receptors induces some of the same long-term effects in the brain as bona fide antidepressants on cell signaling proteins, such as brain-derived neurotrophic factor (BDNF), and hippocampal neurogenesis (Musazzi et al., 2005). These results raise the possibility that NK1 antagonists could conceivably be used as augmentation agents in combination with a traditional antidepressant. Following the lack of success of NK1 receptor antagonists, some companies have shifted their focus toward antagonists at other NK receptors. There are indications from preclinical studies that NK2 antagonists may have more consistent anxiolytic and antidepressant effects than NK1 antagonists. For example, saredutant (SR48968) is an NK2 antagonist currently in phase 3 clinical trials. Saredutant is also being tested for the treatment of generalized anxiety disorder. Hypothalamic Feeding Peptides There have been explosive advances over the past decade in understanding hypothalamic peptides that regulate feeding behavior. Recent work has begun to draw connections between these hypothalamic feeding peptides and depression (Nestler and Carlezon, 2006). Of particular note is melanin-concentrating hormone (MCH), a major orexigenic (proappetite) peptide expressed in a subset of lateral hypothalamic neurons. The MCH1

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receptor, the only subtype expressed in rodents, is coupled to Gi and shows remarkable enrichment in the nucleus accumbens. Direct administration of MCH into this region stimulates feeding behavior, whereas blockade of the MCH1 receptor decreases feeding (Georgescu et al., 2005). Intracerebroventricular or intrahypothalamic MCH administration has similar effects. Moreover, several MCH1 receptor antagonists, including nonpeptidic small molecule antagonists, administered systemically or directly into the nucleus accumbens, exert antidepressantlike effects in the FST (Shimazaki et al., 2006). A similar antidepressant-like phenotype is observed in mice lacking MCH or the MCH1 receptor, while a prodepressantlike phenotype is seen in MCH-overexpressing animals. Taken together, these data provide a strong case that MCH antagonists, by disrupting MCH signaling to the nucleus accumbens, might provide a highly novel mechanism for antidepressant medications. These drugs would also reduce weight, which could be particularly useful in the subset of patients with depression who show weight gain. Evaluating these agents in humans is now the major obstacle. Several other hypothalamic feeding peptides have also attracted attention in the depression field. These include anorexigenic peptides, such as melanocortin (aMSH) and cocaine- and amphetamine-regulated transcript (CART), and orexigenic peptides, such as orexin (hypocretin), agouti-related peptide (ARP), and neuropeptide Y (NPY). Many of these peptides have been shown to not only regulate feeding, but to also alter reward mechanisms, which suggests possible effects on anhedoniarelated symptoms (Nestler and Carlezon, 2006). This is the case of NPY, which has attracted particular attention as a possible antidepressant target, because of its pattern of expression and regulation, well beyond the hypothalamus, in limbic brain circuits (Karl and Herzog, 2007). The role of NPY in the regulation of stress responses has been widely investigated in human and animal investigations. Several studies have demonstrated down-regulation of NPY levels in CSF, plasma, and prefrontal cortex (PFC) of patients with depression and victims of suicide. Similar alterations of NPY gene expression and peptide content have been reported in animal models of depression, including stress-induced anhedonia and the learned helplessness. Several lines of evidence suggest that stimulation of NPY neurotransmission may bear antidepressant properties. In rodents, central administration of NPY has been shown to elicit dose-dependent anxiolytic and antidepressant-like effects in several animal models, including the FST, in rats and mice. Up to now, two of the six NPY receptors (Y1–Y6) have received significant attention as possible mediators of NPY antidepressant-like activity. The Y1 receptor is mainly located postsynaptically and is enriched in the cerebral cortex and hippocampus. Intracerebroventricular administration of the Y1 selective

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peptidic agonist [Leu31;Pro34]PYY reduced the immobility time of rats in the FST. More recently, selective Y1 nonpeptidic antagonists, BIBP3226 and BIBO3304, were shown to block the effect of NPY (Ishida et al., 2007). Due to their function as inhibitory presynaptic autoand hetero-receptors in human and rat CNS, NPY Y2 receptors are also interesting targets (Tschenett et al., 2003). Deletion or blockade of these receptors results in enhanced release of NPY, as well as other transmitters such as g-aminobutyric acid (GABA) and dopamine (DA). Y2 receptor knockout mice display an anxiolytic- and antidepressant-like phenotype. A similar profile was observed after administration of the potent and selective Y2 receptor antagonist BIIE0246 (Bacchi et al., 2006). Several clinical trials of NPY-based compounds are being conducted for obesity, but to our knowledge no clinical study of the aforementioned compounds has yet been carried out for depression. NEUROTROPHIC FACTORS AND RELATED TRANSDUCTION PATHWAYS A host of fundamentally new targets has emerged as a result of open-ended molecular and cellular approaches. In some cases, these targets were previously studied for their role in seemingly unrelated biological functions. In most cases, their role in normal brain function and in the pathophysiology of depression is not currently understood. However, these molecules appear as effective as monoaminergic reference compounds in several animal models. BDNF and TrkB signaling The neurotrophic hypothesis of depression and antidepressant action was based originally on findings in rodents that acute or chronic stress decreases expression of BDNF in hippocampus and that diverse classes of antidepressant treatments produce the opposite effect and prevent the actions of stress (R.S. Duman and Monteggia, 2006). These observations led to the suggestion (still unproven) that perhaps such changes in BDNF could in part mediate the structural damage and reduced neurogenesis seen in hippocampus after stress and the prevention of these effects by antidepressant treatments (see above). Importantly, reduced BDNF levels in the hippocampus have been reported in some patients with depression on autopsy, an abnormality not seen in those patients treated with antidepressants. Up-regulation of hippocampal BDNF expression by numerous types of pharmacological and nonpharmacological clinically effective antidepressant interventions is now a highly replicated result (Conti et al., 2007). Together, these data support the possibility that drugs that activate BDNF signaling in hippocampus might

be antidepressant. Direct evidence for this hypothesis comes from experiments where injection of BDNF into the rodent hippocampus exerts antidepressant-like effects in the FST and learned helplessness test (Shirayama et al., 2002; Tanis et al., 2007). Conversely, inducible knockout of BDNF from the hippocampus and other forebrain regions prevents the antidepressant effects of drugs that activate BDNF (Monteggia et al., 2004). Although a great deal of work remains to validate this hypothesis, the main challenge from a drug discovery point of view is that BDNF is not an easy drug target. A range of compounds have been designed to modulate BDNF signaling through various mechanisms, such as direct or indirect tyrosine kinase receptor (TrkB) receptor agonists and neurotrophin potentiators or releasers. Several clinical trials have failed, due to problems in delivery and unforeseen severe side effects of neurotrophic factors. Nevertheless, a small subset of the compounds, acting on intracellular signaling pathways downstream of TrkB receptors, shows promise. Indeed, BDNF activation of TrkB leads to diverse physiological effects by regulating a complex cascade of postreceptor pathways, which involve PI3K-Akt, PLCg, and Ras-Raf-Erk, each of which represents a putative drug target. Inhibition of extracellular signal regulated kinases (ERK) has, for example, been shown to block the activity of antidepressants in animal models (C.H. Duman et al., 2007). This raises the possibility that drugs that stimulate ERK signaling, such as inhibitors of dualspecificity phosphatases (enzymes that dephosphorylate and inactivate ERK), may be used to potentiate antidepressant activity (Tanis et al., 2007). Activation of TrkB receptors can also be induced by ligands at G protein– coupled receptors in the absence of neurotrophins. Adenosine and pituitary adenylyl cyclase-activating peptide (PACAP), for example, have been shown to induce Trk activation through their respective G protein–coupled receptors and the subsequent activation of Src family kinases to promote cell survival. Transactivation of Trks by G protein–coupled receptors is emerging as a new strategy to transactivate trophic activities and could potentially reveal novel drug targets (Jeanneteau and Chao, 2006). In theory, numerous other proteins might be targeted for antidepressant development; however, several obstacles remain: first, we do not yet know which of these pathways are most crucial for the antidepressant actions of BDNF in animal models; second, most of these signaling proteins are broadly expressed throughout the brain and peripheral tissues, which heightens concerns about toxicity of any drug directed against them; and third, the lack of availability of small molecule agonists for most of these signaling proteins means that their potential antidepressant activity cannot easily be assessed. Another complication is that, although BDNF might exert antidepressant-like effects at the level of the hippo-

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campus, its actions might be different, or even the opposite, in other neural circuits. The best example is the ventral tegmental area-nucleus accumbens reward circuit, in which chronic stress increases BDNF expression, local BDNF infusion exerts a pro-depression-like effect in the FST, and blockade of BDNF function exerts an antidepressant-like effect (Eisch et al., 2003). A more recent study found a similar antidepressant-like effect upon viral-mediated local knockout of BDNF from the ventral tegmental area in a social defeat paradigm (Berton et al., 2006). These findings raise caution about the goal of developing an antidepressant based on BDNF because a drug that promotes BDNF function might produce competing effects in different brain regions. In addition to BDNF, other neurotrophic factors warrant consideration as potential leads for antidepressant development. A recent DNA microarray study of the human hippocampus found that several genes in the fibroblast growth factor (FGF) family—FGF and some of its receptors—are down-regulated in the hippocampus of patients with depression (Turner et al., 2006). This is interesting in light of the knowledge that FGF seems to be an important endogenous regulator of neurogenesis in the adult rat hippocampus. Another candidate of interest is vascular endothelial growth factor (VEGF), which was initially characterized for its role in angiogenesis but also exerts direct mitogenic effects on neural progenitors in vitro. Results from a recent study demonstrate that VEGF is induced by multiple classes of antidepressants at time points consistent with the induction of cell proliferation and therapeutic action of these treatments. Vascular endothelial growth factor signaling through the Flk-1 receptor seems to be required for antidepressant-induced cell proliferation and behavioral responses to chronic antidepressants (WarnerSchmidt and Duman, 2007). Still other neurotrophic factors are known to be regulated in the hippocampus by stress and antidepressant treatments, which are currently being evaluated in depression models (Tanis et al., 2007). Although studies of neurotrophic mechanisms in depression and antidepressant action have provided important heuristic models for the field, it may be difficult to translate these discoveries into new treatment approaches for depression due to the complex biology of these systems. PHOSPHODIESTERASE INHIBITORS Phosphodiesterases (PDEs) catalyze the degradation of cAMP and cyclic guanosine monophosphate (cGMP). The potential antidepressant activity of PDE inhibitors dates back decades to the notion that these drugs would be expected to promote the actions of NE at b adrenergic receptors, which were hypothesized at the time to partly mediate antidepressant responses. Indeed,

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there were early indications that rolipram, a nonselective PDE4 inhibitor, might be antidepressant in small clinical trials (see R.S. Duman et al., 1997; R.S. Duman, 2004). These early trials failed because of intense nausea and vomiting induced by rolipram and related PDE4 inhibitors. Renewed interest in PDE4 inhibitors as antidepressants has come from the findings that they induce BDNF expression in hippocampus. This effect might be mediated by activation of the cAMP pathway, which leads to the activation of the transcription factor cAMP-response element (CRE) binding protein (CREB) and to the direct induction of the BDNF gene via a CRE site in its promoter. Induction of CREB itself in the hippocampus exerts an antidepressant-like effect in the FST (R.S. Duman, 2004). Thus, PDE4 inhibitors might provide an indirect way to promote CREB and BDNF function and exert an antidepressant effect. Meanwhile, there is intense interest in PDE4 inhibitors as cognitive enhancers, a possibility that is also based on the role of CREB in the hippocampus in mediating important forms of learning and memory. The major challenge, however, remains side effects: is it possible to inhibit PDE4 in the hippocampus and exert antidepressant and cognitive enhancing effects without inhibiting PDE4 in brain-stem regions which causes nausea and vomiting? A second major challenge is that inhibition of PDE isoforms might not be antidepressant or cognitive enhancing in all brain regions. There is growing evidence that stimulation of the cAMP pathway and CREB in nucleus accumbens is prodepressant. Thus, mechanisms to oppose, rather than to enhance, activity of this pathway might be more suitable for antidepressant drug discovery efforts (Carlezon et al., 2005). Similarly, stimulation of the cAMP pathway in frontal cortical regions can inhibit cognitive function in aged animals, which again highlights potential problems of targeting PDE isoforms that are widely expressed in the brain. On the positive side, there are four subtypes of PDE4, PDE4A through PDE4D, each encoded by a different gene, with multiple splice variants of each subtype. It is conceivable that a particular subtype enriched in hippocampus could be targeted for antidepressant and cognition-enhancing effects, although this remains conjectural. In addition, there are many other PDE isoforms, some of which show highly restricted patterns of expression in the brain. For example, PDE10A is highly enriched in the striatum. It, too, could potentially be targeted for antidepressant development. A recent study pointed to the PDE4B isoform as a choice candidate by showing that mutation in DISC1 (disrupted in schizophrenia 1), a specific binding partner of PDE4B, results in lower PDE4B activity, a depressive phenotype in mice, and a selective resistance to the antidepressant effect of rolipram (Clapcote et al., 2007). Moreover, there are many other families of signaling proteins that modulate G protein-adenylyl cyclase ac-

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tivity, such as regulators of G protein signaling (RGS) proteins, subtypes of which show restricted expression patterns in the brain. These proteins too represent potential drug targets. GLUTAMATE ACTING DRUGS The link between glutamatergic neurotransmission and the pathophysiology of depression has been increasingly demonstrated since the 1950s, when the moodelevating properties of anti-infectious agents with some N-methyl-D-aspartate (NMDA) glutamate receptor antagonist activity (for example, D-cycloserine and amantadine) were first reported (Paul and Skolnick, 2003; Sanacora et al., 2003). A rapid and sustained antidepressant effect of a single IV bolus of ketamine, a dissociative anesthetic and NMDA receptor antagonist, was subsequently demonstrated in a placebo-controlled trial (Zarate, Singh, Carlson, et al., 2006). The application of ketamine and related drugs as antidepressants is obviously limited by their severe psychotomimetic effects. However, recent clinical trials have been assessing the antidepressant potential of the weaker NMDA antagonist memantine and the glutamate release inhibitor, riluzole, both of which have been approved by the U.S. Federal Drug Administration (FDA) for cognitive enhancement and neuroprotection, respectively. Although memantine proved devoid of antidepressant activity in a double-blind, placebo-controlled study (Zarate, Singh, Quiroz, et al., 2006), recent work suggests the efficacy of riluzole as an augmentation strategy for treatmentresistant depression (Sanacora et al., 2007). Although clinical evidence that supports the antidepressant efficacy of NMDA antagonists is still relatively weak, preclinical research increasingly suggests that reduced NMDA receptor function is antidepressant-like in several animal models and prevents stress-induced alterations in hippocampal neuronal morphology, and that chronic treatment with bona fide antidepressants down-regulates NMDA receptors or reduces glutamate release via presynaptic mechanisms (Pittenger et al., 2007). In parallel, it has been reported that activation of a-amino-3-hydroxy-5-methyl-4-isoxasolepropionic acid (AMPA) glutamate receptors increases BDNF expression and rapidly stimulates neurogenesis and neuronal sprouting, in the hippocampus. Based on these observations, AMPA receptor potentiators have been evaluated in models of depression (Bleakman et al., 2007). Positive allosteric modulators, which avoid the rapid desensitization of AMPA receptors seen with full agonists, were reported to have similar activity as tricyclic and SSRI antidepressants in the FST and tail suspension test. Interestingly, AMPA receptor potentiators were also active in reducing rat submissive behavior

(a behavioral model that responds selectively to chronic antidepressant treatment) with a shorter onset of action than an SSRI. There are also some indications that monoamine-based antidepressants promote AMPA receptor function. Given the dominant role of ionotropic glutamate receptors in synaptic activity and plasticity throughout the brain, including cognition-, emotion-, and reward-related circuits, it is not surprising that agents that affect these receptors could exert antidepressant activity. It remains to be seen whether such drugs could have the selectivity and safety required. One proposed strategy would be to target any of several metabotropic (or G protein–coupled) glutamate receptors, which seem to differentially modulate the activity of the ionotropic receptors and might thereby mediate safer and more selective effects. mGlu receptors indeed modulate glutamatergic neuronal excitation and plasticity via presynaptic, postsynaptic, and glial mechanisms. In particular, compounds that antagonize mGluR2, mGluR3, and/or mGluR5 receptors have shown antidepressantlike activity in rodent models (Witkin et al., 2007). CIRCADIAN GENE PRODUCTS Several observations link mood disorders and circadian rhythms. Prominent alterations of circadian rhythms have long been described in depression and other mood disorders (see McClung, 2007). Many patients with depression report their most serious symptoms in the morning with some improvement as the day progresses. This might represent an exaggeration of diurnal fluctuations in mood, motivation, energy level, and responses to rewarding stimuli that are seen commonly in the healthy population. The molecular basis for these rhythms seen under normal and pathological conditions is poorly understood. Most of the treatments that are currently employed to treat mood disorders are known to alter the circadian clock. This is obviously the case of total sleep deprivation (TSD) and bright light therapy, but there are data supporting the idea that many chemical mood stabilizers and antidepressants also derive at least some of their therapeutic efficacy by affecting the circadian clock. For example, the mood stabilizers lithium and valproate have been shown to alter the circadian period, leading to a longer period in Drosophila, rodents, nonhuman primates, and humans. This effect on circadian rhythms could involve the inhibition of glycogen synthase kinase 3 b (GSK3b ) that modifies multiple members of the molecular clock. It is proposed that this action of lithium on the circadian clock is important in its therapeutic efficacy. Similarly, the antidepressant fluoxetine also affects circadian output by producing a phase advance in the firing of suprachiasmatic nucleus (SCN) neurons.

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The biology that underlies the association between circadian rhythms and mood disorders is still unknown but may come from the influence of the molecular clock on certain neurotransmitters and their receptors. Indeed, some of the neurotransmitters that have been implicated in mood regulation, including serotonin, NE, and dopamine, have a circadian rhythm in their levels, release, and synthesis-related enzymes or in the expression and activity of several of their receptors. How these circuits are controlled in a circadian fashion is still uncertain, but molecular mechanisms are starting to be unraveled. Most research on circadian rhythms has focused on the SCN of the hypothalamus, which is considered the master circadian pacemaker of the brain (Reppert and Weaver, 2002; Takahashi, 2004). Here, circadian rhythms are generated at the molecular level by Clock (a Pas domain containing transcription factor), which dimerizes with Bmal; and the dimer induces the expression of Per (Period) and Cry (Cryptochrome) genes, which in turn feedback to repress Clock-Bmal activity. In addition, Clock-Bmal, Per, and Cry regulate the expression of many other genes, which presumably drive the many circadian variations in cell function. This molecular cycle in the SCN is entrained by light and appears to be essential for matching circadian rhythms with the light–dark cycle. More recent research, however, has indicated that control of circadian rhythms is far more complicated than this simple model. Clock, Bmal, Per, and Cry genes, as well as several related genes, are expressed broadly throughout the brain, including limbic regions implicated in mood regulation, although little is known about their function outside the SCN. Behavioral studies aimed at investigating the role of individual circadian genes in mood regulation are just beginning. Interestingly, transgenic mice overexpressing the circadian modulator, GSK3b, are hyperactive and have reduced immobility in the FST, indicative of less depression-like behavior, and an increased startle response (Prickaerts et al., 2006). A similar manic- or antidepressant-like-phenotype has also been observed in mice lacking functional Clock protein (King et al., 1997). Their behavioral phenotype includes an antidepressant-like profile in the FST and learned helplessness test, and reduced anxiety or increased risk-taking behavior in several assays. These mice also display an increase in the rewarding effects of cocaine, sucrose, and intracranial self-stimulation (Roybal et al., 2007). Interestingly, in vivo recordings have demonstrated increased in vivo firing of dopaminergic neurons in the ventral tegmental area of the Clock mutant mice. These neurons express Clock, which regulates several genes that are important in dopaminergic transmission (McClung et al., 2005). A major influence of the Clock gene in the ventral tegmental area on emotional behavior is further emphasized by the partial rescue of

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the manic-like phenotype in Clock mutant mice upon overexpression of Clock protein selectively in this brain region (Roybal et al., 2007). Interestingly, antidepressant treatments also increase Clock expression in hippocampus (Uz et al., 2005; Manev and Uz, 2006). Additional behavioral studies with mice lacking other circadian genes are ongoing. There has been interest in a Clock-like protein, termed neuronal Pas domain protein-2 (NPAS2), which dimerizes with Bmal to regulate the circadian expression of Per, Cry, and many other genes (Garcia et al., 2000). Interestingly, NPAS2 is not expressed in the SCN but is found at high levels in several limbic regions, particularly the nucleus accumbens. NPAS2 knockout mice show deficits in the ability to entrain to nonlight stimuli, such as food. It has been suggested that NPAS2 is a crucial mediator of circadian rhythms in an individual’s emotional state via actions in nucleus accumbens and other limbic regions. Taken together, these early studies support the hypothesis that circadian genes may function abnormally in depression and other mood disorders. This work also suggests that drugs aimed at influencing particular target genes for these circadian transcription factors, which are expressed within distinct brain circuits, deserve attention as targets for possible new treatment agents for depression. Melatonin, the main secretory product of the pineal gland, which contributes to circadian rhythm synchronization, has also triggered significant interest as a possible antidepressant target. Because initial attempts to demonstrate antidepressant activity of melatonin were unsuccessful, the hypothesis was tested that melatonin receptor agonists could improve psychomotor tone in patients with depression. This was confirmed with agomelatine, an agonist of the MT1 and MT2 melatonin receptors; the drug is also an antagonist at the serotonin 5-HT2C receptor (Bourin et al., 2004). The compound has proven to be highly effective in animal models of depression, including induction of hippocampal neurogenesis, and reported to have significant activity in human depression trials (den Boer et al., 2006). Agomelatine also seems to produce fewer adverse side effects than some other antidepressant medications, and it alleviates many of the sleep problems associated with depression that can be exacerbated by SSRI treatment, making it a potentially valuable new treatment for depression (Fuchs et al., 2006). As expected by its pharmacologic profile, agomelatine has been shown to resynchronize circadian rhythms in body temperature, cortisol, and other hormones in animal models and in humans, which may underlie some of its therapeutic effects. On the other hand, there have been negative trials of agomelatine in depression such that its efficacy will require further investigation. The contribution of 5-HT2C antagonism to agomelatine’s actions remains unknown.

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FUTURE DIRECTIONS

REFERENCES

Antidepressant drug discovery is at a crossroads. Available medications with monoamine-based mechanisms will be going off patent in the next decade, while proof of concept studies for some of the best neuropeptide and neuroendocrine targets (for example, CRF, SP, and glucocorticoid receptors), which are based largely on stress models, should at long last be available within the next few years. At the same time, a host of fundamentally new targets has emerged as a result of more open-ended molecular and cellular approaches in concert with improving, albeit still imperfect, animal models of stress. Progress with some of these targets (for example, BDNF) has been hampered by the difficult chemistry involved. Nevertheless, this research has suggested numerous biomarkers or endophenotypes for depression, for example, BDNF expression, hippocampal neurogenesis, neuronal morphology, CREB activity, to name just a few, but all of these remain inaccessible in living patients. A major leap forward in the field will require identification of genes that confer risk for depression in humans, and understanding how specific types of environmental factors interact synergistically with that genetic vulnerability. This will make it possible to develop more valid animal models of human depression. Important advances will also require the development of ever more penetrating brain imaging methodologies to enable the detection of molecular and cellular biomarkers in living patients. Such discoveries should make it possible at long last to delineate bona fide subtypes of depression, which will likely show distinct etiological and pathophysiological mechanisms. Ultimately, translation of these discoveries into improved treatments, with fundamentally novel mechanisms of action, may require such advances, so that a particular treatment can be matched to a particular genotype or endophenotype. More invasive treatments may also become feasible for individuals who are severely ill, including deep brain stimulation or even viral-mediated gene transfer, to correct abnormalities observed in particular patients. Of course, all this remains a promissory note. Given past failures to develop non-monoamine-based antidepressants, it is possible that there is something unique about prolonged enhancement of serotonergic or noradrenergic function that causes palliative improvement in a wide range of stress-related disorders including depression and many other conditions. But we reject this nihilistic view based on the extraordinary advances in neurobiology and molecular therapeutics, which make it difficult for us to fully anticipate today improvements that might occur decades from now in psychiatric treatments. We believe that the difficulty of developing non-monoamine-based antidepressants must not obfuscate the importance and eventual feasibility of the goal, given the great clinical need.

Agid, Y., Buzsaki, G., Diamond, D.M., Frackowiak, R., Giedd, J., Girault, J.A., Grace, A., Lambert, J.J., Manji, H., Mayberg, H., Popoli, M., Prochiantz, A., Richter-Levin, G., Somogyi, P., Spedding, M., Svenningsson, P., and Weinberger, D. (2007) How can drug discovery for psychiatric disorders be improved? Nat. Rev. Drug Discov. 6:189–201. Akama, K.T., and McEwen, B.S. (2005) Gene therapy to bet on: protecting neurons from stress hormones 1. Trends Pharmacol. Sci. 26:169–172. Bacchi, F., Mathe, A.A., Jimenez, P., Stasi, L., Arban, R., Gerrard, P., and Caberlotto, L. (2006) Anxiolytic-like effect of the selective neuropeptide Y Y2 receptor antagonist BIIE0246 in the elevated plus-maze. Peptides 27:3202–3207. Bale, T.L., and Vale, W.W. (2004) CRF and CRF receptors: role in stress responsivity and other behaviors. Ann. Rev. Pharmacol. Toxicol. 44:525–557. Bao, A.M., Meynen, G., and Swaab, D.F. (2007) The stress system in depression and neurodegeneration: focus on the human hypothalamus. Brain Res. Rev. Epub ahead of print. Barden, N. (2004) Implication of the hypothalamic-pituitary-adrenal axis in the physiopathology of depression. J. Psychiatr. Neurosci. 29:185–193. Berton, O., McClung, C.A., Dileone, R.J., Krishnan, V., Renthal, W., Russo, S.J., Graham, D., Tsankova, N.M., Bolanos, C.A., Rios, M., Monteggia, L.M., Self, D.W., and Nestler, E.J. (2006) Essential role of BDNF in the mesolimbic dopamine pathway in social defeat stress. Science 311:864–868. Berton, O., and Nestler, E.J. (2006) New approaches to antidepressant drug discovery: beyond monoamines. Nat. Rev. Neurosci. 7:137–151. Binder, E.B., Salyakina, D., Lichtner, P., Wochnik, G.M., Ising, M., Putz, B., et al. (2004) Polymorphisms in FKBP5 are associated with increased recurrence of depressive episodes and rapid response to antidepressant treatment. Nature Gen. 36:1319–1325. Bleakman, D., Alt, A., and Witkin, J.M. (2007) AMPA receptors in the therapeutic management of depression. CNS Neurol. Disord. Drug Targets 6:117–126. Blier, P., Gobbi, G., Haddjeri, N., Santarelli, L., Mathew, G., and Hen, R. (2004) Impact of substance P receptor antagonism on the serotonin and norepinephrine systems: relevance to the antidepressant/anxiolytic response 18. J. Psychiatr. Neurosci. 29:208 – 218. Bourin, M., Mocaer, E., and Porsolt, R. (2004) Antidepressant-like activity of S 20098 (agomelatine) in the forced swimming test in rodents: involvement of melatonin and serotonin receptors. J. Psychiatry Neurosci. 29:126–133. Boyle, M.P., Brewer, J.A., Funatsu, M., Wozniak, D F., Tsien, J.Z., Izumi, Y., and Muglia, L.J. (2005) Acquired deficit of forebrain glucocorticoid receptor produces depression-like changes in adrenal axis regulation and behavior. Proc. Natl. Acad. Sci. USA 102:473– 478. Boyle, M.P., Brewer, J.A., Vogt, S.K., Wozniak, D.F., and Muglia, L.J. (2004) Genetic dissection of stress response pathways in vivo. Endocr. Res. 30:859–863. Carlezon, W.A., Jr., Duman, R.S., and Nestler, E.J. (2005) The many faces of CREB. Trends Neurosci. 28:436 – 445. Chahl, L.A. (2006) Tachykinins and neuropsychiatric disorders. Curr. Drug Targets 7:993–1003. Charmandari, E., Tsigos, C., and Chrousos, G. (2005) Endocrinology of the stress response 1. Ann. Rev. Physiol. 67:259–284. Clapcote, S.J., Lipina, T.V., Millar, J.K., Mackie, S., Christie, S., Ogawa, F., Lerch, J.P., Trimble, K., Uchiyama, M., Sakuraba, Y., Kaneda, H., Shiroishi, T., Houslay, M.D., Henkelman, R.M., Sled, J.G., Gondo, Y., Porteous, D.J., and Roder, J.C. (2007) Behavioral phenotypes of Disc1 missense mutations in mice. Neuron 54:387– 402. Conti, B., Maier, R., Barr, A.M., Morale, M.C., Lu, X., Sanna, P.P., Bilbe, G., Hoyer, D., and Bartfai, T. (2007) Region-specific transcriptional changes following the three antidepressant treatments

34: NOVEL TARGETS FOR ANTIDEPRESSANT TREATMENTS electro convulsive therapy, sleep deprivation and fluoxetine. Mol. Psychiatry 12:167–189. de Kloet, E.R., Joels, M., and Holsboer, F. (2005) Stress and the brain: from adaptation to disease. Nat. Rev. Neurosci. 6:463– 475. den Boer, J.A., Bosker, F.J., and Meesters, Y. (2006) Clinical efficacy of agomelatine in depression: the evidence. Int. Clin. Psychopharmacol. 21(Suppl 1):S21–S24. Drew, M.R., and Hen, R. (2007) Adult hippocampal neurogenesis as target for the treatment of depression. CNS Neurol. Disord. Drug Targets 6:205–218. Duman, C.H., Schlesinger, L., Kodama, M., Russell, D.S., and Duman, R.S. (2007) A role for MAP kinase signaling in behavioral models of depression and antidepressant treatment. Biol. Psychiatry 61: 661– 670. Duman, R.S. (2004) Role of neurotrophic factors in the etiology and treatment of mood disorders. Neuromolecular Med. 5:11–25. Duman, R. S., Heninger, G.R., and Nestler, E.J. (1997) A molecular and cellular theory of depression. Arch. Gen. Psychiatr. 54:597– 606. Duman, R.S., and Monteggia, L.M. (2006) A neurotrophic model for stress-related mood disorders. Biol. Psychiatry 59:1116–1127. Eisch, A.J., Bolanos, C.A., de Wit, J., Simonak, R.D., Pudiak, C.M., Barrot, M., Verhaagen, J., and Nestler, E.J. (2003) Brain-derived neurotrophic factor in the ventral midbrain-nucleus accumbens pathway: a role in depression. Biol. Psychiatry 54:994 –1005. Fekete, E.M., and Zorrilla, E.P. (2007) Physiology, pharmacology, and therapeutic relevance of urocortins in mammals: ancient CRF paralogs. Front. Neuroendocrinol. 28:1–27. Flores, B.H., Kenna, H., Keller, J., Solvason, H.B., and Schatzberg, A.F. (2006) Clinical and biological effects of mifepristone treatment for psychotic depression. Neuropsychopharmacology 31:628–636. Fuchs, E., Simon, M., and Schmelting, B. (2006) Pharmacology of a new antidepressant: benefit of the implication of the melatonergic system. Int. Clin. Psychopharmacol. 21(Suppl 1):S17–S20. Garcia, J.A., Zhang, D., Estill, S.J., Michnoff, C., Rutter, J., Reick, M., Scott, K., Diaz-Arrastia, R., and McKnight, S.L. (2000) Impaired cued and contextual memory in NPAS2-deficient mice. Science 288:2226–2230. Georgescu, D., Sears, R.M., Hommel, J.D., Barrot, M., Bolanos, C.A., Marsh, D.J., Bednarek, M.A., Bibb, J.A., Maratos-Flier, E., Nestler, E.J., and DiLeone, R.J. (2005) The hypothalamic neuropeptide melanin-concentrating hormone acts in the nucleus accumbens to modulate feeding behavior and forced-swim performance. J. Neurosci. 25:2933–2940. Gillespie, C. F., and Nemeroff, C.B. (2005) Hypercortisolemia and depression. Psychosom. Med. 67(Suppl 1):S26–S28. Hawes, J.J., and Picciotto, M.R. (2004) Characterization of GalR1, GalR2, and GalR3 immunoreactivity in catecholaminergic nuclei of the mouse brain. J. Comp. Neurol. 479:410 – 423. Heinrichs, S.C., and Koob, G.F. (2004) Corticotropin-releasing factor in brain: a role in activation, arousal, and affect regulation. J. Pharmacol. Exp. Ther. 311:427– 440. Heurteaux, C., Lucas, G., Guy, N., El Yacoubi, M., Thummler, S., Peng, X.D., Noble, F., Blondeau, N., Widmann, C., Borsotto, M., Gobbi, G., Vaugeois, J. M., Debonnel, G., and Lazdunski, M. (2006) Deletion of the background potassium channel TREK-1 results in a depression-resistant phenotype. Nat. Neurosci. 9:1134 – 1141. Hillhouse, E.W., and Grammatopoulos, D.K. (2006) The molecular mechanisms underlying the regulation of the biological activity of corticotropin-releasing hormone receptors: implications for physiology and pathophysiology. Endocr. Rev. 27:260 –286. Holmes, A., and Picciotto, M.R. (2006) Galanin: a novel therapeutic target for depression, anxiety disorders and drug addiction? CNS Neurol. Disord. Drug Targets 5:225–232. Ishida, H., Shirayama, Y., Iwata, M., Katayama, S., Yamamoto, A., Kawahara, R., and Nakagome, K. (2007) Infusion of neuropeptide Y into CA3 region of hippocampus produces antidepressantlike effect via Y1 receptor. Hippocampus 17:271–280.

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Ising, M., Zimmermann, U.S., Kunzel, H.E., Uhr, M., Foster, A.C., Learned-Coughlin, S.M., Holsboer, F., and Grigoriadis, D.E. (2007) High-affinity CRF(1) receptor antagonist NBI-34041: preclinical and clinical data suggest safety and efficacy in attenuating elevated stress response. Neuropsychopharmacology 32(9):1941–1949. Jeanneteau, F., and Chao, M.V. (2006) Promoting neurotrophic effects by GPCR ligands. Novartis Found. Symp. 276:181–189; discussion 189–192, 233–187, 275–181. Karl, T., and Herzog, H. (2007) Behavioral profiling of NPY in aggression and neuropsychiatric diseases. Peptides 28:326–333. Karlsson, R.M., and Holmes, A. (2006) Galanin as a modulator of anxiety and depression and a therapeutic target for affective disease. Amino Acids 31:231–239. Kaufer, D., Ogle, W.O., Pincus, Z.S., Clark, K.L., Nicholas, A.C., Dinkel, K.M., Dumas, T.C., Ferguson, D., Lee, A.L., Winters, M.A., and Sapolsky, R.M. (2004) Restructuring the neuronal stress response with anti-glucocorticoid gene delivery. Nat. Neurosci. 7: 947–953. Keck, M.E. (2006) Corticotropin-releasing factor, vasopressin and receptor systems in depression and anxiety. Amino Acids 31:241– 250. Keck, M.E., Ohl, F., Holsboer, F., and Muller, M.B. (2005) Listening to mutant mice: a spotlight on the role of CRF/CRF receptor systems in affective disorders. Neurosci. Biobehav. Rev. 29:867–889. Keck, M.E., Welt, T., Muller, M.B., Uhr, M., Ohl, F., Wigger, A., Toschi, N., Holsboer, F., and Landgraf, R. (2003) Reduction of hypothalamic vasopressinergic hyperdrive contributes to clinically relevant behavioral and neuroendocrine effects of chronic paroxetine treatment in a psychopathological rat model. Neuropsychopharmacology 28:235–243. Kehne, J.H. (2007) The CRF1 receptor, a novel target for the treatment of depression, anxiety, and stress-related disorders. CNS Neurol. Disord. Drug Targets 6:163–182. King, D.P., Zhao, Y., Sangoram, A.M., Wilsbacher, L.D., Tanaka, M., Antoch, M.P., Steeves, T.D., Vitaterna, M.H., Kornhauser, J.M., Lowrey, P.L., Turek, F.W., and Takahashi, J.S. (1997) Positional cloning of the mouse circadian clock gene. Cell 89:641– 653. Korte, S.M., Koolhaas, J.M., Wingfield, J.C., and McEwen, B.S. (2005) The Darwinian concept of stress: benefits of allostasis and costs of allostatic load and the trade-offs in health and disease 17. Neurosci. Biobehav. Rev. 29:3–38. Kramer, M.S., Cutler, N., Feighner, J., Shrivastava, R., Carman, J., Sramek, J.J., Reines, S.A., Liu, G.H., Snavely, D., Wyatt-Knowles, E., Hale, J.J., Mills, S.G., MacCoss, M., Swain, C.J., Harrison, T., Hill, R.G., Hefti, F., Scolnick, E.M., Cascieri, M.A., Chicchi, G.G., Sadowski, S., Williams, A.R., Hewson, L., Smith, D., Carlson, E.J., Hargreaves, R.J., and Rupniak, N.M.J. (1998) Distinct mechanism for antidepressant activity by blockade of central substance P receptors 50. Science 281:1640 –1645. Li, Y.W., Fitzgerald, L., Wong, H., Lelas, S., Zhang, G., Lindner, M.D., Wallace, T., McElroy, J., Lodge, N.J., Gilligan, P., and Zaczek, R. (2005) The pharmacology of DMP696 and DMP904, nonpeptidergic CRF1 receptor antagonists. CNS Drug Rev. 11: 21–52. Lolait, S.J., Stewart, L.Q., Jessop, D.S., Young, W.S., 3rd, and O’Carroll, A.M. (2007) The hypothalamic-pituitary-adrenal axis response to stress in mice lacking functional vasopressin V1b receptors. Endocrinology 148:849–856. Lu, X., Barr, A.M., Kinney, J.W., Sanna, P., Conti, B., Behrens, M.M., and Bartfai, T. (2005) A role for galanin in antidepressant actions with a focus on the dorsal raphe nucleus. Proc. Natl. Acad. Sci. USA 102:874 –879. Lu, X., Lundstrom, L., Langel, U., and Bartfai, T. (2005) Galanin receptor ligands. Neuropeptides 39:143–146. Lu, X., Mazarati, A., Sanna, P., Shinmei, S., and Bartfai, T. (2005) Distribution and differential regulation of galanin receptor subtypes in rat brain: effects of seizure activity. Neuropeptides 39: 147–152.

542

MOOD DISORDERS

Lu, X., Sharkey, L., and Bartfai, T. (2007) The brain galanin receptors: targets for novel antidepressant drugs. CNS Neurol. Disord. Drug Targets 6:183–192. Manev, H., and Uz, T. (2006) Clock genes: influencing and being influenced by psychoactive drugs. Trends Pharmacol. Sci. 27:186–189. Manji, H.K., Drevets, W.C., and Charney, D.S. (2001) The cellular neurobiology of depression. Nat. Med. 7:541–547. McClung, C.A. (2007) Circadian genes, rhythms and the biology of mood disorders. Pharmacol. Ther. 114:222–232. McClung, C.A., Sidiropoulou, K., Vitaterna, M., Takahashi, J.S., White, F.J., Cooper, D.C., and Nestler, E.J. (2005) Regulation of dopaminergic transmission and cocaine reward by the Clock gene. Proc. Natl. Acad. Sci. USA 102:9377–9381. Monteggia, L.M., Barrot, M., Powell, C.M., Berton, O., Galanis, V., Gemelli, T., Meuth, S., Nagy, A., Greene, R.W., and Nestler, E.J. (2004) Essential role of brain-derived neurotrophic factor in adult hippocampal function. Proc. Natl. Acad. Sci. USA 101:10827– 10832. Murck, H., Held, K., Ziegenbein, M., Kunzel, H., Holsboer, F., and Steiger, A. (2004) Intravenous administration of the neuropeptide galanin has fast antidepressant efficacy and affects the sleep EEG. Psychoneuroendocrinology 29:1205–1211. Musazzi, L., Perez, J., Hunt, S.P., Racagni, G., and Popoli, M. (2005) Changes in signaling pathways regulating neuroplasticity induced by neurokinin 1 receptor knockout. Eur. J. Neurosci. 21:1370– 1378. Nestler, E.J., Barrot, M., DiLeone, R.J., Eisch, A.J., Gold, S.J., and Monteggia, L.M. (2002) Neurobiology of depression. Neuron 34: 13–25. Nestler, E.J., and Carlezon, W.A., Jr. (2006) The mesolimbic dopamine reward circuit in depression. Biol. Psychiatry 59:1151–1159. Ogren, S.O., Kuteeva, E., Hokfelt, T., and Kehr, J. (2006) Galanin receptor antagonists: a potential novel pharmacological treatment for mood disorders. CNS Drugs 20:633–654. Pacher, P., and Kecskemeti, V. (2004) Trends in the development of new antidepressants. Is there a light at the end of the tunnel? Curr. Med. Chem. 11:925–943. Pare, D., Quirk, G.J., and Ledoux, J.E. (2004) New vistas on amygdala networks in conditioned fear. J. Neurophysiol. 92:1–9. Pariante, C.M., and Miller, A.H. (2001) Glucocorticoid receptors in major depression: Relevance to pathophysiology and treatment 1. Biol. Psychiatry 49:391– 404. Park, S.K., Nguyen, M.D., Fischer, A., Luke, M.P., Affar el, B., Dieffenbach, P.B., Tseng, H.C., Shi, Y., and Tsai, L.H. (2005) Par-4 links dopamine signaling and depression. Cell 122:275–287. Paul, I.A., and Skolnick, P. (2003) Glutamate and depression: clinical and preclinical studies. Ann. N. Y. Acad. Sci. 1003:250–272. Pennefather, J.N., Lecci, A., Candenas, M.L., Patak, E., Pinto, F.M., and Maggi, C.A. (2004) Tachykinins and tachykinin receptors: a growing family. Life Sci. 74:1445–1463. Pittenger, C., Sanacora, G., and Krystal, J.H. (2007) The NMDA receptor as a therapeutic target in major depressive disorder. CNS Neurol. Disord. Drug Targets 6:101–115. Prickaerts, J., Moechars, D., Cryns, K., Lenaerts, I., van Craenendonck, H., Goris, I., Daneels, G., Bouwknecht, J.A., and Steckler, T. (2006) Transgenic mice overexpressing glycogen synthase kinase 3beta: a putative model of hyperactivity and mania. J. Neurosci. 26: 9022–9029. Reppert, S.M., and Weaver, D.R. (2002) Coordination of circadian timing in mammals. Nature 418:935–941. Roybal, K., Theobold, D., Graham, A., DiNieri, J.A., Russo, S.J., Krishnan, V., Chakravarty, S., Peevey, J., Oehrlein, N., Birnbaum, S., Vitaterna, M.H., Orsulak, P., Takahashi, J.S., Nestler, E.J., Carlezon, W.A., Jr., and McClung, C.A. (2007) Mania-like behavior induced by disruption of CLOCK. Proc. Natl. Acad. Sci. USA 104:6406–6411. Rupniak, N.M.J., Carlson, E.J., Webb, J.K., Harrison, T., Porsolt, R.D., Roux, S., de Felipe, C., Hunt, S.P., Oates, B., and Wheeldon, A.

(2001) Comparison of the phenotype of NK1R−/− mice with pharmacological blockade of the substance P (NK1) receptor in assays for antidepressant and anxiolytic drugs. Behav. Pharmacol. 12: 497–508. Sanacora, G., Kendell, S.F., Levin, Y., Simen, A.A., Fenton, L.R., Coric, V., and Krystal, J.H. (2007) Preliminary evidence of riluzole efficacy in antidepressant-treated patients with residual depressive symptoms. Biol. Psychiatry 61:822–825. Sanacora, G., Rothman, D.L., Mason, G., and Krystal, J.H. (2003) Clinical studies implementing glutamate neurotransmission in mood disorders. Ann. N. Y. Acad. Sci. 1003:292–308. Sapolsky, R.M. (2000) Stress hormones: Good and bad.. Neurobiol. Dis. 7:540–542. Shaw, A.M., Boules, M., Zhang, Y., Williams, K., Robinson, J., Carlier, P.R., and Richelson, E. (2007) Antidepressant-like effects of novel triple reuptake inhibitors, PRC025 and PRC050. Eur. J. Pharmacol. 555:30–36. Shimazaki, T., Yoshimizu, T., and Chaki, S. (2006) Melanin-concentrating hormone MCH1 receptor antagonists: a potential new approach to the treatment of depression and anxiety disorders. CNS Drugs 20:801–811. Shirayama, Y., Chen, A.C., Nakagawa, S., Russell, D.S., and Duman, R.S. (2002) Brain-derived neurotrophic factor produces antidepressant effects in behavioral models of depression. J. Neurosci. 22:3251–3261. Svenningsson, P., Chergui, K., Rachleff, I., Flajolet, M., Zhang, X., El Yacoubi, M., Vaugeois, J.M., Nomikos, G.G., and Greengard, P. (2006) Alterations in 5-HT1B receptor function by p11 in depression-like states. Science 311:77–80. Swanson, C.J., Blackburn, T.P., Zhang, X., Zheng, K., Xu, Z.Q., Hokfelt, T., Wolinsky, T.D., Konkel, M.J., Chen, H., Zhong, H., Walker, M.W., Craig, D.A., Gerald, C.P., and Branchek, T.A. (2005) Anxiolytic- and antidepressant-like profiles of the galanin-3 receptor (Gal3) antagonists SNAP 37889 and SNAP 398299. Proc. Natl. Acad. Sci. USA 102:17489–17494. Takahashi, J.S. (2004) Finding new clock components: past and future. J. Biol. Rhythms 19:339–347. Tanis, K.Q., Newton, S.S., and Duman, R.S. (2007) Targeting neurotrophic/growth factor expression and signaling for antidepressant drug development. CNS Neurol. Disord. Drug Targets 6: 151–160. Tsankova, N., Renthal, W., Kumar, A., and Nestler, E.J. (2007) Epigenetic regulation in psychiatric disorders. Nature Rev. Neurosci. 8:355–367. Tschenett, A., Singewald, N., Carli, M., Balducci, C., Salchner, P., Vezzani, A., Herzog, H., and Sperk, G. (2003) Reduced anxiety and improved stress coping ability in mice lacking NPY-Y2 receptors. Eur. J. Neurosci. 18:143–148. Turner, C.A., Akil, H., Watson, S.J., and Evans, S.J. (2006) The fibroblast growth factor system and mood disorders. Biol. Psychiatry 59:1128–1135. Uz, T., Ahmed, R., Akhisaroglu, M., Kurtuncu, M., Imbesi, M., Dirim Arslan, A., and Manev, H. (2005) Effect of fluoxetine and cocaine on the expression of clock genes in the mouse hippocampus and striatum. Neuroscience 134:1309–1316. Warner-Schmidt, J.L., and Duman, R.S. (2007) VEGF is an essential mediator of the neurogenic and behavioral actions of antidepressants. Proc. Natl. Acad. Sci. USA 104:4647– 4652. Wei, Q., Lu, X.Y., Liu, L., Schafer, G., Shieh, K.R., Burke, S., Robinson, T.E., Watson, S.J., Seasholtz, A.F., and Akil, H. (2004) Glucocorticoid receptor overexpression in forebrain: a mouse model of increased emotional lability. Proc. Natl. Acad. Sci. USA 101:11851– 11856. Wermuth, C.G. (2006) Similarity in drugs: reflections on analogue design. Drug Discov. Today 11:348–354. Witkin, J.M., Marek, G.J., Johnson, B.G., and Schoepp, D.D. (2007) Metabotropic glutamate receptors in the control of mood disorders. CNS Neurol. Disord. Drug Targets 6:87–100.

34: NOVEL TARGETS FOR ANTIDEPRESSANT TREATMENTS Yoshitake, T., Reenila, I., Ogren, S.O., Hokfelt, T., and Kehr, J. (2003) Galanin attenuates basal and antidepressant drug-induced increase of extracellular serotonin and noradrenaline levels in the rat hippocampus. Neurosci. Lett. 339:239–242. Zarate, C.A., Jr., Singh, J.B., Carlson, P.J., Brutsche, N.E., Ameli, R., Luckenbaugh, D.A., Charney, D.S., and Manji, H.K. (2006) A randomized trial of an N-methyl-D-aspartate antagonist in treat-

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ment-resistant major depression. Arch. Gen. Psychiatry 63:856– 864. Zarate, C.A., Jr., Singh, J.B., Quiroz, J.A., De Jesus, G., Denicoff, K.K., Luckenbaugh, D.A., Manji, H.K., and Charney, D.S. (2006) A double-blind, placebo-controlled study of memantine in the treatment of major depression. Am. J. Psychiatry 163:153–155.

35 The Neurobiology of Menstrual Cycle-Related Mood Disorders DAVID R. RUBINOW, PETER J. SCHMIDT, SAMANTHA MELTZER-BRODY,

Reproductive endocrine-related mood disorders are affective disturbances that appear in concert with changes in reproductive endocrine activity. They include psychiatric disturbances occurring during menarche, pregnancy or postpartum, the perimenopause, or the menstrual cycle. Also included are disturbances consequent to manipulation of gonadal steroids or reproductive status (for example, hormone replacement therapy or gonadal suppression). Menstrual cycle–related mood disorders refer to disturbances of mood and behavior that are observed in a menstrual-cycle-phase specific fashion. These include disturbances that appear de novo during a given menstrual cycle phase (for example, during the luteal phase) as well as menstrual cycle modulation of the appearance or symptom severity of a preexisting psychiatric disorder. In this chapter, we focus on the former, that is, mood disorders appearing de novo during the luteal phase (hereafter referred to as MRMD). By posing and answering a series of questions, we organize recently obtained data that will help to define the effects of gonadal steroids on the brain and the contribution of gonadal steroids to the underlying neurobiology of MRMD. NEUROMODULATORY EFFECTS OF GONADAL STEROIDS The best support for the neuromodulatory effects of gonadal steroids is found in their dramatic and widely ranging cellular actions. In fact, gonadal steroids have been shown to play a role in all stages of neural development, including neurogenesis, synaptogenesis, neural migration, growth, differentiation, survival, and death (Pilgrim and Hutchison, 1994). These effects occur largely as a consequence of the ability of gonadal steroids to modulate genomic transcription. As transcriptional regulators, the receptors for gonadal steroids direct or modulate the synthesis of the synthetic and metabolic enzymes as well as receptor proteins for many neurotransmitters 544

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and neuropeptides (Ciocca and Roig, 1995). The advances of the past 15 years, however, have demonstrated that the cellular effects of gonadal steroids are far more complex, powerful, and comprehensive than suggested by their originally described genomic actions. First, as the mechanics of transcription became elucidated, it became clear that activated steroid receptors influence transcription not as solitary agents but in combination with other intracellular proteins (Halachmi et al., 1994). These protein–protein interactions were such that an activated receptor might enhance, reduce, initiate, or terminate transcription of a particular gene solely as a function of the specific proteins with which it interacted (and the ability of these proteins to enhance or hinder the recruitment of the general transcription factor apparatus). The expression or activation state of these proteins—coregulators (coactivators or corepressors)—proved to be tissue specific, thus suggesting the means by which a hormone receptor modulator (for example, tamoxifen) could act like an (estrogen) agonist in some tissues (for example, bone) and like an (estrogen) antagonist in others (for example, breast) (Jackson et al., 1997; C.L. Smith et al., 1997; Hall and McDonnell, 2005). Another group of intracellular proteins, the cointegrators, provided a means by which classical hormone receptors could bind to and regulate sites other than hormone response elements (for example, estrogen receptor [ER] or glucocorticoid receptor [GR] binding cyclic AMP-response element binding [CREB] protein [CBP] and, subsequently, the AP1 binding site) (Uht et al., 1997), and competition for cointegrator or other transcriptional regulatory proteins was demonstrated as a mechanism by which even ligand-free hormone receptors could influence (for example, squelch or interfere with) the transcriptional efficacy of other activated hormone receptors (Meyer et al., 1989). Thus, the intracellular hormone receptor environment as well as the extracellular hormone environment might dictate the response to hormone receptor activation.

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Second, the hormone receptors were found to exist in different forms. For example, isoforms of the progesterone receptor, PRA and PRB (the latter of which contains a 164 amino acid N-terminal extension), have different distributions and biological actions (Chalbos and Galtier, 1994), and two separate forms of the estrogen receptor, ERa and ERb , are encoded on different chromosomes (6 and 14, respectively), have different patterns of distribution in the brain, different affinity patterns for certain ligands, and a range of different actions (including those created by estrogen receptor heterodimers; Paech et al., 1997; Shughrue et al., 1997; Kuiper et al., 1998). Further, a variant of ERb , ERb 2 , is expressed in the brain, where it can heterodimerize with the ERa or ERb receptors (J.T. Moore et al., 1998) and inhibit their transcriptional actions (Maruyama et al., 1998). Third, a variety of substances (for example, nerve growth factor, insulin) are capable of activating a steroid receptor even in the absence of ligand (Ignar-Trowbridge et al., 1992; Aronica et al., 1994). This crosstalk is exemplified by the ability of dopamine to induce lordosis by activating the progesterone receptor (Power et al., 1991; Mani et al., 1994). Fourth, the relatively slow, genomic effects of gonadal steroids have been expanded in two dimensions: time, with a variety of rapid (seconds to minutes) effects observed; and targets, which now include ion channels and a variety of second-messenger systems. Several lines of evidence indicate that the rapid effects of E2 are not likely to be the consequence of nuclear events but rather must be related to events occurring at the cell surface (Karkanias and Etgen, 1993; Black et al., 1994; Kelly and Wagner, 1999; Collins and Webb, 1999;ToranAllerand et al., 1999; Singh et al., 2000; Kato, 2001; Wyckoff et al., 2001; Razandi et al., 2002; Qiu et al., 2003). Both classical and unique ERs exist in the caveolae or caveolar-like microdomains of membranes where they link to scaffolding proteins (for example, caveolin-1, flotillin; Toran-Allerand et al., 2002) and multiple signaling molecules, particularly the G proteins, which then activate a wide array of signal transduction systems, including adenylate cyclase/protein kinase A (PKA; Szego and Davis, 1967; Aronica et al., 1994; Gu and Moss, 1996; Qiu et al., 2003), phospholipase C/phosphotidylinositol/diacylglycerol (Le Mellay et al., 1997; Simoncini et al., 2000; Qiu et al., 2003), nitric oxide synthase (Simoncini et al., 2000), protein kinase B (Akt) (L. Zhang et al., 2001), and mitogen-activated protein kinase (MAPK) (Black et al., 1994; Collins and Webb, 1999; Toran-Allerand et al., 1999; Singh et al., 2000; Kato, 2001; Razandi et al., 2003). Through alterations in signal transduction or by direct binding, E2 can also regulate ion channel activity (for example, calcium and potassium channels) and hence, cellular activation (Qiu et al., 2003; Razandi et al., 2003; Zhang et al., 2005).

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Finally, the activity of membrane receptors is acutely modulated by gonadal steroids (for example, glutamate receptors by estradiol and g -aminobutyric acid [GABA] receptors by the 5-alpha reduced metabolite of progesterone, allopregnanolone) (Majewska et al., 1986; Wong and Moss, 1992). Adding to the complexity of the effects described above is their tissue- and even cell-specific nature (for example, estradiol increases MAPK in neurons but decreases it in astrocytes) (Watters et al., 1997; L. Zhang et al., 2002). Fifth, gonadal steroids regulate cell survival. Neuroprotective effects of E2 have been described in neurons grown in serum-free media or those exposed to glutamate, amyloid-b, hydrogen peroxide, ischemia, or glucose deprivation (McEwen and Alves, 1999; Dubal and Wise, 2002). Some of these effects appear to lack stereospecificity (that is, are not classical receptor mediated) and may be attributable to the antioxidant properties of E2 (Mooradian, 1993; Behl et al., 1997), although data from one report are consistent with a receptor-mediated effect (Singer et al., 1996). Gonadal steroids may also modulate cell survival through effects on cell survival proteins (for example, Bcl-2, BAX), MAPK, Akt, or even amyloid precursor protein and Ab metabolism (Black et al., 1994; Garcia-Segura et al., 1998; Gouras et al., 2000; L. Zhang et al., 2002). Sixth, some actions of gonadal steroids on brain appear to be context and developmental stage dependent. Toran-Allerand (1994) showed that estrogen displays reciprocal interactions with growth factors and their receptors (for example, p51 and trk A, neurotrophins) in such a way as to regulate, throughout development, the response to estrogen stimulation: estrogen stimulates its own receptor early in development, inhibits it during adulthood, and stimulates it again in the context of brain injury. Additionally, we demonstrated that the ability to modulate serotonin receptor subtype and GABA receptor subunit transcription in rat brain with exogenous administration of gonadal steroids or gonadal steroid receptor blockade is largely dependent on the developmental stage (for example, last prenatal week vs. fourth postnatal week) during which the intervention occurs (L. Zhang et al., 1999). Finally, the effects of gonadal steroids do not occur in isolation but, rather, in exquisite interaction with the environment. Juraska (1990), for example, demonstrated that the rearing environment (enriched vs. impoverished) dramatically influences sex differences in dendritic branching in the rat cortex and hippocampus. Further, the size of the spinal nucleus of the bulbocavernosus and the degree of adult male sexual behavior in rats is in part regulated by the amount of anogenital licking they receive as pups from their mothers, an activity that is elicited from the dams by the androgen the pups secrete in their urine (C.L. Moore et al., 1992). These environmental influences may include diet and

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medication, as short-chain fatty acids (including valproic acid) dramatically increase cellular sensitivity to gonadal steroids by amplifying their transcriptional potency through inhibition of histonic deacetylase and stimulation of MAPK (Jansen et al., 2004). The vicissitudes of gonadal steroids and their receptors, therefore, direct neural architecture and provide the means by which the response of the CNS to incoming stimuli may be altered. The extent to which these effects underlie or contribute to differential pharmacologic efficacy or behavioral differences observed across individuals is unclear but is of considerable potential relevance for MRMD and other reproductive endocrinerelated mood disorders. THE VALIDITY OF MENSTRUAL CYCLE–RELATED MOOD DISORDERS AS A DIAGNOSIS Unlike other diagnoses in medicine, MRMD is a timeoriented and not a symptom-oriented diagnosis. The symptoms are relatively nonspecific; rather it is their exclusive appearance during the luteal phase that defines the disorder. As such, the diagnosis cannot be made based on history but instead requires a prospective demonstration that symptoms are confined to the luteal phase, disappearing at or soon after the onset of menses. Although many variations on this theme may potentially exist, use of a more restrictive definition has been necessary to ensure the homogeneity of samples across studies necessary for comparison and generalization of results obtained. Employment of diagnostic guidelines (National Institute of Mental Health, 1983; American Psychiatric Association, 1994; Pincus et al., 2007) has demonstrated the existence of MRMD and permitted resolution of many (but not all) of the controversies in the literature regarding the neurobiological basis of MRMD. LUTEAL PHASE–SPECIFIC PHYSIOLOGIC ABNORMALITIES AND MRMD Given the temporal coincidence of symptoms and the luteal phase in women with MRMD, early investigators sought, as an etiology, a disturbance in reproductive endocrine function. Comparisons of basal plasma hormone levels in women with MRMD and controls have revealed no consistent diagnosis-related differences. Specifically, we observed no diagnosis-related differences in the plasma levels, areas under the curve, or patterns of hormone secretion for estradiol, progesterone, follicle stimulating hormone (FSH), or luteinizing hormone (LH) (Rubinow et al., 1988), findings in concert with those of Backstrom et al. (1983) comparing patients with high and low degrees of cyclical mood change.

Findings from subsequent studies of estradiol, progesterone, testosterone, and LH pulsatility also have been inconsistent (Backstrom and Aakvaag, 1981; Facchinetti et al., 1990; Eriksson et al., 1992; Reame et al., 1992; Facchinetti et al., 1993; Redei and Freeman, 1995; Wang et al., 1996; Bloch et al., 1998), suggesting that MRMD is not characterized by abnormal circulating plasma levels of gonadal steroids or gonadotropins or by hypothalamic-pituitary-ovarian axis dysfunction. Several studies do, however, suggest that levels of estrogen, progesterone, or “neurosteroids” (for example, pregnenolone sulfate) may be correlated with symptom severity in women with MRMD (Halbreich et al., 1986; Schechter et al., 1996; Wang et al., 1996). Studies of a variety of other endocrine factors in patients with MRMD have been similarly unrevealing. In general, no differences have been observed in basal plasma cortisol levels, urinary free cortisol, the circadian pattern of plasma cortisol secretion, or basal plasma adrenocorticotropic hormone (ACTH) levels (Rubinow and Schmidt, 1995). (Decreased ACTH levels in MRMD patients across the menstrual cycle and no differences from controls have been reported; Redei and Freeman, 1993; Rosenstein et al., 1996; Bloch et al., 1998.) We did observe a significantly greater cortisol (but not ACTH) response to ovine corticotropin releasing hormone (CRH) in patients with MRMD compared with controls; the exaggerated response appeared to reflect lower baseline plasma cortisol values and appeared in the follicular and luteal phases (Rabin et al., 1990). In contrast, the ACTH and cortisol responses to the serotonin2C (5-HT2C) agonist/5-HT2A antagonist m-chlorophenylpiperazine (m-CPP) were blunted in patients with MRMD during both menstrual cycle phases (with the difference in cortisol reaching statistical significance in the luteal phase only) (Su et al., 1997). Despite the appearance of abnormal baseline thyroid function in 10% of our patients and abnormal (blunted and exaggerated) thyroid stimulating hormone (TSH) response to thyroid releasing hormone (TRH) in 30% of our patients, the vast majority of patients with MRMD have normal hypothalamic-pituitary-thyroid axis function (Schmidt et al., 1993). Luteal phase decreases in plasma beta endorphin (Chuong et al., 1985; Facchinetti et al., 1987) and platelet serotonin uptake (Ashby et al., 1988) have been reported in MRMD; neither the diagnostic group–related decreases nor their confinement to the luteal phase are consistently observed (Malmgren et al., 1987; Tulenheimo et al., 1987; Hamilton and Gallant, 1988; Veeninga and Westenberg, 1992; Bloch et al., 1998). Finally, neither diagnostic nor cycle-related (with the exception of 3-methoxy-4-hydroxyphenylglycol [MHPG]) differences were observed in two studies of cerebrospinal fluid (Parry et al., 1991; Eriksson et al., 1994).

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In conclusion, there are no clearly demonstrated endocrine or other biological abnormalities in MRMD. Further, for the overwhelming majority of biologic factors for which diagnostic group–related differences have been suggested or demonstrated, the difference is not confined to the luteal phase but rather appears in follicular and luteal phases. These differences include increased prevalence of abnormal TSH response to TRH (Roy-Byrne et al., 1987), decreased slow-wave sleep (Lee et al., 1990), increased brain-stem auditory–evoked response latencies (Howard et al., 1992), phase advanced temperature minima and offset of melatonin secretion (Parry et al., 1989; Parry et al., 1990), decreased red blood cell magnesium level (Sherwood et al., 1986; Rosenstein et al., 1994), decreased arginine vasopressin (AVP) level (Prange et al., 1977), blunted growth hormone and cortisol response to L-tryptophan (Bancroft et al., 1991), blunted ACTH response to m-CPP (Su et al., 1997), decreased evening basal plasma cortisol (Rabin et al., 1990), decreased (or increased) free testosterone (Eriksson et al., 1992; Bloch et al., 1998), and increased cortisol response to CRH infusion (Rabin et al., 1990). Even if these differences are confirmed, their persistence across the menstrual cycle would appear to argue against their direct role in the expression of a disorder confined to the luteal phase. Presently, then, there is no clearly demonstrated luteal phase– specific physiologic abnormality in MRMD.

LUTEAL PHASE OVARIAN STEROIDS AND THE SYMPTOMS OF MRMD Given the absence of basal or stimulated reproductive endocrine abnormalities or luteal phase–specific biological abnormalities in MRMD, one could reasonably ask whether the luteal phase is required for the expression of MRMD. We (Schmidt et al., 1991) answered this question by blinding women with MRMD to menstrual cycle phase with the progesterone antagonist mifepristone (RU-486) combined with either human chorionic gonadotropin (hCG) or placebo. Mifepristone administered alone 7 days after the midcycle LH surge precipitated menses and the premature termination of the luteal phase, while the addition of hCG preserved the luteal phase even after the mifepristoneinduced menses. Consequently, following the mifepristone-induced menses, patients did not know whether they were in the follicular phase of a new cycle (mifepristone alone) or in the preserved luteal phase of the first cycle (mifepristone plus hCG). We observed that women with MRMD experienced their characteristic premenstrual mood state after the mifepristone-induced menses in both groups, despite the presence of an experimentally induced follicular phase in the women re-

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ceiving mifepristone alone. The mid to late luteal phase, then, is clearly not required for the appearance of MRMD symptoms. It, nonetheless, remained possible that symptoms could be triggered by hormonal events prior to the mid to late luteal phase, consistent with reports that the suppression of ovulation results in a remission of MRMD symptoms (Muse et al., 1984; Casson et al., 1990). IS OVARIAN ACTIVITY REQUIRED FOR THE EXPRESSION OF MRMD? Studies that employ different methods to suppress or eliminate ovarian function (for example, gonadotropin releasing hormone [GnRH] agonists, the synthetic androgen danazol, or oophorectomy) consistently demonstrate the therapeutic efficacy of ovarian suppression in MRMD. It is, however, difficult to ascribe the efficacy to ovarian suppression per se, given the lack of efficacy of oral contraceptives (which inhibit ovulation) (Graham and Sherwin, 1992) and the reported efficacy of danazol when administered after ovulation (Sarno et al., 1987), thereby leaving unclear the mechanisms of its efficacy. We (Schmidt et al., 1998) confirmed the efficacy shown by others of GnRH agonists (for example, leuprolide acetate [Lupron] in the treatment of MRMD; Muse et al., 1984; Glazener et al., 1985; Bancroft et al., 1987; Mortola et al., 1991; Mezrow et al., 1994). Consistent with Bancroft et al.’s (1987) earlier observations, a therapeutic response was not observed in all patients despite the consistent reduction of gonadal steroid levels to hypogonadal levels. Although the majority of study participants did show a therapeutic response (10/18), the mechanism of action remained unclear (for example, low plasma gonadal steroid levels, consistent gonadal steroid levels, anovulation, suppression of follicular development). This uncertainty was in part addressed by the double-blind, placebo-controlled reintroduction of estradiol (0.1 mg estraderm patch) or progesterone (200 mg BID by suppository) in the study participants in whom Lupron displayed efficacy. The results unequivocally demonstrated the precipitation of a wide range of characteristic symptoms of MRMD during estrogen and progesterone addback but not during placebo addback (Fig. 35.1). Muse (1989) and Mortola et al. (1991) previously described the return of symptoms during 1month trials of estrogen, progestin, or placebo, although symptom return was not seen by Mortola et al. (1991) with the combination of estrogen and progestin. Despite the questions raised by Mortola’s study (for example, why was placebo as able to induce the return of behavioral symptoms as were the gonadal steroids, and why did solitary gonadal steroids precipitate the return of symptoms but sequential administration fail to stim-

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SADNESS

most

MOOD DISORDERS 3

2

least 1 Week

1 2 3 4 5 6 7 8 LEUPROLIDE ALONE

SADNESS

most

Trigger

Women with MRMD

3

1 2 3 4 1 2 3 4 E2 ⫹ LEUPROLIDE

P4 ⫹ LEUPROLIDE

Normal Women

2

least 1 Week

1 2 3 4 5 6 7 8 LEUPROLIDE ALONE

1 2 3 4 1 2 3 4 E2 ⫹ LEUPROLIDE

P4 ⫹ LEUPROLIDE

FIGURE 35.1 Ten women with MRMD and 15 controls had minimal mood and behavioral symptoms during Lupron. In contrast, women with MRMD but not the controls had a significant increase in sadness during either estradiol (E2) or progesterone (P4) administration. Histograms represent the mean (+/− SE) of the seven daily scores on the daily rating form sadness scale for each of the 8 weeks preceding hormone replacement (Lupron alone) and during the 4 weeks of Lupron plus E2 and Lupron plus P4 replacement. A score of one indicates that the symptom was not present and a score of six indicates that it was present in the extreme. MRMD: menstrual cycle–related mood disorders; SE: standard error. (Schmidt et al., 1998).

ulate symptom return?), the combined results from our study and those of Muse (1989) and Mortola et al. (1991) strongly suggest the role of gonadal steroids in the occurrence of MRMD symptoms. Particularly striking, however, is the observation that controls lacking a history of MRMD and going through the same protocol (that is, Lupron-induced hypogonadism followed by gonadal steroid addback) showed no perturbation of mood during hypogonadism and no mood disturbance during hormonal addback (Fig. 35.1). It would appear, therefore, that women with a history of MRMD are differentially sensitive to the mood-perturbing effects of gonadal steroids, as similar steroid manipulations in women without a history of MRMD are without effect. This differential sensitivity may also be consistent with the observations mentioned earlier that MRMD symptoms are correlated with progesterone levels in women with MRMD despite mean levels in patients that are not different from those in controls. TRIGGER AND SUSCEPTIBILITY If gonadal steroids trigger MRMD in some women, how do they do so and why not in all women?

To determine whether the steroid-induced mood disturbances in women with MRMD are caused by the change in hormone levels (with reintroduction representing permissive—but not sufficient— effects of elevated hormone levels interacting with an infradian driver), we recently administered Lupron followed by 3 months of continuous estradiol and progesterone replacement. This paradigm demonstrated that it is the change in gonadal steroids that triggers the mood disturbance; that is, reintroduction of gonadal steroids precipitated a selflimited episode with no subsequent dysphoria over the remainder of the 3 months. These findings suggest that continuous administration of oral contraceptives might, after the first precipitated episode, effectively prevent the recurrence of all other symptoms (due to the stable hormone levels). Possibly consistent with this hypothesis is the recent demonstration of the efficacy of oral contraceptives when administered with a reduced pill-free interval (Yonkers et al., 2005). Susceptibility An obvious source of differences in response phenotype is found in possible genotypic differences. Known polymorphisms in gonadal steroid receptors have been shown to alter receptor transcriptional efficiency (for example, CAG repeat in exon 1 of the androgen receptor; progins insertion in intron 7 of the progesterone receptor) and to be associated with differential illness risk (that is, prostate cancer, breast cancer; Giovannucci et al., 1997; Beilin et al., 1999; Wang-Gohrke et al., 2000; J.X. Zhang et al., 2004). Additionally, the susceptibility to the disruptive effects of estradiol on reproductive development differs enormously (up to a hundredfold) between mouse strains, with genotype contributing more to the variance than the dose of estradiol employed (Spearow et al., 1999). There is precedent, then, for inferring that polymorphisms in genes involved in the gonadal steroid signaling pathway or in gonadal steroid-regulated genes may alter the nature or strength of the steroid signal as well as the phenotype. Although some earlier candidate gene studies did not find significant associations with MRMD (Melke et al., 2003), we have recently identified a region of the estrogen receptor ERa gene (ESR1) containing multiple polymorphic alleles that are associated with MRMD (Huo et al., 2007). Further, this association was significant only in those women with the Val Val genotype of the COMT Val158Met polymorphism, thus lending support to the idea that the effects of multiple genes may interact in creating a dysphoric behavioral response to normal gonadal steroid levels. Demonstration of a relationship between genetic variations in ESR1 and MRMD is very promising for several reasons. First, ER alpha plays a major role in arousal

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(Garey et al., 2003), the dysfunction of which could underlie somatic, cognitive, and affective symptoms of MRMD. Second, ERa regulates the signaling of neurotransmitter systems implicated in the etiopathogenesis and treatment of MRMD. For example, extensive links exist between estrogen and serotonin function, with the latter involved in mood regulation and the selective therapeutic effects of selective serotonin reuptake inhibitors (SSRIs) in MRMD (Rubinow et al., 1998). At least some of the effects of estradiol are mediated through serotonin 1A receptors, which are up-regulated through nuclear factor-kappa B (NF-κB) by ERa but not ERb (Wissink et al., 2001). Third, the estrogen receptor has clear physiologic relevance in MRMD as the receptor for a hormone that can trigger the onset of symptoms of the disorder (Schmidt et al., 1998).

OTHER NEUROBIOLOGIC SYSTEMS IMPLICATED IN THE PATHOPHYSIOLOGY OF MRMD Serotonin A variety of observations implicate dysfunction of serotonergic neurons in MRMD. Although investigations utilizing pharmacologic probes to test 5-HT system function in women with MRMD have yielded inconsistent results (Bancroft et al., 1991; Veeninga and Westenberg, 1992), treatment studies consistently demonstrate the therapeutic efficacy of serotonin-enhancing agents (for example, clomipramine and fluoxetine) for many women with MRMD (Dimmock et al., 2000). Nonserotonin selective antidepressants appear inferior in efficacy to the SSRIs (Eriksson et al., 1995). Further, acute tryptophan depletion, mediated by a dietary manipulation, was reported in one study (Menkes et al., 1994) to exacerbate symptoms in women with MRMD during follicular and luteal phases of the menstrual cycle. Additionally, we observed an acute therapeutic response in women with MRMD following oral administration of the 5-HT2C agonist/5HT2A antagonist, m-CPP, as well as a delayed (24 hours) reversal of the efficacy of fluoxetine by the serotonin receptor “antagonist” metergoline (Su et al., 1997; Roca et al., 2002). These data converge to strongly suggest the role of the serotonin system in the pathophysiology of MRMD. As the majority of abnormalities in neuroendocrine response to serotonergic agents in MRMD are observed in both phases of the cycle (and because approximately 40% of women with MRMD do not respond to SSRIs), serotonergic dysfunction cannot be implicated as a direct cause of MRMD. It may, however, convey a vulnerability to mood destabilization in association with changes in gonadal steroids seen during the menstrual cycle, a particularly intriguing possibility given the multiple reciprocal interactions that exist throughout development

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between gonadal steroids and serotonin (Rubinow et al., 1998). Neurosteroids A second potential source of susceptibility is the conversion of progesterone to its neurosteroid metabolites. Observations central to these speculations include the following: 1. The GABA receptor (the presumed mediator of anxiolysis) is positively modulated by the 5-alpha and -beta reduced metabolites of progesterone (allopregnanolone and pregnanolone, respectively) (Majewska et al., 1986) and is remodeled by these metabolites (Li and O’Malley, 2003; Shen et al., 2005; Maguire and Mody, 2007). 2. Withdrawal of progesterone in rats produces anxiety and insensitivity to benzodiazepines due to withdrawal of allopregnanolone, with consequent induction of GABAA alpha-4 subunit levels, and inhibition of GABA currents (S.S. Smith, Gong, Hsu, et al., 1998; S.S. Smith, Gong, Li, et al., 1998). 3. Allopregnanolone displays anxiolytic effects in several animal anxiety models (Kellner et al., 1983; Bitran et al., 1991; Wieland et al., 1991) and may be involved in the stress response (Purdy et al., 1991). 4. Decreased plasma allopregnanolone levels are seen in major depressive disorder and in depression associated with alcohol withdrawal, with an increase in levels seen in plasma and cerebrospinal fluid (CSF) following successful antidepressant treatment (Romeo et al., 1996; Romeo et al., 1998; Uzunova et al., 1998; Ströhle et al., 1999; although see Eser et al., 2006). 5. Antidepressants may promote the reductive activity of one of the neurosteroid synthetic enzymes (3 alphahydroxysteroid oxidoreductase), thus favoring the formation of allopregnanolone (Griffin and Mellon, 1999). 6. Cerebral cortical inhibition increases during the luteal phase, a presumed effect of increased allopregnanolone levels and a finding absent in women with MRMD (M.J. Smith et al., 2002; M.J. Smith et al., 2003; Maguire et al., 2005). 7. Patients with MRMD show differences in pregnanolone-modulated saccadic eye velocity (SEV) and sedation in the luteal phase compared with controls (Sundstrom and Backstrom, 1998b) (although the reported differences seem attributable to an SEV response to vehicle in those with MRMD and a blunted sedation response in the follicular phase in controls). 8. Patients with high severity MRMD show blunted SEV and sedation responses to GABAA receptor agonists —pregnanolone (Sundstrom and Backstrom, 1998a) or midazolam (Sundstrom et al., 1997)—compared with patients with low severity MRMD. 9. Women with MRMD have blunted allopregnanolone responses to stress and evidence of altered metabo-

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lism of progesterone to allopregnanolone (Girdler et al., 2001; Klatzkin et al., 2006). Studies to date fail to demonstrate any consistent diagnosis-related differences in allopregnanolone or pregnanolone (Schmidt et al., 1994; Wang et al., 1996; Girdler et al., 2001) nor any difference in pregnanolone levels in women with MRMD before and after successful treatment with antidepressants (Sundstrom and Backstrom, 1998a). Nonetheless, a recent study by Shen et al. (2007) demonstrated that changes in the GABA receptor induced by decreases in allopregnanolone can reverse the effects of allopregnanolone on the receptor and exaggerate anxiolytic responses to stressors in the absence of basal changes in anxiety. Consequently, changes in neurosteroid levels remain intriguing as possible contributors to the triggering of or susceptibility to MRMD.

HYPOTHALAMIC-PITUITARY-ADRENAL (HPA) AXIS Disturbances of the hypothalamic-pituitary-adrenal (HPA) axis function are implicated in the pathophysiology of affective disorder, and it is, therefore, tempting to speculate that similar dysregulation of the stress response may contribute to the susceptibility to affective disturbance seen in women with MRMD. Observations of abnormal HPA axis activity in depression and numerous reciprocal regulatory interactions between the stress and reproductive axes suggested that MRMD might be characterized by disturbances in the HPA axis. As mentioned above, studies of basal plasma measures of the HPA axis have been largely unrevealing. Nonetheless, studies of stimulated HPA axis activity provide evidence of the involvement of this neuroendocrine axis in MRMD. Roca et al. (2003) showed a differential HPA axis response to exercise stimulation in women with MRMD compared with controls. Women with MRMD fail to show the luteal phase increase in stimulated AVP, ACTH, and cortisol seen in normal women and additionally display adrenal hyporesponsivity. As it is progesterone rather than estradiol that enhances exercisestimulated HPA activity (Roca et al., 2003), women with MRMD display an abnormal response to progesterone. A variety of data support these observations. In a prior study (Su et al., 1997), we showed that mCPP stimulated cortisol was significantly blunted in the luteal (but not the follicular) phase in women with MRMD, consistent with the current findings as well as with data from Girdler et al. (2001) showing decreased luteal phase–stimulated cortisol in women with MRMD. Additionally, blunted or absent cortisol response to CRH or naloxone, respectively, was observed in the luteal phase in women with MRMD (Facchinetti et al., 1994). In a separate earlier study (Rabin et al., 1990), we showed that women with MRMD display low evening cortisol levels across the menstrual cycle, seen as well by Parry

et al. (2000) and Odber et al. (1998) and consistent with either adrenal hyposensitivity or altered circadian cortisol dynamics (although, see Steiner et al., 1984; Parry et al., 1994). Bancroft et al. (1991) identified blunted levels across the menstrual cycle of tryptophan-stimulated cortisol secretion in women with MRMD. Finally, an abnormal response to (presumed) luteal phase progesterone in women with MRMD was also seen in their failure to manifest the normal luteal phase alteration in the timing of the cortisol acrophase (Parry et al., 2000). These data, then, suggest the following: stimulated cortisol (albeit paradigm specific) is decreased in women with MRMD relative to controls during the luteal phase; the adrenal response to ACTH may be blunted in women with MRMD; women with MRMD manifest an abnormal HPA axis (and mood) response to progesterone; women with MRMD display disturbances of the HPA axis that are markedly different from those identified in major depression. Although the determinants of these observations are unclear, they provide another compelling example of differential response to gonadal steroids in women with MRMD and suggest an additional potential source of vulnerability to affective disturbance. CONCLUSIONS To identify what the study of MRMD may contribute to our understanding of the effects of gonadal steroids on brain and behavior, several observations must be integrated. First, there does not appear to be a disturbance of reproductive endocrine function that underlies MRMD. Second, changes in levels of estrogen and progesterone appear to be capable of triggering mood disturbances in a susceptible population; that is, some preexisting vulnerability must explain the capacity of the same biologic stimulus (for example, gonadal steroids) to elicit a differential behavioral response across groups of people. Third, perturbations of nonreproductive endocrine systems appear capable of precipitating MRMD. Menstrual cycle–related mood disorders may appear in the context of hypothyroidism (with symptoms responsive to thyroid hormone replacement; Schmidt et al., 1990), and provocative (Bancroft, 1993; Su et al., 1997) and especially treatment studies (Stone et al., 1990) suggest the relevance of the serotonin system to MRMD. Menstrual cycle–related mood disorders, then, may represent a behavioral state that is triggered by a reproductive endocrine stimulus in those who may be rendered susceptible to behavioral state changes by antecedent experiential events (for example, history of major depression; DeJong et al., 1985) or physical or sexual abuse (Paddison et al., 1990) or biological conditions (for example, hypothyroidism; Schmidt et al., 1990). Treatment can, therefore, be directed to either eliminating the trigger (for example,

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ovarian suppression) or correcting the “vulnerability” (for example, serotonergic antidepressants; Stone et al., 1990). Although the means by which alterations in gonadal steroids trigger changes in behavioral state in certain individuals are unclear, it is nonetheless striking that, in contrast to the pathological function of other endocrine systems (for example, adrenal, thyroid) seen in association with mood disorders, gonadal steroids may precipitate mood disturbances in the context of normal ovarian function. This suggests that further study of the interactions between gonadal steroids and other neuroactive systems may help elucidate general mechanisms underlying affective regulation as well as the physiologic substrate that predisposes certain people to experience reproductive endocrine-related mood disorders. REFERENCES American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Aronica, S.M., Kraus, W.L., and Katzenellenbogen, B.S. (1994) Estrogen action via the cAMP signaling pathway: stimulation of adenylate cyclase and cAMP-regulated gene transcription. Proc. Natl. Acad. Sci. USA 91(18):8517–8521. Ashby, C.R., Jr., Carr, L.A., Cook, C.L., Steptoe, M.M., and Franks, D.D. (1988) Alteration of platelet serotonergic mechanisms and monoamine oxidase activity in premenstrual syndrome. Biol. Psychiatry 24(2):225–233. Backstrom, T., and Aakvaag, A. (1981) Plasma prolactin and testosterone during the luteal phase in women with premenstrual tension syndrome. Psychoneuroendocrinology 6(3):245–251. Backstrom, T., Sanders, D., Leask, R., Davidson, D., Warner, P., and Bancroft, J. (1983) Mood, sexuality, hormones, and the menstrual cycle: II. Hormone levels and their relationship to the premenstrual syndrome. Psychosom. Med. 45(6):503–507. Bancroft, J. (1993) The premenstrual syndrome—a reappraisal of the concept and the evidence. Psychol. Med. (Suppl 24):1– 47. Bancroft, J., Boyle, H., Warner, P., and Fraser, H.M. (1987) The use of an LHRH agonist, buserelin, in the long-term management of premenstrual syndromes. Clin. Endocrinol. 27(2):171–182. Bancroft, J., Cook, A., Davidson, D., Bennie, J., and Goodwin, G. (1991) Blunting of neuroendocrine responses to infusion of Ltryptophan in women with perimenstrual mood change. Psychol. Med. 21(2):305–312. Behl, C., et al. (1997) Neuroprotection against oxidative stress by estrogens: structure-activity relationship. Mol. Pharmacol. 51(4): 535–541. Beilin, J., and Zajac, J.D. (1999) Function of the human androgen receptor varies according to CAG repeat number within the normal range. Proceedings of the 81st Annual Meeting of the Endocrine Society 500(abstr.). Bitran, D., Hilvers, R.J., and Kellogg, C.K. (1991) Anxiolytic effects of 3a-hydroxy-5a[b]-pregnan-20-one: endogenous metabolites of progesterone that are active at the GABAA receptor. Brain Res. 561:157–161. Black, L.J., et al. (1994) Raloxifene (LY139481 HCI) prevents bone loss and reduces serum cholesterol without causing uterine hypertrophy in ovariectomized rats. J. Clin. Invest. 93(1):63–69. Bloch, M., Schmidt, P.J., Su, T.-P., Tobin, M.B., and Rubinow, D.R. (1998) Pituitary-adrenal hormones and testosterone across the menstrual cycle in women with premenstrual syndrome and controls. Biol. Psychiatry 43(12):897–903. Casson, P., Hahn, P.M., VanVugt, D.A., and Reid, R.L. (1990) Lasting response to ovariectomy in severe intractable premenstrual syndrome. Am. J. Obstet. Gynecol. 162(1):99–105.

551

Chalbos, D., and Galtier, F. (1994) Differential effect of forms A and B of human progesterone receptor on estradiol-dependent transcription. J. Biol. Chem. 269(37):23007–23012. Chuong, C.J., Coulam, C.B., Kao, P.C., Bergstralh, E., and Go, V.L. (1985) Neuropeptide levels in premenstrual syndrome. Fert. Steril. 44(6):760–765. Ciocca, D.R., and Roig, L.M. (1995) Estrogen receptors in human nontarget tissues: biological and clinical implications. Endocr. Rev. 16(1):35–62. Collins, P., and Webb, C. (1999) Estrogen hits the surface. Nat. Med. 5(12):1130–1131. DeJong, R., Rubinow, D.R., Roy-Byrne, P.P., Hoban, M.C., Grover, G.N., and Post, R.M. (1985) Premenstrual mood disorder and psychiatric illness. Am. J. Psychiatry 142:1359–1361. Dimmock, P.W., Wyatt, K.M., Jones, P.W., and O’Brien, P.M.S. (2000) Efficacy of selective serotonin-reuptake inhibitors in premenstrual syndrome: a systematic review. Lancet 356(9236):1131–1136. Dubal, D.B., and Wise, P.M. (2002) Estrogen and neuroprotection: from clinical observations to molecular mechanisms. Dialogues Clin. Neurosci. 4:149–162. Eriksson, E., Alling, C., Andersch, B., Andersson, K., and Berggren, U. (1994) Cerebrospinal fluid levels of monoamine metabolites: a preliminary study of their relation to menstrual cycle phase, sex steroids, and pituitary hormones in healthy women and in women with premenstrual syndrome. Neuropsychopharmacology 11(3):201–213. Eriksson, E., Hedberg, M.A., Andersch, B., and Sundblad, C. (1995) The serotonin reuptake inhibitor paroxetine is superior to the noradrenaline reuptake inhibitor maprotiline in the treatment of premenstrual syndrome. Neuropsychopharmacology 12(2):167–176. Eriksson, E., Sundblad, C., Lisjo, P., Modigh, K., and Andersch, B. (1992) Serum levels of androgens are higher in women with premenstrual irritability and dysphoria than in controls. Psychoneuroendocrinology 17(2/3):195–204. Eser, D., Schule, C., Baghai, T.C., Romeo, E., and Rupprecht, R. (2006) Neuroactive steroids in depression and anxiety disorders: clinical studies. Neuroendocrinology 84:244 –254. Facchinetti, F., Fioroni, L., Martignoni, E., Sances, G., Costa, A., and Genazzani, A.R. (1994) Changes of opioid modulation of the hypothalamo-pituitary-adrenal axis in patients with severe premenstrual syndrome. Psychosomatic Med. 56(5):418– 422. Facchinetti, F., Genazzani, A.D., Martignoni, E., Fioroni, L., Nappi, G., and Genazzani, A.R. (1993) Neuroendocrine changes in luteal function in patients with premenstrual syndrome. J. Clin. Endocrinol. Metab. 76(5):1123–1127. Facchinetti, F., Genazzani, A.D., Martignoni, E., Fioroni, L., Sances, G., and Genazzani, A.R. (1990) Neuroendocrine correlates of premenstrual syndrome: changes in the pulsatile pattern of plasma LH. Psychoneuroendocrinology 15(4):269–277. Facchinetti, F., Martignoni, E., Petraglia, F., Sances, M., Nappi, G., and Genazzani, A. (1987) Premenstrual fall of plasma B-endorphin in patients with premenstrual syndrome. Fertil. Steril. 47(4): 570–573. Garcia-Segura, L.M., Cardona-Gomez, P., Naftolin, F., and Chowen, J.A. (1998) Estradiol upregulates Bcl-2 expression in adult brain neurons. Neuroreport 9(4):593–597. Garey, J., et al. (2003) Genetic contributions to generalized arousal of brain and behavior. Proc. Natl. Acad. Sci. USA 100(19):11019– 11022. Giovannucci, E., et al. (1997) The CAG repeat within the androgen receptor gene and its relationship to prostate cancer. Proc. Natl. Acad. Sci. USA 94(7):3320–3323. Girdler, S.S., Straneva, P.A., Light, K.C., Pedersen, C.A., and Morrow, A.L. (2001) Allopregnanolone levels and reactivity to mental stress in premenstrual dysphoric disorder. Biol. Psychiatry 49(9):788–797. Glazener, C.M.A., Bailey, I., and Hull, M.G.R. (1985) Effectiveness of vaginal administration of progesterone. Br. J. Obstet. Gynaecol. 92(4):364–368.

552

MOOD DISORDERS

Gouras, G.K., et al. (2000) Testosterone reduces neuronal secretion of Alzheimer’s beta-amyloid peptides. Proc. Natl. Acad. Sci. USA 97(3):1202–1205. Graham, C.A., and Sherwin, B.B. (1992) A prospective treatment study of premenstrual symptoms using a triphasic oral contraceptive. J. Psychosom. Res. 36(3):257–266. Griffin, L.D., and Mellon, S.H. (1999) Selective serotonin reuptake inhibitors directly alter activity of neurosteroidogenic enzymes. Proc. Natl. Acad. Sci. USA 96(23):13512–13517. Gu, Q., and Moss, R.L. (1996) 17 beta-estradiol potentiates kainate-induced currents via activation of the cAMP cascade. J. Neurosci. 16(11):3620–3629. Halachmi, S., Marden, E., Martin, G., MacKay, H., Abbondanza, C., and Brown, M. (1994) Estrogen receptor-associated proteins: possible mediators of hormone-induced transcription. Science 264(5164):1455–1458. Halbreich, U., Endicott, J., Goldstein, S., and Nee, J. (1986) Premenstrual changes and changes in gonadal hormones. Acta Psychiatr. Scand. 74:576–586. Hall, J.M., and McDonnell, D.P. (2005) Coregulators in nuclear estrogen receptor action. Mol. Interv. 5(6):343–356. Hamilton, J.A., and Gallant, S. (1988) Premenstrual symptom changes and plasma b-endorphin/b-lipotropin throughout the menstrual cycle. Psychoneuroendocrinology 13:505–514. Howard, R., Mason, P., Taghavi, E., and Spears, G. (1992) Brainstem auditory evoked responses (BAERs) during the menstrual cycle in women with and without premenstrual syndrome. Biol. Psychiatry 32(8):682–690. Huo, L., et al. (2007) Risk for premenstrual dysphoric disorder is associated with genetic vatiation in ESR1, the estrogen receptor alpha gene. Biol. Psychiatry 62(8):925–933. Ignar-Trowbridge, D.M., et al. (1992) Coupling of dual signaling pathways: epidermal growth factor action involves the estrogen receptor. Proc. Natl. Acad. Sci USA 89(10):4658– 4662. Jackson, T.A., Richer, J.K., Bain, D.L., Takimoto, G.S., Tung, L., and Horwitz, K.B. (1997) The partial agonist activity of antagonist-occupied steroid receptors is controlled by a novel hinge domain-binding co-activator L7/SPA and the corepressors N-COR or SMRT. Mol. Endocrinol. 11:693–705. Jansen, M., Nagal, S., Miranda, P., Lobenhofer, E., Afshari, C., and McDonnell, D.P. (2004) Short-chain fatty acids enhance nuclear receptor activity through mitogen-activated protein kinase activation and histone deacetylase inhibition. Proc. Natl. Acad. Sci. USA 101(18):7199–7204. Juraska, J.M. (1990). The structure of the rat cerebral cortex: effects of gender and the environment. In: Kolb, B., and Tees, R.C., eds. The Cerebral Cortex of the Rat. Cambridge, MA: MIT Press, pp. 483–505. Karkanias, G.B., and Etgen, A.M. (1993) Estradiol attenuates alpha 2-adrenoceptor-mediated inhibition of hypothalamic norepinephrine release. J. Neuroscience 13(8):3448–3455. Kato, S. (2001) Estrogen receptor-mediated cross-talk with growth factor signaling pathways. Breast Cancer 8(1):3–9. Kellner, C.H., Rakita, R.M., Rubinow, D.R., Gold, P.W., Ballenger, J.C., and Post, R.M. (1983) Tetrahydrobiopterin levels in cerebrospinal fluid of affectively ill patients [letter]. Lancet 2(8340):55–56. Kelly, M.J., and Wagner, E.J. (1999) Estrogen modulation of G-proteincoupled receptors. Trends Endocrin. Metab. 10:369–374. Klatzkin, R.R., Morrow, A.L., Light, K.C., Pedersen, C., and Girdler, S.S. (2006) Histories of depression, allopregnanolone responses to stress, and premenstrual symptoms in women. Biol. Psychol. 116(1):2–11. Kuiper, G.G.J.M., Shughrue, P.J., Merchenthaler, I., and Gustafsson, J.-A. (1998) The estrogen receptor b subtype: a novel mediator of estrogen action in neuroendocrine systems. Front. Neuroendocrinol. 19:253–286.

Le Mellay, V., Grosse, B., and Lieberherr, M. (1997) Phospholipase C beta and membrane action of calcitriol and estradiol. J. Biol. Chem. 272(18):11902–11907. Lee, K.A., Shaver, J.F., Giblin, E.C., and Woods, N.F. (1990) Sleep patterns related to menstrual cycle phase and premenstrual affective symptoms. Sleep 13(5):403– 409. Li, X., and O’Malley, B.W. (2003) Unfolding the action of progesterone receptors. J. Biol. Chem. 278(41):39261–39264. Maguire, J.L., and Mody, I. (2007) Neurosteroid synthesis-mediated regulation of GABA(a) receptors: relevance to the ovarian cycle stress. J. Neurosci. 27(9):2155–2162. Maguire, J.L., Stell, B.M., Rafizadeh, M., and Mody, I. (2005) Ovarian cycle-linked changes in GABAA receptors mediating tonic inhibition after seizure susceptibility and anxiety. Nat. Neurosci. 8(6):797–804. Majewska, M.D., Harrison, N.L., Schwartz, R.D., Barker, J.L., and Paul, S.M. (1986) Steroid hormone metabolites are barbituratelike modulators of the GABA receptor. Science 232(4753): 1004 –1007. Malmgren, R., Collins, A., and Nilsson, C.G. (1987) Platelet serotonin uptake and effects of vitamin B6-treatment in premenstrual tension. Neuropsychobiology 18(2):83–88. Mani, S.K., Blaustein, J.D., Allen, J.M.C., Law, S.W., O’Malley, B.W., and Clark, J.H. (1994) Inhibition of rat sexual behavior by antisense oligonucleotides to the progesterone receptor. Endocrinology 135(4):1409–1414. Maruyama, K., et al. (1998) A novel isoform of rat estrogen receptor b with 18 amino acid insertion in the ligand binding domain as a putative dominant negative regular of estrogen action. Biochem. Biophys. Res. Comm. 246:142–147. McEwen, B.S., and Alves, S.E. (1999) Estrogen actions in the central nervous system. Endocr. Rev. 20:279–307. Melke, J., et al. (2003) Serotonin transporter gene polymorphisms and platelet [3H]paroxetine binding in premenstrual dysphoria. Psychoneuroendocrinology 28(3):446 – 458. Menkes, D.B., Coates, D.C., and Fawcett, J.P. (1994) Acute tryptophan depletion aggravates premenstrual syndrome. J. Affect. Disord. 32(1):37– 44. Meyer, M.-E., Gronemeyer, H., Turcott, B., Bocquel, M.-T., Tasset, D., and Chambon, P. (1989) Steroid hormone receptors compete for factors that mediate their enhancer function. Cell 57(3):433– 442. Mezrow, G., Shoupe, D., Spicer, D., Lobo, R., Leung, B., and Pike, M. (1994) Depot leuprolide acetate with estrogen and progestin add-back for long-term treatment of premenstrual syndrome. Fertil. Steril. 62(5):932–937. Mooradian, A.D. (1993) Antioxidant properties of steroids. J. Steroid Biochem. Mol. Biol. 45:509–511. Moore, C.L., Dou, H., and Juraska, J.M. (1992) Maternal stimulation affects the number of motor neurons in a sexually dimorphic nucleus of the lumbar spinal cord. Brain Res. 572(1/2): 52–56. Moore, J.T., et al. (1998) Cloning and characterization of human estrogen receptor b isoforms. Biochem. Biophys. Res. Comm. 247: 75–78. Mortola, J.F., Girton, L., and Fischer, U. (1991) Successful treatment of severe premenstrual syndrome by combined use of gonadotropin-releasing hormone agonist and estrogen/progestin. J. Clin. Endocrinol. Metab.72(2):252A–252F. Muse, K. (1989) Gonadotropin-releasing hormone agonist-suppressed premenstrual syndrome (PMS): PMS symptom induction by estrogen, progestin, or both. Abstracts of the Society for Gynecologic Investigation 4:118. Muse, K.N., Cetel, N.S., Futterman, L.A., and Yen, S.S.C. (1984) The premenstrual syndrome: effects of “medical ovariectomy.” New Eng. J. Med. 311(21):1345–1349.

35: THE NEUROBIOLOGY OF MENSTRUAL CYCLE-RELATED MOOD DISORDERS National Institute of Mental Health. (1983). NIMH Premenstrual Syndrome Workshop Guidelines. NIMH 6001 Executive Blvd., Room 8235, MSC9669 Bethesda, MD, 20892. Odber, J., Cawood, E.H.H., and Bancroft, J. (1998) Salivary cortisol in women with and without premenstrual mood changes. J. Psychosom. Res. 45(6):557–568. Paddison, P.L., Gise, L.H., Lebovits, A., Strain, J.J., Cirasole, D.M., and Levine, J.P. (1990) Sexual abuse and premenstrual syndrome: comparison between a lower and higher socioeconomic group. Psychosomatics 31(3):265–272. Paech, K., et al. (1997) Differential ligand activation of estrogen receptors ERa and ERb at AP1 sites. Science 277:1508–1510. Parry, B.L., et al. (1990) Altered waveform of plasma nocturnal melatonin secretion in premenstrual syndrome. Arch. Gen. Psychiatry 47(12):1139–1146. Parry, B.L., et al. (1991) CSF and endocrine studies of premenstrual syndrome. Neuropsychopharmacology 5(2):127–137. Parry, B.L., et al. (1994) Neuroendocrine effects of light therapy in late luteal phase dysphoric disorder. Biol. Psychiatry 36(6):356–364. Parry, B.L., Javeed, S., Laughlin, G.A., Hauger, R., and Clopton, P. (2000) Cortisol circadian rhythms during the menstrual cycle and with sleep deprivation in premenstrual dysphoric disorder and normal control subjects. Biol. Psychiatry 48(9):920–931. Parry, B.L., Mendelson, W.B., Duncan, W.B., Sack, D.A., and Wehr, T.A. (1989) Longitudinal sleep EEG, temperature, and activity measurements across the menstrual cycle in patients with premenstrual depression and in age-matched controls. Psychiatry Res. 30(3):285–303. Pilgrim, C., and Hutchison, J.B. (1994) Developmental regulation of sex differences in the brain: can the role of gonadal steroids be redefined? Neuroscience 60(4):843–855. Pincus, S.M., Schmidt, P.J., Palladino-Negro, P., and Rubinow, D.R. (2007) Differentiation of women with premenstrual dysphoric disorder, recurrent brief depression, and healthy controls by daily mood rating dynamics. J. Psychiatric Res. 42(5):337–347. Power, R.F., Mani, S.K., Codina, J., Conneely, O.M., and O’Malley, B.W. (1991) Dopaminergic and ligand-independent activation of steroid hormone receptors. Science 254(5038):1636–1639. Prange, A.J., Jr., Lipton, M.A., Nemeroff, C.B., and Wilson, I.C. (1977) The role of hormones in depression. Life Sci. 20(8):1305– 1318. Purdy, R.H., Morrow, A.L., Moore, P.H., Jr., and Paul, S.M. (1991) Stress-induced elevations of gamma-aminobutyric acid type A receptor-active steroids in the rat brain. Proc. Natl. Acad. Sci. USA 88(10):4553– 4557. Qiu, J., et al. (2003) Rapid signaling of estrogen in hypothalamic neurons involves a novel G-protein-coupled estrogen receptor that activates protein kinase C. J. Neurosci. 23(29):9529–9540. Rabin, D.S., et al. (1990) Hypothalamic-pituitary-adrenal function in patients with the premenstrual syndrome. J. Clin. Endocrinol. Metab. 75(5):1158–1162. Razandi, M., Oh, P., Pedram, A., Schnitzer, J., and Levin, E.R. (2002) ERs associate with and regulate the production of caveolin: implications for signaling and cellular actions. Mol. Endocrinology 16(1):100–115. Razandi, M., Pedram, A., Park, S.T., and Levin, E.R. (2003) Proximal events in signaling by plasma membrane estrogen receptors. J. Biol. Chem. 278(4):2701–2712. Reame, N.E., Marshall, J.C., and Kelch, R.P. (1992) Pulsatile LH secretion in women with premenstrual syndrome (PMS): evidence for normal neuroregulation of the menstrual cycle. Psychoneuroendocrinology 17(2/3):205–213. Redei, E., and Freeman, E.W. (1993) Preliminary evidence for plasma adrenocorticotropin levels as biological correlates of premenstrual symptoms. Acta Endocrinol. (Copenh) 128(6):536–542.

553

Redei, E., and Freeman, E.W. (1995) Daily plasma estradiol and progesterone levels over the menstrual cycle and their relation to premenstrual symptoms. Psychoneuroendocrinology 20(3):259– 267. Roca, C.A., et al. (2003) Differential menstrual cycle regulation of hypothalamic-pituitary-adrenal axis in women with premenstrual syndrome and controls. J. Clin. Endocrinol. Metab. 88(7):3057– 3063. Roca, C.A., Schmidt, P.J., Smith, M.J., Danaceau, M.A., Murphy, D.L., and Rubinow, D.R. (2002) Effects of metergoline on symptoms in women with premenstrual dysphoric disorder. Am. J. Psychiatry 159(11):1876–1881. Romeo, E., et al. (1996) Marked decrease of plasma neuroactive steroids during alcohol withdrawal. Clin. Neuropharmacol. 19(4): 366–369. Romeo, E., et al. (1998) Effects of antidepressant treatment on neuroactive steroids in major depression. Am. J. Psychiatry 155(7): 910–913. Rosenstein, D.L., Elin, R.J., Hosseini, J.M., Grover, G., and Rubinow, D.R. (1994) Magnesium measures across the menstrual cycle in premenstrual syndrome. Biol. Psychiatry 35(8):557–561. Rosenstein, D.L., Kalogeras, K.T., Kalafut, M., Malley, J., and Rubinow, D.R. (1996) Peripheral measures of arginine vasopressin, atrial natriuretic peptide and adrenocorticotropic hormone in premenstrual syndrome. Psychoneuroendocrinology 21(3):347–359. Roy-Byrne, P.P., Rubinow, D.R., Hoban, M.C., Grover, G.N., and Blank, D. (1987) TSH and prolactin responses to TRH in patients with premenstrual syndrome. Am. J. Psychiatry 144(4):480– 484. Rubinow, D.R., et al. (1988) Changes in plasma hormones across the menstrual cycle in patients with menstrually related mood disorder and in control subjects. Am. J. Obstet. Gynecol. 158(1): 5–11. Rubinow, D.R., and Schmidt, P.J. (1995) The neuroendocrinology of menstrual cycle mood disorders. Ann. N. Y. Acad. Sci.771:648– 659. Rubinow, D.R., Schmidt, P.J., and Roca, C.A. (1998) Estrogen-serotonin interactions: implications for affective regulation. Biol. Psychiatry 44(9):839–850. Sarno, A.P., Miller, E.J., Jr., and Lundblad, E.G. (1987) Premenstrual syndrome: beneficial effects of periodic, low-dose danazol. Obstet. Gynecol. 70(1):33–36. Schechter, D., Strasser, T.J., Endicott, J., Petkova, E., and Nee, J. (1996) Role of ovarian steroids in modulating mood in premenstrual syndrome. Abstracts of the Society of Biological Psychiatry 51st Annual Meeting 39:646. Schmidt, P.J., Grover, G.N., Roy-Byrne, P.P., and Rubinow, D.R. (1993) Thyroid function in women with premenstrual syndrome. J. Clin. Endocrinol. Metab. 76(3):671– 674. Schmidt, P.J., Nieman, L.K., Danaceau, M.A., Adams, L.F., and Rubinow, D.R. (1998) Differential behavioral effects of gonadal steroids in women with and in those without premenstrual syndrome. N. Eng. J. Med. 338(4):209–216. Schmidt, P.J., Nieman, L.K., Grover, G.N., Muller, K.L., Merriam, G.R., and Rubinow, D.R. (1991) Lack of effect of induced menses on symptoms in women with premenstrual syndrome. N. Eng. J. Med. 324(17):1174–1179. Schmidt, P.J., Purdy, R.H., Moore, P.H., Jr., Paul, S.M., and Rubinow, D.R. (1994) Circulating levels of anxiolytic steroids in the luteal phase in women with premenstrual syndrome and in control subjects. J. Clin. Endocrinol. Metab. 79(5):1256–1260. Schmidt, P.J., Rosenfeld, D., Muller, K.L., Grover, G.N., and Rubinow, D.R. (1990) A case of autoimmune thyroiditis presenting as menstrual related mood disorder. J. Clin. Psychiatry 51(1): 434 – 436.

554

MOOD DISORDERS

Shen, H., et al. (2007) Reversal of neurosteroid effects at a4ß2d GABAa receptors triggers anxiety at puberty. Nat. Neurosci. 10(4):469–477. Shen, H., Gong, Q.H., Yuan, M., and Smith, S.S. (2005) Short-term steroid treatment increases delta GABA(A) receptor subunit expression in rat CA1 hippocampus: pharmacological and behavioral effects. Neuropharmacology 49(5):573–586. Sherwood, R.A., Rocks, B.F., Stewart, A., and Saxton, R.S. (1986) Magnesium and the premenstrual syndrome. Ann. Clin. Biochem. 23:667–670. Shughrue, P.J., Lane, M.V., and Merchenthaler, I. (1997) Comparative distribution of estrogen receptor-a and -b mRNA in the rat central nervous system. J. Comp. Neurol. 388:507–525. Simoncini, T., Hafezi-Moghadam, A., Brazil, D.P., Ley, K., Chin, W.W., and Liao, J.K. (2000) Interaction of oestrogen receptor with the regulatory subunit of phyosphatidylinositol-3-OH-kinase. Nature 407(6803):538–541. Singer, C.A., Rogers, K.L., Strickland, T.M., and Dorsa, D.M. (1996) Estrogen protects primary cortical neurons from glutamate toxicity. Neurosci. Lett. 212(1):13–16. Singh, M., Setalo, G., Jr., Guan, X., Frail, D.E., and Toran-Allerand, C.D. (2000) Estrogen-induced activation of the mitogenactivated protein kinase cascade in the cerebral cortex of estrogen receptor-alpha knock-out mice. J. Neurosci. 20(5):1694–1700. Smith, C.L., Nauaz, Z., and O’Malley, B.W. (1997) Co-activator and co-repressor regulation of the agonist/antagonist activity of the mixed antiestrogen, 4-hydroxytamoxifen. Mol. Endocrinol. 11(6):657–666. Smith, M.J., Adams, L.F., Schmidt, P.J., Rubinow, D.R., and Wassermann, E.M. (2002) Effects of ovarian hormone on human cortical excitability. Ann. Neurol. 51(5):599–603. Smith, M.J., Adams, L.F., Schmidt, P.J., Rubinow, D.R., and Wassermann, E.M. (2003) Abnormal luteal phase excitability of the motor cortex in women with premenstrual syndrome. Biol. Psychiatry 54(7):757–762. Smith, S.S., Gong, Q.H., Hsu, F.-C., Markowitz, R.S., French-Mullen, J.M.H., and Li, X. (1998) GABAA receptor alpha-4 subunit suppression prevents withdrawal properties of an endogenous steroid. Nature 392(6679):926–930. Smith, S.S., Gong, Q.H., Li, X., et al. (1998) Withdrawal from 3aOH-5a-pregnan-20-one using a pseudopregnancy model alters the kinetics of hippocampal GABAA-gated current and increases the GABAA receptor a4 subunit in association with increased anxiety. J. Neurosci. 18(14):5275–5284. Spearow, J.L., Doemeny, P., Sera, R., Leffler, R., and Barkley, M. (1999) Genetic variation in susceptibility to endocrine disruption by estrogen in mice. Science 285(5431):1259–1261. Steiner, M., Haskett, R.F., Carroll, B.J., Hays, S.E., and Rubin, R.T. (1984) Plasma prolactin and severe premenstrual tension. Psychoneuroendocrinology 9(1):29–35. Stone, A.B., Pearlstein, T.B., and Brown, W.A. (1990) Fluoxetine in the treatment of premenstrual syndrome. Psychopharmacol. Bull. 26:331–335. Ströhle, A., et al. (1999) Concentrations of 3 alpha-reduced neuroactive steroids and their precursors in plasma of patients with major depression and after clinical recovery. Biol. Psychiatry 45(3):274–277. Su, T.-P., Schmidt, P.J., Danaceau, M., Murphy, D.L., and Rubinow, D.R. (1997) Effect of menstrual cycle phase on neuroendocrine and behavioral responses to the serotonin agonist m-chlorophenylpiperazine in women with premenstrual syndrome and controls. J. Clin. Endocrinol. Metab. 82(4):1220–1228. Sundstrom, I., and Backstrom, T. (1998a) Citalopram increases pregnanolone sensitivity in patients with premenstrual syndrome: an open trial. Psychoneuroendocrinology 23(1):73–88.

Sundstrom, I., and Backstrom, T. (1998b) Patients with premenstrual syndrome have decreased saccadic eye velocity compared to control subjects. Biol. Psychiatry 44(8):755–764. Sundstrom, I., Nyberg, S., and Backstrom, T. (1997) Patients with premenstrual syndrome have reduced sensitivity to midazolam compared to control subjects. Neuropsychopharmacology 17(6): 370–381. Szego, C.M., and Davis, J.S. (1967) Adenosine 3', 5'-monophosphate in rat uterus: acute elevation by estrogen. Proc. Natl. Acad. Sci. USA 58:1711–1718. Toran-Allerand, C.D. (1994). Developmental interactions of estrogens with the neurotrophins and their receptors. In: Micevych, P., and Hammer, R.P., eds. Neurobiological Effects of Sex Steroid Hormones. Cambridge, UK: Cambridge University Press, pp. 391– 411. Toran-Allerand, C.D., et al. (2002) ER-X: a novel, plasma membrane-associated, putative estrogen receptor that is regulated during development and after ischemic brain injury. J. Neurosci. 22(19):8391–8401. Toran-Allerand, C.D., Singh, M., and Setalo, G., Jr. (1999) Novel mechanisms of estrogen action in the brain: new players in an old story. Front. Neuroendocrinol. 20(2):97–121. Tulenheimo, A., Laatikainen, T., and Salminen, K. (1987) Plasma b-endorphin immunoreactivity in premenstrual tension. Br. J. Obstet. Gynaecol. 94(1):26–29. Uht, R.M., Anderson, C.M., Webb, P., and Kushner, P.J. (1997) Transcriptional activities of estrogen and glucocorticoid receptors are functionally integrated at the AP-1 response element. Endocrinology 138(7):2900–2908. Uzunova, V., et al. (1998) Increase in the cerebrospinal fluid content of neurosteroids in patients with unipolar major depression who are receiving fluoxetine or fluvoxamine. Proc. Natl. Acad. Sci. USA 95:3239–3244. Veeninga, A.T., and Westenberg, H.G.M. (1992) Serotonergic function and late luteal phase dysphoric disorder. Psychopharmacology (Berl) 108(1/2):153–158. Wang, M., Seippel, L., Purdy, R.H., and Bäckström, T. (1996) Relationship between symptom severity and steroid variation in women with premenstrual syndrome: study on serum pregnenolone, pregnenolone sulfate, 5a-pregnane-3,20-dione and 3a-hydroxy-5apregnan-20-one. J. Clin. Endocrinol. Metab. 81:1076–1082. Wang-Gohrke, S., Chang-Claude, J., Becher, H., Kieback, D.G., and Runnebaum, I.B. (2000) Progesterone receptor gene polymorphism is associated with decreased risk for breast cancer by age 50. Cancer Res. 60(9):2348–2350. Watters, J.J., Campbell, J.S., Cunningham, M.J., Krebs, E.G., and Dorsa D.M. (1997) Rapid membrane effects of steroids in neuroblastoma cells: effects of estrogen on mitogen activated protein kinase signaling cascade and c-fos immediate early gene transcription. Endocrinology 138:4030– 4033. Wieland, S., Lan, N.C., Mirasedeghi, S., and Gee, K.W. (1991) Anxiolytic activity of the progesterone metabolite 5a-pregnan-3a-olone. Brain Res. 27:263–268. Wissink, S., van der Burg, B., Katzenellenbogen, B.S., and van der Saag, P.T. (2001) Synergistic activation of the serotonin-1A receptor by nuclear factor-kappaB and estrogen. Mol. Endocrinol. 15(4):543–552. Wong, M., and Moss, R.L. (1992) Long-term and short-term electrophysiological effects of estrogen on the synaptic properties of hippocampal CA1 neurons. J. Neurosci. 12(8):3217–3225. Wyckoff, M.H., et al. (2001) Plasma membrane estrogen receptors are coupled to endothelial nitric-oxide synthase through Gai. J. Biol. Chem. 279(29):27071–27076. Yonkers, K.A., Brown, C., Pearlstein, T.B., Foegh, M., SampsonLanders, C., and Rapkin, A. (2005) Efficacy of a new low-dose

35: THE NEUROBIOLOGY OF MENSTRUAL CYCLE-RELATED MOOD DISORDERS oral contraceptive with drospirenone in premenstrual dysphoric disorder. Obstet. Gynecol. 106(3):492–501. Zhang, J.X., Labaree, D.C., Mor, G., and Hochberg, R.B. (2004) Estrogen to antiestrogen with a single methylene group resulting in an unusual steroidal selective estrogen receptor modulator. J. Clin. Endocrinol. Metab. 89:3527–3535. Zhang, L., et al. (2001) Estrogen protects against beta-amyloidinduced neurotoxicity in rat hippocampal neurons by activation of Akt. Neuroreport 12(9):1919–1923. Zhang, L., et al. (2002) Sex-related differences in MAPKs activationin rat astrocytes: effects of estrogen on cell death. Mol. Brain Res. 103(1/2):1–11.

555

Zhang, L., et al. (2005) Direct binding of estradiol enhances Slack (sequence like a calcium-activated potassium channel) channels’ activity. Neuroscience 131(2):275–282. Zhang, L., Ma, W., Barker, J.L., and Rubinow, D.R. (1999) Sex differences in expression of serotonin receptors (subtypes 1A and 2A) in rat brain: a possible role of testosterone. Neuroscience 94(1):251–259.

36 Depression and Medical Illness TAMI D. BENTON, PAUL CRITS-CHRISTOPH, BENOIT DUBÉ, A N D

DWIGHT L. EVANS

Depression continues to threaten the health and wellbeing of individuals worldwide. Current prevalence estimates of major depressive disorder and dysthymia suggest that 16.6% of individuals will experience a depressive episode during their lifetimes (Kessler et al., 2005). The World Health Organization projected that depression will remain a leading cause of disability by the year 2020, second only to cardiovascular disease (Michaud et al., 2001). Depression is much more prevalent among those with medical conditions when compared to the general population of the United States (Patten, 2001; Egede, 2007) and is associated with higher health care costs, adverse health behaviors, significant functional impairment, lost work productivity, occupational disability, and increased health care utilization (Katon, 2003). Moreover, a growing body of evidence suggests that depression may be a cause or consequence of some medical illnesses, such as cardiovascular disease, human immunodeficiency virus/ acquired immunodeficiency syndrome (HIV/AIDS), cancer, epilepsy, and stroke (Evans and Charney, 2003). Depression makes everything worse. Increased efforts to understand the comorbidity between medical illnesses and depression have now prompted investigators to search for potential shared etiological mechanisms that might explain the higher comorbidity between medical illnesses and depression (Evans et al., 2005). This research has identified the potential role of inflammatory responses in the pathophysiology of depression, finding higher levels of pro-inflammatory cytokines, acute phase proteins, chemokines, and cellular adhesion molecules (Raison et al., 2006). In this chapter, we provide an overview of the relevant recent research linking depression and medical illness. We first present an overview of the link between depression and medical illness in general, beginning with epidemiological studies. This is followed by review of research on the possible mechanism for the connection between depression and medical illness, highlighting the role of the immune system and research on sickness behaviors. The nature of the connection between depression and several specific medical illnesses in humans (cardiac disease, cancer, HIV/AIDS) is then 556

explored. We then outline basics of the assessment of depression in the context of medical illness. We conclude with a presentation of treatment considerations for depression in specific medically ill populations. PREVALENCE OF DEPRESSION IN THE MEDICALLY ILL Major depressive disorder (MDD) is a common medical disorder with an average lifetime prevalence of about 16.6% of the U.S. population and is 2 times more prevalent in women when compared to men (Kessler et al., 2005; Wang et al., 2005). Depressive disorders are even more prevalent among the medically ill when compared to the general population of the United States (Egede, 2007). The prevalence of depression among individuals who are medically ill increases as one moves along the continuum from community settings (3%–5%) to primary care settings (5%–10%) to inpatient medical settings (10%–14%) (Katon, 2003). Prevalence estimates for depressive disorders among those populations with specific medical conditions are even higher, ranging from 20%–55% (Evans et al., 2005). Mechanisms of Comorbidity Although a considerable body of evidence supports the relationship between depression and medical illnesses, the mechanisms mediating these relationships remain unclear. Recent research efforts, prompted in part by the high prevalence of depression among medically ill populations such as those with diabetes, cancer, and cardiovascular disease (Table 36.1), have sought to link the known inflammatory processes underlying these disorders to that of major depression. In fact, recent evidence suggests that depressive disorders may be characterized as conditions of immune activation (Wellens and Ridker, 2004; Wellens and Hotamisligil, 2005). These theories have been based upon the observations that the treatment of patients with cytokines can produce symptoms of depression, that immune system activation is present in some individuals with depression, and that depression occurs more frequently in those indi-

36: DEPRESSION AND MEDICAL ILLNESS

36.1 Depression in Patients with Comorbid Medical Illness

TABLE

Comorbid Medical Illness

Prevalence Rate (%)

Cardiac disease

17–27 (Rudisch and Nemeroff, 2003)

Cerebrovascular disease

14–19 (Robinson, 2003)

Alzheimer’s disease

30–50 (H.B. Lee and Lyketsos, 2003)

Parkinson’s disease

4–75 (McDonald et al., 2003)

Epilepsy Recurrent

20–55 (Kanner, 2003)

Controlled

3–9 (Kanner, 2003)

Diabetes Self-reported

26 (Anderson et al., 2001)

Diagnostic interview

9 (Anderson et al., 2001)

Cancer

22–29 (Raison and Miller, 2003)

HIV/AIDS

5–20 (Cruess et al., 2003)

Pain

30–54 (Campbell et al., 2003)

Obesity

20–30

General population

10.3 (Kessler et al., 1994)

AIDS = acquired immunodeficiency syndrome; HIV = human immunodeficiency virus. Adapted from Evans et al., 2005, with permission.

viduals with medical disorders associated with immune dysfunction. Furthermore, immune activation can be induced in animals by the administration of specific endotoxins and cytokines, producing a sickness behavior in animals that resembles that of humans with major depression, and chronic antidepressant treatment can inhibit sickness behaviors in humans who are depressed. Additionally, certain cytokines activate cerebral noradernergic and serotonergic systems that have been implicated in major depressive illness and its treatment (Dunn et al., 2005). Recent investigations of inflammatory processes as potential contributors to the pathogenesis of major depression represent a significant shift in the conceptualization of depression. Central to these theories is the role of cytokines. Cytokines are proteins and glycoproteins secreted by immune cells that function as signals among and between immune cells. Cytokines are the hormones of the immune system. They can be secreted by immune and nonimmune cells and can affect cells outside of the immune system. They function locally and systemically to modulate and regulate immune functions throughout the body, including those of the central nervous system. The role of cytokines in the pathogenesis of depression has been suggested by clinical and experimental observations. Cytokines have been shown to be effective in the treatment of certain cancers, hepatitis C, viral infections, and multiple sclerosis. Moreover, individuals treated with cytokines for the treatment of infectious

557

diseases or cancer have been observed to develop a behavioral syndrome referred to as the “sickness syndrome” that is very similar to major depression. This syndrome is characterized by anhedonia, cognitive dysfunction, anxiety, irritability, psychomotor slowing, anergia, fatigue, anorexia, sleep alterations, and increased sensitivity to pain (Dunn et al., 1999; Yirmiya et al., 1999; de Beaurepaire et al., 2005). Although the exact prevalence is unknown, studies suggest that the incidence of depression associated with cytokine therapy ranges from 0%– 45%, depending upon the medical conditions and study designs. Moreover, the behavioral syndrome induced by cytokine treatment has been shown to be responsive to treatment with standard antidepressant medications, suggesting that the behaviors described as the “sickness syndrome” are related to major depression. However, antidepressant treatment has been noted to be more effective on the mood symptoms than on neurovegetative symptoms (Miyoka et al., 1999; Musselman, Lawson, et al., 2001; Capuron et al., 2002). Sickness Behaviors in Animals Investigators have sought to understand the observed immune abnormalities in individuals with depression for more than 30 years (Weisse, 1992). Some early studies suggested increased immune activation in individuals with depression (Kronfol, 2002). The observations by investigators using animal models that immune challenge produced a syndrome in animals similar to depression in adults provided further evidence for a relationship between depression and immunity. These behavioral observations in animals, called “sickness behaviors,” are characterized by decreases in feeding, exploration and sexual activities, and increases in sleep and body temperature. These changes were thought to be protective, to facilitate recovery, and to protect the animal during illness. It was also recognized that sickness behavior could be induced in animals by administering endotoxin and interleukin-1 (IL-1) (Hart, 1988), suggesting that these symptoms might be effectively treated with cytokine antagonists (Kent et al., 1992). R.S. Smith (1991) posited a macrophage theory of depression in an attempt to explain the relationship between sickness behavior and depression, suggesting that the IL-1 secreted by macrophages caused depression. These early efforts to link theories of depression and inflammation have stimulated much investigation and information about sickness behaviors in animals and depression in humans. Although the analogies between sickness behaviors and depression are not perfect, they are informative and useful for understanding the potential relationships between inflammation and depression (R.S. Smith, 1991; Maes et al., 1993). Studies utilizing animal models to test the effect of cytokines on behavior using IL-1 and the endotoxin

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lipopolysaccharide (LPS), a potent stimulator of the proinflammatory cytokines IL1, IL6, tumor necrosis factor alpha (TNF-) and interferon gamma (IFN-g ), have yielded the following results: 1. IL1 and LPS induce sickness behaviors (Kent et al., 1992; Dantzer, 2001; Larson and Dunn, 2001). 2. IFN-a produces some mild behavioral changes but not sickness syndrome, fever or hypothalamic-pituitaryadrenal (HPA) axis activation (Valentine et al., 1998). 3. LPS and IL-1 induce a hypersensitivity to pain (Watkins et al., 1994). 4. IL-1, LPS, and infections decrease feeding and result in weight loss (Swiergiel et al., 1997). 5. IL1 and LPS increase slow-wave sleep time (Krueger et al., 2003). The suggested similarities between sickness behaviors and depression are further supported by reported efficacy of antidepressants in the treatments of sickness behaviors in animals. Yirmiya (1996), using rats, studied the effects of LPS-induced sickness behavior and its response to antidepressant treatment. In an experiment designed to test depression using anhedonia as a proxy, a saccharin solution was used as a reward each time the animals pressed a bar. The rats in this experiment pressed the bar for the release of the reward (saccharin) much less frequently after administration of LPS. The same rats were then treated for 3–5 weeks with imipramine, resulting in the inhibition of anhedonia in the LPS-treated rats (Yirmiya, 1996). These results were replicated by other investigators using desmethylimipramine (Shen et al., 1999) and fluoxetine (Yirmiya et al., 2001), although the fluoxetine effect was less robust. Studies using paroxetine and venlafaxine have not demonstrated the same effect (Shen et al., 1999). These same experiments were carried out with mice; however, similar effects were not evident in mice (Yirmiya et al., 1999; Dunn and Swiergel, 2001). These studies suggest that the effects of chronic antidepressant treatments are observed most often with LPS and less so with IL1 in rats, but not in mice. Cytokine Theory of Depression The hypothesis that pro-inflammatory cytokines play a key role in depression has been generated by the above findings and others suggesting that immune abnormalities might contribute to depression. Several studies comparing cytokines in people with MDD have found increases in certain cytokines compared to people without MDD (Anisman et al., 2005; K.M. Lee and Kim, 2006; Pavon et al., 2006). Although association does not mean causality, there are many reasons to believe that the abnormalities of inflammation found in depression may contribute to its pathology. Patients who are medically ill who exhibit immune activation or inflammation second-

ary to infections, autoimmune diseases (Minden and Schiffer, 1990; Dickens et al., 2002), and neoplastic diseases demonstrate higher rates of depression. Additionally, the use of cytokines for treatments of infections or neoplasms induces behavioral changes, including a depressive syndrome. Cytokines have also been found to influence all of the pathophysiologic domains relevant to depression. Cytokines have been shown to cause alterations in the metabolism of monoamine neurotransmitters relevant to depression, specifically serotonin, dopamine (DA), and norepinephrine (NE) (Szabo et al., 2004); to have stimulatory effects on HPA axis functioning through activation of corticotropin-releasing hormone (CRH) in the amygdala and the hypothalamus; to induce resistance of nervous, endocrine, and immune system tissues to circulating glucocorticoid hormones stimulating the glucocorticoid resistance found in patients with depression; to induce enzymes that metabolize tryptophan, the primary precursor of serotonin, and may inhibit pathways involved in thyroid hormone metabolism and to activate NF-κB, a transcription factor that signals the inflammatory cascade, in the brain (Irwin and Miller, 2007). DEPRESSION IN MEDICAL ILLNESS Early investigations suggested the presence of defective immune functioning in individuals with depression (Weisse, 1992), and that the defects might place them at risk for certain medical illnesses. Additionally, several large epidemiologic studies suggest that prior episodes of major depression may be an important risk factor for the development of some medical illnesses such as coronary artery disease and diabetes (Eaton et al., 1996). Recent theories suggest that individuals with depression and who are medically healthy have activated inflammatory pathways manifested by increased proinflammatory cytokines, increased acute phase proteins, increased chemokines, and adhesion molecules (Danner et al., 2003; Tiemeier et al., 2003; Alesci et al., 2005). This association between depression and inflammation remains evident even in the context of mild depressive symptoms (Suarez et al., 2004). If, as suggested, immune activation is the direct cause of depression, then depression should be more prevalent in disease states characterized by chronic inflammation. Indeed, depression has been reported to be more common in some inflammatory illnesses such as multiple sclerosis (MS) (Minden and Schiffer, 1990), allergy (Marshall and Colon, 1993), and rheumatoid arthritis (Dickens et al., 2002). Depression and depressive symptoms have also been associated with inflammatory markers in cardiovascular disease (Lesperance et al., 2004; Miller et al., 2005) and cancer (Musselman, Miller, et al., 2001; Bower et al., 2002; Meyers et al., 2005).

36: DEPRESSION AND MEDICAL ILLNESS TABLE

559

36.2 Screening Tools Used for Depression in Patients Who Are Medically Ill

Instrument

Description

Advantage/Disadvantage

Center for Epidemiological Studies Depression Scale (CES-D; Radloff, 1977)

20-item self-report instrument of which only four are somatic; recommended cutoff score of 17

The Hospital Anxiety and Depression Scale (HADS; Zigmond and Snaith, 1983)

14-item self-report with separate 7-item subscale for depression and anxiety

Wide use in patients who are medically ill High sensitivity and specificity Lack of consensus on optimal cut scores Positive predictive value low

Cutoff scores range from 7–21 Beck Depression Inventory–II (BDI-II; Beck et al., 1996)

21-item self-report measure Cutoff scores: 10 - mild; 20 - moderate; 30 - severe

Brief and highly acceptable to patients Not extensively validated as a screen Lack of consensus about utility of cutoff scores Validated as an accurate self-report measure in patients who are medically ill Less acceptable to patients due to forced-choice format and complex response alternatives Sensitivity and specificity high and positive predictive value high

The Patient Health Questionnaire–9 (PHQ-9; Kroenke et al., 2002)

9-item self-report depression module of the PHQ Cutoff Scores: 5 - mild; 10 - moderate; 15 - moderately severe; 20 - severe

Zung Self-Rating Scale for Depression (Zung, 1965)

20-item self-report Likert-type scale scores 1– 4 with highest possible score of 80

Full PHQ well validated in primary care/medical specialty clinics in United States, Europe, and China Good sensitivity and specificity Validated as an accurate self-report measure in patients who are medically ill Good sensitivity and specificity

Cutoff scores: > 50 for depression Hamilton Depression Rating Scale (Hamilton, 1960)

17-item scale; Clinician administered Cutoff: 10–13 mild; 14 –17 moderate; > 17 severe

Validated as an accurate measure in patients who are medically ill Good treatment change measure High specificity and sensitivity

Although a relatively large evidence base supports the idea that dysregulation of the immune system may contribute to the pathogenesis of major depression, other studies have found conflicting results or no association between depression and immune parameters or inflammation (Haack et al., 1999; Steptoe et al., 2003; Whooley et al., 2007). As suggested by Glassman and Miller (2007), some negative studies are to be expected and those negative studies do not cancel out multiple positive ones. Another factor that might explain variation between studies is the type of immune system variable or inflammatory marker examined. Along these lines, Pike and Irwin (2006) found that, among patients with MDD relative to controls, there was evidence for decreases in NK cell activity (indicating impairment in the immune system) and higher levels of IL-6 (indicating immune activation). Furthermore, changes in NK cell activity were uncorrelated with levels of IL-6. Thus, depression may have independent effects on these different aspects of the immune system. Cardiac Disease A relatively large body of literature has established that there is an intimate connection between depression

and cardiovascular disease. Prevalence rates of depression among individuals with coronary artery disease (CAD) (including those with unstable angina, acute myocardial infarction, congestive heart failure, and coronary artery bypass graft surgery) are significantly higher than in the general population, ranging from 17%–27% (Rudish and Nemeroff, 2003). When depressive symptoms are present, the risk for onset of CAD is increased by 1.64-fold (95% confidence interval [CI], 1.41–1.90) (Wulsin, 2004). If an episode of MDD occurs in the 3– 4 months following a myocardial infarction (MI), the likelihood of dying in the next year is more than 3 times greater than that observed when no episode of MDD has occurred (Lett et al., 2004). The connection between depression and cardiac disease does not appear to be due to the association between depression and other known risk factors (for example, smoking, history of MI).Thus, depression appears to be an independent cardiac risk factor. For example, depression has been found to be a significant predictor of mortality 6 and 18 months following MI, even after adjusting for other risk factors such as left ventricular dysfunction and previous MI (Frasure-Smith et al., 1993, 1995).

560

MOOD DISORDERS

Depression also affects the outcome of cardiac surgery. In the one year following coronary artery bypass graft (CABG), the presence of depression is associated with recurrence of cardiac events (Connerney et al., 2001). Another study found that moderate to severe depressive symptoms on the day prior to surgery, or mild depression persisting from baseline to 6-month follow-up after surgery, were associated with increased mortality rates over the next 5 years. Mechanisms of comorbidity Emerging evidence points to several possible mechanisms linking depression to cardiovascular diseases. These include hypothalamic-pituitary-adrenocortical and sympathomedullary hyperactivity, platelet mechanisms, inflammation, and reduced heart rate variability (HRV) (Musselman et al., 1998; Skala et al., 2006). Early studies documented HPA axis dysregulation in depression (Nemeroff, 1996; Wulsin, 2004). It is also well known that the administration of corticosteroids is associated with increases in cardiovascular disease risk factors, including hypercholesterolemia, hypertriglyceridemia, and hypertension (Musselman et al., 1998). Consistent with this potential mechanism, elevated plasma cortisol has been found to be associated with moderate to severe coronary atherosclerosis in young and middleaged men (Troxler et al., 1977). Sympathoadrenal hyperactivity may also influence platelets. Individuals with depression show increased levels of plasma NE in response to cold or orthostatic challenge (Roy et al., 1987), and such stressors may enhance platelet activity (Markovitz and Matthews, 1991; Anfossi and Tovati, 1996). Increased platelet activity has been found in those with MDD (Musselman et al., 1996). Moreover, patients with depression and with ischemic heart disease show elevated platelet factor 4 and plasma b -thromboglobulin levels (Laghrissi-Thode et al., 1997; Kuipers et al., 2002). We reviewed in the previous section on depression and medical illness the literature proposing inflammatory processes, particularly the role of cytokines, as potential contributors to the pathogenesis of MDD. But inflammatory cytokines have also been found to be elevated in patients with CAD, and the extent of elevation of specific markers such as IL-6, TNF-a and C reactive protein (CRP), are directly associated with coronary and cerebrovascular disease events and progression of heart failure (Cesari et al., 2003; Shapiro, 2005). Increases in circulating levels of IL-6 and CRP are also found in depression (Miller et al., 2002). Two recent studies have provided further pieces of the puzzle linking inflammation, depression, and CAD. In one small, carefully controlled study examining the relationships between depression and inflammation, Kling and colleagues (2007) examined CRP and serum amyloid A (SAA) in a group of 18 unmedicated women with ma-

jor depression in remission compared to 18 body mass index (BMI) matched healthy controls. Serum amyloid A was increased significantly and on average by 86% in the remitted unmedicated groups, and serum CRP was increased significantly and by an average of almost threefold when compared to controls. Their findings suggest a sustained pro-inflammatory state in women who have clinically recovered and who no longer take antidepressant medications. The authors suggest that the persistence of this pro-inflammatory state might contribute to the increased CAD risk associated with MDD. In the second recent study examining the relationship between depression and coronary events, FrasureSmith and colleagues (Frasure-Smith, et al., 2007) assessed 702 individuals (602 men) for depression and inflammatory markers (CRP), IL-6, and soluble adhesion molecules at 2 months postdischarge for an acute coronary syndrome, and then followed them for 2 years for major adverse cardiac events defined as cardiac death, survived MI or cardiac arrest, and nonelective revascularization. Of this sample, 102 individuals (78 men) experienced at least one major adverse cardiac event. Elevated scores on the Beck Depression Inventory–II > 14 (BDI-II) and current major depression were significantly related to major adverse coronary events over 2 years, and this association was stronger in men than women. The study also found an association between elevated depressive symptoms, CRP, and soluble intercellular adhesion molecules (sICAM-1), but not IL-6, providing support for the association of depression and inflammation (Frasure-Smith et al., 2007). Another possible mechanism linking depression and CAD may be HRV, a measure of the balance between sympathetic and parasympathetic inputs to the cardiac conduction system. In healthy individuals with good cardiac function, a high degree of HRV is typically observed. Patients with severe CAD or heart failure often have significantly decreased HRV (Richardson et al., 1996). Reduced HRV has been found to contribute to ventricular arrhythmias and sudden cardiac death (Dekker et al., 2000). Studies that found diminished HRV in depression raised the possibility that HRV might be the link between depression and CAD (Rechlin et al., 1994; Stein et al., 2000; Nahsoni et al., 2004; van der Kooy et al., 2006). Indeed, a recent study found that HRV partially mediates the relation between depression and increased risk for mortality after acute myocardial infarction (Carney et al., 2005). Heart rate variability has also been recently found to be associated with increased markers of inflammation in patients with heart failure and acute coronary syndromes (Aronson et al., 2001; Malave et al., 2003; Lanza et al., 2006). In addition to its direct impact on CAD, depression also appears to worsen the impact of other cardiac risk factors. For example, this appears to be true for premature ventricular contractions. A meta-analysis of psychosocial risks for cardiac mortality found that the high-

36: DEPRESSION AND MEDICAL ILLNESS

est death rate (60%) for patients at 18 months post-MI was in a subgroup with elevated depressive symptoms and high levels of premature ventricular contractions (PVCs) (Frasure-Smith et al., 1995). Depression can also indirectly increase the risk of CAD. The pessimism and low energy often found in clinical depression can lead individuals to be less adherent to exercise programs, smoking cessation programs, dietary changes, and pharmacological interventions for CAD (Blumenthal et al., 1982; Camacho et al., 1991; Glazer et al., 2002; Wang et al., 2002; Skala et al., 2006). The lack of adequately addressing these other risk factors will then put the individual with depression at even greater risk for a future cardiac event. Cancer The prevalence of depression is higher among those with cancer than in the general population, potentially substantially so (Evans et al., 1986; Carr et al., 2002; Raison and Miller, 2003). Prevalence estimates, however, vary across malignancy types and disease severity (Raison and Miller, 2003; Evans et al., 2005). Small sample sizes and nonstandardized definitions of depression have also hindered research in this area (Evans et al., 2005). The general range of prevalence estimates for MDD among patients with cancer has been reported to be 1.5%–50% across studies, with an overall rate of 24% (McDaniel et al., 1995). The presence of depression has been associated with a poorer prognosis and increased mortality in patients with cancer (Hermann-Lingen et al., 2001; Faller and Bulzebruck, 2002; Evans et al., 2005). However, like with other medical illnesses, the bidirectionality of the relationship between the medical condition and depression needs to be considered. A number of cancer-related factors, such as stress related to the cancer diagnosis and treatment, cancer medications, nutritional or endocrine disturbances, or brain metastasis, may contribute to the onset of depression (Raison and Nemeroff, 2000; Massie and Greenberg, 2005). Furthermore, as discussed with cardiac disease, patients with depression and cancer might be poorly adherent to treatment regimens or might engage in adverse health behaviors. The other direction of influence—the impact of depression on the course of cancer—has been an increasing focus of research. Although early studies reported depression was associated with immunosuppression, which might increase cancer risk in susceptible individuals (Evans et al., 1992; Herbert and Cohen, 1993; Evans et al., 2005), recent studies suggest that the inflammation associated with the illness may be associated with the onset of depressive symptoms. Recent evidence suggests that release of pro-inflammatory cytokines during tissue damage and destruction and its associated inflammation can have a substantial impact

561

on neurotransmitter function, neuroendocrine function, and behavior resulting in the “sickness syndrome.” The observation that a significant percentage of patients with cancer treated with the cytokine IFN-a develops a behavioral syndrome with similarities to major depression has been an impetus for the recent investigations in this area. Cytokine therapies are well known to cause neurobehavioral symptoms including major depression in up to 50% of patients with cancer undergoing cytokine treatment with IFN-a (Musselman, Lawson, et al., 2001; Capuron et al., 2002) and IL-2 (Capuron et al., 2004). Among patients with cancer, patients with depression and cancer were found to have significantly higher levels of IL-6 compared to patients with cancer and no depression and healthy controls (Musselman, Miller, et al., 2001). More recent studies have found associations between specific depressive symptoms and elevated cytokines; for example, some investigators have found elevated IL-6 concentrations in patients with cancer presenting with fatigue and impaired executive functioning (Collado-Hidalgo et al., 2006). Capuron and colleagues (Capuron et al., 2002; Capuron et al., 2004) and Musselman, Lawson, et al. (2001) have described two distinct behavioral syndromes that occur in individuals who become depressed with cytokine therapies. One syndrome is characterized by depressed mood, anxiety, irritability, and memory and attentional disturbances. This syndrome is reported to occur within the first 3 months of therapy in susceptible individuals (Musselman, Lawson, et al., 2001; Capuron et al., 2002; Capuron et al., 2004). The other syndrome, characterized by the neurovegetative symptoms of fatigue, psychomotor slowing, anorexia, and altered sleep patterns, occurs within the first few weeks of IFN-a therapy and persists at later stages of therapy (Capuron et al., 2002). These two different syndromes are thought to have different responsiveness to antidepressant treatment. The mood and cognitive symptoms were responsive to pretreatment with paroxetine (Capuron et al., 2002) whereas the neurovegetative symptoms were not, suggesting that these systems may have different pathophysiologic pathways. Although depressive symptoms are very responsive to antidepressant treatment, the neurovegetative symptoms described in the “sickness syndrome” have been less responsive to antidepressant treatments, perhaps requiring a different treatment approach (Capuron et al., 2002; Raison and Miller, 2003). HIV/AIDS Early studies of prevalence rates of depression among individuals with HIV/AIDS showed wide variability across studies due to varying methods of assessment of depression, regional variations, and small sample sizes (Smith et al., 1996). In general, however, meta-analyses of these early studies revealed that those with HIV were nearly

562

MOOD DISORDERS

twice as likely to have a diagnosis of major depression compared to individuals who were HIV-negative (Ciesla and Roberts, 2001). Subsequent studies have provided better prevalence estimates, overcoming the limitations of earlier studies. A large-scale study using a national representative probability sample in the United States found that, among individuals who were HIV-positive receiving medical care for HIV, 35% screened positive for MDD and 26.5% screened positive for dysthymia (21% screened positive for both) (Lyketsos et al., 1993). As these diagnoses were based on a brief screening interview, a subsequent article examined only the subset of individuals who had received a full diagnostic interview and reported prevalence rates of 22% for MDD and 5% for dysthymia (Orlando et al., 2002). These rates are still substantially higher than the rates of depressive disorders found in the general population. Rates for men and women who are HIV-positive did not differ in this national study (Lyketsos et al., 1993), although other studies have found that women who were HIVpositive may be particularly susceptible to MDD, with rates of current MDD about 4 times higher in women who are HIV-positive (19.4%) compared to women who were HIV-negative (4.8%) (Morrison et al., 2002). Large-scale studies of depressive disorders among children who are HIV-positive are lacking, but meta-analyses of available small studies estimated the prevalence of a Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) depressive disorder in this population at 25% (Scharko, 2006). The impact of depression on the course and treatment of HIV/AIDS is striking. Clinical depression, elevated levels of depressive symptoms, or general psychological stress are associated with poor adherence to antiretroviral treatment, deterioration in psychosocial functioning, more rapid progression of HIV/AIDS, and higher mortality (Burack et al., 1993; Lyketsos et al., 1993; Evans et al., 1995; Mayne et al., 1996; PageShafer et al., 1996; Patterson et al., 1996; Ickovics et al., 2001; Leserman et al., 2002; Evans et al., 2005). One study of over 2000 women who were HIV-positive followed for 7½ years found that those with chronic depression had 1.7 times greater odds of dying compared to women without depression (Cook et al., 2004). The impact of depression on mortality remained even after controlling for antiretroviral therapy use, mental health treatment, medication adherence, substance abuse, clinical indicators (baseline CD4 count, baseline viral load, baseline HIV symptoms), and demographic factors. It is important to note that the impact of depression on the progression of HIV/AIDS needs to be assessed over a relatively long period of time given the long latency period between infection with the HIV virus and the progression of AIDS. Indeed, studies that examined the impact of depression on HIV over relatively shorter periods of time (6 months to 2 years) have some-

times failed to document an influence (Rabkin et al., 1991; Vedhara et al., 1999).

Mechanisms of HIV effect and depression Although there is evidence supporting a relationship between depression and HIV disease progression, little is known about the mechanisms underlying this relationship. It is possible that poor health habits might explain the relationship between depression and course of HIV/AIDS, but support for the impact of poor health habits on this relationship is lacking (Page-Shafer et al., 1996; Ickovics et al., 2001; Leserman et al., 2002; Leserman, 2003). Disruption of the HPA axis has been investigated as a possible mediator of the depression–immune status relationship in animal and human studies (Friedman and Irwin, 1997; Cupps and Fauci, 2002). Levels of cortisol have been linked to stress and depression in HIV (Gorman et al., 1991), and it is hypothesized that cortisol may influence immune response by altering the profiles of cytokines secreted (Clerici et al., 1997). In addition, NE has been shown to affect HIV replication (Cole et al., 1998). Another possible mediator is the neuropeptide substance P. Studies have found plasma levels of substance P to be higher in persons with HIV, and elevated substance P levels associated with decreased NK cell populations (Ho et al., 1996; Douglas et al., 2001). Depression might affect HIV disease progression by altering the functioning of killer lymphocytes (NK and cytotoxic T-lymphocytes) thereby diminishing host defenses against HIV infection (Ironson et al., 2001; Evans et al., 2002; Leserman, 2003). Consistent with this hypothesis, stressful life events, poor social support, and chronic depression have all been associated with more rapid declines in CD4 lymphocyte counts (Burack et al., 1993; Kemeny and Dean, 1995; Kemeny et al., 1995) and progression to AIDS (Ickovics et al., 2001; Leserman et al., 2002; Leserman, 2003). Depression also has an affect on adherence to HIV treatment regimens. Patients with HIV and depressive disorders have greater difficulty in accessing antiretroviral therapy and adhering to treatment once accessed (Fairfield et al., 1999; Gordillo et al., 1999; Li et al., 2005).

ASSESSMENT OF DEPRESSION IN MEDICAL ILLNESS Many psychological and physical factors can make the diagnosis of depression among those with medical illness challenging for the clinician. The classic signs and symptoms of depressive disorders such as depressed mood, dysphoric affect, fatigue, pain, psychomotor retardation, anorexia, weight loss, cognitive impairment, and insomnia can represent demoralization or the med-

36: DEPRESSION AND MEDICAL ILLNESS

ical illness itself. Thoughts of death or a hastened desire for death is not a reliable sign for depressive disorders in this population but may represent demoralization (Radloff, 1977; Kissane et al., 2001). The loss of ability to experience pleasure in many activities may be the result of physical suffering or disability and not a symptom of depression. Some medical conditions that are progressive, such as cancers and neurological conditions, have depressive symptoms that may change over time due to the illness or treatments for the illness. No standardized approach exists currently for diagnosing depression among the individuals who are medically ill. We continue to rely on the mental status examination and DSM-IV criteria for depression (Evans et al., 2005). Investigators have examined the utility of excluding symptoms that can occur as part of the medical condition and the depressive condition (exclusive approach) versus the more favored inclusive approach that counts all symptoms when making a diagnosis of depression, but the findings have been inconclusive (Newport and Nemeroff, 1998; Raison and Miller, 2003). Fortunately, several well-validated instruments are available to assist the clinician in making the diagnosis of depression in the presence of medical symptoms and in monitoring treatment response (Table 36.2). TREATMENT OF DEPRESSION IN MEDICAL ILLNESS There are a growing number of well-controlled trials examining the efficacy of antidepressant treatments among individuals who are medically ill. This growing body of evidence provides strong support for the effective use of antidepressant medications for the treatment of mood disorders in these populations. The challenge for the clinician is to identify an effective agent and dosing regimen, whose mechanism of action and side-effect profile will not exacerbate the coexisting medical condition. In addition to studies of cardiac disease, HIV/AIDS, and cancer (reviewed below), double-blind, randomized controlled trials have demonstrated the effectiveness of antidepressants in the treatment of depression in individuals with stroke (Anderson and Lauritzen, 1994; Rasmussen et al., 2003), Alzheimer’s disease (Karlsson et al., 2000; Lyketsos et al., 2000), diabetes (Lustman et al., 2000), and MS (Mohr et al., 2001). There is increasing evidence that selective serotonin reuptake inhibitors (SSRIs) in particular not only improve depressive symptoms but also may result in positive effects on the co-occurring medical illness. For example, fluoxetine has been shown to improve glycemic control in patients with diabetes mellitus (Lustman et al., 2000). One caution in the use of SSRI or serotonin norepinephrine reuptake inhibitors (SNRIs) is that under certain circumstances the side effects of these medications may add to the existing physical problems associated

563

with the medical condition. Potentially serious side effects of SSRIs include the syndrome of inappropriate antidiuretic hormone secretion (SIADH) and platelet dysfunction that can lead to bleeding problems (Turner et al., 2007). There is also some evidence that the motor symptoms in Parkinson’s disease can be exacerbated by SSRIs (Richard et al., 1999). An even greater concern is the potential for drug interactions. Patients with serious medical conditions, particularly the elderly, often are receiving multiple medications for their illnesses, elevating the risk of drug interactions. The presence of hepatic disease, for example, may affect metabolism and excretion of SSRIs and significantly alter their pharmacokinetics (Beliles and Stoudemire, 1998). Tricyclic antidepressants (TCAs) are effective in the treatment of depression, and their safety and side-effect profiles are well known. Despite evidence of their efficacy in the treatment of depression among patients with cerebrovascular disease, Alzheimer’s disease, Parkinson’s disease, cancer, HIV/AIDS, epilepsy, chronic pain, and diabetes (Evans et al., 2005), the widespread use of SSRIs and SNRIs has substantially reduced the clinical use of TCAs. Moreover, because TCAs are strong antagonists of cholinergic, histaminic, and a-adrenergic receptors and can affect cardiac conduction, there are concerns about the use of TCAs with some co-occurring medical conditions. Tricyclic antidepressant discontinuation rates as high as one third have been observed in patients who were medically ill because of adverse effects (Popkin et al., 1985; Rabkin, Rabkin, Harrison, and Wagner, 1994). Like TCAs, monoamine oxidase inhibitors (MAOIs) are effective in the treatment of depression but are now less commonly used. The MAOIs, phenelzine and tranyclcypromine, can produce hypertensive reactions following the ingestion of foods containing high levels of tyramine, over-the-counter sympathomimetics, and stimulants. A potentially fatal serotonin syndrome may occur when SSRIs or SNRIs are combined with MAOIs (Bernstein, 1994). Psychostimulants (methylphenidate and dextroamphetamine) have also been used to treat depression in patients with various medical conditions. Limited data, however, support their use in patients who are medically ill. These agents may be useful due to their rapid onset of action in elevating mood, increasing appetite, and diminishing fatigue (Masand, Pickett, and Murray, 1991).

ANTIDEPRESSANT TREATMENTS FOR DEPRESSION IN CARDIAC DISEASE, CANCER, AND HIV Cardiac Disease The treatment of depression in the context of cardiac disease has been an area of great interest due to the well-established relationships between CAD, depression,

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and mortality. Four randomized controlled trials (RCTs) have established the efficacy and safety of antidepressants in the treatment of patients with cardiac disease with depression. In the Sertraline Antidepressant Heart Attack Trial (SADHART) trial (Glassman et al., 2002), 369 patients with major depression after hospitalization for unstable angina or acute MI were randomized to double-blind treatment with sertraline or placebo. The primary goal of the study was to examine the effects of sertraline on depressive symptoms in this population; the trial was not powered to determine effects on morbidity and mortality (that is, only seven deaths occurred during the follow-up period). The results indicated that sertraline was safe and effective for the treatment of depression in patients who were post-MI (Glassman et al., 2002). In addition, sertraline was superior in absolute numerical terms to placebo in the rate of recurrent MI, mortality, heart failure, and angina. Limited data from the SADHART study also suggests a potential cardioprotective effect of sertraline in the treatment of this population, although these data require confirmation by larger prospective trials (Glassman et al., 2002). The second major trial examining antidepressants in cardiac disease was the Enhancing Recovery in Coronary Heart Disease (ENRICHD) trial. In this trial, 2481 patients who were post-MI with depression or low perceived social support were randomized to a 6-month course of either cognitive-behavioral therapy (CBT) or usual care, both of which were supplemented with an SSRI antidepressant (typically sertraline) when indicated. Primary outcomes in these trials were reinfarction rates and mortality; secondary outcomes were measures of depression and social support. No treatment effects were seen in regard to mortality or recurrence of MI. However, the CBT intervention had significantly greater improvements in depression and social support compared to those in the usual care group. There was some evidence that antidepressant treatment had an impact on mortality, but because there was no randomization to antidepressant treatment in this study this effect must be interpreted with caution (Writing Committee for the ENRICHD Investigators, 2003). The third study, the Myocardial Infarction and Depression Intervention Trial (MIND-IT), examined the antidepressant efficacy of an SNRI (mirtazapine) in patients (N = 91) with post-MI depressive disorder. Although no significant difference between drug and placebo was evident on the primary measure of depressive symptoms, there was evidence of a drug effect on several secondary depression measures and global improvement (Honig et al., 2007). The fourth study was the Canadian Cardiac Randomized Evaluation of Antidepressant and Psychotherapy Efficacy (CREATE) project (Lesperance et al., 2007).

In a 2 × 2 design, patients (N = 284) with CAD and depression were randomly assigned to receive 12 weekly sessions of interpersonal psychotherapy (IPT) plus clinical management or clinical management only, and also randomly assigned to the SSRI citalopram or placebo. Citalopram was superior to placebo on the primary measure of depression. There was no evidence of a benefit of IPT over clinical management alone. Taken in total, these trials provide considerable evidence that SSRIs are efficacious in the treatment of depression among those with cardiac disease. However, a positive impact of such depression treatment on the course of cardiac disease has not been clearly established. Cancer A number of antidepressant treatment trials in patients with depression with cancer have demonstrated the effectiveness of TCAs and SSRIs (Evans et al., 1988; Razavi et al., 1996; Holland et al., 1998; Pezella et al., 2001; Roscoe et al., 2005). One small study of major depression among women with breast cancer compared the efficacy of an SSRI (paroxetine) to a TCA (desipramine) but found no difference in efficacy (Musselman et al., 2006). As with the treatment of depression in patients with no cancer, SSRIs are generally preferred over TCAs because of fewer sedative and autonomic side effects. In addition to the SSRIs and TCAs, mirtazapine and mianserin have shown promising results in open trials (Costa et al., 1985; Van Heeringen and Zivkov, 1996; Theobald et al., 2002). Mirtazapine can cause weight gain, which might actually be advantageous in anorexic-cachectic patients with cancer but may be a concern in those already gaining weight from steroids or from chemotherapy (Theobald et al., 2002). SSRIs and the SNRI venlafaxine have been shown to reduce the number and intensity of hot flashes and night sweats in women without depression who become menopausal after chemotherapy for breast cancer or who have a recurrence of vasomotor symptoms when they discontinue hormone replacement therapy (Duffy et al., 1999; Stearns et al., 2000; Loberiza et al., 2002). Psychostimulants (methylphenidate, dextroamphetamine) also are used with patients with cancer to promote a sense of well being, treat depression, decrease fatigue, and improve cognitive function (Rozans et al., 2002) In addition, psychostimulants may be used as adjuvants to potentiate the analgesic effects of opioids and to counteract their sedative effects (Rozans et al., 2002). Another consideration in patients with cancer is depression that can result from certain cancer treatments that activate the immune system. In particular, treatment with IFN-a can cause the onset of new depressive episodes or trigger a recurrence of a recent ep-

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isode. In one study, patients with advanced melanoma who received 12 months of IL-a developed fatigue, anxiety, insomnia, and depression (Kirkwood et al., 2002). In a placebo-controlled trial, the use of an antidepressant (paroxetine) at the time of IFN-a treatment was found to reduce the incidence of depressive episodes and reduce the rate of discontinuation of IFN-a treatment (Musselman, Lawson, et al., 2001). Despite this finding, prophylactic use of antidepressants for patients with cancer is not currently recommended. HIV/AIDS Numerous well-designed studies have supported the effectiveness of TCAs and SSRIs for treating depression in adults with HIV (Rabkin, Rabkin, Harrison, and Wagner, 1994; Rabkin, Rabkin, and Wagner, 1994; Rabkin, Wagner, and Rabkin, 1994; Ferrando et al., 1997; Grassi et al., 1997; Elliot et al., 1998; Zisook et al, 1998; Ferrando et al., 1999; Cruess et al., 2003; Caballero and Nahata, 2005). Head-to-head studies comparing TCAs and SSRIs have shown equal efficacy for both, but, as expected, a less favorable side-effect profile for TCAs. For example, in one placebo-controlled study comparing imipramine, paroxetine, and placebo in 75 individuals who were HIV-positive, the two antidepressants were found to be equally effective when compared to placebo, but the dropout rates due to anticholinergic side effects with imipramine were 48%, compared to 20% with paroxetine and 24% with placebo (Elliot et al., 1998). One small open-label study evaluated the efficacy of three SSRIs (paroxetine, fluoxetine, and sertraline) in individuals who were HIV-seropositive (Ferrando et al., 1997). A substantial (83%) number of individuals reported improvements in depression and somatic symptoms related to HIV disease, but the dropout rate (27%) in this 6-week study was high. Because of the small sample size, the comparative effects of the three SSRIs could not be evaluated. Another small noncontrolled study found that paroxetine improved depressive symptoms among individuals who were HIV-positive with clinical depression (Grassi et al., 1997). Overall, these studies are suggestive of the effectiveness of SSRIs in reducing depressive symptoms in individuals who are HIV-seropositive, although larger placebo-controlled studies are needed. Open trials have also suggested that sustainedrelease bupropion (Theobald et al., 2002) and mirtazapine (Currier et al., 2003) may be useful for the treatment of depression in individuals who are HIV-seropositive. Although no studies have yet examined duloxetine in patients who are HIV-positive, this medication has shown efficacy for the treatment of certain pain conditions, including diabetic peripheral neuropathic pain (Wernicke

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et al., 2006). It is possible that duloxetine might therefore be helpful with the polyneuropathy that occurs in HIV/AIDS, although this hypothesis awaits empirical support. Psychostimulants (methylphenidate and dextroamphetamine) have also been studied in placebo-controlled trials in patients with depression and HIV. There have been two small uncontrolled studies of psychostimulants in the treatment of depression in HIV/AIDS (Fernandez et al., 1995; Wagner et al., 1997), and one small, placebocontrolled study that showed efficacy (Wagner and Rabkin, 2000). Reductions in depressive symptoms as early as 2 weeks after initiating treatment have been reported (Wagner et al., 1997). In another study, among patients who were HIV-positive who also had significant levels of fatigue, methylphenidate and pemoline (another psychostimulant) were found to be significantly superior to placebo in decreasing fatigue, and improvement in fatigue was significantly associated with improved quality of life and decreased levels of depression (Breitbart et al., 2001). Reductions in testosterone levels among individuals with HIV/AIDS can be associated with changes in mood, appetite, and sexual function (Rabkin, Wagner, and Rabkin, 2000). Testosterone supplementation has therefore been examined as one way to improve mood, energy, and sexual function. In one study enrolling symptomatic patients who were HIV-positive, testosterone was significantly better than placebo at restoring libido and energy, alleviating depressed mood, and increasing muscle mass (Rabkin, Ferrando, et al., 2000). The adrenal steroid dehydroepiandrosterone (DHEA) has also been evaluated in an uncontrolled pilot study and appears promising (Rabkin, Wagner, and Rabkin, 2000). As with other medical and nonmedical populations, the choice of an antidepressant agent in patients with HIV must be guided by the potential for drug–drug interactions and potential positive or negative interactions between drug and disease. CONCLUSIONS Depressive disorders are prevalent among those with chronic medical conditions and have been shown to increase symptom burden and functional disability, adversely affect self-care, decrease adherence to treatment, and to decrease quality of life. A considerable body of evidence suggests that depression is associated with immune suppression and immune activation. Depression-associated cellular immune suppression may be a mechanism whereby depression may have an adverse effect on immune-based diseases such as cancer and AIDS. On the other hand, depression-associated immune activation may be a mechanism whereby depres-

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sion may have an adverse effect on diseases such as cardiovascular disease and diabetes. Antidepressant treatments have been effective in the treatment of many of the symptoms of depression in individuals who are medically ill, and the presence of depression should be aggressively identified and targeted, Larger-scale studies are needed to determine if the treatment of depression in individuals who are medically ill might improve overall medical outcomes or prevent disease progression. Further studies may also shed light on the immune mechanisms underlying depression and comorbid medical illness. REFERENCES Alesci, S., Martinez, P.E., Kelkar, S., Ilias, I., Ronsaville, D.S., Listwak, S.J., Licinio, J., Gold, H.K.,Chrousos, G.P., Gold, P.W., and Kling, M.A. (2005) Major depression is associated with significant diurnal elevations in plasma interleukin-6 levels, a shift of its circadian rhythm and loss of physiological complexity in its secretion: clinical implications. J. Clin. Endocrinol. Metab. 90: 1279–1283. American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: APPI. Anderson, G.B.K., and Lauritzen, L. (1994) Effective treatment of poststroke depression with the selective serotonin reuptake inhibitor citalopram. Stroke 25:1099–1104. Anderson, R.L., Clouse, R.E., Freedland, K.E., and Lustman, P.J. (2001) The prevalence of comorbid depression in adults with diabetes; A meta-analysis. Diabetes 24:1069–1078. Anfossi, G., and Tovati, M. (1996) Role of catecholamines in platelet function: pathophysiological and clinical significance. Eur. J. Clin. Invest. 32:643–648. Anisman, H., Merali, Z., Poulter, M.O., and Hayley, S. (2005) Cytokines as a precipitant of depressive illness: animal and human studies. Curr. Pharm. Des. 11:963–972. Aronson, D., Mittleman, M.A., and Burger, A.J. (2001) Interleukin6 levels are inversely correlated with heart rate variability in patients with decompensated heart failure, J. Cardiovasc. Electrophysiol. 12:294 –300. Banki, C.M., Bissette, G., Arato, M., O’Connor, L., Nemeroff, C.B. (1987) Cerebrospinal fluid corticotropin-releasing factor-like immunoreactivity in depression and schizophrenia. Am. J. Psychiatry 144:873–877. Barron, L., and Shapiro, M. (2001) Psychiatric disorders and drug use among human immunodeficiency virus-infected adults in the United States. Archi. Gen. Psychiatry 58:721–728 Beck, A.T., Steer, R., and Brown, G.K. (1996) Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation. Beliles, K., and Stoudemire, A. (1998) Psychopharmacologic treatment of depression in the medically ill. Psychosomatics 39:S2–S19. Bernstein, J.G. (1994) Handbook of Drug Therapy in Psychiatry. St. Louis, MO: Mosby Yearbook Inc. Blumenthal, J.A., Williams, R.S., Wallace, A.G., Williams, R.B., Jr., and Needles, T.L. (1982) Physiological and psychological variables predict compliance to prescribed exercise therapy in patients recovering from myocardial infarction. Psychosom. Med. 44:519– 527. Bower, J.E., Ganz, P.A., Najib, A., and Fahey, J.L. (2002) Fatigue and proinflammatory cytokines activity in breast cancer survivors. Psychosom. Med. 64:604–611. Breitbart, W., Rosenfeld, B., Kaim, M., and Funesti-Esch, J. (2001) A randomized, double-blind, placebo-controlled trial of psycho-

stimulants for the treatment of fatigue in ambulatory patients with human immunodeficiency virus disease. Arch. Intl. Med. 161:411– 420. Burack, J.H., Barrett, D.C., Stall, R.D., Chesney, M.A., Ekstrand, M.L., and Coates, T.J. (1993) Depressive symptoms and CD4 lymphocyte decline among HIV-infected men. JAMA 270:2568– 2573. Caballero, J., and Nahata, M.C. (2005) Use of selective serotoninreuptake inhibitors in the treatment of depression in adults with HIV. Ann. Pharmacother. 39:141–145. Camacho, T.C., Roberts, R.E., Lazarus, N.B., Kaplan, G.A., and Cohen, R.D. (1991) Physical activity and depression: evidence from the Alameda County Study. Am. J. Epidemiol. 134:220–231. Campbell, L.C., Claum, D.J., and Keefe, F.J. (2003) Persistent pain and depression: a biopsychosocial perspective. Biol. Psychiatry 54:399–409. Capuron, L., Gumnick, J.F., Musselman, D.C., Lawson, D.H., Reemsnydira, A., Nemeroff, C.B., and Miller, A.H. (2002) Neurobehavioral effects of interferon-alpha in cancer patients: phenomenology and paroxetine responsiveness of symptom dimensions. Neuropsychopharmacology 26:643–652. Capuron, L., Raison, C.L., Musselman, D.L., Lawson, D.H., Nemeroff, C.B., and Miller, A.H. (2003) Association of HPA axis response to initial injection of interferon-alpha. Am. J. Psychiatry 160:1342–1345. Capuron, L., Ravaud, A., Miller, A.H., and Dantzer, R. (2004) Baseline mood and psychosocial characteristics of patients developing depressive symptoms during interleukin-2 and/or interferonalpha cancer therapy. Brain Behav. Immun. 18:205–213. Carney, R.M., Blumenthal, J.A., Freedland, K.E., Stein, P.K., Howells, W.B., Berkman, L.F., Watkins, L.L., Czajkowski, S.M., Hayana, J., Domitrovich, P.P., and Jaffe, A.S. (2005) Low heart rate variability and the effect of depression on post-myocardial infarction mortality. Arch. Int. Med. 165:1486–1491. Carr, D., Goudas, L., Lawrence, D., Pirl, W., Lau, J., DeVine, D., Litt, M., Kupelnick, B., and Miller, K. (2002) Management of Cancer Symptoms: Pain, Depression and Fatigue (Agency for Healthcare Research and Quality: Evidence Report/Technology Assessment Number 61). Agency for Healthcare Research and Quality, Rockville, MD. Cesari, M., Penninx, B.W.J.H., Newman, A.B., Kritchevsky, S.B., Nieklas, B.J., Sutton-Tyrell, K., Rubin, S.M., Ding, J.Z., Simmonsick, E.M., Harris, T.B., and Pahon, M. (2003) Inflammatory markers and onset of cardiovascular events: results from the health ABC study. Circulation 108:2317–2322. Ciesla, J.A., and Roberts, J.E. (2001) Meta-analysis of the relationship between HIV infection and risk for depressive disorders. Am. J. Psychiatry 158:725–730. Clerici, M., Trabattoni, D., Piconi, S., Fusi, M.L., Ruzzante, S., Clerici, C., and Villa, M.L. (1997) A possible role for the cortisol/anticortisols imbalance in the progression of human immunodeficiency virus. Psychoneuroendocrinology 22:S27–S31. Cole, S.W., Korin, Y.D., Fahey, J.L., and Zack, J.A. (1998) Norepinephrine accelerates HIV replication via protein kinase A dependent effects on cytokine production. J. Immunol. 161:610– 616. Collado-Hidalgo, A., Bower, J.E., Ganz, P.A., Cole, S.W., and Irwin, M.R. (2006) Inflammatory biomarkers for persistent fatigue in breast cancer survivors. Clin. Cancer Res. 12:2759–2766. Connerney, I., Shapiro, P.A., McLaughlin, J.S., Bagiella, E., and Sloan, R.P. (2001) Relation between depression after coronary artery bypass surgery and 12-month outcome: a prospective study. Lancet 358:1766–1771. Cook, J.A., Grey, D., Burke, J., Cohen, M.H., Gurtman, A.C., Richardson, J.L., Wilson, T.E., Young, M.A., and Hessol, N.A. (2004) Depressive symptoms and AIDS-related mortality among a mul-

36: DEPRESSION AND MEDICAL ILLNESS tisite cohort of HIV positive women. Am. J. Pub. Health 94:1133– 1140. Costa, D., Mogos, I., and Toma, T. (1985) Efficacy and safety of mianserin in the treatment of depression in women with cancer. Acta Psychiatr. Scand. 320:85–92. Cruess, D.G., Evans, D.L., Repetto, M.J., Gettes, D., Douglas, S.D., and Petitto, J.M. (2003) Prevalence, diagnosis and pharmacological treatment of mood disorders in HIV disease. Biol. Psychiatry 54:307–316. Cupps, T.R., and Fauci, A.S. (2002) Cortiscosteroid-mediated immunoregulation in man. Immunol. Rev. 65:133–155. Currier, M.B., Molina, G., and Kato, M.A. (2003) A prospective trial of sustained buproprion for depression in HIV-seropositive and AIDS patients. Psychosomatics 44:120–125. Danner, M., Stanislav, V., Abramson, J., and Vaccarino, V. (2003) Association between depression and elevated C-reactive protein. Psychosom. Med. 65:347–356. Dantzer, R. (2001) Cytokine-induced sickness behavior: where do we stand? Brain Behav. Immun. 15:7–24. De Beaurepaire, R., Swiergiel, A.H., and Dunn, A.J. (2005) Neuroimmune mediators: are cytokines mediators of depression? In: Licinio, J., and Wong, M.-L., eds. Biology of Depression: From Novel Insights to Therapeutic Strategies. Weinheim, Germany: Wiley-VCH, pp. 557–581. Dekker, J.M., Crow, R.S., Folsom, A.R., Hannan, P.J., Liao, D., Swenne, C.A., and Shouten, E.G. (2000) Low heart rate variability in a 2-minute rhythm strip predicts risk of coronary heart disease and mortality from several causes: the ARIC Study. Atherosclerosis Risk in Communities. Circulation 102(11):1239–1244. Dickens, C., McGowan, L., Clark-Carter, D., and Creed, F. (2002) Depression in rheumatoid arthritis: a systematic review of the literature with meta-analysis. Psychosom. Med. 64:52–60. Douglas, S.D., Ho, W.Z., Gettes, D.R., Cnaan, A., Zuao, H.G., Leserman, J., Petitto, J.M., Golden, R.N., and Evans, D.L. (2001) Elevated substance P levels in HIV-infected men. AIDS 15:2043–2045. Duffy, L.S., Greenberg, D.B., Younger, J., and Ferraro, M.G. (1999) Iatrogenic acute estrogen deficiency and psychiatric syndromes in breast cancer patients. Psychosomatics 40:304–308. Dunn, A.J., and Swiergiel, A.H. (2001) The reductions in sweetened milk intake induced by interleukin-1 and endotoxin are not prevented by chronic antidepressant treatment. Neuroimmunomodulation 9:163. Dunn, A.J., Swiergiel, A.H., and de Beaurepaire, R. (2005) Cytokines as mediators of depression: what can we learn from animal studies? Neurosci. Biobehav. Rev. 29:891–909. Dunn, A.J., Wang, J., and Ando, T. (1999) Effects of cytokines on cerebral neurotransmission. Comparison with the effects of stress. Adv. Exp. Med. Biol. 461:117–127. Eaton, W., Armenian, H., Gallo, J., Pratt, L., and Ford, D.E. (1996) Depression and risk for onset of type II diabetes. A prospective population based study. Diabetes Care 19:1097–2002. Egede, L.E. (2007) Major depression in individuals with chronic medical disorders: prevalence, correlates and association with health utilization, lost productivity and functional disability. Gen. Hosp. Psychiatry 29:409– 416. Elliot, A.J., Uldall, K.K., Bergam, K., Russo, J., Claypoole, K., and Roy-Bryne, P.P. (1998) Randomized placebo-controlled trial of paroxetine versus imipramine in depressed HIV-positive outpatients. Am. J. Psychiatry 155:367–372. Evans, D.L., and Charney, D.S. (2003) Mood disorders and medical illness: a major public health problem. Biol. Psychiatry 54:177– 180. Evans, D.L., Charney, D.S., Lewis, L., Golden, R.N., Gorman, J.M., Krishnan, K.R.R., Nemeroff, C.B., Bremner, J.D., Carney, R.M., Coyne, J.C., Delong, M.R., Frasure-Smith, N., Glassman, A.H., Gold, P.W., Grant, I., Gwyther, L., Ironson, G., Johnson, R.L.,

567

Kanner, A.M., Katon, W.J., Kaufmann, P.G., Keefe, F.J., Ketter, T., Laughren, T.P., Leserman, J., Lyketsos, C.G., McDonald, W.M., McEwen, B.S., Miller, A.H., Musselman, D., O’Connor, C., Petitto, J.M., Pollock, B.G., Robinson, R.G., Roose, S.P., Rowland, J., Sheline, Y., Sheps, D.S., Simon, G., Spiegel, D., Stunkard, A., Sunderland, T., Tibbits, P., and Valvo, W.J. (2005) Mood disorders in the medically ill: scientific review and recommendations. Biol. Psychiatry 58:175–189. Evans, D.L., Leserman, J., Perkins, D.O., Stern, R.A., Murphy, C., Tamul, K., Liao, D.P., Vanderhost, C.M., Hall, C.D., Folds, J.D., Golden, R.N., and Petitto, J.M. (1995) Stress associated reductions of cytoxic T lymphocytes and natural killer cells in asymptomatic HIV infection. Am. J. Psychiatry 152:543–550. Evans, D.L., McCartney, C.F., Haggerty, J.J., Nemeroff, C.B., Golden, R.N., Simon, J.B., Quade, D., Holmes, V., Droba, M., Mason, G.A., Fowler, W.C., and Raft, D. (1988) Treatment of depression in cancer patients is associated with better life adaptation: a pilot study. Psychosom. Med. 50:72–76. Evans, D.L., McCartney, C.F., Nemeroff, C.B., Raft, D., Quade, D., and Golden, R.N., Haggerty, J.J., Holmes, V., Simon, J.S., Droba, M., Mason, G.A., and Fowler, W.C. (1986) Depression in women treated for gynecological cancer: clinical and neuroendocrine assessment. Am. J. Psychiatry 143:447– 452. Evans, D.L., Petitto, J.M., Golden, R.N., Pederson, C.A., Corrigan, M., Gilmore, J.H., Silva, S.G., Quade, D., and Ozer, H. (1992) Circulating natural killer cell phenotypes in men and women with major depression: relation to cytotoxic activity and severity of depression. Arch. Gen. Psychiatry 49:388–395. Evans, D.L., Ten Have, T., Douglas, S.D., Gettes, D.R., Morrison, M., Chiappini, M.S., Brinker-Spence, P., Job, C., Mercer, D.E., Wang, Y.L., Cruess, D., Dube, B., Dalen, E.A., Brown, T., Bauer, R., and Petitto, J.M. (2002) Association of depression with viral load, CD8 T lymphocytes, and natural killer cells in women with HIV infection. Am. J. Psychiatry 159:1752–1759. Fairfield, K.M., Libman, H., Davis, R.B., Eisenberg, D.M., and Phillips, R.S. (1999) Delays in protease inhibitor use in clinical practice. J. Gen. Intl. Med. 14:395– 401. Faller, H., and Bulzebruck, H. (2002) Coping and survival in lung cancer: A 10-year follow-up. Am. J. Psychiatry 159:2105–2107. Fernandez, F., Levy, J.K., Samley, H.R., Pirozzolo, F.J., Lachar, D., Crowley, J., Adams, S., Ross, B., and Ruiz, P. (1995) Effects of methylphenidate in HIV-related depression: a comparative trial with Desipramine. Int. J. Psychiat. Med. 25:53–67. Ferrando, S.J., Goldman, J.D., and Charness, W. (1997) Selective serotonin reuptake inhibitor treatment of depression in symptomatic HIV infection and AIDS: improvement in affective and somatic symptoms. Gen. Hosp. Psychiatry 19:89–97. Ferrando, S.J., Rabkin, J.G., de Moore, G.M., and Rabkin, R. (1999) Antidepressant treatment of depression in HIV-seropositive women. J. Clin. Psychiatry 60:741–746. Frasure-Smith, N., Irwin, M.R., Suave, C., Lesperance, J., and Theroux, P. (2007) Depression, C-reactive protein and two-year major adverse cardiac events in men after acute coronary syndromes. Biol. Psychiatry 62:302–308. Frasure-Smith, N., Lesperance, F., and Talajic, M. (1993) Depression following myocardial infarction: impact on 6-month survival. JAMA 270:1819–1825. Frasure-Smith, N., Lesperance, F., and Talajic, M. (1995) Depression and 18 month prognosis after myocardial infarction. Circulation 91:999–1005. Friedman, E.M., and Irwin, M.R. (1997) Modulation of immune cell function by the autonomic nervous system. Pharmacol. Thera. 74:27–38. Glassman, A.H., Califf, R.M., and Swedberg, K. (2002) Sertraline treatment of major depression in patients with acute MI or unstable angina. JAMA 288:701–709.

568

MOOD DISORDERS

Glassman, A.H., and Miller, G.E. (2007) Where there is depression, there is inflammation … sometimes! Biol. Psychiatry 62:280–281. Glazer, K.M., Emery, C.F., Frid, D.J., and Banyasz, R.E. (2002) Psychological predictors of adherence and outcomes among patients in cardiac rehabilitation. J. Cardiopulm. Rehab. 22:40–46. Gordillo, V., del Amo, J., Soriano, V., and Gonzalez-Lahorz, J. (1999) Sociodemographic and psychological variables influencing adherence to antiretroviral therapy. AIDS 13:1763–1769. Gorman, J.M., Kertzner, R., Cooper, T., Goetz, R.R., Lagomasino, I., Novacenko, H., Williams, J.B.W., Stern, Y., Mayeux, R., and Ehrhardt, A.A. (1991) Glucocorticoid level and neuropsychiatric symptoms in homosexual men with HIV infection. Am. J. Psychiatry 148:42– 45. Grassi, B., Gambini, O., and Graghentini, I. (1997) Efficacy of paroxetine for treatment of depression in the context of HIV infection. Pharmacotherapy 30:70–71. Haack, M., Hinze-Selch, D., Fenzel, T., Kraus, T., Kuhn, M., Schuld, A., and Pollmacher, T. (1999) Plasma levels of cytokines and soluble cytokine receptors in psychiatric patients upon hospital admission: effects of confounding factors and diagnosis. J. Psychiatric Res. 33:407– 418. Hamilton, M. (1960) A rating scale for depression. J. Neurol Neurosurg Psychiatry 23:56–62. Hart, B.L. (1988) Biological basis of behavior of sick animals. Neurosci. Behav. Rev. 12:123–137. Herbert, T.B., and Cohen, S. (1993) Depression and immunity: A meta-analytic review. Psychol. Bull. 113:472– 486. Herrmann-Lingen, C., Klemme, H., and Meyer, T. (2001) Depressed mood, physician-rated prognosis, and comorbidity as independent predictors of 1-year mortality in consecutive medical inpatients. J. Psychosom. Res. 50:295–301. Ho, W.Z., Cnaan, A., Li, Y.H., Zhao, H.Q., Lee, H.R., Song, L., and Douglas, S.D. (1996) Substance P modulates human immunodeficiency virus replication in human peripheral blood monocyte-derived macrophages. Aids Res. Human Retrov. 12:195– 198. Holland, J.C., Romano, S.J., Heiligenstein, J.H., Tepner, R.G., and Wilson, M.G. (1998) A controlled trial of fluoxetine and desipramine in depressed women with advanced cancer. PsychoOncology 7:291–300. Honig, A., Kuyper, A.M.G., Schene, A.H., Van Melle, J.P., DeJonge, P., Tulner, D.M., Schins, A., Crijns, H.J.G.M., Kuijpers, P.M.J.C., Vossen, H., Lousbereg, R., and Ormel, J. (2007) Treatment of postmyocardial infarction depressive disorder: a randomized, placebocontrolled trial with mirtazapine. Psychosom. Med. 69:606– 613. Ickovics, J.R., Hamburger, M.E., Vlahov, D., Schoenbaum, E.E., Schuman, P., Boland, R.J., Moore, J., HIV Epidemiology Research Study. (2001) CD4 cell count decline and depressive symptoms among HIV seropositive women: longitudinal analysis from the HIV Epidemiology Research study. JAMA 285:1466– 1474. Ironson, G., Balbin, E., Solomon, G., Fahey, J., Klimas, N., Schneiderman, N., and Fletcher, M.A. (2001) Relative preservation of natural killer cell cytoxicity and number in healthy AIDS patients with low CD4 counts. AIDS 15:2065–2073. Irwin, M.R., and Miller, A.H. (2007) Depressive disorders and immunity: 20 years of progress and discovery. Brain, Behav. Immun. 21(4):374–383. Kanner, A. (2003) Depression in epilepsy: prevalence, clinical semiology, pathogenic mechanisms and treatment. Biol. Psychiatry 54:388–298. Karlsson, I., Goddaris, J., Lima, G.A.D., Nygaard, H., Simanyi, M., Taal, M., and Eglin, M. (2000) A randomized double blind comparison of the efficacy and safety of citalopram compared to mianserin in elderly, depressed patients with or without mild to moderate dementia. Int. J. Geriat. Psychiatry 15:295–305.

Katon, W.J. (2003) Clinical and health services relationships between major depression, depressive symptoms and general medical illness. Biol. Psychiatry 54:216–226. Kemeny, M.E., and Dean, L. (1995) Effects of AIDS-related bereavement on HIV progression among New York City gay men. AIDS Educ. Prev. 7(Supp):36– 47. Kemeny, M.E., Weiner, H., Duran, R., Taylor, S.E., Visscher, B., and Fahey, J.L. (1995) Immune system changes after the death of a partner in HIV-positive gay men. Psychosom. Med. 57:547–554. Kent, S., Bluthe, R.M., Kelley, K.W., and Dantzer, R. (1992) Sickness behavior as a new target for drug development. Trends Pharmacol. Sci. 13:24–28. Kessler, R.C., Berglund, P., Demler, O., Jin, R., Merikangas, K.R., and Walters, E.E. (2005) Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62:593–602. Kessler, R.C., McGonagle, K.A., Zhao, S.Y., Nelson, C.B., Huges, M., Eshleman, S., Wittchin, H.U., and Kendler, K.S. (1994) Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: results from the National Comorbidity Survey. Arch. Gen. Psychiatry 51:8–19. Kirkwood, J.M., Bender, C., Agarwala, S., Tarhini, A., Shipe-Spotloe, J., Smelko, B., Donnely, S., and Stover, L. (2002) Mechanisms and management of toxicities associated with high-dose interferon alfa-2b therapy. J. Clin. Oncology 20:3703–3718. Kissane, D., Clarke, D.M., and Street, A.F. (2001) Demoralization syndrome: a relevant psychiatric diagnosis for palliative care. J. Palliat. Care 17:12–21. Kling, M.A., Alesci, S., Csako, G., Costello, R., Luckenbaugh, D.A., Bonne, O., Duncko, R., Drevets, W.C., Manji, H.K., Charney, D.S., Gold, P.W., and Neumeister, A. (2007) Sustained low-grade pro-inflammatory state in unmedicated, remitted women with major depressive disorder as evidenced by elevated serum levels of the acute phase proteins C-reactive protein and serum amyloid A. Biol. Psychiatry 62:309–313. Kroenke, K., Spritzer, R.L., and Williams, J.B. (2002) The PHQ-9: a new depression diagnostic and severity measure. Psychiatric Annals 32:509–515. Kronfol, Z. (2002) Immune dysregulation in major depression: a critical review of existing evidence. Int. J. Neuropsychopharmacol. 5:333–343. Krueger, R.F., Chentsova-Dutton, Y.E., Markon, K.E., Goldberg, D., and Ormel, J. (2003) A cross-cultural study of the structure of comorbidity among common psychopathological syndromes in the general health care setting. J. Abnorm. Psychol. 112:437– 447. Kuipers, P.M., Hamulyuk, K., Strik, J.J., Wellens, H.J., and Honig, A. (2002) Beta-thromboglobulin and platelet factor 4 levels in post- myocardial infarction patients with major depression. Psychiatry Res. 109:207–210. Laghrissi-Thode, F., Wagner, W.R., Pollack, B.G., Johnson, P.C., and Finkel, M.S. (1997) Elevated platelet factor 4 and beta-thromboglobulin plasma levels in depressed patients with ischemic heart disease. Biol. Psychiatry 42:290–295. Lanza, G.A., Sgueglia, G.A., Cianflone, D., Rebuzz, A.G., Angeloni, G., Sestito, A., Infusino, F., Crea, F., and Maseri, A. (2006) Relation of heart rate variability to serum levels of C-reactive protein in patients with unstable angina pectoris. Am. J. Cardiology 97: 1702–1706. Larson, S.J., and Dunn, A.J. (2001) Behavioral effects of cytokines. Brain Beh. Immun. 15:371–387. Lee, H.B., and Lyketsos, C.G. (2003) Depression in Alzheimer’s disease: heterogeneity and related issues. Biol. Psychiatry 54:353– 362. Lee, K.M., and Kim, Y.K. (2006) The role of IL-12 and TGF-beta1 in the pathophysiology of major depressive disorder. Int. Immunopharmacol. 6:298–1304.

36: DEPRESSION AND MEDICAL ILLNESS Leserman, J. (2003) HIV disease progression: Depression, stress, and possible mechanisms. Biol. Psychiatry 54:295–306. Leserman, J., Petitto, M., Gu, H., Gaynes, B.N., Barroso, J., Golden, R.N., Perkins, D.O., Folds, J.D., and Evans, D.L. (2002) Progression to AIDS, a clinical AIDS condition and mortality: Psychosocial and physiological predictors. Psychol. Med. 32:1059–1073. Lesperance, F., Frasure-Smith, N., Koszycki, D., Laliberte, M.A., Van Zyl, L.T., Baker, B., Swenson, J.R., Ghatavi, K., Abramson, B.L., Dorian, P., and Guertain, M.C. (2007) Effects of citalopram and interpersonal psychotherapy on depression in patients with coronary artery disease: the Canadian Cardiac Randomized Evaluation of Antidepressant and Psychotherapy Efficacy (CREATE) trial. JAMA 297:367–379. Lesperance, F., Frasure-Smith, N., Theroux, P., and Irwin, M. (2004) The association between major depression and levels of soluble intercellular adhesion molecule 1, interleukin-6, and C-reactive protein in patients with recent acute coronary syndromes. Am. J. Psychiatry 161:271–277. Lett, H.S., Blumenthal, J.A., Babyak, M.A., Sherwood, A., Strauman, T., Robins, C., and Newman, M.F. (2004) Depression as a risk factor for coronary artery disease: evidence, mechanisms, and treatment. Psychosom. Med. 66:305–315. Li, A., Withoff, S., and Verma, I.M. (2005) Inflammation-associated cancer: NF-kappaB is the lynchpin. Trends Immunol. 26:318–325. Loberiza, F.R., Jr., Rizzo, J.D., Bredeson, Cn., Antin, J.H., Horowitz, M.M., Weeks, J.C., and Lee, S.J. (2002) Association of depressive syndrome and early deaths among patients after stemcell transplantation for malignant diseases. J. Clin. Oncology 20: 2118–2126. Lustman, P.J., Freedland, K.E., Griffith, L.S., and Clouse, R.E. (2000) Fluoxetine for depression in diabetes: a randomized double-blind placebo controlled trial. Diabetes Care 23:618–623. Lyketsos, C.G., Hoover, D.R., Guccione, M., Senterfitt, W., Dew, M.A., Wesch, J., Vanraden, M.J., Treisman, G.J., and Morgenstern, H. (1993) Depressive symptoms as predictors of medical outcomes in HIV infection. JAMA 270:2563–2567. Lyketsos, C.G., Sheppard, J.M.E., Steele, C.D., Kopunek, S., Steinberg, M., Baker, A.S., Brandt, J., and Rabins, P.V. (2000) Randomized placebo-controlled double blind clinical trial of sertraline in the treatment of depression complicating Alzheimer’s disease: initial results from the depression in Alzheimer’s disease study. Am. J. Psychiatry 157:1686–1689. Maes, M., Bosmans, E., Meltzer, H.Y., Sharpe, S., and Suy, E. (1993) Interleukin-1b: A putative mediator of HPA axis hyperactivity in major depression? Am. J. Psychiatry 150:1189–1193. Malave, H.A., Taylor, A.A., Nattama, J., Deswal, A., and Mann, D. L. (2003) Circulating levels of tumor necrosis factor correlate with indexes of depressed heart rate variability: a study in patients with mild-to-moderate heart failure. Chest 123:716–724. Markovitz, J.H., and Matthews, K.A. (1991) Platelets and coronary heart disease: potential psychophysiologic mechanisms. Psychosom. Med. 53:643–668. Marshall, P., and Colon, E. (1993) Effects of allergy season on mood and cognitive function. Ann. Allergy 71:251–258. Masand, P., Pickett, P., and Murray, G.B. (1991) Psychostimulants for secondary depression in medical illness. Psychosomatics 32: 203–208. Massie, M.J., and Greenberg, D.B.L. (2005) Oncology. In: Levenson, J., ed. Textbook of Psychosomatic Medicine. Washington, DC: American Psychiatric Publishing, pp. 517–534. Mayne, T.J., Vittinghoff, E., Chesney, M.A., Barrett, D.C., and Coates, T.J. (1996) Depressive affect and survival among gay and bisexual men infected with HIV. Arch. Int. Med. 156:2233– 2238. McDaniel, J.S., Musselman, D.L., Porter, M.R., Reed, D.A., and Nemeroff, C.B. (1995) Depression in patients with cancer: diagnosis, biology, and treatment. Arch. Gen. Psychiatry 52:89–99.

569

McDonald, W.M., Richards, I.H., and DeLong, M.R. (2003) The prevalence, etiology and treatment of depression in Parkinson’s disease. Biol. Psychiatry 54:363–375. Meyers, C.A., Albitar, M., and Estey, E. (2005) Cognitive impairment, fatigue and cytokine levels in patients with acute myelogenous leukemia or myelodysplastic syndrome. Cancer 104:788– 793. Michaud, C.M., Murray, M.C., and Bloom, B.R. (2001) Burden of disease: implications for future research. JAMA 285:535–539. Miller, G.E., Freedland, K.E., Duntley, S., and Carney, R.M. (2005) Relation of depressive symptoms to C reactive protein and pathogen burden cytomegalovirus, herpes simplex virus, Epstein Barr virus: in patients with earlier acute coronary syndromes. Am. J. Cardiol. 95:317–321. Miller, G.E., Stetler, C.A., Carney, R.M., Freedland, K.E., and Banks, W.A. (2002) Clinical depression and inflammatory risk markers for coronary heart disease. Am. J. Cardiol. 90:1279–1283. Minden, S.L., and Schiffer, R.B. (1990) Affective disorders in multiple sclerosis: review and recommendations for clinical research. Arch. Neurol. 47:98–104. Miyoka, H., Otsubo, T., Kamijima, K., Ishii, M., Onuki, M., and Mitamura, K. (1999) Depression from interferon therapy in patients with hepatitis C. Am. J. Psychiatry 156:1120. Mohr, D.C., Boudewyn, A.C., Goodkin, D.E., Bostrom, A., and Epstein, L. (2001) Comparative outcomes for individual cognitivebehavior therapy, supportive-expressive group psychotherapy and sertraline for the treatment of depression in multiple sclerosis. J. Consult. Clin. Psychol. 69:942–949. Morrison, M.F., Petitto, J.M., Ten Have, T., Gettes, D.R., Chiappini, M.S., Weber, A.L., Brinker-Spence, P., Bauer, R.M., Douglas, S.D., and Evans, D.L. (2002) Depressive and anxiety disorders in women with HIV infection. Am. J. Psychiatry 159:789–796. Musselman, D.L., Evans, D.L., and Nemeroff, C.B. (1998) The relationship of depression to cardiovascular disease. Arch. Gen. Psychiatry 55:580–592. Musselman, D.L., Lawson, D.H., Gumnick, J.F., Manatunga, A.K., Penna, S., Goodkin, R.S., Greiner, K., Nemeroff, C.B., and Miller, A.H. (2001) Paroxetine for the prevention of depression induced by high-dose interferon alpha. N. Eng. J. Med. 344:961–966. Musselman, D.L., Miller, A.H., Porter, M.R., Manatunga, A., Gao, F., Penna, S., Landry, J., Glover, S., McDaniel, J.S., and Nemeroff, C.B. (2001) Higher than normal plasma interleukin-6 concentrations in cancer patients with depression: preliminary findings. Am. J. Psychiatry 158:1252–1257. Musselman, D.L., Somerset, W.I., Guo, Y., Manatunga, A.K., Porter, M., Penna, S., Lewison, B., Goodkin, R., Lawson, K., Lawson, D., Evans, D.L., and Nemeroff, C.B. (2006) A double-blind, multicenter, parallel group study of paroxetine, desipramine, or placebo in breast cancer patients (stages I, II, III, and IV) with major depression. J. Clin. Psychiatry 67:288–296. Musselman, D.L., Tomer, A., Manatunga, A.K., Knight, B.T., Porter, M.R., Kasey, S., Marzec, U., Harker, L.A., and Nemeroff, C.B. (1996) Exaggerated platelet reactivity in major depressive disorder. Am. J. Psychiatry 153:1313–1317. Nahshoni, E., Aravat, D., Aizenberg, D., Sigler, M., Zalsman, G., Strasberg, B., Imbar, S., Adler, E., and Weizman, A. (2004) Heart rate variability in patients with major depression. Psychosomatics 45:129–134. Nemeroff, C.B. (1996) The corticotrophin-releasing factor (CRF) hypothesis of depression: new findings and new directions. Mol. Psychiatry 1:336–342. Newport, D.J., and Nemeroff, C.F. (1998) Assessment and treatment of depression in cancer treatment. J. Psychosom. Res. 45:215– 237. Orlando, M., Burnam, M.A., Beckman, R., Morton, S.C., London, A.S., Bing, E.G., and Fleishman, J.A. (2002) Re-estimating the prevalence of psychiatric disorders in a nationally representative

570

MOOD DISORDERS

sample of persons receiving care for HIV: results from the HIV Cost and Services Utilization Study. Int. J. Meth. Psychiatric Res. 11:75–82. Page-Shafer, K., Delorenze, G.N., Satariano, W.A., and Winkelstein, W., Jr. (1996) Comorbidity and survival in HIV-infected men in the San Francisco Men’s Health Survey. Ann. Epidemiol. 6:420– 430. Patten, S. (2001) Long-term medical conditions and major depression in a Canadian population study at waves 1 and 2. J. Affect. Disord. 63:35–41. Patterson, T.L., Shaw, W.S., Semple, S.J., Cherner, M., McCutchan, J.A., Atkinson, J.H., Grant, I., and Nannis, E. (1996) Relationship of psychosocial factors to HIV disease progression. Ann. Behav. Med. 18:30–39. Pavon, L., Sandoval-Lopez, G., Eugenia Hernandez, M., Loria, F., Estrada, I., Perez, M., Moreno, J., Avila, U., Leff, P., Anton, B., and Heinze, G. (2006) Th2 cytokine response in major depressive disorder patients before treatment. J. Neuroimmunol. 172: 156–165. Pezella, G., Moslinger-Gehmayr, R., and Contu, A. (2001) Treatment of depression in patients with breast cancer: a comparison between paroxetine and amitriptyline. Breast Cancer Res. Treat. 70:1–10. Pike, J.L., and Irwin, M.R. (2006) Dissociation of inflammatory markers and natural killer cell activity in major depressive disorder. Brain Behav. Immun. 20(2):169–174. Popkin, M.K., Callies, A.L., and Mackenzie, T.B. (1985) The outcome of antidepressant use in the medically ill. Arch. Gen. Psychiatry 42:1160–1163. Rabkin, J.G., Ferrando, S.J., Wagner, G.J., and Rabkin, R. (2000) DHEA treatment for HIV+ patients: effects on mood, androgenic and anabolic parameters. Psychoneuroendocrinology 25:53–68. Rabkin, J.G., Rabkin, R., Harrison, W., and Wagner, G. (1994) Effect of imipramine on mood and enumerative measures of immune status in depressed patients with HIV illness. Am. J. Psychiatry 151:516–523. Rabkin, J.G., Rabkin, R., and Wagner, G. (1994) Effect of fluoxetine on mood and immune status in depressed patients with HIV illness. J. Clin. Psychiatry 55:92–97. Rabkin, J.G., Wagner, G.J., and Rabkin, R. (1994) Effects of sertraline on mood and immune status in patients with major depression and HIV illness: an open trial. J. Clin. Psychiatry 55:433– 439. Rabkin, J.G., Wagner, G.J., and Rabkin, R. (2000) A double-blind, placebo-controlled trial of testosterone for HIV-positive men with hypogonadal symptoms. Arch. Gen. Psychiatry 57:141–147. Rabkin, J.G., Williams, J.B., Remien, R.H., Goetz, R., Kertzner, R., and Gorman, J.M. (1991) Depression, distress, lymphocyte subsets, and human immunodeficiency virus symptoms on two occasions in HIV-positive homosexual men. Arch. Gen. Psychiatry 48:111–119. Radloff, L.S. (1977) The CES-D: a self report depression scale for research in the general population. Applied Psychological Measures 3:385–401. Raison, C.L., Capuron, L., and Miller, A. (2006) Cytokines sing the blues: inflammation and the pathogenesis of depression. Trends Immunol. 27:24–31. Raison, C.L., and Miller, A.H. (2003) Depression in cancer: new developments regarding diagnosis and treatment. Biol. Psychiatry 54:283–294. Raison, C.L., and Nemeroff, C.B. (2000) Cancer and depression: prevalence, diagnosis, and treatment. Home Health Care Consult. 7:34–41. Rasmussen, A., Lunde, M., Poulsen, D.L., Sorensen, K., Qvitzau, S., and Bech, P. (2003) A double-blind, placebo-controlled study of sertraline in the prevention of depression in stroke patients. Psychosomatics 44:216–221.

Razavi, D., Allilaire, J.F., Smith, M., Salimpour, A., Verra, M., Desclaux, B., Saltel, P., Piollet, I., Gauvain Piquard, A., Trichard, C., Cordier, B., Fresco, R., Guillibert, E., Sechter, D., Orth, J.P., Bouhassira, M., Mesters, P., and Blin, P. (1996) The effect of fluoxetine on anxiety and depression symptoms in cancer patients. Acta Psychiatr. Scand. 94:205–210. Rechlin, T., Weis, M., Spitzer, A., and Kaschka, W.P. (1994) Are affective disorders associated with alterations of heart rate variability? J. Affect. Disord. 32:271–275. Richard, I.H., Maughan, A., and Kurlan, R. (1999) Do serotonin reuptake inhibitor antidepressants worsen Parkinson’s disease? A retrospective case series. Movement Disord. 14:155–157. Richardson, P., Mckenna, W., Bristow, M., Maisch, B., Mautner, B., O’Connell, J., Olson, E., Thiene, G., Goodwin, J., Gyarfas, I., Martin, I., Nordet, P. (1996) Report of the 1995 World Health Organization/International Society and Federation of Cardiology Task Force on the definition and classification of cardiomyopathies. Circulation 93(5):1043–1065. Robinson, R.G. (2003) Post-stroke depression: prevalence, diagnosis, treatment and disease progression. Biol. Psychiatry 54:376– 387. Roscoe, J.A., Morrow, G.R., Hickock, J.T., Mustian, K.M., Griggs, J.J., Matteson, S.E., Bushunow, P., Qazi, R., and Smith, B. (2005) Effect of paroxetine hydrochloride (paxil) on fatigue and depression in breast cancer patients receiving chemotherapy. Breast Cancer Res. Treat. 89:243–249. Roy, A., Guthrie, S., and Pickar, D. (1987) Plasma norepinephrine responses to cold challenge in depressed patients and normal controls. Psychiatry Res. 21:161–168. Rozans, M., Dreisbach, A., Lertora, J.J., and Kahn, M.J. (2002) Palliative uses of methylphenidate in patients with cancer: a review. J. Clin. Oncology 20:335–339. Rudish, B., and Nemeroff, C.B. (2003) Epidemiology of comorbid coronary artery disease and depression. Biol. Psychiatry 54:227– 240. Scharko, A.M. (2006) DSM psychiatric disorders in the context of pediatric HIV/AIDS. AIDS Care 18:441– 445. Shapiro, A.P. (2005) Heart disease. In: Levenson, J., ed. Textbook of Psychosomatic Medicine. Washington, DC: America Psychiatric Publishing, pp. 423– 444. Shen, W.W., Swartz, C.M., and Calhoun, J.W. (1999) Is inhibition of nitric oxide synthase a mechanism for SSRI-induced bleeding? Psychosomatics 40:268–269. Skala, J.A., Freedland, K.E., and Carney, R.M. (2006) Coronary heart disease and depression: a review of recent mechanistic research. Can. J. Psychiatry 51:738–745. Smith, D.K., Warren, D., Solomon, L., Schuman, P., Stein, M., Greenburg, B., and Moore, J. (1996) The design, participants and selected early findings of the HIV Epidemiology Research study. In: O’Leary, A., Jemmott, L.S., eds. Women and AIDS: Coping and Care. New York: Plenum Press, pp. 185–206. Smith, R.S. (1991) The macrophage theory of depression. Medical Hypotheses 35:298–306. Stearns, V., Isaacs, C., Rowland, J., Crawford, J., Ellis, M.J., and Kramer, R. (2000) A pilot trial assessing the efficacy of paroxetine hydrochloride (paxil) in controlling for hot flashes in breast cancer survivors. Ann. Oncology 11:17–22. Stein, P.K., Carney, R.M., Freedland, K.E., Skala, J.A., Jaffe, A.S., Kleiger, R.E., and Rottman, J.N. (2000) Heart rate variability is related to the severity of depression in patients with coronary heart disease. J. Psychosom. Res. 48:493–500. Steptoe, A., Kunz-Ebrecht, S.R., and Owen, N. (2003) Lack of association between depressive symptoms and markers of immune and vascular inflammation in middle-aged men and women. Psychol. Med. 33:667–674. Suarez, E.C., Lewis, J.G., Krishnan, R.R., and Young, K.H. (2004) Enhanced expression of cytokines and chemokines by blood mon-

36: DEPRESSION AND MEDICAL ILLNESS ocytes to in vitro and lipopolysaccharide stimulation are associated with hostility and severity of depressive symptoms in healthy women. Psychoneuroendocrinology 29:1119–1128. Swiergiel, A.H., Smagin, G.N., and Dunn, A.J. (1997) Influenza virus infection of mice induces anorexia: comparison with endotoxin and interleukin-1 and the effects of indomethacin. Pharmacol. Biochem. Behav. 57:389–396. Szabo, S.T., Gould, T.D., and Manji, H.K. (2004) Neurotransmitters, receptors, signal transduction, and second messengers in psychiatric disorders. In: Schatzberg, A.F., and Nemeroff, C.B., eds. Textbook of Psychopharmacology, 3rd ed. Arlington, VA: American Psychiatric Publishing, Inc., pp. 3–52. Theobald, D.E., Kirsch, K.L., Holtsclaw, E., Donaghy, K., and Passik, S.D. (2002) An open label, crossover trial of Mirtazapine (15 and 30 mg) in cancer patients with pain and other distressing symptoms. J. Pain Sympt. Mgmt. 23:442–227. Tiemeier, H., Hofman, A., van Tujil, H.R., Kiliaan, A.J., Meijer, J., and Breteler, M.M. (2003) Inflammatory proteins and depression in the elderly. Epidemiology 14:103–107. Troxler, R.G., Sprague, E.A., Albanese, R.A., Fuchs, R., and Thompson, A.J. (1977) The association of elevated plasma cortisol and early atherosclerosis as demonstrated by coronary angiography. Atherosclerosis 26:151–162. Turner, M.S., May, D.B., Arthur, R.R., and Xiong, G.L. (2007) Clinical impact of selective serotonin reuptake inhibitors therapy with bleeding risks. J. Int. Med. 261:205–213. Valentine, A.D., Meyers, C.A., Kling, M.A., Richelson, E., and Hauser, P. (1998) Mood and cognitive side effects of interferonalpha therapy. Semin. Oncology 25:39–47. Van der Kooy, K.G., Van Hout, H.P., Van Marwijk, H.W., De Haan, M., Stehouwer, C.D., and Beekman, A.T. (2006) Differences in heart rate variability between depressed and non-depressed elderly. Int. J. Geriat. Psychiatry 21:147–150. Van Heeringen, K., and Zivkov, M. (1996) Pharmacological treatment of depression in cancer patients: a placebo controlled study of mianserin. Br. J. Psychiatry 169:440– 443. Vedhara, K., Schifitto, G., and McDermott, M. (1999) Disease progression in HIV-positive women with moderate to severe immunosupression: the role of depression. Dana Consortium on Therapy for HIV Dementia and Related Cognitive Disorders. Behav. Med. 25:43– 47. Wagner, G.J., Rabkin, J., and Rabkin, R. (1997) Dextroamphetamine as a treatment for depression and low energy in AIDS patients: a pilot study. J. Psychosom. Res. 42:407– 411. Wagner, G.J., and Rabkin, R. (2000) Effects of dextramphetamine on depression and fatigue inn men with HIV: a double-blind, placebo-controlled trial. J. Clin. Psychiatry 61:436– 440. Wang, P.S., Bong, R., Knight, E., Glynn, R.J., Mogun, H., and Avorn, J. (2002) Noncompliance with antihypertensive medications: the impact of depressive symptoms and psychosocial factors. J. Gen. Int. Med. 17:504–511. Wang, P.S., Lane, M., Olfson, M., Pincus, H.A., Wells, K.B., and Kessler, R.C. (2005) Twelve-month use of mental health services

571

in the United States. Results from the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62:629–640. Watkins, L.F., Weirtelak, E.P., Goehler, L.E., Smith, K.P., Martin, D., Maier, S.F. (1994) Characterization of cytokine induced hyperalgesia. Brain Res.654:15–26. Weisse, C.S. (1992) Depression and immunocompetence, a review of the literature. Psychol. Bull. 111:475– 489. Wellens, J.T., and Ridker, P.M. (2004) Inflammation as a cardiovascular risk factor. Circulation 109:2–10. Wellens, K.E., and Hotamisligil, G.S. (2005) Inflammation, stress and diabetes. J. Clin. Invest. 115:1111–1119. Wernicke, J.F., Pritchett, Y.L., D’Souza, D.N., Waninger, A., Tran, P., Iyengar, S., and Raskin, J. (2006) A randomized controlled trial of duloxetine in diabetic peripheral neuropathic pain. Neurology 67:1411–1420. Whooley, M.A., Caska, C.M., Hendrickson, B.E., Rourke, M.A., Ho, J., and Ali, S. (2007) Depression and inflammation in patients with coronary heart disease: findings from the Heart and Soul Study. Biol. Psychiatry 62:314–320. Williams, L.S., Kroenke, K., Bakas, T., Plue, L.D., Brizendine, E., Tu, W.Z., and Hendrie, H. (2007) Care management of poststroke depression: a randomized, controlled trial. Stroke 38:998– 1003. Writing Committee for the ENRICHD Investigators. (2003) Effects of treating depression and low perceived social support on clinical events after myocardial infarction: the enhancing recovery in coronary heart disease patients (ENRICHD). JAMA 289:3106– 3116. Wulsin, L.R., (2004) Is depression a major risk factor for coronary disease? A systematic review of the epidemiologic evidence. Harv. Rev. Psychiatry 12:79–95. Wulsin, L.R., Viewig, W.V., and Fernandez, A. (2004) Treating depression in patients with cardiovascular disease. Curr. Psychiatry 3:20–34. Yirmiya, R. (1996) Endotoxin produces a depressive-like episode in rats. Brain Res. 711:163–174. Yirmiya, R., Pollack, Y., Barak, O., Avitsur, R., Ovadia, H., Bette, M., Weihe, E., and Weidenfeld, J. (2001) Effects of antidepressant drugs on the behavioral and physiological responses to lipopolysaccharide (LPS) in rodents. Neuropsychopharmacology 24: 531–543. Yirmiya, R., Weidenfeld, J., Pollak, Y., Morag, M., Morag, A., Avitsur, R., Barak, O., Reichenberg, A., Cohen, E., Shavit, Y., and Ovadia, H. (1999) Cytokines, ‘depression due to general medical condition’ and antidepressant drugs. Adv. Exper. Med. Biol. 461:283– 316. Zigmond, A.S., and Snaith, R.P. (1983) The Hospital Anxiety and Depression Scale. Acta Psychiatr. Scand. 67:361–370. Zisook, S., Peterkin, J., Goggin, K.J., Sledge, P., Atkinson, J.H., and Grant, I. (1998) Treatment of major depression in HIV-seropositive men. J. Clin. Psychiatry 59:217–224. Zung, W.W. (1965) A self-rating scale for depression. Arch. Gen. Psychiatry 12:63–70.

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V

ANXIETY DISORDERS ANTONIA S. NEW

T

A N D

DENNIS S. CHARNEY

HE chapters in this section reflect the advances in preclinical and clinical neuroscience that have enhanced our understanding of the diagnosis, pathophysiology, and treatment of anxiety disorders. This progress has the potential to revolutionize the means by which anxiety disorders are diagnosed. The major limitation of current diagnostic classification systems is that they are not based on etiology, pathophysiology, or treatment response. Stein and Bienvenu (Chapter 37) provide a comprehensive review of the current and future classification systems for anxiety disorders. They review the empirical evidence for and against alternative classification systems to Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV; American Psychiatric Association, 1994), including a model that considers anxiety disorders to emerge from a single corepathological process, and a related dimensional model for anxiety disorders. They argue that neurobiological evidence in anxiety disorder is growing very rapidly and that any classification that does not take into account, over the coming years, the relationship between genotype, anxiety phenotype (including specific neurocircuitry), and environmental influences will be unsatisfying and temporary (Caspi and Moffitt, 2006). It is imperative to discover specific genes that relate to vulnerability to anxiety disorders if we are to make fundamental progress in improving diagnostic precision, understanding pathophysiology, and identifying new molecular targets for drug development. Hamilton and Fyer (Chapter 38) review evidence for heritability as well as studies that have implicated specific genes for a number of anxiety disorders, including panic disorder, phobias, generalized anxiety disorder, obsessivecompulsive disorder (OCD), and anxiety personality traits. All of these disorders carry rather high heritability, with 20%– 40% of the phenotypic variance accounted for by additive genetic effects. They review the complexity of identifying specific genes or haplotypes for these disorders. For example, a number of different chromosomal locations have been discovered in pedigrees replete with panic disorder (Crowe et al., 2001; Gelernter et al., 2001; Thorgeirsson et al., 2003; Fyer et al., 2006), raising the possibility of genetic heterogeneity across different

populations. They also review preclinical investigations using “knockout” and “knockin” technology, which have implicated specific genes in anxiety disorders. These techniques have demonstrated a critical role for the 5hydroxytryptamine-1A (5-HT1A) receptor in anxiety, supported by findings in 5-HT1A knockout mice indicating that altered function of 5-HT1A receptors early in life can produce long-term abnormalities in the regulation of anxiety behaviors (Gross et al., 2002) and by evidence that the overexpression of 5-HT1A results in lower levels of “anxiety-like” behavior (Kusserow et al., 2004). Preclinical studies have also demonstrated a role for different subtypes of the corticotrophin releasing hormone (CRH-R1, CRH-R2) and the possible interplay between these two subtypes in mediating stress responsiveness (Bale and Vale, 2004). Important clues to the pathogenesis of anxiety disorders come from the work by McEwen (Chapter 40). The results from these preclinical investigations have had a major influence on the focus of current clinical investigations of anxiety disorders. Animal models of anxiety disorders have been very useful in identifying, with a surprising degree of specificity, the effects of psychological stress on brain structure and function. Among the prominent examples are the observations that a variety of stressors in different animal species suppress neurogenesis and reduce hippocampal volume and that specific pharmacological agents such as glutamate release inhibitors, glucocorticoid receptor antagonists, standard antidepressants, and putative antidepressants such as substance P antagonists may reverse or prevent these effects. This line of research has produced a number of hypotheses that may lead to novel therapeutic approaches to stressrelated anxiety disorders. Elegant work by McEwen and colleagues has emphasized the role of allostasis and allostatic load as important principles when considering the acute adaptive and maladaptive responses of the brain and body to stress. This work has implications for preventive approaches to stress-related psychopathology and the psychobiological mechanisms of resilience and vulnerability to extreme psychological stress (Charney, 2004).

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The neural circuits and associated neural mechanisms that may relate to the signs and symptoms of anxiety disorders are the subject of intensive preclinical investigation. Sullivan and colleagues (Chapter 39) review the adaptive value of fear and anxiety and present models for how the neural systems underlying these normal behaviors might go awry in pathological anxiety disorders. They review the evidence for the roles for brain structures such as the amygdala, hippocampus, locus coeruleus, bed nucleus of the stria terminalis, and cortical regions in fear conditioning, extinction, sensitization, and the consolidation and reconsolidation of emotional memories. The neurochemical modulation of these brain structures by neuromodulators such as cortisol, corticotropin releasing hormone (CRH), glutamate, and norepinephrine have provided important clues to prevent, attenuate, or reverse the effects of traumatic and fear-inducing stimuli on the symptoms associated with fear conditioning and the impact of memories on psychological and physiological functions. Finally, they introduce a multimodal model for acquired adaptation to stress through “stress inoculation” in squirrel monkeys (Lyons and Parker, 2007). These neural mechanisms and associated brain structures have proven to be related to the pathophysiology and treatment of anxiety disorders as described by Kent and Rauch (Chapter 43) and Swedo and Grant (Chapter 42). Neuroimaging studies in patients with post-traumatic stress disorder (PTSD) have largely been consistent with preclinical studies and have revealed abnormalities in a neural fear circuit featuring the amygdala, hippocampus, and prefrontal cortex. Reductions in hippocampal volume have repeatedly been identified in patients with PTSD. Neuroreceptor imaging studies have begun to identify alterations in receptor systems implicated in anxiety and fear regulation. Functional imaging findings in panic disorder, though less conclusive than that of some of the other anxiety disorders, point to abnormalities in the hippocampal/parahippocampal region at rest. During symptom provocation, patients with panic disorder exhibit activation of insular and motor striatal regions, whereas reductions are seen in widespread cortical regions, including the prefrontal cortex. Magnetic resonance spectroscopy (MRS) findings suggest that patients with panic disorder exhibit an exaggerated hemodynamic response to hypocapnea, which is manifest as relatively greater global vasoconstriction. Likewise, receptor binding studies suggest widespread abnormalities in the g -aminobutyric acid (GABA)ergic/benzodiazepine system. Neuroimaging studies in OCD differ substantially from that of other anxiety disorders because of evidence of specific frontocortical-striatal inefficiency in conjunction with orbitofrontal hyperactivity. Swedo and Grant consider current hypotheses regarding the etiology and pathophysiology of OCD. It appears

highly likely that OCD, as currently defined, probably reflects several different disease entities whose psychopathology ranges from neuroimmune dysfunction to abnormalities in neurotransmitters and neuropeptides. This chapter reviews recent evidence of specific molecular targets for the immune response that underlies pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS). In addition, recent clinical trials in OCD are reviewed. In the next to last chapter in this section, Mathew and colleagues (Chapter 44) review novel pharmacology in the treatment of anxiety disorders. Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for a number of anxiety disorders, due to their favorable side-effect profile, although tricyclic antidepressants and monoamine oxidase inhibitors continue to have a role. This chapter also reviews recent head-to-head trials of SSRIs and selective noradrenergic reuptake inhibitors (SNRIs) and demonstrates comparable efficacy for these agents. Finally, the authors point to disappointing results in the treatment of PTSD, with a recent report from the Institute of Medicine as evidence of the inadequacy of determining efficacy in the treatment of PTSD. REFERENCES American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Bale, T.L., and Vale, W.W. (2004) CRF and CRF receptors: role in stress responsivity and other behaviors. Ann. Rev. Pharmacol. Toxicol. 44:525–557. Caspi, A., and Moffitt, T.E. (2006) Gene-environment interactions in psychiatry: joining forces with neuroscience. Nat. Rev. Neurosci. 7:583–590. Charney, D.S. (2004) Psychobiological mechanisms of resilience and vulnerability: implications for successful adaptation to extreme stress. Am. J. Psychiatry 161:195–216. Crowe, R.R., Goedken, R., Samuelson, S., et al. (2001) Genomewide survey of panic disorder. Am. J. Med. Genet. 105:105–109. Fyer, A.J., Hamilton, S.P., Durner, M., et al. (2006) A third-pass genome scan in panic disorder: evidence for multiple susceptibility loci. Biol. Psychiatry 60:388–401. Gelernter, J., Bonvicini, K., Page, G., et al. (2001) Linkage genome scan for loci predisposing to panic disorder or agoraphobia. Am. J. Med. Genet. 105:548–557. Gross, C., Zhuang, X., Stark, K., et al. (2002) Serotonin1A receptor acts during development to establish normal anxiety-like behaviour in the adult. Nature 416:396– 400. Kusserow, H., Davies, B., Hortnagl, H., et al. (2004) Reduced anxiety-related behaviour in transgenic mice overexpressing serotonin 1A receptors. Brain Res. Mol. Brain Res. 129:104 –116. Lyons, D.M., Parker, K.J. (2007) Stress inoculation-induced indications of resilience in monkeys. J. Trauma Stress 20:423– 433. Thorgeirsson, T.E., Oskarsson, H., Desnica, N., et al. (2003) Anxiety with panic disorder linked to chromosome 9q in Iceland. Am. J. Hum. Genet. 72:1221–1230.

37

Diagnostic Classification of Anxiety Disorders: DSM-V and Beyond MURRAY B. STEIN

A N D

O. JOSEPH BIENVENU

The goal of this chapter is to provide a synthetic overview of current and future classification systems for anxiety disorders. In so doing, we intend to familiarize the reader with the historical origins of our current nosology, as a preface for showing how these have evolved to their present state. We touch on some of the current controversies in the diagnosis of anxiety disorders and comment on how these may be reflected in future changes to the diagnostic criteria. Much of the content of this chapter focuses on alternative models for diagnostic classification of the anxiety disorders. Prominent among these models is the specification that the anxiety disorders might be more parsimoniously represented by a core pathological process that underlies them all (for example, neurosis). The empirical evidence for and against this notion will be reviewed. Finally, we propose future approaches to diagnostic classification that take into account the neurobiology of the conditions, and perhaps even their etiologic origins. BACK TO THE FUTURE It has been said that those who do not remember the past are doomed to repeat it. In an effort to prevent this from happening, we believe that a backward look at the evolution of the anxiety disorder diagnostic criteria is in order. This retrospective viewpoint provides a framework from which to speculate about how future versions of the Diagnostic and Statistical Manual of Mental Disorders (DSM) (DSM-V and beyond) might be configured, and on what basis. DSM-II (and International Classification of Diseases [ICD]-8) included what we now call the anxiety disorders in the “neuroses” category. Anxiety neurosis subsumed panic disorder and generalized anxiety disorder (GAD); phobic neurosis included agoraphobia, social phobia, specific phobia, and separation anxiety disorder; and obsessive-compulsive neurosis equates to obsessivecompulsive disorder (OCD). (Traumatic neurosis, though not codified in DSM-II, was used in the literature of

the era and fits with what we now term posttraumatic stress disorder.) DSM-III came along in 1980 and made some radical changes to the diagnostic criteria, most notably the separation of the neuroses along the diagnostic lines we now recognize. DSM-III dropped the “neurosis” category in large part, it seems, to prevent clinicians from inferring that a psychodynamic etiologic process was being named (as DSM-III was furtively and consistently an atheoretical, descriptive document). But it also took note that panic disorder and GAD, in particular, were different entities with different family history, course, and perhaps response to treatment (American Psychiatric Association [APA], 1980). Centrality of Panic to Diagnostic Classification The idea that panic attacks (and panic disorder) are distinguishable from other forms of background anxiety has been one of the major (if not the major) organizing principles in the classification of anxiety disorders for the past two decades. From DSM-III through DSM-III-R and DSM-IV, epidemiologic studies have been guided by the construct of panic attacks and panic disorder as distinct from other forms of anxiety (Markowitz et al., 1989; Klerman et al., 1991; Horwath et al., 1993; Eaton et al., 1994; Fyer et al., 1996). Influenced strongly by the seminal observations of Donald F. Klein and colleagues that panic attacks responded to imipramine, whereas anticipatory anxiety did not (Klein et al., 1978), this position has proved instrumental in the way we approach anxiety disorder classification, particularly in North America. Agoraphobia Without Panic: The Exception to a Rule? It is beyond the scope of this chapter to review the evidence for and against considering panic disorder (distinguished by the presence of uncued, or spontaneous panic attacks) as distinct from other forms of anxiety where panic attacks also occur but are less likely to be spontaneous (that is, any of the phobic disorders, where paroxysms of anxiety and physical symptoms may occur 575

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upon exposure to the phobic stimulus). Suffice it to say that there is ample evidence, though this has not gone unchallenged. Most contentious has been the idea that agoraphobia is virtually always a consequence of panic disorder. Many epidemiological studies have reported a high prevalence of “agoraphobia without panic” (Robins et al., 1984; Eaton et al., 1994; Wittchen et al., 1998), the existence of which runs contrary to the dogma that agoraphobia develops only as a complication of unbridled panic attacks (Katerndahl, 2000). Although some cases of agoraphobia without panic undoubtedly reflect the limitations of large-scale diagnostic interviews that miss some cases of preexisting spontaneous panic while picking up the more current agoraphobia, and which misclassify some cases of specific phobia as agoraphobia (Horwath et al., 1993), there are inarguably many cases of agoraphobia where panic was never present (Wittchen et al., 1998; Hayward et al., 2003). Some of these cases are probably pseudoagoraphobia associated with limitations attributable to medical illness (for example, phobic limitations associated with the postural instability of vestibular dysfunction) (Marks, 1981; Stein et al., 1994), some are better considered specific phobias (Wittchen et al., 1998; Bienvenu et al., 2006), and others are more classic agoraphobia where panic is truly absent. Furthermore, whereas panic disorder is thought to develop from panic attacks that occur “out of the blue,” there is evidence that persons prone to panic have prodromal symptoms (some of which can be thought of as agoraphobic symptoms) that can antedate the panic by many years (Fava et al., 1988; Lelliott et al., 1989). Bienvenu and colleagues (2006) examined prospective data from the Baltimore Epidemiologic Catchment Area (ECA) site wherein a sample of 1920 adults were assessed with the Diagnostic Interview Schedule (DIS) in 1981 and again approximately 13 years later. As expected, baseline DIS/DSM-III panic disorder strongly predicted first incidence of DSM-III-R agoraphobia; however, baseline agoraphobia without spontaneous panic attacks also robustly predicted first incidence of panic disorder, even when possible diagnostic misclassification of agoraphobia was taken into account using clinical reappraisal methods. These data strongly suggest that the implied one-way causal relationship between spontaneous panic attacks and agoraphobia in DSM-IV is incorrect. Observations such as these have called into question the primacy of panic for our diagnostic classification system, but the idea is sufficiently ensconced that resistance to change may be substantial. Generalized Anxiety Disorder: Worrying About Worries and Duration Since DSM-III, nosologists have attempted to reliably and validly define GAD. Over time, the diagnostic construct

has been narrowed and may be more reliable, but several investigators have cast doubt on its ultimate utility. For example, in DSM-III-R, the minimum duration criterion was increased from 1 month to 6 months, with little empirical support for this change (Breslau & Davis, 1985). Kendler et al. (1992a) found that, if anything, 1-month GAD was more heritable than 6-month GAD, thus disputing the notion that shorter-duration symptoms are more likely to be environmentally mediated transient stress reactions. We divided community participants into five mutually exclusive symptom categories: (1) DSM-III-R GAD, (2) 6 months of worry or anxiety with 6 associated symptoms, (3) 1 month of anxiety with or (4) without 6 associated symptoms, and (5) no anxiety, and investigated their demographic and comorbidity profiles as external construct validators. The first three groups were homogeneous with regard to these validators, but their profiles differed from those of participants with fewer than six symptoms or no anxiety. Thus, requiring six symptoms produced a group with a particular epidemiologic profile. Neither the nature of the participants’ worries nor the duration of symptoms influenced this profile (Bienvenu et al., 1998). Other groups have used external construct validators to address the GAD duration criterion. Kessler and colleagues (2005) examined data from the U.S. National Comorbidity Survey Replication (NCS-R), a U.S. household survey carried out during 2001–2003. There were few differences between cases with episodes of 1–5 months and those with episodes of ≥ 6 months in onset, persistence, impairment, comorbidity, parental GAD, or sociodemographic correlates. The authors concluded that, given the relative comparability of persons with a GAD-like syndrome with episodes of < 6 months duration to those with 6 or more months duration, little basis could be provided for excluding the former group from a diagnosis (Kessler et al., 2005). Angst et al. (2006) conducted a similar analysis using data from the Zurich Cohort Study. The authors defined generalized anxiety syndromes with varying duration criteria (2 weeks, 1 month, 3 months, and 6 months) and found no significant differences in family history of anxiety, work impairment, distress, treatment rates, or comorbidity with major depressive episodes, bipolar disorder, or suicide attempts. Only social impairment related to the length of episodes. Importantly, the 6-month criterion of DSM-III-R and DSM-IV GAD would preclude this diagnosis in about one half of the participants treated for generalized anxiety syndromes. The authors concluded that GAD syndromes of varying duration form a continuum with comparable clinical relevance. DSM-IV considers “excessive” worry to be paramount for a GAD diagnosis, but this requirement is absent in ICD-10. Again analyzing data from the NCS-R, Ruscio

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et al. (2005) compared (1) nonexcessive worriers meeting all other DSM-IV criteria for GAD with (2) respondents who met full GAD criteria, and (3) other survey respondents to consider the implications of removing the excessiveness requirement. When the “excessiveness” requirement was removed, the lifetime prevalence of GAD increased by approximately 40%. Interestingly, there were some important differences between GAD with and without “excessive” worry: the latter had an earlier age at onset and greater chronicity, symptom severity, and psychiatric co-morbidity. However, cases not meeting the “excessive” requirement still had substantial impairment and treatment seeking compared to respondents without GAD, suggesting that they represented a less severely affected group than the “excessive” cases. It is reasonable to conclude from these data that the “excessive” requirement, while having the impact of identifying more severe cases of GAD, does not seem to distinguish a qualitatively distinct group of individuals. In that sense, it could be argued that retaining the “excessive” requirement is somewhat arbitrary but perhaps establishes a clinically reasonable threshold for severity that warrants particular attention. The authors concluded that the findings challenge the validity of the excessiveness requirement and highlight the need for further research into the optimal definition of GAD (Ruscio et al., 2005). In conclusion, among the anxiety disorders, the diagnostic criteria for GAD have fluxed the most in the various iterations of DSM—perhaps for good reason, as better empirical data emerge to challenge current criteria—and may do so again in DSM-V (see below). PROPHESIZING CHANGES TO DSM There are several areas where changes to the diagnostic criteria may occur in DSM-V. In making these prognostications, we must emphasize that expressed here are the opinions of the authors, based largely on our knowledge of discussions that ensued during the preparation of the DSM-IV, text revision (DSM-IV TR; APA, 2000) and published information relevant to DSM-V (Regier, 2007). But they do not represent any official position on the part of the DSM-V Task Force and may or may not be acted upon. Joining MDD and GAD at the Hip? One proposal being considered for DSM-V is to add GAD to the mood disorders category. The rationale for this proposal is that GAD and major depressive disorder (MDD) overlap substantially, cross-sectionally and longitudinally (Kessler et al., 2001). There are also data suggesting that genetic risk factors for GAD and MDD are substantially overlapping (Kendler et al.,

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1992b; Hettema, Prescott, and Kendler, 2001), lending further credence to the notion that these two disorders belong in the same category. Interestingly, although both these disorders are associated with high neuroticism, much of the genetic covariance between GAD and MDD is not shared with genetic factors that influence neuroticism (Kendler et al., 2007; Hettema et al., 2006). The proposal to put MDD and GAD in the same category raises interesting, fundamental questions about what constitutes a “category” of mental disorders, and what shared factors would warrant mutual categorization of disorders. Another interesting question is what impact moving a disorder from one category to another will have on research, clinical practice, and health policy. If this proposal moves forward in DSM-V, we may find out. Should OCD Go its Own Way? Some in the field argue that OCD and related conditions should have their own diagnostic grouping, separate from the rest of the conditions traditionally categorized as anxiety disorders (Bartz & Hollander, 2006); at least one workgroup has met to discuss this notion for DSM-V (Regier, 2007). Several arguments have been put forth for this separation, including evidence that the functional neurocircuitry implicated in OCD appears to differ, to some extent, from that of other anxiety disorders; these arguments have varying levels of empirical support and are not uncontroversial (Bartz and Hollander, 2006). Mataix-Cols et al. (2007) found that 40% of 187 OCD experts surveyed felt that OCD should not be removed from the supraordinate category of anxiety disorders. This position was particularly common among nonpsychiatrists, and the main reasons for this position were that OCD and anxiety disorders tend to co-occur and respond to similar treatments. The authors concluded that there is insufficient consensus at this time to decide whether or not OCD should be removed from the anxiety disorders (Mataix-Cols et al., 2007) Categorizing the Response to Trauma The history of PTSD as a diagnostic entity is uniquely informative as a case in point of how accrued scientific knowledge has influenced classification decisions. Known variously in the literature as traumatic neurosis, shell shock, or war neurosis, PTSD first appeared in DSM-III to describe a syndrome that occurred following a psychologically traumatic event “that is generally outside the range of usual human experience” (APA, 1980). When viewed from this perspective, PTSD was a fairly uncommon disorder (Helzer et al., 1987). Subsequent epidemiologic research revealed, however, that many forms of serious, potentially deleterious psychological

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trauma were unfortunately not outside the range of usual human experience (Breslau et al., 1991), leading to a refinement and broadening of the criteria in DSM-IV to their present form that specify the “potentially lifethreatening” characteristics of the trauma (Breslau & Kessler, 2001). A PTSD symptom was shuffled among categories between DSM-III and DSM-III-R (physiologic reactivity upon exposure to reminders of the event moved from the hyperarousal to the reexperiencing cluster) when it was shown that it clustered with other symptoms in that category. And a new diagnostic entity, acute stress disorder (ASD), was introduced into the diagnostic nomenclature in DSM-IV. This entity was created to account for persons who have significant symptoms in the immediate (within 1 month) aftermath of serious trauma, before PTSD can have developed (by definition, PTSD is only diagnosed 1 month after trauma). The PTSD and ASD criteria seem ripe for change. First, it has often (though not always) (Breslau et al., 2004) been noted that the DSM-IV criteria for PTSD are too restrictive in that they fail to identify many persons with PTSD symptoms and clinically significant impairment and/or distress in the aftermath of trauma (Stein et al., 1997; Marshall et al., 2001). This observation has led to the widespread convention in the literature of identifying (and often lumping together with full syndromal PTSD) persons with “subthreshold” or “partial” PTSD. These are persons who have experienced significant trauma and yet fall one or two symptoms short of meeting the full DSM-IV criteria. Most investigators have acknowledged that reexperiencing (cluster B) symptoms are integral to the diagnosis of PTSD and required that these symptoms be present for a subthreshold diagnosis, while permitting fewer than the required (that is, by DSM-IV) number of avoidance or numbing (cluster C) or hyperarousal (cluster D) symptoms. Adding to the confusion is the requirement in the DSM that PTSD symptoms be spread across the three diagnostic clusters in a stereotyped fashion, a custom that has little empirical support. Simplified approaches to diagnosis (for example, doing away with specific cluster C or D requirements), which have the virtue of being easier to remember and therefore more likely to be appropriately applied in clinical settings, are currently being tested (Norman et al., 2007). For these reasons, the diagnostic criteria for PTSD may see refinement in DSM-V. The ASD diagnostic category has also seen its share of controversy in its short existence. It emphasizes the presence of dissociative symptoms to a much greater extent than its slightly later-occurring counterpart, PTSD. The rationale for the emphasis on dissociative symptoms is the finding in many studies that the presence of peritraumatic dissociative symptoms predicts later PTSD symptoms over and above the variance accounted for

by other (that is, reexperiencing, avoidance and numbing, and hyperarousal) acute stress symptoms (Classen et al., 1998; Ehlers et al., 1998; Murray et al., 2002). However, some studies have failed to find that dissociative symptoms provide any unique predictive utility for subsequent PTSD (Brewin et al., 1999), supporting an argument against requiring dissociative symptoms as a core feature of ASD (Marshall et al., 1999). Although the controversy is far from settled, it is clear that the current ASD criteria—though perhaps offering good positive predictive value for subsequent PTSD— fail to account for many (more than one half, in some studies) (Murray et al., 2002) of the individuals who go on to develop PTSD (that is, despite not having DSM-IV ASD as a forerunner). Some investigators have found that an ASD definition that does not necessitate the presence of dissociative symptoms (“subthreshold ASD”) is equally predictive of later PTSD (Harvey and Bryant, 1999). It is also arguable that the ASD is part of a continuum of the response to traumatic stress, and that it merges with time into acute and then chronic PTSD (Shalev, 2002). If this is true, and there are no clear demarcations between ASD and PTSD other than chronology, then it is in fact reasonable to wonder if there is merit to retaining the ASD diagnosis at all (Brewin et al., 2003), or if it would be more parsimonious to identify stages of one disorder—PTSD. For all these reasons, the ASD diagnostic criteria are prime candidates for revision—or serious consideration as to the merits of excising the diagnosis altogether—in DSM-V. Spinning Psychopathology on its Axes: Tilting at Windmills? Another area where changes relevant to DSM anxiety disorders might be anticipated is in the overlap between certain Axis I and Axis II (that is, personality) disorders. It is well-recognized, and has been for some time (Holt et al., 1992; Widiger, 1992), that the generalized form of social anxiety disorder (GSAD) on Axis I and avoidant personality disorder (APD) on Axis II are substantially (50%–90% of cases) overlapping (van Velzen et al., 2000; Tillfors et al., 2001). Although DSMIV explicitly directs attention to this extensive overlap in the diagnostic criteria for social anxiety disorder, it did nothing to resolve the apparent redundancy of this bi-axial representation for what is almost certainly the same set of phenomena (Chavira and Stein, 2002). This particular issue exemplifies one of the problems that beleaguer the Axis I versus Axis II distinction, namely, that some so-called Axis I disorders have characteristics typically ascribed to an Axis II disorder: onset in childhood and characteristic of the individual’s longterm functioning. Persons with GSAD usually have the onset of the disorder very early in life and, in fact, often

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start off with a behaviorally inhibited temperament that merges imperceptibly into the social phobia once the individual is old enough to express symptoms that meet diagnostic criteria (Biederman et al., 2001; Stein et al., 2001). In this regard, this particular Axis I disorder often has the look and feel of a personality disorder. What, then, is the additional information contained in additionally applying an Axis II diagnosis, APD, to so many of these individuals? One might argue that applying the Axis II diagnosis would be warranted if it told us something useful about the course or prognosis of such persons. In a large naturalistic 5-year follow-up study of patients with anxiety disorders, the presence of APD was found to predict a 41% lower likelihood of remission from social anxiety disorder, compared to those without APD (Massion et al., 2002). In that study, Global Assessment Scale scores at baseline clearly demonstrated that patients with APD, who made up approximately 35% of the sample, were more severely impaired than those without APD. If APD is predictive of poorer outcomes only because it denotes a more severe form of the illness, then this fact could easily be conveyed without invoking the need for an additional diagnosis on a separate axis. For this reason, as foreshadowed in the DSM-IV TR (APA, 2000), we expect APD to go the way of the dinosaur in DSMV. This is not to imply, however, that personality is unimportant in GSAD (or, indeed, in other forms of psychopathology). It is merely intended to underscore the notion that abnormal personality characteristics are implicitly embedded within certain Axis I disorder definitions—GSAD being a case in point—and that future versions of our classificatory system would do well to eliminate this nosological redundancy. However, before we consign APD to the diagnostic scrap heap, we must address the somewhat unexpected finding in some surveys (e.g., Grant et al., 2005) that there are substantial numbers of individuals in the community who meet diagnostic criteria for APD but not for social anxiety disorder. ALTERNATIVE MODELS FOR DIAGNOSTIC CLASSIFICATION OF ANXIETY DISORDERS DSM is a categorical nosology wherein you either have a disorder or you don’t. An alternative to the categorical approach to classification is a dimensional approach (Kessler, 2002), which some would call a spectrum approach (Maser and Patterson, 2002). There are pros and cons to each of these classificatory approaches. A categorical approach to diagnosis has the advantage of yielding a picture of a classic patient, from which deviations are to be expected. This may be easier to teach and might be expected to yield more reliable diagnoses (though this claim is unproven). A dimensional approach

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lets you see an individual from various perspectives, thereby reducing the need to pigeonhole people (or rely heavily on “not otherwise specified [NOS]” diagnoses). A dimensional approach also has the advantage of strictly limiting the tendency for persons to acquire more and more diagnoses with each subsequent edition of DSM. The current and lifetime prevalence of additional (that is, comorbid) Axis I disorders in principal anxiety and mood disorders among patients in an anxiety disorders outpatient clinic was found to be 57% and 81%, respectively (Brown et al., 2001). This comorbidity conundrum, surely an artifact of DSM’s categorical imperative, would not occur (or would be markedly attenuated) with a dimensional approach to diagnosis: Each individual would have only one diagnosis (or perhaps only one diagnosis in the mood–anxiety spectrum, though he or she might carry another in the substance-use spectrum, for example), but the variegation in his or her psychopathology would be expressed along dimensional lines. To the extent that simplification can be seen as a virtue in and of itself, the reduction in comorbidity that would be associated with a move to a dimensional approach is appealing. Are there other considerations? At first glance, it might seem that a categorical approach would do a better job than a dimensional approach at enabling the separation of normal from pathological. But this is illusory, as we see from the flurry of publications about the high prevalence of “subthreshold” anxiety disorders (for example, subthreshold panic disorder; Batelaan et al., 2007), and the difficulty (or futility) of separating them from “full” anxiety disorders (Davidson et al., 1994; Olfson et al., 1996; Bienvenu et al., 1998; Stein et al., 2000; Marshall et al., 2001). DSM with its categorical nosology implies that if you have less than the “disorder,” you have nothing. Yet empirical research and common sense indicate that this is surely not the case. A better solution might be to identify dimensions of psychopathology that afflict an individual and then independently assess the aggregate extent to which that individual is impaired by his or her symptoms. It is this latter assessment that would determine presence of a mental disorder and the trappings thereof (for example, eligibility for treatment, possibility of disability determination). In contrast, awareness of the patient’s symptom dimensions could guide treatment with an eye toward including therapeutic elements empirically proven for that symptom cluster. For example, if the patient suffered from obsessive–compulsive and depressive symptoms, it might be possible to prioritize these on the basis of severity, and then sequentially institute cognitive-behavioral modules targeted at the symptoms. Farther in the future, if dimensional approaches to psychopathology are more successful than have been our current diagnostic approaches at elucidating differential neurobiologies (Maser and Patterson, 2002),

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it might be possible to similarly choose among neural system–specific treatments in an equally rational fashion. Personality theorists seem to be leaning toward instituting a dimensional approach to personality disorder diagnosis in DSM-V (Livesley and Jang, 1998; Widiger and Samuel, 2005). Applying a dimensional nosology to anxiety disorders, for many of the same reasons, has considerable appeal. Let us consider several possible approaches to this venture. Neurosis Revisited: Splitters Unite! Neurosis is a concept that has been present since the beginning of modern psychiatric classification. Though initially considered a single condition (Tyrer, 1985), it has gradually been divided into many supposedly distinct entities, as influenced by clinicians such as Carter (1853), Freud (1895/1924), Janet (1908), Kraepelin (1921), Lewis (1934), and Klein (1964). In DSM-II, there were phobic, anxiety, obsessive–compulsive, hysterical, depressive, and neurasthenic neuroses. In DSM-III, the anxiety disorders were reconstructed as above, hysterical neuroses were classified as either somatoform or dissociative disorders, depressive neuroses were classified as affective disorders, and neurasthenic neurosis was eliminated. One argument for the utility of the neurosis construct is that there is such extensive “comorbidity” among the various neurotic conditions, especially if one takes a lifetime perspective. High comorbidity among anxiety and depressive disorders is a consistent finding in clinical and community studies (Maser and Cloninger, 1990; Kessler, 1995; Merikangas et al., 1996). It may be that, by focusing on what is distinct about each condition, we have paid too little attention to what they have in common. That is, there may be a “core psychopathological process” that relates these conditions (Krueger, 1999a). What accounts for the high comorbidity among neurotic conditions? Slater and Slater (1944) proposed a theory of neurosis in which constitutional predisposing factors, including personality, influence the likelihood of neurotic symptoms in the context of environmental stressors. Hans Eysenck believed that the combination of personality traits, high neuroticism (one’s tendency to experience negative emotions and cope poorly), and low extraversion (one’s quantity and intensity of interpersonal interactions and positive emotions) predisposed persons to neurotic conditions (Eysenck and Rachman, 1965). This combination of personality traits is also referred to as “trait anxiety” (Gray, 1970) and “harm avoidance” (Cloninger et al., 1993) and is highly related to mood and anxiety disorders, as is its related construct, neuroticism (also referred to as “negative affect”; Clark et al., 1994). However, in the context of the current nomenclature of anxiety and depressive disorders, neither extraversion nor one of its aspects, “positive

affect,” appear to be associated with all of these conditions, though low extraversion is associated with social phobia and agoraphobia (Solyom et al., 1986; Brown et al., 1998; Bienvenu et al., 2001; Bienvenu et al., 2007). Bievenu and colleagues (2001) found that elevated neuroticism, and, to a lesser extent, reduced extraversion, accounted for a substantial portion of anxiety and depressive disorder comorbidity in a community sample. It should be noted that it remains unclear how personality traits are related to anxiety disorders, as this area has not been investigated nearly as much as has the relationship between high neuroticism and major depression. High neuroticism appears to be a predisposing factor for, a complication of, a negative prognostic factor in, and a result of common genetic and environmental determinants with major depression (Kendler et al., 1993; Clark et al., 1994). A few studies suggest that high neuroticism or its analogues predict the onset of anxiety disorders (Angst and Vollrath, 1991; Krueger, 1999a). Cross-sectional twin analyses suggest that there is substantial overlap between the genetic factors that influence individual variation in neuroticism and those that increase liability for a variety of anxiety disorders (Hettema et al., 2006). Extraversion has received less attention, though we recently found that the genetic factors that influence (low) extraversion also appear to influence liability to social phobia and agoraphobia (Bienvenu et al., 2007). A Fear-Phobia-Anxiety Dimension? Alternate systems for dimensional classification have recently been proposed. These have been empirically derived by examining the co-aggregation of symptoms elicited by DSM-III-R or DSM-IV–based diagnostic interviews. Krueger (1999b) conducted a confirmatory factor analysis of common mental disorders in the community-based National Comorbidity Survey. He found that two factors—“internalizing” (represented as one higher-order factor with two lower-order, highly intercorrelated factors, “anxious-misery” and “fear”) and “externalizing” (encompassing DSM-III-R diagnoses of antisocial personality disorder, alcohol and drug dependence) emerged. The internalizing factor covered all of the anxiety (and mood) disorders. Krueger and colleagues (1998) further argued that if so many disorders have “comorbidity,” then maybe this is the signal rather than the noise, and that the true structure of mental disorders is represented by these latent constructs. In looking in detail at the internalizing factor that includes the anxiety and unipolar mood diagnoses, Krueger and Finger (2001) also found that higher scores along this factor are associated with higher social costs, “a phenomenon not well captured by the ‘comorbidity’ concept” (p. 140). They concluded that the field would benefit from the development of measures that permit

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the assessment of the full range of the internalizing factor in a graded, continuous fashion. With similar goals in mind, Vollebergh and colleagues (2001) analyzed the underlying latent structure of 12-month DSM-III-R diagnoses of nine common disorders in a large (N = 7076) Dutch general population sample. They tried to establish stability across a 1-year period (“structural stability”) and to evaluate individual differences in mental disorders at the levels of the latent dimensions (differential stability). They found that a three-dimensional model provided the best fit to the observed data: (1) alcohol, drug dependence; (2) mood disorders (MDD, dysthymia)—including GAD; and (3) phobic disorders and panic. The authors concluded that their findings “underline the argument for focusing on core psychopathological processes rather than on their manifestation as distinguished disorders in future population studies on common mental disorders” (Vollebergh et al., 2001, p. 597). Both of the aforementioned studies are constrained in having limited their questions to those already instrumental to the DSM-III-R and DSM-IV definitions. It might not be surprising, then, that certain DSM disorders fit neatly into the latent structure underlying such a system. Future epidemiologic studies that ask respondents about a much broader range of symptoms may or may not find a similar latent structure; this remains to be determined. Despite this limitation, however, the take-home message from these studies is that nature does not feel compelled to follow the rules of our current DSM. If this is true, we must seriously wonder about the futility of conducting research (epidemiologic, neurobiologic, and outcomes) that adheres so carefully to the DSM nosology. Future studies in our field should strongly consider measuring at least some of these dimensional aspects, even if the primary focus is on more “traditional” DSM-based diagnoses. As a case in point, a recent population-based twin study showed that whereas genetic correlations between neuroticism and each of the “internalizing disorders” were high, there was a neuroticism-independent genetic factor that significantly increased risk for MDD, GAD, and panic disorder (Hettema et al., 2006). In contrast, there was no evidence of personality-independent genetic factors for social phobia or agoraphobia (Bienvenu et al., 2007). This type of approach demonstrates the complexities of diagnostic categorization, as well as the heuristic value of using a multimodel approach to research of this genre. A FEAR FOR ALL REASONS: A DIMENSIONAL OR QUANTITATIVE TRAIT APPROACH The neurosis construct, as outlined above, attempts to inclusively describe core features that cut across most of what we recognize as anxiety and related conditions.

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The attempt there is to model key characteristics of anxiety within a single domain, thereby explaining much of the variance in what separates normality from anxietybased psychopathology. The neurosis model has as one of its very appealing properties the ability to boil down multiple anxiety-related behaviors into a single construct. This might be thought of as a higher-order factor that is typical of all or most persons with anxiety disorders. An alternative, though conceptually related notion, would be to identify and quantify the presence of anxietyrelated psychopathology along a variety of dimensions. For example, one might identify a panic–agoraphobic spectrum, a social phobia–shyness spectrum, and an obsessive–compulsive spectrum, as has recently been espoused (Cassano et al., 1997; Dell’Osso et al., 2002; Maser and Patterson, 2002; Nestadt et al., 2002). This approach could, we suppose, be integrated with the concept of neurosis. Just as neurosis can be viewed as a higher-order factor underlying the symptoms of most anxiety-related conditions (Andrews et al., 1990), these more disorder-specific dimensions could be viewed as more differentiated (lower-order) factors. This model, it should be noted, is consistent with genetic modeling of the heritability of phobias: There appear to exist common genes that convey a general vulnerability for “phobia proneness” (Kendler et al., 1999), as well as other genes that convey unique (or disorder-specific) vulnerability (Hettema, Neale, and Kendler, 2001). From a clinical perspective, we might note that an individual has a “neurotic disorder,” and then specify the characteristics of that person’s neurotic disorder along dimensional lines. An example might be: neurotic disorder with predominantly social anxiety-related features. A New “DSM”: A “Dimensional Symptoms Manual” What are the practical implications of considering a move to a dimensional system of anxiety (and perhaps mood) disorder nosology? First, we can expect an outcry from practitioners and researchers alike questioning the need to change the status quo. Any dramatic change to our classificatory system, a mere 20-plus years after the introduction of DSM-III, is bound to elicit cries of incredulity, “What, not again!” This outcry would be warranted, as there are presently insufficient data to support this sea change in our approach to diagnosis. Before a wholesale switch from discrete to dimensional diagnosis could be recommended, a plethora of studies comparing and contrasting the strengths or weaknesses of each approach in a variety of settings (for example, community, cross-cultural, primary care, specialty outpatient clinic, hospital-based) would be necessary. We should not expect these changes to come swiftly (if at all). They will surely not be a part of DSM-V but may see the light of day in future generations of this venerable tome.

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Farther into the Future Ultimately, scientific support will accrue for moving from a symptom-based classification system to an etiologically based diagnostic system for anxiety disorders. Although our understanding of the neurobiology of anxiety disorders is growing in leaps and bounds, we are not there yet. If forced to speculate, we could envision the trajectory of current research eventually (5 to 10 years down the road) leading to a genetically based classification system (for example, disorders associated with abnormal serotonin transporter function) (Lesch et al., 1996; Jorm et al., 2000) or a system that recognizes interactions between life stress and genetic susceptibility (for example, disorders associated with childhood maltreatment and abnormal serotonin transporter function) (Caspi and Moffitt, 2006; Stein et al., 2008). Alternative—although by no means mutually exclusive— systems could group disorders based on shared abnormalities in function within specific brain regions (for example, the amygdala) (Etkin and Wager, 2007; Stein et al., 2007; Tillfors et al., 2002; Phan et al., 2006) or alterations in corticolimbic connectivity (Shin et al., 2005) (which may, at least in part, be genetically mediated; Pezawas et al., 2005). Prefaced on a solid understanding of the neurobiological basis of anxiety, the development of an etiologically based diagnostic system is our field’s holy grail. We must recognize that anything short of that is bound to be inadequate, certain to be ephemeral, but nonetheless clinically and heuristically useful as we strive toward that goal. REFERENCES American Psychiatric Association. (1980) Diagnostic and Statistical Manual of Mental Disorders, 3rd ed. Washington, DC: Author. American Psychiatric Association. (2000) Diagnostic and Statistical Manual of Mental Disorders, 4th ed., text rev. Washington, DC: Author. Andrews, G., Stewart, G., Morris-Yates, A., Holt, P., and Henderson, S. (1990) Evidence for a general neurotic syndrome. B. J. Psychiatry 157:6–12. Angst, J., Gamma, A., Joseph, B.O., Eaton, W.W., Ajdacic, V., Eich, D., et al. (2006) Varying temporal criteria for generalized anxiety disorder: prevalence and clinical characteristics in a young age cohort. Psychol. Med. 36:1283–1292. Angst, J., and Vollrath, M. (1991) The natural history of anxiety disorders. Acta Psychiatr. Scand. 84:446– 452. Bartz, J.A., and Hollander, E. (2006) Is obsessive-compulsive disorder an anxiety disorder? Prog. Neuropsychopharmacol. Biol. Psychiatry 30:338–352. Batelaan, N., de Graaf, R., Van Balkom, A., Vollebergh, W., and Beekman, A. (2007) Thresholds for health and thresholds for illness: panic disorder versus subthreshold panic disorder. Psychol. Med. 37:247–256. Biederman, J., Hirshfeld-Becker, D.R., Rosenbaum, J.F., Hérot, C., Friedman, D., Snidman, N., et al. (2001) Further evidence of association between behavioral inhibition and social anxiety in children. Am. J. Psychiatry 158:1673–1679. Bienvenu, O.J., Brown, C., Samuels, J.F., et al. (2001) Normal personality traits and comorbidity among phobic, panic, and major depressive disorders. Psychiatry Res. 102:73–85.

Bienvenu, O.J., Hettema, J.M., Neale, M.C., Prescott, C.A., and Kendler, K.S. (2007) Low extraversion and high neuroticism as indices of genetic and environmental risk for social phobia, agoraphobia, and animal phobia. Am. J. Psychiatry 164(11): 1714–1721. Bienvenu, O.J., Nestadt, G., and Eaton, W.W. (1998) Characterizing generalized anxiety: temporal and symptomatic thresholds. J. Nerv. Ment. Dis. 186:51–56. Bienvenu, O.J., Nestadt, G., Samuels, J.F., Howard, W.T., Costa, P. T., Jr., and Eaton, W.W. (2001) Phobic, panic, and major depressive disorders and the five-factor model of personality. J. Nerv. Ment. Dis. 189:154–161. Bienvenu, O.J., Onyike, C.U., Stein, M.B., Chen, L.S., Samuels, J., Nestadt, G., et al. (2006) Agoraphobia in adults: incidence and longitudinal relationship with panic. Br. J. Psychiatry 188:432– 438. Breslau, N., and Davis, G.C. (1985) DSM-III generalized anxiety disorder: an empirical investigation of more stringent criteria. Psychiatry Res. 14:231–238. Breslau, N., Davis, G.C., Andreski, P., and Peterson, E.L. (1991) Traumatic events and posttraumatic stress disorder in an urban population of young adults. Arch. Gen. Psychiatry 48:216–222. Breslau, N., and Kessler, R.C. (2001) The stressor criterion in DSMIV posttraumatic stress disorder: an empirical investigation. Biol. Psychiatry 50:699–704. Breslau, N., Lucia, V.C., and Davis, G.C. (2004) Partial PTSD versus full PTSD: an empirical examination of associated impairment. Psychol. Med. 34:1205–1214. Brewin, C.R., Andrews, B., and Rose, S. (2003) Diagnostic overlap between acute stress disorder and PTSD in victims of violent crime. Am. J. Psychiatry 160:783–785. Brewin, C.R., Andrews, B., Rose, S., and Kirk, M. (1999) Acute stress disorder and posttraumatic stress disorder in victims of violent crime. Am. J. Psychiatry 156:360–366. Brown, T.A., Campbell, L.A., Lehman, C.L., Grisham, J.R., and Mancill, R.B. (2001) Current and lifetime comorbidity of the DSM-IV anxiety and mood disorders in a large clinical sample. J. Abnorm. Psychol. 110:585–599. Brown, T.A., Chorpita, B.F., and Barlow, D.H. (1998) Structural relationships among dimensions of the DSM-IV anxiety and mood disorders and dimensions of negative affect, positive affect, and autonomic arousal. J. Abnorm. Psychol. 107:179–192. Carter, R.B. (1853) On the Pathology and Treatment of Hysteria. London: Churchill. Caspi, A., and Moffitt, T.E. (2006) Gene-environment interactions in psychiatry: joining forces with neuroscience. Nat. Rev. Neurosci. 7:583–590. Cassano, G.B., Michelini, S., Shear, M.K., Coli, E., Maser, J.D., and Frank, E. (1997) The panic agoraphobic spectrum: a descriptive approach to the assessment and treatment of subtle symptoms. Am. J. Psychiatry 154:27–38. Chavira, D.A., and Stein, M.B. (2002) Phenomenology of social phobia. In: Stein, D.J., and Hollander, E., eds. The American Psychiatric Publishing Textbook of Anxiety Disorders. Washington, DC: American Psychiatric Publishing, pp. 289–300. Clark, L.A., Watson, D., and Mineka, S. (1994) Temperament, personality, and the mood and anxiety disorders. J. Abnorm. Psychol. 103:103–116. Classen, C., Koopman, C., Hales, R., and Spiegel, D. (1998) Acute stress disorder as a predictor of posttraumatic stress symptoms. Am. J. Psychiatry 155:620–624. Cloninger, C.R., Svrakic, N.M., and Przybeck, T.R. (1993) A psychobiological model of temperament and character. Arch. Gen. Psychiatry 50:975–990. Davidson, J.R., Hughes, D.C., George, L.K., & Blazer, D.G. (1994) The boundary of social phobia. Exploring the threshold. Arch. Gen. Psychiatry 51:975–983. Dell’Osso, L., Rucci, P., Cassano, G.B., Maser, J.D., Endicott, J., Shear, M.K., et al. (2002) Measuring social anxiety and

37: DIAGNOSTIC CLASSIFICATION obsessive-compulsive spectra: Comparison of interviews and selfreport instruments. Compre. Psychiatry 43:81–87. Eaton, W.W., Kessler, R.C., Wittchen, H.-U., and Magee, W.J. (1994) Panic and panic disorder in the United States. Am. J. Psychiatry 151:413– 420. Ehlers, A., Mayou, R.A., and Bryant, B. (1998) Psychological predictors of chronic posttraumatic stress disorder after motor vehicle accidents. J. Abnorm. Psychol. 107:508–519. Etkin, A., and Wager, T.D. (2007) Functional neuroimaging of anxiety: A meta-analysis of emotional processing in PTSD, Social Anxiety Disorder, and Specific Phobia. Am. J. Psychiatry 164:1476– 1488. Eysenck, H.J., and Rachman, S. (1965) The Causes and Cures of Neurosis. San Diego, CA: Robert R. Knapp. Fava, G. A., Grandi, S., and Canestrari, R. (1988) Prodromal symptoms in panic disorder with agoraphobia. Am. J. Psychiatry, 145: 1564–1567. Freud, S. (1895) The justification for detaching from neurasthenia a particular syndrome: the anxiety neurosis. In: J. Strachey, trans. and ed. Standard Edition of the Complete Psychological Works of Sigmund Freud, volume 3. London: Hogarth Press, pp. 90–116. (Original work published 1924) Fyer, A.J., Katon, W., Hollifield, M., Rassnick, H., Mannuzza, S., Chapman, T., et al. (1996) The DSM-IV Panic Disorder Field Trial: Panic attack frequency and functional disability. Anxiety 2:157–166. Grant, B.F., Hasin, D.S., Blanco, C., Stinson, F.S., Chou, S.P., Goldstein, R.B., et al. (2005) The epidemiology of social anxiety disorder in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J. Clin. Psychiatry 66:1351–1361. Gray, J.A. (1970) The psychophysiological basis of introversionextraversion. Behav. Res. Ther. 8:249–266. Harvey, A.G., and Bryant, R.A. (1999) The relationship between acute stress disorder and posttraumatic stress disorder: a 2-year prospective evaluation. J. Consult. Clin. Psychol. 67:985–988. Hayward, C., Killen, J.D., and Taylor, C.B. (2003) The relationship between agoraphobia symptoms and panic disorder in a nonclinical sample of adolescents. Psychol. Med. 33:733–738. Helzer, J., Robins, L., and McEvoy, L. (1987) Post-traumatic stress disorder in the general population: findings of the Epidemiologic Catchment Area survey. New Engl. J. Med. 317:1630–1634. Hettema, J.M., Neale, M.C., and Kendler, K.S. (2001) A review and meta-analysis of the genetic epidemiology of anxiety disorders. Am. J. Psychiatry 158:1568–1578. Hettema, J.M., Neale, M.C., Myers, J.M., Prescott, C.A., and Kendler, K.S. (2006) A population-based twin study of the relationship between neuroticism and internalizing disorders. Am. J. Psychiatry 163:857–864. Hettema, J.M., Prescott, C.A., and Kendler, K.S. (2001) A population-based twin study of generalized anxiety disorder in men and women. J. Nerv. Ment. Dis. 189:413– 420. Holt, C.S., Heimberg, R.G., and Hope, D.A. (1992) Avoidant personality disorder and the generalized subtype of social phobia. J. Abnorm. Psycho. 101:318–325. Horwath, E., Lish, J.D., Johnson, J., Hornig, C.D., and Weissman, M. M. (1993) Agoraphobia without panic: clinical reappraisal of an epidemologic finding. Am. J. Psychiatry 150:1496–1501. Janet, P. (1908) Obsessions and Psychasthenia. Paris: Alcan. Jorm, A.F., Prior, M., Sanson, A., Smart, D., Zhang, Y., and Easteal, S. (2000) Association of a functional polymorphism of the serotonin transporter gene with anxiety-related temperament and behavior problems in children: a longitudinal study from infancy to the mid-teens. Mol. Psychiatry 5:542–547. Katerndahl, D.A. (2000) Predictors of the development of phobic avoidance. J. Clin. Psychiatry 61:618–623. Kendler, K.S., Gardner, C.O., Gatz, M., and Pedersen, N.L. (2006) The sources of co-morbidity between major depression and

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generalized anxiety disorder in a Swedish national twin sample. Psychol. Med. 37(3):453– 462. Kendler, K.S., Karkowski, L.M., and Prescott, C.A. (1999) Fears and phobias: reliability and heritability. Psychol. Med. 29:539–553. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1992a) Generalized anxiety disorder in women: a population-based twin study. Arch. Gen. Psychiatry 49:267–272. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1992b) Major depression and generalized anxiety disorder: same genes, (partly) different environments? Arch. Gen. Psychiatry 49:716–722. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., Martin, N. G., and Eaves, L. J. (1993) A longitudinal twin study of personality and major depression in women. Arch. Gen. Psychiatry 50: 853–862. Kessler, R.C. (1995) Epidemiology of psychiatric comorbidity. In: Tsuang, M.T., Tohen, M., and Zahner, G.E.P., eds. Textbook in Psychiatric Epidemiology. New York: John Wiley and Sons, pp. 179–197. Kessler, R.C. (2002) The categorical versus dimensional assessment controversy in the sociology of mental illness. J. Health Soc. Behav. 43:171–188. Kessler, R.C., Brandenburg, N., Lane, M., Roy-Byrne, P., Stang, P. D., Stein, D.J., et al. (2005) Rethinking the duration requirement for generalized anxiety disorder: evidence from the National Comorbidity Survey Replication. Psychol. Med. 35:1073–1082. Kessler, R.C., Keller, M.B., and Wittchen, H.-U. (2001) The epidemiology of generalized anxiety disorder. Psychiatr. Clin. North Am. 24:19–37. Klein, D.F. (1964) Delineation of two drug-responsive anxiety syndromes. Psychopharmacology 5:397– 408. Klein, D.F., Zitrin, C.M., and Woerner, M.G. (1978) Antidepressants, anxiety, panic and phobia. In Lipton, M.A., DiMascio, A., and Killam, K.F., eds. Psychopharmacology: A Generation of Progress. New York: Raven Press, pp. 1401–1410. Klerman, G.L., Weissman, M.M., Ouellette, R., Johnson, J., and Greenwald, S. (1991) Panic attacks in the community: Social morbidity and health care utilization. JAMA 265:742–746. Kraepelin, E. (1921) Manic-Depressive Insanity and Paranoia. Edinburgh, UK: Livingstone Press. Krueger, R.F. (1999a) Personality traits in late adolescence predict mental disorders in early adulthood: a prospective-epidemiological study. J. Pers. 67:39–65. Krueger, R.F. (1999b) The structure of common mental disorders. Arch. Gen. Psychiatry 56:921–926. Krueger, R.F., Caspi, A., Moffitt, T.E., and Silva, P.A. (1998) The structure and stability of common mental disorders (DSM-III-R): a longitudinal-epidemiological study. J. Abnorm. Psychol. 107: 216–227. Krueger, R.F., and Finger, M.S. (2001) Using item response theory to understand comorbidity among anxiety and unipolar mood disorders. Psychol. Assess. 13:140–151. Lelliott, P., Marks, I., McNamee, G., and Tobena, A. (1989) Onset of panic disorder with agoraphobia. Toward an integrated model. Arch. Gen. Psychiatry 46:1000–1004. Lesch, K.-P., Bengel, D., Heils, A., Sabol, S.A., Greenberg, B.D., Petri, S., et al. (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274:1527–1531. Lewis, A.J. (1934) Melancholia: a historical review. J. Ment. Sci. 80:1– 42. Livesley, W.J., and Jang, K.L. (1998) Toward an empirically based classification of personality disorder. J. Personal. Disord. 14:137–151. Markowitz, J.S., Weissman, M.M., Ouellette, R., Lish, J.D., and Klerman, G.L. (1989) Quality of life in panic disorder. Arch. Gen. Psychiatry 46:984–992. Marks, I.M. (1981) Space “phobia”: a pseudo-agoraphobic syndrome. J. Neurol. Neurosurg. Psychiatry 44:387–391.

584

ANXIETY DISORDERS

Marshall, R.D., Olfson, M., Hellman, F., Blanco, C., Guardino, M., and Struening, E. (2001) Comorbidity, impairment, and suicidality in subthreshold PTSD. Am. J. Psychiatry 158:1467–1473. Marshall, R.D., Spitzer, R.L., and Liebowitz, M.R. (1999) Review and critique of the new DSM-IV diagnosis of Acute Stress Disorder. Am. J. Psychiatry 156:1677–1685. Maser, J.D., and Cloninger, C.R. (1990) Comorbidity of anxiety and mood disorders: introduction and overview. In: Maser, J.D., and Cloninger, C. R., eds. Comorbidity of Mood and Anxiety Disorders. Washington, DC: American Psychiatric Press, pp. 3–12. Maser, J.D., and Patterson, T. (2002) Spectrum and nosology: implications for DSM-V. Psychiatr. Clin. North Am. 25(4):855–885. Massion, A.O., Dyck, I., Shea, M.T., Phillips, K.A., Warshaw, M.G., and Keller, M.B. (2002) Personality disorders and time to remission in generalized anxiety disorder, social phobia, and panic disorder. Arch. Gen. Psychiatry 59:434– 440. Mataix-Cols, D., Pertusa, A., and Leckman, J.F. (2007) Issues for DSM-V: how should obsessive-compulsive and related disorders be classified? Am. J. Psychiatry 164:1313– 1314. Merikangas, K.R., Angst, J., Eaton, W.W., Canino, G., Rubio-Stipec, M., Wacker, H., et al. (1996) Comorbidity and boundaries of affective disorders with anxiety disorders and substance misuse: results of an international task force. Br. J. Psychiatry 168: 58–67. Murray, J., Ehlers, A., and Mayou, R.A. (2002) Dissociation and post-traumatic stress disorder: two prospective studies of road traffic accident survivors. Br. J. Psychiatry 180:363–368. Nestadt, G., Samuels, J.F., Riddle, M.A., Bienvenu, O.J., Liang, K.Y., Grados, M., et al. (2002) OCD: Defining the phenotype. Journal of Clinical Psychiatry 63(Suppl 6):5–7. Norman, S.B., Stein, M.B., and Davidson, J.R. (2007) Profiling posttraumatic functional impairment. J. Nerv. Ment. Dis. 195: 48–53. Olfson, M., Broadhead, W.E., Weissman, M.M., Leon, A.C., Farber, L., Hoven, C., et al. (1996) Subthreshold psychiatric symptoms in a primary care group practice. Arch. Gen. Psychiatry 53:880–886. Pezawas, L., Meyer-Lindenberg, A., Drabant, E.M., Verchinski, B. A., Munoz, K.E., Kolachana, B.S., et al. (2005) 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nat. Neurosci. 8: 828–834. Phan, K.L., Britton, J.C., Taylor, S.F., Fig, L.M., and Liberzon, I. (2006) Corticolimbic blood flow during nontraumatic emotional processing in posttraumatic stress disorder. Arch. Gen. Psychiatry 63:184–192. Regier, D.A. (2007) Obsessive-compulsive behavior spectrum: refining the research agenda for the DSM-V. CNS. Spectr. 12:343–344. Robins, L.N., Helzer, J.E., Weissman, M.M., Orvaschel, H., Gruenber, E., Burke, J.D., et al. (1984) Lifetime prevalence of specific psychiatric disorders in three sites. Arch. Gen. Psychiatry 41:949– 958. Ruscio, A.M., Lane, M., Roy-Byrne, P., Stang, P.E., Stein, D.J., Wittchen, H.U., et al. (2005) Should excessive worry be required for a diagnosis of generalized anxiety disorder? Results from the US National Comorbidity Survey Replication. Psychol. Med. 35: 1761–1772.

Shalev, A.Y. (2002) Acute stress reactions in adults. Biol. Psychiatry 51:532–543. Shin, L.M., Wright, C.I., Cannistraro, P.A., Wedig, M.M., McMullin, K., Martis, B., et al. (2005) A functional magnetic resonance imaging study of amygdala and medial prefrontal cortex responses to overtly presented fearful faces in posttraumatic stress disorder. Arch. Gen. Psychiatry 62:273–281. Slater, E., and Slater, P. (1944) A heuristic theory of neurosis. J. Neurol. Neurosurg. Psychiatry 7:49–55. Solyom, L., Ledwidge, B., and Solyom, C. (1986) Delineating social phobia. Br. J. Psychiatry 149:464 – 470. Stein, M.B., Asmundson, G.J.G., Ireland, D., and Walker, J.R. (1994) Panic disorder in patients attending a clinic for vestibular disorders. Am. J. Psychiatry 151:1697–1700. Stein, M.B., Chavira, D.A., and Jang, K.L. (2001) Bringing up bashful baby: Developmental pathways to social phobia. Psychiatr. Clin. North Am. 24:661–675. Stein, M.B., Schork, N.J., and Gelernter, J. (2008) Gene-by-environment (serotonin transporter and childhood maltreatment) interaction for anxiety sensitivity, an intermediate phenotype for anxiety disorders. Neuropsychopharmacology 33:312–319. Stein, M.B., Simmons, A., Feinstein, J.S., and Paulus, M.P. (2007) Increased amygdala and insula activation during emotion processing in anxiety-prone subjects. Am. J. Psychiatry 164:318–327. Stein, M.B., Torgrud, L.J., and Walker, J.R. (2000) Social phobia symptoms, subtypes and severity: findings from a community survey. Arch. Gen. Psychiatry 57:1046–1052. Stein, M.B., Walker, J.R., Hazen, A.L., and Forde, D.R. (1997) Full and partial posttraumatic stress disorder: findings from a community survey. Am. J. Psychiatry 154:1114–1119. Tillfors, M., Furmark, T., Ekselius, L., and Fredrikson, M. (2001) Social phobia and avoidant personality disorder as related to parental history of social anxiety: a general population study. Behav. Res. Ther. 39:289–298. Tillfors, M., Furmark, T., Marteinsdottir, I., and Fredrikson, M. (2002) Cerebral blood flow during anticipation of public speaking in social phobia: a PET study. Biol. Psychiatry 52:1113–1119. Tyrer, P. (1985) Neurosis divisible? Lancet 1:685–688. van Velzen, C.J.M., Emmelkamp, P.M.G., and Scholing, A. (2000) Generalized social phobia versus avoidant personality disorder: Differences in psychopathology, personality traits, and social and occupational functioning. J. Anx. Disord. 14:395– 411. Vollebergh, W.A.M., Iedema, J., Bijl, R.V., de Graaf, R., Smit, F., and Ormel, J. (2001) The structure and stability of common mental disorders: The NEMESIS study. Arch. Gen. Psychiatry 58: 597–603. Widiger, T.A. (1992) Generalized social phobia versus avoidant personality disorder: a commentary on three studies. J. Abnorm. Psychol. 101:340–343. Widiger, T.A., and Samuel, D.B. (2005) Diagnostic categories or dimensions? A question for the Diagnostic and Statistical Manual of Mental Disorders--fifth edition. J. Abnorm. Psychol. 114: 494 – 504. Wittchen, H.-U., Reed, V., and Kessler, R.C. (1998) The relationship of agoraphobia and panic in a community sample of adolescents and young adults. Arch. Gen. Psychiatry 55:1017–1024.

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The Molecular Genetics of Anxiety Disorders STEVEN P. HAMILTON

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Anxiety disorders are the most common type of mental disorder. The lifetime incidence of Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV; American Psychiatric Association [APA], 1994) anxiety disorders is estimated to be 28.8% among 9282 participants in the National Comorbidity Survey Replication (Kessler, Berglund, et al., 2005). This face-to-face fully structured survey additionally found that the average age of onset of anxiety disorders was 11 years. Among the anxiety disorders studied, the lifetime prevalence rates were 4.7% for panic disorder (PD), 12.5% for specific phobia, 12.1% for social anxiety disorder (SAD), 5.7% for generalized anxiety disorder (GAD), and 1.6% for obsessive–compulsive disorder (OCD). Data from the same survey found that the 12-month prevalence of DSM-IV anxiety disorders was estimated to be 18.1%, nearly twice that of mood disorders (Kessler, Chiu, et al., 2005). For specific disorders, 12-month prevalence rates were 2.7% for PD, 8.7% for specific phobia, 6.8% for SAD, 3.1% for GAD, and 1.0% for OCD. A striking observation among anxiety disorders involves the marked imbalance in the ratio of femaleto-male cases of these disorders. Females show a 1.6fold higher risk for an anxiety disorder than do males (Kessler, Berglund, et al., 2005). For much of the 20th century, anxiety disorders (subsumed under neuroses) were conceptualized as psychogenic conditions related to intrapsychic conflict. Contemporary biological psychiatry builds a case for a more prominent role for dysfunction of key neural circuits involved with emotional regulation and fear processing. Much of this argument relies on empirical psychopharmacological observations in humans (Klein, 1964), as well as experimental data from nonhuman model systems (Shekhar et al., 2001). In addition to acquired alterations in the distributed networks involved with anxiety, it is possible that an inherited biological predisposition to anxiety disorders may account for a substantial proportion of the likelihood for developing such disorders. Several decades of epidemiologically oriented research in human populations

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has shown that anxiety disorders consistently exhibit aggregation in families, and that the source of this aggregation is likely due to genetic factors. Meta-analysis of family studies, in which the risk of having a disorder in relatives of a proband affected with the disorder is calculated and compared to relatives of persons without the disorder, has been carried out for major anxiety disorders. This assessment showed that PD, specific phobia, SAD, GAD, and OCD all showed significant levels of familial aggregation (Hettema, Neale, and Kendler, 2001). Twin studies, in which differences in disease concordance rates between monozygotic and dizygotic twins are used to support a genetic component to a trait, suggest a strong contribution from genes in the liability to PD, specific phobia, SAD, and GAD. The lack of twin studies for OCD for meta-analysis precluded adequate assessment of heritability (Hettema, Neale, and Kendler, 2001). Further exploration of twin data using multivariate structural equation modeling led to the conclusion that though there are prevalence differences between genders, it appears that genetic and environmental risk factors underlying anxiety disorders do not differ between males and females (Hettema et al., 2005).

GENETIC EPIDEMIOLOGY AND MOLECULAR GENETICS OF ANXIETY DISORDERS Panic Disorder Genetic epidemiology Panic disorder (PD) is characterized by panic attacks, defined as the experience of spontaneous intense anxiety associated with an array of psychological and somatic symptoms. The diagnosis of PD requires recurrent panic attacks, accompanied by anticipatory anxiety, worry about the implications of the attacks, or significant attack-related behavior changes for at least one month (APA, 1994). As a disorder, PD is a relatively recent clinical concept, deriving from observations of the 585

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pharmacologic dissection of anxiety syndromes (Klein, 1964) as well as the development of operational criteria for the syndrome in DSM-III (APA, 1980). As noted above, the 12-month prevalence of PD is 2.7% (Kessler, Chiu, et al., 2005). This recent estimate is similar to previous estimates from an international epidemiologic study involving 40,000 participants, in whom the lifetime prevalence of PD was reported to be between 1.4% and 2.9% (Weissman et al., 1997). On Taiwan, where the reported rates of psychiatric disorders are generally lower than other countries, there was an outlier with a rate of 0.4%. Twice as many females are affected as males (Eaton et al., 1994). The mean age of onset is 24 years, with the span between 25 and 44 years of age being the period of highest risk for the disorder (Robins et al., 1984). Early descriptions of syndromes corresponding to PD have noted a familial pattern (Oppenheimer and Rothschild, 1918; Cohen et al., 1951). The use of direct interviews of probands and their relatives using operationalized criteria led to rigorous family studies. Crowe et al. found that depending on the clinical definition, the relative risk for first-degree relatives of panic probands was 7.8–10.7, suggesting prominent familial aggregation (Crowe et al., 1980; Crowe et al., 1983). These studies showed that compared with male relatives, the risk was double for female relatives. These initial observations have been confirmed in a series of family studies from a variety of research groups (Noyes et al., 1986; Hopper et al., 1987; Maier et al., 1993; Mendlewicz et al., 1993; Weissman, 1993; Fyer et al., 1995). A review of adequately designed studies reports that familial aggregation studies demonstrate a relative risk of 7.8 (range 2.6–20) to first-degree relatives of persons with PD (Knowles and Weissman, 1995). Extension of the analyses to second-degree relatives of probands with PD using the family history approach showed a relative risk of 6.8, with 9.5% of seconddegree relatives of panic probands compared to 1.4% among relatives of controls, again with female relatives being at higher risk (Pauls, Noyes, and Crowe, 1979). The family study method has also been used to identify interesting clinical patterns that appear to have a familial component. For example, one study found an increased relative risk of PD in first-degree relatives of PD probands with early (< 20 years) versus later onset panic (Goldstein et al., 1997). Similar approaches have used theoretical and clinical observations about PD, namely the “false suffocation alarm” hypothesis of PD (Klein, 1993), to test for familial transmission of symptom complexes. Using smothering symptoms as a probe, it was found that the first-degree relatives of probands with panic accompanied by smothering symptoms had a 2.7-fold higher risk for panic and a 5.7-fold higher risk for panic with smothering symptoms when compared to the first-degree relatives of panic probands

who did not experience smothering symptoms (Horwath et al., 1997). Although family studies demonstrate a familial pattern of PD aggregation, other epidemiological designs, such as twin studies, are required to show that the pattern is a result of genetic factors. Prior to the use of rigorous diagnostic criteria, early twin studies using vaguely defined syndromes, such as “neurosis,” showed higher concordance rates in monozygotic twins when compared to dizygotic twins, suggesting a genetic etiology (Slater and Shields, 1969). Studies using DSM criteria also supported a genetic component for PD, first in smaller samples (Torgersen, 1983; Skre et al., 1993; Perna et al., 1997), and then in much larger twin registry samples (Kendler et al., 1993b; Scherrer et al., 2000). A metaanalysis combining family study and twin data found that the observed data best fit a model consisting of additive genetic factors and individual environmental factors, with a heritability of 0.48 (Hettema, Neale, and Kendler, 2001). Family and twin studies thus support a modest genetic contribution to PD. Despite this observation, it is not apparent how genetic transmission occurs in PD; an initial study using DSM criteria proposed a single-gene dominant model (Pauls, Crowe, and Noyes, 1979; Pauls et al., 1980), a model subsequently modified as showing that neither dominant nor polygenic modes of inheritance could be ruled out (Crowe et al., 1983). Later segregation analyses argued that recessive and dominant models were equally likely (Vieland et al., 1993), and predicted known twin concordance rates (Vieland et al., 1996). Although segregation analyses accept a genetic component to PD, they have not determined the mode of inheritance. The co-occurrence of PD with other psychiatric conditions has led to hypotheses about genetic determinants common to more than one disorder. For example, one study of families demonstrated that by itself PD was not associated with increased risk of depression in relatives, yet comorbid depression and panic increased the risk that relatives would have either condition by itself, or as comorbid panic and depression (Weissman et al., 1993). These data argue for panic and depression being separable conditions. Nonetheless, it has been observed that children of parents with depression show high rates of anxiety disorders in general (Weissman et al., 2005), although not necessarily PD (Biederman et al., 2001). Studies of bipolar disorder (BPD) pedigrees have resulted in the observation of segregation of PD in particular families. In one study, investigators documented that approximately 18% of persons with BPD in their pedigrees had comorbid PD, and that only 5 of 41 persons with PD did not also have BPD (MacKinnon et al., 1997), providing support for a subgroup of families with a heritable susceptibility to BPD and/or PD (MacKinnon et al., 2002). This research group determined that the genetic link-

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age signal previously detected on chromosome 18 with their entire family set (Stine et al., 1995) could be further narrowed to the group of families in which the index BPD proband had PD (MacKinnon et al., 1998). Clinically, mania is notable for rapid mood switching in the presence of familiar PD (MacKinnon et al., 2003). More evidence for the possibility that both disorders share a common genetic mechanism would come from a reciprocal assessment of BPD in pedigrees selected for the segregation of PD. There is now a large literature indicating that infused lactate, inhaled carbon dioxide (CO2), or other “panicogens” precipitate panic attacks in individuals with PD, but not in healthy controls (Gorman et al., 1990). More recently, several groups have investigated whether this vulnerability may be related to a heritable risk factor that predisposes to PD. The two studies investigating lactate vulnerability are inconclusive. One found that participants with high rates of anxiety disorders among their first-degree family members were more likely to exhibit panic attacks in response to the infusion of lactate (Balon et al., 1989). The other found no differences in rates of panic or any other anxiety disorders in relatives of patients with PD who panicked during lactate infusion versus relatives of patients with PD who did not panic during the infusion (Reschke et al., 1995). More extensive exploration of heritability has been done with carbon dioxide (CO2) challenges. The observations that panic attacks in response to 35% CO2 challenge are significantly more common among healthy relatives of PD probands than among similarly healthy first-degree relatives of controls has been replicated by three investigator groups (Perna et al., 1995; Coryell, 1997; van Beek and Griez, 2000). Panic to CO2 has also been associated with a higher familial risk for PD (Perna et al., 1996) and a community-based twin study found concordance for a panic attack after CO2 inhalation to be 4 times higher in monozygotic twins compared to dizygotic twins, suggesting a genetic component (Bellodi et al., 1998). A second twin study, using mathematical modeling, found an additive genetic contribution to panic symptoms following CO2 challenge with moderate heritability estimate (that is, 0.4–0.5) (Battaglia et al., 2007). One exception to these findings is the lack of the response in children with a parent with PD (Pine et al., 2005). It remains to be seen if the genetic factors underlying CO2 and lactate sensitivity contribute to the genetic risk of PD. Molecular genetics Guided by suggestive family study and twin data, efforts have been mounted over the past two decades to identify genes for PD. Prior to the use of deoxyribonucleic acid (DNA)-based microsatellite markers, genetic linkage analysis in 26 pedigrees segregating PD with

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polymorphic blood cell markers and DNA markers near those loci were not positive (Crowe et al., 1987; Crowe et al., 1990). Twenty-three of these same families underwent a genome scan, with modest evidence for linkage (logarithm of odds ratio [LOD] score = 2.23) on chromosome 7p12 (Crowe et al., 2001). A second group ascertained families with multiple individuals with PD (Fyer and Weissman, 1999) and carried out a genome scan in 23 families that resulted in modest linkage also in the chromosome 7p15 region (Knowles et al., 1998). Expansion of this sample to 120 families showed diminished support for this region but identified two loci, on chromosomes 15q and 2q, exhibiting genome-wide statistical significance (Fyer et al., 2006). A third group performed genetic linkage analysis of a genome scan in 20 pedigrees, reporting modest evidence for linkage on chromosome 1q (Gelernter et al., 2001), a region not identified in previous scans. An additional 25 Icelandic families underwent genome scanning using a complex phenotype including PD, phobias, GAD, and somatoform pain, with a reported LOD score of 4.18 in the region of chromosome 9q31, again a region not seen in previous scans (Thorgeirsson et al., 2003). The discrepancy between these findings may suggest genetic heterogeneity in that differing samples from differing populations may harbor different combinations of risk alleles. Given the rich research literature in the biology of fear and anxiety, there are numerous plausible candidate genes potentially involved in PD susceptibility. Attempts to associate variants on these genes with PD have proven inconclusive (Gratacos et al., 2007). Genes representing most components of putative panic-related physiology, including receptors for γ -aminobutyric acid (GABA), monoamines, and neuropeptides, have been studied. Two genes stand out from these studies: the adenosine 2A receptor and catechol-O-methyltransferase (COMT). Two studies in Caucasian populations investigating the adenosine 2A receptor reported association or linkage (Deckert et al., 1998; Hamilton et al., 2004); however, two Asian studies did not report a similar association (Yamada et al., 2001; Lam et al., 2005). Catechol-O-methyltransferase is notable in that atleast five studies support the role of this gene in PD (Hamilton et al., 2002; Woo et al., 2002; Domschke et al., 2004; Woo et al., 2004; Rothe et al., 2006) in Caucasian and Asian populations. Several reasons may explain the typically negative or conflicting findings, most notably (1) low statistical power due to limited sample sizes, (2) population heterogeneity at the genetic level, (3) low prior probability compounding by multiple comparisons issues, and (4) heterogeneity in phenotype. In summary, linkage studies have not provided strong evidence of genomic regions that are highly likely to be related to PD, possibly reflective of the lower sensitivity of parametric linkage studies in diseases of uncertain mode of inheritance and in which multiple genes

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of small effect may be operative. This last point has also hampered candidate gene-oriented studies. It is hoped that the current use of genome-wide association methods in large clinical samples will provide novel insights into PD genetics. Phobias Specific phobia and SAD constitute the most common anxiety disorders. Specific phobia is notable for an unreasonable and persistent fear of objects or situations. The phobic stimulus rapidly elicits intense anxiety accompanied by physiological symptoms of arousal, leading to avoidance of the stimulus. Social anxiety disorder (formerly social phobia) is characterized by marked fear of social or performance situations. Again, these stimuli provoke intense anxiety, often panic attacks, and result in avoidance behaviors. There are fewer family studies of phobia, but they support familial aggregation of these disorders. For specific phobia, rates of the disorder among first-degree relatives of probands was 31%, compared to 9% in relatives of nonphobic controls, resulting in a four-fold increase in risk (Fyer et al., 1995). Studies focusing on familial aggregation of generalized social phobia also document elevated rates in families of probands compared to controls (Fyer et al., 1993; Mannuzza et al., 1995; Stein, Chartier, Hazen, et al., 1998). Twin studies also support a genetic contribution to phobias, suggesting moderate genetic heritability in the range of 0.3–0.4 across phobia types. Interestingly, the residual risk has little contribution from shared environment and instead derives from environmental factors unique to the individual (Hettema, Neale, and Kendler, 2001). The strongest evidence derives from investigation of over 2000 twin pairs in the populationbased Virginia Twin Registry (Kendler et al., 1992b, 1993a; Hettema et al., 2005) using a DSM-based instrument that identified social phobia and the animal and situational subtypes of specific phobia. The multivariate genetic model that best fit the observed data suggested a shared genetic liability between phobias, amounting to 30%– 40% of the risk, as well as individual-specific environmental factors (Kendler et al., 1992b; Kendler et al., 2001) Specific heritabilities were estimated at 0.51, 0.47, and 0.46 for social phobia, and the animal and situational subtypes of specific phobia, respectively. More recently, twin studies of preadolescent children in which parents were interviewed about fears and phobias in their children showed high heritability and a more prominent contribution from family environment (that is shared environment) (Lichtenstein and Annas, 2000; Bolton et al., 2006). Other twin studies have focused on determining the heritability of a broader nonclinical definition of irrational fears (Torgersen, 1979; Rose and Ditto, 1983; Phillips et al., 1987; Sundet et al., 2003). These studies

identify participants who have specific irrational fears, but some will also have DSM phobia, whereas some will not meet full criteria. For example, two studies using the Fear Survey Schedule (Geer, 1965), which includes 51 common fears were carried out in a substantial number of twins (Phillips et al., 1987; Sundet et al., 2003). Both studies found that specific genetic factors account for substantial liability for fears that are commonly seen in specific phobia, such as small animals or situations (water, heights, enclosed spaces), with moderate heritability, ranging from 20%– 47%. Molecular genetics Despite its high prevalence, specific phobia has not been the focus of molecular genetic investigations. No linkage studies in pedigrees identified through specific phobia probands have been carried out. One study focusing on specific phobia as a phenotype utilized a pedigree sample collected using PD probands (Gelernter et al., 2003). Fourteen of the available pedigrees contained more than one participant with DSM-III-R specific phobia, with natural environment and situational phobias predominating, with most having onset prior to age 20. Parametric analysis of a microsatellite genomic screen showed a peak on chromosome 14 at 36.7cM, with a LOD score = 3.17 under a dominant genetic model. Correlation of phobia subtypes with linkage results suggests that the observed chromosome 14 region was identified in families enriched for nonsituational phobia subtypes. Using a similar approach in their PD pedigrees, Gelernter et al. (2004) performed analyses focusing on SAD. A nonparametric linkage score of 3.4 occurred at 62cM on chromosome 16, while a parametric LOD score of 2.22 was observed at 71cM, also on chromosome 16 (Gelernter et al., 2004). This same group subsequently broadened their anxiety phenotype and utilized a novel statistical method implementing “fuzzy clustering” methodology (Kaabi et al., 2006). The phenotypes of specific phobia, SAD, PD, and agoraphobia were examined in 19 pedigrees, assuming that all of these disorders were expression of a single underlying genetic trait. This analysis resulted in a genome-wide significant linkage to chromosome 4q31-q34, near the neuropeptide Y1 receptor gene (NPY1R), which encodes a protein that plays a role in experimental anxiety (Sorensen et al., 2004). A similar approach was carried out in Icelandic pedigrees by combining anxiety disorder phenotypes in 62 pedigrees in which 33% and 50% of participants with anxiety disorder had specific phobia and SAD, respectively. A maximum allelesharing LOD score of 2.0 was reported for chromosome 9q at 104cM for the broad anxiety phenotype, increasing to 4.18 when examining a smaller group of 25 families that had one or more individuals with PD

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(Thorgeirsson et al., 2003). There are no reported candidate gene studies of specific phobia. Two negative candidate gene studies of SAD, looking at dopamine and serotonin genes (Stein, Chartier, Kozak, et al., 1998; Kennedy et al., 2001) have been reported. Generalized Anxiety Disorder Genetic epidemiology Generalized anxiety disorder (GAD) is characterized by persistent and excessive worry about several aspects of everyday life (for example, work, relationships) that is present “more days than not” for at least 6 months (DSM-IV) and is accompanied by two or more symptoms of arousal (for example, irritability, muscle tension, sleep disturbance). The lifetime prevalence of GAD is estimated at 5%–6% (Kessler, Berglund, et al., 2005) using the 6-month DSM-IV duration criterion and 9% if this requirement is reduced to 1 month (Ruscio et al., 2007). Generalized anxiety disorder is more common in women, and as many as 80% of individuals have comorbid anxiety or depression (Kessler, Chiu, et al., 2005). The genetic epidemiology of GAD has been a subject of interest in recent years, particularly in connection with attempts to clarify the diagnosis and its relationship to depression. As part of these efforts the criteria have changed a great deal over the past 30 years so that the relevance of earlier findings to the current DSM-IV definition may require additional verification. There are three reported direct interview family studies of GAD. Two were conducted in clinical populations (Noyes et al., 1987; Mendlewicz et al., 1993) and the third in a population based community sample (Newman and Bland, 2006). Results are generally consistent with familial aggregation of GAD but vary in the strength. Noyes et al. (1987) found significant familial aggregation of GAD in relatives of GAD probands versus relatives of well controls (19.5% vs. 3.5%; p < 001). The Mendlewicz et al. (1993) study included four proband groups (major depressive disorder [MDD], panic disorder [PD], GAD, and well controls). Although the morbidity risk for GAD in relatives of GAD probands was higher than that in relatives of controls (8.9 vs. 1.9) this difference did not reach the 0.05 level of significance in the four-way comparison. Newman and Bland (2006) found that relatives of GAD probands were 1½ to 2 times as likely to have GAD as relatives of controls. Molecular genetics Results of two large registry-based twin studies (Roy et al., 1995; Kendler, 1996; Hettema, Prescott, and Kendler, 2001; Mackintosh et al., 2006) indicate a modest to

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moderate genetic contributions to GAD with heritabilities in the range of 15%–40%. The residual heritability for GAD comes from specific environmental events, with no evidence of influence from family (common) environment. Analyses by Kendler and colleagues in both of these twin registries (Virginia, Sweden) also indicate that there is complete overlap in the genetic factors that contribute to risk for GAD and major depression. According to this model, environmental factors specific to the individual determine whether the clinical syndrome is expressed as GAD or MDD (Kendler et al., 1992a; Roy et al., 1995; Kendler, 1996; Kendler et al., 2007). There are no published linkage studies or replicated candidate gene findings for GAD, although two small studies of a mixture of individuals with anxiety disorder found an association between the monoamine oxidase A gene (MAO-A) and GAD, although using different genetic markers (Tadic et al., 2003; Samochowiec et al., 2004). Obsessive–Compulsive Disorder Genetic epidemiology In obsessive–compulsive disorder (OCD), patients report obsessions, or persistent intrusive thoughts, usually focused on checking, symmetry, or contamination. Compulsions, or ritualistic tasks interfering with normal functioning, are also characteristic of OCD. Obsessive– compulsive disorder was thought to be relatively uncommon, with a prevalence of about 0.05%, before the methodological improvements seen in the large epidemiologic studies of the 1980s (Rasmussen and Eisen, 1992). The Epidemiologic Catchment Area (ECA) study, using some 9500 participants in early reports (Robins et al., 1984), and then 18,500 persons in later analyses (Karno et al., 1988), reported lifetime prevalence of DSM-III OCD ranging from 1.3% to 3.0%, in line with the 1.9% to 2.5% rates of the Cross National Collaborative Group (Weissman et al., 1994) and the more recent estimate of lifetime prevalence of 1.6% in the National Comorbidity Survey replication (Kessler, Berglund, et al., 2005). Estimates of prevalence over 6 months in the ECA sample were 1.3%–2.0% (Myers et al., 1984), although there has been some question about the stability of the diagnosis (Nelson and Rice, 1997). Like most anxiety disorders, OCD is more common in females, although this difference is slight, with some reports prior to 1970 of a slight excess (51% female vs. 49% male) (Black, 1974), although more recent studies suggest a female to male ratio of about 1.2–1.6 to one (Weissman et al., 1994). The typical age at onset of OCD is 19.5 years for males and 22.0 years for females, which represents a significant difference (Rasmussen and Eisen, 1992). This difference appears to be reflected in

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the difference in OCD gender ratios for prepubertal childhood onset (3:1, male:female) and postpubertal adolescent onset (∼1:1, male:female). It has been observed that early-onset OCD in males is associated with more frequent birth complications as well as severe and sustained symptomatology (Flament et al., 1990; Lensi et al., 1996). Obsessive–compulsive disorder has been closely studied in children and adolescents, where the disorder can be particularly impairing. As mentioned above, one provocative finding in children is the reversal of the gender ratio (Hollingsworth et al., 1980; Swedo, Rapoport, Leonard, et al., 1989), although the sex ratio observed in adolescent OCD is more characteristic of that in adults (Flament et al., 1988). Family studies prior to the use of operationalized diagnostic criteria suggested familial aggregation of obsessional states (Lewis, 1936; Brown, 1942). A large number of studies carried out starting in the 1970s, despite prominent methodological heterogeneity, also documented higher risk of OCD in first-degree relatives of OCD probands. For example, a review of 11 OCD family studies found rates of OCD in first-degree relatives to be 9.5%–25% for child probands and 0%– 20% in adult probands (Sobin and Karayiorgou, 2000). Rates were higher for studies using direct interviews as opposed to family histories. The data also suggest that early-onset OCD may represent a more heritable form of the disorder (Pauls et al., 1995; Nestadt, Samuels, et al., 2000; Hanna, Himle, et al., 2005), though this finding is not universal (Black et al., 1992; Fyer et al., 2005), and suggests that there may exist heterogeneity in OCD with regard to familial aggregation. Twin studies are not common for OCD, and there are no adoption studies. Several early studies, utilizing a total of 328 dizygotic twin pairs and 233 monozygotic twin pairs, found marginal evidence for a genetic component for OCD based on twin concordance, and usually only when OCD was grouped with other psychopathology (Carey and Gottesman, 1981; Torgersen, 1983; Andrews et al., 1990). For example, when considering a clustering of disorders comprised of dysthymia, MDD, GAD, PD, and OCD, monozygotic concordance rates were 10.2% in 186 pairs, compared to 9.6% in 260 dizygotic pairs, an insignificant difference (Andrews et al., 1990). Assessment of DSM-IV OCD at age 6 with a much larger collection of twins supports a more substantial genetic influence (Bolton et al., 2007). An alternative approach has been to use twin studies for the analysis of the heritability of obsessive–compulsive symptoms, instead of the categorical disorder. An investigation of 10,110 twin pairs from the Netherlands and the United States, composed only of children, found that there was a strong additive genetic influence (∼55%) for obsessive–compulsive symptoms, with the remainder influenced by unique environmental factors (Hudziak et al., 2004). Similar studies in adults are generally supportive of this estimate,

although they tend to be somewhat smaller (Clifford et al., 1984; Jonnal et al., 2000; Van Grootheest et al., 2007). The heterogenous experimental methodologies in the OCD twin literature add complexity to interpreting the data, especially given the lack of unbiased epidemiologically based samples. Because of these differences, meta-analysis of the extant twin studies has not been possible (Hettema, Neale, and Kendler, 2001). Yet the overall implication of these studies is that OCD has a genetic component, particularly when assessed in childhood (Van Grootheest et al., 2005). Efforts to define the mode of inheritance of OCD, as with PD, are not supportive of a simple pattern of genetic transmission. Although some studies of segregation suggest a simple genetic model (Cavallini et al., 1999; Nestadt, Lan, et al., 2000; Hanna, Fingerlin, et al., 2005), others are unable to discern a precise mode of inheritance (Alsobrook et al., 1999). Given the phenotypic heterogeneity of OCD, it would be surprising if a single major locus influences the predisposition to OCD, and it may be prudent to consider the possibility that multiple genes may be involved. Careful investigation of early-onset OCD has generated intriguing observations relating to broader categories of psychopathology (Leonard et al., 1999). For example, early-onset OCD appears to cluster in families (do Rosario-Campos et al., 2005) and is often associated with Tourette’s disorder and tics (Pauls et al., 1986; Leonard et al., 1992; Pauls et al., 1995), whereas by themselves tics are more common in families segregating OCD (Grados et al., 2001). The presence of obsessive–compulsive symptoms in disorders such as autism has been used to subset families for genetic studies (Buxbaum et al., 2004; McCauley et al., 2004) and has been proposed as a way to focus gene-finding efforts (Miguel et al., 2004). A striking example of this approach stems from the observation of high rates of obsessive–compulsive symptoms in children with the post-streptococcal autoimmune syndrome Sydenham’s chorea (Swedo, Rapoport, Cheslow, et al., 1989), leading to description of pediatric autoimmune neuropsychiatric disorder associated with streptococcal infections (PANDAS) (Swedo et al., 1998). Subsequent research showed that children with PANDAS, Sydenham’s chorea, and Tourette’s disorder were positive for D8/17, a monoclonal antibody, significantly more often than controls (Murphy et al., 1997; Swedo et al., 1997). The fact that first-degree relatives of PANDAS probands have higher rates of OCD when compared to the population suggests a potential genetic component to this interesting phenotype (Lougee et al., 2000). Molecular genetics Seven families were analyzed in the first OCD genome scan and were ascertained through pediatric-onset probands (Hanna et al., 2002). The authors observed a

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maximum multipoint linkage score of 2.25 on chromosome 9p, which was to 1.97 when additional samples and markers were added. When an additional 26 families were added, support for linkage in this region dissipated, while a separate peak on chromosome 10p emerged (Hanna et al., 2007). Another group, using 41 affected sibling pairs, also observed linkage in the region of chromosome 9p described above, reporting a parametric heterogeneity LOD score of 2.26 (Willour et al., 2004). When this latter sample was expanded to 219 families, a genome scan was performed, this region was not prominent. Instead, the investigators observed their strongest finding to be a multipoint nonparametric analysis (p = 0.0003) on chromosome 3q, with less support for regions on chromosomes 1, 7, and 15 (Shugart et al., 2006). These same families have been used to analyze obsessive–compulsive symptoms as endophenotypes, with some evidence for linkage (p = 0.0001) of chromosome 14 to hoarding symptoms in families with two or more relatives with hoarding obsessions or compulsions (Samuels et al., 2007), which have been found to cluster in families (Hasler et al., 2007) and show moderate heritability (Mathews et al., 2007). Candidate gene association studies in OCD are driven primarily by clinical observations and pharmacologic data (Goodman et al., 1990), with serotonin pathway genes under the most initial focus. For example, serotonin transporter function in blood and brain in patients with OCD is altered (Delorme et al., 2005; Hesse et al., 2005; Hasselbalch et al., 2007), and early studies of the coding sequence of the gene showed it to be unaltered in patients with OCD (Altemus et al., 1996; Di Bella et al., 1996). A number of family-based and casecontrol association studies have been reported, with conflicting results. Some groups report associations with particular variants within the gene (Ozaki et al., 2003; Hu et al., 2006). The largest studies do not support an association to the repeat polymorphism (5-HTTLPR) in the promoter region of the gene (Wendland et al., 2007), and meta-analysis suggests very minimal association (Dickel et al., 2007; Lin, 2007). The investigation of other candidate genes, including those encoding serotonin receptors and dopamine system proteins, have likewise shown inconclusive findings (Hemmings and Stein, 2006). Another gene gaining much attention with OCD is COMT, which is involved in the enzymatic metabolism of monoamine neurotransmitters. Analysis of a polymorphism leading to a valine to methionine substitution in the protein that results in alterations in activity initially suggested an association between the lower activity allele in male patients with OCD (Karayiorgou et al., 1997), which was confirmed in a subsequent study using family samples (Karayiorgou et al., 1999). Subsequent studies and a meta-analysis of extant literature (Azzam and Mathews, 2003) suggest that this gene likely has a small effect on OCD, which

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may be concentrated in males (Denys et al., 2006; Pooley et al., 2007). Researchers have capitalized on the positional cloning efforts in OCD described in the previous section by identifying in the chromosome 9p region a reasonable candidate gene, SLC1A1, which encodes the neuronal and epithelial high-affinity glutamate transporter EAAC1. Initial sequencing of the coding sequence of this gene revealed no functional polymorphisms or mutations (Veenstra-VanderWeele et al., 2001). Two later studies with a combined total of 228 families used family-based analyses of nine markers in each study, with five overlapping between studies. One study reported three single nucleotide polymorphisms (SNPs) being associated with OCD, with the signal primarily coming from males (Arnold et al., 2006). The second study reported two SNPs being associated with OCD, with one of those being associated in male samples (Dickel et al., 2006). Interestingly, these two SNPs were also genotyped in the first study but were not associated with OCD. As with PD, linkage analysis has not identified strong regions of linkage to OCD, a common experience with complex disorders. Given the modest samples used for hypothesis-based candidate gene testing, it is not surprising that results are equivocal. Similarly, the limited understanding of the biological substrates for OCD has led to analysis of sensible candidates, albeit with a very low a priori likelihood of success (Sullivan et al., 2001; Sullivan, 2007). Genetic Studies of Anxious Personality Traits As a tendency toward negative affective states, neuroticism is a personality trait included in most all models of personality (Cloninger, 1987). For example, in the five-factor model, neuroticism is characterized by traits corresponding to anxiety, depression, impulsiveness, and self-consciousness (Ebstein, 2006). Genes likely play a prominent role in neuroticism, as a study of nearly 46,000 twins found that a simple genetic model was sufficient to explain familial correlation of neuroticism, and that there was little evidence of nongenetic origins for intrafamily resemblance (Lake et al., 2000). This and other studies suggest neuroticism to be more than moderately heritable (for example, heritability [h2] = 0.5–0.6) (Jang et al., 1996; Rettew et al., 2006). Most studies in clinical and community populations have also noted a strong association between neuroticism and anxiety and depression. For example, higher neuroticism scores are correlated with levels of depression and anxiety symptoms as measured by the Eysenck Personality Inventory and the Beck Depression Scale (Jylha and Isometsa, 2006). In a survey of some 731 participants from the general U.S. population, elevated neuroticism was associated with the diagnosis of depression, as well as all anxiety disorders that were examined, including specific phobia, SAD, agoraphobia, PD, GAD,

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and OCD (Bienvenu et al., 2004). In a smaller subsample from the same population, neuroticism was associated with comorbidity between many of these same disorders (Bienvenu et al., 2001), a finding also observed in psychiatric outpatients (Cuijpers et al., 2005). These data suggest that it might prove beneficial to consider personality traits such as neuroticism to share an underlying genetic architecture with anxiety disorders. Using structural equation modeling in a sample of 9270 twins, Hettema et al. (2006) sought to examine this possibility of looking at the correlation between neuroticism and a group of “internalizing” disorders, including depression, PD, agoraphobia, SAD, GAD, and two subtypes of specific phobias (situational, animal). They found that neuroticism shared significant genetic risk with these disorders (Hettema et al., 2006). When examining GAD alone, the genetic overlap between GAD and neuroticism was nearly complete, with a correlation of 0.8 (Hettema et al., 2004). Twin studies also suggest a substantial genetic correlation between major depression and neuroticism (Kendler et al., 2006). The observations above have prompted attempts to identify the genetic determinants of personality traits such as neuroticism. Given the relative ease in acquiring personality data via self-administered instruments, large samples are often feasible for genetic studies of personality traits. For example, one group used information gathered from nearly 35,000 sibling pairs, allowing them to select pairs discordant for measures of neuroticism, as well as pairs concordant for high scores or low scores, resulting in 629 sibling pairs for analysis (Fullerton et al., 2003). A genome screen reported significant linkage to neuroticism, or quantitative trait loci (QTL), on chromosomes 1q, 4q, 7p, 12q, and 13q. The authors further observed that the findings on chromosomes 1, 12, and 13 were specific to females. A study with a similar design, selecting 757 individuals in 297 sibships out of a total of over 34,000 individuals, was used to examine a phenotype based on factor analysis involving neuroticism scores combined with subscales of anxiety and mood questionnaires. A genome screen in these families revealed modestly elevated LOD scores on chromosomes 1p and 6p, also with a gender effect (Nash et al., 2004). A study carried out in 129 sibling pairs collected on the basis of nicotine dependence, in which personality measures were taken, was also subjected to a genome screen, which found elevated, but not significant at the genome-wide level, LOD scores in the 1p and 11q regions (Neale et al., 2005), which were also present in the analysis of Fullerton et al. (2003). A final study utilizes a genomewide association approach, in which hundreds of thousands of SNPs are genotyped simultaneously on a microarray. These markers, roughly spaced across the

genome, allow a test of association between the marker and a phenotype, typically by comparing the magnitude of allele frequency differences for each marker between cases and matched controls (Christensen and Murray, 2007). In the first such study of this kind with neuroticism, 2054 individuals were selected from over 88,000 participants for their extreme high and low neuroticism scores (Shifman et al., 2008). Given the prohibitive cost of individually genotyping the samples, the investigators pooled DNA samples for genotyping. They obtained data on about 450,000 SNPs and found that none of the markers met statistical significance using a threshold taking into account the large number of tests carried out. They genotyped the 19 best SNPs in a replication sample of 1534 individuals in the top or bottom 10% of the neuroticism distribution taken from their original 88,000 participants. Only one SNP, in the cyclic adenosine monophosphate (cAMP)-specific phosphodiesterase 4D gene (PDE4D), met their criteria for replicating the association seen in their initial sample. Unfortunately, this finding was not seen in three additional external replication groups the investigators genotyped, totaling 2199 individuals. The authors did not observe association signals in the previously reported linkage regions mentioned above. These results raise the possibility that much larger samples may be required to detect small genetic influences on neuroticism. Genetic association studies have also been used to look at the possible role of specific genes in neuroticism. These genes are typically chosen based on biological hypotheses regarding mood and anxiety. For example, the serotonin transporter has been studied, with an association reported in a sample of 505 participants (Lesch et al., 1996), as well as in a meta-analysis of a number of small studies (Sen et al., 2004). This finding did not stand up in a larger single study of 4800 participants (Willis-Owen et al., 2005), nor in other recent large samples (Middeldorp et al., 2007). Animal Studies of Anxiety Much work has been carried out using rodents to understand the neurophysiology, neuropharmacology, and neuroanatomy of anxiety. The slow progress in identifying genes conferring risk for anxiety disorder has led to great interest in pursuing genetic approaches in animal model systems. Two genetic approaches have been extensively utilized in rodents to advance the understanding of anxiety biology. First, genome screens for linkage to anxiety-related traits make use of standard behavior paradigms and the ability to cross large numbers of mice efficiently. Behaviors that are analogous to human anxiety can be identified, and animals can be bred and selected for extremes of these traits such

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that they are homozygous across the genome. Interbreeding of these inbred and phenotypically divergent strains results in animals (F1 generation) each harboring a copy from each parent (for example, high trait vs. low trait) for each chromosome pair. These F1 mice are then interbred, and the resulting F2 generation tested for their behavioral trait of interest. This random mixing of genomes facilitates mapping of QTLs, by looking for regions of the genome most resembling the high-trait line in F2 animals with the highest trait scores (Flint et al., 2005). One example of this approach involves an analysis of behavior of mice on the elevated plus maze, a measure of anxiety-related behavior. This model uses the observation that rodents tend to avoid open and well-lit areas where they may be visible to predators. Paradigms like the elevated plus measure the frequency in which animals will explore these open spaces, presumably testing a balance between exploratory behavior and fear-based behavior. Investigators have further refined analysis of such behaviors, including activity on the maze and defecation, conceptualizing them as measures of “emotionality.” One such group genotyped 879 F2 mice progeny of two strains selected to have high and low levels of activity on the elevated plus maze. Behavioral testing carried out on these F2 mice showed strong evidence of linkage between three chromosomal regions and emotionality (Flint et al., 1995). Subsequent work with larger numbers of animals and more anxiety phenotypes has confirmed many of these findings (Turri et al., 1999; Turri, Datta, et al., 2001; Turri, Henderson, et al., 2001; Turri et al., 2004), as have other investigators (Gershenfeld et al., 1997; Gershenfeld and Paul, 1997), yet the actual identification of a gene that serves as the QTL has proven elusive and suggests substantial complexity underlying anxiety-related traits in mice (Willis-Owen and Flint, 2006). Other anxiety-related traits, such as contextual fear conditioning, have been used to discover QTLs (Caldarone et al., 1997; Wehner et al., 1997; Fernandez-Teruel et al., 2002). Although genes identified in this manner will be examined in human behaviors, there are challenges in interpreting these studies with regard to human pathology. The applicability of these ethological paradigms is itself problematic, particularly when extrapolating from adaptive behavior in rodents to maladaptive behavior in humans (Overall, 2000; Shekhar et al., 2001). The resolution of mapping in F2 generations is low, making it necessary to pursue large genomic regions or to use outbred mice in follow-up studies (Talbot et al., 1999). Finally, the genetic architecture of the trait may require innovative statistical approaches (Mott et al., 2000). The second major approach for using genetics to address similarities between anxiety in animal systems and anxiety disorders in humans involves gene targeting stud-

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ies. These studies typically delete a gene or components of a gene in vitro on a length of DNA identical to the genomic region in vivo. This is done in such a way that the gene is rendered inactive and not transcribed or translated. This engineered targeting construct is introduced into embryonic stem cells, where it replaces the normal copy of the gene through homologous recombination. Clones of embryonic stem cells bearing the mutated gene are selected, typically through the use of a toxic drug that can only be deactivated by a drugresistance gene that is one module of the targeting construct. These recombinant embryonic stem cells are then injected into mouse embryos that are 3 to 4 days of age, followed by implantation into foster mothers. The embryos develop into “chimeras” derived from the embryo and the embryonic stem cells; thus some fraction of the mouse will consist of cells bearing the introduced mutation, with the hope that the germ cell line will contain mutant cells to allow transmission of the mutation. These mice are bred to normal mice, and the offspring are tested for the presence of the altered gene. Mice carrying the introduced “null” allele can be interbred to generate animals homozygous for that allele. Dosage effects can be examined when the deletion or “knock-out” is heterozygous or homozygous, and technical innovations allow temporal and spatial precision to the inactivation of the gene target (Tecott, 2003). Mice can then be examined for gross defects and also subjected to behavioral testing paradigms such as the open field or elevated plus maze, as described above. It is possible to also introduce constitutively active or over-active versions of genes. This approach can similarly be used to introduce specific versions of human gene, such as those carrying particular mutations or polymorphisms seen in human genes (Chen et al., 2006). This approach has been used to examine the effects of gene deletion for a large array of genes thought to play a role in anxiety. These genes include components of the serotonergic pathway (serotonin transporter, serotonin receptors), monoamine-related genes (MAO-A, COMT, dopamine receptors), GABA and glutamate pathways, and corticotropin releasing hormone-related genes (Holmes, 2001). Beyond these genes, deletion (or overexpression) of any of a lengthy list of other genes involved in various central nervous system has been noted to result in alterations in anxiety-related behaviors. These include genes as obscure as those encoding α1,3-fucosyltransferase IX, the cellular prion protein, or transient receptor potential vanilloid type 1 channel, to more obvious genes for norepinephrine and vasopressin receptors. One of the most well studied genes in this manner involves the serotonin 1A (5-HT1A) receptor. The near simultaneous reports of successful deletion of this gene by three groups all described mice who spent signifi-

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cantly less time in the center of an open field or entered open arms of an elevated maze when compared to their wild-type littermates (Heisler et al., 1998; Parks et al., 1998; Ramboz et al., 1998). A dosage effect was noted, with mice heterozygous for the null allele showing an intermediate phenotype and approximately half the expression of the 5-HT1A protein compared to wild type (Ramboz et al., 1998). Subsequent work using conditional knockout methods showed that a normal phenotype could be “rescued” when 5-HT1A was expressed selectively in knockout mice in the hippocampus and cortex (but not in the raphé nuclei) and during the postnatal (but not adult) period (Gross et al., 2002). Interestingly, mice engineered to overexpress 5-HT1A exhibit less anxiety-like behavior than control animals (Kusserow et al., 2004). These observations provide support for the contention that dysfunction of the 5HT1A receptor may lead to elevated serotonin levels, resulting in excess anxiety. This hypothesis has led to much subsequent investigation into the role that this interesting receptor may play in mood and anxiety states (Santarelli et al., 2003; Klemenhagen et al., 2005) and provides rationale for candidate gene studies in human anxiety disorders such as PD, where a common promoter SNP in HTR1A was found to be associated (Rothe et al., 2004). One molecular component of the stress response is corticotropin releasing hormone (CRH), whose release from the hypothalamus stimulates adrenocorticotropic hormone (ACTH) release from cells of the anterior pituitary, leading to adrenal gland release of glucocorticoids to elicit blood glucose mobilization. Several lines of research suggest that CRH function is dysregulated in mood and anxiety disorders (Britton et al., 1986; Butler et al., 1990), leading to a rationale for using CRH antagonists for treatment of these disorders (Arborelius et al., 1999). Not surprisingly, gene-targeting studies in mice have been used to examine the role of CRH-related genes in anxiety and other phenotypes. Overexpression of the protein CRH itself showed elevated anxiety, as measured on the elevated plus, which was reversed with administration of a CRH antagonist (Stenzel-Poore et al., 1994). Surprisingly, deletion of this gene does not result in a discernible anxiety phenotype (Weninger et al., 1999). There are two CRH receptors, termed types 1 and 2. Both have different distributions in the central nervous system, and both bind to CRH as well as the anxiogenic neuropeptide urocortin (Moreau et al., 1997). Each of the genes encoding these receptors has been deleted in mice. Deletion of CRHR1, which is expressed in the amygdala, hippocampus, anterior pituitary, neocortex, and cerebellum, led to mice that exhibited less anxiety-like behavior in standard experimental paradigms (Smith et al., 1998; Timpl et al., 1998). These results are in keeping with the known anxiolytic effect of CRHR1 antagonists (Zorrilla et al., 2002). Given the

known pharmacology of the CRHR2 receptor, it would be expected that deletion of the CRHR2 gene would have similar effects to CRHR1. It turns out that removal of CRHR2 resulted in increased anxiety-related behaviors in three separate strains of mice (Bale et al., 2000; Coste et al., 2000; Kishimoto et al., 2000). Each of the three strains differed slightly in the extent of their anxiety phenotypes, suggesting parental strain effects. These results suggest a scenario in which CRHR1 and CRHR2 act to balance responsiveness to stress, with CRHR1 mediating CRH signals increasing anxiety, and CRHR2 dampening anxiety via urocortin or related peptides (Bale and Vale, 2004). CONCLUSION The anxiety disorders discussed in this chapter are all moderately heritable, with 20%–40% of the phenotypic variance explained by additive genetic effects. The standard methods of the past two decades for mapping genes for complex disorders, linkage analysis in pedigrees or candidate gene association studies, while providing important leads, are being supplanted by methods made possible by several developments in the field. First, the Human Genome Project and International HapMap Project have provided the raw material for studies examining dense maps of informative markers across the genome. Second, technological advances in array-based genotyping have facilitated the simultaneous, and relatively inexpensive, analysis of hundreds of thousands of SNPs in a single assay. Finally, the recognition that very large samples will be needed to recognize subtle genetic effects has led to increased efforts to ascertain sizable (that is, 1000 to 2000 cases) population-based samples and has fostered collaboration between research groups. Numerous successful applications of this genome-wide association approach have surfaced since 2005 (Klein et al., 2005; Scott et al., 2007; Wellcome Trust Case Control Consortium, 2007), with the promise of such studies for psychiatric disorders becoming a reality. Challenges for this approach involve the reliance on assumptions regarding the genetic model for anxiety disorders, as well as how to differentiate authentic genetic associations in the midst of hundreds of thousands or even millions of statistical tests involving billions of genotypes. An example of the former problem involves debate about whether risk variants for any particular disorder are common in a chosen population, versus the possibility that risk at any gene is determined by a collection of uncommon or rare variants. The latter challenge derives from the fundamental problem of assessing statistical significance of any particular association between a DNA variant and a phenotype. For example, at least 25,000 markers in a genome scan of 500,000 markers would be ex-

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pected to meet traditional criteria (p = 0.05) for statistical significance, by chance. Yet correction for every test ignores the realities of marker-to-marker correlation, as well as the possibility that multiple variants may be associated with the phenotype. Many of these debates may be resolved when reported associations are replicated in independent samples or in meta-analyses. Although animal studies have provided hints at the identity of genes that may influence anxiety disorders in humans, it is hoped that the unbiased genome-wide approaches described here will foster new discoveries of new genes or known genes not considered to be related to anxiety disorders and their many manifestations. Such discoveries are likely to generate focused genetic analyses in human anxiety disorder populations and to foster new directions for animal model studies.

REFERENCES Alsobrook, J.P. II, Leckman, J.F., Goodman, W.K., Rasmussen, S.A., and Pauls, D.L. (1999) Segregation analysis of obsessive-compulsive disorder using symptom- based factor scores. Am. J. Med. Genet. 88:669–675. Altemus, M., Murphy, D.L., Greenberg, B., and Lesch, K.-P. (1996) Intact coding region of the serotonin transporter gene in obsessive-compulsive disorder. Am. J. Med. Genet. 67:409–411. American Psychiatric Association. (1980) Diagnostic and Statistical Manual of Mental Disorders, 3rd ed. Washington, DC: American Psychiatric Association. American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: American Psychiatric Association. Andrews, G., Stewart, G., Allen, R., and Henderson, A.S. (1990) The genetics of six neurotic disorders: a twin study. J. Affect. Disord. 19:23–29. Arborelius, L., Owens, M.J., Plotsky, P.M., and Nemeroff, C.B. (1999) The role of corticotropin-releasing factor in depression and anxiety disorders. J. Endocrinol. 160:1–12. Arnold, P.D., Sicard, T., Burroughs, E., Richter, M.A., and Kennedy, J.L. (2006) Glutamate transporter gene SLC1A1 associated with obsessive-compulsive disorder. Arch. Gen. Psychiatry 63:769–776. Azzam, A., and Mathews, C.A. (2003) Meta-analysis of the association between the catecholamine-O-methyl-transferase gene and obsessive-compulsive disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. 123:64–69. Bale, T.L., Contarino, A., Smith, G.W., Chan, R., Gold, L.H., Sawchenko, P.E., Koob, G.F., Vale, W.W., and Lee, K.F. (2000) Mice deficient for corticotropin-releasing hormone receptor-2 display anxiety-like behaviour and are hypersensitive to stress. Nat. Genet. 24:410–414. Bale, T.L., and Vale, W.W. (2004) CRF and CRF receptors: role in stress responsivity and other behaviors. Ann. Rev. Pharmacol. Toxicol. 44: 525–557. Balon, R., Jordan, M., Pohl, R., and Yeragani, V.K. (1989) Family history of anxiety disorders in control subjects with lactate-induced panic attacks. Am. J. Psychiatry 146:1304–1306. Battaglia, M., Ogliari, A., Harris, J., Spatola, C.A.M., Pesenti-Gritti, P., Reichborn-Kjennerud, T., Torgersen, S., Kringlen, E., and Tambs, K. (2007) A genetic study of the acute anxious response to carbon dioxide stimulation in man. J. Psychiatric Res. 41:906–917. Bellodi, L., Perna, G., Caldirola, D., Arancio, C., Bertani, A., and Di Bella, D. (1998) CO2-induced panic attacks: a twin study. Am. J. Psychiatry 155:1184–1188.

595

Biederman, J., Faraone, S.V., Hirshfeld-Becker, D.R., Friedman, D., Robin, J.A., and Rosenbaum, J.F. (2001) Patterns of psychopathology and dysfunction in high-risk children of parents with panic disorder and major depression. Am. J. Psychiatry 158: 49–57. Bienvenu, O.J., Brown, C., Samuels, J.F., Liang, K.Y., Costa, P.T., Eaton, W.W., and Nestadt, G. (2001) Normal personality traits and comorbidity among phobic, panic and major depressive disorders. Psychiatry Res. 102:73–85. Bienvenu, O.J., Samuels, J.F., Costa, P.T., Reti, I.M., Eaton, W.W., and Nestadt, G. (2004) Anxiety and depressive disorders and the five-factor model of personality: a higher- and lower-order personality trait investigation in a community sample. Depress. Anxiety 20:92–97. Black, A. (1974) The natural history of obsessional neurosis. In: Beech, H.R., ed. Obsessional States. London: Methuen, pp. 19–54. Black, D.W., Noyes, R., Jr., Goldstein, R.B., and Blum, N. (1992) A family study of obsessive-compulsive disorder. Arch. Gen. Psychiatry 49:362–368. Bolton, D., Eley, T.C., O’Connor, T.G., Perrin, S., Rabe-Hesketh, S., Rijsdijk, F., and Smith, P. (2006) Prevalence and genetic and environmental influences on anxiety disorders in 6-year-old twins. Psychol. Med. 36:335–344. Bolton, D., Rijsdijk, F., O’Connor, T.G., Perrin, S., and Eley, T.C. (2007) Obsessive-compulsive disorder, tics and anxiety in 6-yearold twins. Psychol. Med. 37:39–48. Britton, K.T., Lee, G., Vale, W., Rivier, J., and Koob, G.F. (1986) Corticotropin releasing factor (CRF) receptor antagonist blocks activating and “anxiogenic” actions of CRF in the rat. Brain Res. 369:303–306. Brown, F.W. (1942) Heredity in the psychoneuroses. Proc. Royal Soc. Med. 35:785–790. Butler, P.D., Weiss, J.M., Stout, J.C., and Nemeroff, C.B. (1990) Corticotropin-releasing factor produces fear-enhancing and behavioral activating effects following infusion into the locus coeruleus. J. Neuroscience 10:176–183. Buxbaum, J.D., Silverman, J., Keddache, M., Smith, C.J., Hollander, E., Ramoz, N., and Reichert, J.G. (2004) Linkage analysis for autism in a subset families with obsessive-compulsive behaviors: evidence for an autism susceptibility gene on chromosome 1 and further support for susceptibility genes on chromosome 6 and 19. Mol. Psychiatry 9:144–150. Caldarone, B., Saavedra, C., Tartaglia, K., Wehner, J.M., Dudek, B. C., and Flaherty, L. (1997) Quantitative trait loci analysis affecting contextual conditioning in mice. Nat. Genet. 17:335–337. Carey, G., and Gottesman, I.I. (1981) Twin and family studies of anxiety, phobic, and obsessive disorders. In: Klein, D.F., and Rabkin, J.D., eds. Anxiety: New Research and Changing Concepts. New York: Raven Press, pp. 117–136. Cavallini, M.C., Pasquale, L., Bellodi, L., and Smeraldi, E. (1999) Complex segregation analysis for obsessive compulsive disorder and related disorders. Am. J. Med. Genet. 88:38–43. Chen, Z.Y., Jing, D., Bath, K.G., Ieraci, A., Khan, T., Siao, C.J., Herrera, D.G., Toth, M., Yang, C., McEwen, B.S., Hempstead, B.L., and Lee, F.S. (2006) Genetic variant BDNF (Val66Met) polymorphism alters anxiety-related behavior. Science 314:140– 143. Christensen, K., and Murray, J.C. (2007) What genome-wide association studies can do for medicine. New Engl. J. Med. 356:1094– 1097. Clifford, C.A., Murray, R.M., and Fulker, D.W. (1984) Genetic and environmental influences on obsessional traits and symptoms. Psychol. Med. 14:791–800. Cloninger, C.R. (1987) A systematic method for clinical description and classification of personality variants. A proposal. Arch. Gen. Psychiatry 44:573–588. Cohen, M.E., Badal, D.W., Kilpatrick, A., Reed, E.W., and White, P. D. (1951) The high familial prevalence of neurocirculatory as-

596

ANXIETY DISORDERS

thenia (anxiety neurosis, effort syndrome) Am. J. Hum. Genet. 3:126–158. Coryell, W. (1997) Hypersensitivity to carbon dioxide as a diseasespecific trait marker. Biol. Psychiatry 41:259–263. Coste, S.C., Kesterson, R.A., Heldwein, K.A., Stevens, S.L., Heard, A.D., Hollis, J.H., Murray, S.E., Hill, J.K., Pantely, G.A., Hohimer, A.R., Hatton, D.C., Phillips, T.J., Finn, D.A., Low, M.J., Rittenberg, M.B., Stenzel, P., and Stenzel-Poore, M.P. (2000) Abnormal adaptations to stress and impaired cardiovascular function in mice lacking corticotropin-releasing hormone receptor-2. Nat. Genet. 24:403–409. Crowe, R.C., Pauls, D.L., Slymen, D.J., and Noyes, R. (1980) A family study of anxiety neurosis. Morbidity risk in families of patients with and without mitral valve prolapse. Arch. Gen. Psychiatry 37:77–79. Crowe, R.R., Goedken, R., Wilson, R., Samuelson, S., Nelson, J., and Noyes, R., Jr. (2001) A genome-wide survey of panic disorder. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 105:105–109. Crowe, R.R., Noyes, R., Jr., Pauls, D.L., and Slymen, D. (1983) A family study of panic disorder. Arch. Gen. Psychiatry 40:1065– 1069. Crowe, R.R., Noyes, R., Jr., Samuelson, S., Wesner, R., and Wilson, R. (1990) Close linkage between panic disorder and alphahaptoglobin excluded in 10 families. Arch. Gen. Psychiatry 47: 377–380. Crowe, R.R., Noyes, R., Jr., Wilson, A.F., Elston, R.C., and Ward, L.J. (1987) A linkage study of panic disorder. Arch. Gen. Psychiatry 44:933–937. Cuijpers, P., van Straten, A., and Donker, M. (2005) Personality traits of patients with mood and anxiety disorders. Psychiatry Res. 133:229–237. Deckert, J., Nothen, M.M., Franke, P., Delmo, C., Fritze, J., Knapp, M., Maier, W., Beckmann, H., and Propping, P. (1998) Systematic mutation screening and association study of the A1 and A2a adenosine receptor genes in panic disorder suggest a contribution of the A2a gene to the development of disease. Mol. Psychiatry 3:81–85. Delorme, R., Betancur, C., Callebert, J., Chabane, N., Laplanche, J.L., Mouren-Simeoni, M.C., Launay, J.M., and Leboyer, M. (2005) Platelet serotonergic markers as endophenotypes for obsessivecompulsive disorder. Neuropsychopharmacology 30:1539–1547. Denys, D., Van Nieuwerburgh, F., Deforce, D., and Westenberg, H. (2006) Association between the dopamine D2 receptor TaqI A2 allele and low activity COMT allele with obsessive-compulsive disorder in males. Eur. Neuropsychopharmacology 16:446–450. Di Bella, D., Catalano, M., Balling, U., Smeraldi, E., and Lesch, K.P. (1996) Systematic screening for mutations in the coding region of the human serotonin transporter (5-HTT) gene using PCR and DGGE. Am. J. Med. Genet. 67:541–545. Dickel, D.E., Veenstra-VanderWeele, J., Bivens, N.C., Wu, X., Fischer, D.J., Van Etten-Lee, M., Himle, J.A., Leventhal, B.L., Cook, J., and Hanna, G.L. (2007) Association studies of serotonin system candidate genes in early-onset obsessive-compulsive disorder. Biol. Psychiatry 61:322–329. Dickel, D.E., Veenstra-VanderWeele, J., Cox, N.J., Wu, X., Fischer, D.J., Van Etten-Lee, M., Himle, J.A., Leventhal, B.L., Cook, E. H., Jr., and Hanna, G.L. (2006) Association testing of the positional and functional candidate gene SLC1A1/EAAC1 in earlyonset obsessive-compulsive disorder. Arch. Gen. Psychiatry 63: 778–785. do Rosario-Campos, M.C., Leckman, J.F., Curi, M., Quatrano, S., Katsovitch, L., Miguel, E.C., and Pauls, D.L. (2005) A family study of early-onset obsessive-compulsive disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet. 136:92–97. Domschke, K., Freitag, C.M., Kuhlenbaumer, G., Schirmacher, A., Sand, P., Nyhuis, P., Jacob, C., Fritze, J., Franke, P., Rietschel, M., Garritsen, H.S., Fimmers, R., Nothen, M.M., Lesch, K.P., Stogbauer, F., and Deckert, J. (2004) Association of the func-

tional V158M catechol-O-methyl-transferase polymorphism with panic disorder in women. Int. J. Neuropsychopharmacol. 7:183– 188. Eaton, W.W., Kessler, R.C., Wittchen, H.U., and Magee, W.J. (1994) Panic and panic disorder in the United States. Am. J. Psychiatry 151:413–420. Ebstein, R.P. (2006) The molecular genetic architecture of human personality: beyond self-report questionnaires. Mol. Psychiatry 11:427–445. Fernandez-Teruel, A., Escorihuela, R.M., Gray, J.A., Aguilar, R., Gil, L., Gimenez-Llort, L., Tobena, A., Bhomra, A., Nicod, A., Mott, R., Driscoll, P., Dawson, G.R., and Flint, J. (2002) A quantitative trait locus influencing anxiety in the laboratory rat. Genome Res. 12:618–626. Flament, M.F., Koby, E., Rapoport, J.L., Berg, C.J., Zahn, T., Cox, C., Denckla, M., and Lenane, M. (1990) Childhood obsessivecompulsive disorder: a prospective follow-up study. J. Child Psychol. Psychiatry 31:363–380. Flament, M.F., Whitaker, A., Rapoport, J.L., Davies, M., Berg, C.Z., Kalikow, K., Sceery, W., and Shaffer, D. (1988) Obsessive compulsive disorder in adolescence: an epidemiological study. J. Am. Acad. Child Adolesc. Psychiatry 27:764–771. Flint, J., Corley, R., DeFries, J.C., Fulker, D.W., Gray, J.A., Miller, S., and Collins, A.C. (1995) A simple genetic basis for a complex psychological trait in laboratory mice. Science 269:1432–1435. Flint, J., Valdar, W., Shifman, S., and Mott, R. (2005) Strategies for mapping and cloning quantitative trait genes in rodents. Nat. Rev. Genet. 6:271–286. Fullerton, J., Cubin, M., Tiwari, H., Wang, C., Bomhra, A., Davidson, S., Miller, S., Fairburn, C., Goodwin, G., Neale, M.C., Fiddy, S., Mott, R., Allison, D.B., and Flint, J. (2003) Linkage analysis of extremely discordant and concordant sibling pairs identifies quantitative-trait loci that influence variation in the human personality trait neuroticism. Am. J. Hum. Genet. 72:879–890. Fyer, A.J., Hamilton, S.P., Durner, M., Haghighi, F., Heiman, G.A., Costa, R., Evgrafov, O., Adams, P., de Leon, A.B., Taveras, N., Klein, D.F., Hodge, S.E., Weissman, M.M., and Knowles, J.A. (2006) A third-pass genome scan in panic disorder: evidence for multiple susceptibility loci. Biol. Psychiatry 60:388–401. Fyer, A.J., Lipsitz, J.D., Mannuzza, S., Aronowitz, B., and Chapman, T.F. (2005) A direct interview family study of obsessivecompulsive disorder. I. Psychol. Med. 35:1611–1621. Fyer, A.J., Mannuzza, S., Chapman, T.F., Liebowitz, M.R., and Klein, D.F. (1993) A direct interview family study of social phobia. Arch. Gen. Psychiatry 50:286–293. Fyer, A.J., Mannuzza, S., Chapman, T.F., Martin, L.Y., and Klein, D.F. (1995) Specificity in familial aggregation of phobic disorders. Arch. Gen. Psychiatry 52:564–573. Fyer, A.J., and Weissman, M.M. (1999) Genetic linkage study of panic: clinical methodology and description of pedigrees. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 88:173–181. Geer, J.H. (1965) The development of a scale to measure fear. Behav. Res. Ther. 3:45–53. Gelernter, J., Bonvicini, K., Page, G., Woods, S.W., Goddard, A.W., Kruger, S., Pauls, D.L., and Goodson, S. (2001) Linkage genome scan for loci predisposing to panic disorder or agoraphobia. Am. J. Med. Genet. 105:548–557. Gelernter, J., Page, G.P., Bonvicini, K., Woods, S.W., Pauls, D.L., and Kruger, S. (2003) A chromosome 14 risk locus for simple phobia: results from a genomewide linkage scan. Mol. Psychiatry 8:71–82. Gelernter, J., Page, G.P., Stein, M.B., and Woods, S.W. (2004) Genome-wide linkage scan for loci predisposing to social phobia: evidence for a chromosome 16 risk locus. Am. J. Psychiatry 161: 59–66. Gershenfeld, H.K., Neumann, P.E., Mathis, C., Crawley, J.N., Li, X., and Paul, S.M. (1997) Mapping quantitative trait loci for open-field behavior in mice. Behav. Genet. 27:201–210.

38: MOLECULAR GENETICS Gershenfeld, H.K., and Paul, S.M. (1997) Mapping quantitative trait loci for fear-like behaviors in mice. Genomics 46:1–8. Goldstein, R.B., Wickramaratne, P.J., Horwath, E., and Weissman, M.M. (1997) Familial aggregation and phenomenology of “earlyonset” (at or before age 20 years) panic disorder. Arch. Gen. Psychiatry 54:271–278. Goodman, W.K., McDougle, C.J., Price, L.H., Riddle, M.A., Pauls, D.L., and Leckman, J.F. (1990) Beyond the serotonin hypothesis: a role for dopamine in some forms of obsessive compulsive disorder? J. Clin. Psychiatry 51(Suppl 8):36–43. Gorman, J.M., Papp, L.A., Martinez, J., Goetz, R.R., Hollander, E., Liebowitz, M.R., and Jordan, F. (1990) High-dose carbon dioxide challenge test in anxiety disorder patients. Biol. Psychiatry 28:743–757. Grados, M.A., Riddle, M.A., Samuels, J.F., Liang, K.Y., Hoehn-Saric, R., Bienvenu, O.J., Walkup, J.T., Song, D., and Nestadt, G. (2001) The familial phenotype of obsessive-compulsive disorder in relation to tic disorders: the Hopkins OCD family study. Biol. Psychiatry 50:559–565. Gratacos, M., Sahun, I., Gallego, X., Mador-Arjona, A., Estivill, X., and Dierssen, M. (2007) Candidate genes for panic disorder: insight from human and mouse genetic studies. Genes Brain Behav. 6:2–23. Gross, C., Zhuang, X., Stark, K., Ramboz, S., Oosting, R., Kirby, L., Santarelli, L., Beck, S., and Hen, R. (2002) Serotonin1A receptor acts during development to establish normal anxiety-like behaviour in the adult. Nature 416:396–400. Hamilton, S.P., Slager, S.L., De Leon, A.B., Heiman, G.A., Klein, D. F., Hodge, S.E., Weissman, M.M., Fyer, A.J., and Knowles, J.A. (2004) Evidence for genetic linkage between a polymorphism in the adenosine 2A receptor and panic disorder. Neuropsychopharmacology 29:558–565. Hamilton, S.P., Slager, S.L., Heiman, G.A., Deng, Z., Haghighi, F., Klein, D.F., Hodge, S.E., Weissman, M.M., Fyer, A.J., and Knowles, J.A. (2002) Evidence for a susceptibility locus for panic disorder near the catechol-O-methyltransferase gene on chromosome 22. Biol. Psychiatry 51:591–601. Hanna, G.L., Fingerlin, T.E., Himle, J.A., and Boehnke, M. (2005) Complex segregation analysis of obsessive-compulsive disorder in families with pediatric probands. Hum. Hered. 60:1–9. Hanna, G.L., Himle, J.A., Curtis, G.C., and Gillespie, B.W. (2005) A family study of obsessive-compulsive disorder with pediatric probands. Am. J. Med. Genet. B Neuropsychiatr. Genet. 134:13–19. Hanna, G.L., Veenstra-VanderWeele, J., Cox, N.J., Boehnke, M., Himle, J.A., Curtis, G.C., Leventhal, B.L., and Cook, E.H., Jr. (2002) Genome-wide linkage analysis of families with obsessivecompulsive disorder ascertained through pediatric probands. Am. J. Med. Genet. 114:541–552. Hanna, G.L., Veenstra-VanderWeele, J., Cox, N.J., Van Etten, M., Fischer, D.J., Himle, J.A., Bivens, N.C., Wu, X., Roe, C.A., Hennessy, K.A., Dickel, D.E., Leventhal, B.L., and Cook, E.H., Jr. (2007) Evidence for a susceptibility locus on chromosome 10p15 in early-onset obsessive-compulsive disorder. Biol. Psychiatry 62 (8):831–832. Hasler, G., Pinto, A., Greenberg, B.D., Samuels, J., Fyer, A.J., Pauls, D., Knowles, J.A., McCracken, J.T., Piacentini, J., Riddle, M.A., Rauch, S.L., Rasmussen, S.A., Willour, V.L., Grados, M.A., Cullen, B., Bienvenu, O.J., Shugart, Y.Y., Liang, K.Y., Hoehn-Saric, R., Wang, Y., Ronquillo, J., Nestadt, G., and Murphy, D.L. (2007) Familiality of factor analysis-derived YBOCS dimensions in OCDaffected sibling pairs from the OCD Collaborative Genetics Study. Biol. Psychiatry 61:617–625. Hasselbalch, S.G., Hansen, E.S., Jakobsen, T.B., Pinborg, L.H., Lonborg, J.H., and Bolwig, T.G. (2007) Reduced midbrain-pons serotonin transporter binding in patients with obsessive-compulsive disorder. Acta Psychiatr. Scand. 115:388–394. Heisler, L.K., Chu, H.M., Brennan, T.J., Danao, J.A., Bajwa, P., Parsons, L.H., and Tecott, L.H. (1998) Elevated anxiety and antide-

597

pressant-like responses in serotonin 5-HT1A receptor mutant mice. Proc. Natl. Acad Sci. USA 95:15049–15054. Hemmings, S.M., and Stein, D.J. (2006) The current status of association studies in obsessive-compulsive disorder. Psychiatry Clin. North Am. 29:411–444. Hesse, S., Muller, U., Lincke, T., Barthel, H., Villmann, T., Angermeyer, M.C., Sabri, O., and Stengler-Wenzke, K. (2005) Serotonin and dopamine transporter imaging in patients with obsessive-compulsive disorder. Psychiatry Res. Neuroimaging 140:63–72. Hettema, J.M., Neale, M.C., and Kendler, K.S. (2001) A review and meta-analysis of the genetic epidemiology of anxiety disorders. Am. J. Psychiatry 158:1568–1578. Hettema, J.M., Neale, M.C., Myers, J.M., Prescott, C.A., and Kendler, K.S. (2006) A population-based twin study of the relationship between neuroticism and internalizing disorders. Am. J. Psychiatry 163:857–864. Hettema, J.M., Prescott, C.A., and Kendler, K.S. (2001) A population-based twin study of generalized anxiety disorder in men and women. J. Nerv. Ment. Dis. 189:413–420. Hettema, J.M., Prescott, C.A., and Kendler, K.S. (2004) Genetic and environmental sources of covariation between generalized anxiety disorder and neuroticism. Am. J. Psychiatry 161:1581– 1587. Hettema, J.M., Prescott, C.A., Myers, J.M., Neale, M.C., and Kendler, K.S. (2005) The structure of genetic and environmental risk factors for anxiety disorders in men and women. Arch. Gen. Psychiatry 62:182–189. Hollingsworth, C.E., Tanguay, P.E., Grossman, L., and Pabst, P. (1980) Long-term outcome of obsessive-compulsive disorder in childhood. J. Am. Acad. Child Adolesc. Psychiatry 19:134–144. Holmes, A. (2001) Targeted gene mutation approaches to the study of anxiety-like behavior in mice. Neurosci. Biobehav. Rev. 25: 261–273. Hopper, J.L., Judd, F.K., Derrick, P.L., and Burrows, G.D. (1987) A family study of panic disorder. Genet. Epidemiol. 4:33–41. Horwath, E., Adams, P., Wickramaratne, P., Pine, D., and Weissman, M.M. (1997) Panic disorder with smothering symptoms: evidence for increased risk in first-degree relatives. Depress. Anxiety 6:147–153. Hu, X.Z., Lipsky, R.H., Zhu, G., Akhtar, L.A., Taubman, J., Greenberg, B.D., Xu, K., Arnold, P.D., Richter, M.A., Kennedy, J.L., Murphy, D.L., and Goldman, D. (2006) Serotonin transporter promoter gain-of-function genotypes are linked to obsessivecompulsive disorder. Am. J. Hum. Genet. 78:815–826. Hudziak, J.J., van Beijsterveldt, C.E.M., Althoff, R.R., Stanger, C., Rettew, D.C., Nelson, E.C., Todd, R.D., Bartels, M., and Boomsma, D.I. (2004) Genetic and environmental contributions to the Child Behavior Checklist Obsessive-Compulsive Scale: A cross-cultural twin study. Arch. Gen. Psychiatry 61:608–616. Jang, K.L., Livesley, W.J., and Vernon, P.A. (1996) Heritability of the big five personality dimensions and their facets: a twin study. J. Pers. 64:577–591. Jonnal, A.H., Gardner, C.O., Prescott, C.A., and Kendler, K.S. (2000) Obsessive and compulsive symptoms in a general population sample of female twins. Am. J. Med. Genet. 96:791–796. Jylha, P., and Isometsa, E. (2006) The relationship of neuroticism and extraversion to symptoms of anxiety and depression in the general population. Depress. Anxiety 23:281–289. Kaabi, B., Gelernter, J., Woods, S.W., Goddard, A., Page, G.P., and Elston, R.C. (2006) Genome scan for loci predisposing to anxiety disorders using a novel multivariate approach: strong evidence for a chromosome 4 risk locus. Am. J. Hum. Genet. 78:543–553. Karayiorgou, M., Altemus, M., Galke, B.L., Goldman, D., Murphy, D.L., Ott, J., and Gogos, J.A. (1997) Genotype determining low catechol-O-methyltransferase activity as a risk factor for obsessivecompulsive disorder. Proc. Natl. Acad. Sci. USA 94:4572– 4575.

598

ANXIETY DISORDERS

Karayiorgou, M., Sobin, C., Blundell, M.L., Galke, B.L., Malinova, L., Goldberg, P., Ott, J., and Gogos, J.A. (1999) Family-based association studies support a sexually dimorphic effect of COMT and MAOA on genetic susceptibility to obsessive-compulsive disorder. Biol. Psychiatry 45:1178–1189. Karno, M., Golding, J.M., Sorenson, S.B., and Burnam, M.A. (1988) The epidemiology of obsessive-compulsive disorder in five US communities. Arch. Gen. Psychiatry 45:1094–1099. Kendler, K.S. (1996) Major depression and generalised anxiety disorder. Same genes, (partly) different environments—revisited. Br. J. Psychiatry 30(Suppl):68–75. Kendler, K.S., Gardner, C.O., Gatz, M., and Pedersen, N.L. (2007) The sources of co-morbidity between major depression and generalized anxiety disorder in a Swedish national twin sample. Psychol. Med. 37:453–462. Kendler, K.S., Gatz, M., Gardner, C.O., and Pedersen, N.L. (2006) Personality and major depression: a Swedish longitudinal, population-based twin study. Arch. Gen. Psychiatry 63:1113–1120. Kendler, K.S., Myers, J., Prescott, C.A., and Neale, M.C. (2001) The genetic epidemiology of irrational fears and phobias in men. Arch. Gen. Psychiatry 58:257–265. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1992a) Major depression and generalized anxiety disorder. Same genes, (partly) different environments? Arch. Gen. Psychiatry 49:716–722. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1992b) The genetic epidemiology of phobias in women. The interrelationship of agoraphobia, social phobia, situational phobia, and simple phobia. Arch. Gen. Psychiatry 49:273–281. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1993a) Major depression and phobias: the genetic and environmental sources of comorbidity. Psychol. Med. 23:361–371. Kendler, K.S., Neale, M.C., Kessler, R.C., Heath, A.C., and Eaves, L.J. (1993b) Panic disorder in women: a population-based twin study. Psychol. Med. 23:397–406. Kennedy, J.L., Neves-Pereira, M., King, N., Lizak, M.V., Basile, V.S., Chartier, M.J., and Stein, M.B. (2001) Dopamine system genes not linked to social phobia. Psychiatr. Genet. 11:213–217. Kessler, R.C., Berglund, P., Demler, O., Jin, R., Merikangas, K.R., and Walters, E.E. (2005) Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62:593–602. Kessler, R.C., Chiu, W.T., Demler, O., and Walters, E.E. (2005) Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62:617–627. Kishimoto, T., Radulovic, J., Radulovic, M., Lin, C.R., Schrick, C., Hooshmand, F., Hermanson, O., Rosenfeld, M.G., and Spiess, J. (2000) Deletion of crhr2 reveals an anxiolytic role for corticotropin- releasing hormone receptor-2. Nat. Genet. 24:415–419. Klein, D.F. (1964) Delineation of two drug-responsive anxiety syndromes. Psychopharmacology 5:397–408. Klein, D.F. (1993) False suffocation alarms, spontaneous panics, and related conditions. An integrative hypothesis. Arch. Gen. Psychiatry 50:306–317. Klein, R.J., Zeiss, C., Chew, E.Y., Tsai, J.Y., Sackler, R.S., Haynes, C., Henning, A.K., SanGiovanni, J.P., Mane, S.M., Mayne, S.T., Bracken, M.B., Ferris, F.L., Ott, J., Barnstable, C., and Hoh, J. (2005) Complement factor H polymorphism in age-related macular degeneration. Science 308:385–389. Klemenhagen, K.C., Gordon, J.A., David, D.J., Hen, R., and Gross, C.T. (2005) Increased fear response to contextual cues in mice lacking the 5-HT1A receptor. Neuropsychopharmacology 31: 101–111. Knowles, J.A., Fyer, A.J., Vieland, V.J., Weissman, M.M., Hodge, S.E., Heiman, G.A., Haghighi, F., de Jesus, G.M., Rassnick, H.,

Preud’homme-Rivelli, X., Austin, T., Cunjak, J., Mick, S., Fine, L.D., Woodley, K.A., Das, K., Maier, W., Adams, P.B., Freimer, N.B., Klein, D.F., and Gilliam, T.C. (1998) Results of a genomewide genetic screen for panic disorder. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 81:139–147. Knowles, J.A., and Weissman, M.M. (1995) Panic disorder and agoraphobia. In: Oldham, J.M., and Riba, M.B., eds. Review of Psychiatry, Volume 14. Washington, DC: American Psychiatric Press, pp. 383–404. Kusserow, H., Davies, B., Hortnagl, H., Voigt, I., Stroh, T., Bert, B., Deng, D.R., Fink, H., Veh, R.W., and Theuring, F. (2004) Reduced anxiety-related behaviour in transgenic mice overexpressing serotonin1A receptors. Mol. Brain Res. 129:104–116. Lake, R.I., Eaves, L.J., Maes, H.H., Heath, A.C., and Martin, N.G. (2000) Further evidence against the environmental transmission of individual differences in neuroticism from a collaborative study of 45,850 twins and relatives on two continents. Behav. Genet. 30:223–233. Lam, P., Hong, C.J., and Tsai, S.J. (2005) Association study of A2a adenosine receptor genetic polymorphism in panic disorder. Neurosci. Lett. 378:98–101. Lensi, P., Cassano, G.B., Correddu, G., Ravagli, S., Kunovac, J.L., and Akiskal, H.S. (1996) Obsessive-compulsive disorder. Familial-developmental history, symptomatology, comorbidity and course with special reference to gender- related differences. Br. J. Psychiatry 169:101–107. Leonard, H.L., Lenane, M.C., Swedo, S.E., Rettew, D.C., Gershon, E.S., and Rapoport, J.L. (1992) Tics and Tourette’s disorder: a 2to 7-year follow-up of 54 obsessive- compulsive children. Am. J. Psychiatry 149:1244–1251. Leonard, H.L., Swedo, S.E., Garvey, M., Beer, D., Perlmutter, S., Lougee, L., Karitani, M., and Dubbert, B. (1999) Postinfectious and other forms of obsessive-compulsive disorder. Child Adolesc. Psychiatry Clin. N. Am. 8:497–511. Lesch, K.-P., Bengel, D., Heils, A., Sabol, S.Z., Greenberg, B.D., Petri, S., Benjamin, J., Müller, C.R., Hamer, D.H., and Murphy, D. L. (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274:1527–1531. Lewis, A. (1936) Problems of obsessional illness. Proc. Royal Soc. Med. 29:325–336. Lichtenstein, P., and Annas, P. (2000) Heritability and prevalence of specific fears and phobias in childhood. J. Child Psychol. Psychiatry 41:927–937. Lin, P.Y. (2007) Meta-analysis of the association of serotonin transporter gene polymorphism with obsessive-compulsive disorder. Prog. Neuro-Psychopharm. Biol. Psychiatry 31:683–689. Lougee, L., Perlmutter, S.J., Nicolson, R., Garvey, M.A., and Swedo, S.E. (2000) Psychiatric disorders in first-degree relatives of children with pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS). J. Am. Acad. Child Adolesc. Psychiatry 39:1120–1126. MacKinnon, D.F., McMahon, F.J., Simpson, S.G., McInnis, M.G., and DePaulo, J.R. (1997) Panic disorder with familial bipolar disorder. Biol. Psychiatry 42:90–95. MacKinnon, D.F., Xu, J., McMahon, F.J., Simpson, S.G., Stine, O.C., McInnis, M.G., and DePaulo, J.R. (1998) Bipolar disorder and panic disorder in families: an analysis of chromosome 18 data. Am. J. Psychiatry 155:829–831. MacKinnon, D.F., Zandi, P.P., Cooper, J., Potash, J.B., Simpson, S. G., Gershon, E., Nurnberger, J., Reich, T., and DePaulo, J.R. (2002) Comorbid bipolar disorder and panic disorder in families with a high prevalence of bipolar disorder. Am. J. Psychiatry 159: 30–35. MacKinnon, D.F., Zandi, P.P., Gershon, E.S., Nurnberger, J.I., Jr., and DePaulo, J.R., Jr. (2003) Association of rapid mood switch-

38: MOLECULAR GENETICS ing with panic disorder and familial panic risk in familial bipolar disorder. Am. J. Psychiatry 160:1696–1698. Mackintosh, M.A., Gatz, M., Wetherell, J.L., and Pedersen, N.L. (2006) A twin study of lifetime generalized anxiety disorder (GAD) in older adults: genetic and environmental influences shared by neuroticism and GAD. Twin Res. Hum. Genet. 9:30–37. Maier, W., Lichtermann, D., Minges, J., Oehrlein, A., and Franke, P. (1993) A controlled family study in panic disorder. J. Psychiatry Res. 27:79–87. Mannuzza, S., Schneier, F.R., Chapman, T.F., Liebowitz, M.R., Klein, D.F., and Fyer, A.J. (1995) Generalized social phobia. Reliability and validity. Arch. Gen. Psychiatry 52:230–237. Mathews, C.A., Nievergelt, C.M., Azzam, A., Garrido, H., Chavira, D.A., Wessel, J., Bagnarello, M., Reus, V.I., and Schork, N.J. (2007) Heritability and clinical features of multigenerational families with obsessive-compulsive disorder and hoarding. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144:174–182. McCauley, J.L., Olson, L.M., Dowd, M., Amin, T., Steele, A., Blakely, R.D., Folstein, S.E., Haines, J.L., and Sutcliffe, J.S. (2004) Linkage and association analysis at the serotonin transporter (SLC 6A4) locus in a rigid-compulsive subset of autism. Am. J. Med. Genet. B Neuropsychiatr. Genet. 127:104–112. Mendlewicz, J., Papadimitriou, G., and Wilmotte, J. (1993) Family study of panic disorder: comparison with generalized anxiety disorder, major depression and normal subjects. Psychiatry Genet. 3:73–78. Middeldorp, C.M., de Geus, E.J., Beem, A.L., Lakenberg, N., Hottenga, J.J., Slagboom, P.E., and Boomsma, D.I. (2007) Family based association analyses between the serotonin transporter gene polymorphism (5-HTTLPR) and neuroticism, anxiety and depression. Behav. Genet. 37:294–301. Miguel, E.C., Leckman, J.F., Rauch, S., do Rosario-Campos, M.C., Hounie, A.G., Mercadante, M.T., Chacon, P., and Pauls, D.L. (2004) Obsessive-compulsive disorder phenotypes: implications for genetic studies. Mol. Psychiatry 10:258–275. Moreau, J.L., Kilpatrick, G., and Jenck, F. (1997) Urocortin, a novel neuropeptide with anxiogenic-like properties. Neuroreport 8: 1697–1701. Mott, R., Talbot, C.J., Turri, M.G., Collins, A.C., and Flint, J. (2000) A method for fine mapping quantitative trait loci in outbred animal stocks. Proc. Natl. Acad. Sci. USA 97:12649–12654. Murphy, T.K., Goodman, W.K., Fudge, M.W., Williams, R.C., Jr., Ayoub, E.M., Dalal, M., Lewis, M.H., and Zabriskie, J.B. (1997) B lymphocyte antigen D8/17: a peripheral marker for childhoodonset obsessive-compulsive disorder and Tourette’s syndrome? Am. J. Psychiatry 154:402–407. Myers, J.K., Weissman, M.M., Tischler, G.L., Holzer, C.E. III, Leaf, P.J., Orvaschel, H., Anthony, J.C., Boyd, J.H., Burke, J.D., Jr., and Kramer, M. (1984) Six-month prevalence of psychiatric disorders in three communities 1980 to 1982. Arch. Gen. Psychiatry 41:959–967. Nash, M.W., Huezo-Diaz, P., Williamson, R.J., Sterne, A., Purcell, S., Hoda, F., Cherny, S.S., Abecasis, G.R., Prince, M., Gray, J.A., Ball, D., Asherson, P., Mann, A., Goldberg, D., McGuffin, P., Farmer, A., Plomin, R., Craig, I.W., and Sham, P.C. (2004) Genome-wide linkage analysis of a composite index of neuroticism and mood-related scales in extreme selected sibships. Hum. Mol. Genet. 13:2173–2182. Neale, B.M., Sullivan, P.F., and Kendler, K.S. (2005) A genome scan of neuroticism in nicotine dependent smokers. Am. J. Med. Genet. B Neuropsychiatr. Genet. 132:65–69. Nelson, E. and Rice, J. (1997) Stability of diagnosis of obsessivecompulsive disorder in the Epidemiologic Catchment Area Study. Am. J. Psychiatry 154:826–831. Nestadt, G., Lan, T., Samuels, J., Riddle, M., Bienvenu, O.J. III, Liang, K.Y., Hoehn-Saric, R., Cullen, B., Grados, M., Beaty, T.

599

H., and Shugart, Y.Y. (2000) Complex segregation analysis provides compelling evidence for a major gene underlying obsessivecompulsive disorder and for heterogeneity by sex. Am. J. Hum. Genet. 67:1611–1616. Nestadt, G., Samuels, J., Riddle, M., Bienvenu, O.J. III, Liang, K.Y., LaBuda, M., Walkup, J., Grados, M., and Hoehn-Saric, R. (2000) A family study of obsessive-compulsive disorder. Arch. Gen. Psychiatry 57:358–363. Newman, S.C., and Bland, R.C. (2006) A population-based family study of DSM-III generalized anxiety disorder. Psychol. Med. 36: 1275–1281. Noyes, R., Jr., Clarkson, C., Crowe, R.R., Yates, W.R., and McChesney, C.M. (1987) A family study of generalized anxiety disorder. Am. J. Psychiatry 144:1019–1024. Noyes, R., Jr., Crowe, R.R., Harris, E.L., Hamra, B.J., McChesney, C.M., and Chaudhry, D.R. (1986) Relationship between panic disorder and agoraphobia. A family study. Arch. Gen. Psychiatry 43:227–232. Oppenheimer, B.S., and Rothschild, M.A. (1918) The psychoneurotic factor in the irritable heart of soldiers. JAMA 70:1919–1922. Overall, K.L. (2000) Natural animal models of human psychiatric conditions: assessment of mechanism and validity. Prog. Neuropsychopharmacol. Biol. Psychiatry 24:727–776. Ozaki, N., Goldman, D., Kaye, W.H., Plotnicov, K., Greenberg, B. D., Lappalainen, J., Rudnick, G., and Murphy, D.L. (2003) Serotonin transporter missense mutation associated with a complex neuropsychiatric phenotype. Mol. Psychiatry 8:933–936. Parks, C.L., Robinson, P.S., Sibille, E., Shenk, T., and Toth, M. (1998) Increased anxiety of mice lacking the serotonin1A receptor. Proc. Natl. Acad. Sci. USA 95:10734–10739. Pauls, D.L., Alsobrook, J.P., Goodman, W., Rasmussen, S., and Leckman, J.F. (1995) A family study of obsessive-compulsive disorder. Am. J. Psychiatry 152:76–84. Pauls, D.L., Bucher, K.D., Crowe, R.R., and Noyes, R., Jr. (1980) A genetic study of panic disorder pedigrees. Am. J. Hum. Genet. 32:639–644. Pauls, D.L., Crowe, R.R., and Noyes, R., Jr. (1979) Distribution of ancestral secondary cases in anxiety neurosis (panic disorder). J. Affect. Disord. 1:387–390. Pauls, D.L., Noyes, R., Jr., and Crowe, R.R. (1979) The familial prevalence in second-degree relatives of patients with anxiety neurosis (panic disorder). J. Affect. Disord. 1:279–285. Pauls, D.L., Towbin, K.E., Leckman, J.F., Zahner, G.E., and Cohen, D.J. (1986) Gilles de la Tourette’s syndrome and obsessivecompulsive disorder. Evidence supporting a genetic relationship. Arch. Gen. Psychiatry 43:1180–1182. Perna, G., Bertani, A., Caldirola, D., and Bellodi, L. (1996) Family history of panic disorder and hypersensitivity to CO2 in patients with panic disorder. Am. J. Psychiatry 153: 1060–1064. Perna, G., Caldirola, D., Arancio, C., and Bellodi, L. (1997) Panic attacks: a twin study. Psychiatry Res. 66:69–71. Perna, G., Cocchi, S., Bertani, A., Arancio, C., and Bellodi, L. (1995) Sensitivity to 35% CO2 in healthy first-degree relatives of patients with panic disorder. Am. J. Psychiatry 152:623–625. Phillips, K., Fulker, D.W., and Rose, R.J. (1987) Path analysis of seven fear factors in adult twin and sibling pairs and their parents. Genet. Epidemiol. 4:345–355. Pine, D.S., Klein, R.G., Roberson-Nay, R., Mannuzza, S., Moulton, J.L. III, Woldehawariat, G., and Guardino, M. (2005) Response to 5% carbon dioxide in children and adolescents: relationship to panic disorder in parents and anxiety disorders in subjects. Arch. Gen. Psychiatry 62:73–80. Pooley, E.C., Fineberg, N., and Harrison, P.J. (2007) The met158 allele of catechol-O-methyltransferase (COMT) is associated with obsessive-compulsive disorder in men: case-control study and metaanalysis. Mol. Psychiatry 12:556–561.

600

ANXIETY DISORDERS

Ramboz, S., Oosting, R., Amara, D.A., Kung, H.F., Blier, P., Mendelsohn, M., Mann, J.J., Brunner, D., and Hen, R. (1998) Serotonin receptor 1A knockout: an animal model of anxiety-related disorder. Proc. Natl. Acad. Sci USA 95:14476–14481. Rasmussen, S.A., and Eisen, J.L. (1992) The epidemiology and clinical features of obsessive compulsive disorder. Psychiatry Clin. North Am. 15:743–758. Reschke, A.H., Mannuzza, S., Chapman, T.F., Lipsitz, J.D., Liebowitz, M.R., Gorman, J.M., Klein, D.F., and Fyer, A.J. (1995) Sodium lactate response and familial risk for panic disorder. Am. J. Psychiatry 152:277–279. Rettew, D.C., Vink, J.M., Willemsen, G., Doyle, A., Hudziak, J.J., and Boomsma, D.I. (2006) The genetic architecture of neuroticism in 3301 Dutch adolescent twins as a function of age and sex: a study from the Dutch twin register. Twin Res. Hum. Genet. 9:24–29. Robins, L.N., Helzer, J.E., Weissman, M.M., Orvaschel, H., Gruenberg, E., Burke, J.D., Jr., and Regier, D.A. (1984) Lifetime prevalence of specific psychiatric disorders in three sites. Arch. Gen. Psychiatry 41:949–958. Rose, R.J., and Ditto, W.B. (1983) A developmental-genetic analysis of common fears from early adolescence to early adulthood. Child Dev. 54:361–368. Rothe, C., Gutknecht, L., Freitag, C., Tauber, R., Mossner, R., Franke, P., Fritze, J., Wagner, G., Peikert, G., Wenda, B., Sand, P., Jacob, C., Rietschel, M., Nothen, M.M., Garritsen, H., Fimmers, R., Deckert, J., and Lesch, K.P. (2004) Association of a functional 1019C>G 5-HT1A receptor gene polymorphism with panic disorder with agoraphobia. Int. J. Neuropsychopharmacol. 7:189– 192. Rothe, C., Koszycki, D., Bradwejn, J., King, N., Deluca, V., Tharmalingam, S., Macciardi, F., Deckert, J., and Kennedy, J.L. (2006) Association of the Val158Met catechol o-methyltransferase genetic polymorphism with panic disorder. Neuropsychopharmacol. 10:2237–2242 Roy, M.A., Neale, M.C., Pedersen, N.L., Mathe, A.A., and Kendler, K.S. (1995) A twin study of generalized anxiety disorder and major depression. Psychol. Med. 25:1037–1049. Ruscio, A.M., Chiu, W.T., Roy-Byrne, P., Stang, P.E., Stein, D.J., Wittchen, H.U., and Kessler, R.C. (2007) Broadening the definition of generalized anxiety disorder: Effects on prevalence and associations with other disorders in the National Comorbidity Survey Replication. J. Anxiety Disord. 21:662–676. Samochowiec, J., Hajduk, A., Samochowiec, A., Horodnicki, J., Stepien, G., Grzywacz, A., and Kucharska-Mazur, J. (2004) Association studies of MAO-A, COMT, and 5-HTT genes polymorphisms in patients with anxiety disorders of the phobic spectrum. Psychiatry Res. 128: 21–26. Samuels, J., Shugart, Y.Y., Grados, M.A., Willour, V.L., Bienvenu, O.J., Greenberg, B.D., Knowles, J.A., McCracken, J.T., Rauch, S.L., Murphy, D.L., Wang, Y., Pinto, A., Fyer, A.J., Piacentini, J., Pauls, D.L., Cullen, B., Rasmussen, S.A., Hoehn-Saric, R., Valle, D., Liang, K.Y., Riddle, M.A., and Nestadt, G. (2007) Significant linkage to compulsive hoarding on chromosome 14 in families with obsessive-compulsive disorder: results from the OCD Collaborative Genetics Study. Am. J. Psychiatry 164:493–499. Santarelli, L., Saxe, M., Gross, C., Surget, A., Battaglia, F., Dulawa, S., Weisstaub, N., Lee, J., Duman, R., Arancio, O., Belzung, C., and Hen, R. (2003) Requirement of hippocampal neurogenesis for the behavioral effects of antidepressants. Science 301:805– 809. Scherrer, J.F., True, W.R., Xian, H., Lyons, M.J., Eisen, S.A., Goldberg, J., Lin, N., and Tsuang, M.T. (2000) Evidence for genetic influences common and specific to symptoms of generalized anxiety and panic. J. Affect. Disord. 57:25–35. Scott, L.J., Mohlke, K.L., Bonnycastle, L.L., Willer, C.J., Li, Y., Duren, W.L., Erdos, M.R., Stringham, H.M., Chines, P.S., Jackson, A.

U., Prokunina-Olsson, L., Ding, C.J., Swift, A.J., Narisu, N., Hu, T., Pruim, R., Xiao, R., Li, X.Y., Conneely, K.N., Riebow, N.L., Sprau, A.G., Tong, M., White, P.P., Hetrick, K.N., Barnhart, M. W., Bark, C.W., Goldstein, J.L., Watkins, L., Xiang, F., Saramies, J., Buchanan, T.A., Watanabe, R.M., Valle, T.T., Kinnunen, L., Abecasis, G.R., Pugh, E.W., Doheny, K.F., Bergman, R.N., Tuomilehto, J., Collins, F.S., and Boehnke, M. (2007) A genomewide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316:1341–1345. Sen, S., Burmeister, M., and Ghosh, D. (2004) Meta-analysis of the association between a serotonin transporter promoter polymorphism (5-HTTLPR) and anxiety-related personality traits. Am. J. Med. Genet. B Neuropsychiatr. Genet. 127:85–89. Shekhar, A., McCann, U.D., Meaney, M.J., Blanchard, D.C., Davis, M., Frey, K.A., Liberzon, I., Overall, K.L., Shear, M.K., Tecott, L.H., and Winsky, L. (2001) Summary of a National Institute of Mental Health workshop: developing animal models of anxiety disorders. Psychopharmacology (Berl) 157:327–339. Shifman, S., Bhomra, A., Smiley, S., Wray, N.R., James, M.R., Martin, N.G., Hettema, J.M., An, S.S., Neale, M.C., van den Oord, E.J.C.G., Kendler, K.S., Chen, X., Boomsma, D.I., Middeldorp, C.M., Hottenga, J.J., Slagboom, P.E., and Flint, J. (2008) A whole genome association study of neuroticism using DNA pooling. Mol. Psychiatry 13(3):302–312. Shugart, Y.Y., Samuels, J., Willour, V.L., Grados, M.A., Greenberg, B.D., Knowles, J.A., McCracken, J.T., Rauch, S.L., Murphy, D. L., Wang, Y., Pinto, A., Fyer, A.J., Piacentini, J., Pauls, D.L., Cullen, B., Page, J., Rasmussen, S.A., Bienvenu, O.J., Hoehn-Saric, R., Valle, D., Liang, K.Y., Riddle, M.A., and Nestadt, G. (2006) Genomewide linkage scan for obsessive-compulsive disorder: evidence for susceptibility loci on chromosomes 3q, 7p, 1q, 15q, and 6q. Mol. Psychiatry 11:763–770. Skre, I., Onstad, S., Torgersen, S., Lygren, S., and Kringlen, E. (1993) A twin study of DSM-III-R anxiety disorders. Acta Psychiatr. Scand. 88:85–92. Slater, E., and Shields, J. (1969) Genetical aspects of anxiety. In Lader, M.H., ed. Studies of Anxiety. Ashford, UK: Headly Brothers, pp. 62–71. Smith, G.W., Aubry, J.M., Dellu, F., Contarino, A., Bilezikjian, L. M., Gold, L.H., Chen, R., Marchuk, Y., Hauser, C., Bentley, C.A., Sawchenko, P.E., Koob, G.F., Vale, W., and Lee, K.F. (1998) Corticotropin releasing factor receptor 1-deficient mice display decreased anxiety, impaired stress response, and aberrant neuroendocrine development. Neuron 20:1093–1102. Sobin, C., and Karayiorgou, M. (2000) The genetic basis and neurobiological characteristics of obsessive-compulsive disorder. In: Pfaff, D.W., Berrettini, W.H., Joh, T.H., and Maxson, S.C., eds. Genetic Influences on Neural and Behavioral Functions. Boca Raton: CRC Press, pp. 83–104. Sorensen, G., Lindberg, C., Wortwein, G., Bolwig, T.G., and Woldbye, D.P. (2004) Differential roles for neuropeptide Y Y1 and Y5 receptors in anxiety and sedation. J. Neurosci. Res. 77:723–729. Stein, B., Chartier, J., Kozak, M.V., King, N., and Kennedy, J.L. (1998) Genetic linkage to the serotonin transporter protein and 5HT2A receptor genes excluded in generalized social phobia. Psychiatry Res. 81:283–291. Stein, M.B., Chartier, M.J., Hazen, A.L., Kozak, M.V., Tancer, M.E., Lander, S., Furer, P., Chubaty, D., and Walker, J.R. (1998) A direct-interview family study of generalized social phobia. Am. J. Psychiatry 155:90–97. Stenzel-Poore, M.P., Heinrichs, S.C., Rivest, S., Koob, G.F., and Vale, W.W. (1994) Overproduction of corticotropin-releasing factor in transgenic mice: a genetic model of anxiogenic behavior. J. Neuroscience 14:2579–2584. Stine, O.C., Xu, J., Koskela, R., McMahon, F.J., Gschwend, M., Friddle, C., Clark, C.D., McInnis, M.G., Simpson, S.G., and Bre-

38: MOLECULAR GENETICS schel, T.S. (1995) Evidence for linkage of bipolar disorder to chromosome 18 with a parent- of-origin effect. Am. J. Hum. Genet. 57:1384–1394. Sullivan, P.F. (2007) Spurious genetic associations. Biol. Psychiatry 61:1121–1126. Sullivan, P.F., Eaves, L.J., Kendler, K.S., and Neale, M.C. (2001) Genetic case-control association studies in neuropsychiatry. Arch. Gen. Psychiatry 58:1015–1024. Sundet, J.M., Skre, I., Okkenhaug, J.J., and Tambs, K. (2003) Genetic and environmental causes of the interrelationships between selfreported fears. A study of a non-clinical sample of Norwegian identical twins and their families. Scand. J. Psychology 44:97–106. Swedo, S.E., Leonard, H.L., Garvey, M., Mittleman, B., Allen, A.J., Perlmutter, S., Lougee, L., Dow, S., Zamkoff, J., and Dubbert, B.K. (1998) Pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections: clinical description of the first 50 cases. Am. J. Psychiatry 155:264–271. Swedo, S.E., Leonard, H.L., Mittleman, B.B., Allen, A.J., Rapoport, J.L., Dow, S.P., Kanter, M.E., Chapman, F., and Zabriskie, J. (1997) Identification of children with pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections by a marker associated with rheumatic fever [see comments]. Am. J. Psychiatry 154:110–112. Swedo, S.E., Rapoport, J.L., Cheslow, D.L., Leonard, H.L., Ayoub, E.M., Hosier, D.M., and Wald, E.R. (1989) High prevalence of obsessive-compulsive symptoms in patients with Sydenham’s chorea. Am. J. Psychiatry 146:246–249. Swedo, S.E., Rapoport, J.L., Leonard, H., Lenane, M., and Cheslow, D. (1989) Obsessive-compulsive disorder in children and adolescents. Clinical phenomenology of 70 consecutive cases. Arch. Gen. Psychiatry 46:335–341. Tadic, A., Rujescu, D., Szegedi, A., Giegling, I., Singer, P., Moller, H.J., and Dahmen, N. (2003) Association of a MAOA gene variant with generalized anxiety disorder, but not with panic disorder or major depression. Am. J. Med. Genet. B Neuropsychiatr. Genet. 117:1–6. Talbot, C.J., Nicod, A., Cherny, S.S., Fulker, D.W., Collins, A.C., and Flint, J. (1999) High-resolution mapping of quantitative trait loci in outbred mice. Nat. Genet. 21:305–308. Tecott, L.H. (2003) The genes and brains of mice and men. Am. J. Psychiatry 160:646–656. Thorgeirsson, T.E., Oskarsson, H., Desnica, N., Kostic, J.P., Stefansson, J.G., Kolbeinsson, H., Lindal, E., Gagunashvili, N., Frigge, M.L., Kong, A., Stefansson, K., and Gulcher, J.R. (2003) Anxiety with panic disorder linked to chromosome 9q in Iceland. Am. J. Hum. Genet. 72:1221–1230. Timpl, P., Spanagel, R., Sillaber, I., Kresse, A., Reul, J.M., Stalla, G. K., Blanquet, V., Steckler, T., Holsboer, F., and Wurst, W. (1998) Impaired stress response and reduced anxiety in mice lacking a functional corticotropin-releasing hormone receptor 1. Nat. Genet. 19: 162–166. Torgersen, S. (1979) The nature and origin of common phobic fears. Br. J. Psychiatry 134:343–351. Torgersen, S. (1983) Genetic factors in anxiety disorders. Arch. Gen. Psychiatry 40:1085–1089. Turri, M.G., Datta, S.R., DeFries, J., Henderson, N.D., and Flint, J. (2001) QTL analysis identifies multiple behavioral dimensions in ethological tests of anxiety in laboratory mice. Curr. Biol. 11: 725–734. Turri, M.G., DeFries, J.C., Henderson, N.D., and Flint, J. (2004) Multivariate analysis of quantitative trait loci influencing variation in anxiety-related behavior in laboratory mice. Mamm. Genome 15:69–76. Turri, M.G., Henderson, N.D., DeFries, J.C., and Flint, J. (2001) Quantitative trait locus mapping in laboratory mice derived from a replicated selection experiment for open-field activity. Genetics 158:1217–1226.

601

Turri, M.G., Talbot, C.J., Radcliffe, R.A., Wehner, J.M., and Flint, J. (1999) High-resolution mapping of quantitative trait loci for emotionality in selected strains of mice. Mamm. Genome 10: 1098–1101. van Beek, N., and Griez, E. (2000) Reactivity to a 35% CO2 challenge in healthy first-degree relatives of patients with panic disorder. Biol. Psychiatry 47:830–835. Van Grootheest, D.S., Cath, D.C., Beekman, A.T., and Boomsma, D.I. (2005) Twin studies on obsessive-compulsive disorder: a review. Twin Res. Hum. Genet. 8:450–458. Van Grootheest, D.S., Cath, D.C., Beekman, A.T., and Boomsma, D.I. (2007) Genetic and environmental influences on obsessivecompulsive symptoms in adults: a population-based twin-family study. Psychol. Med. 11:1635–1644. Veenstra-VanderWeele, J., Kim, S.J., Gonen, D., Hanna, G.L., Leventhal, B.L., and Cook, E.H., Jr. (2001) Genomic organization of the SLC1A1/EAAC1 gene and mutation screening in early-onset obsessive-compulsive disorder. Mol. Psychiatry 6:160–167. Vieland, V.J., Goodman, D.W., Chapman, T., and Fyer, A.J. (1996) New segregation analysis of panic disorder. Am. J. Med. Genet. 67:147–153. Vieland, V.J., Hodge, S.E., Lish, J.D., Adams, P., and Weissman, M.M. (1993) Segregation analysis of panic disorder. Psychiatry Genet. 3:63–71. Wehner, J.M., Radcliffe, R.A., Rosmann, S.T., Christensen, S.C., Rasmussen, D.L., Fulker, D.W., and Wiles, M. (1997) Quantitative trait locus analysis of contextual fear conditioning in mice. Nat. Genet. 17:331–334. Weissman, M.M. (1993) Family genetic studies of panic disorder. J. Psychiatry Res. 27:69–78. Weissman, M.M., Bland, R.C., Canino, G.J., Faravelli, C., Greenwald, S., Hwu, H.-G., Joyce, P.R., Karam, E.G., Lee, C.-K., Lellouch, J., Lépine, J.-P., Newman, S.C., Oakley-Browne, M.A., RubioStipec, M., Wells, J.E., Wickramaratne, P.J., Wittchen, H.-U., and Yeh, E.-K. (1997) The cross-national epidemiology of panic disorder. Arch. Gen. Psychiatry 54:305–309. Weissman, M.M., Bland, R.C., Canino, G.J., Greenwald, S., Hwu, H.G., Lee, C.K., Newman, S.C., Oakley-Browne, M.A., RubioStipec, M., and Wickramaratne, P.J. (1994) The cross national epidemiology of obsessive compulsive disorder. The Cross National Collaborative Group. J. Clin. Psychiatry 55(Suppl): 5–10. Weissman, M.M., Wickramaratne, P.J., Adams, P.B., Lish, J.D., Horwath, E., Charney, D., Woods, S.W., Leeman, E., and Frosch, E. (1993) The relationship between panic disorder and major depression. Arch. Gen. Psychiatry 50:767–780. Weissman, M.M., Wickramaratne, P., Nomura, Y., Warner, V., Verdeli, H., Pilowsky, D.J., Grillon, C., and Bruder, G. (2005) Families at high and low risk for depression: a 3-generation study. Arch. Gen. Psychiatry 62:29–36. Wellcome Trust Case Control Consortium. (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447:661–678. Wendland, J.R., Kruse, M.R., Cromer, K.C., and Murphy, D.L. (2007) A large case-control study of common functional SLC6A4 and BDNF variants in obsessive-compulsive disorder. Neuropsychopharmacology 32:2543–2551. Weninger, S.C., Dunn, A.J., Muglia, L.J., Dikkes, P., Miczek, K.A., Swiergiel, A.H., Berridge, C.W., and Majzoub, J.A. (1999) Stressinduced behaviors require the corticotropin-releasing hormone (CRH) receptor, but not CRH. Proc. Natl. Acad. Sci. USA 96: 8283–8288. Willis-Owen, S.A., and Flint, J. (2006) The genetic basis of emotional behaviour in mice. Eur. J. Hum. Genet. 14:721–728. Willis-Owen, S.A.G., Turri, M.G., Munafo, M.R., Surtees, P.G., Wainwright, N.W.J., Brixey, R.D., and Flint, J. (2005) The serotonin transporter length polymorphism, neuroticism, and depression: a

602

ANXIETY DISORDERS

comprehensive assessment of association. Biol. Psychiatry 58: 451–456. Willour, V.L., Yao, S.Y., Samuels, J., Grados, M., Cullen, B., Bienvenu, O.J. III, Wang, Y., Liang, K.Y., Valle, D., Hoehn-Saric, R., Riddle, M., and Nestadt, G. (2004) Replication study supports evidence for linkage to 9p24 in obsessive-compulsive disorder. Am. J. Hum. Genet. 75:508–513. Woo, J.M., Yoon, K.S., Choi, Y.H., Oh, K.S., Lee, Y.S., and Yu, B.H. (2004) The association between panic disorder and the L/L genotype of catechol-O-methyltransferase. J. Psychiatric Res. 38: 365–370.

Woo, J.M., Yoon, K.S., and Yu, B.H. (2002) Catechol O-methyltransferase genetic polymorphism in panic disorder. Am. J. Psychiatry 159:1785–1787. Yamada, K., Hattori, E., Shimizu, M., Sugaya, A., Shibuya, H., and Yoshikawa, T. (2001) Association studies of the cholecystokinin B receptor and A2a adenosine receptor genes in panic disorder. J. Neural Transm. 108:837–848. Zorrilla, E.P., Valdez, G.R., Nozulak, J., Koob, G.F., and Markou, A. (2002) Effects of antalarmin, a CRF type 1 receptor antagonist, on anxiety-like behavior and motor activation in the rat. Brain Res. 952:188–199.

39 The Neurobiology of Fear and Anxiety: Contributions of Animal Models to Current Understanding GREGORY M. SULLIVAN, JACEK DEBIEC, DAVID E.A. BUSH, DAVID M. LYONS,

A N D

JOSEPH E. LEDOUX

Animal models have played an essential role in elucidating the pathophysiology of a broad range of human diseases. The yield from animal work in the behavioral sciences is becoming increasingly realized, especially in anxiety and other psychiatric disorders. Animal models offer unparalleled access to the biochemical pathways, cellular mechanisms, synaptic changes, and neuronal circuits that mediate the physiological and behavioral responses of fear, anxiety, and avoidance. There has been a broader appreciation of the relevance of many decades of neuroscience studies for elucidating the neurobiology mediating anxious behaviors. Notable progress has been especially made in understanding innate and learned fear. Recent years have seen more cross-disciplinary communication and collaborations between clinical researchers of the anxiety disorders and neuroscientists focused on the underpinnings of emotional behaviors. Greater emphasis has been placed on the translational potential of animal models for the development of novel therapeutic approaches to pathological anxiety, and the fruits of these labors are beginning to emerge. Although there is no ideal or comprehensive model for any particular anxiety disorder, there has been the reciprocal development of more clinically informed animal models. To this end, adaptations of existing animal models of anxiety allow an improved ability to investigate key aspects of psychopathology. This chapter focuses on the fundamental contributions of animal models to the emerging understanding of fearful and anxious behaviors and the neuropathologies that underlie the anxiety disorders. WHAT IS FEAR? Imagine this. You step into the street. Without a thought, you jump back, barely avoiding being struck down.

You find yourself back on the curb trembling, breaking out in a sweat; your heart is racing, you can barely catch your breath; the “feeling of adrenaline” is spreading throughout your body, you feel nauseated, confused; the environment seems unreal. Only after do you realize a car was moving directly toward you at high speed. Knowing that you escaped fate, your reaction quickly subsides. You feel back to yourself in the next few minutes. What happened? Simply put, you just witnessed the operation of one of the most basic emotion systems of the brain: the fear system. This system, which evolved to cope with sudden dangers, was activated more or less unconsciously by the sensory input coming though your visual system. It saved you from harm. Fear occurs when one encounters stimuli that predict danger. It is a normal and adaptive response to a threatening situation. Activation of the fear system results in a coordinated and rapid array of behavioral, autonomic, and endocrine changes that enhance the likelihood of the organism’s survival. Yet we often refer to fear as if it were solely a subjective state of consciousness. William James (1884) pointed out over a century ago that the conscious feeling of fear that a human experiences when confronted with a threat is but one outcome of an array of responses rather than the essence of the underlying emotion, and that, contrary to popular opinion, behavioral and physiological responses during emotion do not depend on conscious processing. Indeed, all animals have the ability to detect danger and respond physiologically in such a way as to enhance the probability of survival, regardless of whether they are able to consciously experience fear (LeDoux, 1996, 2000). When you jumped back from the speeding car, you were unconsciously responding to the threat. A conscious feeling of fear played no role. Recent human studies support the idea that conscious awareness of fear-inducing stimuli is not requisite for 603

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the production of emotional responses (Ohman and Mineka, 2001; Whalen et al., 2004; Phelps, 2006). The defensive behavioral responses to adverse challenge are often termed “freeze, fight, or flight” behaviors. The concurrent physiological changes generally support these motor responses by increasing availability of energy and shifting blood supply to body systems necessary for immediate defense, namely the brain and musculoskeletal system. Included are changes in the autonomic nervous system and the release of stress hormones. These are components of Selye’s (1950) general adaptation system. In the short run, they support behavioral responses that increase survival, such as enhancement of learning and memory (McGaugh and Roozendaal, 2002). Over time, however, they can lead to maladaptive consequences, including impairments in memory and other cognitive functions and physical well-being (McEwen, 2004). Converging evidence has shown that despite the great differences in the sensory, cognitive, and behavioral capacities of the human brain compared with those of other animal species (Kalueff and Tuohimaa, 2004), the systems that have evolved in all animals to detect danger and regulate the fear response involve similar molecular, cellular, and circuitry mechanisms (LeDoux, 1996, 2000; Maren, 2001; Kalin et al. 2004; Phelps, 2004; Sotres-Bayon et al., 2004; Phelps and LeDoux, 2005; Quirk and Beer, 2006). In humans, monkeys, and rodents, a temporal lobe region known as the amygdala plays a key role in threat processing, the medial prefrontal cortex (PFC) plays a key role in fear regulation, and the hippocampus plays a key role in providing information about the context in which a threatening challenge is occurring (Figure 39.1). Therefore, regardless of whether other animals have conscious feelings of emotion similar to those experienced by humans, the fundamental similarities in the evolutionarily conserved

fear networks form the basis for exploring the mechanisms underlying the behavioral and physiological responses associated with fear using animal models. Nonhuman primate models play a vital role in bridging the gap between rodent models and clinical studies in humans, particularly with regard to elucidating the functional neuroanatomy of brain regions such as PFC in which the prospects for rodent research are limited by phylogeny. THE CONTRAST BETWEEN FEAR AND ANXIETY Like fear, anxiety is a normal and adaptive response that ensures dangers are either avoided or reduced through preparation and vigilance. Well-defined threatening stimuli that are immediately present or imminent in the environment elicit a fear response. When the threat is more poorly defined and temporally remote, such as anticipation of a future adverse or threatening circumstance, the behavioral state it elicits is typically referred to as anxiety. From this perspective, an operational distinction between fear and anxiety is that fear is a sensorydriven and time-limited response to potential adversity, whereas anxiety is a preparatory state activated by cognitive processes predicting more distant future adversity. This activated state may be time limited or selfsustaining. It may also be reinforced further by the arousal of the fear system by external stimuli, internal stimuli (somatic sensations of the fear response itself), or cognitive processes ruminating on potential adversity, whether real or imagined, and whether the threat is possible and likely or physically impossible, at least as we understand the world (alien abduction). A distinction between state anxiety and trait anxiety in humans has often been emphasized (Spielberger et al., 1970). State anxiety is considered a transient response elicited by a particular stimulus or situation. Trait anxiety is considered an enduring or chronic anxious condition that is present across multiple situations. Trait anxiety is not necessarily pathological, as it may improve survival depending on the environmental challenges encountered. For example, in chimpanzees the level of maternal vigilance for ensuring the safety of their dependent offspring from outside predation, as well as danger from conspecifics, members of their own species, is an adaptive anxious trait (Kutsukake, 2006). Only when such traits lead to behaviors that are counterproductive to a healthy or adaptive lifestyle does a disorder exist. PATHOLOGICAL FEAR AND ANXIETY

FIGURE 39.1 Partners in fear—amygdala, hippocampus, vmPFC. vmPFC: ventromedial prefrontal cortex.

Fear and anxiety become pathological when they are exaggerated in form, are nonadaptive with respect to

39: NEUROBIOLOGY OF FEAR AND ANXIETY

environmental challenges, and result in marked disability and/or maladaptive avoidance. As we just noted, under some conditions hypervigilance is adaptive. However, it is also a common symptom of posttraumatic stress disorder (PTSD) and is considered pathological in this anxiety disorder because it is activated by situations or contexts in which threat is unlikely to be present. Pathological anxiety is not unique to humans. A common example occurs in certain breeds of dogs that exhibit objective physiological and behavioral responses remarkably similar to several clinical anxiety syndromes in humans including separation anxiety, specific phobias (thunder, loud or noxious noises), panic-like attacks, posttraumatic stress responses, and compulsive behaviors (Overall, 2000). Moreover, there are a number of rodent and nonhuman primate models of pathological fear and anxiety that have been developed for neurobiological study in the laboratory. Despite our inability to gauge the conscious experience of the afflicted animal, the pathological anxiety syndromes observed in animals represent convincing models for pathological states of anxiety in humans. Support for the notion of common underlying neurobiological substrates is provided by the fact that the same classes of pharmacological treatments and behavioral interventions shown to be efficacious in human anxiety disorders also relieve the signs of pathological anxiety in monkeys, dogs, and rodents (Kalin et al., 1991; Overall, 1997; Huot et al., 2001; Burghardt et al., 2004). The term anxiety is often used as if it describes one basic emotional state. Yet the term is employed clinically and colloquially to label a number of quite diverse psychic and physical symptoms. Table 39.1 lists common symptoms of anxiety, divided into broader categories of psychic, somatic, and motoric anxiety symptoms. Because most of these symptoms require self-report, it might appear untenable to elucidate the underlying brain mechanisms by use of animal models. Yet the current diagnostic method in psychiatry involves a patient interview regarding the behavioral and physiological symptoms experienced over time, and, to a lesser extent, anxious behaviors observed by the clinician during the interview. In other words, the patient is asked to provide a retrospective report from the perspective of an observer of the symptoms that lead to seeking treatment. One could imagine an alternative method, albeit impractical, in which instead the clinician trailed the patient for some period of time, scoring different behaviors and measuring physiological responses manifested upon the variety of daily challenges of life. From this perspective, investigating the mediators of the defensive behaviors and the physiological responses within controlled environmental conditions in animal models of anxiety is a reasonable approach for revealing the neurobiology underlying the expression of anxiety signs and symptoms that occur naturalistically in humans.

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39.1 Examples of the Wide Array of Symptoms Encompassed by the Term Anxiety TABLE

Psychic Ruminative inappropriate worry Catastrophic misappraisals Feelings of unreality (derealization) Feeling outside one’s self (depersonalization) Overwhelming urge to flee Somatic Shortness of breath Chest pressure, pains, or tightness Palpitations or heart pounding Sweating or hot flushes Chills Dry mouth Choking sensation Nausea or abdominal discomfort Urinary urgency Hyperesthesia Numbness or tingling Motoric Feeling “jittery” or “keyed up” Muscular tension Fidgeting or pacing Akisthisia-like agitation

Human anxiety disorders are currently diagnosed using the categorical system of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM). Most of the anxiety disorders included in the current edition (DSM-IV-TR) are characterized by extreme symptoms of fear, anxiety, and avoidance that, by definition, have been significantly impairing to the individual’s psychosocial function (American Psychiatric Association, 2000). They are grouped into the diagnostic class of anxiety disorders based on subjective criterion of shared phenomenological features. It is the unique constellations of these features that distinguish the anxiety disorders diagnostically. In the DSM-V, due to be completed in a few years, there will be greater emphasis on categorizing mood and anxiety conditions within an empirically based structure that reflects inherent similarities among disorders (Watson, 2005). Underlying factor analytic structural dimensions, supported by genotypic evidence, point to a reclassification of panic disorder, agoraphobia, social phobia, and specific phobia as within the dimension of “fear disorders,” whereas generalized anxiety disorder would be reclassified within the dimension of “distress disorders” along with major depressive disorder and dysthymic disorder. Posttraumatic stress disorder poses

606

ANXIETY DISORDERS

a bigger quandary as the current symptom constellation includes elements of the distress disorders such as diminished interests in activities as well as those of fear disorders such as avoidance and hyperarousal. It is likely that such a new categorization system will work better with animal models of anxiety, as the measurable behaviors in the models parallel the common underlying dimensions more than the currently employed phenomenological clusterings.

39.2 Examples of Commonly Measured Behavioral and Physiological Parameters in Anxiety Models

TABLE

Behavioral Motor behaviors

Types Intensities Frequencies Latencies

Vocalizations Physiological

ANIMAL MODELS OF FEAR AND ANXIETY Below, we start by summarizing several key features of animal models that help in understanding the value of a particular animal model. Then, we turn to animal models of fear and anxiety. We argue that most animal models reflect normal fear and anxiety—that is, the kinds of fear and anxiety responses that occur in the daily life of a species—rather than reflecting pathological fear and anxiety. Of the various models of normal fear and anxiety, we will focus on Pavlovian fear conditioning because it is the model most amenable to a neurobiological analysis. We then consider several variations or manipulations that, when added to fear conditioning, provide ways of pursuing the underlying mechanisms of pathological anxiety.

Neuroendocrine

Corticosterone (rodent) Cortisol (primate) Adrenaline Autonomic

Blood pressure Heart rate Respiration Temperature

Incontinence

Urinary Fecal

Electrophysiological Single neurons Field potentials Microdialysis Chemical milieu

Neurotransmitter release

Central

Molecular, cellular, structural Confirmation of electrode, cannulae, or lesion placement Stomach ulceration Immune organs and function

Features of Animal Models Animal models do not typically mimic the DSM anxiety syndromes, but, rather, they can be adapted to specify and study key behavioral and physiological components or symptoms of the clinical syndromes. For example, greater or prolonged physiological responses to perceived threats are often observed in most anxiety disorders, such as changes in autonomic responses or facilitated startle responses (Hoehn-Saric et al., 1991; Roth, 2005; Cornwell et al., 2006). Similarly, rodent behavioral paradigms of Pavlovian fear conditioning and fear-potentiated startle elicit autonomic and startle responses, and they are therefore used as models of these components of anxiety (Davis, 2006). The last several decades have seen the introduction of a host of animal models, predominantly involving rodents, which are proposed to measure different aspects of anxiety. The behavioral parameters measured in these models are quite varied. Examples include the degree of spontaneous avoidance of environmental stimuli (bright lighting, open spaces, heights), social avoidance of conspecifics, response to predators or predator odors, learned responses to aversive stimuli, and behavioral responses to conflict between appetitive behaviors and avoidance of fear-inducing stimuli. Measurements may also be made of the physiological responses to the challenges posed by the paradigm. Table 39.2

ACTH

Histopathology

Peripheral

ACTH = adrenocorticotrophic hormone.

lists some examples of commonly measured behavioral and physiological parameters in anxiety models. Animal models of anxiety permit the acquisition of prospective data on a short-term and long-term basis under controlled conditions. Much of this critical work cannot be performed in humans for ethical and practical reasons. The anxiety models allow exploration of interventions that attenuate or enhance particular responses as well as studies that elucidate underlying neurobiological mechanisms of anxious behaviors. Importantly, adaptations of the basic anxiety models are playing a critical role in many of the advances in the elucidation of the neuropathologies of the various anxiety disorders.

39: NEUROBIOLOGY OF FEAR AND ANXIETY

The validity of a model is the degree to which a model is useful for some purpose. Face validity refers to the phenomenological similarities between the model and the human psychiatric condition. As originally proposed by McKinney and Bunney (1969), animal models of psychiatric disorders have a high degree of face validity when the model is produced by etiological factors known to produce the human disorder; the model resembles the behavioral manifestations and symptoms of the human disorder; the model has an underlying physiology similar to the human disorder; and the model responds to therapeutic treatments known to be effective in human patients. How these criteria are evaluated and established in animal models of psychiatric disorders is clearly discussed elsewhere in detail (Weiss and Kilts, 1998; McKinney, 2001). Construct validity refers to the theoretical rational for linking a process in a model to a process hypothesized to produce in humans a key symptom of a given disorder. To establish construct validity, a theory for understanding a process in the human disorder is mapped or shown to be equivalent to the process being studied in an animal model (Sarter and Bruno, 2002). Due to the shared aspects of the phylogenetic histories, humans and other animals are often homologous at molecular, cellular, synaptic, and circuitry levels of analysis. A model is considered to have good predictive validity based on the ability to make accurate predictions about the human phenomenon of interest. More specifically in the realm of drug development, predictive validity is the ability of the model to identify drugs of therapeutic efficacy in humans. Here, the goal is often to screen many drugs to identify the few that alter a behavior in a similar manner to an existing set of drugs such as a particular class of anxiolytics. The measured behavior need not resemble a behavior of human anxiety conditions. Models for Pursuing the Neurobiology of “Normal” Fear and Anxiety As noted, most models of fear and anxiety are models of perfectly natural states of fear or anxiety that occur in the daily lives of animals rather than models of pathological fear or anxiety. Models of “normal” fear and anxiety can be broadly divided into those that do not require learning (unlearned) and those that are based on conditioning (learned). Table 39.3A lists some examples of unlearned behavioral paradigms including the open field test, the elevated plus-maze (EPM), the light–dark box exploration test, predator exposure, and the social interaction test. Because little or no training is involved in such paradigms, they are often described as tests of innate fear. However, it is not possible to rule out prior experiences that contribute to the way an animal performs under these conditions. In contrast,

607

learned fear tasks are variations on fear conditioning, instrumental avoidance conditioning, or conflict tests in which an aversive stimulus must be endured to obtain an appetitive reward. Table 39.3B lists examples of learned behavioral paradigms including Pavlovian fear conditioning (to a cue or a context), fear-potentiated startle, instrumental avoidance (active and passive), and punishment-induced conflict. Behavioral models of anxiety generally provide for two main avenues of pursuit. One is the rapid screening of compounds for therapeutic potential. The other is the elucidation of the underlying neurobiology. What constitutes a good animal model for fearful, anxious, or avoidant behaviors depends to a large degree on which avenue is being pursued. For the purpose of screening drugs for activity on particular behavioral measures, the model should have good predictive validity, be easy to execute, be cost effective, and produce consistent and stable results. For these reasons, the unlearned models are especially useful for drug screening. However, some learned conflict paradigms have also been notably useful in the identification and testing of novel agents (McCown et al., 1983; Millan and Brocco, 2003). It is important to note that most of the antianxiety drugs that have been developed and screened using animal models have employed tests of normal fear and anxiety rather than models of pathological fear or anxiety. For pursuing the underlying neural mechanisms of normal and pathological anxiety, choosing a behavioral paradigm in which the circuitry is well-defined assumes greater importance. A model may prove to have excellent face and predictive validity, yet it may also be unmanageable for pursuing specific underlying mechanisms. For example, the EPM is a popular model for drug discovery that includes the measurement of spontaneous avoidance of the open arms and has good predictive validity for anxiolytic and anxiogenic agents that alter time spent in the open arms (relative to total time spent in open and closed arms). The model allows for rapid drug screening without behavioral training or other more involved procedures. Yet very little is understood about the neural substrates that mediate these behaviors, and therefore this model is not amenable to circuit analysis. Given that circuit analysis is a critical early step in the detailed pursuit of neuronal, synaptic, molecular, and genetic mechanisms in the brain (J.A. Gray, 1983; Lister, 1990; Willner, 1991; Shekhar et al., 2001), inability to pursue the circuitry is a significant drawback of the EPM and other unlearned models. In fact, many of the commonly employed animal models of fear and anxiety are not very suitable for circuit analyses due to the lack of specificity of either the conditions eliciting the behavior or of the behavioral responses themselves. Pavlovian fear conditioning is a noteworthy exception, as it has turned out to be highly

608 TABLE

ANXIETY DISORDERS

39.3A Examples of Unlearned/Unconditioned Anxiety Models Related Disorders/ Human Analogue

Animal Model

Key References

Ethological conflict tests Open field test (± appetitive stimuli)

GAD, panic w/agoraphobia

General: (Hall, 1934; Prut and Belzung, 2003) Amygdala: (Wallace et al., 2004; Heldt and Ressler, 2006) Hippocampus: (Kostowski et al., 1989) Lateral Septum: (Henry et al., 2006)

Elevated plus-maze

GAD, panic w/agoraphobia, fear of heights

General: (Pellow and File, 1986; Treit and Menard, 1997) Amygdala: (Helfer et al., 1996; Akwa et al., 1999; Moller et al., 1999; Wallace et al., 2004; Kokare et al., 2005); but see (Decker et al., 1995; Gonzalez et al., 1996; Moller et al., 1997) Hippocampus: (Kostowski et al., 1989; Cheeta et al., 2000; Degroot et al., 2001; Degroot and Treit, 2002) Septum: (Pesold and Treit, 1992; Cheeta et al., 2000; Degroot et al., 2001) Medial prefrontal cortex: (Shah and Treit, 2004) Dorsal periaqueductal gray (Aguiar and Brandao, 1996; Matheus and Guimaraes, 1997; Kask et al., 1998; Netto and Guimaraes, 2004)

Light-dark box exploration test

GAD

General: (Costall et al., 1989; Bourin and Hascoet, 2003) Amygdala: (de la Mora et al., 2005) Lateral Septum: (Henry et al., 2006)

Holeboard (nose pokes) Social interaction test

(File and Wardill, 1975) Social anxiety disorder; fear of crowds, GAD

General: (File and Seth, 2003) Amygdala: (Gonzalez et al., 1996; Helfer et al., 1996) Hippocampus and Lateral Septum: (Cheeta et al., 2000)

Neophobia (to novel objects)

Behavioral inhibition

Hyponeophagia (latency to start eating)

(Griebel et al., 1993) (Shephard and Broadhurst, 1982)

Aversion tests Defensive burying/shock probe

GAD, active coping

General: (Treit et al., 1981; Treit and Menard, 1997) Hippocampus: (Degroot et al., 2001; Degroot and Treit, 2002) Septum: (Degroot et al., 2001) mPFC: (Shah and Treit, 2004)

Predator exposure (actual or odor)

Traumatic experience, fear of predators of humans (lions, coyotes)

General: (D.C. Blanchard et al., 2003; Adamec et al., 2005) Amygdala: (L.K. Takahashi et al., 2007) Hippocampus: (Diamond et al., 2006) Bed Nucleus of the Stria Terminalis: (Fendt et al., 2005) PFC: (Beekman et al., 2005)

Underwater immersion

PTSD

(Richter-Levin, 1998; Datta and Tipton, 2006)

GAD: generalized anxiety disorder; PTSD: posttraumatic stress disorder.

amenable to pursuing neural mechanisms. As is reviewed below, studies of fear conditioning have already characterized the fear system at the level of the circuits, neurons, synapses, genes, and molecules involved. Moreover, the circuits underlying the acquisition, expression, and extinction of conditioned fear have been shown to

be similar in humans and rodents (Phelps and LeDoux, 2005). This has not been possible for most other anxiety paradigms not only because of the poorly defined circuitry, but also the human behavioral equivalents are not obvious for the apparent species-specific behaviors found in paradigms such as those measured in

39: NEUROBIOLOGY OF FEAR AND ANXIETY TABLE

609

39.3B Examples of Learned Anxiety Models

Animal Model

Related Disorders/ Human Analogue

Key References

Conditioned fear to cues Directly elicited: Fear conditioning (cued)

PTSD, specific phobias, panic attacks

(Phillips and LeDoux, 1992)

GAD, conflict

(Thiebot et al., 1980; Moller et al., 1997; Akwa et al., 1999; Moller et al., 1999; Repa et al., 2001; Anglada-Figueroa and Quirk, 2005)

PTSD, specific phobias, increased startle reflex

(Liang et al., 1992; Davis et al., 1993; M. Kim and Davis, 1993; D.L. Walker et al., 2003)

Fear conditioning (context)

PTSD, specific phobias, panic disorder with agoraphobia

(J.J. Kim and Fanselow, 1992; Phillips and LeDoux, 1992; Nader et al., 2001)

Conditioned place-aversion/drug discrimination

Substance use disorders

General: (Cunningham et al., 2006)

Suppression of instrumental behavior: Conditioned suppression (bar pressing to CS)

Reflex potentiation: Fear-potentiated acoustic startle

Conditioned fear to context

Fear-motivated instrumental responses Instrumental escape/avoidance tasks Passive avoidance

(Nation and Matheny, 1980) PTSD, GAD

(Quirarte et al., 1997; Roozendaal and McGaugh, 1997; Treit and Menard, 1997; Roozendaal et al., 1999)

Active avoidance Escape from fear (EFF)

(Miyamoto et al., 1985; Nordby et al., 2006) PTSD, GAD, panic disorder with agoraphobia, active coping

General and Amygdala: (Amorapanth et al., 2000)

Geller–Seifter Test (frequency of conditioned response coincidental to shock)

Conflict

(Iversen, 1980)

Vogel Lick Test (frequency of conditioned licking coincidental to shock)

Conflict

(Vogel et al., 1971)

Punishment-induced conflict

PTSD: posttraumatic stress disorder; GAD: generalized anxiety disorder.

the EPM, the open field test, or shock probe burying. The value of fear conditioning–based models is also highlighted by the observation that learned fear is an important component of most, if not all, anxiety disorders (Rosen and Schulkin, 1998; Shekhar et al., 2005). Therefore, there is reason to suspect that information processing through, or dependent upon, the brain’s fear system may be different in individuals suffering from pathological anxiety. We therefore review in detail much of what has been learned about fear conditioning, from the circuitry down to the molecular mediators. We then discuss several ways in which the

fear conditioning model for anxiety may be adapted to form hybrid models that offer improved opportunities for identifying the neuropathological correlates of the anxiety disorders. Pavlovian Fear Conditioning as a Model for Pursuing the Neural Mechanisms Underlying Normal Fear Much of the current understanding of the neurobiology of fear and anxiety has come from studies of fear conditioning. Below, we first summarize behavioral aspects of fear conditioning; we next turn to the neural

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ANXIETY DISORDERS

pathways underlying the acquisition, expression, and storage of fear memory, and circuits of fear regulation and extinction; and finally, we describe the cellular, synaptic, and molecular mechanisms involved. Behavioral aspects of fear conditioning Pavlov first described how an initially neutral, innocuous stimulus, termed the conditioned stimulus (CS), could acquire emotional properties if it was perceived simultaneously with a biologically salient event, termed the unconditioned stimulus (US) (Pavlov and Anrep, 1927). The hardwired response to the US is termed the unconditioned response (UR), and the acquired response to the CS is the conditioned response (CR). For example, in classical fear conditioning a rat is exposed to a tone, and, before the tone ceases, it also receives a mild electric shock to the feet. As a result it learns that the CS predicts threat. Now the physiological and behavioral responses that are hard wired for response to the US have also come under the control of the CS. However, it should also be mentioned that the UR and CR are not identical. Certain UR behaviors, such as jumping and vocalization, are elicited by the foot shock US but are not elicited by the tone CS alone. In general, after as few as one CS–US pairing, it can be demonstrated that the animal has learned to respond to the tone alone with an array of stereotyped elements that make up a fear response. These measurable responses include defensive postures (freezing), autonomic changes (heart rate, blood pressure, respiration), decreased pain sensitivity (hypoalgesia), potentiation of reflexes (for example, fear-potentiated startle and eyeblink response), and endocrine activation (corticosteroid and adrenaline release). Figure 39.2 presents a schematic diagram of fear conditioning. Although the characteristics of the individual elements tend to be species specific, the array of responses is common to many species including humans, monkeys, and rodents.

FIGURE

39.2 Schematic diagram of fear conditioning.

It is also possible to establish conditioned fear associations through “higher order conditioning.” Here a distinct stimulus (CS2) is paired with an established fear CS (CS1), which endows the CS2 with fear-eliciting properties indirectly through its association with CS1 (Gewirtz and Davis, 2000). In addition, it has been shown in monkeys that simply observing a fearful response, such as to a snake, in a conspecific can result in a CR in the observer when later exposed to the stimulus (Mineka and Cook, 1993). Recent work in humans indicates observational conditioning also can occur in humans (Olsson and Phelps, 2004). Neural mechanisms of acquisition, storage, and expression of conditioned fear The neurocircuitry of Pavlovian fear conditioning is well established, with general agreement that the amygdala is essential for the acquisition and expression of conditioned fear responses (Davis, 1992; Kapp et al., 1992; LeDoux, 1992; Fanselow, 1994). The amygdala is composed of several structurally and functionally heterogeneous nuclei residing in the medial temporal lobe. It is within the amygdala that information about the CS and the US converge, and efferent pathways from the amygdala control, in parallel, the autonomic, endocrine, and behavioral responses. The nuclei of the amygdala identified as relevant to fear conditioning are the lateral (LA), basal (B), accessory basal (AB), and central (CE) nuclei. Sometimes the adjacent LA and B nuclei are referred to together as the basolateral nucleus (BLA). Studies in several species including rats, cats, and monkeys are in general agreement about the interconnections between LA, B, AB, and CE (Amaral et al., 1992; Pare et al., 1995; Pitkänen et al., 1997; Cassell et al., 1999). Although LA and CE participate in fear conditioning (LeDoux, 2000; Maren, 2001; Davis, 2006), some debate exists about the role of each and the manner in which they interact (Cardinal et al., 2002; Pare et al., 2004; Balleine and Killcross, 2006; Wilensky et al., 2006). Other brain regions to which the amygdala sends projections mediate the individual components of the fear response. The circuit crucial to auditory fear conditioning involves tone CS information that is received via the sensory apparatus of the ear and is relayed through brain stem to the auditory portion of thalamus (LeDoux, 1996, 2000; Sigurdsson et al., 2007). Auditory thalamus relays the CS information via at least two distinct pathways. Electrophysiological studies have demonstrated a rapid, monosynaptic thalamo-amygdala pathway (12 msec) and a slower, polysynaptic thalamo-cortico-amygdala pathway (30–40 msec). Both pathways, which transmit information via ionotropic glutamatergic synapses, converge on neurons in LA. The thalamo-amygdala pathway is believed to provide for a rapid response to

39: NEUROBIOLOGY OF FEAR AND ANXIETY

threatening environmental stimuli, but the representation of the environmental stimuli is considered crude. In contrast, the thalamo-cortico-amygdala pathway may provide a more complex representation due to processing through sensory cortex, providing for a more appropriate, albeit slower, response to the perceived stimuli. This arrangement allows the response to danger to begin before there is conscious appreciation of the stimulus. See Figure 39.3 for a diagram of the neural circuits identified through auditory fear conditioning. The transmission of US information (representing the mild foot shock) is less well understood but is thought in part to involve a relay via the spinothalamic tract to thalamic areas projecting to LA (LeDoux et al., 1987; LeDoux et al., 1990). An electrophysiological response of neurons in LA is recorded when pain receptors are stimulated, and some of these cells have also been demonstrated to respond to the auditory CS (Romanski et al., 1993). As well, other sensory modalities have pathways with nerve terminals that synapse mainly in LA (LeDoux et al., 1990; Amaral et al., 1992; Mascagni et al., 1993; McDonald, 1998). The central nucleus is often referred to as the main output station of the amygdala because it is critical for the expression of the conditioned fear response (LeDoux et al., 1988; Davis, 1992; Kapp et al., 1992; Maren and Fanselow, 1996). More recent work suggests CE may also play a role in fear acquisition and memory consolidation (Pare et al., 2004; Samson and Pare, 2005; Wilensky et al., 2006). The central nucleus sends projections to diverse brain regions that mediate the specific components of a fear response. For example, CE projections to the periaqueductal gray are involved in freezing behavior and pain modulation; those through the bed nucleus of the stria terminalis (BNST) and preoptic area, as well as sparse projections directly from CE to the paraventricular nucleus of the hypothala-

39.3 Diagram of neural circuits identified through auditory fear conditioning.

FIGURE

611

mus, appear to modulate hypothalamic-pituitary-adrenal (HPA) axis activity; and those to the parabrachial nucleus, lateral hypothalamus, and dorsal motor nucleus of the vagus are involved in autonomic responses such as cardiovascular and respiratory alterations (LeDoux et al., 1988; Van de Kar et al., 1991; Davis, 1992; Manning, 1998) (see Fig. 39.3). Another view is that CE mediates different learned fear responses than those mediated by the LA (Cardinal et al., 2002; Balleine and Killcross, 2006). Contextual fear conditioning is similar to fear conditioning to a cue CS, such as a tone, in that an association can rapidly be learned between a foot shock and a representation of the environment (the context) in which the foot shock was received. When simply placed back in that environment in which it had previously received a foot shock, the animal will respond with the same stereotyped array of responses described for auditory fear conditioning. The pathways that mediate this association appear to differ from conditioning to a simple cue in that conditioning to the context depends not only on the amygdala nuclei involved in auditory fear conditioning, but also on the hippocampus (R.J. Blanchard et al., 1970; J.J. Kim and Fanselow, 1992; Phillips and LeDoux, 1992; Maren et al., 1997; Frankland et al., 1998). Similar to auditory fear conditioning, intra-amygdala processing of contextual information predicting danger ultimately results in output pathways from amygdala to particular brain areas mediating components of the fear response. Different amygdala nuclei appear to mediate independent fear learning systems. For example, rats can be trained on an operant conditioning paradigm known as the escape from fear (EFF) task in which the CS reinforces an escape motor response that terminates the CS. Whereas CE lesion blocks conditioned freezing but not EFF behavior, lesions of B block EFF but not conditioned freezing (Amorapanth et al., 2000). Lateral nucleus lesions interfere with both responses, suggesting plasticity there contributes to both. A related paradigm involves the ability to learn avoidance of a CSpaired shock that was contingent upon a lever press (Killcross et al., 1997). Lesions of BLA but not CE block the avoidance learning. In these paradigms, LA relays information to B, which processes the CS as a learned incentive. This processing in turn may activate motor circuits of striatum. The amygdala has also been shown to have a modulatory influence for implicit learning systems that do not involve fear. For example, intra-amygdala amphetamine administration enhances memory for a spatial, hippocampus-dependent memory task as well as for a motor learning, caudate-dependent task (Packard and Teather, 1998). Inhibitory avoidance, for example, is a complex task that depends on the hippocampus and other structures. In this task, an animal must learn to

612

ANXIETY DISORDERS

avoid entering a context that was previously paired with a foot shock. Neurochemical activity in the amygdala has been shown to contribute to the efficacy of this complex form of learning (for reviews see McGaugh, 2004, 2006). However, the amygdala does not seem to perform this modulatory function for fear conditioning because inactivation of the amygdala immediately posttraining does not affect the strength of the memory stored (Wilensky et al., 1999, 2000). Neural systems of fear regulation and extinction The PFC also plays a critical role in the normal expression and extinction of fear responses (Morgan et al., 1993; Morgan and LeDoux, 1995, 1999; Morgan et al., 2003; Quirk and Beer, 2006). Extinction is the form of learning whereby the CR to a repeatedly presented CS (in a previously conditioned animal) diminishes over repetitions of the CS. Importantly, extinction of a previously consolidated fear memory does not typically erase the learned association between the CS and the US. Rather, extinction involves new learning that regulates fear expression. However, recent study suggests that extinction training administered shortly after an aversive experience, when the fear memories are not yet consolidated, may engage mechanisms resembling “unlearning” processes (Myers et al., 2006). Furthermore, another report demonstrates that the efficacy of early extinction depends on the level of fear present during the extinction trial intervention (Maren and Chang, 2006). Lesion studies suggest that the ventromedial PFC (vmPFC), which in rat includes the prelimbic and infralimbic cortex, plays a role in the consolidation and/ or expression of extinction (Morgan et al., 1993; Quirk et al., 2000). However, the initial acquisition of extinction appears to critically involve N-methyl-D-aspartate (NMDA) receptor activation in the LA/B (Sotres-Bayon et al., 2007). Hippocampal inputs to vmPFC appear to perform a gating function for expression of extinction, with the hippocampus-vmPFC circuit likely providing contextual information (Sotres-Bayon et al., 2004). Projections from vmPFC to γ-aminobutyric acid (GABA) ergic interneurons of amygdala, known as intercalated cells (ITC), appear to be inhibitory for CE output, and ITC activity may be modulated by D1-dopaminergic, μ-opioid, and oxytocin receptors. Prefrontal cortex dopamine has been specifically implicated in the expression and extinction of conditioned fear responses (Pezze and Feldon, 2004). Although infralimbic cortex has an inhibitory role in fear expression, the more dorsally located prelimbic cortex has been shown to be excitatory. Human functional magnetic resonance imaging (fMRI) studies support a role for vmPFC in the expression of extinction learning, with recent evidence suggesting the

human homologues of infralimbic and prelimbic cortex, the subgenual (BA25) and dorsal anterior cingulate cortex (dACC; BA32), respectively, play opposing roles in modulation of response to conditioned fear stimuli (Quirk and Beer, 2006). Expression of extinction learning in humans has been shown to activate vmPFC and hippocampus in a context-dependent manner, implicating the hippocampal-vmPFC circuit in fear regulation after extinction (Kalisch et al., 2006). Anxiety disorders such as PTSD may involve fear system hyperactivity as a result of deficient function in the hippocampal-vmPFC circuit, with impairment in extinction recall and its modulation by context (Rauch et al., 2006). Current psychotherapies for PTSD such as prolonged exposure (to the individual’s own trauma story) may work by encouraging extinction of cue and contextual fear memories associated with the trauma rather than sustaining the typical avoidance pattern to such stimuli. Because the prelimbic cortex has been found to be excitatory for fear expression, localized disruption of its homologue in humans, the dACC, via deep brain stimulation (DBS) may offer a therapeutic approach for particular anxiety conditions similar to the use of DBS in refractory depression (Mayberg et al., 2005). Synaptic and modulatory mechanisms of fear acquisition, expression, and extinction Neurotransmission through the aforementioned fear circuits is largely carried out through glutamatergic neurons that transmit across synapses via rapid, ion-channeldependent mechanisms. Several classes of neurochemicals released at synaptic boutons by other types of neurons have been shown to be modulators of the fearful and anxious responses mediated by such glutamatergic neurons. These include the amino acid transmitter GABA; monoamines such as serotonin, noradrenaline, and dopamine; and neuropeptides such as corticotropin-releasing factor (CRF). GABAergic neurons make up the main braking system for glutamatergic neurotransmission, also transmitting through ion-channel receptors. Indeed, removal of tonic inhibition in amygdala by local administration of a GABA antagonist to BLA in awake rats results in an increase in anxiety-like behaviors and autonomic response (Sanders et al., 1995), and this effect can be blocked by preinfusion of glutamatergic receptor antagonists into BLA (Sajdyk and Shekhar, 1997). Monoaminergic (serotonergic, dopaminergic, noradrenergic) neurons generally play a modulatory role on glutamatergic neurotransmission, either directly or via GABAergic interneurons, through slower postsynaptic mechanisms involving G protein–coupled receptors. For example, within LA serotonin appears to inhibit ionotropic glutamatergic neurotransmission via activation

39: NEUROBIOLOGY OF FEAR AND ANXIETY

of GABAergic interneurons, a process that depends on presence of the stress hormone corticosterone (Stutzmann et al., 1998; Stutzmann and LeDoux, 1999). Noradrenaline enhances consolidation of inhibitory avoidance through activation of β-adrenergic receptors in BLA (Ferry et al., 1999). Although there is much evidence showing the enhancing effect of norepinephrine (NE) on fear learning (McGaugh, 2006), the exact role of noradrenergic transmission in LA in the acquisition (Bush et al., in prep), consolidation (Kobayashi and Kobayashi, 2001; H.J. Lee et al., 2001; Debiec and Ledoux, 2004; Murchison et al., 2004; Bush et al., 2007) and retrieval (Murchison et al., 2004) of fear conditioning requires further studies. Recent data demonstrate that postretrieval noradrenergic blockade in LA using β-adrenergic receptor antagonist propranolol disrupts reconsolidation processes and results in lasting attenuation of learned fear responses (Debiec and LeDoux, 2004). There are also glutamatergic neurons that form slower, metabotropic, glutamatergic synapses that also modulate ionotropic glutamatergic neurotransmission. The group I metabotropic glutamate receptor subtype 5 (mGluR5) is requisite for acquisition of fear memory (Fendt and Schmid, 2002; Rodrigues et al., 2002), whereas the mGluR1 is essential for extinction of learned fear but not acquisition (J. Kim et al., 2007). Corticotrophin-releasing factor is a 41-amino acid polypeptide first isolated from hypothalamus that was shown to activate the HPA axis (Vale et al., 1981). The amygdala is a major extra-hypothalamic source of CRF-secreting neurons and has significant expression of the two major types of CRF receptors (De Souza et al., 1985; Perrin et al., 1993; Chalmers et al., 1995; Smagin et al., 1996; Dieterich et al., 1997; Rominger et al., 1998). Stressful challenge results in CRF release in amygdala (Roozendaal et al., 2002). Direct stimulation of CRF receptors in BLA increases anxiety-related behaviors (Sajdyk et al., 1999). In fact, CRF agonists generally enhance anxious responding on diverse anxiety paradigms, including facilitation of conditioned fear acquisition, facilitation of acoustic startle, suppression of exploration on the EPM, enhancement of place aversion, and enhancement of defensive burying. Corticotrophin-releasing factor antagonists generally reduce these same behaviors (Swiergiel et al., 1992; Menzaghi et al., 1994; T.S. Gray and Bingaman, 1996; Smagin et al., 1996; Koob, 1999; Koob and Heinrichs, 1999; Martins et al., 2000). The enhancement of acoustic startle by intraventricular CRF is blocked by chemical lesion of BNST, indicating another important site of action for CRF in an anxiety-related behavior (Y. Lee and Davis, 1997). Also, CRF-expressing neurons project from CE to locus coeruleus (Van de Kar et al., 1991) and modulate output of noradrenaline in forebrain (Bouret et al., 2003).

613

Molecular mediators of learning and memory in the fear system New learning implies lasting changes in brain so that what has been learned may be retrieved in the future. Memory consolidation is the process whereby shortterm memory is transformed into long-term memory, and much work indicates this is a process dependent on new protein synthesis (for review see Rodrigues et al., 2004). Studies using targeted pharmacological manipulations have characterized the role of LA in the acquisition, consolidation and storage of auditory fear conditioning in rodents (Fanselow and LeDoux, 1999; Maren, 2001; Schafe et al., 2001; Rodrigues et al., 2004; Dityatev and Bolshakov, 2005; Faber et al., 2005; Pape et al., 2005). Interference or enhancement of the molecular pathways involved in aversive learning in LA modulates retention of conditioned fear responses. A growing body of data suggests that retrieval of consolidated fear memories, by presentation of a learned cue, triggers a reconsolidation process in LA that renders the retrieved memories susceptible to pharmacological disruption (Nader et al., 2000). One widely studied model for the establishment of stable memories is long-term potentiation (LTP). In LTP, application of a high-frequency stimulation of afferent fibers to a synapse can result in long-lasting increase in the efficiency of neurotransmission through the synapse (Bliss and Lomo, 1973). In the case of fear learning, LTP-like changes occur in the auditory thalamoamygdala pathway after fear conditioning to tone (Rogan et al., 1997). Stimulation of this glutamatergic pathway has been shown to result in LTP of synapses in LA through a mechanism dependent on activation of voltage-gated calcium ion channels on the postsynaptic neuron (Weisskopf et al., 1999). Known inhibitors of LTP, including inhibition of protein synthesis, protein kinase A (PKA), and extracellular signal regulated kinases/mitogen-activated protein (ERK/MAP) kinase activity (Huang et al., 1996; Huang and Kandel, 1998; Huang et al., 2000), have also been shown to disrupt fear memory consolidation given by systemic injection and local amygdala infusion, yet they leave short-term memory intact (Schafe et al., 1999; Schafe et al., 2000; Schafe and LeDoux, 2000) (see Figure 39.4a-e). The long-term changes that support stable fear memory appear to occur through plastic changes in the synapses within amygdala. Coincident activation of postsynaptic neurons in amygdala by presynaptic afferents separately carrying the CS and US sensory information sets in motion a molecular cascade of synaptic events that involve activation of postsynaptic receptors, ion flow through membrane channels, action potentials, activation of second-messenger systems, activation of transcriptional factors, new protein synthesis, and, ultimately, microstructural changes in the microanatomy of

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ANXIETY DISORDERS

39.4 Map kinase inhibitor on short-term memory/long-term memory (STM/LTM).

FIGURE

the synapse. Within the more dorsal region of the dorsal portion of LA (LAd) there are neurons with converging sensory inputs that demonstrate transient plastic changes, termed trigger cells (Repa et al., 2001). Neurons in the more ventral region of LAd demonstrate long-lasting plastic changes, termed storage cells. It appears that the storage cells of LAd relay information to the medial portion of LA, and from there information is relayed to CE. One of the three main types of postsynaptic ionotropic receptors for glutamate is termed the NMDA receptor. Within BLA, NMDA-dependent and NMDAindependent forms of LTP have been identified (Weisskopf et al., 1999; Bauer et al., 2002). One of the peptide subunits that make up this receptor is termed the NR2B subunit. It has been shown using an inhibitor of the NR2B subunit that it is involved in acquisition but not consolidation of fear memory (Rodrigues et al., 2001), and the subunit is requisite for LTP in amyg-

dala (Bauer et al., 2002). This suggests the NR2B subunit is involved in the short-term form of synaptic memory required for transient changes in neurotransmission that occur during fear learning, but not in the protein synthesis–dependent changes that occur over hours that mediate development of long-term synaptic plasticity. Corticotrophin-releasing factor receptors have been implicated in the long-lasting changes that occur within the amygdala associated with pathological anxiety responses (Sajdyk et al., 1999). Acute activation of CRF receptors in BLA in vitro has been shown to increase the excitability of BLA neurons through effects on the slow after hyperpolarizing potential (Rainnie et al., 1992). Moreover, the CRF-induced behavioral syndrome correlates with cellular mechanisms of neuronal plasticity, suggesting a mechanism by which stressful challenges result in lasting changes in response to future adversity (Rainnie et al., 2004). Homologous to the amygdala’s role in fear memory consolidation, the vmPFC appears to be key to extinction-related plasticity. Local administration of inhibitors of protein synthesis and protein kinases in vmPFC does not affect short-term expression of extinction but does impair consolidation of extinction (Quirk and Beer, 2006). However, the vmPFC contribution to the consolidation of fear extinction may depend on learning mechanisms that first take place in the amygdala, because infusion of ifenprodil, an antagonist for NR2Bcontaining NMDA receptors, directly into the amygdala disrupts the initial acquisition of fear extinction (SotresBayon et al, 2007). A model for fear extinction has proposed that the amygdala is crucial for the acquisition of extinction, and that plasticity in the vmPFC is important for gating the later expression of extinction (Sotres-Bayon et al., 2004). Animal model work on consolidation of fear memories and extinction has directly led to several potential modes of therapeutic intervention for anxiety conditions with presumed fear system hyperactivity. For example, there have been trials of amnestic agents to block memory consolidation (Pitman and Delahanty, 2005) or reconsolidation (Nader et al., 2000; Debiec and LeDoux, 2004; Brunet et al., 2008) to reduce anxiety-provoking intrusive memories in trauma and PTSD. Also, there has been employment of the antibiotic d-cycloserine to enhance extinction in exposure therapy, based on this molecule’s partial NMDA antagonist properties (Walker et al., 2002; Ressler et al., 2004; Davis et al., 2006). Use of fear conditioning as a biological probe The breadth of molecular, synaptic, cellular, and circuitry information on fear conditioning make this anxiety paradigm ideal to serve as a biological probe of the roles of the individual components of the fear network, in particular anxious behaviors and anxiety dis-

39: NEUROBIOLOGY OF FEAR AND ANXIETY

orders (Cannistraro and Rauch, 2003). Thus, not only may contributions of intra-amygdala processes for anxious responding be investigated, but those of other mediators of the fear circuitry such as hippocampus and regions of PFC may be detected and pursued at many levels within the fear conditioning model. Functional imaging in humans may be used to verify the applicability of fear conditioning models, dissect distinguishing loci of abnormal activity between anxiety disorders, and study the neurobiological effects of therapeutic interventions. For example, PTSD and panic involve exaggerated amygdala responses to a conditioned fear stimulus (Bremner, 2004). However, activity in hippocampus and PFC regions may separate PTSD and panic. One might predict that PTSD may have a muted hippocampal response to context, given that such patients often respond to threats in inappropriate contexts. Patients with panic, on the other hand, may have heightened hippocampal activity due to their exaggerated concern about contexts in which panic may be evoked. Although the central role of the amygdala in fear conditioning is well established, it should be noted that the amygdala’s role in anxiety has been debated. Gray and McNaughton’s behavioral inhibition model of anxiety places emphasis on the role of the septohippocampal system (McNaughton and Gray, 2000; McNaughton, 2006), and Davis has described a key role for BNST in anxiety as opposed to fear (Davis et al., 1997; Walker et al., 2003). Yet the behavioral paradigms on which these theories are based involve tasks that require the processing of fear-inducing contextual information. Given that the BNST (G.M. Sullivan et al., 2004) and hippocampus (J.J. Kim and Fanselow, 1992; Phillips and LeDoux, 1992; Maren et al., 1997; Fanselow, 2000; Liu et al., 2004) are requisite for contextual fear conditioning and are densely interconnected (Herman et al., 2005), it is important to distinguish the roles of these regions in contextual processing from a specialized role in anxiety. Anxiety does appear to engage cognitive processes to a greater extent than fear, which is consistent with key roles for hippocampus and BNST. But imaging studies in healthy volunteers have demonstrated an increase in amygdala signal upon induction of anxiety (Phelps et al., 2001). Moreover, there are several examples of abnormally enhanced amygdala signal in several of the anxiety disorders (Stein et al., 2002; Protopopescu et al., 2005; Shin et al., 2005; Straube et al., 2005), suggesting a role for the amygdala in anxiety as well as fear. Multimodal Models for Understanding Pathological Anxiety and the Anxiety Disorders The aforementioned animal models generally involve healthy animals in which measurements are made of

615

the fearful and anxious responses to the environmental challenges posed by the paradigms (Lister, 1990). Due to the relatively poor reliability of an individual’s performance between tasks, it is suggested that most models, especially those in normal animals with limited genetic variability, measure state fear and anxiety to a greater degree than trait fear and anxiety (Andreatini and Bacellar, 2000). This is not analogous to human anxiety disorders in which pathological anxiety is commonly an enduring feature, and a large degree of the variability in symptoms is accounted for by genetic predisposition. In other words, individuals with anxiety disorders are not simply reacting to the environmental conditions (Hidalgo and Davidson, 2000) but, rather, appear to have a greater predisposition or susceptibility. Therefore, for the purpose of uncovering the neurobiology of pathological anxiety and the anxiety disorders, a paradigm should instead reveal a condition present in the animal through a measurable response. The basic anxiety paradigms may be better adapted through various manipulations to better model the pathological behavioral symptoms characteristic of particular anxiety disorders. In this section we look beyond models of normal fear and anxiety to consider hybrid models that explicitly examine factors that are thought to contribute to psychopathology. An approach to modeling anxiety disorders that shows much promise for understanding pathological anxiety is combining fear conditioning with other experimental manipulations that enhance the predictive, face, and/ or construct validity of the model. Table 39.3C lists some examples of hybrid models that may be more relevant to trait anxiety and the pathological anxiety found in the anxiety disorders. Although hybrid anxiety models may utilize other anxiety paradigms, including the unlearned types, fear conditioning offers the advantage of the well-described circuitry and cellular biology. The manipulations we briefly discuss fall into a few general categories: physiological interventions, usually involving systemic or localized administration of drugs with known physiological effects; stressful interventions during development or in adulthood; and genetic alterations, such as those produced by selective breeding or by modification of deoxyribonucleic acid (DNA). We also discuss a novel route of selection by phenotype or trait. Physiological models have been used to assess the effects of altering function in fear circuits on subsequent fearful and anxious behaviors. This has involved generation of hyperexcitability of specific brain regions such as BLA and hypothalamus by administration of chemicals or induction of partial kindling (Sanders et al., 1995; Keim and Shekhar, 1996; Rosen et al., 1996; Sajdyk et al., 1999). Models considered relevant to panic disorder include treatments with drugs that produce panic attacks in humans, including lactate (Shekhar et al.,

616 TABLE

ANXIETY DISORDERS

39.3C Examples of Hybrid (Learned/Unlearned) Models of Trait Anxiety Related Disorders/ Human Analogue

Animal Model

Key References

Pathophysiological models Periaqueductal gray stimulation

Panic disorder, GAD

(Graeff et al., 1993)

Lactate and social interaction

Panic disorder

Amygdala (BLA): (Sajdyk et al., 1999) Hypothalamus (dorsomedial): (Shekhar et al., 1996)

Doxapram and fear conditioning

Panic with agoraphobia

(G.M. Sullivan et al., 2003)

Bicuculline

Aversive memory consolidation

(Brioni and McGaugh, 1988; Castellano and McGaugh, 1990)

Stress models Developmental stress Stress in altricial neonate

(R. Sullivan et al., 2006)

Maternal separation/handling

(Plotsky et al., 2005)

Ultrasonic vocalization (abrupt isolation from nest)

(Hofer, 1996)

Variable foraging demand (bonnet macaque)

PTSD, panic disorder, GAD, social anxiety disorder

(Rosenblum and Paully, 1984; Coplan et al., 1992; Rosenblum and Andrews, 1994; Coplan et al., 1998; Coplan et al., 2001)

Stress inoculation (squirrel monkey)

No PTSD subsequent to trauma (resilience)

(Parker et al., 2004; Lyons and Parker, 2007)

Adult stress Single prolonged stress

PTSD

(Liberzon et al., 1999)

Fear-potentiated behavior on the elevated plus-maze

GAD, PTSD

(Adamec et al., 2004; also see Mechiel Korte and De Boer, 2003)

Genetic models Selective breeding Roman rat; Lewis rats

(Driscoll et al., 1998; Cohen et al., 2006)

Transgenic and knock-out models

(Finn et al., 2003)

5-HT system

(Heisler et al., 1998; Parks et al., 1998; Ramboz et al., 1998)

CRF system

(Heinrichs et al., 1997)

GABA system

(Kash et al., 1999)

Trait selection models Selection based on behavioral phenotype

PTSD

(Bush et al., 2007)

GAD: generalized anxiety disorder; PTSD: posttraumatic stress disorder; BLA: basolateral amygdala; CRF: corticotrophin releasing factor; GABA: γ -aminobutyric acid.

1996) or doxapram (G.M. Sullivan et al., 2003), and testing for enhancement of fear and anxiety on unlearned and learned tests such as the open field test, the social interaction test, and fear conditioning. An example of a physiological intervention is the combination of fear conditioning with administration of the respiratory stimulant doxapram, a drug that elicits a panic attack in most patients with panic disorder (Y.J. Lee et al., 1993). Doxapram enhances acquisition of conditioned fear memory (G.M. Sullivan et al., 2003), and, at the same dose, enhances CRF release in CE but not in BNST or hypothalamus (Choi et al., 2005).

Doxapram is known to induce hyperventilation via activation of carotid body chemoreceptors, thereby producing a (false) visceral signal to brain indicating poor air. Because the circuitry of conditioned fear is well described, it is possible to test the hypothesis that this visceral signal induces panic-like symptoms by altering the threat processing of internal or external events through CE. Developmental models have assessed the effects of stress in early life on fearful and anxious behaviors manifested later in life (Rosenblum and Paully, 1984; Coplan et al., 1992; Levine, 1994; Shanks et al., 1995;

39: NEUROBIOLOGY OF FEAR AND ANXIETY

Hofer, 1996; Meaney et al., 1996; Heim et al., 1997; Francis et al., 1999; Francis and Meaney, 1999; Graham et al., 1999; Meaney et al., 2000; R. Sullivan, 2003; Moriceau et al., 2004; Imanaka et al., 2006; R. Sullivan et al., 2006; Tsoory and Richter-Levin, 2006). In rodents, for example, early exposure to maternal deprivation permanently alters central CRF systems and related behavioral and hormonal responses to subsequent stressors throughout life (Plotsky et al., 2005). Ecologically informed studies of maternal availability have likewise identified similar outcomes in nonhuman primates. Bonnet macaque monkeys raised by their mothers in variable-foraging demand conditions respond to novel situations with increased anxiety compared to age-matched monkeys raised as low-foraging demand controls (Rosenblum and Andrews, 1994). As adults, these same monkeys exhibit significant differences in cerebrospinal fluid levels of monoamines, somatostatin, and CRF (Coplan et al., 1998; Coplan et al., 2001). These findings agree with evidence from humans that early exposure to severe forms of stress is a risk factor for the development of mood and anxiety disorders (Davidson et al., 2004; Heim et al., 2004). Far less researched, but of equal importance, are indications that early life stressors may also foster resilience. Ongoing studies of squirrel monkeys suggest that early exposure to stressful events that are not overwhelming but challenging enough to elicit emotional activation and cognitive processing may make subsequent coping efforts more efficient, and therefore easier and more likely to be used later in life (Lyons and Parker, 2007). Figures 39.5A and 39.5B show the behavioral and neuroendocrine differences, respectively, of such “stress inoculation.” Behavioral manipulations in adulthood that affect structure and function of fear circuits often involve exposure to acute or chronic stressors (Cohen and Zohar, 2004; Miller and McEwen, 2006). Examples include restraint or immobilization, cold exposure, electric shock, predator exposure, and underwater submersion (Rittenhouse et al., 1992; Richter-Levin, 1998; Mechiel Korte and De Boer, 2003; Cohen et al., 2004; Morilak et al., 2005; Rau et al., 2005; Adamec et al., 2006). Repeated exposure to these stressors in adulthood increases fear and aggression, alters contextual fear responses, affects performance on the EPM, and attenuates spatial memory. Restraint stress also facilitates fear conditioning, results in dendritic atrophy in hippocampus and medial PFC, suppresses neurogenesis in the dentate gyrus, and induces dendritic hypertrophy and sprouting of new synapses in the amygdala (Miller and McEwen, 2006). These stress-induced aspects of neural plasticity suggest a putative link between remodeling of fear circuits and the development of anxiety as modeled in adult rodents. Chronic stress and underwater submersion have also been used in rodent research to mimic the requi-

617

39.5A Measures of behavior in monkeys exposed to intermittent stress inoculation (IS) compared to no-stress (NS) condition (adapted from Parker et al., 2004).

FIGURE

site stressful events of traumatic anxiety disorders such as PTSD (Servatius et al., 1995; Richter-Levin, 1998; Cohen et al., 1999; Adamec et al., 2004; Cohen and Zohar, 2004; Pitman and Delahanty, 2005; Matar et al., 2006; T. Takahashi et al., 2006).

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ANXIETY DISORDERS

same context but with novel cues added, they do not exhibit the normal decrement in fear response seen in wild-type mice (Klemenhagen et al., 2006). This difference in sensitivity to novel stimuli has been likened to a memory bias for threatening cues in an otherwise neutral environment as may occur in human patients with panic disorder and PTSD. Given the well-described role of hippocampus in providing a representation of context to amygdala, focused investigation of hippocampal-amygdala interactions involving the 5-HT1A receptor is suggested. The serotonin system has also been implicated in the discovery of associations between anxiety and naturally occurring genetic polymorphisms. In particular, an insertion/deletion event in the serotonin transporter– linked polymorphic region (5HTTLPR) is known to produce long (l) and short (s) alleles in humans and rhesus monkeys (Lesch et al., 1997). The short allele decreases transcriptional efficiency and is thought to diminish expression of the serotonin transporter that

FIGURE 39.5B Plasma levels of hormones in monkeys exposed to intermittent stress inoculation (IS) compared to a no-stress (NS) condition (adapted from Parker et al., 2004).

Genetic manipulations before behavioral assessments of fear and anxiety in rodent models have generally been achieved by two main methods. One is selective breeding of rat strains with the goal of enhancing or attenuating particular measures of fear and anxiety (C.D. Walker et al., 1989; Ferrel et al., 1995; Escorihuela et al., 1997; Wehner et al., 1997; Escorihuela et al., 1999; Pisula and Osinski, 2000; Paterson et al., 2001; Yilmazer-Hanker et al., 2002; Steimer and Driscoll, 2003; Aguilar et al., 2004; Morilak et al., 2005). The other is creation of transgenic mice that have altered expression of particular genes that code for proteins in brain circuits of interest, and testing for changes in behavioral performance on anxiety-inducing paradigms (Heisler et al., 1998; Tecott et al., 1998; Low et al., 2000; Tecott, 2000; Sibille and Hen, 2001; Gross and Hen, 2004; Leonardo and Hen, 2006). An example of the latter approach comes from studies of fear conditioning in the 5-HT1A knockout mouse. When previously context-conditioned 5-HT1A-null mice are tested in the

FIGURE

39.6 Phenotype selection for fear reactivity and recovery.

39: NEUROBIOLOGY OF FEAR AND ANXIETY

disrupts control of extracellular concentrations of serotonin in neural circuits. Humans homozygous for the short allele (s/s) are more anxious and display greater muscle tension, increased shyness, and more harm avoidance compared to humans that are homozygous (l/l) or heterozygous (l/s) for the long allele. Similar associations have been reported for infant and adult rhesus monkeys (Champoux et al., 2002; Barr et al., 2004; Bethea et al., 2004). It has been proposed that consideration be given to individual differences in susceptibility and resilience in animal models of anxiety disorders (Charney, 2004). This is particularly important in models for PTSD, as it is well documented that similar levels of exposure to a horrific trauma results in development of PTSD in a relatively small proportion of those exposed (Charney, 2004; Yehuda, 2004). Of note, phenotypic variability in most animal models of fear and anxiety is obscured by the usual practice of reporting the variation around the mean. Recent work shows that fear reactivity scores in conditioned animals are normally distributed in unselected Sprague–Dawley rats (Bush et al., 2007). When given fear extinction training, rats that show similarly high levels of fear reactivity can also be separated into fast and slow fear recovery groups. Figures 39.6A and 39.6B show the phenotypic differences in fear reactivity and fear recovery of these selected groups. The slowextinguishing group is proposed to have relevance for PTSD, the psychopathology of which involves a failure to recover from trauma (Yehuda, 2004). Similar to microarray analyses of gene expression in selectively bred rats (Zhang et al., 2005; Pearson et al., 2006), these trait-selected rats offer opportunities to correlate gene expression with fearful and anxious phenotypic expression. Thus, models that consider individual phenotypic differences in fearful and anxious responding will likely be among the more effective for modeling the anxiety disorders (Cohen et al., 2004; Bush et al., 2007). CONCLUSIONS A variety of animal models have been developed for fear and anxiety. Much of the current conceptualization of the underlying neurobiology of the anxiety disorders has been derived from neuroscience research employing rodent and nonhuman primate models. Some models apply to normal fearful and anxious responses in humans, whereas others are more applicable to anxiety disorders. Because each of the DSM-defined anxiety disorders has a unique symptom profile, it is especially important to carefully attend to behavioral details of the models to provide insights into specific disorders. Behavioral models that induce fear and anxiety symptoms in normal animals can be combined with other manipulations to emulate anxiety disorders. Some

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models such as fear conditioning apply to many disorders (learning in anxiety disorders) whereas others focus on specific disorders. In addition to face, predictive, and construct validity, consideration needs to be given to the value of the model for pursuing underlying neural mechanisms. Fear conditioning is particularly good in this category because of the extensively defined molecular, cellular, synaptic, and circuitry foundations. Brain regions involved in conditioned fear acquisition, expression, and regulation such as amygdala, hippocampus, and vmPFC have been implicated in a variety of anxiety disorders; therefore fear conditioning can be utilized as a bioassay to assess different functional changes that may occur in these areas in different disorders. Basic neuroscience research on animal models is providing hypotheses that can be tested in patients with anxiety disorders, with functional imaging technologies now offering a heretofore unavailable window on the correlates of regional activity in the human brain. Future research will likely offer many additional and perhaps more powerful applications of findings from animal models to our emerging understanding of anxiety disorders. REFERENCES Adamec, R.E., Blundell, J., et al. (2005) Neural circuit changes mediating lasting brain and behavioral response to predator stress. Neurosci. Biobehav. Rev. 29(8):1225–1241. Adamec, R.E., Blundell, J., et al. (2006) Relationship of the predatory attack experience to neural plasticity, pCREB expression and neuroendocrine response. Neurosci. Biobehav. Rev. 30(3):356–375. Adamec, R., Walling, S., et al. (2004) Long-lasting, selective, anxiogenic effects of feline predator stress in mice. Physiol. Behav. 83(3):401–410. Aguiar, M.S., and Brandao, M.L. (1996) Effects of microinjections of the neuropeptide substance P in the dorsal periaqueductal gray on the behaviour of rats in the plus-maze test. Physiol. Behav. 60(4):1183–1186. Aguilar, R., Gil, L., et al. (2004) Genetically-based behavioral traits influence the effects of Shuttle Box avoidance overtraining and extinction upon intertrial responding: a study with the Roman rat strains. Behav. Processes 66(1):63–72. Akwa, Y., Purdy, R.H., et al. (1999) The amygdala mediates the anxiolytic-like effect of the neurosteroid allopregnanolone in rat. Behav. Brain Res. 106(1-2):119–125. Amaral, D.G., Price, J.L., et al. (1992) Anatomical organization of the primate amygdaloid complex. In: Aggleton, J.P., ed. The Amygdala: Neurobiological Aspects of Emotion, Memory, and Mental Dysfunction. New York: Wiley-Liss, Inc., pp. 1–66. American Psychiatric Association. (2000) Diagnostic and Statistical Manual of Mental Disorders, text rev.. Washington, DC: Author. Amorapanth, P., LeDoux, J.E., et al. (2000) Different lateral amygdala outputs mediate reactions and actions elicited by a feararousing stimulus. Nat. Neurosci. 3(1):74–79. Andreatini, R., and Bacellar, L.F. (2000) Animal models: trait or state measure? The test-retest reliability of the elevated plus-maze and behavioral despair. Prog. Neuropsychopharmacol. Biol. Psychiatry 24(4):549–560. Anglada-Figueroa, D., and Quirk, G.J. (2005) Lesions of the basal amygdala block expression of conditioned fear but not extinction. J. Neurosci. 25(42):9680–9685.

620

ANXIETY DISORDERS

Balleine, B.W., and Killcross, S. (2006) Parallel incentive processing: an integrated view of amygdala function. Trends Neurosci. 29(5): 272–279. Barr, C. S., T. K. Newman, et al. (2004) Sexual dichotomy of an interaction between early adversity and the serotonin transporter gene promoter variant in rhesus macaques. Proc. Natl. Acad. Sci. USA 101(33):12358–12363. Bauer, E. P., Schafe, G.E., et al. (2002) NMDA receptors and L-type voltage-gated calcium channels contribute to long-term potentiation and different components of fear memory formation in the lateral amygdala. J. Neurosci. 22(12):5239–5249. Beekman, M., Flachskamm, C., et al. (2005) Effects of exposure to a predator on behaviour and serotonergic neurotransmission in different brain regions of C57bl/6N mice. Eur. J. Neurosci. 21(10): 2825–2836. Bethea, C.L., Streicher, J.M., et al. (2004) Anxious behavior and fenfluramine-induced prolactin secretion in young rhesus macaques with different alleles of the serotonin reuptake transporter polymorphism (5HTTLPR). Behav. Genet. 34(3):295–307. Blanchard, D.C., Griebel, G., et al. (2003) Conditioning and residual emotionality effects of predator stimuli: some reflections on stress and emotion. Prog. Neuropsychopharmacol. Biol. Psychiatry 27(8):1177–1185. Blanchard, R.J., Blanchard, D.C., et al. (1970) Hippocampal lesions in rats and their effect on activity, avoidance, and aggression. J. Comp. Physiol. Psychol. 71(1):92–101. Bliss, T.V., and Lomo, T. (1973) Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. J. Physiol. 232(2): 331–356. Bouret, S., Duvel, A., et al. (2003) Phasic activation of locus ceruleus neurons by the central nucleus of the amygdala. J. Neurosci. 23(8):3491–3497. Bourin, M., and Hascoet, M. (2003) The mouse light/dark box test. Eur. J. Pharmacol. 463(1/3):55–65. Bremner, J.D. (2004) Brain imaging in anxiety disorders. Expert Rev. Neurother. 4(2):275–284. Brioni, J.D., and McGaugh, J.L. (1988) Post-training administration of GABAergic antagonists enhances retention of aversively motivated tasks. Psychopharmacology (Berl) 96(4):505–510. Brunet, A., Orr, S.P., Tremblay, J., Robertson, K., Nader, K., Pitman, R.K. (2008) Effect of post-retrieval propranolol on psychophysiologic responding during subsequent script-driven traumatic imagery in post-traumatic stress disorder. J. Psychiatry Res. 42(6): 503–506. Burghardt, N.S., Sullivan, G.M., et al. (2004) The selective serotonin reuptake inhibitor citalopram increases fear after acute treatment but reduces fear with chronic treatment: a comparison with tianeptine. Biol. Psychiatry 55(12):1171–1178. Bush, D.E.A., Sotres-Bayon, F., et al. (2007) Individual differences in fear: isolating fear reactivity and fear recovery phenotypes. J. Trauma Stress 20(4):413–422. Cannistraro, P.A., and Rauch, S.L. (2003) Neural circuitry of anxiety: evidence from structural and functional neuroimaging studies. Psychopharmacol. Bull. 37(4):8–25. Cardinal, R.N., Parkinson, J.A., et al. (2002) Effects of selective excitotoxic lesions of the nucleus accumbens core, anterior cingulate cortex, and central nucleus of the amygdala on autoshaping performance in rats. Behav. Neurosci. 116(4):553–567. Cassell, M.D., Freedman, L.J., et al. (1999) The intrinsic organization of the central extended amygdala. Ann. N. Y. Acad. Sci. 877:217–241. Castellano, C., and McGaugh, J.L. (1990) Effects of post-training bicuculline and muscimol on retention: lack of state dependency. Behav. Neural Biol. 54(2):156–164. Chalmers, D.T., Lovenberg, T.W., et al. (1995) Localization of novel corticotropin-releasing factor receptor (CRF2) mRNA expression to specific subcortical nuclei in rat brain: comparison with

CRF1 receptor mRNA expression. J. Neurosci. 15(10):6340– 6350. Champoux, M., Bennett, A., et al. (2002) Serotonin transporter gene polymorphism, differential early rearing, and behavior in rhesus monkey neonates. Mol. Psychiatry 7(10):1058–1063. Charney, D.S. (2004) Psychobiological mechanisms of resilience and vulnerability: implications for successful adaptation to extreme stress. Am. J. Psychiatry 161(2):195–216. Cheeta, S., Kenny, P.J., et al. (2000) Hippocampal and septal injections of nicotine and 8-OH-DPAT distinguish among different animal tests of anxiety. Prog. Neuropsychopharmacol. Biol. Psychiatry 24(7):1053–1067. Choi, S.H., Kim, S.J., et al. (2005) Doxapram increases corticotropin-releasing factor immunoreactivity and mRNA expression in the rat central nucleus of the amygdala. Peptides 26(11):2246– 2251. Cohen, H., and Zohar, J. (2004) An animal model of posttraumatic stress disorder: the use of cut-off behavioral criteria. Ann. N. Y. Acad. Sci. 1032:167–178. Cohen, H., Zohar, J., et al. (2004) Setting apart the affected: the use of behavioral criteria in animal models of post traumatic stress disorder. Neuropsychopharmacology 29(11):1962–1970. Cohen, H., Zohar, J., et al. (2006) Blunted HPA axis response to stress influences susceptibility to posttraumatic stress response in rats. Biol. Psychiatry 59(12):1208–1218. Cohen, H., Kaplan, Z., et al. (1999) CCK-antagonists in a rat exposed to acute stress: implication for anxiety associated with posttraumatic stress disorder. Depress. Anxiety 10(1):8–17. Coplan, J.D., Rosenblum, L.A., et al. (1992) Behavioral effects of oral yohimbine in differentially reared nonhuman primates. Neuropsychopharmacology 6(1):31–37. Coplan, J.D., Smith, E.L., et al. (2001) Variable foraging demand rearing: sustained elevations in cisternal cerebrospinal fluid corticotropin-releasing factor concentrations in adult primates. Biol. Psychiatry 50(3):200–204. Coplan, J.D., Trost, R.C., et al. (1998) Cerebrospinal fluid concentrations of somatostatin and biogenic amines in grown primates reared by mothers exposed to manipulated foraging conditions. Arch. Gen. Psychiatry 55(5):473–477. Cornwell, B.R., Johnson, L., et al. (2006) Anticipation of public speaking in virtual reality reveals a relationship between trait social anxiety and startle reactivity. Biol. Psychiatry 59(7):664–666. Costall, B., Jones, B.J., et al. (1989) Exploration of mice in a black and white test box: validation as a model of anxiety. Pharmacol. Biochem. Behav. 32(3):777–785. Cunningham, C.L., Gremel, C.M., et al. (2006) Drug-induced conditioned place preference and aversion in mice. Nat. Protoc. 1(4): 1662–1670. Datta, A., and Tipton, M. (2006) Respiratory responses to cold water immersion: neural pathways, interactions, and clinical consequences awake and asleep. J. Appl. Physiol. 100(6):2057– 2064. Davidson, J.R., Stein, D.J., et al. (2004) Posttraumatic stress disorder: acquisition, recognition, course, and treatment. J. Neuropsychiatry Clin. Neurosci. 16(2):135–147. Davis, M. (1992) The role of the amygdala in fear and anxiety. Annu. Rev. Neurosci. 15:353–375. Davis, M. (2006) Neural systems involved in fear and anxiety measured with fear-potentiated startle. Am. Psychol. 61(8):741–756. Davis, M., Falls, W.A., et al. (1993) Fear-potentiated startle: a neural and pharmacological analysis. Behav. Brain Res. 58(1/2):175–198. Davis, M., Ressler, K., et al. (2006) Effects of D-cycloserine on extinction: translation from preclinical to clinical work. Biol. Psychiatry 60(4):369–375. Davis, M., Walker, D.L., et al. (1997) Roles of the amygdala and bed nucleus of the stria terminalis in fear and anxiety measured with the acoustic startle reflex. Possible relevance to PTSD. Ann. N. Y. Acad. Sci. 821:305–331.

39: NEUROBIOLOGY OF FEAR AND ANXIETY de la Mora, M.P., Cardenas-Cachon, L., et al. (2005) Anxiolytic effects of intra-amygdaloid injection of the D1 antagonist SCH 23390 in the rat. Neurosci. Lett. 377(2):101–105. De Souza, E.B., Insel, T.R., et al. (1985) Corticotropin-releasing factor receptors are widely distributed within the rat central nervous system: an autoradiographic study. J. Neurosci. 5(12):3189–3203. Debiec, J., and LeDoux, J.E. (2004) Disruption of reconsolidation but not consolidation of auditory fear conditioning by noradrenergic blockade in the amygdala. Neuroscience 129(2):267–272. Decker, M.W., Curzon, P., et al. (1995) Influence of separate and combined septal and amygdala lesions on memory, acoustic startle, anxiety, and locomotor activity in rats. Neurobiol. Learn. Mem. 64(2):156–168. Degroot, A., Kashluba, S., et al. (2001) Septal GABAergic and hippocampal cholinergic systems modulate anxiety in the plus-maze and shock-probe tests. Pharmacol. Biochem. Behav. 69(3-4):391– 399. Degroot, A., and Treit, D. (2002) Dorsal and ventral hippocampal cholinergic systems modulate anxiety in the plus-maze and shockprobe tests. Brain Res. 949(1-2):60–70. Diamond, D.M., Campbell, A.M., et al. (2006) Influence of predator stress on the consolidation versus retrieval of long-term spatial memory and hippocampal spinogenesis. Hippocampus 16(7): 571–576. Dieterich, K.D., Lehnert. H., et al. (1997) Corticotropin-releasing factor receptors: an overview. Exp. Clin. Endocrinol. Diabetes 105(2):65–82. Dityatev, A.E., and Bolshakov, V.Y. (2005) Amygdala, long-term potentiation, and fear conditioning. Neuroscientist 11(1):75–88. Driscoll, P., Escorihuela, R.M., et al. (1998) Genetic selection and differential stress responses. The Roman lines/strains of rats. Ann. N. Y. Acad. Sci. 851:501–510. Escorihuela, R.M., Fernandez-Teruel, A., et al. (1997) Labyrinth exploration, emotional reactivity, and conditioned fear in young Roman/Verh inbred rats. Behav. Genet. 27(6):573–578. Escorihuela, R.M., Fernandez-Teruel, A., et al. (1999) Inbred Roman high- and low-avoidance rats: differences in anxiety, noveltyseeking, and shuttlebox behaviors. Physiol. Behav. 67(1):19–26. Faber, E.S., Delaney, A.J., et al. (2005) SK channels regulate excitatory synaptic transmission and plasticity in the lateral amygdala. Nat. Neurosci. 8(5):635–641. Fanselow, M.S. (1994) Neural organization of the defensive behavior system responsible for fear. Psychonom. Bull. Rev. 1:429–438. Fanselow, M.S. (2000) Contextual fear, gestalt memories, and the hippocampus. Behav. Brain Res. 110(1-2):73–81. Fanselow, M.S., and LeDoux, J.E. (1999) Why we think plasticity underlying Pavlovian fear conditioning occurs in the basolateral amygdala. Neuron 23(2):229–232. Fendt, M., and Schmid, S. (2002) Metabotropic glutamate receptors are involved in amygdaloid plasticity. Eur. J. Neurosci. 15(9): 1535–1541. Fendt, M., Siegl, S., et al. (2005) Noradrenaline transmission within the ventral bed nucleus of the stria terminalis is critical for fear behavior induced by trimethylthiazoline, a component of fox odor. J. Neurosci. 25(25):5998–6004. Ferre, P., Fernandez-Teruel, A., et al. (1995) Behavior of the Roman/ Verh high- and low-avoidance rat lines in anxiety tests: relationship with defecation and self-grooming. Physiol. Behav. 58(6): 1209–1213. Ferry, B., Roozendaal, B., et al. (1999) Role of norepinephrine in mediating stress hormone regulation of long-term memory storage: a critical involvement of the amygdala. Biol. Psychiatry 46(9): 1140–1152. File, S.E., and Seth, P. (2003) A review of 25 years of the social interaction test. Eur. J. Pharmacol. 463(1/3):35–53. File, S.E., and Wardill, A.G. (1975) Validity of head-dipping as a measure of exploration in a modified hole-board. Psychopharmacologia 44(1):53–59.

621

Finn, D.A., Rutledge-Gorman, M.T., et al. (2003) Genetic animal models of anxiety. Neurogenetics 4(3):109–135. Francis, D.D., Caldji, C., et al. (1999) The role of corticotropin-releasing factor--norepinephrine systems in mediating the effects of early experience on the development of behavioral and endocrine responses to stress. Biol. Psychiatry 46(9):1153–1166. Francis, D.D., and Meaney, M.J. (1999) Maternal care and the development of stress responses. Curr. Opin. Neurobiol. 9(1): 128–134. Frankland, P.W., Cestari, V., et al. (1998) The dorsal hippocampus is essential for context discrimination but not for contextual conditioning. Behav. Neurosci. 112(4):863–874. Gewirtz, J.C., and Davis, M. (2000) Using pavlovian higher-order conditioning paradigms to investigate the neural substrates of emotional learning and memory. Learn. Mem. 7(5):257–266. Gonzalez, L.E., Andrews, N., et al. (1996) 5-HT1A and benzodiazepine receptors in the basolateral amygdala modulate anxiety in the social interaction test, but not in the elevated plus-maze. Brain Res. 732(1/2):145–153. Graeff, F.G., Silveira, M.C., et al. (1993) Role of the amygdala and periaqueductal gray in anxiety and panic. Behav. Brain Res. 58 (1-2):123–131. Graham, Y.P., Heim, C., et al. (1999) The effects of neonatal stress on brain development: implications for psychopathology. Dev. Psychopathol. 11(3):545–565. Gray, J.A. (1983) A theory of anxiety: the role of the limbic system. Encephale. 9(4 Suppl 2):161B–166B. Gray, T.S., and Bingaman, E.W. (1996) The amygdala: corticotropinreleasing factor, steroids, and stress. Crit. Rev. Neurobiol. 10(2): 155–168. Griebel, G., Belzung, C., et al. (1993) The free-exploratory paradigm: an effective method for measuring neophobic behaviour in mice and testing potential neophobia-reducing drugs. Behav. Pharmacol. 4(6):637–644. Gross, C., and Hen, R. (2004) The developmental origins of anxiety. Nat. Rev. Neurosci. 5(7):545–552. Hall, C.S. (1934) Emotional behavior in the rat. I. Defecation and urination as measures of individual differences in emotionality. J. Comp. Psychology 18(3):385–403. Heim, C., Owens, M.J., et al. (1997) Persistent changes in corticotropin-releasing factor systems due to early life stress: relationship to the pathophysiology of major depression and post-traumatic stress disorder. Psychopharmacol. Bull. 33(2):185–192. Heim, C., Plotsky, P.M., et al. (2004) Importance of studying the contributions of early adverse experience to neurobiological findings in depression. Neuropsychopharmacology 29(4):641–648. Heinrichs, S.C., Lapsansky, J., et al. (1997) Corticotropin-releasing factor CRF1, but not CRF2, receptors mediate anxiogenic-like behavior. Regul. Pept. 71(1):15–21. Heisler, L.K., Chu, H.M., et al. (1998) Elevated anxiety and antidepressant-like responses in serotonin 5-HT1A receptor mutant mice. Proc. Natl. Acad. Sci. USA 95(25):15049–15054. Heldt, S.A., and Ressler, K.J. (2006) Localized injections of midazolam into the amygdala and hippocampus induce differential changes in anxiolytic-like motor activity in mice. Behav. Pharmacol. 17(4):349–356. Helfer, V., Deransart, C., et al. (1996) Amygdala kindling in the rat: anxiogenic-like consequences. Neuroscience 73(4):971–978. Henry, B., Vale, W., et al. (2006) The effect of lateral septum corticotropin-releasing factor receptor 2 activation on anxiety is modulated by stress. J. Neurosci. 26(36):9142–9152. Herman, J.P., Ostrander, M.M., et al. (2005) Limbic system mechanisms of stress regulation: hypothalamo-pituitary-adrenocortical axis. Prog. Neuropsychopharmacol. Biol. Psychiatry 29(8): 1201–1213. Hidalgo, R.B., and Davidson, J.R. (2000) Posttraumatic stress disorder: epidemiology and health-related considerations. J. Clin. Psychiatry 61(Suppl 7):5–13.

622

ANXIETY DISORDERS

Hoehn-Saric, R., McLeod, D.R., et al. (1991) Psychophysiological response patterns in panic disorder. Acta Psychiatr. Scand. 83(1):4–11. Hofer, M.A. (1996) Multiple regulators of ultrasonic vocalization in the infant rat. Psychoneuroendocrinology 21(2):203–217. Huang, Y.Y., and Kandel, E.R. (1998) Postsynaptic induction and PKA-dependent expression of LTP in the lateral amygdala. Neuron 21(1):169–178. Huang, Y.Y., Martin, K.C., et al. (2000) Both protein kinase A and mitogen-activated protein kinase are required in the amygdala for the macromolecular synthesis-dependent late phase of longterm potentiation. J. Neurosci. 20(17):6317–6325. Huang, Y.Y., Nguyen, P.V., et al. (1996) Long-lasting forms of synaptic potentiation in the mammalian hippocampus. Learn. Mem. 3(2/3):74–85. Huot, R.L., Thrivikraman, K.V., et al. (2001) Development of adult ethanol preference and anxiety as a consequence of neonatal maternal separation in Long Evans rats and reversal with antidepressant treatment. Psychopharmacology (Berl) 158(4):366–373. Imanaka, A., Morinobu, S., et al. (2006) Importance of early environment in the development of post-traumatic stress disorderlike behaviors. Behav. Brain Res. 173(1):129–137. Iversen, S.D. (1980) Animal models of anxiety and benzodiazepine actions. Arzneimittelforschung 30(5a):862–868. James, W. (1884) What is an emotion? Mind 9:188–205. Kalin, N.H., Shelton, S.E., et al. (1991) Effects of alprazolam on fear-related behavioral, hormonal, and catecholamine responses in infant rhesus monkeys. Life Sci. 49(26):2031–2044. Kalin, N.H., Shelton, S.E., et al. (2004) The role of the central nucleus of the amygdala in mediating fear and anxiety in the primate. J. Neurosci. 24(24):5506–5515. Kalisch, R., Korenfeld, E., et al. (2006) Context-dependent human extinction memory is mediated by a ventromedial prefrontal and hippocampal network. J. Neurosci. 26(37):9503–9511. Kalueff, A.V., and Tuohimaa, P. (2004) Experimental modeling of anxiety and depression. Acta Neurobiol. Exp. (Wars) 64(4):439– 448. Kapp, B.S., Whalen, P.J., et al. (1992) Amygdaloid contributions to conditioned arousal and sensory information processing. In: Aggleton, J.P., ed. The Amygdala: Neurobiological Aspects of Emotion, Memory, and Mental Dysfunction.. New York: Wiley-Liss, pp. 229–254. Kash, S.F., Tecott, L.H., et al. (1999) Increased anxiety and altered responses to anxiolytics in mice deficient in the 65-kDa isoform of glutamic acid decarboxylase. Proc. Natl. Acad. Sci. USA 96(4): 1698–1703. Kask, A., Rago, L., et al. (1998) Anxiogenic-like effect of the NPY Y1 receptor antagonist BIBP3226 administered into the dorsal periaqueductal gray matter in rats. Regul. Pept. 75-76:255–262. Keim, S.R., and Shekhar, A. (1996) The effects of GABAA receptor blockade in the dorsomedial hypothalamic nucleus on corticotrophin (ACTH) and corticosterone secretion in male rats. Brain Res. 739(1/2):46–51. Killcross, S., Robbins, T.W., et al. (1997) Different types of fear-conditioned behaviour mediated by separate nuclei within amygdala. Nature 388(6640):377–380. Kim, J.J., and Fanselow, M.S. (1992) Modality-specific retrograde amnesia of fear. Science 256(5057):675–677. Kim, J., Lee, S., et al. (2007) Blockade of amygdala metabotropic glutamate receptor subtype 1 impairs fear extinction. Biochem. Biophys. Res. Commun. 355(1):188–193. Kim, M., and Davis, M. (1993) Electrolytic lesions of the amygdala block acquisition and expression of fear-potentiated startle even with extensive training but do not prevent reacquisition. Behav. Neurosci. 107(4):580–595. Klemenhagen, K.C., Gordon, J.A., et al. (2006) Increased fear response to contextual cues in mice lacking the 5-HT1A receptor. Neuropsychopharmacology 31(1):101–111.

Kobayashi, K., and Kobayashi, T. (2001) Genetic evidence for noradrenergic control of long-term memory consolidation. Brain Dev. 23(Suppl 1):S16–S23. Kokare, D.M., Dandekar, M.P., et al. (2005) Interaction between neuropeptide Y and alpha-melanocyte stimulating hormone in amygdala regulates anxiety in rats. Brain Res. 1043(1/2):107– 114. Koob, G.F. (1999) Corticotropin-releasing factor, norepinephrine, and stress. Biol. Psychiatry 46(9):1167–1180. Koob, G.F., and Heinrichs, S.C. (1999) A role for corticotropin releasing factor and urocortin in behavioral responses to stressors. Brain Res. 848(1/2):141–152. Kostowski, W., Plaznik, A., et al. (1989) Intra-hippocampal buspirone in animal models of anxiety. Eur. J. Pharmacol. 168(3):393–396. Kutsukake, N. (2006) The context and quality of social relationships affect vigilence behavior in wild chimpanzees. Ethology 112 (6):581–591. LeDoux, J.E. (1992) Emotion and the amygdala. In: Aggleton, J.P., ed. The Amygdala: Neurobiological Aspects of Emotion, Memory, and Mental Dysfunction. New York: Wiley-Liss, Inc., pp. 339–351. LeDoux, J.E. (1996) The Emotional Brain: the Mysterious Underpinnings of Emotional Life. New York: Simon & Schuster. LeDoux, J.E. (2000) Emotion circuits in the brain. Annu. Rev. Neurosci. 23:155–184. LeDoux, J.E., Farb, C., et al. (1990) Topographic organization of neurons in the acoustic thalamus that project to the amygdala. J. Neurosci. 10(4):1043–1054. LeDoux, J.E., Ruggiero, D.A., et al. (1987) Topographic organization of convergent projections to the thalamus from the inferior colliculus and spinal cord in the rat. J. Comp. Neurol. 264(1): 123–146. LeDoux, J.E., Iwata, J., et al. (1988) Different projections of the central amygdaloid nucleus mediate autonomic and behavioral correlates of conditioned fear. J. Neurosci. 8(7):2517–2529. LeDoux, J.E., Cicchetti, P., et al. (1990) The lateral amygdaloid nucleus: sensory interface of the amygdala in fear conditioning. J. Neurosci. 10(4):1062–1069. Lee, H.J., Berger, S.Y., et al. (2001) Post-training injections of catecholaminergic drugs do not modulate fear conditioning in rats and mice. Neurosci. Lett. 303(2):123–126. Lee, Y., and Davis, M. (1997) Role of the hippocampus, the bed nucleus of the stria terminalis, and the amygdala in the excitatory effect of corticotropin-releasing hormone on the acoustic startle reflex. J. Neurosci. 17(16):6434–6446. Lee, Y.J., Curtis, G.C., et al. (1993) Panic attacks induced by doxapram. Biol. Psychiatry 33(4):295–297. Leonardo, E.D., and Hen, R. (2006) Genetics of affective and anxiety disorders. Annu. Rev. Psychol. 57:117–137. Lesch, K.P., Meyer, J., et al. (1997) The 5-HT transporter gene-linked polymorphic region (5-HTTLPR) in evolutionary perspective: alternative biallelic variation in rhesus monkeys. Rapid communication. J. Neural Transm. 104(11/12):1259–1266. Levine, S. (1994) The ontogeny of the hypothalamic-pituitary-adrenal axis. The influence of maternal factors. Ann. N. Y. Acad. Sci. 746:275–288; discussion 289–293. Liang, K.C., Melia, K.R., et al. (1992) Lesions of the central nucleus of the amygdala, but not the paraventricular nucleus of the hypothalamus, block the excitatory effects of corticotropin-releasing factor on the acoustic startle reflex. J. Neurosci. 12(6):2313– 2320. Liberzon, I., Lopez, J.F., et al. (1999) Differential regulation of hippocampal glucocorticoid receptors mRNA and fast feedback: relevance to post-traumatic stress disorder. J. Neuroendocrinol. 11(1): 11–17. Lister, R.G. (1990) Ethologically-based animal models of anxiety disorders. Pharmacol. Ther. 46(3):321–340.

39: NEUROBIOLOGY OF FEAR AND ANXIETY Liu, I.Y., Lyons, W.E., et al. (2004) Brain-derived neurotrophic factor plays a critical role in contextual fear conditioning. J. Neurosci. 24(36):7958–7963. Low, K., Crestani, F., et al. (2000) Molecular and neuronal substrate for the selective attenuation of anxiety. Science 290(5489):131–134. Lyons, D.M., and Parker, K.J. (2007) Stress inoculation-induced indications of resilience in monkeys. J. Traum. Stress 24(4):423– 433. Manning, B.H. (1998) A lateralized deficit in morphine antinociception after unilateral inactivation of the central amygdala. J. Neurosci. 18(22):9453–9470. Maren, S. (2001) Neurobiology of Pavlovian fear conditioning. Annu. Rev. Neurosci. 24:897–931. Maren, S., and Chang, C.H. (2006) Recent fear is resistant to extinction. Proc. Natl. Acad. Sci. USA 103(47):18020–18025. Maren, S., and Fanselow, M.S. (1996) The amygdala and fear conditioning: has the nut been cracked? Neuron 16(2):237–240. Maren, S., Aharonov, G., et al. (1997) Neurotoxic lesions of the dorsal hippocampus and Pavlovian fear conditioning in rats. Behav. Brain Res. 88(2):261–274. Martins, A.P., Marras, R.A., et al. (2000) Anxiolytic effect of a CRH receptor antagonist in the dorsal periaqueductal gray. Depress. Anxiety 12(2):99–101. Mascagni, F., McDonald, A.J., et al. (1993) Corticoamygdaloid and corticocortical projections of the rat temporal cortex: a Phaseolus vulgaris leucoagglutinin study. Neuroscience 57(3):697–715. Matar, M.A., Cohen, H., et al. (2006) The effect of early poststressor intervention with sertraline on behavioral responses in an animal model of post-traumatic stress disorder. Neuropsychopharmacology 31(12):2610–2618. Matheus, M.G., and Guimaraes, F.S. (1997) Antagonism of nonNMDA receptors in the dorsal periaqueductal grey induces anxiolytic effect in the elevated plus maze. Psychopharmacology (Berl) 132(1):14–18. Mayberg, H.S., Lozano, A.M., et al. (2005) Deep brain stimulation for treatment-resistant depression. Neuron 45(5):651–660. McCown, T.J., Vogel, R.A., et al. (1983) An efficient chronic conflict paradigm: lick suppression by incremental footshock. Pharmacol. Biochem. Behav. 18(2):277–279. McDonald, A.J. (1998) Cortical pathways to the mammalian amygdala. Prog. Neurobiol. 55(3):257–332. McEwen, B.S. (2004) Protection and damage from acute and chronic stress: allostasis and allostatic overload and relevance to the pathophysiology of psychiatric disorders. Ann. N. Y. Acad. Sci. 1032:1–7. McGaugh, J.L. (2004) The amygdala modulates the consolidation of memories of emotionally arousing experiences. Annu. Rev. Neurosci. 27:1–28. McGaugh, J.L. (2006) Make mild moments memorable: add a little arousal. Trends Cogn. Sci. 10(8):345–347. McGaugh, J.L., and Roozendaal, B. (2002) Role of adrenal stress hormones in forming lasting memories in the brain. Curr. Opin. Neurobiol. 12(2):205–210. McKinney, W.T. (2001) Overview of the past contributions of animal models and their changing place in psychiatry. Semin. Clin. Neuropsychiatry 6(1):68–78. McKinney, W.T., Jr., and Bunney, W.E., Jr. (1969) Animal model of depression. I. Review of evidence: implications for research. Arch. Gen. Psychiatry 21(2):240–248. McNaughton, N. (2006) The role of the subiculum within the behavioural inhibition system. Behav. Brain Res. 174(2):232–250. McNaughton, N., and Gray, J.A. (2000) Anxiolytic action on the behavioural inhibition system implies multiple types of arousal contribute to anxiety. J. Affect. Disord. 61(3):161–176. Meaney, M.J., Diorio, J., et al. (1996) Early environmental regulation of forebrain glucocorticoid receptor gene expression: implications for adrenocortical responses to stress. Dev. Neurosci. 18 (1/2):49–72.

623

Meaney, M.J., Diorio, J., et al. (2000) Postnatal handling increases the expression of cAMP-inducible transcription factors in the rat hippocampus: the effects of thyroid hormones and serotonin. J. Neurosci. 20(10):3926–3935. Mechiel Korte, S., and De Boer, S.F. (2003) A robust animal model of state anxiety: fear-potentiated behaviour in the elevated plusmaze. Eur. J. Pharmacol. 463(1/3):163–175. Menzaghi, F., Howard, R.L., et al. (1994) Characterization of a novel and potent corticotropin-releasing factor antagonist in rats. J. Pharmacol. Exp. Ther. 269(2):564–572. Millan, M.J., and Brocco, M. (2003) The Vogel conflict test: procedural aspects, gamma-aminobutyric acid, glutamate and monoamines. Eur. J. Pharmacol. 463(1/3):67–96. Miller, M.M., and McEwen, B.S. (2006) Establishing an agenda for translational research on PTSD. Ann. N. Y. Acad. Sci. 1071:294– 312. Mineka, S., and Cook, M. (1993) Mechanisms involved in the observational conditioning of fear. J. Exp. Psychol. Gen. 122(1): 23–38. Miyamoto, M., Shintani, M., et al. (1985) Lesioning of the rat basal forebrain leads to memory impairments in passive and active avoidance tasks. Brain Res. 328(1):97–104. Moller, C., Wiklund, L., et al. (1997) Decreased experimental anxiety and voluntary ethanol consumption in rats following central but not basolateral amygdala lesions. Brain Res. 760(1-2):94– 101. Moller, C., Sommer, W., et al. (1999) Anxiogenic-like action of galanin after intra-amygdala administration in the rat. Neuropsychopharmacology 21(4):507–512. Morgan, M.A., and LeDoux, J.E. (1995) Differential contribution of dorsal and ventral medial prefrontal cortex to the acquisition and extinction of conditioned fear in rats. Behav. Neurosci. 109 (4):681–688. Morgan, M.A., and LeDoux, J.E. (1999) Contribution of ventrolateral prefrontal cortex to the acquisition and extinction of conditioned fear in rats. Neurobiol. Learn. Mem. 72(3):244–251. Morgan, M.A., Schulkin, J., et al. (2003) Ventral medial prefrontal cortex and emotional perseveration: the memory for prior extinction training. Behav. Brain Res. 146(1/2):121–130. Morgan, M.A., Romanski, L.M., et al. (1993) Extinction of emotional learning: contribution of medial prefrontal cortex. Neurosci. Lett. 163(1):109–113. Moriceau, S., Roth, T.L., et al. (2004) Corticosterone controls the developmental emergence of fear and amygdala function to predator odors in infant rat pups. Int. J. Dev. Neurosci. 22(5/6): 415–422. Morilak, D.A., Barrera, G., et al. (2005) Role of brain norepinephrine in the behavioral response to stress. Prog. Neuropsychopharmacol. Biol. Psychiatry 29(8):1214–1224. Murchison, C.F., Zhang, X.Y., et al. (2004) A distinct role for norepinephrine in memory retrieval. Cell 117(1):131–143. Myers, K.M., Ressler, K.J., et al. (2006) Different mechanisms of fear extinction dependent on length of time since fear acquisition. Learn. Mem. 13(2):216–223. Nader, K., Schafe, G.E., et al. (2000) Fear memories require protein synthesis in the amygdala for reconsolidation after retrieval. Nature 406(6797):722–726. Nader, K., Majidishad, P., et al. (2001) Damage to the lateral and central, but not other, amygdaloid nuclei prevents the acquisition of auditory fear conditioning. Learn. Mem. 8(3):156–163. Nation, J.R., and Matheny, J.L. (1980) Instrumental escape responding after passive avoidance training: support for an incompatible response account of learned helplessness. Am. J. Psychol. 93(2): 299–308. Netto, C.F., and Guimaraes, F.S. (2004) Anxiogenic effect of cholecystokinin in the dorsal periaqueductal gray. Neuropsychopharmacology 29(1):101–107.

624

ANXIETY DISORDERS

Nordby, T., Torras-Garcia, M., et al. (2006) Posttraining epinephrine treatment reduces the need for extensive training. Physiol. Behav. 89(5):718–723. Ohman, A., and Mineka, S. (2001) Fears, phobias, and preparedness: toward an evolved module of fear and fear learning. Psychol. Rev. 108(3):483–522. Olsson, A., and Phelps, E.A. (2004) Learned fear of “unseen” faces after Pavlovian, observational, and instructed fear. Psychol. Sci. 15(12):822–828. Overall, K.L. (1997) Clinical Behavioral Medicine for Small Animals. St. Louis, MO: Mosby, Inc. Overall, K.L. (2000) Natural animal models of human psychiatric conditions: assessment of mechanism and validity. Prog. Neuropsychopharmacol. Biol. Psychiatry 24(5):727–776. Packard, M.G., and Teather, L.A. (1998) Amygdala modulation of multiple memory systems: hippocampus and caudate-putamen. Neurobiol. Learn. Mem. 69(2):163–203. Pape, H.C., Narayanan, R.T., et al. (2005) Theta activity in neurons and networks of the amygdala related to long-term fear memory. Hippocampus 15(7):874–880. Pare, D., Quirk, G.J., et al. (2004) New vistas on amygdala networks in conditioned fear. J. Neurophysiol. 92(1):1–9. Pare, D., Smith, Y., et al. (1995) Intra-amygdaloid projections of the basolateral and basomedial nuclei in the cat: Phaseolus vulgarisleucoagglutinin anterograde tracing at the light and electron microscopic level. Neuroscience 69(2):567–583. Parker, K.J., Buckmaster, C.L., et al. (2004) Prospective investigation of stress inoculation in young monkeys. Arch. Gen. Psychiatry 61(9):933–941. Parks, C.L., Robinson, P.S., et al. (1998) Increased anxiety of mice lacking the serotonin1A receptor. Proc. Natl. Acad. Sci. USA 95 (18):10734–10739. Paterson, A., Whiting, P.J., et al. (2001) Lack of consistent behavioural effects of Maudsley reactive and non-reactive rats in a number of animal tests of anxiety and activity. Psychopharmacology (Berl) 154(4):336–342. Pavlov, I.P., and Anrep, G.V. (1927) Conditioned reflexes; an investigation of the physiological activity of the cerebral cortex. London: Oxford University Press: Humphrey Milford. Pearson, K.A., Stephen, A., et al. (2006) Identifying genes in monoamine nuclei that may determine stress vulnerability and depressive behavior in Wistar-Kyoto rats. Neuropsychopharmacology 31(11):2449–2461. Pellow, S., and File, S.E. (1986) Anxiolytic and anxiogenic drug effects on exploratory activity in an elevated plus-maze: a novel test of anxiety in the rat. Pharmacol. Biochem. Behav. 24(3):525–529. Perrin, M.H., Donaldson, C.J., et al. (1993) Cloning and functional expression of a rat brain corticotropin releasing factor (CRF) receptor. Endocrinology 133(6):3058–3061. Pesold, C., and Treit, D. (1992) Excitotoxic lesions of the septum produce anxiolytic effects in the elevated plus-maze and the shockprobe burying tests. Physiol. Behav. 52(1):37–47. Pezze, M.A., and Feldon, J. (2004) Mesolimbic dopaminergic pathways in fear conditioning. Prog. Neurobiol. 74(5):301–320. Phelps, E.A. (2004) Human emotion and memory: interactions of the amygdala and hippocampal complex. Curr. Opin. Neurobiol. 14(2):198–202. Phelps, E.A. (2006) Emotion and cognition: insights from studies of the human amygdala. Annu. Rev. Psychol. 57:27–53. Phelps, E.A., and LeDoux, J.E. (2005) Contributions of the amygdala to emotion processing: from animal models to human behavior. Neuron 48(2):175–187. Phelps, E.A., O’Connor, K.J., et al. (2001) Activation of the left amygdala to a cognitive representation of fear. Nat. Neurosci. 4(4): 437–441. Phillips, R.G., and LeDoux, J.E. (1992) Differential contribution of amygdala and hippocampus to cued and contextual fear conditioning. Behav. Neurosci. 106(2):274–285.

Pisula, W., and Osinski, J.T. (2000) A comparative study of the behavioral patterns of RLA/Verh and RHA/Verh rats in the exploration box. Behav. Genet. 30(5):375–384. Pitkänen, A., Savander, V., et al. (1997) Organization of intraamygdaloid circuitries: an emerging framework for understanding functions of the amygdala. Trends Neurosci. 20(11):517–523. Pitman, R.K., and Delahanty, D.L. (2005) Conceptually driven pharmacologic approaches to acute trauma. CNS Spectr. 10(2):99– 106. Plotsky, P.M., Thrivikraman, K.V., et al. (2005) Long-term consequences of neonatal rearing on central corticotropin-releasing factor systems in adult male rat offspring. Neuropsychopharmacology 30(12):2192–2204. Protopopescu, X., Pan, H., et al. (2005) Differential time courses and specificity of amygdala activity in posttraumatic stress disorder subjects and normal control subjects. Biol. Psychiatry 57(5): 464–473. Prut, L., and Belzung, C. (2003) The open field as a paradigm to measure the effects of drugs on anxiety-like behaviors: a review. Eur. J. Pharmacol. 463(1/3):3–33. Quirarte, G.L., Roozendaal, B., et al. (1997) Glucocorticoid enhancement of memory storage involves noradrenergic activation in the basolateral amygdala. Proc. Natl. Acad. Sci. USA 94(25):14048– 14053. Quirk, G.J., and Beer, J.S. (2006) Prefrontal involvement in the regulation of emotion: convergence of rat and human studies. Curr. Opin. Neurobiol. 16(6):723–727. Quirk, G.J., Russo, G.K., et al. (2000) The role of ventromedial prefrontal cortex in the recovery of extinguished fear. J. Neurosci. 20(16):6225–6231. Rainnie, D.G., Fernhout, B.J., et al. (1992) Differential actions of corticotropin releasing factor on basolateral and central amygdaloid neurones, in vitro. J. Pharmacol. Exp. Ther. 263(2):846–858. Rainnie, D.G., Bergeron, R., et al. (2004) Corticotrophin releasing factor-induced synaptic plasticity in the amygdala translates stress into emotional disorders. J. Neurosci. 24(14):3471–3479. Ramboz, S., Oosting, R., et al. (1998) Serotonin receptor 1A knockout: an animal model of anxiety-related disorder. Proc. Natl. Acad. Sci. USA 95(24):14476–14481. Rau, V., DeCola, J.P., et al. (2005) Stress-induced enhancement of fear learning: an animal model of posttraumatic stress disorder. Neurosci. Biobehav. Rev. 29(8):1207–1223. Rauch, S.L., Shin, L.M., et al. (2006) Neurocircuitry models of posttraumatic stress disorder and extinction: human neuroimaging research--past, present, and future. Biol. Psychiatry 60(4):376– 382. Repa, J.C., Muller, J., et al. (2001) Two different lateral amygdala cell populations contribute to the initiation and storage of memory. Nat. Neurosci. 4(7):724–731. Ressler, K.J., Rothbaum, B.O., et al. (2004) Cognitive enhancers as adjuncts to psychotherapy: use of D-cycloserine in phobic individuals to facilitate extinction of fear. Arch. Gen. Psychiatry 61(11): 1136–1144. Richter-Levin, G. (1998) Acute and long-term behavioral correlates of underwater trauma—potential relevance to stress and poststress syndromes. Psychiatry Res. 79(1):73–83. Rittenhouse, P.A., Bakkum, E.A., et al. (1992) Comparison of neuroendocrine and behavioral effects of ipsapirone, a 5-HT1A agonist, in three stress paradigms: immobilization, forced swim and conditioned fear. Brain Res. 580(1/2):205–214. Rodrigues, S.M., Bauer, E.P., et al. (2002) The group I metabotropic glutamate receptor mGluR5 is required for fear memory formation and long-term potentiation in the lateral amygdala. J. Neurosci. 22(12):5219–5229. Rodrigues, S.M., Schafe, G.E., et al. (2001) Intra-amygdala blockade of the NR2B subunit of the NMDA receptor disrupts the acquisition but not the expression of fear conditioning. J. Neurosci. 21(17):6889–6896.

39: NEUROBIOLOGY OF FEAR AND ANXIETY Rodrigues, S.M., Schafe, G.E., et al. (2004) Molecular mechanisms underlying emotional learning and memory in the lateral amygdala. Neuron 44(1):75–91. Rogan, M.T., Staubli, U.V., et al. (1997) Fear conditioning induces associative long-term potentiation in the amygdala. Nature 390 (6660):604–607. Romanski, L.M., Clugnet, M.C., et al. (1993) Somatosensory and auditory convergence in the lateral nucleus of the amygdala. Behav. Neurosci. 107(3):444–450. Rominger, D.H., Rominger, C.M., et al. (1998) Characterization of [125I]sauvagine binding to CRH2 receptors: membrane homogenate and autoradiographic studies. J. Pharmacol. Exp. Ther. 286 (1):459–468. Roozendaal, B., and McGaugh, J.L. (1997) Basolateral amygdala lesions block the memory-enhancing effect of glucocorticoid administration in the dorsal hippocampus of rats. Eur. J. Neurosci. 9(1):76–83. Roozendaal, B., Nguyen, B.T., et al. (1999) Basolateral amygdala noradrenergic influence enables enhancement of memory consolidation induced by hippocampal glucocorticoid receptor activation. Proc. Natl. Acad. Sci. USA 96(20):11642–11647. Roozendaal, B., Brunson, K.L., et al. (2002) Involvement of stressreleased corticotropin-releasing hormone in the basolateral amygdala in regulating memory consolidation. Proc. Natl. Acad. Sci. USA 99(21):13908–13913. Rosen, J.B., and Schulkin, J. (1998) From normal fear to pathological anxiety. Psychol. Rev. 105(2):325–350. Rosen, J.B., Hamerman, E., et al. (1996) Hyperexcitability: exaggerated fear-potentiated startle produced by partial amygdala kindling. Behav. Neurosci. 110(1):43–50. Rosenblum, L.A., and Andrews, M.W. (1994) Influences of environmental demand on maternal behavior and infant development. Acta Paediatr. (Suppl 397):57–63. Rosenblum, L.A., and Paully, G.S. (1984) The effects of varying environmental demands on maternal and infant behavior. Child Dev. 55(1):305–314. Roth, W.T. (2005) Physiological markers for anxiety: panic disorder and phobias. Int. J. Psychophysiol. 58(2/3):190–198. Sajdyk, T.J., and Shekhar, A. (1997) Excitatory amino acid receptor antagonists block the cardiovascular and anxiety responses elicited by gamma-aminobutyric acidA receptor blockade in the basolateral amygdala of rats. J. Pharmacol. Exp. Ther. 283(2):969– 977. Sajdyk, T.J., Schober, D.A., et al. (1999) Role of corticotropinreleasing factor and urocortin within the basolateral amygdala of rats in anxiety and panic responses. Behav. Brain Res. 100(1/2): 207–215. Samson, R.D., and Pare, D. (2005) Activity-dependent synaptic plasticity in the central nucleus of the amygdala. J. Neurosci. 25(7):1847–1855. Sanders, S.K., Morzorati, S.L., et al. (1995) Priming of experimental anxiety by repeated subthreshold GABA blockade in the rat amygdala. Brain Res. 699(2):250–259. Sarter, M., and Bruno, J.P. (2002) Animal models in biological psychiatry. In: D’haenen, H., den Boer, J.A., and Willner, P., eds. Biological Psychiatry. New York: John Wiley & Sons Ltd., pp. 1–8. Schafe, G.E., Atkins, C.M., et al. (2000) Activation of ERK/MAP kinase in the amygdala is required for memory consolidation of Pavlovian fear conditioning. J. Neurosci. 20(21):8177–8187. Schafe, G.E., and LeDoux, J.E. (2000) Memory consolidation of auditory Pavlovian fear conditioning requires protein synthesis and protein kinase A in the amygdala. J. Neurosci. 20(18):RC96. Schafe, G.E., Nadel, N.V., et al. (1999) Memory consolidation for contextual and auditory fear conditioning is dependent on protein synthesis, PKA, and MAP kinase. Learn. Mem. 6(2):97–110. Schafe, G.E., Nader, K., et al. (2001) Memory consolidation of Pavlovian fear conditioning: a cellular and molecular perspective. Trends Neurosci. 24(9):540–546.

625

Selye, H. (1950) The Physiology and Pathology of Exposure to Stress. Montreal, Canada: Acta, Inc. Servatius, R.J., Ottenweller, J.E., et al. (1995) Delayed startle sensitization distinguishes rats exposed to one or three stress sessions: further evidence toward an animal model of PTSD. Biol. Psychiatry 38(8):539–546. Shah, A.A., and Treit, D. (2004) Infusions of midazolam into the medial prefrontal cortex produce anxiolytic effects in the elevated plus-maze and shock-probe burying tests. Brain Res. 996 (1):31–40. Shanks, N., Larocque, S., et al. (1995) Neonatal endotoxin exposure alters the development of the hypothalamic-pituitary-adrenal axis: early illness and later responsivity to stress. J. Neurosci. 15(1 Pt 1): 376–384. Shekhar, A., Keim, S.R., et al. (1996) Dorsomedial hypothalamic GABA dysfunction produces physiological arousal following sodium lactate infusions. Pharmacol. Biochem. Behav. 55(2):249–256. Shekhar, A., McCann, U.D., et al. (2001) Summary of a National Institute of Mental Health workshop: developing animal models of anxiety disorders. Psychopharmacology (Berl) 157(4):327–339. Shekhar, A., Truitt, W., et al. (2005) Role of stress, corticotrophin releasing factor (CRF) and amygdala plasticity in chronic anxiety. Stress 8(4):209–219. Shephard, R.A., and Broadhurst, P.L. (1982) Hyponeophagia and arousal in rats: effects of diazepam, 5-methoxy-N,N-dimethyltryptamine, d-amphetamine and food deprivation. Psychopharmacology (Berl) 78(4):368–372. Shin, L.M., Wright, C.I., et al. (2005) A functional magnetic resonance imaging study of amygdala and medial prefrontal cortex responses to overtly presented fearful faces in posttraumatic stress disorder. Arch. Gen. Psychiatry 62(3):273–281. Sibille, E., and Hen, R. (2001) Combining genetic and genomic approaches to study mood disorders. Eur. Neuropsychopharmacol. 11(6):413–421. Sigurdsson, T., Doyere, V., et al. (2007) Long-term potentiation in the amygdala: a cellular mechanism of fear learning and memory. Neuropharmacology 52(1):215–227. Smagin, G.N., Harris, R.B., et al. (1996) Corticotropin-releasing factor receptor antagonist infused into the locus coeruleus attenuates immobilization stress-induced defensive withdrawal in rats. Neurosci. Lett. 220(3):167–170. Sotres-Bayon, F., Bush, D.E.A. et al. (2007) Acquisition of fear extinction requires activation of NR2B-containing NMDA receptors in the lateral amygdala. Neuropsychopharmacology 32(9): 1929–1940. Sotres-Bayon, F., Bush, D.E.A., et al. (2004) Emotional perseveration: an update on prefrontal-amygdala interactions in fear extinction. Learn. Mem. 11(5):525–535. Spielberger, C.D., Gorsuch, R.C., et al. (1970) Manual for the Stait Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press. Steimer, T., and Driscoll, P. (2003) Divergent stress responses and coping styles in psychogenetically selected Roman high-(RHA) and low-(RLA) avoidance rats: behavioural, neuroendocrine and developmental aspects. Stress 6(2):87–100. Stein, M.B., Goldin, P.R., et al. (2002) Increased amygdala activation to angry and contemptuous faces in generalized social phobia. Arch. Gen. Psychiatry 59(11):1027–1034. Straube, T., Mentzel, H.J., et al. (2005) Common and distinct brain activation to threat and safety signals in social phobia. Neuropsychobiology 52(3):163–168. Stutzmann, G.E., and LeDoux, J.E. (1999) GABAergic antagonists block the inhibitory effects of serotonin in the lateral amygdala: a mechanism for modulation of sensory inputs related to fear conditioning. J. Neurosci. 19(11):RC8. Stutzmann, G.E., McEwen, B.S., et al. (1998) Serotonin modulation of sensory inputs to the lateral amygdala: dependency on corticosterone. J. Neurosci. 18(22):9529–9538.

626

ANXIETY DISORDERS

Sullivan, G.M., Apergis, J., et al. (2003) Rodent doxapram model of panic: behavioral effects and c-Fos immunoreactivity in the amygdala. Biol. Psychiatry 53(10):863–870. Sullivan, G.M., Apergis, J., et al. (2004) Lesions in the bed nucleus of the stria terminalis disrupt corticosterone and freezing responses elicited by a contextual but not by a specific cue-conditioned fear stimulus. Neuroscience 128(1):7–14. Sullivan, R.M. (2003) Developing a sense of safety: the neurobiology of neonatal attachment. Ann. N. Y. Acad. Sci. 1008:122– 131. Sullivan, R., Wilson, D.A., et al. (2006) The International Society for Developmental Psychobiology Annual Meeting Symposium: Impact of early life experiences on brain and behavioral development. Dev. Psychobiol. 48(7):583–602. Swiergiel, A.H., Takahashi, L.K., et al. (1992) Antagonism of corticotropin-releasing factor receptors in the locus coeruleus attenuates shock-induced freezing in rats. Brain Res. 587(2):263–268. Takahashi, L.K., Hubbard, D.T., et al. (2007) Predator odor-induced conditioned fear involves the basolateral and medial amygdala. Behav. Neurosci. 121(1):100–110. Takahashi, T., Morinobu, S., et al. (2006) Effect of paroxetine on enhanced contextual fear induced by single prolonged stress in rats. Psychopharmacology (Berl) 189(2):165–173. Tecott, L.H. (2000) Designer genes and anti-anxiety drugs. Nat. Neurosci. 3(6):529–530. Tecott, L.H., Logue, S.F., et al. (1998) Perturbed dentate gyrus function in serotonin 5-HT2C receptor mutant mice. Proc. Natl. Acad. Sci. USA 95(25):15026–15031. Thiebot, M.H., Jobert, A., et al. (1980) Conditioned suppression of behavior: its reversal by intra raphe microinjection of chlordiazepoxide and GABA. Neurosci. Lett. 16(2):213–217. Treit, D., and Menard, J. (1997) Dissociations among the anxiolytic effects of septal, hippocampal, and amygdaloid lesions. Behav. Neurosci. 111(3):653–658. Treit, D., Pinel, J.P., et al. (1981) Conditioned defensive burying: a new paradigm for the study of anxiolytic agents. Pharmacol. Biochem. Behav. 15(4):619–626. Tsoory, M., and Richter-Levin, G. (2006) Learning under stress in the adult rat is differentially affected by “juvenile” or “adolescent” stress. Int. J. Neuropsychopharmacol. 9(6):713–728. Vale, W., Spiess, J., et al. (1981) Characterization of a 41-residue ovine hypothalamic peptide that stimulates secretion of corticotropin and beta-endorphin. Science 213(4514):1394–1397. Van de Kar, L.D., Piechowski, R.A., et al. (1991) Amygdaloid lesions: differential effect on conditioned stress and immobilization-induced increases in corticosterone and renin secretion. Neuroendocrinology 54(2):89–95. Vogel, J.R., Beer, B., et al. (1971) A simple and reliable conflict procedure for testing anti-anxiety agents. Psychopharmacologia 21(1): 1–7. Walker, C.D., Rivest, R.W., et al. (1989) Differential activation of the pituitary-adrenocortical axis after stress in the rat: use of two

genetically selected lines (Roman low- and high-avoidance rats) as a model. J. Endocrinol. 123(3):477–485. Walker, D.L., Toufexis, D.J., et al. (2003) Role of the bed nucleus of the stria terminalis versus the amygdala in fear, stress, and anxiety. Eur. J. Pharmacol. 463(1-3):199–216. Walker, D.L., Ressler, K.J., et al. (2002) Facilitation of conditioned fear extinction by systemic administration or intra-amygdala infusions of D-cycloserine as assessed with fear-potentiated startle in rats. J. Neurosci. 22(6):2343–2351. Wallace, T.L., Stellitano, K.E., et al. (2004) Effects of cyclic adenosine monophosphate response element binding protein overexpression in the basolateral amygdala on behavioral models of depression and anxiety. Biol. Psychiatry 56(3):151–160. Watson, D. (2005) Rethinking the mood and anxiety disorders: a quantitative hierarchical model for DSM-V. J. Abnorm. Psychol. 114(4):522–536. Wehner, J.M., Radcliffe, R.A., et al. (1997) Quantitative trait locus analysis of contextual fear conditioning in mice. Nat. Genet. 17(3): 331–334. Weiss, J.M., and Kilts, C.D. (1998) Animal models of depression and schizophrenia. In: Schatzberg, A.F., and Nemeroff, C.B., eds. Textbook of Psychopharmacology. Washington, DC: American Psychiatric Press, pp. 89–131. Weisskopf, M.G., Bauer, E.P., et al. (1999) L-type voltage-gated calcium channels mediate NMDA-independent associative long-term potentiation at thalamic input synapses to the amygdala. J. Neurosci. 19(23):10512–10519. Whalen, P.J., Kagan, J., et al. (2004) Human amygdala responsivity to masked fearful eye whites. Science 306(5704):2061. Wilensky, A.E., Schafe, G.E., et al. (1999) Functional inactivation of the amygdala before but not after auditory fear conditioning prevents memory formation. J. Neurosci. 19(24):RC48. Wilensky, A.E., Schafe, G.E., et al. (2000) The amygdala modulates memory consolidation of fear-motivated inhibitory avoidance learning but not classical fear conditioning. J. Neurosci. 20(18): 7059–7066. Wilensky, A.E., Schafe, G.E., et al. (2006) Rethinking the fear circuit: the central nucleus of the amygdala is required for the acquisition, consolidation, and expression of Pavlovian fear conditioning. J. Neurosci. 26(48):12387–12396. Willner, P. (1991) Animal models as simulations of depression. Trends Pharmacol. Sci. 12(4):131–136. Yehuda, R. (2004) Risk and resilience in posttraumatic stress disorder. J. Clin. Psychiatry 65(Suppl 1):29–36. Yilmazer-Hanke, D.M., Faber-Zuschratter, H., et al. (2002) Contribution of amygdala neurons containing peptides and calciumbinding proteins to fear-potentiated startle and explorationrelated anxiety in inbred Roman high- and low-avoidance rats. Eur. J. Neurosci. 15(7):1206–1218. Zhang, S., Amstein, T., et al. (2005) Molecular correlates of emotional learning using genetically selected rat lines. Genes Brain Behav. 4(2):99–109.

40 Stress-Induced Structural and Functional Plasticity in the Brain: Protection, Damage, and Brain–Body Communication BRUCE S. M

C

EWEN

There is increasing evidence that the adult brain possesses a remarkable ability to adapt and change with experience. Long regarded as a rather static and unchanging organ, except for electrophysiological responsivity, such as long-term potentiation (LTP) (Bliss and Lomo, 1973), the brain has gradually been recognized as capable of undergoing rewiring after brain damage (Parnavelas et al., 1974) and also able to grow and change in terms of dendritic branching, angiogenesis, and glial cell proliferation during cumulated experience (Greenough and Bailey, 1988). More specific physiological changes in synaptic connectivity have also been recognized in relation to hormone action in the spinal cord (Arnold and Breedlove, 1985), and in environmentally directed plasticity of the adult songbird brain (DeVoogd and Nottebohm, 1981). Seasonally varying neurogenesis of restricted areas of the adult songbird brain is recognized as a part of this plasticity (Rasika et al., 1994; Rasika et al., 1999). Rather than being isolated examples of plasticity in certain species, there are increasing indications that structural change—neuronal replacement, remodeling of dendrites, turnover of synapses—is a feature of the adult brain’s response to what happens to the individual. Nowhere is this better illustrated in the mammalian brain than in the hippocampus, where all three types of structural plasticity have been recently recognized and investigated using a combination of morphological, molecular, pharmacological, electrophysiological, and behavioral approaches. The hippocampal formation is an important brain structure in episodic, declarative, contextual, and spatial learning, as well as a component of the control of a variety of vegetative functions such as adrenocorticotropic hormone (ACTH) secretion (Jacobson and Sapolsky, 1991; Eichenbaum and Otto, 1992; Phillips and LeDoux, 1992). It is also a plastic and vulnerable

brain structure that is damaged by stroke and head trauma and is susceptible to damage during aging and repeated stress (Sapolsky, 1992). In 1968, we showed that hippocampal neurons express receptors for circulating adrenal steroids (McEwen et al., 1968), and subsequent work in many laboratories has shown that the hippocampus has two types of adrenal steroid receptors that mediate a variety of effects on neuronal excitability, neurochemistry, and structural plasticity (De Kloet et al., 1996). Hippocampal neurons also possess receptors for estrogens (Loy et al., 1988; DonCarlos et al., 1991; Weiland, Orikasa, et al., 1997) and androgens (J.E. Kerr et al., 1995) and show plasticity during sexual differentiation and in adult life in responses to gonadal steroids (Gould, Westlind-Danielsson, et al., 1990; Roof, 1993). Recent work has revealed that adrenal and gonadal steroids are involved in four types of plasticity in the hippocampal formation. First, they reversibly and biphasically modulate excitability of hippocampal neurons and influence the magnitude of LTP, as well as producing long-term depression (Pavlides et al., 1994; Pavlides, Kimura, et al., 1995; Pavlides, Watanabe, et al., 1995; Pavlides et al., 1996). These effects may be involved in biphasic effects of adrenal secretion on excitability and cognitive function and memory during the diurnal rhythm and after stress (Barnes et al., 1977; Dana and Martinez, 1984; Diamond et al., 1992; Diamond et al., 1996). Second, adrenal steroids participate along with excitatory amino acids in regulating neurogenesis and neuronal replacement of dentate gyrus granule neurons, in which acute stressful experiences can suppress the ongoing neurogenesis (Cameron and Gould, 1996a). It is likely that these effects may be involved in fear-related learning and memory because of the anatomical connections between the dentate gyrus and the amygdala, a 627

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brain area important in memory of aversive and fearproducing experiences (LeDoux, 1995). Third, ovarian steroids regulated synaptic turnover in the hippocampus by a mechanism involving excitatory amino acids (McEwen et al., 2001; McEwen, Gould, et al., 1995). These effects may underlie the impairment of hippocampaldependent memory functions in women after loss or suppression of ovarian function. Finally, adrenal steroids participate along with excitatory amino acids in stress-induced remodeling of dendrites in the CA3 region of hippocampus, a process that affects only the apical dendrites and results in cognitive impairment in the learning of spatial and shortterm memory tasks (McEwen, 1999). Besides atrophy of neuronal processes, severe and prolonged stress causes neuronal loss (Rozovsky et al., 2002), and the relationship between reversible atrophy and permanent damage is an important issue that is relevant to recent reports that the human hippocampus undergoes shrinkage in Cushing’s syndrome, normal aging, dementia, recurrent depressive illness, schizophrenia, and posttraumatic stress disorder (PTSD). There is also stress-induced remodeling in amygdala and prefrontal cortex (PFC). This chapter summarizes these various types of plasticity and discusses them in the broader context of how the brain responds to environmental demands, including those related to stressful life events. It is likely that the pathophysiological aspects of the adaptation to prolonged stress involves a loss of plasticity and an increased vulnerability to damage. This is discussed in relation to human psychiatric illness, aging, and comorbidities associated with them. ROLE OF THE HIPPOCAMPUS IN BEHAVIORAL AND NEUROENDOCRINE ADAPTATION The hippocampus and amygdala are key limbic brain structures that process experiences by interfacing with lower vegetative brain areas and higher cortical centers, particularly the PFC. They also help to interpret, on the basis of current and past experiences, whether an event is threatening or otherwise stressful and help to determine the behavioral, neuroendocrine, and autonomic responses. The amygdala is an essential neural component in the memory of fearful and emotionally laden events, whereas the hippocampus is concerned with determining the context in which such events take place, as well as other aspects of episodic and declarative memory (Squire and Zola-Morgan, 1991; Eichenbaum and Otto, 1992; Phillips and LeDoux, 1992). Whereas lesions of the central or lateral amygdala will abolish conditioning of the freezing response of an animal to tone paired with shock, a hippocampal lesion has no such effect; on the other hand, the hippocampal lesion will abolish conditioning of the freezing response to the

“context,” that is, to the environment of a particular conditioning chamber (Phillips and LeDoux, 1992). The amygdala and hippocampus are also linked to each other anatomically and functionally (Knigge, 1961; Pitkanen et al., 2000). For example, lesions of the basolateral amygdaloid nucleus reduce LTP in the dentate gyrus, and stimulation of this nucleus facilitates dentate gyrus LTP (Ikegaya et al., 1994, 1995). The hippocampus and amygdala also have a regulatory role in the hypothalamic-pituitary-adrenal (HPA) axis activity, with the hippocampus in general being inhibitory and the amygdala acting as a facilitator of the HPA stress response (Knigge, 1961; McEwen, 1977; Jacobson and Sapolsky, 1991; Herman et al., 1996). However, this statement oversimplifies a great deal of complexity. For example, within the hippocampus, certain sites respond to electrical stimulation by increasing HPA activity (Dunn and Orr, 1984). Moreover, other brain areas are involved: for example, a recent brain lesion and steroid implant study indicates that the medial PFC plays an important role in containing the HPA response to psychological (for example, restraint), but not to ether stress (Diorio et al., 1993). Glucocorticoid implants into the medial PFC reduce the magnitude of the HPA response to stress, as well as reducing plasma insulin levels (Diorio et al., 1993; Akana et al., 2001). These findings point to the important topic of steroid feedback, in general, and sites outside of the hippocampus and hypothalamus in the control of HPA activity. It is important to note that the HPA axis is dynamically regulated, and that steroid feedback operates at several levels in relation to neural control of the turning on and shutting off of the stress response (Akana et al., 1988; Jacobson et al., 1988). Besides rate-sensitive and level-sensitive feedback, delayed feedback may be viewed as a thermostat (steroid elevation turning down ACTH release) and a modulation by neural activity, which can be inhibitory (perhaps via the g-aminobutyric acid [GABA] system), as well as excitatory upon the paraventricular nucleus (PVN), corticotrophin releasing factor (CRF), and arginine vasopressin (AVP) neurons (Herman et al., 1996). The bed nucleus of the stria terminalis is reported to have inhibitory and excitatory pathways to the PVN that regulate limbic system inputs to the HPA axis (Spano et al., 2007). The demonstration that constant steroid feedback via corticosterone (CORT) pellets implanted into rats with an adrenalectomy (ADX rats) normalizes ACTH levels but allows for sustained ACTH secretion after stress highlights the importance of neural control in the shut-off of the HPA stress response (Akana et al., 1988; Jacobson et al., 1988). The fact that in the same study, diurnal exposure to corticosterone (CORT) in the drinking water also normalized ACTH levels in ADX rats but allowed for a more rapid termination of the HPA stress response, even when no steroid was pres-

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ent, further highlights the importance of understanding the role of adrenal steroids in priming neural mechanisms that subserve shut-off of the HPA axis (Akana et al., 1988; Jacobson et al., 1988). A further aspect of feedback regulation of HPA function is the ability of energy sources, such as sucrose, to reduce ACTH secretion independently of adrenal steroids (Laugero et al., 2001). Because of these two interrelated roles of the hippocampus (see Fig. 40.1), a role in aspects of memory and regulation of HPA activity, impairment of hippocampal function through changes in either excitability, reversible plasticity, or permanent damage may be expected to have two effects: The first is to impair hippocampal involvement in episodic, declarative, contextual, and spatial memory; impairments of these functions are likely to debilitate an individual’s ability to process information in new situations and to make decisions about how to deal with new challenges. The second effect is to impair the hippocampal role in regulating HPA activity, particularly the shut-off of the stress response, leading to elevated HPA activity and further exacerbating the actions of adrenal steroids in the long-term effects of repeated stress. This concept, first called the glucocorticoid cascade hypothesis of hippocampal aging (Sapolsky et al., 1986), stands at the center of the notion of “allostasis” and “allostatic load” that are discussed at the conclusion of this chapter. In summary, the amygdala, PFC, and hippocampus are brain structures that play a key role in turning on and shutting off the HPA axis during stress, acting at least in part through the bed nucleus of the stria terminalis and its projections to the paraventricular nuclei where corticotrophin releasing factor (CRF) is produced that drives ACTH secretion. Negative feedback by glucocorticoids is one aspect of a more complex process

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of neurally mediated regulation of HPA axis activity in which adrenal steroids play a regulatory role. ADAPTIVE PLASTICITY OF THE HIPPOCAMPUS The hippocampus expresses receptors for circulating adrenal steroids, as well as gonadal steroids; this remarkable property has made this brain structure a focal point for understanding the central nervous system (CNS) actions of circulating stress and gonadal hormones. As part of the cognitive and the vegetative aspects of the response to stressful events, the hippocampus is itself a very dynamic structure and is capable of changes in neuronal morphology and function that are modulated by circulating adrenal steroids acting through Type I (mineralocorticoid) and Type II (glucocorticoid) receptors (McEwen et al., 1968). Such receptors are expressed together in principal neurons of the Ammon’s horn and dentate gyrus. The hippocampus also has receptors for gonadal steroids, with androgen receptors having been found in CA1 pyramidal neurons (J.E. Kerr et al., 1995) and estrogen receptors (ERs) in scattered interneurons in CA1 and dentate gyrus (Loy et al., 1988; DonCarlos et al., 1991; Weiland, Orikasa, et al., 1997). The hippocampus undergoes sexual differentiation and displays neuroanatomical sex differences as a result of the developmental actions of testosterone (Gould, Westlind-Danielsson, et al., 1990; Roof, 1993). Below, several types of plasticity are summarized, starting with a discussion of rapid plasticity related to excitability changes and then followed by a summary of structural plasticity in which changes in synapse formation, dendritic remodelling, and neuronal turnover are found in the adult hippocampus. Rapid Plasticity of Excitability and Long-Term Potentiation

Cognitive function Episodic and declarative memory Contextual memory Spatial memory pyramidal neuron

CA1

CA3 granule neuron Entorhinal cortex

Dentate gyrus

pyramidal neuron

HPA activity Output via ventral subiculum to the BNST BNST projects to the PVN and regulates CRF neurons

40.1 Hippocampal circuitry showing the two main functions of the hippocampal formation, cognitive function, and influencing hypothalamo-pituitary-adrenal (HPA) activity.

FIGURE

Adrenal steroids modulate the excitability of hippocampal neurons, as illustrated by the phenomenon of LTP (Bliss and Lomo, 1973) (see Fig. 40.2). A single burst of high-frequency stimulation to hippocampal afferents immediately alters the responsiveness of neurons to subsequent acute stimulation, an effect lasting over many hours to days. A number of recent studies have demonstrated in the hippocampal CA1 field and the dentate gyrus that acute stress and acute glucocorticoid elevation produces an impairment in LTP or its close relative, primed-burst potentiation, PBP (Diamond et al., 1992; Pavlides et al., 1993; Diamond et al., 1994). There is a U-shaped dose-response curve, with low levels of CORT facilitating PBP and high levels inhibiting PBP in the CA1 region (Diamond et al., 1992). In the dentate gyrus and CA1 and CA3 fields, LTP can be modulated rapidly (within 1 hour) and biphasically by

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BIPHASIC EFFECTS of ADRENAL STEROIDS on LTP 1) 2) 3)

Involve NMDA-dependent pathways Mossy fiber pathway is non-NMDA Type I receptors facilitate Type II receptors inhibit pyramidal neuron

CA1

CA3 granule neuron Entorhinal cortex

Dentate gyrus

pyramidal neuron

Adrenal steriod effects on excitability - some specific systems affected Type I receptors INHIBIT calcium channel activity, cholinergic excitation, and 5HTIA-mediated inhibition. Type II receptors FACILITATE calcium channel activity, cholinergic excitation, and 5HTIA-mediated inhibition.

40.2 Hippocampal 3-cell circuitry. Adrenal steroids had biphasic effects on long-term potentiation in N-methyl-D-aspartate (NMDA)-dependent pathways. Type I (mineralocorticoid) and Type II (glucocorticoid) receptors have opposite effects on calcium channel activity, cholinergic excitation, and 5HT1A-receptor mediated inhibition.

FIGURE

adrenal steroids acting, respectively, via Type I and Type II receptors (Pavlides, Kimura, et al., 1995; Pavlides, Watanabe, et al., 1995; Pavlides et al., 1996). Moreover, in awake, freely moving ADX rats, the enhancement of LTP by the Type I receptor agonist, aldosterone, lasts for at least 24 hours, at which time it is still markedly higher than ADX rats given only vehicle treatment before LTP induction (Pavlides et al., 1994). Mineralocorticoid receptors (MR or Type I) have an unusual role, namely, that, as determined by genetic deletion of the MR, they are essential for a rapid nongenomic effect of CORT in the mouse hippocampus that increases excitatory postsynaptic potentials (Karst et al., 2005). A similar rapid CORT effect on glutamate levels has been reported for the rat hippocampus, and this action is not blocked by RU-486 and hence does not appear to be mediated by the glucocorticoid receptors (GR or Type II) (Venero and Borrell, 1999). Regarding how these biphasic effects come about, it is very likely that principal neurons in dentate gyrus and Ammon’s horn contain both types of receptors, considering the distribution of messenger ribonucleic acid (mRNA), immunocytochemical reactivity, and binding for Type I and Type II adrenal steroid receptor subtypes (De Kloet et al., 1996). In studies on pyramidal neurons of the CA1 region, adrenal steroids have been shown to act via Type I and Type II adrenal steroid receptors to maintain and modulate excitability of hippocampal neurons (Beck et al., 1994; Joels and De Kloet, 1994; Birnstiel and Beck, 1995). Type I receptor activation in hippocampus from ADX rats is associated with reduced calcium currents through voltage-gated channels, reduced responses to serotonin via 5-HT1A receptors and to carbachol via muscarinic receptors, and

stable responses to synaptic inputs involving excitatory and inhibitory amino acids (Hesen and Joels, 1996a, 1996b). Additional activation of Type II receptors causes increased calcium currents and enhanced responses to excitatory amino acids, serotonin, and carbachol (Joels and De Kloet, 1994; Joels, 1997), and very high levels of Type II receptor activation markedly increase calcium currents (D. Kerr and Campbell, 1992) and also leads to increased N-methyl-D-aspartate (NMDA) receptor expression on hippocampal neurons (Weiland et al., 1995). Acute stress also increases NMDA R1 mRNA but decreases a-amino-3-hydroxy-5-methyl-4-isoxasolepropionic acid (AMPA) receptor subunit A mRNA levels without affecting mRNA levels of subunits B and C (Bartanusz et al., 1995). Kainate receptor mRNA levels were also affected by acute CORT treatment, with lowdose occupancy of Type I receptors increasing mRNA levels for kainate receptor 1 and 2 and also for the GluR7 subunit of the AMPA receptor and high-dose occupancy of Type II, as well as Type I receptors reversing this effect (Joels et al., 1996). Besides these effects, specific Type I and Type II agonists given to ADX rats produce a variety of other effects on various aspects of gene expression in hippocampus associated with neurotransmission (Lupien and McEwen, 1997). Taken together with effects on hippocampal neuronal excitability described in the next section, what is surprising about these nonoverlapping actions of Type I and Type II receptors on gene products in hippocampus is that they defy the classical model of adrenal steroid receptor action via a common glucocorticoid response element (GRE) (Evans and Arriza, 1989) and point to a different and possibly more complex mode of MR and glucocorticoid regulation of gene expression (Miner and Yamamoto, 1991; Reichardt and Schutz, 1998). It should be noted that the regulation of preprotachykinin A gene mRNA levels in rat forebrain regions does follow the predictions of the classic GRE in that Type I and Type II agonist treatments of ADX rats elevate mRNA levels for this neuropeptide (Pompei et al., 1995). However, many other responses to glucocorticoids follow a pattern independent of the GRE because deletion of the deoxyribonucleic acid (DNA) binding domain of the glucocorticoid receptors still allows certain actions of glucocorticoids to occur (Reichardt and Schutz, 1998). The fact that Type I and Type II adrenal steroid receptor activation has been characterized separately in ADX rats using selective agonists raises the question of what happens when both receptors are activated simultaneously over the physiological range of CORT. Under such conditions it is necessary to consider Type I/Type II receptor heterodimers (Trapp et al., 1994), as well as other comodulators of steroid-regulated gene expression such as immediate early genes (see below). This is important because we have noted that hippo-

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campal neurons in Ammon’s horn and dentate gyrus express both types of receptors, and it remains to be seen how different the consequences of combined receptor activation are from the information summarized using selective Type I and Type II receptor agonists and antagonists. Another issue to be resolved is the extent to which pyramidal neurons and granule neurons show similar molecular responses to adrenal steroid actions on excitability. From the standpoint of LTP, the biphasic actions of adrenal steroids in dentate gyrus and Ammon’s horn occur in pathways using NMDA receptors and not in the mossy fiber non-NMDA pathway (Pavlides and McEwen, 1999). The commonality of adrenal steroid effects on NMDA receptor expression, on calcium channel activity, and on the sensitivity to carbachol and to serotonin via 5HT1A receptors is, therefore, an important issue when looking at different hippocampal fields. Behavioral actions can be attributed to Type I (MR) or Type II (GR) activation (Korte, 2001). At low concentrations that occupy Type I receptors, CORT exerts a permissive effect on acute freezing behavior and acute fear-related plus maze behavior. At high circulating levels that occupy Type II as well as Type I receptors, CORT enhances acquisition, conditioning, and consolidation of an inescapable stressful experience. High corticosteroid levels also potentiate fear but at the same time appear to play a role in the extinction of active avoidance. In summary, adrenal steroids play a regulatory role on excitability in the hippocampus by acting through Type I (mineralocorticoid) and Type II (glucocorticoid) receptors that are present in neurons of Ammon’s horn and the dentate gyrus. There are parallel effects on behavior and excitability of neurons that suggest an inverted U-shaped dose-response relationship, with lowto-moderate corticosteroid levels enhancing function and high stress levels having the opposite effect. Type I receptors also determine the ability of glucocorticoids to rapidly enhance excitatory transmission through a nongenomic mechanism. Hormones, Neurotransmitters, and Neuronal Birth and Death in Dentate Gyrus Removal of adrenal steroids Granule neurons of the adult dentate gyrus depend on adrenal steroids for their survival, and adrenalectomy (ADX) of an adult rat increases the rate of granule neuron death (Sloviter et al., 1989; Gould, Woolley, et al., 1990). Three months after ADX, some rats showed an almost total loss of dentate gyrus granule neurons (Sloviter et al., 1989), and this finding at the time conflicted with the prevailing view that adrenal steroids cause neuronal death in Ammon’s horn (see below), and it

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was puzzling because only some ADX rats showed the loss of the entire dentate gyrus. It now appears that a unique property of adult dentate granule neurons, not shared by cerebellar or olfactory bulb granule neurons, is for bilateral ADX to cause apoptotic death within 3– 7 days (Gould, Woolley, et al., 1990). Besides apoptosis, the lack of adrenal steroids leads to a decreased branching of dendrites of dentate gyrus granule cells (Gould, Woolley, et al., 1990; Wossink et al., 2001). The enhanced expression after ADX of the neuropeptide, calcitonin gene-related peptide (CGRP), in the inner molecular layer of the dentate gyrus may be related to the adaptation of the surrounding tissue to the rapid loss of neurons (Bulloch et al., 1996). The loss of the entire dentate gyrus occurs only in some rats and may well be explained by the absence of accessory adrenal tissue in those rats. When not removed at the time of ADX, this tissue can supply enough adrenal steroids to prevent neuronal loss, and we have found that very low levels of adrenal steroids, sufficient to occupy Type I adrenal steroid receptors, block dentate gyrus neuronal loss (Woolley et al., 1991). Although this is the case for adult hippocampus, Type II adrenal steroid receptors appear to be involved in inhibiting apoptosis in the neonatal hippocampus (Gould, Tanapat, and McEwen, 1997). This latter finding helps explain how massive apoptosis in the dentate gyrus occurs around postnatal day 6, in spite of glucocorticoid levels that are sufficient to occupy Type I receptors around this age (Meaney, Viau, et al., 1988). Cell proliferation in the dentate gyrus of rats and other mammals In adult rats, granule cell birth is accelerated by ADX (Gould and McEwen, 1993) (see Fig. 40.3). Newly born neurons, staining for neuron-specific enolase, arise in the hilus of the adult rat dentate gyrus, very close to the granule cell layer, and then migrate into the granule cell layer, presumably along a vimentin-staining radial glial network that is also enhanced by ADX (Gould and McEwen, 1993; Cameron and Gould, 1996a,1996b). The precursors for the newly generated cells appear to be related to astrocytes that express glial fibrillary acidic protein (GFAP) (Seri et al., 2001). Although Type I adrenal steroid receptors suppress neuronal turnover in adult dentate gyrus, most neuroblasts labeled with [3H] thymidine lack Type I and Type II adrenal steroid receptors (Cameron and Gould, 1996a), indicating steroidal regulation occurs via messengers from unidentified steroid-sensitive cells. The possibility that other trophic factors may be involved is currently under investigation by Gould and her colleagues. Is the neurogenesis seen in rat and vole dentate gyrus an isolated phenomenon for those species or a broader phenomenon applicable to a select group of neurons in

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Concerning the impairment of hippocampal function that may accompany adrenocortical insufficiency, several reports have indicated that long-term ADX rats that have damage to the dentate gyrus, like that described by Sloviter et al., (1989), show modest deficits in spatial memory (Armstrong et al., 1993; Conrad and Roy, 1995). It is particularly interesting that the spatial memory deficits after 42 days of ADX cannot be reversed by either glucocorticoid treatment or the antidepressant fluoxetine (Gong et al., 2007), which, in nonADX animals, is able to increase neurogenesis (Duman et al., 2001). It is of further interest in relation to antidepressant actions that serotonin modulates the ability of CORT to suppress neurogenesis (Huang and Herbert, 2005) and that the ability of selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine to increase neurogenesis requires the normal diurnal rhythm of HPA activity (Huang and Herbert, 2006). Regulators of neurogenesis

40.3 Entorhinal cortex input to the dentate gyrus and circulating adrenal steroids regulate turnover of granule neurons in the adult rat brain. Adrenalectomy increases the rates of cell birth and cell death, whereas entorhinal cortex lesions or blockade of N-methyl-Daspartate (NMDA) receptors increase neurogenesis without affecting the number of dying granule neurons. As a result of NMDA receptor blockade, the size of the adult dentate gyrus increases.

FIGURE

the adult vertebrate brain? Studies of neurogenesis in songbird brain in relation to season of the year support the broader view (Rasika et al. 1994), but previous studies of neurogenesis in adult primate and human brain have produced largely negative results (Rakic, 1985). However, the dentate gyrus has not been a primary focus, and there have been no attempts to increase neurogenesis using either NMDA receptor blockade or ADX. Recent studies of the tree shrew, an insectovore, indicate that adult neurogenesis does occur in the dentate gyrus, and that it increases after acute NMDA receptor blockade and decreases after acute psychosocial stress (Gould, McEwen, et al., 1997). Dentate gyrus neurogenesis also has been shown to occur in the marmoset (Gould et al., 1998), a new-world primate, as well as in an old-world primate species, the rhesus monkey (Fuchs and Gould, 2000; Gould et al., 2001) and in the adult human dentate gyrus (Eriksson et al., 1998). In the human brain, it should also be noted that acute adrenocortical insufficiency, analogous to ADX, has been reported to result in dentate gyrus granule neuron death (Maehlen and Torvik, 1990).

There are negative and positive regulators of neurogenesis. Among the most important negative regulators discovered thus far are the excitatory amino acids. Blockade of NMDA receptors or removal of excitatory entorhinal cortical input to dentate gyrus markedly accelerates neurogenesis (see Fig. 40.3). N-methyl-D-aspartate receptor blockade also increases total dentate granule neuron number because it does not change the rate of granule neuron death (Cameron et al., 1995) until several weeks later when there is an elimination of cells that have not established connections (Nacher and McEwen, 2006). Application of NMDA has the opposite effect, namely, to suppress neuronal birth (Cameron et al., 1995). Like the story with Type I (MR) receptors, newly born granule neurons do not express NMDA R1 receptors, and so there must be another NMDA-responsive, as well as steroid-sensitive, cell type involved. Certain types of acute and chronic stress inhibit neurogenesis. Acute stress involving the odor of a natural predator, the fox, inhibits neurogenesis in the adult rat (Galea et al., 1996). Acute psychosocial stress in the adult tree shrew, involving largely visual cues, inhibits neurogenesis (Gould, McEwen, et al., 1997). Inhibition of neurogenesis is also seen in the dentate gyrus of the marmoset after acute psychosocial stress (Gould et al., 1998). However, acute restraint stress does not inhibit neurogenesis, although chronic restraint stress for 21 days does inhibit dentate gyrus neurogenesis (Pham et al., 2003), and the learning of a contextual fear conditioning task is accompanied by suppression of dentate gyrus cell proliferation (Pham et al., 2003). Granule neuron birth is accelerated by seizure-like activity (Parent et al., 1997), and the stimulus for this neurogenesis is likely to be apoptotic cell death because

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seizures kill granule neurons (Bengzon et al., 1997) and local increases in apoptosis simulate local neurogenesis (Cameron and Gould, 1996b). Granule neuron birth is also accelerated by blocking NMDA receptors or lesioning the excitatory perforant pathway input from the entorhinal cortex (Cameron et al., 1995). Unlike ADX, these treatments do not increase granule neuron apoptosis acutely, but only after a lag of several weeks, and a single dose of an NMDA-blocking drug results in a 20% increase in dentate gyrus neuron number several weeks later (Cameron et al., 1995; Nacher et al., 2001). Thus, although increased apoptosis leads to increased neurogenesis (Gould and Tanapat, 1997), the two processes occur in different regions of the granule cell layer and can be uncoupled from each other. Nevertheless, the adrenal steroid suppression of neurogenesis is through an NMDA-receptor mechanism (Gould, Tanapat, and Cameron, 1997; Noguchi et al., 1990). As noted earlier, serotonin is a positive signal for neurogenesis in the adult dentate gyrus (Brezun and Daszuta, 1999, 2000). Treatment with the serotoninreleasing drug d fenfluramine increased neurogenesis (Gould, 1999). Likewise, the 5-HT1A agonist 8 hydroxy DPAT stimulated neurogenesis, whereas blockade of 5-HT1A receptors had the opposite effect and prevented the effect of d fenfluramine treatment (Gould, 1999), as well as preventing increased neurogenesis caused by pilocarpine-induced seizures (Radley and Jacobs, 2002). Various chronic antidepressant treatments also increase dentate gyrus cell proliferation in the absence of applied stress (Malberg et al., 2000). One antidepressant has been shown to prevent the suppression of neurogenesis by psychosocial stress in the tree shrew (Czeh et al., 2001). Estrogen treatment acutely enhances dentate gyrus cell proliferation (Tanapat et al., 1999). The mechanism for this enhancement may well involve serotonin because serotonin depletion by P-chlorophenylalanine (PCPA) abolishes the stimulatory effect of estradiol in ovariectomized female rats (Brezun and Daszuta, 1999). Interestingly, the enhancement of polysialated neural cell adhesion molecule (PSA-NCAM) expression by estrogen is not prevented by serotonin depletion. Circulating insulin-like growth factor (IGF-1) is another stimulator of neurogenesis (Aberg et al., 2000; O’Kusky et al., 2000). IGF-1 is a 7.5kDa protein and, yet, it is taken up into cerebrospinal fluid (CSF) by a process that is independent of IGF receptors or binding proteins (Pulford and Ishii, 2001). In rats, voluntary running in a running wheel has been reported to increase neurogenesis in the dentate gyrus (van Praag et al., 1999). Such exercise increases the uptake of IGF-1 from the blood and activates c-Fos expression in dentate gyrus and other brain regions in a manner that is mimicked by IGF-1 administration into the circulation

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(Carro et al., 2000). Moreover, immunoneutralization of IGF-1 blocks the effects of exercise to enhance neurogenesis (Trejo et al., 2001). Receptors for IGF-1, IGF2, and insulin are expressed in the hippocampus (Dore, Kar, Rowe, et al., 1997), with IGF-1 receptors undergoing a decrease after adrenalectomy (Islam et al., 1998). Although IGF-1, IGF-2, and insulin binding do not decrease with age in the rat hippocampus (Dore, Kar, Rowe, et al., 1997), the level of IGF-1 mRNA undergoes a small but selective decrease in some hippocampal fields (Lai et al., 2000). Exogenous IGF-1 ameliorates memory deficits in aging rats (Markowska et al., 1998) and enhances glucose uptake in the aging hippocampus (Lynch et al., 2001) as well as having neuroprotective actions (Dore, Kar, and Quirion, 1997; Takadera et al., 1999; Gleichmann et al., 2000). Adaptive value of neuronal turnover in the dentate gyrus Adult neurogenesis in the dentate gyrus and cerebral cortex results in neurons that eventually turn over and are replaced by other neurons (Gould et al., 2001). Naturalistic stimuli, such as the odor of a predator to a rat, or a psychosocial stress encounter for a tree shrew, turn off ongoing neurogenesis (Gould, McEwen, et al., 1997; Parent et al., 1998). Chronic psychosocial stress in the tree shrew results in a more substantial inhibition of neurogenesis than after a single acute stressful encounter; moreover, the dentate gyrus is 30% smaller in the chronically stressed tree shrew, although granule neuron number only shows a trend for reduction (Gould and Fuchs, unpublished observations). This finding suggests that there may be other changes such as remodeling of dendritic branching to account for the decrease in dentate gyrus volume, and, indeed, recent studies on dendritic remodeling caused by glucocorticiods and also by repeated stress indicate that dentate gyrus dendrites undergo dendritic remodeling along with dendrites in CA3 and CA1 pyramidal neurons (Sousa et al., 2000). Thus the ability of the dentate gyrus to expand and contract its neuronal population may be a natural event in the life of an adult rat and tree shrew. What other uses could there be for this mechanism? One explanation for why the dentate gyrus makes new cells in adult life, as well as gets rid of them, is to process spatial information and related aspects of memory (Sherry et al., 1992). Birds that use space around them to hide and locate food, and voles as well as deer mice that traverse large distances to find mates, have larger hippocampal volumes than closely related species that do not; moreover, there are indications that hippocampal volume may change during the breeding season (Sherry et al., 1992; Galea et al., 1994). Indeed, the rate of neuro-

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genesis in the male and female prairie vole varies according to the breeding season (Galea and McEwen, 1998). Recent data on voles suggests that it is the dentate gyrus that exhibits this plasticity (Galea and McEwen, 1999). The hippocampus also appears to affect the survival of newly formed dentate granule neurons. When rats were trained in a task involving the hippocampus, the survival of previously labelled granule neurons was prolonged (Gould et al., 1999). In contrast, an enriched environment has been found to increase dentate gyrus volume in mice by increasing neuronal survival without altering the rate of neurogenesis (Kempermann et al., 1997). In the enriched environment studies (Kempermann et al., 1997), increased dentate gyrus volume was accompanied by better performance on spatial learning tasks. In contrast, decreased dentate gyrus volume in chronically stressed tree shrews is paralleled by impaired spatial learning and memory (Ohl and Fuchs, 1999), although this might be as much due to atrophy of dendrites of CA3 pyramidal neurons and dentate granule neurons (see above) as to reduced dentate gyrus neurogenesis. Thus there are several ways to maintain the balance between neuronal apoptosis and neurogenesis. There is an ongoing debate regarding the function of newly generated neurons in learning and memory and other functions of the hippocampus (Leuner et al., 2006). For example, there is evidence that behavioral tasks that involve the hippocampus prolong survival of newly generated neurons. Ablation of newly generated neurons by chemical means or X irradiation impairs some but not all hippocampal functions. In summary, neurogenesis and neuronal replacement occurs in the dentate gyrus of the hippocampal formation. It is increased by exercise and by a number of antidepressant treatments and decreased by certain types of stress (Malberg et al., 2000; Leuner et al., 2006; Saxe et al., 2006). Learning tasks that involve the hippocampus appear to increase survival of recently generated neurons, and ablation of newly generated neurons impairs some hippocampal dependent memory tasks (Leuner et al., 2006; Saxe et al., 2006). Formation and Breakdown of Synapses Hippocampal pyramidal neurons demonstrate a reversible synaptogenesis in CA1 pyramidal neurons that is regulated by ovarian steroids and excitatory amino acids via NMDA receptors in female rats (McEwen, Gould, et al., 1995). The CA1 synaptic plasticity is a rapid event, occurring during the female rats’ 5-day estrous cycle, with the synapses taking several days to be induced under the influence of estrogens and endogenous glutamic acid, and then disappearing within 12 hours under the influence of the proestrus surge of progesterone (McEwen, Gould, et al., 1995).

Even though the hippocampus expresses few estrogen and progestin receptors, this structure displays a robust response to estrogen and progestin treatment and to endogenous ovarian steroids during the natural estrous cycle. This first became evident with the finding of cyclic variations in the threshold of the dorsal hippocampus to elicitation of seizures, with the greatest sensitivity occurring on proestrus (Terasawa and Timiras, 1968). But, does the hippocampus contain ERs? Mapping studies of [3H]estradiol uptake in hippocampus (Loy et al., 1988), and then by immunocytochemistry (DonCarlos et al., 1991; Weiland et al., 1996), showed a sparse distribution of cells containing intracellular ERs in what appear to be interneurons in the CA1 region, as well as other regions of Ammon’s horn (Loy et al., 1988). There was also an indication that the CA1 region of hippocampus contains some estrogeninducible progesterone receptors, albeit at much lower levels than in the hypothalamus (Parsons et al., 1982), although it has been impossible thus far to localize them in the hippocampus using immunocytochemistry (Waters et al., in press). However, data from in situ hybridization revealed the presence of low levels of progestin receptor mRNA in the CA1 and CA3 regions of Ammon’s horn (Hagihara et al., 1992). None of the receptor localization data suggested that the hippocampus would be a major target for estrogen or progesterone action, compared to brain regions such as the hypothalamus. The picture changed when morphological studies demonstrated that estrogen treatment induces dendritic spines and new synapses not only in the ventromedial hypothalamus of the female rat but also increases density of dendritic spines on pyramidal neurons in the hippocampus (for review, see McEwen and Woolley, 1994). Estrogen effects on dendritic spines were found only in the CA1 region and not in the CA3 region or in dentate gyrus. Moreover, spine density changed cyclically during the estrus cycle of the female rat. There were also parallel changes in synapse density on dendritic spines revealed by electron microscopy, strongly supporting the notion that new synapses are induced by estradiol. Taken together, these morphological studies indicate that synapses are formed and broken down rapidly during the natural reproductive cycle of the rat. The critical involvement of progesterone was indicated by the fact that progesterone administration rapidly potentiated estrogen-induced spine formation but then triggered the down-regulation of spines on CA1 neurons. The down-regulation of dendritic spines occurred slowly when estrogen was withdrawn but took place within 8–12 hours when progesterone was administered; moreover, the natural down-regulation of dendritic spines between the proestrus peak and the trough on the day of estrus was blocked by the progesterone antagonist RU38486 (Woolley and McEwen, 1993).

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Antagonism of the progesterone effect by RU38486 is consistent with the involvement of intracellular progestin receptors and is compatible with the finding, noted above, of estrogen-inducible progestin receptors in the CA1 region of hippocampus (Parsons et al., 1982). However, there is another important factor, namely, the fact that estrogen induction of new spine synapses on CA1 pyramidal neurons is blocked by concurrent administration of NMDA receptor antagonists but not by antagonists of cholinergic and AMPA-kainate receptors (Woolley and McEwen, 1994). Spine synapses are excitatory, and it is likely that NMDA receptors occur on them; one of the long-term effects of estradiol is to induce NMDA receptor binding sites in the CA1 region of the hippocampus (Weiland, 1992a) and to increase immunoreactivity for the NMDA R1 subunit in the cell bodies and dendrites of CA1 pyramidal neurons, while not altering NMDA R1 mRNA levels measured by in situ hybridization (Gazzaley et al., 1996) (see Fig. 40.4). Thus, it may be that activation of NMDA receptors themselves could lead to induction of new synapses, in which case estrogen induction of NMDA receptors would then become a primary event leading to synapse formation. As discussed by Woolley and McEwen (1994), NMDA receptors gate calcium ions, and this may be an important factor in the extension and retraction of dendritic spines: for example, NMDA receptor activation promotes dephosphorylation of mitogen-activated protein (MAP2) and alters the interaction of this cytoskeletal protein with actin and tubulin.

40.4 Estradiol regulates synaptogenesis on CA1 pyramidal neurons in the adult female rat hippocampus. Blocking N-methyl-Daspartate (NMDA) receptors prevents the estrogen effect, and estrogen treatment increases expression of NMDA receptor protein on CA1 neurons. Estrogen-receptor immunoreactivity is found in interneurons, which are likely to be inhibitory. We speculate in this figure that these interneurons may synapse on other inhibitory interneurons and thus produce a disinhibition on the CA1 pyramidal neurons.

FIGURE

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As to the possible significance of the presence of ERs in inhibitory interneurons and not in CA1 pyramidal neurons in which spine formation takes place, estradiol treatment induced glutamic acid decarboxylase (GAD) mRNA in inhibitory interneurons within the CA1 pyramidal cell layer (Weiland, 1992b). This would potentially increase inhibitory activity within these neurons, although it is not clear where they exert their inhibitory effect, on the pyramidal neurons themselves or on other inhibitory interneurons (see Fig. 40.4). In this connection, there are studies pointing to estrogen effects that excite hippocampal CA1 pyramidal neurons, possibly through disinhibition. One explanation is that estrogen actions on inhibitory interneurons might in some manner disinhibit the pyramidal neurons, allowing for removal of the magnesium blockade and activation of NMDA receptors (see Woolley and McEwen, 1994, for discussion). Recent data on embryonic hippocampal neurons in cell culture have shown that estradiol induces spines over a time course of 24–48 hours by a process that is blocked by the antiestrogen tamoxifen and by the NMDA antagonist APV but not by the AMPA/kainate antagonist DNQX (D.D. Murphy and Segal, 1996). The phosphorylation of cyclic adenosine monophosphate (cAMP)response element binding (CREB) has been implicated in this process (D.D. Murphy and Segal, 1997), and a decrease in brain-derived neurotrophic factor (BDNF) and inhibitory GABA transmission are also implicated (D.D. Murphy, Cole, Greenberger, et al., 1998; D.D. Murphy, Cole, and Segal, 1998). In vivo data also support a role for a transient estrogen-induced inhibition of GABA levels in inhibitory interneurons in the CA1 region (Rudick and Woolley, 2001). Besides cell nuclear ER, there is increasing evidence for nonnuclear ER that interact with second-messenger pathways. A seminal study reported that transfection of ERa and ERb into Chinese hamster ovarian cells resulted in expression of both ERs in a form that couples to second-messenger systems that are stimulated by estrogen and blocked at least partially by nonsteroidal estrogen antagonists (Razandi et al., 1999). Previous studies had indicated that nonnuclear ERs can be seen at the light microscopic level in cultured cells (Clarke et al., 2000) and also at the electron microscopic (EM) level in hypothalamus (Blaustein et al., 1992). The proliferation of articles on nonnuclear actions of estrogen via membrane ER and membrane-associated ER (e.g., Kelly and Levin, 2001; see above) has reinforced the importance of investigating nonnuclear actions of estrogens in the hippocampus. Stimulated by this evidence, we used electron microscopy to examine ERa localization in rat hippocampal formation (Milner et al., 2001). We were able to see at the EM level the cell nuclear labelling seen by light microscopy in some GABA interneurons. In addition, some

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pyramidal and granule neuron perikarya have small amounts of ERa immunoreactive (IR) in the nuclear membrane, which is consistent with a recent report that 125 I estradiol labels a small number of estrogen binding sites in cell nuclei of hippocampal principal cells (Shughrue and Merchenthaler, 2000). In stratum radiatum of CA1, we found half of the total ERa-IR in unmyelinated axons and axon terminals containing small synaptic vesicles. This is of potential functional relevance, given findings that estrogen can influence neurotransmitter release (see McEwen et al., 2001, for references). The synaptic ERa-IR was found in terminals that formed asymmetric and symmetric synapses on dendritic shafts and spines, suggesting that excitatory and inhibitory transmitter systems are associated with ERa (Milner et al., 2001). Around 25% of the ERa-IR was found in dendritic spines of principal cells, where it was often associated with spine apparati and/or postsynaptic densities, suggesting that estrogen might act locally to regulate calcium availability, phosphorylation, or protein synthesis. Finally, the remaining 25% of ERa-IR was found in astrocytic profiles, often located near the spines of principal cells. The close association between the ERa-IR and dendritic spines supports a possible local, nongenomic role for this ER in regulation of dendritic spine density via second-messenger systems. Initial in vivo and in vitro studies in the hippocampus of one second-messenger pathway, the phosphorylation of CREB, have indicated that estrogen has rapid effects that are evident within as little as 15 minutes to increase phosphoCREB immunoreactivity in cell nuclei of hippocampal pyramidal neurons (Lee et al., 2000). One pathway by which CREB phosphorylation may occur involves phosphoinositol3 (PI3) kinase, or Akt, system (Datta et al., 1999). Studies are under way to try to connect these events together in the early actions of estrogen on hippocampal neurons that precede the induction of synapse formation. We next consider how nonnuclear and nuclear actions of ER may be coordinated in regulating synapse formation. How can nuclear and nonnuclear actions of estrogen work together in the hippocampus? There is strong evidence in vivo and in vitro supporting an indirect GABAergic mediation of estrogen actions on synapse formation involving the ERa-containing inhibitory interneurons (D.D. Murphy, Cole, Greenberger, et al., 1998; Rudick and Woolley, 2000). The in vitro evidence comes from in vitro studies of E-induced synapse formation, in which estrogen induces spines on dendrites of dissociated hippocampal neurons by a process that is blocked by an NMDA receptor antagonist and not by an AMPA/ kainate receptor blocker (D.D. Murphy and Segal, 1996). Furthermore, estrogen treatment was found to increase expression of phosphorylated CREB, and a specific antisense to CREB prevented the formation of dendritic spines and the elevation in phosphoCREB IR (D.D.

Murphy and Segal, 1997). The cellular location of ERa in the cultures, resembling the in vivo localization, was in putative inhibitory interneurons, that is, GAD-immunoreactive cells that constituted around 20% of total neuronal population. Estrogen treatment caused decreases in GAD content and the number of neurons expressing GAD, and mimicking this decrease with an inhibitor of GABA synthesis, mercaptopropionic acid, caused an up-regulation of dendritic spine density, paralleling the effects of estrogen (D.D. Murphy, Cole, Greenberger, et al., 1998). Thus, estrogen-induced synapse formation may involve the suppression of GABA inhibitory input to the pyramidal neurons where the synapses are being generated. An additional role of estrogen is to mobilize the movement of synaptic vesicles in ERa-containing presynaptic boutons of inhibitory interneurons that have the cholecystokinin neurochemical phenotype and which also express neuropeptide Y (NPY), a modulator that inhibits excitatory activity (Het and Wolf, 2007). Estrogen treatment has also been shown to increase expression of NPY in a subset of inhibitory interneurons in hippocampus (Nakamura and McEwen, 2005). Estrogen treatment may exert effects on NPY expression via BDNF (Franklin and Perrot-Sinal, 2006). These effects of estrogen via NPY may be relevant not only to synapse formation but also to the neuroprotective effects of estrogens in relation to stroke (Wise et al., 2005). Thus, nuclear ER in interneurons plays a role in regulating the inhibitory tone upon pyramidal cells that, on the one hand, helps to regulate synapse formation and, on the other hand, may reduce neuronal excitability in relation to seizures and seizure-related damage. Concurrently, ER in dendritic spines may be associated with the activation of messenger ribonucleic acid (mRNA) translation from polyribosomes (Tiedge et al., 2001) or endomembrane structures found in spines (Pierce et al., 2000). In addition, other second-messenger signaling effects might include the phosphorylation of neurotransmitter receptors or ion channels. Estrogen receptor in certain presynaptic terminals might modulate neurotransmitter release or reuptake (see McEwen et al., 2001, for references). Moreover, ER-mediated activation of second-messenger systems in dendritic spines and presynaptic endings might lead to retrograde signal transduction back to the cell nucleus, perhaps via Akt or CREB, providing another pathway through which estrogen could regulate gene expression. In summary, estradiol exerts important regulatory effects on synapse formation in the hippocampus by acting via nongenomic and genomic ERs found in diverse locations: inhibitory interneurons, cholinergic synapses, dendrites, and spines of excitatory neurons. Besides enhancing aspects of cognitive function (Sherwin, 2003), estrogen effects also include neuroprotection in relation to stroke.

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Rapid Plasticity of Dendrites During Hibernation and Recovery Hibernating ground squirrels and hamsters show a rapid atrophy or retraction of apical dendrites of CA3 pyramidal neurons that develops as fast as the hibernating state and can be reversed rapidly within several hours (Popov and Bocharova, 1992; Popov, Bocharova, and Bragin, 1992; Magarinos et al., 2006; Spanswick et al., 2007). This plasticity is seen on apical dendrites of CA3 pyramidal neurons that receive a powerful synaptic input from the dentate gyrus. Although anatomically similar to the stress-induced atrophy in rats and tree shrews (see below), it is not yet clear if this process involves the same mechanisms; however, if this is the case, the question becomes what factors make the atrophy rapid in hibernation and slow in relation to repeated stress. Delayed Remodeling of Dendrites Prolonged or repeated stress or glucocorticoid exposure causes atrophy of apical dendrites of CA3 pyramidal neurons, which resembles at least superficially what is seen in hibernation. In the hibernation and stress studies, dendritic length and branching are assessed by morphometry after silver staining neurons with the single-section Golgi technique. More recently, electron microscopy has revealed that stress and glucocorticoids alter morphology of presynaptic mossy fiber terminals in the stratum lucidum region of CA3 (Magarinos et al., 1997). Initially, atrophy of apical dendrites of CA3 pyramidal neurons, and not dentate granule neurons or CA1 pyramidal neurons, was found after 21 days of daily CORT exposure and also after 21 days of 6 hours/day repeated restraint stress (reviewed in McEwen, Albeck, et al., 1995). Psychosocial stress also causes apical dendrites of CA3 pyramidal neurons to atrophy in rats (McKittrick et al., 2000) and in an insectivore, the tree shrew (Magarinos et al., 1996). Stress- and CORT-induced atrophy were prevented by the antiepileptic drug, phenytoin (Dilantin), thus implicating the release and actions of excitatory amino acids because phenytoin blocks glutamate release and antagonizes sodium channels and T-type calcium channels that are activated during glutamate-induced excitation (Taylor and Meldrum, 1995). This result is consistent with evidence that stress induces release of glutamate in hippocampus and other brain regions by a process dependent on the presence of the adrenal glands (see Magarinos et al., 1996; McEwen, Albeck, et al., 1995). Indeed, NMDA receptor blockade is also effective in preventing stress-induced dendritic atrophy (see McEwen, Albeck, et al., 1995). A model of the cellular and neurochemical interactions involved in dendritic atrophy is presented in Fig-

FIGURE 40.5 Stress causes atrophy, or remodelling, of apical dendrites of CA3 pyramidal neurons. Pharmacological blockade of dendritic atrophy indicates that glucocorticoid secretion is involved and that the final common path involves excitatory amino acid release via N-methyl-D-aspartate (NMDA) receptors. The mossy fiber terminals on the base of the apical dendrites appears to play the primary role in initiating the atrophy, and presynaptic kainate receptors on mossy fiber endings are likely to play an important role. However, serotonin release also appears to play a role because a serotonin reuptake enhancer, tianeptine, prevents atrophy (see text). Benzodiazepine treatment also prevents atrophy, presumably by enhancing the inhibitory input on interneurons. GR: glucocorticoid receptor; MR: mineralocorticoid receptor.

ure 40.5, and it emphasizes the interactions among neurons and neurotransmitters. The role of adrenal steroids is discussed below. Besides glutamate, other participating neurotransmitters include GABA and serotonin. Inhibitory interneurons have a significant role in controlling hippocampal neuronal excitability (Freund and Buzsaki, 1996), and involvement of the GABA-benzodiazepine receptor system is strongly suggested by the ability of a benzodiazepine, adinazolam, to block dendritic atrophy (Magarinos et al., 1999). As for serotonin, repeated restraint stress in rats and psychosocial stress causes changes in the hippocampal formation that include not only atrophy of dendrites of CA3c pyramidal neurons but also suppression of 5-HT1A receptor binding (McEwen, Albeck, et al., 1995; McKittrick et al., 2000). Serotonin is released by stressors and tianeptine, an atypical tricyclic antidepressant that enhances serotonin reuptake and thus reduces extracellular 5-HT levels, preventing stress- and CORT-induced dendritic atrophy of CA3c pyramidal neurons (Watanabe et al., 1992). In contrast, several inhibitors of serotonin reupake—fluoxetine, fluvoxamine, and desipramine, an inhibitor of noradrenaline uptake—failed to block atrophy (Magarinos et al., 1999). Thus the effect of tianeptine on CA3 pyramidal neuron morphology is not likely to be due to its reported effects to reduce CORT secretion (Delbende et al., 1991) but may instead be related to its reported effects to enhance the reuptake of serotonin within the

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hippocampus (Whitton et al., 1991). Further evidence for serotonin involvement in dendritic atrophy comes from studies of psychosocial stress in rats, in that dominant and subordinant rats show both dendritic atrophy as well as down-regulation of 5-HT transporter expression in the CA3 region, indicating either a reduced density of serotonin terminals or a reduced expression of the transporter (McKittrick et al., 2000). However, dominant rats show a greater reduction in 5-HT transporter sites than subordinants, and dominants also show a greater dendritic atrophy (McKittrick et al., 2000). Because CORT- and stress-induced atrophy of CA3 pyramidal neurons is blocked by phenytoin as well as by tianeptine (see McEwen, Albeck, et al., 1995), serotonin released by stress or CORT may interact pre- or postsynaptically with glutamate released by stress or CORT, and the final common path may involve interactive effects between serotonin and glutamate receptors on the dendrites of CA3 neurons innervated by mossy fibers from the dentate gyrus. There is evidence for interactions between serotonin and NMDA receptors, indicating that serotonin potentiates NMDA receptor binding as well as activity of NMDA receptors and may do so via 5-HT2 receptors (Mennini and Miari, 1991; Rahmann and Neumann, 1993). Glucocorticoid treatment causes dendritic atrophy, and stress-induced atrophy is blocked by treatment with an adrenal steroid synthesis blocker, cyanoketone (see Magarinos and McEwen, 1995a, 1995b). What is the role of adrenal steroids in relation to the neurotransmitter involvement cited above? A primary site of action is the release of glutamate, because ADX markedly reduces the magnitude of the excitatory amino acid (EAA) release evoked by restraint stress (Lowy et al., 1993; Moghaddam et al., 1994). In this connection, mossy fiber terminals from dentate granule neurons in the stratum lucidum of CA3 apical dendrites show morphological alterations as a result of chronic stress (Magarinos et al., 1997). These changes involve reorganization of synaptic vesicles in the synaptic terminal, with a higher density occurring in regions adjacent to active synaptic zones. The stratum lucidum zone of CA3 contains high levels of kainate receptors, as demonstrated by quantitative autoradiography, and, as noted above, these receptors are decreased in density by ADX and restored to normal by CORT replacement (Watanabe et al., 1995). Because kainate receptors are feed-forward autoreceptors for EAAs on presynaptic mossy fiber nerve endings (see Fig. 40.5), the effects of adrenal steroids are consistent with the dependence of stress-induced glutamate release on the presence of the adrenal glands (Lowy et al., 1993; Moghaddam et al., 1994). Another possibility is that CORT or stress alters CA3 neuronal atrophy through regulation of GABAergic synaptic inhibition (see Fig. 40.5). In support of this notion,

low levels of CORT alter mRNA levels for specific subunits of GABA-A receptors in CA3 and the dentate gyrus of ADX rats (Orchinik et al., 1994), whereas stress levels of CORT have produced different effects on GABAA receptor subunit mRNA levels and receptor binding in hippocampal subregions, including CA3 (Orchinik et al., 2001). Therefore, it appears that CORT may alter the excitability of hippocampal neurons through regulation of GABA-A receptor expression, but it remains to be seen if the corticosteroid effects on neuronal morphology involve changes in the number or pharmacological properties of GABA-A receptors. Stress and glucocorticoid treatment cause enhanced expression of NMDA receptors in hippocampus (Bartanusz et al., 1995; Weiland, Orchinik, and Tanapat, 1997), and this is another potential mechanism by which adrenal steroids are involved in dendritic atrophy (see Fig. 40.5). It is puzzling, however, that NMDA receptors are not expressed in the stratum lucidum where mossy fibers terminate (Monaghan et al., 1983), given the evidence cited above for the importance of this innervation for dendritic atrophy. The presence of NMDA receptors on the more distal aspects of CA3 dendrites suggests that the mossy fiber activation of glutamate release triggers a much more widespread activity of EAAs affecting the entire dendritic tree of the CA3 pyramidal neurons. Following upon the widespread activation of NMDA receptors, the increased levels of intracellular calcium may make the dendritic cytoskeleton become depolymerized or undergo proteolysis (see McEwen, Albeck, et al., 1995, for discussion). Stress is also reported to alter the expression of the neurotrophins, BDNF and Neurotrophin-3 (NT-3), in hippocampus (Smith et al., 1995). Very little is known about the adrenal steroid receptor types involved in these effects, or the localization of stress and adrenal steroid effects on neurotrophin expression within the hippocampus and their relationship to the conditions of repeated stress that bring about morphological changes. However, conditions that cause dendritic atrophy, such as repeated restraint stress or psychosocial stress, do not appear to change neurotrophin expression in hippocampus (Kuroda and McEwen, 1998), indicating that neurotrophins are probably not directly involved in the mechanism of dendritic atrophy. In summary, stress and application of glucocorticoids cause a remodeling of dendrites of neurons in the hippocampus, primarily those of pyramidal cells in the CA3 region but also granule neurons of the dentate gyrus. This process is reversible with termination of the stressor or excess glucocorticoid, and it is blocked by inhibitors of EAA neurotransmission. Thus, as is also the case, with E-induced synapse formation, the stress-induced remodeling is not due to steroid hormones acting alone but rather in combination with EAA neurotransmission.

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Remodeling of Neurons in Amygdala and Hippocampus Acute and repeated stress (21 days of chronic restraint stress [CRS]) also cause functional and structural changes in other brain regions such as the PFC and amygdala. Chronic restraint stress and chronic immobilization caused dendritic shortening in medial PFC (Sousa et al., 2000; Wellman, 2001; Vyas et al., 2002; Cook and Wellman, 2004; Kreibich and Blendy, 2004; Radley et al., 2004; Brown et al., 2005; Radley et al., 2005; Radley et al., 2006) but produced dendritic growth in neurons in amygdala (Vyas et al., 2002), as well as in orbitofrontal cortex (OFC) (Liston et al., 2006). These actions of stress are reminiscent of recent work on experimenter versus self-administered morphine and amphetamine, in which different, and sometimes opposite, effects were seen on dendritic spine density in OFC, medial PFC, and hippocampus CA1 (Robinson and Kolb, 1997). For example, amphetamine self-administration increased spine density on pyramidal neurons in the medial PFC and decreased spine density on OFC pyramidal neurons (Crombag et al., 2005). Along with many other brain regions, the amygdala and PFC also contain adrenal steroid receptors (Ahima and Harlan, 1990; Ahima et al., 1991); however, the role of adrenal steroids, EAAs, and other mediators has not yet been studied in detail in these brain regions, in contrast to the hippocampus. Nevertheless, glucocorticoids do appear to play a role because 3 weeks of chronic CORT treatment was shown to produce retraction of dendrites in medial PFC (Wellman, 2001), although with subtle differences in the qualitative nature of the effect from what has been described after CRS (Radley et al., 2004). Another study determined the effect of ADX or either chronic treatment for 4 weeks with CORT or dexamethasone on volume and neuron number in the PFC (Cerqueira et al., 2005). Dexamethasone treatment at a dose that may have been high enough to enter the brain (although this was not directly measured) caused a loss of neurons in Layer II of the infralimbic, prelimbic, and cingulate cortex, whereas CORT treatment reduced the volume but not the neuron number of these cortical regions (Cerqueira et al., 2005). The dexamethasone treatment was particularly effective in impairing working memory and cognitive flexibility using working memory task in a Morris water maze (Cerqueira et al., 2005). Effects of chronic stress were not investigated in this study. These data notwithstanding, the cautions expressed above concerning differences between chronic stress and chronic glucocorticoid treatment must be kept in mind for the PFC, as well as the amygdala, that has not been studied yet in this regard. Behavioral correlates of CRS-induced remodeling in the PFC include impairment in attention set shifting,

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possibly reflecting structural remodeling in the medial PFC (Liston et al., 2006). Attention set shifting is a task in which a rat first learns that either odor or the digging medium in a pair of bowls predicts where food reward is to be found; then new cues are introduced, and the rat needs to learn which ones predict the location of food (Birrell and Brown, 2000). There is also a report that CRS impairs extinction of a fear conditioning task (Miracle et al., 2006). This is an important lead because the PFC is involved in extinction, a type of learning (Santini et al., 2004), but much more research is needed to explore the complex relationship between stress, fear conditioning, extinction, and possible morphological remodeling that may well accompany each of these experiences. Regarding the amygdala, chronic stress for 21 days or longer not only impairs hippocampal-dependent cognitive function (McEwen, 1999), but also enhances amygdala-dependent unlearned fear and fear conditioning (Conrad et al., 1999) that are consistent with the opposite effects of stress on hippocampal and amygdala structure. Chronic stress also increases aggression between animals living in the same cage, and this is likely to reflect another aspect of hyperactivity of the amygdala (Wood et al., 2003). Moreover, chronic CORT treatment in the drinking water produces an anxiogenic effect in mice (Ardayfio and Kim, 2006), an effect that could be due to the glucocorticoid enhancement of corticotrophin releasing factor (CRF) activity in the amygdala (Corodimas et al., 1994; Makino et al., 1994). As for mechanism of remodeling, besides the possible role of glucocorticoids and EAAs, tissue plasminogen activator (tPA) is required for acute stress to not only activate indices of structural plasticity but also to enhance anxiety (Melchor et al., 2003). These effects occur in the medial and central amygdala and not in basolateral amygdala, and the release of CRF acting via CRF-1 receptors appears to be responsible (Matys et al., 2004). Nothing is yet known about the role of tPA, if any, in the PFC, although tPA does appear to play a role in stress-induced reductions of spine synapse number in the CA1 region of the mouse hippocampus (Pawlak et al., 2005), as noted earlier. Brain-derived neurotrophic factor may also play a role in amygdala because overexpression of BDNF, without any applied stressor, enhances anxiety in an elevated plus maze and increases spine density on basolateral amygdala neurons, and this occludes the effect of immobilization stress on anxiety and spine density (Govindarajan et al., 2006). As noted above for hippocampus, BDNF overexpressing mice also show reduced behavioral depression in the Porsolt forced-swim task and show protection against stress-induced shortening of dendrites in the CA3 region (Govindarajan et al., 2006). In summary, repeated stress causes dendrites in the basolateral amygdala and OFC to expand and increases

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the density of excitatory spine synapse, whereas repeated stress causes dendrites and spines in the medial PFC to undergo shortening and retraction. Although the role of glucocorticoids and EAAs is likely, but so far unexplored, there is evidence in amygdala for the participation of other mediators such as BDNF and tPA. Interactions between amygdala, prefrontal cortex, and hippocampus The PFC, amygdala, and hippocampus are interconnected and influence each other via direct and indirect neural activity (McDonald, 1987; McDonald et al., 1996; Akirav and Richter-Levin, 1999; Petrovich et al., 2001; Ghashghaei and Barbas, 2002). For example, inactivation of the amygdala blocks stress-induced impairment of hippocampal LTP and spatial memory (Kim et al., 2005), and stimulation of basolateral amygdala enhances dentate gyrus field potentials (Ikegaya et al., 1996), whereas stimulation of medial PFC decreases responsiveness of central amygdala output neurons (Quirk et al., 2003). The processing of emotional memories with contextual information requires amygdala–hippocampal interactions (Phillips and LeDoux, 1992; Richardson et al., 2004) whereas the PFC, with its powerful influence on amygdala activity (Quirk et al., 2003), plays an important role in fear extinction (Milad and Quirk, 2002; Morgan and LeDoux, 1995). Because of these interactions, future studies need to address their possible role in the morphological and functional changes produced by single and repeated stress.

HIPPOCAMPAL NEURONAL DAMAGE RESULTING FROM CHRONIC STRESS AND AGING Neuroanatomical Findings An important issue is the relationship between the remodeling of CA3 neurons induced by repeated doses of CORT or by CRS and the thinning and apparent loss of pyramidal neurons that has been reported after 12 weeks of CORT treatment in rats and prolonged, severe psychosocial stress in vervet monkeys (see Sapolsky, 1992). As noted above, we have seen that chronic psychosocial stress in tree shrews causes remodeling of CA3 pyramidal neurons, much as restraint stress does in rats (Magarinos et al., 1996). However, we have also noted that the remodeling produced by stress in rats is reversible, within 7–14 days after the termination of stress. A possible link may be the fate of inhibitory interneurons that receive intense innervation from mossy fibers of dentate gyrus granule neurons and which are especially vulnerable to a variety of insults (Hsu and Buzsaki, 1993). If some of these neurons were to die as a result of repeated restraint stress, then there

might be a cumulative effect over time, in which repeated bouts of stress might progressively deplete the dentate gyrus of the buffering action that these inhibitory neurons appear to provide. However, there is a big gap in our understanding between neuronal remodeling and permanent cell loss either of interneurons or of pyramidal neurons, and one of the most surprising and puzzling findings concerning glucocorticoids and neuronal damage in the hippocampus was the morphological changes resulting from prolonged exposure to stress or stress hormones that were interpreted as indicating neuronal damage and pyramidal cell loss. Adrenocorticotrophic hormone or cortisone administration was reported to mature guinea pigs, causing neurons in hippocampus and other forebrain regions to stain darkly and appear necrotic, as if undergoing remodeling, then perhaps also dying (AusDerMuhlen and Ockenfels, 1969). Other investigators have described the appearance of “darkly stained” CA3 pyramidal neurons following repeated cold swim stress in rats (Mizoguchi et al., 1992) and psychosocial stress in tree shrews (Fuchs et al., 1995). Although the interpretation of these findings may be questioned in light of the report that darkly stained neurons can develop artifactually from physical trauma in fixing brains for histological analysis (Cammermeyer, 1978), the findings in the guinea pig were instrumental in stimulating the work of Landfield and colleagues that showed that aging in the rat results in thinning of the pyramidal cell layer in hippocampus and that this change was retarded by ADX in midlife (Landfield, 1987). Robert Sapolsky (1992) then demonstrated that 12 weeks of daily CORT injections into young adult rats mimicked the pyramidal neuron thinning seen in aging, and subsequent work on subordinant vervet monkeys revealed a thinning and apparent necrosis of CA3 pyramidal neurons that implied some kind of stress-related hippocampal damage. However, dying cells are rarely seen because they disappear rapidly, and the evidence for neuronal loss depends on counting of cells in histological material. This issue has been raised recently (Rasmussen et al., 1996), using revised stereological procedures for estimated neuronal number, showing that aging rats that are cognitively impaired do not necessarily show reduced hippocampal neuron number. A similar conclusion was reached for cognitively impaired middle-aged rats without the use of elaborate neuronal counting methods (Issa et al., 1990), and a recent study on rats with age-related spatial memory impairment has revealed altered expression of markers of glial hypertrophy and oxidative stress that are interpreted as evidence for synaptic and dendritic pruning rather than neuronal loss (Sugaya et al., 1996). However, none of these studies have directly looked for dendritic remodeling or synapse loss, and such studies are urgently needed. Moreover, there is

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not sufficient evidence presently to exclude neuronal loss as a later stage of the aging process, and some of the evidence mentioned above can be interpreted either way. Furthermore, the work of Sapolsky alluded to above first showed thinning of pyramidal neuron number in aging rats and rats treated for 12 weeks with daily CORT injections; Sapolsky then demonstrated that EAAs play an important role in the cell loss by showing, first, that glucocorticoids exacerbate kainic acid–induced damage to hippocampus, as well as ischemic damage; and, second, that glucocorticoids potentiate EAA killing of hippocampal neurons in culture (Sapolsky, 1992). Recent work (Lowy et al., 1995) has brought this issue full circle by demonstrating using intracerebral microdialysis in hippocampus that restraint stress-induced glutamate release is not only exacerbated in aging rats but that it continues for some time after stress is terminated. Although this mechanism is consistent with enhanced dendritic remodeling and synapse loss in the aging hippocampus, it is also consistent with the possibility of enhanced rates of neuronal damage and loss by the same mechanisms that are implicated in ischemia- and traumainduced hippocampal neuronal destruction (Choi, 1988; Siesjo and Bengtsson, 1989; Sapolsky, 1992). In summary, the aging hippocampus appears to lose functional capacity more rapidly in some individuals than in others. Rather than being the result of outright neuron loss, these changes appear to reflect loss of synaptic connectivity and dendritic pruning resulting from increased oxidative stress in which excitatory amino acid activity and glucocorticoids very likely play a role. LIFELONG IMPLICATIONS OF STRESSFUL EXPERIENCES Long-term stress also accelerates a number of biological markers of aging in rats, including increasing the excitability of CA1 pyramidal neurons via a calciumdependent mechanism and causing loss of hippocampal pyramidal neurons (S. Kerr et al., 1991). An important factor may be the enhancement by glucocorticoids of calcium currents in hippocampus (D. Kerr and Campbell, 1992) (see also Table 40.1), in view of the key role of calcium ions in destructive, as well as plastic processes in hippocampal neurons. It will be important to learn how regional neural activity is altered in such conditions as traumatic stress and recurrent depressive illness and how long-term changes in neural activity may alter structure and function of neurons, particularly in the hippocampus. Another aspect of stressful experiences is the developmental influence of early stress and of neonatal handling on the life course of aging and age-related cognitive impairment. As discussed elsewhere (Meaney, Aitken, et al., 1988; Meaney et al., 1994), such early experi-

TABLE

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40.1 Atrophy of the Human Hippocampus

Situation or Condition

References

Recurrent depressive illness

(Sheline et al., 1996; Sheline et al., 1999)

PTSD

(Bremner et al., 1995; Gurvits et al., 1996)

Aging, preceding dementia

(Golomb et al., 1994; Zhuang et al., 1999)

Dementia

(Quirk and Armony, 1997)

Cushing’s syndrome

(Starkman et al., 1999; Snyder et al., 2001)

Schizophrenia

(Bogerts et al., 1993; Fukuzako et al., 1996)

For another summary of hippocampal atrophy in the human brain, see Sapolsky (1996). PTSD: posttraumatic stress disorder.

ences can either increase or decrease the rate of brain aging through a mechanism in which the activity of the HPA axis appears to be involved. The early experiences are believed to set the level of responsiveness of the HPA axis and autonomic nervous system in such a way that these systems either overreact in animals subject to early unpredictable stress or underreact in animals exposed to the neonatal handling procedure. TRANSLATION TO THE HUMAN BRAIN Much of the impetus for studying the effects of stress on the structure of the human brain has come from the animal studies summarized thus far. Although there is very little evidence regarding the effects of ordinary life stressors on brain structure, there are indications from functional imaging of individuals undergoing ordinary stressors, such as counting backwards, that there are lasting changes in neural activity (Wang et al., 2005). Moreover, the study of depressive illness and anxiety disorders has also provided some insights. Life events are known to precipitate depressive illness in individuals with certain genetic predispositions (Kessler, 1997; Kendler, 1998; Caspi et al., 2003). Moreover, brain regions such as the hippocampus, amygdala, and PFC show altered patterns of activity in positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) and also demonstrate changes in volume of these structures with recurrent depression: decreased volume of hippocampus and PFC and amygdala (Drevets et al., 1997; Sheline et al., 1999; Sheline et al., 2003). Interestingly, amygdala volume has been reported to increase in the first episode of depression, whereas hippocampal volume is not decreased (Frodl et al., 2003; MacQueen et al., 2003). It has been known for some time that stress hormones, such as cortisol, are involved in psychopathology, reflecting emotional arousal and

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psychic disorganization rather than the specific disorder per se (Sachar et al., 1973). We now know that adrenocortical hormones enter the brain and produce a wide range of effects upon it. In Cushing’s disease, there are depressive symptoms that can be relieved by surgical correction of the hypercortisolemia (B.E.P. Murphy, 1991; Starkman and Schteingart, 1981). Major depression and Cushing’s disease are associated with chronic elevation of cortisol that results in gradual loss of minerals from bone and abdominal obesity. In major depressive illness, as well as in Cushing’s disease, the duration of the illness and not the age of the patients predicts a progressive reduction in volume of the hippocampus, determined by structural MRI (Starkman et al., 1992; Sheline et al., 1999). Moreover, there are a variety of other anxiety-related disorders, such as PTSD (Pitman, 2001; Bremner, 2002) and borderline personality disorder (Driessen et al., 2000), in which atrophy of the hippocampus has been reported, suggesting that this is a common process reflecting chronic imbalance in the activity of adaptive systems, such as the HPA axis, but also including endogenous neurotransmitters, such as glutamate. Another important factor in hippocampal volume and function is glucose regulation. Poor glucose regulation is associated with smaller hippocampal volume and poorer memory function in individuals in their sixties and seventies who have “mild cognitive impairment” (MCI) (Convit et al., 2003), and MCI and Type 2, as well as Type 1, diabetes are recognized as risk factors for dementia (Ott et al., 1996; de Leon et al., 2001; Haan, 2006). That the hippocampus and possibly other brain regions is responsive to glucose and insulin, as well as other metabolic hormones, makes it imperative to consider broader aspects of brain–body relationships in relation to acute and chronic stress.

STRESSFUL EXPERIENCE AND DISEASE What is Lacking in the Current Discussion of Stress Having noted the effects of stress on the brain, and particularly on the hippocampus, we now turn to the broader topic of stress, that is, how individuals interpret and respond to potentially stressful events, and how this may lead to disease. The problem with the concept of stress is that it does not do justice to the many situations in an individual’s life that are more pervasive and long-lasting than a stressful life event, such as those related to living environment, interpersonal relationships, and employment. Moreover, the stress concept does not adequately reconcile the paradox between the body’s adaptive mechanisms and how these same mechanisms may become involved in pathophysiological processes. As an alternative to talking about stress,

we discuss below two concepts: “allostasis” (Sterling and Eyer, 1988) and “allostatic load” (McEwen and Stellar, 1993), which pertain to adaptation and the cost of adaptation for the body and brain, respectively. The sensitivity and vulnerability of the hippocampus discussed above, as manifested in the interactions between EAAs, serotonin, and glucocorticoids, is an especially good example of the notion of allostasis and allostatic load, in that the release of these neuromodulators is an adaptive response (allostasis) to a potentially stressful event, whereas the long-term consequences of this allostasis is an atrophy of neuronal processes that compromises hippocampal function (allostatic load). Moreover, the role of the hippocampus in interpreting and responding to potential stressors plays an important role in determining the level of “allostatic load” that an individual will experience because selective attention to cues and use of contextual information based upon prior experiences may improve the discriminative capability and allow the individual to respond to a potential stressor in a way that minimizes the allostatic load. Allostasis and Allostatic Load What is allostasis? The body has systems that respond to the body state (like waking, sleeping, lying, standing, exercising) and to the external environment and that promote adaptation to activities such as locomotion and to aversive stimuli—like noise and crowding, hostility, fatigue, isolation, hunger, excessive heat or cold—and threats to safety. These systems include the HPA axis; the autonomic nervous system; the metabolic systems—thyroid axis, insulin, glucagon and the gut; and the immune system. They are closely coupled to the psychological make-up of the individual, in that those people who are fearful and reactive will have more reactive physiological responses, whereas those individuals who have proactive planning skills and psychological buffers will have less reactive responses and more stability in their physiology. Adversity, including interpersonal conflict and social instability, accelerate pathophysiological processes and result in increased incidence of morbidity and mortality. The cardiovascular system is one of the most susceptible. For example, blood pressure increases are a sensitive index of job stress in factory workers and other repetitive jobs with time pressures (Melin et al., 1999) and of job instability in British civil service departments undergoing privitization (Ferrie et al., 2002), and cardiovascular disease is a primary reason for the increased death rate in Eastern Europe in the social collapse following the fall of communism (Bobak and Marmot, 1996). It should be noted that blood pressure surges are linked to accelerated atherosclerosis (Kaplan et al., 1991), as well as increased risk for myocardial infarction (Muller et al., 1989). Besides the cardiovascular

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system, there are indications that metabolic disorders and abdominal obesity are increased at the lower end of the socioeconomic status gradient in Swedish males (Larsson et al., 1989). Immune system function is also a likely target (Cohen et al., 1992), with increased vulnerability to infections and possibly even to cancer, but there is far less evidence on this point. We have noted throughout this chapter that individuals respond in different ways to adversity and threats (real or implied) to their safety and homeostasis. Physiological responses of the autonomic nervous system, HPA axis, cardiovascular, metabolic, and immune systems lead to protection and adaptation of the organism to these challenges. This process, referred to as allostasis, is an essential component of maintaining homeostasis. However, adaptation to adversity has a price, and we have come to define the cost of adaptation as allostatic load (McEwen and Stellar, 1993). Much of our ability to make a breakthrough in understanding the linkage between behavior, brain function, and health depends on our making progress in defining and operationalizing the concept of allostatic load. Allostatic load is the wear and tear on the body and brain resulting from chronic overactivity or inactivity of physiological systems that are normally involved in adaptation to environmental challenge. Although it is true that physiological parameters such as blood oxygen and pH are maintained in a narrow range (homeostasis), the cardiovascular system, metabolic machinery, immune system, and central nervous system all show a large range of activity as a function of the time of day and in response to external and internal demands (allostasis). These systems are involved in coping and adaptation, and, as a general rule, they are most useful when they can be rapidly mobilized and then turned down in their activity again when not needed. It is when they are not turned off or turned down that these systems become dangerous for health. Moreover, the inability to turn on these systems when needed also produces a load on the body because the normal protection afforded by these systems is lacking. An important aspect of allostasis and allostatic load is the notion of anticipation (Schulkin et al., 1994). Although originally introduced in relation to explaining the reflex that prevents us from blacking out when we get out of bed in the morning (Sterling and Eyer, 1988), anticipation also implies psychological states, such as worry and anxiety, as well as cognitive preparation for a coming event. Because anticipation can drive the output of mediators (this is particularly true of hormones such as ACTH, cortisol, and adrenalin), it is likely that states of prolonged anxiety and anticipation can result in allostatic load (Schulkin et al., 1994). However, this is one of many notions that need experimental testing. Other important aspects of individual responses in relation to allostasis and allostatic load are the health-

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damaging and health-promoting behaviors such as smoking, drinking, choice of diet, and exercise. These may be regarded as part of the overall notion of allostasis—that is, how individuals attempt to cope with a challenge—and they also contribute in some ways that are known to allostatic load (for example, a rich diet accelerates atherosclerosis and progression to Type II diabetes; smoking exacerbates blood pressure and atherogenesis; exercise has an ameliorative effect). Types of allostatic load There are three types of physiological response that make up allostatic load. The first type is simply due to frequent stressors; for example, blood pressure surges not only trigger myocardial infarction (MI) in susceptible individuals, but their repetition also accelerates atherosclerosis and primes the risk for MI. Here, it is the frequency and intensity of the “hits” or events that determine how much allostatic load of this type, although frequent stress may lead into the other types described below as the body responds to repeated events by either failing to shut off neural and endocrine responses or failing to respond adequately. Posttraumatic stress disorder is an example of how an acute traumatic event leads to an HPA axis that may not respond adequately to acute challenge (Yehuda et al., 1991). The second type of allostatic load involved failure to turn off adaptive autonomic and neuroendocrine responses, for example, blood pressure elevations in repetitive, time-pressured work (Lundberg et al., 1989) and the fact that glucocorticoids accelerate obesity and Type II diabetes. Moreover, we have seen above that persistent glucocorticoid elevation and/or excitatory activity in brain causes dendritic remodeling and neuronal death in hippocampus. The third type of allostatic load is the failure to respond adequately to a challenge, for example, autoimmunity and inflammation that is associated with inadequate endogenous glucocorticoid responses, as in the Lewis rat (Sternberg et al., 1989) and possibly also in chronic fatigue syndrome and fibromyalgia (Griep et al., 1993; Crofford et al., 1994; Demitrack, 1996). In this situation, other systems—such as inflammatory cytokines—show elevated activity, and this respect shows an allostatic load because of the inadequate HPA activity, which normally “contains” their activity. Individuals showing these patterns are likely to be distributed differently across gradients of socioeconomic status but not confined exclusively to one part of the gradient. Thus it is important to distinguish between characteristics of groups and the vulnerability of individuals. It is necessary to study the biology–behavior interface to understand the forms of allostatic load and their relationship to diseases in individuals, while developing tools for recognizing how these traits are dis-

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tributed and what aspects of the various communities in which they live may contribute to their occurrence. Measurement of allostatic load One of the major challenges is how to measure allostatic load. An initial attempt in this direction (Seeman et al., 1997; McEwen and Seeman, 1999) used data from the MacArthur Successful Aging study to follow 10 measures of increased activity of allostatic systems between 1988 and 1991. Individuals were classified as to whether they were in the most extreme quartile (highest in systolic blood pressure; overnight urinary cortisol, catecholamines; waist/hip ratio; glycosylated hemoglobin; ratio cholesterol:high density lipoprotein [HDL]; lowest in dehydroepiandrosterone [DHEA]-sulfate and HDL cholesterol). The analysis indicated that individuals who were high functioning in 1988 had lower allostatic load scores than individuals who were lower functioning; moreover, those people who were higher functioning in 1988 who had the highest allostatic load scores (most extreme quartile in at least one or more allostatic load measures) had the highest probability of showing cardiovascular disease in 1991 and also showed the greatest decline in cognitive measures and measures of physical functioning (Seeman et al., 1997; Seeman et al., 2001). The cognitive decline was unexpected on the basis of traditional thinking about the allostatic load measures and risk for disease, but it is quite consistent with the picture that is painted in the present review and in other chapters in this volume. Clearly, this is just the beginning of this type of analysis, and much more needs to be done to test and operationalize the utility of allostatic load measures, as well as to broaden them to include immune system related disorders and the three types of allostatic load described above. How and why do allostatic systems malfunction and lead to allostatic load? Allostatic load refers to an imbalance in systems that promote adaptation. As noted above, this imbalance can simply be the result of too much repeated stress, but it also can be the result of adaptive systems that are out of balance and fail to shut off or, alternatively, systems that fail to turn on adequately. How does such imbalance arise? One possibility is that repeated stress causes systems to wear out or become exhausted, leading either to the failure of shut-off or failure to respond. As proposed by Sapolsky in the glucocorticoid cascade hypothesis of stress and aging (Sapolsky et al., 1986; Sapolsky, 1992), the wearing out of the mechanism that keeps HPA activity contained is likely to involve, at least in part, dysfunction of the hippocampus. Evidence to support this has been obtained in studies

of aging rats by finding that there are age-impaired animals with HPA hyperactivity and cognitive impairment (Meaney, Aitken, et al., 1988; Issa et al., 1990; Meaney et al., 1994). On the other extreme, we have noted the failure to mount an adequate HPA response is a feature of the Lewis rat that results in increased vulnerability to autoimmune and inflammatory disturbances (Sternberg et al., 1989; Sternberg et al., 1996). Such a hyporesponsive state may be induced by severe stress because we have found a stress-induced state of HPA hyporesponsiveness among rats that become subordinate in a psychosocial living situation called the “visible burrow system” (VBS) (Blanchard et al., 1993; Albeck et al., 1997). In these rats, there is a very limited HPA response to experimenter-applied stressors, and hypothalamic CRF mRNA levels are abnormally low (Albeck et al., 1997), and this is a condition that develops gradually during the 14-day VBS exposure, indicating that it is brought about in response to the severity of the stress and the individual responses to the stress. In summary, the same mediators that help the body and brain adapt to acute stressors (allostasis) are also involved in processes that impair function and exacerbate disease processes (allostatic load). POSITIVE AFFECT, SELF-ESTEEM, AND SOCIAL SUPPORT Not all stressful experiences are bad, and there are factors in the social environment and personalities of individuals that provide some buffering and resilience in the face of stressors. Having a positive outlook on life and good self-esteem appear to have long-lasting health consequences (Pressman and Cohen, 2005), and good social support is also a positive influence on the measures of allostatic load (Seeman et al., 2002). Positive affect, assessed by aggregating momentary experiences throughout a working or leisure day, was found to be associated with lower cortisol production and higher heart rate variability (showing higher parasympathetic activity), as well as a lower fibrinogen response to a mental stress test (Steptoe et al., 2005). On the other hand, poor self-esteem has been shown to cause recurrent increases in cortisol levels during a repetition of a public-speaking challenge in which those individuals with good self-esteem are able to habituate, that is, attenuate their cortisol response after the first speech (Kirschbaum et al., 1995). Furthermore, poor self-esteem and low internal locus of control have been related to 12%–13% smaller volume of the hippocampus, as well as higher cortisol levels during a mental arithmetic stressor (Pruessner et al., 1999; Pruessner et al., 2005). Related to positive affect and self-esteem is the role of friends and social interactions in maintaining a healthy

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outlook on life. Loneliness, often found in people with low self-esteem, has been associated with larger cortisol responses to wakening in the morning and higher fibrinogen and natural killer cell responses to a mental stress test, as well as sleep problems (Steptoe et al., 2004). On the other hand, having three or more regular social contacts, as opposed to none to two such contacts, is associated with lower allostatic load scores (Seeman et al., 2002). CONCLUSIONS The main thesis of this chapter is that the adult brain is a plastic and malleable organ and that changes brought about by the environment are largely beneficial to the individual. The hippocampus is a brain region in which this plasticity has been seen in various forms, ranging from replacement of neurons of the dentate gyrus, to synapse turnover in the estrous cycle of the female rat, to remodelling of dendrites in hibernation and after repeated psychosocial stress. We suspect that, although the hippocampus is exceptionally sensitive and vulnerable, the plasticity seen in the hippocampus is representative of plasticity going on to various extents in other brain regions as well. We have also seen that structural plasticity with stress goes on in the amygdala and regions of the PFC, with increases in dendritic branching and synapse density occurring in some regions and decreases in others. We have seen that the various forms of hippocampal plasticity occur as a result of an interaction between circulating hormones and endogenous neurotransmitters, especially, EAAs. This means that neural activity, and therefore the neural responses to experience, and the circulating hormonal environment that is also sensitive to experience are important regulators of adult plasticity. The existence of multiple regulators of this plasticity allows for a greater range of outcomes. N-methyl-D-aspartate receptors play a key role in regulating neurogenesis in dentate gyrus, synapse turnover on CA1 pyramidal neurons, and dendritic remodelling of CA3 neurons. Yet that is not all, and NMDA receptors are also involved in the developing nervous system as facilitators of neuronal migration (Komuro and Rakic, 1995). However, there is a noteworthy paradox, in that NMDA receptors are implicated in the developing visual system in reducing synaptic contact in the developing retinal axon arbors (Yen et al., 1995) and NMDA receptor blockade results in rapid acquisition of dendritic spines by visual thalamic neurons (J.E. Kerr et al., 1995). It seems that hippocampus and visual system neurons respond in opposite ways to NMDA receptors because a recent report on embryonic hippocampal neurons in culture indicated that NMDA

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receptor blockade prevents E-induced synaptogenesis (D.D. Murphy and Segal, 1996). Besides discussing plasticity, we have also noted the potentially damaging aspects of stressful experience and we have described two concepts: allostasis, the process of adaptation that maintains homeostasis, and allostatic load, the price the body pays for having to adapt to various challenges. The gradual wear and tear on tissues and organs of the body resulting from allostatic load is postulated to be a major factor in accelerating disease processes for which there is either a pathogen or a genetic predisposition. Allostatic load provides a more physiological conceptualization of the consequences of “chronic stress.” One of the implications of allostatic load is that the wear and tear is a form of “premature aging.” One of the features of the aging process is the loss of plasticity, and this has been reported for stress responsiveness of the aging HPA axis (reviewed in McEwen, 1992). Is this in fact the case for the types of plasticity described at the beginning of this article? In several cases we can say that there is a loss of plasticity with age. For example, the aging dentate gyrus loses the ability to replace granule neurons (Seki and Arai, 1995; Kuhn et al., 1996), although this suppression is reversed by ADX (Cameron and McKay, 1999) and, at least partially, by blocking NMDA receptors (Nacher et al., 2001). We also know that the ability of repeated stress to down-regulate GRs in the rat hippocampus is lost in aging rats, with the emergence of stress-induced neuronal thinning in the pyramidal cell layer (Landfield and Eldridge, 1994). We do not yet know whether aging increases or decreases stress-induced dendritic remodeling, and the answer to this question will help us know if atrophy and remodelling of dendrites of CA3 pyramidal neurons is the first step to damage or a protective mechanism. Because the atrophy does not affect the whole neuron, and is reversible, we believe that it represents a physiological adaptive mechanism to severe and recurrent stress. However, it is unclear if atrophy is the first stage that leads to neuronal death or a mechanism that protects neurons at the expense of some cognitive function. Insofar as the atrophy seen in CA3 pyramidal neurons is the tip of the iceberg, so to speak, and represents atrophy occurring throughout the hippocampus, this model is relevant to the atrophy of the human hippocampus that has been described in Cushing’s syndrome, normal aging, dementia, recurrent depressive illness, schizophrenia, and PTSD. In these cases, the problem is to distinguish between reversible atrophy and permanent cell loss because the former situation is potentially treatable at the time that the atrophy is discovered, whereas the latter may be preventable with earlier intervention at the time the initial trauma is taking place.

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REFERENCES Aberg, M.A.I., Aberg, N.D., Hedbacker, H., Oscarsson, J., and Eriksson, P.S. (2000) Peripheral infusion of IGF-1 selectively induces neurogenesis in the adult rat hippocampus. J. Neurosci. 20:2896–2903. Ahima, R., Krozowski, Z., and Harlan, R. (1991) Type I corticosteroid receptor-like immunoreactivity in the rat CNS: distribution and regulation by corticosteroids. J. Comp. Neurol. 313:522– 538. Ahima, R.S., and Harlan, R.E. (1990) Charting of type II glucocorticoid receptor-like immunoreactivity in the rat central nervous system. Neuroscience 39:579–604. Akana, S., Jacobson, L., Cascio, C., Shinsako, J., and Dallman, M. (1988) Constant corticosterone replacement normalizes basal adrenocorticotropin (ACTH) but permits sustained ACTH hypersecretion after stress in adrenalectomized rats. Endocrinology 122: 1337–1342. Akana, S.F., Chu, A., Soriano, L., and Dallman, M.F. (2001) Corticosterone exerts site-specific and state-dependent effects in prefrontal cortex and amygdala on regulation of adrenocorticotropic hormone, insulin and fat depots. J. Neuroendocrin. 13: 625–637. Akirav, I., and Richter-Levin, G. (1999) Biphasic modulation of hippocampal plasticity by behavioral stress and basolateral amygdala stimulation in the rat. J. Neurosci. 19:10530–10535. Albeck, D.S., McKittrick, C.R., Blanchard, D.C., Blanchard, R.J., Nikulina, J., McEwen, B.S., and Sakai, R.R. (1997) Chronic social stress alters expression of corticotrophin releasing factor and arginine vasopressin mRNA expression in rat brain. J. Neurosci. 17:4895–4903. Ardayfio, P., and Kim, K.-S. (2006) Anxiogenic-like effect of chronic corticosterone in the light-dark emergency task in mice. Behav. Neurosci. 120:249–256. Armstrong, J.D., McIntyre, D.C., Neubort, S., and Sloviter, R.S. (1993) Learning and memory after adrenalectomy-induced hippocampal dentate granule cell degeneration in the rat. Hippocampus 3:359– 371. Arnold, A., and Breedlove, S. (1985) Organizational and activational effects of sex steroids on brain and behavior: a reanalysis. Horm. Behav. 19:469–498. AusDerMuhlen, K., and Ockenfels, H. (1969) Morphologische veranderungen im diencephalon und telencephalon: storungen des regelkreises adenohypophysenebennierenrinde [Morphological alterations in the diencephalons and telencephalon: disturbance of the HPA axis]. Mikrosck. Anat. 93:126–141. Barnes, C., McNaughton, B., Goddard, G., Douglas, R., and Adamec, R. (1977) Circadian rhythm of synaptic excitability in rat and monkey central nervous system. Science 197:91–92. Bartanusz, V., Aubry, J.M., Pagliusi, S., Jezova, D., Baffi, J., and Kiss, J.Z. (1995) Stress-induced changes in messenger RNA levels of N-methyl-D-aspartate and Ampa receptor subunits in selected regions of the rat hippocampus and hypothalamus. Neuroscience 66:247–252. Beck, S.G., List, T.J., and Choi, K.C. (1994) Long- and short- term administration of corticosterone alters CA1 hippocampal neuronal properties. Neuroendocrinology 60:261–272. Bengzon, J., Kokaia, Z., Elmer, E., Nanobashvili, A., Kokaia, M., and Lindvall, O. (1997) Apoptosis and proliferation of dentate gyrus neurons after single and intermittent limbic seizures. Proc. Natl. Acad. Sci. USA 94:10432–10437. Birnstiel, S., and Beck, S.G. (1995) Modulation of the 5-hydroxytryptamine-4 receptor-mediated response by short-term and longterm administration of corticosterone in rat CA1 hippocampal pyramidal neurons. J. Pharm. Exp. Ther. 273:1132–1138. Birrell, J.M., and Brown, V.J. (2000) Medial frontal cortex mediates perceptual attentional set shifting in the rat. J. Neurosci. 20: 4320–4324.

Blanchard, D.C., Sakai, R.R., McEwen, B.S., Weiss, S.M., and Blanchard, R.J. (1993) Subordination stress: behavioral, brain and neuroendocrine correlates. Behav. Brain Res. 58:113–121. Blaustein, J.D., Lehman, M.N., Turcotte, J.C., and Greene, G. (1992) Estrogen receptors in dendrites and axon terminals in guinea pig hypothalamus. Endocrinology 131:281–290. Bliss, T.V.P., and Lomo, T. (1973) Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit following stimulation of the perforant path. J. Physiology 232: 331–356. Bobak, M., and Marmot, M. (1996) East-West mortality divide and its potential explanations: proposed research agenda. BMJ 312: 421–425. Bogerts, B., Lieberman, J.A., Ashtair, M., Bilder, R.M., De Greef, G., Lerner, G., Johns, C., and Masiar, S. (1993) Hippocampusamygdala volumes and psychopathology in chronic schizophrenia. Biol. Psychiatry 33:236–246. Bremner, J.D. (2002) Neuroimaging studies in post-traumatic stress disorder. Curr. Psychiatry Reports 4:254–263. Bremner, J.D., Randall, P., Scott, T.M., Bronen, R.A., Seibyl, J.P., Southwick, S.M., Delaney, R.C., McCarthy, G., Charney, D.S., and Innis, R.B. (1995) MRI-based measurement of hippocampal volume in patients with combat-related posttraumatic stress disorder. Am. J. Psychiatry 152:973–981. Brezun, J.M., and Daszuta, A. (1999) Depletion in serotonin decreases neurogenesis in the dentate gyrus and the subventricular zone of adult rats. Neuroscience 89:999–1002. Brezun, J.M., and Daszuta, A. (2000) Serotonin may stimulate granule cell proliferation in the adult hippocampus, as observed in rats grafted with foetal raphe neurons. Eur. J. Neurosci. 12:391–396. Brown, S.M., Henning, S., and Wellman, C.L. (2005) Mild, shortterm stress alters dendritic morphology in rat medial prefrontal cortex. Cereb. Cortex 30:1–9. Bulloch, K., Prasad, A., Conrad, C.D., McEwen, B.S., and Milner, T.A. (1996) Calcitonin gene-related peptide level in the rat dentate gyrus increases after damage. Neuroreport 7:1036–1040. Cameron, H.A., and Gould, E. (1996a) The control of neuronal birth and survival. In: Shaw, C.A., ed. Receptor Dynamics in Neural Development. New York: CRC Press, pp. 141–157. Cameron, H.A., and Gould, E. (1996b) Distinct populations of cells in the adult dentate gyrus undergo mitosis or apoptosis in response to adrenalectomy. J. Comp. Neurol. 369:56–63. Cameron, H.A., McEwen, B.S., and Gould, E. (1995) Regulation of adult neurogenesis by excitatory input and NMDA receptor activation in the dentate gyrus. J. Neurosci. 15:4687–4692. Cameron, H.A., and McKay, R.D.G. (1999) Restoring production of hippocampal neurons in old age. Nat. Neurosci. 2:894–897. Cammermeyer, J. (1978) Is the solitary dark neuron a manifestation of postmortem trauma to the brain inadequately fixed by perfusion? Histochemistry 56:97–115. Carro, E., Nunez, A., Busiguina, S., and Torres-Aleman, I. (2000) Circulating insulin-like growth factor I mediates effects of exercise on the brain. J. Neurosci. 20:2926–2933. Caspi, A., Sugden, K., Moffitt, T.E., Taylor, A., Craig, I.W., Harrington, H., McClay, J., Mill, J., Martin, J., Braithwaite, A., and Poulton, R. (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301:386–389. Cerqueira, J.J., Pego, J.M., Taipa, R., Bessa, J.M., Almeida, O.F.X., and Sousa, N. (2005) Morphological correlates of corticosteroidinduced changes in prefrontal cortex-dependent behaviors. J. Neurosci. 25:7792–7800. Choi, D.W. (1988) Glutamate neurotoxicity and diseases of the nervous system. Neuron 1:623–634. Clarke, C.H., Norfleet, A.M., Clarke, M.S.F., Watson, C.S., Cunningham, K.A., and Thomas, M.L. (2000) Perimembrane localization of the estrogen receptor protein in neuronal processes of cultured hippocampal neurons. Neuroendocrinology 71:34–42.

40: STRESS-INDUCED STRUCTURAL AND FUNCTIONAL PLASTICITY IN THE BRAIN Cohen, S., Kaplan, J.R., Cunnick, J.E., Manuck, S.B., and Rabin, B. S. (1992) Chronic social stress, affiliation and cellular immune response in nonhuman primates. Psychol. Sci. 3:301–304. Conrad, C.D., Magarinos, A.M., LeDoux, J.E., and McEwen, B.S. (1999) Repeated restraint stress facilitates fear conditioning independently of causing hippocampal CA3 dendritic atrophy. Behav. Neurosci. 113:902–913. Conrad, C.D., Magarinos, A.M., LeDoux, J.E., and McEwen, B.S. (1999) Repeated restraint stress facilitates fear conditioning independently of causing hippocampal CA3 dendritic atrophy. Behav. Neurosci. 113:902–913. Conrad, C.D., and Roy, E.J. (1995) Dentate gyrus destruction and spatial learning impairment after corticosteroid removal in young and middle-aged rats. Hippocampus 5:1–15. Convit, A., Wolf, O.T., Tarshish, C., and de Leon, M.J. (2003) Reduced glucose tolerance is associated with poor memory performance and hippocampal atrophy among normal elderly. Proc. Natl. Acad. Sci. USA 100:2019–2022. Cook, S.C., and Wellman, C.L. (2004) Chronic stress alters dendritic morphology in rat medial prefrontal cortex. J. Neurobiol. 60:236–248. Corodimas, K.P., LeDoux, J.E., Gold, P.W., and Schulkin, J. (1994) Corticosterone potentiation of learned fear. Ann. N. Y. Acad. Sci. 746:392. Crofford, L.J., Pillemer, S.R., Kalogeras, K., Cash, J.M., Michelson, D., Kling, M.A., Sternberg, E.M., Gold, P.W., Chrousos, G.P., and Wilder, R.L. (1994) Hypothalamic-pituitary-adrenal axis perturbations in patients with fibromyalgia. Arthritis Rheum. 37: 1583–1592. Crombag, H.S., Gorny, G., Li, Y., Kolb, B., and Robinson, T.E. (2005) Opposite effects of amphetamine self-administration experience on dendritic spines in the medial and orbital prefrontal cortex. Cereb. Cortex 15:341–348. Czeh, B., Michaelis, T., Watanabe, T., Frahm, J., de Biurrun, G., van Kampen, M., Bartolomucci, A., and Fuchs, E. (2001) Stressinduced changes in cerebral metabolites, hippocampal volume and cell proliferation are prevented by antidepressant treatment with tianeptine. Proc. Natl. Acad. Sci. USA 98:12796–12801. Dana, R.C., and Martinez, J.L. (1984) Effect of adrenalectomy on the circadian rhythm of LTP. Brain Res. 308:392–395. Datta, S.R., Brunet, A., and Greenberg, M.E. (1999) Cellular survival: a play in three Akts. Genes & Devel. 13:2905–2927. De Kloet, E.R., Azmitia, E.C., and Landfield, P.W. (1996) Brain corticosteroid receptors: studies on the mechanism, function, and neurotoxicity of corticosteroid action. Ann. N. Y. Acad. Sci. 746: 1–499. de Leon, M.J., Convit, A., Wolf, O.T., Tarshish, C.Y., DeSanti, S., Rusinek, H., Tsui, W., Kandil, E., Scherer, A.J., Roche, A., Imossi, A., Thorn, E., Bobinski, M., Caraos, C., Lesbre, P., Schlyer, D., Poirier, J., Reisberg, B., and Fowler, J. (2001) Prediction of cognitive decline in normal elderly subjects with 2-[18F]fluoro-2-deoxyD-glucose/positron-emission tomography (FDG/PET). Proc. Natl. Acad. Sci. USA 98:10966–10971. Delbende, C., Contesse, V., Mocaer, E., Kamoun, A., and Vaudry, H. (1991) The novel antidepressant, tianeptine, reduces stressevoked stimulation of the hypothalamo-pituitary-adrenal axis. Eur. J. Pharmacol. 202:391–396. Demitrack, M.A. (1996) Neuroendocrine research strategies in chronic fatigue syndrome. In: Goodnick, P.J., and Klimas, N.G., eds. Chronic Fatigue and Related Immune Deficiency Syndromes. Washington, DC: American Psychiatric Press, Inc, pp. 45–66. DeVoogd, T., and Nottebohm, F. (1981) Gonadal hormones induce dendritic growth in the adult avian brain. Science 214:202–204. Diamond, D.M., Bennett, M.C., Fleshner, M., and Rose, G.M. (1992) Inverted-U relationship between the level of peripheral corticosterone and the magnitude of hippocampal primed burst potentiation. Hippocampus 2:421–430.

647

Diamond, D.M., Fleshner, M., Ingersoll, N., and Rose, G.M. (1996) Psychological stress impairs spatial working memory: relevance to electrophysiological studies of hippocampal function. Behav. Neurosci. 110:661–672. Diamond, D.M., Fleshner, M., and Rose, G.M. (1994) Psychological stress repeatedly blocks hippocampal primed burst potentiation in behaving rats. Behav. Brain Res. 62:1–9. Diorio, D., Viau, V., and Meaney, M.J. (1993) The role of the medial prefrontal cortex (cingulate gyrus) in the regulation of hypothalamic-pituitary-adrenal responses to stress. J. Neurosci. 13: 3839–3847. DonCarlos, L.L., Monroy, E., and Morrell, J.I. (1991) Distribution of estrogen receptor-immunoreactive cells in the forebrain of the female guinea pig. J. Comp. Neurol. 305:591–612. Dore, S., Kar, S., and Quirion, R. (1997) Insulin-like growth factor I protects and rescues hippocampal neurons against beta-amyloid and human amylin-induced toxicity. Proc. Natl. Acad. Sci. USA 94:4772–4777. Dore, S., Kar, S., Rowe, W., and Quirion, R. (1997) Distribution and levels of [125I]IGF-I, [125I]IGF-II and [125I]insulin receptor binding sites in the hippocampus of aged memory-unimpaired and impaired rats. Neurosci. 80:1033–1040. Drevets, W.C., Price, J.L., Simpson, J.R. Jr, Todd, R.D., Reich, T., Vannier, M., and Raichle, M.E. (1997) Subgenual prefrontal cortex abnormalities in mood disorders. Nature 386:824–827. Driessen, M., Hermann, J., Stahl, K., Zwaan, M., Meier, S., Hill, A., Osterheider, M., and Petersen, D. (2000) Magnetic resonance imaging volumes of the hippocampus and the amygdala in women with borderline personality disorder and early traumatization. Arch. Gen. Psychiatry 57:1115–1122. Duman, R.S., Nakagawa, S., and Malberg, J. (2001) Regulation of adult neurogenesis by antidepressant treatment. Neuropsychopharmacology 25:836–844. Dunn, J., and Orr, S. (1984) Differential plasma corticosterone responses to hippocampal stimulation. Exp. Brain Res. 54:1–6. Eichenbaum, H., and Otto, T. (1992) The hippocampus - what does it do? Behav. Neural. Biol. 57:2–36. Eriksson, P.S., Permlieva, E., Bjork-Eriksson, T., Alborn, A.-M., Nordborg, C., Peterson, D.A., and Gage, F.H. (1998) Neurogenesis in the adult human hippocampus. Nat. Med. 4:1313–1317. Evans, R.M., and Arriza, J.L. (1989) A molecular framework for the actions of glucocorticoid hormones in the nervous system. Neuron 2:1105–1112. Ferrie, J.E., Shipley, M.J., Stansfeld, S.A., and Marmot, M.G. (2002) Effects of chronic job insecurity and change in job security on self reported health, minor psychiatric morbidity, physiological measures, and health related behaviours in British civil servants: the Whitehall II study. J. Epidemiol. Community Health 56:450–454. Franklin, T.B., and Perrot-Sinal, T.S. (2006) Sex and ovarian steroids modulate brain-derived neurotrophic factor (BDNF) protein levels in rat hippocampus under stressful and non-stressful conditions. Psychoneuroendocrinology 31:38–48. Freund, T.F., and Buzsaki, G. (1996) Interneurons of the hippocampus. Hippocampus 6:345–470. Frodl, T., Meisenzahl, E.M., Zetzsche, T., Born, C., Jager, M., Groll, C., Bottlender, R., Leinsinger, G., and Moller, H.-J. (2003) Larger amygdala volumes in first depressive episode as compared to recurrent major depression and healthy control subjects. Biol. Psychiatry 53:338–344. Fuchs, E., and Gould, E. (2000) Mini-review: in vivo neurogenesis in the adult brain: regulation and functional implications. Eur. J. Neurosci. 12:2211–2214. Fuchs, E., Uno, H., and Flugge, G. (1995) Chronic psychosocial stress induces morphological alterations in hippocampal pyramidal neurons of the tree shrew. Brain Res. 673:275–282. Fukuzako, H., Fukuzako, T., Hashiguchi, T., Hokazono, Y., Takeuchi, K., Hirakawa, K., Ueyama, K., Takigawa, M., Kajiya, Y., Nakajo, M.,

648

ANXIETY DISORDERS

and Fujimoto, T. (1996) Reduction in hippocampal formation volume is caused mainly by its shortening in chronic schizophrenia: Assessment by MRI. Biol. Psychiatry 39:938–945. Galea, L.A.M., Kavaliers, M., Ossenkopp, K.-P., Innes, D., and Hargreaves, E.L. (1994) Sexually dimorphic spatial learning varies seasonally in two populations of deer mice. Brain Res. 635:18–26. Galea, L.A.M., and McEwen, B.S. (1999) Sex and seasonal differences in the rate of cell proliferation in the dentate gyrus of adult wild meadow voles. Neuroscience 89:955–964. Galea, L.A.M., Tanapat, P., and Gould, E. (1996) Exposure to predator odor suppresses cell proliferation in the dentate gyrus of adult rats via a cholinergic mechanism. Abstract, Soc. Neurosci. 22:474.8. Gazzaley, A.H., Weiland, N.G., McEwen, B.S., and Morrison, J.H. (1996) Differential regulation of NMDAR1 mRNA and protein by estradiol in the RAt hippocampus. J. Neurosci. 16:6830– 6838. Ghashghaei, H.T., and Barbas, H. (2002) Pathways for emotion: Interactions of prefrontal and anterior temporal pathways in the amygdala of the Rhesus monkey. Neuroscience 115:1261–1279. Gleichmann, M., Weller, M., and Schulz, J.B. (2000) Insulin-like growth factor-1 mediated protection from neuronal apoptosis is linked to phosphorylation of the pro-apoptotic protein BAD but not to inhibition of cytochrome c translocation in rat cerebellar neurons. Neurosci. Lett. 282:69–72. Golomb, J., DeLeon, M.J., George, A.E., Kluger, A., Convit, A., Rusinek, H., DeSanti, S., Litt, A., Foo, S.H., and Ferris, S.H. (1994) Hippocampal atrophy correlates with severe cognitive impairment in elderly patients with suspected normal pressure hydrocephalus. J. Neurol. Neurosurg. Psychiatry 57:590–593. Gong, C., Wang, T.-W., Huang, H.S., and Parent, J.M. (2007) Reelin regulates neuronal progenitor migration in intact and epileptic hippocampus. J. Neurosci. 27:1803–1811. Gould, E. (1999) Serotonin and hippocampal neurogenesis. Neuropsychopharmacology 21:46S–51S. Gould, E., Beylin, A., Tanapat, P., Reeves, A., and Shors, T.J. (1999) Learning enhances adult neurogenesis in the hippocampal formation. Nat. Neurosci. 2:260–265. Gould, E., and McEwen, B.S. (1993) Neuronal birth and death. Curr. Opin. Neurobiol. 3:676–682. Gould, E., McEwen, B.S., Tanapat, P., Galea, L.A.M., and Fuchs, E. (1997) Neurogenesis in the dentate gyrus of the adult tree shrew is regulated by psychosocial stress and NMDA receptor activation. J. Neurosci. 17:2492–2498. Gould, E., and Tanapat, P. (1997) Lesion-induced proliferation of neuronal progenitors in the dentate gyrus of the adult rat. Neuroscience 80:427–436. Gould, E., Tanapat, P., and Cameron, H.A. (1997) Adrenal steroids suppress granule cell death in the developing dentate gyrus through an NMDA receptor-dependent mechanism. Devel. Brain Res. 103:91–93. Gould, E., Tanapat, P., and McEwen, B.S. (1997) Activation of the type 2 adrenal steroid receptor can rescue granule cells from death during development. Devel. Brain Res. 101:265–268. Gould, E., Tanapat, P., McEwen, B.S., Flugge, G., and Fuchs, E. (1998) Proliferation of granule cell precursors in the dentate gyrus of adult monkeys is diminished by stress. Proc. Natl. Acad. Sci. USA 95:3168–3171. Gould, E., Vail, N., Wagers, M., and Gross, C.G. (2001) Adult-generated hippocampal and neocortical neurons in macaques have a transient existence. Proc. Natl. Acad. Sci. USA 98:10910–10917. Gould, E., Westlind-Danielsson, A., Frankfurt, M., and McEwen, B.S. (1990) Sex differences and thyroid hormone sensitivity of hippocampal pyramidal neurons. J. Neurosci. 10:996–1003. Gould, E., Woolley, C., and McEwen, B.S. (1990) Short-term glucocorticoid manipulations affect neuronal morphology and survival in the adult dentate gyrus. Neuroscience 37:367–375.

Govindarajan, A., Rao, B.S.S., Nair, D., Trinh, M., Mawjee, N., Tonegawa, S., and Chattarji, S. (2006) Transgenic brain-derived neurotrophic factor expression causes both anxiogenic and antidepressant effects. Proc. Natl. Acad. Sci. USA 103:13208– 13213. Greenough, W.T., and Bailey, C.H. (1988) The anatomy of a memory: convergence of results across a diversity of tests. Trends Neurosci. 11:142–147. Griep, E.N., Boersma, J.W., and De Kloet, E.R. (1993) Altered reactivity of the hypothalamic-pituitary-adrenal axis in the primary fibromyalgia syndrome. J. Rheumatol. 20:469–474. Gurvits, T.V., Shenton, M.E., Hokama, H., Ohta, H., Lasko, N.B., Gilbertson, M.W., Orr, S.P., Kikinis, R., Jolesz, F.A., McCarley, R.W., and Pitman, R.K. (1996) Magnetic resonance imaging study of hippocampal volume in chronic, combat-related posttraumatic stress disorder. Biol. Psychiatry 40:1091–1099. Haan, M.N. (2006) Therapy insight: type 2 diabetes mellitus and the risk of late-onset Alzheimer’s disease. Nat. Clin. Prac. Neurol. 2: 159–166. Hagihara, K., Hirata, S., Osada, T., Hirai, M., and Kato, J. (1992) Distribution of cells containing progesterone receptor mRNA in the female rat di- and telencephalon: an in situ hybridization study. Mol. Brain Res. 14:239–249. Herman, J.P., Prewitt, C.M.F., and Cullinan, W.E. (1996) Neuronal circuit regulation of the hypothalamo-pituitary-adrenocortical stress axis. Crit. Rev. Neurobiol. 10:371–394. Hesen, W., and Joels, M. (1996a) Carbachol responsiveness of rat CA1 hippocampal neurons in vitro: Modulation by corticosterone and stress. Stress 1:63–72. Hesen, W., and Joels, M. (1996b) Modulation of 5HT1A responsiveness in CA1 pyramidal neurons by in vivo activation of corticosteroid receptors. J. Neuroendocrinol. 8:433–438. Het, S., and Wolf, O.T. (2007) Mood changes in response to psychosocial stress in healthy young women: effects of pretreatment with cortisol. Behav. Neurosci. 121:11–20. Hsu, M., and Buzsaki, G. (1993) Vulnerability of mossy fiber targets in the rat hippocampus to forebrain ischemia. J. Neurosci. 13: 3964–3979. Huang, G.-J., and Herbert, J. (2005) Serotonin modulates the suppressive effects of corticosterone on proliferating progenitor cells in the dentate gyrus of the hippocampus in the adult rat. Neuropsychopharmacology 30:231–241. Huang, G.-J., and Herbert, J. (2006) Stimulation of neurogenesis in the hippocampus of the adult rat by fluoxetine requires rhythmic change in corticosterone. Biol. Psychiatry 59:619–624. Ikegaya, Y., Saito, H., and Abe, K. (1994) Attenuated hippocampal long-term potentiation in basolateral amygdala-lesioned rats. Brain Res. 656:157–164. Ikegaya, Y., Saito, H., and Abe, K. (1995) High-frequency stimulation of the basolateral amygdala facilitates the induction of longterm potentiation in the dentate gyrus in vivo. Neurosci. Res. 22:203–207. Ikegaya, Y., Saito, H., and Abe, K. (1996) Dentate gyrus field potentials evoked by stimulation of the basolateral amygdaloid nucleus in anesthetized rats. Brain Res. 718:53–60. Islam, A., Ayer-LeLievre, C., Heigenskold, C., Bogdanovic, N., Winblad, B., and Adem, A. (1998) Changes in IGF-1 receptors in the hippocampus of adult rats after long-term adrenalectomy: receptor autoradiography and in situ hybridization histochemistry. Brain Res. 797:342–346. Issa, A., Rowe, W., Gauthier, S., and Meaney, M. (1990) Hypothalamic-pituitary-adrenal activity in aged, cognitively impaired and cognitively unimpaired rats. J. Neurosci. 10:3247–3254. Jacobson, L., Akana, S.F., Cascio, C.S., Shinsako, J., and Dallman, M.F. (1988) Circadian variations in plasma corticosterone permit normal termination of adrenocorticotropin responses to stress. Endocrinology 122:1343–1348.

40: STRESS-INDUCED STRUCTURAL AND FUNCTIONAL PLASTICITY IN THE BRAIN Jacobson, L., and Sapolsky, R. (1991) The role of the hippocampus in feedback regulation of the hypothalamic-pituitary-adrenocortical axis. Endocr. Rev. 12:118–134. Joels, M. (1997) Steroid hormones and excitability in the mammalian brain. Front. Neuroendocrinol. 18:2–48. Joels, M., Bosma, A., Hendriksen, H., Diegenbach, P., and Kamphuis, W. (1996) Corticosteroid actions on the expression of kainate receptor subunit mRNAs in rat hippocampus. Mol. Brain Res. 37: 15–20. Joels, M., and De Kloet, E.R. (1994) Mineralocorticoid and glucocorticoid receptors in the brain. Implications for ion permeability and transmitter systems. Progr. Neurobiol. 43:1–36. Kaplan, J.R., Pettersson, K., Manuck, S.B., and Olsson, G. (1991) Role of sympathoadrenal medullary activation in the initiation and progression of atherosclerosis. Circulation 84(Suppl 6):VI23– VI32. Karst, H., Berger, S., Turiault, M., Tronche, F., Schutz, G., and Joels, M. (2005) Mineralocorticoid receptors are indispensable for nongenomic modulation of hippocampal glutamate transmission by corticosterone. Proc. Natl. Acad. Sci. USA 102:19204–19207. Kelly, M.J., and Levin, E.R. (2001) Rapid actions of plasma membrane estrogen receptors. Trends Endo. Metab. 12:152–156. Kempermann, G., Kuhn, H.G., and Gage, F.H. (1997) More hippocampal neurons in adult mice living in an enriched environment. Nature 586:493–495. Kendler, K.S. (1998) Major depression and the environment: a psychiatric genetic perspective. Pharmacopsychiatry 31:5–9. Kerr, D., and Campbell, L. (1992) Hippocampal glucocorticoid receptor activation enhances voltage-dependent calcium conductances: relevance to brain aging. Proc. Natl. Acad. Sci. USA 89: 8527–8531. Kerr, J.E., Allore, R.J., Beck, S.G., and Handa, R.J. (1995) Distribution and hormonal regulation of androgen receptor (AR) and AR messenger ribonucleic acid in the rat hippocampus. Endocrinology 136:3213–3221. Kerr, S., Campbell, L., Applegate, M., Brodish, A., and Landfield, P. (1991) Chronic stress-induced acceleration of electrophysiologic and morphometric biomarkers of hippocampal aging. J. Neurosci. 11:1316–1324. Kessler, R.C. (1997) The effects of stressful life events on depression. Annu. Rev. Psychol. 48:191–214. Kim, J.J., Koo, J.W., Lee, H.J., and Han, J.-S. (2005) Amygdalar inactivation blocks stress-induced impairments in hippocampal longterm potentiation and spatial memory. J. Neurosci. 25:1532– 1539. Kirschbaum, C., Prussner, J.C., Stone, A.A., Federenko, I., Gaab, J., Lintz, D., Schommer, N., and Hellhammer, D.H. (1995) Persistent high cortisol responses to repeated psychological stress in a subpopulation of healthy men. Psychosom. Med. 57:468–474. Knigge, K. (1961) Adrenocortical response to stress in rats with lesions in hippocampus and amygdala. Proc. Soc. Exp. Biol. Med. 180:18–20. Komuro, H., and Rakic, P. (1995) Modulation of neuronal migration by NMDA receptors. Science 260:95–97. Korte, S.M. (2001) Corticosteroids in relation to fear, anxiety and psychopathology. Neurosci. & Biobehav. Rev. 25:117–142. Kreibich, A.S., and Blendy, J.A. (2004) cAMP response elementbinding protein is required for stress but not cocaine-induced reinstatement. J. Neurosci. 24:6686–6692. Kuhn, G.H., Dickinson-Anson, H., and Gage, F.H. (1996) Neurogenesis in the dentate gyrus of the adult rat: age-related decrease of neuronal progenitor proliferation. J. Neurosci. 16:2027– 2033. Kuroda, Y., and McEwen, B.S. (1998) Effect of chronic restraint stress and tianeptine on growth factors, GAP-43 and MAP2 mRNA expression in the rat hippocampus. Mol. Brain Res. 59: 35–39.

649

Lai, M., Hibberd, C.J., Gluckman, P.D., and Seckl, J.R. (2000) Reduced expression of insulin-like growth factor 1 messenger RNA in the hippocampus of aged rats. Neurosci. Lett. 288:66–70. Landfield, P. (1987) Modulation of brain aging correlates by longterm alterations of adrenal steroids and neurally-active peptides. Prog. Brain Res. 72:279–300. Landfield, P.W., and Eldridge, J.C. (1994) Evolving aspects of the glucocorticoid hypothesis of brain aging: hormonal modulation of neuronal calcium homeostasis. Neurobiol. Aging 15:579–588. Larsson, B., Seidell, J., Svardsudd, K., Welin, L., Tibblin, G., Wilhelmesen, L., and Bjorntorp, P. (1989) Obesity, adipose tissue distribution and health in men-the study of men born in 1913. Appetite 13:37–44. Laugero, K.D., Bell, M.E., Bhatnagar, S., Soriano, L., and Dallman, M.F. (2001) Sucrose ingestion normalizes central expression of corticotropin-releasing-factor messenger ribonucleic acid and energy balance in adrenalectomized rats: a glucocorticoid-metabolicbrain axis? Endocrinology 142:2796–2804. LeDoux, J.E. (1995) In search of an emotional system in the brain: leaping from fear to emotion and consciousness. In: Gazzaniga M, ed. The Cognitive Neurosciences. Cambridge, MA: MIT Press, pp. 1049–1061. Lee, S.J., Dunlop, J.C., Alves, S.E., Brake, W.G., and McEwen, B.S. (2000) PCREB immunoreactivity in the rat hippocampus following estrogen treatment: In vivo and in vitro studies. Abstracts Soc. Neurosci. 26:294. Leuner, B., Gould, E., and Shors, T.J. (2006) Is there a link between adult neurogenesis and learning? Hippocampus 26:216–224. Liston, C., Miller, M.M., Goldwater, D.S., Radley, J.J., Rocher, A.B., Hof, P.R., Morrison, J.H., and McEwen, B.S. (2006) Stress-induced alterations in prefrontal cortical dendritic morphology predict selective impairments in perceptual attentional set-shifting. J. Neurosci. 26:7870–7874. Lowy, M.T., Gault, L., and Yamamoto, B.K. (1993) Adrenalectomy attenuates stress-induced elevations in extracellular glutamate concentrations in the hippocampus. J. Neurochem. 61:1957–1960. Lowy, M.T., Wittenberg, L., and Yamamoto, B.K. (1995) Effect of acute stress on hippocampal glutamate levels and spectrin proteolysis in young and aged rats. J. Neurochem. 65:268–274. Loy, R., Gerlach, J., and McEwen, B.S. (1988) Autoradiographic localization of estradiol-binding neurons in rat hippocampal formation and entorhinal cortex. Dev. Brain Res. 39:245–251. Lundberg, U., Granqvist, M., Hansson, T., Magnusson, M., and Wallin, L. (1989) Psychological and physiological stress responses during repetitive work at an assembly line. Work & Stress 3: 143–153. Lupien, S.J., and McEwen, B.S. (1997) The acute effects of corticosteroids on cognition: integration of animal and human model studies. Brain Res. Rev. 24:1–27. Lynch, C.D., Lyons, D., Khan, A., Bennett, S.A., and Sonntag, W.E. (2001) Insulin-like growth factor-1 selectively increases glucose utilization in brains of aged animals. Endocrinology 142:506– 509. MacQueen, G.M., Campbell, S., McEwen, B.S., Macdonald, K., Amano, S., Joffe, R.T., Nahmias, C., and Young, L.T. (2003) Course of illness, hippocampal function, and hippocampal volume in major depression. Proc. Natl. Acad. Sci. USA 100:1387–1392. Maehlen, J., and Torvik, A. (1990) Necrosis of granule cells of hippocampus in adrenocortical failure. Acta Neuropathol. 80: 85–87. Magarinos, A.M., Deslandes, A., and McEwen, B.S. (1999) Effects of antidepressants and benzodiazepine treatments on the dendritic structure of CA3 pyramidal neurons after chronic stress. Eur. J. Pharm. 371:113–122. Magarinos, A.M., and McEwen, B.S. (1995a) Stress-induced atrophy of apical dendrites of hippocampal CA3c neurons: comparison of stressors. Neuroscience 69:83–88.

650

ANXIETY DISORDERS

Magarinos, A.M., and McEwen, B.S. (1995b) Stress-induced atrophy of apical dendrites of hippocampal CA3c neurons: involvement of glucocorticoid secretion and excitatory amino acid receptors. Neuroscience 69:89–98. Magarinos, A.M., McEwen, B.S., Flugge, G., and Fuchs, E. (1996) Chronic psychosocial stress causes apical dendritic atrophy of hippocampal CA3 pyramidal neurons in subordinate tree shrews. J. Neurosci. 16:3534–3540. Magarinos, A.M., McEwen, B.S., Saboureau, M., and Pevet, P. (2006) Rapid and reversible changes in intrahippocampal connectivity during the course of hibernation in European hamsters. Proc. Natl. Acad. Sci. USA 49:18775–18780. Magarinos, A.M., Verdugo Garcia, J.M., and McEwen, B.S. (1997) Chronic restraint stress alters synaptic terminal structure in hippocampus. Proc. Natl. Acad. Sci. USA 94:14002–14008. Makino, S., Gold, P.W., and Schulkin, J. (1994) Corticosterone effects on corticotropin-releasing hormone mRNA in the central nucleus of the amygdala and the parvocellular region of the paraventricular nucleus of the hypothalamus. Brain Res. 640:105–112. Malberg, J.E., Eisch, A.J., Nestler, E.J., and Duman, R.S. (2000) Chronic antidepressant treatment increases neurogenesis in adult rat hippocampus. J. Neurosci. 20:9104–9110. Markowska, A.L., Mooney, M., and Sonntag, W.E. (1998) Insulinlike growth factor-1 ameliorates age-related behavioral deficits. Neuroscience 87:559–569. Matys, T., Pawlak, R., Matys, E., Pavlides, C., McEwen, B.S., and Strickland, S. (2004) Tissue plasminogen activator promotes the effects of corticotropin releasing factor on the amygdala and anxiety-like behavior. Proc. Natl. Acad. Sci. USA 101:16345– 16350. McDonald, A.J. (1987) Organization of amygdaloid projections to the mediodorsal thalamus and prefrontal cortex: a fluorescence retrograde transport study in the rat. J. Comp. Neurol. 262:46–58. McDonald, A.J., Mascagni, F., and Guo, L. (1996) Projections of the medial and lateral prefrontal cortices to the amygdala: a Phaseolus vulgaris leucoagglutinin study in the rat. Neuroscience 71:55–75. McEwen, B.S. (1977) Adrenal steroid feedback on neuroendocrine tissues. Ann. N.Y. Acad. Sci. 297:568–579. McEwen, B.S. (1992) Re-examination of the glucocorticoid cascade hypothesis of stress and aging. In: Swaab, D., Hoffman, M., Mirmiran, R., Ravid, F., van Leeuwen, F., eds. Progress in Brain Research. Amsterdam: Elsevier, pp. 365–383. McEwen, B.S. (1999) Stress and hippocampal plasticity. Annu. Rev. Neurosci. 22:105–122. McEwen, B.S., Akama, K., Alves, S., Brake, W.G., Bulloch, K., Lee, S., Li, C., Yuen, G., and Milner, T.A. (2001) Tracking the estrogen receptor in neurons: implications for estrogen-induced synapse formation. Proc. Natl. Acad. Sci. USA 98:7093–7100. McEwen, B.S., Albeck, D., Cameron, H., Chao, H.M., Gould, E., Hastings, N., Kuroda, Y., Luine, V., Magarinos, A.M., McKittrick, C.R., Orchinik, M., Pavlides, C., Vaher, P., Watanabe, Y., and Weiland, N. (1995) Stress and the brain: a paradoxical role for adrenal steroids. In: Litwack, G.D., ed. Vitamins and Hormones. Academic Press, Inc., pp. 371–402. McEwen, B.S., Gould, E., Orchinik, M., Weiland, N.G., and Woolley, C.S. (1995) Oestrogens and the structural and functional plasticity of neurons: implications for memory, ageing and neurodegenerative processes. In: Goode, J., ed. Ciba Foundation Symposium #191 The Non-reproductive Actions of Sex Steroids. London: CIBA Foundation, pp. 52–73. McEwen, B.S., and Seeman, T. (1999) Protective and damaging effects of mediators of stress: elaborating and testing the concepts of allostasis and allostatic load. Ann. N.Y. Acad. Sci. 896:30–47. McEwen, B.S., and Stellar, E. (1993) Stress and the individual: mechanisms leading to disease. Arch. Int. Med. 153:2093–2101.

McEwen, B.S., Weiss, J., and Schwartz, L. (1968) Selective retention of corticosterone by limbic structures in rat brain. Nature 220: 911–912. McEwen, B.S., and Woolley, C.S. (1994) Estradiol and progesterone regulate neuronal structure and synaptic connectivity in adult as well as developing brain. Exp. Gerontol. 29:431–436. McKittrick, C.R., Magarinos, A.M., Blanchard, D.C., Blanchard, R.J., McEwen, B.S., and Sakai, R.R. (2000) Chronic social stress reduces dendritic arbors in CA3 of hippocampus and decreases binding to serotonin transporter sites. Synapse 36:85–94. Meaney, M., Aitken, D., Berkel, H., Bhatnagar, S., and Sapolsky, R. (1988) Effect of neonatal handling of age-related impairments associated with the hippocampus. Science 239:766–768. Meaney, M., Viau, V., Aitken, D., and Bhatnagar, S. (1988) Stressinduced occupancy and translocation of hippocampal glucocorticoid receptors. Brain Res. 445:198–203. Meaney, M.J., Tannenbaum, B., Francis, D., Bhatnagar, S., Shanks, N., Viau, V., O’Donnell, D., and Plotsky, P.M. (1994) Early environmental programming hypothalamic-pituitary-adrenal responses to stress. Sem. Neurosci. 6:247–259. Melchor, J.P., Pawlak, R., and Strickland, S. (2003) The tissue plasminogen activator - plasminogen proteolytic cascade accelerates amyloid-b (Ab) degradation and inhibits Ab-induced neurodegeneration. J. Neurosci. 23:8867–8871. Melin, B., Lundberg, U., Soderlund, J., and Granqvist, M. (1999) Psychological and physiological stress reactions of male and female assembly workers: a comparison between two different forms of work organization. J. Organiz. Behav. 20: 47–61. Mennini, T., and Miari, A. (1991) Modulation of (3H) glutamate binding by seratonin in the rat hippocampus: an autoradiographic study. Life Sci. 49:283–292. Milad, M.R., and Quirk, G.J. (2002) Neurons in medial prefrontal cortex signal memory for fear extinction. Nature 420:70–74. Milner, T.A., McEwen, B.S., Hayashi, S., Li, C.J., Reagen, L., and Alves, S.E. (2001) Ultrastructural evidence that hippocampal alpha estrogen receptors are located at extranuclear sites. J. Comp. Neurol. 429:355–371. Miner, J.N., and Yamamoto, K.R. (1991) Regulatory crosstalk at composite response elements. Trends Biochem. Sci. 16:423–426. Miracle, A.D., Brace, M.F., Huyck, K.D., Singler, S.A., and Wellman, C.L. (2006) Chronic stress impairs recall of extinction of conditioned fear. Neurobiol. Learn. Mem. 85:213–218. Mizoguchi, K., Kunishita, T., Chui, D.H., and Tabira, T. (1992) Stress induces neuronal death in the hippocampus of castrated rats. Neurosci. Letts. 138:157–160. Moghaddam, B., Boliano, M.L., Stein-Behrens, B., and Sapolsky, R. (1994) Glucocorticoids mediate the stress-induced extracellular accumulation of glutamate. Brain Res. 655:251–254. Monaghan, D.T., Holets, V.R., Toy, D.W., and Cotman, C.W. (1983) Anatomical distributions of four pharmacologically distinct 3HL-glutamate binding sites. Nature 306:176–179. Morgan, M.A., and LeDoux, J.E. (1995) Differential contribution of dorsal and ventral medial prefrontal cortex to the acquisition and extinction of conditioned fear in rats. Behav. Neurosci. 109: 681–688. Muller, J.E., Tofler, G., and Stone, P. (1989) Circadian variation and triggers of onset of acute caridovascular disease. Circulation 79:733–743. Murphy, B.E.P. (1991) Treatment of major depression with steroid suppressive drugs. J. Steroid Biochem. Molec. Biol. 39:239–244. Murphy, D.D., Cole, N.B., Greenberger, V., and Segal, M. (1998) Estradiol increases dendritic spine density by reducing GABA neurotransmission in hippocampal neurons. J. Neurosci. 18: 2550–2559. Murphy, D.D., Cole, N.B., and Segal, M. (1998) Brain-derived neurotrophic factor mediates estradiol-induced dendritic spine for-

40: STRESS-INDUCED STRUCTURAL AND FUNCTIONAL PLASTICITY IN THE BRAIN mation in hippocampal neurons. Proc. Natl. Acad. Sci. USA 95: 11412–11417. Murphy, D.D., and Segal, M. (1996) Regulation of dendritic spine density in cultured rat hippocampal neurons by steroid hormones. J. Neurosci. 16:4059–4068. Murphy, D.D., and Segal, M. (1997) Morphological plasticity of dendritic spines in central neurons is mediated by activation of cAMP response element binding protein. Proc. Natl. Acad. Sci. USA 94:1482–1487. Nacher, J., and McEwen, B.S. (2006) The role of N-methyl-D-aspartate receptors in neurogenesis. Hippocampus 16:267–270. Nacher, J., Rosell, D.R., Alonso-Llosa, G., and McEwen, B.S. (2001) NMDA receptor antagonist treatment induces a long-lasting increase in the number of proliferating cells, PSA-NCAM-immunoreactive granule neurons and radial glia in the adult rat dentate gyrus. Eur. J. Neurosci. 13:512–520. Nakamura, N.H., and McEwen, B.S. (2005) Changes in interneuronal phenotypes regulated by estradiol in the adult rat hippocampus: A potential role for neuropeptide Y. Neuroscience 136:357– 369. Noguchi, S., Higashi, K., and Kawamura, M. (1990) A posssible role of the a-subunit of (Na,K)-ATPase in facilitating correct assembly of the b-subunit into the membrane. J. Biol. Chem. 265: 5991–5995. Ohl, F., and Fuchs, E. (1999) Differential effects of chronic stress on memory processes in the tree shrew. Cog. Brain Res. 7:379–387. O’Kusky, J.R., Ye, P., and D’Ercole, A.J. (2000) Insulin-like growth factor-1 promotes neurogenesis and synaptogenesis in the hippocampal dentate gyrus during postnatal development. J. Neurosci. 20:8435–8442. Orchinik, M., Carroll, S.S., Li, Y.-H., McEwen, B.S., and Weiland, N.G. (2001) Heterogeneity of hippocampal GABAA receptors: regulation by corticosterone. J. Neurosci. 21:330–339. Orchinik, M., Weiland, N.G., and McEwen, B.S. (1994) Adrenalectomy selectively regulates GABAa receptor subunit expression in the hippocampus. Mol. Cell. Neurosci. 5:451–458. Ott, A., Stolk, R.P., Hofman, A., van Harskamp, F., Grobbee, D.E., and Breteler, M.M.B. (1996) Association of diabetes mellitus and dementia: The Rotterdam study. Diabetologia 39:1392–1397. Parent, J.M., Janumpalli, S., McNamara, J.O., and Lowenstein, D.H. (1998) Increased dentate granule cell neurogenesis following amygdala kindling in the adult rat. Neurosci. Lett. 247:9–12. Parent, J.M., Yu, T.W., Leibowitz, R.T., Geschwind, D.H., Sloviter, R.S., and Lowenstein, D.H. (1997) Dentate granule cell neurogenesis is increased by seizures and contributes to aberrant network reorganization in the adult rat hippocampus. J. Neurosci. 17:3727–3738. Parnavelas, J., Lynch, G., Brecha, N., Cotman, C., and Globus, A. (1974) Spine loss and regrowth in hippocampus following deafferentation. Nature 248:71–73. Parsons, B., Rainbow, T.C., MacLusky, N., and McEwen, B.S. (1982) Progestin receptor levels in rat hypothalamic and limbic nuclei. J. Neurosci. 2:1446–1452. Pavlides, C., Kimura, A., Magarinos, A.M., and McEwen, B.S. (1994) Type I adrenal steroid receptors prolong hippocampal long-term potentiation. Neuroreport 5:2673–2677. Pavlides, C., Kimura, A., Magarinos, A.M., and McEwen, B.S. (1995) Hippocampal homosynaptic long-term depression/depotentiation induced by adrenal steroids. Neuroscience 68:379–385. Pavlides, C., and McEwen, B.S. (1999) Effects of mineralocorticoid and glucocorticoid receptors on long-term potentiation in the CA3 hippocampal field. Brain Res. 851:204–214. Pavlides, C., Ogawa, S., Kimura, A., and McEwen, B. (1996) Role of adrenal steroid mineralocorticoid and glucocorticoid receptors in long-term potentiation in the CA1 field of hippocampal slices. Brain Res. 738:229–235.

651

Pavlides, C., Watanabe, Y., Magarinos, A.M., and McEwen, B.S. (1995) Opposing role of adrenal steroid Type I and Type II receptors in hippocampal long-term potentiation. Neuroscience 68: 387–394. Pavlides, C., Watanabe, Y., and McEwen, B.S. (1993) Effects of glucocorticoids on hippocampal long-term potentiation. Hippocampus 3:183–192. Pawlak, R., Rao, B.S.S., Melchor, J.P., Chattarji, S., McEwen, B., and Strickland, S. (2005) Tissue plasminogen activator and plasminogen mediate stress-induced decline of neuronal and cognitive functions in the mouse hippocampus. Proc. Natl. Acad. Sci. USA 102:18201–18206. Petrovich, G.D., Canteras, N.S., and Swanson, L.W. (2001) Combinatorial amygdalar inputs to hippocampal domains and hypothalamic behavior systems. Brain Res. Rev. 38:247–289. Pham, K., Nacher, J., Hof, P.R., and McEwen, B.S. (2003) Repeated, but not acute, restraint stress suppresses proliferation of neural precursor cells and increases PSA-NCAM expression in the adult rat dentate gyrus. J. Neurosci. 17:879–886. Phillips, R.G., and LeDoux, J.E. (1992) Differential contribution of amygdala and hippocampus to cued and contextual fear conditioning. Behav. Neurosci. 106:274–285. Pierce, J.P., van Leyen, K., and McCarthy, J.B. (2000) Translocation machinery for synthesis of integral membrane and secretory proteins in dendritic spines. Nat. Neurosci. 3:311–313. Pitkanen, A., Pikkarainen, M., Nurminen, N., and Ylinen, A. (2000) Reciprocal connections between the amygdala and the hippocampal formation, perirhinal cortex, and postrhinal cortex in rat. Ann. N.Y. Acad. Sci. 911:369–391. Pitman, R.K. (2001) Hippocampal diminution in PTSD: More (or less?) than meets the eye. Hippocampus 11:73–74. Pompei, P., Riftina, F., and McEwen, B.S. (1995) Effect of adrenal steroids on preproneurokinin-A gene expression in discrete regions of the rat brain. Mol. Brain Res. 33:209–216. Popov, V.I., and Bocharova, L.S. (1992) Hibernation-induced structural changes in synaptic contacts between mossy fibres and hippocampal pyramidal neurons. Neuroscience 48:53–62. Popov, V.I., Bocharova, L.S., and Bragin, A.G. (1992) Repeated changes of dendritic morphology in the hippocampus of ground squirrels in the course of hibernation. Neuroscience 48:45–51. Pressman, S.D., and Cohen, S. (2005) Does positive affect influence health? Psychol. Bull. 131:925–971. Pruessner, J.C., Baldwin, M.W., Dedovic, K., Renwick, R.M.N.K., Lord, C., Meaney, M., and Lupien, S. (2005) Self-esteem, locus of control, hippocampal volume, and cortisol regulation in young and old adulthood. NeuroImage 28:815–826. Pruessner, J.C., Hellhammer, D.H., and Kirschbaum, C. (1999) Low self-esteem, induced failure and the adrenocortical stress response. Personality and Individual Differences 27:477–489. Pulford, B.E., and Ishii, D.N. (2001) Uptake of circulating insulinlike growth factors (IGFs) into cerebrospinal fluid appears to be independent of the IGF receptors as well as IGF-binding proteins. Endocrinology 142:213–220. Quirk, G.J., and Armony, J.L. (1997) Fear conditioning enhances different temporal components of tone-evoked spike trains in auditory cortex and lateral amygdala. Neuron 19:613–624. Quirk, G.J., Likhtik, E., Pelletier, J.G., and Pare, D. (2003) Stimulation of medial prefrontal cortex decreases the responsiveness of central amygdala output neurons. J. Neurosci. 23:8800–8807. Radley, J.J., and Jacobs, B.L. (2002) 5-HT1A receptor antagonist administration decreases cell proliferation in the dentate gyrus. Brain Res. 955:264–267. Radley, J.J., Sisti, H.M., Hao, J., Rocher, A.B., McCall, T., Hof, P.R., McEwen, B.S., and Morrison, J.H. (2004) Chronic behavioral stress induces apical dendritic reorganization in pyramidal neurons of the medial prefrontal cortex. Neuroscience 125:1–6.

652

ANXIETY DISORDERS

Radley, J.J., Rocher, A.B., Janssen, W.G.M., Hof, P.R., McEwen, B.S., and Morrison, J.H. (2005) Reversibility of apical dendritic retraction in the rat medial prefrontal cortex following repeated stress. Exp. Neurol. 196:199–203. Radley, J.J., Rocher, A.B., Miller, M., Janssen, W.G.M., Liston, C., Hof, P.R., McEwen, B.S., and Morrison, J.H. (2006) Repeated stress induces dendritic spine loss in the rat medial prefrontal cortex. Cereb. Cortex 16:313–320. Rahmann, S., and Neumann, R.S. (1993) Activation of 5-HT2 receptors facilitates depolarization of neocortical neurons by Nmethyl-D-aspartate. Eur. J. Pharmacol. 231:347–354. Rakic, P. (1985) Limits of neurogenesis in primates. Science 227: 1054–1056. Rasika, S., Alvarez-Buylla, A., and Nottebohm, F. (1999) BDNF mediates the effects of testosterone on the survival of new neurons in an adult brain. Neuron 22:53–62. Rasika, S., Nottebohm, F., and Alvarez-Buylla, A. (1994) Testosterone increases the recruitment and/or survival of new high vocal center neurons in adult female canaries. Proc. Natl. Acad. Sci. USA 91:7854–7858. Rasmussen, T., Schliemann, T., Sorensen, J.C., Zimmer, J., and West, M.J. (1996) Memory impaired aged rats: no loss of principal hippocampal and subicular neurons. Neurobiol. Aging 14:143– 147. Razandi, M., Pedram, A., Greene, G.L., and Levin, E.R. (1999) Cell membrane and nuclear estrogen receptors (ERs) originate from a single transcript: Studies of ERa and ERb expressed in Chinese hamster ovary cells. Mol. Endocrinol. 13:307–319. Reichardt, H.M., and Schutz, G. (1998) Glucocorticoid signalling multiple variations of a common theme. Mol. Cell. Endocrinol. 146:1–6. Richardson, M.P., Strange, B.A., and Dolan, R.J. (2004) Encoding of emotional memories depends on amygdala and hippocampus and their interactions. Nat. Neurosci. 7:278–285. Robinson, T.E., and Kolb, B. (1997) Persistent structural modifications in nucleus accumbens and prefrontal cortex neurons produced by previous experience with amphetamine. J. Neurosci. 17:8491–8497. Roof, R.L. (1993) The dentate gyrus is sexually dimorphic in prepubescent rats: testosterone plays a significant role. Brain Res. 610: 148–151. Rozovsky, I., Wei, M., Stone, D.J., Zanjani, H., Anderson, C.P., Morgan, T.E., and Finch, C.E. (2002) Estradiol (E2) enhances neurite outgrowth by repressing glial fibrillary acidic protein expression and reorganizing laminin. Endocrinology 143:636–646. Rudick, C.N., and Woolley, C.S. (2000) Estradiol induces a phasic Fos response in the hippocampal CA1 and CA3 regions of adult female rats. Hippocampus 10:274–283. Rudick, C.N., and Woolley, C.S. (2001) Estrogen regulates functional inhibition of hippocampal CA1 pyramidal cells in the adult female rat. J. Neurosci. 21:6532–6543. Sachar, E.J., Hellman, L., Roffwarg, H.P., Halpern, F.S., Fukushima, D.K., and Gallagher, T.F. (1973) Disrupted 24-hour patterns of cortisol secretion in psychotic depression. Arch. Gen. Psychiatry 28:19–24. Santini, E., Ge, H., Ren, K., Pena de Ortiz, S., and Quirk, G.J. (2004) Consolidation of fear extinction requires protein synthesis in the medial prefrontal cortex. J. Neurosci. 24:5704–5710. Sapolsky, R. (1992) Stress, the Aging Brain and the Mechanisms of Neuron Death. Cambridge, MA: MIT Press. Sapolsky, R.M. (1996) Why stress is bad for your brain. Science 273:749–750. Sapolsky, R., Krey, L., and McEwen, B.S. (1986) The neuroendocrinology of stress and aging: the glucocorticoid cascade hypothesis. Endocr. Rev. 7:284–301. Saxe, M.D., Battaglia, F., Wang, J.-W., Malleret, G., David, D.J., Monckton, J.E., Garcia, A.D.R., Sofroniew, M.V., Kandel, E.R.,

Santarelli, L., Hen, R., and Drew, M.R. (2006) Ablation of hippocampal neurogenesis impairs contextual fear conditioning and synaptic plasticity in the dentate gyrus. Proc. Natl. Acad. Sci. USA 103:17501–17506. Schulkin, J., McEwen, B.S., and Gold, P.W. (1994) Allostasis, amygdala, and anticipatory angst. Neurosci. Biobehav. Rev. 18:385– 396. Seeman, T.E., McEwen, B.S., Rowe, J.W., and Singer, B.H. (2001) Allostatic load as a marker of cumulative biological risk: MacArthur Studies of Successful Aging. Proc. Natl. Acad. Sci. USA 98: 4770–4775. Seeman, T.E., Singer, B.H., Rowe, J.W., Horwitz, R.I., and McEwen, B.S. (1997) Price of adaptation--allostatic load and its health consequences: MacArthur studies of successful aging. Arch. Intern. Med. 157:2259–2268. Seeman, T.E., Singer, B.H., Ryff, C.D., Dienberg, G., and Levy-Storms, L. (2002) Social relationships, gender, and allostatic load across two age cohorts. Psychosom. Med. 64:395–406. Seki, T., and Arai, Y. (1995) Age-related production of new granule cells in the adult dentate gyrus. Neuroreport 6:2479–2482. Seri, B., Garcia-Verdugo, J.M., McEwen, B.S., and Alvarez-Buylla, A. (2001) Astrocytes give rise to new neurons in the adult mammalian hippocampus. J. Neurosci. 21:7153–7160. Sheline, Y.I., Gado, M.H., and Kraemer, H.C. (2003) Untreated depression and hippocampal volume loss. Am. J. Psychiatry 160: 1516–1518. Sheline, Y.I., Sanghavi, M., Mintun, M.A., and Gado, M.H. (1999) Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. J. Neurosci. 19:5034–5043. Sheline, Y.I., Wang, P.W., Gado, M.H., Csernansky, J.C., and Vannier, M.W. (1996) Hippocampal atrophy in recurrent major depression. Proc. Natl. Acad. Sci. USA 93:3908–3913. Sherry, D.F., Jacobs, L.F., and Gaulin, S.J. (1992) Spatial memory and adaptive specialization of the hippocampus. Trends Neurosci. 15:298–303. Sherwin, B.B. (2003) Estrogen and cognitive functioning in women. Endocrine Rev. 24:133–151. Shughrue, P.J., and Merchenthaler, I. (2000) Evidence for novel estrogen binding sites in the rat hippocampus. Neuroscience 99: 605–612. Siesjo, B., and Bengtsson, F. (1989) Calcium fluxes, calcium antagonists and calcium-related pathology in brain ischemia, hypoglycemia and spreading depression: a unifying hypothesis. J. Cereb. Blood Flow Metab. 9:127–140. Sloviter, R., Valiquette, G., Abrams, G., Ronk, E., Sollas, A., Paul, L., and Neubort, S. (1989) Selective loss of hippocampal granule cells in the mature rat brain after adrenalectomy. Science 243: 535–538. Smith, M.A., Makino, S., Kvetnansky, R., and Post, R.M. (1995) Stress and glucocorticoids affect the expression of brain-derived neurotrophic factor and neurotrophin-3 mRNAs in the hippocampus. J. Neurosci. 15:1768–1777. Snyder, J.S., Kee, N., and Wojtowicz, J.M. (2001) Effects of adult neurogenesis on synaptic plasticity in the rat dentate gyrus. J. Neurophysiol. 85:2423–2431. Sousa, N., Lukoyanov, N.V., Madeira, M.D., Almeida, O.F.X., and Paula-Barbosa, M.M. (2000) Reorganization of the morphology of hippocampal neurites and synapses after stress-induced damage correlates with behavioral improvement. Neuroscience 97: 253–266. Spano, M.S., Ellgren, M., Wang, X., and Hurd, Y.L. (2007) Prenatal cannabis exposure increases heroin seeking with allostatic changes in limbic enkephalin systems in adulthood. Biol. Psychiatry 61: 554–563. Spanswick, S.C., Epp, J.R., Keith, J.R., and Sutherland, R.J. (2007) Adrenalectomy-induced granule cell degeneration in the hippo-

40: STRESS-INDUCED STRUCTURAL AND FUNCTIONAL PLASTICITY IN THE BRAIN campus causes spatial memory deficits that are not reversed by chronic treatment with corticosterone or fluoxetine. Hippocampus 17:137–146. Squire, L.R., and Zola-Morgan, S. (1991) The medial temporal lob memory system. Science 253:1380–1386. Starkman, M.N., Gebarski, S.S., Berent, S., and Schteingart, D.E. (1992) Hippocampal formation volume, memory dysfunction, and cortisol levels in patients with Cushing’s syndrome. Biol. Psychiatry 32:756–765. Starkman, M.N., Giordani, B., Gebrski, S.S., Berent, S., Schork, M.A., and Schteingart, D.E. (1999) Decrease in cortisol reverses human hippocampal atrophy following treatment of Cushing’s disease. Biol. Psychiatry 46:1595–1602. Starkman, M.N., and Schteingart, D.E. (1981) Neuropsychiatric manifestations of patients with Cushing’s syndrome. Arch. Intern. Med. 141:215–219. Steptoe, A., Owen, N., Kunz-Ebrecht, S.R., and Brydon, L. (2004) Loneliness and neuroendocrine, cardiovascular, and inflammatory stress responses in middle-aged men and women. Psychoneuroendocrinology 29:593–611. Steptoe, A., Wardle, J., and Marmot, M. (2005) Positive affect and health-related neuroendocrine, cardiovascular, and inflammatory processes. Proc. Natl. Acad. Sci. USA 102:6508–6512. Sterling, P., and Eyer, J. (1988) Allostasis: A new paradigm to explain arousal pathology. In: Fisher, S., and Reason, J., eds. Handbook of Life Stress, Cognition and Health. New York: John Wiley & Sons, pp. 629–649. Sternberg, E., Young, S.I., Bernardini, R., Calogero, A., Chrousos, G., Gold, P., and Wilder, R. (1989) A central nervous system defect in biosynthesis of corticotropin-releasing hormone is associated with susceptibility to streptococcal cell wall-induced arthritis in Lewis rats. Proc. Natl. Acad. Sci. USA 86:4771–4775. Sternberg, E.M., Hill, J.M., and Chrousos, G.P. (1996) Inflammatory mediator-induced hypothalamic-pituitary-adrenal axis activation is defective in streptococcal cell wall arthritis susceptible Lewis rats. Proc. Natl. Acad. Sci. USA 86:2374–2378. Sternberg, E.M., Young, W.S., Bernardini, R., Calogero, A.E., Chrousos, G.P., Gold, P.W., and Wilder, R.L. (1989) A central nervous system defect in biosynthesis of corticotropin-releasing hormone is associated with susceptibility to streptococcal cell wall-induced arthritis in Lewis rats. Proc. Natl. Acad. Sci. USA 86:4771– 4775. Sugaya, K., Chouinard, M., Greene, R., Robbins, M., Personett, D., Kent, C., Gallagher, M., and McKinney, M. (1996) Molecular indices of neuronal and glial plasticity in the hippocampal formation in a rodent model of age-induced spatial learning impairment. J. Neurosci. 16:3427–3443. Takadera, T., Matsuda, I., and Ohyashiki, T. (1999) Apoptotic cell death and caspase-3 activation induced by N-methyl-D-aspartate receptor antagonists and their prevention by insulin-like growth factor I. J. Neurochem. 73:548–556. Tanapat, P., Hastings, N.B., Reeves, A.J., and Gould, E. (1999) Estrogen stimulates a transient increase in the number of new neurons in the dentate gyrus of the adult female rat. J. Neurosci. 19:5792–5801. Taylor, C.P., and Meldrum, B.S. (1995) Na+ channels as targets for neuroprotective drugs. Trends Neurosci. 16:309–316. Terasawa. E., and Timiras, P. (1968) Electrical activity during the estrous cycle of the rat: cyclic changes in limbic structures. Endocrinology 83:207N216. Tiedge, H., Bloom, F.E., and Richter, D. (2001) Colloquium: Molecular kinesis in cellular function and plasticity. Proc. Natl. Acad. Sci. USA 98:6997–7106. Trapp, T., Rupprecht, R., Castren, M., Reul, J.M.H.M., and Holsboer, F. (1994) Heterodimerization between mineralocorticoid and glucocorticoid receptor: A new principle of glucocorticoid action in the CNS. Neuron 13:1457–1462.

653

Trejo, J.L., Carro, E., and Torres-Aleman, I. (2001) Circulating insulin-like growth factor I mediates exercise-induced increases in the number of new neurons in the adult hippocampus. J. Neurosci. 21:1628–1634. van Praag, H., Kempermann, G., and Gage, F.H. (1999) Running increases cell proliferation and neurogenesis in the adult mouse dentate gyrus. Nat. Neurosci. 2:266–270. Venero, C., and Borrell, J. (1999) Rapid glucocorticoid effects on excitatory amino acid levels in the hippocampus: a microdialysis study in freely moving rats. Eur. J. Neurosci. 1:2465–2473. Vyas, A., Mitra, R., Rao, B.S.S., and Chattarji, S. (2002) Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons. J. Neurosci. 22:6810– 6818. Wang, J., Rao, H., Wetmore, G.S., Furlan, P.M., Korczykowski, M., Dinges, D.F., and Detre, J.A. (2005) Perfusion functional MRI reveals cerebral blood flow pattern under psychological stress. Proc. Natl. Acad. Sci. USA 102:17804–17809. Watanabe, Y., Gould, E., Daniels, D., Cameron, H., and McEwen, B.S. (1992) Tianeptine attenuates stress-induced morphological changes in the hippocampus. Eur. J. Pharm. 222:157–162. Watanabe, Y., Weiland, N.G., and McEwen, B.S. (1995) Effects of adrenal steroid manipulations and repeated restraint stress on dynorphin mRNA levels and excitatory amino acid receptor binding in hippocampus. Brain Res. 680:217–225. Waters, E.M., Torres-Reveron, A., McEwen, B.S., Milner, T.A. (in press) Ultrastructural localization of extranuclear progestin receptors in the rat hippocampal formation. J. Comp. Neurol. in press Weiland, N.G. (1992a) Estradiol selectively regulates agonist binding sites on the N-methyl-D-aspartate receptor complex in the CA1 region of the hippocampus. Endocrinology 131:662–668. Weiland, N.G. (1992b) Glutamic acid decarboxylase messenger ribonucleic acid is regulated by estradiol and progesterone in the hippocampus. Endocrinology 131:2697–2702. Weiland, N.G., Orchinik, M., and McEwen, B.S. (1995) Corticosterone regulates mRNA levels of specific subunits of the NMDA receptor in the hippocampus but not in cortex of rats. Abstracts, Soc. Neurosci. 21:207.12. Weiland, N.G., Orchinik, M., and Tanapat, P. (1997) Chronic corticosterone treatment induces parallel changes in N-methyl-Daspartate receptor subunit messenger RNA levels and antagonist binding sites in the hippocampus. Neuroscience 78:653–662. Weiland N.G., Orikasa, C., Hayashi, S., and McEwen, B.S. (1996) Localization of estrogen receptors in the hippocampus of male and female rats. Soc. Neurosci. Abstr. 22:618. Weiland, N.G., Orikasa, C., Hayashi, S., and McEwen, B.S. (1997) Distribution and hormone regulation of estrogen receptor immunoreactive cells in the hippocampus of male and female rats. J. Comp. Neurol. 388:603–612. Wellman, C.L. (2001) Dendritic reorganization in pyramidal neurons in medial prefrontal cortex after chronic corticosterone administration. J. Neurobiol. 49:245–253. Whitton, P.S., Sarna, G.S., O’Connell, M.T.O., and Curzon, G. (1991) The effect of the novel antidepressant tianeptine on the concentration of 5-hydroxytryptamine in rat hippocampal dialysates in vivo. Neuropharmacology 30:1–4. Wise, P.M., Dubal, D.B., Rau, S.W., Brown, C.M., and Suzuki, S. (2005) Are estrogens protective or risk factors in brain injury and neurodegeneration? Reevaluation after the women’s health initiative. Endocrine Rev. 26:308–312. Wood, G.E., Young, L.T., Reagan, L.P., and McEwen, B.S. (2003) Acute and chronic restraint stress alter the incidence of social conflict in male rats. Horm. & Behav. 43:205–213. Woolley, C., Gould, E., Sakai, R., Spencer, R., and McEwen, B.S. (1991) Effects of aldosterone or RU28362 treatment on adrenalectomy-induced cell death in the dentate gyrus of the adult rat. Brain Res. 554:312–315.

654

ANXIETY DISORDERS

Woolley, C., and McEwen, B.S. (1993) Roles of estradiol and progesterone in regulation of hippocampal dendritic spine density during the estrous cycle in the rat. J. Comp. Neurol. 336: 293–306. Woolley, C., and McEwen, B.S. (1994) Estradiol regulates hippocampal dendritic spine density via an N-methyl-D-aspartate receptor dependent mechanism. J. Neuroscience 108:263–272. Wossink, J., Karst, H., Mayboroda, O., and Joels, M. (2001) Morphological and functional properties of rat dentate granule cells after adrenalectomy. Neuroscience 108:263–272.

Yehuda, R., Giller, E., Southwick, S., Lowy, M., and Mason, J. (1991) Hypothalamic-pituitary-adrenal dysfunction in posttraumatic stress disorder. Biol. Psychiatry 30:1031–1048. Yen, L., Sibley, J.T., and Constantine-Paton, M. (1995) Analysis of synaptic distribution within single retinal axonal arbors after chronic NMDA treatment. J. Neurosci. 15:4712–4725. Zhuang, X., Gross, C., Santarelli, L., Compan, V., Trillat, A.-C., and Hen, R. (1999) Altered emotional states in knockout mice lacking 5-HT1A or 5-HT1B receptors. Neuropsychopharmacology 21:52S–60S.

41 The Neurobiology of Anxiety Disorders AMIR GARAKANI, JAMES W. MURROUGH, DENNIS S. CHARNEY,

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There is continuing expansion in our knowledge of the neurobiological and neurochemical bases of fear and anxiety. Specific neurochemical and neuropeptide systems have been demonstrated to play important roles in the behaviors associated with fear and anxiety-producing stimuli. Long-term dysregulation of these systems appear to contribute to the development of anxiety disorders, including panic disorder, posttraumatic stress disorder (PTSD), and social anxiety disorder. These neurochemical and neuropeptide systems have been shown to have effects on distinct cortical and subcortical brain areas that are relevant to the mediation of the symptoms associated with anxiety disorders. These areas include the amygdala, prefrontal cortex (PFC), hippocampus, anterior cingulate cortex (ACC), and the insula. Advances in functional neuroimaging have allowed for the intensive investigation of how these regions contribute to anxiety states. Moreover, advances in molecular genetics portend the identification of the genes underlying the neurobiological disturbances that increase the vulnerability to anxiety disorders. This chapter reviews preclinical and clinical research pertinent to the neurobiological basis of anxiety disorders. The implications of this synthesis for the discovery of anxiety disorder vulnerability genes and novel psychopharmacological approaches is also discussed.

NEURAL MECHANISMS OF FEAR AND ANXIETY

J. DOUGLAS BREMNER

(learning), he then removed the food, and rang the bell only. This caused the dog to salivate, a conditioned response (CR) to a new conditioned stimulus (CS). In summary, classical conditioning is a process by which a neutral stimulus becomes a CS. Pavlovian conditioning can also be applied to the model of fear learning. In nature, animals need to be able to recognize and respond appropriately to threats (Blair et al., 2001); therefore, fear is a highly useful adaptive trait meant to protect us from potential danger. When certain environmental cues, traumas, persistent stress, or other stimuli trigger persistent aversive responses, fear can develop into anxiety. A notable example was the Little Albert experiment (J.B. Watson and Raynor, 1920). In their experiment, an 11-year-old boy was given a rat with which to play and had no fear reaction. The rat was presented again, but this time coupled with a long banging noise (an US), causing Albert to cry (UR). After several trials, Albert was shown the rat (CS) without the noise but still cried (CR). He had the same reaction when he was presented with a piece of fur that resembled the color and shape of the rat, which is an example of how his fear had generalized. In addition to being unethical, this experiment illustrates how an aversive stimulus (US) can continue to cause a CR, whereas nonaversive cues will not cause a CR if they are continually presented without the US. This process is called extinction and is discussed later (see also Garakani et al., 2006, for a review of classical conditioning).

Classical Fear Conditioning The concept of classical conditioning was set forth in the famous experiment of Ivan Pavlov (1927). He began by describing how a dog, when presented with food, salivates. The food represents an unconditioned stimulus (US) creating an unconditioned response (UR). He then rang a bell, a neutral stimulus, while presenting the food, thereby linking the US to the ringing. After several trials of ringing the bell while presenting the food

Neuroanatomy of Anxiety A comprehensive review of this area is covered in Chapter 39. G.M. Sullivan and others discuss in detail the pathway by which fear stimuli are translated into the expression of anxiety symptoms. A brief overview follows now. The amygdala has a prominent role in the etiology of anxiety disorders (Pare et al., 2004). It has been 655

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shown to be involved in the acquisition of fearful stimuli, and a part of the “fear loop pathway.” Studies of humans with damage to their amygdala have shown that they have impairment in their ability to acquire fear responses (Adolphs et al., 2005). The amygdala, which is found in the medial temporal lobes, consists of 13 nuclei, with the basal amygdala, lateral amygdala, and central nucleus of the amygdala (CEA) playing a role in the fear response (Rosen, 2004). The pathway begins when fear-related conditioned stimuli are transmitted to the thalamus by external and visceral pathways. Afferents then reach the lateral amygdala via two parallel circuits: a rapid subcortical path directly from the dorsal (sensory) thalamus and a slower regulatory cortical pathway encompassing primary somatosensory cortices, the insula, and anterior cingulate/PFC. Contextual CSs are projected to the lateral amygdala from the hippocampus and perhaps the bed nucleus of the stria terminalis (BNST). The long loop pathway indicates that sensory information relayed to the amygdala undergoes substantial higher-level processing, thereby enabling assignment of significance, based upon prior experience, to complex stimuli. Cortical involvement in fear conditioning is clinically relevant because it provides a mechanism by which cognitive factors will influence whether symptoms are experienced or not following stress exposure (LeDoux, 2000; SotresBayon et al., 2006). During the expression of fear-related behaviors, the lateral amygdala engages the CEA, which as the principal output nucleus projects to areas of the hypothalamus and brain stem that mediate the autonomic, endocrine, and behavioral responses associated with fear and anxiety (Schafe et al., 2001). The molecular and cellular mechanisms that underlie synaptic plasticity in amygdala-dependent learned fear are an area of very active investigation (Shumyatsky et al., 2002; Schroeder and Shinnick-Gallagher, 2004). Long-term potentiation (LTP) in the lateral amygdala (LA) appears to be a critical mechanism for storing memories of the CS–US association (Chapman et al., 1990; Blair et al., 2001). A variety of behavioral and electrophysiological data have led LeDoux and colleagues to propose a model to explain how neural responses to the CS and US in the LA could influence LTP-like changes that store memories during fear conditioning. This model proposes that calcium entry through N-methyl-D-aspartate (NMDA) receptors and voltage-gated calcium channels (VGCCs) initiates the molecular processes to consolidate synaptic changes into long-term memory (Blair et al., 2001). Short-term memory requires calcium entry only through NMDA receptors. This hypothesis leads to several predictions that may have relevance to the discovery of novel therapeutics for anxiety disorders. It suggests that blocking NMDA receptors in the amygdala during learning should im-

pair short- and long-term fear memory. It has been demonstrated in rodents that NMDA antagonists such as D,L-2-amino-5-phosphonovaleric acid (AP5) can block fear acquisition (Rodrigues et al., 2001; Goosens and Maren, 2004; Matus-Amat et al., 2007), whereas some studies have shown that expression is blocked as well (Maren et al., 1996; Jasnow et al., 2004). Studies of NMDA receptor antagonists for anxiety in humans have been limited. Blockade of VGCCs appears to block longterm but not short-term memory (Bauer et al., 2002; Cain et al., 2002; McKinney and Murphy, 2006). This would suggest that clinically available calcium channel blockers such as verapamil and nimodipine may be helpful in diminishing the intensity and impact of recently acquired fear memory. There are, however, a limited number of studies of these agents for anxiety disorders (Balon and Ramesh, 1996). A more promising area is the investigation of agents such as gabapentin and pregabalin that act as alpha2delta ligands to calcium channels (Stahl, 2004). See Mula et al. (2007) for a recent comprehensive review of anticonvulsants in anxiety disorders. Consolidation The process of consolidation refers to the transfer of short-term memory into long-term memory (McGaugh, 2002). This process requires protein synthesis, which is thought to occur in the hippocampus each time a memory is retrieved (Rossato et al., 2007). After retrieval, memory traces are unstable and require another consolidation, known as reconsolidation, to become formed (see below). Protein synthesis inhibitors such as anisomycin have been used to block memory consolidation (Lin et al, 2003; Santini et al., 2004), by a proposed mechanism of regulating transcription of brain-derived neurotrophic factor (BDNF) (Ou and Gean, 2007). Anisomycin has been shown to have anxiolytic properties in an animal model of predator stress (Adamec, Strasser, et al., 2006), and to reduce PTSD symptoms in rats (Cohen et al., 2006). Studies using inhibitory avoidance learning procedures have been used to support the view that the amygdala is not the sole site for fear learning but, in addition, can modulate the strength of memory storage in other brain structures (McGaugh and Roozendaal, 2002). Specific drugs and neurotransmitters infused into the basolateral amygdala (BLA) influence consolidation of memory for inhibitory avoidance training. Posttraining peripheral or intraamygdala infusions of drugs affecting g -aminobutyric acid (GABA), opioid, glucocorticoid, and muscarinic acetylcholine receptors have dose- and time-dependent effects on memory consolidation (McGaugh, 2002). Norepinephrine (NE) infused directly into the BLA after inhibitory avoidance training enhances memory consolidation, indicating that the

41: NEUROBIOLOGY

degree of activation of the noradrenergic system within the amygdala by an aversive experience may predict the extent of the long-term memory for the experience (McIntyre et al., 2002). Interactions among corticotropin releasing hormone (CRH), cortisol, and NE have very important effects on memory consolidation, which is likely to be relevant to the effects of traumatic stress on memory. Extensive evidence indicates that glucocorticoids influence long-term memory consolidation via stimulation of glucocorticoid receptors (GR). The glucocorticoid effects on memory consolidation require activation of the BLA, and lesions of the BLA block retention enhancement of intrahippocampal infusions of a GR agonist. Additionally, the BLA is a critical locus of interaction between glucocorticoids and NE in modulating memory consolidation (McGaugh and Roozendaal, 2002; Roozendaal, Okuda, et al., 2006). There is extensive evidence consistent with a role for CRH in mediating stress effects on memory consolidation. Activation of CRH receptors in the BLA by CRH released from the CEA facilitates stress effects on memory consolidation. Memory enhancement produced by CRH infusions in the hippocampus is blocked by propranolol, suggesting that CRH, through a presynaptic mechanism, stimulates NE release in the hippocampus (Roozendaal et al., 2002; Roozendaal, Hui, et al., 2006). Excessive stress-induced release of CRH, cortisol, and NE are likely to lead to development of indelible traumatic memories and associated reexperiencing symptoms. Administration of CRH antagonists, GR antagonists, and b-adrenergic receptor antagonists may prevent these effects in vulnerable individuals. A preclinical trial with mice showed that corticosterone, a glucocorticoid, administered after contextual fear reactivation, can block memory recall (Cai et al., 2006). This effect on memory has been found in human investigations as well (de Quervain et al., 2000; de Quervain et al., 2003). A double-blind, placebo-controlled, crossover trial by de Quervain’s group (Aerni et al., 2004) reported that 3-month treatment with low-dose cortisol resulted in a reduction in PTSD symptoms as rated by the Clinician Administered PTSD Scale (CAPS). More recently, cortisol or placebo was administered to patients with spider phobia and social phobia. In two separate trials, they found that cortisol reduced fear in response to a Trier Social Stress Test, and in individuals with spider phobia, to a photographic stimulus (Soravia et al., 2006). There is also some support for the use of glucocorticoids to prevent PTSD after trauma (de Quervain, 2008). In summary, these results support the concept that CRH, via an interaction with glucocorticoids, interacts with the noradrenergic system to consolidate traumatic memories. Drugs that target this pathway may provide novel therapeutics for anxiety disorders such as PTSD and phobia.

657

Reconsolidation The process by which old, reactivated memories undergo another round of consolidation is called reconsolidation (D˛ebiec et al., 2002; Myers and Davis, 2002). The process of reconsolidation is relevant to vulnerability and resilience to the effects of extreme stress. It is the rule rather than the exception that memories are reactivated by cues associated with the original trauma. Repeated reactivation of these memories may serve to strengthen the memories and facilitate long-term consolidation (Przbyslawski et al., 1999; Sara, 2000). Each time a traumatic memory is retrieved, it is integrated into an ongoing perceptual and emotional experience and becomes part of a new memory. It is also worth noting that traumatic memories have been shown to mask a neutral one. For example, stimuli that are emotionally laden are more likely to cause amnesia to preceding words, when compared to neutral stimuli (Kern et al., 2005). Moreover, recent preclinical studies indicate that consolidated memories for auditory fear conditioning, which are stored in the amygdala (Jin et al., 2007), hippocampal-dependent contextual fear memory (Fischer et al., 2004), and hippocampal-dependent memory associated with inhibitory avoidance (Milekic and Alberini, 2002) are sensitive to disruption upon reactivation, by administration with a protein synthesis inhibitor directly into the amygdala and hippocampus. The reconsolidation process, which has enormous clinical implications, results in a reactivated memory trace that returns to a state of lability and must undergo consolidation once more if it is to remain in long-term storage. Some controversies remain regarding the temporal persistence of systems reconsolidation. D˛ebiec and colleagues (2002) found that intrahippocampal infusions of anisomycin caused amnesia for a consolidated hippocampal-dependent memory if the memory was reactivated even up to 45 days after training. Milekic and Alberini (2002), however, found that the ability of an intrahippocampal infusion of anisomycin to produce amnesia for an inhibitory avoidance task was evident only when the memory was recent (up to 7 days). Duvarci and Nader (2004) showed that there was no recovery of the anisomycininduced reconsolidation deficit over 24 days. Other studies have shown that after hippocampal injections of anisomycin, there are no immediate deficits, but in some cases amnesia was present at 48 hours (Power et al., 2006; Canal and Gold, 2007; Canal et al., 2007). Further work is needed in this area to clarify these findings, and their applicability to clinical treatment (Rudy et al., 2006). The reconsolidation process involves NMDA receptors, b -adrenergic receptors, and requires cyclic adenosine monophosphate (cAMP) response-element binding protein (CREB) induction. The CREB requirement

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ANXIETY DISORDERS

suggests that nuclear protein synthesis is necessary (Kida et al., 2002, Wagatsuma et al., 2006). This remarkable lability of a memory trace, which permits reorganization of an existing memory in a retrieval environment, provides a theoretical basis for psychotherapeutic and pharmatherapeutic intervention for traumatic stress exposure as well as other anxiety disorders. Preclinical studies have shown that NMDA receptor antagonists impair reconsolidation (Przbyslawski and Sara, 1997; J.L. Lee et al., 2006). There are also studies under way investigating the use of glucocorticoids to block reconsolidation of fear memories. Recently, it was shown that RU 28486 (mifepristone) impairs retrieval of traumatic memories during an inhibitory avoidance procedure using foot shock (Tronel and Alberini, 2007). Propranolol, a beta-receptor antagonist, also act, to block reconsolidation but does not impair integration of new memories (D˛ebiec and Ledoux, 2004). It can exert these central effects because it crosses the bloodbrain-barrier (BBB), in contrast to peripherally acting beta blockers (Van Stegeren et al., 1998). Propranolol has been shown to block reconsolidation of emotional stimuli in animal studies (Przybyslawski et al., 1999; D˛ebiec and Ledoux, 2004; Diergaarde et al., 2006), and impaired recall and retention of emotional memories in humans (Cahill et al., 1994; Van Stegeren et al., 1998; Strange et al., 2003; Hurlemann et al., 2005; Van Stegeren et al., 2005). Grillon et al. (2004) showed that in healthy volunteers receiving propranolol versus placebo, those on propranolol had a reduction contextual fear conditioning, but no effect on cue conditioning, as measured by skin conductance and subjective arousal levels. A study by Pitman’s group, however, could not confirm this finding using skin conductance measures in patients with PTSD (Orr et al., 2006). The implication of these preliminary findings is that administration of a beta-receptor antagonist shortly after trauma exposure or after reactivation of memory associated with the anxiety-inducing event may reduce the strength of the original memory. Indeed, there have been studies using these agents immediately after trauma and in patients with PTSD. Pitman et al. (2002) were the first to conduct a randomized, double-blind placebo-controlled trial of propranolol administered 6 hours after exposure to a trauma, for up to 10 days, to determine if it was effective in preventing PTSD. The results were not statistically significant due to a small sample size. A recently published trial studied adult men and women admitted to a trauma service, and in a randomized, double-blind fashion, administered within 48 hours either propranolol, gabapentin, or placebo for 14 days, and followed the patients over 8 months. In spite of a large number of eligible subjects (n=569), only a small number (n=48) enrolled in one of the three study arms, in large part due to patient refusal. Overall, the investigation failed to show that the medications dif-

fered from placebo. Other antiadrenergic agents have been studied as potential treatments for PTSD, by reducing NE. Two studies have reported that guanfacine, an a-2 agonist, was not effective in reducing symptoms (Davis et al., 2008). Conversely, prazosin, an a-1 antagonist that has been used off-label for treatment of nightmares in PTSD, was shown in replication to reduce nightmares (Raskind et al., 2003; Raskind et al., 2007) and to reduce daytime symptoms, as evidenced by attenuated distress from verbal trauma cues on an emotional Stroop paradigm (Taylor et al., 2006). It is important to note that there have been ethical concerns raised about the use of these agents when their mechanism of action in reducing symptoms is not fully understood (Henry et al., 2007). Nonetheless, drugs like propranolol do not “erase” or “block” memories but instead merely attenuate their “overconsolidation” and excessive recall. Further research will hopefully help elucidate the importance of this work in the treatment and possible prevention of PTSD. Extinction The process of extinction occurs when the CS is presented repeatedly in the absence of the US, thereby reducing the conditioned fear response (for example, the dog in Pavlov’s experiments stops salivating after several trials of hearing the bell but seeing no food). Extinction represents a new form of learning and is not simply an erasing of old memories (Quirk, 2002). It forms the rational for exposure-based psychotherapies for the treatment of anxiety disorders characterized by exaggerated fear responses. Individuals who have the ability to quickly attenuate learned fear through a powerful and efficient extinction process are likely to function more effectively under dangerous conditions. Extinction is characterized by many of the same neural mechanisms that occur in fear acquisition. The pathway begins with a reduction in neuronal firing in the LA in response to the fear stimulus. The lateral amygdala then interacts with the CEA and basal nuclei, either directly or through intercalated cell masses (ICM) (Sotres-Bayon et al., 2006). The hippocampus modulates contextual fear processing. It is important to note the integral role of the medial prefrontal cortex (mPFC) in regulating fear extinction by inhibition of the amygdala. It has been shown that the consolidation of extinction most likely involves potentiation of inputs into the mPFC by means of NMDA-dependent plasticity (Burgos-Robles et al., 2007). The BLA sends direct excitatory inputs to the mPFC, and NMDA antagonists infused into the BLA blocks extinction (Feltenstein and See, 2007; Yang et al., 2007). The ability of the mPFC to modulate fear behaviors is probably related to projections from the mPFC via GABA interneurons to the BLA (Royer et al., 2000). Infralimbic neurons, which

41: NEUROBIOLOGY

are part of the mPFC, fire only when rats are recalling extinction; greater firing correlates with reduced fear behaviors (Milad and Quirk, 2002). Some studies have shown that lesions in the mPFC, in particular the infralimbic nucleus (M.A. Morgan et al., 1993; Quirk et al., 2000; Milad and Quirk, 2002), or injection with protein synthesis inhibitors (Santini et al., 2004), block extinction, indicating that the mPFC might store longterm extinction memory. There have, however, been inconsistent findings in other studies (Farinelli et al., 2006; Garcia et al., 2006). More research is needed to clarify the exact mechanism of interaction of the mPFC with other structures in the fear loop (Myers and Davis, 2007). Failure to achieve an adequate level of activation of the mPFC after extinction might lead to persistent fear responses (Herry and Garcia, 2002). Animal models have shown that acute or chronic stress adversely affect fear extinction in the mPFC (Miracle et al., 2006), by a mechanism of dendritic retraction (Cook and Wellman, 2004; Radley et al., 2004; Izquierdo et al., 2006). Individuals with the capacity to function well following states of high fear may have potent mPFC inhibition of amygdala responsiveness. In contrast, patients with PTSD exhibit depressed ventral mPFC activity that correlates with increased autonomic arousal after exposure to traumatic reminders (Bremner et al., 1999; Williams et al., 2006). Consistent with this hypothesis, it has been shown that patients with PTSD had increased amygdala activation during fear acquisition and decreased mPFC/anterior cingulate activity during extinction (Bremner et al., 2005; Williams et al., 2006). Activation of amygdala NMDA receptors by glutamate (Glu) is essential to extinction (Myers and Davis, 2007), and L-type VGCCs also contribute to extinction plasticity (Cain et al., 2002; Cain et al., 2005). Nmethyl-D-aspartate receptor antagonists have been shown to block extinction, whereas an NMDA receptor partial agonist, d-cycloserine (DCS), had the opposite effect (J.L. Lee et al., 2006; Tomilenko and Dubrovina, 2007). Preclinical studies found that DCS injected into the amygdala reduced fear startle and may facilitate the extinction process when DCS is given in combination with behavioral therapy in patients with anxiety disorders (Davis, 2002). There have been several human studies using DCS in anxiety disorders. In a pilot double-blind, placebo-controlled trial of patients with PTSD, DCS was not effective as a stand-alone treatment (Heresco-Levy et al., 2002). Studies have focused on the effect of DCS on enhancing response to exposure therapy. To date, it has been reported that augmentation of exposure therapy with DCS is effective in reducing fear in patients with acrophobia, a specific phobia (Ressler et al., 2004), and social phobia (Hofmann et al., 2006; Guastella et al., 2008), although it

659

had no statistically significant effect in a study of spider phobia (Guastella et al., 2007). These preclinical and clinical investigations suggest that clinical research paradigms capable of evaluating the mechanisms of fear conditioning in clinical populations would be of great value. As these mechanisms become better understood, potential therapeutic interventions will emerge as well. THE NEUROCHEMICAL BASIS OF FEAR AND ANXIETY Specific neurotransmitters and neuropeptides act on brain areas noted above in the mediation of fear and anxiety responses. These neurochemicals are released during stress, and chronic stress results in long-term alterations in the function of these systems. Stress axis neurochemical systems prepare the organism for threat in multiple ways: through increased attention and vigilance, modulation of memory (to maximize the use of prior experience), planning, and preparation for action. In addition, these systems have peripheral effects, which include increased heart rate and blood pressure (catecholamines) and rapid modulation of the body’s use of energy (cortisol). The neurobiological responses to threat and severe stress are clearly adaptive and have survival value, but they also can have maladaptive consequences when they become chronically activated. Examination of the preclinical data concerning neurochemical substrates of the stress response, the long-term impact of early life exposure to stress, and possible stress-induced neurotoxicity provides a context to consider clinical investigations of the pathophysiology of the anxiety disorders. Noradrenergic System Stressful stimuli of many types produce marked increases in brain noradrenergic function. Stress produces regional selective increases in NE turnover in the locus coeruleus (LC), limbic regions (hypothalamus, hippocampus, and amygdala), and cerebral cortex. These changes can be elicited with immobilization stress, foot shock stress, tail-pinch stress, and conditioned fear. Exposure to stressors from which the animal cannot escape results in behavioral deficits termed learned helplessness. The learned helplessness state is associated with depletion of NE, probably reflecting the point at which synthesis cannot keep up with demand. These studies have been reviewed elsewhere in detail (Bremner et al., 1996a, 1996b). Neurons in the LC are activated in association with fear and anxiety states (Abercrombie and Jacobs, 1987; Redmond, 1987), and the limbic and cortical regions innervated by the LC are involved in the elaboration of adaptive responses to stress (Foote et al., 1983; Morilak et al., 2005). Most types of sensory stimuli

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result in a brief activation of NE neurons, whereas a wide array of stressful stimuli, such as electric shock, immobilization, loud noise, or forced swim, result in a more robust, prolonged activation. Norepinephrine has been shown to specifically modulate the behavioral component of the stress response in animals, and anxietylike behaviors are increased by drugs that potentiate NE transmission (Charney et al., 1987a). Locus coeruleus NE neurons in freely moving cats were activated twofold to threefold by confrontation with either a dog or an aggressive cat, although exposure to other novel stimuli (such as a nonaggressive cat) did not increase the firing rate (Levine et al., 1990). Although the integrity of NE neurons is necessary for certain types of fear-related behaviors, normal patterns of non-fearrelated ambulatory activity are not necessarily disrupted by chemical lesions of the NE system in rats (Murrough et al., 2000). A series of investigations have shown that certain stressors elicit increased responsiveness of LC neurons to excitatory stimulation, which is in part mediated by a-2 adrenoreceptors (AR). a-2-ARs are a heterogeneous group of inhibitory G protein–coupled receptors in the central nervous system (CNS) that are found as autoreceptors on the somas of NE-containing neurons and serve an important role in providing negative feedback and containment of the NE response. Antagonism of a-2-ARs with idazoxan or yohimbine increases the response of LC neurons to excitatory stimuli without altering their baseline firing rate (Simson and Weiss, 1988). Acute cold restraint stress results in decreased density of a-2-ARs in the hippocampus and amygdala (Torda et al., 1984). Further, in chronically cold-stressed rats, the release of NE produced by yohimbine (Nisenbaum and Abercrombie, 1993) or repeated stress (Nisenbaum et al., 1991) in the hippocampus is enhanced. It has been hypothesized that a functional blockade of a-2ARs is a consequence of NE depletion with inescapable stress, resulting in enhancement of LC neurons responsiveness to stimuli (Simson and Weiss, 1988). In addition, a-2-AR knockout mice exhibit increases in autonomic activity and anxiety-related behaviors (Lähdesmäki et al., 2002), enhanced startle response and deficiencies in prepulse inhibition (Sallinen et al., 1998; Lähdesmäki et al., 2004), and enhanced physiological and behavioral alterations resulting from administration of D-amphetamine (Lähdesmäki et al., 2004). An important recent study in healthy humans demonstrated the effects of an a-2C-AR polymorphism on NE activity at rest and in response to a yohimbine challenge (Neumeister et al., 2005). The a-2C-Del322325 polymorphism is an in-frame deletion of homologous repeats at codons 322–325 of the a-2C-AR subtype and has been associated with impaired feedback and enhanced NE release in animals. African American carriers of the a-2C-Del322-325 polymorphisms

have an elevated risk of congestive heart failure, perhaps due to chronic higher levels of circulating peripheral NE. The study by Neumeister and colleagues (2005) found that individuals homozygous for the a-2C-Del322325 polymorphism had higher levels of NE at rest and more sustained increases in NE, heart rate, and anxiety in response to a yohimbine challenge compared to noncarriers of the polymorphism. A second study of the polymorphism in patients with remitted major depressive disorder (MDD) demonstrated differential recruitment of cortical and limbic brain regions in carriers, suggesting a direct impact of the a-2C-Del322-325 polymorphism on brain function relevant to emotional processing (Neumeister et al., 2006). There is strong evidence that the brain noradrenergic system is involved in mediating fear conditioning (Rasmussen et al., 1986; Charney and Deutch, 1996). Neutral stimuli paired with shock (CS) produce increases in brain NE metabolism and behavioral deficits similar to those elicited by the shock alone (Cassens et al., 1981), as well as increased firing of cells in the LC (Rasmussen et al., 1986). An intact noradrenergic system appears to be necessary for the acquisition of fearconditioned responses (Cose and Robbins, 1987), and NE activation in the amygdala was recently demonstrated to be necessary for glucocorticoid-mediated enhancement of memory (Roozendaal, Okuda, et al., 2006). Chronic symptoms experienced by patients with an anxiety disorder, such as panic attacks, insomnia, startle, and autonomic hyperarousal, are characteristic of increased noradrenergic function (Charney et al., 1984; Charney et al., 1987a). Potential drugs of abuse, such as alcohol, opiates, and benzodiazepines (but not cocaine), decrease firing of noradrenergic neurons. Increases in the abuse of these substances parallel increased anxiety symptoms, providing evidence for self-medication of these symptoms that is explainable based on animal studies of noradrenergic function. In addition, patients with anxiety disorders frequently report significant improvement of symptoms of hyperarousal and intrusive memories with alcohol, benzodiazepines, and opiates, which decreases LC firing, but worsening of these symptoms with cocaine, which increases LC firing. Many patients with anxiety disorders demonstrate an increased susceptibility to psychosocial stress. Behavioral sensitization may account for these clinical phenomena. In the laboratory model of sensitization, single or repeated exposure to physical stimuli or pharmacological agents sensitizes an animal to subsequent stressors (reviewed in Charney et al., 1993). For example, in animals with a history of prior stress, there is a potentiated release of NE in the hippocampus with subsequent exposure to stressors (Nisenbaum et al., 1991). Similar findings were observed in mPFC (Finlay and Abercrombie, 1991). The hypothesis that sensiti-

41: NEUROBIOLOGY

zation is the underlying neural mechanism contributing to the course of anxiety disorders is supported by clinical studies demonstrating that repeated exposure to traumatic stress is an important risk factor for the development of anxiety disorders, particularly PTSD (Table 41.1). There is compelling evidence that NE plays a role in the pathophysiology of PTSD. Well-designed psychophysiological studies have documented heightened au-

TABLE

661

tonomic or sympathetic nervous system arousal in combat veterans with chronic PTSD (Prins et al., 1995). Because central noradrenergic and peripheral sympathetic systems function in concert (Aston-Jones et al., 1991), the data from these psychophysiological investigations are consistent with the hypothesis that noradrenergic hyperreactivity in patients with PTSD may be associated with the conditioned or sensitized responses to specific traumatic stimuli.

41.1 Neural Mechanisms Related to Pathophysiology and Treatment of Anxiety Disorders

Mechanism

Neurochemical Systems

Brain Regions

Pathophysiology

Treatment Development

Pavlovian (cue-specific) fear conditioning

Glutamate, NMDA receptors, VGCCs

Medial prefrontal cortex, cingulate, dorsal thalamus, lateral amygdala, central nucleus of amygdala

May account for common clinical observation in panic disorder and PTSD that sensory and cognitive stimuli associated with or resembling the frightening experience elicit panic attacks, flashbacks, and autonomic symptoms

Treatment with NMDA receptor antagonist and VGCC antagonist may attenuate acquisition of fear

Inhibitory avoidance (contextual fear)

Norepinephrine/b adrenergic receptor, cortisol/glucocorticoid receptor, CRH, GABA, opioids, acetylcholine

Medial prefrontal cortex, basolateral amygdala, hippocampus, BNST, entorhinal cortex

Excessive stress-mediated release of CRH, cortisol, development of indelible fear memories. Chronic anxiety and phobic symptoms may result from excessive contextual fear conditioning

CRH antagonists and b -adrenergic receptor agonists and NE may have preventive effects

Reconsolidation

Glutamate, NMDA receptors, norepinephrine, b - adrenergic receptors, CREB

Amygdala, hippocampus

Repeated reactivation and reconsolidation may further strengthen the memory trace and lead to persistence of trauma and phobia-related symptoms

Treatment with NMDA receptor and b -adrenergic receptor antagonists after memory reactivation may reduce the strength of the original anxietyprovoking memory

Extinction

Glutamate, NMDA receptors, VGCCs, NE, DA, GABA

Medial prefrontal sensory cortex, amygdala

Failure in neural mechanisms of extinction may relate to persistent traumatic memories, reexperiencing symptoms, autonomic hyperarousal, and phobic behaviors

Psychotherapies need to be developed that facilitate extinction through the use of conditioned inhibitors and the learning of new memories. The combination of extinctionbased psychotherapy and D-cycloserine may be a particularly effective treatment.

Sensitization

Dopaminergic, noradrenergic NMDA receptors

Nucleus accumbens, May explain the adverse amygdala, striatum, effects of early-life trauma hypothalamus on subsequent responses to stressful life events. May play a role in the chronic course of evolution of the many anxiety disorders and, in some cases, the worsening of the illness over time

Suggests that the efficacy of treatment may vary according to the state of evolution of the disease process. Emphasizes the importance of early intervention.

BNST: bed nucleus of the stria terminalis; CREB: cyclic adenosine monophosphate response element binding protein; CRH: corticotropin releasing hormone; GABA: g -aminobutyric acid; NE: norepinephrine; NMDA: N-methyl-D-aspartate; PAG: periaqueductal gray; VGCC: voltage gated calcium channels; PTSD: posttraumatic stress disorder; DA: dopamine.

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Evaluation of plasma and urinary NE concentrations have generally, but not entirely, supported the idea of exaggerated NE activity in patients with PTSD. Yehuda and colleagues found elevated plasma NE levels in combat veterans with PTSD compared to patients with MDD (Yehuda et al., 1998), and elevated 24-hour urinary NE and epinephrine among a group of inpatients with PTSD compared to healthy controls (Yehuda et al., 1992). Plasma levels of NE were found to be elevated throughout a 24-hour collection period in another study (Yehuda et al., 1995), as were cerebrospinal fluid (CSF) levels of NE in patients with PTSD (D.G. Baker et al., 1997). Exposure to traumatic reminders in the form of combat films results in increased epinephrine (McFall et al., 1992) and NE (Blanchard et al., 1991) release. However, some studies have demonstrated no difference in plasma NE levels between patients with PTSD and healthy controls (Southwick et al., 1993), or in urinary 24-hour concentrations (Mellman et al., 1995). Women with PTSD secondary to childhood sexual abuse did have significantly elevated levels of NE, epinephrine, and cortisol in 24-hour urine samples (Lemieux and Coe, 1995), and girls who were sexually abused excreted significantly greater amounts of catecholamine metabolites, metanephrine, vanillylmandelic acid, and homovanillic acid than girls who were not sexually abused (DeBellis et al., 1994). A more recent investigation of CSF NE in patients with PTSD found a positive association between severity of PTSD symptoms and CSF NE level (Geracioti et al., 2001). A second study by this group found that CSF NE levels correlated with mean systolic blood pressure in healthy controls but not in patients with PTSD, further suggesting an uncoupling of central and peripheral NE function in patients with PTSD (Strawn et al., 2004). Studies of peripheral NE function have demonstrated alterations in a-2-AR function and the cAMP signal transduction system in patients with PTSD. Decreases in platelet a-2-AR number (Perry et al., 1987), platelet basal adenosine, isoproterenol, forskolin-stimulated cAMP signal transduction (Lerer et al., 1987), and basal platelet monoamine oxidase (MAO) activity (Davidson et al., 1985) have been found in PTSD. These findings may reflect chronic high levels of NE release that would lead to compensatory receptor down-regulation and decreased responsiveness. Patients with combat-related PTSD compared to healthy controls had enhanced behavioral, biochemical, and cardiovascular responses to the a-2-AR antagonist yohimbine, which stimulates central NE release (Southwick et al., 1993; Southwick et al., 1997). Moreover, a positron emission tomography (PET) study demonstrated that patients with PTSD have a cerebral metabolic response to yohimbine consistent with increased NE release (Bremner, Innis, et al., 1997).

There is considerable evidence that abnormal regulation of brain noradrenergic systems is also involved in the pathophysiology of panic disorder. Patients with panic disorder are very sensitive to the anxiogenic effects of yohimbine in addition to having exaggerated plasma 3-methoxy-4 hydroxyphenylethylene glycol (MHPG), cortisol, and cardiovascular responses (Charney et al., 1984; Charney et al., 1987a; Gurguis and Uhde, 1990; Albus et al., 1992; Charney et al., 1992; Yeragani et al., 1992). Children with a variety of anxiety disorders exhibit greater anxiogenic responses to yohimbine than normal comparison children (Sallee et al., 2000). The responses to the a-2-AR agonist clonidine are also abnormal in patients with panic disorder. Clonidine administration caused greater hypotension, greater decreases in plasma MHPG, and less sedation in patients with panic than in controls (Uhde et al., 1988; Nutt, 1989; Coplan, Papp, et al., 1995; Coplan, Pine, et al., 1995; Marshall et al., 2002). Few studies have examined noradrenergic function in patients with phobic disorders. In patients with specific phobias, increases in subjective anxiety and increased heart rate, blood pressure, plasma NE, and epinephrine have been associated with exposure to the phobic stimulus (Nesse et al., 1985). This finding may be of interest from the standpoint of the model of conditioned fear, reviewed above, in which a potentiated release of NE occurs in response to a reexposure to the original stressful stimulus. Patients with social phobia have been found to have greater increases in plasma NE than healthy controls and patients with panic disorder (Stein et al., 1992). In contrast to patients with panic disorder, the density of lymphocyte a-2-AR is normal in patients with social phobia (Stein et al., 1993). The growth hormone response to intravenous clonidine (a marker of central a2-receptor function) is blunted in patients with social phobia (Tancer et al., 1990) (Table 41.2). Hypothalamic-Pituitary-Adrenal (HPA) Axis There is consistent evidence that many forms of psychological stress increase the synthesis and release of cortisol. Cortisol serves to mobilize and replenish energy stores and contributes to increased arousal, vigilance, focused attention, and memory formation, as well as inhibition of the growth and reproductive systems and containment of the immune response. Cortisol has important regulatory effects on brain regions important for fear and anxiety including the hippocampus, amygdala, and PFC. Glucocorticoids can enhance amygdala activity, increase CRH messenger ribonucleic acid (mRNA) concentrations in the CEA (Makino et al., 1994, 1995; Shepard et al., 2000), increase the effects of CRH on conditioned fear, and facilitate the encoding of emotion-related memory (Roozendaal, 2000).

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41.2 Evidence for Altered Catecholaminergic Function in Anxiety Disorders TABLE

PTSD

Panic Disorder

Increased resting heart rate and blood pressure at rest

+/−

+/−

Increased heart rate and blood pressure response to traumatic reminders/panic attacks

+++

++

Increased resting urinary NE and E

+

+/−

Increased resting plasma NE or MHPG

++

−

Increased plasma NE with traumatic reminders/panic attacks

+

+/−

Decreased binding to platelet a 2 receptors

+

+/−

Decrease in basal and stimulated activity of cAMP

+/−

−

Decrease in platelet MAO activity

−

NS

Increased symptoms, heart rate, and plasma MHPG with yohimbine noradrenergic challenge

++

+++

Differential brain metabolic response to yohimbine

+

+

−, one or more studies did not support this finding (with no positive studies) or the majority of studies do not support this finding; +/−, an equal number of studies do and do not support this finding; +, at least one study supports this finding and no studies do not support the finding or the majority of studies support the finding; ++, two or more studies support this finding and no studies do not support the finding; +++, three or more studies support this finding, and no studies do not support the finding. PTSD: posttraumatic stress disorder; NE: norepinephrine; E: epinephrine; MHPG: 3-methosy-4-hydroxyphenylglycol; cAMP: cyclic adenosine 39,59monophosphate; MAO: monoamine oxidase; NS: not studied.

Interestingly, this glucocorticoid enhancement of emotional memory has recently been shown to be dependent on arousal-induced endogenous activation of NE in the amygdala (Roozendal, Hui, et al., 2006; Roozendal, Okuda, et al., 2006). Adrenal steroids such as cortisol have biphasic effects on hippocampal excitability and cognitive function and memory (Diamond et al., 1996). These effects contribute to adaptive alterations in behaviors induced by cortisol during the acute response to stress. It is key, however, that the stress-induced increases in cortisol ultimately be constrained through an elaborate negative feedback system involving GR and mineralocorticoid receptors (MR). The hippocampus has a very high concentration of corticosteroid receptors and plays an important role in GR-mediated negative feedback of the HPA axis. Excessive, sustained cortisol secretion can have serious adverse effects on the body including hypertension, osteoporosis, immunosuppression, insulin resistance, dyslipidemia, dyscoagulation, and, ultimately, atherosclerosis and cardiovascular disease (Karlamangla et al., 2002). In the brain, a sustained

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increase in glucocorticoid levels negatively affects multiple aspects of neural cell structure and function in the hippocampus, including impaired cell survival, altered metabolism, and changes in cell morphology, and adversely affects hippocampal-dependent cognitive and memory function (McEwen, 2000). Antidepressants have demonstrated the ability to decease the negative effects of stress-related glucocorticoid elevations on hippocampal structure and function, at least in part by promoting neurogenesis and/or reducing apoptosis (Malberg et al., 2000). Alterations in the HPA axis and the hippocampus have been demonstrated in patients with PTSD. Studies of baseline peripheral cortisol levels using 24-hour measurement have yielded mixed results, although the preponderance of data suggest either normal or lower levels of cortisol, contrary to original expectations (Rasmusson et al., 2001; Yehuda, 2006). However, a recent study did demonstrate elevated CSF concentrations of cortisol in eight patients with PTSD, suggesting a dissociation between peripheral and CNS cortisol levels (D.G. Baker et al., 2005). Patients with chronic PTSD consistently demonstrate increased suppression of cortisol with low-dose dexamethasone, the opposite pattern to that of major depression. Using a cognitive challenge paradigm, Bremner and colleagues (2003) demonstrated increased cortisol levels during a prestress anticipatory anxiety period and in response to the stressor in patients with PTSD, although low baseline 24 hour cortisol during a resting period, compared to controls. Patients with PTSD may also have an increased number of GRs on peripheral lymphocytes. An increase in GR function in central brain structures such as the hypothalamus or hippocampus may result in enhanced suppression of cortisol feedback and therefore decreased peripheral cortisol levels (Yehuda, 2002, 2006). Overall, the character of the HPA axis in PTSD appears to be one of decreased peripheral cortisol and increased central feedback sensitivity, although the clinical significance of these findings remains to be determined. Consistent with preclinical evidence of stress- and glucocorticoidmediated hippocampal impairments, several studies have now replicated the original finding of reduced hippocampal volume in patients with PTSD (Bremner, 2006). Please see Chapter 43 of this volume for a complete discussion of neuroanatomical and neuroimaging findings in PTSD. Studies of HPA axis function in patients with panic disorder have been inconsistent, although an increased “central drive” is suggested. Blunted adrenocorticotropic hormone (ACTH) responses to CRH have been reported in some studies (Roy-Byrne, Uhde, Post, et al., 1986; Holsboer et al., 1987) but not in others (Rapaport et al., 1989). Normal and elevated rates of cortisol nonsuppression following dexamethasone (DEX) administration have been reported (Coryell and Noyes, 1988).

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The responsiveness of the HPA system to a combined DEX-CRH challenge test was found to be higher in patients with panic disorder than in healthy controls but lower than in patients with depression (Roy-Byrne, Uhde, Post, et al., 1986; Rapaport et al., 1989). Urinary-free cortisol test results have been inconsistent (Kathol et al., 1988; Uhde et al., 1988). In a study of 24-hour secretion of ACTH and cortisol in panic disorder, only subtle abnormalities were seen. Patients had elevated overnight cortisol secretion and greater amplitude of ultraradian secretory episodes (Abelson and Curtis, 1996). Patients with more severe panic disorder symptoms may be more likely to have elevated cortisol secretion (Bandelow et al., 2000). Interestingly, a study of cognitive intervention in patients with panic disorder and healthy controls found that the intervention was able to significantly reduce the elevation of cortisol and ACTH by pentagastrin challenge, although it had no effect on panic symptoms (Abelson et al., 2005). In a recent review of their own data utilizing circadian and challenge paradigms, Abelson et al. (2007) argued that panic disorder is associated with HPA axis hypersensitivity to environmental contextual cues such as novelty, rather than baseline hyperactivity per se (Table 41.3). Corticotropin Releasing Hormone Corticotropin releasing hormone is one of the most important mediators of the stress response, coordinat-

TABLE 41.3 Evidence for Alterations in CRF-HPA Axis Function in Anxiety Disorders

PTSD

Panic Disorder

+/−a

+/−

Altered plasma cortisol with 24-hour sampling

++ (dec.)

+ (inc.)

Supersuppression with DST

+++

NS

Blunted ACTH response to CRF

+/−

+/−

Elevated CRF in CSF

++

−

Increased lymphocyte glucocorticoid receptors

++

NS

Alterations in urinary cortisol

−, one or more studies did not support this finding (with no positive studies) or the majority of studies do not support this finding; +/−, an equal number of studies do and do not support this finding; +, at least one study supports this finding and no studies do not support the finding or the majority of studies support the finding; ++, two or more studies support this finding and no studies do not support the finding; +++, three or more studies support this finding, and no studies do not support the finding. aFindings of decreased urinary cortisol in older male combat veterans and Holocaust survivors and increased cortisol in younger female abuse survivors may be explainable by differences in gender, age, trauma type, or developmental epoch at the time of the trauma. ACTH: adrenocorticotropic hormone; CRF: corticotropin releasing factor; CSF: cerebrospinal fluid; dec.: decrease; DST: dihydrostreptomycin; HPA: hypothalamic-pituitary-adrenal axis; inc.: increase; NS: not studied; PTSD: posttraumatic stress disorder.

ing the adaptive behavioral and physiological changes that occur during stress (Grammatopoulos and Chrousos, 2002). Mounting preclinical and clinic evidence implicates CRH dysregulation in human anxiety disorders and depression. Hypothalamic levels of CRH are increased by stress, resulting in activation of the HPA axis and increased release of cortisol and dehydroepiandrosterone (DHEA). Equally important are the extrahypothalamic effects of CRH. Neurons containing CRH are located throughout the brain, including the prefrontal and cingulate cortices, central nucleus of the amygdala, BNST, nucleus accumbens, periaqueductal gray (PAG), and brain-stem nuclei such as the major NE-containing nucleus, the LC, and the serotonin nuclei in the dorsal and median raphé (Steckler and Holsboer, 1999). Increased activity of CRH-containing neurons in the amygdala is associated with fear-related behaviors, whereas cortical CRH may reduce reward expectation. In animals, CRH inhibits a variety of appetitive functions such as food intake, sexual activity, and endocrine programs for growth and reproduction, whereas administration of CRH antagonists increases appetitive and sexual behaviors. It appears that early-life stress can produce long-term elevation of brain CRH activity, and that the individual response to heightened CRH function may depend upon the social environment, past trauma history, and behavioral dominance (Brunson et al., 2001; Strome et al., 2002). Persistent elevation of hypothalamic and extrahypothalamic CRH contributes greatly to the psychobiological allostatic load. CRH-1 and CRH-2 receptors are found in the pituitary gland and throughout the neocortex (especially in prefrontal, cingulate, striate, and insular cortices), amygdala, and hippocampal formation in the primate brain. The presence of CRH-1 (but not CRH-2) receptors within the LC, nucleus of the solitary tract, thalamus, and striatum, and the presence of CRH-2 (but not CRH-1) receptors in the choroid plexus, certain hypothalamic nuclei, the nucleus prepositus, and BNST suggest that each receptor subtype has distinct roles within the primate brain (Sanchez et al., 1999). Mice deficient in CRH-1 display decreased anxietylike behavior and an impaired stress response (Bale et al., 2002). In contrast, CRH-2-deficient mice display increased anxiety-like behavior and are hypersensitive to stress (Bale et al., 2000; Coste et al., 2000). Thus, evidence exists in favor of opposite functional roles for the two known CRH receptors; activation of CRH-1 receptors may be responsible for increased anxiety-like responses, and stimulation of CRH-2 receptors may produce anxiolytic-like responses. Regulation of the relative contributions of the two CRH receptor subtypes to brain CRH pathways may be essential to coordinating psychological and physiological responses to stressors (Bale et al., 2002). Thus far, it has not been possible

41: NEUROBIOLOGY

to evaluate CRH-1 and CRH-2 receptors in living humans, although efforts are ongoing to develop CRH receptor PET ligands. Given the evidence for anxiogenic effects of CRH-1 receptor stimulation, the development of CRH-1 antagonists constitutes a promising future pharmacotherapy for anxiety disorders, and clinical investigations in humans are currently under way for PTSD, as well as major depression (Risbrough and Stein, 2006; Valdez, 2006). Most studies of the CRH system in humans have focused on major depression and suggest excessive CRH activity. Available evidence also points to increased CRH activity in PTSD. It was recently reported that patients with PTSD had higher plasma CRH levels compared to traumatized veterans without PTSD and healthy volunteers (de Kloet, Vermetten, Geuze, Lentjes et al., 2008). Bremner, Licinio, and colleagues (1997) found increased levels of CRH in the CSF in patients with combatrelated chronic PTSD based upon a single lumbar puncture determination. D.G. Baker and associates (1997) found elevations of CSF CRH throughout a 24-hour period. These findings are important to consider in the context of preclinical studies demonstrating that basal CSF CRH is elevated in primates that have experienced early life stress (Coplan et al., 1996); that the effects of CRH on behavior occur in a context-dependent manner (Strome et al., 2002); and that early-life exposure of the hippocampus to elevated levels of CRH is associated with hippocampal damage later in life (Brunson et al., 2001). Intracerebroventricular injection of CRH produces an increase in hippocampal MR levels, suggesting that CRH is an important regulator of HPA axis regulation. A single nucleotide polymorphism (SNP) in the CRH gene has recently been associated with behavioral inhibition, a childhood trait that predicts adult anxiety, although the functional impact of the SNP on CRH has yet to be determined (Smoller et al., 2003; Smoller et al., 2005). The findings of elevated CRH in PTSD may be related to the clinical observation that early-life stress increases the risk of developing PTSD following traumatic stress exposure later in life. Whether elevated CRH is a trait vulnerability for the development PTSD, or is a state-dependent marker of PTSD, is an important question that has yet to be resolved. Elevated CRH in the hippocampus may relate to the mechanism responsible for reduced hippocampal volume observed in PTSD. Finally, the ability of CRH to increase MR density may provide an explanation for the elevated CRH and normal-to-low cortisol levels found in some patients with PTSD (Table 41.3). Neurosteroids Certain steroids are considered neuroactive steroids, or neurosteroids, by their influence on neuronal function.

665

This occurs by their binding to intracellular receptors, which may act as transcription factors in the regulation of gene expression (Rupprecht, 2003). Several neurosteroids, particularly 3a -reduced metabolites of progesterone and deoxycorticosterone, modulate ligandgated channels via nongenomic mechanisms (Strömberg et al., 2006). They are positive modulators of GABA-A receptors through the central nucleus of the amygdala, in a process involving NMDA receptors (Wang et al., 2007). Thus, they have been shown to have anxiolytic effects in animal models (Vanover et al., 2000). They counteract the anxiogenic effects of CRH and reduce CRH gene expression (Rupprecht, 2003). In challenge studies of patients with panic disorder, cholecystokinin-4 (CCK-4) and lactate-induced panic attacks are associated with a decrease in the metabolites 3a, 5a -tetrahydroprogesterone (THP) (allopregnanolone, ALLO), 3, 5b -THP (pregnanolone), and an increase in 3B, 5a -THP in patients with panic disorder, suggesting that a decrease in GABA tone that does not occur in healthy subjects (Ströhle et al., 2003; Zwanzger et al., 2004; Eser et al., 2005). Interestingly, Eser et al. (2005) did find an increase in 3a, 5a -tetrahydrodeoxycorticosterone (THDOC) after CCK-4-induced panic in healthy volunteers. Progesterone has been shown to have anxiolytic effects in animal models, which was shown to be a result of the increase in ALLO (Bitran et al., 1993; Reddy et al., 2005). Studies of neurosteroid levels in patients with social phobia and GAD have been inconsistent, with some showing decreased pregnenolone plasma levels, but no significant change in other steroids such as ALLO (Semeniuk et al., 2001; Heydari and Le Mellédo, 2002), and others showing no difference between groups (Laufer et al., 2005). Rasmusson et al. (2006) found decreased CSF ALLO in premenopausal women with PTSD. Studies in panic disorder have found elevated progesterone levels in female patients with panic disorder during the mid-luteal and premenstrual phase, a finding suggesting that 3a -reduced neurosteroids may serve as a counterregulatory mechanism against spontaneous panic attacks (Brambilla et al., 2003). Consistent with the increase in progesterone during pregnancy, it has been shown in animal studies that anxiety behaviors decrease as well, an effect that is reversed by finasteride (de Brito Faturi et al., 2006; Mann, 2006). A study of pregnant women found an improvement in baseline anxiety scores in healthy subjects (Paoletti et al., 2006) and those with preexisting panic disorder (Hertzberg and Wahlbeck, 1999), correlated with increased levels of ALLO and THDOC. Finally, neurosteroids may play a role in the antidepressant and anxiolytic mechanism of selective serotonin reuptake inhibitors (SSRIs). Animal models of induced stress have shown that agents such as fluoxetine increase brain ALLO or normalize decreased brain

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ANXIETY DISORDERS

ALLO, by a nonserotonergic mechanism (Pinna et al., 2006; Matsumoto et al., 2007). To date, the development of neurosteroids as potential treatment of anxiety disorders has been limited. The availability of synthetic analogues of 3a -reduced neuroactive steroids (for example, ganaxolone) can test the concept that such compounds might have anxiolytic efficacy (Eser at al., 2006). Arginine Vasopressin CRH and arginine vasopressin (AVP) are the major secretagogues of the HPA/stress system. However, AVP has been studied much less than CRH, and our knowledge of the functional activity and pharmacology of AVP and its receptors in the regulation of HPA activity rests largely on studies conducted in rodents. Arginine vasopressin has ACTH-releasing properties when administered alone in humans, a response that may be dependant on the ambient endogenous CRH level. Following the combination of AVP and CRH, a much greater ACTH response is seen, and both peptides are required for maximal pituitary-adrenal stimulation. The sensitivity of CRH and AVP transcription to glucocorticoid feedback apparently differs, and AVP-stimulated ACTH secretion may be refractory to glucocorticoid feedback (Tilbrook and Clarke, 2006). Vasopressinergic regulation of the HPA axis may therefore be critical for sustaining corticotrophic responsiveness in the presence of high-circulating glucocorticoid levels during chronic stress (Makara et al., 2004). S. Watson et al. (2006) found elevated AVP in subjects with bipolar and depression disorders after a DEX suppression test. In animals deficient for the CRH-1 receptor, selective compensatory activation of the hypothalamic AVP system occurs, which maintains basal ACTH secretion and HPA activity (Müller et al., 2000). Similar response patterns have been observed following chronic stress, leading to the hypothesis that CRH plays a predominantly permissive role in HPA regulation but that AVP represents the dynamic mediator of ACTH release (Aguilera and Rabadan-Diehl, 2000). Arginine vasopressin is produced by the parvocellular neurons of the paraventricular nucleus and is secreted into the pituitary portal circulation from axon terminals projecting to the external zone of the median eminence (Engelman et al., 2004). It is primarily released following a variety of stimuli including increasing plasma osmolality, hypovolemia, hypotension, and hypoglycemia. In addition to its role in fluid metabolism regulation, AVP has been implicated in learning and memory processes, pain sensitivity, synchronization of biological rhythms, and the timing and quality of rapid eye movement sleep. Extrahypothalamic AVPcontaining neurons have also been characterized in the rat, notably in the medial amygdala, that innervate lim-

bic structures such as the lateral septum and the ventral hippocampus. In these latter structures, AVP was suggested to act as a neurotransmitter, exerting its action by binding to specific G protein–coupled receptors, that is, V1A and V1B, which are widely distributed in the CNS, including the septum, cortex, and hippocampus (Hernando et al., 2001). Studies have shown V1A receptor knockout mice to have reduced anxiety behaviors in tasks such as the elevated plus maze and forced swim, suggesting a significant role of AVP in social recognition (Bielsky et al., 2004; Egashira et al., 2007). In addition, overexpression of V1A caused increased anxiety behaviors (Bielsky et al., 2005). In recent years, AVP V1B antagonists, in particular SSR 149415, have exhibited significant anxioloytic and antidepressant effects in various classical animal models (Griebel et al., 2002; Salomé et al., 2006; Shimazaki et al., 2006; Hodgson et al., 2007). There is work under way to develop these agents as antidepressants and anxiolytics (Serradeil-Le Gal et al., 2005). In the first reported AVP-related study conducted in patients with anxiety disorder (Maes et al., 1999), increased serum prolyl endopeptidase (an AVP-degradating enzyme) activity was found in PTSD, suggesting a lower AVP concentration in PTSD, leading to decreased HPA axis activity in this disorder. This finding is of particular interest given the discrepant findings of increased CSF CRH levels and normal-low cortisol reported for PTSD. Also, a recent study found elevated plasma AVP in male veterans with PTSD, compared to veterans without PTSD and healthy controls (de Kloet, Vermetten, Geuze, Wiegant et al., 2008). Therefore, AVP may play a pivotal role in PTSD. In a study using intransal AVP administration to healthy men and women (aged 17– 24), Thompson and others (2006) reported that AVP, versus placebo, attenuated heart rate and skin conductance responses to angry faces. There was also a sex difference in regards to the effects of AVP versus placebo on social recognition, with men having greater agonistic facial muscle response and decreased perception of friendliness to unfamiliar male faces, whereas women had the opposite response when presented with unfamiliar female faces. Sex differences have been found in animal studies as well and were hypothesized to be related to testosterone (Toufexis et al., 2005). Additional studies of AVP function in other anxiety disorders are indicated. Neuropeptide Y Neuropeptide Y (NPY) is a highly conserved 36 amino acid peptide and is among the most abundant peptides found in the mammalian brain. To date, a total of seven NPY receptor subtypes (Y1–Y7) have been identified, with only Y1–Y5 being found in mammals. There are four brain areas in which neurons containing NPY are

41: NEUROBIOLOGY

densely concentrated: the LC (Makino et al., 2000), paraventricular nucleus of the hypothalamus (R.A. Baker and Herkenham, 1995), septohippocampal neurons (Risold and Swanson, 1997), and nucleus of solitary tract and ventrolateral medulla (Pieribone et al., 1992). Moderate levels are found in the amygdala, hippocampus, cerebral cortex, basal ganglia, and the thalamus (Allen et al., 1983). Evidence suggesting the involvement of the amygdala in the anxiolytic effects of NPY is robust and probably occurs via the NPY-Y1 receptor (Heilig et al., 1993; Heilig, 1995; Sajdyk, Vandergriff, et al., 1999). Microinjection of NPY into the central nucleus of the amygdala reduces anxious behaviors. The up-regulation of amygdala NPY mRNA levels following chronic stress suggests that NPY may be involved in the adaptive responses to stress exposure (Thorsell et al., 1999). Primeaux et al. (2005) showed in rats that NPY overexpression, accomplished by a Herpes virus vector, caused increased amygdalar NPY, and increased time in open arms of mazes, as compared to rats with reduced amygdalar NPY. Their study also showed that injection of an NPY-1 antagonist bilaterally into the amygdala had a reduction of time in the open maze (a sign of increased anxiety behavior), compared to rats receiving saline. Treatment of rats exposed to maternal separation with acupuncture increased NPY expression in the BLA reduced anxiety-like behaviors (Park et al., 2005). In addition, NPY may be involved in the consolidation of fear memories; injection of NPY into the amygdala impairs memory retention in a foot shock avoidance paradigm (Flood et al., 1989). It is thought that NPY exerts its anxiolytic effects via modulation of the glutamatergic system, as evidenced by changes in NPY mRNA after administration of Glu receptor agonists (Wieron´ska et al., 2005). The anxiolytic effects of NPY also involve the LC, possibly via the NPY-Y2 receptor. Also, NPY reduces the firing of LC neurons (Illes et al., 1993). Finally, NPY has behaviorally relevant effects on the hippocampus. Transgenic rats with hippocampal NPY overexpression have attenuated sensitivity to the behavioral consequences of stress and impaired spatial learning (Thorsell et al., 2000). Intrahippocampal injection of NPY into rats had an anxiolytic effect via Glu receptor ligands, which was blocked by injection of Y1 and Y2 antagonists (Smiałowska et al., 2007). There are important functional interactions between NPY and CRH (Heilig et al., 1994; Britton et al., 2000). Neuropeptide Y counteracts the anxiogenic effects of CRH, and a CRH antagonist blocks the anxiogenic effects of an NPY-Y1 antagonist (Kask et al., 1997). The antagonistic interaction has been shown to be related to bidirectional synaptic GABAergic transmission in the BNST (Kash and Winder, 2006). Thus, it has been suggested that the balance between NPY and CRH neurotransmission is important to the emotional responses

667

to stress (Heilig et al., 1994). In general, brain regions that express CRH and CRH receptors also contain NPY and NPY receptors, and their functional effects are often opposite (Kask et al., 2002) especially at the level of the LC (Smagin et al., 1996; Kask et al., 1998a), amygdala (Sajdyk, Vandergriff, et al., 1999; Sheriff et al., 2001), and PAG (Kask et al., 1998b; Martins et al., 2001). These data suggest an important role for the NPY system in the psychobiology of resilience and vulnerability to stress. Neuropeptide Y has counterregulatory effects on CRH and LC-NE systems at brain sites that are important in the expression of anxiety, fear, and depression. Preliminary studies in special operations soldiers under extreme training stress indicate that high NPY levels are associated with better performance (C.A. Morgan et al., 2000; C.A. Morgan et al., 2002). Patients with PTSD have been shown to have reduced plasma NPY levels and a blunted yohimbine-induced NPY increase (Rasmusson et al., 2000). A study comparing plasma NPY levels in combat veterans with PTSD, healthy combat veterans, and healthy noncombat veterans found that the combat veterans had lower plasma NPY, while there was no difference between the veterans with and without PTSD (C.A. Morgan et al., 2003). This suggests that trauma exposure itself, independent of the development of PTSD, has a role in regulating stress and peptide levels. Liberzon et al. (2007) reported a similar finding in opioid peptide receptors (see below). A recent study of patients recovered from PTSD showed that they had increased plasma NPY (Yehuda et al., 2006). Studies of NPY levels in other anxiety disorders are limited. Rasmusson et al. (1998) showed an increase in plasma NPY in subjects receiving the panicogen yohimbine, compared to saline placebo. One trial failed to show a difference in plasma NPY levels among patients with panic disorder, social phobia, and normal controls (Stein et al., 1996). To date, there are no published studies of NPY for the treatment of anxiety disorders. Antoninjevic et al. (2000) administered NPY intravenously to healthy volunteers and found it to increase sleep, by a mechanism of HPA axis inhibition. It has been shown that NPY can be administered safely via an intranasal route and rapidly cross the BBB (Born et al., 2002). Intranasal NPY has been studied in healthy volunteers to evaluate its systemic effects (Lacroix et al., 1996; Hallschmid et al., 2003). Further investigations of this unique mode of administration are currently under way, with the hope to apply these findings to develop novel therapeutics for mood and anxiety disorders. Galanin Galanin is a peptide that, in humans, contains 30 amino acids. It has been demonstrated to be involved in a

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number of physiological and behavioral functions including learning and cognition, pain control, food intake, neuroendocrine control, cardiovascular regulation, and, more recently, depression, and anxiety (Karlsson and Holmes, 2006). Approximately 80% of noradrenergic cells in the LC coexpress galanin. A dense galanin immunoreactive fiber system originating in the LC innervates forebrain and midbrain structures including the hippocampus, hypothalamus, amygdala, and PFC (Gentleman et al., 1989; P.V. Holmes and Crawley, 1995; Perez et al., 2001; Hawes and Picciotto, 2004). Neurophysiological studies have shown that galanin reduces the firing rate of the LC, possibly by stimulating the galanin-1 receptor (Gal-R1) (Sevcik et al., 1993; Xu et al., 2001; Hawes et al., 2005).The mechanism by which galanin reduces NE release at LC projections to the amygdala, hypothalamus, and PFC may be via a direct action of galanin on these brain regions via galanin-synthesizing neurons or by stimulating galanin receptors in these regions (Khoshbouei, Cecchi, Dove, et al., 2002; Xu et al., 2001). Of the three known galanin receptor subtypes (GalR1, Gal-R2, Gal-R3), Gal-1 has also been shown to play a role in fear processes, Gal-R1 receptor mRNA levels are high in the amygdala, hypothalamus, and BNST (Gustafson et al., 1996), and Gal-R1-deficient mice show increased anxiety-like behavior (A. Holmes, Kinney, et al., 2003). Gottsch and others (2005) reported that Gal-R2 receptor knockout mice were found to have no behavioral or physiological changes in response to contextual fear conditioning or stress-induced hypothermia, whereas K.R. Bailey et al. (2007) found anxiogenic-like phenotype to the elevated-plus maze (EPM) task only. Galanin-overexpressing transgenic mice do not exhibit an anxiety-like phenotype when tested under baseline (nonchallenged) conditions. However, these mice are unresponsive to the anxiogenic effects of the a -2 receptor antagonist, yohimbine (A. Holmes, Yang, and Crawley, 2002). Consistent with this observation, galanin administered directly into the CEA blocks the anxiogenic effects of stress, which is associated with increased NE release in the CEA. Yohimbine increases galanin release in the CEA (Khoshbouei, Cecchi, Dove, et al., 2002; Barrera et al., 2006). Galanin administration and galanin overexpression in the hippocampus result in deficits in fear conditioning (Kinney et al., 2002). Studies in rats have shown that galanin administered centrally modulates anxiety-related behaviors, exhibiting effects that were either anxiolytic (Bing et al., 1993; Karlsson et al., 2005) or anxiogenic (Moller et al., 1999; Khoshbouei, Cecchi, and Morilak, 2002). Recently, Rajarao and others (2007) reported that galnon, a galanin receptor agonist, had anxiolytic-like properties that were reversible when M35, a galanin receptor antagonist, was injected. A similar finding was reported on a Forced

Swim Test with rats, suggesting an antidepressant effect of galanin as well (Kuteeva et al., 2007). It should be noted, however, that Gal-R3 antagonists, SNAP 37889 and SNAP 398299, were found to have anxiolytic and antidepressant properties in several animal models, such as forced swim and stress-induced hyperthermia (Swanson et al., 2005). This study suggests that the galanin exerts this effect by demonstrating a diminishing of inhibition of 5-HT receptors in the hippocampus. The study of galanin function in persons with psychiatric illness has been limited. A study of postmenopausal women compared to women of normal menstruation reported lower serum galanin levels in postmenopausal women with climacteric symptoms and ratings of subjective nervousness (Słopie c´ et al., 2004). To date, there is only one known study of galanin in anxiety disorders. Unschuld et al. (2008) conducted a genetic study of men and women with panic disorder, investigating six SNPs of the galanin gene. They reported a statistically significant association between severity of symptoms and two haplotypes, but only in the female patients. This finding, taken with the preclinical studies, should provide the impetus for the use of galanin receptor agonists as novel targets for antianxiety drug development (Karlsson and Holmes, 2006). Dopaminergic System In animals, acute stress influences dopamine (DA) release and metabolism in a number of specific brain areas important in affective behavior, including the basolateral nucleus of the amygdala, the nucleus accumbens and the mPFC. Dopamine innervation of the mPFC appears to be particularly vulnerable to stress; lowintensity stress (such as that associated with conditioned fear) or brief exposure to stress increases DA release and metabolism in the PFC in the absence of overt changes in other mesotelencephalic DA regions. Lowintensity electric foot shock increases in vivo tyrosine hydroxylase and DA turnover in the mPFC, but not in the nucleus accumbens or striatum. Stress can enhance DA release and metabolism in other areas receiving DA innervation, provided that greater-intensity or longerduration stress is used. Thus, mPFC DA innervation is preferentially activated by stress compared to mesolimbic and nigrostriatal systems, and the mesolimbic DA innervation appears to be more sensitive to stress than the striatal DA innervation (Deutch and Young, 1995). Uncontrollable stress activates mPFC DA release (Ventura et al., 2002) and inhibits nucleus accumbens DA release (Cabib and Puglisi-Allegra, 1996; Cabib et al., 2002), which may reflect reciprocal interactions between cortical and subcortical DA targets. Lesions of the amygdala before and after training in a CS model

41: NEUROBIOLOGY

block stress-induced mPFC DA metabolic activation, suggesting amygdala control of stress-induced DA activation and a role for integrating the behavioral and neuroendocrine components of the stress response (Goldstein et al., 1996). There is preclinical evidence that the susceptibility of the mesocortical DA system to stress activation may be in part genetically determined. It has been suggested that excessive mesocortical DA release by stressful events may represent a vulnerability to depression and favor helpless reactions through an inhibition of subcortical DA transmission (Cabib et al., 2002; Ventura et al., 2002). These observations may be due to the effect of DA on reward mechanisms. On the other hand, lesions of mPFC DA neurons delay extinction of the conditioned fear stress response (no effect on acquisition), indicating that prefrontal DA neurons are involved in facilitating extinction of the fear response. This suggests that reduced prefrontal cortical DA results in the preservation of fear produced by a conditioned stressor, a situation hypothesized to occur in PTSD (Morrow et al., 1999). One way to reconcile these two sets of data is to suggest that there is an optimal range for stress-induced increases in mPFC cortical DA release to facilitate adaptive behavioral responses. Too much mPFC cortical DA release produces cognitive impairment, and an inhibition in nucleus accumbens DA activity results in abnormalities in motivation and reward mechanisms. Insufficient prefrontal cortical DA release delays extinction of conditioned fear. Several clinical investigations have reported increased urinary and plasma DA concentrations (Hamner and Diamond, 1993; Lemieux and Coe, 1995) in PTSD. Two candidate genes in the DA system that have been investigated to date in PTSD are the gene for the DA D2 receptor (DRD2) and the dopamine transporter gene (DAT) (Broekman et al., 2007). DRD2 has been previously implicated in substance abuse, attentiondeficit/hyperactivity disorder (ADHD), and Tourette’s syndrome. Although an associated between the DRD2 A1 allele and PTSD was initially reported (Comings et al., 1996), this was not replicated by a subsequent study (Gelernter et al., 1999). A later study found an association between the DRD2 A1 allele and PTSD, but only in individuals with significant comorbid alcohol abuse (Young et al., 2002). The only study to date of the DAT gene in PTSD did find an association between the DAT SLC6A3 3'-variable number tandem repeat (VNTR) and DA reactivity in patients with PTSD. The clinical significance of this finding remains to be determined. Roy-Byrne, Uhde, Post, et al. (1986) found a higher concentration of the DA metabolite homovanillic acid in plasma in patients with panic disorder with high levels of anxiety and frequent panic attacks. Patients with panic disorder were shown to have a greater growth

669

hormone response to the DA agonist apomorphine than patients with depression (Pichot et al., 1992). However, Eriksson et al. (1991) found no alteration in CSF homovanillic acid levels in patients with panic disorder and no correlations with anxiety severity or panic attacks. Catechol-O-methyltransferase (COMT) catalyzes the degradation of DA and the Val158Met polymorphism demonstrated an association with phobic anxiety in a large group of healthy woman (McGrath et al., 2004). A recent meta-analysis of six case-control studies of COMT Val158Met in panic disorder found no overall association but did find a significant association of the 158Val allele in Caucasian populations, and on the other hand, a trend towards association of the 158Met allele in Asian populations (Domschke et al., 2007). There is preliminary evidence that a reduced density of the DA transporter and D2 receptor density exists in patients with social anxiety disorders (Tiihonen et al., 1997; Schneier et al., 2000). Serotonin Different types of acute stress result in increased serotonin (5-HT) turnover in the PFC, nucleus accumbens, amygdala, and lateral hypothalamus (Kent et al., 2002; Briones-Aranda et al., 2005). Serotonin release may have anxiogenic and anxiolytic effects, depending upon the region of the forebrain involved and the receptor subtype activated. According to the hypothesis of Deakin and Graeff (1991), serotonin, released from the dorsal raphé nucleus, has a dual role in anxiety: acting via the amygdala and PFC to regulate defensive responses to threats and anticipatory anxiety (as seen in GAD); and, activating the dorsal periaqueductal gray (dPAG), thereby inhibiting defensive behaviors such as fight or flight (associated with panic disorder). For example, anxiogenic effects are mediated via the 5-HT2A receptor, whereas stimulation of 5-HT1A receptors is anxiolytic and may even relate to adaptive responses to aversive events (Charney and Drevets, 2002; Graeff, 2004). Understanding the function of the 5-HT1A receptor is probably most pertinent to the current review. The 5-HT1A receptors are found in the superficial cortical layers, hippocampus, amygdala, and raphé nucleus (primarily presynaptic) (Hamon et al., 1990; Varnas et al., 2004). The behavioral phenotype of 5-HT1A knockout mice includes increases in anxiety-like behaviors (Parks et al., 1998; Klemenhagen et al., 2006), whereas in mice overexpressing the 5-HT receptor these traits are reduced (Kusserow et al., 2004). These behaviors are mediated by postsynaptic 5-HT1A receptors in the hippocampus, amygdala, and cortex (Gross et al., 2002; Mehta et al., 2007). Of great interest is the finding that embryonic and early postnatal shutdown of 5-HT1A receptor expression produces an anxiety phenotype that cannot be rescued with restoration of 5-HT1A receptors

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(Gross et al., 2002). However, when 5-HT1A receptor expression is reduced in adulthood and then reinstated, the anxiety phenotype is no longer present. These results suggest that altered function of 5-HT1A receptors early in life can produce long-term abnormalities in the regulation of anxiety behaviors (Gross et al., 2002). This has been shown in animal studies using the stress model of maternal separation (Gartside et al., 2003; Vicentic et al., 2006). There may also be important functional interactions between the 5-HT1A and benzodiazepine receptors. In one study of 5-HT1A knockout mice, down-regulation of benzodiazepine GABA a -1 and a -2 receptor subunits as well as benzodiazepine-resistant anxiety in the EPM was reported (Sibille et al., 2000; S.J. Bailey and Toth, 2004). However, a subsequent study did not replicate these results using mice with a different genetic background (Pattij et al., 2002), raising the possibility that genetic background can affect the functional interplay between 5-HT1A and benzodiazepine systems (Bruening et al., 2006). These results suggest a scenario in which early-life stress is postulated to increase CRH and cortisol levels, which in turn down-regulate 5-HT1A receptors, resulting in lower threshold for anxiogenic stressful life events (van Riel et al., 2004). Alternatively, 5-HT1A receptors may be decreased on a genetic basis. The density of 5HT1A receptors is reduced in patients with depression when they are depressed as well as in remission (Drevets et al., 1999; Bhagwagar et al., 2004; Moses-Kolko et al., 2007). Examination in patients with anxiety disorders, compared to healthy controls, have shown a reduction of 5-HT1A receptor binding in certain brain regions such as the amygdala, anterior cingulate, and raphé nucleus, in patients with panic disorder (Neumeister et al., 2004) and social anxiety disorder (Lanzenberger et al., 2007). There was no change in 5-HT1A receptor binding after exposure to stress in PTSD (Bonne et al., 2005). Another important area of investigation has been the serotonin transporter (5-HTT) and its gene (SCL6A4). Polymorphisms of promoter region of SCL6A4 (5-HTTLPR), with a short (s) and long (l) allele coded on chromosome 17q11.2, have been linked to mood and anxiety disorders (Hariri et al., 2005). In particular, carriers of one (ls, heterozygotes) or two (ss, homozygotes) of the s allele have been shown to have lower 5HTT expression and decreased 5-HT reuptake (Lesch et al., 1996). Preclinical trials have reported greater anxiety-like behaviors in rodents with altered 5-HT transporters, either by 5-HTT knockout mutation (Holmes, Lit, et al., 2003; Adamec, Burton, et al., 2006), or blockade of 5-HTT with SSRIs (Ansorge et al., 2004). In humans, studies of healthy volunteers, with no psychiatric history, showed, using blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI), that carriers of the s allele had higher reactiv-

ity in the amygdala to fearful faces, without apparent gender differences (Hariri et al., 2002; Hariri et al., 2005). A PET investigation of healthy volunteers showed that individuals heterozygous (sl) or homozygous (ss) for the 5-HTTLPR s allele had lower 5-HT1A receptor binding than individuals homozygous (ll) for the l allele (David et al., 2005). A study of children with homozygous s alleles had higher rates of shyness, a potential predictor of anxiety disorders later in life (Battaglia et al., 2005; Hayden et al., 2007). Early-life stresses, in combination with the presence of the s allele, confer greater susceptibility to depression or behavioral inhibition in children (Kaufman et al., 2004; Fox et al., 2005) or later-life depression (Caspi et al., 2003). These above studies suggest a strong interplay between genes and environment. There are, however, ample numbers of trials failing to show an association between the s allele and fear behaviors as they relate to life stress in children and adults (Lang et al., 2004; Becker et al., 2007), whereas meta-analyses reveal a heterogeneity of results (Munafo et al., 2003; Sen et al., 2004). In addition, studies of the 5-HRRLPR in anxiety disorders have been inconsistent. Smaller-scale studies have found an association between serotonin transporter promoter polymorphism and susceptibility to PTSD (H.J. Lee et al., 2005), symptom severity in social phobia (Furmark et al., 2004), and response to SSRI in social phobia (Stein et al., 2006). A recent meta-analysis found a lack of association between 5-HTTLPR and panic disorder (Blaya et al., 2007). Clinical studies of 5-HT function in anxiety disorders have had similarly mixed results. Platelet imipramine binding (a marker of the serotonin reuptake site), which is generally reduced in depression, has been found to be normal in panic disorder (Innis et al., 1987; Uhde et al., 1987), whereas platelet 5-HT uptake in panic disorder has been reported to be elevated (Norman et al., 1986), normal (Balon et al., 1987), or reduced (Pecknold et al., 1988). Dell’Osso et al. (2004) found that patients with panic disorder had reduced responsiveness to 5-HT in platelets due to dysfunction in the cAMP pathway, an effect that was reversed with treatment with paroxetine. One study found that patients with panic disorder had lower levels of circulating 5-HT than controls (Schneider et al., 1987). Thus, no clear pattern of abnormality in 5-HT function in panic disorder has emerged from analysis of peripheral blood elements. Interestingly, a recent study did show increased turnover of 5-HT (taken from a jugular venous blood sample) in patients with panic disorder, but not during a panic attack, and that this turnover was reversed by an SSRI and was not related to the serotonin transporter genotype (Esler et al., 2007). To date, pharmacological challenge studies of 5-HT in panic disorder have also been unable to establish a definite role for 5-HT in the pathophysiology of panic

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(Maron and Shlik, 2006). Challenges with the 5-HT precursors l-tryptophan (Charney and Heninger, 1986) and 5-hydroxytryptophan (5-HTP) (DenBoer and Westenberg, 1990; Schruers et al., 2002) did not discriminate between panic disorder and controls on neuroendocrine measures. Conversely, tryptophan depletion (TD) was not anxiogenic in unmedicated patients with panic disorder (Goddard et al., 1994). Tryptophan depletion has also been shown to acutely lower brain 5-HT levels, with some studies showing an enhanced response to panicogens such as carbon dioxide (Schruers et al., 2000), and a reversal of the antipanic effects of paroxetine using flumazenil (C. Bell et al., 2002). Another study failed to demonstrate such an effect after CCK-4 challenge in patients with panic disorder successfully treated with citalopram (Tõru et al., 2006). Challenge with the 5HT releasing agent fenfluramine has been reported to be anxiogenic and to produce greater increases in plasma prolactin and cortisol in patients with panic disorder compared to controls (Targum and Marshall, 1989). Studies with the 5-HT agonist m-chloromethylpiperazine (mCPP), a probe of postsynaptic 5-HT2 receptor function, have produced equivocal findings. Increases in anxiety and plasma cortisol in patients with panic disorder compared to controls have been reported with oral (Kahn et al., 1988) but not intravenous administration of mCPP (Charney et al., 1987b), although van der Wee et al. (2004) did show greater behavioral effects of intravenous mCPP in patients with panic disorder versus controls. Overall, it remains unclear whether the etiology of panic disorder is related to an excess of 5-HT or is instead due to a deficit of serotonin (Maron and Shlik, 2006). It is likely that serotonin exerts an inhibitory effect on panic through its interactions with other neurotransmitters. Challenge studies in other anxiety disorders have been limited. In one study, 5 of 14 patients with PTSD had a panic attack and four had a flashback following mCPP administration. In contrast, no patient had a panic attack and one patient experienced a flashback following the infusion of placebo saline. Thus, a subgroup of patients with PTSD exhibited a marked behavioral sensitivity to serotonergic provocation, raising the possibility of pathophysiologic subtypes among traumatized combat veterans (Southwick et al., 1997) (Table 41.4). An investigation of 14 patients with social anxiety disorder treated with either paroxetine or citalopram found that TD caused an increase in behavioral anxiety on the challenge day, suggesting that the efficacy of SSRI is dependent on 5-HT availability (Argyropoulos et al., 2004). In addition, patients with panic and social anxiety disorders undergoing treatment with SSRI or cognitive-behavioral therapy (CBT) were shown that TD caused a greater psychological and cardiovascular reactivity to stress, compared to sham depletion (Davies et al., 2006) (Table 41.4).

41.4 Evidence for Alterations in Other Neurotransmitter Systems in Anxiety Disorders TABLE

PTSD

Panic Disorder

Increased symptomatology with benzodiazepine antagonist

−

++

Decreased number of benzodiazepine receptors

+

++

Naloxone-reversible analgesia

+

NS

Increased plasma b-endorphin response to exercise

+

NS

Elevated levels of CSFendorphin

+

−

Decreased serotonin reuptake site binding in platelets

++

+/−

Decreased serotonin transmitter in platelets

−

+/−

Blunted prolactin response to 5-HT1A probe

−

+

Altered serotonin effect on cAMP in platelets (5-HT1A probe)

−

NS

Increased anxiogenic responses to 5-HT agonists

+

+/−

Increased baseline indices of thyroid function

+

−

Increased TSH response to TRH

+

−

+

−

+

+++

Benzodiazepine

Opiate

Serotonin

Thyroid

Somatostatin Increased somatostatin levels at baseline in CSF Cholecystokinin Increased anxiogenic responses to CCK agonists

−, one or more studies did not support this finding (with no positive studies) or the majority of studies do not support this finding; +/−, an equal number of studies do and do not support this finding; +, at least one study supports this finding and no studies do not support the finding or the majority of studies support the finding; ++, two or more studies support this finding and no studies do not support the finding; +++, three or more studies support this finding, and no studies do not support the finding. cAMP: cyclic adenosine 39,59-monophosphate; CCK: cholecystokinin; CSF: cerebrospinal fluid; 5-HT: serotonin; NS: not studied; PTSD: posttraumatic stress disorder; SPECT: single photon emission computed tomography; TSH: thyroid stimulating hormone; TRH: thyrotropin releasing hormone.

Benzodiazepine System g-amino butyric acid (GABA), the primary inhibitory neurotransmitter in the brain, consists of GABA-A, fastacting, chloride-gated ligand receptors, and GABA-B, slower-acting G protein–coupled potassium ligand receptors. GABA-A, a heteropentameric receptor, is made

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ANXIETY DISORDERS

up of five protein subunits and at least seven families (a 1–6; b 1–3; a 1–3; d ; r 1–3; e; q ), with the majority of GABA complexes consisting of a-1 (Mohler, 2006). Agents such as benzodiazepines, barbiturates, ethanol, anticonvulsants, and neurosteroids are positive allosteric modulators of GABA-A receptors. In addition to GABA receptor, benzodiazepine receptors are also present throughout the brain, with the highest concentration in cortical gray matter. Central benzodiazepine receptors and GABA-A receptors are part of the same macromolecular complex. These receptors have distinct binding sites, although they are functionally coupled and regulate each other in an allosteric manner. Interestingly, the presence of these endogenous benzodiazepine receptors has led to speculation about the existence of naturally occurring benzodiazepines (Sand et al., 2000). g-amino butyric acid has been known to play an important role in the pathophysiology and treatment of anxiety disorders (Nemeroff, 2003). Preclinical studies have contributed to the understanding of the nature of this role. Administration of inverse agonists of benzodiazepine receptors, such as b-carboline-3-carboxylic acid ethyl ester (b-CCE), result in behavioral and biological effects similar to those seen in anxiety and stress, including increases in heart rate, blood pressure, plasma cortisol, and catecholamines (Braestrup et al., 1982). Administration of the b-carboline FG 7142 results in an increase in local cerebral glucose use in brain structures involved in memory, including the lateral septal nucleus, mammillary bodies, and anterior thalamic nuclei (Ableitner and Herz, 1987). The effects of the bcarbolines are blocked by administration of benzodiazepines (Ninan et al., 1982). Recent investigations using anxiogenic inverse agonists (Atack et al., 2005), anxiolytic selective agonists (Dias et al., 2005), or behavioral paradigms (Morris et al., 2006), have suggested that a -2 and a -3 subunits are both critical in mediating anxiety processes. Studies of mixed selective a -2/a -3 agonists such as have shown them to have potential anxiolytic properties in animal studies (see review by Rupprecht et al., 2006). One partial a -2/a -3 agonist, TPA-23, was shown to be an effective nonsedating anxiolytic in rodents and primates, an effect thought to be due to its antagonism of a -1/a -5 (Atack et al., 2006). In addition to its sedating effects, the a -1 subunit is also involved in the amnestic effects of benzodiazepines, as demonstrated in studies of learning and memory (Savic´, Obradovic´, Uresic´, Cook, Sarma, et al., 2005; Savic´, Obradovic´, Uresic´, Cook, Yin, et al., 2005). A recent study found a reduction in expression of the GABA-A a -2 subunit 6 hours after fear conditioning (Mei et al., 2005). Studies using uncontrollable stress as an animal model for the anxiety disorders found evidence for alterations in benzodiazepine receptor function. Animals exposed

to acute inescapable stress in the form of cold swim or foot shock develop a decrease in benzodiazepine receptor binding in frontal cortex, with mixed results for cerebral cortex, hippocampus, and hypothalamus and no change in occipital cortex, striatum, midbrain, thalamus, cerebellum, and pons (Weizman et al., 1990). Chronic stress in the form of foot shock or cold swim resulted in decreases in benzodiazepine receptor binding in cerebral cortex, frontal cortex, hippocampus, and hypothalamus, with mixed results for cerebellum, midbrain, and striatum, and no changes in occipital cortex or pons (Drugan et al., 1989; Weizman et al., 1989, 1990). Decreases in benzodiazepine receptor binding are associated with alterations in memory manifested by deficits in maze escape behaviors (Drugan et al., 1989; Weizman et al., 1989). A decrease in benzodiazepine receptor binding (Bmax) has been demonstrated in the so-called Maudsley genetically fearful strain of rat in comparison to nonfearful rats in several brain structures including the hippocampus (Robertson et al., 1978). Rat pups exposed to prenatal stress showed decreased numbers of benzodiazepine receptors in the central nucleus of the amygdala and the hippocampus and increased anxiety-like behaviors during an EPM (Barros et al., 2006). A study of the genetic effects of chronic stress on the GABA system did not show a change in expression of the GABA-A subunits (Verkuyl et al., 2004). Despite preclinical support for the involvement of benzodiazepine systems in stress, clinical investigations of the function of this system in patients with anxiety disorders have been limited. The inability to identify measurable variables in vivo in humans that reflect central benzodiazepine system function has contributed to the paucity of research in this area. However, evidence from clinical studies performed to date suggests a possible role for alterations in benzodiazepine receptor function in disorders of anxiety and stress. Pharmacological challenge studies support a role for benzodiazepine function in anxiety in normal humans. The benzodiazepine receptor inverse agonist FG 7142 induces severe anxiety resembling panic attacks and biological characteristics of anxiety in healthy individuals (Dorow et al., 1983). This observation raises the question of whether there exist endogenous equivalents to FG 7142 that might be released to provoke panic attacks. One candidate for such an endogenous ligand is diazepam-binding inhibitor (DBI). However, CSF levels of DBI are normal in patients with panic disorder (Payeur et al., 1992). Interestingly, a recent genetic study showed a higher rate of a polymorphism of the DBI gene in persons with anxiety disorders with panic attack, as compared to controls (Thoeringer et al., 2007). Administration of the benzodiazepine receptor antagonist flumazenil to patients with panic disorder results in an increase in panic attacks and subjective anxiety in comparison to controls (Nutt et al., 1990; Woods

41: NEUROBIOLOGY

et al., 1991). Oral (Woods et al., 1991) and intravenous flumazenil (Nutt et al., 1990) have been shown to produce panic in a subgroup of patients with panic disorder but not in healthy individuals (Zedkova et al., 2003; E.C. Bell et al., 2004). Benzodiazepine-induced changes in sedation and cortisol levels, as well as in saccadic eye movement velocity, have been suggested to be indicative of benzodiazepine receptor–mediated actions. Patients with panic disorder were found to be less sensitive than controls to diazepam using saccadic eye movement velocity as a dependent measure, suggesting a functional subsensitivity of the GABA-benzodiazepine supramolecular complex in brain-stem regions controlling saccadic eye movements (Roy-Byrne et al., 1996). Other evidence for alterations in benzodiazepine receptor function in patients with panic disorder includes a diminished sensitivity to suppression of plasma NE, epinephrine, and pulse following administration of diazepam in comparison to controls (Roy-Byrne et al., 1989). Neuroimaging studies reveal reduced cortical and subcortical benzodiazepine receptor binding in patients with panic disorder (Bremner, Innis, White, et al., 2000) and PTSD (Bremner, Innis, Southwick, et al., 2000), although Fujita et al. (2004) was unable to replicate this finding in a subsequent study of patients with PTSD. Imaging studies comparing patients with panic disorder to controls have reported reduced GABA levels in the occipital cortex (Goddard et al., 2001) and the anterior cingulate and basal ganglia (Ham et al., 2007). Using magnetic resonance spectroscopy (MRS), Gooddard et al. (2004) also showed in a small sample that patients with panic disorder had a decreased GABA neural response to acute benzodiazepine administration, and decreased cortical GABA with chronic treatment. In addition, a recent PET study showed a reduction in GABA-A binding in the insula of patients with panic disorder (Cameron et al., 2007). These findings could be related to a down-regulation of benzodiazepine receptor binding following exposure to the stress. Other possible explanations are that stress results in changes in receptor affinity, changes in an endogenous benzodiazepine ligand (the existence of which is controversial), or stress-related alterations in GABAergic transmission or neurosteroids that affect benzodiazepine receptor binding. A preexisting low level of benzodiazepine receptor density may be a genetic risk factor for the development of stress-related anxiety disorders (Table 41.4). Vaiva et al. (2004) studied victims of motor vehicle accidents, measuring plasma GABA immediately after the accident, and reported that individuals who developed PTSD 6 weeks later had lower plasma GABA, compared to those who did not develop PTSD. At one year, the PTSD group continued to have lower plasma GABA than the non-PTSD group, but those with plasma GABA levels above 0.2 mmol no longer had symptoms of PTSD (Vaiva et al., 2006).

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The last two decades have seen a shift away from the practice of indiscriminate prescribing of benzodiazepines, due to concerns relating to long-term effects on cognition and the abuse liability (Rosenbaum, 2005). In turn, other GABA agonists, in particular the new class of anticonvulsants, have been studied as a safer option. Pregabalin has been shown in several doubleblind, placebo-controlled trials to be effective and safe for the treatment of GAD (Rickels et al., 2005; Montgomery et al., 2006; Feltner et al., 2008) and social phobia (Pande et al., 2004). Tiagabine, a GABA reuptake inhibitor, was shown in a study of patients with GAD to reduced symptoms versus placebo in one analysis but not another (Pollack et al., 2005), and in a study of PTSD patients, was shown to not be statistically significant from placebo (Davidson et al., 2007). Larger trials need to be done to determine if these agents are effective as a stand-alone treatment for various anxiety disorders. Cholecystokinin Cholecystokinin (CCK) is an anxiogenic neuropeptide present in the gastrointestinal tract as well as in the brain that has recently been suggested as a neural substrate for human anxiety (Harro, 2006). Neurons containing CCK are found with high density in the cerebral cortex, amygdala, and hippocampus. They are also found in the midbrain including the PAG, substantia nigra, and raphé nuclei. Iontophoretic administration of CCK has depolarizing effects on pyramidal neurons, suggesting that CCK it may serve as an excitatory neurotransmitter. Cholecystokinin-4-8 has stimulatory effects on action potentials in the dentate gyrus of the hippocampus. Activation of hippocampal neurons is suppressed by low-dose benzodiazepines. Cholecystokinin agonists are anxiogenic in a variety of animal models of anxiety, while CCK antagonists have anxiolytic effects in these tests (Hano et al., 1993; Bourin and Dailly, 2004). Several studies have shown that the panicogenic effect of CCK-4 on the dorsolateral PAG was blocked when rats were pretreated with a CCK-2 antagonist (Netto and Guimaraes, 2004; Zanoveli et al., 2004; Bertoglio and Zangrossi, 2005; Bertoglio et al., 2007). One study of patients with panic disorder found them to be more sensitive to the anxiogenic effects of CCK4 and a closely related peptide, pentagastrin, and these effects were blocked by L-365,260, a CCK antagonist (Bradwejn, Koszycki, Couetoux du Tetre, et al., 1994). CCK-4 was found to not have anxiogenic effects in a small sample of patients with social phobia and obsessive–compulsive disorder (OCD) (Katzman et al., 2004). In a small sample of patients with PTSD, CCK-4 had enhanced anxiogenic effects compared to responses in healthy subjects (Kellner et al., 2000). Imipramine also antagonizes the panicogenic effects of CCK-4 in patients

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with panic disorder (Bradwejn and Koszycki, 1994). The mechanism is unclear but may relate to the ability of imipramine to down-regulate b -adrenergic receptors because propranolol antagonizes the anxiogenic actions of CCK-4 (Bradwejn and Koszycki, 1994). Levels of CCK in the CSF are lower in patients with panic disorder than in controls, raising the possibility of enhanced function of CCK receptors (Lydiard et al., 1992). The mechanism responsible for the enhanced sensitivity to CCK-4 has not been elucidated. Patients may have elevated production or turnover of CCK or increased sensitivity of CCK receptors. There is also evidence of CCK-B gene polymorphisms in patients with panic disorder, suggesting a possible genetic vulnerability (Hösing et al., 2004). All of this evidence has prompted the study of CCK-B receptor antagonists as potential antianxiety drugs, but placebo-controlled trials have consistently shown these agents to not be effective in panic and GAD (Adams et al., 1995; Goddard et al., 1999) and panic disorder (Kramer et al., 1995; van Megen et al., 1997; Pande et al., 1999). Neuroimaging research should further elucidate the role of CCK in anxiety and help identify potential targets for treatment. Opioid Peptides One of the primary behavioral effects of uncontrollable stress is analgesia, which results from the release of endogenous opiates, which include beta-endorphin, enkephalin, and dynorphin. Significant analgesia is observed following uncontrollable but not controllable stress and also is seen following presentation of neutral stimuli previously paired with aversive stimuli (Fanselow, 1986). Stress-induced analgesia was also found to be correlated with the development of PTSD hyperarousal in women who were battered 3 months after the index trauma (Nishith, et al., 2002). There is also evidence that sensitization occurs because reexposure to less intense shock in rats previously exposed to uncontrollable shock also results in analgesia (Maier, 1986). These effects are likely to be mediated, in part, by a stress-induced release of endogenous opiates in the brain stem. Moreover, opioid peptides are elevated after acute uncontrollable shock (Madden et al., 1977), and uncontrollable but not controllable shock decreases the density of m-opiate receptors (Stuckey et al., 1989). It is thought that opioid peptides play a role in Pavlovian fear conditioning, in particular extinction (McNally et al., 2004). McNally and others (McNally and Cole, 2006; Cole and McNally, 2007) have shown that muopioid receptors in the ventrolateral PAG are involved in predicting errors during fear learning in rats, using electric foot shock. Their studies have also shown that opioid receptor antagonists, such as naloxone, block this learning. These opioid peptides may also exert an

effect on fear learning and cognition through an antagonistic interaction with CCK (see review by Hebb et al., 2005). Given these facts, it is reasonable to study opiate systems in the anxiety disorders. Only a few studies have looked at opiate function in PTSD. Hoffman et al. (1989) reported significantly lower morning and evening plasma beta-endorphin levels in 21 patients with PTSD compared to 20 controls. The results were viewed as support for van der Kolk’s (1981) hypothesis that patients with PTSD have a chronic depletion of endogenous opiates, which causes them to seek out recurrent stressors to increase opiate release. Another study found no differences in plasma levels of methionine-enkephalin between patients with PTSD and controls, although the degradation half-life was significantly higher in the PTSD group (Wolf, 1991). In a pharmacological challenge of the opiate system, patients with PTSD showed reduced pain sensitivity compared to veterans without PTSD following exposure to a combat film. This reaction was reversible by the opiate antagonist naloxone. These findings could be explained by increased release of endogenous opiates with stress in PTSD (Pitman et al., 1990). This conclusion is supported by a report of elevated levels of CSF betaendorphin in PTSD (D.G. Baker et al., 1997). Whether alterations in endogenous opiates contribute to the core symptoms seen in PTSD is not clear. It has been hypothesized that symptoms of avoidance and numbing are related to a dysregulation of opioid systems in PTSD (Charney et al., 1993). Further, it has been suggested that the use of opiates in chronic PTSD may represent a form of self-medication. Consistent with this, Bremner, Southwick, Darnell, and Charney (1996) found, in structured interviews, that a significant number of patients with combat-related PTSD reported that opiates reduced their symptoms of hyperarousal. Animal studies have shown that opiates are powerful suppressants of central and peripheral noradrenergic activity. If, as suggested earlier in this chapter, some PTSD symptomatology is mediated by noradrenergic hyperactivity, then opiates may serve to “treat” or reduce that hypersensitivity and accompanying symptoms. On the other hand, during opiate withdrawal, when opiates are decreased and noradrenergic activity is increased, PTSD symptoms may become acutely exacerbated. In fact, many symptoms of PTSD are similar to those seen during opiate withdrawal. Liberzon et al. (2007) conducted a PET imaging study of combat and noncombat subjects with and without PTSD, versus healthy volunteers, to study mu-opioid receptor binding potential (BP) in relevant cortical and limbic areas. They reported that in combat individuals, with and without PTSD, there was a decrease in mu-opioid receptor BP in the mPFC, insula, and dorsal ACC, and higher BP in the orbitofrontal cortex and subgenual ACC, compared to controls. This difference was greater in the combat

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PTSD group compared to the non-PTSD combat group. These findings may be due to adaptive increase in endogenous opioid after trauma exposure, though leads to a down-regulation of opioid receptors, or may be the result of a decrease in inhibitory interneurons (Liberzon et al., 2007). Studies of trauma in children indicate that opiates, such as morphine, given in the hospital after the event, may prevent the development of PTSD, by reduction of separation anxiety (Saxe et al., 2001; Saxe et al., 2006). Conversely, opioid antagonists, such as naloxone, naltrexone, and nalmefene, have been shown, in a few small-scale pilot studies, to have efficacy in treating hyperarousal symptoms in patients with preexisting PTSD (Glover, 1993; Lubin et al., 2002; Petrakis et al., 2007). Additional studies of opiate receptor function and its functional interaction with other neurotransmitter and peptide systems in anxiety disorders are indicated (Zubieta et al., 2003) (Table 41.4). Respiratory System Dysfunction in Panic Disorder The original observation that an intravenous infusion of lactate produces panic anxiety in susceptible individuals but not in normal individuals was made by Pitts and McClure (1967). Subsequently, the reliability of panic provocation by sodium lactate was well established (reviewed in Papp et al., 1993). The lactate response appears to be specific for panic disorder compared with other anxiety disorders and psychiatric conditions. The panicogenic mechanism of lactate has not been established. One theory is based upon the fact that systemic alkalosis causes vasoconstriction of cerebral vessels, which in turn induces cerebral ischemia, with a rise in the intracellular lactate:pyruvate ratio. Further, infused lactate results in a rapid passive elevation in the lactate:pyruvate ratio in localized brain regions outside the blood-brain-barrier, such as the chemoreceptor zones. These two mechanisms lower the intracellular pH in medullary chemoreceptors. The theory suggests that in patients with panic there is dysregulation (greater sensitivity to alterations in pH) in this region; thus, a panic response is triggered. This theory predicts that panic could be triggered in any patient if the medullary pH is changed sufficiently. The limitations of the model include the fact that it is not yet known whether the pH changes in the local circulation are mirrored intracellularly. Recent evidence on the physiological effects of sodium bicarbonate has revealed a paradoxical intracellular acidosis, so the same may be true of lactate. Still, there is no clear evidence that intracellular acidosis will initiate neural activity, as the theory requires. The model predicts that hypoxia is a profound stimulus for chemoreceptor stimulation, and hyperventilation is belied by experiments

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in which removal of CO2 from inspired air leads to loss of consciousness without anxiety or air hunger. A second major hypothesis of lactate’s panicogenic effect asserts that it occurs via the induction of a metabolic alkalosis. Infused lactate is metabolized to bicarbonate. Bicarbonate is further metabolized to CO2, which quickly permeates the CNS. This central buildup of CO2 increases the ventilatory rate via a direct stimulation of ventral medullary chemoreceptors. Increasing the brain pCO2 concentration has been shown to be a profound stimulus for LC activation, which could cause panic via central noradrenergic activation (Gorman et al., 1989). Although the lactate-CO2 theory has considerable appeal, there is a suggestion from initial studies with the isomer d-lactate that this may not be the whole explanation. There is a preliminary report that this isomer also is panicogenic (Gorman et al., 1990) but is not metabolized to CO2. The behavioral effects of lactate and bicarbonate infusion have been compared (Gorman et al., 1989). Both substances provoke panic in susceptible patients; however, bicarbonate is somewhat less anxiogenic than lactate. This finding argues against alkalosis alone being the panicogenic stimulus. Gorman and colleagues (1989) concluded that stimulation of respiratory centers to produce increased ventilation, hypocapnia, and respiratory alkalosis were common effects produced by bicarbonate and lactate. Panic can also be provoked by increases in pCO2 (hypercapnia). This can be done slowly, such as by rebreathing air or by breathing 5%–7% CO2 in air (Gorman et al., 1988; Gorman et al., 1989). Alternatively, panic attacks can be provoked by taking only one or two deep breaths of 35% CO2 (van Den Hout and Griez, 1984; Griez et al., 1987). The CO2 studies have revealed abnormalities in ventilatory physiology in children and adults with panic disorder (Pine et al., 1998) Hyperventilation and increased CO2 hypersensitivity have also been posited as an explanation for symptoms of panic disorder (Papp et al., 1993). According to the model, elevated levels of pCO2 lead to activation of the vagus nerve, which, through the nucleus tractus solitarius, stimulates the LC and provokes hyperventilation. Increased tidal volume drives down pCO2, with increased respiratory alkalosis and symptoms of panic. Hyperactive chemoreceptors lead to hyperventilation to reduce pCO2, which results in panic symptomatology. A corollary model to the hyperventilation hypothesis (Klein, 1993) states that patients with panic disorder suffer from a physiological misinterpretation of a suffocation monitor that evokes a suffocation alarm system. This produces sudden respiratory distress, quickly followed by hyperventilation, panic, and an urge to flee. This model posits that hypersensitivity to CO2 is due to the deranged suffocation alarm system. The neuroanatomical site for such a dysfunction in respiratory

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control could involve a number of structures including activation of the rostral and ventral anterior cingulate cortices, hippocampus, amygdala, insula, and fusiform gyrus, and deactivation of anterior and dorsal cingulate cortices and PFC (Brannan et al., 2001). More recent investigations have used different agents to induce panic. Doxapram, a carotid body stimulant, has been shown to reliably induce panic symptoms in patients with panic disorder but not healthy controls (Abelson, Nesse, et al., 1996). Imaging studies have reliably used doxapram to cause physiological symptoms of panic, such as increased respiration and heart rate, including one study that obtained PET images of patients during a doxapram challenge versus saline placebo (Garakani et al., 2007). CONCLUDING REMARKS This chapter began with a description of the neuroanatomical and neurochemical bases of classical fear conditioning, a model based on findings from abundant animal studies. The task of finding correlates in humans has been more of a challenge. Most research done in healthy volunteers has demonstrated the role of the amygdala in fear pathways but has also shown the critical importance of other areas, such as the anterior cingulate cortex, PFC, and hippocampus. Using functional neuroimaging, combined with emotional faces paradigms, emotional Stroop, and memory and learning tasks, several neuroimaging studies of patients with PTSD, social phobia, and panic disorder have shown, in addition to amygdalar activation, increased signal in areas such as the anterior cingulate cortex, and reduced activity in the medial PFC. Recent work has also begun to shed light on the insula, and how altered function in this brain region contributes to exaggerated interoceptive responses in individuals who are anxiety prone. This has been supported by recent findings of altered insular function in patients with panic disorder (Cameron et al., 2007), PTSD, and social phobia (Lanzenberger et al., 2007; Sareen et al., 2007); please see Chapter 43 on Neuroimaging Studies of Anxiety Disorders for further discussion of this topic. Various neurochemicals and neuropeptides are implicated in the etiology of anxiety disorders. Although originally thought to involve primarily norepinephrine, it is apparent now that the manifestation of anxiety symptoms involves a complex interplay of compounds in the CNS and periphery. A good example is the manner in which neurosteroids such as allopregnanolone can modulate the activity of GABA-A receptors, an effect that can be reversed by administration of fluoxetine, a serotonergic agent (Matsumoto et al., 2007). Although the significance of substances such as galanin and NPY in human anxiety remains unclear, further

investigations will continue to shed light in this area. Other compounds such as oxytocin (Kirsch et al., 2005; Meinlschmidt and Heim, 2007) and substance P have shown a potential role in the etiology of anxiety and thereby are potential targets of novel therapeutics. For instance, there was a study showing that a substance P-neurokinin-1 receptor antagonist alleviated symptoms of social phobia, when compared with placebo (Furmark et al., 2005). A large Phase II investigation of this drug in the treatment of PTSD is under way. Work is commencing to examine the genetic basis of the neural mechanisms of fear conditioning. There have been several recent advances in understanding the genetic contribution and molecular machinery related to amygdala-dependent learned fear. A gene encoding gastrin-releasing peptide (Grp) has been identified in the lateral amygdala. The Grp receptor (GRPR) is expressed in GABAergic interneurons and mediates their inhibition of principal neurons. In GRPR knockout mice, this inhibition is reduced and LTP is enhanced. These mice have enhanced and prolonged fear memory for auditory and contextual cues, indicating that the Grp signaling pathway may serve as an inhibitory feedback constraint on learned fear (Bédard et al., 2007). Gastrinreleasing peptide antagonists have been shown to have anxiolytic effects in animal models (Bastaki et al., 2003). The work further supports the role of GABA in fear and anxiety states (Goddard et al., 2001) and suggests that the genetic basis of vulnerability to anxiety may relate to Grp, GRPR, and GABA (Ishikawa-Brush et al., 1997). In addition, there continues to be investigation of other genetic polymorphisms, such as the 5-HTTLPR, CRH gene, diazepam binding inhibitor, and COMT Val158Met, to determine more conclusively whether these genetic alterations are associated with and/or confer susceptibility to anxiety disorders. Multidisciplinary studies that use neurochemical, neuroimaging, and genetic approaches have the potential to clarify the complex relationships among genotype, phe-notype, and psychobiological responses to stress. REFERENCES Abelson, J.L., and Curtis, G.C. (1996) Hypothalamic-pituitary-adrenal axis activity in panic disorder. Arch. Gen. Psychiatry 53:323–332. Abelson, J.L., Khan, S., Liberzon, I., and Young, E.A. (2007) HPA axis activity in patients with panic disorder: review and synthesis of four studies. Depress. Anxiety 24:66–76. Abelson, J.L., Liberzon, I., Young, E.A., and Khan, S. (2005) Cognitive modulation of the endocrine stress response to a pharmacological challenge in normal and panic disorder subjects. Arch. Gen. Psychiatry 62:668–675. Abelson, J.L., Nesse, R.M., Weg, J.G., and Curtis, G.C. (1996) Respiratory psychophysiology and anxiety: cognitive intervention in the doxapram model of panic. Psychosom. Med. 58:302–313. Abercrombie, E.D., and Jacobs, B.L (1987) Single-unit response of noradrenergic neurons in the locus coeruleus of freely moving cats, I: acutely presented stressful and nonstressful stimuli. J. Neurosci. 7:2837–2843.

41: NEUROBIOLOGY Ableitner, A., and Herz, A. (1987) Changes in local cerebral glucose utilization induced by the a-carbolines FG 7142 and DMCM reveal brain structures involved in the control of anxiety and seizure activity. J. Neurosci. 7:1047–1055. Adamec, R., Burton, P., Blundell, J., Murphy, D.L., and Holmes, A. (2006) Vulnerability to mild predator stress in serotonin transporter knockout mice. Behav. Brain Res. 170(1):126–140. Adamec, R., Strasser, K., Blundell, J., Burton, P., and McKay, D.W. (2006) Protein synthesis and the mechanisms of lasting change in anxiety induced by severe stress. Behav. Brain Res. 167:270–286. Adams, J.B., Pyke, R.E., Costa, J., Cutler, N.R., Schweizer, E., Wilcox, C.S., Wisselink, P.G., Greiner, M., Pierce, M.W., and Pande, A.C. (1995) A double-blind, placebo-controlled study of a CCK-B receptor antagonist, CI-988, in patients with generalized anxiety disorder. J. Clin. Psychopharmacol. 15:428–434. Adolphs, R., Gosselin, F., Buchanan, T.W., Tranel, D., Schyns, P., and Damasio, A.R. (2005) A mechanism for impaired fear recognition after amygdala damage. Nature 433:68–72. Aerni, A., Traber, R., Hock, C., Roozendaal, B., Schelling, G., Papassotiropoulos, A., Nitsch, R.M., Schnyder, U., and de Quervain, D.J. (2004) Low-dose cortisol for symptoms of posttraumatic stress disorder. Am. J. Psychiatry 161:1488–1490. Aguilera, G., and Rabadan-Diehl, C. (2000) Vasopressinergic regulation of the hypothalamic-pituitary-adrenal axis: implications for stress adaptation. Regul. Pept. 96:23–29. Albus, M., Zahn, T.P., and Brier, A. (1992) Anxiogenic properties of yohimbine: behavioral, physiological and biochemical measures. Eur. Arch. Psychiatry 241:337–344. Allen, Y.S., Adrian, T.E., Allen, J.M., Tatemoto, K., Crow, T.J., Bloom, S.R., and Polak, J.M. (1983) Neuropeptide Y distribution in the rat brain. Science 221:877–879. Ansorge, M.S., Zhou, M., Lira, A., Hen, R., and Gingrich, J.A. (2004) Early-life blockade of the 5-HT transporter alters emotional behavior in adult mice. Science 306:879–881. Antonijevic, I.A., Murck, H., Bohlhalter, S., Frieboes, R.M., Holsboer, F., and Steiger, A. (2000) Neuropeptide Y promotes sleep and inhibits ACTH and cortisol release in young men. Neuropharmacology 39:1474–1481. Argyropoulos, S.V., Hood, S.D., Adrover, M., Bell, C.J., Rich, A.S., Nash, J.R., Rich, N.C., Witchel, H.J., and Nutt, D.J. (2004) Tryptophan depletion reverses the therapeutic effect of selective serotonin reuptake inhibitors in social anxiety disorder. Biol. Psychiatry 56:503–509. Aston-Jones, G., Shipley, M.T., Chouvet, G., Ennis, M., VanBockstaele, E.J., Pieribone, V., and Shiekhattar, R. (1991) Afferent regulation of locus coeruleus neurons: anatomy, physiology and pharmacology. Progr. Brain Res. 88:47–75. Atack, J.R., Hutson, P.H., Collinson, N., Marshall, G., Bentley, G., Moyes, C., Cook, S.M., Collins, I., Wafford, K., McKernan, R. M., and Dawson, G.R. (2005) Anxiogenic properties of an inverse agonist selective for alpha3 subunit-containing GABA A receptors. Br. J. Pharmacol. 144:357–366. Atack, J.R., Wafford, K.A., Tye, S.J., Cook, S.M., Sohal, B., Pike, A., Sur, C., Melillo, D., Bristow, L., Bromidge, F., Ragan, I., Kerby, J., Street, L., Carling, R., Castro, J.L., Whiting, P., Dawson, G. R., and McKernan, R.M. (2006) TPA023 [7-(1,1-dimethylethyl)6-(2-ethyl-2H-1,2,4-triazol-3-ylmethoxy)-3-(2-fluorophenyl)1,2,4-triazolo[4,3-b]pyridazine], an agonist selective for alpha2and alpha3-containing GABAA receptors, is a nonsedating anxiolytic in rodents and primates. J. Pharmacol. Exp. Ther. 316: 410–422. Bailey, K.R., Pavlova, M.N., Rohde, A.D., Hohmann, J.G., and Crawley, J.N. (2007) Galanin receptor subtype 2 (GalR2) null mutant mice display an anxiogenic-like phenotype specific to the elevated plus-maze. Pharmacol. Biochem. Behav. 86:8–20. Bailey, S.J., and Toth, M. (2004) Variability in the benzodiazepine response of serotonin 5-HT1A receptor null mice displaying anx-

677

iety-like phenotype: evidence for genetic modifiers in the 5-HTmediated regulation of GABA(A) receptors. J. Neurosci. 24:6343– 6351. Baker, D.G., Ekhator, N.N., Kasckow, J.W., Dashevsky, B., Horn, P.S., Bednarik, L., and Geracioti, T.D., Jr. (2005) Higher levels of basal serial CSF cortisol in combat veterans with posttraumatic stress disorder. Am. J. Psychiatry 162:992–994. Baker, D.G., West, S.A., Orth, D.N., Hill, K.K., Nicholson, W.E., Ekhator, N.N., Bruce, A.B., Wortman, M.D., Keck, P.E., and Geracioti, J.D. (1997) Cerebrospinal fluid and plasma beta endorphin in combat veterans with posttraumatic stress disorder. Psychoneuroendocrinology 22:517–529. Baker, R.A., and Herkenham, M. (1995) Arcuate nucleus neurons that project to the hypothalamic paraventricular nucleus: neuropeptidergic identity and consequences of adrenalectomy on mRNA levels in the rat. J. Comp. Neurol. 358:518–530. Bale, T.L., Contarino, A., Smith, G.W., Chan, R., Gold, L.H., Sawchenko, P.E., Koob, G.F., Vale, W.W., and Lee, K.F. (2000) Mice deficient for corticotrophin-releasing hormone receptor-2 display anxiety-like behavior and are hypersensitive to stress. Nature Genet. 24:410–414. Bale, T.L., Picetti, R., Contarino, A., Koob, G.F., Vale, W.W., and Kuo-Fen, L. (2002) Mice deficient for both corticotrophin-releasing factor receptor 1 (CRFR1) and CRFR2 have an impaired stress response and display sexually dichotomous anxiety-like behavior. J. Neurosci. 22:193–199. Balon, R., Poh, R., Yeragani, V., Rainey, J., and Oxenkrug, G.F. (1987) Platelet serotonin levels in panic disorder. Acta Psychiatr. Scand. 75:315. Balon, R., and Ramesh, C. (1996) Calcium channel blockers for anxiety disorders? Ann. Clin. Psychiatry 8:215–220. Bandelow, B., Wedekind, D., Sandvoss, V., Broocks, A., Hajak, G., Pauls, J., Peter, H., and Ruther, E. (2000) Diurnal variation of cortisol in panic disorder. Psychiatry Res. 95:245–250. Barrera, G., Hernandez, A., Poulin, J.F., Laforest, S., Drolet, G., and Morilak, D.A. (2006) Galanin-mediated anxiolytic effect in rat central amygdala is not a result of corelease from noradrenergic terminals. Synapse 59:27–40. Barros, V.G., Rodriguez, P., Martijena, I.D., Perez, A., Molina, V.A., and Antonelli, M.C. (2006) Prenatal stress and early adoption effects on benzodiazepine receptors and anxiogenic behavior in the adult rat brain. Synapse 60:609–618. Bastaki, S.M., Hasan, M.Y., Chandranath, S.I., Schmassmann, A., and Garner, A. (2003) PD-136,450: a CCK2 (gastrin) receptor antagonist with antisecretory, anxiolytic and antiulcer activity. Mol. Cell Biochem. 252:83–90. Battaglia, M., Ogliari, A., Zanoni, A., Citterio, A., Pozzoli, U., Giorda, R., Maffei, C., and Marino, C. (2005) Influence of the serotonin transporter promoter gene and shyness on children’s cerebral responses to facial expressions. Arch. Gen. Psychiatry 62:85–94. Bauer, E.P., Schafe, G.E., and LeDoux, J.E. (2002) NMDA receptors and L-type voltage-gated calcium channels contribute to longterm potentiation and different components of fear memory formation in the lateral amygdala. J. Neurosci. 22:5239–5249. Becker, K., El-Faddagh, M., Schmidt, M.H., and Laucht, M. (2007) Is the serotonin transporter polymorphism (5-HTTLPR) associated with harm avoidance and internalising problems in childhood and adolescence? J. Neural Transm. 114:395–402. Bédard, T., Mountney, C., Kent, P., Anisman, H., and Merali, Z. (2007) Role of gastrin-releasing peptide and neuromedin B in anxiety and fear-related behavior. Behav. Brain Res. 179:133– 140. Bell, C., Forshall, S., Adrover, M., Nash, J., Hood, S., Argyropoulos, S., Rich, A., and Nutt, D.J. (2002) Does 5-HT restrain panic? A tryptophan depletion study in panic disorder patients recovered on paroxetine. J. Psychopharmacol. 16:5–14.

678

ANXIETY DISORDERS

Bell, E.C., Baker, G.B., Poag, C., Bellavance, F., Khudabux, J., and Le Melledo, J.M. (2004) Response to flumazenil in the late luteal phase and follicular phase of the menstrual cycle in healthy control females. Psychopharmacology (Berl) 172:248–254. Bertoglio, L.J., de Bortoli, V.C., and Zangrossi, H., Jr. (2007) Cholecystokinin-2 receptors modulate freezing and escape behaviors evoked by the electrical stimulation of the rat dorsolateral periaqueductal gray. Brain Res. 1156:133–138. Bertoglio, L.J., and Zangrossi, H., Jr. (2005) Involvement of dorsolateral periaqueductal gray cholecystokinin-2 receptors in the regulation of a panic-related behavior in rats. Brain Res. 1059: 46–51. Bhagwagar, Z., Rabiner, E.A., Sargent, P.A., Grasby, P.M., and Cowen, P.J. (2004) Persistent reduction in brain serotonin1A receptor binding in recovered depressed men measured by positron emission tomography with [11C]WAY-100635. Mol. Psychiatry 9: 386–392. Bielsky, I.F., Hu, S.B., Ren, X., Terwilliger, E.F., and Young, L.J. (2005) The V1a vasopressin receptor is necessary and sufficient for normal social recognition: a gene replacement study. Neuron 47:503–513. Bielsky, I.F., Hu, S.B., Szegda, K.L., Westphal, H., and Young, L.J. (2004) Profound impairment in social recognition and reduction in anxiety-like behavior in vasopressin V1a receptor knockout mice. Neuropsychopharmacology 29:483–493. Bing, O., Moller, C., Engel, J.A., Soderpal, B., and Heilig, M. (1993) Anxiolytic-like action of centrally administered galanin. Neurosci. Lett. 164:17–20. Bitran, D., Purdy, R.H., and Kellogg, C.K. (1993) Anxiolytic effect of progesterone is associated with increases in cortical allopregnanolone and GABA A receptor function. Pharmacol. Biochem. Behav. 45:423–428. Blair, H.T., Schafe, G.E., Bauer, E.P., Rodrigues, S.M., and LeDoux, J.E. (2001) Synaptic plasticity in the lateral amygdala: a cellular hypothesis of fear conditioning. Learn. Mem. 8:229–242. Blanchard, E.B., Kolb, L.C., Prins, A., Gates, S., and McCoy, G.C. (1991) Changes in plasma norepinephrine to combat-related stimuli among Vietnam veterans with posttraumatic stress disorder. J. Nerv. Ment. Dis. 179:371–373. Blaya, C., Salum, G.A., Lima, M.S., Leistner-Segal, S., and Manfro, G.G. (2007) Lack of association between the serotonin transporter promoter polymorphism (5-HTTLPR) and panic disorder: a systematic review and meta-analysis. Behav. Brain Funct. 3:41. Bonne, O., Bain, E., Neumeister, A., Nugent, A.C., Vythilingam, M., Carson, R.E., Luckenbaugh, D.A., Eckelman, W., Herscovitch, P., Drevets, W.C., and Charney, D.S. (2005) No change in serotonin type 1A receptor binding in patients with posttraumatic stress disorder. Am. J. Psychiatry 162:383–385. Born, J., Lange, T., Kern, W., McGregor, G.P., Bickel, U., and Fehm, H.L. (2002) Sniffing neuropeptides: a transnasal approach to the human brain. Nat. Neuroscience 5:514–516. Bourin, M., and Dailly, E. (2004) Cholecystokinin and panic disorder. Acta Neuropsychiatr. 16:85–93. Bradwejn, J., and Koszycki, D. (1994) Imipramine antagonism of the panicogenic effects of CCK-4 in panic disorder patients. Am. J. Psychiatry 151:261–263. Bradwejn, J., Koszycki, D., Couetoux du Tetre, A., van Megen, H., den boer, J., Westenberg, H., and Annable, L. (1994) The panicogenic effects of CCK-4 are antagonized by L-365-260, a CCK receptor antagonist, in patients with panic disorder. Arch. Gen. Psychiatry 51:486–493. Braestrup, C., Schmiechen, R., Neef, G., Nielsen, M., and Petersen, E.N. (1982) Interaction of convulsive ligands with benzodiazepine receptors. Science 216:1241–1243. Brambilla, F., Biggio, G., Pisu, M.G., Bellodi, L., Perna, G., Bogdanovich-Djukic, V., Purdy, R.H., and Serra, M. (2003) Neurosteroid secretion in panic disorder. Psychiatry Res. 118:107–116.

Brannan, S., Liotti, M., Egan, G., Shade, R., Masdden, L., Robillard, R., Stofer, K., Denton, D., and Fox, P.T. (2001) Neuroimaging of cerebral activations and deactivations associated with hypercapnia and hunger for air. Proc. Natl. Acad. Sci. USA 98:2029–2034. Bremner, J.D. (2006) Stress and brain atrophy. CNS Neurol. Disord. Drug Targets 5:503–512. Bremner, J.D., et al. (1999) Neural correlates of exposure to traumatic pictures and sound in Vietnam combat veterans with and without posttraumatic stress disorder: a positron emission tomography study. Biol. Psychiatry 45:806–816. Bremner, J.D., Innis, R.B., Ng, C.K., Staib, L., Duncan, J., Bronen, R., Zubal, G., Rich, D., Krystal, J.H., Dey, H., Soufer, R., and Charney, D.S. (1997) PET measurement of central metabolic correlates of yohimbine administration in posttraumatic stress disorder. Arch. Gen. Psychiatry 54:246–256. Bremner, J.D., Innis, R.B., Southwick, S.M., Staib, L., Zoghbi, S., and Charney, D.S. (2000) Decreased benzodiazepine receptor binding in prefrontal cortex in combat-related posttraumatic stress disorder. Am. J. Psychiatry 157:1120–1126. Bremner, J.D., Innis, R.B., White, T., Fujita, M., Silbersweig, D., Goddard, A.W., Staib, L., Stern, E., Cappiello, A., Woods, S., Baldwin, R., and Charney, D.S. (2000) SPECT [I-123] iomazenil measurement of the benzodiazepine receptor in panic disorder. Biol. Psychiatry 47:96–106. Bremner, J.D., Krystal, J.H., Southwick, S.M., and Charney, D.S. (1996a) Noradrenergic mechanisms in stress and anxiety: I. Preclinical studies. Synapse 23:28–38. Bremner, J.D., Krystal, J.H., Southwick, S.M., and Charney, D.S. (1996b) Noradrenergic mechanisms in stress and anxiety: II. Clinical studies. Synapse 23:39–51. Bremner, J.D., Licinio, J., Darnell, A., Krystal, J.H., Owens, M., Southwick, S.M., Nemeroff, C.B., and Charney, D.S. (1997) Elevated CSF corticotropin-releasing factor concentrations in posttraumatic stress disorder. Am. J. Psychiatry 154:624–629. Bremner, J.D., Southwick, S.M., Darnell, A., and Charney, D.S. (1996) Chronic PTSD in Vietnam combat veterans: course of illness and substance abuse. Am. J. Psychiatry 153:369–375. Bremner, J.D., Vermetten, E., Schmahl, C., Vaccarino, V., Vythilingam, M., Afzal, N., Grillon, C., and Charney, D.S. (2005) Positron emission tomographic imaging of neural correlates of a fear acquisition and extinction paradigm in women with childhood sexualabuse-related post-traumatic stress disorder. Psychol. Med. 35: 791–806. Bremner, J.D., Vythilingam, M., Vermetten, E., Adil, J., Khan, S., Nazeer, A., Afzal, N., McGlashan, T., Elzinga, B., Anderson, G.M., Heninger, G., Southwick, S.M., and Charney, D.S. (2003) Cortisol response to a cognitive stress challenge in posttraumatic stress disorder (PTSD) related to childhood abuse. Psychoneuroendocrinology 28:733–750. Briones-Aranda, A., Rocha, L., and Picazo, O. (2005) Influence of forced swimming stress on 5-HT1A receptors and serotonin levels in mouse brain. Prog. Neuropsychopharmacol. Biol. Psychiatry 29:275–281. Britton, K.T., Akwa, Y., Spina, M.G., and Koob, G.F. (2000) Neuropeptide Y blocks anxiogenic-like behavioral action of corticotrophin-releasing factor in an operant conflict test and elevated plus maze. Peptides 21:37–44. Broekman, B.F., Olff, M., and Boer, F. (2007) The genetic background to PTSD. Neurosci. Biobehav. Rev. 31:348–362. Bruening, S., Oh, E., Hetzenauer, A., Escobar-Alvarez, S., Westphalen, R.I., Hemmings, H.C., Jr., Singewald, N., Shippenberg, T., and Toth, M. (2006) The anxiety-like phenotype of 5-HT receptor null mice is associated with genetic background-specific perturbations in the prefrontal cortex GABA-glutamate system. J. Neurochem. 99:892–899. Brunson, K.L., Eghbal-Ahmadi, M., Bender, R., Chen, Y., and Baram, T.Z. (2001) Long-term, progressive hippocampal cell loss and

41: NEUROBIOLOGY dysfunction induced by early-life administration of corticotrophin-releasing hormone reproduce the effects of early-life stress. Proc. Natl. Acad. Sci. USA 98:8856–8861. Burgos-Robles, A., Vidal-Gonzalez, I., Santini, E., and Quirk, G.J. (2007) Consolidation of fear extinction requires NMDA receptor-dependent bursting in the ventromedial prefrontal cortex. Neuron 53:871–880. Cabib, S., and Puglisi-Allegra, S. (1996) Different effects of repeated stressful experiences on mesocortical and mesolimbic dopamine metabolism. Neuroscience 73:375–380. Cabib, S., Ventgura, R., and Puglisi-Allegra, S. (2002) Opposite imbalances between mesocortical and mesoaccumbens dopamine responses to stress by the same genotype depending on living conditions. Behav. Brain Res. 129:179–185. Cahill, L., Prins, B., Weber, M., and McGaugh, J.L. (1994) Betaadrenergic activation and memory for emotional events. Nature 371:702–704. Cai, W.H., Blundell, J., Han, J., Greene, R.W., and Powell, C.M. (2006) Postreactivation glucocorticoids impair recall of established fear memory. J. Neurosci. 26:9560–9566. Cain, C., Blouin, A., and Barad, M.G. (2002) L-type voltage-gated calcium channels are required for extinction but not for acquisition or expression, of conditional fear in mice. J. Neurosci. 22: 9113–9121. Cain, C.K., Godsil, B.P., Jami, S., and Barad, M. (2005) The L-type calcium channel blocker nifedipine impairs extinction, but not reduced contingency effects, in mice. Learn. Mem. 12: 277–284. Cameron, O.G., Huang, G.C., Nichols, T., Koeppe, R.A., Minoshima, S., Rose, D., and Frey, K.A. (2007) Reduced gamma-aminobutyric acid(A)-benzodiazepine binding sites in insular cortex of individuals with panic disorder. Arch. Gen. Psychiatry 64:793– 800. Canal, C.E., Chang, Q., and Gold, P.E. (2007) Amnesia produced by altered release of neurotransmitters after intraamygdala injections of a protein synthesis inhibitor. Proc. Natl. Acad. Sci. USA 104:12500–12505. Canal, C.E., and Gold, P.E. (2007) Different temporal profiles of amnesia after intra-hippocampus and intra-amygdala infusions of anisomycin. Behav. Neurosci. 121:732–741. Caspi, A., Sugden, K., Moffitt, T.E., Taylor, A., Craig, I.W., Harrington, H., McClay, J., Mill, J., Martin, J., Braithwaite, A., and Poulton, R. (2003) Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 301: 386–389. Cassens, G., Kuruc, A., Roffman, M., Orsulak, P., and Schildkraut, J.J. (1981) Alterations in brain norepinephrine metabolism and behavior induced by environmental stimuli previously paired with inescapable shock. Behav. Brain Res. 2:387–407. Chapman, P.F., Kairiss, E.W., Keenan, C.L., and Brown, T.H. (1990) Long-term synaptic potentiation in the amygdala. Synapse 6:271– 278. Charney, D.S. and Deutch, A.Y. (1996) A functional neuroanatomy of anxiety and fear: implications for the pathophysiology and treatment of anxiety disorders. Crit. Rev. Neurobiol. 10:419– 446. Charney, D.S., Deutch, A.Y., Krystal, J.H., Southwick, S.M., and Davis, M. (1993) Psychobiologic mechanisms of posttraumatic stress disorder. Arch. Gen. Psychiatry 50:294–299. Charney, D.S., and Drevets, W.D. (2002) Neurobiological basis of anxiety disorders. In: Davis, K.L., Charney, D., Coyle, J.T., and Nemeroff, C., eds. Neuropsychopharmacology: The Fifth Generation of Progress. Baltimore: Lippincott Williams & Wilkins, pp. 901–930. Charney, D.S., and Heninger, G.R. (1986) Serotonin function in panic disorders. The effects of intravenous tryptophan in healthy subjects and panic disorder patients before and after alprazolam treatment. Arch. Gen. Psychiatry 43:1059–1065.

679

Charney, D.S., Heninger, G.R., and Breier, A. (1984) Noradrenergic function in panic anxiety: effects of yohimbine in healthy subjects and patients with agoraphobia and panic disorder. Arch. Gen. Psychiatry 41:751–763. Charney, D.S., Woods, S.W., Goodman, W.K., and Heninger, G.R. (1987a) Neurobiological mechanisms of panic anxiety: biochemical and behavioral correlates of yohimbine-induced panic attacks. Am. J. Psychiatry 144:1030–1036. Charney, D.S., Woods, S.W., Goodman, W.K., and Heninger, G.R. (1987b) Serotonin function in anxiety. II. Effects of the serotonin agonist MCPP in panic disorder patients and healthy subjects. Psychopharmacology 92:14–24. Charney, D.S., Woods, S.W., Krystal, J.H., Nagy, L.M., and Heninger, G.R. (1992) Noradrenergic neuronal dysregulation in panic disorder: the effects of intravenous yohimbine and clonidine in panic disorder patients. Acta Psychiatr. Scand. 86:273–282. Cohen, H., Kaplan, Z., Matar, M.A., Loewenthal, U., Kozlovsky, N., and Zohar, J. (2006) Anisomycin, a protein synthesis inhibitor, disrupts traumatic memory consolidation and attenuates posttraumatic stress response in rats. Biol. Psychiatry 60:767–776. Cole, S., and McNally, G.P. (2007) Opioid receptors mediate direct predictive fear learning: evidence from one-trial blocking. Learn. Mem. 14:229–235. Comings, D.E., Muhleman, D., and Gysin, R. (1996) Dopamine D2 receptor (DRD2) gene and susceptibility to posttraumatic stress disorder: a study and replication. Biol. Psychiatry 40:368–372. Cook, S.C., and Wellman, C.L. (2004) Chronic stress alters dendritic morphology in rat medial prefrontal cortex. J. Neurobiol. 60:236–248. Coplan, J.D., Andrews, M.W., Rosenblum, L.A., Owens, M.J., Friedman, S., Gorman, J.M., and Nemeroff, C.B. (1996) Persistent elevations of cerebrospinal fluid concentrations of corticotropinreleasing factor in adult nonhuman primates exposed to earlylife stressors: implications for the pathophysiology of mood and anxiety disorders. Proc. Natl. Acad. Sci. USA 93:1619–1623. Coplan, J.D., Papp, L.A., Martinez, M.A., Pine, P., Rosenblum, L. A., Cooper, T., Liebowitz, M.R., and Gorman, J.M. (1995) Persistence of blunted human growth hormone response to clonidine in fluoxetine-treated patients with panic disorder. Am. J. Psychiatry 152:619–622. Coplan, J.D., Pine, D., Papp, L., Martinez, J., Cooper, T., Rosenblum, L.A., and Gorman, J.M. (1995) Uncoupling of the noradrenergic-hypothalamic-pituitary adrenal axis in panic disorder patients. Neuropsychopharmacology 13:65–73. Coryell, W., and Noyes, R. (1988) HPA axis disturbance and treatment outcome in panic disorder. Biol. Psychiatry 24:762–766. Cose, B.J., and Robbins, T.W. (1987) Dissociable effects of lesions to dorsal and ventral noradrenergic bundle on the acquisition, performance, and extinction of aversive conditioning. Behav. Neurosci. 101:476–488. Coste, S.C., Kesterson, R.A., Heldwein, K.A., Stevens, S.L., Heard, A.D., Hollis, J.H., Murray, S.E., Hill, J.K., Pantely, G.A., Hohimer, A.R., Hatton, D.C., Phillips, T.J., Finn, D.A., Low, M.J., Rittenberg, M.B., Stenzel, P., and Stenzel-Poore, M.P. (2000) Abnormal adaptations to stress and impaired cardiovascular function in mice lacking corticotrophin-releasing hormone receptor2. Nature Genet. 24:403–409. David, S.P., Murthy, N.V., Rabiner, E.A., Munafo, M.R., Johnstone, E.C., Jacob, R., Walton, R.T., and Grasby, P.M. (2005) A functional genetic variation of the serotonin (5-HT) transporter affects 5-HT1A receptor binding in humans. J. Neurosci. 25:2586– 2590. Davidson, J., Lipper, S., Kilts, C.D., Mahorney, S., and Hammett, E. (1985) Platelet MAO activity in posttraumatic stress disorder. Am. J. Psychiatry 142:1341–1343. Davidson, J.R., Brady, K., Mellman, T.A., Stein, M.B., and Pollack, M.H. (2007) The efficacy and tolerability of tiagabine in adult

680

ANXIETY DISORDERS

patients with post-traumatic stress disorder. J. Clin. Psychopharmacol. 27:85–88. Davies, S.J., Hood, S.D., Argyropoulos, S.V., Morris, K., Bell, C., Witchel, H.J., Jackson, P.R., Nutt, D.J., and Potokar, J.P. (2006) Depleting serotonin enhances both cardiovascular and psychological stress reactivity in recovered patients with anxiety disorders. J. Clin. Psychopharmacol. 26:414–418. Davis, L.L., Ward, C., Rasmusson, A., Newell, J.M., Frazier, E., Southwick, S.M. (2008) A placebo-controlled trial of guanfacine for the treatment of posttraumatic stress disorder in veterans. Psychopharmacol. Bull. 41:8–18. Davis, M. (2002) The role of NMDA receptors and MAP kinase in the amygdala in extinction of fear: clinical implications for exposure therapy. Eur. J. Neurosci. 16:395–398. DeBellis, M.D., Lefter, L., Trickett, P.K., and Putnam, F.W. (1994) Urinary catecholamine excretion in sexually abused girls. J. Am. Acad. Child Adolesc. Psychiatry 33:320–327. De˛biec, J., and Ledoux, J.E. (2004) Disruption of reconsolidation but not consolidation of auditory fear conditioning by noradrenergic blockade in the amygdala. Neuroscience 129:267–272. De˛biec, J., LeDoux, J.E., and Nader, K. (2002) Cellular and systems reconsolidation in the hippocampus. Neuron 36:527–538. de Brito Faturi, C., Teixeira-Silva, F., and Leite, J.R. (2006) The anxiolytic effect of pregnancy in rats is reversed by finasteride. Pharmacol. Biochem. Behav. 85:569–574. de Kloet, C.S., Vermetten, E., Geuze, E., Lentjes, E.G., Heijnen, C.J., Stalla, G.K., and Westenberg, H.G. (2008) Elevated plasma corticotrophin-releasing hormone levels in veterans with posttraumatic stress disorder. Prog. Brain Res. 167:287– 291. de Kloet, C.S., Vermetten, E., Geuze, E., Wiegant, V.M., and Westenberg, H.G. (2008) Elevated plasma arginine vasopressin levels in veterans with posttraumatic stress disorder. J. Psychiatr. Res. 42:192–198. Dell’Osso, L., Carmassi, C., Palego, L., Trincavelli, M.L., Tuscano, D., Montali, M., Sbrana, S., Ciapparelli, A., Lucacchini, A., Cassano, G.B., and Martini, C. (2004) Serotonin-mediated cyclic AMP inhibitory pathway in platelets of patients affected by panic disorder. Neuropsychobiology 50:28–36. DenBoer, J.A., and Westenberg, H.G.M. (1990) Behavioral, neuroendocrine, and biochemical effects of 5-hydroxytryptophan administration in panic disorder. Psychiatry Res. 31:367–378. de Quervain, D.J. (2008) Glucocorticoid-induced reduction of traumatic memories: implications for the treatment of PTSD. Prog. Brain Res. 167:239–247. de Quervain, D.J., Henke, K., Aerni, A., Treyer, V., McGaugh, J.L., Berthold, T., Nitsch, R.M., Buck, A., Roozendaal, B., and Hock, C. (2003) Glucocorticoid-induced impairment of declarative memory retrieval is associated with reduced blood flow in the medial temporal lobe. Eur. J. Neurosci. 17:1296–302. de Quervain, D.J., Roozendaal, B., Nitsch, R.M., McGaugh, J.L., and Hock, C. (2000) Acute cortisone administration impairs retrieval of long-term declarative memory in humans. Nat. Neurosci. 3:313–314. Deutch, A.Y., and Young, C.D. (1995) A model of the stress-induced activation of prefrontal cortical dopamine systems: coping and the development of post-traumatic stress disorder. In: Friedman, M.J., Charney, D.S., and Deutch, A.Y., eds. Neurobiological and Clinical Consequences of Stress. Philadelphia: Lippincott-Raven, pp. 163–175. Diamond, D.M., Fleshner, M., Ingersoll, N., and Rose, G.M. (1996) Psychological stress impairs spatial working memory: relevance to electrophysiological studies of hippocampal function. Behav. Neurosci. 110:661–672. Dias, R., Sheppard, W.F., Fradley, R.L., Garrett, E.M., Stanley, J.L., Tye, S.J., Goodacre, S., Lincoln, R.J., Cook, S.M., Conley, R., Hallett, D., Humphries, A.C., Thompson, S.A., Wafford, K.A., Street, L.J., Castro, J.L., Whiting, P.J., Rosahl, T.W., Atack, J.R.,

McKernan, R.M., Dawson, G.R., and Reynolds, D.S. (2005) Evidence for a significant role of alpha 3-containing GABAA receptors in mediating the anxiolytic effects of benzodiazepines. J. Neurosci. 25:10682–10688. Diergaarde, L., Schoffelmeer, A.N., and De Vries, T.J. (2006) Betaadrenoceptor mediated inhibition of long-term reward-related memory reconsolidation. Behav. Brain Res. 170:333–336. Domschke, K., Deckert, J., O’donovan, M.C., and Glatt, S.J. (2007) Meta-analysis of COMT val158met in panic disorder: ethnic heterogeneity and gender specificity. Am. J. Med. Genet. 144: 667–673. Dorow, R., Horowski, R., Paschelke, G., Amin, M., and Braestrup, C. (1983) Severe anxiety induced by FG7142, a beta-carboline ligand for benzodiazepine receptors. Lancet 2:98–99. Drevets, W.C., Frank, J.C., Kupfer, D.J., Holt, D., Greer, P.J., Huang, Y., Gautier, C., and Mathis C. (1999) PET imaging of serotonin 1A receptor binding in depression. Biol. Psychiatry 46:1375–1387. Drugan, R.C., Morrow, A.L., Weizman, R., Weizman, A., Deutsch, S.I., Crawley, J.N., and Paul, S.M. (1989) Stress-induced behavioral depression in the rat is associated with a decrease in GABA receptor-mediated chloride ion flux and brain benzodiazepine receptor occupancy. Brain Res. 487:45–51. Duvarci, S., and Nader, K. (2004) Characterization of fear memory reconsolidation. J. Neurosci. 24:9269–9275. Egashira, N., Tanoue, A., Matsuda, T., Koushi, E., Harada, S., Takano, Y., Tsujimoto, G., Mishima, K., Iwasaki, K., and Fujiwara, M. (2007) Impaired social interaction and reduced anxiety-related behavior in vasopressin V1a receptor knockout mice. Behav. Brain Res. 178:123–127. Engelmann, M., Landgraf, R., Wotjak, C.T. (2004) The hypothalamic-neurohypophysial system regulates the hypothalamicpituitary-adrenal axis under stress: an old concept revisited. Front. Neuroendocrinol. 25:132–149. Eriksson, E., Westberg, P., Alling, C., Thuresson, K., and Modigh, K. (1991) Cerebrospinal fluid levels of monoamine metabolites in panic disorder. Psychiatry Res. 36:243–251. Eser, D., di Michele, F., Zwanzger, P., Pasini, A., Baghai, T.C., Schule, C., Rupprecht, R., and Romeo, E. (2005) Panic induction with cholecystokinin-tetrapeptide (CCK-4) Increases plasma concentrations of the neuroactive steroid 3alpha, 5alpha tetrahydrodeoxycorticosterone (3alpha, 5alpha-THDOC) in healthy volunteers. Neuropsychopharmacology 30:192–195. Eser, D., Schule, C., Baghai, T.C., Romeo, E., and Rupprecht, R. (2006) Neuroactive steroids in depression and anxiety disorders: clinical studies. Neuroendocrinology 84:244–254. Esler, M., Lambert, E., Alvarenga, M., Socratous, F., Richards, J., Barton, D., Pier, C., Brenchley, C., Dawood, T., Hastings, J., Guo, L., Haikerwal, D., Kaye, D., Jennings, G., Kalff, V., Kelly, M., Wiesner, G., and Lambert, G. (2007) Increased brain serotonin turnover in panic disorder patients in the absence of a panic attack: reduction by a selective serotonin reuptake inhibitor. Stress 10:295–304. Fanselow, M.S. (1986) Conditioned fear-induced opiate analgesia: a competing motivational state theory of stress analgesia. Ann. N.Y. Acad. Sci. 467:40–54. Farinelli, M., Deschaux, O., Hugues, S., Thevenet, A., and Garcia, R. (2006) Hippocampal train stimulation modulates recall of fear extinction independently of prefrontal cortex synaptic plasticity and lesions. Learn. Mem. 13:329–334. Feltenstein, M.W., and See, R.E. (2007) NMDA receptor blockade in the basolateral amygdala disrupts consolidation of stimulusreward memory and extinction learning during reinstatement of cocaine-seeking in an animal model of relapse. Neurobiol. Learn. Mem. 88:435–444. Feltner, D., Wittchen, H.U., Kavoussi, R., Brock, J., Baldinetti, F., and Pande, A.C. (2008) Long-term efficacy of pregabalin in generalized anxiety disorder. Int. Clin. Psychopharmacol. 23:18–28.

41: NEUROBIOLOGY Finlay, J.M., and Abercrombie, E.D. (1991) Stress induced sensitization of norepinephrine release in the medial prefrontal cortex. Soc. Neurosci. Abstr. 17:151. Fischer, A., Sananbenesi, F., Schrick, C., Spiess, J., and Radulovic, J. (2004) Distinct roles of hippocampal de novo protein synthesis and actin rearrangement in extinction of contextual fear. J. Neurosci. 24:1962–1966. Flood, J.F., Baker, M.L., Hernandez, E.N., and Morley, J.E. (1989) Modulation of memory processing by neuropeptide Y varies with brain injection site. Brain Res. 503:73–82. Foote, S.L., Bloom, F.E., and Aston-Jones, G. (1983) Nucleus locus coeruleus: new evidence for anatomical and physiological specificity. Physiol. Rev. 63:844–914. Fox, N.A., Nichols, K.E., Henderson, H.A., Rubin, K., Schmidt, L., Hamer, D., Ernst, M., and Pine, D.S. (2005) Evidence for a geneenvironment interaction in predicting behavioral inhibition in middle childhood. Psychol. Sci. 16:921–926. Fujita, M., Southwick, S.M., Denucci, C.C., Zoghbi, S.S, Dillon, M.S., Baldwin, R.M., Bozkurt, A., Kugaya, A., Verhoeff, N.P., Seibyl, J.P., and Innis, R.B. (2004) Central type benzodiazepine receptors in Gulf War veterans with posttraumatic stress disorder. Biol. Psychiatry 56:95–100. Furmark, T., Appel, L., Michelgard, A., Wahlstedt, K., Ahs, F., Zancan, S., Jacobsson, E., Flyckt, K., Grohp, M., Bergstrom, M., Pich, E. M., Nilsson, L.G., Bani, M., Langstrom, B., and Fredrikson, M. (2005) Cerebral blood flow changes after treatment of social phobia with the neurokinin-1 antagonist GR205171, citalopram, or placebo. Biol. Psychiatry 58(2):132–142. Furmark, T., Tillfors, M., Garpenstrand, H., Marteinsdottir, I., Långström, B., Oreland, L., and Fredrikson, M. (2004) Serotonin transporter polymorphism related to amygdala excitability and symptom severity in patients with social phobia. Neurosci. Lett. 362: 189–192. Garakani, A., Buchsbaum, M.S., Newmark, R.E., Goodman, C., Aaronson, C.J., Martinez, J.M., Torosjan, Y., Chu, K.W., and Gorman, J.M. (2007) The effect of doxapram on brain imaging in patients with panic disorder. Eur. Neuropsychopharmacol. 17: 672–686. Garakani, A., Mathew, S.J., and Charney, D.S. (2006) Neurobiology of anxiety disorders and implications for treatment. Mt. Sinai J. Med. 73:941–949. Garcia, R., Chang, C.H., and Maren, S. (2006) Electrolytic lesions of the medial prefrontal cortex do not interfere with long-term memory of extinction of conditioned fear. Learn. Mem. 13: 14–17. Gartside, S.E., Johnson, D.A., Leitch, M.M., Troakes, C., and Ingram, C.D. (2003) Early life adversity programs changes in central 5-HT neuronal function in adulthood. Eur. J. Neurosci. 17: 2401–2408. Gelernter, J., Southwick, S., Goodson, S., Morgan, A., Nagy, L., and Charney, D.S. (1999) No association between D2 dopamine receptor (DRD2) “A” system alleles or DRD2 haplotypes and posttraumatic stress disorder. Biol. Psychiatry 45:620–625. Gentleman, S.M., Falkai, P., Bogerts, B., Herrero, M.T., Polak, J.M., and Roberts, G.W. (1989) Distribution of galanin-like immunoreactivity in the human brain. Brain Res. 505:311–315. Geracioti, T.D., Jr., Baker, D.G., Ekhator, N.N., West, S.A., Hill, K.K., Bruce, A.B., Schmidt, D., Rounds-Kugler, B., Yehuda, R., Keck, P.E., Jr., and Kasckow, J.W. (2001) CSF norepinephrine concentrations in posttraumatic stress disorder. Am. J. Psychiatry 158:1227–1230. Glover, H. (1993) A preliminary trial of nalmefene for the treatment of emotional numbing in combat veterans with post-traumatic stress disorder. Isr. J. Psychiatry Relat. Sci. 30:255–263. Goddard, A.W., Mason, G.F., Almai, A., Rothman, D.L., Behar, K.L., Petroff, O.A., Charney, D.S., and Krystal, J.H. (2001) Reductions in occipital cortex GABA levels in panic disorder detected

681

with 1h-magnetic resonance spectroscopy. Arch. Gen. Psychiatry 58:556–561. Goddard, A.W., Mason, G.F., Appel, M., Rothman, D.L., Gueorguieva, R., Behar, K.L., and Krystal, J.H. (2004) Impaired GABA neuronal response to acute benzodiazepine administration in panic disorder. Am. J. Psychiatry 161:2186–2193. Goddard, A.W., Sholomskas, D.E., Augeri, F.M., Walton, K.E., Charney, D.S., Heninger, G.R., Goodman, W.K. and Price, L.H. (1994) Effects of tryptophan depletion in panic disorders. Biol. Psychiatry 36:775–777. Goddard, A.W., Woods, S.W., Money, R., Pande, A.C., Charney, D.S., Goodman, W.K., Heninger, G.R., and Price, L.H. (1999) Effects of the CCK(B) antagonist CI-988 on responses to mCPP in generalized anxiety disorder. Psychiatry Res. 85:225–240. Goldstein, L.E., Rasmusson, A.M., Bunney, B.S., and Roth, R.H. (1996) Role of the amygdala in the coordination of behavioral, neuroendocrine, and prefrontal cortical monoamine responses to psychological stress in the rat. J. Neurosci. 16:4787–4798. Goosens, K.A., and Maren, S. (2004) NMDA receptors are essential for the acquisition, but not expression, of conditional fear and associative spike firing in the lateral amygdala. Eur. J. Neurosci. 20:537–548. Gorman, J.M., Battista, D., Goetz, R., et al. (1989) A comparison of sodium bicarbonate and sodium lactate infusion in the induction of panic attacks. Arch. Gen. Psychiatry 46:145–150. Gorman, J.M., Fyer, M.R., Goetz, R., Askanazi, J., Liebowitz, M.R., Fyer, A.J., and Klein, D.F. (1988) Ventilatory physiology of patients with panic disorder. Arch. Gen. Psychiatry 45:31–39. Gorman, J.M., Goetz, R.R., Dillon, D., et al. (1990) Sodium d-lactate infusion in panic disorder patients. Neuropsychopharmacology 3:181–190. Gottsch, M.L., Zeng, H., Hohmann, J.G., Weinshenker, D., Clifton, D.K., and Steiner, R.A. (2005) Phenotypic analysis of mice deficient in the type 2 galanin receptor (GALR2). Mol. Cell Biol. 25:4804–4811. Graeff, F.G. (2004) Serotonin, the periaqueductal gray and panic. Neurosci. Biobehav. Rev. 28:239–259. Grammatopoulos, D.K., and Chrousos, G.P. (2002) Functional characteristics of CRH receptors and potential clinical applications of CRH-receptor antagonists. Trends Endocrinol. Metab. 13:436–444. Griebel, G., Simiand, J., Serrradeil-Le Gal, L.C., Wagnon, J., Pascal, M., Scatton, B., Maffrand, J.P., and Soubrie, P. (2002) Anxiolytic-and antidepressant-like effects of the non-peptide vasopressin V1b receptor antagonist, SSR149415, suggest an innovative approach for the treatment of stress-related disorders. Proc. Natl. Acad. Sci. USA 99(9):6370–6375. Griez, E., Lousberg, H., Van Den Hout, M.A., and van der Molen, G.M. (1987) Carbon dioxide vulnerability in panic disorder. Psychiatry Res. 20:87–95. Grillon, C., Cordova, J., Morgan, C.A., Charney, D.S., and Davis, M. (2004) Effects of the beta-blocker propranolol on cued and contextual fear conditioning in humans. Psychopharmacology (Berl) 175:342–352. Gross, C., Zhuang, X., Stark, K., Ramboz, S., Oosting, R., Kirby, L., et al. (2002) Serotonin 1A receptor acts during development to establish normal anxiety-like behavior in the adult. Nature 416:396–400. Guastella, A.J., Richardson, R., Lovibond, P.F., Rapee, R.M., Gaston, J.E., Mitchell, P., and Dadds, M.R. (2008) A randomized controlled trial of D-cycloserine enhancement of exposure therapy for social anxiety disorder. Biol. Psychiatry 63:544–549. Guastella, A.J., Dadds, M.R., Lovibond, P.F., Mitchell, P., and Richardson, R. (2007) A randomized controlled trial of the effect of d-cycloserine on exposure therapy for spider fear. J. Psychiatry Res. 41:466–471. Gurguis, G.N.M., and Uhde, T.W. (1990) Plasma 3-methoxy-4 hydroxyphenylethylene glycol (MHPG) and growth hormone

682

ANXIETY DISORDERS

responses in panic disorder patients and normal controls. Psychoneuroendocrinology 15:217–224. Gustafson, E.L., Smith, K.E., Durkin, M.M., Gerald, C., and Branchek, T.A. (1996) Distribution of a rat galanin receptor mRNA in rat brain. Neuroreport 7:953–957. Hallschmid, M., Gais, S., Meinert, S., and Born, J. (2003) NPY attenuates positive cortical DC-potential shift upon food intake in man. Psychoneuroendocrinology 28:529–539. Ham, B.J., Sung, Y., Kim, N., Kim, S.J., Kim, J.E., Kim, D.J., Lee, J. Y., Kim, J.H., Yoon, S.J., and Lyoo, I.K. (2007) Decreased GABA levels in anterior cingulate and basal ganglia in medicated subjects with panic disorder: a proton magnetic resonance spectroscopy (1H-MRS) study. Prog. Neuropsychopharmacol. Biol. Psychiatry 31:403–411. Hamner, M.B., and Diamond, B.I. (1993) Elevated plasma dopamine in posttraumatic stress disorder: a preliminary report. Biol. Psychiatry 33:304–306. Hamon, M., Gozlan, H., El Mestikawy, S., Emerit, M., Bolanos, F., and Schechter, L. (1990) The central 5-HT1a receptors: pharmacological biochemical, functional, and regulatory properties. Ann. NY Acad. Sci. 600:114–129. Hano, J., Vasar, E., and Bradwejn, J. (1993) Cholecystokinm in animal and human research on anxiety. Trends Pharmacol. Sci. 14: 244–249. Hariri A.R., Drabant, E.M., Munoz, K.E., Kolachana, B.S., Mattay, V.S., Egan, M.F., and Weinberger, D.R. (2005) A susceptibility gene for affective disorders and the response of the human amygdala. Arch. Gen. Psychiatry 62:146–152. Hariri, A.R., Mattay, V.S., Tessitore, A., Kolachana, B., Fera, F., Goldman, D., Egan, M.F., and Weinberger, D.R. (2002) Serotonin transporter genetic variation and the response of the human amygdala. Science 297:400–403. Harro, J. (2006) CCK and NPY as anti-anxiety treatment targets: promises, pitfalls, and strategies. Amino Acids 31:215–230. Hawes, J.J., Brunzell, D.H., Wynick, D., Zachariou, V., and Picciotto, M.R. (2005) GalR1, but not GalR2 or GalR3, levels are regulated by galanin signaling in the locus coeruleus through a cyclic AMP-dependent mechanism. J. Neurochem. 93:1168–1176. Hawes, J.J., and Picciotto, M.R. (2004) Characterization of GalR1, GalR2, and GalR3 immunoreactivity in catecholaminergic nuclei of the mouse brain. J. Comp. Neurol. 479(4):410–423. Hayden, E.P., Dougherty, L.R., Maloney, B., Emily Durbin, C., Olino, T.M., Nurnberger, J.I., Jr., Lahiri, D.K., and Klein, D.N. (2007) Temperamental fearfulness in childhood and the serotonin transporter promoter region polymorphism: a multimethod association study. Psychiatr. Genet. 17:135–142. Hebb, A.L., Poulin, J.F., Roach, S.P., Zacharko, R.M., and Drolet, G. (2005) Cholecystokinin and endogenous opioid peptides: interactive influence on pain, cognition, and emotion. Prog. Neuropsychopharmacol. Biol. Psychiatry 29:1225–1238. Heilig, M. (1995) Antisense inhibition of neuropeptide Y (NPY)-Y1 receptor expression blocks the anxiolytic-like action of NPY in amygdala and paradoxically increases feeding. Regul. Pept. 59: 201–205. Heilig, M., Koob, G.F., Ekman, R., and Britton, K.T. (1994) Corticotropin-releasing factor and neuropeptide Y: role in emotional integration. Trends Neurosci. 17:80–85. Heilig, M., McLeod, S., Brot, M., Heinrichs, S.C., Menzaghi, F., Koob, G.F., and Britton, K.T. (1993) Anxiolytic-like action of neuropeptide Y: mediation by Y1 receptors in amygdala, and dissociation from food intake effects. Neuropsychopharmacology 8: 357–363. Henry, M., Fishman, J.R., and Youngner, S.J. (2007) Propranolol and the prevention of post-traumatic stress disorder: is it wrong to erase the “sting” of bad memories? Am. J. Bioeth. 7:12–20. Heresco-Levy, U., Kremer, I., Javitt, D.C., Goichman, R., Reshef, A., Blanaru, M., and Cohen, T. (2002) Pilot-controlled trial of

D-cycloserine for the treatment of post-traumatic stress disorder. Int. J. Neuropsychopharmacol. 5:301–307. Hernando, F., Schoots, O., Lolait, S.J., and Burbach, J.P. (2001) Immunohistochemical localization of the vasopressin V1b receptor in the rat brain and pituitary gland: anatomical support for its involvement in the central effects of vasopressin. Endocrinology 142:1659–1668. Herry, C., and Garcia, R. (2002) Prefrontal cortex long-term potentiation but not long-term depression is associated with maintenance of extinction of learned fear in mice. J. Neurosci. 22:577–583. Hertzberg, T., and Wahlbeck, K. (1999) The impact of pregnancy and puerperium on panic disorder: a review. J. Psychsom. Obstet. Gynaecol. 20:59–64. Heydari, B., and Le Mellédo, J.M. (2002) Low pregnenolone sulphate plasma concentrations in patients with generalized social phobia. Psychol. Med. 32:929–933. Hodgson, R.A., Higgins, G.A., Guthrie, D.H., Lu, S.X., Pond, A.J., Mullins, D.E., Guzzi, M.F., Parker, E.M., and Varty, G.B. (2007) Comparison of the V1b antagonist, SSR149415, and the CRF1 antagonist, CP-154,526, in rodent models of anxiety and depression. Pharmacol. Biochem. Behav. 86:431–440. Hoffman, L., Watsgon, P.D., Wilson, G., and Montgomery, J. (1989) Low plasma endorphin in posttraumatic stress disorder. Aust. N.Z. J. Psychiatry 23:268–273. Hofmann, S.G., Meuret, A.E., Smits, J.A., Simon, N.M., Pollack, M.H., Eisenmenger, K., Shiekh, M., and Otto, M.W. (2006) Augmentation of exposure therapy with D-cycloserine for social anxiety disorder. Arch. Gen. Psychiatry 63:298–304. Holmes, A., Kinney, J.W., Wrenn, C.C., Li, Q., Yang, R.J., Ma, L., Vishwanath, J., Saavedra, M., Innerfield, C.E., Jacoby, A.S., Shine, J., Iismaa, T.P., and Crawley, J.N. (2003) Galanin GAL-R1 receptor null mutant mice display increased anxiety-like behavior specific to the elevated plus-maze. Neuropsychopharmacology 28: 1031–1044. Holmes, A., Lit, Q., Murphy, D.L., Gold, E., and Crawley, J.N. (2003) Abnormal anxiety-related behavior in serotonin transporter null mutant mice: the influence of genetic background. Genes Brain Behav. 2:365–380. Holmes, A., Yang, R.J., and Crawley, J.N. (2002) Evaluation of an anxiety-related phenotype in galanin overexpressing transgenic mice. J. Mol. Neurosci. 18:151–165. Holmes, A., Yang, R.J., Murphy, D.L., and Crawley, J.N. (2002) Evaluation of antidepressant-related behavioral responses to mice lacking the serotonin transporter. Neuropsychopharmacology 27: 914–923. Holmes, P.V., and Crawley, J.N. (1995) Coexisting neurotransmitters in central noradrenergic neurons. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 347–353. Holsboer, F., von Bardeleben, U., Buller, R., Heuser, I., and Steiger, A. (1987) Stimulation response to corticotropin-releasing hormone (CRH) in patients with depression, alcoholism and panic disorder. Horm. Metab. Res. 16(Suppl.):80–88. Hösing, V.G., Schirmacher, A., Kuhlenbäumer, G., Freitag, C., Sand, P., Schlesiger, C., Jacob, C., Fritze, J., Franke, P., Rietschel, M., Garritsen, H., Nöthen, M.M., Fimmers, R., Stögbauer, F., and Deckert, J. (2004) Cholecystokinin- and cholecystokinin-B-receptor gene polymorphisms in panic disorder. J. Neural Transm. (Suppl. 68):147–156. Hurlemann, R., Hawellek, B., Matusch, A., Kolsch, H., Wollersen, H., Madea, B., Vogeley, K., Maier, W., and Dolan, R.J. (2005) Noradrenergic modulation of emotion-induced forgetting and remembering. J. Neurosci. 25:6343–6349. Illes, P., Finta, E.P., and Nieber, K. (1993) Neuropeptide Y potentiates via Y2-receptors: the inhibitory effect of noradrenaline in rat locus coeruleus neurons. Nauyn Schmiedebergs Arch. Pharmacol. 348:546–548.

41: NEUROBIOLOGY Innis, R.B., Charney, D.S., and Heninger, G.R. (1987) Differential 3H imipramine platelet binding in patients with panic disorder and depression. Psychiatry Res. 21:33–41. Ishikawa-Brush, Y., Powell, J.F., Bolton, P., Miller, A.P., Francis, F., Willard, H.F., Lehrach, H., and Monaco, A.P. (1997) Autism and multiple exostoses associated with an X-8 translocation occurring within the GRPR gene and 39 to the SDC2 gene. Hum. Mol. Genet. 6:1241–1250. Izquierdo, A., Wellman, C.L., and Holmes, A. (2006) Brief uncontrollable stress causes dendritic retraction in infralimbic cortex and resistance to fear extinction in mice. J. Neurosci. 26:5733– 5738. Jasnow, A.M., Cooper, M.A., and Huhman, K.L. (2004) N-methylD-aspartate receptors in the amygdala are necessary for the acquisition and expression of conditioned defeat. Neuroscience 123: 625–634. Jin, X.C., Lu, Y.F., Yang, X.F., Ma, L., and Li, B.M. (2007) Glucocorticoid receptors in the basolateral nucleus of amygdala are required for postreactivation reconsolidation of auditory fear memory. Eur. J. Neurosci. 25:3702–3712. Kahn, R.S., Asnis, G.M., Wetzler, S., Asnis, G.M., and Barr, G. (1988) Serotonin and anxiety revisited. Biol. Psychiatry 23:189–208. Karlamangla, A.S., Singer, B.H., McEwen, B.S., Rowe, J.W., and Seeman, T.E. (2002) Allostatic load as a predictor of functional decline: MacArthur studies of successful aging. J. Clin. Epidemiol. 55:696–710. Karlsson, R.M., and Holmes, A. (2006) Galanin as a modulator of anxiety and depression and a therapeutic target for affective disease. Amino Acids 31:231–239. Karlsson, R.M., Holmes, A., Heilig, M., and Crawley, J.N. (2005) Anxiolytic-like actions of centrally-administered neuropeptide Y, but not galanin, in C57BL/6J mice. Pharmacol. Biochem. Behav. 80:427–436. Kash, T.L., and Winder, D.G. (2006) Neuropeptide Y and corticotropin-releasing factor bi-directionally modulate inhibitory synaptic transmission in the bed nucleus of the stria terminalis. Neuropharmacology 51:1013–1022. Kask, A., Harro, J., von Horsten, S., Redrobe, J.P., Dumont, Y., and Quiron, R. (2002) The neurocircuitry and receptor subtypes mediating anxiolytic-like effects of neuropeptide Y. Neurosci. Behav. Rev. 26:259–283. Kask, A., Rago, L., and Harro, J. (1997) Alpha-lhelical CRF (9-41) prevents anxiogenic-like effect on NPY Y1 receptor antagonist BIBP3226 in rats. Neuroreport 8:3645–3647. Kask, A., Rago, L., and Harro, J. (1998a) Anxiolytic-like effect of neuropeptide Y (NPY) and NPY 13-36 microinjected into vicinity of locus coeruleus in rats. Brain Res. 788:345–348. Kask, A., Rago, L., and Harro, J. (1998b) NPY Y1 receptors in the dorsal periaqueductal gray matter regulate anxiety in the social interaction test. Neuroreport 9:2713–2716. Kathol, R.G., Anton, R., Noyes, R., Lopez, A.L., and Reich, J.H. (1988) Relationship of urinary free cortisol levels in patients with panic disorder to symptoms of depression and agoraphobia. Psychiatry Res. 24:211–221. Katzman, M.A., Koszycki, D., and Bradwejn, J. (2004) Effects of CCK-tetrapeptide in patients with social phobia and obsessivecompulsive disorder. Depress. Anxiety 20:51–58. Kaufman, J., Yang, B.Z., Douglas-Palumberi, H., Houshyar, S., Lipschitz, D., Krystal, J.H., and Gelernter, J. (2004) Social supports and serotonin transporter gene moderate depression in maltreated children. Proc. Natl. Acad. Sci. USA 101:17316–17321. Kellner, M., Wiedemann, K., Yassouridis, A., Levengood, R., Guo, L.S., Holsboer, F., and Yehuda, R. (2000) Behavioral and endocrine response to cholecystokinin tetrapeptide in patients with posttraumatic stress disorder. Biol. Psychiatry 47:107–111. Kent, J.M., Mathew, S.J., and Gorman, J.M. (2002) Molecular targets in the treatment of anxiety. Biol. Psychiatry 52:1008–1030.

683

Kern, R.P., Libkuman, T.M., Otani, H., and Holmes, K. (2005) Emotional stimuli, divided attention, and memory. Emotion 5:408– 417. Khoshbouei, H., Cecchi, M., Dove, S., Javors, M., and Morilak, D.A. (2002) Behavioral reactivity to stress: Amplification of stressinduced noradrenergic activation elicits a galanin-mediated anxiolytic effect in central amygdala. Pharmacol. Biochem. Behav. 71:407–417. Khoshbouei, H., Cecchi, M., and Morilak, D.A. (2002) Modulatory effects of galanin in the lateral bed nucleus of the stria terminalis on behavioral and neuroendocrine responses to acute stress. Neuropsychopharmacology 27:25–34. Kida, S., Josselyn, S.A., de Ortiz, S.P., Kogan, J.H., Chevere, I., Masushige, S., and Silva, A.J. (2002) CREB required for the stability of new and reactivated fear memories. Nature Neurosci. 4:348– 355. Kim, J.J., and Diamond, D.M. (2002) The stressed hippocampus, synaptic plasticity and lost memories. Nat. Rev. Neurosci. 3:453–462. Kinney, J.W., Starosta, G., Holmes, A., Wrenn, C.C., Yang, R.J., Harris, A.P., Long, K.C., and Crawley, J.N. (2002) Deficits in trace cued fear conditioning in galanin-treated rats and galaninoverexpressing transgenic mice. Learn. Mem. 9:178–190. Kirsch, P., Esslinger, C., Chen, Q., Mier, D., Lis, S., Siddhanti, S., Gruppe, H., Mattay, V.S., Gallhofer, B., and Meyer-Lindenberg, A. (2005) Oxytocin modulates neural circuitry for social cognition and fear in humans. J. Neurosci. 25:11489–11493. Klein, D.F. (1993) False suffocation alarms, spontaneous panics, and related conditions. Arch. Gen. Psychiatry 50:306–317. Klemenhagen, K.C., Gordon, J.A., David, D.J., Hen, R., and Gross, C.T. (2006) Increased fear response to contextual cues in mice lacking the 5-HT1A receptor. Neuropsychopharmacology 31:101– 111. Kramer, M.S., Cutler, N.R., Ballenger, J.C., Patterson, W.M., Mendels, J., Chenault, A., Shrivastava, R., Matzura-Wolfe, D., Lines, C., and Reines, S. (1995) A placebo-controlled trial of L-365,260, a CCKB antagonist, in panic disorder. Biol. Psychiatry 37:462– 466. Kusserow, H., Davies, B., Hörtnagl, H., Voigt, I., Stroh, T., Bert, B., Deng, D.R., Fink, H., Veh, R.W., and Theuring, F. (2004) Reduced anxiety-related behaviour in transgenic mice overexpressing serotonin 1A receptors. Brain Res. Mol. Brain Res. 129:104– 116. Kuteeva, E., Wardi, T., Hokfelt, T., and Ogren, S.O. (2007) Galanin enhances and a galanin antagonist attenuates depression-like behaviour in the rat. Eur. Neuropsychopharmacol. 17:64–69. Lacroix, J.S., Ricchetti, A.P., Morel, D., Mossimann, B., Waeber, B., and Grouzmann, E. (1996) Intranasal administration of neuropeptide Y in man: systemic absorption and functional effects. Br. J. Pharmacol. 118:2079–2084. Lähdesmäki, J., Sallinen, J., MacDonald, E., Kobilka, B.K., Fagerholm, V., and Scheinin, M. (2002) Behavioral and neurochemical characterization of alpha(2A)-adrenergic receptor knockout mice. Neuroscience 113:289–299. Lähdesmäki, J., Sallinen, J., MacDonald, E., and Scheinin, M. (2004) Alpha2A-adrenoceptors are important modulators of the effects of D-amphetamine on startle reactivity and brain monoamines. Neuropsychopharmacology 29:1282–1293. Lang, U.E., Bajbouj, M., Wernicke, C., Rommelspacher, H., DankerHopfe, H., and Gallinat, J. (2004) No association of a functional polymorphism in the serotonin transporter gene promoter and anxiety-related personality traits. Neuropsychobiology 49:182– 184. Lanzenberger, R.R., Mitterhauser, M., Spindelegger, C., Wadsak, W., Klein, N., Mien, L.K., Holik, A., Attarbaschi, T., Mossaheb, N., Sacher, J., Geiss-Granadia, T., Kletter, K., Kasper, S., and Tauscher, J. (2007) Reduced serotonin-1A receptor binding in social anxiety disorder. Biol. Psychiatry 61:1081–1089.

684

ANXIETY DISORDERS

Laufer, N., Maayan, R., Hermesh, H., Marom, S., Gilad, R., Strous, R., and Weizman, A. (2005) Involvement of GABA-A receptor modulating neuroactive steroids in patients with social phobia. Psychiatry Res. 137:131–136. LeDoux, J.E. (2000) Emotion circuits in the brain. Annu. Rev. Neurosci. 23:155–184. Lee, H.J., Lee, M.S., Kang, R.H., Kim, H., Kim, S.D., Kee, B.S., Kim, Y.H., Kim, Y.K., Kim, J.B., Yeon, B.K., Oh, K.S., Oh, B.H., Yoon, J.S., Lee, C., Jung, H.Y., Chee, I.S., and Paik, I.H. (2005) Influence of the serotonin transporter promoter gene polymorphism on susceptibility to posttraumatic stress disorder. Depress. Anxiety 21:135–139. Lee, J.L., Milton, A.L., and Everitt, B.J. (2006) Reconsolidation and extinction of conditioned fear: inhibition and potentiation. J. Neurosci. 26:10051–10056. Lee, Y., Schulkin, J., and Davis, M. (1994) Effect of corticosterone on the enhancement of the acoustic startle reflex by corticotrophin releasing factor (CRF). Brain Res. 666:93–98. Lemieux, A.M., and Coe, C.L. (1995) Abuse-related PTSD: evidence for chronic neuroendocrine activation in women. Psychosom. Med. 57:105–115. Lerer, B., Ebstein, R.P., Shestatsky, M., Shemesh, Z., and Greenberg, D. (1987) Cyclic AMP signal transduction in posttraumatic stress disorder. Am. J. Psychiatry 144:1324–1327. Lesch, K.P., Bengel, D., Heils, A., Sabol, S.Z., Greenberg, B.D., Petri, S., Benjamin, J., Muller, C.R., Hamer, D.H., and Murphy, D. L. (1996) Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science 274:1527–1531. Levine, E.S., Litto, W.J., and Jacobs, B.L. (1990) Activity of cat locus coeruleus noradrenergic neurons during the defense reaction. Brain Res. 531:189–195. Liberzon, I., Taylor, S.F., Phan, K.L., Britton, J.C., Fig, L.M., Bueller, J.A., Koeppe, R.A., and Zubieta, J.K. (2007) Altered central micro-opioid receptor binding after psychological trauma. Biol. Psychiatry 61:1030–1038. Lin, C.H., Yeh, S.H., Lu, H.Y., and Gean, P.W. (2003) The similarities and diversities of signal pathways leading to consolidation of conditioning and consolidation of extinction of fear memory. J. Neurosci. 23:8310–8317. Lubin, G., Weizman, A., Shmushkevitz, M., and Valevski, A. (2002) Short-term treatment of post-traumatic stress disorder with naltrexone: An open-label preliminary study. Hum. Psychopharmacol. 17:181–185. Lydiard, R.B., Ballenger, J.C., Laraia, M.T., Fossey, M.D., and Beinfeld, M.C. (1992) CSF cholecystokinin concentrations in patients with panic disorder and normal comparison subjects. Am. J. Psychiatry 149:691–693. Madden, J., Akil, H., Patrick, R.L., and Barchas, J.D. (1977) Stress induced parallel changes in central opioid levels and pain responsiveness in the rat. Nature 265:358–360. Maes, M., Lin, A.H., Delmeire, L., Van Gastael, A., Kenis, G., De Jongh, R., and Bosmans, E. (1999) Elevated serum interleukin-6 (IL-6) and IL-6 receptor concentrations in posttraumatic stress disorder following accidental man-made traumatic events. Biol. Psychiatry 45(7):833–839. Maier, S.F. (1986) Stressor controllability and stress induced analgesia. Ann. N.Y. Acad. Sci. 467:55–72. Makara, G.B., Mergl, Z., and Zelena, D. (2004) The role of vasopressin in hypothalamo-pituitary-adrenal axis activation during stress: an assessment of the evidence. Ann. N. Y. Acad. Sci. 1018:151–161. Makino, S., Baker, R.A., Smith, M.A., and Gold, P.W. (2000) Differential regulation of neuropeptide Y mRNA expression in the accurate nucleus and locus coeruleus by stress and antidepressants. J. Neuroendocrinol. 12:387–395. Makino, S., Gold, P.W., and Schulkin, J. (1994) Effects of corticosterone on CRH mRNA and content in the bed nucleus of the stria

terminalis; comparison with the effects in the central nucleus of the amygdala and the paraventricular nucleus of the hypothalamus. Brain Res. 675:141–149. Makino, S., Gold, P.W., and Schulkin, J. (1995) Corticosterone effects on corticotrophin-releasing hormone mRNA in the central nucleus of the amygdala and the parvocellular region of the paraventricular nucleus of the hypothalamus. Brain Res. 640:105– 112. Malberg, J.E., Eisch, A.J., Nestler, E.J., and Duman, R.S. (2000) Chronic antidepressant treatment increases neurogenesis in adult rat hippocampus. J. Neurosci. 20:9104–9110. Mann, P.E. (2006) Finasteride delays the onset of maternal behavior in primigravid rats. Physiol. Behav. 88:333–338. Maren, S., Aharonov, G., Stote, D.L., and Fanselow, M.S. (1996) N-methyl-D-aspartate receptors in the basolateral amygdala are required for both acquisition and expression of conditional fear in rats. Behav. Neurosci. 110:1365–1374. Maron, E., and Shlik, J. (2006) Serotonin function in panic disorder: important, but why? Neuropsychopharmacology 31:1–11. Marshall, R.D., Blanco, C., Printz, D., Liebowitz, M.R., Klein, D.F., and Coplan, J. (2002) A pilot study of noradrenergic and HPA axis functioning in PTS vs. panic disorder. Psychiatry Res. 110: 219–230. Martins, A.P., Maras, R.A., and Guimaraes, F.S. (2001) Anxiolytic effect of a CRH receptor antagonist in the dorsal periaqueductal gray. Depress. Anxiety 12:99–101. Matsumoto, K., Puia, G., Dong, E., and Pinna, G. (2007) GABA(A) receptor neurotransmission dysfunction in a mouse model of social isolation-induced stress: possible insights into a non-serotonergic mechanism of action of SSRIs in mood and anxiety disorders. Stress 10:3–12. Matus-Amat, P., Higgins, E.A., Sprunger, D., Wright-Hardesty, K., and Rudy, J.W. (2007) The role of dorsal hippocampus and basolateral amygdala NMDA receptors in the acquisition and retrieval of context and contextual fear memories. Behav. Neurosci. 121:721–731. McEwen B.S. (2000) Effects of adverse experiences for brain structure and function. Biol. Psychiatry 48:721–731. McFall, M.E., Veith, R.C., and Murburg, M.M. (1992) Basal sympathoadrenal function in posttraumatic stress disorder. Biol. Psychiatry 31:1050–1056. McGaugh, J.L. (2002) Memory consolidation and the amygdala: a systems perspective. Trends Neurosci. 25:456–461. McGaugh, J.L., and Roozendaal, B. (2002) Role of adrenal stress hormones in forming lasting memory in the brain. Curr. Opin. Neurobiol. 12:205–210. McGrath, M., Kawachi, I., Ascherio, A., Colditz, G.A., Hunter, D. J., and De Vivo, I. (2004) Association between catechol-O-methyltransferase and phobic anxiety. Am. J. Psychiatry 161:1703– 1705. McIntyre, C.K., Hatfield, T., and McGaugh, J.L. (2002) Amygdala norepinephrine levels after training predict inhibitory avoidance retention performance in rats. Eur. J. Neurosci. 16:1223–1226. McKinney, B.C., and Murphy, G.G. (2006) The L-type voltage-gated calcium channel Cav1.3 mediates consolidation, but not extinction, of contextually conditioned fear in mice. Learn. Mem. 13: 584–589. McNally, G.P. and Cole, S. (2006) Opioid receptors in the midbrain periaqueductal gray regulate prediction errors during Pavlovian fear conditioning. Behav. Neurosci. 120:313–323. McNally, G.P., Pigg, M., and Weidemann, G. (2004) Opioid receptors in the midbrain periaqueductal gray regulate extinction of pavlovian fear conditioning. J. Neurosci. 24:6912–6919. Mehta, M., Ahmed, Z., Fernando, S.S., Cano-Sanchez, P., Adayev, T., Ziemnicka, D., Wieraszko, A., and Banerjee, P. (2007) Plasticity of 5-HT 1A receptor-mediated signaling during early postnatal brain development. J. Neurochem. 101:918–928.

41: NEUROBIOLOGY Mei, B., Li, C., Dong, S., Jiang, C.H., Wang, H., and Hu, Y. (2005) Distinct gene expression profiles in hippocampus and amygdala after fear conditioning. Brain Res. Bull. 67:1–12. Meinlschmidt, G., and Heim, C. (2007) Sensitivity to intranasal oxytocin in adult men with early parental separation. Biol. Psychiatry 61:1109–1111. Mellman, T.A., Kumar, A., Kulick-Bell, R., Kumar, M., and Nolan, B. (1995) Nocturnal/daytime urine norepinephrine measures and sleep in combat-related PTSD. Biol. Psychiatry 38:174–179. Milad, M.R., and Quirk, G.J. (2002) Neurons in medial prefrontal cortex signal memory for fear extinction. Nature 420:70–74. Milekic, M.H., and Alberini, C.M. (2002) Temporally graded requirement for protein synthesis following memory reactivation. Neuron 36:521–525. Miracle, A.D., Brace, M.F., Huyck, K.D., Singler, S.A., and Wellman, C.L. (2006) Chronic stress impairs recall of extinction of conditioned fear. Neurobiol. Learn. Mem. 85:213–218. Möhler, H. (2006) GABAA receptors in central nervous system disease: anxiety, epilepsy, and insomnia. J. Recept. Signal Transduct. Res. 26:731–740. Moller, C., Sommer, W., Thorsell, A., and Heilig, M. (1999) Anxiogenic-like action of galanin after intra-amygdala administration in the rat. Neuropsychopharmacology 21:507–512. Montgomery, S.A., Tobias, K., Zornberg, G.L., Kasper, S., and Pande, A.C. (2006) Efficacy and safety of pregabalin in the treatment of generalized anxiety disorder: a 6-week, multicenter, randomized, double-blind, placebo-controlled comparison of pregabalin and venlafaxine. J. Clin. Psychiatry 67:771–782. Morgan, C.A., Rasmusson, A.M., Wang, S., Hoyt, G., Hauger, R.L., and Hazlett, G. (2002) Neuropeptide-Y, cortisol, and subjective distress in humans exposed to acute stress: replication and extension of previous report. Biol. Psychiatry 52:136–142. Morgan, C.A., Rasmusson, A.M., Winters, B., Hauger, R.L., Morgan, J., Hazlett, G., and Southwick, S. (2003) Trauma exposure rather than posttraumatic stress disorder is associated with reduced baseline plasma neuropeptide-Y levels. Biol. Psychiatry 54:1087–1091. Morgan, C.A., Wang, S., Mason, J., Southwick, S.M., Fox, P., Hazlett, G., Charney, D.S., and Greenfield, G. (2000) Hormone profiles in humans experiencing military survival training. Biol. Psychiatry 47:891–901. Morgan, M.A., Romanski, L.M., and LeDoux, J.E. (1993) Extinction of emotional learning: contribution of medial prefrontal cortex. Neurosci. Lett. 163:109–113. Morilak, D.A., Barrera, G., Echevarria, D.J., Garcia, A.S., Hernandez, A., Ma, S., and Petre, C.O. (2005) Role of brain norepinephrine in the behavioral response to stress. Prog. Neuropsychopharmacol. Biol. Psychiatry 29:1214–1224. Morris, H.V., Dawson, G.R., Reynolds, D.S., Atack, J.R., and Stephens, D.N. (2006) Both alpha2 and alpha3 GABAA receptor subtypes mediate the anxiolytic properties of benzodiazepine site ligands in the conditioned emotional response paradigm. Eur. J. Neurosci. 23:2495–504. Morrow, B.A., Elsworth, J.D., Rasmusson, A.M., and Roth, R.H. (1999) The role of mesoprefrontal dopamine neurons in the acquisition and expression of conditioned fear in the rat. Neuroscience 92(2):553–564. Moses-Kolko, E.L., Price, J.C., Thase, M.E., Meltzer, C.C., Kupfer, D.J., Mathis, C.A., Bogers, W.D., Berman, S.R., Houck, P.R., Schneider, T.N., and Drevets, W.C. (2007) Measurement of 5HT1A receptor binding in depressed adults before and after antidepressant drug treatment using positron emission tomography and [11C]WAY-100635. Synapse 61:523–530. Mula, M., Pini, S., and Cassano, G.B. (2007) The role of anticonvulsant drugs in anxiety disorders: a critical review of the evidence. J. Clin. Psychopharmacol. 27:263–272. Müller, M.B., Landgraf, R., Preil, J., Sillaber, I., Kresse, A.E., Keck, M.E., Zimmermann, S., Holsboer, F., and Wurst, W. (2000) Se-

685

lective activation of the hypothalamic vasopressinergic system in mice deficient for the corticotropin-releasing hormone receptor 1 is dependent on glucocorticoids. Endocrinology 141:4262– 4269. Munafo, M.R., Clarke, T.G., Moore, L.R, Payne, E., Walton, R., and Flint, J. (2003) Genetic polymorphisms and personality in healthy adults: a systematic review and meta-analysis. Mol. Psychiatry 8:471–484. Murrough, J.W., Boss-Williams, K.A., Emery, M.S., Bonsall, R.W., and Weiss, J.M. (2000) Depletion of brain norepinephrine does not reduce spontaneous ambulatory activity of rats in the home cage. Brain Res. 883:125–130. Myers, K.M., and Davis, M. (2002) Systems-level reconsolidation: re-engagement of the hippocampus with memory reactivation. Neuron 36:340–343. Myers, K.M., and Davis, M. (2007) Mechanisms of fear extinction. Mol. Psychiatry 12:120–150. Nemeroff, C.B. (2003) The role of GABA in the pathophysiology and treatment of anxiety disorders. Psychopharmacol. Bull. 37: 133–146. Nesse, R.M., Curtis, G.C., Thyer, B.A., McCann, D.S., Huber-Smith, M.J., and Knopf, R.F. (1985) Endocrine and cardiovascular responses during phobic anxiety. Psychosom. Med. 47:320–327. Netto, C.F., and Guimaraes, F.S. (2004) Anxiogenic effect of cholecystokinin in the dorsal periaqueductal gray. Neuropsychopharmacology 29:101–107. Neumeister, A., Bain, E., Nugent, A.C., Carson, R.E., Bonne, O., Luckenbaugh, D.A., Eckelman, W., Herscovitch, P., Charney, D. S., and Drevets, W.C. (2004) Reduced serotonin type 1A receptor binding in panic disorder. J. Neurosci. 24:589–591. Neumeister, A., Charney, D.S., Belfer, I., Geraci, M., Holmes, C., Sharabi, Y., Alim, T., Bonne, O., Luckenbaugh, D.A., Manji, H., Goldman, D., and Goldstein, D.S. (2005) Sympathoneural and adrenomedullary functional effects of alpha2C-adrenoreceptor gene polymorphism in healthy humans. Pharmacogenet. Genomics 15:143–149. Neumeister, A., Drevets, W.C., Belfer, I., Luckenbaugh, D.A., Henry, S., Bonne, O., Herscovitch, P., Goldman, D., and Charney, D.S. (2006) Effects of a alpha 2C-adrenoreceptor gene polymorphism on neural responses to facial expressions in depression. Neuropsychopharmacology 31:1750–1756. Neylan, T.C., Lenoci, M., Samuelson, K.W., Metzler, T.J., Henn-Haase, C., Hierholzer, R.W., Lindley, S.E., Otte, C., Schoenfeld, F.B., Yesavage, J.A., and Marmar, C.R. (2006) No improvement of posttraumatic stress disorder symptoms with guanfacine treatment. Am. J. Psychiatry 163:2186–2188. Ninan, P.T., Insel, T.M., Cohen, R.M., Cook, J.M., Skolnick, P., and Paul, S.M. (1982) Benzodiazepine receptor-mediated experimental “anxiety” in primates. Science 218:1332–1334. Nisenbaum, L.K., and Abercrombie, E.D. (1993) Presynaptic alterations associated with enhancement of evoked release and synthesis of NE in hippocampus of chemically cold stressed rats. Brain Res. 608:280–287. Nisenbaum, L.K., Zigmund, M.J., Sved, A.F., and Abercrombie, E. D. (1991) Prior exposure to chronic stress results in enhanced synthesis and release of hippocampal norepinephrine in response to a novel stressor. J. Neurosci. 11:1473–1484. Nishith, P., Griffin, M.G., and Poth, T.L. (2002) Stress-induced analgesia: prediction of posttraumatic stress symptoms in battered versus nonbattered women. Biol. Psychiatry 51:867–874. Norman, T.R., Judd, F.K., Gregory, M., James, R.H., Kimber, N.M., McIntyre, I.M., and Burrows, G.D. (1986) Platelet serotonin uptake in panic disorder. J. Affect. Disord. 11:69–72. Nutt, D.J. (1989) Altered alpha2-adrenoceptor sensitivity in panic disorder. Arch. Gen. Psychiatry 46:165–169. Nutt, D.J., Glue, P., Lawson, C., and Wilson, S. (1990) Flumazenil provocation of panic attacks: evidence for altered benzodiazepine

686

ANXIETY DISORDERS

receptor sensitivity in panic disorder. Arch. Gen. Psychiatry 47: 917–925. Orr, S.P., Milad, M.R., Metzger, L.J., Lasko, N.B., Gilbertson, M. W., and Pitman, R.K. (2006) Effects of beta blockade, PTSD diagnosis, and explicit threat on the extinction and retention of an aversively conditioned response. Biol. Psychol. 73:262–771. Ou, L.C., and Gean, P.W. (2007) Transcriptional regulation of brainderived neurotrophic factor in the amygdala during consolidation of fear memory. Mol. Pharmacol. 72:350–358. Pande, A.C., Feltner, D.E., Jefferson, J.W., Davidson, J.R., Pollack, M., Stein, M.B., Lydiard, R.B., Futterer, R., Robinson, P., Slomkowski, M., DuBoff, E., Phelps, M., Janney, C.A., and Werth, J.L. (2004) Efficacy of the novel anxiolytic pregabalin in social anxiety disorder: a placebo-controlled, multicenter study. J. Clin. Psychopharmacol. 24:141–149. Pande, A.C., Greiner, M., Adams, J.B., Lydiard, R.B., and Pierce, M.W. (1999) Placebo-controlled trial of the CCK-B antagonist, CI-988, in panic disorder. Biol. Psychiatry 46:860–862. Paoletti, A.M., Romagnino, S., Contu, R., Orrù, M.M., Marotto, M.F., Zedda, P., Lello, S., Biggio, G., Concas, A., and Melis, G.B. (2006) Observational study on the stability of the psychological status during normal pregnancy and increased blood levels of neuroactive steroids with GABA-A receptor agonist activity. Psychoneuroendocrinology 31:485–492. Papp, L.A., Klein, D.F., and Gorman, J.M. (1993) Carbon dioxide hypersensitivity, hyperventilation, and panic disorder. Am. J. Psychiatry 150:1149–1155. Pare, D., Quirk, G.J., and Ledoux, J.E. (2004) New vistas on amygdala networks in conditioned fear. J. Neurophysiol. 92:1–9. Park, H.J., Chae, Y., Jang, J., Shim, I., Lee, H., and Lim, S. (2005) The effect of acupuncture on anxiety and neuropeptide Y expression in the basolateral amygdala of maternally separated rats. Neurosci. Lett. 377:179–184. Parks, C., Robinson, P., Sibille, E., Shenk, T., and Toth, M. (1998) Increased anxiety of mice lacking the serotonin 1A receptor. Proc. Natl. Acad. Sci. USA 95:10734–10739. Pattij, T., Groenink, L., Oosting, R.S., van der Gugten, J., Maes, R.A.A., and Olivier, B. (2002) GABAA-benzodiazepine receptor complex sensitivity in 5-HT1A receptor knockout mice on a 129/ Sv background. Eur. J. Pharmacol. 447:67–74. Pavlov, I.P. (1927) Conditioned Reflexes. London: Oxford University Press. Payeur, R., Lydiard, R.B., Ballenger, J.C., Laraia, M.T., Fossey, M.D., and Zealberg, J. (1992) CSF diazepam-binding inhibitor concentrations in panic disorder. Biol. Psychol. 32:712–716. Pecknold, J.C., Suranyi-Cadotte, B., Chang, H., and Nait, N.P.V. (1988) Serotonin uptake in panic disorder and agoraphobia. Neuropsychopharmacology 1:173–176. Perez, S.E., Wynic, D., Steiner, R.A., and Mufson, E.J. (2001) Distribution of galaninergic immunoreactivity in the brain of the mouse. J. Comp. Neurol. 434:158–185. Perry, B.D., Giller, E.L., and Southwick, S.M. (1987) Altered platelet alpha2 adrenergic binding sites in posttraumatic stress disorder. Am. J. Psychiatry 144:1511–1512. Petrakis, I., Ralevski, E., Nich, C., Levinson, C., Carroll K, Poling, J., Rounsaville, B., and VA VISN I MIRECC Study Group. (2007) Naltrexone and disulfiram in patients with alcohol dependence and current depression. J. Clin. Psychopharmacol. 27:160–165. Pichot, W., Annsseau, M., Moreno, A.G., Hansenne, M., and Von Frenckell, R. (1992) Dopaminergic function in panic disorder: comparison with major and minor depression. Biol. Psychiatry 32:1004–1011. Pieribone, V.A., Brodin, L., Friberg, K., Dahlstrand, J., Soderberg, C., Larhammar, D., and Hokfelt, T. (1992) Differential expression of mRNAs for neuropeptide Y-related peptides in rat nervous tissues: possible evolutionary conservation. J. Neurosci. 12: 3361–3371.

Pine, D.S., Coplan, J.D., Lazlo, A.P., Klein, R.G., Martinez, J.M., Kovalenko, P., Tancer, N., Moreau, D., Dummit, E.S., Shaffer, D., Klein, D.F., and Gorman, J.M. (1998) Ventilatory physiology of children and adolescents with anxiety disorders. Arch. Gen. Psychiatry 55:123–129. Pinna, G., Costa, E., and Guidotti, A. (2006) Fluoxetine and norfluoxetine stereospecifically and selectively increase brain neurosteroid content at doses that are inactive on 5-HT reuptake. Psychopharmacology 186:362–372. Pitman, R.K., Sanders, K.M., Zusman, R.M., Healy, A.R., Cheema, F., Lasko, N.B., Cahill, L., and Orr, S.P. (2002) Pilot study of secondary prevention of posttraumatic stress disorder with propranolol. Biol. Psychiatry 51:189–192. Pitman, R.K., van der Kolk, B.A., Orr, S.P., and Greenberg, M.S. (1990) Naloxone reversible analgesic response to combat-related stimuli in posttraumatic stress disorder. Arch. Gen. Psychiatry 47:541–544. Pitts, L.N., and McClure, J.N. (1967) Lactate metabolism in anxiety neuroses. N. Engl. J. Med. 277:1329–1336. Pollack, M.H., Roy-Byrne, P.P., Van Ameringen, M., Snyder, H., Brown, C., Ondrasik, J., and Rickels, K. (2005) The selective GABA reuptake inhibitor tiagabine for the treatment of generalized anxiety disorder: results of a placebo-controlled study. J. Clin. Psychiatry 66:1401–1408. Power, A.E., Berlau, D.J., McGaugh, J.L., and Steward, O. (2006) Anisomycin infused into the hippocampus fails to block “reconsolidation” but impairs extinction: the role of re-exposure duration. Learn. Mem. 13:27–34. Primeaux, S.D., Wilson, S.P., Cusick, M.C., York, D.A., and Wilson, M.A. (2005) Effects of altered amygdalar neuropeptide Y expression on anxiety-related behaviors. Neuropsychopharmacology 30:1589–1597. Prins, A., Kaloupek, D.G., and Keane, T.M. (1995) Psychophysiological evidence for autonomic arousal and startle in traumatized adult populations. In: Friedman, M.J., Charney, D.S., and Deutch, A.Y., eds. Neurobiological and Clinical Consequences of Stress: From Normal Adaptation to PTSD. New York: Raven Press, pp. 291–314. Przybyslawski, J., Roullet, P., and Sara, S.J. (1999) Attenuation of emotional and nonemotional memories after their reactivation: role of b-adrenergic receptors. J. Neurosci. 19:6623–6628. Przybyslawski, J., and Sara, S.J. (1997) Reconsolidation of memory after its reactivation. Behav. Brain Res. 84:241–246. Quirk, G.J. (2002) Memory for extinction of conditioned fear is long-lasting and persists following spontaneous recovery. Learn. Mem. 9:402–407. Quirk, G.J., Russo, G.K., Barron, J.L., and Lebron, K. (2000) The role of ventral medial prefrontal cortex in the recovery of extinguished fear. J. Neurosci. 20:6225–6231. Radley, J.J., Sisti, H.M., Hao, J., Rocher, A.B., McCall, T., Hof, P.R., McEwen, B.S., and Morrison, J.H. (2004) Chronic behavioral stress induces apical dendritic reorganization in pyramidal neurons of the medial prefrontal cortex. Neuroscience 125:1–6. Rajarao, S.J., Platt, B., Sukoff, S.J., Lin, Q., Bender, C.N., Nieuwenhuijsen, B.W., Ring, R.H., Schechter, L.E., Rosenzweig-Lipson, S., and Beyer, C.E. (2007) Anxiolytic-like activity of the nonselective galanin receptor agonist, galnon. Neuropeptides 41:307– 320. Rapaport, M.H., Risch, S.C., Golshan, S., and Gillin, J.C. (1989) Neuroendocrine effects of ovine corticotropin-releasing hormone in panic disorder patients. Biol. Psychiatry 26:344–348. Raskind, M.A., Peskind, E.R., Hoff, D.J., Hart, K.L., Holmes, H.A., Warren, D., Shofer, J., O’Connell, J., Taylor, F., Gross, C., Rohde, K., and McFall, M.E. (2007) A parallel group placebo controlled study of prazosin for trauma nightmares and sleep disturbance in combat veterans with post-traumatic stress disorder. Biol. Psychiatry 61:928–934.

41: NEUROBIOLOGY Raskind, M.A., Peskind, E.R., Kanter, E.D., Petrie, E.C., Radant, A., Thompson, C.E., Dobie, D.J., Hoff, D., Rein, R.J., Straits-Troster, K., Thomas, R.G., and McFall, M.M. (2003) Reduction of nightmares and other PTSD symptoms in combat veterans by prazosin: a placebo-controlled study. Am. J. Psychiatry 160:371–373. Rasmusson, A.M., Southwick, S.M., Hauger, R.L., and Charney, D.S. (1998) Plasma neuropeptide Y (NPY) increases in humans in response to the alpha 2 antagonist yohimbine. Neuropsychopharmacology 19:95–98. Rasmusson, A.M., Hauger, R.I., Morgan, C.A., Bremner, J.D., Charney, D.S., and Southwick, S.M. (2000) Low baseline and yohimbinestimulated plasma neuropeptide Y (NPY) levels in combatrelated PTSD. Biol. Psychiatry 47:526–539. Rasmusson, A.M., Lipschitz, D.S., Wang, S., Hu, S., Vojvoda, D., Bremner, J.D., Southwick, S.M., and Charney, D.S. (2001) Increased pituitary and adrenal reactivity in premenopausal women with posttraumatic stress disorder. Biol. Psychiatry 50:965– 977. Rasmusson, A.M., Pinna, G., Paliwal, P., Weisman, D., Gottschalk, C., Charney, D., Krystal, J., and Guidotti, A. (2006) Decreased cerebrospinal fluid allopregnanolone levels in women with posttraumatic stress disorder. Biol. Psychiatry 60:704–713. Rasmussen, K., Marilak, D.A., and Jacobs, B.L. (1986) Single unit activity of the locus coeruleus in the freely moving cat. I: during naturalistic behaviors and in response to simple and complex stimuli. Brain Res. 371:324–334. Reddy, D.S., O’Malley, B.W., and Rogawski, M.A. (2005) Anxiolytic activity of progesterone in progesterone receptor knockout mice. Neuropharmacology 48:14–24. Redmond, D.E., Jr. (1987) Studies of the nucleus locus coeruleus in monkeys and hypotheses for neuropsychopharmacology. In: Meltzer, H.Y., ed. Psychopharmacology: The Third Generation of Progress. New York: Raven Press, pp. 967–975. Ressler, K.J., Rothbaum, B.O., Tannenbaum, L., Anderson, P., Graap, K., Zimand, E., Hodges, L., and Davis, M. (2004) Cognitive enhancers as adjuncts to psychotherapy: use of D-cycloserine in phobic individuals to facilitate extinction of fear. Arch. Gen. Psychiatry 61:1136–1144. Rickels, K., Pollack, M.H., Feltner, D.E., Lydiard, R.B., Zimbroff, D.L., Bielski, R.J., Tobias, K., Brock, J.D., Zornberg, G.L., and Pande, A.C. (2005) Pregabalin for treatment of generalized anxiety disorder: a 4-week, multicenter, double-blind, placebocontrolled trial of pregabalin and alprazolam. Arch. Gen. Psychiatry 62:1022–1030. Risbrough, V.B., and Stein, M.B. (2006) Role of corticotropin releasing factor in anxiety disorders: a translational research perspective. Horm. Behavior 50:550–561. Risold, P.Y., and Swanson, L.W. (1997) Chemoarchitecture of the rat lateral septal nucleus. Brain Res. Rev. 24:91–113. Robertson, H.A., Martin, I.L., and Candy, J.M. (1978) Differences in benzodiazepine receptor binding in Maudsley-reactive and nonreactive rats. Eur. J. Pharmacol. 50:455–457. Rodrigues, S.M., Schafe, G.E., and LeDoux, J.E. (2001) Intra-amygdala blockade of the NR2B subunit of the NMDA receptor disrupts the acquisition but not the expression of fear conditioning. J. Neurosci. 21:6889–6896. Roozendaal, B. (2000) Glucocorticoids and the regulation of memory consolidation. Psychoneuroendocrinology 25:213–238. Roozendaal, B., Brunson, K.L., Holloway, B.L., McGaugh, J.L., and Baram, T.Z. (2002) Involvement of stress-released corticotrophinreleasing hormone in the basolateral amygdala in regulating memory consolidation. Proc. Natl. Acad. Sci. USA 99:13908– 13913. Roozendaal, B., Hui, G.K., Hui, I.R., Berlau, D.J., McGaugh, J.L., and Weinberger, N.M. (2006) Basolateral amygdala noradrenergic activity mediates corticosterone-induced enhancement of auditory fear conditioning. Neurobiol. Learn. Mem. 86:249–255.

687

Roozendaal, B., Okuda, S., Van der Zee, E.A., and McGaugh, J.L. (2006) Glucocorticoid enhancement of memory requires arousalinduced noradrenergic activation in the basolateral amygdala. Proc. Natl. Acad. Sci. USA 103:6741–6746. Rosen, J.B. (2004) The neurobiology of conditioned and unconditioned fear: a neurobehavioral system analysis of the amygdala. Behav. Cogn. Neurosci. Rev. 3:23–41. Rosenbaum, J.F. (2005) Attitudes toward benzodiazepines over the years. J. Clin. Psychiatry 66 (Suppl 2):4–8. Rossato, J.I., Bevilaqua, L.R., Myskiw, J.C., Medina, J.H., Izquierdo, I., and Cammarota, M. (2007) On the role of hippocampal protein synthesis in the consolidation and reconsolidation of object recognition memory. Learn. Mem. 14:36–46. Roy-Byrne, P.P., Lewis, N., Villacres, E., Diem, H., Greenblatt, D.J., Shader, R.I., and Veith, R. (1989) Preliminary evidence of benzodiazepine subsensitivity in panic disorder. Biol. Psychiatry 26: 744–748. Roy-Byrne, P.P., Uhde, T.W., Post, R.M., Gallucci, W., Chrousos, G.P., and Gold, P.W. (1986) The corticotropin-releasing hormone stimulation test in patients with panic disorder. Am. J. Psychiatry 143:896–899. Roy-Byrne, P.P., Wingerson, D.K., Radant, A., Greenblatt, D.J., and Cowley, D.S. (1996) Reduced benzodiazepine sensitivity in patients with panic disorder: comparison with patients with obsessive-compulsive disorder and normal subjects. Am. J. Psychol. 153:1444–1449. Royer, S., Martina, M., and Paré, D. (2000) Polarized synaptic interactions between intercalated neurons of the amygdala. J. Neurophysiol. 83:3509–3518. Rudy, J.W., Biedenkapp, J.C., Moineau, J., and Bolding, K. (2006) Anisomycin and the reconsolidation hypothesis. Learn. Mem. 13:1–3. Rupprecht, R. (2003) Neuroactive steroids: mechanism of action and neuropharmacological properties. Psychoneuroendocrinology 28: 139–168. Rupprecht, R., Eser, D., Zwanzger, P., and Moller, H.J. (2006) GABAA receptors as targets for novel anxiolytic drugs. World J. Biol. Psychiatry 7:231–237. Sajdyk, T.J., Vandergriff, M.G., and Gehlert, D.R. (1999) Amygdala neuropeptide Y Y1 receptors mediate the anxiolytic-like actions of neuropeptide Y in the social interaction test. Eur. J. Pharmacol. 368:143–147. Sallee, F.R., Sethuraman, G., Sine, L., and Liu, H. (2000) Yohimbine challenge in children with anxiety disorders. Am. J. Psychiatry 157:1236–1242. Sallinen, J., Haapalinna, A., Viitamaa, T., Kobilka, B.K., and Scheinin, M. (1998) Adrenergic alpha2C-receptors modulate the acoustic startle reflex, prepulse inhibition, and aggression in mice. J. Neurosci. 18:3035–3042. Salomé, N., Stemmelin, J., Cohen, C., and Griebel, G. (2006) Differential roles of amygdaloid nuclei in the anxiolytic- and antidepressant-like effects of the V1b receptor antagonist, SSR149415, in rats. Psychopharmacology (Berl) 187:237–244. Samson, R.D., and Pare, D. (2005) Activity-dependent synaptic plasticity in the central nucleus of the amygdala. J. Neurosci. 25:1847– 1855. Sanchez, M.M., Young, L.J., Plotsky, P.M., and Insel, T.R. (1999) Autoradiographic and in situ hybridization localization of corticotrophin-releasing factor 1 and 2 receptors in nonhuman primate brain. J. Comp. Neurol. 408:365–377. Sand, P., Kavvadias, D., Feineis, D., Riederer, P., Schreier, P., Kleinschnitz, M., Czygan, F.C., Abou-Mandour, A., Bringmann, G., and Beckmann, H. (2000) Naturally occurring benzodiazepines: current status of research and clinical implications. Eur. Arch. Psychiatry Clin. Neurosci. 250:194–202. Santini, E., Ge, H., Ren, K., Peña de Ortiz, S., and Quirk, G.J. (2004) Consolidation of fear extinction requires protein synthesis in the medial prefrontal cortex. J. Neurosci. 24:5704–5410.

688

ANXIETY DISORDERS

Sara, S.J. (2000) Retrieval and reconsolidation: toward a neurobiology of remembering. Learn. Mem. 7:73–84. Sareen, J., Campbell, D.W., Leslie, W.D., Malisza, K.L., Stein, M.B., Paulus, M.P., Kravetsky, L.B, Kjernisted, K.D., Walker, J.R., and Reiss, J.P. (2007) Striatal function in generalized social phobia: a functional magnetic resonance imaging study. Biol. Psychiatry 61: 396–404. Savic´, M.M., Obradovic´, D.I., Ugresic´, N.D., Cook, J.M., Sarma, P.V., and Bokonjic´, D.R. (2005) Bidirectional effects of benzodiazepine binding site ligands on active avoidance acquisition and retention: differential antagonism by flumazenil and beta-CCt. Psychopharmacology (Berl) 180:455–465. Savic´, M.M., Obradovic´, D.I., Ugresic´, N.D., Cook, J.M., Yin, W., and Bokonjic´, D.R. (2005) Bidirectional effects of benzodiazepine binding site ligands in the passive avoidance task: differential antagonism by flumazenil and beta-CCt. Behav. Brain Res. 158:293–300. Saxe, G., Geary, M., Bedard, K., Bosquet, M., Miller, A., Koenen, K., Stoddard, F., and Moulton, S. (2006) Separation anxiety as a mediator between acute morphine administration and PTSD symptoms in injured children. Ann. N.Y. Acad. Sci. 1071:41–45. Saxe, G., Stoddard, F., Courtney, D., Cunningham, K., Chawla, N., Sheridan, R., King, D., and King, L. (2001) Relationship between acute morphine and the course of PTSD in children with burns. J. Am. Acad. Child. Adolesc. Psychiatry 40:915–921. Schafe, G.E., Nader, K., Blair, H.T., and LeDoux, J.E. (2001) Memory consolidation of Pavlovian fear conditioning: a cellular and molecular perspective. Trends Neurosci. 24:540–546. Schneider, L.S., Munjack, D., Severson, J.A., and Palmer, R. (1987) Platelet H3 imipramine binding in generalized anxiety disorder, panic disorder, and agoraphobia with panic attacks. Biol. Psychiatry 21:3–41. Schneier, F.R., Liebowitz, M.R., Abi-Dargham, A., Zea-Ponce, Y., Lin, S.H., and Laruelle, M. (2000) Low dopamine D2 receptor binding in social phobia. Amer. J. Psychiatry 157:457–459. Schroeder, B.W., and Shinnick-Gallagher, P. (2004) Fear memories induce a switch in stimulus response and signaling mechanisms for long-term potentiation in the lateral amygdala. Eur. J. Neurosci. 20:549–556. Schruers, K., Klaassen, T., Pols, H., Overbeek, T., Deutz, N.E., and Griez, E. (2000) Effects of tryptophan depletion on carbon dioxide provoked panic in panic disorder patients. Psychiatry Res. 93:179–187. Schruers, K., vanDiest, R., Nicolson, N., and Griez, E. (2002) L-5Hydroxytryptophan induced increase in salivary cortisol in panic disorder patients and healthy volunteers. Psychopharmacology 161:365–369. Semeniuk, T., Jhangri, G.S., and Le Mellédo, J.M. (2001) Neuroactive steroid levels in patients with generalized anxiety disorder. J. Neuropsychiatry Clin. Neurosci. 13:396–398. Sen, S., Burmeister, M., and Ghosh, D. (2004) Meta-analysis of the association between a serotonin transporter promoter polymorphism (5-HTTLPR) and anxiety-related personality traits. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 127:85–89. Serradeil-Le Gal, C., Wagnon, J. 3rd, Tonnerre, B., Roux, R., Garcia, G., Griebel, G., and Aulombard, A. (2005) An overview of SSR149415, a selective nonpeptide vasopressin V(1b) receptor antagonist for the treatment of stress-related disorders. CNS Drug Rev. 11:53–68. Sevcik, J., Finta, E.P., and Illes, P. (1993) Galanin receptors inhibit the spontaneous firing of locus coeruleus neurons and interact with mu-opioid receptors. Eur. J. Pharmacol. 230:223–230. Shepard, J.D., Barron, K.W., and Myers, D.A. (2000) Corticosterone delivery to the amygdala increases corticotrophin-releasing factor mRNA in the central amygdaloid nucleus and anxiety-like behavior. Brain Res. 861:288–295. Sheriff, S., Dautzenberg, F.M., Mulchahey, J.J., Pisarska, M., Hauger, R.L., Chance, W.T., Balasubramaniam, A., and Kasckow, J.W.

(2001) Interaction of neuropeptide Y and corticotrophin-releasing factor signaling pathways in AR-5 amygdalar cells. Peptides 22 (12):2083–2089. Shimazaki, T., Iijima, M., and Chaki, S. (2006) The pituitary mediates the anxiolytic-like effects of the vasopressin V1B receptor antagonist, SSR149415, in a social interaction test in rats. Eur. J. Pharmacol. 543:63–67. Shumyatsky, G., Tsvetkov, E., Malleret, G., Vronskaya, S., Horton, M., Hampton, L., Battey, J.F., Dulac, C., Kandel, E.R., and Bolshakov, V.Y. (2002) Identification of a signaling network in lateral nucleus of amygdala important for inhibiting memory specifically related to learned fear. Cell 111:905–918. Sibille, E., Pavlides, C., Benke, D., and Thth, M. (2000) Genetic inactivation of the serotonin 1A receptor in mice results in downregulation of major GABA-A receptor a subunits, reduction of GABA-A receptor binding, and benzodiazepine-resistant anxiety. J. Neurosci. 20:2758–2765. Simson, P.E., and Weiss, J.M. (1988) Altered activity of the locus coeruleus in an animal model of depression. Neuropsychopharmacology 1:287–295. Słopiec´, R., Meczekalski, B., and Warenik-Szymankiewicz, A. (2004) Relationship between climacteric symptoms and serum galanin levels in post-menopausal women. J. Endocrinol. Invest. 27: RC21–23. Smagin, G.N., Harris, R.B., and Ryan, D.H. (1996) Corticotropinreleasing factor receptor antagonist infused into the locus coeruleus attenuates immobilization stress-induced defensive withdrawal in rats. Neurosci. Lett. 220:167–170. Smiałowska, M., Wieroc´ska, J.M., Domin, H., and Zieba, B. (2007) The effect of intrahippocampal injection of group II and III metobotropic glutamate receptor agonists on anxiety; the role of neuropeptide Y. Neuropsychopharmacology 32:1242–1250. Smoller, J.W., Rosenbaum, J.F., Biederman, J., Kennedy, J., Dai, D., Racette, S.R., Laird, N.M., Kagan, J., Snidman, N., HirshfeldBecker, D., Tsuang, M.T., Sklar, P.B., and Slaugenhaupt, S.A. (2003) Association of a genetic marker at the corticotropin-releasing hormon locus with behavioral inhibition. Biol. Psychiatry 54:1376– 1381. Smoller, J.W., Yamaki, L.H., Fagerness, J.A., Biederman, J., Racette, S., Laird, N.M., Sklar, P.B., Kagan, J., Snidman, N., Faraone, S. V., and Hirshfeld-Baker, D. (2005) The corticotropin-releasing hormone gene and behavioral inhibition in children at risk for panic disorder. Biol. Psychiatry 57:1485–1492. Soravia, L.M., Heinrichs, M., Aerni, A., Maroni, C., Schelling, G., Ehlert, U., Roozendaal, B., de Quervain, D.J. (2006) Glucocorticoids reduce phobic fear in humans. Proc. Natl. Acad. Sci. USA 103:5585–5590. Sotres-Bayon, F., Cain, C.K., and LeDoux, J.E. (2006) Brain mechanisms of fear extinction: historical perspectives on the contribution of prefrontal cortex. Biol. Psychiatry 60:329–336. Southwick, S.M., Krystal, J.H., Bremner, J.D., Morgan, C.A., Nicolaou, A., Nagy, L.M., Johnson, D.R., Heninger, G.R., and Charney, D.S. (1997) Noradrenergic and serotonergic function in posttraumatic stress disorder. Arch. Gen. Psychiatry 54:749– 758. Southwick, S.M., Krystal, J.H., Morgan, C.A., Johnson, D., Nagy, L.M., Nicolaou, A., Heninger, G.R., and Charney, D.S. (1993) Abnormal noradrenergic function in posttraumatic stress disorder. Arch. Gen. Psychiatry 50:266–274. Stahl, S.M. (2004) Mechanism of action of alpha2delta ligands: voltage sensitive calcium channel (VSCC) modulators. J. Clin. Psychiatry 65:1033–1034. Steckler, T., and Holsboer, F. (1999) Corticotropin-releasing hormone receptor subtypes and emotion. Biol. Psychiatry 46:1480– 1508. Stein, M.B., Hauger, R.L., Dhalla, K.S., Chartier, M.J., and Asmundson, G.J. (1996) Plasma neuropeptide Y in anxiety disorders: find-

41: NEUROBIOLOGY ings in panic disorder and social phobia. Psychiatry Res. 59:183– 188. Stein, M.B., Huzel, L.L., and Delaney, S.M. (1993) Lymphocyte b-adrenoceptors in social phobia. Biol. Psychiatry 34:45–50. Stein, M.B., Seedat, S., and Gelernter, J. (2006) Serotonin transporter gene promoter polymorphism predicts SSRI response in generalized social anxiety disorder. Psychopharmacology (Berl) 187:68–72. Stein, M.B., Tancer, M.E., and Uhde, T.W. (1992) Heart rate and plasma norepinephrine responsivity to orthostatic challenge in anxiety disorders. Comparison of patients with panic disorder and social phobia and normal control subjects. Arch. Gen. Psychiatry 49:311–317. Strange, B.A., Hurlemann, R., and Dolan, R.J. (2003) An emotioninduced retrograde amnesia in humans is amygdala- and betaadrenergic-dependent. Proc. Natl. Acad. Sci. USA 100:13626– 13631. Strawn, J.R., Ekhator, N.N., Horn, P.S., Baker, D.G., and Geracioti, T.D., Jr. (2004) Blood pressure and cerebrospinal fluid norepinephrine in combat-related posttraumatic stress disorder. Psychosom. Med. 66:757–759. Ströhle, A., Romeo, E., DiMichele, F., Pasini, A., Herman, B., Gajewsky, G., Holsboer, F., and Rupprecht, R. (2003) Induced panic attacks shift g-aminobutyric acid type A receptor modulatory neuroactive steroid composition in patients with panic disorder. Arch. Gen. Psychiatry 60:161–168. Strömberg, J., Haage, D., Taube, M., Bäckström, T., and Lundgren, P. (2006) Neurosteroid modulation of allopregnanolone and GABA effect on the GABA-A receptor. Neuroscience 143:73–81. Strome, E.M., Trevor, G.H.W., Higley, J.D., Liriaux, D.L., Suomi, S. J., and Doudet, D.J. (2002) Intracerebroventricular corticotrophin-releasing factor increased limbic glucose metabolism and has social context dependent behavioral effects in nonhuman primates. Proc. Natl. Acad. Sci. USA 99:15749–15754. Stuckey, J., Marra, S., Minor, T., and Insel, T.R. (1989) Changes in m opiate receptors following inescapable shock. Brain Res. 476: 167–169. Swanson, C.J., Blackburn, T.P., Zhang, X., Zheng, K., Xu, Z.Q., Hokfelt, T., Wolinsky, T.D., Konkel, M.J., Chen, H., Zhong, H., Walker, M.W., Craig, D.A., Gerald, C.P., and Branchek, T.A. (2005) Anxiolytic- and antidepressant-like profiles of the galanin3 receptor (Gal3) antagonists SNAP 37889 and SNAP 398299. Proc. Natl. Acad. Sci. USA 102:17489–7494. Tancer, M.E., Stein, M.B., and Uhde, T.W. (1990) Effects of thyrotropin-releasing hormone on blood pressure and heart rate in phobic and panic patients: a pilot study. Biol. Psychiatry 27:781–783. Targum, S.D., and Marshall, L.E. (1989) Fenfluramine provocation of anxiety in patients with panic disorder. Psychiatry Res. 28: 295–306. Taylor, F.B., Lowe, K., Thompson, C., McFall, M.M., Peskind, E.R., Kanter, E.D., Allison, N., Williams, J., Martin, P., and Raskind, M.A. (2006) Daytime prazosin reduces psychological distress to trauma specific cues in civilian trauma posttraumatic stress disorder. Biol. Psychiatry 59:577–581. Thoeringer, C.K., Binder, E.B., Salyakina, D., Erhardt, A., Ising, M, Unschuld, P.G., Kern, N., Lucae, S., Brueckl, T.M., Mueller, M. B., Fuchs, B., Puetz, B., Lieb, R., Uhr, M., Holsboer, F., MuellerMyhsok, B., and Keck, M.E. (2007) Association of a Met88Val diazepam binding inhibitor (DBI) gene polymorphism and anxiety disorders with panic attacks. J. Psychiatry Res. 41:579–584. Thompson, R.R., George, K., Walton, J.C., Orr, S.P., and Benson, J. (2006) Sex-specific influences of vasopressin on human social communication. Proc. Natl. Acad. Sci. USA 103:7889–7894. Thorsell, A., Carlsson, K., Ekman, R., and Heilig, M. (1999) Behavioral and endocrine adaptation, and up-regulation of NPY expression in rat amygdala following repeated restraint stress. Neuroreport 10:3003–3007.

689

Thorsell, A., Michalkiewicz, M., Dumont, Y., Quirion, R., Caberlotto, L., Rimondini, R., Mathe, A.A., and Helig, M. (2000) Behavioral insensitivity to restraint stress, absent fear suppression of behavior and impaired spatial learning in transgenic rats with hippocampal neuropeptide Y overexpression. Proc. Natl. Acad. Sci. USA 97:12852–12857. Tiihonen, J., Kuikka, J., Bergstrom, K., Lepola, U., Koponen, H., and Leinonen, E. (1997) Dopamine reuptake site densities in patients with social phobia. Am. J. Psychiatry 154:239–242. Tilbrook, A.J., and Clarke, I.J. (2006) Neuroendocrine mechanisms of innate states of attenuated responsiveness of the hypothalamopituitary adrenal axis to stress. Front. Neuroendocrinol. 27:285– 307. Tomilenko, R.A., and Dubrovina, N.I. (2007) Effects of activation and blockade of NMDA receptors on the extinction of a conditioned passive avoidance response in mice with different levels of anxiety. Neurosci. Behav. Physiol. 37:509–515. Torda, T., Kvetnansky, R., and Petrikova, M. (1984) Effect of repeated immobilization stress on rat central and peripheral adrenoceptors. In: Usdin, E., Kvetnansky, R., and Axelrod, J., eds. Stress: The Role of Catecholamines and Other Neurotransmitters. New York: Gordon & Breach, pp. 691–701. Tõru, I., Shlik, J., Maron, E., Vasar, V., and Nutt, D.J. (2006) Tryptophan depletion does not modify response to CCK-4 challenge in patients with panic disorder after treatment with citalopram. Psychopharmacology (Berl) 186:107–112. Toufexis, D., Davis, C., Hammond, A., and Davis, M. (2005) Sex differences in hormonal modulation of anxiety measured with light-enhanced startle: possible role for arginine vasopressin in the male. J. Neurosci. 25:9010–9016. Tronel, S., and Alberini, C.M. (2007) Persistent disruption of a traumatic memory by postretrieval inactivation of glucocorticoid receptors in the amygdala. Biol. Psychiatry 62:33–39. Uhde, T.W., Berrettini, W.H., Roy-Byrne, P.P., Boulenger, J.P., and Post, R.M. (1987) Platelet 3H-imipramine binding in patients with panic disorder. Biol. Psychiatry 22:52–58. Uhde, T.W., Joffe, R.T., Jimerson, D.C., and Post, R.M. (1988) Normal urinary free cortisol and plasma MHPG in panic disorder: clinical and theoretical implications. Biol. Psychiatry 23:575–585. Unschuld, P.G., Ising, M., Erhardt, A., Lucae, S., Kohli, M., Kloiber, S., Salyakina, D., Thoeringer, C.K., Kern, N., Lieb, R., Uhr, M., Binder, E.B., Müller-Myhsok, B., Holsboer, F., and Keck, M.E. (2008) Polymorphisms in the galanin gene are associated with symptom-severity in female patients suffering from panic disorder. J. Affect. Disord. 105:177–184. Vaiva, G., Boss, V., Ducrocq, F., Fontaine, M., Devos, P., Brunet, A., Laffargue, P., Goudemand, M., and Thomas, P. (2006) Relationship between posttrauma GABA plasma levels and PTSD at 1year follow-up. Am. J. Psychiatry 163:1446–1448. Vaiva, G., Thomas, P., Ducrocq, F., Fontaine, M., Boss, V., Devos, P., Rascle, C., Cottencin, O., Brunet, A., Laffargue, P., and Goudemand, M. (2004) Low posttrauma GABA plasma levels as a predictive factor in the development of acute posttraumatic stress disorder. Biol. Psychiatry 55:250–254. Valdez, G.R. (2006) Development of CRF1 receptor antagonists as antidepressants and anxiolytics. CNS Drugs 20:887–896. van Den Hout, M.A., and Griez, E. (1984) Panic symptoms after inhalation of carbon dioxide. Br. J. Psychiatry 144:503–507. van der Kolk, B.A., Greenberg, M.S., Orr, S.P., et al. (1981) Endogenous opioids, stress induced analgesia and posttraumatic stress disorder. Psychopharmacol. Bull. 25:417–421. van der Wee, N.J., Fiselier, J., van Megen, H.J., and Westenberg, H.G. (2004) Behavioural effects of rapid intravenous administration of meta-chlorophenylpiperazine in patients with panic disorder and controls. Eur. Neuropsychopharmacol. 14:413–417. van Megen, H.J., Westenberg, H.G., den Boer, J.A., Slaap, B., van Es-Radhakishun, F., and Pande, A.C. (1997) The cholecystoki-

690

ANXIETY DISORDERS

nin-B receptor antagonist CI-988 failed to affect CCK-4 induced symptoms in panic disorder patients. Psychopharmacology (Berl) 129:243–248. van Riel, E., van Gemert, N.G., Meijer, O.C., and Joels, M. (2004) Effect of early life stress on serotonin responses in the hippocampus of young adult rats. Synapse 53:11–19. Van Stegeren, A.H., Everaerd, W., Cahill, L., McGaugh, J.L., and Gooren, L.J. (1998) Memory for emotional events: differential effects of centrally versus peripherally acting beta-blocking agents. Psychopharmacology (Berl) 138:305–310. Van Stegeren, A.H., Goekoop, R., Everaerd, W., Scheltens, P., Barkhof, F., Kuijer, J.P., and Rombouts, S.A. (2005) Noradrenaline mediates amygdala activation in men and women during encoding of emotional material. NeuroImage 24:898–909. Vanover, K.E., Rosenzweig-Lipson, S., Hawkinson, J.E., Lan, N.C., Belluzzi, J.D., Stein, L., Barrett, J.E., Wood, P.L., and Carter, R. B. (2000) Characterization of the anxiolytic properties of a novel neuroactive steroid, Co 2-6749 (GMA-839; WAY-141839; 3alpha, 21-dihydroxy-3beta-trifluoromethyl-19-nor-5beta-pregnan20-one), a selective modulator of gamma-aminobutyric acid(A) receptors. J. Pharmacol. Exp. Ther. 295:337–345. Varnas, K., Halldin, C., and Hall, H. (2004) Autoradiographic distribution of serotonin transporters and receptor subtypes in human brain. Hum. Brain Mapp. 22:246–260. Ventura, R., Cabib, S., and Puglisi-Allegra, S. (2002) Genetic susceptibility of mesocortical dopamine to stress determines liability to inhibition of mesoaccumbens dopamine and to behavioral despair in a mouse model of depression. Neuroscience 115:99– 1007. Verkuyl, J.M., Hemby, S.E., and Joëls, M. (2004) Chronic stress attenuates GABAergic inhibition and alters gene expression of parvocellular neurons in rat hypothalamus. Eur. J. Neurosci. 20: 1665–1673. Vicentic, A., Francis, D., Moffett, M., Lakatos, A., Rogge, G., Hubert, G.W., Harley, J., and Kuhar, M.J. (2006) Maternal separation alters serotonergic transporter densities and serotonergic 1A receptors in rat brain. Neuroscience 140:355–365. Wagatsuma, A., Azami, S., Sakura, M., Hatakeyama, D., Aonuma, H., and Ito, E. (2006) De Novo synthesis of CREB in a presynaptic neuron is required for synaptic enhancement involved in memory consolidation. J. Neurosci. Res. 84:954–960. Wang, C., Marx, C.E., Morrow, A.L., Wilson, W.A., and Moore, S.D. (2007) Neurosteroid modulation of GABAergic neurotransmission in the central amygdala: a role for NMDA receptors. Neurosci. Lett. 415:118–123. Watson, J.B., and Raynor, R. (1920) Conditioned emotional reactions. J. Exp. Psychol. 3:1–14. Watson, S., Gallagher, P., Ferrier, I.N., and Young, A.H. (2006) Postdexamethasone arginine vasopressin levels in patients with severe mood disorders. J. Psychiatry Res. 40:353–359. Weizman, A., Weizman, R., Kook, K.A., Vocci, F., Deutsch, S.I., and Paul, S.M. (1990) Adrenalectomy prevents the stress-induced decrease in in vivo [3H]Ro 15-1788 binding to GABAA benzodiazepine receptors in the mouse. Brain Res. 519:347–350. Weizman, R., Weizman, A., Kook, K.A., Vocci, F., Deutsch, S.I., and Paul, S.M. (1989) Repeated swim stress alters brain benzodiazepine receptors measured in vivo. J. Pharmacol. Exp. Ther. 249: 701–707. Wieron´ska, J.M., Szewczyk, B., Pałucha, A., Bran´ski, P., Zieba, B., and Smiałowska, M. (2005) Anxiolytic action of group II and III metabotropic glutamate receptors agonists involves neuropeptide Y in the amygdala. Pharmacol. Rep. 57:734–743. Williams, L.M., Kemp. A.H., Felmingham, K., Barton, M., Olivieri, G., Peduto, A., Gordon, E., and Bryant, R.A. (2006) Trauma

modulates amygdala and medial prefrontal responses to consciously attended fear. Neuroimage 29:347–357. Wolf, M. (1991) Plasma methionine enkephalin in PTSD. Biol. Psychiatry 29:295–308. Woods, S.W., Charney, D.S., Silver, J.M., Krystal, J.H., and Heninger, G.R. (1991) Behavioral, biochemical and cardiovascular responses to the benzodiazepine receptor antagonist flumazenil in panic disorder. Psychiatry Res. 36:115–124. Xu, Z.Q., Tong, Y.G., and Hokfelt, T. (2001) Galanin enhances noradrenaline-induced outward current on locus coeruleus noradrenergic neurons. Neuroreport 12:1179–1182. Yang, Y.L., Chao, P.K., Ro, L.S., Wo, Y.Y., and Lu, K.T. (2007) Glutamate NMDA receptors within the amygdala participate in the modulatory effect of glucocorticoids on extinction of conditioned fear in rats. Neuropsychopharmacology 32:1042–1051. Yehuda, R. (2002) Posttraumatic stress disorder. N. Engl. J. Med. 346:108–114. Yehuda, R. (2006) Advances in understanding neuroendocrine alterations in PTSD and their therapeutic implications. Ann. N. Y. Acad. Sci. 1071:137–166. Yehuda, R., Boisoneau, D., Lowy, M.T., and Giller, E.L., Jr. (1995) Dose response changes in plasma cortisol and lymphocyte glucocorticoid receptors following dexamethasone administration in combat veterans with and without posttraumatic stress disorder. Arch. Gen. Psychiatry 52:583–593. Yehuda, R., Brand, S., and Yang, R.K. (2006) Plasma neuropeptide Y concentrations in combat exposed veterans: relationship to trauma exposure, recovery from PTSD, and coping. Biol. Psychiatry 59:660–663. Yehuda, R., Siever, L.J., and Teicher, M.H. (1998) Plasma norepinephrine and 3-methoxy-4-hydroxyphenylglycol concentrations and severity of depression in combat posttraumatic stress disorder and major depressive disorder. Biol. Psychiatry 44:56–63. Yehuda, R., Southwick, S., Giller, E.L., Ma, X., and Mason, J.W. (1992) Urinary catecholamine excretion and severity of PTSD symptoms in Vietnam combat veterans. J. Nerv. Ment. Dis. 180: 321-325. Yeragani, V.K., Berger, R., Pohl, R., Srinivasan, K., Balon, R., Ramesh, C., Weinberg, P., and Berchou, R. (1992) Effects of yohimbine on heart rate variability in panic disorder patients and normal controls. J. Cardiovasc. Pharmacol. 20:609–618. Young, B.R., Lawford, E.P., Noble, B., Kann, A., Wilkie, T., Ritchie, L., Shadforth, A., and Shadforth, S. (2002) Harmful drinking in military veterans with post-traumatic stress disorder: association with the D2 dopamine receptor A1 allele. Alcohol and Alcoholism 37:451–456. Zanoveli, J.M., Netto, C.F., Guimarães, F.S., and Zangrossi, H., Jr. (2004) Systemic and intra-dorsal periaqueductal gray injections of cholecystokinin sulfated octapeptide (CCK-8s) induce a paniclike response in rats submitted to the elevated T-maze. Peptides 25:1935–1941. Zedkova, L., Coupland, N.J., Man, G.C., Dinsa, G., and Sanghera, G. (2003) Panic-related responses to pentagastrin, flumazenil, and thyrotropin-releasing hormone in healthy volunteers. Depress. Anxiety 17:78–87. Zubieta, J.K., Heitzeg, M.M., Smith, Y.R., Bueller, J.A., Xu, K., Xu, Y., Koeppe, R.A., Stohler, C.S., and Goldamn, D. (2003) COMT val met genotype affects m-opioid neurotransmitter response to a pain stressor. Science 299:1240–1243. Zwanzger, P., Eser, D., Padberg, F., Baghai, T.C., Schule, C., Rupprecht, R., di Michele, F., Romeo, E., Pasini, A., and Strohle, A. (2004) Neuroactive steroids are not affected by panic induction with 50 microg cholecystokinin-tetrapeptide (CCK-4) in healthy volunteers. J. Psychiatry Res. 38:215–217.

42 The Neurobiology and Treatment of Obsessive–Compulsive Disorder SUSAN E. SWEDO

A N D

PAUL GRANT

Obsessive–compulsive disorder (OCD) is defined in Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) by the presence of repetitive, intrusive thoughts and/or compulsions that are felt to be unreasonable or irrational and that interfere significantly with function or cause marked distress (American Psychiatric Association [APA], 1994). There is currently debate over some aspects of the diagnostic criteria—including whether obsessions are inevitably present and what degree of insight is required concerning the irrationality of symptoms. The DSM-IV states that compulsions are designed to neutralize or prevent some dreaded event, yet over one third of adults and about 40% of children deny that their compulsions are driven by an obsessive thought (Karno et al., 1988; Swedo et al., 1989). The degree of insight needed for the diagnosis is also in dispute, as some adult patients believe their obsessions, at least some of the time (Insel and Akiskal, 1986; Kozak and Foa, 1994). Eisen and colleagues (1998) developed the Brown Assessment of Beliefs Scale (BABS) to assess insight among patients with OCD and found that 30% had limited insight into their obsessions. The current definition of OCD allows the diagnosis to be made “with poor insight” for an individual who “for most of the time in the current episode, does not recognize that the obsessions or compulsions are excessive or unreasonable” (APA, 1994, p. 419). Children are particularly likely to lack insight into the irrationality of their symptoms, as noted in the DSM-IV criteria, which allow the diagnosis to be made in pediatric patients despite a lack of awareness of the irrationality of the symptoms (APA, 1994). Obsessions commonly involve a preoccupation with contamination, doubting, symmetry, religious or sexual themes, or a premonition that a bad outcome will result if a specific ritual is not executed. Compulsions consist of ritualized behaviors such as washing, cleaning, checking, repeating, counting, arranging, and hoarding. Although compulsions usually involve a physical action, they may also take the form of a mental ritual, such as repeating specific thoughts or prayers. The com-

pulsions may also be tic-like in character and require repetition until the person experiences the “just right” feeling of having eliminated a feeling of disquiet. The “just right” characteristic is one of several symptom clusters that Leckman and colleagues (1997) use to divide OCD into four phenomenological subtypes. The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) (Goodman et al., 1989) is a useful tool in assessing the presence and severity of obsessions and compulsions, not only because it provides a means of systematic assessment, but also because many patients find it reassuring to see their “crazy” obsessive–compulsive symptoms listed and categorized. EPIDEMIOLOGY Obsessive–compulsive disorder was once considered rare, but advances in diagnosis and treatment have led to recognition that the disorder is a major worldwide health problem (Weissman et al., 1994). The Epidemiological Catchment Area (ECA) study of over 18,500 adults at five different sites in the United States (New Haven, Connecticut; Baltimore, Maryland; St. Louis, Missouri; Durham, North Carolina; and Los Angeles, California) was the first large-scale epidemiological study to include OCD as a separate category and to provide information about the incidence and prevalence of the disorder (Robins et al., 1981). Using the Diagnostic Interview Schedule (DIS), a structured interview designed for lay interviewers, lifetime prevalence rates ranging from 1.9%–3.3% were demonstrated at the various sites. Even when other disorders were excluded, the rates were 1.2%–2.4%, approximately 25–60 times greater than had been estimated on the basis of clinical populations (Karno et al., 1988). A recent study conducted in northern Germany found that the lifetime prevalence of OCD in adults aged 18–64 was 0.5% (Grabe et al., 2000). The discrepancy between earlier and more recent estimates is discussed in a report based on Australian National Survey of Mental Heath and Well-Being 691

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(Crino et al., 2005). In that epidemiological survey, the 12-month prevalence of adult OCD was 0.6%, a number attributed to employing DSM-IV criteria, rather than the DSM-III criteria of earlier surveys. The mean age of onset in the ECA study ranged from 20 to 25 years, with nearly one half of the patients reporting that their symptoms had begun during childhood or adolescence (Karno and Golding, 1990). Subsequent epidemiological studies of children and adolescents have confirmed that the disorder is common in the pediatric population as well, with reported prevalence rates ranging from 0.5% (Wittchen et al., 1998) to 4.0% (Douglass et al., 1995). Several authors have reported the prevalence of OCD among adolescents to be approximately 2%, consistent with adults’ reports of symptom onset during childhood or adolescence (reviewed in A.H. Zohar, 1999.) COMORBIDITY Comorbid psychopathology is common among patients with OCD. In a recently published study of a large health maintenance organization population in northern California, three fourths of the adults were found to have at least one comorbid psychiatric diagnosis (Fireman et al., 2001). The secondary disorders included major depression (56%), other anxiety disorders (26%; particularly panic disorder, 14%, and generalized anxiety disorder, 14%), and adjustment disorder (12%). Comorbidity was also common among the pediatric patients with OCD, with attention-deficit/hyperactivity disorder (ADHD) occurring most commonly (34%), closely followed by major depression (33%), Tourette syndrome (18%), oppositional defiant disorder (17%), and overanxious disorder (16%) (Fireman et al., 2001). This pattern of comorbidity was similar to that previously observed in the National Institute of Mental Health (NIMH) pediatric OCD cohort, where only 26% of the pediatric patients had OCD as a single diagnosis (Swedo et al., 1989). Tic disorders (30%), major depression (26%), and specific developmental disabilities (24%) were the most common comorbidities found. Rates were also increased for simple phobias (17%), overanxious disorder (16%), adjustment disorder with depressed mood (13%), oppositional disorder (11%), attention deficit disorder (10%), conduct disorder (7%), separation anxiety disorder (7%), and enuresis/encopresis (4%) (Swedo et al., 1989). It is quite likely that an early onset of OCD is associated with particular phenotypic differences. For example, higher rates of tic-like compulsions and of tics may be seen in adult OCD when the onset was in childhood (Rosario-Campos et al., 2001). Early investigations suggested that obsessive– compulsive personality disorder (OCPD) might serve as

a temperamental predisposition for OCD (Black et al., 1993) or as an alternative manifestation of the disorder (Rasmussen and Tsuang, 1986). These conclusions were brought into question by subsequent studies reporting that the prevalence of compulsive personality disorder in adult patients with OCD was not higher than expected in the community (reviewed by Attiullah et al., 2000.) Baer and colleagues (1990) used the Structured Interview for the DSM-III Personality Disorders (SID-P) to assess personality traits among patients with OCD and found that dependent (12%) and histrionic (9%) personality disorders occurred more frequently than OCPD (6%) among patients with OCD. Further, when individual factors of OCPD were considered, patients with OCD were found to have difficulties with perfectionism (82%) and indecisiveness (70%) more frequently than did healthy controls, but not other OCPD characteristics, such as restricted ability to express warmth (32%), rigidity (32%), and excessive devotion to work (18%) (as cited in Attiullah et al., 2000). A more recent longitudinal study revealed that three of the eight OCPD criteria were significantly more frequent among patients with OCD (n = 89) than among patients without OCD (n = 540 with major depression and/or anxiety disorders) (Eisen et al., 2006). The possibility has been raised that OCPD may develop as a secondary or adaptive response to OCD. Evidence supporting this postulate comes from followup evaluations of adolescents diagnosed with OCD in a community survey, a significant proportion of whom no longer met criteria for OCD but did have features of OCPD: rigidity, excessive attention to details, and social isolation, among others (Berg et al., 1989). A study conducted by Ricciardi and colleagues at Harvard (1992) provides additional support for the concept that OCPD may occur as a consequence of OCD rather than as a predictor of disease, as features of OCPD remitted in 9 of 10 patients successfully treated for OCD. This suggests that there may be unique associations between OCD and OCPD symptoms, as compared to other anxiety disorders or to major depression. On the other hand, Albert and colleagues (2004) did not find a specific increase in OCPD among patients with OCD, as those with panic disorder had similarly elevated rates (23% and 17%, respectively), in comparison with healthy controls (3%). NEUROBIOLOGY Basal Ganglia Dysfunction Systematic research over the past two decades has demonstrated that OCD is associated with dysfunction of the corticostriato-thalamocortical circuitry, particularly in the orbitofrontal cortex and caudate nucleus (see Saxena and Rauch, 2000, for review). As shown

42: NEUROBIOLOGY AND TREATMENT OF OBSESSIVE–COMPULSIVE DISORDER

in Figure 42.1, dysfunction at several different points in the corticostriato-thalamocortical circuit might produce similar neuropsychiatric symptoms. Evidence for basal ganglia dysfunction is provided by neuroimaging studies (reviewed in Chapter 43) and by the association of OCD with neurological disorders known to involve basal ganglia structures, including Tourette syndrome (TS), Sydenham’s chorea (SC; discussed below), and Huntington’s chorea (Cummings and Cunningham, 1992). The first description of neurologically based OCD comes from Constantin von Economo’s treatise (1931) on postencephalitic Parkinson’s disease, wherein patients suffered basal ganglia destruction as a result of severe influenza infections. Von Economo noted the “compulsory nature” of the motor tics and ritual-like behaviors that his patients exhibited. Von Economo’s patients, like patients with OCD, described “having to” act, while not “wanting to”—that is, they experienced a neurologically based loss of volitional control. Motor and vocal tics, including TS, occur frequently in association with OCD. The relationship between tics and OCD is complex, as motor tics often have a behavioral component suggestive of compulsive rituals, whereas OCD compulsions may lack accompanying

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obsessive thoughts, making them look like tics if the rituals are simple, repetitive behaviors such as touching or tapping. The overlap between tics and OCD is most apparent in pediatric patient populations, where up to two thirds of children with OCD are observed to have comorbid tics (Leonard et al., 1992) and 20%– 80% of children with TS report obsessive–compulsive symptoms (Leckman et al., 1997). It is unknown just how the pattern and severity of obsessive–compulsive symptoms differ between patients with TS and those with primary OCD, but preliminary impressions suggest that the compulsions associated with TS may be less severe than those in nontic OCD and more likely to involve symmetry, rubbing, touching, staring, or blinking rituals than washing and cleaning (Leckman et al., 1997). Indirect evidence for basal ganglia involvement in OCD is provided by the efficacy of psychosurgical lesions that disconnect the basal ganglia from the frontal cortex, particularly capsulotomy (Mindus, 1991) and cingulectomy (Dougherty et al., 2002). In capsulotomy, bilateral basal lesions are made in the anterior limb of the internal capsule to interrupt frontal-cingulate projections; however, the surgical target lies within the striatum, near the caudate nuclei. To perform a cingulectomy, the anterior portion of the cingulate gyrus is lesioned, interrupting tracks between the cingulate gyrus and the frontal lobes and destroying all of the efferent projections of the anterior cingulate cortex. Both procedures result in significant reduction of obsessions and compulsions. The success of psychosurgery is, of course, not conclusive evidence of a basal ganglia defect in OCD, as the lesions could be anywhere upstream from the site of treatment (Fig. 41.1), but it does focus interest on frontal-striatal tracts (for review, see Greenberg et al., 2000). Neuroimmune Dysfunction

42.1 Models of basal ganglia dysfunction in obsessive–compulsive disorder. A. In this model, the primary area of dysfunction is in the striatum, reducing its inhibition of the globus pallidus externa (GPe) (indirect pathway), which causes the GPe to increase its inhibition of the subthalamic nucleus (STN), thus reducing the STN’s stimulation of the globus pallidus interna/substantia nigra (Gpi/SNr) (pars reticulata). This causes a reduction in GPi/SNr inhibition of the thalamus, which then can increase its stimulation of the frontal cortex. B. In this alternative construct, the GPi is the primary site of pathology. Without the GPi’s inhibition, the thalamus increases its stimulation of the frontal cortex, which could produce symptoms directly, or through increased stimulation of the striatum.

FIGURE

Parallels between SC, the neurological manifestation of rheumatic fever, and childhood-onset OCD suggest that the two disorders may have a shared etiopathogenesis (Garvey et al., 1998). The disorders have similar regional localization, with evidence of dysfunction of the orbitofrontal-striatal circuitry in OCD and SC. Further, over 70% of children with SC report that they experienced an abrupt onset of repetitive, unwanted thoughts and behaviors 2 to 4 weeks prior to the onset of their chorea (Swedo et al., 1993). The obsessions and compulsions peak in intensity concomitantly with the chorea and wane slowly over the ensuing months. A subgroup of patients with childhood-onset OCD was noted to have a similar symptom course. The OCD exacerbations occurred following group A beta-hemolytic streptococcal (GABHS) infections, accompanied by a cluster of comorbid symptoms, including emotional la-

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bility, separation anxiety, and attentional difficulties (Swedo et al., 1998). The children were young (6–7 years old at symptom onset), predominantly male, and often had comorbid tics. To indicate their shared clinical features (and presumed etiopathogenesis), the subgroup was identified by the acronym PANDAS—pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (Swedo et al., 1998). The major distinguishing feature of the PANDAS subgroup is the temporal association between neuropsychiatric symptom exacerbations and GABHS infections—that is, positive (or rising) antistreptococcal antibody titers or a positive throat culture during neuropsychiatric symptom relapses and evidence of GABHS negativity during periods of remission (Perlmutter et al., 1998). This one-to-one correlation is necessary to distinguish GABHS-triggered exacerbations of the PANDAS subgroup from the more typical waxing and waning course seen in TS and some cases of childhood-onset OCD. The temporal association between GABHS infections and neuropsychiatric symptom exacerbations suggested that prevention of the infections might result in decreased severity of the obsessive-compulsive symptoms. An 8-month-long placebo-controlled crossover trial of penicillin prophylaxis was undertaken (4 months of penicillin followed by 4 months of placebo or vice versa) (Garvey et al., 1999). The penicillin prophylaxis failed to achieve the primary objective of significantly reducing GABHS infections (14 of 35 infections occurred during the penicillin phase), so it was not surprising that there were no between-phase differences in OCD or tic severity. Poor compliance appeared to have contributed to penicillin’s lack of effectiveness because missed doses were frequent. This problem was addressed in a trial comparing the effectiveness of penicillin and azithromycin as prophylactic agents, in which data demonstrated a reduction in the number of GABHS infections and neuropsychiatric symptom exacerbations during the study period (Snider et al., 2005). The role of the immune system in the etiology of OCD and tic disorders is unclear, but clinical observations suggest that symptoms result from a combination of local, regional, and systemic abnormalities (Hamilton et al., 2001). The striking effectiveness of immunomodulatory therapies, such as therapeutic plasma exchange and intravenous immunoglobulin (IVIG), suggests that there is systemic involvement, at least in individuals who are severely affected (Perlmutter et al., 1999). Magnetic resonance imaging (MRI) scans reveal enlargements of the caudate, putamen, and globus pallidus, which points to regional inflammatory changes (Giedd et al., 1996; Giedd et al., 2000), whereas local autoimmune reactions are suggested by the presence of serum antibodies that cross-react with neurons of the caudate, putamen, and globus pallidus (Kiessling et al., 1994). Husby and colleagues (1976) were the first to

describe cross-reactive antibodies in SC. Although the antibodies were labeled antineuronal, they noted that the antibodies must have been raised against epitopes on the GABHS bacteria, and then cross-reacted with cells of the caudate nucleus and subthalamus. It was the cross-reactivity that distinguished the antibodies found in the patients with SC from antineuronal antibodies found in patients with lupus erythematosus and other neurological disorders (Husby et al., 1976). Several groups have subsequently reported the presence of antineuronal antibodies in patients with childhood-onset OCD and/or tic disorders (Kiessling et al., 1994; Singer et al., 1998; Morshed et al., 2001). A more specific autoimmune effect has been demonstrated recently. Antibodies found in patients with acute SC reacted with neuronal cells and induced calcium calmodulin–dependent protein kinase II, raising tyrosine hydroxylase, and leading to dopamine (DA) release, possibly accounting for the movement disorder in that syndrome (Kirvan et al., 2006). In the same laboratory, serum from children in the PANDAS subgroup reacted with N-acetylglucosamine from GABHS and with human lysoganglioside in a manner parallel to that seen in SC. The most compelling evidence for a role for immunological dysfunction in the PANDAS subgroup comes from results of a randomized, placebo-controlled trial of IVIG and plasma exchange (Perlmutter et al., 1999). Both immunomodulatory therapies produced significant improvements in neuropsychiatric symptom severity. Placebo IVIG administration had no demonstrable effect on obsessive–compulsive symptoms at 1-month follow-up, whereas IVIG and plasma exchange treatments produced mean symptom reductions of 45% and 58%, respectively. One-year follow-up revealed that 14 of 17 children (82%) continued to be “much” or “very much” improved from baseline (Perlmutter et al., 1999). The effectiveness of the immunomodulatory therapies suggests that circulating immune factors play a role in the pathophysiology of the symptoms, but no specific hypotheses can be formulated on the basis of the treatment response because of the broad spectrum of action of IVIG and plasma exchange. Neurotransmitter Abnormalities Serotonin The serotonergic hypothesis of OCD is based on the selective efficacy of drugs with specific serotonergic activity (Ananth et al., 1981; Insel et al., 1985; DeVeaughGeiss et al., 1989) and on challenge tests with serotonergic agonists. Challenges with sumatriptin (Bastani et al., 1990) and metachlorophenylpiperazine (mCPP) (J. Zohar et al., 1987; J. Zohar et al., 1988; Pigott et al., 1991) show that OCD symptoms are exacerbated by these serotonin agonists. In contrast, metergoline, a

42: NEUROBIOLOGY AND TREATMENT OF OBSESSIVE–COMPULSIVE DISORDER

serotonin antagonist, has been shown to protect against mCPP’s behavioral effects (Pigott et al., 1991). Medications that block serotonin reuptake, such as clomipramine and the selective serotonin reuptake inhibitors (SSRIs), fluoxetine, fluvoxamine, sertraline, paroxetine, and citalopram, have been shown to be the most effective pharmacological treatments for OCD (see “Pharmacotherapy”). Clomipramine is a tricyclic antidepressant that is a relatively selective and potent inhibitor of active serotonin uptake in the brain (it also blocks histamine H2 receptors, and cholinergic and adrenergic receptors and has antidopaminergic properties). Its metabolite, desmethylclomipramine, is also effective in blocking serotonin reuptake (and reuptake of noradrenaline) (Vythilingum et al., 2000). The response of OCD symptoms to clomipramine, and not to the equally effective antidepressant desipramine (Ananth et al., 1981; Insel et al., 1985; Leonard et al., 1989), indicates a remarkable specificity of effect of the serotonin uptake inhibitors for OCD. No unselected group of patients with depression, for example, would show such a differential response. Additional evidence for the serotonergic hypothesis is provided by several studies in children and adolescents with OCD. The first, conducted by Flament et al. (1985; Flament et al., 1987), demonstrated that response to clomipramine correlated with the pretreatment platelet serotonin concentration. A high pretreatment level of serotonin was a strong predictor of a clinical response, and, within this sample, platelet serotonin concentrations were lower in the patients who are more severely ill. However, there were no differences in serotonin concentration from age-/sex-matched controls. A study of cerebrospinal fluid (CSF) monoamines in 43 children and adolescents with OCD revealed that 5-hydroxyindoleacetic acid, the major metabolite of serotonin, correlated most strongly with the response to clomipramine therapy; that is, the most successful responders had the highest levels of 5-hydroxyindoleacetic acid in the CSF (Swedo et al., 1992). A more recent study, employing positron emission tomography (PET) and serotonergic ligands, found evidence for decreased serotonin synthesis in the ventral prefrontal cortex and caudate nucleus in treatment-naive patients with OCD 8 to 13 years of age (Rosenberg et al., 1998). The latter study provides support for the serotonergic hypothesis of OCD and for dysfunction within the basal ganglia–frontal cortex circuitry. The serotonergic hypothesis is undoubtedly too simple to account for the complexity of OCD (Delgado and Moreno, 1998; Greist and Jefferson, 1998). If the defect were limited to serotonergic dysfunction, clomipramine and the SSRIs would be effective in eliminating symptoms in all patients; unfortunately, this is not the case. Partial treatment response is common in OCD, and up to 40% of patients fail to improve signifi-

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cantly with SSRI administration (Hollander et al., 2000). Individual patients also have variable patterns of response to the different SSRIs, suggesting that the nonserotonergic properties of the medication may also play key roles, and that the antiobsessional effect may actually result from an alteration in the balance of serotonin and other monoamines, and/or changes in receptor functions (Murphy et al., 1989). Support for this hypothesis is provided by the results of meta-analyses demonstrating that clomipramine (a relatively “dirty” drug) is significantly more effective than the SSRIs, fluoxetine, fluvoxamine, and sertraline, in the treatment of OCD (Greist et al., 1995). A meta-analysis of studies of pharmacologic treatment of OCD in children has demonstrated a similar effect (Geller et al., 2003). Dopamine and other neurotransmitters Dopaminergic dysfunction in OCD is suggested not only by the obsessive–compulsive symptoms in patients with basal ganglia disorders (discussed above), but also by the increase in obsessive–compulsive symptoms following high-dose stimulant administration (Frye and Arnold, 1981) and by occasional amelioration of symptoms following the use of DA blocking agents (Goodman et al., 1990; McDougle, 1997; Stein et al., 1997). High-dose stimulant administration has been thought to produce simple stereotypies, rather than more complex compulsive or obsessive behavior; however, compulsive symptoms have been observed in children with attention deficit disorder and hyperactivity during treatment with high-dose amphetamines (1 mg/kg d-amphetamine or 2 mg/kg methylphenidate) (Borcherding et al., 1990). For example, a 7-year-old boy spent several hours each evening vacuuming the carpet in his home and another played with Lego blocks for 2 days, stopping only to eat and sleep. As in OCD, the children also became overly concerned with details and produced holes in their papers with repeated erasing, trying to get a single letter perfectly shaped. However, no psychological distress accompanied the obsessive–compulsive behaviors in the stimulant-induced cases, leading to speculation that repetitive thoughts and behaviors (obsessions and compulsions) may result from dopaminergic overactivity and that serotonin dysregulation is required for ego-dystonicity. Observations in TS appear to provide support for this hypothesis. In TS, motor and vocal tics are not reported to be ego-dystonic (although they may become physically uncomfortable) and appear to result from dopaminergic overactivity overcoming serotonergic inhibition. Some direct support is found in one study in which single photon emission computed tomography (SPECT) scans demonstrated increased DA transporter in left caudate and left putamen nuclei in adult drug-naïve patients with OCD (van der Wee et al., 2004). In contrast, OCD is primarily a serotonergic

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defect. Here, a primary lack of serotonin results in an inability to inhibit normal dopaminergic activity, and fixed action patterns (obsessions and compulsions) are inappropriately released. Ego-dystonicity could then be related to the primary serotonin defect or could be secondary to the loss of volitional control (Swedo and Rapoport, 1990). Glutamate, the primary excitatory neurotransmitter in the brain, plays a key role at several points in the frontostriatal-thalamocortical circuit. Glutamatergic excess (relative or absolute) could contribute to OCD symptomatology through a variety of mechanisms. Evidence for a glutamatergic excess in the pathophysiology of OCD is found in a recent report in which CSF had significantly higher glutamate levels in drug-naïve adult patients with clinically significant OCD compared to controls (Chakrabarty et al., 2005). Additional support is provided by an open label trial of riluzole, a relative glutamate antagonist, which demonstrated benefits for five of 13 patients with OCD (Coric et al., 2005). These therapeutic effects in OCD are postulated to result from a reduction in frontal cortical (excitatory) output to the striatum, which would reduce the striatal inhibition of the globus pallidus and substantia nigra, and allow greater inhibition of the thalamus and less cortical excitation. McGrath and colleagues (2000) postulated effectiveness of similar compounds in a mouse model of TS and OCD. Neuroendocrine Dysfunction Although most OCD investigations concentrate on hormonal aberrations as secondary rather than primary to the disorder, case reports and anecdotal experience suggest that hormonal dysfunction and OCD may be etiologically related (Swedo, 1989). Symptoms of OCD often begin during early puberty, and some female patients experience an increase in obsessive thoughts and rituals immediately before their menses. Other hints at an influence of gonadal steroid on obsessive–compulsive symptomatology include the increased frequency of OCD during the postpartum period (Rasmussen and Eisen, 1992) and reports of successful antiandrogen therapy for obsessive–compulsive symptoms (Casas et al., 1986). In the latter study, five of five patients with OCD experienced a remission in their symptoms following treatment with cyproterone acetate, a potent antiandrogen. At the NIMH, two boys (aged 8 and 15) and a 14-yearold girl were treated with spironolactone, a peripheral antiandrogen, with antitesterone effects and testolactone, a peripheral antiestrogen medication. All experienced a temporary reduction of obsessions and compulsions but relapsed within 3–4 months (Salzberg and Swedo, 1992). Leckman and colleagues (1994) suggested that oxytocin abnormalities may be involved in OCD. These

investigators cited oxytocin-mediated mating behaviors in animals as a possible model for some OCD symptoms (Leckman and Mayes, 1999) and found abnormal concentrations of CSF oxytocin among a small group of children with OCD and tic disorders. In a larger group of 43 children and adolescents studied at the NIMH (Swedo et al., 1992; Altemus et al., 1994), CSF oxytocin levels were not significantly correlated with OCD severity but were correlated with depressive symptoms. Interestingly, arginine vasopressin (AVP) concentrations were inversely related to OCD severity (Swedo et al., 1992) but decreased following treatment with clomipramine (Altemus et al., 1994). Altemus et al. (1992) found significantly increased CSF AVP concentrations at baseline among adult patients with OCD and noted that patients secreted significantly more AVP into plasma in response to hypertonic saline than did controls. The latter results are in keeping with Barton’s (1987) observations of OCD among patients with diabetes insipidus, a disorder with elevated central AVP concentrations. At present, there is not sufficient evidence to implicate hormonal dysfunction as a direct cause of OCD. However, some intriguing data build a circumstantial case for an association between OCD and growth hormone abnormalities, perhaps through the serotonergic system. In an epidemiological study of OCD among high school students (Flament et al., 1988), males with OCD were noted to be smaller and thinner than the community normal controls and males with other psychiatric illnesses (Hamburger et al., 1989). There were no reductions in the height or weight of the adolescent girls with OCD. The small size of the OCD males could be due to an effective lack of growth hormone or to a delay in the pubertal growth spurt, although, of course, no causality is demonstrated by the relationship. To address the issue of causality, future research might employ direct assays, hormonal challenges, or therapeutic interventions. TREATMENT OF OBSESSIVE–COMPULSIVE DISORDER The treatment of OCD requires an integrated approach, as it is unusual for patients to respond fully to either cognitive-behavior therapy (CBT) or medications. A combination of behavioral and pharmacological approaches provides the maximum benefit for most patients. Obsessive–compulsive disorder is a chronic condition, and longterm therapy is often required, although lower medication doses may suffice (Ravizza et al., 1998). Discontinuation studies have shown that 80% of patients relapsed by the 2-year follow-up (Dolberg et al., 1996), although the rate was somewhat lower among patients receiving concomitant CBT (Stanley and Turner, 1995). When discontinuation is attempted, tapering should be gradual,

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usually over several weeks. Long-term (that is, indefinite) drug maintenance is suggested after two to four relapses. Cognitive-Behavioral Therapy Cognitive-behavioral therapy for OCD encompasses three treatment types: (1) exposure and response prevention (ERP), (2) cognitive therapy, and (3) relaxation training. Of the three, only ERP has been shown to be consistently effective in reducing OCD symptom severity (Baer and Greist, 1997; Marks, 1997; Shafran, 1998). Cognitive therapy (for example, changing false beliefs regarding risk and responsibility, challenging the reality of obsessions and the necessity for compulsions; Emmelkamp and Beens, 1991) is generally viewed as ineffective if used as the sole treatment for OCD, but it may be helpful for patients with overvalued ideation (Neziroglu et al., 2000), and if it facilitates participation in ERP (Shafron and Somers, 1998). Relaxation therapy is used mainly to manage anxiety during exposure (March, 1995), but it has no direct benefits for the obsessive–compulsive symptoms. Exposure and response prevention for OCD involves (1) daily exposure to cues avoided because of their inducing discomfort and rituals and (2) maintaining exposure and not ritualizing for at least an hour or until the discomfort slowly subsides (March, 1995; Greist, 1996). A minimal trial of ERP consists of 10–20 hours of treatment with ERP (Baer and Greist, 1997), with in vivo exposure being preferred over imaginal exposure (Foa et al., 1985). The strategies employed must be tailored to the patient’s symptoms. For example, contamination fears, symmetry rituals, counting/repeating, hoarding, and aggressive urges are amenable to ERP, but the technique is not generally appropriate for pathological doubting or pure obsessions such as scrupulosity or violent images. Obsessional slowness is difficult to treat with either behavioral therapy or medications (Wolff and Rapoport, 1988). Exposure with response prevention can have lasting benefits and longterm symptom remissions are possible, particularly when booster sessions are used to address migration of symptoms and relapses brought on by stress (Greist, 1996). Therapist-directed ERP has been shown to be the most effective means of treating OCD (Abramowitz, 1998). However, the shortage of trained therapists and the expense of therapist-directed ERP have mandated the development of alternative strategies. Several selfhelp programs for behavior therapy have been developed, including computer- and telephone-administered programs (e.g., Baer and Greist, 1997; Clark et al., 1998). Manualized approaches have also proven successful for adults (Van Noppen et al., 1997) and pediatric patients (March et al., 1994; March and Mulle, 1998). Cognitive behavioral group therapy has also

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been demonstrated to be effective (Sousa et al., 2006). In general, ERP appears to confer similar benefits in the pediatric population as it does for adults (March et al., 2001). The child must be old enough to understand fully the goals and requirements of treatment and to tolerate the discomforts inherent to exposure (see March et al., 2001, for more details.) There is recent evidence that the combination of CBT and medication may have greater clinical efficacy in adults and children (March et al., 2004; O’Connor et al., 2006). Pharmacotherapy A serotonin reuptake inhibitor (SRI), most often an SSRI, is the drug treatment of choice for OCD. If there is an insufficient response to the SSRI at 10–12 weeks, another SSRI may be tried. Although only 50%–60% of patients respond to initial SSRI treatment, approximately 70%–80% will have at least a partial response to at least one of the SSRIs. To date, no baseline predictors of treatment response have been identified. Augmentation with other agents may be helpful for partial responders, particularly when comorbid tics are present (McDougle, 1997). Serotonin reuptake inhibitors Clomipramine was the first SRI antidepressant to be shown to be effective for OCD (Clomipramine Collaborative Study Group, 1991), with subsequent controlled trials documenting antiobsessional effects of the SSRIs (in order of increasing selectivity: fluoxetine, fluvoxamine, sertraline, paroxetine, and citalopram). All have been shown to be effective in multicenter double-blind trials (see Vythilingum et al., 2000, for a review of adult studies; Rapoport and Inoff-Germain, 2000, for a review of pediatric studies.) Table 42.1 gives the dosage ranges of the SRIs for treatment of adult and pediatric patients, as well as the half-life of the compounds (Montgomery et al., 2001). To avoid difficulties with adverse effects, it is advisable to “start low, go slow,” initiating therapy with low dosages and titrating upward slowly over a period of a few weeks. Patients should be warned that the medications take time to work and that an adequate trial is usually at least 10 weeks in duration (at the maximally tolerated dosage). Patients should also be told that trials of more than one agent or use of augmenting agents may be required. Recent research in adults (e.g., Sallee et al., 1998), including one placebo-controlled study (Fallon et al., 1998), indicates that intravenous administration of clomipramine speeds the initial response and increases response rates (even among previously nonresponsive patients). The hypothesized mechanism involves the greater bioavailability of the more serotonergic parent

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42.1 Serotonin Reuptake Inhibitor Treatment of Obsessive–Compulsive Disorder

Drug Clomipramine 24 hours Fluoxetine 96 hours

Fluvoxamine 24 hours

Adult Dosage Up to 250 mg/day

Child/Adolescent Dosage Controlled trials for patients aged 6 years

Half-Life 12–

3 mg/kg (max. 250 mg) Up to 80 mg/day

Controlled trials for patients aged 8 years

(NorFLX, 7–10 days)

2.5–80 mg

Up to 300 mg/day

Indicated for patients aged 8 years

48–

12–

50–200 mg/day Sertraline 24 hours

Up to 200 mg/day

Indicated for patients aged 6 years

12–

25–200 mg/day Paroxetine hours

Up to 60 mg/day

Open trial in 8- to 17-year-olds

24

No pediatric indications Citalopram hours

Up to 60 mg/day (indicated for open trial in 9- to 18-year-olds treatment of depression, not OCD)

No pediatric indications

35

OCD: Obsessive–compulsive disorder.

compound, clomipramine, versus the more noradrenergic metabolite, desmethylclomipramine, as a result of bypassing first-pass hepatoenteric metabolism. Following the initial intravenous infusion, clomipramine therapy is maintained orally. Experience in pediatric patients is limited, but two open trials and two placebocontrolled cases suggest that intravenous clomipramine may offer therapeutic benefits to children as well (Sallee et al., 1998). Other medications Clonazepam is a benzodiazepine with anxiolytic properties and serotonergic effects (Pigott, L’Heureux, Rubenstein, et al., 1992; Park et al., 1997). Pigott, L’Heureux, Rubenstein, and colleagues (1992) found significant improvement on one of three ratings of OCD severity when clonazepam (3–4 mg/day) was added to ongoing fluoxetine or clomipramine therapy. A case report of pediatric efficacy has also been published (Leonard et al., 1994). Venlafaxine, a serotonin-norepinephrine reuptake inhibitor, has demonstrated efficacy equal to that of the SRI paroxetine in a double-blind comparison with 75 patients in each arm of the study (Denys et al., 2003). Buspirone is a partial agonist of the 5-hydroxytryptamine-1A (5-HT1A) receptor and appears to enhance serotonergic neurotransmission. Open trials had suggested benefit from buspirone augmentation of SSRIs, but placebo-controlled trials failed to demonstrate significant benefits when buspirone was added to clomipramine (Pigott, L’Heureux, Hill, et al., 1992), fluvox-

amine (McDougle et al., 1993), or fluoxetine therapy (Grady et al., 1993). Neuroleptics, such as haloperidol, have been shown to be useful as augmenting agents, particularly in cases with comorbid tic disorders. McDougle and colleagues (1994) demonstrated significant improvements when haloperidol (mean dose 6.2 +/–3.0 mg/day) was added to fluvoxamine therapy. Eleven of 17 (65%) patients randomized to receive haloperidol responded to therapy, while none of the 17 patients receiving placebo had significant treatment gains. Further, eight of eight patients with comorbid tics had a significant reduction in OCD symptom severity (McDougle et al., 1994). Pediatric experience with haloperidol has been limited in OCD, although it is used frequently in children and adolescents with tic disorders (Leckman et al., 1997). Pimozide was noted to be of significant benefit among 9 of 17 patients previously nonresponsive to fluvoxamine therapy (McDougle et al., 1990). Because of the long-term risks of tardive dyskinesias occurring with neuroleptic administration, these drugs should be considered only if atypical antipsychotics are ineffective. Risperidone is an atypical antipsychotic medication with demonstrated benefits as an augmenting agent in OCD. Saxena and colleagues (1996) treated 16 patients with a combination of risperidone and SSRI and found that 14 (87%) had a significant reduction in OCD severity within 3 weeks of the addition of risperidone. Of particular interest, given the treatment-refractory nature of violent obsessive images, patients with this symptom were most likely to respond and to demonstrate significant benefits after only a few days of augmentation

42: NEUROBIOLOGY AND TREATMENT OF OBSESSIVE–COMPULSIVE DISORDER

(Saxena et al., 1996). Lombroso and colleagues (1995) found that risperidone augmentation of paroxetine or sertraline was effective for pediatric patients with comorbid OCD and tic disorders. Riluzole was used successfully to augment other pharmacotherapy in an adult patient who had failed treatment with prior regimens for his severe and refractory OCD and major depressive disorder (Coric et al., 2003). There have also been case reports of benefit of riluzole for a patient with chronic skin-picking as well as an eating disorder (Sasso et al., 2006) and in a patient with self-injurious behavior (Pittenger et al., 2005). To our knowledge, there have been no reports of the use of riluzole for the treatment of children and adolescents with OCD. But in an open-label study in our own laboratory, six young people (ages 8–16) took riluzole up to 60 mg twice a day for 12 weeks. Four patients were considered “responders” and have elected to discontinue other medications and continue taking riluzole (Grant et al., 2007) Two other patients did not have significant symptom improvement but have elected to remain on riluzole therapy. Of the two nonresponders, one was female—of possible importance, given the recent finding of significant association of a gene, which codes for an excitatory amino acid carrier, with early onset OCD in male (but not female) patients (Arnold et al., 2006; Dickel et al., 2006). A number of other drugs (namely, N-acetylcysteine, psilocin, morphine, inositol, sumatriptan) have seemed to show promise in individual cases, but published controlled trials are not yet available. SUMMARY Obsessive–compulsive disorder is a chronic disabling condition that often has its onset during childhood. The neurobiological basis for the disorder is unknown but appears to involve dysregulation of frontostriatalthalamocortical circuitry and the serotonergic system. Cognitive-behavior therapy and serotonin-reuptake inhibiting medications have been shown to be effective treatments for OCD, particularly when used in combination. Further research is needed to better define the clinical characteristics of OCD, as well as to delineate its etiology and pathophysiology. REFERENCES Abramowitz, J.S. (1998) Does cognitive-behavioral therapy cure obsessive-compulsive disorder? A meta-analytic evaluation of clinical significance. Behav. Ther. 29:339–355. Albert, U., Maina, G., Forner, F., and Bogetto, F. (2004) DSM-IV obsessive-compulsive personality disorder: prevalence in patients with anxiety disorders and in healthy comparison subjects. Compr. Psychiatry 45:325–332. Altemus, M., Pigott, T., Kalogeras, K.T., Demitrack, M., Dubbert, B., Murphy, D.L., and Gold, P.W. (1992) Abnormalities in the regu-

699

lation of vasopressin and corticotropin releasing factor secretion in obsessive-compulsive disorder. Arch. Gen. Psychiatry 49:9–20. Altemus, M., Swedo, S.E., Leonard, H.L., Richter, D., Rubinow, D.R., Potter, W.Z., and Rapoport, J.L. (1994) Changes in cerebrospinal fluid neurochemistry during treatment of obsessivecompulsive disorder with clomipramine. Arch. Gen. Psychiatry 51:794–803. American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Ananth, J., Pecknold, J., van Den Steen, N., and Engelsmann, F. (1981) Double-blind comparative study of clomipramine and amitryptyline in obsessive neurosis. Prog. Neuropsychopharmacol. Biol. Psychiatry 5:257–262. Arnold, P.D., Sicard, T., Burrougs, E., Richter, M.A., and Kennedy, J.L. (2006) Glutamate transporter gene slc1a1 associated with obsessive-compulsive disorder. Arch. Gen. Psychiatry 63:769– 776. Attiullah, N., Eisen, J.L., and Rasmussen, S.A. (2000) Clinical features of obsessive-compulsive disorder. Psychiatr. Clin. North Am. 23(3):469–491. Baer L., and Greist, J.H. (1997) An interactive computer-administered self-assessment and self-help program for behavior therapy. J. Clin. Psychiatry 58(Suppl 12):23–28. Baer, L., Jenike, M.A., Ricciardi, J.N., et al. (1990) Standardized assessment of personality disorders in obsessive-compulsive disorder. Arch. Gen. Psychiatry 47:826–830. Barton, R. (1987) Diabetes insipidus and obsessional neurosis. Adv. Biochem. Psychopharmacol. 43:347–349. Bastani, B., Nash, J.F., and Meltzer, H.Y. (1990) Prolactin and cortisol responses to MK-212, a serotonin agonist, in obsessivecompulsive disorder. Arch. Gen. Psychiatry 47:833–839. Berg, C.Z., Rapoport, J.L., Whitaker, A., Davies, M., Leonard, H., Swedo, S.E., et al. (1989) Childhood obsessive compulsive disorder: a two-year prospective follow-up of a community sample. J. Am. Acad. Child Adolesc. Psychiatry 28:528–533. Black, D., Noyes, R., Pfohl, B., et al. (1993) Personality disorder in obsessive-compulsive volunteers, well comparison subjects and their first-degree relatives. Am. J. Psychiatry 150:1226–1232. Borcherding, B., Keysor, C., Rapoport, J.L., Elia, J., and Amass, J. (1990) Motor vocal tics and compulsive behaviors on stimulant drugs: is there a common vulnerability? Psychiatry Res. 33: 83–94. Casas, M.E., Alvarez, P., Duro, C., Garcia Ribera, C., Udina, C., Velat, A., et al. (1986) Antiandrogenic treatment of obsessive compulsive disorder neurosis. Acta Psychiatr. Scand. 73:221–222. Chakrabarty, K., Bhattacharyya, S., Khanna, S., and Christopher, R. (2005) Glutamatergic dysfunction on OCD. Neuropsychopharmacology 30:1735–1740. Clark, A., Kirby, K.C., Daniels, B.A., and Marks, I.M. (1998) A pilot study of computer-aided vicarious exposure for obsessivecompulsive disorder. Aust. NZ J. Psychiatry 32:268–275. Clomipramine Collaborative Study Group. (1991) Clomipramine in the treatment of patients with obsessive-compulsive disorder. Arch. Gen. Psychiatry 43:730–738. Coric, V., Milanovic, S., Wasylink, S., Patel, P., Malison, R., Krystal, J.H. (2003) Beneficial effects of the antiglutamatergic agent riluzole in a patient diagnosed with obsessive-compulsive disorder and major depressive disorder. Psychopharmacology 167:219– 220. Coric, V., Taskiran, S., Pittenger, C., Wasylink, S., Mathalon, D.H., Valentine, G., Saksa, J., Wu, Y., Gueorguieva, R., Sanacora, G., Malison, R., and Krystal, J.H. (2005) Riluzole augmentation in treatment-resistant obsessive-compulsive disorder: an open-label trial. Biol. Psychiatry 58:424–428. Crino, R., Slade, T., and Andrews, G. (2005) The changing prevalence and severity of obsessive-compulsive disorder criteria from DSM-III to DSM-IV. Am. J. Psychiatry 162:876–882.

700

ANXIETY DISORDERS

Cummings, J.L., and Cunningham, K. (1992) Obsessive-compulsive disorder in Huntington’s disease. Biol. Psychiatry 31:263–270. Delgado, P.L., and Moreno, F.A. (1998) Different roles for serotonin in anti-obsessional drug action and the pathophysiology of obsessive-compulsive disorder. Br. J. Psychiatry 173(Suppl 35):21–25. Denys, D.A., van der Wee, N., Van Megen, H.J., and Westenberg, H.M. (2003) A double blind comparison of venlafaxine and paroxetine in obsessive-compulsive disorder. J. Clin. Psychopharmacology 23:568–575. DeVeaugh-Geiss, J., Landau, P., and Katz, R. (1989) Treatment of obsessive-compulsive disorder with clomipramine. Psychiatry Ann. 19:97–101. Dickel, D.E., Veenstr-Vanderweele, J., Cox, N.J., Wu, X., Fischer, D.J., Van Etten-Lee, M., Himle, J.A., Leventhal, B.L., Cook, J.E., Hanna, G.L. (2006) Association testing of the positional and functional candidate gene slc1a1/eaac1 in early-onset obsessivecompulsive disorder. Arch. Gen. Psychiatry 63:778–785. Dolberg, O.T., Iancu, I., and Zohar, J. (1996) Treatment duration of obsessive compulsive disorder. Eur. Psychiatry 11:403–406. Dougherty, D.D., Baer, L., Cosgrove, G.R., Cassem, E.H., Price, B.H., Nierenberg, A.A., Jenike, M.A., and Rauch, S.L. (2002) Prospective long-term follow-up of 44 patients who received cingulotomy for treatment-refractory obsessive-compulsive disorder. Am. J. Psychiatry 159(2):269–275. Douglass, H.M., Moffitt, T.E., Dar, R., et al. (1995) Obsessivecompulsive disorder in a birth cohort of 18 year olds: prevalence and predictors. J. Am. Acad. Child Adolesc. Psychiatry 34:1424– 1431. Eisen, J.L., Coles, M.E., Shea, M.T., Pagano, M.E., Stout, R.L., Yen, S., Grilo, C.M., and Rasmussen, S.A. (2006) Clarifying the convergence between obsessive-compulsive personality disorder criteria and obsessive-compulsive disorder. J. Personality Disord. 20:294–305. Eisen, J.L., Phillips, K.A., Rasmussen, S.A., et al. (1998) The Brown Assessment of Beliefs Scale (BABS): reliability and validity. Am. J. Psychiatry 155:102–108. Emmelkamp, P.M., and Beens, H. (1991) Cognitive therapy with obsessive-compulsive disorder: a comparative evaluation. Behav. Res. Ther. 29:293–300. Fallon, B.A., Liebowitz, M.R., Campeas, R., Schneier, F.R., Marshall, R., Davies, S., et al. (1998) Intravenous clomipramine for obsessive-compulsive disorder refractory to oral clomipramine. A placebo controlled study. Arch. Gen. Psychiatry 55:918–924. Fireman, B., Koran, L.M., Leventhal, J.L., and Jacobson, A. (2001) The prevalence of clinically recognized obsessive-compulsive disorder in a large health maintenance organization. Am. J. Psychiatry 158:1904–1910. Flament, M.F., Rapoport, J.L., Berg, C.J., Sceery, W., Kilts, C., Mellstrom, B., et al. (1985) Clomipramine treatment of childhood compulsive disorder: a double-blind controlled study. Arch. Gen. Psychiatry 42:977–983. Flament, M.F., Rapoport, J.L., Murphy, D.L., Berg, C.J., and Lake, R. (1987) Biochemical changes during clomipramine treatment of childhood obsessive compulsive disorder. Arch. Gen. Psychiatry 44:219–225. Flament, M.F., Whitaker, A., Rapoport, J., Davis, M., Berg, C.Z., Kalikow, K., et al. (1988) Obsessive compulsive disorder in adolescence: an epidemiological study. J. Am. Acad. Child Adolesc. Psychiatry 27:764–771. Foa, E.B., Steketee, G.S., and Grayson, J.B. (1985) Imaginal and in vivo exposure: a comparison with obsessive-compulsive checkers. Behav. Ther. 16:292–303. Frye, P., and Arnold, L. (1981) Persistent amphetamine-induced compulsive rituals: response to pyridoxine (B6). Biol. Psychiatry 16:583–587. Garvey, M.A., Giedd, J., and Swedo, S.E. (1998) PANDAS: the search for environmental triggers of pediatric neuropsychiatric

disorders. Lessons from rheumatic fever. J. Child. Neurol. 13(9): 413–423. Garvey, M.A., Perlmutter, S.J., Allen, A.J., Hamburger, S., Lougee, L., Leonard, H.L., Witowski, M.E., Dubbert, B., and Swedo, S.E. (1999) A pilot study of penicillin prophylaxis for neuropsychiatric exacerbations triggered by streptococcal infections. Biol. Psychiatry 45:1564–1571. Geller, D., Biederman, J., Stewart, S.E., Mullen, B., Martin, A., Spencer, T., and Faraone, S.V. (2003) Which SSRI? a meta-analysis of pharmacotherapy trials in pediatric obsessive-compulsive disorder. Am. J. Psychiatry 160:1919–1928. Giedd, J.N., Rapoport, J.L., Garvey, M.A., Perlmutter, S., and Swedo, S.E. (2000) MRI assessment of children with obsessive-compulsive disorder or tics associated with streptococcal infection. Am. J. Psychiatry 157:281–283. Giedd, J.N., Rapoport, J.L., Leonard, H.L., Richter, D., and Swedo, S.E. (1996) Case study: acute basal ganglia enlargement and obsessive-compulsive symptoms in an adolescent boy. J. Am. Acad. Child Adolesc. Psychiatry 35:913–915. Goodman, W.K., McDougle, C.J., Price, L.H., Riddle, M.A., Pauls, D.L., and Leckman, J.F. (1990) Beyond the serotonin hypothesis: a role for dopamine in some forms of obsessive compulsive disorder? J. Clin. Psychiatry 51(Suppl):36–43. Goodman, W.K., Price, L.H., Rasmussen, S.A., et al. (1989) The Yale-Brown Obsessive-Compulsive Scale: I. Development, use and reliability. Arch. Gen. Psychiatry 46:1006–1011. Grabe, H.J., Meyer, C.H., Hapke, U., et al. (2000) Prevalence, quality of life and psychosocial function in obsessive-compulsive disorder and subclinical obsessive-compulsive disorder in northern Germany. Eur. Arch. Psychiatry Clin. Neurosci. 250:262–268. Grady, T.A., Pigott, T.A., L’Heureux, F., Hill, J.L., Bernstein, S.E., and Murphy, D.L. (1993) Double-blind study of adjuvant buspirone for fluoxetine-treated patients with obsessive-compulsive disorder. Am. J. Psychiatry 150:819–821. Grant, P., Lougee L., Hirschtritt, M., and Swedo, S.E. (2007) An open-label trial of riluzole, a glutamate antagonist, in children with treatment-resistant obsessive-compulsive disorder. J. Child Adolesc. Psychopharmacology 17(6): 761–767. Greenberg, B.D., Murphy, D.L., and Rasmussen, S.A. (2000) Neuroanatomically based approaches to obsessive-compulsive disorder. Psychiatry Clin. North Am. 23(3):671–686. Greist, J.H. (1996) New developments in behaviour therapy for obsessive-compulsive disorder. Int. Clin. Psychopharmacol. 11(Suppl 5): 63–73. Greist, J.H., and Jefferson, J.W. (1998) Pharmacotherapy for obsessive-compulsive disorder. Br. J. Psychiatry 173(Suppl 35):64–70. Greist, J.H., Jefferson, J.W., Kobak, K.A., et al. (1995) Efficacy and tolerability of serotonin transport inhibitors in obsessive-compulsive disorder: a meta-analysis. Arch. Gen. Psychiatry 52:53–60. Hamburger, S.D., Swedo, S., Whitaker, A., Davies, M., and Rapoport, J.L. (1989) Growth rate in adolescents with obsessive-compulsive disorder. Am. J. Psychiatry 146:652–655. Hamilton, C.S., Garvey, M.A., and Swedo, S.E. (2001) Therapeutic implications of immunology for tics and obsessive-compulsive disorder. In: Cohen, D.J., Goetz, C.G., and Jankovic, J., eds. Tourette Syndrome. Philadelphia: Lippincott, Williams & Wilkins, pp. 311–318. Hollander, E., Kaplan, A., Allen, A., and Cartwright, C. (2000) Pharmacotherapy for obsessive-compulsive disorder. Psychiatr. Clin. North Am. 23(3):643–656. Husby, G., Van de Rijn, I., Zabriskie, J.B., Abdin, Z.H., and Williams, R.C. (1976) Antibodies reacting with cytoplasm of subthalamic and caudate nuclei neurons in chorea and acute rheumatic fever. J. Exp. Med. 144:1094–1110. Insel, T.R., and Akiskal, H.S. (1986) Obsessive-compulsive disorder with psychotic features: a phenomenologic analysis. Am. J. Psychiatry 143:1527–1533.

42: NEUROBIOLOGY AND TREATMENT OF OBSESSIVE–COMPULSIVE DISORDER Insel, T.R., Mueller, E.A., Alterman, I., Linnoila, M.M., and Murphy, D.L. (1985) Obsessive-compulsive disorder and serotonin: is there a connection? Biol. Psychiatry 20:1174–1188. Karno, M., and Golding, J. (1990) Obsessive compulsive disorder. In: Robins, L., and Regier D.A., eds. Psychiatric Disorders in America: The Epidemiological Catchment Area Study. New York: Free Press, pp. 204-209. Karno, M., Golding, J., Sorenson, S., and Burnam, A. (1988) The epidemiology of obsessive compulsive disorder in five U.S. communities. Arch. Gen. Psychiatry 45:1094–1099. Kiessling, L.S., Marcotte, A.C., and Culpepper, L. (1994) Antineuronal antibodies: tics and obsessive-compulsive symptoms. J. Dev. Behav. Pediatr. 15:421–425. Kirvan, C.A., Swedo, S., Kurahara, D., and Cunningham, M.W. (2006) Streptococcal mimicry and antibody-mediated cell signaling in the pathogenesis of Sydenham’s chorea. Autoimmunity 39:21–29. Kozak, M.J., and Foa, E.B. (1994) Obsessions, overvalued ideas and delusions in obsessive-compulsive disorder. Behav. Res. Ther. 32:343–353. Leckman, J.F., and Mayes, L.C. (1999) Preoccupations and behaviors associated with romantic and Parental love: Perspectives on the origin of obsessive-compulsive disorder. Child Adolesc. Psychiatr. Clin. North Am. 8(3):635–665. Leckman, J.F., Goodman, W.K., North, W.G., Chappell, P.B., Price, L.H., Pauls, D.L., et al. (1994) The role of central oxytocin in obsessive compulsive disorder and related normal behavior. Psychoneuroendocrinology 19:723–749. Leckman, J.F., Grice, D.E., Boardman, J., Zhang, H., Vitale, A., Bondi, C., et al. (1997) Symptoms of obsessive-compulsive disorder. Am. J. Psychiatry 154(7):911–917. Leonard, H.L., Lenane, M.C., Swedo, S.E., Rettew, D.C., Gershon, E.S., and Rapoport, J.L. (1992) Tics and Tourette’s disorder: a 2to 7-year follow-up of 54 obsessive-compulsive children. Am. J. Psychiatry 149:1244–1251. Leonard, H.L., Swedo, S., Rapoport, J., Koby, E., Lenane, M., Cheslow, D., et al. (1989) Treatment of childhood obsessive compulsive disorder with clomipramine and desmethylimipramine: a double-blind crossover comparison. Arch. Gen. Psychiatry 46: 1088–1092. Leonard, H.L., Topol, D., Bukstein, O., Hindmarsh, D., Allen, A.J., and Swedo, S.E. (1994) Clonazepam as an augmenting agent in the treatment of childhood-onset obsessive-compulsive disorder. J. Am. Acad. Child Adolesc. Psychiatry 33:792–794. Lombroso, P.J., Scahill, L., King, R.A., Lynch, K.A., Chappell, P.B., Peterson, B.S., et al. (1995) Risperidone treatment of children and adolescents with chronic tic disorders: a preliminary report. J. Am. Acad. Child Adolesc. Psychiatry 34:1147–1152. March, J., et al. (2004) Cognitive-behavioral therapy, sertraline, and their combination for children and adolescents with obsessivecompulsive disorder. the POTS Randomized Controlled Trial. JAMA 292:1969–1976. March, J.S. (1995) Cognitive-behavioral psychotherapy for children and adolescents with OCD: a review and recommendations for treatment. J. Am. Acad. Child Adolesc. Psychiatry 34:7–18. March, J.S., Franklin, M., Nelson, A., and Foa, E. (2001) Cognitivebehavioral psychotherapy for pediatric obsessive-compulsive disorder. J. Clin. Child Psychol. 30(1):8–18. March, J.S., and Mulle, K. (1998) OCD in Children and Adolescents. A Cognitive-Behavioral Treatment Manual. New York: Guilford Press. March, J.S., Mulle, K., and Herbel, B. (1994) Behavioral psychotherapy for children and adolescents with obsessive-compulsive disorder: an open trial of a new protocol-driven treatment package. J. Am. Acad. Child Adolesc. Psychiatry 33:333–341. Marks, I. (1997) Behavior therapy for obsessive-compulsive disorder. A decade of progress. Can. J. Psychiatry 42:1021–1026.

701

McDougle, C.J. (1997) Update on pharmacologic management of OCD: agents and augmentation. J. Clin. Psychiatry 58(Suppl 12):11–17. McDougle, C.J., Goodman, W.K., Leckman, J.F., Holzer, J.C., Barr, L.C., McCance-Katz, E.F., Heninger, G.R., and Price, L.H. (1993) Limited therapeutic effect of addition of buspirone to fluvoxamine-refractory obsessive compulsive disorder. Am. J. Psychiatry 150:647–649. McDougle, C.J., Goodman, W.K., Leckman, J.F., Lee, N.C., Heninger, G.R., and Price, L.H. (1994) Haloperidol addition in fluvoxamine-refractory obsessive-compulsive disorder—a double-blind, placebo-controlled study in patients with and without tics. Arch. Gen. Psychiatry 51:302–308. McDougle, C.J., Goodman, W.K., Price, L.H., Delgado, P.L., Krystal, J.H., Charney, D.S., and Heninger, G.R. (1990) Neuroleptic addition in fluvoxamine-refractory obsessive-compulsive disorder. Am. J. Psychiatry 147:652–654. McGrath, M.J., Campbell, K.M., Parks, C.R.I., and Burton, F.H. (2000) Glutamatergic drugs exacerbate symptomatic behavior in a transgenic model of comorbid Tourette’s syndrome and obsessive-compulsive disorder. Brain Res. 877:23–30. Mindus, P. (1991) Capsulotomy in Anxiety Disorders: A Multidisciplinary Study. Stockholm: Karolinska Institute Press. Montgomery, S.A., Kasper, S., Stein, D.J., Bang Hedgaard, K., and Lemming, O.M. (2001) Citalopram 20 mg, 40 mg, and 60 mg are all effective and well tolerated compared with placebo in obsessive-compulsive disorder. Int. Clin. Psychopharmacol. 16(2): 75–86. Morshed, S.A., Parveen, S., Leckman, J.F., Mercadante, M.T., Bittencourt Kiss, M.H., Miguel, E.C., et al. (2001) Antibodies against neural, nuclear, cytoskeletal, and streptococcal epitopes in children and adults with Tourette’s syndrome, Sydenham’s chorea, and autoimmune disorders. Biol. Psychiatry 50(8):566– 577. Murphy, D., Zohar, J., Pato, M., Pigott, T., and Insel, T. (1989) Obsessive compulsive disorder as a 5-HT subsystem behavioral disorder. Br. J. Psychiatry 155(Suppl):15–24. Neziroglu, F., Hsia, C., and Yaryura-Tobias, J.A. (2000) Behavioral, cognitive, and family therapy for obsessive-compulsive and related disorders. Psychiatry Clin. North Am. 23(3):657–670. O’Connor, K.P., Aardema, F., Robillard, S., Guay, S., Pelissier, M.C., Todorov, C., Borgeat, F., Leblanc, V., Grenier, S., and Doucet, P. (2006) Cognitive behaviour therapy and medication in the treatment of obsessive-compulsive disorder. Acta Psychiatr. Scand. 113:408–419. Park, L.T., Jefferson, J.W., and Greist, J.H. (1997) Obsessive-compulsive disorder. Treatment options. CNS Drugs 7:187–202. Perlmutter, S.J., Garvey, M.A., Castellanos, X., Mittleman, B.B., Giedd, J., Rapoport, J.L., and Swedo, S.E. (1998) A case of pediatric autoimmune neuropsychiatric disorders associated with stretpcoccal infections (PANDAS). Am. J. Psychiatry 155(11): 1592–1598. Perlmutter, S.J., Leitman, S.F., Garvey, M.A., Hamburger, S., Feldman, E., Leonard, H.L., et al. (1999) Therapeutic plasma exchange and intravenous immunoglobulin for obsessive compulsive disorder and tic disorders in childhood. Lancet 354: 1153–1158. Pigott, T.A., L’Heureux, F., Hill, J.L., Bihari, K., Bernstein, S.E., and Murphy, D.L. (1992) A double-blind study of adjuvant buspirone hydrochloride in clomipramine-treated patients with obsessive-compulsive disorder. J. Clin. Psychopharmacol. 12:11–18. Pigott, T.A., L’Heureux, F., Rubenstein, C.S., Hill, J.L., and Murphy, D.L. (1992) A controlled trial of clonazepam augmentation in OCD patients tested with clomipramine or fluoxetine [Abstract no. 144]. In: New Research Program and Abstracts of the 145th Annual Meeting of the American Psychiatric Association. Washington, DC: American Psychiatric Association, p. 82.

702

ANXIETY DISORDERS

Pigott, T.A., Zohar, J., Hill, J.L., Berstein, S.E., Grover, G.N., Zohar-Kadouch, R.C., and Murphy, D.L. (1991) Metergoline blocks the behavioral and neuroendocrine effects of orally administered m-CPP in patients with OCD. Biol. Psychiatry 29:418–426. Pittenger, C., Krystal, J.H., and Coric, V. (2005) Initial evidence of the benefits of glutamate modulating agents in the treatment of self-injurious behavior associated with borderline personality disorder. J. Clinical Psychiatry 66:1492–1493. Rapoport, J.L., and Inoff-Germain, G. (2000) Treatment of obsessive-compulsive disorder in children and adolescents. J. Child Psychol. Psychiatry 41(4):419–431. Rasmussen, S.A., and Eisen, J.L. (1992) The epidemiology and differential diagnosis of obsessive-compulsive disorder. J. Clin. Psychiatry 53(Suppl):4–10. Rasmussen, S.A., and Tsuang, M.T. (1986) DSM-III obsessivecompulsive disorder: clinical characteristics and family history. Am. J. Psychiatry 143:317–322. Ravizza, L., Maina, G., Bogetto, F., Albert, U., Barzega, G., and Bellino, S. (1998) Long term treatment of obsessive-compulsive disorder. CNS Drugs 10:247–255. Ricciardi, J.N., Baer, L., Jenike, M.A., et al. (1992) Changes in DSMIII-R axis II diagnoses following treatment of obsessive-compulsive disorder. Am. J. Psychiatry 149:829–831. Robins, L., Helzer, J., Crougham, J., and Ratcliffe, K. (1981) The NIMH Epidemiological Catchment Area study. Arch. Gen. Psychiatry 38:381–389. Rosario-Campos, M., Leckman, J.F., Mercadante, M.T., Shavitt, R.G., Silva, D.A., Prado, H., Sada, P., Zamignani, D., and Miguel, E.C. (2001) Adults with early-onset obsessive-compulsive disorder. Am. J. Psychiatry 158:1899–1903. Rosenberg, D.R., Chugani, D.C., Muzik, O., et al. (1998) Altered serotonin synthesis in fronto-striatal circuitry in pediatric obsessive-compulsive disorder. Biol. Psychiatry 43(8 Suppl 1): 245. Sallee, F.R., Koran, L.M., Pallanti, S., Carson, S.W., and Sethuraman, G. (1998) Intravenous clomipramine challenge in obsessivecompulsive disorder: predicting response to oral therapy at eight weeks. Biol. Psychiatry 44:220–227. Salzberg, A., and Swedo, S.E. (1992) Oxytocin and vasopressin in obsessive-compulsive disorder. Am. J. Psychiatry 149:713–714. Sasso, D.A., Kalanithi, P.S.A., Trueblood, K.V., Pittenger, C., Kelmendi, B., Wayslink, S., Malison, R.T., Krystal, J.H., and Coric, V. (2006) Beneficial effects of the glutamate-modulating agent riluzole on disordered eating and pathological skin-picking behaviors. J. Clin. Psychopharmacol. 26:685–686. Saxena, S., and Rauch, S.L. (2000) Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder. Psychiatr. Clin. North Am. 23(3):563–586. Saxena, S., Wang, D., Bystritsky, A., and Baxter, L.R., Jr. (1996) Risperidone augmentation of SRI treatment for refractory obsessivecompulsive disorder. J. Clin. Psychiatry 57:303–306. Shafran, R. (1998) Childhood obsessive-compulsive disorder. In: Graham, P., ed. Cognitive Behavior Therapy for Children and Families. Cambridge, UK: Cambridge University Press, pp. 45–73. Shafron, N.A., and Somers, J. (1998) Treating adolescent obsessivecompulsive disorder: applications of the cognitive theory. Behav. Res. Ther. 36:93–97. Singer, H.S., Giuliano, J.D., Hansen, B.H., et al. (1998) Antibodies against human putamen in children with Tourette syndrome. Neurology 50:1618–1624. Snider, L.A., Lougee, L., Slattery, M., Grant, P., and Swedo, S.E. (2005) Anatibiotic prophylaxis with azithromycin or penicillin in childhood-onset neuropsychiatric disorders. Biol. Psychiatry 57: 788–792. Sousa, M.B., Isolan, L.R., Oliveira, R.R., Manfro, G.G., Cordioli, A. (2006) A randomized clinical trial of cognitive-behavioral group therapy and sertraline in the treatment of obsessive-

compulsive disorder. J. Clin. Psychiatry 67:1133–1139. Stanley, M.A., and Turner, S.M. (1995) Current status of pharmacological and behavioral treatment of obsessive-compulsive disorder. Behav. Ther. 26:163–186. Stein, D.J., Bouwer, C., Hawkridge, S., and Emsley, R.A. (1997) Risperidone augmentation of serotonin reuptake inhibitors in obsessive-compulsive and related disorders. J. Clin. Psychiatry 58: 119–122. Swedo, S., and Rapoport, J.L. (1990) Neurochemical and neuroendocrine consideration of obsessive-compulsive disorders in childhood. In: Deutsch, S.I., Weizman, A., and Weizman, R., eds. Application of Basic Neurosciences to Child Psychiatry. New York: Plenum Medical Books, pp. 275–284. Swedo, S., Leonard, H.L., Kruesi, M.J.P., Rettew, D., Listwak, S.J., Berrettini, W., et al. (1992) Cerebrospinal fluid neurochemistry of children and adolescents with obsessive compulsive disorder. Arch. Gen. Psychiatry 49:29–36. Swedo, S., Rapoport, J.L., Leonard, H.L., Lenane, M., and Cheslow, D. (1989) Obsessive compulsive disorder in children and adolescents: clinical phenomenology of 70 consecutive cases. Arch. Gen. Psychiatry 46:335–341. Swedo, S.E. (1989) Rituals and releasers: an ethological model of OCD. In: Rapoport, J.L., ed. Obsessive Compulsive Disorder in Children and Adolescents. Washington, DC: American Psychiatric Press, pp. 269–288. Swedo, S.E., Leonard, H.L., Garvey, M., Mittleman, B., Allen, A.J., Perlmutter, S., et al. (1998) Pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS): clinical description of the first 50 cases. Am. J. Psychiatry 155: 264–271. Swedo, S.E., Leonard, H.L., Schapiro, M.B., Casey, B.J., Mannheim, G.B., Lenane, M.C., et al. (1993) Sydenham’s chorea: physical and psychological symptoms of St. Vitus dance. Pediatrics 91: 706–713. van der Wee, N., Stevens, H., Hardeman, J.A., Mandl, R.C., Denys, D.A., Van Megen, H.J., Kahn, R.S., and Westenberg, H.M. (2004) Enhanced dopamine transporter density in psychotropicnaive patients with obsessive-compulsive disorder shown by [123i]b-cit spect. Am. J. Psychiatry 161:2201–2206. Van Noppen, B., Skeketee, G., McCorkle, B., et al. (1997) Group and multifamily behavioral treatment for obsessive compulsive disorder: a pilot study. J. Anxiety Disord. 11:431–446. Von Economo, C. (1931) Encephalitis Lethargica: Its Sequelae and Treatment. London: Oxford University Press. Vythilingum, B., Cartwright, C., and Hollander, E. (2000) Pharmacotherapy of obsessive-compulsive disorder: experience with the selective serotonin reuptake inhibitors. Int. Clin. Psychopharmacol. 15(Suppl 2):S7–S13. Weissman, M.M., Bland, R.C., Canino, G.J., Greenwald, S., Hwu, H-G., Lee, C.K., et al. (1994) The cross-national epidemiology of obsessive-compulsive disorder. J. Clin. Psychiatry 55(Suppl 3):5–10. Wittchen, H.U., Nelson, C.B., and Lachner, G. (1998) Prevalence of mental disorders and psychosocial impairments in adolescents and young adults. Psychol. Med. 28:109–126. Wolff, R., and Rapoport, J.L. (1988) Behavioral treatment of childhood obsessive compulsive disorder. Behav. Modif. 12:252–256. Zohar, A.H. (1999) The epidemiology of obsessive-compulsive disorder in children and adolescents. Child Adolesc. Psychiatr. Clin. North Am. 8(3):445–460. Zohar, J., Insel, T., and Zohar-Kadouch, R. (1988) Serotonergic responsivity in obsessive-compulsive effects of chronic clomipramine treatment. Arch. Gen. Psychiatry 45:167–172. Zohar, J., Mueller, E.A., Insel, T.R., Zohar-Kadouch, R., and Murphy, D. (1987) Serotonergic responsivity in obsessive-compulsive disorder: comparison with patients and healthy controls. Arch. Gen. Psychiatry 44:946–951.

43 Neuroimaging Studies of Anxiety Disorders JUSTINE M. KENT

A N D

SCOTT L. RAUCH

A virtual explosion in neuroimaging research has marked the past decade, with convergent data from various imaging studies informing our neurobiological models of the anxiety disorders. Within the field of anxiety disorders research, neuroimaging techniques are being used to investigate the structure, function, and neurochemistry of the brain in vivo. In this chapter, we discuss the burgeoning field of neuroimaging research in the context of neurocircuitry models of the anxiety disorders. This chapter necessarily extends previous reviews that we have written, together with our colleagues, on the neurobiology of anxiety (Rauch and Baxter, 1998; Rauch, Shin, Whalen, et al., 1998; Rauch, Whalen, et al., 1998; Kent et al., 2000; Saxena and Rauch, 2000; Kent, Sullivan, Rauch, et al., 2002; Cannistraro and Rauch, 2003; Phillips et al., 2003; Deckersbach et al., 2006; Rauch et al., 2006; Shin et al., 2006). ANXIETY AND THE ANXIETY DISORDERS Although anxiety and fear are normal human emotional states, the anxiety disorders are characterized by maladaptive fearful responding and distressing psychic and somatic symptoms, which result in significant functional impairment. Obsessive–compulsive disorder (OCD) is characterized by intrusive, unwanted thoughts (that is, obsessions) and ritualized, repetitive behaviors (that is, compulsions). Obsessions are typically accompanied by anxiety that drives the compulsions. The compulsions are performed to neutralize the obsessions and associated anxiety. Posttraumatic stress disorder (PTSD) is one of few psychiatric conditions for which an etiology is clearly defined. It is characterized by significant anxiety symptoms following an emotionally severely traumatic event. The main features of PTSD include reexperiencing phenomena (for example, flashbacks), avoidance (for example, avoiding situations that remind the individual of the traumatic event), and hyperarousal (for example, an exaggerated startle response). Phobias are characterized by consistently heightened anxiety responses to innocuous stimuli or situations. Social

phobia (or social anxiety disorder) is characterized by excessive, often-paralyzing anxiety in response to a range of different social and performance situations. Specific phobias involve phobic responses to any of various stimuli or situations (for example, heights, insects, snakes, enclosed spaces). Finally, panic disorder (PD) is characterized by recurrent panic attacks, often occurring spontaneously, without overt precipitants, and the presence of anticipatory anxiety and phobic avoidance. During panic attacks, the individual experiences an acute crescendo of fear and anxiety, accompanied by physical symptoms such as shortness of breath, racing heart, palpitations, sweating, and dizziness, as well as emotional and cognitive symptoms such as an intense feeling of dread and the desire to escape the given situation/surroundings. Unreasonable avoidance of places or situations where the individual believes panic attacks are more likely to occur is a common result of repeated panic episodes. A common factor of the anxiety disorders is exaggerated fear in response to relatively innocuous stimuli (for example, phobias) or spontaneous fear responses in the absence of true threat (for example, PD). Thus, normal fear responding has been examined as a potential model for the neuroanatomical basis of maladaptive anxiety. Current neurobiological models of anxiety are based primarily on patterns of dysfunction within the so-called fear neurocircuitry, largely established through preclinical models of stress responding and fear conditioning (LeDoux et al., 1988; Davis, 1992). NEUROANATOMY RELEVANT TO ANXIETY AND FEAR Sensory information processing is critical to threat assessment and occurs via pathways running through the anterior thalamus to the amygdala (LeDoux et al., 1990). The amygdala, located in the anterior part of the medial temporal lobe, is the central node for the coordination of autonomic and behavioral fear responding. Thus, the amygdala is critical in preliminary threat 703

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assessment, and in preparation for action in response to threat via its ascending projections to motor areas and descending projections to brain stem nuclei that control autonomic responses and arousal. Importantly, the amygdala also facilitates the acquisition of additional information regarding the specific threat via reciprocal projections to subcortical and limbic cortical regions (Aggleton, 1992; LeDoux, 1996). Brain regions providing important feedback to the amygdala include (1) medial frontal cortex, (2) the hippocampus, and (3) cortico-striato-thalamic circuits that mediate gating at the level of the thalamus, thereby regulating the flow of incoming information that reaches the amygdala. Medial frontal cortex, including anterior cingulate and medial and orbitofrontal cortex (OFC), is believed to provide critical top-down governance over the amygdala, suppressing the fear response once danger has passed or when the meaning of a potentially threatening stimulus has changed. The hippocampus provides information about the context of a situation and may call on information about the environment retrieved from explicit memory stores. Dysfunction of the hippocampus has been shown to result in poor contextual stimulus discrimination, which may be related to the overgeneralization of fear responding seen in anxiety disorders. In addition, neurochemical modulators may affect the activity within each of these various brain areas and at nodes of the entire neurocircuitry system outlined above. Ascending projections from the raphé nuclei (serotonin) and the locus ceruleus (norepinephrine) are prime modulators of activity (Salzman et al., 1993; Charney et al., 1995; Kent et al., 1998). Recently, there has been increasing interest in the role of glutamate in anxiety disorders, as numerous preclinical studies have shown that chronic stress increases the activity of this potentially neurotoxic excitatory amino acid. Theoretical models now link stress to increased glucocorticoid activity, to hippocampal damage, and to anxiety and depression. It has been proposed that glucocorticoids may actually affect the suppression of neurogenesis in the hippocampus via their action on excitatory glutamate pathways (Cameron et al., 1998). In addition, chronically raised cortisol levels facilitate hippocampal neuronal death, leading to further dysregulation of the hypothalamic-pituitary axis (Sapolsky, 1986, 2000). Although this area is somewhat controversial, it has nevertheless led to attempts to treat anxiety with corticotropin releasing factor (CRF) antagonists (Holsboer, 1999), in addition to traditional anxiolytic medications targeting the serotonergic, noradrenergic, and g -aminobutyric acid (GABA) ergic systems. In this chapter, we discuss modern neuroimaging techniques employed in investigating structural, functional, and neurochemical aspects of anxiety. Morphometric magnetic resonance imaging (mMRI) has replaced com-

puted axial tomography (CAT scanning) as the current approach to structural neuroimaging. Contemporary mMRI typically entails semiautomated or fully automated schemes for segmenting defined brain structures so that corresponding volumes can be precisely calculated. Strategies for parcellating cortical territories, as well as subdividing subcortical nuclei, are being implemented to provide more exact volumetric data. Magnetic resonance diffusion tensor imaging (DTI) is a complementary neuroimaging technique used for assessing regional white matter tract orientation and connectivity in vivo. Fiber tract orientation and tissue anisotropy are estimated with DTI, then algorithms are employed in three dimensions to determine white matter tract orientations (Jones et al., 1999). Methods for inferring regional connectivity from diffusion data are being implemented to create directional maps (Poupon et al., 2001; Sato et al., 2001). Thus, this noninvasive technique is a potential means of assessing alterations in orientation and connectivity within white matter tracks and of evaluating progressive changes in connectivity over time in psychiatric, neurological, and developmental disorders. Functional imaging methods include positron emission tomography (PET) with tracers that measure blood flow (for example, oxygen-15-labeled carbon dioxide or oxygen-15-labeled water) or glucose metabolism (that is, F-18-labeled fluorodeoxyglucose [FDG]); single photon emission computed tomography (SPECT) with tracers that measure correlates of blood flow (for example, technetium-99-labeled hexamethyl propylene amine oxime [TcHMPAO]); and functional magnetic resonance imaging (fMRI) to measure blood oxygenation level-dependent (BOLD) signal changes. Patterns reflecting regional brain activity are generated with each of these techniques. The resultant brain activity maps from functional imaging studies are sensitive to the state of the subject at the time of tracer distribution or image acquisition. Therefore, functional imaging paradigms are categorized by the type of state manipulations employed. In neutral state paradigms, subjects are studied during a nominal resting state or while performing a nonspecific continuous task. Between-group comparisons are then made to test hypotheses regarding group differences in regional brain activity, without particular attention to state variables. In symptom provocation paradigms, subjects are typically scanned during a neutral (control) state, and then scanned in a symptomatic state in which anxiety is intentionally induced through the use of specific pharmacological and/or behavioral stimuli. Withingroup comparisons are made to test hypotheses regarding the anatomy underlying the symptomatic state, whereas group × condition interactions identify differing responses in patient versus control groups. In cognitive activation paradigms, subjects are studied while performing specially designed cognitive-behavioral tasks.

43: NEUROIMAGING STUDIES

This approach aims to increase sensitivity by employing tasks that specifically activate brain regions or systems of interest. Again, group × condition interactions are sought to test the functional integrity of specific brain systems in patients versus healthy controls. In treatment paradigms, patients are scanned in the context of a treatment protocol, usually before and after a pharmacological or behavioral therapy treatment trial. Within-group comparisons are then made to test hypotheses regarding changes in patterns of brain activity associated with symptomatic improvement. Also, correlational analyses can be performed to identify pretreatment brain activity predictive of treatment response. Imaging studies of neurochemistry have employed PET and SPECT methods in conjunction with radiolabeled high-affinity ligands to characterize regional receptor number and or affinity in vivo (that is, neuroreceptor characterization studies). Proton magnetic resonance spectroscopy (1H MRS) is a brain-imaging technique that permits a noninvasive means of quantifying endogenous brain chemistry and examining regional cellular energetics and function in vivo. Employing the physical principles used in MRI, several chemical species are routinely measured by 1H MRS, including Nacetylaspartate (NAA), cytosolic choline (Cho), myoinositol (mI), and creatine (Cr). In addition, particular 1 H MRS editing techniques (Rothman et al., 1993) now allow for investigation of amino acid concentrations of glutamate, glutamine, and GABA (Sanacora et al., 1999). N-acetylaspartate is a cell marker, the concentration of which correlates with neuronal density (Barker, 2001). Another MRS-visible compound, the Cho resonance, reflects a pool of choline composed of acetylcholine and the by-products of phosphatidylcholine hydrolysis, phosphocholine, and glycerophosphocholine. Abnormalities in the Cho resonance have been linked to abnormalities in myelination, cerebral oxidative metabolism, and alterations in intraneuronal signaling (Jung et al., 2002). The Cr resonance reflects systemic energy use and storage. The Cr signal is considered a valid internal standard in ratio analyses commonly used in measuring neurometabolic change due to its stability within individuals over time (Moats et al., 1994; Ross and Michaelis, 1994). These various neuroimaging techniques should be viewed as complementary, providing convergent information about structural, functional, and neurochemical integrity in brain systems of interest.

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of OCD (see Rauch, Whalen, et al., 1998; Saxena and Rauch, 2000, for review). Within the context of this model, one view is that striatal pathology (specifically within the caudate nucleus) leads to inefficient gating at the level of the thalamus, which results in hyperactivity within orbitofrontal and anterior cingulate cortices (Fig. 43.1). The symptomatic expression of hyperactivity within orbitofronal cortex may manifest as intrusive thoughts, whereas hyperactivity within the anterior cingulate cortex (ACC) may be associated with generalized anxiety. In this model, compulsions are viewed as repetitive behaviors that are performed to recruit the inefficient striatum so as to ultimately achieve thalamic gating and thereby neutralize unwelcome thoughts and attendant anxiety. Structural Imaging Findings Volumetric MRI studies in OCD have focused on brain structures identified in functional neuroimaging studies as key areas of aberrant activity. These brain regions include the striatum, thalamus, amygdala, and OFC. Studies of adult patients with OCD examining the striatum with modern mMRI techniques have reported inconsistent findings. Results from three of these investigations suggest volumetric abnormalities in OCD involving the caudate nucleus (Scarone et al., 1992;

OBSESSIVE–COMPULSIVE DISORDER Neuroanatomical Model of Obsessive–Compulsive Disorder (Cortico-Striatal Model) Aberrant functioning within the cortico-striato-thalamocortical circuitry is the foundation of current models

FIGURE 43.1 Schematized neuroanatomical model of obsessive–compulsive disorder indicating direct and indirect (via the STN) pathways of the cortico-striato-thalamo-cortical circuit. AMYG: amygdala; GABA: g -aminobutyric acid; STN: subthalamic nucleus.

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Robinson et al., 1995; Jenike et al., 1996), with other studies reporting no significant differences in caudate volumes versus controls groups (Aylward et al., 1996; J.-J. Kim et al., 2001; Riffkin et al., 2005). Magnetic resonance imaging has also demonstrated abnormal thalamus volumes in several studies (Gilbert et al., 2000; Rosenberg, Benazon, et al., 2000; J.-J. Kim et al., 2001) Perhaps more consistent is the report of reduced volume of the orbitofrontal cortices in OCD (Szeszko et al., 1999; Choi et al., 2004; Kang et al., 2004; Pujol et al., 2004; Atmaca et al., 2006; Atmaca et al., 2007). Of note, using a voxel-based analysis of segmented gray matter images, J.-J. Kim and colleagues (2001) reported increased gray matter volume in the OFC of patients with OCD. Thus, despite potentially overall reduced volume, increased gray matter density in the orbitofrontal region suggests hyperconnectivity, consistent with the hypermetabolism seen in the frontal-subcortical circuitry implicated as being aberrant in OCD. In this context, of particular interest is a report using mMRI techniques to examine changes in subcortical structures following lesioning of the anterior cingulate in nine patients with treatment-resistant OCD (Rauch, Kim, et al., 2000). Significant reductions in the caudate nucleus postcingulotomy were found, with the degree of reduction correlating positively with the extent of lesioning. These findings confirm the important connectivity between the anterior cingulate and the caudate and suggest that changes in structures distant from the site of lesioning may be responsible for clinical improvement. Studies examining amygdala volumes in OCD have yielded contradictory results, with one study reporting decreased amygdala volume bilaterally in patients with OCD compared with healthy controls (Szesko et al., 1999), whereas another study reported increased left amygdala volume and reduced hippocampal volume bilaterally (Kwon et al., 2003). Several pediatric studies have focused on brain regional volumetric changes in OCD. Rosenberg et al. (1997) performed the first mMRI study in treatmentnaïve pediatric patients, examining 19 patients with OCD and 19 case-matched, psychiatrically healthy comparisons. They found reduced striatal volumes in the OCD group versus the control group, with volume inversely related to OCD symptom severity. Several years later, Szeszko and colleagues (2004) reported similar findings in a study of 23 drug-naïve pediatric patients with OCD when compared with 27 healthy controls. Patients with OCD had smaller globus pallidus volumes than healthy volunteers, although there were no volumetric differences between the two groups for the caudate or putamen. Two studies have focused on children with streptococcal infection-associated OCD. In a study by Giedd et al. (2000) of 34 children with OCD and/or chronic

tics associated with group A b-hemolytic streptococcal (GABHS) infection compared to 82 matched healthy controls, average basal ganglia size (caudate, putamen, globus pallidus) was increased in the OCD group. No difference was reported in basal ganglia size between the 18 children with a primary diagnosis of OCD and the 16 children with a primary diagnosis of chronic tic disorder, although there was much overlap in symptomatology across the two groups. Because of the significant comorbidity of OCD, tic disorders, and attention-deficit/hyperactivity disorder (ADHD), Peterson and colleagues (2000) attempted to clarify the association between diagnosis, GABHS infection, and basal ganglia enlargement. They studied a primarily pediatric sample, consisting of patients with OCD, chronic tic disorder, or ADHD ranging in age from 7 to 55 years. High anti-GABHS antibody titers were associated with a diagnosis of ADHD, while increasing titers of GABHS antibodies were associated with enlargement of putamen and globus pallidus volumes in the ADHD and OCD diagnostic groups. The finding of elevated titers associated with ADHD raises the question of whether outcomes in previous studies reporting associations between elevated antibodies and OCD may have been affected by the presence of comorbid ADHD. Pursuing an interest in investigating potential volumetric abnormalities related to limbic-hypothalamicpituitary-adrenal axis abnormalities in OCD, MacMaster and colleagues (2006) used mMRI to investigate pituitary volumes in pediatric patients with OCD versus healthy controls. They found smaller pituitary volume in boys with OCD versus healthy boys, which was inversely correlated with compulsive behavior severity. Two studies have examined the effect of treatment on thalamic volumes in children with OCD. Gilbert and colleagues (2000) reported enlarged thalamic volumes in 21 drug-naïve children with OCD when compared to 21 case-matched controls, consistent with the group’s earlier report with a smaller sample (Rosenberg et al., 1997). Ten of these 21 patients with OCD underwent repeat mMRI studies posttreatment with 12 weeks of paroxetine monotherapy. Paroxetine treatment was associated with a significant decrease in thalamic volume (19%) and was associated with improvement in OCD symptoms. In a study by the same group (Rosenberg, Benazon, et al., 2000) employing cognitive-behavioral therapy (CBT) as the treatment in a similar 12-week design, 11 drug-naïve children with OCD, aged 8–17, underwent mMRI studies before and after treatment. Although these children demonstrated significant overall improvement in their OCD symptoms (30% reduction), unlike the investigators’ earlier study employing paroxetine treatment, the authors did not find a positive response to CBT to be associated with significant change in thalamic volume. This suggests that reductions in thalamic size in response to treatment

43: NEUROIMAGING STUDIES

may be specific to selective serotonin reuptake inhibitor (SSRI) treatment and not necessarily directly related to treatment response. In summary, although there has been a recent growth in the number of structural brain imaging studies in OCD, these studies have not consistently demonstrated volumetric differences which could be considered pathognomonic for OCD. Differing results may be due to methodology (region-of-interest [ROI] vs. voxel-based morphometry [VBM] ROI vs. VBM approaches) and/or heterogeneity in OCD samples. Functional Imaging Findings A convergence of data from a majority, but not all (Crespo-Facorro et al., 1999), neutral-state paradigm studies employing PET and SPECT indicates that patients with OCD exhibit elevated regional brain activity within OFC and ACC in comparison with normal controls (Baxter et al., 1987; Baxter et al., 1988; Nordahl et al., 1989; Swedo et al., 1989; Machlin et al., 1991; Rubin et al., 1992; Alpetkin et al., 2001); however, decreased activity has been reported in the dorsal posterior cingulate cortex (Saxena et al., 2004). A metaanalysis reconciled these apparently inconsistent findings with regard to OFC results in OCD (Milad and Rauch, 2007); specifically, elevated OFC activity is consistently observed in anterior and lateral portions of OFC whereas findings of decreased OFC activity have been confined to posteromedial regions. This is consistent with a model whereby anterolateral OFC mediates negative cognitions (obsessions), whereas the posteromedial OFC plays a critical role in extinction capacity (see Milad and Rauch, 2007) Increased activity in the thalamus has also been reported in several neutralstate studies (Swedo et al., 1989; Perani et al., 1995; Alpetkin et al., 2001; Saxena et al., 2001). Observed differences in regional activity within the caudate nucleus have been less consistent (Baxter et al., 1987; Baxter et al., 1988; Rubin et al., 1992). Findings from functional imaging studies focusing on treatment effects (Benkelfat et al., 1990; Hoehn-Saric et al., 1991; Baxter et al., 1992; Swedo et al., 1992; Perani et al., 1995; J.M. Schwartz et al., 1996; Saxena et al., 1999; Hoehn-Saric et al., 2001; Hansen et al., 2002; Saxena et al., 2002; Diler et al., 2004; Ho Pian et al., 2005) suggest that attenuation of abnormal regional brain activity within OFC, ACC, and caudate nucleus is associated with symptomatic improvement. Interestingly, similar changes have been observed with pharmacological and behavioral therapies (e.g., Baxter et al., 1992; J.M. Schwartz et al., 1996). Of note, the magnitude of frontal cortical activity prior to treatment has been found to predict the treatment response, with lower pretreatment OFC metabolism associated with better serotonin reuptake inhibi-

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tor (SRI) response (Swedo et al., 1992; Brody et al., 1998; Saxena et al., 1999; Rauch et al., 2002). Decreased regional brain activity in the right caudate (Baxter et al., 1992; J.M. Schwartz et al., 1996; Saxena et al., 1999; Saxena et al., 2002; Diler et al., 2004) and the thalamus (Baxter et al., 1992; Saxena et al., 2002; Ho Pian et al., 2005) have also been associated with treatment response in OCD. In summary, the brain changes best correlated with OCD treatment response are attenuation of activity in the OFC, right caudate, and thalamus. Given the explosion of functional imaging studies in OCD utilizing symptom provocation and emotional stimuli techniques, a complete review of these studies is outside of the scope of this chapter. Results of these studies are briefly summarized in Table 43.1. Overall, functional imaging studies employing symptom provocation have fairly consistently reported increased brain activity within anterior/lateral OFC, thalamus, and caudate. This includes studies employing PET (McGuire et al., 1994; Rauch et al., 1994) as well as functional MRI (Breiter et al., 1996; Adler et al., 2000; Chen et al., 2004; Mataix-Cols et al., 2004) techniques. Response to symptom provocation in the cingulate cortex varies across studies. About half of studies have reported increased cingulate activation in OCD versus healthy control subjects during symptom provocation. Comparison of these results with those from studies of other anxiety disorders suggests that anterior/lateral orbitofrontal and caudate activation is relatively specific to OCD, whereas activation of posteromedial orbitofrontal and ACC may be a nonspecific marker of anxiety, often observed in other anxiety disorders and in normal anxiety states (Rauch and Baxter, 1998). Various cognitive activation paradigms have also been employed in the study of OCD, with the intention of targeting specific brain regions of interest. These cognitive activation paradigms have focused in two areas: memory/learning and response inhibition. Rauch and colleagues (Rauch et al., 1997a; Rauch, Whalen, Curran, et al., 2001) employed an implicit (that is, nonconscious) learning paradigm shown to reliably recruit striatum (Rauch, Savage, Brown, et al., 1995; Rauch, Whalen, Savage, et al., 1997). Findings from the first study using PET (Rauch et al., 1997a) were later replicated in a second study using fMRI (Rauch, Whalen, Curran, et al., 2001). Consistent across these two studies was a failure of patients with OCD to normally recruit striatum, instead activating medial temporal regions typically associated with conscious information processing. This occurred despite normal performance by the patients with OCD on the learning task, suggesting that temporal cortex activation is actively compensating for deficits within the frontal cortical-striatothalamo-frontal cortical circuitry. Following on these first studies, other groups have also demonstrated fail-

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43.1 Summary of Functional Neuroimaging Findings in OCD

Paradigm Employed Neutral state

Identified Areas of Elevated Metabolism, CBF or BOLD Signal

Identified Areas of Decreased Metabolism, CBF or BOLD Signal

OFC, ACC

References Alpetkin et al., 2001 Baxter et al., 1987; Baxter et al., 1988 Diler et al., 2004 Machlin et al., 1991 Nordahl et al., 1989 Perani et al., 1995 Rubin et al., 1992 Swedo et al., 1989

thalamus

Alpetkin et al., 2001 Perani et al., 1995 Saxena et al., 2001 Swedo et al., 1989

Symptom provocation

OFC, caudate, thalamus

Adler et al., 2000 Breiter et al., 1996 Chen et al., 2004 Mataix-Cols et al., 2004 McGuire et al., 1994 Rauch et al., 1994 Shapira et al., 2003

Cognitive tasks: • Implicit learning paradigm

Medial temporal cortex

Lack of normal striatal activation

Rauch, Savage, et al., 1997; Rauch, Whalen, Curran, et al., 2001

• Word generation

OFC

Lack of OFC suppression at rest

Pujol et al., 1999

Lack of L caudate activation

Fernandez et al., 2003

• Tower of Hanoi • Response-conflict task

ACC

Ursu et al., 2003

• Spatial N-back task

ACC

Van der Wee et al., 2003

• Interference task

Rostral ACC

Fitzgerald et al., 2005

• Go/No-Go task

Rostral & caudal ACC, OFC

Maltby et al., 2005

• Stroop task

ACC, R caudate

Nakao et al., 2005

DLPFC, caudate

Van der Heuvel et al., 2005a

• Tower of London task

ACC

• Stroop task

Amygdala, L hypothalamus

Van der Heuvel et al., 2005b

• Conflict task

ACC, L parietal

Viard et al., 2005

OFC: orbitofrontal cortex; ACC: anterior cingulate gyrus; AMCC: anterior-medial cingulate gyrus; PCC: posterior cingulate gyrus; DLPFC: dorsolateral prefrontal cortex; CBF: cerebral blood flow; BOLD: blood oxygen level dependent; OCD: obsessive-compulsive disorder.

ure of activation of the striatum in patients with OCD during tasks of learning and memory involving planning and sequencing (A. Fernandez et al., 2003; Van den Heuvel et al., 2005b). Other groups have employed cognitive paradigms and fMRI to study cognitive interference and response inhibition in OCD. Results of these studies suggest that overactivity in the anteriormedial cingulate cortex in patients with OCD may reflect heightened error monitoring and heightened conflict monitoring in this population (Ursu et al., 2003; Fitzgerald et al., 2005; Maltby et al., 2005; Viard et al., 2005). In a study employing emotional and color Stroop tasks, van den Heuvel and colleagues (2005a)

demonstrated that greater interference by OCD-related words was associated with increased activity in the dorsal anterior cingulate in patients with OCD versus healthy controls. In addition, OCD-related word naming elicited greater amygdalar and hypothalamic activation in the OCD group when contrasted with neutral words. Imaging Studies of Neurochemistry, Neurotransmitter, and Neuroreceptor Imaging Magnetic resonance spectroscopy studies in OCD have reported neurochemical abnormalities in several of the brain regions central to neuroanatomical models of

43: NEUROIMAGING STUDIES

OCD: striatum, thalamus, and ACC. Ebert and colleagues (1997) reported relatively reduced NAA resonance (a marker of healthy neuronal density) in right striatum and ACC in 12 patients with OCD in comparison with 6 healthy controls. Similarly, Bartha and colleagues (1998) found reduced left striatal NAA concentrations in 13 patients with OCD versus 13 matched controls. Rosenberg et al. (2001) studied 11 children, aged 8–15, with OCD and 11 healthy case-matched controls using MRS. They found a significant bilateral increase in cytosolic Cho in the medial thalami of the children with OCD versus the control group, with no between-group differences in NAA or Cr signals in this region. Russell and colleagues (2003) reported abnormalities in NAA and Cr in the dorsolateral PFC. Results of the adult studies of MRS-NAA are convergent with those from mMRI studies; reduced NAA is consistent with primary pathology within the striatum associated with subtle volumetric abnormalities or reductions in measures of healthy neuronal density. Several studies have reported the reduction of elevated glutamate and glutamine (Glx) in the caudate in response to SRI treatment (Moore et al., 1998; Rosenberg, MacMaster, et al., 2000; Bolton et al., 2001), whereas CBT did not result in Glx reductions (Benazon et al., 2003). These findings are consistent with the model of OCD suggesting orbitofrontal hyperactivity, mirrored by elevated glutamate at the site of glutamatergic projections from OFC to the striatum, which is attenuated by successful SRI treatment. Studies in OCD examining neurotransmitter and receptor dysfunction have focused on the serotonin and dopamine (DA) systems. Results have been somewhat contradictory, with some (Stengler-Wenzke et al., 2004; Hesse et al., 2005), but not all (Simpson et al., 2003), studies reporting decreased serotonin transporter availability in the brain stem and midbrain in patients with OCD versus healthy controls. Adams and colleagues (2005) reported increased 5-HT2A receptor binding in the caudate in patients with OCD. Results from studies of the DA system in OCD have also been contradictory. To date, studies have reported increased DA transporter (DAT) density (C.-H. Kim et al., 2003; van der Wee et al., 2004), and decreased DAT density (Hesse et al., 2005) in the basal ganglia of patients with OCD. Reduced D2 receptor binding has been reported in the caudate in OCD (Denys et al., 2005). Summary Dysregulation of activity in the orbitofrontal-caudate pathway within the cortico-striato-thalamo-cortical circuitry has been identified in OCD and appears to be specific to this disorder. In particular, elevated activity in anterolateral OFC may be central to obsessions. It should be noted that abnormal activity of the paralim-

709

bic cortex, including ACC, has been implicated in several anxiety disorders, and these regions are believed to mediate nonspecific aspects of the anxious state. Likewise, diminished activity in posteromedial OFC may be a common feature of anxiety disorders. Primary striatal pathology is also suggested in OCD by results from mMRI studies showing reduced striatal volume, as well as MRS results of reduced striatal NAA signal. In the provoked symptomatic state, hyperactivity within OFC is consistently identified in OCD. In addition, in normal patients, the performance of repetitive motor routines does facilitate striatal recruitment in the service of thalamic gating, a pattern that does not occur in patients with OCD. In summary, data from structural, functional, and neurochemical imaging studies support a working model of striatal pathology and striato-thalamic inefficiency, together with anterolateral orbitofrontal hyperactivity. And of possible clinical relevance, the magnitude of orbitofrontal hyperactivity in OCD predicts response to treatment, with lesser activity correlated with a better response to SRIs.

POSTTRAUMATIC STRESS DISORDER Neuroanatomical Model of Posttraumatic Stress Disorder (Amygdalocentric Model) Here we briefly summarize a neurocircuitry model of PTSD (Rauch, Shin, Whalen, et al., 1998; Rauch et al., 2006) that emphasizes the amygdala’s central role in directing an individual’s response to perceived danger through its reciprocal connections with the hippocampus, medial prefrontal cortex (PFC), and other cortical areas associated with higher cognitive functions. This model hypothesizes hyperresponsivity within the amygdala to threat-related stimuli, with inadequate topdown governance over the amygdala by ventral/medial PFC (including the rostral ACC, medial PFC, subcallosal cortex, and OFC) and the hippocampus (Fig. 43.2). This hyperresponsivity of the amygdala mediates symptoms of hyperarousal and may explain the indelible quality of the emotional memory of the traumatic event. Activity in the ventral/medial PFC has been linked to habituation to repetitive stimuli in which there is no imminent threat. Inadequate influence by ventral/medial PFC on the amygdala is believed to be responsible for the lack of habituation that characterizes PTSD, as well as the capacity to suppress attention and response to trauma-related stimuli. Another hallmark of PTSD, the overgeneralization of fear responding to nonthreatening stimuli, is associated with decreased hippocampal function. Abnormal hippocampal input is thus believed to result in deficits in identifying safe versus threatening contexts, as well as accompanying explicit memory difficulties (Bremner et al., 1995). Functional

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ANXIETY DISORDERS

43.2 Schematized neuroanatomical model of posttraumatic stress disorder indicating critical pathways in threat assessment and responding. ACad: affective division of the anterior cingulate; AMYG: amygdala. FIGURE

neuroimaging findings in PTSD also suggest that in threatening situations, patients with PTSD reallocate neural resources to regions that mediate fear responding at the expense of cortical areas mediating higher cognitive functions. This model might be viewed as fear conditioning gone awry, with a lack of appropriate habituation and extinction and a lack of contextual discrimination. The pathogenesis of PTSD can be conceptualized as a fear conditioning process that is superimposed on some diathesis, which might involve a predisposition to amygdala hyperresponsivity, lack of sufficient functional connectivity between the anterior cingulate and the amygdala, hippocampal deficiency, and/or exaggerated susceptibility to stress. In fact, current theories suggest that damage to or sensitization of this system may be a consequence of prior exposure to stress. In this model, chronic PTSD is a result of progressive deterioration of function within this amygdala-based system. Structural Imaging Findings The focus of mMRI studies of PTSD has been primarily the hippocampus, a brain structure known to be susceptible to stress-induced damage via the action of glucocorticoids and excitatory amino acids. In the first study to examine relative hippocampal volumes in PTSD using mMRI techniques, Bremner and colleagues (1995) studied 26 Vietnam combat veterans with PTSD and 22 civilian comparison subjects. They found that right hippocampal volumes were 8% smaller in the PTSD group than in the control group, and this difference

persisted when years of education and alcohol abuse were considered as covariates. Of note, the mean left hippocampal volume was also smaller (3.8%) in the PTSD group versus the comparison group, although this difference did not achieve statistical significance. On a task measuring verbal performance, the patients with PTSD performed more poorly than the controls, and their percent retention scores on this test directly correlated with right hippocampal volume (that is, lower scores were associated with smaller right hippocampal volumes). Pavic and colleagues (2007) reported similar findings of reduced right hippocampal volumes in patients with PTSD versus healthy controls in a group of 15 war veterans with combat-related chronic PTSD. To compare the relative contribution of combat exposure to hippocampal structural change, Gurvits and colleagues (1996) studied three groups of individuals using mMRI: seven Vietnam combat veterans with PTSD, seven Vietnam combat veterans without PTSD, and eight nonveterans without PTSD. They found significantly smaller hippocampal volumes bilaterally in the PTSD group compared with the combat-exposed and civilian control cohorts. These findings withstood adjustments for age, total brain volume, and lifetime alcohol consumption. There were no significant differences in hippocampal volume between the two control groups. Interestingly, when the 14 combat-exposed veterans were examined together, total hippocampal volume was inversely correlated with the extent of combat exposure and PTSD symptom severity. In a carefully controlled study examining pairs of Vietnam combat veterans and their noncombat-exposed identical twins, Pitman and colleagues (2006) attempted to tease out whether decreased hippocampal volume represents a preexisting vulnerability to develop PTSD or whether it results from trauma exposure. They reported that decreased hippocampal volume and the presence of abnormal cavum septum pellucidum were present in combat veteran twins with PTSD and their unexposed twins, compared to combat veterans without PTSD and their unexposed twins, suggesting that these structural abnormalities represent vulnerability factors for the development of PTSD. Similar to the negative results of mMRI studies of children and adolescents with OCD, results of pediatric studies of PTSD differed from those of adult trauma studies in that investigators failed to find differences in hippocampal volumes between patients with PTSD and healthy controls. Four recent studies investigated potential brain alterations in children and adolescents with PTSD (De Bellis et al., 1999; De Bellis et al., 2001; De Bellis et al., 2002; Carrion et al., 2001). In a crosssectional study, De Bellis et al. (1999) measured hippocampal volumes in 44 children who were maltreated and adolescents with PTSD and in 61 age-matched controls. The children with PTSD did not show significant

43: NEUROIMAGING STUDIES

differences in hippocampal volume compared with healthy controls; however, the patients with PTSD had smaller total brain and cerebral volumes. Of note, brain volume correlated positively with age of onset of PTSD trauma, with the children who experienced traumatic stress at the youngest ages exhibiting the smallest brain volumes. In addition, brain volume was negatively correlated with duration of abuse. Because hippocampal volume is known to increase in children before puberty and then decrease in the postpubertal period, De Bellis and colleagues (2001) conducted a second study to longitudinally examine brain volume changes in nine prepubertal patients with maltreatment-related PTSD and in an equal number of matched healthy controls who were yoked to the patients with PTSD on several variables including age, Tanner developmental stage, and length of time between scans. Subjects underwent mMRI at baseline (prepuberty) and at least 2 years later (late stages of puberty). The investigators hypothesized that childhood trauma would affect hippocampal growth during puberty, and that as a result, the PTSD groups would show greater reductions in hippocampal volume over time than the matched controls. However, they found no significant differences in hippocampal, amygdala, or temporal lobe volumes either at baseline or at follow-up, and there were no differences in volumes between groups across time and pubertal development. Carrion et al. (2001) used mMRI to measure brain volumes in a sample of 24 children and adolescents with a history of trauma and PTSD symptoms (50% of the sample had a formal diagnosis of current PTSD). The MRI scans of these 24 children were compared to 24 age- and gender-matched controls’ MRI scans from an archived sample of children with no psychopathology and normal development. The children with a history of trauma exposure had smaller total brain and cerebral volumes than the control group. Of note, the PTSD group did not demonstrate the typical frontal lobe asymmetry (right/left) seen in the control group, instead manifesting symmetrical frontal lobes. Although hippocampal volume was reduced in the PTSD group, this finding was not significant when corrected for total brain volume. Directed by findings of superior temporal gyrus event– related potential abnormalities in adult patients with PTSD, De Bellis and colleagues (2002) performed a volumetric study of this region, implicated in verbal and nonverbal auditory processing, in a pediatric sample with PTSD. The comparison of 43 children and adolescents who were maltreated with PTSD with 61 healthy controls demonstrated larger superior temporal gyrus volumes in the patients with PTSD associated with a loss of the normal asymmetry pattern. The authors concluded that these alterations may be due to abnormal developmental changes in this maltreated sample with

711

pediatric PTSD. Other studies’ findings support the idea that, in children, trauma exposure and the development of PTSD may hinder the normal development of the cerebellum, which is known to play a role in cognitive development. In a study of children with maltreatment-related PTSD, right, left, and total cerebellar volumes were smaller in patients with PTSD than in the control groups of children with generalized anxiety disorder and healthy children who were nonabused (De Bellis and Kuchibhatla, 2006). Overall, the sum of the findings from these pediatric PTSD studies suggests a more generalized effect of traumatic stress in early development, affecting not just hippocampal, but also total brain volume. One potential area of exception, where a specific effect has been demonstrated, is within the superior temporal gyrus. Contrary to the pediatric findings, in mMRI studies of adults with PTSD resulting from childhood abuse, investigators have reported hippocampal volumetric differences similar to those found in studies examining samples with PTSD resulting from traumatic exposure in adulthood. Bremner and colleagues (1997) studied 17 adult survivors of childhood sexual and/or physical abuse with PTSD and 21 healthy comparisons with no reported history of childhood abuse. The patients with PTSD had 12% smaller left hippocampal volumes than the control group. Stein and colleagues (1997) studied hippocampal volume in 21 adult survivors of childhood sexual abuse (most of whom had PTSD) and a control group of 21 adults who reported no childhood history of abuse. They reported 5% smaller left hippocampal volumes in the abused cohort. Of note, total hippocampal volume in patients with PTSD was negatively correlated with PTSD symptom severity. In a related study, Driessen et al. (2000) measured hippocampal and amygdala volumes in 21 women with borderline personality disorder (BPD), most of whom had reported histories of early trauma, and in 21 healthy women with no psychiatric histories. They found that the patients with BPD had smaller hippocampal and amygdalar volumes than the control group. Interestingly, hippocampal volume was negatively correlated with the degree and duration of early trauma only when the patients with BPD and controls were examined together. A meta-analysis of structural brain abnormalities in PTSD (Karl et al., 2006) confirmed that patients with PTSD have significantly smaller hippocampal volumes compared to controls with and without a history of trauma exposure. The authors highlighted that several factors influence outcome in structural neuroimaging studies, including imaging methodology, symptom severity, medication exposure, and age and gender. Results of this meta-analysis suggest that hippocampal volume differences correlate with PTSD severity, and that these differences may not be evident until adulthood.

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ANXIETY DISORDERS

Other areas of structural investigation in PTSD include the ACC, caudate, and cerebellum. Rauch and colleagues (2003) reported selective reductions in the rostral ACC and subcallosal cortex in trauma-exposed women with PTSD when compared with trauma-exposed women without PTSD, supporting the importance of these structures in prevailing neurocircuitry models of PTSD. Cohen and colleagues (2006) reported that exposure to traumatic adverse childhood events among adults without psychopathology correlated with reduced anterior cingulate and caudate volumes, which may represent the effects of early life stress on brain development. Interestingly, one study reported possible shape differences in the anterior cingulate in PTSD (Corbo et al., 2005). In addition, PTSD severity has been found to be inversely correlated with anterior cingulate volume (Yamasue et al., 2003; Woodward et al., 2006). In response to several functional neuroimaging studies demonstrating involvement of the cerebellar vermis in PTSD, Levitt and colleagues (2006) examined the volume of the cerebellar vermis using mMRI in a group of veterans discordant for combat exposure in Vietnam. They found no significant structural differences of the cerebellar vermis in veterans with combat-related PTSD versus veterans with no PTSD. In summary, most but not all (Jatzko et al., 2006) studies of adult patients with PTSD with either childhood or adult traumatic exposure support an association between reduced hippocampal volume and PTSD. However, the negative findings reported in pediatric studies suggest that hippocampal atrophy may develop progressively over time. In support of the hypothesis that the maintenance of chronic PTSD symptoms is required to affect hippocampal volumes, studies of patients with new-onset PTSD have not reported reduced hippocampal volumes (Bonne et al., 2001, Notestine et al., 2002). Several studies have reported decreased frontal cortex volumes in PTSD, with the anterior cingulate in particular noted to be reduced in patients with PTSD when compared to trauma-exposed controls. However, lingering questions regarding the effects of acute versus prolonged exposure to trauma and the age at which trauma exposure occurs remain to be answered. Functional Imaging Findings The literature reporting on functional imaging in PTSD is rapidly expanding (see Lanius et al., 2005; Liberzon and Martis, 2006; Shin et al., 2006, for reviews). Although there is some heterogeneity in these reports, certain findings are fairly consistent and point to many of the same areas implicated in neuroanatomical models of anxiety based on fear conditioning: the amygdala, hippocampus, anterior cingulate and orbitofrontal cortices, and related frontal cortical areas. Functional

imaging studies in PTSD have been conducted during resting, so-called neutral states, and by employing several different provocation paradigms: (1) external trauma reminders, (2) script-driven imagery, (3) pharmacological challenge, (4) cognitive tasks, and (5) auditory performance tasks. In the first study to employ a script-drive imagery paradigm to induce PTSD symptoms while acquiring functional images, Rauch and colleagues (1996) studied a mixed-gender cohort of patients with PTSD using PET under neutral versus provoked conditions. Patients with PTSD exhibited increased regional cerebral blood flow (rCBF) within right orbitofrontal, insular, anterior temporal, and visual cortex, as well as ACC and the right amygdala in response to symptom provocation. Decreases in rCBF were observed within left inferior frontal (Broca’s area) and left middle temporal cortex. Although conclusions from this study are limited by the lack of a comparison group, the areas of increased versus decreased activity during symptom provocation are consistent with the model of shunting of CBF to limbic areas involved in fight/flight responding at the expense of cortical areas mediating higher cognitive functions. The need for controlled studies was emphasized by Fischer and colleagues (1996), who studied individuals exposed to the emotional stress of an armed bank robbery who did not go on to develop PTSD. Using PET, rCBF measurements were made during a provoked condition, while individuals watched an actual security videotape of the robbery, and during a control condition, while they watched a neutral videotape of park scenes. In the exposure versus control contrast, the authors also found rCBF increases within orbitofrontal and visual cortex, as well as within posterior cingulate cortex. In addition, rCBF decreases were noted in a variety of regions, including Broca’s area. Results of this study suggest that individuals with PTSD and psychiatrically healthy controls may demonstrate similar patterns of brain activity in response to stimuli reminiscent of emotionally traumatic events. This early work established the groundwork for the more formal, controlled comparisons to follow. Since the time of these initial studies, a growing body of controlled functional imaging studies in PTSD has been reported. The major findings of these studies are highlighted in Table 43.2. Among studies employing symptom provocation paradigms, brain areas demonstrating the greatest relative differences in PTSD versus controls are the amygdala, anterior cingulate, and areas of the frontal cortex (Bremner et al., 1997; Bremner, Narayan, et al., 1999; Bremner, Staib, et al., 1999; Britton et al., 2005; Liberzon et al., 1999; Zubieta et al., 1999; Pissiota et al., 2002; Rauch et al., 1996; Shin et al., 1997; Shin et al., 1999; Lanius et al., 2001; Osuch et al., 2001; Lanius et al., 2002; Lanius et al., 2003; Shin et al., 2004; Phan, Britton, et al., 2006).

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713

43.2 Summary of Functional Neuroimaging Findings in PTSD

Paradigm Employed Combat script-driven imagery or external trauma reminders

Identified Areas of Elevated Metabolism, CBF or BOLD Signal amygdala, sensorimotor cortex, periaqueductal gray

Identified Areas of Decreased Metabolism, CBF or BOLD Signal ACC, inferior frontal gyrus (Broca’s area), medial PFC hippocampus

References Rauch et al., 1996 Shin et al., 1997 Liberzon et al., 1999 Bremner, Narayan, et al., 1999a Pissiota et al., 2002 Shin et al., 2004 Britton et al., 2005

Noncombat script-driven imagery or external trauma reminders

PCC, orbitofrontal cortex, amygdala

ACC, thalamus, hippocampus Medial PFC, inferior frontal gyrus (Broca’s area)

Bremner, Staib, et al., 1999b Lanius et al., 2001 Shin et al., 1999 Gilboa et al., 2004 Protopopescu et al., 2005

Symptom provocation (Pharmacologic challenge)

hippocampus, PFC

Bremner et al., 1997

Cognitive task

ACC

Shin et al., 2001

Non-trauma-related emotional image processing

Medial PFC

Phan et al., 2006

Emotional facial expressions: Fearful vs. happy (masked)

Rauch, Whalen, Shin et al., 2000

Amygdala

Armony et al., 2005 Fearful vs. neutral (explicit)

Left amygdala

ACC, Medial PFC

Williams et al., 2006

Fearful vs. happy (explicit)

Amygdala

Medial PFC

Shin et al., 2005

OFC: orbitofrontal cortex; ACC: anterior cingulate gyrus; PCC: posterior cingulate gyrus; PFC: prefrontal cortex; CBF: cerebral blood flow; BOLD: blood oxygen level dependent.

Heightened amygdala activity has been reported in patients with PTSD in response to symptom provocation using various script-driven and trauma cue paradigms (Rauch et al., 1996; Shin et al., 1997; Liberzon et al., 1999; Pissiota et al., 2002; Shin et al., 2004; Protopopescu et al., 2005). Shin and colleagues (1997) studied patients with combat-related PTSD and matched trauma-exposed controls without PTSD in a PET cognitive activation paradigm. Subjects were required to make judgments about pictures from three categories: neutral, general negative, and combat-related. The paradigm also entailed two types of tasks: one involved responding while actually seeing the pictures (perception), and the other involved responding while recalling the pictures (imagery). The PTSD group showed several areas of significant rCBF change not seen in the controls: increased rCBF was found within the right amygdala and ACC during the combat imagery versus comparison conditions, and decreased rCBF was found within left inferior frontal cortex (Broca’s area) for the combat perception versus negative perception contrast. These findings closely paralleled results from the PTSD symptom provocation study of Rauch et al. (1996). In a PET-

CBF study of seven patients with PTSD resulting from trauma experienced in wars within the past decade, Pissiota et al. (2002) used traumatic war-related sounds to provoke symptoms of PTSD during scanning. When contrasting traumatic and neutral sound exposure, the investigators demonstrated greater activation in the right amygdala, right sensorimotor areas/sensory cortex, primary and supplementary motor cortices, cerebellar vermis, and periaqueductal gray during the traumatic condition. Activation of these motor and sensorimotor areas, the cerebellum, the amygdala, and the PAG is consistent with a functional circuitry coordinating motor preparedness in response to threatening emotional sensory inputs. Using fMRI techniques, Rauch, Whalen, Shin, et al. (2000) studied eight men with combat-related PTSD and the same number of combat-exposed controls using a backward-masking technique employing exposure to fearful, neutral, and happy facial expressions. In comparison to the control group, the patients with PTSD exhibited significantly greater activation of the amygdala during the masked-fearful versus masked-happy exposures. In addition, fMRI signal intensity change in the amygdala in response to the fearful versus happy

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contrast correlated with the severity of PTSD symptoms as measured by the Clinician Administered PTSD Scale (CAPS). Lack of significant medial prefrontal recruitment during this task suggests that amygdalar differences between the groups were occurring independently of frontal cortical input. Although the findings are not completely consistent, the majority of neuroimaging studies in PTSD have reported no significant response or diminished activation in the ACC (Bremner, Narayan, et al., 1999; Bremner, Staib, et al., 1999; Shin et al., 1999; Semple et al., 2000; Shin et al., 2001; Britton et al., 2005). Attenuation of the ACC and ventral prefrontal cortical areas has been shown in patients with PTSD traumatized by sexual abuse (Bremner, Narayan, et al., 1999; Shin et al., 1999) and by combat exposure (Bremner, Staib, et al., 1999). Shin and colleagues (2001) designed a study to specifically test the functional integrity of the ACC in patients with PTSD using an Emotional Counting Stroop task, a reliable means of recruiting the anterior cingulate in healthy, nonpsychiatric patients. Eight combat veterans with PTSD and eight combat-exposed veterans were studied with fMRI under three separate conditions in which they counted combat-related, generally negative, and neutral words. The PTSD group failed to activate rostral ACC in the combat versus general negative word conditions, while the non-PTSD group exhibited significant rostral ACC activation. Whalen, Bush, and colleagues (1998) proposed that activation of rostral anterior cingulate may play a regulatory role in processing emotional stimuli so as not to impair competing task performance. Similar results were recently reported by Lanius and colleagues (2001) using fMRI and a high field strength (4 Tesla) magnet with superior resolution. Using a symptom provocation paradigm with scripted imagery to study patients with noncombat-related PTSD, they found brain activation to be lower in the PTSD group versus the control group in the anterior cingulate, medial frontal cortex (BA 11), and thalamus. The authors hypothesized that the differential thalamic activation may be related to disruption in sensory processing at the level of the thalamus and/or disruption of the relay of sensory information from the thalamus to other subcortical structures. Although the majority of studies have found that PTSD patients fail to recruit anterior cingulate during provoked conditions, this finding is not completely consistent. In the Pissiota study described above, the investigators found no significant difference in anterior cingulate activity between the neutral and provocation conditions (Pissiota et al., 2002). Liberzon and colleagues (1999) used SPECT to study Vietnam veterans with and without PTSD, as well as a group of controls with no history of combat exposure. They contrasted the brain activation profiles associated with exposure

to auditory combat stimuli versus white noise. Although all three groups showed increased rCBF in anterior cingulate and middle prefrontal gyrus, only the PTSD group exhibited significant activation of the left amygdala/ nucleus accumbens region. Osuch and colleagues (2001) suggested that some of the differences in reported findings in symptom provocation studies in PTSD may be attributable to the presence or absence of flashbacks, episodes of intense reexperiencing of trauma imagery. They used PET to study a mixed-gender cohort of 12 treatment-unresponsive patients with PTSD at rest and after exposure to individually tailored trauma scripts. All patients were taking stable doses of antidepressants and/or benzodiazepines at the time of scanning. Eight patients, who had adequate data and reported experiencing flashbacks during the scanning, were included in the rCBF analyses. Positive correlations were reported between flashback intensity and left hippocampal, left inferior frontal, left somatosenory, and cerebellar cortices, brain stem, right insula, and right putamen. Flashback intensity was inversely correlated with bilateral superior frontal, fusiform, and medial temporal cortices. These results are consistent with several other studies showing relatively decreased superior frontal rCBF in PTSD versus control groups in response to symptom provocation paradigms (Rauch et al., 1996; Liberzon et al., 1999; Shin et al., 1999). Another approach to examining the functional neurocircuitry of PTSD is the use of trauma-unrelated affective stimuli such as emotional facial expressions. In response to fearful facial expressions, patients with PTSD show exaggerated responses in the amygdala (Rauch, Whalen, Shin, et al., 2000; Shin et al., 2005; Williams et al., 2006). Neutral auditory oddball paradigms and continuous performance tasks have also elicited exaggerated amgydalar activation in patients with PTSD versus healthy controls (Bryant et al., 2005; Semple et al., 2000). In summary, amygdalar hyperactivity and anterior cingulate hyporesponsivity have been identified as key features of the functional neurocircuitry of PTSD. Amygdala responsivity has been found to be positively correlated with PTSD symptom severity, whereas medial PFC responsivity has been shown to be inversely correlated. Imaging Studies of Neurochemistry In a preliminary study, Schuff and colleagues (1997) measured NAA using proton MRS imaging in seven veterans with PTSD and an equal number of nonveteran controls. Although they found a nonsignificantly smaller volume of the right hippocampus (6%) in the PTSD group versus the control group with mMRI, they found a more marked 18% reduction in right hippo-

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campal NAA with MRS. This study did not, however, control for level of alcohol abuse, a factor known to affect the volume of certain brain structures. To clarify the potential contribution of alcohol exposure, Schuff et al. (2001) conducted a second, larger study of 18 men with combat-related PTSD and 19 male comparisons. An attempt was made to control for alcohol exposure by including only men with no reported alcohol or drug abuse during the 5 years prior to scanning. In this larger sample, no significant difference in hippocampal volume was found between the groups; however, a bilateral reduction in NAA averaging 23% was reported in the men with PTSD compared to the controls. Creatine-containing compounds were also reduced in the right hippocampus of the men with PTSD. Two recent studies lend support to the hypothesis that hippocampal neuronal function may be compromised in PTSD. In a study of 26 subway fire survivors with PTSD compared with 25 age- and sex-matched controls, NAA levels were reduced in the bilateral hippocampi, as measured by proton MRS (Ham et al., 2007). N-acetylasparate (NAA) levels were negatively correlated with reports of reexperiencing symptoms of the traumatic event in the PTSD group. In another study examining the results of traumatic exposure to a major fire, Li and colleagues (2006) studied 12 patients with PTSD compared with 12 subjects exposed to the same trauma without developing PTSD. Using proton MRS, the NAA/Cr ratio was reduced in the left hippocampus of those patients with PTSD compared to those without. These metabolic changes suggest that aberrations in hippocampal neurochemistry may be present, affecting function, regardless of hippocampal volume loss in patients with PTSD. Following functional imaging studies implicating the ACC in the pathophysiology of PTSD, De Bellis et al. (2000) measured NAA concentration using proton MRS in the anterior cingulate of 11 children and adolescents with maltreatment-related PTSD and an equal number of matched comparisons. They found that the PTSD cohort exhibited relatively lower NAA/Cr ratios than the control group, concluding that neuronal integrity in the anterior cingulate may be altered in childhood PTSD. Ham and colleagues (2007) reported a similar finding of reduced NAA levels in the ACC of patients with PTSD surviving a subway fire, again suggesting reduced neuronal function in the ACC. In a study of women reporting a history of intimate partner violence and PTSD, an increase in Cho/Cr ratio in the ACC, suggestive of glial alterations, was found (Seedat et al., 2005). A limited number of investigations of neuroreceptor function in PTSD have been reported, focusing on the benzodiazepine/GABA and serotonin receptor systems. Bremner, Innis, Southwick, et al. (2000) measured benzodiazepine receptor binding in 13 patients with combat-

715

related PTSD and 13 case-matched controls. Subjects were studied with the radioligand [123I]iomazenil using SPECT, with distribution volume, a benzodiazepine receptor binding measure, as the outcome measure. Patients with PTSD showed a significant reduction (41%) in distribution volume in the PFC (BA 9) compared to healthy controls. No other brain regions demonstrated group differences of either increased or decreased binding. Although the finding of lower benzodiazepine binding in frontal cortex is consistent with animal studies showing decreased benzodiazepine binding in the same region in response to stress, it should be noted that a subsequent study also examining combat veterans failed to replicate this finding (Fujita et al., 2004). Bonne and colleagues (2005) examined the serotonin 5-HT1A receptor in PTSD using PET and found no significant differences in the 5-HT1A volume of distribution or binding potential between the PTSD and healthy comparison groups in any brain region. Lack of a finding for the 5HT1A receptor in PTSD differs from studies in panic disorder and social anxiety disorder (SAD), where reductions in 5-HT1A binding have been reported (Neumeister et al., 2004; Lanzenberger et al., 2007). Summary Taken together, imaging data from various studies support the current neurocircuitry model of PTSD that emphasizes the functional relationship between a triad of brain structures: the amygdala, hippocampus, and ventral/medial PFC. Morphometric MRI studies show decreased hippocampal volume, which is convergent with MRS findings of decreased NAA in the hippocampus. Functional studies indicate a rightward shift in hippocampal activity at rest. When exposed to reminders of traumatic events, patients most consistently appear to recruit anterior paralimbic regions as well as the amygdala, while exhibiting decreased activity within other heteromodal cortical areas. In comparison with controls, however, patients with PTSD exhibit diminished anterior cingulate activation, and morphometric MRI studies suggest that anterior cingulate volume may be reduced in PTSD.

PANIC DISORDER Neuroanatomical Models of Panic Disorder Pathophysiological models of PD are as disparate as the methods used to provoke panic attacks in neurobiological challenge studies (Coplan and Lydiard, 1998). Proposed models have emphasized a number of widely varied factors including dysregulated ascending noradrenergic and/or serotonergic systems, abnormal responsivity to CO2 at the level of brain stem (so-called false

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suffocation alarm), global cerebral abnormalities in lactate metabolism, and abnormalities in the hippocampalamygdalar circuitry. Perhaps the greatest challenge to investigators has been to provide a satisfactory model to explain the occurrence of spontaneous panic attacks. By contrast, the behavioral sequelae of recurrent panic attacks, such as agoraphobic avoidance, are more readily explained by learning theory and the fear conditioning model. Abnormal regulation of homeostasis in the fear neurocircuitry, due to either aberrant modulation by monoamine systems or aberrant processing of sensory and/ or biochemical information, might lead to spontaneous recruitment of the normal anxiety/fear circuitry, resulting in a spontaneous panic attack as an aberrant event. Another possibility is that panic attacks evolve in the context of what should be minor anxiety episodes because of failures in constraint by systems responsible for limiting anxiety responding. Similar to the previously discussed model of PTSD, hippocampal deficits might underlie such a mechanism in the case of PD. Finally, panic episodes that are described as spontaneous, without an identifiable precipitant, might in fact be anxiety responses to unconscious stimuli, and therefore the anxiety circuitry is being recruited without conscious awareness. Because it is now established that activation of the subcortical amygdalar circuit described by LeDoux (1996) occurs in the absence of conscious awareness that a threat-related stimulus has been presented (e.g., Whalen, Rauch, et al., 1998), this is another possible explanation for the occurrence of spontaneous panic episodes (Fig. 43.3). In summary, PD might be characterized by fundamental amygdala hyperresponsivity to subtle (even unconscious) environmental cues,

CORTEX Medial prefrontal

Cingulate

Insula

AMYGDALA

S E N S O R Y

Lat CNA

Hippocampus Basal

T H A L A M U S

SENSORY, VISCERAL STIMULI

PBN Hypothalamus LC Autonomic + Pituitary/Adrenal Activation

NTS

43.3 Pathways critical in fear conditioning, with relevance to preliminary models in panic disorder and social anxiety disorder. CNA: central nucleus of the amygdala; LC: locus ceruleus; NTS: nucleus of the solitary tract.

FIGURE

triggering full-scale, threat-related responding with insufficient top-down governance. Structural Imaging Findings Of the structural imaging studies reported in PD, an early qualitative study by Fontaine and colleagues (1990) examined the MRI scans of 31 consecutive patients with PD and 20 matched healthy controls. They found a higher frequency of gross structural abnormalities in the PD group (40%) compared with the control group (10%), with the most striking focal findings in the PD group being abnormal signal or asymmetric atrophy of the right temporal lobe. Vythilingam and colleagues (2000) published a quantitative mMRI study focusing on the temporal lobe and hippocampus of 13 patients with PD and 14 healthy comparisons. They found a significantly smaller mean volume of the temporal lobes in the PD group versus the comparison group, while finding no significant differences in hippocampal volume between the groups. In a more recent voxel-based morphometric study, patients with PD demonstrated significantly increased gray matter volume in the midbrain and brain-stem rostral pons in comparison to healthy controls, and a trend for decreased PFC volume (Protopopescu et al., 2006). These results support earlier proposed neuroanatomical models of panic disorder, hypothesizing panic attacks originating in brain-stem loci (Gorman et al., 1989; Gorman et al., 2000). Functional Imaging Findings Two studies have examined rCBF in patients with PD at rest. In an early neutral-state PET study, Reiman and colleagues (1986) studied 16 patients with PD and 25 normal controls. Of the 16 patients with PD, 8 had previously been determined to be sensitive to lactateinduced panic. This subset of patients with PD had abnormally low left/right ratios of parahippocampal blood flow at rest. Several years later, De Cristofaro et al. (1993) used SPECT to measure rCBF at rest in seven treatment-naive patients with PD and five age-matched healthy comparisons. The investigators found that the patients with PD exhibited greater rCBF in left occipital cortex and lower rCBF in the hippocampal area compared to the control group. In studies examining regional cerebral glucose metabolic rate (rCMRglu in patients with PD in neutral (unprovoked) states, Nordahl et al. (1990) used PET-FDG methods to measure (rCMRglu) in 12 patients with PD and 30 normal controls while they engaged in an auditory continuous performance task. The PD group exhibited a lower left/right hippocampal ratio compared to the healthy comparisons. In a later study including female subjects only, Bisaga et al. (1998) used PET-FDG to study six patients with PD and an equal number of

43: NEUROIMAGING STUDIES

matched controls. Differing from earlier studies, which found lower left-sided activity, the patients with PD in this study displayed elevated rCMRglu in the left hippocampus and parahippocampal area. In addition, the patients with PD demonstrated reduced rCMRglu in right inferior parietal and right superior temporal cortex. Four symptom provocation studies of PD have been published, three of which employed pharmacological challenges while the fourth employed anxiety situation imagery exposure. In an early provocation study, Stewart et al. (1988) used the xenon inhalation method in conjunction with SPECT to measure CBF in superficial cortical areas during lactate-induced panic. Ten patients with PD and five normal controls were studied during sodium lactate infusion and during saline infusion as a control measure. Six of the patients with PD and none of the controls experienced panic attacks in response to lactate infusion. The patients with PD who experienced lactate-induced panic attacks displayed global cortical decreases in CBF, while the patients with PD and healthy controls who did not panic exhibited global cortical increases in CBF during lactate infusions, the normal expected physiological response to an osmotic load. In another pharmacological challenge study employing yohimbine and SPECT, Woods et al. (1988) studied six patients with PD and an equal number of normal controls. Yohimbine administration increased anxiety and decreased rCBF in bilateral frontal cortex in the patients with PD versus the controls. In another study, Reiman et al. (1989) used PET methods to measure rCBF in 17 patients with PD and 15 normal controls during lactate infusions. The eight patients who panicked to lactate infusion exhibited rCBF increases in bilateral temporopolar cortex and bilateral insular cortex/claustrum/putamen relative to the normal controls and to the patients with PD who did not experience lactate-induced panic attacks. The finding of increased rCBF in the temporal poles was later attributed to extracranial artifact from muscular contractions (Drevets et al., 1992; Benkelfat et al., 1995). In the only published symptom provocation study using fMRI, directed imagery in neutral and high-anxiety situations was individually tailored for six patients with PD and six healthy controls. Imaging during exposure blocks revealed increased activity during high-anxiety versus neutral anxiety imagery in the patients with PD, but not the controls in the inferior frontal cortex, OFC, hippocampus, and anterior and posterior cingulate (Bystritsky et al., 2001). In a published case report, Fischer and colleagues (1998) captured a spontaneous panic attack during PET imaging. The neuroimaging profile revealed decreased rCBF in right orbitofrontal, prelimbic (area 25), anterior cingulate, and anterior temporal cortex during the acute event.

717

Of relevance are two studies in medically healthy, nonpsychiatric subjects examining the brain rCBF response to the panicogen, cholecystokinin tetrapeptide (CCK-4). Benkelfat and colleagues (1995) used CCK-4 infusions to produce a reliable panic response and normal saline infusions as a control condition. Subjects were also studied in an anticipatory anxiety condition during which they expected to receive CCK-4 but were actually injected with saline. During anticipatory anxiety, rCBF increased in the left OFC and cerebellum. Anxiety induced by CCK-4 was associated with rCBF increases in ACC, cerebellum, and a bilateral region spanning the insula, claustrum, and amygdala. Following this study, Javenmard and colleagues (1999) examined rCBF during CCK-4-induced panic attacks at two different time points (the first minute or the second minute after CCK-4 bolus injection). Early phase changes in rCBF occurred in the hypothalamus region, while late phase changes included rCBF increases in the claustrum-insular region. Consistent with findings of decreased frontal cortical blood flow in patients with PD during panic episodes, early and late phases in this study were associated with rCBF decreases in the medial frontal region. However, in contrast to results of the group’s previous study, an anticipatory anxiety condition was associated with rCBF increases in ACC and decreases in visual cortex. In a study examining the effects of imipramine treatment on rCMRglu in patients with PD using PET-FDG, Nordahl and colleagues (1998) found a rightward shift in symmetry within hippocampus and posterior inferior frontal cortex, consistent with their previously reported findings in untreated patients with PD (Nordahl et al., 1990). In addition, compared with the untreated group, the imipramine-treated group exhibited rCMRglu decreases in posterior OFC similar to the changes observed in OCD following successful treatment (e.g., Baxter et al., 1992). More recently, the effect of CBT on regional brain glucose utilization in PD was examined using the 18-FDG PET technique (Sakai et al., 2006). Treatment responders (11 of 12) demonstrated attenuation of glucose utilization in the right hippocampus, left ACC, left cerebellum, and pons. In addition, increased glucose utilization was found in the medial PFC bilaterally, supporting the idea of an adaptive increase in top-down governance via prefrontal cortical inhibition of limbic circuitry. In a PET imaging study using an agonist challenge to alter serotonin neurotransmission, Meyer and colleagues (2000) measured rCBF before and after an intravenous infusion of d-fenfluramine (an inducer of serotonin release) in a sample of women with PD. Nine patients with PD and 18 healthy comparisons underwent PET scans, pre- and post-fenfluramine injection. The patients with PD demonstrated relatively lower baseline rCBF in the cingulate and the left posterior parietal-

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superior temporal region compared to the nonanxious controls. In response to the fenfluramine challenge, patients with PD demonstrated increased rCBF in the cingulate and left dorsolateral PFC and decreased rCBF in the posterior temporal cortex (also seen in the control group). Differences in fenfluramine-related changes were found between patients and controls, with a significantly greater increase in rCBF occurring in the women with PD in the left posterior inferior parietal-superior temporal cortex compared to the healthy controls. Imaging Studies of Neurochemistry Dager and colleagues have used MRS methods in three successive studies focusing on brain lactate levels in PD (Dager et al., 1995; Dager et al., 1999; Friedman et al., 2000). In a 1995 report, the group measured brain lactate levels during hyperventilation in seven treatment-responsive patients with PD and an equal number of healthy controls. Although no significant differences were found in brain lactate levels at rest, the PD group showed a significantly greater rise in brain lactate in response to the same level of hyperventilation compared to the control group. Notably, there were no significant between-group differences in blood lactate levels either before or after hyperventilation. Dager and colleagues hypothesized that patients with PD might develop higher levels of brain lactate during hyperventilation as a consequence of an exaggerated rCBF vasoconstrictive response to hypocapnia. In their second study, Dager et al. (1999) used MRS to measure brain lactate levels during lactate infusions in 15 patients with PD and 10 healthy comparison subjects. Compared to the healthy controls, the PD group showed significantly higher brain lactate levels during lactate infusion, suggesting reduced clearance rather than higher production of lactate in PD. The fact that this effect was global, rather than regional, is consistent with a potential widespread abnormality in cerebral vascular regulation in PD. In a third study, the investigators examined brain tissue versus the cerebrospinal fluid (CSF) compartment lactate response to metabolic challenge with lactate infusion in four patients with PD (Friedman et al., 2000). Through this study, they were able to confirm their hypothesis that the differentially greater rise in brain lactate in patients with PD postlactate infusion demonstrated in their first two studies is the result of tissue-based changes and is not attributable to CSF changes. The group went on to examine whether excessive brain lactate and delayed end-tidal CO2 recovery was a result of aberrant brain acid-base regulation in PD (Friedman et al., 2006). Nine patients with PD and 11 healthy controls were compared during regulated hyperventilation and recovery, using phosphorous spectroscopy to measure brain pH. Patients with PD demonstrated greater hypocapnia during hyperventilation, but in comparison with healthy controls, their

pH response was blunted. The authors hypothesized that this exaggerated buffering seen in patients with PD might be accounted for by increased lactate levels. Owing to the popular use of the SRIs as first-line treatments for PD, there has been interest in investigating potential abnormalities in serotonergic transmission in the pathophysiology of PD. Preclinical models of chronic anxiety have implicated the 5-HT1A receptor (Fedotova et al., 2004). In a study aimed at investigating the relevance of the 5-HT1A receptor binding properties to panic anxiety, Neumeister et al. (2004) used PET and the [18F]-FCWAY radioligand to measure central 5-HT1A receptor binding in 16 unmedicated patients with PD (7 with comorbid depression) and 15 matched healthy controls. The PD group, regardless of comorbid depression status, demonstrated lower volumes of distribution in the anterior and posterior cingulate and the raphé, implicating the 5-HT1A receptor in the pathophysiology of PD. The hypothesized involvement of the benzodiazepine receptor in stress and anxiety has prompted several investigators to measure benzodiazepine receptor binding in patients with PD. Because some of these studies suffer from various methodological problems, (including lack of a medically healthy, nonanxious control group), only those studies with an adequate control group and medication-free patients are discussed below. Using SPECT with [123I]iomazenil, Kuikka et al. (1995) measured benzodiazepine receptor uptake in 17 patients with PD and an equal number of matched healthy comparisons. Compared to the control group, the patients with PD exhibited a greater left/right ratio in benzodiazepine receptor uptake, which was most prominent in PFC. Malizia et al. (1998) used PET and carbon11-labeled flumazenil to measure benzodiazepine receptor binding in 7 patients with PD and 8 healthy comparisons. They reported global reductions in benzodiazepine receptor binding in the patients with PD versus the controls, which was greatest in the right orbitofrontal and right insular cortices. Bremner, Innis, White, and colleagues (2000) used SPECT and [123I] iomazenil to measure benzodiazepine receptor density in 13 patients with PD and 16 healthy controls. Decreased benzodiazepine receptor binding was found in the left hippocampus and precuneus in the patients with PD relative to the controls. Although the authors did not find between-group differences in binding in PFC overall, they did report a negative correlation between binding in the PFC and panic attack symptoms in the patients with PD. This finding suggests that the decrease in prefrontal benzodiazepine binding may be a state-specific rather than a trait finding. In addition to benzodiazepine receptor binding abnormalities, reductions in cortical GABA levels have also been demonstrated in patients with PD compared to healthy controls. Goddard et al. (2004) examined whether patients with PD might also have an abnor-

43: NEUROIMAGING STUDIES

mal GABA response to the administration of a benzodiazepine. Using a proton MRS technique, they studied occipital GABA levels before and after clonazepam administration in 10 patients with PD and 9 healthy controls. Patients with PD demonstrated a minimal reduction in occipital GABA levels in response to acute clonazepam administration compared to the expected significant reduction measured in healthy comparisons. The authors hypothesize that the blunted, deficient response to benzodiazepine administration in patients with PD may be related to an abnormality in gene expression or function of the GABA synthetic enzyme glutamate decarboxylase 65 (GAD65). In summary, the majority (Malizia et al., 1998; Bremner, Innis, White, et al., 2000) but not all (Brandt et al., 1998) of benzodiazepine receptor binding studies have demonstrated decreased binding in frontal and insular cortex, areas important in modulating the amygdalacentered fear circuitry.

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dence exists indicating that phobias develop principally in the absence of an initial threatening exposure. Researchers have suggested that modeling of fearful responding by others underlies the appearance of phobias in the absence of direct experience. However, another possibility is that phobias represent dysfunction within systems specific to archetypal varieties of potentially threatening stimuli or situations. For instance, if humans have evolved one neural network specifically designed to assess social cues for threatening content and another to assess threat from small animals, and so on, aberrant functioning in these pathways might represent the pathophysiology underlying phobias. Currently, neuroanatomically based models for the phobias remain in the early stages of development (Fyer, 1998; Stein, 1998; Mathew et al., 2001), with neuroimaging studies of the type described below informing such models. Structural Imaging Findings

Summary The body of neuroimaging data on PD is less conclusive than that of some of the other anxiety disorders. Overall, together with mMRI findings, functional abnormalities in the hippocampal/parahippocampal region appear to be a marker at rest. During symptom provocation, patients with PD exhibit activation of insular and motor striatal regions, while reductions are seen in widespread cortical regions, including the PFC. Dager and colleagues’ MRS studies of brain lactate suggest that patients with PD exhibit an exaggerated hemodynamic response to hypocapnia, manifest as relatively greater vasoconstriction, which appears to be global. Likewise, receptor binding studies suggest widespread abnormalities in the GABAergic/benzodiazepine system. These findings are also most pronounced in hippocampal, insular, and prefrontal regions; however, they should be interpreted with caution, considering the potential effects of prior exposure to psychotropic medications. Neurobiological models of PD have proposed aberrant monoaminergic neurotransmitter modulation, originating in the corresponding brain stem nuclei, as a key factor underlying the abnormalities of metabolism, hemodynamics, and chemistry found in widespread cortical areas. Although limited, data implicate medial temporal lobe structures in PD, suggesting a potential role for hippocampal or amygdala dysfunction in this disorder.

SOCIAL AND SPECIFIC PHOBIAS Neuroanatomical Models of Phobias If one accepts the premise that all phobias are learned, they can be viewed as another example of fear conditioning to specific stimuli or situations. However, evi-

Despite the high prevalence of specific and social phobias, there are surprisingly few neuroimaging studies in these areas. Using mMRI methods, Rauch and colleagues (2004) demonstrated increased cortical thicknesses in the insular, rostral anterior cingulate and posterior cingulate along with the left visual cortex in a group of patients with specific phobia (animal type) compared with a nonphobic control group. A single volumetric study has been reported in social phobia (Potts et al., 1994); however, no significant betweengroup differences were found in any of the brain regions examined. Functional Imaging Findings Studies employing functional imaging in combination with symptom provocation paradigms in patients with specific phobias have reported varying results. In an initial study by Mountz and colleagues (1989), patients with small-animal phobias responded to feared stimuli with increases in heart rate and respiratory rates, and with subjective reports of increasing anxiety during exposure. However, no changes in rCBF measurements were observed with PET imaging. Review of this study suggests that the negative findings may have been a result of the data analytic methods employed. In a series of studies of specific phobias from another laboratory, exposure to fearful stimuli resulted in fairly uniform results. In the earliest study, Wik and colleagues (1993) measured rCBF in patients with snake phobias during exposure to videotapes of neutral, generally aversive, and snake-related scenes. During the phobic condition, they found significant increases in rCBF within secondary visual cortex, while rCBF decreases were noted within PFC, posterior cingulate cortex, anterior temporopolar cortex, and hippocampus.

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In two other studies, including an analogous study of patients with spider phobias, these findings were largely replicated (Fredrikson et al., 1993; Fredrikson et al., 1995). Rauch, Savage, Alpert, and colleagues (1995), using PET, employed a different paradigm from the studies described above, exposing a sample of patients with a variety of small-animal phobias to phobia-related and control stimuli in vivo and acquired images with the patients’ eyes closed, as opposed to the eyes-open method employed in previous studies. This difference resulted in a lack of visual cortical activation, which, interestingly, appeared to be replaced by somatosensory cortical activation, suggesting that the patients may have been involved in tactile imagery, as indeed they reported fears of coming into contact with the feared animal. Besides the somatosensory cortex, the main areas exhibiting rCBF increases in response to the feared stimuli included multiple anterior paralimbic territories (that is, right anterior cingulate, right anterior temporal pole, left posterior OFC, and left insular cortex), left somatosensory cortex, and left thalamus. Scheinle and colleagues (2005) reported similar results in a group of patients with spider phobias and were the first group to demonstrate activation of the amygdala during exposure to feared stimuli when compared with healthy controls. Later, Straube, Mentzel, and colleagues (2006) examined brain activation patterns to phobia-related (spiders) versus neutral pictures during a direct viewing task and a distraction task. They found greater amygdalar activation in patients with phobias versus healthy controls in both tasks but found that the right amygdala was activated only during the distraction task, suggesting its role may be in automatic processing of potentially threatening stimuli. Although regional brain activation changes had been found in response to treatment in other anxiety disorders, Paquette et al. (2003) were the first group to study the regional brain changes resulting from treatment of specific phobia with CBT. They studied 12 patients with spider phobias using fMRI, before and after CBT during the viewing of an emotional activation task involving viewing films of spiders. Prior to treatment, the right dorsolateral PFC and parahippocampal gyrus were activated, which was significantly attenuated postsuccessful CBT treatment. In a similar study, patients with spider phobias were randomly assigned to treatment with CBT or to a waiting list (control group) (Straube, Glauer, et al., 2006). Attenuation of hyperactivity in the insula and ACC correlated with reduction in phobic symptoms in response to CBT treatment. The number of functional imaging studies in social phobia continues to expand, with cognitive activation studies performed in conjunction with fMRI yielding informative results (Table 43.3). Patients with social phobia demonstrate specific areas of enhanced regional brain activity when exposed to social threat signaled

by viewing negative facial expressions. Functional MRI studies have shown that patients with social phobia demonstrate greater amygdala activation than healthy comparisons to angry (Stein et al., 2002; Straube et al., 2004; Phan, Fitzgerald, et al., 2006) and neutral facial expressions (Birbaumer et al., 1998; Viet et al., 2002; Cooney et al., 2006). Patients with social phobia also demonstrate increased insula activation to faces displaying anger or disgust versus neutral faces when compared to controls (Straube et al., 2004; Amir et al., 2005; Straube et al., 2005). The ACC also shows greater activation in patients with social phobia than in healthy controls during exposure to negative facial expressions (Straube et al., 2004; Amir et al., 2005) In addition to these regions, an area implicated in the processing of emotional facial content is the fusiform gyrus, located in the extrastriatal visual cortex. Patients with social phobia show greater activation in the fusiform during the processing of facial expressions, regardless of valence, suggesting enhanced processing of human facial expressions in social phobia (Straube et al., 2005). Although enhanced activity within the regions of the amygdala, insula, and ACC in response to cues suggesting social disapproval or threat is predicted based on neurocircuitry models of fear, there is evidence that patients with social phobia are more likely to interpret neutral or ambiguous facial expressions negatively (Winton et al., 1995). Several studies have demonstrated enhanced amygdala activation in patients with social phobia versus controls when viewing neutral faces alone (Cooney et al., 2006) or paired with aversive stimuli (Birbaumer et al., 1998; Schneider et al., 1999; Viet et al., 2002). Functional MRI techniques have also been used to demonstrate that amygdala reactivity in patients with generalized social phobia increases in relationship to the emotional intensity of the faces presented (Yoon et al., 2007). Public speaking, a prominent performance fear in patients with social phobia, has been effective as a means of provoking anxiety during neuroimaging. In a symptom provocation study that required subjects to speak in front of an audience (public speaking task) versus alone (private speaking task), Tillfors and colleagues (2001) studied the rCBF response of 18 patients with social phobia and 6 nonanxious, healthy comparisons using PET. Patients with social phobia demonstrated a significantly greater rCBF response in the right amygdala and periamygdaloid cortex compared to controls in response to the public versus private speaking task. In addition, rCBF decreased in patients with social phobia in the orbitofrontal and insular cortices and the temporal pole, while healthy comparisons demonstrated increases in rCBF in these same areas. In a similar study, Loberbaum and colleagues (2004) used fMRI to image brain activity while eight patients with generalized so-

43: NEUROIMAGING STUDIES TABLE

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43.3 Summary of Functional Neuroimaging Findings in Social Phobia

Paradigm Employed

Identified Areas of Elevated Metabolism, CBF or BOLD Signal in Patients with Social Phobia versus Healthy Controls

References

Emotional facial expressions: Neutral (explicit)

Amygdala

Birbaumer et al., 1998 Cooney et al., 2006

Neutral (conditioned using aversive odor

Amygdala and hippocampus

Schneider et al., 1999

Neutral (conditioned using painful stimulus)

Orbitofrontal cortex, R insula, ACC, R amygdala, L dorsolateral PFC

Veit et al., 2002

Angry vs. happy (implicit)

Amygdala, parahippocampal gyrus, uncus, Medial PFC, sup and inf frontal gyri

Stein et al., 2002

Angry vs. neutral (implicit)

Amygdala, parahippocampal gyrus, fusiform Gyrus, sup temportal sulcus

Straube et al., 2004

Angry (explicit)

R amygdala, fusiform gyrus

Straube et al., 2005

Contempt vs. happy (implicit)

Amygdala, parahippocampal gyrus, uncus, Medial PFC, sup and inf frontal gyri

Stein et al., 2002

Harsh vs. happy (implicit)

Dorsal medial PFC, L inf frontal gyrus, R sup frontal gyrus, L amygdala, uncus L parahippocampal gyrus

Stein et al., 2002

Harsh vs. happy (explicit)

R amygdala

Phan, Fitzgerald et al., 2006

Disgust vs. neutral (explicit)

ACC, caudate, insula, inf and mid frontal gyri, Mid and sup frontal gyri, sup occipital gyrus

Amir et al., 2005

Happy (explicit)

R amygdala, fusiform

Straube et al., 2005

Faces of varying emotional intensity

Amygdala, L insula, R sup parietal gyrus, R mid frontal gyrus, R lingual gyrus

Yoon et al., 2007

Public vs. private speaking

R amygdaloid complex

Tillfors et al., 2001

Anticipation of public speaking

L amygdaloid complex, L insula, L temporal pole, L pons, L striatum

Loberman et al., 2004

Public speaking:

OFC: orbitofrontal cortex; ACC: anterior cingulate gyrus; PCC: posterior cingulate gyrus; PFC: prefrontal cortex; CBF: Cerebral blood flow; BOLD: blood oxygen level dependent; SAD: social anxiety disorder.

cial phobia and six healthy controls anticipated making public speeches. When brain activity during the rest period was subtracted from the anticipation period, patients with social phobia demonstrated greater subcortical, limbic, and lateral paralimbic activity (including the amygdala, parahippocampal gyrus, and insula), while showing decreases in the PFC compared to healthy controls. Thus, there is a relatively consistent response pattern across social phobia provocation studies. This pattern consists of increased subcortical/limbic activity accompanied by relatively decreased frontal cortical activity. This shift in brain activity likely reflects a failure of cortical processing and activation of the phylogenetically older subcortical fear circuitry. Thus, in response

to exposure to either human face stimuli or the stress of public speaking, patients with social phobia display exaggerated activity within key structures in fear responding, such as the amygdala and medial temporal areas at the expense of activity in prefrontal cortical regions. There are two reported imaging studies examining the effects of treatment on regional brain activity in social phobia. Van der Linden et al. (2000) examined the effects of pharmacotherapy with the SSRI citalopram on rCBF with SPECT. Fifteen patients with social phobia underwent scanning before and after 8 weeks of treatment with citalopram. Because no control group was studied, baseline differences in rCBF were not reported; nonetheless, in response to treatment, reduc-

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tions in rCBF were noted in the anterolateral left temporal cortex, left cingulate, and left midfrontal cortex. Those patients judged as nonresponders to treatment demonstrated greater rCBF at baseline in the anterolateral left temporal cortex and the lateral left midfrontal cortex compared to responders. Interpretation of the results of this study is limited by the fact that several patients had other comorbid anxiety disorders and two patients were taking additional psychotropic medications at the time of scanning. Another study examined the effects of two different anxiety treatments, pharmacotherapy with an SSRI and CBT, on rCBF in patients with social phobia. In a randomized design, 18 patients were scanned using PET techniques during a public speaking task (Furmark et al., 2002). Patients were divided into three groups: citalopram treatment, CBT, or waiting list (control group). Regional CBF was measured before and after 9 weeks of treatment or 9 weeks on the waiting list. Results demonstrated similar changes in rCBF in responders of both treatment groups in response to public speaking: bilateral decreases in rCBF in the amygdala, hippocampus, and related periamygdaloid, perihippocampal, and rhinal cortices, while no significant changes in rCBF were observed in the waiting list control group. These findings suggest that pharmacotherapy and CBT, in reducing social anxiety symptoms, attenuate activity in brain regions associated with the neural network identified as underlying danger perception and fear responding. Change in rCBF followed improvement and was not specific to treatment modality. Imaging Studies of Neurochemistry The DA and serotonin systems have been the focus of investigation in imaging studies of neurochemistry in social phobia. Tiihonen et al. (1997) used the radiotracer I-123-labeled-2b-carbomethoxy-3b-(4-iodophenyl) (bCIT) with SPECT to measure the density of DA reuptake sites in 11 patients with social phobia and 28 healthy comparisons. They reported significantly reduced striatal DA reuptake binding site density in the social phobia group compared to the control group. Subsequent to this report of low DAT density in social phobia, Schneier et al. (2000) measured DA D2 receptor binding in the striatums of 10 patients with social phobia and 10 matched healthy comparisons using the radiotracer [123I]iodobenzamide with SPECT. The patients with social phobia demonstrated significantly decreased D2 receptor binding, with a trend (p = .07) toward a negative correlation of binding potential and score on the Liebowitz Social Anxiety Scale. Using PET techniques, Kent, Coplan, Lombardo, et. al. (2002) examined paroxetine occupancy of the serotonin reuptake transporter (SERT) in patients with social phobia during treatment at typical antianxiety doses

(20 – 40mg/day). After 3 to 6 months of continuous treatment, paroxetine achieved very high occupancy levels at the SERT in all brain regions measured. In a PET study examining 5-HT1A receptor binding potential in social phobia (Lanzenberger et al., 2007), several brain areas implicated in the fear circuitry were identified as having significantly lower 5-HT1A binding potential in patients with social phobia, including the amygdala, insula, and dorsal raphe. These studies lend support to the validity of the SERT and 5-HT1A receptors as targets in the treatment of social anxiety. Summary The sum of imaging findings in specific phobia suggests that activation of anterior paralimbic regions, in addition to activation of the sensory cortex mediating input of the phobic stimulus, is associated with excessive fearful responding on stimulus exposure. It is promising that there are now several convergent findings in the social phobia literature. In response to exposure either to human face stimuli or to the stress of public speaking, patients with social phobia demonstrate exaggerated activity in the amygdala and related medial temporal lobe areas. Patients with social phobia also show abnormal activity within medial temporal lobe structures during aversive conditioning with human face stimuli, consistent with aberrant assignment of threat to human faces. Evidence supporting deficits in DA function in social phobia has now been reported in two studies, consistent with theories implicating the DA system in social reward (Stein, 1998). In addition to the DA system, results of imaging studies support the targeting of the serotonin system in treatment. CONCLUSIONS AND FUTURE DIRECTIONS Neurobiological models of the anxiety disorders are evolving as a result of significant input from findings of neuroimaging studies related to the structure, function, and neurochemistry of the brain. These findings suggest that the anxiety disorders share certain mediating anatomy such as the anterior paralimibic cortex, sensory cortex, amygdala, hippocampus, and striatum. However, imaging techniques have also begun to delineate signature abnormalities of brain structure and/ or function specific to the individual anxiety disorders. Overall, this work holds the promise of pathophysiology-based diagnosis, which, in turn, will lead to more targeted and effective treatments. Neuroimaging studies of OCD have demonstrated dysfunction within the cortico-striato-thalamo-cortical circuitry. Future investigations will likely focus on these structures and on the interactions among the nodes that constitute this system. Theories about the neurobiol-

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ogy of PTSD have been informed by animal studies of fear conditioning implicating the amygdala and related limbic cortical structures. Neuroimaging studies of PTSD have provided an initial means for testing the relevance of this neurocircuitry in patients. A convergence of evidence from these studies supports prevailing models of PTSD focusing on the amygdala and its relationship with the hippocampus and medial PFC (particularly anterior cingulate dysfunction). Although less neuroimaging research pertaining to the phobias exists in the literature, there is preliminary evidence of increased activity within sensory pathways and anterior paralimbic regions in specific phobias, which may reflect a hypersensitivity within systems evolved for assessing specific archetypal classes of potentially threatening stimuli (for example, animals, heights). In social phobia, exaggerated amygdalar responsivity to human face stimuli is likewise consistent with hypersensitivity within a specialized system to a discrete class of stimuli. For PD, neuroimaging research has identified a wide range of possible neural substrates underlying this anxiety disorder. Regional abnormalities within the temporal lobe may reflect fundamental deficits in threat assessment similar to those found in social phobia and PTSD. However, more global abnormalities in homeostatic mechanisms related to lactate metabolism and vascular responses to CO2, as well as widespread abnormalities in benzodiazepine receptor binding, may prove specific to PD. Clearly, an issue in all neuroimaging research in anxiety disorders is the presence of other comorbid anxiety disorders, substance abuse, and varying degrees of comorbid depression. Future studies should begin to include psychiatric comparison groups in addition to healthy controls, and to consider the contributing role of substance abuse and depressive symptoms to neurobiological findings. This is necessary to establish the specificity of findings versus their generalizability across classes of psychopathology. As evidenced by the mounting evidence in OCD, longitudinal studies with a developmental perspective will be critical in understanding the pathophysiology of anxiety disorders. For example, the relationship between early temperament and the development of social phobia (C.E. Schwartz et al., 1999) calls for studies beginning in childhood, as do OCD and related disorders that have an early onset. Also, proneness to developing PTSD and how brain changes evolve following trauma exposure is best addressed with studies that acquire data prior to trauma exposure and follow patients over time. As morphometric and functional imaging methods improve with advances in technology, neurochemical methods will continue to evolve. As new radioligands with greater specificity and sensitivity are developed, it will become possible to investigate receptor population changes at critical nodes within the relevant neurocir-

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cuitry and answer questions regarding neuropharmacology. Magnetic resonance spectroscopy is enabling measurement of metabolic markers in specific brain regions in vivo, as well as the change in neurochemical balance associated with specific pharmacological interventions. In summary, neuroimaging data are being used to help advance neurobiological models of the anxiety disorders. Convergent data have provided relatively cohesive models of OCD and PTSD, whereas the data for phobias and PD do not yet provide as clear a picture. The potential of neuroimaging to help delineate the pathophysiology of the anxiety disorders is now being realized, and future research in this domain will likely also lead to enhanced treatments for people suffering from these disorders.

REFERENCES Adams, K.H., Hansen, E.S., Pinborg, L.H., et al. (2005) Patients with obsessive-compulsive disorder have increased 5-HT2a receptor binding in the caudate nuclei. Int. J. Neuropsychopharmacol. 8:1–11. Adler, C.M., McDonough-Ryan, P., Sax, K.W., Holland, S.K., Arndt, S., and Strakowski, S.M. (2000) fMRI of neuronal activation with symptom provocation in unmedicated patients with obsessive compulsive disorder. J. Psychiatr. Res. 34:317–324. Aggleton, J.P., ed. (1992) The Amygdala: Neurobiological Aspects of Emotion, Memory and Mental Dysfunction. New York: WileyLiss. Alptekin, K., Degirmenci, B., Kivircik, B., Durak, H., Yemez, B., Derebek, E., and Tunca, Z. (2001) Tc-99m HMPAO brain perfusion SPECT in drug-free obsessive-compulsive patients without depression. Psychiatry Res. 107:51–56. Amir, N., Klumpp, H., Elias, J., et al. (2005) Increased activation of the anterior cingulate cortex during processing of disgust faces in individuals with social phobia. Biol. Psychiatry 57:975–981. Armony, J.L., Corbo, V., Clement, M.H., et al. (2005) Amygdala response in patients with acute PTSD to masked and unmasked emotional facial expressions. Am. J. Psychiatry 162:1961–1963. Atmaca, M., Yildirim, B.H., Ozdemir, B.H., et al. (2006) Volumetric MRI assessment of brain regions in patients with refractory obsessive-compulsive disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 30:1051–1057. Atmaca, M., Yildirim, H., Ozdemir, H., et al. (2007) Volumetric MRI study of key brain regions implicated in obsessive-compulsive disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 31: 46–52. Aylward, E.H., Harris, G.J., Hoehn-Saric, R., et al. (1996) Normal caudate nucleus in obsessive-compulsive disorder assessed by quantitative neuroimaging. Arch. Gen. Psychiatry 53:577–584. Barker, P.B. (2001) N-acetyl aspartate—a neuronal marker? Ann. Neurol. 49(4):423–424. Bartha, R., Stein, M.B., Williamson, P.C., et al. (1998) A short echo 1H spectroscopy and volumetric MRI study of the corpus striatum in patients with obsessive-compulsive disorder and comparison subjects. Am. J. Psychiatry 155(11):1584–1591. Baxter, L.R., Phelps, M.E., Mazziotta, J.C., et al. (1987) Local cerebral glucose metabolic rates in obsessive compulsive disorder: a comparison with rates in unipolar depression and in normal controls. Arch. Gen. Psychiatry 44:211–218. Baxter, L.R., Jr., Schwartz, J.M., Bergman, K.S., et al. (1992) Caudate glucose metabolic rate changes with both drug and behavior

724

ANXIETY DISORDERS

therapy for obsessive-compulsive disorder. Arch. Gen. Psychiatry 49:681–689. Baxter, L.R., Schwartz, J.M., Mazziotta, J.C., et al. (1988) Cerebral glucose metabolic rates in nondepressed patients with obsessivecompulsive disorder. Am. J. Psychiatry 145:1560–1563. Benazon, N.R., Moore, G.J., and Rosenberg, D.R. (2003) Neurochemical analyses in pediatric obsessive-compulsive disorder in patients treated with cognitive behavioral therapy. J. Am. Acad. Child Adoles. Psychiatry 42:1279–1285. Benkelfat, C., Bradwejn, J., Meyer, E., et al. (1995) Functional neuroanatomy of CCK4-induced anxiety in normal healthy volunteers. Am. J. Psychiatry 152:1180–1184. Benkelfat, C., Nordahl, T.E., Semple, W.E., et al. (1990) Local cerebral glucose metabolic rates in obsessive-compulsive disorder: patients treated with clomipramine. Arch. Gen. Psychiatry 47: 840–848. Birbaumer, N., Grodd, W., Diedrich, O., et al. (1998) fMRI reveals amygdala activation to human faces in social phobics. Neuroreport 9(6):1223–1226. Bisaga, A., Katz, J.L., Antonini, A., et al. (1998) Cerebral glucose metabolism in women with panic disorder. Am. J. Psychiatry 155: 1178–1183. Bolton, J., Moore, G.J., MacMillan, S., et al. (2001) Case study: caudate glutamaterigc changes with paroxetine persist after medication discontinuation in pediatric OCD. J. Am. Acad. Child Adoles. Psychiatry 40:903–906. Bonne, O., Baine, E., Neumeister, A., et al. (2005) No change in serotonin type 1A receptor binding in patients with posttraumatic stress disorder. Am. J. Psychiatry 162:383–385. Bonne, O., Brandes, D., Gilboa, A., Bomori, J.M., Shenton, M.E., Pitman, R.K., and Shalev, A.Y. (2001) Longitudinal MRI study of hippocampal volume in trauma survivors with PTSD. Am. J. Psychiatry 158:1248–1251. Brandt, C.A., Meller, J., Keweloh, L., et al. (1998) Increased benzodiazepine receptor density in the prefrontal cortex in patients with panic disorder. J. Neural Transm. 105:1325–1333. Breiter, H.C., Rauch, S.L., Kwong, K.K., et al. (1996) Functional magnetic resonance imaging of symptom provocation in obsessive compulsive disorder. Arch. Gen. Psychiatry 53:595–606. Bremner, J.D., Innis, R.B., Southwick, S.M., Staib, L., Zoghbi, S., and Charney, D.S. (2000) Decreased benzodiazepine receptor binding in prefrontal cortex in combat-related posttraumatic stress disorder. Am. J. Psychiatry 157:1120–1126. Bremner, J.D., Innis, R.B., White, T., Fujita, M., Silbersweig, D., Goddard, A.W., Staib, L., Stern, E., Cappiello, A., Woods, S., Baldwin, R., and Charney, D.S. (2000) SPECT [I-123]Iomazenil measurement of the benzodiazepine receptor in panic disorder. Biol. Psychiatry 47:96–106. Bremner, J.D., Narayan, M., Staib, L.H., Southwick, S.M., McGlashum, T., and Charney, D.S. (1999) Neural correlates of memories of childhood sexual abuse in women with and without posttraumatic stress disorder. Am. J. Psychiatry 156:1787–1795. Bremner, J.D., Randall, P., Scott, T.M., et al. (1995) MRI-based measurement of hippocampal volume in patients with combat-related posttraumatic stress disorder. Am. J. Psychiatry 152:973–981. Bremner, J.D., Randall, P., Vermetten, E., et al. (1997) Magnetic resonance imaging–based measurement of hippocampal volume in posttraumatic stress disorder related to childhood physical and sexual abuse—a preliminary report. Biol. Psychiatry 41:23–32. Bremner, J.D., Staib, L.H., Kaloupek, D., et al. (1999) Neural correlates of exposure to traumatic pictures and sound in Vietnam combat veterans with and without posttraumatic stress disorder: a positron emission tomography study. Biol. Psychiatry 45:806– 816. Britton, J.C., Phan, K.L., Taylor, S.F., et al. (2005) Corticolimbic blood flow in posttraumatic stress disorder during script-driven imagery. Biol. Psychiatry 57:832–840.

Brody, A.L., Saxena, S., Schwartz, J.M., et al. (1998) FDG-PET predictors of response to behavioral therapy versus pharmacotherapy in obsessive-compulsive disorder. Psychiatry Res. Neuroimag. 84:1–6. Bryant, R.A., Felmingham, K.L., Kempt, A.H., et al. (2005) Neural networks of information processing in posttraumatic stress disorder: a functional magnetic resonance imaging study. Biol. Psychiatry 58:111–118. Bystritsky, A., Pontillo, D., Powers, M., Sabb, F.W., Craske, M.G., and Bookheimer, S.Y. (2001) Functional MRI changes during panic anticipation and imagery exposure. Neuroreport 12:3953– 3957. Cameron, H.A., Hazel, T.G., and McKay, R.D. (1998) Regulation of neurogenesis by growth factors and neurotransmitters. J. Neurobiol. 36(2):287–306. Cannistraro, P.A., and Rauch, S.L. (2003) Neural circuitry of anxiety: evidence from structural and functional neuroimaging studies. Psychopharmacol. Bull. 37:8–25. Carrion, V.G., Weems, C.F., Eliez, S., Patwardhan, A., Brown, W., Ray, R.D., and Reiss, A.L. (2001) Attenuation of frontal asymmetry in pediatric posttraumatic stress disorder. Biol. Psychiatry 50:943–951. Charney, D.S., Bremner, J.D., and Redmond, D.E. (1995) Noradrenergic neural substrates for anxiety and fear: clinical associations based on pre-clinical research. In: Bloom, F.E., and Kupfer, D.J., eds. Psychopharmacology: The Fourth Generation of Progress. New York: Raven Press, pp. 387–396. Chen, X.L., Xiet, J.X., Han, H.B., et al. (2004) MR perfusionweighted imaging and quantitative analysis of cerebral hemodynamics with symptom provocation in unmedicated patients with obsessive-compulsive disorder. Neurosci. Lett. 370:206–211. Choi, J.S., Kang, D.H., Kim, J.J., et al. (2004) Left anterior subregion of orbitofrontal cortex volume reduction and impaired organizational strategies in obsessive-compulsive disorder. J. Psychiatr. Res. 38:193–199. Cohen, R.A., Grieve, S., Hoth, K.F., et al. (2006) Early life stress and morphometry of the adult anterior cingulate cortex and caudate nuclei. Biol. Psychiatry 59:975–982. Cooney, R.E., Atlas, L.Y., Joormann, J. et al. (2006) Amygdala activation in the processing of neutral faces in social anxiety disorder: is neutral really neutral? Psychiatry Res. Neuroimag. 148: 55–59. Coplan, J.D., and Lydiard, R.B. (1998) Brain circuits in panic disorder. Biol. Psychiatry 44:1264–1276. Corbo, V., Clement, M.H., Armony, J.L., et al. (2005) Size versus shape differences: contrasting voxel-based and volumetric analyses of the anterior cingulate cortex in individuals with acute posttraumtic stress disorder. Biol. Psychiatry 58:119–124. Crespo-Facorro, B., Cabranes, J.A., Lopez-Ibor Alcocer, M.I., Paya, B., Fernandez Perez, C., Encinas, M., Ayuso Mateos, J.L., and Lopez Ibor, J.J., Jr. (1999) Regional cerebral blood flow in obsessive-compulsive patients with and without a chronic tic disorder. A SPECT study. Eur. Arch. Psychiatry Clin. Neurosci. 249:156– 161. Dager, S.R., Friedman, S.D., Heide, A., Layton, M.E., Richards, T., Artru, A., Strauss, W., Hayes, C., and Posse, S. (1999) Two-dimensional proton echo-planar spectroscopic imaging of brain metabolic changes during lactate-induced panic. Arch. Gen. Psychiatry 56(1):70–77. Dager, S.R., Strauss, W.L., Marro, K.I., Richards, T.L., Metzger, G.D., and Artru, A.A. (1995) Proton magnetic resonance spectroscopy investigation of hyperventilation in subjects with panic disorder and comparison subjects. Am. J. Psychiatry 152(5):666–672. Davis, M. (1992) The role of the amygdala in fear and anxiety. Annu. Rev. Neurosci. 58(Suppl 2):26–28. De Bellis, M.D., Hall, J., Boring, A.M., Frustaci, K., and Moritz, G. (2001) A pilot longitudinal study of hippocampal volumes in pe-

43: NEUROIMAGING STUDIES diatric maltreatment-related posttraumatic stress disorder. Biol. Psychiatry 50:305–309. De Bellis, M.D., Keshavan, M.S., Clark, D.B., Case, B.J., Giedd, J.N., Boring, A.M., Frustaci, K., and Ryan, N.C. (1999) A.E. Bennett Research Award. Developmental traumatology. Part II: Brain development. Biol. Psychiatry 45:1271–1284. De Bellis, M.D., Keshavan, M.S., Frustaci, K., Shifflett, H., Iyengar, S., Beers, S.R., and Hall, J. (2002) Superior temporal gyrus volumes in maltreated children and adolescents with PTSD. Biol. Psychiatry 51:544–552. De Bellis, M.D., Keshavan, M.S., Spencer, S., and Hall, J. (2000) Nacetylaspartate concentration in the anterior cingulate of maltreated children and adolescents with PTSD. Am. J. Psychiatry 157:1175–1177. De Bellis, M.D., and Kuchibhatla, M. (2006) Cerebellar volumes in pediatric maltreatment-related posttraumatic stress disorder. Biol. Psychiatry 60:697–703. Deckersbach, T., Dougherty, D.D., and Rauch, S.L. (2006) Functional imaging of mood and anxiety disorders. Neuroimaging 16: 1–10. De Cristofaro, M.T., Sessarego, A., Pupi, A., Biondi, F., and Faravelli, C. (1993) Brain perfusion abnormalities in drug-naive, lactatesensitive panic patients: a SPECT study. Biol. Psychiatry 33(7): 505–512. Denys, D., van der Wee, N.J., Janssen, J., et al. (2005) Low level of dopaminergic D2 receptor binding in obsessive-compulsive disorder. Biol. Psychiatry 55:1041–1045. Diler, R.S., Kibar, M., and Avci, A. (2004) Pharmacotherapy and regional cerebral blood flow in children with obsessive-compulsive disorder. Yonsei Medical Journal 45:90–99. Drevets, W.C., Videen, T.O., MacLeod, A.K., et al. (1992) PET images of blood flow changes during anxiety: a correction. Science 256:1696. Driessen, M., Herrmann, J., Stahl, K., Zwaan, M., Meier, S., Hill, A., Osterheider, M., and Petersen, D. (2000) Magnetic resonance imaging volumes of the hippocampus and amygdala in women with borderline personality disorder and early traumatization. Arch. Gen. Psychiatry 57:1115–1122. Ebert, D., Speck, O., Konig, A., Berger, M., Hennig, J., and Hohagen, F. (1997) 1H-magnetic resonance spectroscopy in obsessive-compulsive disorder: evidence for neuronal loss in the cingulate gyrus and the right striatum. Psychiatry Res. 74(3):173–176. Fedotova, J.O., Hartmann, G., Lenard, L., et al. (2004) Effects of 5HT1A receptor agonist and antagonist on anxiety in intact and ovariectomized female rats. Acta Physiol. Hung. 91:175–184. Fernandez, A., Pino Alonso, M., Matix-Cols, D., et al. (2003) Neuroactivation o f the Tower of Hanoi in patients with obsessivecompulsive disorder and healthy volunteers. Rev. Esp. Med. Nuc. 22:376–385. Fischer, H., Andersson, J.L., Furmark, T., and Fredrikson, M. (1998) Brain correlates of an unexpected panic attack: a human positron emission tomographic study. Neurosci. Lett. 251(2):137–140. Fischer, H., Wik, G., and Fredrikson, M. (1996) Functional neuroanatomy of robbery re-experience: affective memories studied with PET. Neuroreport 7:2081–2086. Fitzgerald, K.D., Welsh, R.C., Gehring, W.J., et al. (2005) Error-related hyperactivity of the anterior cingulate cortex in obsessive-compulsive disorder. Biol. Psychiatry 57:287–294. Fontaine, R., Breton, G., Dery, R., Fontaine, S., and Elie, R. (1990) Temporal lobe abnormalities in panic disorder: an MRI study. Biol. Psychiatry 27(3):304–310. Fredrikson, M., Wik, G., Annas, P., et al. (1995) Functional neuroanatomy of visually elicited simple phobic fear: additional data and theoretical analysis. Psychophysiology 32:43–48. Fredrikson, M., Wik, G., Greitz, T., et al. (1993) Regional cerebral blood flow during experimental fear. Psychophysiology 30:126– 130.

725

Friedman, S.D., Dager, S.R., Richards, T.L., Petropoulos, H., and Posse, S. (2000) Modeling brain compartmental lactate response to metabolic challenge: a feasibility study. Psychiatry Res. 98: 55–66. Friedman, S.D., Mathis, C.M., Hayes, C., Renshaw, P., and Dager, S.R. (2006) Brain pH response to hyperventilation in panic disorder: preliminary evidence for altered acid-base regulation. Am. J. Psychiatry 163:710–715. Fujita, M., Southwick, S.M., Denucci, C.C., et al. (2004) Central type benzodiazepine receptors in gulf War veterans with posttraumatic stress disorder. Biol. Psychiatry 56:95–100. Furmark, T., Tillfors, M., Marteinsdottir, I., Fischer, H., Pissiota, A., Langstrom, B., and Fredrikson M. (2002) Common changes in cerebral blood flow in patients with social phobia treated with citalopram or cognitive-behavioral therapy. Arch. Gen. Psychiatry 59:425–433. Fyer, A.J. (1998) Current approaches to etiology and pathophysiology of specific phobia. Biol. Psychiatry 44:1295–1304. Giedd, J.N., Rapoport, J.L., Garvey, M.A., Perlmutter, S., and Swedo, S.E. (2000) MRI assessment of children with obsessive-compulsive disorder or tics associated with streptococcal infection. Am. J. Psychiatry 157:281–283. Gilbert, A.R., Moore, G.J., Keshavan, M.S., Paulson, L.A.D., Narula, V., MacMaster, F.P., Stewart, C.M., and Rosenberg, D.R. (2000) Decrease in thalamic volumes of pediatric patients with obsessive-compulsive disorder who are taking paroxetine. Arch. Gen. Psychiatry 57:449–456. Gilboa, A., Shalev, A.Y., Laor, L., et al. (2004) Functional connectivity of the prefrontal cortex and the amygdala in posttraumatic stress disorder. Biol. Psychiatry 55:263–272. Goddard, A.W., Mason, G.F., Appel, M., et al. (2004) Impaired GABA neuronal response to acute benzodiazepine administration in panic disorder. Am. J. Psychiatry 161:2186–2193. Gorman, J.M., Kent, J.M., Sullivan, G.M., et al. (2000) Neuroanatomical hypothesis of panic disorder, revised. Am. J. Psychiatry 157:493–505. Gorman, J.M., Lietowitz, M.R., Fyer, A.J., et al. (1989) A neuroantomical hypothesis for panic disorder. Am. J. Psychiatry 146: 148–161. Gurvits, T.V., Shenton, M.E., Hokama, H., et al. (1996) Magnetic resonance imaging study of hippocampal volume in chronic, combat-related posttraumatic stress disorder. Biol. Psychiatry 40:1091–1099. Ham, B.J., Chey, J., Yoon, S.J., et al. (2007) Decreased N-acetyl-aspartate levels in anterior cingulate and hippocampus in subjects with post-traumatic stress disorder: a proton magnetic resonance spectroscopy study. Eur. J. Neurosci. 25:324–329. Hansen, E.S., Hasselbach, S., Law, I., et al. (2002) The caudate nucleus in obsessive-compulsive disorder. Reduced metabolism following treatment with paroxetine: a PET study. Int. J. Neuropsychopharmacol. 5:1–10. Hesse, S., Muller, U., Lincke, T., et al. (2005) Serotonin and dopamine transporter imaging in patients with obsessive-compulsive disorder. Psychiatry Res. 30:63–72. Hoehn-Saric, R., Pearlson, G.D., Harris, G.J., et al. (1991) Effects of fluoxetine on regional cerebral blood flow in obsessive-compulsive patients. Am. J. Psychiatry 148:1243–1245. Hoehn-Saric, R., Schlaepfer, T.E., Greenberg, B.D., et al. (2001) Cerebral blood flow in obsessive-compulsive patients with major depression: effect of treatment with sertraline or desipramine on treatment responders and non-responders. Psychiatry Res. 108: 89–100. Holsboer, F. (1999) The rationale for corticotropin-releasing hormone receptor (CRH-R) antagonists to treat depression and anxiety. J. Psychiatr. Res. 33:181–214. Ho Pian, K.L., van Megan, H.J.G.M., Ramsy, N.F., et al. (2005) Decreased thalamic blood flow in obsessive-compulsive disorder pa-

726

ANXIETY DISORDERS

tients responding to fluvoxamine. Psychiatry Res: Neuroimag. 138: 89–97. Jatzko, A., Rothenhofer, S., Schmitt, A., et al. (2006) Hippocampal volume in chronic posttraumatic stress disorder (PTSD): MRI study using two different evaluation methods. J. Affect. Disord. 94:121–126. Javanmard, M., Shlik, J., Kennedy, S.H., Vaccarino, F.J., Houle, S., and Bradwejn, J. (1999) Neuroanatomic correlates of CCK-4-induced panic attacks in healthy humans: a comparison of two time points. Biol. Psychiatry 45(7):872–882. Jenike, M.A., Breiter, H.C., Baer, L., et al. (1996) Cerebral structural abnormalities in obsessive-compulsive disorder: a quantitative morphometric magnetic resonance imaging study. Arch. Gen. Psychiatry 53:625–632. Jones, D.K., Simmons, A., Williams, S.C., and Horsfield, M.A. (1999) Non-invasive assessment of axonal fiber connectivity in the human brain via diffusion tensor MRI. Magn. Reson. Med. 42: 37–41. Jung, R.E., Yeo, R.A., Love, T.M., Petropoulos, H., Sibbitt, W.L., and Brooks, W.M. (2002) Biochemical markers of mood: a proton MR spectroscopy study of normal human brain. Biol. Psychiatry 51:224–229. Kang, D.H., Kim, J.J., Choi, J.S., et al. (2004) Volumetric investigation of the frontal-subcortical circuitry in patients with obsessive-compulsive disorder. J. Neuropsychiatry Clin. Neurosci. 16: 342–349. Karl, A., Schaefer, M., Malta, L.S., et al. (2006) A meta-analysis of structural brain abnormalities in PTSD. Neurosci. Biobehav. Rev. 30:1004–1031. Kent, J.M., Coplan, J.D., and Gorman, J.M. (1998) Clinical utility of the selective serotonin reuptake inhibitors in the spectrum of anxiety. Biol. Psychiatry 44:812–824. Kent, J.M., Coplan, J.D., Lombardo, I., et al. (2002) Occupancy of brain serotonin transporters during treatment with paroxetine in patients with social phobia: a positron emission tomography study with 11C McN 5652. Psychopharmacology (Berl) 164:341– 348. Kent, J.M., Sullivan, G.S., and Rauch, S.L. (2000) The neurobiology of fear: relevance to panic disorder and posttraumatic stress disorder. Psychiatr. Ann. 30:733–742. Kent, J.M., Sullivan, G.S., and Rauch, S.L. (2002) Neural circuitry and signaling in anxiety. In: Kaplan, G.B., and Hammer, R.P., eds. Brain Circuitry and Signaling in Psychiatry. Washington, DC: American Psychiatric Press, pp. 125–152. Kim, C.-H., Koo, M.-S., Cheon, K.-A., et al. (2003) Dopamine transporter density of basal ganglia assessed [123I] IPT SPET in obsessive-compulsive disorder. Eur. J Nucl. Med. Molecular Imaging 30:1637–1643. Kim, J.-J., Lee, M.C., Kim, J., Kim, I.Y., Kim, S.I., Han, M.H., Chang, K.-H., and Kwon, J.S. (2001) Grey matter abnormalities in obsessive-compulsive disorder. Br. J. Psychiatry 179:330–334. Kuikka, J.T., Pitkanen, A., Lepola, U., et al. (1995) Abnormal regional benzodiazepine receptor uptake in the prefrontal cortex in patients with panic disorder. Nucl. Med. Commun. 16(4):273– 280. Kwon, J.S., Shin, Y.W., Kim, C.W., et al. (2003) Similarity and disparity of obsessive-compulsive disorder and schizophrenia in MR volumetric abnormalities of the hippocampus-amygdala complex. J. Neurol. Neurosurg. Psychiatry 74:962–964. Lanius, R.A., Williamson, P.C., Bluhm, R.L, et al. (2005) Functional connectivity of dissociative responses in posttraumatic stress disorder: a functional magnetic resonance imaging investigation. Biol. Psychiatry 57:873–884. Lanius, R.A., Williamson, P.C., Boksman, K., et al. (2002) Brain activation during script-driven imagery induced dissociative responses in PTSD: a functional MRI investigation. Biol. Psychiatry 52:305– 311.

Lanius, R.A., Williamson, P.C., Densmore, M., Boksman, K., Gupta, M.A., Neufeld, R.W., Gati, J.S., and Menon, R.S. (2001) Neural correlates of traumatic memories in posttraumatic stress disorder: a functional MRI investigation. Am. J. Psychiatry 158:1920– 1922. Lanius, R.A., Williamson, P.C., Hopper, J., et al. (2003) Recall of emotional states in posttraumatic stress disorder: an fMRI investigation. Biol. Psychiatry 53:204–210. Lanzenberger, R.R., Mitterhauser, M., Spindelegger, C., et al. (2007) Reduced serotonin-1A receptor binding in social anxiety disorder. Biol. Psychiatry 61:1081–1089. LeDoux, J.E. (1996) The Emotional Brain. New York: Simon & Schuster. LeDoux, J.E., Cicchetti, P., Xagoraris, A., et al. (1990) The lateral amygdaloid nucleus: sensory interface of the amygdala in fear conditioning. J. Neurosci. 10:1062–1069. LeDoux, J.E., Iwata, J., Cicchetti, P., et al. (1988) Different projections of the central amygdaloid nucleus mediate autonomic and behavioral correlates of conditioned fear. J. Neurosci. 8:2517– 2519. Levitt, J.J., Chen, Q.C., May, F.S., et al. (2006) Volume of cerebellar vermis in monozygotic twins discordant for combat exposure: lack of relationship to post-traumatic stress disorder. Psychiatry Res. 148:143–149. Li, L., Chen, S., Liu, J., Zhang, J., He, Z., and Lin, X. (2006) Magnetic resonance imaging and magnetic resonance spectroscopy study of deficits in hippocampal structure in fire victims with recentonset posttraumatic stress disorder. Can. J. Psychiatry 51:431–437. Liberzon, I., and Martis, B. (2006) Neuroimaging studies of emotional responses in PTSD. Ann. N.Y. Acad. Sci. 1071:87–109. Liberzon, I., Taylor, S.F., Amdur, R., et al. (1999) Brain activation in PTSD in response to trauma-related stimuli. Biol. Psychiatry 45: 817–826. Loberbaum, J.P., Kose, S., Johnson, M.R., et al. (2004) Neural correlates of speech anticipatory anxiety in generalized social phobia. Neuroreport 15:2701–2705. Machlin, S.R., Harris, G.J., Pearlson, G.D., et al. (1991) Elevated medial-frontal cerebral blood flow in obsessive-compulsive patients: a SPECT study. Am. J. Psychiatry 148:1240–1242. MacMaster, F.P., Russell, A., Mirza, Y., et al. (2006) Pituitary volume in pediatric obsessive-compulsive disorder. Biol. Psychiatry 59:252–257. Malizia, A.L., Cunningham, V.J., Bell, C.J., Liddle, P.F., Jones, T., and Nutt, D.J. (1998) Decreased brain GABA(A)-benzodiazepine receptor binding in panic disorder: preliminary results from a quantitative PET study. Arch. Gen. Psychiatry 55:715–720. Maltby, N., Tolin, D.F., Worhunsky, P., et al. (2005) Dysfunctional action monitoring hyperactivates frontal-striatal circuits in obsessive-compulsive disorder: an event-related fMRI study. NeuroImage 24:495–503. Mataix-Cols, D., Wooderson, S., Lawrence, N., et al. (2004) Distinct neural correlates of washing, checking, and hoarding symptom dimensions in obsessive-compulsive disorder. Arch. Gen. Psychiatry 61:564–576. Mathew, S.J., Coplan, J.D., and Gorman, J.M. (2001) Neurobiological mechanisms of social anxiety disorder. Am. J. Psychiatry 158: 1558–1567. McGuire, P.K., Bench, C.J., Frith, C.D., et al. (1994) Functional anatomy of obsessive-compulsive phenomena. Br. J. Psychiatry 164: 459–468. Meyer, J.H., Swinson, R., Kennedy, S.H., Houle, S., and Brown, G.M. (2000) Increased left posterior parietal-temporal cortex activation after d-fenfluramine in women with panic disorder. Psychiatry Res. 98:133–143. Milad, M.R., Rauch S.L. (2007) The role of the orbitofrontal cortex in anxiety disorders. Ann. N.Y. Acad. Sci. Dec;1121:546–561. Epub 2007 Aug 14.

43: NEUROIMAGING STUDIES Moats, R., Ernst, T., Shonk, R., and Ross, B. (1994) Abnormal cerebral metabolite concentrations in patients with probable Alzheimer disease. Magn. Reson. Med. 32:110–115. Moore, G.J., MacMaster, F.P., Stewart, C., and Rosenberg, D.R. (1998) Case study: caudate glutamatergic changes with paroxetine therapy for pediatric obsessive-compulsive disorder. Am. Acad. Child Adolesc. Psychiatry 37(6):663–667. Mountz, J.M., Modell, J.G., Wilson, M.W., et al. (1989) Positron emission tomographic evaluation of cerebral blood flow during state anxiety in simple phobia. Arch. Gen. Psychiatry 46:501– 504. Nakao, T., Nakagawa, A., Yoshiura, T., et al. (2005) A functional MRI comparison of patients with obsessive-compulsive disorder and normal controls during a Chinese character Stroop task. Psychiatry Res. 139:101–114. Neumeister, A., Bain, E., Nugent, A.C., et al. (2004) Reduced serotonin type 1A receptor binding in panic disorder. J. Neurosci. 24:589–591. Nordahl, T.E., Benkelfat, C., Semple, W., et al. (1989) Cerebral glucose metabolic rates in obsessive-compulsive disorder. Neuropsychopharmacology 2:23–28. Nordahl, T.E., Semple, W.E., Gross, M., et al. (1990) Cerebral glucose metabolic differences in patients with panic disorder. Neuropsychopharmacology 3:261–272. Nordahl, T.E., Stein, M.B., Benkelfat, C., et al. (1998) Regional cerebral metabolic asymmetries replicated in an independent group of patients with panic disorders. Biol. Psychiatry 44(10):998– 1006. Notestine C.F., Stein M.B., Kennedy, C.M., et al. (2002) Brain morphometry in female victims of intimate partner violence with and without posttraumatic stress disorder. Biol. Psychiatry 51:1089– 1101. Osuch, E.A., Benson, B., Geraci, M., Podell, D., Herscovitch, P., McCann, U.D., and Post, R.M. (2001) Regional cerebral blood flow correlated with flashback intensity in patients with posttraumatic stress disorder. Biol. Psychiatry 50:246–253. Paquette, V., Lavesque, J., Mensour, B, et al. (2003) “Change the mind and you change the brain”: effects of cognitive-behavioral therapy on the neural correlatos of spider phobia. NeuroImage 18:401–409. Pavic, L., Gregurek, R., Rados, M., et al. (2007) Smaller right hippocampus in war veterans with posttraumatic stress disorder. Psychiatry Res. 154:191–198. Perani, D., Colombo, C., Bressi, S., et al. (1995) FDG PET study in obsessive-compulsive disorder: a clinical metabolic correlation study after treatment. Br. J. Psychiatry 166:244–250. Peterson, B.S., Leckman, J.F., Tucker, D., Scahill, L., Staib, L., Zhang, H., King, R., Cohen, D.J., Gore, J.C., and Lombroso, P. (2000) Preliminary findings of antistreptococcal antibody titers and basal ganglia volumes in tic, obsessive-compulsive, and attention-deficit/hyperactivity disorders. Arch. Gen. Psychiatry 57: 364–372. Phan, K.L., Britton, J.C., Taylor, S.F., et al. (2006) Corticolimbic flood flow during nontraumatic emotional processing in posttraumatic stress disorder. Arch. Gen. Psychiatry 63:184–192. Phan, K.L., Fitzgerald, D.A., Nathan P.J., and Tancer, M.E. (2006) Association between amygdala hyperactivity to harsh faces and severity of social anxiety in generalized social phobia. Biol. Psychiatry 59:424–429. Phillips, M.L., Drevets, W.C., Rauch, S.L., et al. (2003) Neurobiology of emotion perception II: Implications for major psychiatric disorders. Biol. Psychiatry 54:515–528. Pillay S.S., Rogowska, J., Gruber, S.A., Simpson, N., and Yurgelun-Todd, D.A. (2007) Recognition of happy facial affect in panic disorder: An fMRI study. J. Anxiety Disord. 21:38–93. Pissiota, A., Frans, O., Fernandez, M., von Knorring, L., Fischer, H., and Fredrikson, M. (2002) Neurofunctional correlates of post-

727

traumatic stress disorder: a PET symptom provocation study. Eur. Arch. Psychiatry Clin. Neurosci. 252:68–75. Pitman, R.K., Gilbertson, M.W., Gurvits, T.V., et al. (2006) Clarifying the origin of biological abnormalities in PTSD through the study of identical twins discordant for combat exposure. Ann. N.Y. Acad. Sci. 1071:242–254. Potts, N.L., Davidson, J.R., Krishnan, K.R., and Doraiswamy, P.M. (1994) Magnetic resonance imaging in social phobia. Psychiatry Res. 52(1):35–42. Poupon, P., Mangin, J., Clark, C.A., Frouin, V., Regis, J., Le Bihan, D., and Bloch, I. (2001) Towards inference of human brain connectivity from MR diffusion tensor data. Med. Image Anal. 5: 1–15. Protopopescu, X., Pan, H., Tuescher, O., et al. (2005) Differential time courses and specificity of amygdala activity in posttraumatic stress disorder subjects and normal control subjects. Biol. Psychiatry 57:464–473. Protopopescu, X., Pan, H., Tuescher, O., et al. (2006) Increased brain stem volume in panic disorder: a voxel-based morphometric study. Neuroreport 17:361–363. Pujol, J., Soriano-Mas, C., Alonso, P., et al. (2004) Mapping structural brain alterations in obsessive-compulsive disorder. Arch. Gen. Psychiatry 61:720–730. Pujol, J., Torres, L., Deus, J., et al. (1999) Functional magnetic resonance imaging study of frontal lobe activation during word generation in obsessive-compulsive disorder. Biol. Psychiatry 45:891– 897. Rauch, S.L., and Baxter, L.R. (1998) Neuroimaging of OCD and related disorders. In: Jenike, M.A., Baer, L., Minichiello, W.E., eds. Obsessive-Compulsive Disorders: Theory and Management. Boston: Mosby, pp. 289–317. Rauch, S.L., Jenike, M.A., Alpert, N.M., et al. (1994) Regional cerebral blood flow measured during symptom provocation in obsessive-compulsive disorder using 15O-labeled CO2 and positron emission tomography. Arch. Gen. Psychiatry 51:62–70. Rauch, S.L., Kim, H., Makris, N., Cosgrove, G.R., Cassem, E.H., Savage, C.R., Price, B., Nierenberg, A.A., Shera, D., Baer, L., Buchbinder, B., Caviness, V., Jenike, M.A., and Kennedy, D.N. (2000) Volume reduction in caudate nucleus following stereotactic lesions of anterior cingulate cortex in humans: a morphometric magnetic resonance imaging study. J. Neurosurg. 93:1019– 1025. Rauch, S.L., Savage, C.R., Alpert, N.M., et al. (1995) A positron emission tomographic study of simple phobic symptom provocation. Arch. Gen. Psychiatry 52:20–28. Rauch, S.L., Savage, C.R., Alpert, N.M., et al. (1997) The functional neuroanatomy of anxiety: a study of three disorders using PET and symptom provocation. Biol. Psychiatry 42:446–452. Rauch, S.L., Savage, C.R., Brown, H.D., et al. (1995) A PET investigation of implicit and explicit sequence learning. Hum. Brain Mapp. 3:271–286. Rauch, S.L., Shin, L.M., and Phelps, E.A. (2006) Neurocircuitry models of posttraumatic stress disorder and extinction: human neuroimaging research—past, present, and future. Biol. Psychiatry 60:376–382. Rauch, S.L., Shin, L.M., Dougherty, D.D., et al. (2002) Predictors of fluvoxamine response in contamination-related obsessive-compulsive disorder: a PET symptom provocation study. Neuropsychopharmacology 27:782–791. Rauch, S.L, Shin, L.M., Segal, E., et al. (2003) Selectively reduced regional cortical volumes in post-traumatic stress disorder. Neuroreport 14:913–916. Rauch, S.L., Shin, L.M., Whalen, P.J., and Pitman, R.K. (1998) Neuroimaging and the neuroanatomy of PTSD. CNS Spectrums 3(Suppl 2):30–41. Rauch, S.L., van der Kolk, B.A., Fisler, R.E., et al. (1996) A symptom provocation study of posttraumatic stress disorder using

728

ANXIETY DISORDERS

positron emission tomography and script-driven imagery. Arch. Gen. Psychiatry 53:380–387. Rauch, S.L., Whalen, P.J., Curran, T., Shin, L.M., Coffey, B.J., Savage, C.R., McInerney, S.C., Baer, L., and Jenike, M.A. (2001) Probing striato-thalamic function in OCD and TS using neuroimaging methods. In: Cohen, D.J., Jankovic, J., and Goetz, C.G., eds. Tourette Syndrome. Philadelphia: Lippincott, Williams & Wilkins, pp. 207–224. Rauch, S.L., Whalen, P.J., Dougherty, D.D., and Jenike, M.A. (1998) Neurobiological models of obsessive compulsive disorders. In: Jenike, M.A., Baer, L., and Minichiello, W.E., eds. ObsessiveCompulsive Disorders: Practical Management. Boston: Mosby, pp. 222–253. Rauch, S.L., Whalen, P.J., Savage, C.R., et al. (1997) Striatal recruitment during an implicit sequence learning task as measured by functional magnetic resonance imaging. Hum. Brain Mapp. 5: 124–132. Rauch, S.L., Whalen, P.J., Shin, L.M., McInerney, S.C., Macklin, M.L., Lasko, N.B., Orr, S.P., and Pittman, R.K. (2000) Exaggerated amygdala response to masked facial stimuli in posttraumatic stress disorder: a functional MRI study. Biol. Psychiatry 47:769– 776. Rauch, S.L, Wright, C.I., Martix, B., et al. (2004) A magnetic resonance imaging study of cortical thickness in animal phobia. Biol. Psychiatry 55:946–952. Reiman, E.M., Raichle, M.E., Robins, E., et al. (1986) The application of positron emission tomography to the study of panic disorder. Am. J. Psychiatry 143:469–477. Reiman, E.M., Raichle, M.E., Robins, E., et al. (1989) Neuroanatomical correlates of a lactate-induced anxiety attack. Arch. Gen. Psychiatry 46:493–500. Riffkin J., Yacel, M., Maruff, P., et al. (2005) A manual and automated MRI study of anterior cingulate and orbito-frontal cortices and caudate nucleus in obsessive-compulsive disorder: comparison with healthy controls and patients with schizophrenia. Psychiatry Res. 138:99–113. Robinson, D., Wu, H., Munne, R.A., et al. (1995) Reduced caudate nucleus volume in obsessive-compulsive disorder. Arch. Gen. Psychiatry 52:393–398. Rosenberg, D.R., Amponsah, A., Sullivan, A., MacMillan, S., and Moore, G.J. (2001) Increased medial thalamic choline in pediatric obsessive-compulsive disorder as detected by quantitative in vivo spectroscopic imaging. J. Child Neurol. 16:636–641. Rosenberg, D.R., Benazon, N.R., Gilbert, A., Sullivan, A., and Moore, G.J. (2000) Thalamic volume in pediatric obsessive-compulsive disorder patients before and after cognitive behavioral therapy. Biol. Psychiatry 48:294–300. Rosenberg, D.R., Keshevan, M.S., O’Hearn, K.M., et al. (1997) Frontostriatal measurement in treatment-naive children with obsessive-compulsive disorder. Arch. Gen. Psychiatry 554: 824–830. Rosenberg, D.R., MacMaster, F.P., Keshavan, M., et al. (2000) Decrease in caudate glutamate concentrations in pediatric obsessive-compulsive disorder patients taking paroxetine. J. Am. Acad. Child Adoles. Psychiatry 39:1096–1103. Ross, B.D., and Michaelis, T. (1994) Clinical applications of magnetic resonance spectroscopy. Magn. Reson. Q. 10:191–247. Rothman, D.L., Petroff, O.A.C., Behar, K.L., and Mattson, R.H. (1993) Localized H NMR measurements of g-aminobutyric acid in human brain in vivo. Proc. Natl. Acad. Sci. USA 90:5662– 5666. Rubin, R.T., Villaneuva-Myer, J., Ananth, J., et al. (1992) Regional xenon-133 cerebral blood flow and cerebral technetium 99m HMPAO uptake in unmedicated patients with obsessive-compulsive disorder and matched normal control subjects. Arch. Gen. Psychiatry 49:695–702. Russell, A., Cortese, B., Lorch, E., et al. (2003) Localized functional neurochemical marker abnormalities in dorsolateral prefrontal

cortex in pediatric obsessive-compulsive disorder. J. Chil. Adolesc. Psychopharmacol. 13 Suppl 1:S31–38. Sakai, Y., Kumano, H., Nishikawa, M., et al. (2006) Changes in cerebral glucose utilization in patients with panic disorder treated with cognitive behavioral therapy. NeuroImage 33: 218–226. Salzman, C., Miyawaki, E.K., le Bars, P., and Kerrihard, T.N. (1993) Neurobiologic basis of anxiety and its treatment. Harv. Rev. Psychiatry 1:197–206. Sanacora, G., Mason, G.F., Rothman, D.L., Behar, K.L., Hyder, F., Petroff, O.A.C., Berman, R.M., Charney, D.S., and Krystal, J.H. (1999) Reduced cortical g-aminobutyric acid levels in depressed patients by proton magnetic spectroscopy. Arch. Gen. Psychiatry 56:1043–1047. Sapolsky, R.M. (1986) Glucocorticoid toxicity in the hippocampus. Temporal aspects of synergy with kainic acid. Neuroendocrinology 43(3):440–444. Sapolsky, R.M. (2000) Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Arch. Gen. Psychiatry 57:825–835. Sato, T., Hasan, K., Alexander, A.L., and Minato, K. (2001) Structural connectivity in white matter using the projected diffusiontensor distance. Medinfo 10(Pt 2):929–932. Saxena, S., and Rauch, S.L. (2000) Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder. Psychiatr. Clin. North Am. 23:563–584. Saxena, S., Brody, A.L., Ho, M.L., Alborzian, S., Ho, M.K., Maidment, K.M., Huang, S.-C., Wu, H.-M., Au, S.C., and Baxter, L.R. (2001) Cerebral metabolism in major depression and obsessive-compulsive disorder occurring separately and concurrently. Biol. Psychiatry 50:159–170. Saxena, S., Brody, A.L., Ho, M.L., Alborzian, S., Maidment, K.M., Zohrabi, S., Ho, M.K., Huang, S.-C., Wu, H.-M., and Baxter, L. R. (2002) Differential cerebral metabolic changes with paroxetine treatment of obsessive-compulsive disorder vs major depression. Arch. Gen. Psychiatry 59:250–261. Saxena, S., Brody, A.L., Maidment, K.M., et al. (2004) Cerebral glucose metabolism in obsessive-compulsive hoarding. Am. J. Psychiatry 161:1038–1048. Saxena, S., Brody, A.L., Maidment, K.M., Dunkin, J.J., Colgan, M., Alborzian, S., Phelps, M.E., and Baxter, L.R. (1999) Localized orbitofrontal and subcortical metabolic changes and predictors of response to paroxetine treatment in obsessive-compulsive disorder. Neuropsychopharmacology 21:683–693. Scarone, S., Colombo, C., Livian, S., et al. (1992) Increased right caudate nucleus size in obsessive compulsive disorder: detection with magnetic resonance imaging. Psychiatry Res. Neuroimag. 45:115–121. Schienle, A., Schaufer, A., Walter, B., et al. (2005) Brain activation of spider phobics towards disorder-relevant, generally disgustand fear-inducing pictures. Neurosci. Lett. 388:1–6. Schneider, F., Weiss, U., Kessler, C., et al. (1999) Subcortical correlates of differential classical conditioning of aversive emotional reactions in social phobia. Biol. Psychiatry 45:863–871. Schneier, F.R., Liebowitz, M.R., Abi-Dargham, A., Zea-Ponce, Y., Shu-Hsing, L., and Laruelle, M. (2000) Low dopamine D2 receptor binding potential in social phobia. Am. J. Psychiatry 157:457– 459. Schuff, N., Marmar, C.R., Weiss, D.S., et al. (1997) Reduced hippocampal volume and N-acetyl aspartate in posttraumatic stress disorder. In: Yehuda, R., and McFarlane, A.C., eds. Psychobiology of Posttraumatic Stress Disorder, Vol. 821. New York: New York Academy of Sciences, pp. 516–520. Schuff, N., Neylan, T.C., Lenoci, M.A., Du, A.-T., Weiss, D.S., Marmar, C.R., and Weiner, M.W. (2001) Decreased hippocampal Nacetylaspartate in the absence of atrophy in posttraumatic stress disorder. Biol. Psychiatry 50:952–959. Schunck, T., Erb, G., Mathis A., et al. (2006) Functional magnetic resonance imaging characterization of CCK-4 –induced panic at-

43: NEUROIMAGING STUDIES tack and subsequent anticipatory anxiety. NeuroImage 31:1197– 1208. Schwartz, C.E., Snidman, N., and Kagan, J. (1999) Adolescent social anxiety as an outcome of inhibited temperament in childhood. J. Am. Acad. Child Adolesc. Psychiatry 38:1008–1015. Schwartz, J.M., Stoessel, P.W., Baxter, L.R., et al. (1996) Systematic changes in cerebral glucose metabolic rate after successful behavior modification. Arch. Gen. Psychiatry 53:109–113. Seedat, S., Videen, J.S., Kennedy, C.M., and Stein, M.B. (2005) Single voxel proton magnetic resonance spectroscopy in women with and without intimate partner violence-related posttraumatic stress disorder. Psychiatry Res. 139:249–258. Semple, W.E., Goyer, P.F., McCormick, R., Donovan, B., Muzic, R.F., Jr., Rugle, L., McCutcheon, K., Lewis, C., Liebling, D., Kowaliw, S., Vapenik, K., Semple, M.A., Flener, C.R., and Schulz, S.C. (2000) Higher brain blood flow at amygdala and lower frontal cortex blood flow in PTSD patients with comorbid cocaine and alcohol abuse compared with normals. Psychiatry 63:65–74. Shapira, N.A., Liu, Y., He, A.G., et al. (2003) Brain activation by disgust-inducing pictures in obsessive-compulsive disorder. 54: 751–756. Shin, L.M., Kosslyn, S.M., McNally, R.J., et al. (1997) Visual imagery and perception in posttraumatic stress disorder: a positron emission tomographic investigation. Arch. Gen. Psychiatry 54: 233–241. Shin, L.M., McNally, R.J., Kosslyn, S.M., et al. (1999) Regional cerebral blood flow during script-driven imagery in childhood sexual abuse–related posttraumatic stress disorder: a PET investigation. Am. J. Psychiatry 156:575–584. Shin, L.M., Orr, S.P., Carson, M.A., et al. (2004) Regional cerebral blood flow in the amygdala and medial prefrontal cortex during traumatic imagery in male and female Vietnam veterans with PTSD. Arch. Gen. Psychiatry 61:168–176. Shin, L.M., Rauch, R.L., and Pitman, R.K. (2006) Amygdala, medial prefrontal cortex and hippocampal function in PTSD. Ann. N.Y. Acad. Sci. 1071:67–79. Shin, L.M., Whalen, P.J., Pitman, R.K., Bush, G., Macklin, M.L., Lasko, N.B., Orr, S.P., McInerney, S.C., and Rauch, S.L. (2001) An fMRI study of anterior cingulate function in posttraumatic stress disorder. Biol. Psychiatry 50:932–942. Shin, L.M., Wright, C.I., Cannistraro, P.A., et al. (2005) A functional magnetic resonance imaging study of amygdala and medial prefrontal cortex responses to overtly presented fearful faces in posttraumatic stress disorder. Arch. Gen. Psychiatry 62: 273–281. Simpson, H.B., Lombardo, I., Slifstein, M., et al. (2003) Serotonin transporters in obsessive-compulsive disorder: A positron emission tomography study with [11-C]McN 5652. Biol. Psychiatry 54:1414–1421. Stein, M.B. (1998) Neurobiological perspectives on social phobia: from affiliation to zoology. Biol. Psychiatry 44:1277–1285. Stein, M.B., Goldin, P.R., Sareen, J, et al. (2002) Increased amygdala activation to angry and contemptuous faces in generalized social phobia. Arch. Gen. Psychiatry 59:1027–1034. Stein, M.B., Koverola, C., Hanna, C., et al. (1997) Hippocampal volume in women victimized by childhood sexual abuse. Psychol. Med. 27:951–960. Stengler-Wenzke, K., Muller, U., Angermeyer, M.C., et al. (2004) Reduced serotonin transporter availability in obsessive-compulsive disorder. Eur. Arch. Clin. Neurosci. 254:252–255. Stewart, R.S., Devous, M.D. Sr., Rush, A.J., Lane, L., and Bonte, F.J. (1988) Cerebral blood flow changes during sodium-lactate-induced panic attacks. Am. J. Psychiatry 145(4):442–449. Straube, T., Glauer, M., Dilger, S., et al. (2006) Effects of cognitivebehavioral therapy on brain activation in specific phobia. NeuroImage 29:125–135. Straube, T., Kolassa, I-T., Glauer, M., et al. (2004) Effect of task conditions on brain responses to threatening faces in social pho-

729

bics: an event-related functional magnetic resonance imaging study. Biol. Psychiatry 56:921–930. Straube, T., Mentzel, H.J., and Miltner, W.H. (2005) Common and distinct brain activation to threat and safety signals in social phobia. Neuropsychobiology 52:163–168. Straube, T., Mentzel, H.J., and Miltner, W.H. (2006) Neural mechanisms of automatic and direct processing of phobogenic stimuli in specific phobia. Biol. Psychiatry 59:162–170. Swedo, S.E., Pietrini, P., Leonard, H.L., et al. (1992) Cerebral glucose metabolism in childhood-onset obsessive-compulsive disorder: revisualization during pharmacotherapy. Arch. Gen. Psychiatry 49:690–694. Swedo, S.E., Shapiro, M.B., Grady, C.L., et al. (1989) Cerebral glucose metabolism in childhood-onset obsessive-compulsive disorder. Arch. Gen. Psychiatry 46:518–523. Szeszko, P.R., MacMillan, S., McMeniman, M., et al. (2004) Brain structural abnormalities in psychotropic drug-naïve pediatric obsessive compulsive disorder. Am. J. Psychiatry 161:1049–1056. Szeszko, P.R., Robinson, D., Alvir, J.M., et al. (1999) Orbital frontal and amygala volume reductions in obsessive-compulsive disorder. Arch. Gen. Psychiatry 56:913–919. Tiihonen, J., Kuikka, J., Bergstrom, K., Lepola, U., Koponen, H., and Leinonen, E. (1997) Dopamine reuptake site densities in patients with social phobia. Am. J. Psychiatry 154(2):239–242. Tillfors, M., Furmark, T., Marteinsdottir, I., Fischer, H., Pissiota, A., Langstrom, B., and Fredrikson, M. (2001) Cerebral blood flow in subjects with social phobia during stressful speaking tasks: a PET study. Am. J. Psychiatry 158:1220–1226. Ursu, S., Stenger, V.A., Shear, M.K., et al. (2003) Overactive action monitoring in obsessive-compulsive disorder: evidence from functional magnetic resonance imaging. Psychological Sci. 14: 347–353. van den Heuvel, O.A., Veltman, D.J., Groenewegen, H.J., et al. (2005a) Disorder-specific neuroanatomical correlates of attentional bias in obsessive-compulsive disorder, panic disorder, and hypochondriasis. Arch. Gen. Psychiatry 62:922–933. van den Heuvel, O.A., Veltman, D.J., Groenenwegen, H.J., et al. (2005b) Frontal striatal dysfunction during planning in obsessive-compulsive disorder. Arch. Gen. Psychiatry 62:301–310. Van der Linden, G., van Heerden, B., Warwick, J., Wessels, C., van Kradenburg, J., Zungu-Dirwayi, N., and Stein, D.J. (2000) Functional brain imaging and pharmacotherapy in social phobia: single photon emission computed tomography before and after treatment with the selective serotonin reuptake inhibitor citalopram. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 24:419–438. van der Wee, N.J., Stevens, H., Hardeman, J.A., et al. (2004) Enhanced dopamine transporter density in psychotropic-naive patients with obsessive-compulsive disorder shown by [123-I]b-CIT SPECT. Am. J. Psychiatry 161:2201–2206. Whalen, P.J., Bush, G., McNally, R.J., et al. (1998) The emotional counting Stroop paradigm: an fMRI probe of the anterior cingulate affective division. Biol. Psychiatry 44:1219–1228. Whalen, P.J., Rauch, S.L., Etcoff, N.L., McInerney, S., Lee, M.B., and Jenike, M.A. (1998) Masked presentations of emotional facial expressions modulate amygdala activity without explicit knowledge. J. Neurosci. 18:411–418. Viard, A., Flament, M.F., Artiges, E., et al. (2005) Cognitive control in childhood-onset obsessive-compulsive disorder: a functional MRI study. Psychol. Med. 35:1007–1017. Viet, R., Flor, H., Erb, M., et al. (2002) Brain circuits involved in emotional learning in antisocial behavior and social phobia in humans. Neurosci. Lett. 328:233–236. Vythilingam, M., Anderson, E.R., Goddard, A., Woods, S.W., Staib, L.H., Charney, D.S., and Bremner, J.D. (2000) Temporal lobe volume in panic disorder—a quantitative magnetic resonance imaging study. Psychiatry Res. 99:75–82. Wik, G., Fredrikson, M., Ericson, K., et al. (1993) A functional cerebral response to frightening visual stimulation. Psychiatry Res. Neuroimag. 50:15–24.

730

ANXIETY DISORDERS

Williams, L.M., Kempt, A.H., Felmingham, K., et al. (2006) Trauma modulates amygdala and medial prefrontal responses to consciously attended fear. NeuroImage 29:347–357. Winton, E.C., Clark, D.M., and Edelmann, R.J. (1995) Social anxiety, fear or negative evaluation and the detection of negative emotion in others. Behaviour Res. Ther. 33:193–196. Woods, S.W., Koster, K., Krystal, J.K., et al. (1988) Yohimbine alters regional cerebral blood flow in panic disorder. Lancet 2:678. Woodward, S.H., Kaloupek, D.F., Streeter, C.C., et al. (2006) Decreased anterior cingulate volume in combat-related PTSD. Biol. Psychiatry 59:582–587.

Yamasue, H., Kasai, K., Iwanami, A., et al. (2003) Voxel-based analysis of MRI reveals anterior cingulate gray-matter volume reduction in posttraumatic stress disorder due to terrorism. Proc. Natl. Acad. Sci. 1000:9039–9043. Yoon, K.L., Fitzgerald, D.A., Angstadt, M. et al. (2007) Amygdala reactivity to emotional faces at high and low intensity in generalized social phobia: a 4-Tesla functional MRI study. Psychiatry Res: Neuroimag. 154:93–98. Zubieta, J.K., Chinitz, J.A., Lombardi, U., et al. (1999) Medial frontal cortex involvement in PTSD symptoms: a SPECT study. J. Psychiatric Res. 33:259–264.

44 Pharmacotherapy of Anxiety Disorders SANJAY J. MATHEW, ELLEN J. HOFFMAN,

A N D

DENNIS S. CHARNEY

This chapter reviews pharmacological treatments for patients with anxiety disorders, focusing on the published randomized controlled trial (RCT) literature (pharmacological treatment of obsessive–compulsive disorder (OCD) is discussed elsewhere in this volume (see Chapter 42). The anxiety disorders with the greatest evidence for the efficacy of pharmacotherapy are generalized anxiety disorder (GAD), panic disorder (PD), and social anxiety disorder (SAD); accordingly, the chapter is primarily devoted to these three disorders. The medication classes most commonly used for these disorders, the selective serotonin reuptake inhibitors (SSRIs) and serotonin and norepinephrine reuptake inhibitors (SNRIs), are first presented, and then other commonly utilized pharmacotherapy approaches such as the benzodiazepines, anticonvulsants, and atypical antipsychotics are reviewed. We conclude with recommendations for areas of future investigation and limitations of current approaches. Due to space limitations (and publication bias), we undoubtedly have failed to review every RCT conducted in the anxiety disorders as of July 2007, including those therapies categorized under complementary and alternative medicine. With new clinical trials data emerging in this therapeutic area at a rapid pace, the evidence base is a constantly moving target. Thus, in making informed decisions regarding an individual medication’s efficacy, it is imperative for clinicians and researchers to consult several sources for up-to-date safety and efficacy information. First, drug manufacturer websites are encouraged to maintain registries of all clinical trials conducted on a compound, regardless of publication status, in which key methodological details of clinical trials are available (however, for older generic medications this data is unavailable). Second, all clinical trials initiated after 2005 must be formally registered on www.clini caltrials.gov, which summarizes the major end points and trial design for new studies. For a reasonably updated collection of evidence-based guidelines for anxiety and related conditions, including post-traumatic

stress disorder (PTSD), the reader is encouraged to evaluate summaries of clinical trials data from several independent, web-accessible sources that include published and unpublished drug manufacturer data: (1) National Institute for Health and Clinical Excellence (NICE) guidelines (www.nice.org.uk) and (2) Cochrane Reviews, specifically Cochrane Depression, Anxiety & Neurosis Group (CCDAN) Controlled Trials Register (www.coch rane.org), and for PTSD, the International Psychopharmacology Algorithm Project (www.ipap.org). SELECTIVE SEROTONIN REUPTAKE INHIBITORS (SSRIs) Selective serotonin reuptake inhibitors are considered first-line medications for the treatment of the anxiety disorders, including GAD, PD, SAD, and PTSD (Davidson 2006; Katon, 2006; D.J. Stein, Ipser, et al. 2006; Mathew and Hoffman, in press). Table 44.1 shows the SSRIs that have received U.S. Food and Drug Administration (FDA) approval for the treatment of these disorders. Although older classes of antidepressant medications, such as the tricyclic antidepressants (TCAs) and monoamine oxidase inhibitors (MAOIs) have been shown to be effective for many anxiety and mood disorders, SSRIs are the most commonly prescribed due to their more favorable side-effect profile. In addition, in contrast to the benzodiazepines (BZDs), SSRIs have the critical advantage of treating comorbid mood disorders, whereas long-term administration is not associated with physiological dependence or abuse liability. SSRIs in Generalized Anxiety Disorder In the treatment of GAD, multiple randomized, double-blind, placebo-controlled clinical trials using large multicenter sample sizes in the range of approximately 300 to 600 have demonstrated the efficacy of several SSRIs (Mathew and Hoffman, in press). Of the SSRIs, paroxetine and escitalopram are FDA-approved for GAD. 731

TABLE

44.1 FDA-Approved Medications for the Anxiety Disordersa in Adults

Medication

GAD

PD

PTSD

SAD

Anxiety Disordersb

Year of Initial FDA Approval

Daily Dose Range

Other Approved Psychiatric Indications

Y

-

-

-

-

2002

10 –20 mg

MDD

-

Y

-

-

-

1987

20 – 60 mg

MDD, OCD, PMDD Bulimia Nervosa

SSRIs Escitalopram (Lexapro) Fluoxetine (Prozac)

PD: 10 –60 mg Paroxetine

SAD: 20 – 60 mg

(Paxil)

Y

Y

Y

Y

-

1992

GAD, PTSD: 20 –50 mg

MDD, OCD

Paroxetine CR (Paxil CR)

-

Y

-

Y

-

2002

-

Y

Y

Y

-

1991

50–200 mg

MDD, OCD, PMDD

(Cymbalta)

Y

-

-

-

-

2004

30 –120 mg

MDD

Venlafaxine XR (Effexor XR)

Y

Y

-

Y

-

1997

37.5–225 mg

MDD

Yc

-

-

-

Y

1986

15– 60 mg

Short-term relief of anxiety sx.

0.75– 4 mg

Short-term relief of anxiety sx; Anxiety assoc. w/ depression

PD: 12.5 –75 mg SAD: 12.5–37.5 mg

MDD, PMDD

Sertraline (Zoloft) SNRIs Duloxetine

Azapirone Buspirone (BuSpar) Benzodiazepines Alprazolam (Xanax)

Yc

Y

-

-

Y

1981

3–6 mg (suggested) Alprazolam XR (Xanax XR)

Chlordiazepoxide (Librium)

-

Y

-

-

-

2003

1–10 mg (used in clinical trials)

None Short-term relief of anxiety sx; ETOH w/ d; preoperative anxiety

-

-

-

-

Y

1960

15–100 mg

-

Y

-

-

-

1975

0.5– 4 mg

None

15– 60 mg

Short-term relief of anxiety sx.; ETOH w/d

4 – 40 mg

Short-term relief of anxiety sx.; ETOH w/d

1–10 mg

Short-term relief of anxiety sx; anxiety assoc. w/ depression

30–120 mg

Short-term relief of anxiety sx; anxiety assoc. w/depression; anxiety in older patients; ETOH w/d

Clonazepam (Klonopin) Clorazepate (Tranxene)

-

-

-

-

Y

1972

Diazepam (Valium)

-

-

-

-

Y

1963

Lorazepam (Ativan)

-

-

-

-

Y

1977

Oxazepam (Serax)

-

-

-

-

Y

1965

SSRI: selective serotonin reuptake inhibitor; SNRI: serotonin an norepinephrine reuptake inhibitor; GAD: generalized anxiety disorder; PD: panic disorder; PTSD: posttraumatic stress disorder; SAD: social anxiety disorder; MDD: major depressive disorder; PMDD: premenstrual dysphoric disorder; OCD: obsessive– compulsive disorder; ETOH: alcohol; FDA: U.S. Food and Drug Administration. a Table includes DSM-IV-TR anxiety disorders, except OCD. b No individual disorder specified. c Approved for anxiety disorders that correspond most closely to GAD as described in DSM-III.

732

44: PHARMACOTHERAPY

Two 8-week studies found that paroxetine, in fixed or flexible doses, led to significant reductions in the Hamilton Rating Scale for Anxiety (HAM-A) in GAD compared to placebo (Pollack et al., 2001; Rickels et al., 2003). Rickels et al. (2003) documented that 62% and 68% of patients with GAD receiving paroxetine (20 mg or 40 mg/day, respectively) were responders on the Clinical Global Impression–Improvement (CGI-I) scale (obtaining scores of 1 or 2) after 2 months, compared to 46% of patients receiving placebo. In addition, a significant percentage of patients in the paroxetine groups (30% and 36% in the 20 mg, 40 mg groups, respectively) achieved remission (defined as HAM-A ≤ 7) versus placebo (20%) (Rickels et al., 2003). A flexible dose study of paroxetine (20–50 mg/day) found a significant decrease in the anxious mood item on the HAMA, which includes “worrying” and “anticipating the worst,” by the first week of treatment. Significant overall rates of response (62% vs. 47%), defined as CGI-I of 1 or 2, and remission (36% vs. 23%), defined as HAM-A ≤ 7, versus placebo, were found after 8 weeks (Pollack et al., 2001). Escitalopram (10 –20 mg/day) was found to result in significant reductions in total and psychic anxiety subscale scores on HAM-A beginning in the first week of treatment, with significant rates of CGI-I response versus placebo (58% vs. 38%) in the last observation carried forward (LOCF) analysis, and remission (36% vs. 16%, in completers) at the conclusion of the 8-week trial (Davidson, Bose, et al. 2004). Davidson et al. (2005) demonstrated the long-term efficacy of escitalopram in GAD, in a 6-month, open-label extension study for completers of three 8-week, double-blind, controlled escitalopram trials (N = 521, intent-to-treat). This study showed ongoing improvement in HAM-A and qualityof-life scores in the open-label phase, such that 76% of patients were responders and 49% were remitters in the LOCF analysis (Davidson et al., 2005). Longer-term continuation studies have also shown that escitalopram and paroxetine are effective in preventing relapse in GAD (Stocchi et al., 2003; Allgulander et al., 2005). Compared to patients who continued to receive escitalopram or paroxetine for 6 months, the risk of relapse was approximately 4 or 5 times greater, respectively, in the placebo groups (Stocchi et al., 2003; Allgulander et al., 2005). In a head-to-head study of these two SSRIs in GAD (see Table 44.2 for an overview of head-to-head studies in GAD), Bielski et al. (2005) showed that both medications led to improvement in quality of life and similar reductions in HAMA scores after 6 months, though escitalopram resulted in fewer dropouts due to adverse events (AEs) than paroxetine. Although not FDA-approved, sertraline has also been shown to be effective in GAD (Allgulander, Dahl, et al., 2004; Dahl et al., 2005). Allgulander, Dahl, et al.

733

(2004) identified similar response and remission rates for sertraline (50–150 mg/day) after 3 months as those described in the paroxetine studies, with significant reductions in HAM-A scores occurring after 1 month of treatment. One head-to-head study found that sertraline (25–100 mg/day) and paroxetine (10 – 40 mg/day) resulted in comparable response and remission rates, as well as improvement in quality of life scores, after 2 months (Ball et al., 2005; see Table 44.2). Although there is evidence that the other SSRIs (citalopram, fluoxetine, fluvoxamine) treat anxiety symptoms in patients with depression, to our knowledge there are no published RCTs of these medications specifically for GAD. A meta-analysis of 8 RCTs of antidepressants, including imipramine, venlafaxine, and paroxetine, in adults with GAD without comorbid Axis I diagnoses (N = 2058), found that antidepressants were more effective than placebo, with a number-needed-to-treat (NNT) of 5.15 (Kapczinski et al., 2003). Dropout rates were not different among the different antidepressants (Kapczinski et al., 2003). SSRIs in Panic Disorder The goals of PD treatment with SSRIs, according to the Working Group on Panic Disorder (1998), are to decrease the frequency and intensity of panic attacks, decrease anticipatory anxiety, and treat associated depressive symptoms. The safety and overall tolerability of the SSRIs has led to the recommendation of these medications as first-line agents in PD, though SSRIs, TCAs, and BZDs have been shown to be equally effective in the treatment of PD and associated anxiety symptoms (Heuer et al., in press). As patients with PD may be particularly sensitive to medication side effects, starting SSRIs at low doses with slow titration is recommended to minimize adverse effects that may occur early in treatment, including nausea, anxiety, tremors, jitteriness, anorexia, insomnia, and sexual dysfunction (Katon, 2006; Heuer et al., in press). If a patient with PD does not respond to initial treatment with an SSRI, then a trial of another SSRI should be attempted; if an adequate response is not obtained, then switching to a different medication class, such as the SNRIs, TCAs, or BZDs, is recommended (Heuer et al., in press). Meta-analyses support the efficacy of SSRIs in treating PD and have found similar effect sizes of SSRIs compared to older agents, including TCAs and BZDs (Otto et al., 2001; Mitte, 2005). Mitte (2005) performed a meta-analysis of 124 studies examining psychotherapy and pharmacotherapy in PD, finding that though pharmacotherapy was superior to placebo, cognitivebehavioral and behavioral therapies were at least as effective as pharmacotherapy. In addition, there were similar, moderate effect sizes for anxiety reduction (Hedges’ g ≈ 0.40), and similar attrition rates among

TABLE

44.2 Head-to-Head Trials of SSRIs and SNRIs in the Anxiety Disordersa

Author, Study Funding Source

Design, Weeks

Medication(s) Studied, mg/Day

n

Primary Outcome Measuresb

25

% Reduction in

Secondary Outcome Measuresb

Remission Rates %b

Tolerabilityb

Comment

GENERALIZED ANXIETY DISORDER Ball et al. (2005), Pfizer, Inc.

Randomized, double-blind, flexible-dose, 8

Paroxetine 10–40

28

Sertraline 25–100

No significant difference in HAM-A: reductions on IU57.3 GAMS and BAI 55.9 scores, or improvement of Q-LES-Q % Responders (≥50% between 2 groups. HAM-A reduction from baseline):

CGI-S = 1 No significant difference between groups in (normal): posttreatment SAFTEE 40% scores. 46%

No significant difference between two groups. No placebo arm.

68 61 Bielski et al. (2005),

Randomized,

Forest Laboratories, Inc.

double-blind flexible-dose 24

Paroxetine 20–50

61

Mean reduction in

60

HAM-A:

Escitalopram 10–20

Both medications led to improvements over time in CGI-I, CGI-S, quality of life.

NA

% Responders (≥50% Significant improvement in CGI-S over HAM-A reduction time, but no group from baseline): or time x group 90.5 interactions found. 92.0

33.3

–13.3 –15.3

Withdrew due to AE [Sign.]:

No placebo arm.

22.6% 6.6%

% CGI-I ≤ 2 by 24 weeks: 62.3 78.3 Kim et al. (2006),

Randomized,

Korean Health 21 R&D Project

open-label, flexible-dose, 8

Hartford et al. (2007),

Randomized,

Eli Lilly and Company, double-blind, Boehringer Ingelheim Placebocontrolled, flexible, 10

Venlafaxine XR 37.5– 225

21 25

Paroxetine 10–40

Duloxetine 60–120

162

Venlafaxine XR 75–225 (as active comparator)

161

Placebo

164

Mean change in HAM-A:

Both medications led to significant improvements vs. –11.80c placebo on CGI-I, –12.40c PGI-I, SDS, HADS –9.19 anxiety and depression % Responders (≥50% subscales. HAM-A reduction from baseline): 47

36.0

% HAM-A ≤ 7:

Paroxetine resulted in a significant weight gain compared to venlafaxine, (though no patient had weight gain ≥7% baseline body weight); venlafaxine XR led to significant increases in BP compared to paroxetine.

No placebo. There were significant decreases in HAM-A and CGI-S in both groups, though no significant differences between groups.

% Discontinuation due to AE:

No statistical comparisons made between medication groups. Duloxetine and venlafaxine XR led to significant decreases in HAM-A beginning at weeks 1 and 2, respectively, vs. placebo. Discontinuation rates overall were not different among three groups.

23

14.2c

30c

11.0c

19

1.9 % DEAEs: 19.4 26.9c 15.8

54c 37 % Responders (CGI-I ≤ 2): 55.7c 60.4c 41.8 PANIC DISORDER Perna et al. (2001),

Randomized,

None

single-blind, flexible, 8.6

Citalopram 20–50

27

% No agoraphobia:

25

70

Paroxetine 20–50

62 % No anticipatory anxiety: 85 84

Significant decrease in mean PASS scores over time (from beginning to study end), that is, significant “time” effect, for both citalopram and paroxetine, in posthoc comparison.

NA

No significant differences in AE between groups.

Single-blind study. No placebo. Analyses only included completers.

NA

Discontinuation rates due to AE:

Both escitalopram and citalopram led to significant changes vs. PBO on PAS and CGI-I.

Stahl et al. (2003),

Randomized,

Panic attack frequency:

% Panic free:

double-blind,

Escitalopram 10–20

128

Forest Laboratories, Inc.

119

–1.61c

50 (p = 0.051)

Placebocontrolled,

Citalopram 20–40

119

–1.43

39

6.3%

–1.32

38

8.4%

flexible,

Placebo

7.6%

10 Bandelow et al. (2004), Randomized, Pfizer, Inc.

double-blind, flexible, 12

Paroxetine 40–60

113

PAS total score:

115

–12.7

Panic attack frequency:

–13.5

–2.13

Sertraline 50–150

NA

More patients discontinued due to AE in paroxetine group, but NS; Significantly higher weight gain in paroxetine group.

–1.82 CGI-I:

No placebo. During 3-week taper, significantly more patients in sertraline group were panic free vs. paroxetine group.

–2.4 2.2 Pollack et al. (2007),

Randomized,

158

double-blind,

Venlafaxine XR 75

Wyeth Research

placebocontrolled,

Venlafaxine XR 150

161

fixed, 12

Paroxetine 40 Placebo

159 156

% Panic-free (full Significant decrease in symptom attacks) on PASS total score PAS: and PAAS full symptom panic c 54.4 attack frequency, in c 59.7 all medication 60.9 c groups beginning by week 4. 35.3 Significant improvements in all

CGI-S ≤ 2 and no full panic attacks on PASS:

% ≥1 AE:

43.0

67

43.4

% Taper AE:

44.4c

37

23.7

43

c c

74 71 75

No significant differences in efficacy between the two venlafaxine XR groups or the venlafaxine and paroxetine groups. Significant % attained remission vs. placebo by week 6 in both venlafaxine XR groups and by week 8 in the paroxetine group.

(Continued)

TABLE

44.2 Head-to-Head Trials of SSRIs and SNRIs in the Anxiety Disordersa

Author, Study Funding Source

Design, Weeks

Medication(s) Studied, mg/Day

n

(Continued)

Primary Outcome Measuresb

Secondary Outcome Measuresb

% Responders (CGI-I ≤ 2):

medication groups on SDS.

Remission Rates %b

Tolerabilityb

Comment

43 17

76.6c 79.2c 80.6c 55.8 SOCIAL ANXIETY DISORDER Allgulander, Mangano et al. (2004), Wyeth Research

Randomized,

Venlafaxine XR 75–225

129

Change in LSAS:

double-blind,

128

–36.0c

placebocontrolled,

Paroxetine 20–50

132

–35.4c

flexible,

–19.1

Placebo

% Responders (week 12) (CGI-I ≤ 2):

12

Significant improvement on SPIN scores and CGI-S in both venlafaxine XR and paroxetine groups vs. placebo.

LSAS ≤ 30:

% TEAEs:

38c

90

29c

89

All medication groups with significant reductions on CGIS vs. placebo at weeks 12 and 24, (observed cases)

NA

13

Significant increases in total and HDL cholesterol in both medication groups vs. placebo; greater mean increases in heart rate in paroxetine vs. venlafaxine XR groups. Significant increase in weight from baseline in venlafaxine XR group.

69c 66c 36

Lader et al. (2004),

Randomized,

Escitalopram 5

167

H. Lundbeck A/S

double-blind,

Escitalopram 10

167

Change in LSAS (week 12):

170

–38.7c

169

–34.6

166

–39.8c

placebocontrolled, fixed, 12 and 24

Escitalopram 20 Paroxetine 20 (active comparator) Placebo

–39.3c –29.5 % Responders (week 12) (CGI-I ≤ 2) (Observed Cases):

82

Significant reductions in LSAS total scores in venlafaxine XR and paroxetine groups vs. placebo beginning at week 3.

% TEAEs (week 24): 68.9 72.5 78.2 79.3 60.8

LOCF data only given for primary efficacy measure at week 12. LSAS improvement in escitalopram 20 mg group significantly greater than in paroxetine 20 mg group in observed cases by week 16.

69c 66c 71c 72c 50 % Responders (week 24) (CGI-I ≤ 2) (Observed Cases): 79c 76 88c 80c 66 Liebowitz, Gelenberg Randomized, et al. (2005), double-blind, Wyeth Research placebocontrolled, flexible, 12

Venlafaxine XR 75–225

146 147

Change in LSAS (week 12):

Paroxetine 20–50

147

–35.00c

Placebo

–39.20c –22.20 % Responders (week 12) (CGI-I ≤ 2): 58.6c 62.5c 36.1

Both medication groups with significant improvement vs. placebo on Social Phobia Inventory and CGI-S by study end. No significant differences observed between medication groups.

NA

%TEAEs:

Significant differences in LSAS between venlafaxine 95.7 XR and placebo beginning 91.5 at week 1, and paroxetine 85.6 and placebo beginning at week 3. No significant Significant increases in differences in LSAS diastolic and systolic blood between medication groups. pressure, total cholesterol, and HDL vs. placebo observed in both medication groups. Significant decrease in weight noted in venlafaxine XR vs. placebo and paroxetine groups.

Table includes DSM-IV-TR Anxiety Disorders (except OCD and PTSD). LOCF data given unless otherwise noted. Differences between medication groups were not significant unless otherwise noted. c : Significant vs. placebo AE: adverse events; BAI: Beck Anxiety Inventory; CGI-I: Clinical Global Impressions-Improvement scale; CGI-S: Clinical Global Impressions-Severity of Illness; DEAE: Discontinuation-emergent adverse events; HADS: Hospital Anxiety and Depression Scale; HAM-A: Hamilton Rating Scale for Anxiety; IU-GAMS: Indiana University Generalized Anxiety Measurement Scale; LSAS: Liebowitz Social Anxiety Scale; NA: not available; NS: not significant; PAS: Panic and Agoraphobia Scale; PASS: Panic Associated Symptoms Scale; PBO: placebo; PGI-I: Patient Global Impression of Improvement; Q-LES-Q: Quality of Life Enjoyment and Satisfaction Questionnaire; SAFTEE: Systematic Assessment for Treatment Emergent Events; SDS: Sheehan Disability Scale; [Sign.]: significant; SNRI: serotonin-norepinephrine reuptake inhibitor; SPIN: Social Phobia Inventory; SSRI: selective serotonin reuptake inhibitor; TEAEs: treatment-emergent adverse events; BP: blood pressure; HDL: high-density lipoprotein; LOCF: last observation carried forword; OCD: obsessive–compulsive disorder; PTSD: posttraumatic stress disorder. a

b

738

ANXIETY DISORDERS

SSRIs (17 trials), TCAs (23 trials), and BZDs (25 trials) (Mitte, 2005). Otto et al. (2001) analyzed 12 placebocontrolled trials of SSRIs in PD and likewise noted no significant differences in effect size or tolerability between SSRIs and older antidepressants, with a mean study effect size of 0.55 for SSRIs. A meta-analysis by the Cochrane Collaboration reviewed 23 randomized comparisons of combined psychotherapy and antidepressants in PD (Furukawa et al., 2007). This metaanalysis also found that SSRIs (7 trials) and TCAs (14 trials) were similarly effective (Furukawa et al., 2007). Additionally, the authors concluded that in the first 2– 4 months of treatment, combination psychotherapy and pharmacotherapy was more effective than either antidepressant treatment or psychotherapy alone. In the long-term (6–24 months), however, though combination therapy continued to be superior to antidepressant medication alone, it was not superior to psychotherapy alone, though there was no disadvantage of long-term combination treatment (Furukawa et al., 2007). Randomized controlled trials have supported the efficacy of most SSRIs, including the four that are FDAapproved (paroxetine, paroxetine CR, sertraline, and fluoxetine; Table 44.1), as well as fluvoxamine, citalopram, and escitalopram. Paroxetine was the first SSRI to obtain the FDA indication for PD. Placebo-controlled studies, using clomipramine as an active comparator agent, demonstrated that paroxetine’s efficacy in PD after 12 and 36 weeks (Lecrubier, Bakker, et al. 1997, Lecrubier and Judge, 1997). In a 10-week RCT, Ballenger et al. (1998) compared three fixed doses of paroxetine (10, 20, or 40 mg/day) and demonstrated that only the group receiving 40 mg/day of paroxetine was significantly free of panic attacks during the 2 weeks prior to the end of the study (86% of patients) and showed significant reductions in total number of panic attacks by week 4. In a pooled analysis of three 10-week RCTs, controlled-release paroxetine (paroxetine CR) was determined to be significantly more effective than placebo with respect to the percentage of patients who were free of panic attacks in the 2 weeks prior to study end point (63% vs. 53% in the LOCF analysis; 73% vs. 60% of completers) (Sheehan et al., 2005). In addition, paroxetine CR resulted in a significant reduction in the number of full panic attacks by the last 2 weeks of the study, and there was a significant difference in CGI-I response in the paroxetine CR group beginning at week 3 (Sheehan et al., 2005). RCTs have also demonstrated the efficacy of sertraline in PD (Pohl et al., 1998; Pollack et al., 1998; Rapaport et al., 2001). Pohl et al. (1998) provided evidence that treatment with sertraline (50–200 mg/day) was associated with a decrease in number of panic attacks after 10 weeks (77% in the sertraline group vs. 51% for placebo). The authors described a significant decrease in the number of panic attacks per week compared to

placebo by week 3 (observed cases analysis), and significantly more patients in the sertraline group (62%) were panic free by study end point, compared to 46% in the placebo group (Pohl et al., 1998). Also, Pollack et al. (1998) showed that after 10 weeks, sertraline (50 –200 mg/day) led to significant reductions compared to placebo in the frequency of panic attacks and in scores on the Panic Disorder Severity Scale (PDSS), which measures the frequency and severity of panic and agoraphobic symptoms. In a 28-week discontinuation RCT, Rapaport et al. (2001) showed that significantly more patients in the placebo group (33%), compared to those continued on sertraline after 1 year of open-label treatment (13%), experienced exacerbation of PD symptoms (p = 0.005), though the difference in full relapse rates between the two groups was not statistically significant. In a 10-week RCT of two fixed doses of fluoxetine (10 or 20 mg/day), the higher dose resulted in significant improvements on more outcome variables than the lower dose (for example, CGI-I, overall functioning), though only the 10-mg dose resulted in a significant reduction in total panic attack frequency compared to placebo beginning at week 4 (LOCF analysis) (Michelson et al. 1998). In a 24-week continuation phase of this trial, greater numbers of those receiving fluoxetine, compared to those switched to or continuing on placebo, showed ongoing improvement on CGI-I, although this was not a statistically significant difference at end point (Michelson et al., 1998). Michelson et al. (2001) conducted a 12-week RCT of fluoxetine (20 mg/day, increased to a maximum of 60 mg/day after 6 weeks in patients who did not respond sufficiently) and found a statistically significant reduction in PDSS overall scores and a significant increase in the proportion of patients who were panic attack free after 6 and 12 weeks of treatment. There is also controlled evidence for fluvoxamine (Hoehn-Saric et al., 1993; Black et al., 1993; Asnis et al., 2001), escitalopram (Stahl et al., 2003), and citalopram (Wade et al., 1997; Lepola et al., 1998) in PD. Stahl et al. (2003) conducted a 10-week RCT comparing escitalopram (10–20 mg/day), citalopram (20 – 40 mg/day), and placebo and found that escitalopram, but not citalopram, led to a significant decrease in panic attack frequency by study end point, though the proportion of patients who were panic free was significant only at the trend level for the escitalopram group (p = 0.051) (see Table 44.2). Both active medication groups demonstrated significant improvements by study end point on the Panic and Agoraphobia Scale (PAS) as well as CGI-I (Stahl et al., 2003). Two published double-blind studies (8 weeks of acute treatment, followed by 1 year of continuation treatment) found that citalopram or clomipramine was effective compared to placebo (Wade et al., 1997; Lepola et al., 1998). Of note,

44: PHARMACOTHERAPY

these studies identified citalopram 20 –30 mg/day to be more effective than higher citalopram doses (40 – 60 mg/ day) (Wade et al., 1997; Lepola et al., 1998). Another head-to-head randomized, relatively small single-blind randomized study found that after 60 days, citalopram (20 –50 mg/day) and paroxetine (20–50 mg/day) resulted in similar reductions in Panic Associated Symptoms Scale (PASS) scores, which includes panic attack frequency, anticipatory anxiety, and phobic avoidance. No significant difference was observed between the two medication groups; however, only completer analyses are reported (Perna et al., 2001). A head-to-head study of sertraline (50 –150 mg/day) and paroxetine (40–60 mg/day), found that both medications led to similar reductions in the PASS after 12 weeks, though sertraline resulted in less weight gain and had fewer dropouts due to AEs (Bandelow et al., 2004). SSRIs in Social Anxiety Disorder The SSRIs that are FDA approved for SAD are paroxetine, paroxetine CR, and sertraline (Table 44.1). In SAD, SSRIs are typically initiated at one-half of the usual effective dose and increased after the first week of treatment (Schneier, 2006). Although many patients improve within the first few weeks of treatment, it has been suggested that initial SSRI trials should last 12 weeks, as at least 25% of patients who do not respond by week 8 may respond during the ensuing 4 weeks at the same medication dose (Schneier, 2006). Consensus guidelines support the use of continuation pharmacotherapy for those patients who respond during 12 weeks of treatment to decrease the risk of relapse (Schneier, 2006). Meta-analytic studies support the use of SSRIs in SAD. One meta-analysis of 15 published RCTs of SSRIs (with an average duration of 13–14 weeks), found the following averaged d scores for the Liebowitz Social Anxiety Scale (LSAS): paroxetine, 0.526 (5 trials), fluvoxamine, 0.581 (3 trials), sertraline, 0.345 (2 trials), and fluoxetine, –0.029 (1 trial) (Hedges et al., 2007). The between-group differences were not significant, though the authors noted a significant Q statistic, suggesting heterogeneity, or lower level of agreement, in the paroxetine trials for LSAS (Hedges et al., 2007). Effect sizes (ES) for LSAS ranged from – 0.029 to 1.214 for all studies, with a significant Q statistic (Hedges et al., 2007). For CGI-I, the average d score for all studies, which included fluoxetine, fluvoxamine, fluvoxamine CR, paroxetine, paroxetine CR, sertraline, and escitalopram, was 0.986 (Hedges et al., 2007). Another metaanalysis of placebo-controlled studies of SSRIs and non-SSRIs in SAD found an ES for LSAS of 0.65 for six SSRI trials, which included fluvoxamine, paroxetine, and sertraline, with no heterogeneity identified in the SSRI studies (Blanco et al., 2003). No statistically sig-

739

nificant differences were found between medications or medication classes, which included phenelzine (ES = 1.02), clonazepam (0.97), gabapentin (0.78), and brofaromine (0.66), with ES heterogeneity in the phenelzine group (Blanco et al., 2003). Effect sizes for responders (defined as CGI-I ≤ 2) was 4.10 for SSRIs, 5.53 for phenelzine, and 16.61 for BDZs, though there was heterogeneity in the SSRI (due to one study) and phenelzine groups (Blanco et al., 2003). Blanco et al. (2003) supported SSRIs as first-line treatments in SAD due to their tolerability, ability to treat comorbid conditions, and the stability of the ES. The Cochrane Collaboration reviewed 37 RCTs of either SSRIs (paroxetine, sertraline, fluoxetine, fluvoxamine, and escitalopram), MAOIs, reversible inhibitors of monoamine oxidase (RIMAs), and other medications (including BDZs, buspirone, gabapentin) in SAD (D.J. Stein et al., 2000). The authors found that patients who received any medication were less likely than those given placebo to be nonresponders (D.J. Stein et al., 2000). On LSAS and Clinical Global Impression-Severity of Illness (CGI-S), SSRIs were found to reduce symptom severity, while MAOIs (on LSAS) and RIMAs (on CGIS) did not (D.J. Stein et al., 2000). Selective serotonin reuptake inhibitors were the only class of medications found to significantly reduce depressive symptoms. The authors also described similar dropout rates for the medication versus placebo groups (D.J. Stein et al., 2000). They suggest that publication bias was likely based on a CGI-I funnel plot, indicating that there might be more variation in medication responses in SAD than in the trials included in the meta-analysis (D.J. Stein et al., 2000). However, maintenance trials included in the metaanalysis demonstrated decreased relapse risk of medication versus placebo (D.J. Stein et al., 2000). In another meta-analysis of 25 published SSRI trials in SAD, which included 8 RCTs, the authors reported that SSRIs are effective in SAD, as the number of patients responding to medication was approximately 2 times that of the placebo responders (van der Linden et al., 2000). In this report, ES for LSAS in the RCTs ranged from 0.3 to 2.2 (van der Linden et al., 2000). Another meta-analysis compared psychological interventions, including cognitive restructuring and exposure, with pharmacological treatments of SAD, including SSRIs, BZDs, and MAOIs, in trials of approximately 11 weeks (Fedoroff and Taylor, 2001). This meta-analysis included nonblind and uncontrolled studies, as the ESs were similar to those in the double-blind and controlled trials (Fedoroff and Taylor, 2001). On self-report measures, SSRIs and BZDs were found to be equally effective, with the largest mean ESs compared to psychological and other pharmacological treatments (ES for SSRIs = 1.697, BZDs = 2.095) and their confidence intervals overlapped. A trend favored BZDs overall, which outperformed MAOIs and the psychological treatments,

740

ANXIETY DISORDERS

though SSRIs did not (Fedoroff and Taylor, 2001). On observer-rated measures, which included data from only a small number of trials, all of the treatments, including BZDs, SSRIs, MAOIs, and exposure with cognitive restructuring, were similarly effective, and superior to placebo or wait-list control (Fedoroff and Taylor, 2001). Paroxetine was the first medication approved for the treatment of SAD (Davidson et al., 2006). Two flexibly dosed, 12-week, multicenter RCTs of paroxetine 20–50 mg/day demonstrated that paroxetine was more effective than placebo in SAD (M.B. Stein et al., 1998; Baldwin et al., 1999). In one study, there were a significant number of CGI-I responders in the paroxetine versus placebo groups (55% vs. 24% by study end point), beginning at week 4 (M.B. Stein et al., 1998). This study also found that paroxetine resulted in a significant reduction in LSAS compared to placebo beginning at week 2 (M.B. Stein et al., 1998). Another study found that there was a significant reduction in LSAS total score and a significant percentage of CGI-I responders (approximately 66% vs. 32%) in the paroxetine compared to the placebo groups by study end, beginning at week 4 (Baldwin et al., 1999). In a 12-week, placebo-controlled trial of three fixed doses of paroxetine (20, 40, and 60 mg), the 20-mg dose resulted in a significant decrease in LSAS total scores by study end, beginning at week 8, while the number of responders on CGI-I in the 40-mg group (46.6%) was significant compared to placebo (28.3%) by study end and at week 6 (Liebowitz et al., 2002). Paroxetine CR (12.5–37.5 mg/day) has also been shown to be more effective than placebo in SAD in a 12-week RCT (Lepola et al., 2004). Reduction in LSAS total score in the paroxetine CR group was significantly greater than in the placebo group beginning at week 6, and 57% of patients treated with paroxetine CR compared to about 30% of those receiving placebo were responders on CGI-I by study end (Lepola et al., 2004). Also, 28% of patients in the paroxetine CR group achieved CGI-I scores of 1, indicating remission, which was significantly greater than 12% in the placebo group (Lepola et al., 2004). In a 12-week, flexibly dosed RCT of sertraline (50– 200 mg/day) in SAD, significant reductions in LSAS were observed in the sertraline group versus placebo beginning at week 6, with an effect size for LSAS change of 0.43 (Liebowitz et al., 2003). Also, 47% of patients treated with sertraline were CGI-I responders by study end compared to 26% in the placebo group (Liebowitz et al., 2003). Another flexibly dosed, multicenter RCT of sertraline (50–200 mg/day) in SAD also found significant CGI-I response versus placebo by study end (53% vs. 29%) (Van Ameringen et al., 2001). Significantly more patients receiving sertraline (40%) achieved CGI-I scores of 1 by study end, compared to 13% of those receiving placebo (Van Ameringen et al., 2001). Sertraline also resulted in significant reductions on the

Marks Fear Questionnaire Social Phobia subscale and the Brief Social Phobia Scale (BSPS) (Van Ameringen et al., 2001). One RCT compared the efficacy of sertraline monotherapy (50 –150 mg/day), exposure therapy, and combination therapy versus placebo or general medical care during 24 weeks in patients with SAD (Blomhoff et al., 2001). Blomhoff et al. (2001) reported a greater percentage of responders (defined as ≥ 50% reduction of Social Phobia Scale [SPS] symptoms, CGI–Social Phobia [CGI-SP] severity score ≤ 3 and improvement score ≤ 2) in the groups receiving sertraline compared to the nonsertraline groups. Combination therapy and sertraline alone led to significantly greater response compared to placebo (Blomhoff et al., 2001). However, there were more responders in the combination therapy group beginning at week 12, while sertraline alone resulted in a significant percentage of responders by study end point (Blomhoff et al., 2001). In a 1-year follow-up of the patients in the Blomhoff et al. (2001) study, all groups (sertraline alone, exposure alone, combination therapy, and placebo) demonstrated a significant reduction in CGI-SP scores compared to baseline (Haug et al., 2003). This study also found that in the 28 weeks following the conclusion of the 24-week trial, there was a significant reduction in CGI-SP severity scores in the exposure and placebo groups, and a slight nonsignificant deterioration in CGI-SP severity and SPS scores in the sertraline groups (Haug et al., 2003). It should be noted, however, that during the follow-up period, approximately 15%–20% of the patients in each of the groups received treatment with SSRIs, and some patients had been offered exposure therapy or referred to a psychologist or psychiatrist (Haug et al., 2003). Escitalopram (10–20 mg) was also shown in a flexibly dosed, 12-week, multinational RCT to result in significant reductions in LSAS total score and a significant percentage of CGI-I responders (54% vs. 39%) compared to placebo by study end (Kasper et al., 2005). In one 2-site RCT comparing fluoxetine (titrated to 40– 60 mg/day), group comprehensive cognitive-behavioral therapy (CCBT), the combination of fluoxetine and CCBT, and CCBT plus placebo versus placebo alone, CGI-I response rates and BSPS scores for all treatment groups were significantly greater than placebo after 14 weeks, though no differences between the active treatments were described (Davidson, Foa, et al., 2004). There are two published negative RCTs of fluoxetine in SAD, however (Koback et al., 2002; Clark et al., 2003). Clark et al. (2003) found that cognitive therapy was superior to fluoxetine (20–60 mg/day) plus selfexposure on social phobia measures after 16 weeks. A relatively small, single-site, 14-week RCT of fluoxetine (20 mg/day for the first 8 weeks, then up to 60 mg/ day), found significant difference versus placebo on LSAS or CGI-I (Kobak et al., 2002). There is evidence from RCTs for the efficacy of fluvoxamine in SAD. One 12-

44: PHARMACOTHERAPY

week multicenter study showed that fluvoxamine (50– 300 mg/day) led to a significant percentage of CGI-I responders by study end, and significant reductions in LSAS beginning at week 6 (M.B. Stein et al., 1999). Fluvoxamine (150 or 300 mg/day) resulted in a significant improvement compared to placebo in LSAS-Japanese Version total score and CGI-I after 10 weeks in a RCT in Japan (Asakura et al., 2007). Also, two multisite, 12-week RCTs of fluvoxamine CR found that it was superior to placebo in SAD, resulting in significant reductions in LSAS by week 4 at doses ranging from 100–300 mg/day (Davidson, Yaryura, et al., 2004; Westenberg et al., 2004). However, a 12-week extension of one of the 12-week multicenter RCTs of fluvoxamine CR (100–300 mg/day) in SAD found that reductions in LSAS total scores only at trend level significance (p = 0.074) from baseline to the 24-week end point, with a nonsignificant trend towards more CGI-I responders and remitters in the fluvoxamine CR group versus placebo (D.J. Stein et al., 2003). Lader et al. (2004) conducted a 24-week head-to-head study comparing escitalopram at fixed doses of 5, 10, or 20 mg/day, paroxetine 20 mg/day, and placebo in SAD (see Table 44.2). Escitalopram 5 and 20 mg and paroxetine 20 mg produced significant LSAS reductions compared to placebo after 12 weeks in the LOCF analysis (Lader et al., 2004). The efficacy analyses in this study, however, were primarily based on data from observed cases (OC), as LOCF data were not provided (Lader et al., 2004). In the OC sample, all three escitalopram groups and the paroxetine group resulted in significant LSAS reductions by weeks 12 and 24, and a significant percentage of CGI-I responders by week 24 compared to placebo (Lader et al., 2004). Escitalopram 20 mg resulted in significantly greater reductions than paroxetine 20 mg in LSAS mean score by week 16 (Lader et al., 2004). Longer-term relapse-prevention studies of paroxetine, sertraline, and escitalopram in SAD have been conducted. In a 24-week, randomized, double-blind maintenance phase following 12 weeks of single-blind treatment with paroxetine (20–50 mg/day) in a multicenter study, 14% of patients receiving paroxetine relapsed compared to 39% of those receiving placebo (p < 0.001) (D.J. Stein, Versiani, et al., 2002). In addition, patients who received paroxetine in the maintenance phase experienced significant improvements on CGI-I and LSAS by study end point compared to those switched to placebo (D.J. Stein, Versiani, et al., 2002). A small double-blind study (N = 65) randomly assigned patients with SAD who responded to sertraline (50–200 mg/day) in a 20-week RCT to continue sertraline or switch to placebo for 24 weeks; placebo-responders from the initial trial were continued on placebo (Walker et al., 2000). This study reported a relative risk of relapse of about 10 for patients who switched to placebo compared to those continued on sertraline, though the number of completers

741

was small (N = 38). Although there was no significant difference in CGI-I response between the sertralinecontinuation and placebo-switch groups, there were significant differences between the groups on CGI-S and Duke BSPS from baseline to study end, with those continuing on sertraline experiencing reductions in these scores, while the scores of those switched to placebo increased; scores of those in the placebo-responder group also increased (Walker et al., 2000). In a multinational RCT, patients who responded to escitalopram (10–20 mg/day) during a 12-week, open-label phase were randomly assigned either to continue receiving the same dose of escitalopram or to switch to placebo for 24 weeks (Montgomery et al., 2005). This study reported an approximately 3 times greater risk of relapse for those patients switched to placebo compared to those continuing on escitalopram (Montgomery et al., 2005). In the escitalopram group, 22% of patients relapsed compared to 50% in the placebo group, and the median time to relapse was 407 versus 144 days, respectively (Montgomery et al., 2005). SSRIs in Post-Traumatic Stress Disorder Although there are two FDA-approved medications for PTSD (paroxetine and sertraline), ESs have been modest for short-term trials, and superiority of drug over placebo in all three clusters of illness (avoidance/numbing, reexperiencing, and hyperarousal) have only been observed for paroxetine (Marshall et al., 2001; Tucker et al., 2001). A major limitation in the literature to date is the paucity of long-term studies of pharmacotherapy in PTSD (see Cochrane Review of PTSD; D.J. Stein, Ipser, et al., 2006). In view of the limited efficacy of RCT pharmacotherapy data for PTSD and more robust evidence for exposure-based psychotherapies, NICE guidelines have suggested that pharmacotherapy should not be used as a routine first-line treatment for adults in preference to a trauma-focused psychological therapy. SEROTONIN AND NOREPINEPHRINE REUPTAKE INHIBITORS (SNRIs) Serotonin and norepinephrine reuptake inhibitors have emerged as first-line medications along with the SSRIs for the treatment of anxiety disorders. Venlafaxine XR is approved by the FDA for the treatment of GAD, PD, and SAD, and duloxetine recently received FDA approval for GAD (see Table 44.1). SNRIs in Generalized Anxiety Disorder Short- and long-term RCTs have shown that venlafaxine XR is effective in GAD. Regarding long-term studies, two multicenter, 6-month RCTs demonstrated the efficacy of venlafaxine XR over placebo in patients with

742

ANXIETY DISORDERS

GAD (Gelenberg et al., 2000; Allgulander et al., 2001). In a fixed-dose, 24-week RCT, venlafaxine XR (37.5, 75, or 150 mg/day) resulted in significant reductions in HAM-A total scores by study end compared to placebo (Allgulander et al., 2001). All three doses led to significant improvements on HAM-A and CGI-I versus placebo from week 2 onwards except for the venlafaxine XR 37.5-mg group at week 8 (Allgulander et al., 2001). This study provided evidence for a dose-response relationship, as higher doses of venlafaxine XR (75 and 150 mg/day) resulted in greater response rates and relatively faster onset of action on a number of variables assessing anxiety compared to venlafaxine XR 37.5 mg/ day (Allgulander et al., 2001). Another 6-month RCT found that flexibly dosed venlafaxine XR (75–225 mg/ day) resulted in significant response rates (defined as ≥ 40% reduction in HAM-A scores or CGI-I ≤ 2) by week 1, with response rates of ≥ 69% beginning at week 6, compared to rates of 42%–46% in the placebo group (Gelenberg et al., 2000). Short-term studies of venlafaxine XR in GAD include four separate 8-week, multicenter RCTs (Davidson et al., 1999; Rickels et al., 2000; Hackett et al., 2003; Nimatoudis et al., 2004). Rickels et al. (2000) studied venlafaxine XR (75 mg, 150 mg, or 225 mg/day), and found that only venlafaxine XR 225 mg/day resulted in significant reductions in HAM-A and CGI-I scores compared to placebo after 8 weeks. Davidson et al. (1999) compared venlafaxine XR (75 mg or 150 mg/ day), buspirone (30 mg/day, dosed 10 mg three times per day [TID]), and placebo, and reported that by study end point, CGI-I scores, but not total HAM-A scores, significantly improved in the venlafaxine XR 75 mg/day and buspirone groups only compared to placebo (Davidson et al., 1999). In a small RCT (N = 46), Nimatoudis et al. (2004) reported that HAM-A scores were reduced by ≥ 50% in 92% of patients receiving venlafaxine XR (75–150 mg/day) compared to 27% for placebo. This study also identified a significant remission rate (63%) in the venlafaxine XR group (Nimatoudis et al., 2004). Another 8-week, placebo-controlled study compared venlafaxine XR (75 or 150 mg/day) with diazepam (15 mg/day) and found no significant differences in HAM-A or CGI-I scores between the medication and placebo groups. A secondary analysis that omitted study centers where there was no difference between diazepam and placebo showed significant HAMA and CGI-I reductions in both venlafaxine XR groups versus placebo (Hackett et al., 2003). Regarding head-to-head studies, a small (N = 46), open-label study compared venlafaxine XR (37.5–225 mg/day) and paroxetine (10 – 40 mg/day) in GAD (Kim et al., 2006) (see Table 44.2). Both medications resulted in significant reductions in HAM-A and CGI-S after 8 weeks, though there were no significant differences in efficacy between the two groups (Kim et al., 2006).

However, paroxetine resulted in significantly more weight gain than venlafaxine XR, while venlafaxine XR led to significant increases in systolic and diastolic blood pressure compared to paroxetine by study end point (Kim et al., 2006). The efficacy of duloxetine in GAD was demonstrated two 10-week, multicenter RCTs (Hartford et al., 2007; Rynn et al., 2007). Duloxetine (60 –120 mg/day, progressively titrated) resulted in a significant decrease in HAM-A total scores compared to placebo, beginning at week 2, in a mixed-effects repeated measures (MMRM) analysis, with response rates of 40% compared to 32% in the placebo group after 10 weeks (Rynn et al., 2007). There were no significant differences in remission rates, however (Rynn et al., 2007). Also, there were significant increases in heart rate, blood pressure, and some liver measures in the duloxetine group compared to placebo, but the magnitude of the changes was not considered clinically relevant (Rynn et al., 2007). Hartford et al. (2007) conducted a placebocontrolled, head-to-head RCT, in which duloxetine (60– 120 mg/day) was compared to venlafaxine XR (75– 225 mg/day) (see Table 44.2). After 10 weeks, HAM-A total scores decreased significantly in both active treatment groups compared to placebo (Hartford et al., 2007). Mixed-effect repeated measure analysis showed that there were significant reductions in HAM-A beginning in week 1 for the duloxetine group and week 2 for the venlafaxine group (Hartford et al., 2007). However, the percentage of patients achieving response (defined as ≥ 50% reduction in HAM-A) and remission (HAMA total score ≤ 7) by study end was only significant in the venlafaxine XR group versus placebo, though both medications led to a significant percentage of responders on CGI-I (Hartford et al., 2007). There were more discontinuation-emergent AEs during a tapering period for venlafaxine XR versus placebo compared to duloxetine versus placebo (Hartford et al., 2007). SNRIs in Panic Disorder There are two multicenter, double-blind RCTs of venlafaxine XR in PD (Bradwejn et al., 2005, Pollack et al., 2006). In a 10-week trial, venlafaxine XR (75–225 mg/day) resulted in a significant reduction in the frequency of full-symptom panic attacks compared to placebo by study end (Bradwejn et al., 2005). Although venlafaxine XR did not result in a significantly greater number of patients who were panic free by study end point, there was a significant percentage of CGI-I responders and remitters in the venlafaxine XR group versus placebo beginning at weeks 3 and 6, respectively (Bradwejn et al., 2005). There was a significant increase in heart rate in the venlafaxine XR group (change from baseline in supine pulse rate = 2.18 beats/min) (Bradwejn et al., 2005). Another placebo-controlled, double-blind

44: PHARMACOTHERAPY

RCT compared venlafaxine XR (75 or 150 mg/day) and paroxetine 40 mg/day in PD (see Table 44.2) (Pollack et al., 2007). After 12 weeks, both doses of venlafaxine XR and paroxetine resulted in a significant percentage of patients who were free of full-symptom panic attacks, as assessed by the Panic and Anticipatory Anxiety Scale (PAAS), compared to placebo (Pollack et al., 2007). There were no significant differences in comparisons on most efficacy measures between the two venlafaxine XR arms or the venlafaxine XR and paroxetine study arms. All three active medication groups resulted in a significant percentage of CGI-I responders, ranging from approximately 77 to 81%, compared to the placebo response of 56%, by study end point (Pollack et al., 2007). Significantly more patients attained remission (defined as panic free and CGI-S ≤ 2) in the venlafaxine XR and paroxetine groups versus placebo by weeks 6 and 8, respectively (Pollack et al., 2007). A multinational relapse prevention study, in which patients who responded to 12 weeks of open-label treatment with venlafaxine XR (75–225 mg/day) were randomly assigned to continue receiving venlafaxine XR or switch to placebo for a 26-week double-blind phase, showed that venlafaxine XR was significantly better than placebo in preventing relapse (Ferguson et al., 2007). The relapse rate in the placebo group was 50% compared to 22.5% in the venlafaxine XR group, and the percentage of patients who were panic free by study end was 55% versus 76.4% in the two groups, respectively (Ferguson et al., 2007). As of this writing (July 2007), there are no published RCTs of duloxetine in PD. SNRIs in Social Anxiety Disorder There are RCTs to support the efficacy of venlafaxine XR in generalized SAD. Two 12-week, multicenter RCTs of SAD found that venlafaxine XR (75–225 mg/day) led to significantly greater reductions on LSAS than placebo, beginning at week 4 (Rickels et al., 2004) or week 6 (Liebowitz, Mangano, et al., 2005). Rickels et al. (2004) identified 50% of patients as CGI-I responders in the venlafaxine XR group by study end, which was significantly greater than 34% in the placebo group. Liebowitz, Mangano, et al. (2005) also reported a significantly greater percentage of responders in the venlafaxine XR group (44%) compared to placebo (30%), as well as remitters (20% vs. 7%, with remission defined as LSAS ≤ 30) by study end point. Of note, both studies described small but significant increases in supine systolic (~0.5-2.3 mmHg) and diastolic (~0.25-2.6 mmHg) blood pressure, supine pulse rate (~1.3-4.9 beats/ min), and cholesterol levels (~0.3 mmol/L) compared to placebo (Rickels et al., 2004; Liebowitz, Mangano, et al., 2005). In a 6-month, multicenter RCT, fixed low-dose venlafaxine XR (75 mg/day) was compared

743

to flexible higher doses (150–225 mg/day) (M.B. Stein et al., 2005). The low- and high-dose venlafaxine XR groups resulted in significant reductions in LSAS compared to placebo beginning at week 4, and significant response (CGI-I ≤ 2) and remission (defined as LSAS ≤ 30) rates versus placebo by study end (M.B. Stein et al. 2005). There were no significant differences in response and remission rates between the two venlafaxine XR groups (M.B. Stein et al., 2005). There are two head-to-head, placebo-controlled, randomized, 12-week trials comparing venlafaxine XR (75– 225 mg/day) and paroxetine (20–50 mg/day) in SAD (see Table 44.2). Both studies found that the active treatment groups resulted in significant reductions in LSAS and significant response rates compared to placebo, though no significant differences in efficacy were noted between the venlafaxine XR and paroxetine groups by the end point of the studies (Allgulander, Mangano, et al., 2004; Liebowitz, Gelenberg, et al., 2005). At this time (July 2007), there are no published RCTs of duloxetine in SAD. SNRIs in Post-Traumatic Stress Disorder Venlafaxine ER was investigated in a 6-month flexible dose (37.5–300 mg/day) RCT conducted primarily in European study sites (Davidson, Baldwin, et al., 2006). Remission rates, indexed by Clinician-Administered PTSD Scale (CAPS) scores of 20 or lower, were 50.9% for venlafaxine ER and 37.5% for placebo, and improvements were found for reexperiencing and avoidance/ numbing symptoms, but not for hyperarousal (Davidson, 2006). Despite the overall efficacy compared to placebo, the ES for CAPS was 0.31, representing a small effect, with a number NNT for remission of eight. A 12-week multicenter RCT with placebo and sertraline control arms also found efficacy of venlafaxine ER in PTSD (Davidson, Rothbaum, et al., 2006), although the ES for venlafaxine versus placebo was only 0.266. Importantly, both studies used a maximum daily dosage of venlaxine higher than its FDA-approved labeling for its other indications (GAD, SAD, PD, and major depressive disorder). TRICYCLIC ANTIDEPRESSANTS Tricyclic antidepressants have a long history of use in anxiety and related conditions, though their overall poorer tolerability compared to the SSRIs and SNRIs has limited their use. Tricyclic antidepressants are effective treatments for GAD, although few studies have investigated TCAs in Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV; American Psychiatric Association [APA], 1994) defined GAD (Mathew and Hoffman, in press). Rickels et al. (1993)

744

ANXIETY DISORDERS

conducted an 8-week double-blind, placebo-controlled trial comparing imipramine, diazepam, and trazodone in the treatment of patients with DSM-III (APA, 1980) GAD, in which diazepam resulted in the greatest improvement during the first 2 weeks, after which imipramine was significantly more effective in reducing total HAMA scores (reviewed in Baldwin and Polkinghorn, 2005); all three treatment groups were found to be effective in reducing anxiety symptoms by study end point (reviewed in Lydiard and Monnier, 2004). Meta-analyses have demonstrated similar effect sizes of SSRIs and TCAs in PD (see previous SSRIs section for details) (Mitte, 2005; Furukawa et al., 2007). There is support from RCTs for the use of TCAs in the treatment of PD. Barlow et al. (2000) conducted a randomized, placebo-controlled trial in which patients with PD with mild or no agoraphobia were treated with either imipramine alone (up to 300 mg/day), cognitivebehavioral therapy (CBT) alone, CBT and imipramine, or CBT and placebo for 3 months (acute phase), and responders were then followed for 6 months (maintenance phase), and another 6 months after discontinuing treatment. In the acute and maintenance phases, imipramine and CBT were each statistically superior to placebo on PDSS, and on CGI-I in the maintenance phase (Barlow et al., 2000). There were no significant differences in efficacy between imipramine alone and CBT alone, though response quality, as assessed by PDSS average scores, was higher in the imipramine group versus the CBT group in the acute phase (Barlow et al., 2000). Also, in the acute and maintenance phases, CBT plus imipramine produced a higher quality of responses compared to CBT alone (Barlow et al., 2000). In the acute phase, CBT plus imipramine was not superior to CBT plus placebo, but in the maintenance phase, combined treatment produced a significant change in PDSS average score compared to CBT plus placebo (Barlow et al., 2000). At 6-month follow-up, only the CBT groups continued to demonstrate some efficacy versus placebo (Barlow et al., 2000). There is also shortand long-term evidence of clomipramine in PD (Lecrubier and Judge, 1997; Lecrubier et al., 1997). There is no RCT evidence to support the use of TCAs in generalized SAD. MONOAMINE OXIDASE INHIBITORS (MAOIs) AND REVERSIBLE INHIBITORS OF MONOAMINE OXIDASE (RIMAs) There is evidence for the efficacy of MAOIs in PD, SAD, and PTSD (Liebowitz, Hollander, et al., 1990). The use of MAOIs in these disorders is limited by their poorer tolerability, risks of toxicity, and the requirement for patients taking them to follow a low tyramine diet to prevent hypertensive crisis (Davidson, 2006).

The RIMAs are less likely to cause hypertensive crisis, though this class of medications is not approved for use in the United States (Davidson, 2006). In PD, two studies (8 and 24 weeks) found no difference in the efficacy of SSRIs and RIMAs (fluoxetine vs. moclobemide, fluvoxamine vs. brofaromine), after 8 and 24 weeks, respectively, though there were no placebo comparison groups (van Vliet et al., 1996; Tiller et al., 1999). A small, 12-week study found that brofaromine did not result in significant improvement versus placebo in PD (van Vliet et al., 1993). In SAD, some meta-analyses have shown that MAOIs and SSRIs are similarly effective (Fedoroff and Taylor, 2001; Blanco et al., 2003). However, the Cochrane Collaboration reported in their meta-analysis that though all medication groups were superior to placebo in SAD, SSRIs were more effective than RIMAs (see SSRIs section for details) (D.J. Stein et al., 2000). Phenelzine, a nonselective, irreversible MAOI, was found to be significantly more effective in DSM-III SAD than atenolol or placebo in 4and 8-week RCTs (Liebowitz, Schneier, et al., 1990; Liebowitz et al., 1992). Another RCT found that phenelzine and cognitive-behavioral group therapy (CBGT) each led to similar, significant improvements in SAD versus control conditions after 12 weeks, though phenelzine led to better performance on some measures than CBGT (Heimberg et al., 1998), and continued to do so in a 1-year extension of this study for responders to phenelzine or CBGT (Liebowitz et al., 1999). The extension study found no difference in relapse and dropout rates between the two groups in a 6-month maintenance phase, though there was a trend toward greater relapse in the phenelzine group in a 6-month treatment-free follow-up phase (Liebowitz et al., 1999). Some RCTs found that the RIMAs are effective in the short-and long-term in SAD (International et al., 1997; Lott et al., 1997; D.J. Stein, Cameron, et al., 2002; Prasko et al., 2006), whereas other short-term RCTs did not (Noyes et al., 1997; Schneier et al., 1998). There are no RCTs to our knowledge support the use of MAOIs or RIMAs in GAD. ANTICONVULSANTS A number of antiepileptic drugs (AEDs) have been investigated in anxiety disorders, though the strongest evidence to date is for pregabalin in GAD (Mula et al., 2007). Pregabalin, which acts by binding to the α2γ subunit of voltage-gated calcium channel, is FDA approved in 4 conditions: diabetic peripheral neuropathy, postherpetic neuralgia, adjunctive treatment for partial seizures, and most recently, fibromylagia. Randomized controlled trials in GAD have demonstrated short-term efficacy, although no continuation or relapse prevention studies have been published. Pande et al. (2003)

44: PHARMACOTHERAPY

demonstrated significant baseline-to-end point reductions in HAM-A in patients receiving pregabalin (150 or 600 mg/day) or lorazepam (6 mg/day) versus placebo after 4 weeks, and the magnitude of the HAM-A reductions did not differ significantly between treatment groups. However, significantly more patients in the pregabalin 600 mg/day (46%) and lorazepam groups (61%) were HAM-A responders (≥ 50% reduction in HAM-A) compared to the pregabalin 150 mg/day and placebo (27%) groups (Pande et al., 2003). In a randomized, double-blind, placebo-controlled study by Pohl et al. (2005), pregabalin (200 mg/day divided twice a day (BID), 400 mg/day div. BID, or 450 mg/day div. TID) resulted in significantly greater HAM-A response rates (53%–56% vs. 34%) after 6 weeks. Of note, all 3 pregabalin doses resulted in significant reductions in HAM-A compared to placebo beginning at week 1 (Pohl et al., 2005). Rickels et al. (2005) conducted a 4-week, placebo-controlled trial of pregabalin (300, 450, or 600 mg/day div. TID), with alprazolam (1.5 mg/day) as an active comparator. There were significant reductions in HAM-A scores in all three pregabalin groups and the alprazolam group versus placebo by study end point, but only pregabalin 300 mg/day and 600 mg/day resulted in a significant percentage of HAM-A and CGII responders compared to placebo (Rickels et al., 2005). There was suggestion of rapidity of onset, as all doses of pregabalin and alprazolam significantly decreased HAM-A scores compared to placebo at week 1 in an observed case analysis (Rickels et al., 2005). Another multicenter, 4-week RCT found that pregabalin 600 mg/day div. TID and lorazepam (6 mg/day div. TID), but not pregabalin 150 mg/day div. TID, resulted in significant reductions in HAM-A scores versus placebo by study end point. This study, however, did not find significant differences in CGI-I and HAM-A response rates, a secondary outcome measure, for any of the treatment groups (Feltner et al., 2003). Montgomery et al. (2006) conducted a 6-week, randomized, placebocontrolled trial comparing pregabalin (400 or 600 mg/ day div. BID) and venlafaxine (75 mg/day div. BID) in GAD and found that both pregabalin doses and venlafaxine resulted in significant HAM-A reductions versus placebo by end point (Montgomery et al., 2006). There was significant improvement compared to placebo in HAM-A scores beginning at week 1 in both pregabalin groups and at week 2 in the venlafaxine group (Montgomery et al., 2006). The most commonly reported side effects of pregabalin in these studies were somnolence and dizziness, and patients taking the higher doses of pregabalin experienced weight gain of almost 2 kg. Pande et al. (2003) found no significant difference in Physician Withdrawal Checklist (PWC) scores for pregabalin versus placebo, unlike lorazepam, during discontinuation, whereas other studies reported some significant increases in PWC scores for pregabalin versus

745

placebo, though these changes were not considered clinically significant (Feltner et al., 2003; Pohl et al., 2005; Rickels et al., 2005). It has been noted that larger PWC changes than those observed for pregabalin were described in studies of long-term benzodiazepine withdrawal (Feltner et al., 2003), though long-term studies of pregabalin in GAD are needed. As of July 2007, there was only one published multicenter RCT of pregabalin in SAD. Pande et al. (2004) conducted a 10-week, placebo-controlled trial of pregabalin (150 mg/day or 600 mg/day, div. TID), and found that pregabalin 600 mg/day resulted in significant LSAS reductions beginning at week 1, while pregabalin 150 mg/day did not lead to improvements in any efficacy measures (Pande et al., 2004). In the pregabalin 600 mg/day group, 43% of patients were CGII responders, which was significantly greater than in the placebo group (22%), though the percentage of LSAS responders was not significant (Pande et al., 2004). There are no published RCTs of pregabalin in PD or PTSD to date. Gabapentin, an older anticonvulsant medication FDA approved for partial seizures, neuropathic pain, and postherpetic neuralgia, has been extensively used “offlabel” in anxiety disorders, although RCT data has only demonstrated modest benefit. Pande et al. (1999) conducted a 14-week RCT (N = 69) in SAD. Gabapentin (900–3600 mg/day, div. TID) resulted in significant reductions versus placebo in LSAS, BSPS, Social Phobia Inventory, and CGI-I by study end point (Pande et al., 1999). However, LSAS response rate was only 32% in the gabapentin group versus 14% in the placebo group for the ITT population (p = 0.08) (Pande et al., 1999). There is one RCT (N = 103) of gabapentin in PD, which found that there was no significant difference on PAS between the gabapentin (600 –3600 mg/day) and placebo groups after 8 weeks (Pande et al., 2000). In a post-hoc analysis, gabapentin resulted in significant PAS improvement versus placebo in patients with more severe symptoms (PAS ≥ 20), though there was no significant difference versus placebo in the percentage of PAS responders (≥ 50% decrease in PAS from baseline to end point) (Pande et al., 2000). Although case reports have suggested that gabapentin may be an effective adjunctive treatment in GAD and PTSD, there are no published RCTs of gabapentin in these conditions (reviewed in Mula et al., 2007). Although lamotrigine is extensively used in mood disorders, and is FDA approved for maintenance therapy for bipolar disorder, there is minimal data supporting its efficacy in primary anxiety disorders. A preliminary, small (N = 15), 12-week RCT of lamotrigine in PTSD suggested some benefit (Hertzberg et al., 1999). Lamotrigine (slowly titrated over 8 weeks from 25 mg/ day to a maximum dose of 500 mg/day) led to response on the Duke Global Rating for PTSD Scale-Improvement

746

ANXIETY DISORDERS

in 5 of 10 patients, versus 1 of 4 patients treated with placebo (Hertzberg et al., 1999). Improvement in reexperiencing and avoidance/numbing symptoms was described in the lamotrigine group, but not the placebo group (Hertzberg et al., 1999). Surprisingly, there are no published studies of lamotrigine in GAD, PD, or SAD (reviewed in Mula et al., 2007). There is one RCT of topiramate, an FDA-approved medication for migraine prophylaxis and seizures, in PTSD (Tucker et al., 2007). This 12-week study of 38 patients with non-combat-related PTSD found that there was no statistically significant difference in CAPS scores between the topiramate (25 mg/day titrated to 400 mg/ day or maximum tolerated dose, div. BID) and placebo groups by study end point, though there were significant reductions in the topiramate group in the reexperiencing subscale score on CAPS and in Treatment Outcome PTSD Scale, but not in the other secondary efficacy measures (Tucker et al., 2007). There have been two small open-label studies of topiramate as an adjunctive treatment or monotherapy in PTSD (Berlant and van Kammen, 2002; Berlant, 2004) and one in SAD (van Ameringen et al., 2004) suggesting efficacy, though with notable limitations (reviewed in Mula et al., 2007). There are no other published RCTs of topiramate in the nonOCD anxiety disorders. Another anticonvulsant tiagabine, a γ-aminobutyric acid (GABA) reuptake inhibitor, has been studied most extensively for GAD. In a multicenter, 8-week RCT, Pollack et al. (2005) found no significant difference in response rates between tiagabine (titrated from 4 mg/ day to a maximum of 16 mg/day, div. BID) and placebo in the LOCF analysis, though reduction of anxiety symptoms was noted in the tiagabine group in secondary statistical analyses (observed case and MMRM analyses). A small (N = 40), randomized, open-label trial of tiagabine (4–16 mg/day, div. BID) versus paroxetine (20–60 mg/day) in GAD demonstrated that both medications significantly reduced anxiety symptoms per HAM-A after 10 weeks, though this study did not include a placebo arm (Rosenthal, 2003). Davidson et al. (2007) conducted a multicenter, 12-week RCT of tiagabine in PTSD and found no significant differences between the tiagabine (4 –16 mg/day) and placebo groups on CAPS or other outcome measures by study end point. A small (N = 29), open-label study of tiagabine in PTSD suggested improvement in the open-label phase, but in a double-blind discontinuation phase, there was no difference in relapse between the tiagabine and placebo groups (Connor et al., 2006). A small (N = 54), openlabel study of tiagabine in SAD suggested initial promise (Dunlop et al., 2007). Regarding side effects, postmarketing reports found an association with seizures and status epilepticus in patients without epilepsy; since this addition to the package labelling in February 2005,

the off-label use of this medication for anxiety has decreased significantly. A small, 7-week, RCT (N = 19) of the AED levetiracetam was conducted in SAD (Zhang et al., 2005), which found no significant difference in BSPS or LSAS scores between the levetiracetam (500 –3000 mg/day) and placebo groups. The calculated effect size was 0.33 for BSPS and 0.5 for LSAS (Zhang et al., 2005). There are no other RCTs of levetiracetam in the non-OCD anxiety disorders (reviewed in Mula et al., 2007). Small, open-label studies of levetiracetam suggesting some efficacy in SAD (Simon et al., 2004), and in PD (Papp, 2006), and a small, retrospective case analysis suggested efficacy of levetiracetam as an adjunctive medication in treatment-refractory PTSD (Kinrys et al., 2006). Regarding the commonly used AEDs carbamazepine and valproate, there is also limited data supporting its efficacy in primary anxiety disorders. There is a negative RCT of carbamazepine in 14 patients with PD (Uhde et al., 1988). There are three small, open-label studies, two of which did not use standardized measures, and a large retrospective study suggesting some benefit of carbamazepine in PTSD, and an open-label study suggesting possible efficacy in PD (reviewed in Mula et al., 2007). Several open-label studies have suggested efficacy of valproate in PTSD and PD, and one in SAD, and one negative open-label study of valproate monotherapy in PTSD (reviewed in Mula et al., 2007). Evidence for the efficacy of additional AEDs in anxiety disorders, such as oxcarbazepine, phenytoin, and vigabatrin, is low, with no published RCTs of these medications in GAD, PD, SAD, or PTSD to date. BENZODIAZEPINES AND AZAPIRONES Multiple RCTs have demonstrated the short- and longterm efficacy of BZDs in GAD, PD, and SAD (Davidson, 2006; Katon, 2006; Mathew and Hoffman, in press). The principal advantages of BZDs are their rapid onset of action and their ability to be used on a PRN or “as needed” basis for acute panic/anxiety. However, the wellnoted disadvantages of BZDs include the risk of physiological dependence with long-term use (O’Brien, 2005), and their lack of antidepressant effects. Table 44.1 shows the U.S. FDA approved BZDs for anxiety disorders, and Table 44.3 reviews the clinical pharmacology and available preparations of commonly used BZDs. Due to their rapid onset of action, BZDs are commonly used in clinical practice as adjunctive agents for stabilization during initiation of an SSRI/SNRI. Longer-acting BZDs (for example, clonazepam, alprazolam XR) may be utilized to decrease breakthrough anxiety (reviewed in Katon, 2006).

44: PHARMACOTHERAPY

Randomized controlled trials have demonstrated that BZDs are efficacious in the acute treatment of GAD, with a rapid onset of action (Rickels et al., 1993, Rocca et al., 1997). However, long-term use of BZDs in GAD is problematic, as very few patients achieve and sustain remission with BZD monotherapy (Mathew and Hoffman, in press). Rickels et al. (1993) and Rocca et al. (1997) noted that BZDs affected mostly somatic

TABLE

747

symptoms in GAD (for example, muscle tension, gastrointestinal symptoms), whereas psychic symptoms (for example, worry, rumination) were preferentially responsive to antidepressants (imipramine, trazodone). There is evidence from RCTs that BZDs are effective in PD as well (Tesar et al., 1991; Cross-National and S. Group, 1992; Schweizer et al., 1993; Ballenger et al., 1988).

44.3 Characteristics of Commonly Used Benzodiazepines

Generic Name (Brand name) Alprazolam (Xanax)

Routes of Administration PO

Oral Dose Strengths (mg)/ Equivalency Approved Oral Rate of Onset Elimination Active Available (mg) Dose Range (mg) after Oral Dose Half-Life (hr) Metabolites Preparations 0.5

0.75– 4

Intermediate

6–20

-

Alprazolam XR:

0.25, 0.5, 1, 2 Alprazolam Intensol (concentrate solution): 1 mg/ml

3–6(suggested) 1–0 (used in clinical trials)

Alprazolam XR: 0.5, 1, 2, 3 Niravam (alprazolam orally disintegrating): 0.25, 0.5, 1, 2

Chlordiazepoxide

PO

10.0

15–100

Intermediate

30–100

+

PO

0.25

0.5– 4

Intermediate

18– 40

-

5, 10, 25

(Librium) Clonazepam (Klonopin)

Clorazepate (Tranxene)

PO

7.5

15–60

Rapid

30–100

+

Tranxene SD:

PO, PR, IM, IV

5.0

4 – 40

Tranxene T-tab: 3.75, 7.5, 15 Tranxene SD: 11.25, 22.5

11.25–5 Diazepam

0.5, 1, 2 Klonopin Wafers: 0.125, 0.25, 0.5, 1, 2

Rapid

30–100

+

(Valium)

2, 5, 10 Solution: 5 mg/5 ml Intensol: 5 mg/ml Diastat (diazepam rectal): 2.5 gel; AcuDial gel: 10, 20 IM, IV

Lorazepam (Ativan)

PO, IM, IV

1.0

1–10

Intermediate

10–20

-

0.5, 1, 2 Conc.: 2 mg/ml IM, IV

Oxazepam

PO

15.0

30–120

IntermediateSlow

8–12

-

10, 15, 30

PO

30.0

7.5–30

Intermediate

8–20

-

7.5, 15, 30

PO

0.25

0.125–0.5

Intermediate

2–5

-

0.125, 0.25

(Serax) Temazepam (Restoril) Triazolam (Halcion) Source: Adapted from Rosenbaum et al. (2005), Goddard et al. (2002). PO: by mouth; PR: per rectum; IM: intramuscular; IV: intervenous.

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Several RCTs have addressed the practical question of the utility of combination SSRI/benzodiazepine for acute treatment of PD. In a RCT in PD (N = 47), Goddard et al. (2001) compared responses of patients with PD to sertraline (open-label, target dose, 100 mg/day) given in combination with either the BZD clonazepam (0.5 mg TID) or placebo, during the first 4 of 12 weeks of treatment, after which clonazepam was tapered over 3 weeks and discontinued. There was a significantly greater number of responders (p = 0.003) at the end of week 1 in the combined sertraline/clonazepam group (41%) versus sertraline/placebo (4%) (Goddard et al., 2001). At week 3, there was a between-group difference (p = 0.05) favoring the sertraline/clonazepam group, though there were no group differences in response after 4 or 12 weeks, or at other time points during the trial (Goddard et al., 2001). Pollack et al. (2003) conducted a 12-week RCT of patients with PD (N = 60, 34 completers), comparing three treatment arms: paroxetine (mean dose = 39 mg/day)/placebo, paroxetine (mean dose = 37 mg/day)/clonazepam (mean dose = 1.6 mg/day), followed by a taper of clonazepam (over 3 weeks, beginning at week 4), or ongoing combination treatment (mean dose paroxetine = 38.6 mg/day, clonazepam = 1.5 mg/day by study end). Similar to the Goddard et al. (2001) report, there was significant improvement on PDSS early in treatment (generally from weeks 1–5) in the two groups receiving combination treatment versus paroxetine monotherapy, but that all three groups exhibited a significant improvement on PDSS from baseline to end point, and there was no significant difference in outcome among the three groups by study end point (Pollack et al., 2003). There is also evidence to support the use of BZDs in SAD in patients resistant to or unable to tolerate SSRIs (Davidson, 2006; Schneier, 2006). However, in a small RCT of 28 patients with SAD treated with open-label paroxetine (20 – 40 mg/day) and either clonazepam (1– 2 mg/day, div. BID) or placebo for 10 weeks, no significant differences between the two groups were noted early or later in treatment (Seedat and Stein, 2004). To date, there are no published large RCTs of BZDs in adequately characterized samples of PTSD. The azapirone buspirone, a serotonin 1A (5-HT1A) agonist, is approved by the FDA for treating “anxiety disorders,” which correspond most closely to GAD as described in DSM-III. A retrospective analysis of pooled data from eight studies of buspirone versus placebo in GAD found that buspirone resulted in significant improvement on HAM-A versus placebo (p ≤ 0.001) (Gammans et al., 1992). Advantages of the serotonin 1A partial and full agonists include their overall tolerability, lack of addictive potential, and minimal sexual dysfunction or blood pressure effects (reviewed in Mathew and Hoffman, in press), though an important limitation of the azapirones is evidence of decreased efficacy

in patients with past benzodiazepine use (DeMartinis et al., 2000). Randomized controlled trials have not found buspirone to be effective in treating PD (Pohl et al., 1989; Sheehan et al., 1990; Sheehan et al., 1993), or SAD (van Vliet et al., 1997). ATYPICAL ANTIPSYCHOTICS Due to their broad neurochemical effects on postsynaptic 5-HT2 receptors and modulation of 5-HT1A, atypical antipsychotics have been tested for their anxiolytic potential. Two small RCTs have investigated olanzapine and risperidone as adjunctive agents to the SSRIs in GAD (Brawman-Mintzer et al., 2005; Pollack et al., 2006). Pollack et al. (2006) reported in a small (N = 24), single-site RCT that in patients with GAD who did not respond to fluoxetine (20 mg/day) after 6 weeks, olanzapine (mean dose = 8.7 mg/day) versus placebo augmentation resulted in a significant number of responders on HAM-A and CGI-S after 6 weeks. There were no other significant findings on other outcome measures and olanzapine resulted in sedation and significant weight gain (11.0 ± 5.1 lbs. on average, range 2–16 lbs.). In another small (N = 39) RCT, risperidone (0.5–1.5 mg/day) was used as an adjunctive treatment in patients with GAD who did not respond to at least 4 weeks of another medication, either an SSRI, SNRI, benzodiazepine, or other anxiolytic or antidepressant (Brawman-Mintzer et al., 2005). After 5 weeks of adjunctive treatment with risperidone or placebo, there were statistically significant reductions in HAM-A total and psychic anxiety scores in the risperidone versus the placebo augmentation group, but CGI-S reductions and CGI-I response rates were not significant (BrawmanMintzer et al., 2005). Risperidone was well-tolerated overall, though side effects included somnolence, dizziness, and blurred vision (Brawman-Mintzer et al., 2005). Olanzapine (5–20 mg/day) was also investigated as monotherapy for SAD in a very small (N = 12, 7 completers), 8-week RCT, in which there was significant improvement on the BSPS and Social Phobia Inventory, but not on LSAS and CGI-I, in the olanzapine versus placebo groups (Barnett et al., 2002). Risperidone adjunctive therapy was found to have some efficacy in combat-related PTSD (reviewed in Gao et al., 2006). Bartzokis et al. (2004) found that in male patients with chronic, combat-related PTSD, risperidone (titrated to a maximum of 3 mg/day in most patients), added to a stable psychotropic medication regimen (in 92% of patients), including antidepressants, anxiolytics, and/or hypnotics, resulted in significant improvement versus placebo on the CAPS after 16 weeks of treatment, which included an initial Veterans Administration (VA) residential psychosocial program for 5 weeks. Hamner et al. (2003) found that in combat veterans

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with chronic PTSD and psychotic symptoms, adjunctive risperidone (1–6 mg/day) resulted in significant improvement in psychotic symptoms, but not on the CAPS, compared to placebo after 5 weeks. In a 12-week pilot study of 20 women with PTSD related to sexual assault and domestic abuse, Padala et al. (2006) report that risperidone monotherapy (mean dose = 2.62 mg/ day) resulted in a significant decline in Treatment Outcomes PTSD Scale-8 scores from baseline, whereas no difference was observed from baseline to visit in the placebo group. Overall, RCTs of olanzapine in PTSD have been inconsistent, as a small (N = 15) RCT of olanzapine monotherapy (5–20 mg/day) in PTSD found no effect after 10 weeks (Butterfield et al., 2001), whereas an 8-week RCT of olanzapine (mean dose = 15 mg/ day) or placebo augmentation of SSRIs in 19 patients with combat-related PTSD found that olanzapine resulted in significant reductions in CAPS total scores, as well as depressive symptoms and sleep disturbance, but not in the percentage of CGI-I responders (M.B. Stein, Kline, et al., 2002). As of July 2007, to our knowledge, there were no published RCTs of quetiapine, aripiprazole, or ziprasidone in the anxiety disorders. SUMMARY AND FUTURE DIRECTIONS SSRIs and SNRIs will continue to be the primary pharmacotherapy treatments for anxiety disorders for the immediate future, given their overall better tolerability than older antidepressants. In the next decade, further refinements of these monoaminergic-based drugs, including triple reuptake inhibitors will be introduced. Innovations in the development of novel drugs, such as glutamate-modulators, corticotrophin releasing factor CRF antagonists, and neurokinin receptor 1 (NK1) receptor antagonists, as well as anxiety applications for newer anticonvulsants such as pregabalin, may turn out to be valuable alternatives to the benzodiazepines for the induction of rapid anxiolysis. Several areas for further study are recommended. Placebo Responsivity of Anxiety Disorders Randomized controlled trials of anxiety disorders have been plagued by high placebo responsivity, with notable differences across anxiety disorders in the magnitude of placebo responses (Huppert et al., 2004). Identifying moderators and predictors of placebo response in RCTs of anxiety disorders is critical, but very few clinical or demographic characteristics associated with placebo response have been identified (D.J. Stein, Baldwin, et al., 2006). Somewhat surprisingly, trials of PTSD are beleaguered by high placebo responsivity; as a recent example, a multicenter study of venlafaxine XR in chronic PTSD yielded placebo response rates of > 60%

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at 12 weeks (Davidson, Baldwin, et al., 2006). These extraordinarily high rates of placebo responsivity may result from the therapeutic “exposure” and extensive time requirements inherent to the major outcome instrument used in pivotal FDA regulatory studies, the CAPS. Briefer instruments, including self-report inventories, should be used in FDA-pivotal clinical trials, as suggested by Davidson, Baldwin, et al. (2006). Given the very high expected rates of placebo response, placebo arms remain an essential design feature for headto-head drug comparison studies, although industrysupported trials generally have avoided three-arm designs (two comparison drugs and placebo). Head-to-Head Comparisons of Medications The vast majority of comparative pharmacological studies in anxiety disorders is inconclusive (Table 44.2) and offer little guidance to clinicians in choice of agent. With a few noteworthy exceptions (for example, the Eli Lilly-funded head-to-head study of duloxetine and effexor XR), industry-funded clinical trials have found equivalence, or more commonly, noninferiority, of newer agents to older drugs in similar classes. Large-scale National Institute of Mental Health (NIMH) and/or foundation-sponsored comparative effectiveness trials (including psychotherapy arms) are needed in adult anxiety disorders, as has been performed for major depression, bipolar disorder, schizophrenia, and attention-deficit disorder, among other conditions. However, a search of the National Institutes of Health database of funded studies in 2007 (CRISP-Computer Retrieval of Information on Scientific Projects) did not find a single pharmacological clinical trial in any anxiety disorder using the R01 or Center Grant funding mechanisms, suggesting that major gaps in our knowledge base will continue. Analytic Methods As seen in Table 44.2, multiple analytic methods have been used (LOCF, MMRM, OC, completer), often without justification. Journal editors must serve as important arbiters of reporting standards for clinical trials for the anxiety disorders. The recent requirement of posting methodological details of RCTs on www .clinicaltrials.gov is an important step towards transparency. It has been proposed that RCTs in psychiatry should report, in addition to p values, the NNT and success rate difference (SRD) with its standard error and confidence interval (Kraemer and Kupfer, 2006). Assessment of Acute and Long-Term Response in RCTs The ACNP Task Force on Response and Remission for major depressive disorder has recommended that response criteria be met for 3 consecutive weeks to account

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for unstable symptomatic fluctuations and measurement error (Rush et al., 2006). Reliance on a single time point evaluation for 8- or 12-week RCTs in anxiety disorders as the primary outcome measure hinders analyses of durable and clinically meaningful drug–placebo differences. FDA pivotal RCTs in anxiety disorders also rarely assess the durability of acute pharmacotherapy. In contrast, it is standard for psychotherapy trials in anxiety disorders to report long-term outcome (3–6 months or 1 year). Areas of Critical Need Despite the high prevalence and morbidity associated with PTSD, there are currently only two FDA-approved medications for PTSD (sertraline and paroxetine). However, both these medications have ESs below 0.5. Many placebo-controlled trials of other medications in PTSD have failed, and even recent studies of approved medications (for example, sertraline) have failed to show efficacy in specific subgroups of patients with PTSD such as combat veterans (Friedman et al., 2007). REFERENCES Allgulander, C., Dahl, A.A., Austin, et al. (2004) Efficacy of sertraline in a 12-week trial for generalized anxiety disorder. Am. J. Psychiatry 161(9):1642–1649. Allgulander, C., Florea, I., et al. (2005) Prevention of relapse in generalized anxiety disorder by escitalopram treatment. Int. J. Neuropsychopharm. 9:1–11. Allgulander, C., Hackett, D., and Salinas, E. (2001) Venlafaxine extended release (ER) in the treatment of generalised anxiety disorder: twenty-four-week placebo-controlled dose-ranging study. Br. J. Psychiatry 179:15–22. Allgulander, C., Mangano, R., et al. (2004) Efficacy of venlafaxine ER in patients with social anxiety disorder: a double-blind, placebo-controlled, parallel-group comparison with paroxetine. Hum. Psychopharmacol. 19:387–396. American Psychiatric Association (1980) Diagnostic and Statistical Manual of Mental Disorders, 3rd ed. Washington, DC: Author. American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Asakura, S., Tajima, O., and Koyama, T. (2007) Fluvoxamine treatment of generalized social anxiety disorder in Japan: a randomized double-blind, placebo-controlled study. Int. J. Neuropsychopharm. 10(2):263–274. Asnis, G.M., Hameedi, F.A., et al. (2001) Fluvoxamine in the treatment of panic disorder: a multi-center, double-blind, placebocontrolled study in outpatients. Psychiatry Res. 103:1–14. Baldwin, D., Bobes, J., et al. (1999) Paroxetine in social phobia/social anxiety disorder. Randomised, double-blind, placebo-controlled study. Paroxetine Study Group. Br. J. Psychiatry 175:120–126. Baldwin, D.S., and Polkinghorn, C. (2005) Evidence-based pharmacotherapy of generalized anxiety disorder. Int. J. of Neuropsychopharm. 8:293–302. Ball, S.G., Kuhn, A., et al. (2005) Selective serotonin reuptake inhibitor treatment for generalized anxiety disorder: a double-blind, prospective comparison between paroxetine and sertraline. J. Clin. Psychiatry 66(1):94–99. Ballenger, J.C., Burrows, G.D., et al. (1988) Alprazolam in panic disorder and agoraphobia: results from a multicenter trial. I. Ef-

ficacy in short-term treatment. Arch. Gen. Psychiatry 45(5):413– 422. Ballenger, J.C., Wheadon, D.E., et al. (1998) Double-blind, fixeddose, placebo-controlled study of paroxetine in the treatment of panic disorder. Am. J. Psychiatry 155(1):36–42. Bandelow, B., Behnke, K., et al. (2004) Sertraline versus paroxetine in the treatment of panic disorder: an acute, double-blind noninferiority comparison. J. Clin. Psychiatry 65:405–413. Barlow, D.H., Gorman, J.M., et al. (2000) Cognitive-behavioral therapy, imipramine, or their combination for panic disorder: A randomized controlled trial. JAMA 283(19):2529–2536. Barnett, S.D., Kramer, M.L., et al. (2002) Efficacy of olanzapine in social anxiety disorder: a pilot study. J. Psychopharmacol. 16(4): 365–368. Bartzokis, G., Lu, P.H., et al. (2004) Adjunctive risperidone in the treatment of chronic combat-related posttraumatic stress disorder. Biol. Psychiatry 57:474–479. Berlant, J., and van Kammen, D.P. (2002) Open-label topiramate as primary or adjunctive therapy in chronic civilian posttraumatic stress disorder: a preliminary report. J. Clin. Psychiatry 6(1): 15–20. Berlant, J.L. (2004) Prospective open-label study of add-on and monotherapy topiramate in civilians with chronic nonhallucinatory posttraumatic stress disorder. BMC Psychiatry 18(4):24. Bielski, R.J., Bose, A., et al. (2005) A double-blind comparison of escitalopram and paroxetine in the long-term treatment of generalized anxiety disorder. Ann. Clin. Psychiatry 17(2):65–69. Black, D.W., Wesner, R., et al. (1993) A comparison of fluvoxamine, cognitive therapy, and placebo in the treatment of panic disorder. Arch. Gen. Psychiatry 50 (1):44–50. Blanco, C., Schneier, F.R., et al. (2003) Pharmacological treatment of social anxiety disorder: a meta-analysis. Depress. Anxiety 18: 29–40. Blomhoff, S., Haug, T.T., et al. (2001) Randomised controlled general practice trial of sertraline, exposure therapy and combined treatment in generalised social phobia. Br. J. Psychiatry 179: 23–30. Bradwejn, J., Ahokas, A., et al. (2005) Venlafaxine extended-release capsules in panic disorder: flexible-dose, double-blind, placebocontrolled study. Br. J. Psychiatry 187:352–359. Brawman-Mintzer, O., Knapp, R.G., and Nietert, P.J. (2005) Adjunctive risperidone in generalized anxiety disorder: a doubleblind, placebo-controlled study. J. Clin. Psychiatry 66(10):1321– 1325. Butterfield, M.I., Becker, M.E., et al. (2001) Olanzapine in the treatment of post-traumatic stress disorder: a pilot study. Int. Clin. Psychopharmacol. 16:197–203. Clark, D.M., Ehlers, A., et al. (2003) Cognitive therapy versus floxetine in generalized social phobia: a randomized placebo-controlled trial. J. Consult. Clin. Psychology 71(6):1058–1067. Connor, K.M., Davidson, J.R., et al. (2006) Tiagabine for post-traumatic stress disorder: effects of open-label and double-blind discontinuation treatment. Psychopharmacol. (Berl) 184(1):21–25. Cross-National Collaborative Panic Study, Second Phase Investigators (1992) Drug treatment of panic disorder. Comparative efficacy of alprazolam, imipramine, and placebo. Br. J. Psychiatry 160:191–202; discussion 202–205. Dahl, A.A., Ravindran, A., et al. (2005) Sertraline in generalized anxiety disorder: efficacy in treating the psychic and somatic anxiety factors. Acta. Psychiatr. Scand. 111:429–435. Davidson, J., Baldwin, D., Stein, D.J., Kuper, E., Benattia, I., Ahmed, S., Pedersen, R., and Musgnung, J. (2006) Treatment of posttraumatic stress disorder with venlafaxine extended release: a 6month randomized controlled trial. Arch. Gen. Psychiatry 63: 1158–1165. Davidson, J., Rothbaum, B.O., Tucker, P., Asnis, G., Benattia, I., and Musgnung, J.J. (2006) Venlafaxine extended release in post-

44: PHARMACOTHERAPY traumatic stress disorder: A sertraline- and placebo-controlled study. J Clin Psychopharmacol. 26 (3): 259–267. Davidson, J., Yaryura, T., et al. (2004) Fluvoxamine-controlled release formulation for the treatment of generalized social anxiety disorder. J. Clin. Psychopharm. 24(2):118–125. Davidson, J.R.T. (2006) Pharmacotherapy of social anxiety disorder: what does the evidence tell us? J. Clin. Psychiatry 67 (Suppl 12):20–26. Davidson, J.R.T., Bose, A., et al. (2004) Escitalopram in the treatment of generalized anxiety disorder: double-blind, placebo controlled, flexible-dose study. Depress. Anxiety 19:234–240. Davidson, J.R.T., Bose, A., et al. (2005) Safety and efficacy of escitalopram in the long term treatment of generalized anxiety disorder. J. Clin. Psychiatry 66(11):1441–1446. Davidson, J.R.T., Brady, K., et al. (2007) The efficacy and tolerability of tiagabine in adult patients with post-traumatic stress disorder. J. Clin. Psychopharmacol. 27(1):85–88. Davidson, J.R.T., DuPont, R.L., et al. (1999) Efficacy, safety, and tolerability of venlafaxine extended release and buspirone in outpatients with generalized anxiety disorder. J. Clin. Psychiatry 60(8): 528–535. Davidson, J.R.T., Foa, E.B., et al. (2004) Fluoxetine, comprehensive cognitive behavioral therapy, and placebo in generalized social phobia. Arch. Gen. Psychiatry 61:1005–1013. DeMartinis, N., Rynn, M., et al. (2000) Prior benzodiazepine use and buspirone response in the treatment of generalized anxiety disorder. J. Clin. Psychiatry 62(8):657–658. Dunlop, B.W., Papp, L., et al. (2007) Tiagabine for social anxiety disorder. Hum. Psychopharmacol. 22(4):241–244. Federoff, I.C., and Taylor, S. (2001) Psychological and pharmacological treatments of social phobia: a meta-analysis. J. Clin. Psychopharmacol. 21(3):311–324. Feltner, D.E., Crockatt, J.G., et al. (2003) A randomized, doubleblind, placebo-controlled, fixed-dose, multicenter study of pregabalin in patients with generalized anxiety disorder. J. Clin. Psychopharm. 223(3):240–249. Ferguson, J.M., Khan, A., et al. (2007) Relapse prevention of panic disorder in adult outpatient responders to treatment with venlafaxine extended release. J. Clin. Psychiatry 68(1):58–68. Friedman, M.J., Marmar, C.R., et al. (2007) Randomized, doubleblind comparison of sertraline and placebo for posttraumatic stress disorder in a Department of Veterans Affairs setting. J. Clin. Psychiatry 68 (5):711–720. Furukawa, T.A., Watanabe, N., et al. (2007) Combined psychotherapy plus antidepressants for panic disorder with or without agoraphobia. Cochrane Database of Systematic Reviews Issue 1. Art. No.: CD004364. DOI: 10.1002/14651858.CD004364.pub2. Gammans, R.E., Stringfellow, J.C., et al. (1992) Use of buspirone in patients with generalized anxiety disorder and coexisting depressive symptoms. A meta-analysis of eight, randomized, controlled studies. Neuropsychobiology 25(4):193–201. Gao, K., Muzina, D., et al. (2006) Efficacy of typical and atypical antipsychotics for primary and comorbid anxiety symptoms or disorders: a review. J. Clin. Psychiatry 67:1327–1340. Gellenberg, A.J., Lydiard, R.B., et al. (2000) Efficacy of venlafaxine extended-release capsules in nondepressed outpatients with generalized anxiety disorder: a 6-month randomized controlled trial. JAMA 283(23):3082–3088. Goddard, A.W., Brouette, T., et al. (2001) Early coadministration of clonazepam with sertraline for panic disorder. Arch. Gen. Psychiatry 58:681–686. Goddard, A.W., Coplan, J.D., et al. (2002) Principles of pharmacotherapy for the anxiety disorders. In: Charney, D.S., ed. Neurobiology of Mental Illness, 2nd ed. New York: Oxford University Press. Hackett, D., Haudiquet, V., and Salinas, E. (2003) A method for controlling for a high placebo response rate in a comparison of

751

venlafaxine XR and diazepam in the short-term treatment of patients with generalised anxiety disorder. Eur. Psychiatry 18:182–187. Hamner, M.B., Faldowski, R.A., et al. (2003) Adjunctive risperidone treatment in post-traumatic stress disorder: a preliminary controlled trial of effects on comorbid psychotic symptoms. Int. Clin. Psychopharmacol. 18:1–8. Hartford, J., Kornstein, S., et al. (2007) Duloxetine as an SNRI treatment for generalized anxiety disorder: results from a placebo and active-controlled trial. Int. Clin. Psychopharmacol. 22:167–174. Haug, T.T., Blomhoff, S., et al. (2003) Exposure therapy and sertraline in social phobia: 1-year follow-up of a randomised controlled trial. Br. J. Psychiatry 182:312–318. Hedges, D.W., Brown, B.L., et al. (2007) The efficacy of selective serotonin reuptake inhibitors in adult social anxiety disorder: a meta-analysis of double-blind, placebo-controlled trials. J. Psychopharmacol. 21(1):102–111. Heimberg, R.G., Liebowitz, M.R., et al. (1998) Cognitive behavioral group therapy vs. phenelzine therapy for social phobia: 12week outcome. Arch. Gen. Psychiatry 55(12):1133–1141. Hertzberg, M.A., Butterfield, M.I., et al. (1999) A preliminary study of lamotrigine for the treatment of posttraumatic stress disorder. Biol. Psychiatry 45(9):1226–1229. Heuer, L., Mathew, S.J., and Charney, D.S. (in press) Panic disorder. In: Squire, L., Albright, T., Bloom, F., Gage, F., Spitzer, N., eds. New Encyclopedia of Neuroscience. Oxford, UK: Elsevier Ltd. Hoehn-Saric, R., McLeod, D.R., and Hipsley, P.A. (1993) Effect of fluvoxamine on panic disorder. J. Clin. Psychopharmacol. 13(5): 321–326. Huppert, J.D., Schultz, L.T., Foa, E.B., Barlow, D.H., Davidson, J.R.T., Gorman, J.M., Shear, M.K., Simpson, H.B., and Woods, S.W. (2004) Differential response to placebo among patients with social phobia, panic disorder, and obsessive-compulsive disorder. Am. J. Psychiatry 161:1485–1487. International Multicenter Clinical Trial Group on Moclobemide in Social Phobia (1997) The International Multicenter Clinical Trial Group on Moclobemide in Social Phobia. A double-blind, placebo-controlled clinical study. Eur. Arch. Psychiatry Clin. Neurosci. 247(2):71–80. Kapczinski, F.., Lima, M.S., et al. (2003) Antidepressants for generalized anxiety disorder. Cochrane Database of Systematic Reviews Issue 2. Art. No.: CD003592. DOI: 10.1002/14651858. CD003592. Kasper, S., Stein, D.J., et al. (2005) Escitalopram in the treatment of social anxiety disorder. Br. J. Psychiatry 186:222–226. Katon, W.J. (2006) Panic disorder. N. Engl. J. Med. 354(22):2360– 2367. Kim, T.-S., Pae, C.-U., et al. (2006) Comparison of venlafaxine extended release versus paroxetine for treatment of patients with generalized anxiety disorder. Psychiatry Clin. Neurosci. 60:347– 351. Kinrys, G., Wygant, L.E., et al. (2006) Levetiracetam for treatmentrefractory posttraumatic stress disorder. J. Clin. Psychiatry 67: 211–214. Kobak, K.A., Greist, J.H., et al. (2002) Fluoxetine in social phobia: a double-blind, placebo-controlled pilot study. J. Clin. Psychopharmacol. 22:257–262. Kraemer, H.C., and Kupfer, D.J. (2006) Size of treatment effects and their importance to clinical research and practice. Biol. Psychiatry 59(11):990–996. Lader, M., Stender, K., et al. (2004) The efficacy and tolerability of escitalopram in the short- and long-term treatment of social anxiety disorder: a randomized, double-blind, placebo-controlled, fixed-dose study. Depress. Anxiety 19:241–248. Lecrubier, Y., Bakker, A., et al. (1997) A comparison of paroxetine, clomipramine and placebo in the treatment of panic disorder. Collaborative Paroxetine Panic Study Investigators. Acta Psychiatr. Scand. 95(2):145–152.

752

ANXIETY DISORDERS

Lecrubier, Y., and Judge R. (1997) Long-term evaluation of paroxetine, clomipramine and placebo in panic disorder. Collaborative Paroxetine Panic Study Investigators. Acta Psychiatr. Scand. 95(2): 153–60. Leopola, U.M., Wade, A.G., et al. (1998) A controlled, prospective, 1-year trial of citalopram in the treatment of panic disorder. J. Clin. Psychiatry 59(10):528–534. Lepola, U., Bergtholdt, B., et al. (2004) Controlled-release paroxetine in the treatment of patients with social anxiety disorder. J. Clin. Psychiatry 65:222–229. Liebowitz, M.R., DeMartinis, N.A., et al. (2003) Efficacy of sertraline in severe generalized social anxiety disorder: results of a double-blind, placebo-controlled study. J. Clin. Psychiatry 64(7): 785–792. Liebowitz, M.R., Gelenberg, A.J., and Munjack, D. (2005) Venlafaxine extended release vs. placebo and paroxetime in social anxiety disorder. Arch. Gen. Psychiatry 62:190–198. Liebowitz, M.R., Heimberg, R.G. et al. (1999) Cognitive-behavioral group therapy versus phenelzine in social phobia: long-term outcome. Depress. Anxiety 10(3):89–98. Liebowitz, M.R., Hollander, E., et al. (1990) Reversible and irreversible monoamine oxidase inhibitors in other psychiatric disorders. Acta Psychiatr. Scand. (Suppl. 360):29–34. Liebowitz, M.R., Mangano, R.M., et al. (2005) A randomized controlled trial of venlafaxine extended release in generalized social anxiety disorder. J. Clin. Psychiatry 66(2):238–247. Liebowitz, M.R., Schneier, F., et al. (1990) Phenelzine and atenolol in social phobia. Psychopharmacol. Bull. 26(1):123–125. Liebowitz, M.R., Schneier, F., et al. (1992) Phenelzine vs. atenolol in social phobia. A placebo-controlled comparison. Arch. Gen. Psychiatry 49(4):290–300. Liebowitz, M.R., Stein, M.B., Tancer, M., et al. (2002) A randomized, double-blind, fixed-dose comparison of paroxetine and placebo in the treatment of generalized social anxiety disorder. J. Clin. Psychiatry 63:66–74. Lott, M., Greist, J.H., et al. (1997) Brofaromine for social phobia: a multicenter, placebo-controlled, double-blind study. J. Clin. Psychopharmacol. 17(4):255–260. Lydiard, R.B., and Monnier, J. (2004) Pharmacological treatment. In Heimberg, R.C., Turk, C.L., Mannin, D.S., eds. Generalized Anxiety Disorder: Advances in Research and Practice. New York: Guilford Press, pp. 351–379. Marshall, R.D., Beebe, K.L., Oldham, M., and Zaninelli, R. (2001) Efficacy and safety of paroxetine treatment for chronic PTSD: a fixed-dose, placebo-controlled study. Am. J. Psychiatry 158:1982– 1988. Mathew, S.J., and Hoffman, E.J. (in press) Pharmacotherapy of generalized anxiety disorder. In: Antony, M., and Stein, M., eds. Oxford Handbook of Anxiety and Anxiety Disorders. New York: Oxford University Press. Michelson, D., Allgulander, K., et al. (2001) Efficacy of usual antidepressant dosing regimens of fluoxetine in panic disorder. Br. J. Psychiatry 179:514–518. Michelson, D., Lydiard, R.B., et al. (1998) Outcome assessment and clinical improvement in panic disorder: evidence from a randomized controlled trial of fluoxetine and placebo. Am. J. Psychiatry 155(11):1570–1577. Mitte, K. (2005) A meta-analysis of the efficacy of psycho- and pharmacotherapy in panic disorder with and without agoraphobia. J. Affect. Disord. 88:27–45. Montgomery, S.A., Nil, R., et al. (2005) A 24-week randomized, double-blind, placebo-controlled study of escitalopram for the prevention of generalized social anxiety disorder. J. Clin. Psychiatry 66:1270–1278. Montgomery, S.A., Tobias, K., et al. (2006) Efficacy and safety of pregabalin in the treatment of generalized anxiety disorder: a 6week, multicenter, randomized, double-blind placebo-controlled

comparison of pregabalin and venlafaxine. J. Clin. Psychiatry 67: 771–782. Mula, M., Pini, S., and Cassano, G.B. (2007) The role of anticonvulsant drugs in anxiety disorders: a critical review of the evidence. J. Clin. Psychopharmacol. 27(3):263–272. Nimatoudis, I., Zissis, N.P., et al. (2004) Remission rates with venlafaxine extended release in Greek outpatients with generalized anxiety disorder. A double-blind, randomized, placebo controlled study. Int. Clin. Psychopharmacol. 19:331–336. Noyes, R., Moroz, G., et al. (1997) Moclobemide in social phobia: a controlled dose-response trial. J. Clin. Psychopharmacol. 17(4): 247–254. O’Brien, C.P. (2005) Benzodiazepine use, abuse, and dependence. J. Clin. Psychiatry 66(Suppl 2):28–33. Otto, M. W., Tuby, K.S., et al. (2001) An effect-size analysis of the relative efficacy and tolerability of serotonin selective reuptake inhibitors for panic disorder. Am. J. Psychiatry 158:1989–1992. Padala, P.R., Madison, J., et al. (2006) Risperidone monotherapy for post-traumatic stress disorder related to sexual assault and domestic abuse in women. Int. Clin. Psychopharmacol. 21:275– 280. Pande, A.C., Crockatt, J.G., et al. (2003) Pregabalin in generalized anxiety disorder: a placebo-controlled trial. Am J. Psychiatry 160(3):533–540. Pande, A.C., Davidson, J.R.T., et al. (1999) Treatment of social phobia with gabapentin: a placebo-controlled study. J. Clin. Psychopharmacol. 19(4):341–348. Pande, A.C., Feltner, D.E., et al. (2004) Efficacy of the novel anxiolytic pregabalin in social anxiety disorder: a placebo-controlled, multicenter study. J. Clin. Psychopharmacol. 24(2):141–149. Pande, A.C., Pollack, M.H., et al. (2000) Placebo-controlled study of gabapentin treatment of panic disorder. J. Clin. Psychopharmacol. 20(4):467–471. Papp, L.A. (2006) Safety and efficacy of levetiracetam for patients with panic disorder: results of an open-label, fixed-flexible dose study. J. Clin. Psychiatry 67(10):1573–1576. Perna, G., Bertani, A., et al. (2001) A comparison of citalopram and paroxetine in the treatment of panic disorder: a randomized, single-blind study. Pharmacopsychiatry 34:85–90. Pohl, R., Balon, R., et al. (1989) Serotonergic anxiolytics in the treatment of panic disorder: a controlled study with buspirone. Psychopathology 22(Suppl 1):60–67. Pohl, R.B., Feltner, D.E., et al. (2005) Efficacy of pregabalin in the treatment of generalized anxiety disorder. J. Clin. Psychopharm. 25(2):151–158. Pohl, R.B., Wolkow, R.M., et al. (1998) Sertraline in the treatment of panic disorder: a double-blind multicenter trial. Am. J. Psychiatry 155(9):1189–1195. Pollack, M.H., Lepola, U., et al. (2007) A double-blind study of the efficacy of venlafaxine extended-release, paroxetine, and placebo in the treatment of panic disorder. Depress. Anxiety 24:1–14. Pollack, M.H., Otto, M.W., et al. (1998) Sertraline in the treatment of panic disorder. Arch. Gen. Psychiatry 55:1010–1016. Pollack, M.H., Roy-Byrne, P.P., et al. (2005) The selective GABA reuptake inhibitor tiagabine for the treatment of generalized anxiety disorder: results of a placebo-controlled study. J. Clin. Psychiatry 66(11):1401–1408. Pollack, M.H., Simon, N.M., et al. (2003) Combined paroxetine and clonazepam treatment strategies compared to paroxetine monotherapy for panic disorder. J. Psychopharmacol. 17(3):276– 282. Pollack, M.H., Zaninelli, R., et al. (2001) Paroxetine in the treatment of generalized anxiety disorder: results of a placebo-controlled, flexible-dosage trial. J. Clin. Psychiatry 62(5):350–357. Pollack, M.H., Simon, N.M., et al. (2006) Olanzapine augmentation of fluoxetine for refractory generalized anxiety disorder: a placebo controlled study. Biol. Psychiatry 59:211–215.

44: PHARMACOTHERAPY Prasko, J., Dockery C., et al. (2006) Moclobemide and cognitive behavioral therapy in the treatment of social phobia. A six-month controlled study and 24 months of follow up. Neuro. Endocrinol. Lett. 27(4):473–481. Rapaport, M.H., Wolkow, R., et al. (2001) Sertraline treatment of panic disorder: results of a long-term study Acta Psychiatr. Scand. 104:289–298. Rickels, K., Downing, R., et al. (1993) Antidepressants for the treatment of generalized anxiety disorder: a placebo-controlled comparison of imipramine, trazodone, and diazepam. Arch. Gen. Psychiatry 50:884–895. Rickels, K., Mangano, R., and Khan, A. (2004) A double-blind, placebo-controlled study of a flexible dose of venlafaxine ER in adult outpatients with generalized social anxiety disorder. J. Clin. Psychopharm. 24(5):488–496. Rickels, K., Pollack, M.H., et al. (2000) Efficacy of extended-release venlafaxine in nondepressed outpatients with generalized anxiety disorder. Am. J. Psychiatry 157(6):968–974. Rickels, K., Pollack, M.H., et al. (2005) Pregabalin for treatment of generalized anxiety disorder: a 4-week, multicenter, double-blind, placebo-controlled trial of pregabalin and alprazolam. Arch. Gen. Psychiatry 62:1022–1030. Rickels, K., Zaninelli, R., et al. (2003) Paroxetine treatment of generalized anxiety disorder: a double-blind, placebo-controlled study. Am. J. Psychiatry 160(4):749–756. Rocca, P., Fonzo, V., et al. (1997) Paroxetine efficacy in the treatment of generalized anxiety disorder. Acta Psychiatr Scand. 95(5): 444–450. Rosenbaum, J.F., Arana, G.W., et al. (2005) Handbook of Psychiatric Drug Therapy, 5th ed. Philadelphia: Lippincott Williams & Wilkins. Rosenthal, M. (2003) Tiagabine for the treatment of generalized anxiety disorder: a randomized, open-label clinical trial with paroxetine as a positive control. J. Clin. Psychiatry 64(10):1245–1249. Rush, A.J., Kraemer, H.C., et al. (2006) Report by the ACNP Task Force on Response and remission in major depressive disorder. Neuropsychopharmacology 31 (9):1841–1853. Rynn, M., Russell, J., et al. (2007) Efficacy and safety of duloxetine in the treatment of generalized anxiety disorder: a flexible-dose, progressive-titration, placebo-controlled trial. Depress. Anxiety 0:1–8. Schneier, F.R. (2006) Social anxiety disorder. N. Engl. J. Med. 355(10): 1029–1036. Schneier, F.R., Goetz, D., et al. (1998) Placebo-controlled trial of moclobemide in social phobia. Br. J. Psychiatry 172:70–77. Schweizer, E., Rickels, K., et al. (1993) Maintenance drug treatment of panic disorder. I. Results of a prospective, placebo-controlled comparison of alprazolam and imipramine. Arch. Gen. Psychiatry 50(1):51–60. Seedat, S., and Stein, M.B. (2004) Double-blind placebo-controlled assessment of combined clonazepam with paroxetine compared with paroxetine monotherapy for generalized social anxiety disorder. J. Clin. Psychiatry 65(2):244–248. Sheehan, D.V., Burnham, D.B., et al. (2005) Efficacy and tolerability of controlled-release paroxetine in the treatment of panic disorder. J. Clin. Psychiatry 66(1):34–40. Sheehan, D.V., Raj, A.B., et al. (1990) Is buspirone effective for panic disorder? J. Clin. Psychopharmacol. 10(1):3–11. Sheehan, D.V., Raj, A.B., et al. (1993) The relative efficacy of high dose buspirone and alprazolam in the treatment of panic disorder: a double-blind placebo-controlled study. Acta Psychiatr. Scand. 88(1):1–11. Simon, N.M., Worthington, J.J., et al. (2004) An open-label study of levetiracetam for the treatment of social anxiety disorder. J. Clin. Psychiatry 65:1219–1222. Stahl, S.M., Gergel, I., and Li, D. (2003) Escitalopram in the treatment of panic disorder: a randomized, double-blind, placebocontrolled trial. J. Clin. Psychiatry 64:1322–1327.

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Stein, D.J., Baldwin, D.S., Dolberg, O.T., Despiegel, N., and Bandelow, B. (2006) Which factors predict placebo response in anxiety disorders and major depression? An analysis of placebo-controlled studies of escitalopram. J. Clin. Psychiatry 67(11):1741–1746. Stein, D.J., Cameron, A., et al. (2002) Moclobemide is effective and well tolerated in the long-term pharmacotherapy of social anxiety disorder with or without comorbid anxiety disorder. Int. Clin. Psychopharmacol. 17 (4):161–170. Stein, D.J., Ipser, J.C., and van Balkom A.J. (2000) Pharmacotherapy for social anxiety disorder. Cochrane Database of Systematic Reviews Issue 4. Art. No.: CD001206. DOI: 10.1002/14651858. CD001206.pub2. Stein, D.J., Ipser J.C., et al. (2006) Pharmacotherapy for post traumatic stress disorder (PTSD). Cochrane Database Syst. Rev. Issue 1: CD002795. Stein, D.J., Versiani, M., et al. (2002) Efficacy of paroxetine for relapse prevention in social anxiety disorder: a 24-week study. Arch. Gen. Psychiatry 59:1111–1118. Stein, D.J., Westenberg, H.G.M., et al. (2003) Fluvoxamine CR in the long-term treatment of social anxiety disorder: the 12- to 24week extension phase of a multicentre, randomized, placebocontrolled trial. Int. J. Neuropsychopharm. 6(4):317–323. Stein, M.B., Fyer, A.J., et al. (1999) Fluvoxamine treatment of social phobia (social anxiety disorder): a double-blind, placebo-controlled study. Am. J. Psychiatry 156:756–760. Stein, M.B., Kline, N.A., and Matloff, J.L. (2002) Adjunctive olanzapine for SSRI-resistant combat-related PTSD: a double-blind, placebo-controlled study. Am. J. Psychiatry 159:1777–1779. Stein, M.B., Liebowitz, M.R., et al. (1998) Paroxetine treatment of generalized social phobia (social anxiety disorder): a randomized controlled trial. JAMA 280(8):708–713. Stein, M.B., Pollack, M.H., et al. (2005) Efficacy of low and higher dose extended-release venlafaxine in generalized social anxiety disorder: a 6-month randomized controlled trial. Psychopharmacol. 177:280–288. Stocchi, F., Nordera, G., et al. for the Paroxetine Generalized Anxiety Disorder Study Team. (2003) Efficacy and tolerability of paroxetine for the long-term treatment of generalized anxiety disorder. J. Clin. Psychiatry 64(3):250–258. Tesar, G.E., Rosenbaum, J.F., et al. (1991) Double-blind, placebocontrolled comparisons of clonzaepam and alprazolam for panic disorder. J. Clin. Psychiatry 52(2):69–76. Tiller, J.W., Bouwer, C., and Behnke, K. (1999) Moclobemide and fluoxetine for panic disorder. International Panic Disorder Study Group. Eur. Arch. Psychiatry Clin. Neurosci. 249(Suppl 1):S7–S10. Tucker, P., Trautman, R.P., et al. (2007) Efficacy and safety of topiramate monotherapy in civilian post-traumatic stress disorder: a randomized, double-blind, placebo-controlled study. J. Clin. Psychiatry 68:201–206. Tucker, P., Zaninelli, R., Yehuda, R., Ruggiero, L., Dillingham, K., Pitts, C.D. (2001) Paroxetine in the treatment of chronic posttraumatic disorder: results of a placebo-controlled, flexible-dosage trial. J. Clin. Psychiatry 62:860–868. Uhde, T.W., Stein, M.B., and Post, R.M. (1988) Lack of efficacy of carbamazepine in the treatment of panic disorder. Am. J. Psychiatry 145(9):1104–1109. Van Ameringen, M., Mancini, C., et al. (2004) An open trial of topiramate in the treatment of generalized social phobia. J. Clin. Psychiatry 65(12):1674–1678. Van Ameringen, M.A., Lane, R.M., et al. (2001) Sertraline treatment of generalized social phobia: a 20-week, double-blind, placebo-controlled study. Am. J. Psychiatry 158(2):275–281. Van der Linden, G.J., Stein, D.J., and van Balkom, A.J. (2000) The efficacy of the selective serotonin reuptake inhibitors for social anxiety disorder (social phobia): a meta-analysis of randomized controlled trials. Int. Clin. Psychopharmacol. 15(Suppl 2):S15– S23.

754

ANXIETY DISORDERS

van Vliet, I.M., den Boer, J.A., et al. (1996) A double-blind comparative study of brofaromine and fluvoxamine in outpatients with panic disorder. J. Clin. Psychopharmacol. 16(4):299–306. van Vliet, I.M., den Boer, J.A., et al. (1997) Clinical effects of buspirone in social phobia: a double-blind placebo-controlled study. J. Clin. Psychiatry 58(4):164–168. van Vliet, I.M., Westenberg, H.G., and Den Boer, J.A. (1993) MAO inhibitors in panic disorder: clinical effects of treatment with brofaromine. A double blind placebo controlled study. 112(4):483– 489. Wade, A.G., Lepola, U., et al. (1997) The effect of citalopram in panic disorder. Br. J. Psychiatry 170:549–553. Walker, J.R., Van Ameringen, M.A., et al. (2000) Prevention of relapse

in generalized social phobia: results of a 24-week study in responders to 20 weeks of sertraline treatment. J. Clin. Psychopharm. 20(6):636–644. Westenberg, G.M., Stein, D.J., et al. (2004) A double-blind placebocontrolled study of controlled release fluvoxamine for the treatment of generalized social anxiety disorder. J. Clin. Psychopharm. 24(1):49–55. Working Group on Panic Disorder. (1998) Practice guideline for the treatment of patients with panic disorder. Am. J. Psychiatry 155 (Suppl):1–34. Zhang, W., Connor, K.M., and Davidson, J.R. (2005) Levetiracetam in social phobia: a placebo controlled pilot study. J. Psychopharmacol. 19(5):551–553.

VI

SUBSTANCE ABUSE DISORDERS STEVEN E. HYMAN

A

buse of and addiction to nicotine, alcohol, psychostimulants, opiates, and marijuana result in profoundly negative effects on public health and more broadly on societies. The negative effects on health result from the direct pharmacological effects of abused drugs and from the ways in which they are used—for example, smoked or injected using nonsterile needles. Disorders that all too commonly result from drug use include lung cancer, cirrhosis, hepatitis B and C, human immunodeficiency virus, and depression. Drug-related illness and lives focused on obtaining, using, and recovering from drugs entail enormous social costs in terms of lost educational opportunities, lost productivity, and failure in myriad life roles. As a result of direct pharmacological effects and illegal drug trafficking, these substances are also a major cause of violence and crime. The chapters that follow discuss recent progress in neuroscience, behavioral neuroscience, and clinical investigation that sheds light on a very complex series of disorders and their treatment. During the past decade, progress in neuroscience at the molecular and cellular levels has accelerated rapidly (Chapter 46), and the powerful tools of modern genomics and genetics have been brought to bear on the problems of drug abuse and addiction (Chapter 47). The application of genetic engineering to mouse models has brought an important synthesis between behavioral neuroscience and more reductionist approaches (Chapter 45). More recently, mechanistic studies of brain function in animal models has informed (and been informed by) human neurobiology through the application of noninvasive neuroimaging to drugs of abuse and addictive disorders as well as to natural rewards (Chapters 49 and 50). The search for genetic variants that contribute to the human risk of substance abuse disorders (Chapter 47) has proven extremely challenging given the difficulty of defining phenotypes and the complexity of the genetic and nongenetic contributions to risk. The combination of increasingly sophisticated genetic epidemiology with methods derived from modern genomics will likely result, in the coming decade, in the identification of multiple genetic loci that modify risk. Such discov-

eries will have important implications for early intervention and prevention. Even more significant, perhaps, such discoveries will provide critical tools for understanding the pathophysiology of addiction and for the identification of new protein targets in the brain for the development of pharmacological therapies. The need to develop such therapies is clear. While incremental progress continues, the development of broadly effective treatments still lags, especially for psychostimulant addiction. There is, nonetheless, a growing base of convincing data to guide treatment (Chapter 51). The impact of drugs of abuse on the developing fetus can be dire—and all too prevalent (Chapter 48). The challenges facing investigators in this field are enormous. Although the core of research on addiction can focus on known brain reward pathways, research on the developmental effects of drugs must examine the whole brain. The relationship between the human situation and animal models is also quite complex because pregnant human drug abusers are rarely exposed only to a single drug in pure form but often expose themselves and their unborn children to multiple agents, often impure, as well as to malnutrition, high levels of stress, disturbed cycles of sleep, and other problems. Thus, using animal models that are truly informative requires that investigators think through a whole host of issues, including not only the myriad complicating factors just enumerated but also the relevance of different species to human neurobiology, the timing of drug administration during gestation, and when, during subsequent development, to look for behavioral or anatomical abnormalities. Despite the challenges, understanding of the pathophysiology of drug abuse and addiction is further advanced than that of most other psychiatric disorders. The basis for this progress is knowledge of the initial molecular targets for virtually all classes of addictive drugs, of the neural pathways that underlie the rewarding effects of addictive drugs, and availability of useful animal models. As described by Gardner and Wise (Chapter 45) and by Nestler (Chapter 46), the major shared substrate of the reinforcing properties of addictive drugs is the dopaminergic projection that extends

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from the ventral tegmental area (VTA) of the midbrain to the nucleus accumbens and several regions of frontal cortex. The complex inputs and outputs of this mesoaccumbens/mesocortical brain reward pathway and drug-induced changes in the structure and function of these neurons have been critical foci of investigation for more than a decade. Although there is no standard or even fully valid animal model of addiction, the models that we do have are more compelling in terms of their face validity than models we have of essentially any other behavioral disorder. Armed with an anatomical locus and with at least partially successful animal models, a great deal of pharmacological and neurobiological investigation has been possible at a level of detail that has not been feasible for many other disease categories described in this book. By knowing where in the brain to look, and by having the drugs that initiate behaviors of interest, it has been possible to deepen our knowledge of the shortand long-term effects of drugs of abuse on the brain (Chapter 46). This knowledge has also served to focus the neuroimaging research that can be performed on humans on relevant circuits and relevant neurochemical systems—again, an advantage compared with research on most other disease classes described in this book. Thus, Montague and Chiu can study the role of the mesoaccumbens reward circuit in regulating responses

to natural rewards (Chapter 50), while Fowler and Volkow are in a position (Chapter 49) to describe not only adaptations that occur in response to drugs of abuse but also potential vulnerability factors related to brain dopamine systems. Importantly, hypotheses suggested by human imaging experiments can be applied to animal models to investigate underlying mechanisms. Advances in neurobiology have even provided a platform for thinking about therapeutic development. The use of naltrexone and other long-acting opiate antagonists for the treatment of alcoholism follows from our increasing scientific understanding of neural adaptations to drugs of abuse and of neural circuitry contributing to reinforcement. It is important, however, not to underestimate the remaining challenges for our basic scientific understandings and for treatment. For example, we should recognize that our existing treatment armamentarium for adults, let alone for children exposed to drugs in utero, is far from satisfactory. Overcoming the hurdles relating brain mechanisms to behavior, for example, will require increasing discourse among scientists working at different levels of analysis. In some sense, the challenges now facing the addiction research and treatment development communities presage the challenges that will face researchers on mood disorders and schizophrenia as better animal models emerge.

45 Animal Models of Addiction ELIOT L. GARDNER

A N D

ROY A. WISE

Most of our knowledge of the neurobiology of addiction comes from animal models. Inasmuch as addiction is a uniquely human phenomenon (animals only become truly addicted with human help), each animal model is an approximation that captures some but not all of the characteristics of the human condition. The most troublesome fact for the development of animal models is that there is no generally accepted definition of addiction. Addiction is a term usually used to describe a drug self-administration habit, but there is no single criterion that distinguishes habits that qualify as addictions from habits that do not. Thus, there are major differences of opinion as to which drugs are truly addictive. Moreover, there is no single “official” animal model of addiction. Rather, there are several animal models, each of which reflects some real or presumed aspect of the habit-forming properties of addictive drugs. Although the models differ fundamentally, both at the operational and at the theoretical levels, they each tend to identify the same major drugs, the same dose ranges, the same sites of action, and the same routes of administration as being associated with addiction liability (Wise, 1989). The most strongly addictive substances are effective in each of the several models. Because each model seems, on the surface at least, to reflect a different aspect of the habit-forming actions of addictive drugs, the most balanced picture of the abuse liability of a given drug comes from an integrated consideration of the drug’s actions across the full range of models. THEORETICAL PARADIGMS OF HABIT AND CONDITIONING The critical property of addictive drugs is that they are habit forming. Habit has long been studied as one of the central topics of experimental psychology. Three legendary figures have established two broad paradigms for the study of habit formation and habit maintenance. The central process in theories of habit formation is the process of reinforcement. The first to identify the process that would later be given this name was Thorndike, who discussed habit formation as involving the “stamping in” of associations between responses and environmental stimuli. In his formulation of the “law

of effect,” Thorndike held that those actions (responses) regularly followed by a satisfying state of affairs would have their association with a given situation (stimulus) strengthened. Thorndike and Skinner eventually came to use Pavlov’s term reinforcement to refer to the increase in response probability that accompanies the responsecontingent presentation of a reward or “reinforcer.” Drug rewards, like food rewards, serve as a reinforcer in the Thorndikean or Skinnerian sense; each, when presented in a response-contingent manner, increases the probability of the response habits that precede its delivery. This form of reinforcement, termed instrumental or operant reinforcement, is thought to be a core attribute of habit-forming drugs; indeed, instrumental reinforcement is seen by many as the primary, but not the only, contribution to the habits formed by drugs. The instrumental (or operant) paradigm is focused on the behavior of an animal just prior to the presentation of the reinforcer. The reinforcer is presented if and only if the animal meets some arbitrary response criterion, such as pressing a certain lever with a certain force or running down a certain arm of a runway. The experimenter waits patiently for the animal to make the required response and, when the response is made, presents the reinforcing “stimulus.” The dependent variable is the rate or probability of responding, which increases as a habit is established or “learned.” This paradigm has the most obvious face validity; it most clearly represents the acquisition of a drug-seeking habit in laboratory animals. However, it was Pavlov who first used the term and articulated the concept of reinforcement; Pavlov used it to refer to the stamping in of associations between unconditioned and conditioned stimuli rather than between stimuli and responses. Habit-forming drugs are reinforcers in Pavlov’s as well as Skinner’s sense; they establish learned preferences for various stimuli that are associated with their presentation. In the Pavlovian paradigm, the reinforcer is given independent of the animal’s behavior. The reinforcer is the unconditioned stimulus in the Pavlovian paradigm, and it is given in association with an initially neutral stimulus that comes to have significance to the animal only because of its learned association with the reinforcer. 757

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The initially neutral stimulus comes to have significance as a “conditioned stimulus” or “conditioned reinforcer” as the association between it and the drug state develops. Skinner acknowledged Pavlov’s form of reinforcement as respondent reinforcement and distinguished it from the instrumental (operant) reinforcement that was his and Thorndike’s main interest. Skinner was the first to assert that Pavlovian and instrumental reinforcement reflected fundamentally different principles and properties. Laboratory Models The drug self-administration paradigm offers the most obvious animal model of addiction. Laboratory animals will self-administer several classes of addictive drugs by the oral, intragastric, intraperitoneal, intravenous, or even intracranial routes and will do so, in some cases, to the point of physiological dependence. Oral self-administration of ethanol and intravenous selfadministration of heroin represent obvious analogues of human drug seeking, though physical dependence is readily demonstrated in the latter but not so readily demonstrated in the former case. In the strongest version of the model, the animal is required to work for access to the drug and not merely to ingest it. This is an instrumental conditioning paradigm, reflecting response learning, inasmuch as the drug is given in a responsecontingent manner. Because the animal gets the drug if and only if it makes some arbitrary response, the injection is more reliably associated with the internal feedback from action than with any of the external stimuli that are present. In the case where the animal leverpresses for presentation of the drug, the lever-pressing is termed the instrumental response and the ingesting of the drug is termed the consummatory response. The term consummatory reflects the fact that the ingestive response consummates the instrumental sequence; it applies to the terminal acts in all instrumental sequences, not just to ingestion (consider, for example, the consummation of marriage). In the case where the animal lever-presses for injection of the drug, the lever-press qualifies as an instrumental and a consummatory act. Although the drug self-administration model is most often used with fixed-ratio reinforcement contingencies, an interesting variant is one in which progressive-ratio reinforcement is used (Richardson and Roberts, 1996). In progressive-ratio drug self-administration, a progressively increasing workload is imposed upon the animal to receive a drug injection. For example, the workload may increase in a steeply incremental fashion: one lever press required for the first injection, two for the second injection, four for the third, eight for the fourth, and so on. Although typically the workload is not incremented so steeply, in every progressive-ratio drug self-

administration session, a point is reached at which the animal’s responding falls below some criterion level (often, an abrupt cessation of responding)—the progressiveratio “break-point.” This break-point is taken as a measure of reinforcing efficacy. Although originally developed to measure the “reward strength” of sweetened milk solutions (Hodos, 1961), progressive-ratio reinforcement schedules have since been widely used to measure the rewarding efficacy of a wide variety of addictive drugs in several animal species. Rather different estimates of drug-induced reward efficacy are obtained when progressive-ratio break-point is used in different manners—for example, incremental increases in response cost immediately following reinforcement versus incremental increases in response cost at the beginning of a discrete trial or daily test session. Psychostimulants respond preferentially to the former, opiates to the latter— evidence surely that the progressive-ratio reinforcement paradigm cannot be uniformly implemented across drug groups, and evidence perhaps that the motivation to self-administer psychostimulants versus opiates is qualitatively different (Arnold and Roberts, 1997). When implemented astutely, progressive-ratio break-point estimates of the rewarding efficacy of different classes of addictive drugs in animals parallel quite closely the verbal rank orderings of appetitiveness for different classes of addictive drugs given by experienced poly-drug abusing humans (Gardner, 2000). The conditioned place preference paradigm reflects the ability of neutral stimuli to take on conditioned importance for the animal because of their repeated presence in the environment where intoxication is experienced. In the conditioned place preference model, the animals are given drug injections and then confined to one part of the testing apparatus on some days, whereas they are given vehicle injections then confined to another part of the testing apparatus on other days. On test days, the animals are given free choice between the two regions of the test apparatus, and the time spent in each region is measured. Drug reinforcement is reflected in an increase in the time spent in the drugassociated portion of the environment. The conditioned place preference paradigm is a Pavlovian paradigm, reflecting stimulus learning, because the drug is given in a response-independent manner, such that no particular act of the animal is consistently associated with the injection. Rather, it is a particular set of environmental stimuli that becomes associated with drug intoxication. Several models utilize hybrid paradigms, involving instrumental and Pavlovian conditioning. The conditioned reinforcement paradigm involves animals responding instrumentally for a stimulus that has reinforcing value because of its Pavlovian association with drug reward. In the most frequently reported version of this paradigm,

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the animal is trained to self-administer intravenous drugs with a light flash associated with each injection. The animals are then tested in extinction conditions, where the drug reinforcer is no longer available. Here, animals given response-contingent presentations of the light stimulus will respond longer in the absence of any drug reinforcement than will animals in the absence of the light stimulus. A more convincing demonstration of conditioned reinforcement involves animals that passively receive random (response-independent) drug injections that are associated with a light stimulus. In this case, conditioned reinforcement can be demonstrated by the learning of a new instrumental response that is reinforced by the light alone. This is a hybrid paradigm because the conditioned reinforcer is established through Pavlovian conditioning but is demonstrated through instrumental responding. An example of the conditioned reinforcement paradigm is the so-called second-order drug self-administration reinforcement schedule (Everitt and Robbins, 2000). Originally used to study the reinforcing properties of natural rewards, second-order reinforcement schedules were developed into useful tools for studying druginduced reward in the early 1970s (e.g., Goldberg, 1973). Under a second-order reinforcement schedule, a lengthy response sequence is maintained by intermittent reinforcement by a conditioned stimulus (for example, a light flash) that has acquired reinforcing properties by virtue of previous pairing with a primary reinforcer (for example, drug). A typical second-order reinforcement schedule might, for example, require an animal to emit 50 responses to receive a light flash conditioned stimulus, with the drug primary reinforcer being given following the 10th response emitted after an hour of responding has elapsed. The obvious virtue of such reinforcement schedules is that responding for drug reinforcement can be maintained for prolonged periods prior to the actual delivery of the drug. Arguably, such responding can be termed drug-seeking behavior (Goldberg and Tang, 1977) rather than the “drugtaking” behavior measured by more common ratio or interval reinforcement schedules and is uncontaminated by cumulative drug effects. Under such secondorder schedules, responding for drug reward has been shown to be linearly related to dose: the higher the dose, the greater the number of responses (Goldberg and Tang, 1977). This is quite different from the inverted U-shaped dose-response curve generated by more common reinforcement schedules, where higher doses satiate reward substrates in the brain or recruit responseinhibiting (for example, motoric) artifacts. Of clear value to studies of addictive processes, secondorder schedules have been used to dissociate neural mechanisms subserving drug-cue-controlled drug seeking from those subserving drug reward itself. Thus, lesions of the

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basolateral amygdala prevent the learning of cocaine self-administration under second-order reinforcement but not the learning of cocaine self-administration under continuous reinforcement (Whitelaw et al., 1996), suggesting that the basolateral amygdala is not involved in cocaine’s primary rewarding effects but is critically involved in the neural processes by which cocaineassociated environmental cues drive drug-seeking behavior. Compellingly, identical conclusions about the involvement of the basolateral amygdala in cocaine-seeking behavior versus cocaine-induced primary reward were reached (Grimm and See, 2000) using the reinstatement paradigm (see below). Also seemingly clear is the value of the second-order reinforcement paradigm for studying drugs with putative therapeutic utility against cue-evoked drug-seeking behavior. Thus, BP897—an experimental drug with dopamine (DA) D3 receptor antagonist properties (Wood et al., 2000; Wicke and Garcia-Ladona, 2001)—selectively reduces cocaine-seeking behavior as measured by second-order reinforcement but does not modify cocaine self-administration under continuous reinforcement (Pilla et al., 1999). The cue-induced reinstatement paradigm is a second hybrid paradigm. In this paradigm, the animal is trained to self-administer a drug, usually intravenously, and is then subjected to extinction—that is, it is tested under conditions of nonreinforcement until the response habit appears to be “extinguished” (also a term first coined by Pavlov, who used it to describe the loss of a conditioned response when elicited repeatedly by the conditioned stimulus alone, without the “reinforcement” of the unconditioned stimulus). When the animal reaches some criterion of unresponsiveness to the instrumental manipulandum (usually the lever), various stimuli are presented and the behavior of the animal is noted. A stimulus is said to “reinstate” the drug-seeking habit if it causes renewed responding despite the absence of any further response-contingent drug reward. When the stimulus is a drug-associated conditioned stimulus, this is a hybrid paradigm because the animal is trained in the instrumental manner, with response-contingent reinforcement, but is tested in the Pavlovian manner, with potential priming stimuli presented independent of the animal’s behavior. In this paradigm, effective stimuli for reinstatement of seemingly extinguished drug-seeking habits are the stimuli associated with unearned injections of the drug. Such injections are termed priming injections because, like the priming of a pump, they reestablish the normal, but temporarily absent, response. Also effective at reinstating seemingly extinguished drugseeking habits in this paradigm are stress and environmental cues previously associated with the drug-taking habit (Shalev et al., 2002). Many significant contributions to understanding the neuroanatomical substrates of relapse to drug-seeking

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behavior have recently been achieved using the reinstatement paradigm. The nucleus accumbens and the neurotransmitter DA appear to be essential substrates for drug-triggered relapse in the reinstatement paradigm (Grimm and See, 2000; Shalev et al., 2002). The basolateral amygdala and the neurotransmitter glutamate appear to be essential substrates for cue-triggered relapse in the reinstatement paradigm (Grimm and See, 2000; Hayes et al., 2003). The central nucleus of the amygdala, bed nucleus of the stria terminalis, the lateral tegmental noradrenergic projection system, and the corticotrophin-releasing factor (CRF) projection pathways from the central nucleus of the amygdala to the bed nucleus of the stria terminalis and from an unknown origin to the ventral tegmental area appear to be substrates for stress-triggered relapse in the reinstatement paradigm (Shalev et al., 2002; Wang et al., 2005). The brain stimulation reward paradigm can also be used to assess the reward-relevant properties of drugs of abuse; it is also, in this context, a hybrid paradigm. Most drugs of abuse have not only rewarding actions of their own but also tend to potentiate or summate with the rewarding actions of other substances or events. Cannabis is said to enhance the enjoyment of music and sex, and cannabis and alcohol are said to enhance the taste of food. Alcohol and caffeine are said to enhance the enjoyment of nicotine. The brain stimulation reward paradigm models the enhancement of a nondrug reward by a drug reward. In this paradigm, the animals are trained to respond for electrical stimulation of certain brain regions. If response-contingent stimulation is given at a variety of frequencies or intensities, response rate can be assessed as a function of these “dose” parameters, and rate-frequency or rate-intensity functions—analogues of dose-response functions in pharmacology—can be determined. A variety of drugs of abuse cause leftward shifts in these functions, suggesting summation or synergism between the reward provided by the stimulation and some related action of the drug. Inasmuch as only drugs, doses, and central sites of administration known to be rewarding in their own right cause such leftward shifts, it is assumed that it is the rewarding properties of the drugs that summate with the rewarding property of the stimulation (Wise, 1996). The brain stimulation reward paradigm is particularly useful because the effectiveness of various doses of various drugs can be compared on a logarithmic scale that offers a yardstick of the reward-relevant efficacy of the drugs and doses. It is a hybrid paradigm because the animals respond instrumentally for the brain stimulation but receive the drug in a response-independent manner. The brain stimulation reward paradigm has characteristics that differ from drug-induced reward

paradigms. For example, the pattern of responding produced by brain stimulation reward differs from the pattern of responding produced by drug reward. Similarly, extinction patterns differ markedly between the two paradigms. Also, pharmacological antagonism of reinforcement produces an initial compensatory increase in responding for drug reward but an almost immediate decrease in responding for electrical brain stimulation reward. To test the hypothesis that these differences between paradigms reflect differences in the kinetics of drug reward and electrical brain stimulation reward, Lepore and Franklin (1992) developed an interesting variant of the brain stimulation reward paradigm, using frequency-modulated trains of electrical brain stimulation that they labeled “self-administration of self-stimulation.” Using this variant of the brain stimulation reward paradigm, they showed that when the kinetics of rewarding electrical brain stimulation are adjusted to emulate the kinetics of rewarding drugs, differences between brain stimulation reward and drug-induced reward essentially disappear (Lepore and Franklin, 1992). THEORETICAL MODELS OF ADDICTION There are, broadly speaking, two theoretical models of addiction; they are, more generally speaking, two models of motivation. The two models are polar opposites: one involves the striving for pleasure, euphoria, or some other supra-normal condition, whereas the other involves the striving to alleviate pain or discomfort or to satisfy a homeostatic need. The terms describing the motivational extremes are familiar: pleasure versus pain, reward versus punishment, the stick versus the carrot, drive versus incentive. In the first model, termed the positive reinforcement model, the animal is seen as striving for a treat—something special that elevates the animal’s mood above the ordinary. In the subjective terms that accompany addiction theory, the drug is seen in this view as being habit forming because it produces euphoria. In the second model, termed the negative reinforcement model, the drug is seen as reinforcing because it terminates an aversive state, relieving the pain of injury, illness, social isolation, poverty, depression, or relieving its own withdrawal distress, and returning the animal’s mood to normal. The strength of the positive reinforcement model is that it needs no outside agent to account for the acquisition of a drug habit. The drug is viewed as a treat, something that satisfies no need of the individual but rather, like sexual gratification, is simply a source of enjoyment. If a drug serves as a positive reinforcer, that fact alone is sufficient to explain response acquisition. Indeed, response acquisition is the phenomenon that

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positive (instrumental) reinforcement was intended to explain. Positive reinforcement is sufficient, theoretically, to explain why an animal learns a drug-seeking habit and also why an animal maintains such a habit once it is acquired. It also is sufficient to explain why drug habits are quickly reacquired when detoxified patients are returned to situations where they have learned how to earn drugs. The weakness of the positive reinforcement model, if it has a weakness, is that it does not seem, on the surface at least, to explain why drug-seeking habits that once seemed marginal become, eventually, compulsive. The positive reinforcement theorist would answer that this is a potential characteristic of all habits involving strong reinforcement, and that even such seemingly trivial habits as not stepping on cracks can become compulsive with sufficient repetition. The negative reinforcement model suggests that some abnormal negative state must be present before drugseeking habits become compulsive: that the compulsivity of drug seeking in addiction results from the increasing need for the drug just to feel normal. The pure version of this model holds that it is the physiological adaptation to the drug itself that produces the need, that the need is an acquired need analogous, except for the fact that it is acquired, to the need for food. From the perspective of the negative reinforcement model, drug taking is seen as a case of self-medication: self-medication of withdrawal distress in the simple version, or, alternatively, self-medication of some preexisting problem such as illness, estrangement, grief, depression, or poverty. The weakness of the negative reinforcement model is that, unless some preexisting problem like depression, disability, or situational stress is invoked, the model requires an external explanation of how the drug-seeking habit is established. If the relief of withdrawal distress were the only explanation of drug reinforcement, then animals would never take drugs to the point of physiological dependence. A second weakness of the negative reinforcement model is that it offers little explanation of the reinstatement of drug-seeking habits when withdrawal symptoms have abated and preexisting problems have been alleviated. Substrates of Positive Reinforcement Portions of the neural substrates of positive reinforcement have been tentatively identified from converging evidence involving each of these models of addiction and also involving natural rewards such as food and water and the laboratory reward of direct electrical brain stimulation. The most clearly identified elements of brain reward circuitry are the mesolimbic DA system and its primary target neurons, the medium spiny neurons of nucleus accumbens and olfactory tubercle. The first ev-

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idence to implicate monoamine systems in reward function came from studies of the pharmacological modulation of brain stimulation reward: the catecholamine agonist amphetamine increased lever pressing for brain stimulation reward, whereas the catecholamine antagonist chlorpromazine and the catecholamine depleter reserpine each decreased it (Stein, 1962). Subsequent studies with more selective drugs implicated DA rather than the initial suspect, noradrenaline, as the critical transmitter. Selective DA blockers blocked the rewarding effects of hypothalamic brain stimulation while selective noradrenergic blockers did not (Wise, 1989). Selective DA antagonists also proved to block the rewarding effects of intravenous amphetamine (Yokel and Wise, 1975) and cocaine (de Wit and Wise, 1977) as well as the rewarding effects of food and water (Wise, 1982). Subsequent work with cocaine and other catecholamine uptake inhibitors confirms that it is the affinity for the DA transporter rather than the noradrenaline or serotonin transporter that predicts the rewarding effectiveness of these drugs in normal animals (Ritz et al., 1987). That it is the mesolimbic and not the nigro-striatal or the mesocortical branch of the DA system that plays the most important role is suggested by several findings. First, DA-selective lesions of nucleus accumbens, the principal target of the mesolimbic system, block or attenuate the rewarding effects of cocaine and amphetamine. Second, the selective DA antagonist spiroperidol blocks intravenous cocaine reinforcement when injected locally in the nucleus accumbens. Although the neurotoxin-induced lesions of nucleus accumbens may have disrupted the mesocortical as well as the mesolimbic DA system, nucleus accumbens injections of spiroperidol would not. Moreover, direct injections of amphetamine into nucleus accumbens are rewarding as reflected in intracranial self-administration, in conditioned place preference, and in the ability of amphetamine to potentiate hypothalamic brain stimulation reward (for a review, see Wise, 1989). Although the nucleus accumbens has figured strongly in the drug abuse literature, it is not the only rewardrelevant DA terminal field. Cocaine is readily selfadministered into the medial prefrontal cortex (Goeders and Smith, 1983), the major projection of the mesocortical DA system, and is not readily self-administered into the core of nucleus accumbens (Goeders and Smith, 1983; Carlezon et al., 1995). On the other hand, it is self-administered into the shell of nucleus accumbens (Carlezon et al., 1995) and is even more readily selfadministered into the medial olfactory tubercle, an even more ventral portion of the ventral striatum (Ikemoto and Wise, 2004). Thus, it is clear that more than one DA terminal field can serve as a trigger zone for the rewarding effects of addictive drugs.

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When rats are allowed to control their own intake of fixed doses of intravenous amphetamine or cocaine by lever pressing, they learn to adjust their response rate to defend their hourly amphetamine or cocaine intake (Pickens and Thompson, 1971). If the dose per injection is varied within sessions, the latency to the next response is proportional to the size of the previous dose, and if supplemental drug is slowly infused, the animals adjust their response rate in such a way as to compensate accurately (Gerber and Wise, 1989). In the case of d-amphetamine, the animals respond for more drug whenever their blood levels fall to 0.2 μg/ml (Yokel and Pickens, 1974). It seems unlikely that the animals are regulating these drugs independently; rather, it seems likely that they are regulating some common consequence of cocaine and amphetamine in the blood, such as nucleus accumbens DA levels. Indeed, nucleus accumbens DA levels are elevated during intravenous cocaine self-administration, and nucleus accumbens DA levels—which, of course, are correlated with intravenous cocaine levels—appear to be regulated as well (Wise et al., 1995). Opiates also activate the mesolimbic DA system, and, again, each of the animal models points to habit-forming actions involving the activation of the mesolimbic system—opiates disinhibit the DA neurons—or direct inhibition of the medium spiny neurons of nucleus accumbens (which are similarly inhibited by DA). Rewarding opiate actions in the ventral tegmental area have been demonstrated by intracranial morphine and mu and delta opioid self-administration, by conditioned place preference, and by potentiation of brain stimulation reward; ventral tegmental injections of mu and delta opioids also potentiate feeding (see Wise and Bozarth, 1987). The mu opioid (D-Ala2, N-Me-Phe4Gly5-ol)-enkephalin (DAMGO) is 100 times more potent as a reinforcer than is the delta opioid (D-Pen2, DPen5)-enkephalin (DPDPE) (Devine and Wise, 1994); similarly, DAMGO is 100 times more potent in potentiating brain stimulation reward, feeding, and, as measured by nucleus accumbens microdialysis, DA release (Devine et al., 1993). Moreover, ventral tegmental injections of opioid antagonists attenuate the rewarding efficacy of intravenous heroin (Bozarth and Wise, 1986). The habit-forming actions of ventral tegmental opiates appear to involve the disinhibition of dopaminergic cell firing; mu opioids act to inhibit g -aminobutyric acid (GABA)ergic neurons that normally provide tonic inhibition of their dopaminergic neighbors (Johnson and North, 1992). Opiates also have habit-forming effects in nuclus accumbens itself. Morphine is self-administered directly into this nucleus (Olds, 1982), and morphine injections into this nucleus cause conditioned place preference (van

der Kooy et al., 1982). Mu and delta opioids injected into this nucleus also potentiate the rewarding effects of lateral hypothalamic brain stimulation, and opioid antagonists injected into this nucleus can attenuate the rewarding effects of intravenous heroin (Vaccarino et al., 1985). The rewarding actions of opiates in nucleus accumbens appear to be due to the direct inhibition of medium spiny neurons; mu and delta opiates infused into nucleus accumbens itself do not alter local DA levels, whereas kappa agonists decrease local DA levels (Spanagel et al., 1990). It is not clear whether it is the ventral tegmental area or the nucleus accumbens that plays the more dominant role in the rewarding effects of intravenous heroin, but it is clear that self-administered intravenous heroin is sufficient to elevate nucleus accumbens DA (Devine et al., 1993). As with the case of intravenous cocaine selfadministration (Wise et al., 1995), intravenous heroin self-administration is initiated when DA levels fall to some critical “trigger point” that is well above normal resting DA levels. Nucleus accumbens medium spiny neurons also seem important for the habit-forming effects of phencyclidine. Phencyclidine is self-administered directly into nucleus accumbens (Carlezon and Wise, 1996a), where it also facilitates the rewarding effects of lateral hypothalamic brain stimulation (Carlezon and Wise, 1996b). Despite the fact that phencyclidine is, like cocaine and nomifensine, a DA uptake inhibitor, the rewarding effects of nucleus accumbens injections of phencyclidine are, unlike the rewarding effects of nucleus accumbens nomifensine, unaffected by coadministration of the DA antagonist sulpiride (Carlezon and Wise, 1996a). Moreover, the habit-forming effects of phencyclidine are shared by dizocilpine and (±)-3-2-carboxypiperazin-4yl propyl-1-phosphonic acid (CPP), drugs that block N-methyl-D-aspartate (NMDA) receptors, as does phencyclidine, but that do not share with phencyclidine the ability to block DA uptake. Thus, the habit-forming effects of phencyclidine appear to be DA independent and depend instead on the blockade of NMDA-type glutamate receptors. Nucleus accumbens medium spiny neurons receive glutamatergic input from a variety of sites, and glutamate normally excites medium spiny neurons. Thus, NMDA antagonists have the same net effect on the output of nucleus accumbens output neurons as do elevated DA levels; whereas DA decreases nucleus accumbens output by inhibiting medium spiny neuron firing, NMDA antagonists appear to do so by blocking tonic excitatory input to the medium spiny neurons. The mesolimbic DA system is also activated by nicotine and ethanol; although the mechanism of ethanol’s action is not known, nicotine receptors are known to

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be localized to mesolimbic DA neurons (Clarke and Pert, 1985). Ventral tegmental injections of a nicotinic agonist cause conditioned place preferences (Museo and Wise, 1994). Blockade of ventral tegmental nicotinic receptors does not itself alter brain stimulation reward, but it blocks the ability of nicotine to do so (Wise et al., 1998). Cannabis, too, enhances brain stimulation reward (Gardner et al., 1988) and elevates nucleus accumbens DA (Chen et al., 1990), and may be habit forming for this reason. Conditioned place preference for cannabinoid-paired environments has been reported (Lepore et al., 1995; Valjent and Maldonado, 2000; Braida et al., 2001), although contrary findings exist (for a review, see Gardner, 2002). Cannabinoid selfadministration in laboratory animals has also recently been reported (Martellotta et al., 1998; Ledent et al., 1999; Tanda et al., 2000; Justinova et al., 2003; for a review, see Justinova, Goldberg, et al., 2005), as has self-administration of the endogenous cannabinoid anandamide (Justinova, Solinas, et al., 2005). There has been considerable recent attention to the fact that subregions of the ventral striatum have different afferent and efferent connections. The core of nucleus accumbens is similar in this regard to the overlying caudate, whereas the shell of the nucleus accumbens and the olfactory tubercle have similarities to the central amygdala and have been identified as part of the “extended” amygdala. Intracranial self-administration of phencyclidine, dizocilpine, CPP, and nomifensine occurs preferentially with shell and not core injections of the drugs (Carlezon et al., 1995; Carlezon and Wise, 1996a), and intracranial self-administration of cocaine occurs preferentially with olfactory tubercle and, to a lesser extent, shell injections (Ikemoto, 2003). The medial prefrontal cortex also appears to play a role in drug reward. In addition to cocaine (Goeders and Smith, 1983), phencyclidine, dizocilpine, and CPP are self-administered into this region (Carlezon and Wise, 1996a). The mechanism of action has not yet been identified. Substrates of Physical Dependence It has long been assumed that the compulsive drug selfadministration accompanying true addiction results from adaptations in the nervous system resulting from chronic drug exposure. These adaptations are evident during intoxication only insomuch as they reduce the effectiveness of the drug that produces them; they are drugopposite adaptations and thus the theories of addiction in which such adaptations figure prominently are termed opponent-process theories. This phrase was coined by Solomon and Corbit (1974), but it applies to all of the classic theories of drug dependence.

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The most dramatic dependence signs accompany withdrawal from predominantly depressant drugs like opiates, alcohol, barbiturates, and benzodiazepines. The drug-opposite withdrawal symptoms in these cases are signs of hyperexcitability; animals withdrawn from these drugs are agitated and hyperactive, and they are abnormally susceptible to epileptic seizures. Although this hyperexcitable state is not pleasant and can be alleviated by self-administration of the responsible drug, it seems unlikely that the distress of these signs is a powerful source of the motivation to compulsively self-administer drug. Indeed, the experimental manipulations that maximize the classic alcohol withdrawal syndrome are manipulations that minimize voluntary alcohol consumption in laboratory animals, and the manipulations that maximize voluntary consumption are incompatible with physiological dependence (Wise, 1974). Moreover, the brain sites (and, indeed, peripheral autonomic sites) at which opiates induce the neuroadaptations associated with classic withdrawal signs are anatomically distant from the sites at which opiates trigger their habitforming consequences (Bozarth and Wise, 1984). Finally, the psychomotor activation associated with opiate, alcohol, barbiturate, and benzodiazepine withdrawal result from neuroadaptations opposite in fundamental nature to the psychomotor depression associated with cocaine and amphetamine withdrawal. Thus, the classic autonomic and central signs of withdrawal from depressant drugs do not offer a unifying hypothesis of addiction (Wise and Bozarth, 1987). Dependence theory does not necessarily rest, however, on classic withdrawal symptoms. Any one of the multiple neuroadaptations resulting from chronic drug use could serve as a predisposing factor in the compulsive drug craving of addicts. Recent interest has focused on drug-opposite changes in the brain pathways that mediate the rewarding effects of drugs of abuse. Even depressant drugs such as opiates, alcohol, barbiturates, and benzodiazepines have psychomotor stimulant properties that are associated with drug reward (Wise and Bozarth, 1987). Rebound depression of the reward pathways appears to reflect neuroadaptations to chronic intoxication of much greater relevance to drug self-administration than are the traditional withdrawal symptoms of classic addiction theory (Koob and Bloom, 1988). The notion that the reward systems of the brain undergo rebound depression after treatment with addictive drugs was first articulated by Leith and Barrett (1976), who found that brain stimulation reward thresholds were elevated following chronic dosing with amphetamine. Similarly, brain stimulation reward thresholds are elevated following withdrawal from chronic cocaine treatment, and such elevations can be demonstrated after

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self-administered doses of cocaine (Markou and Koob, 1991). Moreover, similar elevations can be demonstrated during spontaneous or precipitated opiate withdrawal states. Thus, depression of brain reward mechanisms offers a possible common denominator bridging the withdrawal symptoms associated with the opiates and the less dramatic signs of dependence associated with the psychomotor stimulants. A number of neurochemical correlates of stimulant and opiate withdrawal have been identified. Among the first to be suggested was DA depletion. Although it was depletion of intracellular DA that was first posited by Dackis and Gold (1985) as a correlate of withdrawal from chronic cocaine treatment, it is depletion of extracellular DA that has been reported following withdrawal of chronic cocaine, amphetamine, morphine, and alcohol. In addition, a number of intracellular changes have been identified in the mesolimbic DA system and in the medium spiny neurons of nucleus accumbens during withdrawal from cocaine, opiates, and alcohol (Self and Nestler, 1995). These changes are associated with alterations of intracellular signaling functions and go beyond the up- or down-regulation of receptors once hypothesized as the basis for changes in drug sensitivity during the development of tolerance and dependence and are more consistent with hypotheses involving enzyme and second-messenger alterations (Goldstein and Goldstein, 1961; Collier, 1980). In each case, the anatomical locus of the changes under current investigation is the diencephalic reward circuitry associated with the rewarding effects of the drugs. Contributions to Knowledge from Animal Models The study of animal models of addiction has contributed a number of insights into the nature of the human condition. First, it reveals that all mammalian species are probably susceptible to the habit-forming effects of opiates and psychomotor stimulants. Thus, it suggests that recreational use of these agents offers a significant risk for most if not all individuals. Given in strong doses and by rapid routes of administration, these drugs have robust actions on biologically primitive circuitry in the brain, and their self-administration is likely to lead to compulsive drug-seeking habits. The animal literature makes it clear that craving is a conditioned response because the drug solution has no distal sensory properties that are evident to the animal (it is usually neither visible nor detectable by smell). Thus, the significance of the place in the environment where the drug is experienced and of the manipulandum that allows the animal to earn injections or drug presentations must be learned by association with the drug state and not with the external stimulus properties of the drug.

The instrumental response (for example, lever pressing) that delivers the drug must be learned, and it can be reinstated by the stimulus properties of the drug itself or by stimuli that have been paired with the drug as well as by some forms of stress (Shaham and Stewart, 1995). Animal self-administration studies have made it clear that physiological dependence is not a necessary condition for compulsive drug-seeking behavior, even in the case of drugs like opiates that are associated with a clear and robust dependence syndrome (Bozarth and Wise, 1984). Animal studies have shown, however, that drug-opposite neuroadaptations occur— within the reward pathways themselves—as a result of self-administered doses of addictive drugs. The effects of each of these neuroadaptations on the rewarding impact of the drugs that produce them remain to be fully identified. Animal studies also reveal that there are individual differences in the likelihood of initiation of drug self-administration, and they suggest that deprivation states and environmental choices can influence the amount of drug self-administration. Such studies underscore the obvious fact that these differences and influences are most evident when marginal doses (for example, ED50) and routes of administration (for example, oral) are offered. Use of Animal Models in the Search for Effective Treatments for Addiction As useful as animal models have been and continue to be in elucidating the neurobiological substrates of addiction, they have also in recent years been put to a more classically pragmatic and practical use in medicine—as screening tools in the search for effective treatments for drug addiction. We illustrate this utility by citing the recent and continuing use of animal models in the identification and development of possible pharmacotherapies for addiction based on three different pharmacotherapeutic strategies. The development of slow-onset long-acting DA transporter blockers is one such strategy. It is based on the hypothesis that vulnerability to addictive drugs may derive, at least in part, from a pathological hypofunctionality of DA neurons in the reward-related meso-accumbens dopaminergic projection system (for reviews, see Gardner, 1999, and Volkow, Fowler, and Wang, 1999; see also Nestler, 1993; Volkow, Wang, et al. 1999; Volkow et al., 2001). On the basis of this hypothesis, a number of approaches have been taken to the discovery and development of selective and potent DA transporter blockers that may serve as developmental templates for anticocaine-addiction pharmacotherapeutic agents (Rothman and Glowa, 1995). A

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wide variety of structural classes have served as such chemical templates for the development of potential therapeutic agents for cocaine addiction, including cocaine analogues (Carroll et al., 1992), tropanes (Madras et al., 1989), benzotropines (Meltzer et al., 1994; Newman et al., 1994), mazindol (Aeberli et al., 1975; Berger et al., 1989), substituted piperazines (Andersen, 1987; Berger et al., 1985; Bonnet et al., 1986; Hsin et al., 2002), indanamines (Froimowitz et al., 2000), and trans-aminotetralines (Welch et al., 1984; Froimowitz et al., 2000). The rapidity with which an addictive drug reaches the brain and elevates nucleus accumbens DA levels appears to correlate positively with addictive potency (Oldendorf, 1992; Volkow et al., 1995). Conversely, slow onset or prolonged duration appears to confer lower reinforcing efficacy. Thus, the cocaine analogue 2b -propanoyl-3b -(4-tolyl)-tropane (PTT), a selective DA reuptake blocker with a slower onset and much longer duration of action than cocaine, does not support intravenous self-administration under fixed-interval reinforcement in rhesus monkeys (Nader et al., 1997). Congruently, the phenyltropane analog 3b -(4-chlorophenyl)tropane-2b -carboxylic acid phenyl ester (RTI113), which has a cocaine-like rapid onset but a much longer duration of action, supports much lower intravenous self-administration in monkeys than does cocaine, despite markedly higher DA receptor occupancy by RTI-113 (99%) than by cocaine (65%) (Howell et al., 2000). In addition, several benzotropine analogues with slower pharmacokinetic properties than cocaine maintain only low rates of intravenous self-administration in rhesus monkeys even though the compounds have substantially higher affinities than cocaine at the DA transporter (Woolverton et al., 2000). Therefore, a major emphasis in the slow-onset long-acting DA transporter blocker medication discovery and development strategy has been on the development of compounds producing slow enhancement of nucleus accumbens DA, having long duration, and showing a slow deactivation profile. Animal models have proven useful in the preclinical screening and development of such compounds. Thus, PTT decreases intravenous cocaine self-administration in rhesus monkeys on a fixed-interval cocaine reinforcement schedule, assessed in terms of decreased response rates and decreased total cocaine intake per test session (Nader et al., 1997). Congruently, 1-[2-[bis(4-fluorophenyl-)methoxy]ethyl]-4-(3-phenylpropyl)piperazine (GBR-12909) dose-dependently decreases cocaine selfadministration in rhesus monkeys under multiple fixedratio schedules of cocaine and food reinforcement (Glowa, Wojnicki, Matecka, Bacher, et al., 1995), with significant reductions in cocaine self-administration obtained

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at GBR-12909 doses that had little or no effect on food self-administration (Villemange et al., 1999; Schenk, 2002). However, GBR-12909’s selectivity for reducing cocaine self-administration versus food self-administration was seen only at low unit doses of cocaine (Glowa, Wojnicki, Matecka, Bacher, et al., 1995). On the other hand, repeated treatment with lower GBR12909 doses appears to sustain the selective suppression of cocaine self-administration versus food self-administration (Glowa, Wojnicki, Matecka, Rice, and Rothman, 1995). Taken with the report that GBR-12909 attenuates cocaine-induced meso-accumbens extracellular DA enhancement in rats (Baumann et al., 1994), the suggestion that development of long-acting GBR12909 analogues may yield useful compounds for treating cocaine addiction appears rational. This line of development has yielded several long-acting piperazine analogues (including decanoate ester depot formulations) that decrease cocaine self-administration in selective and sustained fashion in monkeys and augment extracellular nucleus accumbens DA in slowonset, sustained fashion in laboratory rats (Glowa et al., 1996; Lewis et al., 1999; Hsin et al., 2002; see review by Howell and Wilcox, 2001). Illustrating the use of second-order schedules to infer “drug-seeking” behavior in such medication development schemes, the long-acting phenyltropane analogue RTI-113 has been reported to decrease cocaine self-administration in squirrel monkeys under secondorder reinforcement (Howell et al., 2000). Indanamine analogues have also been developed as potential antiaddiction medications using some of the animal models discussed in this chapter (Froimowitz et al., 2000). Thus, several slow-onset, long-acting indanamine analogue DA transporter blockers have been shown to enhance nucleus accumbens in slow-onset long-duration fashion (Gardner et al., 2006), enhance electrical brainstimulation reward (Gardner et al., 2006), and decrease intravenous cocaine self-administration (Gardner et al., 2006) in laboratory rats, while being devoid of the ability to sustain self-administration themselves (Gardner et al., 2006). Provocatively, the protective effects of at least some of these indanamine analogues against intravenous cocaine self-administration may be most pronounced in genetic strains of rats most prone to high levels of cocaine self-administration (Froimowitz et al., 1999). Trans-aminotetraline derivatives have also been tested using animal models discussed in this chapter, with preliminarily promising results. Slow-onset long-duration enhancement of extracellular nucleus accumbens DA, electrical brain-stimulation reward, and dose-dependent reductions in cocaine self-administration have all been observed (Peng et al., 2005; Peng et al., 2006).

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The development of GABAmimetic compounds acting specifically at the GABAB receptor is another such strategy. It is based on the following facts: (1) GABAergic afferents heavily innervate and modulate neural tone within the ventral tegmental area (Kalivas et al., 1990; Klitenick et al., 1992; Kalivas et al., 1993; Sesack and Pickel, 1995) and nucleus accumbens (Christie et al., 1987; Kiyatkin and Rebec, 1999; Meredith, 1999; Yan, 1999; Ward et al., 2000); (2) the GABAergic medium spiny output neurons from the accumbens have been proposed to constitute a brain reward final common output path (Carlezon and Wise, 1996a); (3) pharmacological modulation of GABAergic tone can affect mesoaccumbens brain-reward functions (Nazzaro and Gardner, 1980); (4) microinjections of the GABAB receptor agonist baclofen into the ventral tegmental area block mu opiate-agonist-induced enhancement of DA release in nucleus accumbens (Kalivas et al., 1990), suggesting that activation of GABAB receptors on DA perikarya inhibits mesoaccumbens dopaminergic reward functions; and (5) acquisition and expression of a conditioned emotional response are accompanied by increased nucleus accumbens GABA levels, and hippocampal lesions attenuate both the enhanced accumbens GABA levels and the expression of the conditioned emotional response (Saul’skaya and Gorbachevskaya, 1999). On the basis of these kinds of data, several of the animal models discussed in this chapter have been used to investigate the possibility that GABAmimetic compounds (especially those targeted at the GABAB receptor) may have potential as antiaddiction pharmacotherapies. Some of this work has focused on the irreversible GABA transaminase inhibitor gamma-vinylGABA (GVG). Gamma-aminobutyric acid transaminase is the primary enzyme involved in the metabolic catabolism of GABA. Gamma-vinyl-GABA, by interfering with this process, significantly enhances brain GABA levels (Jung et al., 1977). As the enhanced GABA is stored within axon terminals and only released during synaptic transmission, GVG preferentially enhances physiologically relevant brain GABA levels (Mattson et al., 1995). GVG dose-dependently attenuates the enhanced nucleus accumbens DA overflow produced by cocaine (Dewey et al., 1997; Dewey et al., 1998; Morgan and Dewey, 1998), nicotine (Dewey et al., 1999; Schiffer et al., 2000), methamphetamine (Gerasimov et al., 1999), heroin (Gerasimov et al., 1999; Xi and Stein, 2000), ethanol (Gerasimov et al., 1999), or a cocaine/heroin (“speedball”) combination (Gerasimov and Dewey, 1999). The effects of GVG on cocaine-enhanced nucleus accumbens DA are mimicked by GVG’s cyclized analogue (a competitive reversible GABA transaminase inhibi-

tor) and by the GABA reuptake inhibitor NNC-711 (Gerasimov et al., 2000). Provocatively, GVG also antagonizes the augmented nucleus accumbens DA produced by environmental cues previously associated with cocaine administration (Gerasimov et al., 2001). When GVG is coadministered intravenously with heroin or microinjected into either the ventral tegmental area or nucleus accumbens, it dose-dependently reduces heroin’s reinforcing efficacy, as indicated by compensatory increases in unit heroin self-administration (Xi and Stein, 2000). At higher doses of GVG, a complete blockade of intravenous heroin (Knapp et al., 1999; Xi and Stein, 2000) or cocaine (Kushner et al., 1999) selfadministration is seen. Similar effects on heroin selfadministration are produced by the reversible GABA transaminase inhibitors aminooxy-acetic acid (AOAA) or ethanolamine-O-sulfate (EOS), and the GABA reuptake inhibitors (±)-nipecotic acid or NO-711 (Xi and Stein, 2000). Gamma-vinyl-GABA also lowers the progressive-ratio break point for intravenous cocaine self-administration (Kushner et al., 1999). Gamma-vinylGABA also attenuates cocaine’s enhancement of electrical brain-stimulation reward (Kushner et al., 1997). Gamma-vinyl-GABA’s inhibition of cocaine-induced DA elevations in the nucleus accumbens is antagonized by the selective GABAB antagonist SCH-50911 (Ashby et al., 1999), implicating the GABAB receptor in GVG’s potential antiaddiction effects. Recently, GVG has been shown to inhibit cocaine-triggered relapse to drug-seeking behavior using the reinstatement model (Peng et al., 2004; Peng et al., 2006; Peng et al., in press; Filip et al., 2007) but fails to inhibit cocaine’s discriminative stimulus effects (Barrett et al., 2005). Provocatively, local nucleus accumbens microinjections of GABAA or GABAB receptor agonists, but not GABA itself, inhibit extracellular nucleus accumbens DA and glutamate (Xi and Stein, 1998, 1999; Xi et al., 2003) and similarly inhibit cocaine or heroin self-administration and reinstatement of drug-seeking behavior (Xi and Stein, 1999; McFarland et al., 2003), raising questions about the neural substrates underlying GVG’s demonstrated actions in animal models. Nonetheless, GVG has moved forward to preliminary clinical trials in humans with promising results (Brodie, Figueroa, and Dewey, 2003; Brodie, Figueroa, Laska, and Dewey 2003), a step that would have been of very low probability without the preceding extensive preclinical investigations using animal models. Similar work has focused on the selective GABAB agonist baclofen. Baclofen produces a dose-dependent reduction in progressive ratio break points for intravenous cocaine self-administration (Roberts et al., 1996; Brebner et al., 2000). Baclofen’s protective effect against cocaine self-administration was also examined using a

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discrete trials procedure, which permits measurements of circadian patterns of self-administration (Roberts and Andrews, 1997). Regardless of the time of light onset, maximum cocaine intake occurred during the final 6 hours of the dark period and was followed by a period of relative abstinence from cocaine self-administration during the light phase. This highly predictable behavioral pattern of self-administration allowed observation of baclofen’s effect on initiation of cocaine selfadministration. Baclofen treatment suppressed cocaine self-administration for at least 4 hours without having any significant effect on operant responding for food self-administration (Roberts and Andrews, 1997). When cocaine was self-administered on a simple fixed ratio (FR1) reinforcement schedule, baclofen suppressed intake of low but not high unit doses of cocaine (Brebner et al., 2000). The baclofen-induced suppression of low-dose cocaine intake was characterized by long pauses in the cocaine self-administration pattern—in contrast to DA antagonist-induced suppression of cocaine self-administration, which is characterized by altered distribution of interinfusion intervals for cocaine. Recently, baclofen pretreatment has been shown to dose-dependently reduce cocaine-enhanced extracellular nucleus accumbens DA (Fada et al., 2003), cocaineenhanced electrical brain-stimulation reward (Slattery et al., 2005), cocaine-seeking behavior under secondorder reinforcement (Di Ciano and Everitt, 2003), and cocaine-triggered relapse to drug-seeking behavior in the reinstatement model (Campbell et al., 1999; Weerts et al., 2007). The novel and highly selective GABAB agonist CGP44532 shows a baclofen-like profile of protection against cocaine self-administration, that is, a dose-dependent decrease in progressive ratio break point for cocaine self-administration, a dose-dependent suppression of initiation of cocaine intake in the discrete trials procedure, and a failure to disrupt operant responding for food (Brebner et al., 1999). Baclofen also appears to protect against opiate self-administration (Xi and Stein, 1999). Baclofen coadministration with intravenous heroin inhibits development of heroin self-administration in drug-naïve rats, and maintenance of heroin selfadministration behavior in heroin-experienced rats. In addition, microinjections of baclofen into the ventral tegmental area reduce heroin-induced enhancement of extracellular DA in the nucleus accumbens (Xi and Stein, 1999). This effect was significantly attenuated by microinjections of the GABAB antagonist 2-hydroxysaclofen into the ventral tegmental area. On the basis of such findings with animal models, augmentation of brain GABAergic function—mediated through the GABAB receptor—may be a rational strategy to pursue at the human level for the pharmacotherapeutic treatment of drug

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addiction. Preliminary recent clinical trials of baclofen in human patients appear promising (Ling et al., 1998; Shoptaw et al., 2003; Haney et al., 2006; but see Lile et al., 2004). A third medication development strategy for possible addiction treatment that owes its existence to the animal models discussed in this chapter is that of DA D3 receptor antagonists. This strategy is based on the following: (1) the hypothesis that mesoaccumbens dopaminergic hypofunctionality may contribute to addiction vulnerability; (2) the fact that the DA D3 receptor shows preferential localization in the mesocorticolimbic system (Levant, 1998; Suzuki et al., 1998); (3) the suggestion that D3 receptor inhibition may activate the mesoaccumbens DA system (Nissbrandt et al., 1995; Ashby et al., 2000); and (4) the suggestion that the D3 receptor plays a role in emotional, motivational, and reinforcement functions, including the reinforcement produced by addictive drugs (Caine and Koob, 1993; Parsons et al., 1996; Pilla et al., 1999). These considerations have prompted the study of compounds acting on the DA D3 receptor system in animal models of addiction. Such studies were initially hampered by lack of D3-selective compounds, until the development of trans-N-[4-[2-(6-cyano-1,2,3,4-tetrahydroisoquinolin2-yl) ethyl]cyclohexyl]-4-quinolininecarboxamide (SB277011A), a novel brain-penetrant, highly selective D3 receptor antagonist (Reavill et al., 2000; Stemp et al., 2000). SB-277011A has high affinity for human and rat D3 receptors, with an 80- to 100-fold selectivity over DA D2 receptors and 180 other central nervous system receptors, enzymes, and ion channels (Reavill et al., 2000; Heidbreder et al., 2005; C.A. Heidbreder et al., 2007, unpublished data). Also, SB-277011A readily enters the brain after systemic administration in laboratory rodents (Reavill et al., 2000; Stemp et al., 2000). In preclinical animal tests with many of the addiction models described in this chapter, SB-277011A shows a highly promising profile (see review by Heidbreder et al., 2005). Specifically, SB-277011A attenuates cocaine- or methamphetamine-enhanced electrical brainstimulation reward (Vorel et al., 2002; Spiller et al., 2008); dose-dependently attenuates acquisition and expression of cocaine-induced conditioned place preference (Vorel et al., 2002); attenuates the acquisition and expression of heroin-induced conditioned place preference (Ashby et al., 2003); produces a pronounced down-shift in the break point (that is, reduces motivation) for intravenous cocaine or methamphetamine selfadministration under progressive-ratio reinforcement conditions (Xi et al., 2005; Higley et al., 2007); attenuates cocaine-seeking behavior under second-order reinforcement conditions (Everitt et al., 2001; Di Ciano et al.,

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2003); dose-dependently attenuates cocaine-triggered, stress-triggered, or environmental cue-triggered relapse to cocaine-seeking behavior in the reinstatement paradigm (Vorel et al., 2002; Cervo et al., 2003; Xi et al., 2004; Gilbert et al., 2005; Gál and Gyertyán, 2006); attenuates incubation of cocaine craving (Xi et al., 2007); attenuates nicotine-enhanced electrical brain-stimulation reward (Pak et al., 2006); attenuates nicotine-induced conditioned place preference (Pak et al., 2006); attenuates nicotine-paired environmental cue-induced locomotor activation (Pak et al., 2006); and attenuates ethanol self-administration in laboratory rats (Thanos et al., 2005) and mice (Heidbreder et al., 2007). Corroborative evidence that SB-277011A’s remarkably broad profile of antiaddiction properties in such a wide variety of preclinical animal models is due to its DA D3 receptor antagonist properties, rather than to some other idiosyncratic pharmacological property, is based upon the similar pattern of animal model findings from another highly selective DA D3 receptor antagonist—NGB-2904 (see, e.g., Xi et al., 2006; for review, see Xi and Gardner, 2007). Arguably, SB-277011A has been shown to have a promising antiaddiction profile in a broader range of addiction-related animal models than any other putative pharmacotherapeutic agent in the history of addiction medicine (for reviews, see Heidbreder et al., 2004; Heidbreder et al., 2005), although GVG and baclofen have also been screened in a broad array of animal models (see above). On a cautionary note, SB-277011A does not attenuate intravenous cocaine self-administration under low-effort (that is, low fixed-ratio reinforcement) or high payoff (large amounts of cocaine per reinforcement) conditions (Vorel et al., 2002; Gál and Gyertyán, 2003; Xi et al., 2005). Despite this caution, the overall profile of SB-277011A’s effects in the animal models of addiction in which it has been tested is highly suggestive of potential utility for DA D3 antagonists as anti-addiction pharmacotherapies. Further development of SB-277011A itself has been halted due to unexpectedly poor bioavailability and short half-life in primates (Austin et al., 2001; Remington and Kapur, 2001). However, the preclinical animal model evidence for presumptive antiaddiction efficacy of high-affinity highselectivity DA D3 receptor antagonists is so extensive that development of other D3-selective antagonists with better bioavailability and more promising pharmacokinetic profiles continues (see, e.g., Newman et al., 2005). Caveats Regarding Animal Models What animal studies do not reveal, except by contrast, is the importance of language and cultural influences in human drug self-administration. One animal apparently cannot learn from another’s death that recreation-

al drug use can be dangerous; they cannot be told that “speed kills.” Nor are singly caged animals influenced by peer pressure, advertising, or warnings from the surgeon general. These aspects of human drug experience are not modeled in animal studies, though they and human intelligence play an important role in human drug self-administration. What animal models can tell us about is our common biological heritage, and about the pharmacological impact of addictive substances on the mammalian species that share that heritage. Thus, they are useful tools of construct validity in the study of the underlying mechanisms—neurobiological and psychological—of addictive processes. To the extent that animal models may also have either face or predictive validity to human addiction, they may also be useful in the search for new and effective treatments for addiction at the human level, and are routinely so used in present-day addiction medicine research.

ACKNOWLEDGMENTS Preparation of this chapter was supported by the Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health. REFERENCES Aeberli, P., Eden, P., Gogerty, J.H., Houlihan, W.J., and Penberthy, C. (1975) 5-Aryl-2,3-dihydro-5H-imidazo[2,1-a]isoindol-5-ols. A novel class of anorectic agents. J. Med. Chem. 18:177–182. Andersen, P.H. (1987) Biochemical and pharmacological characterization of [3H]GBR-12935 binding in vitro to rat striatal membranes: labeling of the dopamine uptake complex. J. Neurochem. 48:1887–1896. Arnold, J.M., and Roberts, D.C.S. (1997) A critique of fixed and progressive ratio schedules used to examine the neural substrates of drug reinforcement. Pharmacol. Biochem. Behav. 57:441–447. Ashby, C.R., Jr., Minabe, Y., Stemp, G., Hagan, J.J., and Middlemiss, D.N. (2000) Acute and chronic administration of the selective D3 receptor antagonist SB-277011-A alters activity of midbrain dopamine neurons in rats: an in vivo electrophysiological study. J. Pharmacol. Exp. Ther. 294:1166–1174. Ashby, C.R., Jr., Paul, M., Gardner, E.L., Heidbreder, C.A., and Hagan, J.J. (2003) Acute administration of the selective D3 receptor antagonist SB-277011A blocks the acquisition and expression of the conditioned place preference response to heroin in male rats. Synapse 48:154–156. Ashby, C.R., Jr., Rohatgi, R., Ngosuwan, J., Borda, T., Gerasimov, M.R., Morgan, A.E., Kushner, S., Brodie, J.D., and Dewey, S.L. (1999) Implication of the GABAB receptor in gamma vinylGABA’s inhibition of cocaine-induced increases in nucleus accumbens dopamine. Synapse 31:151–153. Austin, N.E., Baldwin, S.J., Cutler, L., Deeks, N., Kelly, P.J., Nash, M., Shardlow, C.E., Stemp, G., Thewlis, K.M., Ayrton, A., and Jeffrey, P. (2001) Pharmacokinetics of the novel, high-affinity and selective dopamine D3 receptor antagonist SB-277011 in rat, dog and monkey: in vitro/in vivo correlation and the role of aldehyde oxidase. Xenobiotica 31:677–686. Barrett, A.C., Negus, S.S., Mello, N.K., and Caine S.B. (2005) Effect of GABA agonists and GABA-A receptor modulators on cocaineand food-maintained responding and cocaine discrimination in rats. J. Pharmacol. Exp. Ther. 315:858–871.

45: ANIMAL MODELS OF ADDICTION Baumann, M.H., Char, G.U., de Costa, B.R., Rice, K.C., and Rothman, R.B. (1994) GBR 12909 attenuates cocaine-induced activation of mesolimbic dopamine neurons in the rat. J. Pharmacol. Exp. Ther. 271:1216–1222. Berger, P., Gawin, F., and Kosten, T.R. (1989) Treatment of cocaine abuse with mazindol. Lancet 1:283. Berger, P., Janowsky, A., Vocci, F., Skolnick, P., Schweri, M., and Paul, S.M. (1985) [3H]GBR-12935: a specific high affinity ligand for labeling the dopamine transport complex. Eur. J. Pharmacol. 107:289–290. Bonnet, J.J., Protais, P., Chagraoui, A., and Costentin, J. (1986) High affinity [3H]GBR 12783 binding to a specific site associated with the neuronal dopamine uptake complex in the central nervous system. Eur. J. Pharmacol. 126:211–222. Bozarth, M.A., and Wise, R.A. (1984) Anatomically distinct opiate receptor fields mediate reward and physical dependence. Science 224:516–518. Bozarth, M.A., and Wise, R.A. (1986) Involvement of the ventral tegmental dopamine system in opioid and psychomotor stimulant reinforcement. NIDA Res. Monogr. 67:190–196. Braida, D., Pozzi, M., Cavallini, R., and Sala, M. (2001) Conditioned place preference induced by the cannabinoid agonist CP 55,940: interaction with the opioid system. Neuroscience 104:923–926. Brebner, K., Froestl, W., Andrews, M., Phelan, R., and Roberts, D. C.S. (1999) The GABAB agonist CGP 44532 decreases cocaine self-administration in rats: demonstration using a progressive ratio and a discrete trials procedure. Neuropharmacology 38:1797– 1804. Brebner, K., Phelan, R., and Roberts, D.C.S. (2000) Effects of baclofen on cocaine self-administration in rats reinforced under fixed-ratio 1 and progressive-ratio schedules. Psychopharmacology 148:314–321. Brodie, J.D., Figueroa, E., and Dewey S.L. (2003) Treating cocaine addiction: from preclinical to clinical trial experience with g -vinyl GABA. Synapse 50:261–265. Brodie, J.D., Figueroa, E., Laska, E.M., and Dewey S.L. (2003) Safety and efficacy of g -vinyl GABA (GVG) for the treatment of methamphetamine and/or cocaine addiction. Synapse 55:122–125. Caine, S.B., and Koob, G.F. (1993) Modulation of cocaine selfadministration in the rat through D-3 dopamine receptors. Science 260:1814–1816. Campbell, U.C., Lac, S.T., and Carroll, M.E. (1999) Effects of baclofen on maintenance and reinstatement of intravenous cocaine self-administration in rats. Psychopharmacology 143:209–214. Carlezon, W.A., Jr., Devine, D.P., and Wise, R.A. (1995) Habitforming actions of nomifensine in nucleus accumbens. Psychopharmacology 122:194–197. Carlezon, W.A., Jr., and Wise, R.A. (1996a) Rewarding actions of phencyclidine and related drugs in nucleus accumbens shell and frontal cortex. J. Neurosci. 16:3112–3122. Carlezon, W.A., Jr., and Wise, R.A. (1996b) Microinjections of phencyclidine (PCP) and related drugs into nucleus accumbens shell potentiate medial forebrain bundle brain stimulation reward. Psychopharmacology 128:413–420. Carroll, F.I., Lewin, A.H., Boja, J.W., and Kuhar, M.J. (1992) Cocaine receptor: biochemical characterization and structure-activity relationships of cocaine analogues at the dopamine transporter. J. Med. Chem. 35:969–981. Cervo, L., Carnovali, F., Stark, J.A., and Mennini, T. (2003) Cocaineseeking behavior in response to drug-associated stimuli in rats: involvement of D3 and D2 dopamine receptors. Neuropsychopharmacology 28:1150–1159. Chen, J., Paredes, W., Li, J., Smith, D., Lowinson, J., and Gardner, E. L. (1990) D9-Tetrahydrocannabinol produces naloxone-blockable enhancement of presynaptic basal dopamine efflux in nucleus accumbens of conscious, freely-moving rats as measured by intracerebral microdialysis. Psychopharmacology 102:156–162.

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Christie, M.J., Summers, R.J., Stephenson, J.A., Cook, C.J., and Beart, P.M. (1987) Excitatory amino acid projections to the nucleus accumbens septi in the rat: a retrograde transport study utilizing D[3H]aspartate and [3H]GABA. Neuroscience 22:425–439. Clarke, P.B.S., and Pert, A. (1985) Autoradiographic evidence for nicotine receptors on nigrostriatal and mesolimbic dopaminergic neurons. Brain Res. 348:355–358. Collier, H.O.J. (1980) Cellular site of opiate dependence. Nature 283:625–629. Dackis, C.A., and Gold, M.S. (1985) New concepts in cocaine addiction: the dopamine depletion hypothesis. Neurosci. Biobehav. Rev. 9:469–477. Devine, D.P., Leone, P., Pocock, D., and Wise, R.A. (1993) Differential involvement of ventral tegmental mu, delta and kappa opioid receptors in modulation of basal mesolimbic dopamine release: in vivo microdialysis studies. J. Pharmacol. Exp. Ther. 266:1236– 1246. Devine, D.P., and Wise, R.A. (1994) Self-administration of morphine, DAMGO, and DPDPE into the ventral tegmental area of rats. J. Neurosci. 14:1978–1984. Dewey, S.L., Brodie, J.D., Gerasimov, M., Horan, B., Gardner, E.L., and Ashby, C.R., Jr. (1999) A pharmacologic strategy for the treatment of nicotine addiction. Synapse 31:76–86. Dewey, S.L., Chaurasia, C.S., Chen, C.-E., Volkow, N.D., Clarkson, F.A., Porter, S.P., Straughter-Moore, R.M., Alexoff, D.L., Tedeschi, D., Russo, N.B., Fowler, J.S., and Brodie, J.D. (1997) GABAergic attenuation of cocaine-induced dopamine release and locomotor activity. Synapse 25:393–398. Dewey, S.L., Morgan, A.E., Ashby, C.R., Jr., Horan, B., Kushner, S.A., Logan, J., Volkow, N.D., Fowler, J.S., Gardner, E.L., and Brodie, J.D. (1998) A novel strategy for the treatment of cocaine addiction. Synapse 30:119–129. de Wit, H., and Wise, R.A. (1977) Blockade of cocaine reinforcement in rats with the dopamine receptor blocker pimozide but not with the noradrenergic blockers phentolamine or phenoxybenzamine. Can. J. Psychol. 31:195–203. Di Ciano, P., and Everitt, B.J. (2003) The GABAB receptor agonist baclofen attenuates cocaine- and heroin-seeking behavior by rats. Neuropsychopharmacology 28:510–518. Di Ciano, P., Underwood, R.J., Hagan, J.J., and Everitt, B.J. (2003) Attenuation of cue-controlled cocaine-seeking by a selective D3 dopamine receptor antagonist SB-277011-A. Neuropsychopharmacology 28:329–338. Everitt, B.J., Di Ciano, P., Underwood, R., and Hagan, J. (2001) Attenuation of drug-seeking by a selective D3 dopamine receptor antagonist. Soc. Neurosci. Abstr. 27:1711. Everitt, B.J., and Robbins, T.W. (2000) Second-order schedules of drug reinforcement in rats and monkeys: measurement of reinforcing efficacy and drug-seeking behaviour. Psychopharmacology 153:17–30. Fada, P., Scherma, M., Fresu, A., Collu, M., and Fratta, W. (2003) Baclofen antagonizes nicotine-, cocaine-, and morphine-induced dopamine release in the nucleus accumbens of rat. Synapse 50: 1–6. Filip, M., Frankowska, M., Zaniewska, M. Golda, A., Przegalinski, ´ E., and Vetulani, J. (2007) Diverse effects of GABA-mimetic drugs on cocaine-evoked self-administration and discriminative stimulus effects in rats. Psychopharmacology 192:17–26. Froimowitz, M., Wu, K.-M., Liu, X., Spector, J., Hayes, R., Vorel, S.R., Paredes, W., Ashby, C.R., Jr., and Gardner, E.L. (1999) Slowonset, long-lasting prodrugs as potential medications for cocaine addiction: intravenous cocaine self-administration studies in rat strains with different vulnerabilities to drug-seeking behavior. Soc. Neurosci. Abstr. 25:1574. Froimowitz, M., Wu, K.-M., Moussa, A., Haidar, R.M., Jurayi, J., George, C., and Gardner, E.L. (2000) Slow-onset, long-duration 3-(3',4'-dichlorophenyl)-1-indanamine monoamine reuptake block-

770

SUBSTANCE ABUSE DISORDERS

ers as potential medications to treat cocaine abuse. J. Med. Chem. 43:4981–4992. Gál, K., and Gyertyán, I. (2003) Targeting the dopamine D3 receptor cannot influence continuous reinforcement cocaine selfadministration in rats. Brain Res. Bull. 61:595–601. Gál, K., and Gyertyán, I. (2006) Dopamine D3 as well as D2 receptor ligands attenuate the cue-induced cocaine-seeking in a relapse model in rats. Drug Alcohol Depend. 81:63–70. Gardner, E.L. (1999) The neurobiology and genetics of addiction: implications of the “reward deficiency syndrome” for therapeutic strategies in chemical dependency. In: Elster, J., ed. Addiction: Entries and Exits. New York: Russell Sage, pp. 57–119. Gardner, E.L. (2000) What we have learned about addiction from animal models of drug self-administration. Am. J. Addict. 9:285– 313. Gardner, E.L. (2002) Marijuana addiction and CNS reward-related events. In: Onaivi, E., ed. Biology of Marijuana: From Gene to Behaviour. London: Taylor & Francis, pp. 75–109. Gardner, E.L., Liu, X., Paredes, W., Giordano, A., Spector, J., Lepore, M., Wu, K.-M., and Froimowitz, M. (2006) A slow-onset, longduration indanamine monoamine reuptake inhibitor as a potential maintenance pharmacotherapy for psychostimulant abuse: effects in laboratory rat models relating to addiction. Neuropharmacology 51:993–1003. Gardner, E.L., Paredes, W., Smith, D., Donner, A., Milling, C., Cohen, D., and Morrison, D. (1988) Facilitation of brain stimulation reward by D9-tetrahydrocannabinol. Psychopharmacology 96:142– 144. Gerasimov, M.R., Ashby, C.R., Jr., Gardner, E.L., Mills, M.J., Brodie, J.D., and Dewey, S.L. (1999) Gamma-vinyl GABA inhibits methamphetamine, heroin, or ethanol-induced increases in nucleus accumbens dopamine. Synapse 34:1–19. Gerasimov, M.R., and Dewey, S.L. (1999) Gamma-vinyl g -aminobutyric acid attenuates the synergistic elevations of nucleus accumbens dopamine produced by a cocaine/heroin (speedball) challenge. Eur. J. Pharmacol. 380:1– 4. Gerasimov, M.R., Schiffer, W.K., Brodie, J.D., Lennon, I.C., Taylor, S.J., and Dewey, S.L. (2000) g -Aminobutyric acid mimetic drugs differentially inhibit the dopaminergic response to cocaine. Eur. J. Pharmacol. 395:129–135. Gerasimov, M.R., Schiffer, W.K., Gardner, E.L., Marsteller, D.A., Lennon, I.C., Taylor, S.J., Brodie, J.D., Ashby, C.R., Jr., and Dewey, S.L. (2001) GABAergic blockade of cocaine-associated cue-induced increases in nucleus accumbens dopamine. Eur. J. Pharmacol. 414:205–209. Gerber, G.J., and Wise, R.A. (1989) Pharmacological regulation of intravenous cocaine and heroin self-administration in rats: a variable dose paradigm. Pharmacol. Biochem. Behav. 32:527– 531. Gilbert, J.G., Newman, A.H., Gardner, E.L., Ashby, C.R., Jr., Heidbreder, C.A., Pak, A.C., Peng, X.-Q., and Xi, Z.-X. (2005) Acute administration of SB-277011A, NGB 2904, or BP 897 inhibits cocaine cue-induced reinstatement of drug-seeking behavior in rats: role of dopamine D3 receptors. Synapse 57:17–28. Glowa, J.R., Fantegrossi, W.F., Lewis, D.B., Matecka, D., Rice, K.C., and Rothman, R.B. (1996) Sustained decrease in cocaine-maintained responding in rhesus monkeys with 1-[2-[bis(4-fluorophenyl)methyoxy]ethyl]-4-(3-hydroxy-3-phenylpropyl) piperazinyl decanoate, a long-acting ester derivative of GBR 12909. J. Med. Chem. 39:4689–4691. Glowa, J.R., Wojnicki, F.H.E., Matecka, D., Bacher, J.D., Mansbach, R.S., Balster, R.L., and Rice, K.C. (1995) Effects of dopamine reuptake inhibitors on food- and cocaine-maintained responding: I. Dependence on unit dose of cocaine. Exp. Clin. Psychopharmacol. 3:219–231.

Glowa, J.R., Wojnicki, F.H.E., Matecka, D., Rice, K., and Rothman, R.B. (1995) Effects of dopamine reuptake inhibitors on foodand cocaine-maintained responding: II. Comparisons with other drugs and repeated administrations. Exp. Clin. Psychopharmacol. 3:232–239. Goeders, N.E., and Smith, J.E. (1983) Cortical dopaminergic involvement in cocaine reinforcement. Science 221:773–775. Goeders, N.E., and Smith, J.E. (1993) Intracranial cocaine selfadministration into the medial prefrontal cortex increases dopamine turnover in the nucleus accumbens. J. Pharmacol. Exp. Ther. 265:592–600. Goldberg, S.R. (1973) Comparable behavior maintained under fixedratio and second-order schedules of food presentation, cocaine injection or d-amphetamine injection in the squirrel monkey. J. Pharmacol. Exp. Ther. 186:18–30. Goldberg, S.R., and Tang, A.H. (1977) Behavior maintained under second-order schedules of intravenous morphine injection in squirrel and rhesus monkeys. Psychopharmacology 51:235– 242. Goldstein, D.B., and Goldstein, A. (1961) Possible role of enzyme inhibition and repression in drug tolerance and addiction. Biochem. Pharmacol. 8:48. Grimm, J.W., and See, R.E. (2000) Dissociation of primary and secondary reward-relevant limbic nuclei in an animal model of relapse. Neuropsychopharmacology 22:473–479. Haney, M., Hart, C.L., and Foltin, R.W. (2006) Effects of baclofen on cocaine self-administration: opioid- and nonopioid-dependent volunteers. Neuropsychopharmacology 31:1814–1821. Hayes, R.J., Vorel, S.R., Spector, J., Liu, X., and Gardner, E.L. (2003) Electrical and chemical stimulation of the basolateral complex of the amygdala reinstates cocaine-seeking behavior. Psychopharmacology 168:75–83. Heidbreder, C.A., Andreoli, M., Marcon, C., Hutcheson, D.M., Gardner, E.L., and Ashby, C.R., Jr. (2007) Evidence for the role of dopamine D3 receptors in oral operant alcohol self-administration and reinstatement of alcohol-seeking behavior in mice. Addict. Biol. 12:35–50. Heidbreder, C.A., Andreoli, M., Marcon, C., Thanos, P.K., Ashby, C.R., Jr., and Gardner, E.L. (2004) Role of dopamine D3 receptors in the addictive properties of ethanol. Drugs Today 40:355– 365. Heidbreder, C.A., Gardner, E.L., Xi, Z.-X., Thanos, P.K., Mugnaini, M., Hagan, J.J., and Ashby, C.R., Jr. (2005) The role of central dopamine D3 receptors in drug addiction: a review of pharmacological evidence. Brain Res. Rev. 49:77–105. Higley, A., Li, X., Dillon, C., Ashby, C.R., Jr., Heidbreder, C.A., Gaál, J., Xi, Z.-X., and Gardner, E.L. (2007) The dopamine D3 receptor antagonist SB277011A inhibits methamphetamine selfadministration under a progressive-ratio reinforcement schedule. Paper presented at the 37th annual meeting of the Society for Neuroscience, San Diego, CA, Abstract 814.1. Hodos, W. (1961) Progressive ratio as a measure of reward strength. Science 134:943–944. Howell, L.L., Czoty, P.W., Kuhar, M.J., and Carroll, F.I. (2000) Comparative behavioral pharmacology of cocaine and the selective dopamine uptake inhibitor RTI-113 in the squirrel monkey. J. Pharmacol. Exp. Ther. 292:521–529. Howell, L.L., and Wilcox, K.M. (2001) The dopamine transporter and cocaine medication development: drug self-administration in nonhuman primates. J. Pharmacol. Exp. Ther. 298:1–6. Hsin, L.-W., Dersch, C.M., Baumann, M.H., Stafford, D., Glowa, J.R., Rothman, R.B., Jacobson, A.E., and Rice, K.C. (2002) Development of long-acting dopamine transporter ligands as potential cocaine-abuse therapeutic agents: chiral hydroxyl-containing derivatives of 1-[2-[bis(4-fluorophenyl)methoxy]ethyl]-4-(3-phenyl propyl)

45: ANIMAL MODELS OF ADDICTION piperazine and 1-[2-(diphenylmethoxy)ethyl]-4-(3-phenyl propyl) piperazine. J. Med. Chem. 45:1321–1329. Ikemoto, S. (2003) Involvement of the olfactory tubercle in cocaine reward. J. Neurosci. 23:9305–9311. Ikemoto, S., and Wise, R.A. (2004) Mapping of chemical trigger zones for reward. Neuropharmacology 47:190–201. Johnson, S.W., and North, R.A. (1992) Opioids excite dopamine neurons by hyperpolarization of local interneurons. J. Neurosci. 12:483–488. Jung, M.J., Lippert, B., Metcalf, B.W., Bohlen, P., and Schechter, P.J. (1977) g -Vinyl GABA (4-amino-hex-5-enoic acid), a new selective inhibitor of GABA-T: effects on brain GABA metabolism in mice. J. Neurochem. 29:797–802. Justinova, Z., Goldberg, S.R., Heishman, S.J., and Tanda, G. (2005) Self-administration of cannabinoids by experimental animals and human marijuana smokers. Pharmacol. Biochem. Behav. 81: 285–299. Justinova, Z., Solinas, M., Tanda, G., Redhi, G.H., and Goldberg, S.R. (2005) The endogenous cannabinoid anandamide and its synthetic analog R(+)-methanandamide are intravenously self-administered by squirrel monkeys. J. Neurosci. 25:5645– 5650. Justinova, Z., Tanda, G., Redhi, G.H., and Goldberg, S.R. (2003) Self-administration of D9-tetrahydrocannabinol (THC) by drug naïve squirrel monkeys. Psychopharmacology 169:135–140. Kalivas, P.W., Churchill, L., and Klitenick, M.A. (1993) GABA and enkephalin projection from the nucleus accumbens and ventral pallidum to the ventral tegmental area. Neuroscience 57:1047–1060. Kalivas, P.W., Duffy, P., and Eberhardt, H. (1990) Modulation of A10 dopamine neurons by g -aminobutyric acid agonists. J. Pharmacol. Exp. Ther. 253:858–866. Kiyatkin, E.A., and Rebec, G.V. (1999) Modulation of striatal neuronal activity by glutamate and GABA: iontophoresis in awake, unrestrained rats. Brain Res. 822:88–106. Klitenick, M.A., DeWitte, P., and Kalivas, P.W. (1992) Regulation of somatodendritic dopamine release in the ventral tegmental area by opioids and GABA: an in vivo microdialysis study. J. Neurosci. 12:2623–2632. Knapp, C.M., Cottam, N., Dewey, S.L., and Kornetsky, C. (1999) The GABA transaminase inhibitor, vigabatrin, reduces responding for heroin self-administration. Soc. Neurosci. Abstr. 25:558. Koob, G.F., and Bloom, F.E. (1988) Cellular and molecular mechanisms of drug dependence. Science 242:715–723. Kushner, S.A., Dewey, S.L., and Kornetsky, C. (1997) Gamma-vinyl GABA attenuates cocaine-induced lowering of brain stimulation reward thresholds. Psychopharmacology 133:383–388. Kushner, S.A., Dewey, S.L., and Kornetsky, C. (1999) The irreversible g -aminobutyric acid (GABA) transaminase inhibitor g -vinylGABA blocks cocaine self-administration in rats. J. Pharmacol. Exp. Ther. 290:797–802. Ledent, C., Valverde, O., Cossu, G., Petitet, F., Aubert, J.-F., Beslot, F., Böhme, G.A., Imperato, A., Pedrazzini, T., Roques, B.P., Vassart, G., Fratta, W., and Parmentier, M. (1999) Unresponsiveness to cannabinoids and reduced addictive effects of opiates in CB1 receptor knockout mice. Science 283:401–404. Leith, N.J., and Barrett, R.J. (1976) Amphetamine and the reward system: evidence for tolerance and post-drug depression. Psychopharmacologia 46, 19–25. Lepore, M., and Franklin, K.B.J. (1992) Modelling drug kinetics with brain stimulation: dopamine antagonists increase selfstimulation. Pharmacol. Biochem. Behav. 41:489–496. Lepore, M., Vorel, S.R., Lowinson, J., and Gardner, E.L. (1995) Conditioned place preference induced by D9-tetrahydrocannabinol: comparison with cocaine, morphine, and food reward. Life Sci. 56:2073–2080.

771

Levant, B. (1998) Differential distribution of D3 dopamine receptors in the brains of several mammalian species. Brain Res. 800:269– 274. Lewis, D.B., Matecka, D., Zhang, Y., Hsin, L.-W., Dersch, C.M., Stafford, D., Glowa, J.R., Rothman, R.B., and Rice, K.C. (1999) Oxygenated analogues of 1-[2-(diphenylmethoxy)ethyl]- and 1[2-[bis(4-fluorophenyl)methyoxy]ethyl]-4-(3-phenylpropyl) piperazines (GBR 12935 and GBR 12909) as potential extendedaction cocaine-abuse therapeutic agents. J. Med. Chem. 42:5029– 5042. Lile, J.A., Stoops, W.W., Allen, T.S., Glaser, P.E., Hays, L.R., and Rush, C.R. (2004) Baclofen does not alter the reinforcing, subject-related or cardiovascular effects of intranasal cocaine in humans. Psychopharmacology 171:441–449. Ling, W., Shoptaw, S., and Majewska, D. (1998) Baclofen as a cocaine anti-craving medication: a preliminary clinical study. Neuropsychopharmacology 18:403–404. Madras, B.K., Spealman, R.D., Fahey, M.A., Neumeyer, J.L., Saha, J.K., and Milius, R.A. (1989) Cocaine receptors labeled by [3H]2b -carbomethoxy-3b -(fluorophenyl)tropane. Mol. Pharmacol. 36:518–524. Markou, A., and Koob, G.F. (1991) Postcocaine anhedonia: an animal model of cocaine withdrawal. Neuropsychopharmacology 4:17–26. Martellotta, M.C., Cossu, G., Fattore, L., Gessa, G.L., and Fratta, W. (1998) Self-administration of the cannabinoid receptor agonist WIN 55,212-2 in drug-naive mice. Neuroscience 85:327–330. Mattson, R.H., Petroff, O.A., Rothman, D., and Behar, K. (1995) Vigabatrin: effect on brain GABA levels measured by nuclear magnetic resonance spectroscopy. Acta Neurol. Scand. Suppl. 162:27–30. McFarland, K., Lapish, C.C., and Kalivas, P.W. (2003) Prefrontal glutamate release into the core of the nucleus accumbens mediates cocaine-induced reinstatement of drug-seeking behavior. J. Neurosci. 23:3531–3537. Meltzer, P.C., Liang, A.Y., and Madras, B.K. (1994) The discovery of an unusually selective and novel cocaine analogue: difluoropine. Synthesis and inhibition of binding at cocaine recognition sites. J. Med. Chem. 37:2001–2010. Meredith, G.E. (1999) The synaptic framework for chemical signaling in nucleus accumbens. Ann. N.Y. Acad. Sci. 877:140–156. Morgan, A.E., and Dewey, S.L. (1998) Effects of pharmacologic increases in brain GABA levels on cocaine-induced changes in extracellular dopamine. Synapse 28:60–65. Museo, E., and Wise, R.A. (1994) Place preference conditioning with ventral tegmental injections of cytisine. Life Sci. 55:1179– 1186. Nader, M.A., Grant, K.A., Davies, M.L.H., Mach, R.H., and Childers, S.R. (1997) The reinforcing and discriminative stimulus effects of a novel cocaine analog 2b -propanoyl-3b -(4-tolyl)-tropane in rhesus monkeys. J. Pharmacol. Exp. Ther. 280:541–550. Nazzaro, J.M., and Gardner, E.L. (1980) GABA antagonism lowers self-stimulation thresholds in the ventral tegmental area. Brain Res. 189:279–283. Nestler, E.J. (1993) Molecular mechanisms of drug addiction in the mesolimbic dopamine pathway. Sem. Neurosci. 5:369–376. Newman, A.H., Allen, A.C., Izenwasser, S., and Katz, J.L. (1994) Novel 3a-(diphenylmethoxy)tropane analogues: potent dopamine uptake inhibitors without cocaine-like behavioral profiles. J. Med. Chem. 37:2258–2261. Newman, A.H., Grundt, P., and Nader, M.A. (2005) Dopamine D3 receptor partial agonists and antagonists as potential drug abuse therapeutic agents. J. Med. Chem. 48:3663–3679. Nissbrandt, H., Ekman, A., Eriksson, E., and Heilig, M. (1995) Dopamine D3 receptor antisense influences dopamine synthesis in rat brain. Neuroreport 6:573–576.

772

SUBSTANCE ABUSE DISORDERS

Oldendorf, W.H. (1992) Some relationships between addiction and drug delivery to the brain. NIDA Res. Monogr. 120:13–25. Olds, M.E. (1982) Reinforcing effects of morphine in the nucleus accumbens. Brain Res. 237:429–440. Pak, A.C., Ashby, C.R., Jr., Heidbreder, C.A., Pilla, M., Gilbert, J., Xi, Z.-X., and Gardner, E.L. (2006) The selective dopamine D3 receptor antagonist SB-277011A reduces nicotine-enhanced brain reward and nicotine-paired environmental cue functions. Int. J. Neuropsychopharmacol. 9:585–602. Parsons, L.H., Caine, S.B., Sokoloff, P., Schwartz, J.-C., Koob, G.F., and Weiss, F. (1996) Neurochemical evidence that postsynaptic nucleus accumbens D3 receptor stimulation enhances cocaine reinforcement. J. Neurochem. 67:1078–1089. Peng, X.-Q., Li, X., Gilbert, J.G., Pak, A.C., Ashby, C.R., Jr., Brodie, J.D., Dewey, S.L., Gardner, E.L., and Xi, Z.-X. (in press) Gammavinyl GABA inhibits cocaine-triggered reinstatement of drug-seeking behavior in rats by a non-dopaminergic mechanism. Drug Alcohol Depend. Peng, X.-Q., Xi, Z.-X., Gilbert, J., Campos, A., Dewey, S.L., Schiffer, W.K., Brodie, J.D., Ashby, C.R., Jr., and Gardner, E.L. (2004) Gamma-vinyl GABA, but not gabapentin, inhibits cocaine-triggered reinstatement of drug-seeking behavior in the rat. Paper presented at the 34th annual meeting of the Society for Neuroscience, San Diego, CA, Abstract 691.8. Peng, X.-Q., Xi, Z.-X., Gilbert, J.G., Pak, A.C., Kleitz, H., Gardner, E.L., Gu, Y., and Froimowitz, M. (2005) Behavioral and neurochemical effects of CTDP-31,345, a novel slow-onset and longduration dopamine transporter inhibitor: alone and in combination with cocaine. Paper presented at the 35th annual meeting of the Society for Neuroscience, Washington, DC, Abstract 227.10. Peng, X.-Q., Xi, Z.-X., Li, X., Gilbert, J., Pak, A., Froimowitz, M., and Gardner, E.L. (2006) Methadone pretreatment attenuates heroin’s rewarding effects and heroin-induced dopamine release in the nucleus accumbens: comparison to the effects of CTDP31,345, a long-lasting dopamine transporter inhibitor. Paper presented at the 36th annual meeting of the Society for Neuroscience, Atlanta, GA, Abstract 591.8. Pickens, R., and Thompson, T. (1971) Characteristics of stimulant reinforcement. In: Thompson, T., and Pickens, R., eds. Stimulus Properties of Drugs. New York: Appleton-Century-Crofts, pp. 177–192. Pilla, M., Perachon, S., Sautel, F., Garrido, F., Mann, A., Wermuth, C.G., Schwartz, J.-C., Everitt, B.J., and Sokoloff, P. (1999) Selective inhibition of cocaine-seeking behaviour by a partial dopamine D3 receptor agonist. Nature 400:371–375. Reavill, C., Taylor, S.G., Wood, M.D., Ashmeade, T., Austin, N.E., Avenell, K.Y., Boyfield, I., Branch, C.L., Cilia, J., Coldwell, M.C., Hadley, M.S., Hunter, A.J., Jeffrey, P., Jewitt, F., Johnson, C.N., Jones, D.N.C., Medhurst, A.D., Middlemiss, D.N., Nash, D.J., Riley, G.J., Routledge, C., Stemp, G., Thewlis, K.M., Trail, B., Vong, A.K.K., and Hagan, J.J. (2000) Pharmacological actions of a novel, high-affinity, and selective human dopamine D3 receptor antagonist, SB-277011-A. J. Pharmacol. Exp. Ther. 294: 1154–1165. Remington, G., and Kapur, S. (2001) SB-277011 GlaxoSmithKline. Curr. Opin. Invest. Drugs 2:946–949. Richardson, N.R., and Roberts D.C.S. (1996) Progressive ratio schedules in drug self-administration studies in rats: a method to evaluate reinforcing efficacy. J. Neurosci. Meth. 66:1–11. Ritz, M.C., Lamb, R.J., Goldberg, S.R., and Kuhar, M.J. (1987) Cocaine receptors on dopamine transporters are related to selfadministration of cocaine. Science 237:1219–1223. Roberts, D.C.S., and Andrews, M.M. (1997) Baclofen suppression of cocaine self-administration: demonstration using a discrete trials procedure. Psychopharmacology 131:271–277.

Roberts, D.C.S., Andrews, M.M., and Vickers, G.J. (1996) Baclofen attenuates the reinforcing effects of cocaine. Neuropsychopharmacology 15:417–423. Rothman, R.B., and Glowa, J.R. (1995) A review of the effects of dopaminergic agents on humans, animals, and drug-seeking behavior, and its implications for medication development—focus on GBR-12909. Mol. Neurobiol. 11:1–19. Saul’skaya, N.B., and Gorbachevskaya, A.I. (1999) The role of the hippocampal formation in controlling GABA release in the nucleus accumbens during an emotional conditioned response. Neurosci. Behav. Physiol. 29:461–466. Schenk, S. (2002) Effects of GBR 12909, WIN 35,428 and indatraline on cocaine self-administration and cocaine seeking in rats. Psychopharmacology 160:263–270. Schiffer, W.K., Gerasimov, M.R., Bermel, R.A., Brodie, J.D., and Dewey, S.L. (2000) Stereoselective inhibition of dopaminergic activity by gamma vinyl-GABA following a nicotine or cocaine challenge: a PET/microdialysis study. Life Sci. 66:PL169– PL173. Self, D.W., and Nestler, E.J. (1995) Molecular mechanisms of drug reinforcement and addiction. Annu. Rev. Neurosci. 18:463– 495. Sesack, S.R., and Pickel, V.M. (1995) Ultrastructural relationships between terminals immunoreactive for enkephalin, GABA, or both transmitters in the rat ventral tegmental area. Brain Res. 672:261–275. Shaham, Y., and Stewart, J. (1995) Stress reinstates heroin-seeking in drug-free animals: an effect mimicking heroin, not withdrawal. Psychopharmacology 119:334–341. Shalev, U., Grimm, J.W., and Shaham, Y. (2002) Neurobiology of relapse to heroin and cocaine seeking: a review. Pharmacol. Rev. 54:1–42. Shoptaw, S., Yang, X., Rotheram-Fuller, E.J., Hsieh, Y.C., Kintaudi, P.C., Charuvastra, V.C., and Ling, W. (2003) Randomized placebocontrolled trial of baclofen for cocaine dependence: preliminary effects for individuals with chronic patterns of cocaine use. J. Clin. Psychiatry 64:1440–1448. Slattery, D.A., Markou, A., Froestl, W., and Cryan, J.F. (2005) The GABAB receptor-positive modulator GS39783 and the GABAB receptor agonist baclofen attenuate the reward-facilitating effects of cocaine: intracranial self-stimulation studies in the rat. Neuropsychopharmacology 30:2065–2072. Solomon, R.L., and Corbit, J.D. (1974) An opponent-process theory of motivation: I. Temporal dynamics of affect. Psychol. Rev. 81: 119–145. Spanagel, R., Herz, A., and Shippenberg, T.S. (1990) The effects of opioid peptides on dopamine release in nucleus accumbens: an in vivo microdialysis study. J. Neurochem. 55:1734–1740. Spiller, K., Xi, Z.-X., Peng, X.-Q., Newman, A.H., Ashby, C.R., Jr., Heidbreder, C., Gaál, J., and Gardner E.L. (2008) The putative dopamine D3 receptor antagonists SB-277011A and NGB 2904 and the putative partial D3 receptor agonist BP 897 attenuate methamphetamine-enhanced brain stimulation reward in rats. Psychopharmacology 196:533–542. Stein, L. (1962) Effects and interactions of imipramine, chlorpromazine, reserpine and amphetamine on self-stimulation: possible neurophysiological basis of depression. In: Wortis, J., ed. Recent Advances in Biological Psychiatry. New York: Plenum, pp. 288– 308. Stemp, G., Ashmeade, T., Branch, C.L., Hadley, M.S., Hunter, A.J., Johnson, C.N., Nash, D.J., Thewlis, K.M., Vong, A.K.K., Austin, N.E., Jeffrey, P., Avenell, K.Y., Boyfield, I., Hagan, J.J., Middlemiss, D.N., Reavill, C., Riley, G.J., Routledge, C., and Wood, M. (2000) Design and synthesis of trans-N-[4-[2-(6-cyano-1,2,3,4-tetrahydroisoquinolin-2-yl)ethyl]cyclohexyl]-4-quinolinecarboxamide (SB-277011): a potent and selective dopamine D3 receptor antag-

45: ANIMAL MODELS OF ADDICTION onist with high oral availability and CNS penetration in the rat. J. Med. Chem. 43:1878–1885. Suzuki, M., Hurd, Y.L., Sokoloff, P., Schwartz, J.-C., and Sedvall, G. (1998) D3 dopamine receptor mRNA is widely expressed in the human brain. Brain Res. 779:58–74. Tanda, G., Munzar, P., and Goldberg, S.R. (2000) Self-administration behavior is maintained by the psychoactive ingredient of marijuana in squirrel monkeys. Nat. Neurosci. 3:1073–1074. Thanos, P.K., Katana, J.M., Ashby, C.R., Jr., Michaelides, M., Gardner, E.L., Heidbreder, C.A., and Volkow, N.D. (2005) The selective dopamine D3 receptor antagonist SB-277011-A attenuates ethanol consumption in ethanol preferring (P) and non-preferring (NP) rats. Pharmacol. Biochem. Behav. 81:190–197. Vaccarino, F.J., Bloom, F.E., and Koob, G.F. (1985) Blockade of nucleus accumbens opiate receptors attenuates intravenous heroin reward in the rat. Psychopharmacology 86:7–42. Valjent, E., and Maldonado, R. (2000) A behavioural model to reveal place preference to Δ9-tetrahydrocannabinol in mice. Psychopharmacology 147:436–438. van der Kooy, D., Mucha, R.F., O’Shaughnessy, M., and Bucenieks, P. (1982) Reinforcing effects of brain microinjections of morphine revealed by conditioned place preference. Brain Res. 243:107– 117. Villemange, V.L., Rothman, R.B., Yokoi, F., Rice, K.C., Matecka, D., Dannals, R.F., and Wong, D.F. (1999) Doses of GBR12909 that suppress cocaine self-administration in non-human primates substantially occupy dopamine transporters as measured by [11C] WIN35,428 PET scans. Synapse 32:44–50. Volkow, N.D., Chang, L., Wang, G.-J., Fowler, J.S., Ding, Y.-S., Sedler, M., Logan, J., Franceschi, D., Gatley, S.J., Hitzemann, R., Gifford, A., Wong, C., and Pappas, N. (2001) Low level of brain dopamine D2 receptors in methamphetamine abusers: association with metabolism in the orbitofrontal cortex. Am. J. Psychiatry 158:2015–2021. Volkow, N.D., Ding, Y.-S., Fowler, J.S., Wang, G.-J., Logan, J., Gatley, J.S., Dewey, S., Ashby, C., Liebermann, J., Hitzemann, R., and Wolf, A.P. (1995) Is methylphenidate like cocaine? Studies on their pharmacokinetics and distribution in the human brain. Arch. Gen. Psychiatry 52:456–463. Volkow, N.D., Fowler, J.S., and Wang, G.-J. (1999) Imaging studies on the role of dopamine in cocaine reinforcement and addiction in humans. J. Psychopharmacol. 13:337–345. Volkow, N.D., Wang, G.-J., Fowler, J.S., Logan, J., Gatley, S.J., Gifford, A., Hitzemann, R., Ding, Y.-S., and Pappas, N. (1999) Prediction of reinforcing responses to psychostimulants in humans by brain dopamine D2 receptor levels. Am. J. Psychiatry 156: 1440–1443. Vorel, S.R., Ashby, C.R., Jr., Paul, M., Liu, X., Hayes, R., Hagan, J.J., Middlemiss, D.N., and Gardner, E.L. (2002) Dopamine D3 receptor antagonism inhibits cocaine-seeking and cocaineenhanced brain reward in rats. J. Neurosci. 22:9595–9603. Wang, B., Shaham, Y., Zitzman, D., Azari, S., Wise, R.A., and You, Z.-B. (2005) Cocaine experience establishes control of midbrain glutamate and dopamine by corticotropin-releasing factor: a role in stress-induced relapse to drug seeking. J. Neurosci. 25: 5389– 5396. Ward, B.O., Somerville, E.M., and Clifton, P.G. (2000) Intraaccumbens baclofen selectively enhances feeding behavior in the rat. Physiol. Behav. 68:463–468. Weerts, E.M., Froestl, W., Kaminski, B.J., and Griffiths, R.R. (2007) Attenuation of cocaine-seeking by GABAB receptor agonists baclofen and CGP44532 but not the GABA reuptake inhibitor tiagabine in baboons. Drug Alcohol Depend. 89:206–213. Welch, W.M., Kraska, A.R., Sarges, R., and Koe, B.K. (1984) Nontricyclic antidepressant agents derived from the cis- and trans1-amino-4-aryltetralins. J. Med. Chem. 27:1508–1515.

773

Whitelaw, R.B., Markou, A., Robbins, T.W., and Everitt, B.J. (1996) Excitotoxic lesions of the basolateral amygdala impair the acquisition of cocaine-seeking behaviour under a second-order schedule of reinforcement. Psychopharmacology 127:213–224. Wicke, K., and Garcia-Ladona, J. (2001) The dopamine D3 receptor partial agonist, BP 897, is an antagonist at human dopamine D3 receptors and at rat somatodendritic dopamine D3 receptors. Eur. J. Pharmacol. 424:85–90. Wise, R.A. (1974) Maximization of ethanol intake in the rat. In: Gross, M.M., ed. Alcohol Intoxication and Withdrawal, 2nd ed. New York: Plenum, pp. 279–294. Wise, R.A. (1982) Neuroleptics and operant behavior: the anhedonia hypothesis. Behav. Brain Sci. 5:39–87. Wise, R.A. (1989) The brain and reward. In: Liebman, J.M., and Cooper, S.J., ed. The Neuropharmacological Basis of Reward. Oxford, UK: Oxford University Press, pp. 377–424. Wise, R.A. (1996) Addictive drugs and brain stimulation reward. Annu. Rev. Neurosci. 19:319–340. Wise, R.A., and Bozarth, M.A. (1987) A psychomotor stimulant theory of addiction. Psychol. Rev. 94:469–492. Wise, R.A., Marcangione, C., and Bauco, P. (1998) Blockade of the reward-potentiating effects of nicotine on lateral hypothalamic brain stimulation by chlorisondamine. Synapse 29:72–79. Wise, R.A., Newton, P., Leeb, K., Burnette, B., Pocock, D., and Justice, J.B., Jr. (1995) Fluctuations in nucleus accumbens dopamine concentration during intravenous cocaine self-administration in rats. Psychopharmacology 120:10–20. Wood, M.D., Boyfield, I., Nash, D.J., Jewitt, F.R., Avenell, K.Y., and Riley, G.J. (2000) Evidence for antagonist activity of the dopamine D3 receptor partial agonist, BP 897, at human dopamine D3 receptor. Eur. J. Pharmacol. 407:47–51. Woolverton, W.L., Rowlett, J.K., Wilcox, K.M., Paul, I.A., Kline, R.H., Newman, A.H., and Katz, J.L. (2000) 3'- and 4'-Chlorosubstituted analogs of benztropine: intravenous self-administration and in vitro radioligand bindings studies in rhesus monkeys. Psychopharmacology 147:426–435. Xi, Z.-X., and Gardner, E.L. (2007) Pharmacological actions of NGB 2904, a selective dopamine D3 receptor antagonist, in animal models of drug addiction. CNS Drug Rev. 2:240–259. Xi, Z.-X., Gilbert, J.G., Campos, A.C., Kline, N., Ashby, C.R., Jr., Hagan, J.J., Heidbreder, C.A., and Gardner, E.L. (2004) Blockade of mesolimbic dopamine D3 receptors inhibits stress-induced reinstatement of cocaine-seeking in rats. Psychopharmacology 176:57–65. Xi, Z.-X., Gilbert, J.G., Pak, A.C., Ashby, C.R., Jr., Heidbreder, C. A., and Gardner, E.L. (2005) Selective dopamine D3 receptor antagonism by SB-277011A attenuates cocaine reinforcementas assessed by progressive-ratio and variable-ratio—variable-payoff fixed-ratio cocaine self-administration in rats. Eur. J. Neurosci. 21:3427–3438. Xi, Z.-X., Gilbert, J.G., Peng, X.-Q., Ashby, C.R., Jr., Heidbreder, C.A., and Gardner, E.L. (2007) Blockade of dopamine D3 receptors by SB-277011A inhibits incubation of craving for cocaine in rats. Paper presented at the 69th annual meeting of the College on Problems of Drug Dependence, Quebec City, Canada. Xi, Z.-X., Newman, A.H., Gilbert, J.G., Pak, A.C., Peng, X.-Q., Ashby, C.R. Jr., Gitajn, L., and Gardner, E.L. (2006) The novel dopamine D3 receptor antagonist NGB 2904 inhibits cocaine’s rewarding effects and cocaine-induced reinstatement of drugseeking behavior in rats. Neuropsychopharmacology 31:1393– 1405. Xi, Z.-X., Ramamoorthy, S., Shen, H., Lake, R., Samuvel, D.J., and Kalivas, P.W. (2003) GABA-transmission in the nucleus accumbens is altered after withdrawal from repeated cocaine. J. Neurosci. 23:3498–3505.

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SUBSTANCE ABUSE DISORDERS

Xi, Z.-X., and Stein, E.A. (1998) Nucleus accumbens dopamine release modulation by mesolimbic GABAA receptors—an in vivo electrochemical study. Brain Res. 798:156–165. Xi, Z.-X., and Stein, E.A. (1999) Baclofen inhibits heroin selfadministration behavior and mesolimbic dopamine release. J. Pharmacol. Exp. Ther. 290:1369–1374. Xi, Z.-X., and Stein, E.A. (2000) Increased mesolimbic GABA concentration blocks heroin self-administration in the rat. J. Pharmacol. Exp. Ther. 294:613–619.

Yan, Q.-S. (1999) Focal bicuculline increases extracellular dopamine concentration in the nucleus accumbens of freely moving rats as measured by in vivo microdialysis. Eur. J. Pharmacol. 385:7–13. Yokel, R.A., and Pickens, R. (1974) Drug level of d- and l-amphetamine during intravenous self-administration. Psychopharmacologia 34: 255–264. Yokel, R.A., and Wise, R.A. (1975) Increased lever-pressing for amphetamine after pimozide in rats: implications for a dopamine theory of reward. Science 187:547–549.

46 Cellular and Molecular Mechanisms of Drug Addiction ERIC J. NESTLER

This chapter provides an overview of recent progress made in understanding the molecular basis of drug addiction. After terms commonly used in the field are defined, a brief description of the mechanisms by which drugs of abuse influence synaptic transmission after an acute exposure is provided. Next described are the types of gradually developing, progressive changes that repeated exposure to drugs of abuse can induce in specific brain regions that appear to underlie aspects of addiction. DEFINITION OF TERMS Drug addiction is often defined by the pharmacological terms tolerance, sensitization, dependence, and withdrawal. Tolerance refers to the situation where repeated administration of a drug at the same dose elicits a diminishing effect or the need for an increasing drug dose to produce the same effect. Sensitization, or “reverse tolerance,” refers to the opposite situation where repeated administration of the same drug dose elicits an escalating effect. The same drug can elicit simultaneously tolerance and sensitization to its many different effects. Dependence is defined as the need for continued drug exposure to avoid a withdrawal syndrome, characterized by physical or emotional disturbances when the drug is withdrawn. Each of these responses to repeated drug exposure is presumably caused by molecular and cellular adaptations that the drug produces in specific brain regions. It is important to emphasize that tolerance, sensitization, dependence, and withdrawal are not associated uniquely with drugs of abuse; many medications used clinically that are not addicting (for example, clonidine, propranolol, and tricyclic antidepressants, to name a few) can also produce these effects. Drugs of abuse are unique, however, in terms of their reinforcing properties, described in greater detail in Chapter 45. A drug is classified as a reinforcer if the probability of a drug-seeking response is increased when the response is temporally paired with drug exposure. Upon acute exposure, most abused drugs function as positive reinforcers; this probably involves positive af-

fective responses (for example, euphoria) to the drug, although reinforcement per se may well be distinct from euphoria. Rapid and powerful associations between a drug reinforcer and a drug-seeking response reflect the drug’s ability to directly modulate preexisting brain reinforcement mechanisms, which normally mediate the reinforcement produced by natural reinforcers such as food, sex, and social interaction (Wise, 1998; Koob and LeMoal, 2001; Everitt and Wolf, 2002; Kelley and Berridge, 2002; Hyman et al., 2006). Chronic exposure to reinforcing drugs can lead to drug addiction, best defined as the compulsive seeking (drug craving) and administration of a drug despite grave adverse consequences or as a loss of control over drug intake. The drug-seeking behavior that characterizes drug addiction is different from that seen with acute drug reinforcement, in that addicted individuals exhibit a sustained increase in drug-seeking behavior even when the drug is absent or withdrawn for prolonged periods of time. In this chronic context, a drug may serve not only as a positive reinforcer but also as a negative reinforcer by reducing negative emotional symptoms that can persist long after drug taking ceases. Addictive disorders are often defined clinically as a state of dependence, for example, in the Diagnostic and Statistical Manual of Mental Disorders (published by the American Psychiatric Association). However, it is important to emphasize that in more precise pharmacological terms, we do not yet know the types of neurobiological changes that are responsible for the compulsive drug-seeking behavior that is the clinical hallmark of an addictive disorder. There is evidence that drug craving involves adaptations that underlie the aversive motivational symptoms (for example, dysphoria, anxiety) associated with drug dependence and withdrawal. There also is evidence that drug craving involves adaptations that underlie tolerance to a drug’s reinforcing effects, which might be expected to contribute to the pattern of escalating drug intake often seen clinically. In addition, considerable evidence suggests that drug craving involves adaptations that underlie sensitization to the acute reinforcing effects of a drug and to the priming 775

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effects of a drug or its conditioned cues. These various mechanisms are not mutually exclusive, as complex combinations of them are likely to account for drug addiction. THE SYNAPSE AS THE ACUTE TARGET OF DRUGS OF ABUSE Our understanding of the pharmacological effects of drugs of abuse on the brain has focused on the synapse as the acute target of drug action. All drugs of abuse affect the brain initially by influencing the amount of a neurotransmitter present at the synapse or by interacting with specific neurotransmitter receptors. Table 46.1 lists examples of such acute pharmacological actions of some commonly used drugs of abuse. Opiates are agonists at μ and δ opioid receptors. Cocaine increases synaptic levels of dopamine (DA), serotonin, and norepinephrine (NE) by inhibiting the presynaptic (reuptake) transporters for these monoamines. Amphetamine and its derivatives also increase synaptic levels of the monoamines, but via a distinct mechanism: by increasing monoamine release. Amphetamine itself serves

46.1 Examples of Acute Pharmacological Actions of Drugs of Abuse

TABLE

Drug

Action

Opiates

Agonist at μ, δ, and κ opioid receptorsa

Cocaine

Inhibits dopamine reuptake transportersb

Amphetamine

Stimulates dopamine releaseb

Ethanol

Facilitates GABA-A receptor function and inhibits NMDA glutamate receptor functionc

Nicotine

Agonist at nicotinic acetylcholine receptors

Cannabinoidsa

Agonist at cannabinoid receptorsd

Hallucinogens

Partial agonist at 5-HT2A serotonin receptors

Phencyclidine (PCP)

Antagonist at NMDA glutamate receptors

Inhalants

Unknown

Activity at μ and δ receptors mediates the reinforcing actions of opiates; activity at κ receptors can produce aversion. bCocaine and amphetamine exert analogous actions on serotonergic and noradrenergic systems, which may also contribute to the reinforcing effects of these drugs. cEthanol affects several other ligand-gated channels and, at higher concentrations, voltage-gated channels as well. In addition, ethanol is reported to influence many other neurotransmitter systems, including serotonergic, opioidergic, and dopaminergic systems. It is not known whether these effects are direct or achieved indirectly via actions on various ligand-gated channels. dActivity at CB receptors mediates the reinforcing actions of cannabinoids. 1 Proposed endogenous ligands for the CB1 receptor include the arachidonic acid metabolites, anandamide and 2-arachidonylglycerol. GABAA: γ -aminobutyric acid-A; 5-HT2A: 5-hydroxytryptamine-2A; NMDA: N-methyl-D-aspartate. a

as a substrate for all three monoamine transporters and is transported into monoaminergic nerve terminals, where it disrupts the storage of the monoamine neurotransmitters. This leads to an increase in extravesicular levels of the monoamines and to the reverse transport of the monoamine into the synaptic cleft via the transporters. The best established acute action of ethanol is its ability to facilitate activation of the γ -aminobutyric acidA (GABA-A) receptor by GABA. This action is similar to that of the benzodiazepines and all other sedativehypnotic drugs. The GABA-A receptor is a heteromeric complex (see Chapters 2 and 3); the ability of ethanol and sedative hypnotics to facilitate receptor function depends on the actual subunit composition of the receptor, which differs markedly throughout the brain. Although these drugs interact with the GABA-A receptor at apparently distinct sites, the fact that they converge on the functioning of the same protein complex no doubt explains the long-appreciated cross-tolerance and cross-dependence exhibited by these drugs. Ethanol, unlike other sedativehypnotics, also exerts potent effects on the N-methyl-Daspartate (NMDA) glutamate receptor. Ethanol inhibits the functioning of the receptor, again, not by blocking the glutamate binding site but via a more complex allosteric effect on the receptor complex, which results in diminished glutamate-induced Na+ and Ca2+ flux through the receptor ionophore. Ethanol antagonism of the NMDA receptor appears to contribute to the intoxicating effects of ethanol and perhaps to the dissociative effects seen in people with high ethanol blood levels. Whether ethanol antagonism of the NMDA receptor also contributes to its reinforcing effects remains to be established. At still higher doses, ethanol can exert more general inhibitory effects on other ligand-gated channels as well as on voltagegated ion channels, particularly Na+ and Ca2+ channels. These actions occur only at the extremely high concentrations seen clinically and therefore do not appear to be involved in the reinforcing actions of ethanol, although they may contribute to the severe nervous system depression, and even coma, seen at these blood levels. The fact that drugs of abuse initially influence different neurotransmitter and receptor systems in the brain explains the very different actions produced by these drugs acutely. This is illustrated in Figure 46.1. For example, the presence of very high levels of opioid receptors in the brain stem and spinal cord explains why opiates can exert such profound effects on respiration, level of consciousness, and nociception. In contrast, the importance of noradrenergic mechanisms in the regulation of cardiac function explains why cocaine can exert such profound cardiotoxic effects. In contrast to the many disparate acute actions of drugs of abuse, the drugs do appear to exert some common behavioral effects: as discussed above, they are all positively reinforcing after acute exposure. This suggests that there are certain regions of the brain where

46: CELLULAR AND MOLECULAR MECHANISMS OF DRUG ADDICTION

46.1 Scheme illustrating how initial divergent actions of drugs of abuse can converge on a common neural substrate. Opiates, cocaine, and ethanol act on different initial protein targets. As a result, the drugs elicit very different effects after acute administration because the targets are distributed differentially throughout the central nervous system. However, the targets are each present in the mesolimbic dopamine system, and drug action on the targets results in common functional effects within this system (that is, drug reinforcement). GABA: γ -aminobutyric acid; NMDA: N-methyl-D-aspartate.

FIGURE

the distinct, acute pharmacological actions of the drugs converge in producing the common effect of reinforcement (Fig. 46.1). That is, in certain regions of the brain, which are discussed below, activation of opioid receptors (by opiates), inhibition of monoamine reuptake (by cocaine), or facilitation of GABAergic and inhibition of NMDA glutamatergic neurotransmission (by ethanol) appear to elicit some common responses that mediate drug reinforcement. MOLECULAR AND CELLULAR ADAPTATIONS TO DRUGS OF ABUSE The acute pharmacological actions of a drug of abuse do not per se explain the long-term effects of repeated drug exposure such as addiction. To understand such long-term effects, it is necessary to consider postreceptor intracellular messenger pathways and a neuron’s longterm adaptations to repeated perturbations (see Chapters 4–6). This means that, despite the initial actions of drugs of abuse on extracellular aspects of synaptic function (receptors, transporters, neurotransmitter levels, etc.), the many actions that the drugs exert on brain function are achieved ultimately through the complex network of intracellular messenger pathways that mediates these extracellular mechanisms. Moreover, repeated exposure to drugs of abuse would be expected to produce repeated perturbation of these intracellular pathways, which presumably triggers the many types of molecular and cellular adaptations throughout the brain responsible for tolerance, sensitization, dependence, withdrawal, and, ultimately, addiction.

777

A major advantage of the drug abuse field, as opposed to studies of other mental disorders, is that a great deal is known about the neural circuits in the brain responsible for the behavioral abnormalities that characterize addictive disorders. This knowledge has resulted from the availability of increasingly sophisticated animal models of addiction, described in Chapter 45, which replicate many key features of drug addiction seen clinically. The development of such animal models, in turn, has been facilitated by the fact that drugs of abuse are clear etiological factors in drug addiction, whereas etiological factors for other mental disorders are not yet known with certainty. One of the most important neural circuits involved in addiction is the mesolimbic DA system, which is composed of dopaminergic neurons in the ventral tegmental area (VTA) of the midbrain and the limbic forebrain regions to which these neurons project, most notably the nucleus accumbens (NAc; also called ventral striatum) (Wise, 1998; Koob and LeMoal, 2001). There is now a wealth of evidence that the VTA– NAc pathway is a crucial substrate for the acute rewarding effects of virtually all drugs of abuse and for the derangements in reward mechanisms that contribute to drug addiction. The amygdala appears particularly important in mediating the cue-conditioning effects of drugs of abuse, whereby drug-associated cues elicit powerful drug craving or withdrawal-like symptoms even after prolonged abstinence (Everitt et al., 2001). Another memory-associated brain region, the hippocampus, likely also contributes to the powerful memories of addiction that drive drug seeking and relapse. Regions of frontal cortex, for example, orbitofrontal cortex or medial prefrontal cortex, which normally mediate executive function, are also affected by drugs of abuse: reduced function of these regions is thought to mediate the increased impulsivity and compulsivity associated with addictive states (Kalivas et al., 2005). All of these brain structures, and many others, operate as functionally interconnected circuits, in which druginduced alterations in their functioning mediate a state of addiction (Hyman et al., 2006). Based on this impressive knowledge of the neural substrates of drug abuse and addiction, it has been possible to focus efforts on identifying drug-induced changes, at the molecular and cellular levels, within these specific brain regions that underlie the behavioral abnormalities used to define addiction-like behavior in animal models. The remainder of this chapter discusses the types of molecular and cellular adaptations in reward-related brain regions that have been shown to play important roles in animal models of drug addiction. This chapter cannot be comprehensive due to space limitations. Rather, the sections that follow outline examples of some of the most characterized adaptations implicated in drug addiction. An interesting outcome of this research is that several types of drugs of abuse

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produce some common molecular and cellular adaptations within reward-related brain regions, which has suggested common general mechanisms of drug addiction (Fig. 46.2) in addition to numerous adaptations specific for each addictive substance (Nestler, 2005).

FIGURE 46.2 Highly simplified scheme of some common, chronic actions of drugs of abuse on the VTA-NAc circuit. The top panel (Control) shows a VTA neuron innervating a NAc neuron, and cortical glutamatergic inputs to the VTA and NAc neurons, under normal conditions. After chronic drug administration, several adaptations occur. In the VTA, drug exposure induces TH and increases AMPA glutamatergic responses (Glut), possibly via induction of GluR1 and altered trafficking of AMPA receptors. Also, VTA dopamine neurons decrease in size, an effect demonstrated thus far with chronic opiates only, but presumed for other drugs of abuse due to common associated biochemical adaptations (for example, reduced levels of neurofilament proteins). Induction of CREB activity, and alterations in NTF signaling may partly mediate these various effects. In the NAc, all drugs of abuse induce the transcription factor ΔFosB, which may then mediate some of the shared aspects of addiction via regulation of numerous target genes. Several, but not all, drugs of abuse also induce CREB activity in this region, which may be mediated via up-regulation of the cAMP pathway. Several additional changes have been found for stimulant exposure; it is not yet known whether they generalize to other drugs. Stimulants decrease AMPA glutamatergic responses in NAc neurons, possibly mediated via induction of GluR2 or repression of several postsynaptic density proteins (for example, PSD95, Homer-1). These changes in postsynaptic glutamate responses are associated with complex changes in glutamatergic innervation of the NAc, including reduced glutamatergic transmission at baseline and in response to normal rewards, but enhanced transmission in response to cocaine and associated cues, effects possibly mediated in part via up-regulation of AGS3 (activator of G protein signaling) in cortical neurons and down-regulation of the cystine-glutamate transporter (system xc-) in glia. Stimulants and nicotine also induce dendritic outgrowth of NAc neurons, although opiates are reported to produce the opposite action. The net effect of this complex dysregulation in glutamate function and synaptic structure is not yet known. From Nestler, 2005. VTA: ventral tegmental area; NAc: nucleus accumbens; TH: tyrosine hydroxylase; AMPA: α-amino-3-hydroxy-5methyl-4-isoxasolepropionic acid; CREB: cyclic adenosine monophosphate [cAMP]-response element binding; NTF: neurotrophic factor.

Up-regulation of the cAMP-CREB Pathway in the VTA-NAc One of the best-established molecular mechanisms of drug tolerance and dependence is up-regulation of the cAMP (cyclic adenosine monophosphate) second-messenger and protein phosphorylation pathway (Nestler and Aghajanian, 1997). As reviewed in Chapter 4, this pathway mediates the effects of numerous G protein–coupled receptors, including opioid, DA, and cannabinoid receptors, on neuronal function. According to this hypothesis, depicted in Figure 46.3, prolonged exposure to a drug of abuse, which activates receptors that inhibit the cAMP pathway, triggers compensatory adaptations that oppose this inhibition and restores cAMP pathway function to normal levels. For example, the affected cells make more adenylyl cyclase (the enzyme that catalyzes the synthesis of cAMP) and more protein kinase A (PKA; the enzyme that mediates most of the effects of cAMP on cell function). In the continued presence of the drug, such adaptations mediate tolerance. Upon removal of the drug, the up-regulated cAMP pathway becomes fully functional and mediates aspects of dependence and withdrawal. Such up-regulation of the cAMP pathway, first demonstrated in cultured cells and later characterized more

FIGURE 46.3 Up-regulation of the cAMP pathway as a mechanism of opiate tolerance and dependence. Opiates acutely inhibit the functional activity of the cAMP pathway (indicated by cellular levels of cAMP and cAMP-dependent protein phosphorylation). With continued opiate exposure, functional activity of the cAMP pathway gradually recovers and increases far above control levels following removal of the opiate (for example, by administration of the opioid receptor antagonist naloxone). These changes in the functional state of the cAMP pathway are mediated via the induction of adenylyl cyclase and PKA in response to chronic administration of opiates. Induction of these enzymes accounts for the gradual recovery in the functional activity of the cAMP pathway that occurs during chronic opiate exposure (tolerance) and activation of the cAMP pathway observed upon removal of opiate (dependence and withdrawal). From Nestler, 2004. cAMP: cyclic adenosine monophosphate; PKA: protein kinase A.

46: CELLULAR AND MOLECULAR MECHANISMS OF DRUG ADDICTION

fully in noradrenergic neurons of the locus coeruleus, has now been found in diverse neuronal cell types in the central and peripheral nervous systems in response to chronic exposure to any of several drugs of abuse (Nestler, 2004). Accordingly, this adaptation mediates diverse aspects of drug addiction, depending on the neurons affected (Table 46.2). In the locus coeruleus, for example, up-regulation of the cAMP pathway, seen in response to chronic opiate administration, mediates aspects of physical opiate dependence and withdrawal, while in the NAc, up-regulation of the cAMP pathway in response to chronic opiate, cocaine, amphetamine, or ethanol administration mediates tolerance and dependence in reward mechanisms and is, therefore, an example of a common mechanism of drug addiction mentioned earlier (Fig. 46.2). Drug-induced up-regulation of the cAMP pathway is mediated, in part, via the transcription factor CREB (cAMP response element binding protein). Thus, opiate or stimulant exposure activates CREB in several brain regions, where it serves, among other actions, to increase expression of adenylyl cyclase or PKA isoforms (Nestler and Aghajanian, 1997). Drug regulation of CREB was first discovered in the locus coeruleus and shown, like the up-regulated cAMP pathway, to mediate opiate physical dependence and withdrawal. In contrast, CREB activation in the NAc, in response to opiates or stimulants, mediates tolerance and dependence in drug reward. Drug regulation of CREB in the NAc has received particular attention as a common mechanism of addiction, where its role in the addiction process has been characterized by use of advanced molecular biology tools discussed in Chapter 7. Overexpression of CREB in the NAc, by use of viral-mediated gene transfer or of inducible bitransgenic mice, which mimics drug activation of the protein in this region, decreases an animal’s 46.2 Upregulation of the cAMP Pathway in Opiate Addiction

TABLE

Site of Up-regulation

Functional Consequence

Locus coeruleus

Physical dependence and withdrawal

Ventral tegmental area

Dysphoria during early withdrawal periods

Periaqueductal gray

Dysphoria during early withdrawal periods, and physical dependence and withdrawal

Nucleus accumbens

Dysphoria during early withdrawal periods

Amygdala

Conditioned aspects of addiction

Dorsal horn of spinal cord

Tolerance to opiate-induced analgesia

Myenteric plexus of gut

Tolerance to opiate-induced reductions in intestinal motilityand increases in motility during withdrawal

From Nestler, 2004.

779

sensitivity to the rewarding effects of drugs of abuse (Nestler, 2004; Carlezon et al., 2005). Conversely, blockade of CREB function in this brain region, by overexpression of a dominant negative mutant of CREB (termed mCREB), has the opposite effect. Studies of constitutive CREB knockout mice generally support these overexpression findings (Walters and Blendy, 2001). Together, these investigations substantiate a role for CREB as a homeostatic feedback mechanism that decreases an animal’s responses to subsequent drug exposure. Activation of CREB also induces a negative emotional state, characterized by anhedonia-like symptoms (decreased responses to natural rewards) and increased depressionlike behavior in animal models. These findings support the view that CREB activation by drugs of abuse contributes to aversive symptoms that characterize drug withdrawal states. A recent study has shown that this emotional state induced by CREB contributes to increased drug self-administration, presumably as an effort to overcome the aversive symptoms (Choi et al., 2006). One of the target genes through which CREB, in the NAc, decreases drug reward and produces negative emotional symptoms is the opioid peptide dynorphin (Carlezon et al., 2005). Dynorphin is expressed by a subset of NAc medium spiny neurons. When released, dynorphin activates μ opioid receptors present on VTA DA neuron terminals, where it inhibits DA release (Kreek, 1996; Shippenberg et al., 2001). Dynorphin is therefore part of a feedback loop, which dampens further DA-mediated reward. Activation of CREB in the NAc leads to induction of the dynorphin gene, which increases the gain on this feedback loop and thereby reduces drug reward and induces a negative emotional state. These findings have led to the suggestion that μ opioid antagonists might be of use in treating drug withdrawal states and may also represent a novel treatment for depression (McLaughlin et al., 2003; Carlezon et al., 2005). Chronic exposure to opiates, cocaine, or nicotine induces CREB in the VTA as well, where the behavioral effects are more complex (Olson et al., 2005; Walters et al., 2005). Here, CREB activation can either promote or oppose drug reward mechanisms based on the subregion of the VTA involved. Work is under way to identify target genes for CREB in this region that mediate these effects. Regulation of Opioid and Dopamine Receptor Sensitivity in the VTA–NAc A mechanism of drug tolerance, which has gained increasing attention in recent years, is drug-induced alteration of the physiological responsiveness of opioid, DA, or other G protein–coupled receptors in the VTA– NAc circuit (Fig. 46.4). Chronic exposure to certain opiate drugs down-regulates opioid receptors, and pro-

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longed activation of DA receptors (for example, as seen after cocaine or amphetamine administration) leads to their down-regulation as well. The best-established mechanism of such receptor tolerance involves the functional uncoupling of the receptors from their G proteins via their phosphorylation by G protein–coupled receptor kinase (GRKs). According to this mechanism, the binding of an agonist to a G protein–coupled receptor induces a conformational change in the receptors that render them good substrates for these kinases (Chavkin et al., 2001; von Zastrow et al., 2003). The phosphorylated receptors then bind arrestin, which triggers internalization of the receptor-arrestin complex via a dynamin-dependent pathway (Chapter 5). Another proposed mechanism of receptor tolerance involves druginduced down-regulation of G protein subunits (for example, G a i), which has been observed in several neuronal cell types. A related possibility is that drugs regulate a newly characterized class of signaling protein, regulators of G protein–signaling proteins (RGSs), which regulate the guanosine triphosphate (GTP)ase activity of G protein a subunits and, consequently, the efficacy of receptor signaling (Zachariou et al., 2003). It will be important for future studies to establish the functional role played by these various types of adaptations in receptor signaling within the mesolimbic DA system

FIGURE 46.4 Scheme illustrating possible mechanisms of drug-induced changes in opioid or D2-like dopamine receptor sensitivity. Druginduced adaptations in the efficacy of receptor-Gi/o coupling could contribute to aspects of drug tolerance or sensitization. One possible mechanism is adaptations in processes that mediate acute desensitization of receptor function, such as receptor phosphorylation GRKs and subsequent receptor internalization (1). Other possible mechanisms include alterations in levels of G protein a (2) or bg (3) subunits or of other proteins (for example, phosducin [4]; RGS proteins [5]) that modulate G protein function. Phosphorylation of the receptor by PKA does not mediate acute receptor desensitization (because receptor activation leads to inhibition of the kinase). However, up-regulation of the kinase (6) after chronic drug administration (Fig. 46.3) could phosphorylate and regulate receptor function during withdrawal states. From Nestler and Aghajanian (1997). GRKs: G protein– receptor kinases; RGS: regulators of G protein signaling; PKA: protein kinase A; MAP: mitogen-activated protein.

and other reward-related brain regions in drug abuse models in vivo. Synaptic Plasticity and Regulation of Glutamatergic Systems in the VTA–NAc Although a great deal of attention has focused on drug regulation of DA neurotransmission from the VTA to the NAc, a major advance over the past decade has been an increased appreciation of the importance of glutamatergic innervation to both of these brain regions and the regulation of this excitatory transmission by drugs of abuse. Major glutamatergic inputs to the VTA arise from frontal regions of cerebral cortex and from the peduncular pontine tegmentum and lateral dorsal tegmentum. Major glutamatergic inputs to the NAc arise from frontal cortex, hippocampus, and amygdala. An exciting finding is that virtually any type of drug of abuse induces a long-term potentiation (LTP)–like phenomenon at glutamatergic synapses in the VTA, while cocaine and other stimulants induce long-term depression (LTD)– like changes in the NAc (Thomas and Malenka, 2003; Kauer, 2004). Recent work has focused on the molecular mechanisms by which drugs induce these examples of synaptic plasticity in the VTA–NAc circuit. In the VTA, where drugs enhanced glutamatergic transmission, there is evidence that chronic exposure to drugs of abuse promotes the insertion of AMPA glutamate receptors into active postsynaptic sites of DA neurons in this brain region. There is also evidence that drugs induce the expression of certain α-amino-3-hydroxy-5-methyl-4-isoxasolepropionic acid (AMPA) receptor subunits, for example, GluR1 (Carlezon and Nestler, 2002). Indeed, this induction may be mediated via CREB. The situation is more complicated in the NAc, where drugs are reported to dampen glutamatergic-dependent synaptic plasticity (Wolf, 1998; Sutton et al., 2003; Kalivas, 2004). Here, there remains controversy in the literature concerning whether chronic drug exposure enhances or diminishes glutamatergic neurotransmission, with increases and decreases in glutamate receptor subunits reported. Moreover, there is evidence for increased insertion of AMPA receptors into postsynaptic sites, which is correlated with sensitized behavioral responses to drug (Boudreau and Wolf, 2005). As well, drugs of abuse have been shown to alter the expression of an array of modulatory proteins, located at postsynaptic sites in the NAc, which regulate the activity, stability, or localization of AMPA and NMDA receptors. Some of the drug-induced changes in glutamate receptor subunit expression have been related to induction of CREB or another transcription factor, ΔFosB, as is discussed in the next section. It is likely that drugs also alter glutamergic transmission, and mechanisms of synaptic plasticity in many

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other brain regions, such as frontal cortex, amygdala, and hippocampus, to name a few (see below), although these changes are not as well characterized as similar mechanisms in the VTA–NAc. Induction of ΔFosB in the NAc ΔFosB is a member of the Fos family of transcription factors, which dimerize with a Jun family member to form an active AP-1 (activator protein-1) transcription factor complex. Acute exposure to virtually any drug of abuse rapidly induces c-Fos and all other Fos family members in the NAc and dorsal striatum, with maximal induction seen 2–4 hours after drug administration. Due to the instability of these proteins and their messenger ribonucleic acids (mRNAs), this induction is highly transient, with levels of the transcription factors returning to basal levels within 8–12 hours. ΔFosB shows dramatically different temporal properties of induction. Like the other Fos family members, it is induced rapidly in response to an acute drug exposure, but only to a slight degree (see Fig. 6.7 in Chapter 6). However, unlike all other Fos family proteins, ΔFosB is unusually stable. As a result, during a course of chronic drug administration, ΔFosB protein levels gradually accumulate to high levels in NAc and dorsal striatal neurons and become by far the predominant Fos family protein present (Nestler et al., 2001; McClung et al., 2004). ΔFosB’s stability also means that it persists in these neurons long after cessation of drug intake. ΔFosB thereby provides a novel mechanism by which chronic exposure to drugs of abuse produces long-lasting changes in gene expression even after prolonged withdrawal. The unusual stability of ΔFosB is due to at least two recently discovered mechanisms. ΔFosB is derived from the FosB gene via alternative splicing. Another product of the gene is full-length FosB, which behaves like other Fos family members. The only difference between ΔFosB and FosB is that ΔFosB lacks the terminal 101 amino acids present in the C-terminal end of FosB. Recent work has shown that this C-terminal domain contains two degrons that target full-length FosB to rapid degradation via proteosomal and nonproteosomal mechanisms (Carle et al., 2007). All other Fos family proteins possess similar degrons domains, which are lacking uniquely in ΔFosB. As well, ΔFosB is further stabilized by its phoshorylation at its N-terminus by casein kinase 2 (CK2) and perhaps other protein kinases (Ulery et al., 2006). These biochemical properties offer unique ways to possibly intervene to disrupt the prolonged effects of ΔFosB, for example, CK2 inhibitors, as potential treatments for drug addiction. There is now substantial evidence that induction of ΔFosB in the NAc by drugs of abuse mediates a sensitized state: increased sensitivity to the rewarding effects of drugs of abuse as well as increased incentive

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motivation to self-administer the drugs (Kelz et al., 1999; Colby et al., 2003; McClung et al., 2004; Zachariou et al., 2006). ΔFosB similarly enhances motivation for natural rewards, such as wheel running and sucrose. A great deal of effort has been expended to identify the target genes through which ΔFosB produces this interesting behavioral state. Early estimates are that ΔFosB may account for more than 25% of all the genes whose expression is altered by chronic cocaine administration (McClung and Nestler, 2003). One target gene is cyclindependent kinase 5 (Cdk5): its induction by cocaine and ΔFosB appears to be one mechanism underlying cocaine’s regulation of NAc neuronal morphology (see next section). Another target gene is the AMPA glutamate receptor GluR: its regulation may be part of the molecular mechanisms involved in drug regulation of glutamatergic transmission as outlined earlier. Neurotrophic Mechanisms, Regulation of Neuronal Morphology in the VTA–NAc Recent models of neural plasticity have increasingly implicated changes in neural morphology and synaptic structure in functional adaptations in the nervous system. As just one example, LTP has been associated with increases in the density of dendritic spines on hippocampal neurons (Yuste and Bonhoeffer, 2001). It is not surprising, then, that neurotrophic mechanisms and morphological adaptations have also been implicated in the neural plasticity associated with drug addiction. For example, chronic administration of morphine decreases the size of VTA DA neuron cell bodies as well as axonal transport from the VTA to the NAc (Sklair-Tavron et al., 1996; Russo et al., 2007). These changes are associated with decreased levels of neurofilament proteins and increased levels of glial fibrillary acidic protein (GFAP) in the VTA. Decreased levels of neurofilaments and increased levels of GFAP are often a sign of neural insult or injury, consistent with the morphological changes seen in VTA DA neurons in the drug-treated state (Fig. 46.2). Recent evidence suggests that the reduction in DA cell size in response to chronic morphine is a mechanism of drug tolerance (Russo et al., 2007). Morphological changes have also been observed in the NAc. Chronic administration of several types of stimulants, for example, cocaine, amphetamine, or nicotine increases the density of dendritic spines of NAc medium spiny neurons (Robinson and Kolb, 2004). These changes are similar to those observed in hippocampal neurons in concert with LTP, with one important difference: the changes associated with LTP are relatively short lived, whereas the changes induced by stimulants persist for at least 1 month after drug withdrawal. Although direct evidence linking drug-induced dendritic spine increases in the NAc to altered physiological function of the neurons is lacking, it is tempting to specu-

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late that such morphological changes might contribute to sensitized responses to drug exposure (Fig. 46.5). Moreover, there is evidence that stimulants induce dendritic outgrowth in NAc neurons via induction of ΔFosB and via ΔFosB’s induction of Cdk5 (Norrholm et al., 2003; Lee et al., 2006). Thus, prolonged induction of dendritic spines after chronic cocaine occurs in ΔFosB+ cells and can be prevented by local infusion of a Cdk5 inhibitor. However, the connection between increased dendritic spine density and sensitization remains less certain, given that fact that opiates reportedly decrease dendritic outgrowth in the NAc despite the fact that they clearly induce sensitization (Robinson and Kolb, 2004), and inhibition of Cdk5, while it blocks cocaine’s effects on dendritic spines and increases rather than decreases behavioral responses to the drug (Taylor et al., 2007). Thus, further work is needed to understand the functional consequences of drug-induced morphological changes in the NAc. Identification of drug-induced morphological changes in the VTA and NAc raises the critical question of the underlying molecular mechanisms involved. Possible mediators of these effects are various neurotrophic factors. Although such factors were studied originally for their role in neural growth and differentiation during development, they are now known to regulate signal transduction and neuronal viability in the fully differentiated adult brain (see Chapters 2 and 4). Indeed, there is now direct evidence that several types of neurotrophic factors, including brain-derived neurotrophic factor (BDNF), glial cell line–derived neurotrophic factors (GDNF), and fibroblast growth factor (FGF), among

FIGURE 46.5 Regulation of dendritic structure by drugs of abuse. The figure shows the expansion of a neuron’s dendritic tree after chronic exposure to a drug of abuse, as has been observed in the NAc and prefrontal cortex for cocaine and related psychostimulants. The areas of magnification show an increase in dendritic spines, which is postulated to occur in conjunction with activated nerve terminals. Such alterations in dendritic structure, which are similar to those observed in some learning models (for example, LTP), could mediate long-lived sensitized responses to drugs of abuse or environmental cues. There is evidence that, in the NAc, the cocaine-induced increase in dendritic spines may be mediated via ΔFosB and its induction of Cdk5. NAc: nucleus accumbens; LTP: long-term potentiation; Cdk5: cyclin-dependent kinase-5.

others, acting at the level of the VTA or NAc, can modify an animal’s molecular, cellular, and behavioral responses to drugs of abuse, and that chronic drug exposure can modify these neurotrophic factors or their signaling pathways (see Pierce and Bari, 2001; Bolaños and Nestler, 2004). For example, the ability of morphine to decrease the size of VTA DA neurons has been demonstrated recently to be mediated via morphine-induced downregulation of one of the main signaling pathways for BDNF: the insulin receptor substrate (IRS)-phosphatidylinositol-3-kinase (PI-3-kinase)-protein kinase B (Akt) pathway (Russo et al., 2007). Although further work is clearly needed to better delineate the relationship between drugs of abuse and neurotrophic factors, this line of investigation has provided new information concerning the mechanisms underlying drug addiction and has suggested novel ways to approach its treatment. Regulation of Chromatin Remodeling Mechanisms Recent years have brought explosive increases in our knowledge of how changes in gene expression are associated with changes in chromatin structure. Most of this work has come from the cancer and developmental biology fields and only recently has been applied to neural plasticity in the adult brain (Tsankova et al., 2007). Chromatin remodeling, discussed in greater detail in Chapter 8, refers to posttranslational modifications of histones (for example, acetylation, phosphorylation, and many others), as well as methylation of deoxyribonucleic acid (DNA) itself, which is associated with activation or repression of a given gene. Studies of chromatin remodeling is a high priority for the drug abuse field for two reasons. First, chromatin remodeling, studied with chromatin immunoprecipitation (ChIP) assays, offers the first-ever window into mechanisms of gene regulation within the brain in vivo. For example, this work has made it possible for the first time to study directly whether a particular gene is activated or repressed in the NAc in vivo in addiction models and to identify associated transcription factors. In contrast, before ChIP, it was possible to identify changes in steady state mRNA levels in vivo, but then all studies of mechanisms relied on in vitro investigations. This has been a huge inherent weakness in the field. Second, certain changes in chromatin structure are particularly long lived and hence provide an attractive mechanism by which drugs of abuse cause long-lasting changes in gene expression and, consequently, behavior. To date, a small number of studies have implicated chromatin remodeling in drug abuse models. Acute or chronic administration of cocaine has been shown to increase global levels of histone acetylation (a marker of gene activation) in striatum, with selective increases demonstrated at several specific genes of interest, including c-Fos, FosB, Cdk5, and BDNF (Brami-Cherrier

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et al., 2005; Kumar et al., 2005; Levine et al., 2005). Such ChIP studies have confirmed a role for ΔFosB in directly activating the Cdk5 gene, as inferred from earlier studies (see above). Binge cocaine exposure to adolescent rats causes increased sensitivity to cocaine in adults, which is associated with reduced global levels of histone methylation in frontal cortex (Black et al., 2006). In addition, chromatin remodeling mechanisms have been implicated directly in addiction-related behavior, with modification of histone acetylation altering behavioral responses to cocaine (Kumar et al., 2005; Levine et al., 2005). An exciting innovation is to utilize so-called ChIP on chip assays (ChIP followed by analysis on promoter arrays) to gain a genome-wide view of alterations in chromatin structure and transcription factor binding in brain reward regions after chronic drug exposure. It would be interesting to overlay such information on to DNA expression arrays (e.g., Freeman et al., 2001; McClung and Nestler, 2003; Yao et al., 2004; Yuferov et al., 2005) to obtain a more reliable determination of the genomic effects of drugs of abuse on the brain and to gain initial insight into the underlying mechanisms involved. Although these various studies of chromatin remodeling are clearly in early stages of development, this line of investigation in drug abuse models promises new insight into the molecular mechanisms of drug addiction. Drug-Induced Adaptations in Other Reinforcement-Related Brain Regions The preceding discussion focused on the VTA and NAc as the major sites in the brain of drug-induced adaptations that underlie addiction. Although these regions are no doubt important—indeed, they may be critical— it is also clear that many other brain regions contribute to addiction. As mentioned earlier, there is increasing evidence to indicate the importance of the amygdala, frontal cortical regions, and hippocampus, as well as still other brain areas such as the periaqueductal gray, serotonergic raphé nuclei, and hypothalamus. Considerable work in rodents and humans has shown reduced functional activity of frontal cortical regions as a consequence of chronic drug exposure, and these changes have been related directly to the increased impulsivity and compulsivity seen in addicted states (Volkow and Fowler, 2000). Although the molecular basis of this “hypofrontality” remains incompletely understood, there have been recent advances. The basal activity of cortical glutamatergic pyramidal neurons appears to be reduced at baseline after chronic exposure to cocaine, whereas an acute challenge with cocaine elicits enhanced activation of these neurons. Chronic cocaine use also has been reported to decrease levels of the cystine–glutamate transporter in glial cells in the NAc; this transporter promotes release of glutamate from prefrontal cortical glu-

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tamatergic nerve terminals, perhaps further exaggerating glutamatergic transmission to the NAc when the cell bodies fire in response to cocaine and associated cues (Kalivas et al., 2005) (Fig. 46.2). This has raised the interesting possibility that ligands that regulate this transporter might be of benefit in the treatment of cocaine addiction. Clearly, these changes are complex, and interact with the postsynaptic adaptations in glutamate receptor function in NAc neurons discussed earlier, in ways that remain incompletely understood. Nevertheless, these important findings now highlight the need to characterize the effects of other drugs of abuse, as well as natural rewards, on these same end points. Another interesting outcome of research on these other reward-related brain areas is the finding that many of the drug-induced adaptations characterized in the VTA and NAc are also seen in some of these other brain regions. Drug-induced up-regulation of the cAMP pathway and activation of CREB have been observed not only in the VTA–NAc, as stated above, but also in the amygdala, periaqueductal gray, frontal cortex, and elsewhere (Nestler, 2004, 2005). ΔFosB is induced by chronic drug exposure in prefrontal and orbitofrontal cortex and amygdala as well as in the NAc. In fact, induction seen in the orbitofrontal cortex is much greater in animals that self-administer drug as opposed to those that receive drug passively. This finding suggests particular relevance of ΔFosB induction in orbitofrontal cortex in regulating motivational aspects of addiction, although this remains speculative. The expansion of dendritic spines, observed as a consequence of chronic stimulant exposure in the NAc, is also seen in prefrontal cortex (Robinson and Kolb, 2004). As the roles played by these various brain regions in addiction are established, it will be increasingly possible to relate specific molecular adaptations in these regions to particular functional aspects of addiction. CONCLUSIONS The availability of animal models that increasingly reproduce important features of drug addiction in humans has made it possible to identify specific regions in the brain that play an important role in addictive disorders. The mesolimbic DA system, and related neural circuits involving the amygdala, frontal regions of cerebral cortex, and hippocampus, among several others, are integrally involved in drug reward and in derangements in drug reward mechanisms that are the essential feature of drug addiction clinically. Basic neurobiological investigations are beginning to provide an understanding of the adaptations at the molecular and cellular levels that occur in these various brain regions that are responsible for behavioral features of drug addiction. This chapter focused on drug-induced adaptations in

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the cAMP pathway, in G protein–coupled receptors, in glutamatergic neurotransmission and synaptic plasticity, in neurotrophic factors and their signaling cascades, and in several transcription factors (for example, CREB and ΔFosB) and associated changes in chromatin structure. Some of these molecular and cellular adaptations have been related to drug-induced morphological changes in neurons located within several reward-related brain regions. However, these adaptations, though important, are merely illustrative of modifications in numerous additional neurotransmitters, neurotrophic factors, intracellular signaling pathways, and transcriptional mechanisms induced within these various brain reward regions. As the pathophysiological mechanisms underlying drug addiction become increasingly understood, it will be possible to develop more efficacious pharmacotherapies for the treatment of addictive disorders. REFERENCES Black, Y.D., Maclaren, F.R., Naydenov, A.V., Carlezon, W.A., Jr., Baxter, M.G., and Konradi, C. (2006) Altered attention and prefrontal cortex gene expression in rats after binge-like exposure to cocaine during adolescence. J. Neurosci. 26:9656–9665. Bolaños, C.A., and Nestler, E.J. (2004) Neurotrophic mechanisms in drug addiction. J. Neuromol. Med. 5:69–83. Boudreau, A.C., and Wolf, M.E. (2005) Behavioral sensitization to cocaine is associated with increased AMPA receptor surface expression in the nucleus accumbens. J. Neurosci. 25:9144–9151. Brami-Cherrier, K., Valjent, E., Herve, D., Darragh, J., Corvol, J.C., Pages, C., Arthur, S.J., Girault, J.A., and Caboche, J. (2005) Parsing molecular and behavioral effects of cocaine in mitogen- and stress-activated protein kinase-1 deficient mice. J. Neurosci. 25: 11444–11454. Carle, T.L., Ohnishi. Y.N., Ohnishi, Y.H., Alibhai, I.N., Wilkinson, M.B., Kumar, A., and Nestler, E.J. (2007) Absence of conserved C-terminal degron domain contributes to ΔFosB’s unique stability. Eur. J. Neurosci. 25:3009–3019. Carlezon, W.A., Jr., Duman, R.S., and Nestler, E.J. (2005) The many faces of CREB. Trends Neurosci. 28:436–445. Carlezon, W.A., Jr., and Nestler, E.J. (2002) Elevated levels of GluR1 in the midbrain: a trigger for sensitization to drugs of abuse? Trends Neurosci. 25:610–615. Chavkin, C., McLaughlin, J.P., and Celver, J.P. (2001) Regulation of opioid receptor function by chronic agonist exposure: constitutive activity and desensitization. Mol. Pharmacol. 60:20–25. Choi, K.H., Whisler, K., Graham, D.L., and Self, D.W. (2006) Antisense-induced reduction in nucleus accumbens cyclic AMP response element binding protein attenuates cocaine reinforcement. Neuroscience 137:373–383. Colby, C.R., Whisler, K., Steffen, C., Nestler, E.J., and Self, D.W. (2003) ΔFosB enhances incentive for cocaine. J. Neurosci. 23:2488– 2493. Everitt, B.J., Dickinson, A., and Robbins, T.W. (2001) The neuropsychological basis of addictive behaviour. Brain Res. Rev. 36:129–138. Everitt, B.J., and Wolf, M.E. (2002) Psychomotor stimulant addiction: a neural systems perspective. J. Neurosci. 22:3312–3320. Flores, C., Samaha, A.N., and Stewart, J. (2000) Requirement of endogenous basic fibroblast growth factor for sensitization to amphetamine. J. Neurosci. 20:RC55. Freeman, W.M., Nader, M.A., Nader, S.H., Robertson, D.J., Gioia, L., Mitchell, S.M., Daunais, J.B., Porrino, L.J., Friedman, D.P., and Vrana, K.E. (2001) Chronic cocaine-mediated changes in non-

human primate nucleus accumbens gene expression. J. Neurochem. 77:542–549. Hyman, S.E., Malenka, R.C., and Nestler, E.J. (2006) Neural mechanisms of addiction: the role of reward-related learning and memory. Annu. Rev. Neurosci. 29:565–598. Kalivas, P.W. (2004) Glutamate systems in cocaine addiction. Curr. Opin. Pharmacol. 4:23–29. Kalivas, P.W., Volkow, N., and Seamans, J. (2005) Unmanageable motivation in addiction: a pathology in prefrontal-accumbens glutamate transmission. Neuron 45:647–650. Kauer, J.A. (2004) Learning mechanisms in addiction: synaptic plasticity in the ventral tegmental area as a result of exposure to drugs of abuse. Annu. Rev. Physiol. 66:447–475. Kelley, A.E. and Berridge, K.C. (2002) The neuroscience of natural rewards: Relevance to addictive drugs. J. Neurosci. 22:3306– 3311. Kelz, M.B., Chen, J.S., Carlezon, W.A., Whisler, K., Gilden, L., Beckmann, A.M., Steffen, C., Zhang, Y.-J., Marotti, L., Self, D.W., Tkatch, R., Baranauskas, G., Surmeier, D.J., Neve, R.L., Duman, R.S., Picciotto, M.R., and Nestler, E.J. (1999) Expression of the transcription factor ΔFosB in the brain controls sensitivity to cocaine. Nature 401:272–276. Koob, G.F., and Le Moal, M. (2001) Drug addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology 24:97–129. Kreek, M.J. (1996) Cocaine, dopamine and the endogenous opioid system. J. Addict. Dis. 15:73–96. Kumar, A., Choi, K.-H., Renthal, W., Tsankova, N.M., Theobald, D.E.H., Truong, H.-T., Russo, S.J., LaPlant, Q., Sasaki, T.S., Whistler, K.N., Neve, R.L., Self, D.W., and Nestler, E.J. (2005) Chromatin remodeling is a key mechanism underlying cocaineinduced plasticity in striatum. Neuron 48:303–314. Lee, K.W., Kim, Y., Kim, A.M., Helmin, K., Nairn, A.C., and Greengard, P. (2006) Cocaine-induced dendritic spine formation in D1 and D2 dopamine receptor-containing medium spiny neurons in nucleus accumbens. Proc. Natl. Acad. Sci. USA 103: 3399–3404. Levine, A.A., Guan, Z., Barco, A., Xu, S., Kandel, E.R., and Schwartz, J.H. (2005) CREB-binding protein controls response to cocaine by acetylating histones at the fosB promoter in the mouse striatum. Proc. Natl. Acad. Sci. USA 102:19186–19191. McClung, C.A., and Nestler, E.J. (2003) Regulation of gene expression and cocaine reward by CREB and ΔFosB. Nat. Neurosci. 11:1208–1215. McClung, C.A., Ulery, P.G., Perrotti, L.I., Zachariou, V., Berton, O., and Nestler, E.J. (2004) ΔFosB: A molecular switch for long-term adaptation in the brain. Mol. Brain Res. 132:146–154. McLaughlin, J.P., Marton-Popovici, M., and Chavkin, C. (2003) Kappa opioid receptor antagonism and prodynorphin gene disruption block stress-induced behavioral responses. J. Neurosci. 23:5674–5683. Nestler, E.J. (2004) Historical review: molecular and cellular mechanisms of opiate and cocaine addiction. Trends Pharmacol. Sci. 25:210–218. Nestler, E.J. (2005) Is there a common molecular pathway for addiction? Nat. Neurosci. 8:1445–1449. Nestler, E.J., and Aghajanian, G.K. (1997) Molecular and cellular basis of addiction. Science 278:58–63. Nestler, E.J., Barrot, M., and Self, S.W. (2001) ΔFosB: a molecular switch for addiction. Proc. Natl. Acad. Sci. USA 98:11042–11046. Norrholm, S.D., Bibb, J.A., Nestler, E.J., Ouimet, C.C., Taylor, J.R., and Greengard, P. (2003) Cocaine-induced proliferation of dendritic spines in nucleus accumbens is dependent on the activity of the neuronal kinase Cdk5. Neuroscience 116:19–22. Olson, V.G., Zabetian, C.P., Bolaños, C.A., Edwards, S., Barrot, M., Eisch, A.J., Hughes, T., Self, D.W., Neve, R.L., and Nestler, E.J. (2005) Regulation of drug reward by CREB: evidence for two functionally distinct subregions of the ventral tegmental area. J. Neurosci. 25:5553–5562.

46: CELLULAR AND MOLECULAR MECHANISMS OF DRUG ADDICTION Pierce, R.C., and Bari, A.A. (2001) The role of neurotrophic factors in psychostimulant-induced behavioral and neuronal plasticity. Rev. Neurosci. 12:95–110. Robinson, T.E., and Kolb, B. (2004) Structural plasticity associated with exposure to drugs of abuse. Neuropharmacology 47:S33–S46. Russo, S.J., Bolanos, C.A., Theobald, D.E., DeCarolis, N., Kumar, A., Self, D.W., Russell, D.S., Neve, R.L., Eisch, A.J., and Nestler, E.J. (2007) Insulin receptor substrate-2 in midbrain dopaminergic neurons regulates behavioral and cellular responses to opiates. Nat. Neurosci. 10:93–99. Self, D.W., Genova, L.M., Hope, B.T., Barnhart, W.J., Spencer, J.J., and Nestler, E.J. (1998) Involvement of cAMP-dependent protein kinase in the nucleus accumbens in cocaine self-administration and relapse of cocaine-seeking behavior. J. Neurosci. 18:1848–1859. Shippenberg, T.S., Chefer, V.I., Zapata, A., and Heidbreder, C.A. (2001) Modulation of the behavioral and neurochemical effects of psychostimulants by kappa-opioid receptor systems. Ann. N.Y. Acad. Sci. 937:50–73. Sklair-Tavron, L., Shi, W.-X., Lane, S.B., Harris, H.W., Bunney, B.S., and Nestler, E.J. (1996) Chronic morphine induces visible changes in the morphology of mesolimbic dopamine neurons. Proc. Natl. Acad. Sci. USA 93:11202–11207. Sutton, M.A., Schmidt, E.F., Choi, K.H., Schad, C.A., Whisler, K., Simmons, D., Karanian, D.A., Monteggia, L.M., Neve, R.L., and Self, D.W. (2003) Extinction-induced upregulation in AMPA receptors reduces cocaine-seeking behaviour. Nature 421:70–75. Taylor, J.R., Lynch, W.J., Sanchez, H., Olausson, P., Nestler, E.J., and Bibb, J.A. (2007) Inhibition of Cdk5 in the nucleus accumbens enhances the locomotor activating and incentive motivational effects of cocaine. Proc. Natl. Acad. Sci. USA 104:4147–4152. Thomas, M.J., and Malenka, R.C. (2003) Synaptic plasticity in the mesolimbic dopamine system. Philos. Trans. R. Soc. Lond. B Biol. Sci. 358:815–819. Tsankova, N., Renthal, W., Kumar, A., and Nestler, E.J. (2007) Epigenetic regulation in psychiatric disorders. Nat. Rev. Neurosci. 8:355–367. Ulery, P.G., Rudenko, G., and Nestler, E.J. (2006) Regulation of ΔFosB stability by phosphorylation. J. Neurosci. 26:5131–5142.

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Volkow, N.D., and Fowler, J.S. (2000) Addiction, a disease of compulsion and drive: involvement of the orbitofrontal cortex. Cereb. Cortex 10:318–325. von Zastrow, M., Svingos, A., Haberstock-Debic, H., and Evans, C. (2003) Regulated endocytosis of opioid receptors: cellular mechanisms and proposed roles in physiological adaptation to opiate drugs. Curr. Opin. Chem. Biol. 13:348–353. Walters, C.L., and Blendy, J.A. (2001) Different requirements for cAMP response element binding protein in positive and negative reinforcing properties of drugs of abuse. J. Neurosci. 21:9438– 9444. Walters, C.L., Cleck, J.N., Kuo, Y.C., and Blendy, J.A. (2005) Muopioid receptor and CREB activation are required for nicotine reward. Neuron 46:933–943. Wise, R.A. (1998) Drug-activation of brain reward pathways. Drug Alcohol Depend. 51:13–22. Wolf, M.E. (1998) The role of excitatory amino acids in behavioral sensitization to psychomotor stimulants. Prog. Neurobiol. 54:679– 720. Yao, W.D., Gainetdinov, R.R., Arbuckle, M.I., Sotnikova, T.D., Cyr, M., Beaulieu, J.M., Torres, G.E., Grant, S.G., and Caron, M.G. (2004) Identification of PSD-95 as a regulator of dopaminemediated synaptic and behavioral plasticity. Neuron 41:625–638. Yuferov, V., Nielsen, D., Butelman, E., and Kreek, M.J. (2005) Microarray studies of psychostimulant-induced changes in gene expression. Addict. Biol. 10:101–118. Yuste, R., and Bonhoeffer, T. (2001) Morphological changes in dendritic spines associated with long-term synaptic plasticity. Annu. Rev. Neurosci. 24:1071–1089. Zachariou, V., Bolanos, C.A., Selley, D.E., Theobald, D., Cassidy, M.P., Kelz, M.B., Shaw-Lutchman, T., Berton, O., Sim-Selley, L.J., DiLeone, R.J., Kumar, A., and Nestler, E.J. (2006) ΔFosB: an essential role for ΔFosB in the nucleus accumbens in morphine action. Nat. Neurosci. 9:205–211. Zachariou, V., Georgescu, D., Sanchez, N., Rahman, Z., DiLeone, R., Berton, O., Simon, M., Neve, R.L., Sim-Selley, L.J., Selley, D.E., Gold, S.J., and Nestler, E.J. (2003) Essential role for RGS9 in opiate action. Proc. Natl. Acad. Sci. USA 100:13656–13661.

47 Genetic Epidemiology of Substance Use Disorders KATHLEEN R. MERIKANGAS

Substance abuse is one of the most pervasive psychiatric disorders in contemporary society. Of people sampled in the National Comorbidity Survey Replication (NCS-R), a recently completed nationwide survey of Americans aged 18 and older, 14.6% had a lifetime history of a substance use disorder (SUD; that is, abuse or dependence) (Kessler et al., 2005). In addition, data from the Monitoring the Future study (MTFS), a largescale study of American high-school students, show high prevalence rates of substance use, which increase steadily with age. According to this study, past-month rates of any illicit drug use were 8.5% among 8th graders, 17.3% for 10th graders, and 23.1% for 12th graders (Johnston et al., 2006). A strikingly high number of people develop addictions to substances. Further, children are exposed to substances frequently and at a young age. These high prevalence and exposure rates highlight the need to better understand the etiology of SUDs. Although the majority of people who engage in recreational and/or experimental substance use will not develop drug abuse or dependence, it is important to understand the factors that determine the progression from drug use to dependence. Indeed, a recent survey reveals that Americans view drug abuse as one of the most serious public health problems facing the United States (ICR, 1996). Despite the dramatic advances generated by the sequencing of human genes (Human Genome Project) and progress in molecular biology in gene expression, the identification of specific genetic vulnerability factors for the development of SUDs will require a further complex series of studies of multiple domains influencing susceptibility to drug abuse/dependence. Unlike Mendelian diseases where a specific gene mutation is directly associated with susceptibility to a particular disease, substance abuse/dependence is a multifactorial disorder, which requires environmental exposure to a particular * The views and opinions expressed in this report are those of the authors and should not be construed to represent the views of any of the sponsoring agencies or the United States government.

786

A N D

KEVIN P. CONWAY*

drug as well as several different classes of genes involved in the metabolism, and direct and indirect central nervous system (CNS) effects of drugs. Although socioenvironmental factors appear to play a key role in the initial use of a substance, an interaction between individual biological, physiological, psychological, and environmental processes is associated with the progression to more problematic use. The goals of this chapter are (1) to summarize evidence regarding the genetic epidemiology of SUDs, (2) to review sources of complexity in the etiology of SUDs, and (3) to review current research on the genetic influences in the development of SUDs.

GENETIC EPIDEMIOLOGIC STUDIES Family Studies The family-study design has been useful in illustrating the magnitude of aggregation of SUDs within families as well as the patterns of transmission of SUDs. The family-study method has long been used to show whether a disorder “runs in families,” which often indicates that a disorder has a genetic component. The family-study method compares the prevalence of a disorder in firstdegree relatives of cases to the prevalence of the disorder in first-degree relatives of controls, who are frequently matched to cases on key characteristics such as age, gender, and psychiatric diagnosis. The familial aggregation of alcoholism has been well-established through decades of comprehensive study (for reviews of alcoholism, see Merikangas, 1990; McGue, 1994). Although there has been less systematic research on the familial aggregation of drug use disorders, available empirical evidence demonstrates that drug use disorders also tend to aggregate within families. The results of many familyhistory and uncontrolled family studies (Hill et al., 1977; Croughan, 1985; Gfroerer, 1987; Meller et al., 1988; Mirin et al., 1988; Mirin et al., 1991; Rounsaville et al., 1991; Compton et al., 2002), and controlled stud-

47: GENETIC EPIDEMIOLOGY

ies of first-degree relatives of substance abusers (Bierut et al., 1998; Merikangas, Stolar, et al., 1998; Nurnberger et al., 2004) show elevated rates of SUDs among relatives of drug abusers compared to rates of SUDs in controls. The family study of Merikangas, Stolar, et al. (1998) found an eightfold increased risk of drug use disorders among relatives of probands with drug use disorders as compared to relatives of people with psychiatric disorders and to unaffected controls (Merikangas, Stolar, et al., 1998). High-Risk Studies Studies of offspring of parents with substance abuse disorders are a subset of family studies that provides information on the order of onset and patterns of transitions across drug categories, as well as on premorbid risk factors for the development of substance abuse. Although there have been several high-risk studies of children of alcoholics (Johnson et al., 1989; Chassin et al., 1991; Sher et al., 1991; Hill and Hruska, 1992; Reich et al., 1993; Merikangas, Dierker, et al., 1998; Shuckit and Smith, 1996), there have been very few controlled studies of the offspring of drug abusers. Available studies have yielded consistent findings regarding an increased risk of SUDs among offspring of parents with substance abuse or dependence when compared to those of nonsubstance abusers (Martin et al., 1994; Moss et al., 1994; Merikangas, Dierker, and Szatmari, 1998). In an 8-year follow-up study, offspring of substance abusers were at a twofold increased risk for any SUD and a threefold increased risk for alcohol and marijuana abuse or dependence compared to offspring of control parents (Merikangas and Avenevoli, 2000). Hopfer et al. (2003) also reported parent–child transmission for marijuana use, abuse, and dependence. Some studies have reported specificity for substance use, such that adolescents are particularly likely to use the same illicit drug as their parents (Andrews et al., 1997; Hoffman and Cerbone, 2002; Merikangas and Avenevoli, 2000). High-risk studies are particularly informative for prevention efforts as they aid in the identification of premorbid vulnerability factors that serve as sources of identification for children at risk for particular disorders. One candidate risk factor for SUDs is behavioral disinhibition, a trait-like dysfunction in the ability to control behavior that is socially undesirable or has adverse consequences (Gorenstein and Newman, 1980). Multivariate analysis of a community sample of Colorado twins showed that the considerable covariation among behavior disorders and drug use was accounted for almost entirely by behavioral disinhibition, which is highly heritable and only weakly influenced by shared environmental influences (Young et al., 2000). Recent analyses of family-study data by Tarter and colleagues

787

similarly support a common neurobehavioral disinhibition factor underlying the risk for drug abuse and dependence, which includes a prominent component of impaired executive decision making in youth at risk for drug abuse (Tarter et al., 2003; Tarter et al., 2004). Parents may increase their offspring’s risk of developing substance abuse in numerous ways. Parents increase offspring’s risk by serving as negative role models for the use/abuse of drugs and by using drugs as a coping mechanism (Brook et al., 1986). Additionally, positive expectancies of the effects of substances (Conway et al., 2003) and availability and tolerance of substance use in the home (Hawkins et al., 1992) increase a child’s risk for the development of a SUD. Further, adolescents with a family history of substance abuse are more likely to associate with deviant peers than those without a familial loading (Kandel and Andrews, 1987), indicating interplay between familial and peer influences. Likewise, nearly all of the high-risk studies reveal that different risk factors may be involved across the different “stages” of development of SUDs. Whereas individual characteristics and peer influences strongly influence exposure to and initial patterns of use of alcohol and drugs, family history and psychopathology play a more salient role in the transition to problematic alcohol use and dependence (Cadoret et al., 1986). A more comprehensive review of the literature on family risk and protective factors related to the etiology and progression of SUDs is available elsewhere (Avenevoli et. al., 2005). Twin Studies Although family studies have been helpful in showing that genes may be involved in the development of a SUD, twin studies can provide actual estimates of heritability. Twin studies are informative because identical (monozygotic; MZ) twins share 100% of their genes whereas fraternal (dizygotic; DZ) twins share, on average, 50% of their genes. If genetic factors play an important role in substance use and disorders, then studies of twins should find greater similarity between MZ than DZ twins, assuming that the influence of familial environment on drug use outcomes is equal for MZ and DZ twins. The aggregate twin study data are remarkably consistent in demonstrating that genetic factors play a far greater role in the etiology of more severe patterns of drug use, particularly those which meet diagnostic criteria for abuse or dependence, than initial use or early stages of use, which appear to be more strongly determined by environmental influences (Tsuang et al., 1996; Kendler and Prescott, 1998b; Rhee et al., 2003; Fowler et al., 2007). Studies have examined drug use, abuse, and dependence in general (Grove et al., 1990; Pickens et al., 1991; Jang et al., 1995; Kendler et al.,

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SUBSTANCE ABUSE DISORDERS

2000), as well as a diverse range of specific drugs including nicotine, caffeine, tranquilizers, sedatives, cannabis, cocaine, stimulants, hallucinogens, and opiates (Claridge, Ross, and Hume, 1978; Pedersen, 1981; Gurling et al., 1985; Heath et al., 1993; Heath and Madden, 1995; Heath et al., 1997; True et al., 1997; Kendler and Prescott, 1998a, 1998b; Tsuang et al., 1998; Kendler, Karkowski, and Prescott, 1999; True et al., 1999; Kendler et al., 2000). Table 47.1 gives a summary of recent populationbased twin studies of drug dependence. The tetrachoric correlations shown in Table 47.1 reflect the correlations in the inferred underlying liability for the development of drug abuse. The results of these studies have been highly consistent in demonstrating the role of genetic factors in the etiology of drug use disorders. However, the extent of genetic influence differs according to the trait definition employed, and the age, sex, and source of the sample. The studies reviewed in Table 47.1 demonstrate a wide range of heritability estimates ranging from 0% to 87% in males and 0% to 77% in females, with a median of 53% and 55% for males and females, respectively. The approximately twofold larger correlation between MZ compared to DZ twins reflects the contributions of genetic factors to the specific drug phenotype. Surprisingly, common environmental influences are low in most studies, whereas unique environmental factors play a major role in drug abuse/dependence in these samples. These studies demonstrate the complex interplay (interactions and correlations) between genetic and environmental factors in the etiology of drug abuse. Adoption Studies The classic adoption studies of Cadoret and colleagues (Cadoret et al., 1986; Cadoret, 1992; Cadoret et al., 1995, 1996) have also been highly informative in elucidating the role of genetic factors in the development of drug use and abuse. Although data on biologic parents are often limited with respect to specific patterns of drug use and abuse, Cadoret et al.’s studies provide the strongest evidence to date that genetic factors play an important role in the development of drug abuse. These studies identify two major biologic/genetic pathways to the development of drug abuse in adoptees. The first pathway links substance abuse in the biological parent to drug abuse and dependence in the adoptee. The second pathway appears to be an expression of underlying aggressivity in the adoptee and relates to antisocial personality disorder (ASPD) in the biologic parent (Cadoret et al., 1995, 1996). Moreover, adoptedaway offspring of fathers who are antisocial addicts (compared to either antisocial or addicted) are at especially elevated risk for substance abuse (Langbehn et al., 2003).

SOURCES OF COMPLEXITY OF GENETICS OF SUBSTANCE USE DISORDERS Demographic Correlates Sex differences Substance use disorders are more common in males than in females. Based on the rates from the Epidemiologic Catchment Area Study, men are 5 times more likely to have an alcohol use disorder and 2 to 3 times more likely to have a drug use disorder than women (Anthony and Helzer, 1995). Likewise, the NCS (Kessler et al., 1997), National Longitudinal Alcohol Epidemiologic Survey (NLAES), and National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) found that SUDs were more prevalent among men than women (Grant et al., 2004; Compton et al., 2007). Findings from family and twin studies that have observed the effect of sex on transmission of SUDs have been inconsistent. Whereas some studies show that the relatives of females with alcoholism have a lower threshold for manifestation of alcoholism than those of males with alcoholism, other studies found no difference in the familial aggregation of alcoholism among men and women. For example, one study found that alcohol abuse and dependence were familial among females, whereas only dependence aggregated among the relatives of males with alcohol dependence (Merikangas, Stolar, et al., 1998). Sex differences in transmission of SUDs also emerged in the clinical twin study of van den Bree et al. (1998), who found that the heritability estimates for males were much higher than for females across a broad spectrum of drug use disorders. In contrast, data from the Australian Twin Registry indicate no significant sex differences in estimates of heritability or environmental influence for cannabis dependence (Lynskey et al., 2002) or nicotine withdrawal (Pergadia et al., 2006). The similarity in heritability estimates for males and females shown in Table 47.1 provides further evidence that there are few sex differences in the transmission of SUDs in population-based samples. Age/developmental stage. Twin studies have also begun to examine the role of genetic factors in the development of SUDs in prospective samples of children and adolescents. These studies may inform our understanding of the influence of age and developmental level in the etiology of SUDs. For example, McGue (1994) revealed far greater heritability of drug use disorders among males with early age of onset compared to either those with later age of onset or females. These data suggest that different factors may exert influence at different stages of development, and/or that certain developmental periods are more sensitive than others. Because exposure to drugs generally occurs during early adolescence, the above-cited data derived from adult

TABLE

47.1 Population-Based Twin Studies of Abuse/Dependence of Specific Drugs Conducted in the Last 10 Years Tetrachoric Correlations Monozygotic

Substance

Author(s) and Year

Alcohol

Tobacco

Marijuana

Components of Variance

Dizygotic

Common Environment

Addictive Genetic

Unique Environ/ Error

Samplea

DX Interviewb

Male

Prescott & Kendler, 1999

VETR

SCID-111-R & SSAGA

0.53

Heath et al., 1997d

ANH&MRC

SSAGA

True, Xian, et al., 1999

VETR

DIS-111-R

True, Heath, et al., 1999c

VETR

DIS-111-R

—

—

—

—

0.45

—

0.12

—

0.44

—

Pergadia et al., 2006c, f, h, j

ATR

SSAGA

—

—

—

—

0.61

0.61

0.01

0.01

0.38

0.38

Kendler, Neale, et al., 1999 c, k

VETR

FTQ

—

0.47

—

0.30

—

0.30

—

0.20

—

0.50

True, Xian, et al., 1999c

VETR

DIS-111-R

0.61

—

0.31

—

0.60

—

—

—

0.40

—

Agrawal et al., 2005

VATSPSUD

SCID-111-R

—

—

—

—

0.31

0.36

0.00

0.00

0.69

0.65

Agrawal et al., 2007

ATR

SSAGA

—

—

—

—

0.68

0.55

0.14

0.16

0.18

0.29

Kendler et al., 2006

NIPHTP

M-CIDI

0.77

0.77

0.31

0.31

0.77

0.77

0.00

0.00

0.23

0.23

Lynskey et al., 2002c

ATR

SSAGA

0.70

0.59

0.35

0.51

0.56

0.21

0.13

0.39

0.31

0.40

Kendler et al., 2000

VTR

SCID-111-R

0.59

—

0.20

—

0.58

—

0.00

—

0.42

—

Kendler & Prescott, 1998a

VETR

SCID-111-R

—

0.58

—

0.41

—

0.62

—

0.00

—

0.38

True, Heath, et al., 1999c

VETR

DIS-111-R

—

—

—

—

0.44

—

0.21

—

0.36

—

Tsuang et al., 1996

VETR

DIS-111-R

0.62

—

0.46

—

0.33

—

0.29

—

0.38

—

b

Female

Male

Female

Male

Female

Male

—

0.18

—

0.51

—

—

0.68

0.58

0.20

0.29

0.64

0.64

0.55

—

0.29

—

0.55

—

Female

Male

Female

—

0.49

—-

0.03

0.01

0.33

0.35

—

—

0.45

—

TABLE

47.1 Population-Based Twin Studies of Abuse/Dependence of Specific Drugs Conducted in the Last 10 Years (Continued) Tetrachoric Correlations Monozygotic

Substance Stimulants

Sedatives

Psychedelics

Cocaine

Opiates

Author(s) and Year

Samplea

DX Interviewb

Male

Female

Components of Variance

Dizygotic Male

Female

Common Environment

Addictive Genetic Male

Female

Male

Female

Unique Environ/ Error Male

Female

Agrawal et al., 2005

VATSPSUD

SCID-111-R

—

—

—

—

0.53

0.00

0.00

0.99

0.47

0.01

Lynskey et al., 2007h

ATR

SSAGA

—

—

—

—

0.65

0.65

0.08

0.08

0.28

0.28

Kendler et al., 2000

VTR

SCID-111-R

0.43

—

0.34

—

0.00

—

0.39

—

0.61

—

Tsuang et al., 1996j

VETR

DIS-111-R

0.53

—

0.24

—

0.44

—

0.00

—

0.49

—

Agrawal et al., 2005

VATSPSUD

SCID-111-R

—

—

—

—

0.08

0.38

0.00

0.00

0.92

0.62

Kendler et al., 2000

VETR

SCID-111-R

0.83

—

0.00

—

0.87

—

0.00

—

0.13

—

Tsuang et al., 1996

VETR

DIS-111-R

0.44

—

0.25

—

0.38

—

0.06

—

0.56

—

Kendler et al., 2000

VETR

SCID-111-R

0.00

—

0.00

—

0.79

—

0.00

—

0.21

—

Tsuang et al., 1996

VETR

DIS-111-R

0.44

—

0.32

—

0.25

—

0.19

—

0.56

—

Agrawal et al., 2005

VATSPSUD

SCID-111-R

—

—

—

—

0.08

0.38

0.00

0.00

0.92

0.62

Kendler et al., 2000

VETR

SCID-111-R

0.77

—

0.37

—

0.79

—

0.00

—

0.21

—

Kendler & Prescott, 1998b/c

VETR

SCID-111-R

—

0.68

—

0.08

—

0.65

—

0.00

—

0.35

Tsuang et al., 1996

VETR

DIS-111-R

0.67

—

0.29

—

0.43

—

0.00

—

0.31

—

j

VATSPSUD: Virginia Adult Twin Study of Psychoactive and Substance Use Disorders; VTR: Virginia Twin Registry; VETR, Vietnam Era Twin Registry; ANH & MRC: Australian National Health and Medical Research Council; ATR: Australian Twin Register; MTS: Minnesota Twin Study; NIPHTP: Norwegian Institute of Public Health Twin Panel. b SCID: Structured Clinical Interview for DSM-111-R; SSAGA: Semi-Structured Assessment for the Genetics of Alcoholism; DIS-111-R: Diagnostic Interview Schedule Version 111 Revised; FTQ: Fagerstrom Tolerance Questionnaire; DIS-111: Diagnostic Interview Schedule Version 111; M-CIDI: Munich-Composite International Diagnostic Interview. c Study examines dependence without abuse. d Sample also included 754 unlike-sex pairs. e Sample also included 655 unlike-sex pairs and 753 (377 female and 376 male) single twins. f Sample also included 559 unlike-sex pairs. g Sample also included 338 unlike-sex pairs. h Best-fitting model was obtained when components of variance were constrained to equality across the sexes, thus sex-specific estimates reported here are identical. i DSM-IV nicotine withdrawal was the phenotype. j Non-additive genetic effects were reported for stimulants (0.07) and opiates (0.26). k Study reports Pearson’s r, rather than the tetrachoric correlation. DSM: Diagnostic and Statistical Manual of Mental Disorders. a

47: GENETIC EPIDEMIOLOGY

samples are necessarily susceptible to the biases of all retrospective studies. A study of adolescent twins from the Netherlands (Boomsma et al., 1994) yielded evidence to suggest that the heritability of alcohol use increased with age, whereas shared environmental factors had a stronger impact in early adolescence. Similarly, relying on retrospective reports from adults, Gillespie and colleagues (2007) reported an overall increase in genetic influence and a decline in shared environmental influence from ages 8 to 25. Follow-up studies of this topic will increase understanding of the joint influences of genetic, environmental, and developmental factors on occurrence and persistence of dependence as individuals pass through the risk period for the development of substance dependence. Cohort and generation effects. One key source of complexity in studying the familial transmission of drug abuse is the dramatic changes in patterns of drug use in the general population, as well as within specific subgroups. Rapid shifts in the availability of specific drugs and cultural and geographic patterns of drug use complicate traditional inspection of vertical patterns of concordance for drug use and dependence. Whereas alcohol has been readily available during the past several decades, and cannabis use has been somewhat stable as well, crack cocaine and ecstasy have only been widely available during the past decade, and the misuse of prescription drugs has dramatically increased in very recent years. Conversely, nicotine use has been decreasing rapidly in more recent cohorts. These differences in availability and cultural norms contribute to the difficulty in discriminating exposed but unaffected relatives from those who were never exposed to a particular drug, an issue that poses major methodological challenges (Neal et al., 2006). Within-generation comparisons are therefore more likely to control for exposure to specific substances. Siblings, however, are often responsible for the initiation of other siblings to drugs, which could lead to an overestimation in the heritability of drug use. The association between cohort effects and heritability is largely unexplored. One study found that though prevalence rates for psychoactive substance use differed substantially across three cohorts, there was no systematic relationship between heritability and prevalence of psychoactive substance use (Kendler et al., 2005), suggesting that evolving patterns of drug accessibility and consumption do not significantly affect rates of heritability. Spouse concordance. Several studies have shown spouse concordance for drug use (Vanyukov et al., 1996; Merikangas et al., 1992). This tendency for spouses to be concordant for substance use is another issue that must be integrated into the evaluation of genetic evidence (Grant et al., 2007). Merikangas et al. (1992) reported that more than 90% of interviewed opioid-dependent

791

proband spouses had a history of opioid dependence themselves. Furthermore, these investigations showed a strong association between rates of drug abuse in adult siblings of opioid abusers and the number of their parents with substance abuse. It is therefore critical that spouse concordance be incorporated in genetic analyses of substance abuse. Phenotype Definition One of the major impediments to genetic studies of SUDs is that these conditions are the net result of a series of complex processes that are difficult to capture using currently available methods of measurement. Although analysis requires the drawing of thresholds between different stages of progression of drug use to distinguish drug abuse and dependence from patterns of use, such divisions have limited our ability to characterize the drug use disorder phenotype. A dimensional rating, which depicts progression across a continuum, may better represent the development of addictions. Aggregation of the findings across genetic epidemiologic studies of drug use and drug use disorders is difficult because of the wide variability in the measures employed in these studies, ranging from a few items regarding substance use on self-reported questionnaires to longitudinal characterization of patterns of progression. For example, twin studies of smoking have examined diverse components of smoking, including use, frequency, quantity, age at onset, continued use, current use, current frequency, dependence, severity, and ability to quit (Heath and Madden, 1995); however, the consistency of these measures varies greatly by study. Table 47.2 presents a summary of the range of phenotypes that have been investigated in linkage and association studies of substance use and SUDs. Studies of smoking have employed a full range of components of smoking behaviors, whereas those of illicit drugs, such as those of opioids or cocaine, have generally only assessed dependence. Genetic epidemiologic studies have contributed to our understanding of substance use/abuse phenotypes through systematic investigation of the familiality or heritability of different components of drug use trajectories. For example, the results of several twin studies reveal that genetic factors have greater influence on the development of alcohol dependence and persistence than on initiation and early stages of alcohol use (Whitfield et al., 2004; Sartor et al., 2007). Likewise, family studies have shown that familial factors are more influential in transitions at the more severe end of the drinking spectrum (Bucholz et al., 2000). Polysubstance Use Another important consideration in examining the role of genetic factors in drug use disorders is the tendency

TABLE

47.2 Candidate Genes for Substance Use and Disorders

Genes

Protein

Smoking

Alcohol

Cocaine

Opioids

Polysubstance

Alcohol metabolism ALDH1B

Alcohol dehydrogenase 1B

X

ALDH2

Alcohol dehydrogenase 1C

X

ADH1A

Aldehyde dehydrogenase

X

ADH1B

Aldehyde dehydrogenase

X

ADH4

Aldehyde dehydrogenase

X

Cannabinoid system CNR1

Cannabinoid Receptor 1

X

X

Cholinergic system CHRNA4

Muscarinic acetylcholine receptor α -4

CHRM2

Muscarinic acetylcholine receptor μ-2

X X

X

X

X

X

X

Dopaminergic system DRD2

Dopamine receptor 2

DRD3

Dopamine receptor 3

DRD4

Dopamine receptor 4

DβH

Dopamine beta-hydroxylase

DAT(1) SLC6A3

Dopamine Transporter

COMT

Catechol-O-methyltransferase

X

X

X X X X

X

X

Gabaergic system GABRA1

GABA receptor subunit α1

X

GABRA2

GABA receptor subunit α2

X

GABRB1

GABA receptor subunit β1

X

Nicotine metabolism CYP2A6

Cytochrome P450

X

CYP2D6

X

X

X

X

X

X

X

X

Opioid system OPRM

μ-opioid receptor

OPRD1

κ-opioid receptor

OPRD1

δ -opioid receptor

PENK

Proenkephalin

PDYN

Prodynorphin

X

X

X

X

X X X

Serotonergic system Metabolism TPH1

Tryptophan hydroxylase

HTR1B

Serotonin receptor 1B

COMT

Catechol-O-methyltransferase

SLC6A4

Serotonin Transporter

GABA: γ -aminobutyric acid.

792

X

X

X

X

X X

X

X

X

X

47: GENETIC EPIDEMIOLOGY

for substance abusers to misuse multiple substances, simultaneously as well as longitudinally (Mirin et al., 1991; Merikangas, Dierker, et al., 1998). Most uncontrolled family studies suggest that alcohol and drug dependence aggregate independently in families (Hill et al., 1977; Meller et al., 1988; Mirin et al., 1991; Rounsaville et al., 1991; Luthar and Rounsaville, 1993), although controlled family studies and family-history studies report an increased risk of alcoholism among relatives of drug abusers (or the converse) (Bierut et al., 1998; Merikangas, Stolar, et al., 1998; Compton et al., 2002). Likewise, one twin study revealed a moderate degree of heritability for the frequency of use and the tendency to use numerous illicit substances (h2 = .32; Jang et al., 1995). The specificity of familial aggregation of particular types of substance dependence has been examined in family and twin studies (Bierut et al., 1998; Merikangas, Stolar, et al., 1998; Nurnberger et al., 2004; Tsuang et al., 1998). The results of these studies suggest that the genetic factors underlying drug use disorders are common and specific across different drug use disorders (Vanyukov and Tarter, 2000; Volk et al., 2007). Data from the Yale Family Study of Comorbidity of Substance Abuse and Psychopathology examined the specificity of familial aggregation of the predominant drug of abuse among adult relatives of probands with similar classification. The results revealed a remarkable degree of specificity for familial aggregation of opiates, cannabis, and alcohol, and to a lesser extent, cocaine (Merikangas, Stolar, et al., 1998). On this issue, twin data have been especially useful through the application of biometrical modeling techniques that permit the quantification and comparison of genetic (common and drug-specific) and environmental (shared and nonshared) influences across a range of illicit drugs of abuse (Rhee et al., 2003). Findings from several twin studies show that specific and common factors influence the risk for the different drug use disorders, with increasing consensus for a common vulnerability model (Tsuang et al., 1998; Karkowski et al., 2000; Kendler et al., 2003; Agrawal et al., 2004; Maes et al., 2006; Young et al., 2006; Agrawal et al., 2007). In summary, the aggregate findings of the twin and family studies provide evidence for common familial and genetic factors underlying SUDs in general, as well as substantial components that are unique for specific drugs. Comorbidity with Psychopathology Another phenomenon that has complicated phenotypic definitions of SUDs is the widespread comorbidity between substance use and psychiatric disorders. Some of the largest and most consistent findings have been reported between drug use disorders and ASPD, mood disorders, anxiety disorders, and attention deficit disorder

793

(Quitkin et al., 1972; Rounsaville et al., 1982; Khantzian, 1983; Mirin et al., 1984; Khantzian and Treece, 1985; Weiss and Mirin, et al., 1985; Mirin et al., 1988; Regier et al., 1990; Kessler et al., 1996; Conway et al., 2006). Ross et al. (1988) found that 78% of their treatment sample of patients with SUDs met Diagnostic and Statistical Manual of Mental Disorders, 3rd ed. (DSM-III; American Psychiatric Association, 1980) criteria for a lifetime comorbid psychiatric disorder. Several family studies of drug-dependent probands have examined the effects of comorbid disorders on familial aggregation of SUDs and other psychiatric disorders. Most of the family studies have found increased rates of all major disorders among relatives of substance abusers; however, most have been uncontrolled, and few have accounted for comorbid disorders within the probands (Mirin et al., 1984; Croughan, 1985; Rounsaville et al., 1991). The results of the family studies have demonstrated consistently that there is independent familial aggregation of ASPD and drug use disorders (Rounsaville et al., 1991). Twin studies may provide information on the extent to which familial correlations between disorders result from shared genetic or familial factors. For example, Lin et al. (1996) compared the familial versus nonfamilial links between major depression with alcohol use disorders and drug use disorders. They concluded that whereas comorbidity between major depression and alcohol use disorders resulted from common familial factors, comorbidity with drug use disorders was attributable to nonfamilial factors. Environmental Influences Because environmental exposure to a drug is inherent to the development of SUDs, studies of the genetics of SUDs must account for gene–environment interaction as a major source of complexity of this phenotype. There are numerous environmental factors related to drug exposure, including family dynamics, peer interaction, temperament features, socioeconomic related factors, and cultural norms. These factors interact with the individual’s genetic makeup to influence phenotypic expression (Brook et al., 1986; Simcha-Figan and Schwartz, 1986; Brown, 1989; Brook et al., 1990; Avenevoli et al., 2005). However, because of the overlap in the role of genetic and environmental factors underlying vulnerability to SUDs, it may not be fruitful to devote substantial effort to determining whether risk factors fall on either the environmental or the genetic side of the risk equation. For example, an individual’s genotype may influence his or her use of drugs (gene–environment correlation), and many putative environmental factors, such as exposure to family violence, may actually result from genetic factors common to disinhibition, aggression, and substance abuse.

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Cross-national comparisons and migration studies are useful in identifying environmental and cultural risk factors. Several studies have shown that despite tremendous international variation in rates of SUDs, international patterns of comorbidity are nearly identical. This suggests that the links between SUDs and mental and behavioral disorders may result from biologic factors involved in drug preference, response, and metabolism (Merikangas et al., 1998). Likewise, cross-national comparisons in twin concordance reveal similar heritability estimates despite large differences in prevalence estimates (for example, Norway [low illicit drug use] vs. United States and Australia [high illicit drug use]), thereby suggesting that heritability is unaffected by drug availability (Kendler et al., 2006). The migrant study design is one of the most powerful approaches for identifying cultural and environmental risk factors for a disease. Studies of Asian immigrants to the United States have been used to demonstrate strong environmental contributions to many forms of cancer and heart disease (Kolonel et al., 2004). Recent findings from a migration study of adolescent offspring of Puerto Rican migrant parents compared to nonmigrant parents revealed greater rates of alcohol use among the island Puerto Ricans as compared to the mainland Puerto Rican children (47.7% vs. 28.9%, respectively), whereas the use of illicit drugs was far greater among mainland compared to island Puerto Rican youth (that is, 15.0 vs. 6.9%, respectively; Conway et al., 2007). Investigation of the explanations for greater illicit drug use among migrant youth may yield information on the environmental factors that contribute to substance use and abuse. These findings highlight the importance of country or culture-specific influences on patterns of substance use. GENETIC INFLUENCES Advances in molecular and human genetics have led to the identification of nearly all of the genes underlying Mendelian diseases (that is, those with clear-cut adherence to Mendelian law such as autosomal dominant, autosomal recessive, or X-linked). This progress has been revolutionary in terms of prediction of disease risk (for example, Huntington’s disease; Langbehn et al., 2004), and understanding of pathogenesis (for example, familial hemiplegic migraine; and Alzheimer’s disease, Hardy and Selkoe, 2002). The rapid success in identifying genes for Mendelian diseases generated the expectation that the same research strategies would eventually be successful in identifying genes for complex diseases, such as heart disease, obesity, cancer, diabetes, and many psychiatric conditions, but identification of genes for other complex disorders has proven far more difficult. Recent successes, however, have renewed hopes that replicable candidate genes will be identified in psychiatry in the future.

Linkage Studies The traditional approach for locating a disease gene in humans is linkage analysis, which tests the association between deoxyribonucleic acid (DNA) polymorphic markers and affected status within families. After linkage is detected with an initial marker, many other markers nearby may also be examined. Markers showing the strongest correlation with disease in families are assumed to be closest to the disease locus. Linkage analysis uses DNA sequences with high variability (that is, polymorphisms) to increase the power to identify markers that are associated with a disease within families. Historically, different methodological approaches have been applied. Earlier linkage studies employed restriction fragment length polymorphisms (RFLPs), whereas subsequent studies examined short tandem repeat markers, or “microsatellites,” DNA sequences that show considerable variability among people but whose variability has no functional consequences. More recently, linkage and association studies have examined single nucleotide polymorphisms (SNPs) to track diseases in families. Markers in the candidate region identified by linkage analysis can be used to narrow the location of the disease gene through linkage disequilibrium analysis. Linkage disequilibrium is a population association between two alleles at different loci and occurs when the same founder mutation exists in a large proportion of individuals who are affected in the population studied. Usually, the closer the marker is to the disease locus, the greater the proportion of individuals who are affected who carry the identical allele at the marker (Risch, 2000). However, in measuring the strength of linkage disequilibrium for a given marker, it is also important to select unaffected control individuals from the same population because an allele shared among individuals who are affected may also be common in the general population and thus shared by chance rather than due to proximity to the disease locus (Risch, 2000). For complex human diseases, a simple mode of genetic inheritance is not apparent, and indeed, multiple contributing genetic loci are likely to be involved. Study designs that do not depend on the particular mode of inheritance are required for linkage analysis. Because relatives who are affected provide most of the information for such analyses, studies that focus on searching for increased sharing of marker alleles above chance expectation among relatives who are affected may be employed. The simplest of such studies involves sibships who are affected, where allele sharing in excess of 50% (the expectation when there is no linkage) is sought. Association Studies Association studies generally employ a case-control design to compare candidate genes among individuals affected to those among unrelated unaffected controls.

47: GENETIC EPIDEMIOLOGY

Failure to equate cases and controls may lead to confounding (that is, a spurious association due to an unmeasured factor that is associated with the candidate gene and the disease). In genetic case-control studies, the most likely source of confounding is ethnicity because of differential gene and disease frequencies in different ethnic subgroups. The association study design also generally employs a candidate gene approach to identify susceptibility genes for a particular disorder. The candidate gene approach has enjoyed only limited success because few of the genes that have been identified have withstood the test of replication (Altmuller et al., 2001; Ioannidis et al., 2001; Hirschhorn et al., 2002; Hirschhorn and Daly, 2005). The chief obstacles to identifying genes for complex diseases with the candidate gene approach include the lack of validity of phenotype characterization, biased sampling, inadequate controls, failure to correct for multiple tests, high false-positive rate due to low a priori probability, use of an overly liberal alpha value, and the lack of adequate power of gene searching approaches (Risch, 2000; Glazier et al., 2002; Wacholder et al., 2004; Todd, 2006). In addition, there is a strong publication bias against reports of negative association studies (Ioannidis et al., 2001; Ott, 2004). To offset the high false-positive rate that has plagued the literature on complex disease genetics, journals in nearly all fields of medicine have published editorials about these high rates of false positives or have adopted publication policies that take into account the potential for false positives when reviewing articles (Begg, 2005). Genome-Wide Association Studies Because of the lack of replication of association studies of candidate genes, the genome-wide association method has been proposed as the most promising approach to gene identification in future studies of complex diseases (Botstein and Risch, 2003; Hirschhorn and Daly, 2005). The genome-wide association method, which is based on a systematic search of equally spaced genetic markers across the genome among cases and controls, was demonstrated to have greater power than linkage (withinfamily associations between genetic markers and disease) and association studies, which evaluate associations of prespecified candidate genes and diseases between sibling pairs or between cases and controls (Risch and Merikangas, 1996). The identification of a large set of common SNPs, which explains much of the common variation in the human genome, by the International HapMap Consortium (2005) and the advent of high throughput genotyping chips that can survey over 500,000 of these SNPs at a single pass, have increased the feasibility of mapping individual genome variation quickly, which allows for the comparison of large numbers of cases and controls. Because of these advances, it is possible to conduct whole genome association stud-

795

ies that could link common SNPs as well as copy number variations to vulnerability to complex disorders. Recent successes using this approach include the identification of genes for macular degeneration (Edwards et al., 2005; Haines et al., 2005; Klein et al., 2005) and several other complex disorders including inflammatory bowel diseases (Crohn’s disease and ulcerative colitis; Duerr et al., 2006), diabetes (Groves et al., 2006; Field et al., 2007; Grant et al., 2006; Sladek et al., 2007), and prostate cancer (Amundadottir et al., 2006; Freedman et al., 2006). Although independent replications have confirmed the potential fruitfulness of this approach, it has not yet been successfully applied to gene identification for psychiatric disorders (Couzin and Kaiser, 2007). Gene Identification Studies in Psychiatry Based on the dramatic advances in molecular genetics during the past 20 years, as described above, there has been a major shift in the focus of psychiatric genetic investigations during the past decade from elucidating patterns of familial transmission to localizing genes underlying mental disorders using linkage studies and association studies. Although there remains controversy regarding the constitution of replications of genetic findings for several mental disorders, there are several recent, promising findings in psychiatric genetics. The increasing tendency for collaborative efforts on genetics studies within psychiatry may yield greater power to detect genes of small effect. The emergence of an international consensus on standards for replication (Chanock et al., 2007) and the application of new approaches for identifying genes may lead to an understanding of the etiology of psychiatric disorders such as already exists for numerous other complex diseases. Selection of candidate genes for substance use and disorders has been based either on drug metabolism (pharmacokinetics) or drug response (pharmacodynamics) in the CNS or periphery (Saxon et al., 2007). The brain reward pathway is the system that has been studied most extensively in identifying genetic factors underlying drug abuse. Candidate genes for substance use and disorders have been summarized for smoking by Ho and Tyndale (2007), for opioids and cocaine by Saxon et al. (2007), for alcoholism (Edenberg and Faroud, 2006), and for general vulnerability factors by Kreek et al. (2005). The reader can refer to http://geneticassociationdb.nih.gov for a complete and updated list of the status of findings on specific candidate genes. A summary of candidate genes that have been investigated for one or more of these substances is presented in Table 47.2. With the exception of the alcohol metabolism genes, most of the genes have been investigated in only a few studies, and replications have not been forthcoming. One area that has received widespread attention in the drug abuse field has been the translation of find-

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ings regarding susceptibility genes to clinical settings and to public health as a whole. Because of the multiple levels of influence on drug availability—including macroinfluences such as government, health care, industry, and the education system, as well as environment— it has been proposed that the identification of genes underlying drug use may have less of a contribution to the prevention of drug abuse and dependence than the institution of policy measures that reduce drug exposure (Merikangas and Risch, 2003; Hall, 2005). On the other hand, identification of the genetic factors involved in conferring increased biological vulnerability to drug abuse and dependence as well as cessation may advance our understanding of the pathogenesis of drug abuse and inform efforts to block the effects of drugs and to enhance the effects of treatment. The most compelling potential benefit of gene identification would be the development of medications that block relevant metabolic enzymes to reduce dependence on a particular drug (Saxon et al., 2007). The use of genetic testing for drug abuse vulnerability is far less feasible because of ethical concerns engendered by the potential danger of labeling such individuals as well as the potential for increasing drug use among those who lack a susceptibility marker (Merikangas and Risch, 2003; Hall, 2005; Saxon et al., 2007). SUMMARY AND FUTURE DIRECTIONS Substance use is a complex phenomenon, inherently characterized by a gene–environment interaction because exposure to an exogenous substance is necessary for its expression. This phenotype is ideally suited for investigation using the tools of epidemiology, which can examine the interactions between individual vulnerability factors and environmental exposure. Additional large-scale community epidemiological studies from diverse populations are critical for elucidating the role of genetic and environmental factors in the transmission of substance abuse, validating phenotypic definitions of substance use/abuse, and identifying sources of heterogeneity in the etiology of substance abuse, particularly with respect to the role of comorbid psychiatric disorders and polysubstance abuse. The information gleaned from these studies will ultimately lead to more effective gene identification. This chapter summarized the results of family, twin, adoption, and high-risk studies that concur in concluding that drug use and abuse/dependence are highly familial. The results of twin and adoption studies demonstrate that genetic factors underlie a substantial component of the familial clustering of drug use disorders. Although these human genetic studies have been helpful in looking at patterns of transmission, possible degrees of genetic heritability, and environmental catalysts, there are numerous phenomena that complicate the applica-

tion of the traditional tools of genetics in identifying the specific genes underlying these conditions. Additional research is necessary for the refinement of the definitions and phenotypic descriptions of substance use and progression. Likewise, discrimination of risk factors common to drug use versus those unique to the use of a particular substance, as well as those related to use versus progression and dependence, will be critical in identifying genetic sources of variance. Progress in identifying genes for substance use and disorders through linkage and association studies of candidate genes have generated few findings that meet the standards of external replication. Nevertheless, there is a number of promising candidate genes that may prove to contribute to drug abuse phenotypes as the results of the genome-wide approaches in large samples from collaborative efforts among investigators begin to emerge. These studies may also identify new candidate genes that could advance our understanding of the complex pathways that lead to drug abuse.

REFERENCES Agrawal, A., Lynskey, M.T., Bucholz, K.K., Martin, N.G., Madden, P.A., and Heath, A.C. (2007) Contrasting models of genetic comorbidity for cannabis and other illicit drugs in adult Australian twins. Psychol. Med. 37(1):49–60. Agrawal, A., Neale, M.C., Jacobson, K.C., Prescott, C.A., and Kendler, K.S. (2005) Illicit drug use and abuse/dependence: modeling of two-stage variables using the CCC approach. Addict. Behav. 30:1043–1048. Agrawal, A., Neale, M.C., Prescott, C.A., and Kendler, K.S. (2004) Cannabis and other illicit drugs: comorbid use and abuse/dependence in males and females. Behav. Genet. 34:217–228. Altmuller, J., Palmer, L.J., Fischer, G., Scherb, H., and Wjst, M. (2001) Genomewide scans of complex human diseases: true linkage is hard to find. Am. J. Hum. Genet. 69(5):936–950. American Psychiatric Association. (1980) Diagnostic and Statistical Manual of Mental Disorders, 3rd ed. Washington, DC: Author. Amundadottir, L.T., et al. (2006) A common variant associated with prostate cancer in European and African populations. Nat. Genet. 38:652–658. Andrews, J.A., Hops, H., and Duncan, S.C. (1997) Adolescent modeling of partent substance use: the moderating effect of the relationship with the parent. J. Fam. Psychol. 11:259–270. Anthony, J.C., and Helzer, J.E. (1995) Epidemiology of drug dependence. In: Tsuang, M.T., Tohen, M., Zahner, G.E.P., eds. Textbook in Psychiatric Epidemiology. New York: John Wiley & Sons, pp. 1364–1365. Avenevoli, S., Conway, K.P., and Merikangas, K.R. (2005) Familial risk factors for substance use disorders. In: Hudson, J.L., and Rapee, R.M., eds. Current Thinking on Psychopathology and the Family. Boston: Elsevier, pp. 167–192. Begg, C.B. (2005) Reflections on publication criteria for genetic association studies. Cancer Epidemiol. Biomarkers Prev. 14:1364–1365. Bierut, L.J., Dinwiddie, S.H., Begleiter, H., Crowe, R.R., Hesselbrock, V., Nurnberger, J.I., Jr., Porjesz, B., Schuckit, M.A., and Reich, T. (1998) Familial transmission of substance dependence: alcohol, marijuana, cocaine, and habitual smoking: a report from the Collaborative Study on the Genetics of Alcoholism. Arch. Gen. Psychiatry 55(11):982–988. Boomsma, D.I., Koopmans, J.R., Van Doornen, L.J.P., and Orlebeke, J.F. (1994) Genetic and social influences on starting to smoke: A

47: GENETIC EPIDEMIOLOGY study of Dutch adolescent twins and their parents. Addiction 89: 219–226. Botstein, D., and Risch, N. (2003) Discovering genotypes underlying human phenotypes: past successes for Mendelian disease, future approaches for complex disease. Nat. Gen.33(Suppl):228–237. Brook, J.S., Brook, D.W., Gordon, A.S., Whiteman, M., and Cohen, P. (1990) The psychosocial etiology of adolescent drug use: a family interactional approach. Genet. Soc. Gen. Psychol. Monogr. 116:111– 267. Brook, J.S., Whiteman, M., Gordon, A.S., and Cohen, P. (1986) Some model mechanisms for explaining the impact of maternal and adolescent characteristics on adolescent stage of drug use. Dev. Psychology 22:460–467. Brown, S.A. (1989) Life events of adolescents in relation to personal and parental substance abuse. Am. J. Psychiatry 146:484 – 489. Bucholz, K.K., Heath, A.C., and Madden, P.A. (2000) Transitions in drinking in adolescent females: evidence from the Missouri adolescent female twin study. Alcohol Clin. Exp. Res. 4(6):914–923. Cadoret, R.J. (1992) Genetic and environmental factors in initiation of drug use and the transition to abuse. In: Glantx, M., and Pickens, R., eds. Vulnerability to Drug Abuse. Washington, DC: American Psychological Association, pp. 99–113. Cadoret, R.J., Troughton, E., O’Gorman, T., and Heywood, E. (1986) An adoption study of genetic and environmental factors in drug abuse. Arch. Gen. Psychiatry 43:1131–1136. Cadoret, R.J., Yates, W.R., Troughton, E., Woodworth, G., and Stewart, M.A. (1995) Adoption study demonstrating two genetic pathways to drug abuse. Arch. Gen. Psychiatry 52:42–52. Cadoret, R.J., Yates, W.R., Troughton, E., Woodworth, G., and Stewart, M.A. (1996) An adoption study of drug abuse/dependence in females. Compr. Psychiatry 37:88–94. Chanock, S.J., et al. (2007) Replicating genotype-phenotype associations. Nature 447(7145):655–660. Chassin, L., Rogosch, F., and Barera, M. (1991) Substance use and symptomatology among adolescent children of alcoholics. J. Abnorm. Psychol. 100(4):449–463. Claridge, G., Ross, E., and Hume, W.I. (1978) Sedative Drug Tolerance in Twins. Oxford, UK: Pergamon Press. Compton, W.M., Cottler, L.B., Ridenour, T., Ben-Abdallah, A., and Spitznagel, E.L. (2002) The specificity of family history of alcohol and drug abuse in cocaine abusers. Am. J. Addict. 11(2):85–94. Compton, W.M., Thomas, Y.F., Stinson, F.S., and Grant, B.F. (2007) Prevalence, correlates, disability, and comorbidity of DSM-IV drug abuse and dependence in the United States: results from the national epidemiologic survey on alcohol and related conditions. Arch. Gen. Psychiatry 64(5):566–576. Conway, K.P., Compton, W.M., Stinson, F.S., & Grant, B.F. (2006) Lifetime comorbidity of DSM-IV mood and anxiety disorders and specific drug use disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J. Clin. Psychiatry 67:247–257. Conway, K.P., Swendsen, J.D., Dierker, L., Canino, G., and Merikangas, K.R. (2007) Psychiatric comorbidity and acculturation stress among Puerto Rican substance abusers. Am. J. Prev. Med. 32: S219–S225. Conway, K.P., Swendsen, J.D., and Merikangas, K.R. (2003) Expectancies, alcohol consumption, and problem drinking: the importance of family history. Addict. Behav. 28:823–836. Couzin, J., and Kaiser, J. (2007) Genome wide association studies: closing the net on complex disease genes. Science 64:820–822. Croughan, J.L. (1985) The contributions of family studies to understanding drug abuse. In: Robins, L., ed. Studying Drug Abuse. New Brunswick, NJ: Rutgers University Press, pp. 240–264. Duerr, R.H., Taylor, K.D., Brant, S.R., Rioux, J.D., Silverberg, M.S., Daly, M.J., Steinhart, A.H., Abraham, C., Regueiro, M., Griffiths, A., Dassopoulos, T., Bitton, A., Yang, H., Targan, S., Datta, L.W., Kistner, E.O., Schumm, L.P., Lee, A.T., Gregersen, P.K., Barmada, M.M., Rotter, J.I., Nicolae, D.L., and Cho, J.H. (2006)

797

A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science 314:1461–1463. Edenberg, H.J., and Faroud, T. (2006) The genetics of alcoholism: Identifying specific genes through family studies. Addiction Biol. 11:386–396. Edwards, A., Ritter, R., and Abel, K. (2005) Complement factor H polymorphism and age-related macular degeneration. Science 308: 421– 424. Field, S.F., Howson, J.M., Smyth, D.J., Walker, N.M., Dunger, D.B., and Todd, J.A. (2007) Analysis of the type 2 diabetes gene, TCF7L2, in 13,795 type 1 diabetes cases and control subjects. Diabetologia 50:212–213. Fowler, T., Lifford, K., Shelton, K., Rice, F., Thapar, A., Neale, M.C., McBride, A., and van den Bree, M.B. (2007) Exploring the relationship between genetic and environmental influences on initiation and progression of substance use. Addiction 102(3):413– 422. Freedman, M.L., Haiman, C.A., Patterson, N., McDonald, G.J., Tandon, A., Waliszewska, A., Penney, K., Steen, R.G., Ardlie, K., John, E.M., Oakley-Girvan, I., Whittemore, A.S., Cooney, K.A., Ingles, S.A., Altshuler, D., Henderson, B.E., and Reich, D. (2006) Admixture mapping identifies 8q24 as a prostate cancer risk locus in African-American men. Proc. Natl. Acad. Sci. USA 103: 14068–14073. Gfroerer, J. (1987) Correlation between drug use by teenagers and drug use by older family members. Am. J. Drug Alcohol Abuse 13:95–108. Gillespie, N.A., Kendler, K.S., Prescott, C.A., Aggen, S.H., Gardner, C.O., Jacobson, K., and Neale, M.C. (2007) Longitudinal modeling of genetic and environmental influences on self-reported availability of psychoactive substances: alcohol, cigarettes, marijuana, cocaine, and stimulants. Psychol. Med. 37(7):947–959. Glazier, A.M., Nadeau, J.H., and Aitman, T.J. (2002) Finding genes that underlie complex traits. Science 298(5602):2345–2349. Gorenstein, E.E., and Newman, J.P. (1980) Disinhibitory psychopathology: a new perspective and a model for research. Psychol. Rev. 87(3):301–315. Grant, B.F., Dawson, D.A., Stinson, F.S., Chou, S.P., Dufour, M.C., and Pickering, R.P. (2004) The 12-month prevalence and trends in DSM-IV alcohol abuse and dependence: United States, 1991– 1992 and 2001–2002. Drug Alcohol Depend. 74(3):223–234. Grant, J.D., Heath, A.C., Bucholz, K.K., Madden, P.A., Agrawal, A., Statham, D.J., and Margin, N.G. (2007) Spousal concordance for alcohol dependence: evidence for assortative mating or spousal interaction effects? Alcohol Clin. Exp. Res. 31(5):717–728. Grant, S.F., et al. (2006) Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat. Genet 38: 320–323. Grove, W., Eckert, E., Heston, L., Bouchard, T., Segal, N., and Lykken, D. (1990) Heritability of substance abuse and antisocial behavior: A study of monozygotic twins reared apart. Biol. Psychiatry 27:1293–1304. Groves, C.J., et al. (2006) Association analysis of 6,736 U.K. subjects provides replication and confirms TCF7L2 as a type 2 diabetes susceptibility gene with a substantial effect on individual risk. Diabetes 55:2640–2644. Gurling, H., Grant, S., and Dangl, J. (1985) The genetic and cultural transmission of alcohol use, alcoholism, cigarette smoking and coffee drinking: a review and an example using a log linear cultural transmission model. Br. J. Addict. 80:269–279. Haines, J., Hauser, M., Schmidt, S., et al. (2005) Complement factor H variant increases the risk of age-related macular degeneration. Science 308:419– 421. Hall, W.D. (2005) Will nicotine genetics and a nicotine vaccine prevent cigarette smoking and smoking-related diseases? PLoS Med. 2:860–863. Hardy, J., and Selkoe, D.J. (2002) The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297:353–356.

798

SUBSTANCE ABUSE DISORDERS

Hawkins, J.D., Catalano, R.F., and Miller, J.Y. (1992) Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance abuse prevention. Psychol. Bull. 112:64–105. Heath, A.C., Bulchoz, K.K., Madden, P., Dinwiddie, S.H., Slutske, W.S., Bierut, L.J., Statham, D.J., Dunne, M.P., Whitfield, J.B., and Martin, N.G. (1997) Genetic and environmental contributions to alcohol dependence risk in a national twin sample: consistency of findings in women and men. Psychol. Med. 27:1381–1396. Heath, A.C., Cates, R., Martin, N.G., Meyer, J., Hewitt, J.K., Neale, M.C., and Eaves, L.J. (1993) Genetic contribution to risk of smoking initiation: Comparisons across birth cohorts and across cultures. J. Subst. Abuse 5:221–246. Heath, A.C., and Madden, P.A.F. (1995) Genetic influences on smoking behavior. In: Turner, J.R., Cardon, L.R., and Hewitt, J.K., eds. Behavior Genetic Approaches in Behavioral Medicine. New York: Plenum Press, pp. 45–63. Hill, S.Y., Cloninger, C.R., and Ayre, A.B. (1977) Independent familial transmission of alcoholism and opiate abuse. Alcohol Clin. Exp. Res. 1:335–342. Hill, S.Y., and Hruska, D.R. (1992) Childhood psychopathology in families with multigenerational alcoholism. J. Am. Acad. Child Adolesc. Psychiatry 31(6):1024–1030. Hirschhorn, J.N., and Daly, M.J. (2005) Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6:95–108. Hirschhorn, J.N., Lohmueller, K., Byrne, E., and Hirschhorn, K. (2002) A comprehensive review of genetic association studies. Genet. Med. 4:45–61. Ho, M.K., and Tyndale, R.F. (2007) Overview of the pharmacogenomics of cigarette smoking. Pharmacogenomics J. 7:81–98. Hoffman, J.P., and Cerbone, F.G. (2002) Parental substance use disorder and the risk of adolescent drug abuse: an event history analysis. Drug Alcohol Depend. 66:255–264. Hopfer, C.J., Crowlery, T.J., and Hewitt, J.K. (2003) Review of twin and adoption studies of adolescent substance use. J. Am. Acad. Child Adolesc. Psychiatary 42:710–719. ICR/International Communications Research. (1996) Public Health Survey. Harvard School of Public Health and the Robert Wood Johnson Foundation. International HapMap Consortium. (2005) A haplotype map of the human genome. Nature 437:1299–1320. Ioannidis, J.P., Ntzani, E.E., Trikalinos, T.A., and ContopoulosIoannidis, D.G. (2001) Replication validity of genetic association studies. Nat. Genet. 29:306–309. Jang, K.L., Livesley, W.J., and Vermon, P.A. (1995) Alcohol and drug problems: a multivariate behavioral genetic analysis of comorbidity. Addiction 90:1213–1221. Johnson, S., Leonard, K.E., and Jacob, T. (1989) Drinking, drinking styles and drug use in children of alcoholics, depressives and controls. J. Stud. Alcohol 50(5):427–431. Johnston, L.D., O’Malley, P.M., Bachman, J.G., and Schulenberg, J.E. (2006) Monitoring the Future national survey results on drug use, 1975–2005. Volume I, Secondary school students (NIH Publication No. 06-5883). Bethesda, MD: National Institute on Drug Abuse. Joutel, A., Bousser, M.G., Biousse, V., et al. (1993) A gene for familial hemiplegic migraine maps to chromosome 19. Nat. Genet. 5:40–45. Kandel, D.B., and Andrews, K. (1987) Processes of adolescent socialization by parents and peers. Int. J. Add. 22:319–342. Karkowski, L.M., Prescott, C.A., and Kendler, K.S. (2000) Multivariate assessment of factors influencing illicit substance use in twins from female-female pairs. Am. J. Med. Genet. 96:665–670. Kendler, K., Aggen, S., Tambs, K., and Reichborn-Kjennerud, T. (2006) Illicit psychoactive substance use, abuse and dependence in a population-based sample of Norwegian twins. Psychol. Med. 36(7): 955–962.

Kendler, K.S., Gardner, C., Jacobson, K., Neale, M., and Prescott, C. (2005) Genetic and environmental influences on illicit drug use and tobacco use across birth cohorts. Psychol. Med. 35(9):1349– 1356. Kendler, K.S., Jacobsdon, K.C., Prescott, C.A., and Neale, M.C. (2003) Specificity of genetic and environmental risk factors for use and abuse/dependence of cannabis, cocaine, hallucinogens, sedatives, stimulants, and opiates in male twins. Amer. J. Psychiatry 160: 687–695. Kendler, K.S., Karkowski, L.M., Neale, M.C., and Prescott, C.A. (2000) Illicit psychoactive substance use, heavy use, abuse and dependence in a US population-based sample of male twins. Arch. Gen. Psychiatry 57:261–269. Kendler, K.S., Karkowski, L.M., and Prescott, C.A. (1999) Hallucinogen, opiate, sedative and stimulant use and abuse in a population-based sample of female twins. Acta Psychiatr. Scand. 99: 368–376. Kendler, K.S., Neale, M.C., Sullivan, P., Corey, L.A., Gardner, C.O., and Prescott, C.A. (1999) A population-based twin study in women of smoking initiation and nicotine dependence. Psychol. Med. 29:299–308. Kendler, K.S., and Prescott, C.A. (1998a) Cannabis use, abuse and dependence in a population-based sample of female twins. Am. J. Psychiatry 155:1016–1022. Kendler, K.S., and Prescott, C.A. (1998b) Cocaine use, abuse and dependence in a population based sample of female twins. Br. J. Psychiatry 173:345–350. Kessler, R.C., Berglund, P., Demler, O., Jin, R., Merikangas, K.R., and Walters, E.E. (2005) Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch. Gen. Psychiatry 62(6):593–602. Kessler, R.C., Crum, R.M., Warner, L.A., Nelson, C.B., Schulenberg, J., and Anthony, J.C. (1997) Lifetime co-occurrence of DSM-IIIR alcohol abuse and dependence with other psychiatric disorders in the National Comorbidity Survey. Arch. Gen. Psychiatry 54: 313–321. Kessler, R.C., Nelson, C.B., McGonagle, K.A., Edlund, M.J., Frank, R.G., and Leaf, P.J. (1996) The epidemiology of co-occurring addictive and mental disorders: implications for prevention and service utilization. Am. J. Orthopsychiatry 66:17–31. Khantzian, E.J. (1983) An extreme case of cocaine dependence and marked improvement with methylphenidate treatment. Am. J. Psychiatry 140:784–785. Khantzian, E.J., and Treece, C. (1985) DSM-III psychiatric diagnosis of narcotic addicts: recent findings. Arch. Gen. Psychiatry 42: 1067–1077. Kleber, H.D., and Riordan, C.E. (1982) The treatment of narcotic withdrawal: a historical review. J Clin. Psychiatry 43(6):30–34. Klein, R., Zeiss, C., Chew, E., et al. (2005) Complement factor H polymorphism in age-related macular degeneration. Science 308: 385–389. Kolonel, L.N., Altshuler, D., and Henderson, B.E. (2004) The multiethnic cohort study: exploring genes, lifestyle and cancer risk. Nat. Rev. Cancer 4:519–527. Kreek, M.J., Nielsen, D.A., Butelman, E.R., and LaForge, K.S. (2005) Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction. Nat. Neurosci. 8(11):1450–1457. Langbehn, D.R., Brinkman, R.R., Falush, D., et al. (2004) A new model for prediction of the age of onset and penetrance for Huntington’s disease based on CAG length. Clin. Genet. 65(4):267–277. Langbehn, D.R., Cadoret, R.J., Caspers, K., Troughton, E.P., and Yucuis, R. (2003) Genetic and environmental risk factors for the onset of drug use and problems in adoptees. Drug Alcohol Depend. 69(2):151–167. Lin, N., Eisen, S.A., Scherrer, J.F., Goldberg, J., True, W.R., Lyons, M.J., and Tsuang, M.T. (1996) The influence of familial and non-

47: GENETIC EPIDEMIOLOGY familial factors on the association between major depression and substance abuse/dependence in 1874 monozygotic male twin pairs. Drug Alcohol Depend. 43(1/2):49–55. Luthar, S.S., and Rounsaville, B.J. (1993) Substance misuse and comorbid psychopathology in a high-risk group: a study of siblings of cocaine misusers. Int. J. Addict. 28:415–434. Lynskey, M.T., Grant, J.D., Li, L., Nelson, E.C., Bucholz, K.K., Madden, P.A., Statham, D., Martin, N.G., and Heath, A.C. (2007) Stimulant use and symptoms of abuse/dependence: epidemiology and associations with cqannabis use—a twin study. Drug Alcohol Depend. 86(2–3):147–153. Lynskey, M.T., Heath, A.C., Nelson, E.C., Bucholz, K.K., Madden, P.A.F., Slutske, W.S., Statham, D.J., and Martin, N.G. (2002) Genetic and environmental contributions to cannabis dependence in a national young adult twin sample. Psychol. Med. 32:195–207. Maes, H.H., Neale, M.C., Kendler, K.S., Martin, N.G., Heath, A.C., and Eaves, L.J. (2006) Genetic and cultural transmission of smoking initiation: an extended trwin kinship model. Behav. Genet. 36(3):795–808. Martin, C.S., Earleywine, M., Blackson, T.C., Vanyukov, M.M., Moss, H.B., and Tarter, R.E. (1994) Aggressivity, inattention, hyperactivity, and impulsivity in boys at high and low risk for substance abuse. J. Abnorm. Child Psychol. 22(2):177–203. McGue, M (1994) Genes, environment, and the etiology of alcoholism. In: Zucker, R., Boyd, G., and Howard, J. eds. The Development of Alcohol Problems: Exploring the Biopsychosocial Matrix (Research Monograph No. 26). Rockville, MD: U.S. Department of Health and Human Services. Meller, W.H., Rinehart, R., Cadoret, R.J., and Troughton, E. (1988) Specific familial transmission in substance abuse. Int. J. Addict. 23:1029–1039. Merikangas, K.R. (1990) The genetic epidemiology of alcoholism. Psychol. Med. 20:11–22. Merikangas, K.R., and Avenevoli, S. (2000) Implications of genetic epidemiology for the prevention of substance use disorders. Addict. Behav. 256:807–820. Merikangas, K.R., Dierker, L.C., and Szatmari, P. (1998) Psychopathology among offspring of parents with substance abuse and/or anxiety: a high risk study. J. Child Psychol. Psychiatry 39(5): 711–720. Merikangas, K.R., and Risch, N. (2003) Genomic priorities and public health. Science 24:599–601. Merikangas, D.R., Rounsaville, B.J., and Prusoff, B.A. (1992) Familial factors in vulnerability to substance abuse. In: Glantz, M.D., and Pickens, R.W., eds. Vulnerability to Drug Abuse. Washington, DC: American Psychological Association, pp. 75–98. Merikangas, K.R., Stolar, M., Stevens, D.E., Goulet, J., Preisig, M., Fenton, B., O’Malley, S., and Rounsaville, B.J. (1998) Familial transmission of substance use disorders. Arch. Gen. Psychiatry 55(11): 973–979. Mirin, S.M., Weiss, R.D., Griffin, M.L., and Michael, J.L. (1991) Psychopathology in drug abusers and their families. Compr. Psychiatry 32:36–51. Mirin, S.M., Weiss, R.D., and Michael, J.L. (1988) Pyschopathology in substance abusers: diagnosis and treatment. Am. J. Drug Alcohol Abuse 14:139–157. Mirin, S.M., Weiss, R.D., Sollogub, A., and Michael, J.L. (1984) Affective Illness in Substance Abusers, in Substance Abuse and Psychopathology. Washington, DC: American Psychiatric Press, pp. 58–77. Moss, H.B., Majumder, P.P., and Vanyukov, M. (1994) Familial resemblance for psychoactive substance use disorders: behavioral profile of high risk boys. Addict. Behav. 19(2):199–208. NCI-NHGRI Working Group on Replication in Association Studies, Chanock, S.J., Manolio, T., Boehnke, M., Boerwinkle, E., Hunter, D.J., Thomas, G., Hirschhorn, J.N., Abecasis, G., Altshuler, D., Bailey-Wilson, J.E., Brooks, L.D., Cardon, L.R., Daly, M., Donnelly,

799

P., Fraumeni, J.F., Jr., Freimer, N.B., Gerhard, D.S., Gunter, C., Guttmacher, A.E., Guyer, M.S., Harris, E.L., Hoh, J., Hoover, R., Kong, C.A., Merikangas, K.R., Morton, C.C., Palmer, L.J., Phimister, E.G., Rice, J.P., Roberts, J., Rotimi, C., Tucker, M.A., Vogan, K.J., Wacholder, S., Wijsman, E.M., Winn, D.M., and Collins, F.S. (2007) Replicating genotype-phenotype associations. Nature 447(7145):655–660. Neal, M.C., Aggen, S.H., Maes, H.H., Kubarych, T.S., and Scmitt, J.E. (2006) Methodological issures in the assessment of substance use phenotypes. Addict. Behav. 31(6):1010–1034. Nurnberger, J.I., Wiegand, R., Bucholz, K., O’Connor, S., Meyer, E. T., Reich, T., Rice, J., Schuckit, M., King, L., Petti, T., Bierut, L., Hinrichs, A.L., Kuperman, S., Hesselbrock, V., and Porjesz, B. (2004) A family study of alcohol dependence: coaggregation of multiple disorders in relatives of alcohol-dependent probands. Arch. Gen. Psychiatry 61(12):1246–1256. Ott, J. (2004) Association of genetic loci: replication or not, that is the question. Neurology 63:955–958. Pedersen, N. (1981) Twin similarity for usage of common drugs. Prog. Clin. Biol. Res. 69:53–59. Pergadia, M.L, Heath, A., Martin, N., and Madden, P. (2006) Genetic analyses of DSM-IV nicotine withdrawal in adult twins. Psychol. Med. 36(7):963–972. Pickens, R., Svikis, D., McGue, M., Lykken, D., Heston, L., and Clayton, P. (1991) Heterogeneity in the inheritance of alcoholism: a study of male and female twins. Arch. Gen. Psychiatry 48:19–28. Prescott, C.A., and Kendler, K.S. (1999) Genetic and environmental contributions to alcohol abuse and dependence in a populationbased sample of male twins. Am. J. Psychiatry 156:34 – 40. Quitkin, F.M., Rifkin, A., Kaplan, J., and Klein, D.F. (1972) Phobic anxiety syndrome complicated by drug dependence and addiction. Arch. Gen. Psychiatry 27(2):159–162. Regier, D., Farmer, M.E., Rae, D.S., Locke, B.Z., Keith, S.J., Judd, L.L., et al. (1990) Comorbidity of mental disorders with alchohol and other drug abuse: results from the Epidemiologic Catchment Area (ECA) Study. JAMA 264:2511–2518. Reich, W., Earls, F., Frankel, O., and Shayka, J.J. (1993) Psychopathology in children of alcoholics. J. Am. Acad. Child Adolesc. Psychiatry 32:955–1002. Rhee, S.H., Hewitt, J.D., Young, S.E., Corley, R.P., Crowley, T.J., and Stallings, M.C. (2003) Genetic and environmental influences on substance initiation, use, and problem use in adolescents. Arch. Gen. Psychiatry 60:1256–1264. Risch, N. (2000) Searching for genetic determinants in the new millennium. Nature 405:847–856. Risch, N., and Merikangas, K.R. (1996) The future of genetic studies of complex human diseases. Science 273:1516–1517. Ross, H.E., Glaser, F.B., and Germanson, T. (1988) The prevalence of psychiatric disorders in patients with alcohol and other drug problems. Arch. Gen. Psychiatry 45:1023–1032. Rounsaville, B.J., Kosten, T.R., Weissman, M.M., Prosoff, B., Pauls, D., Anton, S.F., and Merikangas, K.R. (1991) Psychiatric disorders in relatives of probands with opiate addiction. Arch. Gen. Psychiatry 48:33–42. Rounsaville, B.J., Weissman, M.M., Kleber, H., and Wilber, C. (1982) Heterogeneity of psychiatric diagnosis in treated opiate addicts. Arch. Gen. Psychiatry 39(2):161–166. Sartor, C.E., Lynskey, M.T., Heath, A.C., Jacob, T., and True, W. (2007) The role of childhood risk factors in initiation of alcohol use and progression to alcohol dependence. Addiction 102(2):216–225. Saxon, A.J., Oreskovich, M.R., and Brkanac, Z. (2007) Genetic determinants of addiction to opioids and cocaine. Harv. Rev. Psychiatry 13(4):218–232. Sher, K.J., Walitzer, K.S., Wood, P.K., and Brent, E.E. (1991) Characteristics of children of alcoholics: putative risk factors, substance use and abuse, and psychopathology. J. Abnorm. Child Psychol. 100:427–448.

800

SUBSTANCE ABUSE DISORDERS

Simcha-Fagagn, O., and Schwartz, J. (1986) Neighborhood and delinquency: an assessment of contextual effects. Criminology 24: 667–703. Sladek, R., Rocheleau, G., Rung, J., et al. (2007) A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 22:881–885. Tarter, R.E., Kirisci, L., Habeych, M., Reynolds, M., and Vanyukov, M.M. (2004) Neurobehavior disinhibition in childhood predisposes boys to substance use disorder by young adulthood: direct and mediated etiologic pathways. Drug Alcohol Depend. 73:121–132. Tarter, R.E., Kirisci, L., Mezzich, A., Cornelius, J.R., Pajer, K., Vanyukov, M.M., et al. (2003) Neurobehavioral disinhibition in childhood predicts early age at onset of substance use disorder. Am. J. Psychiatry 160:1078–1085. Todd, J.A. (2006) Statistical false positive or true disease pathway? Nat. Genet. 38:731–733. True, W.R., Heath, A.C., Scherrer, J.F., Waterman, B., Goldberg, J., Lin, N., Eisen, S.A., Lyons, M.J., and Tsuang, M.T. (1997) Genetic and environmental contributions to smoking. Addiction 92:1277–1287. True, W.R., Heath, A.C., Scherrer, J.F., Xian, H., Lin, N., Eisen, S.A., Lyons, M.J., Goldberg, J., and Tsuang, M.T. (1999) Interrelationship of genetic and environmental influences on conduct disosrder and alcohol and marijuana dependence symptoms. Am. J. Med. Genet. 88(4):391–397. True, W.R., Xian, H., Scherrer, J.F., Madden, P., Bucholz, K.K., Heath, A.C., Eisen, S.A., Lyons, M.J., Goldberg, J., and Tsuang, M. (1999) Common genetic vulnerability for nicotine and alcohol dependence in men. Arch. Gen. Psychiatry 56:655–661. Tsuang, M.T., Lyons, M.J., Eisen, S.A., Goldberg, J., True, W., Lin, N., Meyer, J.M., Toomey, R., Farone, S.V., and Eaves, L. (1996) Genetic influences on DSM-III-R drug abuse and dependence: a study of 3,372 twin pairs. Am. J. Med. Genet. 67:473–477. Tsuang, M.T., Lyons, M.J., Meyer, J.M., Doyle, T., Eisen, S.A., Goldberg, J., True, W., Lin, N., Toomey, R., and Eaves, L. (1998)

Co-occurrence of abuse of different drugs in men: the role of drug-specific and shared vulnerabilities. Arch. Gen. Psychiatry 55: 967–972. Van den Bree, M.B., Johnson, E.O., Neale, M.C., and Pickens, R.W. (1998) Genetic and environmental influences on drug use and abuse/dependence in male and female twins. Drug Alcohol Depend. 52:231–241. Vanyukov, M.M., Neale, M.C., Moss, H.B., and Tarter, R.E. (1996) Mating assortment and the liability to substance abuse. Drug Alcohol Depend. 42(1):1–10. Vanyukov, M.M., and Tarter, R.E. (2002) Genetic studies of substance abuse. Drug Alcohol Depend. 59:101–123. Volk, H.E., Scherrer, J.F., Bucholz, K.K., Todorov, A., Heath, A.C., Jacob, T., and True, W.R. (2007) Evidence for specificity of transmission of alcohol and nicotine dependence in a offspring of twins design. Drug Alcohol Depend. 87(2–3):225–232. Wacholder, S., Chanock, S., Garcia-Closas, M., El Ghormli, L., and Rothman, N. (2004) Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J. Natl. Cancer Inst. 96:434–442. Weiss, R.D., and Mirin, S.M. (1985) Treatment of chronic cocaine abuse and attention deficit disorder, residual type with magnesium pemoline. Drug Alcohol Depend. 15:69–72. Whitfield, J.B., Zhu, G., Madden, P.A., Neale, M.C., Heath, A.C., and Martin, N.G. (2004) The genetics of alcohol intake and of alcohol dependence. Alcohol Clin. Exp. Res. 28(8):1153–1160. Young, S.E., Rhee, S., Stallings, M., Corley, r., and Hewitt, J. (2006) Genetic and environmental vulnerabilities underlying adolescent substance use and problem use: general or specific? Behav. Genet. 36(4):603–615. Young, S.E., Stallings, M.C., Corley, R.P., Krauter, K.S., and Hewitt, J.K. (2000) Genetic and environmental influences on behavioral dishinhibition. Am. J. Med. Genet. 96:684–695.

48 Effects of Drugs of Abuse on Brain Development BARRY M. LESTER

A N D

BARRY E. KOSOFSKY

The most recent National Household Survey on Drug Abuse estimated that in 2004–2005, 3.9% of pregnant mothers used illicit drugs, including cocaine, in the past month (SAMHSA, 2005a). Even more alarming, the prevalence rate of illegal drug use was higher for pregnant women in the 15- to 18-year age range (12.3%) than for women 18–25 years old (7%). Moreover, the women who abuse illicit drugs often use licit drugs: An estimated 32% of those using one illicit drug during pregnancy also use alcohol and cigarettes. This national survey was based on self-report and thus is likely to underestimate the scope of the problem. Even with these conservative estimates, however, it is safe to say that gestational exposure to licit drugs of abuse such as alcohol and cigarettes and illicit drugs of abuse such as marijuana, cocaine, methamphetamine, and opiates is the single largest preventable cause of in utero developmental compromise of infants in the United States today. PROGRAMS UNDERLYING BRAIN DEVELOPMENT Central nervous system (CNS) development requires a complex orchestration of genetic factors and environmental forces that direct brain maturation and shape infant development in a reproducible yet individualized manner. The protracted timetable of CNS maturation affords a continuum of biologic vulnerability to the developing brain, which starts by 28 days postconception, when the template for brain development is established, and continues throughout gestation, infancy, and childhood. Moreover, the developmental consequences of a toxic CNS insult relate critically to the gestational timing of that exposure and at a given time during fetal development may vary from one brain region to another. Two general classes of CNS developmental disorders can be distinguished: those occurring in the first half of gestation that affect cytogenesis and histogenesis, and those occurring during the second half of gestation that affect brain growth and differentiation. During the organizational phase in the second half of ges-

tation, progressive events (neuroblast proliferation and migration, axonal projection, and synaptogenesis) and regressive events (programmed cell death and selective elimination of processes) critically shape the maturation of brain circuitry. Toxic influences during this period may dramatically alter brain development but may also alter the regressive events that underlie the capacity of the developing brain to compensate for injury. A pattern of molecular, biochemical, and metabolic maturation must parallel normal brain development and may impose regional stage-specific developmental requirements and vulnerabilities for maldevelopment. An understanding of basic mechanisms of drug action on the mother and the fetus following transplacental administration is crucially important for appreciating how such substances mediate their toxic effects in utero. Likewise, a deeper understanding of mechanisms operative during fetal brain development will form the basis for an improved understanding of how programs for brain development can be altered following in utero drug exposures with lasting consequence for brain structure and function. BEHAVIORAL TERATOLOGY This chapter reviews current thinking on the extent to which drugs of abuse may act as behavioral teratogens— drugs capable of altering brain development and subsequent function. Behavioral teratogens can alter internal fetal brain structure and function without any external changes, such as dysmorphic features. To determine whether drugs of abuse are behavioral teratogens requires consideration at four levels of analysis (Grimm, 1987): 1. Behavioral/cognitive level: Are there specific behavioral or cognitive deficits evident in subsets of infants and children who are exposed to drugs? 2. Systems level: Can alterations in particular brain structures and neurochemical systems that underlie the behavioral or cognitive deficits be identified? 801

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3. Developmental level: At which specific time(s) during fetal development is the brain susceptible to the actions of drugs of abuse? 4. Pharmacological/physiological level: What are the mechanisms by which particular drugs of abuse mediate their actions in utero? Part of the difficulty in establishing drugs of abuse as behavioral teratogens is that the behavioral consequences of gestational exposure to such drugs may not be evident at birth but may appear as the behavioral repertoire of the developing child matures. Therefore, one strives to identify antecedents of the behavioral abnormality. One also strives to identify predictive markers (clinical, neuroanatomical, neurophysiological, or neurochemical) of the subsequent expression of the behavioral anomaly. Implicit in this approach is a consideration of the role of genetic and environmental factors that may alter the susceptibility to, or expression of, a teratogenic effect. Over the last 20 years, there has been a tremendous effort to identify in the clinical setting and in preclinical models the extent to which drugs of abuse may act as behavioral teratogens. In general, experimental studies in animals have pursued a “bottomup” approach towards establishing a causal role for drugs of abuse in altering programs for brain development, moving from (4) the pharmacological/physiological level to (3) the developmental level, with the goal of modeling the relevant “clinical deficits” consequent to specific drug exposures at the (2) systems and (1) behavioral/ cognitive levels. Clinical research has progressed in a more “top-down” approach, with the goal of defining at (1) the behavioral/cognitive level and ideally at (2) the systems level, some of the phenotypic consequences in humans exposed to drugs of abuse, with efforts to reach towards (3) the developmental and (4) the pharmacological/physiological levels regarding the mechanistic basis of gestational drug exposure in contributing to that phenotype. One goal for future research would be to bridge across all four levels in preclinical models and clinical studies; although those bridges are most easily constructed in preclinical models, where confounding variables can be controlled (see below), it is often the case that some of the behaviors that one would like to model (for example, selective language delay) may not be accessible to modeling through preclinical experimental animal research programs.

BEHAVIORAL AND MOLECULAR MALFORMATION VERSUS DEFORMATION The effects of drug abuse on the adult brain should be distinguished from the effects of maternal drug abuse on the developing brain in the womb of a pregnant drug abuser. Current progress in substance abuse research identifies that the brain is plastic and that there

are adaptations at the level of neurochemical systems, gene expression, and associated behaviors as a consequence of chronic drug abuse in adults. The repetitive use of drugs leads to alterations in “homeostatic” mechanisms controlling certain central brain structures and chemical systems that have been subverted by virtue of the chronic and recurrent exposure to drugs of abuse. In an effort to adapt to drug-induced alterations in neuronal communication and function, the brain of the drug addict undergoes certain functional neurochemical and molecular maladaptations, which may have behavioral correlates. These maladaptive changes in brain function can be considered a form of “molecular deformation”: the brain was normally formed before drug abuse and was subsequently altered or deformed as a consequence of continued drug administration. It is important to contrast this with the effects of exposing the developing brain to drugs of abuse. The pregnant woman who abuses drugs may in turn perturb fetal neurochemical systems and neuronal communication during critical developmental periods when normal brain structure, circuitry, and biochemical and molecular features are being established. Altered brain function that may ensue can be considered a form of “molecular malformation”: In such infants, the brain is prevented from forming normally. The postnatal consequences of altering genetic and molecular programs for brain development may be sustained for years to come and may be evidenced as altered brain growth, delayed developmental milestones, or altered cognitive, linguistic, or behavioral maturation. As mentioned above, the specific developmental programs affected, and brain structures and systems altered, are likely to depend on the specific pattern of drug abuse as well as the gestational period during which drug exposure occurred. This distinction, that the brain of the infant exposed to drugs of abuse in utero may be malformed, not deformed, is an important extension of a principle of teratogenesis, which has implications regarding appropriate intervention and amelioration of gestational drug-induced disability. One of the critical goals of future clinical research will be to determine the extent to which individual drugs may cause specific molecular malformations, to identify what the behavioral and clinical correlates of such malformations are, and to identify the extent to which particular prenatal interventions may prevent, and specific postnatal therapeutics may correct, compensate, or modify, the expression of such malformations and their behavioral correlates. METHODOLOGICAL COMPLEXITIES AND CONFOUNDING ASPECTS OF CLINICAL STUDIES Some of the limitations of conducting and interpreting clinical research in this area include the multitude of confounding environmental factors that are associated

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with maternal (licit and illicit) drug abuse that may affect fetal and infant development including, but not limited to, altered socioeconomic status (SES); restricted access or limited use of prenatal care; exposure to sexually transmitted diseases; violent and abusive domestic relationships; and chaotic home environments, which may include multiple out-of-home placements, and lifestyles with a lack of adequate and appropriate social supports for mothers or infants. In collecting clinical data to relate in utero drug exposure to altered postnatal development, there are additional methodological complexities: selection biases of health care workers in terms of who is screened, identified, and studied; difficulty with longitudinal follow-up of mothers and infants; problems with the validity of self report versus laboratory testing (for example, of blood, urine, hair, or meconium) to define exposed versus control infants, and with quantitating exposure to one, or more commonly multiple drugs (that is, polypharmacy); and difficulty in conducting prospective longitudinal studies of exposed infants. Identifying the independent effects of in utero exposure to drugs in altering developmental outcomes poses some additional analytical problems (Table 48.1). If a child born to a woman who abuses drugs has altered development postnatally, as compared with control children not exposed to drugs of abuse in utero, are those alterations in development and behavioral maturation: 1. a consequence of inheriting an altered genetic predisposition from one or both parents, which contributed to (maternal) substance-abusing behaviors during pregnancy?

48.1 Determinants of Behavioral Outcomes in Drug-Exposed Children

TABLE

• Genetic predisposition – Novelty seeking, risk taking – Inattention, impulsivity, hyperactivity, learning disabilities – Personality disorders, psychiatric diagnoses • Prenatal environment – Inadequate prenatal medical care – Poverty/malnutrition – Sexually transmitted diseases/intrauterine infection

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2. a consequence of an altered postnatal home environment that is often chaotic, due to continued drugseeking behaviors and substance abuse by the parents, which can alter parent–infant interaction and thereby affect subsequent development? 3. or are they truly a consequence of gestational exposure to drugs of abuse and to the effects that those drugs exert in altering programs for brain development and subsequent behavioral maturation? To some extent, rigorously designed and executed prospective longitudinal clinical studies can control for some of these prenatal and postnatal factors in an effort to correlate gestational exposure to drugs of abuse with altered postnatal outcomes. However, the interpretation of such data is further complicated by the fact that any child who sustains an in utero insult is more sensitive to the quality of the postnatal environment and thereby more vulnerable for developmental impairment when raised in a compromised setting. As with other gestational factors that compromise in utero development, such as prenatal malnutrition, prematurity, infection, or asphyxia, the infant at risk for developmental compromise by virtue of such gestational exposures has a deficit that is contextual: The richer the environment postnatally, the less likely the in utero exposure will be of developmental consequence. Therefore, the child born to a mother who abuses drugs may be at potential risk for “double trouble” resulting from the biological exposure in utero compounded by the effects of a potentially suboptimal postnatal environment, which may accentuate the expression of that insult. In addition, the kinds of behaviors that may be impaired in infants exposed to drugs of abuse in utero may be very subtle alterations in affect, attention, arousal, and action, which are difficult to assess in adults and may be even harder to characterize in developing children or to quantitate in ways that facilitate analytic efforts to identify drug-induced alterations in such behaviors. Having outlined these complexities, a selective review of the literature can highlight how some of the best-designed studies have identified specific prenatal risks that are associated with particular alterations in postnatal outcomes and the extent to which there are markers, either in the perinatal or early postnatal period, that define antecedents of developmental compromise.

• In utero drug exposure – Pattern of drug use: Quantity/frequency/route

ALCOHOL

– Gestational timing of drug use during pregnancy – Concurrent use of multiple drugs of abuse • Postnatal environment – Impaired parental–infant interaction – Inadequate social supports/chaotic lifestyle – Poverty/malnutrition – Depression/abuse

Although alcohol teratogenicity, the adverse consequences of excessive drinking by pregnant women on infant outcome, had been established in biblical times, it was not until the thalidomide epidemic of the 1950s that investigators started thinking more critically about the potential role of alcohol and other drugs of abuse as teratogens. Over 30 years ago, clinical investigators reported

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a constellation of abnormalities evident in infants born to women who abused alcohol. In 1973, investigators identified a clinical syndrome comprising prenatal growth retardation, specific dysmorphic facial features, and CNS compromise and labeled this triad fetal alcohol syndrome (Jones et al., 1973). The incidence of fetal alcohol syndrome (FAS) is approximately one per thousand in the general population but may be somewhat higher in certain ethnic groups. The term fetal alcohol effects (FAE) has been developed to describe children exposed to alcohol in utero with less significant compromise of one or more components of the triad mentioned above (D.W. Smith, 1981). Fetal alcohol effects are probably 3 to 5 times more common than FAS, though there has been much discussion about the definition and use of this terminology and descriptors (for review, see Aase et al., 1995). An alternative proposal for nomenclature followed from an Institute of Medicine report on FAS released in 1996 (Stratton et al., 1996) that identified five categories of diagnostic consequence resulting from fetal exposure to alcohol: 1. FAS with confirmed maternal alcohol exposure 2. FAS without confirmed maternal alcohol exposure 3. Partial FAS with confirmed maternal alcohol exposure 4. Alcohol-related birth defects (ARBD) 5. Alcohol-related neurodevelopmental disorder (ARND) Categories 4 and 5 can coexist and are considered to be “possible prenatal alcohol-related effects,” though categories 1, 2, and 3 are by definition mutually exclusive. Others consider these outcomes as a continuum, lumped under the heading of fetal alcohol spectrum disorder (FASD). Whichever diagnostic categories prove to be most useful and become most widely adopted is less important than an appreciation of the biological complexities involved in attributing specific clinical deficits to gestational exposure to alcohol. Even with a clear phenotype, including the dysmorphic facial appearance associated with FAS, it is often difficult to identify FAS and to attribute the syndrome to maternal alcohol consumption. For reasons including those mentioned above, to confirm the maternal history of a pattern of substantial regular or excessive alcohol intake or of heavy episodic drinking can be problematic either because children are in foster or adoptive care and not accompanied by their biological mothers at clinic visits or because biological mothers are “in denial” or at risk for legal consequences if they define the specifics of their drinking and/or drug habits during pregnancy. Moreover, the fact that certain other gestational toxins can produce facial features consistent with fetal alcohol facies (including anticonvulsant embryopathy, fetal toluene exposure, infants born to mothers with phenylketonuria [PKU], Noonan’s syndrome, and velocardiofacial syn-

drome) combined with other reasons for failure to diagnose FAS at birth (including lack of recognition of the syndrome, reluctance to identify or label women as users, and difficulty making the diagnosis in newborns) has led to imprecise surveillance and identification of the syndrome. It would appear that FAS is correlated with maternal drinking habits that continue despite intervention and can be associated with an early age of onset of drinking, a family history of drinking (especially in female relatives), alcohol-related medical problems, alcohol dependence criteria, and a host of alcoholrelated behaviors. However, even with these maternal historic correlates of alcoholism, it is clear that not all fetuses exposed to high levels of alcohol will be affected: Only 4.3% of offspring of “heavy” drinkers (defined as greater than five drinks per occasion, or two drinks per day) demonstrate FAS, and only an estimated 30%–50% of fetuses born to alcoholics show evidence of FAE. Observations that the incidence of FAS and FAE varies considerably in different ethnic groups may relate to variations in the frequency of particular isozymes of enzymes required for alcohol metabolism (that confer protection vs. vulnerability to the teratogenic effects of alcohol), which may be altered in their distribution among particular ethnic populations. It may also be the case that the cultural acceptability and pattern of drinking varies within certain ethnic groups, and together with socioeconomic factors may contribute to an increased incidence of FAS in certain populations. In particular, lower SES is associated with an approximately 10-fold increased risk for FAS than is seen in middle to higher socioeconomic groups. Mechanisms of Alcohol-Induced Brain Maldevelopment Over the last 15 years, molecular and cellular mechanisms underlying the effects of alcohol on the adult and developing brain have been elucidated, identifying specific neural systems and signal transduction pathways that mediate aspects of alcohol’s effects. Ethanol intoxication occurs at mmol/L concentrations, which are high enough to perturb hydrophobic regions of cell membranes and the lipids and proteins that constitute them (Deitrich et al., 1989). In addition to these nonspecific membrane effects, a subset of receptor-mediated signaling mechanisms is altered by acute ethanol exposure. The receptor for γ -aminobutyric acid (GABA) and the associated chloride channel have been implicated as one of the central sites at which ethanol acts. The long isoform of the γ2 subunit (2L) of the GABA-A receptor is required for modulation of chloride currents by benzodiazepines and ethanol (Wafford et al., 1991). This common site of action for both drugs via altered GABAergic neurotransmission is supported by clinical data (Charness, 1992): Benzodiazepine administration

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and ethanol intoxication share similar features, there is cross tolerance between these drugs when chronically administered, and ethanol withdrawal is partially suppressed by benzodiazepines (whose chief action is to augment GABAergic neurotransmission). Ethanol causes a dose-dependent potentiation of 5-HT3 currents (the serotonin-gated ion channel) in NCB-20 neuroblastoma cells (Lovinger and White, 1991). Because serotonergic systems are implicated in affect and motivation, one can speculate that the rewarding as well as intoxicating properties of alcohol may in part be related to its action at 5-HT receptors. Ethanol inhibits N-methylD-aspartate (NMDA)-gated chloride currents in a dosedependent manner in the nmol range of concentrations (Lovinger et al., 1989) and is associated with postreceptor changes in calcium and cyclic guanosine monophosphate (cGMP). Alterations in memory in alcoholics (such as alcohol blackouts) could conceivably be related to changes in the efficacy of signals transduced via the NMDA receptor. Ethanol has been found to modify opioid systems and signaling, including opioid peptide concentration, release, and binding (Charness, 1992). Some of alcohol’s effects on opiates are mediated by μ-opioid receptor blockade. Ethanol can selectively block adenosine uptake through the nucleoside transporter (Nagy et al., 1990) and may be involved in the adaptive responses to ethanol via second-messenger pathway (cyclic adenosine monophosphate [cAMP]) stimulation. These and additional mechanisms may be operative in compromising the developing fetus. The following factors have been suggested and potentially implicated in contributing to the FAE and FAS phenotype in alcohol-exposed infants: nutritional factors, socioeconomic factors, genetic susceptibility to alcohol effects including alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) polymorphisims, acetaldehyde and fatty acid ethyl ester metabolism, ethanol inhibition of retinoic acid synthesis, alteration of insulin-like growth factor action, alcohol-induced hypoxia and alcohol-induced free radical production, inhibition of cell adhesion mediated by the human L1 gene, and release of L-glutamate by ethanol (for review, see Stoler et al., 1998). Which, if any, of these mechanisms contribute to altered brain growth and differentiation by alcohol has not been clearly established, and additional mechanisms may be operative, with specific consequences on brain maturation. For example, researchers have determined that exposure of developing mouse brain to alcohol alters cell-cycle kinetics (Burchfield et al., 1991), which in turn alters maturation of glial cells (Miller and Robertson, 1993), which is associated with failure of neuroblasts to migrate to their proper targets (Gressens, Lammens, et al., 1992). These investigators suggest that alcohol-induced impairment of neurogenesis and neuronal migration alters brain size and cortical architecture. Other mechanisms “downstream” of

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alcohol-induced receptor mediated changes described above may be operative during CNS maldevelopment. For example, interference with cAMP-dependent kinase activity may account for alcohol-induced growth retardation (Pennington, 1990). Recent studies have emphasized the relevance of prenatal alcohol-induced apoptotic neurodegeneration mediated by glutamatergic antagonism at the NMDA receptor and GABAmimetic actions at the GABA-A receptor as contributing to the impaired brain growth and development seen in FAE and FAS (Ikonomidou et al., 2000). These and many additional animal experiments have clearly documented that ethanol damages developing organisms and that the developing nervous system is particularly vulnerable to these effects (for review, see Driscoll et al., 1990). The Alcohol-Affected Phenotype(s) In the spectrum of alcohol-related effects, FAS is on the most affected end, whereas FAE is a milder phenotype, though even lesser effects may be seen in some subset of infants who are impaired. In a fully affected case, FAS may have the following features (Streissguth et al., 1996): 1. growth retardation including low birth weight, microcephaly, decreased adipose tissue, and failure to thrive 2. A pattern of craniofacial anomalies with the most discriminant features being midface hypoplasia, evident as small palpebral fissures, a flat indistinct philtrum, a thin vermilion border, epicanthal folds, and a depressed nasal bridge 3a. neurological effects which in younger children can include fine and gross motor delays, hypotonia, and tremor 3b. neurological effects which in older children can include impaired IQ (with a mean IQ of 68 for FAS); learning disabilities with impaired cognition, dysfunctional language, deficits in verbal learning and memory, and difficulty dealing with multiple sensory inputs, particularly auditory information; and a specific pattern of behavioral effects including impulsivity, decreased attention span, hyperactivity, difficulty establishing normal peer relationships, lack of remorse, failure to learn from mistakes, lack of judgment, and aggressiveness. As opposed to the alcohol-related growth retardation mentioned above, which is most evident in the newborn and perinatal period, some of the other features of FAE and FAS, in particular the dysmorphic facial appearance and evidence of neurological compromise, are often and easily missed in newborns. During adolescence, the continued growth of alcohol-exposed children may lead to height that overlaps with low normal values for the general population and weight that may normalize or may become obese in some cases.

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Microcephaly often persists, but the change in facial features associated with puberty may mask dysmorphic features that define the fetal alcohol facies. It has been noted that there are increased adverse effects seen in subsequent offspring of alcoholic mothers and an increased association of FAE and FAS with mothers older than 30 years of age, independent of drinking levels (J.L. Jacobson et al., 1996). This suggests that in addition to the worsened drinking habits that are often associated with the progression of alcoholism, there may be other biological factors associated with increased maternal age that puts the fetus at increased risk for adverse effects. Such factors may also contribute to the complexity of quantifying the relationship between exposure and outcome: clear thresholds or dose-response relationships between amount of alcohol consumed and effects on the offspring have never been established. However, the pattern of drinking seems to contribute to outcome in an important way: Daily maternal drinking is not necessary for adverse effects, as binge drinking (greater than five drinks at a sitting) has been associated with learning problems such as impaired academic skills, memory, and attention in exposed offspring. Efforts to relate the timing of the worst alcohol drinking with developmental consequences have suggested, but not clearly confirmed, that alcohol exposure during all three trimesters is associated with worsened growth retardation, an increased incidence of craniofacial abnormalities, and more profound CNS compromise (Autti-Ramo et al., 1992). What has also been shown is that the performance on sequential simultaneous mental composite achievement tests and nonverbal scores in those infants born to women who never drank was better than in those born to mothers who stopped drinking during pregnancy, which in turn was better than in those infants born to mothers who continued to drink (Coles et al., 1991). What the additional burden of other substances commonly used with alcohol in polypharmacy have been raised and considered including whether such effects may be has been considered, including whether such effects may be additive or synergistic. Socialization and Adaptation Alterations in specific postnatal developmental outcomes that have been reported following in utero alcohol exposure include neuropathological, neurophysiological, linguistic, and social and adaptive consequences. In animal studies, ethanol-induced impairment in behavioral performance occurs in ways that parallel several outcome measures from clinical studies (Driscoll et al., 1990). In nonhuman primates, prenatal ethanol exposure results in deficits in object permanence, increased distractibility, and delays in gross motor development (Clarren et al., 1988; Clarren et al., 1992). In rodent models, increases in basal activity (Abel and Berman, 1994) and deficits

in habituation to new environments are observed, which have been interpreted as an impairment of inhibitory systems (Driscoll et al., 1990). Specific deficits in classical (Westergren et al., 1996) and operant conditioning (Clausing et al., 1995; Furuya et al., 1996) have also been reported with gestational ethanol administration in a dose-dependent fashion in adult rats. In clinical studies, the particular impairment of adaptive skills and social judgment in children and teenagers with FAS seems to be out of proportion to intellectual impairment and may be associated with an inability of such individuals to become fully integrated and functional members of society. In a follow-up of 415 patients with FAS and FAE, ages 6 to 51, Streissguth et al. (1996) noted that the most common problems encountered by this population include school difficulties (with a dropout or suspension rate of over 60% by the time children reach 12 years of age); difficulty with the law in 60% of children who are affected by their 12th birthday; mental health problems in approximately 90% of children who are exposed; alcohol and/or drug problems in over 30% of children before 12 years of age; homelessness; confinement, with in-patient treatment for mental health, drug abuse, or criminality in over 50% of those reaching 21 years of age; inappropriate sexual behavior in over 50% of individuals who are affected; dependent living in over 80% who have reached the age of 21; and problems with employment in over 80% who have reached the age of 21. The complexities associated with impaired adaptation and socialization that precluded full societal integration was seen in as significant a fraction of those with FAE as with FAS. In that same study (Streissguth et al., 1996), it was reported that males had a higher rate of school difficulties, were more likely to have been in trouble with the law, and more commonly demonstrated an IQ versus adaptive behavior discrepancy that was associated with a greater incidence of dependent living situations. Of note, in that study the protective factors included living in a stable and nurturing home for more than 70% of the child’s life; diagnoses at younger than age 6 years; no history of physical abuse; a stable living situation for more than 2.8 years; a good-quality home between the years of 8 and 12; eligibility for division of developmental disabilities (that is, support services); and having FAS versus FAE. These data do not imply that having FAS is more protective than FAE. Rather, it may reflect that children with the full-blown syndrome, once identified by virtue of more significant compromise, may be more carefully watched and supervised, with less risk for the secondary disabilities mentioned above. Summary of Alcohol’s Clinical Effects As reviewed above, during the preschool period some children with FAE and FAS demonstrate deficits that

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may include hyperactivity, language delay, and perceptual motor problems. During school years, attention deficit and behavioral problems often emerge. It is important to note that the extent of CNS compromise parallels the degree of dysmorphism, as the individuals with FAS demonstrate the greatest deficits. Other studies incorporating infants exposed to lower amounts of alcohol in utero have demonstrated normal Brazelton Neonatal Behavioral Assessment Scale (NBAS) scores, normal language development at 1, 2, and 3 years, and normal cognition and sustained attention in children who are exposed. This may partially reflect differences in study design, patient ascertainment, and biological exposure. One resolution to these discrepancies is suggested by some of the principles of teratology; there may be many outcomes, with the most profound alterations induced by exposures of greater amount over increased gestational time. For all of these reasons, counseling pregnant women about alcohol exposure and its risks to the fetus is problematic because no lower threshold exists regarding the amount of exposure that is safe, no pattern of drinking seems to be safe, all three trimesters of pregnancy have been implicated as vulnerable times, and the concomitant use of other substances can only aggravate the alcohol effects. Emphasizing the importance of cessation of drinking and its potential benefits to the fetus is the clearest message that can be delivered to pregnant women. Delivering this message to women considering pregnancy, or in their early stages of pregnancy, is an important goal. So is the ability to reinforce this message to alcoholics even during the later stages of pregnancy, when they can be more readily identified and engaged in coordinate efforts to optimize prenatal health care. Efforts in the treatment community to utilize a “stages of change” model (Prochaska and DiClemente, 1992) have tried to use pregnancy as a motivating force to engage pregnant women in therapeutic efforts to decrease drug use and abuse during pregnancy. Implicit in this and other approaches is that by decreasing the incidence and severity of maternal drug abuse, there will be decreased developmental compromise of their offspring, resulting in better outcomes for all. COCAINE The gestational consequences of exposing the fetal brain to cocaine are not yet as clearly understood or characterized as those for alcohol. Reasons for this include 1. There is no observable dysmorphic phenotype that can be attributed to gestational cocaine exposure. 2. Almost every woman who abuses cocaine also uses other substances including alcohol, tobacco, and to a lesser extent marijuana, requiring complex statistical

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design to look for interactive effects, or multivariateregression analyses to determine the additional burden that cocaine imparts on the developing brain beyond that imparted by alcohol. 3. Evaluation of children born to women who were part of the crack epidemic, which peaked in the late 1980s, is not “as far advanced” as the study of the alcohol-exposed population. Cocaine-exposed children, who are now populating middle schools and high schools in greater numbers in many urban centers, are just having their complex academic needs and behavioral problems better defined, and the independent contribution of cocaine exposure to those problems is being ascertained. In the 1980s, the “war on drugs” associated with the crack-cocaine epidemic focused national attention on the relationship between drug use and social and economic problems in society. Early reports on prenatal cocaine effects created a public frenzy and the myth about “unfit to parent” women and their damaged “crack babies.” This affected legal activities by states on policy decisions affecting women who use illegal drugs during pregnancy. The later studies have failed to support significant associations between prenatal cocaine exposure and increased prevalence of serious newborn congenital malformations and medical complications at birth. Longitudinal follow-up studies of the behavior and development of these children suggest that cocaine effects are apparent but more subtle than originally feared. A number of reviews have described inconsistencies in the cocaine literature (Lester et al., 1998; Frank et al., 2001) due to methodological issues including small sample size, confounding of cocaine exposure with exposure to other drugs, lack of biochemical verification for exposure status and levels, lack of adequate control for demographic variables as prenatal care, SES, and out-of-home placement. Current thinking has evolved towards a more balanced position that appreciates that not every child exposed to cocaine in utero has developmental problems but that exposure to cocaine, especially at high doses, in some subset of infants places them at risk for developmental compromise. As with other gestational toxins that have been studied, the expression of that insult depends on the context in which the child is raised. As with alcohol, there does not appear to be one outcome but a spectrum of outcomes, which may relate to the genetics of the mother and infant, to the postnatal environment, and to the specifics of the gestational exposure, including route, dosing, timing, and frequency of drug administration with respect to trimester of fetal development. Moreover, the fact that certain outcomes can be a consequence of gestational cocaine or alcohol exposure (such as microcephaly) makes it very difficult to design and interpret the results of clinical

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studies and to espouse causality to cocaine and/or alcohol in independently contributing to adverse outcomes. In an effort to meet these challenges, the second generation of clinical research on infants who were exposed to drugs has striven to quantitate the exposure to alcohol and cocaine during pregnancy and relate them to the degree and nature of altered postnatal outcomes (see Table 48.2). These more recent studies have investigated whether the timing and amount of cocaine and alcohol used during pregnancy identify which exposures are most likely contributing to which sets of outcomes. Many of these current studies demonstrate greater sophistication in study design and statistical analysis, affording a more rich and complex appreciation of the biology underlying the effects of cocaine and other gestational toxins on the developing brain. The National Institutes of Health (NIH) Maternal Lifestyle Study (MLS) is the largest study of prenatal cocaine exposure and was developed against the backdrop of debate and controversy about the effects on prenatal cocaine exposure on child outcome to address many of these methodological issues. Maternal Lifestyle Study recruited mother/child dyads from 1993 to 1995 at four sites: Wayne State University, the University of Tennessee at Memphis, the University of Miami, and Brown University. The longitudinal sample included 658 children who were exposed, with 730 comparisons group matched on prematurity, race and sex was selected from a larger initial pool of 11,811 children of which 10% were prenatally exposed to cocaine. The exposed group included cocaine and/or opiate use during the pregnancy determined by self-report and/or meconium toxicology. Inclusion in the unexposed group required denial of cocaine or opiate use during pregnancy and negative toxicology results. Other substances known to be asTABLE 48.2 Clinical Studies of In Utero Drug Effects: The Second Generation • Better study design – Improved controls – Multivariate design and analysis – Longer study period of parent–infant interaction – More sensitive instruments • Quantitating exposure – Dose-related vs. threshold effects – High-dose vs. low-dose effects – Polypharmacy (? independent effects) • Analysis of specific though subtle effects – Effect size may be small, requiring larger numbers of participants – Need to relate exposure(s) to outcome(s) – Must analyze drug-specific effects

sociated with cocaine and opiate use (alcohol, marijuana, and tobacco) were included in both groups. Mechanisms of Cocaine-Induced Brain Maldevelopment The primary action of cocaine is mediated by blocking the reuptake of the catecholamine neurotransmitters norepinephrine (NE) and dopamine (DA) and the indoleamine serotonin, thereby potentiating their action at nerve terminals. The peripheral effects of cocaine are a catecholamine-induced increase in sympathetic drive leading to vasoconstriction, hypertension, and tachycardia. The central effects of cocaine derive from increased central aminergic drive leading to CNS stimulation. Numerous investigators have suggested additional mechanisms by which gestational cocaine exposure may alter brain development following acute or chronic (recurrent) drug exposure (see Wilkins et al., 1998). It has been suggested that prenatal cocaine exposure may induce injury to developing tissues (including the brain) by fetal arterial vasoconstriction with resulting alterations in perfusion of vascular territories, perhaps mediated by ischemia/reperfusion injury (Fantel et al., 1992). Cocaine, which crosses the placenta in all species examined, including humans, primates, sheep, rats, and mice, may act directly on fetal tissues, perhaps as a local anesthetic, thereby altering ion permeability in the CNS. One transplacental mechanism by which maternal cocaine exposure may compromise fetal well-being has been suggested by physiologic studies in pregnant sheep. In the model of the fetal ewe (Woods et al., 1987), intravenous injection of cocaine into the pregnant mother (at a dose of cocaine of 1 mg/kg, comparable to commonly abused doses) results in maternal hypertension, with a 34% decrease in uterine blood flow from catecholamine-mediated vasoconstriction of the uterine arteries evident. In that model, the fetal consequences of decreased uterine blood flow are reduced oxygen delivery (hypoxemia), fetal hypertension, and tachycardia (Woods et al., 1987). One of the fetal responses to hypoxemia is release of endogenous catecholamines. The fetal catecholamines and maternal catecholamines, which are transmitted to fetus via the placenta, are circulating in high quantities in the fetus because cocaine, which diffuses to the fetal circulation, prevents their reuptake. These animal studies point to the following classes of potential mechanisms whereby maternal cocaine abuse can compromise fetal brain development: Indirect (maternal): Via catecholamine-mediated placental vascular compromise with consequent fetal hypoxemia and/or ischemic injury Direct (fetal) peripheral: Via catecholamine-mediated effects on fetal vasculature

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Direct (fetal) central: Via direct actions of cocaine on fetal brain (for example, as a local anesthetic) Direct (fetal) central: Via aminergic mechanisms: 1. Altering the fidelity of aminergic signals, which may subserve a trophic role in CNS maturation 2. Altering the integrity of aminergic transmitter systems secondary to developmental perturbation of amine concentration and distribution in fetal brain. In support of the relevance of aminergic mechanisms in contributing to cocaine-induced brain maldevelopment, several preclinical studies have identified alterations in the maturation of aminergic systems consequent to prenatal cocaine exposure. These include a persistent elevation of dopaminergic innervation in rat cortex and hippocampus (Akbari and Azmitia, 1992); a hyperinnervation of serotonin fibers in adult rat striatum (Snyder-Keller and Keller, 1993); alterations in the state of phosphorylation of tyrosine hydroxylase (TH) in postnatal rats (Meyer and Dupont, 1993); an altered density of DA uptake pumps (the site of cocaine binding) in postnatal rats (Stadlin and Keller., 1994); alterations in fetal monkey brain including (1) decreased TH in the substantia nigra and (2) increased D1, D2, and D5 receptor messenger ribonucleic acids (mRNA) and binding in the striatum and forebrain (Ronnekleiv and Naylor, 1995); impaired DA-mediated signal transduction as evidenced by impaired GS coupling, cocaine-induced c-Fos activation, and DA release in postnatal rabbits (Friedman et al., 1993); neurophysiological data suggesting that the basal firing rate of midbrain dopaminergic neurons is altered (Wang and Pitts, 1994); and altered levels of monoamines in rat brain (Keller et al., 1994). Thus, there is increasing evidence from various structural, neurochemical, and neurophysiological studies that young and adult offspring exhibit deficits consistent with an altered “aminergic repertoire” that is associated with transplacental cocaine exposure. Investigators using preclinical models have demonstrated alterations in additional features of brain structure and function: The density of opiate receptors in striatum is altered in the brains of animals exposed to cocaine in utero (Clow et al., 1991); there are long-lived changes in the metabolic rate of limbic brain structures in adults exposed to cocaine in utero (Dow-Edwards et al., 1990); and there is altered precision of cortical cytoarchitectonics in the brains of mice (Gressens, Kosofsky, et al., 1992; see Figure 48.1); and primates (Lidow, 1995) exposed to cocaine in utero. In vitro studies of human fetal brain–derived neural precursor cells treated with cocaine showed marked inhibition of proliferation, migratory response, and cell differentiation. These results point towards existence of several molecular and cellular mechanisms triggered by exposure to cocaine that could adversely affect the fetal brain, with long-term

FIGURE 48.1 Images of rat brain from animals exposed to saline (left side) or cocaine (right side) in utero (20 mg/kg, subcutaneously, twice a day, from E8 to E17 inclusive), reared to adulthood, sacrificed by perfusion, and imaged on a 11.7T Bruker spectrometer (TR/ TE = 800ms/32ms). Magnetic resonance imaging microscopy demonstrates that prenatal exposure to cocaine compromises brain growth, reflected as less neocortical area and an abnormal periventricular signal in striatum in these horizontal images (courtesy of Dr. Russ Jacobs and Dr. Scott Fraser, Beckman Institute, Biological Imaging Center, California Institute of Technology).

implications (Linares et al., 2006). It is likely, though not proven, that similar mechanisms are relevant in clinical settings (for review, see Spear, 1995). The Cocaine-Affected Phenotype Maternal cocaine use during pregnancy is a major public health problem, resulting in perinatal and neonatal complications of enormous cost to society as well as mothers and infants. Some of the alterations in specific postnatal developmental outcomes that have been reported following in utero cocaine exposure will be reviewed by the topic below. Prenatal effects Clinical evidence suggests that cocaine independently contributes to impairment in brain growth that is prenatal in origin and exhibits an inverse dose–response relationship (Mirochnick et al., 1995; Bateman and Chiriboga, 2000). The selective impairment of brain growth demonstrated in a significant subset of infants exposed to cocaine in utero, which is beyond that resulting from the malnutrition associated with maternal cocaine use or with the sociodemographic attributes that characterize pregnant mothers who use cocaine (Zuckerman et al., 1989), is in contrast to the infants exposed to marijuana studied in that same cohort who showed evidence of asymmestric growth retardation

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with relative “head sparing.” The symmetric growth retardation (that is, brain growth impairments that are coordinate with body growth compromise) evident following in utero cocaine (and alcohol) exposure suggests that these drugs are selectively neurotoxic and directly alter fetal brain growth. An interesting and a plausible explanation for the microcephaly seen with cocaine exposure was put forth by Chiroboga (1998): in utero exposure to cocaine results in excess accumulation of postsynaptic monoamines, attributable to the property of cocaine to block the uptake of monoamines. The resulting imbalance of monoamines leads to abnormal growth of the neural cone and dendritic arborization; these events may result in cortical dysgenesis and impaired neuropil growth that in turn could ultimately contribute to microcephaly (Chiriboga, 1998). Consistent with this formulation, some investigators have reported that here is an increased incidence of seizures in neonates exposed to cocaine. In addition to the studies identifying impaired prenatal brain growth, many studies have shown effects of prenatal cocaine use on fetal and neonatal outcomes, including decreases in gestational age, birth weight, and birth length (Oro and Dixon, 1987; Fulroth et al., 1989; Zuckerman et al., 1989). In the MLS, medical complications of mothers in the exposed group were more common but still rare (< 5%; Bauer et al., 2002). Previously reported congenital anomalies identified using head ultrasound were not found in the MLS cohort (Bauer et al., 2005). In contrast, there were some effects on physical growth and central/autonomic nervous system (CNS/ANS) signs (Bada, Das, et al., 2002; Shankaran et al., 2003), though perhaps in part attributable to polydrug use: cocaine-using MLS mothers were 49 times more likely to use other drugs (Lester et al., 2001). Perinatal behavior The results reported from the MLS cohort, as well as others, identifies that cocaine appears to affect dimensions of arousal and reactivity, including greater excitability, poor state regulation, more rapid changes in arousal with stimulation, increased arousal from sleep, and increased physiological lability (Gingras et al., 1990; DiPietro et al., 1995; Mayes et al., 1995; Regalado et al., 1995; Mayes and Carroll, 1996; Regalado et al., 1996; Bendersky and Lewis, 1998; Gingras and O’Donnell, 1998). Numerous investigators have employed the Brazelton NBAS to study habituation, orientation, motor performance, range of state, regulation of state, autonomic regulation, and reflexes in infants exposed to cocaine during the perinatal period. In some studies, cluster-score comparisons between infants exposed to cocaine and control populations demonstrate significant impairment of orientation, motor ability, state regulation, and a number of abnormal reflexes, though

there have been some evident inconsistencies (for review, see Lester et al., 1996). One factor contributing to the variability may relate to the amount of in utero cocaine exposure because impaired regulation of state and motor performance, as reflected by NBAS cluster scores, demonstrates a dose-response relationship with cocaine metabolites (Delaney-Black et al., 1996). Studies of the MLS cohort have confirmed (Bauer et al., 2002) and extended through at least one month of life (Lester et al., 2003) observations that prenatal cocaine exposure affected arousal, hypertonicity, excitability, and acoustic cry characteristics in newborns. Of note, mothers in the cocaine group are less engaged during feeding interaction (LaGasse et al., 2003). Early effects on the trajectory of motor development are additionally evident (Miller-Loncar et al., 2005). A variant of the NBAS specifically developed to evaluate high-risk infants exposed to drugs, termed the Neonatal Intensive Care Unit (NICU) Network Neurodevelopmental Scale (NNNS), may provide increased sensitivity to detect altered neonatal behaviors, as evidenced by an ability to discriminate newborn neurobehavioral patterns of excitability versus lethargy (Napiorkowski et al., 1996). Such alternative behavioral states may reflect direct versus indirect drug action (Napiorkowski et al., 1996). This formulation is supported by data collected with a version of the NBAS modified to study 3-week-old infants (Tronick et al., 1996) that demonstrates a persistence of dose-related effects of cocaine, particularly on the regulation of arousal. Infants exposed to cocaine show more negative affect during faceto-face interaction at 3 months of age in a mother–infant interaction test (Tronick et al., 2005) and at 18 months showed more insecure attachment (Seifer et al., 2004). Infant behavior in this high-risk sample is also affected by factors such as postpartum maternal depression (Salisbury et al., 2007) and parenting stress (Sheinkopf et al., 2005). Neurological development Investigators have defined a syndrome of “hypertonic tetraparesis,” an increase in muscle tone evident in all four extremities, in almost two thirds of the examined infants born to mothers who were abusing cocaine, which was associated with smaller head size at birth (Chiriboga et al., 1995). Most of the affected children in this cohort grew out of their hypertonic tetraparesis by 12– 18 months of age, though within the cocaine-exposed group there was an association between those infants who were initially hypertonic with those children who were subsequently developmentally delayed, as assessed by the Bayley Scales of Infant Development (BSID) through 12 months of age (Chiriboga et al., 1995). Although the motor impairments of newborns exposed to cocaine are dose-dependent (Chiriboga et al., 1999), the lasting effects of such exposure on motor function,

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as measured with the psychomotor development index of the BSID, appear not to be related to level of prenatal exposure (Frank et al., 2001). Recent studies of 2-year old toddlers exposed to cocaine have suggested that motor but not cognitive outcomes may be better than originally anticipated (Singer et al., 2004) and that the motor effects of gestational drug exposure may be significantly ameliorated by early intervention (Frank et al., 2002). The syndrome of hypertonic tetraparesis may distinguish those infants who sustain significant in utero exposure to cocaine versus alcohol, as infants with FAE/ FAS often demonstrate decreased muscle tone (that is, “floppiness”) as compared with the increased muscle tone (that is, “stiffness”) reported in infants exposed to cocaine. Hypertonia is also reported in some infants exposed to opiates in utero. The neuropathophysiological basis for the hypertonia in infants exposed to cocaine, and the extent to which it is a sign of spasticity (that is, implying corticospinal involvement) verses rigidity (that is, implying extrapyramidal involvement) constitutes an important topic for subsequent clinical and preclinical research. As infants who are prenatally exposed to cocaine get older, motor developmental delays and cognitive deficits have been reported, in addition to abnormalities in physical growth (Zuckerman et al., 1989; McCalla et al., 1991; Bateman and Chiriboga, 2000; Behnke et al., 2002; Minnes et al., 2006; Lumeng et al., 2007). Imaging studies showed structural brain abnormalities including periventricular hemorrhages, subependymal and periventricular cysts have been found in children exposed to cocaine in utero (Dixon and Bejar, 1989; Sims, Walther, et al., 1989; Cohen et al., 1994; Singer et al., 1994). Occasional anomalies like cortical infarcts, pachygyria, and schizencephaly have been noted more frequently in association with prenatal cocaine exposure, on computed tomography (CT) and magnetic resonance imaging (MRI) studies (Heier et al., 1991; Gieron-Korthals et al., 1994; Gomez-Anson and Ramsey, 1994). However, prospective controlled studies showed no concrete association of cocaine exposure with cranial anomalies (Behnke et al., 1998; L.M. Smith et al., 2001a; Warner et al., 2006). Language development To address whether selective alterations in expressive language skills were a consequence of in utero cocaine exposure or a consequence of an impoverished postnatal environment, investigators compared 23 infants who were exposed to cocaine in foster care with 23 infants who were not exposed to cocaine in foster care. On the average, children exposed to cocaine demonstrated a 6-month delay in expressive speech at 2 years of age as compared with the unexposed foster-care control population (Nulman et al., 1994). That study additionally determined that the children exposed to cocaine had

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statistically significant impairments in postnatal brain growth through 2 years of age, which likewise suggests that despite proper nutrition and a nurturing postnatal environment, the foster-care cohort exposed to cocaine demonstrated postnatal brain growth retardation. However, investigators have also demonstrated significant deficits in total language acquisition through 7 years of age that are independent of the effects of cocaine on head circumference in a large, well-controlled sample of children exposed to cocaine (Bandstra et al., 2002). Several reports on cocaine literature support moderate language deficits and delay in children exposed to cocaine (Lester et al., 1998; Mentis, 1998; Bandstra et al., 2002; Lewis et al., 2004). Other investigators (Mentis and Lundgren, 1995) employed more sophisticated analyses of the pragmatics of language and reported that the population exposed to cocaine is deficient in some of these more subtle, yet crucially important, features of expressive language maturation. As with FAS, the small head at birth may serve as a “marker” of the child who was exposed to cocaine in utero, and impaired postnatal brain growth may additionally distinguish those children in whom gestational exposure to cocaine has altered programs for brain development in a significant way. However, as with some patients with FAE following in utero cocaine exposure, there may be adverse consequences on language and cognitive development independent of effects on prenatal or postnatal brain growth. Intelligence, learning, and academic performance Follow-up studies through school age show that children exposed to cocaine show small deficits in intelligence (Lester et al., 1998; Richardson, 1998; Bennett et al., 2002; Arendt et al., 2004; Singer et al., 2004). Further, children exposed to cocaine show deficits in component academic skills including poor sustained attention, visual motor integration and visuospatial memory, more disorganization, and less abstract thinking (Loebstein et al., 1997; Delaney-Black et al., 1998; Richardson, 1998; Leech et al., 1999; Delaney-Black et al., 2000; Bandstra et al., 2001; Arendt et al., 2004; Schroder et al., 2004; Noland et al., 2005). In MLS reports, there were no effects due to prenatal cocaine exposure on mental development at ages 1–3 (Messinger et al., 2004). However, effects on IQ emerged at age 4 and increased through age 7 (Lester et al., 2003). This could suggest that cocaine may affect some areas of the brain that are more “transparent” until children reach school age. In the same study (Lester et al., 2003), children exposed to cocaine were 1.5 times more likely to be referred for special education services at age 7. Affect, attention, arousal The MLS investigators have focused on the “four A’s”— affect, attention, arousal, and action—as being those

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areas most at risk for compromise in infants exposed to drugs. Theoretically, primary compromise in the domain of arousal regulation, with its consequences on attentional mechanisms and thereby on executive functioning directly and socialization indirectly, may predict the cognitive and behavioral abnormalities observed in children exposed to cocaine in utero (Mayes, 2002). Although it is a significant challenge to assess affect, attention, and arousal in infants and children younger than 5 years of age, researchers have developed paradigms to assess visual habituation, response to novelty, social attachments, and infant attention. Alterations of state control (Delaney-Black et al., 1996), arousal (Tronick et al., 1996), and habituation evident in some neonates exposed to cocaine, especially those who sustained the most significant in utero exposures, may persist through infancy (Mayes et al., 1995), early childhood (S.W. Jacobson et al., 1996), and beyond (Richardson et al., 1997). Prospective studies reporting such changes have demonstrated differences in response to novelty, but not information processing, in some 3-month-olds exposed to cocaine (Mayes et al., 1995), reflected as a decreased likelihood to start a habituation procedure, and for those who did, an increased likelihood to react with irritability early in the procedure. A dose-response relationship relating the offspring of heavy cocaine users to faster responsiveness on an infant visual expectancy test but to poorer novelty preference performance during their first year of life has been established (S.W. Jacobson et al., 1996). School-age children born to mothers who reported light to moderate cocaine use during pregnancy exhibited deficits in their ability to sustain attention on a computerized vigilance task (Richardson et al., 1997). Problem behavior and externalizing and internalizing behavior have also been reported in children exposed to cocaine through age 7 (Delaney-Black et al., 1998; Delaney-Black et al., 2000; Covington et al., 2001; Accornero et al., 2002; Linares et al., 2006; Bada et al., 2007). In MLS, high prenatal cocaine exposure was associated with higher internalizing, externalizing, and total behavior problems scores on the Child Behavior Checklist (CBCL) from 3 to 7 years of age (Bada et al., 2007). It is anticipated that the use of these and other instruments that are designed to assess more subtle impairments of attention, vigilance, responsivity, and behavioral dysregulation, combined with quantitative assessments of gestational drug exposures, will facilitate an improved understanding of the relationship of in utero drug exposure with alterations in these subtle, but profoundly important, outcomes. Summary of Cocaine’s Clinical Effects In summary, the data outlined regarding transplacental cocaine exposure suggest:

1. Many infants born to mothers who abuse cocaine during gestation demonstrate impaired fetal growth. This appears to be mediated through an indirect effect of poor maternal nutrition and a direct effect of cocaine. The independent contribution of cocaine is a 0.43 cm decrement in head circumference of the newborn (Zuckerman et al., 1989). 2. Some newborns of mothers who abuse cocaine during gestation (including women who limit their cocaine habits to the first trimester) demonstrate altered behavior, as evidenced by abnormalities in state control (abnormalities on the NBAS and the NNNS), with the most pronounced difficulties in orientation, alertness, and arousal. 3. A neurological syndrome of increased tone termed hypertonic tetraparesis is seen in a subset of children exposed to cocaine in utero. This motor system abnormality is transient and resolves in most infants who are affected by 18 months of age. 4. Neurophysiological studies suggest that some newborns exposed to cocaine in utero may evidence CNS dysmaturation; that is, they characterize such infants exposed to cocaine as being younger than chronological age by demonstration of more immature patterns of electrophysiological activity. Normalization of neurophysiological testing (as with neurological examination) occurs in most of the infants who are affected during the first 12–18 months of life. 5. Persistent deficits may be evident in children exposed to cocaine as they get older, including delayed language acquisition, cognitive impairment, or behavioral abnormalities, including difficulty modulating attention, impulsivity, and responsivity, which are challenged in classroom settings. Conclusions regarding the effects of cocaine on the developing human brain are less definite than for the effects of alcohol: The resulting deficits appear to be more subtle, and as with alcohol, only a subset of exposed infants and children exhibit lasting deficits. What is emerging, as was evident in children exposed to alcohol, is that some of the more subtle behaviors that are felt to be at risk in these infants as they grow older are important for socialization, educability, and the adaptive skills that are required for individuals to become enfranchised in schools, communities, and society. Future research will bring a clearer characterization of the deficits evident in these children, of the extent and role that in utero cocaine exposure contributes to these deficits, and of the impact of postnatal interventions to ameliorate such deficits. Whether some children exposed to cocaine will grow up to have other behavioral, learning, and emotional deficits as defined in the section above for alcohol remains to be determined. What is very clear is that clinicians, educators, and biological

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and adoptive parents should be vigilant regarding the special needs of such children as they enter school and beyond. METHAMPHETAMINE The abuse of methamphetamine (METH) in the United States has been well documented. Methamphetamine is the most widely abused amphetamine and, along with other amphetamines, has been categorized as a Schedule II stimulant since 1971 because of its high potential for abuse (Lukas, 1997). In 1999, the number of Americans who had tried METH in their lifetime was 9.4 million (SAMHSA, 2002), double from what it was in 1994 (SAMHSA, 1995). By 2004, the number had reached nearly 12 million (SAMHSA, 2005a). Treatment Episode Data Set (TEDS; based on treatment admissions for substance abuse) recorded a 307% increase in admissions due to METH between 1993 and 2003 (SAMHSA, 2005b), with the highest rates in the Pacific, Mountain, and West North Central states, reflecting the well-known regional concentration of METH use. Although there is controversy about the nature and extent of the METH problem in the United States, including exaggerations reminiscent of the cocaine “epidemic,” there is little argument that METH is a dangerous drug that substantially challenges policy makers, health care professionals, social service providers, and the law enforcement community (King, 2006). There is little information about METH use by pregnant women (Wouldes et al., 2004), further complicated by methodological issues such as definitions of use, sampling methods, and drug use detection procedures (Smeriglio, 1999). The National Pregnancy and Health Survey (National Institute on Drug Abuse [NIDA], 1996) conducted in 1993, was designed to provide a nationally representative sample of live births. This study is based on self-report but includes a subsample with toxicological verification and showed less than 1% METH use by pregnant women. The most recent estimate from the National Survey on Drug Use and Health, based on self-report data from the 2004 survey (SAMHSA, 2005a) showed that, for women of childbearing age, 0.4% of nonpregnant women and 0.1% of pregnant women used METH. The 2003 TEDS database showed a 6.4% prevalence rate for pregnant METH users. Pharmacology Methamphetamine is a CNS stimulant of the sympathetic nervous system with neurotoxic potential for developing monoaminergic systems. As the “first cousin” of amphetamine with the addition of the methyl radical, METH

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exerts its action by releasing DA and serotonin, blocking monoamine reuptake mechanisms, and inhibiting monoamine oxidase (Heller, 2000). The mechanism of action most likely occurs by increasing the synaptic concentrations of the neurotransmitters DA and NE (Heller, 2000) either by direct release from storage vesicles or by inhibition of reuptake (Karch, 1993; Catanzarite and Stein, 1995). Methamphetamine may enhance synaptic catecholamine levels by inhibiting monoamine oxidase, the enzyme responsible for the oxidation of NE and serotonin (Bennett et al., 1993). Amphetamines are considered noncatecholamine sympathomimetics because they lack catecholamine structure yet have sympathomimetic actions (Plessinger, 1998). The structural characteristics are important because they account for the wide distribution and long duration of action of amphetamine. Methamphetamine also has vasoconstrictive effects (Burchfield et al., 1991; Stek et al., 1993) resulting in decreased uteroplacental blood flow and fetal hypoxia (Stek et al., 1995). In addition, METH has anorexic effects on the mother. These maternal/ placental effects could affect fetal development to the above monoaminergic effects. Weight control may also help explain the popularity of METH with women, including pregnant women.

Preclinical Studies Administration of METH to laboratory animals results in profound and long-lasting toxicity to the brain. In rodents, METH is toxic to dopaminergic and serotonergic neurons (Fuller and Hemrick-Leucke, 1992; Pu and Voorhees, 1993). Damage to DA terminals (Seiden and Sabol, 1996; Gibb et al., 1997) is thought to reflect irreversible terminal degeneration (Ricaurte and McCann, 1992). Neurotoxic effects of prenatal METH exposure on serotogenetic neurons produce neurochemical alternations in the CNS (Cabrera et al., 1993; Weissman and Caldecott-Hazard, 1995) thought to be associated with learning impairment, behavioral deficits (Weissman and Caldecott-Hazard, 1995), increased motor activity (Acuff-Smith et al., 1992), enhanced conditioned avoidance responses (Cho et al., 1991), and postural motor movements (Slamberova et al., 2006) seen in METH-exposed animals. Rhesus monkeys show reduced brain monoamines 4 years after the last drug exposure (Woolverton et al., 1989). Administration of METH to laboratory animals also results in motor (Wallace et al., 1999) and learning and memory impairment (Itoh et al., 1991). Studies with rats have shown a range of physical, motor, neurotransmitter, and behavioral effects in offspring exposed to METH. These include increased maternal and offspring mortality, retinal eye defects (Acuff-Smith et al.,

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1992; Yamamoto et al., 1992; Acuff-Smith et al., 1996), cleft palate and rib malformations (Yamamoto et al., 1992), and decreased rate of physical growth and delayed motor development (Cho et al., 1991; Acuff-Smith et al., 1996). Methamphetamine exposure to pregnant dams showed effects on spatial learning in their adult offspring (Slamberova et al., 2006). Spatial learning and attenuated corticosterone response was found in rats with prenatal METH exposure (Williams et al., 2003). In pregnant mice, METH caused dopaminergic nerve terminal degeneration and long-term motor deficits in offspring (Jeng et al., 2005).

2001b) found increased creatine in the striatum of the METH exposure group suggesting an abnormality in energy metabolism. In an MRI study of brain morphometry, these children also exhibited smaller subcortical volumes in the putamen, globus pallidus, and hippocampus (Chang et al., 2004). They also showed neurocognitive deficits in visual motor integration (Beery Test), sustained attention (TOVA), verbal memory, and longterm spatial memory, but no differences in IQ. The deficits in sustained attention and verbal memory, were correlated with reduction in brain structures (Chang et al., 2004).

Clinical Studies—Adult Brain Imaging

Prenatal exposure

There is an emerging literature on METH effects on the structure and chemistry of the human brain. Neuroimaging studies of adult METH abusers showed potential neurotoxic effects in subcortical brain structures, including DA transporters, brain metabolism, and perfusion (Ernst et al., 2000; Volkow et al., 2001; Chang et al., 2002). In studies using positron emission tomography (PET), METH abusers show lower levels of DA transporters in the striatum (McCann et al., 1998; Volkow et al., 2001; Sekine et al., 2003) and prefrontal cortex (Sekine et al., 2003), and differences in regional glucose metabolism (Volkow et al., 2001; London et al., 2004). Other imaging studies of METH abusers have reported alterations in perfusion (Chang et al., 2002), levels of neuronal metabolites (Ernst et al., 2000), and cortical activation (Paulus et al., 2002). There are also relations between imaging and behavior findings. In one study, DA transmitter loss reported in METH abusers (24%–30%) was associated with reduced motor speed and impaired verbal learning (Volkow et al., 2001). Also, in this study the lower DA transporter levels were even seen in patients detoxified for at least 1 year, suggesting that METH effects on the brain may be long lasting. Positron emission tomography studies have shown inhibitory control related to glucose metabolism in the orbitofrontal gyrus in patients who were recovering from METH dependence (Goldstein et al., 2002) and to anterior cingulate, insular, and amygdalar regions of cortex that were correlated with self-report of negative affective states (London et al., 2004). Thompson and associates (Thompson et al., 2004) found gray-matter deficits in the cingulate, limbic, and paralimbic corticies; smaller hippocampal volumes; and white matter hypertrophy in chronic METH users with the hippocampal deficits correlated with memory performance.

There are few studies of the effects of prenatal METH exposure. These studies have many of the methodological problems of the early cocaine literature, including small sample size, confounding with other variables especially other drugs, and problems with the detection of METH exposure status (Billing et al., 1980; Oro and Dixon, 1987; Dixon and Bejar, 1989; Struthers and Hansen, 1992; Hansen et al., 1993; Plessinger, 1998; L. Smith et al., 2003).

Clinical Studies—Child Brain Imaging A study of 12 children exposed to METH and 14 controls using magnetic resonance spectroscopy (Smith et al.,

Medical Outcomes Retrospective studies showed increased incidence of small for gestational age (SGA; Oro and Dixon, 1987; L. Smith et al., 2003) and decreased birth weight and head circumference (Oro and Dixon, 1987). These findings could be due to the vasoconstrictive effects of METH that induced increases in maternal blood pressure, restriction of nutritional substrate, increases in fetal blood pressure, decreases in fetal oxy-hemoglobin saturation, and arterial pH in the fetal ovine model (Burchfield et al., 1991; Stek et al., 1995). Some of METH effects reported in animal studies have also been found in human infants exposed to METH. These include clefting, cardiac anomalies, and fetal growth retardation (Plessinger, 1998). A high rate (35%) of cranial abnormalities was reported in a group of infants prenatally exposed to METH and cocaine (Dixon and Bejar, 1989). Behavioral Outcomes In work by Struthers and associates (Struthers and Hansen, 1992; Hansen et al., 1993), infants who were exposed to METH and/or cocaine at 6 months and 1 year were compared with unexposed controls on the Fagan Test of Infant Intelligence and showed lower visual recognition memory and differences on attention and distractibility and activity level. The most extensive work on prenatal METH exposure is from a series of studies from Sweden with a sample of 66 children exposed to amphetamine who were followed to the age

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of 14 (Cernerud et al., 1996). Initial findings (Billing et al., 1985) included drowsiness during the first few months, emotional signs of autism, speech problems, and signs of wariness of strangers at 1 year, if the mother continued to use throughout pregnancy. At age 4 (Billing et al., 1985), there were no differences in physical growth or health. IQ was lower than a separately selected control group from the population, and the amphetamine group had more disturbed or problem children if the mother was still addicted. Also at age 4 (Billing et al., 1988), child adjustment was predicted by maternal alcohol and drug use, maternal stress, and paternal criminal convictions. At age 8 (Billing et al., 1994), the extent of prenatal exposure predicted psychometric outcome, aggression, peer problems, adjustment, and general assessment. Alcohol also correlated with outcome, as did pregnancy attitudes. Maternal psychiatric treatment, alcohol abuse, and number of custodians correlated with aggressive behavior and general assessment. These children had problems with advancement in school due to delays in math and language and at age 14, they had difficulties with physical fitness activities (Cernerud et al., 1996). The limitations of this work include lack of a control group, small sample size, and confounding with other prenatal drug use (30% used heroin, 81% used alcohol with one third meeting criteria for alcohol abuse, and 80% smoked more than 10 cigarettes/day). The study is also based on self-report and the route of administration of amphetamine was injection, which is less common today in the United States. Therefore, although these findings are limited, they do suggest that these children are at risk for poor child outcome due to drug and psychosocial risk factors. Clearly, we are at the very beginning of our understanding of the effects of prenatal METH exposure on child development (Wouldes et al., 2004) The scant literature that is available is beset by methodological problems. This sentiment was summarized in a 2005 Expert Panel (National Toxicology Program, 2005), which concluded that in terms of the potential adverse reproductive and developmental effects of METH exposure, “studies that focused upon humans were uninterpretable due to such factors as a lack of control of potential confounding factors” (p. 177). Mindful of these limitations and of the “rush to judgment” that followed early cocaine findings, the NIH (NIDA) Infant Development, Environment and Lifestyle (IDEAL) longitudinal study of the effects of prenatal was established in four sites among the hardest hit areas in the United States with regard to rates of METH use: DeMoines, IA; Tulsa, OK; Los Angeles, CA; and Honolulu, HI (for details of the study design, see Arria et al., 2006). IDEAL participants were recruited following delivery and before discharge in 2002–2004. Methamphetamine exposure was determined through mothers’ self-reported use of METH and/or GC/MS confirmation of METH in me-

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conium. Unexposed participants denied METH use during pregnancy and had a negative METH screen. Initial findings, based on the first 1,632 participants (Arria et al., 2006) showed a 5.2% prevalence rate for METH. Smoking was the most common route of administration (79%), and the average age of first METH use was 19 years (range 8 to 38 years). For the longitudinal follow-up, 204 infants exposed to METH were matched with unexposed infants on maternal race, infant birth weight, type of medical insurance, and maternal education. Mothers who used alcohol, tobacco, or marijuana during pregnancy were included in both groups. Methamphetamine use was related to polydrug use, poverty, delayed prenatal care, and increased out-of-home placement of their infant (Grant et al., 2004). These mothers reported lower maternal perceptions on quality of life, greater likelihood of substance use among family and friends, increased risk for ongoing legal difficulties, and a markedly increased likelihood of developing a substance abuse disorder (Derauf et al., 2007). They also reported high levels of exposure to family violence during their own childhood and scored higher on the Child Abuse Potential Inventory (Newman et al., 2007) There were effects of METH on the infant. Infants exposed to METH were 3.5 times more likely to be SGA. Although most infants were full term, the average birth weight was 204 gm less in the METH group than in the comparison group (L.M. Smith et al., 2006). On the NNNS, exposure to METH was associated with lower arousal and increased physiological stress. First trimester METH use was related to greater stress/abstinence signs including CNS stress and physiological stress. Third trimester use was related to poorer quality of movement and greater physiological stress. Higher level of amphetamine metabolites in meconium was associated with poorer quality of movement, increased CNS stress, and poorer regulation (L.M. Smith et al., 2008) Acoustical analysis of the infants’ cry showed prenatal METH exposure related to cry characteristics indicative of CNS reactivity, poorer respiratory control, and neural control of the vocal track (LaGasse et al., 2004). NNNS and cry effects are similar to findings reported in infants exposed to cocaine suggesting neurotoxic effects to the developing fetus. OPIATES Mechanisms of Opioid-Induced Brain Maldevelopment Opiates act through three separate and distinct receptor subtypes, μ, δ, and κ, which have been molecularly cloned and pharmacologically well-characterized. These receptors have different anatomical distributions in the CNS and cellular mechanisms of action employing dif-

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ferent second-messenger systems. μ and δ -receptors act through inhibition of adenylyl cyclase (Duman et al., 1988) and activation of outward potassium currents (North et al., 1987) via inhibitory (Gi/GO) G proteins; κ-receptors act through inhibition of calcium currents, primarily but not exclusively at presynaptic terminals. The differences between the most commonly abused opiate narcotic, heroin (3,6-diacetylmorphine), the common drug of choice for the treatment of opioid dependence, methadone, and morphine are pharmacokinetic, not pharmacodynamic: all three act as at least partiallyselective μ-receptor agonists, whereas heroin, more lipophilic than morphine, more readily crosses the blood– brain barrier, and methadone has a significantly longer elimination half-life (Jaffe and Martin, 1985). Like cocaine, the anatomical and physiological substrate for the rewarding properties of the opiates lie in the dopaminergic mesolimbic and mesocortical projections from the ventral tegmental area (VTA) to the basal forebrain (Koob and Le Moal, 1997; Nestler, 1997). In the case of the opiates, however, enhancement of dopaminergic tone is not a direct action on the nucleus accumbens (NAc) and other forebrain targets but rather occurs through disinhibition of VTA dopaminergic neurons through inhibition of GABAergic inhibitory interneurons intrinsic to the VTA (Johnson and North, 1992). Opiate narcotics therefore utilize the existing enkephalinergic circuitry within the VTA, which acts to increase VTA activity and subsequently enhance dopaminergic transmission to the NAc and other sites within the basal forebrain (Johnson and North, 1992). Many of the experimental findings on the role of DA in the basal forebrain on reward and reinforcement, therefore, are relevant to the mechanism of drug-craving and drug-consuming behavior for the opiates, as well. At a molecular level, the reinforcing actions of the opiates are dependent largely, if not entirely, on their activity at μ-receptors, as μ-receptor knockout mice do not experience the analgesic effects of morphine, do not respond to morphine as if it were rewarding, and do not become physically dependent with chronic administration (Matthes et al., 1996). In preclinical studies, exposure to opiates in utero results in transient and persistent structural and behavioral changes in animal offspring. Morphine treatment of pregnant dams results in changes in the packing density of neurons and their morphology in rat pups: cortical density of neurons is decreased and neuronal processes (for example, dendritic arborization, axonal branching) are significantly smaller compared to controls (Hammer et al., 1989). Conversely, prenatal exposure to the opiate antagonist naloxone results in a significant increase in neuronal packing in the cortex and an increase in neuronal process length and extension (Zagon and McLaughlin, 1986; Hauser et al., 1987), raising the interesting possibility that endogenous opioid systems

play a morphogenetic role in the normal development of the brain. From this standpoint, the toxicity of gestational opiates could be viewed as an impact on normal modulatory, in this instance inhibitory, influences in the normal developmental program of cortical structures. Neurochemical studies of the effects of prenatal opiate exposure on several neurotransmitter systems have yielded mixed results (Fried, 1992). Increases and decreases in opioid receptors have been reported with gestational opiate exposure. Similarly, changes in brain content of the different monoamine neurotransmitters and acetylcholine have been reported by different laboratories to increase, decrease, or remain unchanged. A more consistent finding has been that gestational opiate exposure results in a decrease in nucleic acid synthesis and protein production in the fetal brain. Although studies focusing more specifically on brain reward circuitry have found that G protein–coupled cAMP production is critical to opiate self-administration (Self et al., 1994), that changes in this signal transduction pathway occur with chronic opiate administration in the NAc and VTA of adult animals (Bandstra et al., 2001), and that the change in these neurons is associated with immediateearly gene expression and subsequent target gene regulation (Nestler, 1997), similar studies have not been undertaken in animals who were gestationally exposed to opiates. The Opioid-Affected Phenotype(s) Although the preclinical literature on effects of gestational opiate exposure has described differing findings, perhaps due to different animal species using widely differing doses and scheduling of different opiates (Fried, 1992), a few consistent findings across studies have emerged. Most studies in young animals have shown a decrease in exploratory behavior and an increased latency in response to noxious stimuli after fetal exposure to opiates. Interestingly, similar to results with fetal cocaine exposure, gestational morphine exposure results in increased self-administration of heroin and cocaine (Ramsey et al., 1993) and enhances place preference to morphine (Gagin et al., 1997) in adult animals. Furthermore, prenatal cocaine exposure appears to sensitize rat pups to the pharmacological effects of opiates (Goodwin et al., 1993), lending further support to the idea that drugs of abuse not only act but also exert their developmental toxicities through actions on brain reward systems, and that this toxicity may consist in part of an increased sensitivity of the gestationally drugexposed brain to novel or reinforcing stimuli. In human studies, as with other drugs of abuse, measurement of the precise effects of gestational opiate exposure on neurodevelopment in the absence of the confounding effects of other prenatal and postnatal variables presents a significant challenge to clinical investigators.

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Nonetheless, several small, well-controlled studies have revealed a set of developmental and behavioral abnormalities in these children that appear to be relatively specific to opiate exposure in utero. For example, 1-yearold infants of mothers who were on methadone maintainance showed more disorganized and avoidant behavior when assessed for maternal attachment than infants of mothers who were not abusing drugs matched for age, parity, and socioeconomic factors including educational level and marital status (Goodman et al., 1999). Neonates exposed to opiates scored with the NBAS consistently demonstrate higher levels of arousal at baseline but poorer consolability and poorer motor control, decreased alertness and orientation to stimuli, and decreased habituation to repetitive stimuli than nonexposed controls across several studies (Hans, 1992). Measuring developmental progress with either the Griffith’s Developmental Scale (GDS) or the BSID, 12- to 18-month-old infants of mothers who were addicted to opiates and on methadone-maintainance have been found to have significantly lower scores than age-matched controls (Rosen and Johnson, 1982; Bunikowski et al., 1998); interestingly, one study (Bunikowski et al., 1998) showed no significant difference between the children of mothers who were on methadone maintainance and mothers who continued to abuse illicit opiates (that is, heroin) during pregnancy. Although studies have shown that children exposed to opiates demonstrate later problems with socialization and inattention and may be more impulsive than children who are not exposed (Wilson, 1989; Hans, 1992; Suess et al., 1997), these findings, like those in children exposed to cocaine, are subtle, and the relative contribution of drug exposure per se remains unclear.

CANNABIS Mechanisms of Cannabinoid-Induced Brain Maldevelopment Among the drugs of abuse, cannabinoids were the last for which endogenous receptors (Devane et al., 1988; Matsuda et al., 1990) and ligands (Devane et al., 1992) were identified, and until recently had defied attempts at animal modeling through self-administration (Martellotta et al., 1998). However, it is now appreciated that like all drugs of abuse, delta-9-tetrahydrocannabinol (Δ-9THC, the primary pharmacologically active alkaloid extract from marijuana) exerts its effects in part through facilitation of dopaminergic transmission from the VTA to the forebrain, and that this mechanism involves activation of endogenous opioid systems in the VTA (Tanda et al., 1997). Ironically, changes in brain dopaminergic function with prenatal cannabinoid exposure were recognized prior to the demonstration of THC action on

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mesoaccumbal DA systems: cortical and striatal D1 and D2 receptor binding and TH activity (the ratelimiting enzyme in DA biosynthesis) are persistently decreased in animals who are gestationally exposed to cannabinoid (Walters and Carr, 1986; Rodriguez de Fonseca et al., 1991). Changes are evident among other neurotransmitter systems relevant to the brain reward system, as well. For example, neither GABA content nor the activity of its synthetic enzyme, glutamic acid decarboxylase (GAD), are altered by prenatal Δ-9-THC exposure; however, motor inhibition induced by administration of the GABA-B receptor agonist baclofen, but not by the GABA-A receptor agonist muscimol, was greater in rats which were gestationally exposed to cannabinoid than in controls (Garcia et al., 1996). More often than with other drugs of abuse, sexually dimorphic effects of prenatal cannabinoid exposure are evident in animal studies: measurement of regional brain serotonin levels in newborn rat pups exposed to Δ-9-THC in utero show decreased 5-HT in diencephalic structures in males, but not in females (MolinaHolgado et al., 1996). Adult male rats exposed to Δ-9THC in utero demonstrate decreased μ -opioid receptor binding in the striatum and amygdala, whereas adult females show increased μ-opioid receptor binding in the prefrontal cortex, the amygdala, and the VTA (Vela et al., 1998). Conversely, proenkephalin expression in the striatum of exposed females is decreased, while males are unaffected (Corchero et al., 1998). These and other studies have suggested a functional, and possibly developmental, interrelatedness between the endogenous opioid and cannabinoid systems (Manzanares et al., 1999; Fernandez-Ruiz et al., 2000). At this time, it remains unclear whether these sexually dimorphic effects of prenatal exposure are due to cannabinoid interactions with developing brain monoamine systems, their actions on the developing hypothalamic-pituitaryadrenal axis (Dalterio et al., 1984; Dalterio et al., 1986), or both. The Cannabinoid-Affected Phenotype(s) Although relatively fewer animal studies have looked in detail at behavioral outcomes, increases in grooming behavior, alterations in habituation to novel environments, and interestingly, enhanced sensitization to the reinforcing effects of morphine have been observed in adult animals following gestational cannabinoid exposure (Navarro et al., 1994; Navarro et al., 1995). Inhibition of open-field motor behavior by a D1-selective antagonist, SCH 23390, but not by a D2-selective antagonist, sulpiride, was less marked in adult rats exposed to Δ-9-THC than in controls (Garcia et al., 1996). Sexually dimorphic effects of prenatal cannabinoid exposure are also evident in behavioral experiments in adult animals: female rats exposed to Δ-9-THC in

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utero demonstrate an increased rate of morphine selfadministration compared to controls, whereas males do not (Vela et al., 1998). Conversely, males exposed to Δ-9-THC demonstrate an increased baseline pain threshold and increased tolerance to the analgesic effects of morphine in a tail-flick assay, whereas females do not (Vela et al., 1995). Taken together, these preclinical biochemical and behavioral results suggest that one consequence of prenatal cannabinoid exposure may be that in females the endogenous opioid system is downregulated, resulting in a relatively sensitized state, while in males this system is up-regulated, resulting in a relatively tolerant, or desensitized, state. Much of the clinical data on cognitive and behavioral outcomes following prenatal exposure to marijuana comes from two ongoing long-term longitudinal studies of large cohorts of at-risk children: The Ottawa Prenatal Prospective Study (OPPS) and the Maternal Health Practices and Child Development Study (MHPCD). The primary differences between the patient populations in these two cohorts are that the majority of women in the OPPS are Caucasian and of middle-class SES, whereas the majority of women in the MHPCD are of lower SES and are evenly distributed between Caucasian and African American ethnicities. Nonetheless, the findings of studies of these two cohorts are in significant agreement. On neurological examination, neonates born to mothers using marijuana during pregnancy resemble neonates undergoing mild narcotic withdrawal in that they exhibit more jitteriness and have an exaggerated startle response compared to normal infants (Fried et al., 1987). As toddlers, children exposed to marijuana demonstrate poorer language development than nonexposed age-mates, but not to the same extent as children of mothers who smoked cigarettes during pregnancy; children exposed to marijuana also show more specific impairments in verbal memory (Fried and Watkinson, 1990). A more recent study of a larger cohort using a maternal self-reporting survey (Faden and Graubard, 2000) showed that toddlers that were exposed to marijuana are less socially engaging; once engaged, play for shorter periods of time; and are more fearful than their nonexposed, alcoholexposed, or cigarette-exposed age-mates. In 6-year-old children, prenatal marijuana exposure appears to result in increased inattention and impulsivity as measured by parent–teacher reporting through a modified Conner’s Rating Scale and by testing in a continuous performance task (Leech et al., 1999; Bandstra et al., 2001). This same cohort of children continue to demonstrate poor impulse control, diminished attention span, poor visuospatial reasoning skills, and poor hypothesis testing that persists into adolescence (Fried et al., 1998; Cornelius et al., 2000; Bandstra et al., 2001), suggesting that taken together, the effects of prenatal marijuana exposure may be related more to selective impairment of executive

functioning than to overall delay in global development (Bandstra et al., 2001).

NICOTINE Mechanisms of Nicotine-Induced Brain Maldevelopment The alkaloid nicotine was for many decades thought to exert its pharmacological effects solely through its activity at peripheral autonomic ganglia. Only recently has it come to be fully appreciated that not only does nicotine act at CNS acetylcholine receptors, but also that it is the central actions of nicotine that lead to the physical dependence characteristic of its use. The neural substrate for its addictive properties has been identified as the mesocorticolimbic dopaminergic system (Pich et al., 1997), common to other drugs of abuse. Pharmacologically, it has been clearly demonstrated in animal studies that nicotine stimulates dopaminergic neurotransmission from the VTA to the NAc (Pontieri et al., 1996; Pidoplichko et al., 1997), the sine qua non of brain reward processing in general and of responses to drugs of abuse in particular. Nicotine acts at nicotinic cholinoceptors (nAChR), which are ligand-gated ion channels that mediate excitatory cellular responses and for which the endogenous ligand is the classical neurotransmitter acetylcholine. Like most other ligandgated ion channels, it is a heteromeric, or multisubunit, assembly with binding sites on different protein subunit types. At the molecular level, it has been demonstrated that one particular nAChR subunit, β2, is necessary for the reinforcing effects of nicotine, as β2-subunit deficient knockout mice will not self-administer nicotine (Picciotto et al., 1998). Preclinical studies have demonstrated the effects of fetal nicotine exposure on brain and body growth parameters and have shown changes in several neurochemical systems, particularly NE (Slotkin, 1992). For example, in young adult animals exposed to nicotine in utero, basal NE content and nicotinestimulated NE release were decreased compared to controls (Seidler et al., 1992). Animal studies have also demonstrated changes in other monoamine systems with gestational nicotine exposure. Dopamine synthesis and turnover is decreased in the forebrain and brain stem (Muneoka et al., 1997; Muneoka et al., 1999), striatal and VTA dopamine content is reduced, and striatal D2 receptor binding is decreased in rats exposed to nicotine (Richardson and Tizabi, 1994). Serotonin synthesis and turnover are likewise decreased in the forebrain and brain stem of exposed rats (Muneoka et al., 1997); in addition, serotonin transporter density is increased in brain stem and decreased in forebrain regions with prenatal nicotine exposure (Xu et al., 2001). Prenatal in the neocortex: decreases in somatosensory cortical thick-

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ness and neuronal size were observed in rats who were gestationally exposed to nicotine (Roy and Sabherwal, 1994), suggesting a delay in neocortical neuronal maturation and/or migration similar to that observed in mice who were gestationally exposed to cocaine (Gressens, Kosofsky et al., 1992; Kosofsky et al., 1994).

rette smoking, confirming previous findings regarding increased incidence of smoking in offspring exposed to nicotine in utero (Kandel et al., 1994).

The Nicotine-Affected Phenotype

The literature reviewed above suggests that there are some significant similarities in the way that drugs of abuse with widely different cellular mechanisms of action affect the developing brain. First and foremost, alcohol, cocaine, and tobacco can lead to brain growth retardation. The microcephaly observed at the extreme of the FAS and in a statistically significant percentage of infants exposed to cocaine or tobacco speaks to the selective toxicity of these agents in developing brain. With all three agents, it appears as if the larger the dose of drug and the longer the time of exposure, the more profound the effect. However, the majority of infants exposed to cocaine and/or alcohol and/or tobacco do not have microcephaly. A central question is whether the brains in those children are in fact normal: Is there a continuum of brain vulnerability that only at its extreme results in microcephaly? Can brains be normal in size but not normal in architecture nor normal in function? Are the brains that are smaller necessarily aberrant in structure or function (that is, are the right elements there, just too few of them)? It is interesting that at the neuropathological level, there is evidence that all of these agents exert their teratogenic effects as brain growth retardation, albeit at the higher levels of drug exposures, but is the microcephaly induced by cocaine the same as the microcephaly induced by alcohol or tobacco? Are the mechanisms by which brain growth is compromised following cocaine exposure the same as those following alcohol or tobacco exposure? Are the correlates at the molecular, cellular, and systems level of brain growth retardation the same in individuals within an exposure group or when comparing exposures to different drugs of abuse? Most important, how do the cognitive, language, affective, or attentional deficits evidenced in some of these patients relate to the gross or microscopic changes in their brains? It is of particular interest to note the overlap of behaviors that may be compromised in some individuals exposed to different drugs of abuse. Neonates exposed to alcohol, cocaine, or opiates may demonstrate impaired state regulation as evidenced by altered cluster scores on the NBAS (and more recently, the NNNS). Developmental delay as assessed by the BSID may be evident during the first 2 years of life in individuals exposed to alcohol, cocaine, or opiates. There is some suggestion of compromise of antecedents of language and normal language maturation in 2- to 7-year-olds exposed to either alcohol, cocaine, or marijuana, and more compelling evidence in children exposed to tobacco.

Many preclinical studies have demonstrated clearly that prenatal exposure to nicotine is associated with hyperactivity in young animals that persists into adulthood, measured as increases in open-field exploratory behavior, vertical rearing, and stereotypical movements (Ajarem and Ahmad, 1998; Newman et al., 1999; Richardson and Tizabi, 1994; Shacka et al., 1997; Tizabi et al., 2000). Clinical studies have demonstrated the risks of tobacco smoking on fetal outcome, most notably on spontaneous abortion, birth weight, and other growth measures, including head circumference (Fried et al., 1999; Bandstra et al., 2001). The two large prospective studies of the OPPS and MHPCD cohorts have followed the behavioral and cognitive development of children of mothers who smoked cigarettes from birth through adolescence. In addition, a more recent multicenter survey of a large cohort of children who were exposed to marijuana, alcohol, and/or tobacco (Faden and Graubard, 2000) has corroborated these findings in toddlers. Three-year-old children exposed to nicotine appear to have poorer overall language development than toddlers exposed to marijuana during gestation and their age-matched unexposed peers (Fried and Watkinson, 1990; Faden and Graubard, 2000). Their specific language delays are persistent and are reflected in lower scores on verbal subtests of the Weschler Intelligence Scale for Children–III (WISC-III) administered in early adolescence (Fried et al., 1998). Toddlers exposed to nicotine also appear to be more impulsive and more active than nonexposed playmates, and engage in significantly more oppositional behavior with caregivers than agematched controls (Cornelius et al., 2000; Faden and Graubard, 2000). Later in development, school-age children exposed to tobacco demonstrate a reduced attention span (Fried, 1992; Leech et al., 1999) that persists into adolescence (Fried and Watkinson, 2001). An additional behavioral outcome that has been relatively less studied is the incidence of substance abuse in offspring of mothers who abused drugs during their pregnancy. Although difficult to examine prospectively as yet in children who were exposed to cocaine or opiates, as most cohorts of these children under study are still younger than the typical age of onset of substance experimentation and abuse, a recent investigation (Cornelius et al., 2000) of 10-year-old children exposed to tobacco suggests that prenatal nicotine exposure is an independent risk factor for early experimentation with ciga-

SYNTHESIS: DRUGS OF ABUSE

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Impaired attention, impulsive or aggressive behavior, and hyperactivity are observed to some extent in children exposed to cocaine, alcohol, or opiates, and to a greater extent in those exposed to cannabinoids or nicotine. In young adults with FAS, a persistence of cognitive deficits but particular compromise of socialization and communication skills is evident, which is similar to deficits seen in children exposed to nicotine. Whether this overlap reflects the fact that there are restricted final common pathways reflecting brain compromise or whether this is an artifact of the limited measures with which we can assess neurodevelopmental, cognitive, affective, and language attributes in infants and children should become clearer as more sensitive instruments and more rigorous analyses of larger numbers of exposed infants achieve maturity (see Table 48.2). Alternatively, some have suggested that the common features that characterize drug-exposed infants may be a reflection of a compromised postnatal environment where the mother who abused drugs interacts less and suboptimally with her child, resulting in a child who is less adaptive and socially inappropriate. The limited data on infants who were exposed who have been foster raised, many of whom have similar deficits to those who stay in the biological parent’s household, imply that environment is not wholly responsible for the persistent deficits (Nulman et al., 1994). Developmental Model The model shown in Figure 48.2 (Lester et al., 2004) describes three types of consequences of maternal drug use on child outcome: (1) immediate drug effects (2) latent drug effects, and (3) postnatal environment effects. Immediate drug effects refer to the direct teratogenic consequences of prenatal drug exposure. Such immediate effects emerge during the first year before postnatal environmental effects become increasingly salient. These effects may be transient, such as catch-up in physical growth, or more long lasting, such as behavioral dysregulation that is observed in infancy and persists through school age. Latent drug effects also refer to direct teratogenic effects, but these effects reflect brain function that becomes relevant later in development. Two kinds of latent effects can be described. First, drugs may affect brain function that does not manifest until children are older such as executive function, antisocial behavior, psychopathology, and substance use onset. Second, drugs may affect the brain by causing a predisposition for dependence on drugs. These conditions would be activated during school age when opportunities to use drugs arise, leading to early substance use onset and the gateway hypothesis, that use of licit drugs opens the door to experimentation with illicit drugs. Postnatal environment effects include general environmental factors that include risk and protective fac-

D R U G U S E D U R IN G P R E G N A N C Y PRENATAL E N V IR O N M E N T

PREN ATAL T E R A T O G E N IC IM M E D IA T E T R A N S IE N T

POSTNATAL C A R E G IV IN G E N V IR O N M E N T

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S P E C IF I C

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48.2 The model shown in the figure describes three types of consequences of maternal drug use on child outcome: (1) immediate drug effects, (2) latent drug effects, and (3) postnatal environment effects. Immediate drug effects refer to the direct teratogenic consequences of prenatal drug exposure. From Lester et al., 2004.

FIGURE

tors. Environmental risk factors such as poverty that occur in drug-using and non-drug-using populations are well-established correlates of poor child outcomes. There are also specific aspects of the caregiving environment unique to mothers who use drugs, such as the “children of alcoholics” (COA) effects. Passive exposure to cigarette smoke is a direct teratogenic environmental effect. The model acknowledges the role of genetic factors that may have immediate or latent effects or be transmitted through the caregiving environment. Protective factors can be naturally occurring (connectedness to others) as well as services and interventions. AN AMINERGIC PERSPECTIVE One possibility is that certain chemical systems within the brain subserving particular functions are compromised after exposure to drugs of abuse in utero. One hypothesis is that the affective behaviors that seem to be compromised in some of the drug-exposed population affect behavioral development with primary and secondary consequences. If affect, or the systems subserving affect, are compromised in the neonate, one would observe altered alerting, orientation, and state control. Altered affect in infancy can alter parent–infant interaction and subsequent socialization. One possibility is that compromise of the “affective repertoire” of the neonate prevents and precludes the normal maturation of language: That is, the prevocalization skills including turn taking, face recognition, and imitation require intact affective behaviors. Compromise of those systems may compromise the development of the normal antecedents of language and subsequently the definitive ontogeny of language skills. Additionally, there can be interactions between systems subserving different functions. For example, aminergic systems are thought to play a central role in arousal,

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attention, and affect, as well as motivation and the perception of reward, which are crucial in establishing reinforcement. It is possible that the neurotransmitter systems that store and release the amines (NE, DA, and serotonin) are not normally functioning in some infants exposed to drugs of abuse. As a consequence, cortical and subcortical circuits and targets that require discrete and differential aminergic control as the basis for selective attention may not develop or function normally. Alternatively, or additionally, those cortical and subcortical targets may be abnormal as an independent consequence of the toxic exposure. FUTURE DIRECTIONS These hypotheses can be tested in scientific and clinical domains. It is important to make no assumptions about the relevance of particular neurotransmitter systems or preconceptions about the anatomic or chemical localization of particular skills or behaviors or their antecedents. However, it is important to think about the ontogeny of behavior with respect to its morphological and functional correlates. Traditional clinical assessments of the structure and function of developing brain are restricted to noninvasive measures: head ultrasound, CT scans, and MRI morphometry to look at brain structure; evoked potentials to measure CNS conduction times; electroencephalogram (EEG) to assess electrophysiological function; and assessments of behavior, cognition, language, and temperament. For example, clinical developments in magnetic resonance spectroscopy are now being applied to children exposed to drugs of abuse in utero and suggest that there may be regional changes in energy metabolism in the brains of these children in the absence of frank structural abnormalities (L.M. Smith, et al., 2001a, 2001b). Similarly, functional MRI techniques are becoming more widely employed at many clinical centers and increasingly in pediatric populations, which will ultimately allow investigators to ask questions regarding regional differences in brain activation and blood flow using specific attentional, cognitive, and behavioral tasks. These clinical measures are evolving, and at a first approximation, they afford an opportunity to test hypotheses. One goal for future research is to establish (or refute) relationships between gestational exposures to drugs of abuse and alterations in developmental outcomes. This will allow us to differentiate among the abstract hypotheses we can consider and to frame our subsequent experiments in more direct scientific and clinical initiatives. Most important, it will in an unbiased fashion provide greater biological understanding of the effects of drugs of abuse on the developing brain. In so doing, our attention can be focused on relevant interventions, prenatally and postnatally, with the goal of improving

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outcomes. In considering such future directions for research, clinical questions can be formulated at the four levels of analysis previously discussed (Grimm, 1987): 1. Pharmacological/physiological level: What are the mechanisms by which drugs of abuse can exert toxic effect on the developing brain? 2. Developmental level: What are the factors that influence the individual susceptibility and timing of biological vulnerability of developing brain to the toxic effects of drugs of abuse? 3. Systems level: What are the brain structures and neurochemical systems that subserve the behavioral or cognitive deficits? 4. Behavioral/cognitive level: What behavioral and cognitive deficits are evident in children exposed to drugs of abuse in utero? When do these deficits become evident? What tests are available or can be developed to assess these deficits, and to identify their antecedents? What role do postnatal environmental factors play in the expression of these deficits? To what extent can allocation of appropriate interventions and resources improve the outcomes of infants who are exposed? One challenge for the next phase of clinical research on the effects of drugs of abuse on the developing brain is to design studies that will provide meaningful answers to these questions at each level of analysis. REFERENCES Aase, J.M., Jones, K.L., et al. (1995) Do we need the term “FAE”? Pediatrics 95:428–430. Abel, E.L., and Berman, R.F. (1994) Long-term behavioral effects of prenatal alcohol exposure in rats. Neurotoxicol. Teratol. 16(5): 467–470. Accornero, V.H., Morrow, C.E., et al. (2002) Behavioral outcome of preschoolers exposed prenatally to cocaine: role of maternal behavioral health. J. Pediatrl. Psychol. 27(3):259–269. Acuff-Smith, K.D., George, M., et al. (1992) Preliminary evidence for methamphetamine-induced behavioral and ocular effects in rat offspring following exposure during early organogenesis. Psychopharmacology (Berl) 109(3):255–263. Acuff-Smith, K.D., Schilling, M.A., et al. (1996) Stage-specific effects of prenatal d-methamphetamine exposure on behavioral and eye development in rats. Neurotoxicol. Teratol. 18(2):199–215. Ajarem, J.S., and Ahmad M. (1998) Prenatal nicotine exposure modifies behavior of mice through early development. Pharmacol. Biochem. Behav. 59(2):313–318. Akbari, H.M., and Azmitia, E.C. (1992) Increased tyrosine hydroxylase immunoreactivity in the rat cortex following prenatal cocaine exposure. Developmental Brain Res. 66:277–281. Arendt, R.E., Short, E.J., et al. (2004) Children prenatally exposed to cocaine: developmental outcomes and environmental risks at seven years of age. J. Dev. Behav. Pediatr. 25(2): 83–90. Arria, A.M., Derauf, C., et al. (2006) Methamphetamine and other substance use during pregnancy: preliminary estimates from the Infant Development, Environment and Lifestyles (IDEAL) Study. Matern. Child Health J. 10(3):293–302. Autti-Ramo, I., Korkman, M., et al. (1992) Mental development of 2-year-old children exposed to alcohol in utero. J. Pediatr. 120: 740–746.

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SUBSTANCE ABUSE DISORDERS

Bada, H.S., Bauer, C.R., et al. (2002) Central and autonomic system signs with in utero drug exposure. Arch. Dis. Child Fetal Neonatal. Ed. 87(2):F106–F112. Bada, H.S., Das, A., et al. (2002) Gestational cocaine exposure and intrauterine growth: maternal lifestyle study. Obstet. Gynecol. 100(5 Pt 1):916–924. Bada, H.S., Das, A., et al. (2007) Impact of prenatal cocaine exposure on child behavior problems through school age. Pediatrics 119(2) 348–359. Bandstra, E.S., Morrow, C.E., et al. (2001) Longitudinal investigation of task persistence and sustained attention in children with prenatal cocaine exposure. Neurotoxicol. Teratol. 23(6):545–559. Bandstra, E.S., Morrow, C.E., et al. (2002) Longitudinal influence of prenatal cocaine exposure on child language functioning. Neurotoxicol. Teratol. 24(3):297–308. Bateman, D.A., and Chiriboga, C.A. (2000) Dose-response effect of cocaine on newborn head circumference. Pediatrics 106(3):E33. Bauer, C.R., Langer, J.C., et al. (2005) Acute neonatal effects of cocaine exposure during pregnancy. Arch. Pediatr. Adolesc. Med. 159(9):824–834. Bauer, C.R., Shankaran, S., et al. (2002) The Maternal Lifestyle Study: drug exposure during pregnancy and short-term maternal outcomes. Am. J. Obstet. Gynecol. 186(3):487–495. Behnke, M., Davis Eyler, F., et al. (1998) Incidence and description of structural brain abnormalities in newborns exposed to cocaine. J. Pediatr. 132(2):291–294. Behnke, M., Eyler, F.D. et al. (2002) Cocaine exposure and developmental outcome from birth to 6 months. Neurotoxicol. Teratol. 24(3):283–295. Bendersky, M., and Lewis, M. (1998) Arousal modulation in cocaine-exposed infants. Dev. Psychol. 34(3):555–564. Bennett, D.S., Bendersky, M., et al. (2002) Children’s intellectual and emotional-behavioral adjustment at 4 years as a function of cocaine exposure, maternal characteristics, and environmental risk. Dev. Psychol. 38(5):648–658. Bennett, S., Hyde, J., et al. (1993) Differing neurotoxic potencies of methamphetamine, mazinol, and cocaine in mesencephalic cultures. J. Neurochem. 60(4):1444–1452. Billing, L., Eriksson, M., et al. (1980) Amphetamine addiction and pregnancy: III. One year follow-up of the children. Psychosocial and pediatric aspects. Acta Paediatr. Scand. 69(5):675–680. Billing, L., Eriksson, M., et al. (1985) Pre-school children of amphetamine-addicted mothers: I. Somatic and psychomotor development. Acta Paediatr. Scand. 74(2):179–184. Billing, L., Eriksson, M., et al. (1988) Predictive indicators for adjustment in 4-year-old children whose mothers used amphetamine during pregnancy. Child Abuse Negl. 12(4):503–507. Billing, L., Eriksson, M., et al. (1994) The influence of environmental factors on behavioural problems in 8-year-old children exposed to amphetamine during fetal life. Child Abuse Negl. 18(1):3–9. Bunikowski, R., Grimmer, I., et al. (1998) Neurodevelopmental outcome after prenatal exposure to opiates. Eur. J. Pediatr. 157(9): 724–730. Burchfield, D.J., Lucas, V.W., et al. (1991) Disposition and pharmacodynamics of methamphetamine administration in sheep. JAMA 265:1968–1973. Cabrera, T.M., Levy, A.D., et al. (1993) Prenatal methamphetamine attenuates serotonin mediated renin secretion in male and female rat progeny: evidence for selective long-term dysfunction of serotonin pathways in brain. Synapse 15(3):198–208. Catanzarite, V.A., and Stein, D.A. (1995) “Crystal” and pregnancy-methamphetamine-associated maternal deaths. West J. Med. 162(5): 454–458. Cernerud, L., Eriksson, M., et al. (1996) Amphetamine addiction during pregnancy: 14-year follow-up of growth and school performance. Acta Paediatr. 85(2):204–208. Chang, L., Ernst, T., et al. (2002) Perfusion MRI abnormalities and computerized cognitive deficits in abstinent methamphetamine users. Psychiatry Res.: Neuroimaging 114(2):65–79.

Chang, L., Smith, L.M., et al. (2004) Smaller subcortical volumes and cognitive deficits in children with prenatal methamphetamine exposure. Psychiatry Res. 132(2):95–106. Charness, M.E. (1992) Molecular mechanisms of ethanol intoxication, tolerance, and physical dependence. In: Mendelson J.H., and Mello, N.K., ed. Medical Diagnosis and Treatment of Alcoholism, 3rd ed. New York: McGraw-Hill, pp. 155–200. Chiriboga, C.A. (1998) Neurological correlates of fetal cocaine exposure. Ann. N.Y. Acad. Sci. 846:109–125. Chiriboga, C.A., Brust, J.C., et al. (1999) Dose-response effect of fetal cocaine exposure on newborn neurologic function. Pediatrics 103(1):79–85. Chiriboga, C.A., Vibbert, M., et al. (1995) Neurological correlates of fetal cocaine exposure: transient hypertonia of infancy and early childhood. Pediatrics 96(6):1070–1077. Cho, D.H., Lyu, H.M., et al. (1991) Behavioral teratogenicity of methamphetamine. J. Toxicol. 16(Suppl 1):37–49. Clarren, S.K., Astley, S. J., et al. (1988) Physical anomalies and developmental delays in nonhuman primate infants exposed to weekly doses of ethanol during gestation. Teratology 37(6): 561–569. Clarren, S.K., Astley, S.J., et al. (1992) Cognitive and behavioral deficits in nonhuman primates associated with very early embryonic binge exposures to ethanol. J. Pediatr. 121(5 Pt 1):789–796. Clausing, P., Ferguson S.A., et al. (1995) Prenatal ethanol exposure in rats: long-lasting effects on learning. Neurotoxicol. Teratol. 17(5):545–552. Clow, D.W., Hammer, R.P., Jr., et al. (1991) Gestational cocaine exposure increases opiate receptor binding in weanling offspring. Developmental Brain Res. 59:179–185. Cohen, H.L., Sloves, J.H., et al. (1994) Neurosonographic findings in full-term infants born to maternal cocaine abusers: visualization of subependymal and periventricular cysts. J. Clin. Ultrasound. 22(5):327–333. Coles, C.D., Brown, R.T., et al. (1991) Effects of prenatal alcohol exposure at 6 years: I. Physical and cognitive development. Neurotoxicology 13:1–11. Corchero, J., Garcia-Gil, L., et al. (1998) Perinatal delta9-tetrahydrocannabinol exposure reduces proenkephalin gene expression in the caudate-putamen of adult female rats. Life Sci. 63(10): 843–850. Cornelius M.D., Leech S.L., et al. (2000) Prenatal tobacco exposure: is it a risk factor for early tobacco experimentation? Nicot. Tob. Res. 2(1):45–52. Covington, C., Nordstrom-Klee, B., et al. (2001) Development of an instrument to assess problem behavior in first grade students prenatally exposed to cocaine: II. Validation. J. Subst. Abuse 22(4):217–233. Dalterio, S., Steger R., et al. (1984) Early cannabinoid exposure influences neuroendocrine and reproductive functions in male mice: I. Prenatal exposure. Pharmacol. Biochem. Behav. 20(1):107–113. Dalterio, S.L., Michael S.D., et al. (1986) Perinatal cannabinoid exposure: demasculinization in male mice. Neurobehav. Toxicol. Teratol. 8(4):391–397. Deitrich, R.A., Dunwiddie, T.V., et al. (1989) Mechanism action of ethanol: initial central nervous system actions. Pharmacologic Rev. 41:489–537. Delaney-Black, V., Covington, C., et al. (1996) Prenatal cocaine and neonatal outcome: evaluation of dose-response relationship. Pediatrics 98:735–740. Delaney-Black, V., Covington, C., et al. (1998) Prenatal cocaine exposure and child behavior. Pediatrics 102(4 Pt 1):945–950. Delaney-Black, V., Covington, C., et al. (2000) Teacher-assessed behavior of children prenatally exposed to cocaine. Pediatrics 106(4): 782–791. Derauf, C., LaGasse, L.L., et al. (2007) Demographic and psychosocial characteristics of mothers using methamphetamine during pregnancy: preliminary results of the Infant Development, Environ-

48: EFFECTS OF DRUGS OF ABUSE ON BRAIN DEVELOPMENT ment and Lifestyle Study (IDEAL). Am. J. Drug Alcohol Abuse 33(81):189. Devane, W.A., Dysarz, F.A., et al. (1988) Determination and characterization of a cannabinoid receptor in rat brain. Mol. Pharmacol. 34(5):605–613. Devane, W.A., Hanus, L., et al. (1992) Isolation and structure of a brain constituent that binds to the cannabinoid receptor [see comments]. Science 258(5090):1946–1949. DiPietro, J.A., Suess, P.E., et al. (1995) Reactivity and regulation in cocaine-exposed neonates. Infant Behav. Dev. 18:407– 414. Dixon, S.D., and Bejar, R. (1989) Echoencephalographic findings in neonates associated with maternal cocaine and methamphetamine use: incidence and clinical correlates. J. Pediatr. 115:770– 778. Dow-Edwards, D.L., Freed, L.A., et al. (1990) Structural and functional effects of prenatal cocaine exposure in adult rat brain. Developmental Brain Res. 57:263–268. Driscoll, C.D., Streissguth, A.P., et al. (1990) Prenatal alcohol exposure: comparability of effects in humans and animal models. Neurotox. Teratol. 12:231–237. Duman, R.S., Tallman, J.F., et al. (1988) Acute and chronic opiateregulation of adenylate cyclase in brain: specific effects in locus coeruleus. J. Pharmacol. Exp. Ther. 246(3):1033–1039. Ernst, T., Chang, L., et al. (2000) Evidence for long-term neurotoxicity associated with methamphetamine abuse: a 1H MRS study. Neurology 54(6):1344–1349. Faden, V.B., and Graubard, B.I. (2000) Maternal substance use during pregnancy and developmental outcome at age three. J. Subst. Abuse 12(4):329–340. Fantel, A.G., Barber, C.V., et al. (1992) Studies of the role of ischemia/ reperfusion and superoxide anion radical production in the teratogenicity of cocaine. Neurotox. Teratology 46(3):293–300. Fernandez-Ruiz, J., Berrendero F., et al. (2000) The endogenous cannabinoid system and brain development. Trends Neurosci. 23(1): 14–20. Frank, D.A., Augustyn, M., et al. (2001) Growth, development, and behavior in early childhood following prenatal cocaine exposure: a systematic review. JAMA 285(12):1613–1625. Frank, D.A., Jacobs, R.R., et al. (2002) Level of prenatal cocaine exposure and scores on the Bayley Scales of Infant Development: modifying effects of caregiver, early intervention, and birth weight. Pediatrics 110(6):1143–1152. Fried, P.A. (1992) Clinical implications of smoking: determination of long-term teratogenicity. In: Zagon, I.S., and Slotkin, T.A., eds. Maternal Substance Abuse and the Developing Nervous System. San Diego, CA: Academic Press, pp. 77–76. Fried, P.A., and Watkinson, B. (1990) 36- and 48-month neurobehavioral follow-up of children prenatally exposed to marijuana, cigarettes, and alcohol. J. Dev. Behav. Pediatr. 11(2):49–58. Fried, P.A., and Watkinson, B. (2001) Differential effects on facets of attention in adolescents prenatally exposed to cigarettes and marihuana. Neurotoxicol. Teratol. 23(5):421–430. Fried, P.A., Watkinson, B., et al. (1987) Neonatal neurological status in a low-risk population after prenatal exposure to cigarettes, marijuana, and alcohol. J. Dev. Behav. Pediatr. 8(6):318–326. Fried, P.A., Watkinson, B., et al. (1998) Differential effects on cognitive functioning in 9- to 12-year olds prenatally exposed to cigarettes and marijuana. Neurotoxicol. Teratol. 20(3):293–306. Fried, P.A., Watkinson B., et al. (1999) Growth from birth to early adolescence in offspring prenatally exposed to cigarettes and marijuana. Neurotoxicol. Teratol. 21(5):513–525. Friedman, E., Butkerait, P., et al. (1993) Analysis of receptorstimulated and basal guanine nucleotide binding to membrane G proteins by sodium dodecyl sulfate—polyacrylamide gel electrophoresis. Anal. Biochem. 214:171–178. Fuller, R.W., and Hemrick-Leucke, S.K. (1992) Further studies on the long-term depletion of striatal dopamine in iprindole-treated rats by amphetamine. Neuropharmocology 21(5):433–438.

823

Fulroth, R., Phillips, B., et al. (1989) Perinatal outcome of infants exposed to cocaine and/or heroin in utero. Am. J. Dis. Child 143(8):905–910. Furuya, H., Aikawa, H., et al. (1996) Effects of ethyl alcohol administration to THA rat dams during their gestation period on learning behavior and on levels of monoamines and metabolites in the brain of pups after birth. Alcohol. Clin. Exp. Res. 20(9 Suppl): 305A–310A. Gagin, R., Kook, N., et al. (1997) Prenatal morphine enhances morphine-conditioned place preference in adult rats. Pharmacol. Biochem. Behav. 58(2):525–528. Garcia, L., de Miguel, R., et al. (1996) Perinatal delta 9-tetrahydrocannabinol exposure in rats modifies the responsiveness of midbrain dopaminergic neurons in adulthood to a variety of challenges with dopaminergic drugs. Drug Alcohol Depend. 42(3): 155–166. Gibb, J.W., Johnson, M., et al. (1997) Neurotoxicity of amphetamines and their metabolites. NIDA Res. Monogr. 173:128–145. Gieron-Korthals, M.A., Helal, A., Martinez, C. R. (1994) Expanding spectrum of cocaine induced central nervous system malformations. Brain Dev. 16(3):253–256. Gingras, J.L., and O’Donnell, K.J. (1998) State control in the substance-exposed fetus: I. The fetal neurobehavioral profile: an assessment of fetal state, arousal, and regulation competency. Ann. NY Acad. Sci. 846:262–276. Gingras, J.L., O’Donnell, K.J., et al. (1990) Maternal cocaine addiction and fetal behavioral state: I. A human model for the study of sudden infant death syndrome. Med. Hypotheses 33(4):227– 230. Goldstein, R.Z., Volkow, N.D., et al. (2002) The orbitofrontal cortex in methamphetamine addiction: involvement in fear. Neuroreport 13(17):2253–2257. Gomez-Anson, B., and Ramsey, R.G. (1994) Pachygyria in a neonate with prenatal cocaine exposure: MR features. J Comput. Assist. Tomogr. 18(4):637–639. Goodman, G., Hans, S.L., et al. (1999) Attachment behavior and its antecedents in offspring born to methadone-maintained women. J. Clin. Child Psychol. 28(1):58–69. Goodwin, G.A., Moody, C.A., et al. (1993) Prenatal cocaine exposure increases the behavioral sensitivity of neonatal rat pups to ligands active at opiate receptors. Neurotoxicol. Teratol. 15(6): 425–431. Grant, P., LaGasse, L., et al. (2004) Prenatal methamphetamine use and maternal health care characteristics: preliminary results from the Infant Development, Environment, and Lifestyle Study (IDEAL). Ped. Res. 55(4 Part 2):72A. Gressens, P., Kosofsky, B.E., et al. (1992) Cocaine-induced disturbances of corticogenesis in the developing murine brain. Neurosci. Lett. 140:113–116. Gressens, P., Lammens, M., et al. (1992) Ethanol-induced disturbances of gliogenesis and neuronogenesis in the developing murine brain: an in vitro and in vivo immunohistochemical and ultrastructural study. Alcohol. 27(3):219–226. Grimm, V.E. (1987) Effect of teratogenic exposure on the developing brain: research strategies and possible mechanisms. Dev. Pharmacol. Ther. 10:328–345. Hammer, R.P., Jr., Ricalde, A.A., et al. (1989) Effects of opiates on brain development. Neurotoxicology 10(3):475–483. Hans, S.L. (1992) Maternal opioid drug use and child development. In: Zagon, I.S., and Slotkin, T.A., eds. Maternal Substance Abuse and the Developing Nervous System. San Diego, CA: Academic Press, pp. 177–213. Hansen, R.L., Struthers, J.M., et al. (1993) Visual evoked potentials and visual processing in stimulant drug-exposed infants. Dev. Med. Child Neurol. 35(9):798–805. Hauser, K.F., McLaughlin P.J., et al. (1987) Endogenous opioids regulate dendritic growth and spine formation in developing rat brain. Brain Res. 416(1):157–161.

824

SUBSTANCE ABUSE DISORDERS

Heller, A. (2000) Neurotoxicology and Developmental Effects of Meth and MDMA: Effects of in Utero Exposure to Methamphetamines. Bethesda, MD: National Institute on Drug Abuse. Heier, L.A., Carpanzano, C.R., et al. (1991) Maternal cocaine abuse: the spectrum of radiologic abnormalities in the neonatal CNS. Am. J. Neuroradiol. 12(5):951–956. Ikonomidou, C., Bittigau, P., et al. (2000) Ethanol-induced apoptotic neurodegeneration and fetal alcohol syndrome. Science 287(5455): 1056–1060. Itoh, J., Nabeshima, T., et al. (1991) Utility of an elevated plus-maze for dissociation of amnesic and behavioral effects of drugs in mice. Eur. J. Pharmacol. 194(1):71–76. Jacobson, J.L., Jacobson, S.W., et al. (1996) Increased vulnerability to alcohol-related birth defects in the offspring of mothers over 30. Alcohol Clin. Exp. Res. 20:359–363. Jacobson, S.W., Jacobson, J.L., et al. (1996) New evidence for neurobehavioral effects of in utero cocaine exposure. J. Pediatrics 129:581–589. Jaffe, J.H., and Martin, W.R. (1985) Opioid analgesics and antagonists. In: Gilman, A.G., Goodman, L.S., Rall, T.W., and Murad, F., eds. The Pharmacological Basis of Therapeutics (7th ed.). New York: Macmillan, pp. 491–531. Jeng, W., Wong, A.W., et al. (2005) Methamphetamine-enhanced embryonic oxidative DNA damage and neurodevelopmental deficits. Free Radic. Biol. Med. 39(3):317–326. Johnson, S.W., and North, R.A. (1992) Opioids excite dopamine neurons by hyperpolarization of local interneurons. J. Neurosci. 12(2):483–488. Jones, K.L., Smith, D.W., et al. (1973) Pattern of malformation in offspring of chronic alcoholic mothers. Lancet 1:1267–1271. Kandel, D.B., Wu, P., et al. (1994) Maternal smoking during pregnancy and smoking by adolescent daughters. Am. J. Pub. Health 84(9):1407–1413. Karch, S. (1993) The Pathology of Drug Abuse. Boca Raton, FL: CRC Press. Keller, R.W., Jr., Maisonneuve, I.M., et al. (1994) Effects of prenatal cocaine exposure on the nigrostriatal dopamine system: an in vivo microdialysis study in the rat. Brain Res. 634:266–274. King, R. (2006) The next big thing: methamphetamine in the United States. The Sentencing Project: research and advocacy for reform. Washington, DC: pp. 1– 41. Koob, G.F., and Le Moal, M. (1997) Drug abuse: hedonic homeostatic dysregulation. Science 278(5335):52–58. Kosofsky, B.E., Wilkins, A.S., et al. (1994) Transplacental cocaine exposure: a mouse model demonstrating neuroanatomic and behavioral abnormalities. J. Child Neurol. 9:234–241. LaGasse, L., Derauf, C., et al. (2004) Prenatal methamphetamine exposure and neonatal cry acoustic analysis: preliminary results from the Infant Development, Environment, and Lifestyle Study (IDEAL). Ped. Res. 55(4, Part 2):72A. LaGasse, L., Messinger, D., et al. (2003) Prenatal drug exposure and maternal and infant feeding behavior. Arch. Dis. Child. 88:F391– F399. Leech, S.L., Richardson G.A., et al. (1999) Prenatal substance exposure: effects on attention and impulsivity of 6-year-olds. Neurotoxicol. Teratol. 21(2):109–118. Lester, B.M., Das, A., et al. (2003) Prenatal cocaine exposure and 7-year outcome: IQ and special education. Pediatric Research (53): 534A. Lester, B.M., El Sohly, M., et al. (2001) The Maternal Lifestyle Study: drug use by meconium toxicology and maternal self-report. Pediatrics 107(2):309–317. Lester, B.M., LaGasse, L., et al. (1996) Studies of cocaine-exposed human infants. NIDA Research Monograph. 164:175–210. Lester, B.M., LaGasse, L.L., et al. (1998) Cocaine exposure and children: the meaning of subtle effects. Science 282(5389):633–634. Lester, B.M., LaGasse, L., et al. (2003) The Maternal Lifestyle Study (MLS): Effects of prenatal cocaine and/or opiate exposure on

auditory brain response at one month. J. Pediatrics 142(3):279– 285. Lester, B.M., and Tronick, E.Z. (2004) History and description of the Neonatal Intensive Care Unit Network Neurobehavioral Scale. Pediatrics 113(3 Pt 2):634–640. Lewis, B.A., Singer, L.T., et al. (2004) Four-year language outcomes of children exposed to cocaine in utero. Neurotoxicol. Teratol. 26(5) 617–627. Lidow, M.S. (1995) Prenatal cocaine exposure adversely affects development of the cerebral cortex. Synapse 21(4):332–341. Linares, T.J., Singer, L.T., et al. (2006) Mental health outcomes of cocaine-exposed children at 6 years of age. J. Pediatr. Psychol. 31(1):85–97. Loebstein, R., Koren, G., et al. (1997) Pregnancy outcome and neurodevelopment of children exposed in utero to psychoactive drugs: the Motherisk experience. J. Psychiatry Neurosci. 22(3): 192–196. London, E.D., Simon, S.I., et al. (2004) Regional cerebral dysfunction associated with mood disturbances in abstinent methamphetamine abusers. Arch. Gen. Psychiatry 61:73–84. Lovinger, D.M., and White, G. (1991) Ethanol potentiation of 5-HT3 receptor-mediated ion currents in neuroblastoma cells and isolated adult mammalian neurons. Mol. Pharmacol. 40:263–273. Lovinger, D.M., White, G., et al. (1989) Ethanol inhibits NMDAactivated ion currents in hippocampal neurons. Science 243:1721. Lukas, S. (1997) Proceedings of the National Consensus Meeting on the Use, Abuse, and Sequelae of Methamphetamine with Implications for Prevention, Treatment, and Research. Washington, DC: Center for Substance Abuse Treatment. Lumeng, J.C., Cabral, H.J., et al. (2007) Pre-natal exposures to cocaine and alcohol and physical growth patterns to age 8 years. Neurotoxicol. Teratol. 29(4):446 – 457. Manzanares, J., Corchero, J., et al. (1999) Pharmacological and biochemical interactions between opioids and cannabinoids. Trends Pharmacol. Sci. 20(7):287–294. Martellotta, M.C., Cossu, G., et al. (1998) Self-administration of the cannabinoid receptor agonist WIN 55,212-2 in drug-naive mice. Neuroscience 85(2):327–330. Matsuda, L.A., Lolait, S.J., et al. (1990) Structure of a cannabinoid receptor and functional expression of the cloned cDNA [see comments]. Nature 346(6284):561–564. Matthes, H.W., Maldonado, R., et al. (1996) Loss of morphineinduced analgesia, reward effect and withdrawal symptoms in mice lacking the mu-opioid-receptor gene [see comments]. Nature 383(6603):819–823. Mayes, L.C. (2002) A behavioral teratogenic model of the impact of prenatal cocaine exposure on arousal regulatory systems. Neurotoxicol. Teratol. 24(3):385–395. Mayes, L.C., Bornstein, M.H., et al. (1995) Information processing and developmental assessments in 3-month-old infants exposed prenatally to cocaine. Pediatrics 95(4):539–545. Mayes, L.C., and Carroll, K.M. (1996) Neonatal withdrawal syndrome in infants exposed to cocaine and methadone. Subst. Use Misuse 31(2):241–253. McCalla, S., Minkoff, H.L., et al. (1991) The biologic and social consequences of perinatal cocaine use in an inner-city population: results of an anonymous cross-sectional study. Am. J. Obstet. Gynecol. 164 (2):625–630. McCann, U.D., Wong, D.F., et al. (1998) Reduced striatal dopamine transporter density in abstinent methamphetamine and methcathinone users: evidence from positron emission tomography studies with [11C]WIN-35,428. J. Neurosci. 18:8417–8422. Mentis, M. (1998) In utero cocaine exposure and language development. Semin. Speech Lang. 19(2):147–164. Mentis, M., and Lundgren, K. (1995) Effects of prenatal exposure to cocaine and associated risk factors on language development. J. Speech Hear. Res. 38:1303–1318.

48: EFFECTS OF DRUGS OF ABUSE ON BRAIN DEVELOPMENT Messinger, D.S., Bauer, C.R., et al. (2004) The maternal lifestyle study: cognitive, motor, and behavioral outcomes of cocaine-exposed and opiate-exposed infants through three years of age. Pediatrics 113(6):1677–1685. Meyer, J.S., and Dupont, S.A. (1993) Prenatal cocaine administration stimulates fetal brain tyrosine hydroxylase activity. Brain Res. 608:129–137. Miller, M.W., and Robertson, S. (1993) Prenatal exposure to ethanol alters the postnatal development and transformation of radial glia to astrocytes in the cortex. J. Comp. Neurol. 337(2): 253–266. Miller-Loncar, C., Lester, B.M., et al. (2005) Predictors of motor development in children prenatally exposed to cocaine. Neurotoxicol. Teratol. 27(2):213–220. Minnes, S., Robin, N.H. et al. (2006) Dysmorphic and anthropometric outcomes in 6-year-old prenatally cocaine-exposed children. Neurotoxicol. Teratol. 28(1):28–38. Mirochnick, M., Frank, D.A., et al. (1995) Relation between meconium concentration of the cocaine metabolite benzoylecgonine and fetal growth. J. Pediatrics 126:636–638. Molina-Holgado, F., Amaro, A., et al. (1996) Effect of maternal delta 9-tetrahydrocannabinol on developing serotonergic system. Eur. J. Pharmacol. 316(1):39–42. Muneoka, K., Nakatsu T., et al. (1999) Prenatal administration of nicotine results in dopaminergic alterations in the neocortex. Neurotoxicol. Teratol. 21(5):603–609. Muneoka, K., Ogawa T., et al. (1997) Prenatal nicotine exposure affects the development of the central serotonergic system as well as the dopaminergic system in rat offspring: involvement of route of drug administrations. Brain Res. Dev. Brain Res. 102(1): 117– 126. Nagy, L.E., Diamond, I., et al. (1990) Ethanol increases extracellular adenosine by inhibiting adenosine uptake via the nucleoside transporter. J. Biol. Chem. 265:1946–1951. Napiorkowski, B.S., Lester, B.M., et al. (1996) Effects of in utero substance exposure on infant neurobehavior. Pediatrics 98:71–75. National Institute on Drug Abuse. (1996) National Pregnancy & Health Survey. Rockville, MD: National Institutes of Health. National Toxicology Program. (2005) NTP-CERHR, Expert Panel Report on the Reproductive and Developmental Toxicity of Amphetamine and Methamphetamine. Page 177. http://cerhr.niehs.nih .gov/chemicals/stimulants/amphetamines/Amphetamine_final.pdf. Navarro, M., Rubio P., et al. (1994) Sex-dimorphic psychomotor activation after perinatal exposure to (-)-delta 9-tetrahydrocannabinol. An ontogenic study in Wistar rats. Psychopharmacology (Berl) 116(4):414–422. Navarro, M., Rubio P., et al. (1995) Behavioural consequences of maternal exposure to natural cannabinoids in rats. Psychopharmacology (Berl) 122(1):1–14. Nestler, E.J. (1997) Molecular mechanisms of opiate and cocaine addiction. Curr. Opin. Neurobiol. 7(5):713–719. Newman, E., Risch, E.C., et al. (2007, June 6–9) Methamphetamine abuse, trauma history and child abuse potential. Poster presented at 10th European Conference on Traumatic Stress (ECOTS), Opatija, Croatia. Newman, M.B., Shytle R.D., et al. (1999) Locomotor behavioral effects of prenatal and postnatal nicotine exposure in rat offspring. Behav. Pharmacol. 10(6–7):699–706. Noland, J.S., Singer, L.T. et al. (2005) Prenatal drug exposure and selective attention in preschoolers. Neurotoxicol. Teratol. 27(3): 429–438. North, R.A., Williams, J.T., et al. (1987) Mu and delta receptors belong to a family of receptors that are coupled to potassium channels. Proc. Natl. Acad. Sci. USA 84(15):5487–5491. Nulman, I., Rovet, J., et al. (1994) Neurodevelopment of adopted children exposed in utero to cocaine. Can. Med. Assoc. J. 151: 1592–1597.

825

Oro, A.S., and Dixon, S.D. (1987) Perinatal cocaine and methamphetamine exposure: maternal and neonatal correlates. J. Pediatr. 111(4):571–578. Paulus, M.P., Hozack, N.E., et al. (2002) Behavioral and functional neuroimaging evidence for prefrontal dysfunction in methamphetamine-dependent subjects. Neuropsychopharmacology 26(1): 53–63. Pennington, S.N. (1990) Molecular changes associated with ethanolinduced growth suppression in the chick embryo. Alcohol Clin. Exp. Res. 14:832. Picciotto, M.R., Zoli, M., et al. (1998) Acetylcholine receptors containing the beta2 subunit are involved in the reinforcing properties of nicotine. Nature 391(6663):173–177. Pich, E.M., Pagliusi, S.R., et al. (1997) Common neural substrates for the addictive properties of nicotine and cocaine. Science 275 (5296):83–86. Pidoplichko, V.I., DeBiasi M., et al. (1997) Nicotine activates and desensitizes midbrain dopamine neurons. Nature 390:401–404. Plessinger, M.A. (1998) Prenatal exposure to amphetamines. Risks and adverse outcomes in pregnancy. Obstet. Gynecol. Clin. North Am. 25(1):119–138. Pontieri, F.E., Tanda G., et al. (1996) Effects of nicotine on the nucleus accumbens and similarity to those of addictive drugs. Nature 382:255–257. Prochaska, J.O., and DiClemente, C.C. (1992) Stages of change in the modification of problem behaviors. In: Hersen, M., Eisler, R., Miller, P., eds. Progress in Behavior Modification. New York: Sycamore, pp. 183–218. Pu, C., and Voorhees, C.V. (1993) Developmental dissociation of methamphetamine-induced depletion of dopaminergic terminals and astrocyte reaction in rat striatum. Brain Res. Dev. Brain Res. 72(2):325–328. Ramsey, N.F., Niesink, R.J., et al. (1993) Prenatal exposure to morphine enhances cocaine and heroin self-administration in drugnaive rats. Drug Alcohol Depend. 33(1):41–51. Regalado, M.G., Schechtman, V.L., et al. (1995) Sleep disorganization in cocaine-exposed neonates. Infant Beh. Dev. 18(3):319– 327. Regalado, M.G., Schechtman, V.L., et al. (1996) Cardiac and respiratory patterns during sleep in cocaine-exposed neonates. Early Hum. Dev. 44(3):187–200. Ricaurte, G.A., and McCann, U.D. (1992) Neurotoxic amphetamine analogues: effects in monkeys and implications for humans. Ann. NY Acad. Sci. 648:371–382. Richardson, G.A., Conroy, M.L., et al. (1997) Prenatal cocaine exposure: effects on the development of school-age children. Neurotox. Teratol. 18:627–634. Richardson, S.A., and Tizabi, Y. (1994) Hyperactivity in the offspring of nicotine-treated rats: role of the mesolimbic and nigrostriatal dopaminergic pathways. Pharmacol. Biochem. Behav. 47(2): 331–337. Richardson, G.A. (1998) Prenatal cocaine exposure. A longitudinal study of development. Ann. NY Acad. Sci. 846:144–152. Rodriguez de Fonseca, F., Cebeira M., et al. (1991) Effects of preand perinatal exposure to hashish extracts on the ontogeny of brain dopaminergic neurons. Neuroscience 43(2–3):713–723. Ronnekleiv, O.K., and Naylor, B.R. (1995) Chronic cocaine exposure in the fetal rhesus monkey: consequences for early development of dopamine neurons. J. Neurosci. 15:7330–7343. Rosen, T.S., and Johnson, H.L. (1982) Children of maintained mothers: Follow up at 18 months of age. J. Pediatr. 101:192–196. Roy, T.S., and Sabherwal, U. (1994) Effects of prenatal nicotine exposure on the morphogenesis of somatosensory cortex. Neurotoxicol. Teratol. 16(4):411– 421. Salisbury, A.L., Lester, B., et al. (2007) Prenatal cocaine use and maternal depression: effects on infant neurobehavior. Neurotoxicol. Teratol. 29(3):331–340.

826

SUBSTANCE ABUSE DISORDERS

Substance Abuse and Mental Health Services Administration (SAMHSA). (1995) National Household Survey on Drug Abuse #18. Rockville, MD: Author SAMHSA. (2002) Summary of Findings from the 1999–2000 National Household Survey on Drug Abuse. Rockville, MD: Author. SAMHSA. (2005a) Results from the 2004 National Survey on Drug Use and Health: National Findings. Rockville, MD: Author. SAMHSA. (2005b) Treatment Episode Data Set (TEDS) 1993–2003: National Admissions to Substance Abuse Treatment Services for the Department of Health and Human Services. Rockville, MD: Author. Schroder, M.D., Snyder, P.J., et al. (2004) Impaired performance of children exposed in utero to cocaine on a novel test of visuospatial working memory. Brain Cogn. 55(2):409–412. Seiden, L., and Sabol, K.E. (1996) Methamphetamine and methylenedioxymethamphetamine neurotoxicity: possible mechanisms of cell destruction. NIDA Res. Monogr. 163:251–276. Seidler, F.J., Levin, E.D., et al. (1992) Fetal nicotine exposure ablates the ability of postnatal nicotine challenge to release norepinephrine from rat brain regions. Brain Res. Dev. Brain Res. 69(2): 288–291. Seifer, R., LaGasse, L.L., et al. (2004) Attachment status in children prenatally exposed to cocaine and other substances. Child Dev. 75(3):850–868. Sekine, Y., Minabe, Y., et al. (2003) Association of dopamine transporter loss in the orbitofrontal and dorsolateral prefrontal cortices with methamphetamine-related psychiatric symptoms. Am. J. Psychiatry 160(9):1699–1701. Self, D.W., Terwilliger, R.Z., et al. (1994) Inactivation of Gi and G(o) proteins in nucleus accumbens reduces both cocaine and heroin reinforcement. J. Neurosci. 14(10):6239–6247. Shacka, J.J., Fennell, O.B., et al. (1997) Prenatal nicotine sexdependently alters agonist-induced locomotion and stereotypy. Neurotoxicol. Teratol. 19(6):467– 476. Shankaran, S., Bauer, C.R., et al. (2003) Health-care utilization among mothers and infants following cocaine exposure. J. Perinatol. 23(5):361–367. Sheinkopf, S.J., Lester, B., et al. (2005) Neonatal irritability, prenatal substance exposure, and later parenting stress. J. Pediatr. Psychol. 31:27–40. Sims, M.E., Walther, F.J., et al. (1989) Neonatal ultrasound casebook. Antenatal brain injury and maternal cocaine use. J. Perinatol. 9(3):349–350. Singer, L.T., Minnes, S., et al. (2004) Cognitive outcomes of preschool children with prenatal cocaine exposure. JAMA 291(20): 2448–2456. Singer, L.T., Yamashita, T. S., et al. (1994) Increased incidence of intraventricular hemorrhage and developmental delay in cocaineexposed, very low birth weight infants. J. Pediatr. 124(5 Pt 1): 765–771. Slamberova, R., Pometlova, M., et al. (2006) Postnatal development of rat pups is altered by prenatal methamphetamine exposure. Prog. Neuropsychopharmacol. Biol. Psychiatry 30(1):82–88. Slotkin, T.A. (1992) What can we learn from animal models? In: Zagon, I.S., Slotkin, T.A., eds. Maternal Substance Abuse and the Developing Nervous System. San Diego, CA: Academic Press, pp. 97–124. Smeriglio, V.L. (1999) Prenatal drug exposure and child outcome. Past, present, future. Clin. Perinatol. 26(1):1–16. Smith, D.W. (1981) Fetal alcohol syndrome and fetal alcohol effects. Neurobehav. Toxicol. Teratol. 3:127. Smith, L., Yonekura, M.L., et al. (2003) Effects of prenatal methamphetamine exposure on fetal growth and drug withdrawal symptoms in infants born at term. J. Dev. Behav. Pediatr. 24(1): 17–23.

Smith, L.M., Chang, L., et al. (2001a) Brain proton magnetic resonance spectroscopy and imaging in children exposed to cocaine in utero. Pediatrics 107:227–231. Smith, L.M., Chang, L., et al. (2001b) Brain proton magnetic resonance spectroscopy in children exposed to methamphetamine in utero. Neurology 57(2):255–260. Smith, L.M., LaGasse, L.L., et al. (2008) Prenatal methamphetamine use and neonatal neurobehavioral outcome. Neurotoxicol. Teratol. 30:20–28. Smith, L.M., LaGasse, L.L., et al. (2006) The infant development, environment, and lifestyle study: effects of prenatal methamphetamine exposure, polydrug exposure, and poverty on intrauterine growth. Pediatrics 118(3):1149–1156. Snyder-Keller, A.M., and Keller, R.W., Jr. (1993) Prenatal cocaine increases striatal serotonin innervation without altering the patch/ matrix organization of intrinsic cell types. Dev. Brain Res. 74: 261–267. Spear, L.P. (1995) Neurobehavioral consequences of gestational cocaine exposure: a comparative analysis. In: Rovee-Collier, C., and Lipsitt, L.P., eds. Advances in Infancy Research, Vol. 9. Norwood, NJ: Ablex, pp. 55–105. Stadlin, A., Choi, H.L., et al. (1994) Postnatal changes in [3H]mazindol-labelled dopamine uptake sites in the rat striatum following prenatal cocaine exposure. Brain Res. 637:345–348. Stek, A.M., Baker, R.S., et al. (1995) Fetal responses to maternal and fetal methamphetamine administration in sheep. Am. J. Obstet. Gynecol. 173(5):1592–1598. Stek, A.M., Fisher, B.K., et al. (1993) Maternal and fetal cardiovascular responses to methamphetamine in the pregnant sheep. Am. J. Obstet. Gynecol. 169(4):888–897. Stoler, J.M., Huntington K.S., et al. (1998) The prenatal detection of significant alcohol exposure with maternal blood markers. J. Pediatr. 133(3):346–352. Stratton, K., Howe, C., et al. (1996) Fetal Alcohol Syndrome. Washington, DC: National Academy Press. Streissguth, A.P., Barr, H.M., et al. (1996) Understanding the Occurence of Secondary Disabilities in Clients with Fetal Alcohol Syndrome and Fetal Alcohol Effects. Seattle: University of Washington Press. Struthers, J.M., and Hansen, R.L. (1992) Visual recognition memory in drug-exposed infants. J. Dev. Behav. Pediatr. 13(2):108–111. Suess, P.E., Newlin D.B., et al. (1997) Motivation, sustained attention, and autonomic regulation in school-age boys exposed in utero to opiates and alcohol. Exp. Clin. Psychopharmacol. 5(4): 375–387. Tanda, G., Pontieri, F.E., et al. (1997) Cannabinoid and heroin activation of mesolimbic dopamine transmission by a common mu1 opioid receptor mechanism [see comments]. Science 276(5321): 2048–2050. Thompson, P.M., Hayashi, K.M., et al. (2004) Structural abnormalities in the brains of human subjects who use methamphetamine. J. Neurosci. 24(26):6028–6036. Tizabi, Y., Russell L.T., et al. (2000) Prenatal nicotine exposure: effects on locomotor activity and central [125I]alpha-BT binding in rats. Pharmacol. Biochem. Behav. 66(3):495–500. Tronick, E.Z., Frank, D.A., et al. (1996) Late dose-response effects of prenatal cocaine exposure on newborn behavioral performance. Pediatrics 98:76–83. Tronick, E.Z., Messinger, D.S., et al. (2005) Cocaine exposure is associated with subtle compromises of infants’ and mothers’ social emotional behavior and dyadic features of their interaction in the face-to-face still-face paradigm. Dev. Psychol. 41(5):711–722. Vela, G., Fuentes, J.A., et al. (1995) Perinatal exposure to delta 9tetrahydrocannabinol (delta 9-THC) leads to changes in opioidrelated behavioral patterns in rats. Brain Res. 680(1/2):142– 147.

48: EFFECTS OF DRUGS OF ABUSE ON BRAIN DEVELOPMENT Vela, G., Martin S., et al. (1998) Maternal exposure to delta9tetrahydrocannabinol facilitates morphine self-administration behavior and changes regional binding to central mu opioid receptors in adult offspring female rats. Brain Res. 807(1–2):101–109. Volkow, N.D., Chang, L., et al. (2001) Dopamine transporter losses in methamphetamine abusers are associated with psychomotor impairment. Am. J. Psychiatry 158:377–382. Wafford, K.A., Burnett, D.M., et al. (1991) Ethanol sensitivity of the GABA-A receptor expressed in xenopus oocytes requires 8 amino acids contained in the gamma 2L subunit. Neuron 7:1–20. Wallace, T.L., Gudelsky, G.A., et al. (1999) Methamphetamine-induced neurotoxicity alters locomotor activity, stereotypic behavior, and stimulated dopamine release in the rat. J. Neurosci. 19(20):9141–9148. Walters, D.E. and Carr, L.A. (1986) Changes in brain catecholamine mechanisms following perinatal exposure to marijuana. Pharmacol. Biochem. Behav. 25(4):763–768. Wang, L., and Pitts, D.K. (1994) Perinatal cocaine exposure decreases the number of spontaneously active midbrain dopamine neurons in neonatal rats. Synapse 17:275–277. Warner, T.D., Behnke, M., et al. (2006) Diffusion tensor imaging of frontal white matter and executive functioning in cocaine-exposed children. Pediatrics 118(5):2014–2024. Weissman, A.D., and Caldecott-Hazard, S. (1995) Developmental neurotoxicity to methamphetamines. Clin. Exp. Pharmacol. Physiol. 22(5):372–374. Westergren, S., Rydenhag, B., et al. (1996) Effects of prenatal alcohol exposure on activity and learning in Sprague-Dawley rats. Pharmacol. Biochem. Behav. 55(4):515–520.

827

Wilkins, A.S., Jones K., et al. (1998) Transplacental cocaine exposure. 2: Effects of cocaine dose and gestational timing. Neurotoxicol. Teratol. 20(3):227–238. Williams, M.T., Blankenmeyer, T.L., et al. (2003) Long-term effects of neonatal methamphetamine exposure in rats on spatial learning in the Barnes maze and on cliff avoidance, corticosterone release, and neurotoxicity in adulthood. Brain Res. Dev. Brain Res. 147(1-2):163–175. Wilson, G. S. (1989) Clinical studies of infants and children exposed prenatally to heroin. Ann. NY Acad. Sci. 562:183–194. Woods, J.R., Plessinger, M.A., et al. (1987) Effect of cocaine on uterine blood flow and fetal oxygenation. JAMA 257:957–961. Woolverton, W.L., Ricaurte, G.A., et al. (1989) Long-term effects of chronic methamphetamine administration in rhesus monkeys. Brain Res. 486(1):73–78. Wouldes, T., LaGasse, L., et al. (2004) Maternal methamphetamine use during pregnancy and child outcome: what do we know? N.Z. Med. J. 117(1206):U1180. Xu, Z., Seidler F.J., et al. (2001) Fetal and adolescent nicotine administration: effects on CNS serotonergic systems. Brain Res. 914(1–2):166–178. Yamamoto, Y., Yamamoto, K., et al. (1992) Teratogenic effects of methamphetamine in mice. Nihon Hoigaku Zasshi 46(2):126– 131. Zagon, I.S., and McLaughlin, P.J. (1986) Opioid antagonist-induced modulation of cerebral and hippocampal development: histological and morphometric studies. Brain Res. 393(2):233–246. Zuckerman, B., Frank, D.A., et al. (1989) Effects of maternal marijuana and cocaine use on fetal growth. N. Engl. J. Med. 320(12): 762–768.

49 PET and SPECT Imaging in Substance Abuse Research JOANNA S. FOWLER

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The addiction to legal and illegal drugs poses one of the most medically, socially, and economically devastating public health problems facing modern society. Yet resources dedicated to the prevention and treatment of the addictions lags behind other medical problems. Although the perception of addiction as a lack of willpower or a moral weakness rather than a disease of the brain still persists, modern imaging technologies developed over the last 30 years have documented that drugs of abuse produce measurable changes on the human brain and that many factors including individual biology and genetics, environmental factors, and the characteristics of the drug and the route or vehicle for its administration all play a role. In this chapter we describe positron emission tomography (PET) and single photon emission computed tomography (SPECT) technology that are the main brain imaging methods that have been used in the study of drug addiction. We highlight some of the insights on the effects of drugs of abuse on the human brain that have been gained through the use of brain imaging in humans. We note that there is an increasing trend to use combinations of different radiotracers and imaging methods along with behavioral and drug challenge strategies to probe the complex relationship of pharmacological and functional factors and addictive behaviors. This carries with it the need for large-scale statistical analyses of imaging data sets to extract correlations that will provide mechanistic information of relationships between brain chemistry and behavior. In addition, preclinical studies in animals have been valuable in elucidating mechanisms and in providing deeper insights into results gained from human studies. This chapter is intended to be an update since 2002 (Fowler and Volkow, 2004). We note that a number of recent review articles have appeared on the topic of neuroimaging and addiction (Volkow et al., 2004; Gatley et al., 2005; LingfordHughes, 2005; Chang and Haning, 2006). 828

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PET AND SPECT TECHNOLOGY Modern brain imaging instruments have provided mechanistic information on how the brain works and how drugs of abuse affect the brain. These properties include (1) brain anatomy and tissue composition, (2) neurochemical processes, (3) physiological and functional processes that provide information on brain energy utilization and blood flow and hence can be used to assess regional brain function, and (4) drug distribution and kinetics that provide information uptake, regional distribution, and residence time in the brain. Although we focus on PET and SPECT that are nuclear imaging methods, we note that the use of magnetic resonance imaging (MRI) in addiction research continues to increase and complement the nuclear imaging studies by providing information on brain anatomy and tissue composition as well as brain activation through the use of anatomical MRI, magnetic resonance spectroscopy (MRS), and functional magnetic resonance imaging (fMRI) (Lecchi et al., 2007). Positron emission tomography and SPECT are unique relative to other currently available imaging techniques because they have the highest sensitivity to detect very small concentrations of cellular elements (Fowler et al., 2003; Kung et al., 2003). This property enables the measurement of cellular elements involved with neurotransmission such as receptors, transporters, and enzymes involved with synthesis or metabolism of neurotransmitters (Volkow et al., 2003). There are different radiotracers that can be used to visualize different elements (usually proteins) of the cell. In a PET or SPECT study, a radioactive molecule (radiotracer) is injected into the bloodstream. The energy emitted by the decay of the radioisotope penetrates the body barrier, and thus its location and movement into and out of the brain can be visualized from outside the body using a PET or SPECT scanner.

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Positron emission tomography and SPECT instruments differ in several aspects including the characteristics of the instrumentation, the isotopes used, and the availability of the technology. Generally speaking, the resolution and sensitivity of PET instruments exceeds that of SPECT instruments. The use of positronemitting isotopes with PET offers advantage because positrons interact with electrons generating photons that are liberated 180 degrees apart from each other, which enables their detection without the need of collimators as required with single photon emitter isotopes used with SPECT, and that decrease sensitivity. Positron emission tomography studies are carried out with compounds labeled with positron (β +) emitting radioisotopes that are very short lived. There are positron emitting isotopes for the natural elements of life: carbon-11 (t1/2: 20.4 minutes), oxygen-15 (t1/2: 2 minutes), and nitrogen-13 (t1/2: 10 minutes). There is also a positron emitting isotope of fluorine, fluorine– 18((t1/2: 110 minutes and that can often be used to substitute for hydrogen or oxygen). Thus, organic compounds (including drugs) can be labeled without changing the properties of the parent molecule by substituting carbon–11 for stable carbon (carbon– 12) in the molecule. Positron emission tomography can therefore be uniquely used to determine how much drug penetrates the brain, where a drug binds in the brain, and how fast it moves into and out of the brain (Fowler et al., 1999). This information is crucial because the rate at which a drug enters the brain is known to be a powerful determinant of reinforcement. Positron emission tomography is also unique in the availability of 2-deoxy-2-[18F]fluoro-D-glucose (18FDG, a radiotracer for glucose) can be used to assess glucose metabolism in brain that is of major importance because glucose is the major source of energy for the human brain (Fowler and Ido, 2002). Single photon emission computed tomography radiotracers are labeled with single photon emitting radioisotopes that are significantly longer lived than PET radiotracers. Single photon emission computed tomography radiotracers are usually labeled with iodine123 (t1/2: 13.3 hours) or technetium-99m (t1/2: 6.5 hours). These isotopes cannot be incorporated into a drug molecule because these elements are not found in drugs. Nonetheless, many radioiodine-substituted radiotracers have been developed that have high biological selectivity and affinity for specific proteins in the cell (Kung et al., 2003), and Tc-99m labeled radiotracers such as Tc-99m-HMPAO are widely used to measure brain blood flow. There is no SPECT counterpart to 18FDG for measuring brain glucose metabolism. Positron emission tomography and SPECT can be used as tracer techniques, that is, the radiolabeled compounds are administered in a very tiny chemical quan-

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tity so that there is no pharmacological effect. The use of PET and SPECT radiotracers that have specificity for important cellular elements provides high biochemical specificity and sensitivity to changes produced by drugs or by disease. For example, these radiotracers can be used to differentiate dopamine (DA) transporters that are molecules located in presynaptic terminals from receptors that are mostly located in postsynaptic cells, despite the fact that the transporters and receptors are 20–50 nanometers apart. COCAINE Cocaine binds to DA, norepinephrine (NE), and serotonin transporters (SERTs) with micromolar to submicromolar affinity (Ritz et al., 1987). There is mounting evidence that the binding of cocaine to the DA transporter (DAT) with its rapid ensuing elevation of DA dominates its powerful behavioral effects in humans (Volkow et al., 2003). Cocaine addiction is also typically associated with intense drug craving stimulated by internal (pharmacological) or by environmental cues associated with past drug experience that are likely to be strong contributing factors to relapse that is typical in cocaine treatment approaches. Imaging studies have addressed cocaine abuse from its pharmacokinetic and pharmacodynamic perspectives (Volkow et al., 2003). When a behaviorally active dose of cocaine is administered intravenously along with [11C]cocaine in current cocaine abusers, there is very high and very rapid brain uptake and clearance of the drug in the striatum that contains the reward center (nucleus accumbens). The movement of cocaine into and out of the brain parallels the time course of the intense behavioral “high” measured in the same individuals. Rapid kinetics is consistent with the intense but short-lived “high” and the binge-like pattern of cocaine use in the individual who is addicted. In these same studies, it was determined that a DAT occupancy in excess of 60% is required for a “high” to be perceived (Volkow, Wang, Fischman, et al., 1997). Interestingly, behaviorally active doses of cocaine occupy > 60% of the DATs irrespective of the route of administration (intravenous vs. smoked vs. snorted). However, the time course of the behavioral response was significantly different with the “high” appearing most rapidly with the smoked >intravenous >> intranasal (Volkow et al., 2000). This study provides the first evidence in humans that differences in the reinforcing effects of cocaine as a function of the route of administration are not due to differences in DAT occupancy. It also highlights the importance of the rate of cocaine’s delivery into the brain on its reinforcing effects and corroborates the landmark studies of Balster and Schuster, who pointed this out more than 30 years ago (Balster and Schuster, 1973).

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Positron emission tomography studies measuring DA D2 receptors with [11C]raclopride and other radiotracers have consistently shown long-lasting decreases in DA D2 receptors in cocaine abusers when compared with controls (Fig. 49.1; see also COLOR FIGURE 49.1 in separate insert) (Volkow et al., 2003). Reductions in DA D2 receptors occur across striatal subdivisions in individuals who are cocaine dependent relative to healthy controls (Martinez et al., 2004). Cocaine abusers also showed significant reductions in DA release in response to a challenge dose of the stimulant drug methylphenidate relative to a control group (Volkow, Wang, Fowler, et al., 1997). Decreased DA release is consistent with the hypothesis that the decreases in DA D2 receptors coupled with the decreases in DA release would result in a decreased sensitivity of reward circuits to stimulation by natural reinforcers such as food because the reinforcing effects of food also appear to involve DA release and stimulation of DA D2 receptors (Volkow, Wang, Fowler, et al., 2002). This would be predicted to lead to a decrease in motivational salience for day-to-day environmental stimuli, which would put individuals at greater risk for seeking drug stimulation as a means to temporarily activate these reward circuits. Brain glucose metabolism as measured with 18FDG has been used to identify brain regions that differ as a result of chronic cocaine exposure as well as identify-

ing the brain regions that are activated in response to pharmacological challenge or to cocaine cues. For example, brain glucose metabolism measured in this same group of cocaine abusers in whom DA D2 receptors was measured previously revealed that the reductions in DA D2 receptors were associated with decreased activity in anterior cingulate gyrus (CG) and orbitofrontal cortex (OFC) (Figs. 49.1 and 49.2; see also COLOR FIGURE 49.2 in separate insert) (reviewed in Volkow et al., 2003). These associations could either reflect a disruption of these cortical brain regions secondary to the changes in DA activity or alternatively, it could be interpreted as indicating a disruption of frontal regions, which then deregulate DA cell activity. In contrast to the decrements in metabolic activity observed in detoxified cocaine abusers, the OFC was hypermetabolic in active cocaine abusers in proportion to the intensity of the craving (Volkow et al., 1991). Metabolism also increases in the OFC in the cocaine abusers in response to intravenous administration of the stimulant drug methylphenidate in the abusers reporting intense craving (Volkow, Wang, et al., 1999). This and a more recent study comparing the regional metabolic response to an intravenous dose of methylphenidate identified the right medial prefrontal cortex as a region that is uniquely activated in individuals who are addicted and decreased in controls (Volkow et

49.1 Simplified diagram of a dopamine synapse showing the dopamine transporter, dopamine receptors, and MAO-B (in glia cells). PET images of the human brain (clockwise from upper left) show brain MAO-B inhibition in a smoker measured with [11C]Ldeprenyl-D2, reduced dopamine transporter availability in an abuser

of methamphetamine (measured with [11C]d-threo-methylphenidate), reduced dopamine D2/D3 receptors in an abuser of cocaine (measured with [11C]raclopride) and reduced glucose metabolism in the orbitofrontal cortex (OFC) in a cocaine abuser (measured with 18FDG). MAO-B: monoamine oxidase B; PET: positron emission tomography.

FIGURE

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FIGURE

49.2 The left shows images of brain glucose metabolism in a control and in an abuser of cocaine at the level where the OFC is located. The right side of the figure shows the regression slopes between the availability of dopamine D2 receptors and metabolism in

OFC for a group of abusers of cocaine and for a group of abusers of methamphetamine. Note that the lower the D2 receptor availability, the lower the metabolism in OFC. Modified from Volkow et al., 2004. OFC: orbitofrontal cortex.

al., 2005). These findings suggest that enhanced sensitivity of right medial orbital prefrontal cortex in individuals who are addicted to cocaine may underlie the strong emotional response to the drug and the intense desire to procure it that results in craving and compulsive drug intake. The OFC is involved with learning stimulus–reinforcement associations and with conditioned responses (Rolls, 2000) and could therefore participate in cues or drug-induced craving. Activation of the OFC has also been shown in drug abusers during craving elicited by viewing a video of drug paraphernalia (Grant et al., 1996; Childress et al., 1999) and by recalling previous drug experiences (Wang et al., 1999). Preclinical studies have shown that with repeated drug exposure, neutral stimuli paired with the drug (conditioned stimuli) start to increase DA by themselves, which is an effect that could underlie drug-seeking behavior (P.E. Phillips et al., 2003). Recent studies using [11C]raclopride have shown that the presentation of cocaine cues to the cocaine abuser results in a measurable change in [11C]raclopride binding in the dorsal striatum, indicating that the cocaine cue alone is sufficient to change brain DA levels. Moreover, the magnitude of the DA elevation is associated with the degree of craving that is elicited by these cues (Volkow, Wang, Telang, et al., 2006; Wong et al., 2006). These studies provide evidence that DA in the dorsal striatum (region implicated in habit learning and in action initiation) is involved with craving and is a fundamental component of addiction. Because craving is a key contributor to relapse, strategies aimed at inhibiting DA increases from

conditioned responses are likely to be therapeutically beneficial in cocaine addiction. The endogenous opioid system has also been implicated in cocaine dependence and craving. Brain muopioid binding was increased in cocaine addicts studied 1–4 days after their last use of cocaine using PET and [11C]carfentanil, a radioligand with specificity for the mu-opioid receptor. Increased binding persisted for 4 weeks and was positively correlated with the severity of cocaine craving (Zubieta et al., 1996). In another study extending the experimental period to 12 weeks, mu-opioid receptor binding was found to be elevated in the frontal, anterior cingulate, and lateral temporal cortex after 1 day of abstinence. Mu-opioid receptor binding potential remained elevated in the first two regions after 1 week and in the anterior cingulate and anterior frontal cortex after 12 weeks. Increased binding in some regions at 1 day and 1 week was positively correlated with self-reported cocaine craving, suggesting that chronic cocaine use influences endogenous opioid systems in the human brain and might explain mechanisms of cocaine craving and reinforcement (Gorelick et al., 2005). The role of the brain serotonin system in the chronic neural adaptations to cocaine dependence was studied in 15 individuals who were cocaine dependent during acute abstinence using [123I]β -CIT (Jacobsen et al., 2000) a SPECT tracer for measuring SERT availability and showed significant increases in diencephalic and brain-stem SERT binding, suggesting serotonergic dysfunction during acute cocaine abstinence.

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METHAMPHETAMINE Methamphetamine (METH) is a highly addictive stimulant drug. Its principle pharmacological action is the release of DA and other neurotransmitters through the individual neurotransmitter transporters on the presynaptic neurons and on intracellular vesicles (Barr et al., 2006). Methamphetamine has been shown to be neurotoxic to laboratory animals at doses that are selfadministered in human abusers (Zhu et al., 2006, and references therein), and studies in abusers of METH have documented significant losses in DAT postmortem (Wilson et al., 1996). Among other causes, oxidative stress, excitotoxicity, and mitochondrial dysfunction appear to play a major role in the neurotoxicity produced by METH and other substituted amphetamines (Quinton and Yamamoto, 2006). Neuroimaging studies have addressed the effects of chronic METH abuse on the brain glucose metabolism and on DATs and DA receptors in the METH abuser. In one of these studies, recently abstinent abusers of METH (< 6 months) were scanned with 18FDG, [11C]raclopride (to measure DA D2/D3 receptors) and [11C]d-threo-methylphenidate to measure DATs (reviewed in Volkow et al., 2003) and were evaluated for cognitive and motor performance. Methamphetamine abusers showed losses in DAT that were associated with reduced motor speed and impaired verbal learning (Fig. 49.1). Dopamine D2 receptors were also lower than in the comparison group, and these reductions were associated with reduced glucose metabolism in the OFC (Fig. 49.2). This association is similar to the correlation between DA D2 receptors and brain glucose metabolism observed in cocaine abusers, suggesting that D2 receptor-mediated dysregulation of the OFC could be a common mechanism underlying loss of control and compulsive drug intake (Volkow and Fowler, 2000). Positron emission tomography studies with 18FDG have assessed regional brain function in recently abstinent METH abusers and its relationship to executive function, cognitive deficits, and mood disturbances. One of these studies in abusers who were abstinent with METH reported persistent hypometabolism in the frontal white matter and impairment in frontal executive function that was more prominent in men than in women (Kim et al., 2005). Another study in abusers who were recently abstaining from METH (4–7 days) reported abnormalities in limbic and paralimbic regions that were related to self-reports of depression and anxiety, suggesting that these regions are involved in affective dysregulation and may be an important target of intervention for methamphetamine dependence (London et al., 2004). A combined PET-18FDG/MRI study examining the links between METH-induced deficits in regional brain metabolism and cognitive deficits reported that abusers who were recently abstaining from METH (4–7

days) have cognitive, metabolic, and structural deficits in limbic and paralimbic cortices, and reduced hippocampal volume and that dysfunction in the cingulate and insular cortices contribute to impaired vigilance and other cognitive functions requiring sustained attention (London et al., 2005). The question of whether DAT, brain glucose metabolism, and motor and cognitive function recovers after protracted abstinence (12–17 months) has been addressed in some abusers of METH who had been scanned during early detoxification. Although these studies showed recovery of DAT levels, clinical improvement was not significant (Volkow, Chang, Wang, Fowler, Franceschi, Sedler, Gatley, Miller, et al., 2001). Another PET study in male abusers of METH provided evidence that longer use of METH may cause more severe psychiatric symptoms and greater reduction of DAT (as measured with [11C]WIN 35428) and that the decrease in DAT persists even when METH use ceases (Sekine et al., 2001). A more recent study in this same group of individuals reported that DAT level in the PFC was significantly associated with duration of METH use and severity of psychiatric symptoms (Sekine et al., 2003). The recovery of brain function (as measured with 18FDG) in abusers of METH after protracted withdrawal has also been assessed. During early abstinence, abusers of METH showed changes in metabolism in DA and non-DA brain regions when compared to a control group (Volkow, Chang, Wang, Fowler, Franceschi, Sedler, Gatley, Hitzemann, et al., 2001). Whole brain metabolism in the abusers of METH was 14% higher than that of control, with differences most prominent in the parietal cortex (+20%), a region devoid of DA innervation (Volkow, Chang, Wang, Fowler, Franceschi, Sedler, Gatley, Hitzemann, et al., 2001). Metabolic deficits in the striatum and the thalamus were also observed. Follow-up studies in some of these abusers showed significant metabolic recovery in the thalamus that was associated with improvements in motor and verbal memory tests, whereas decrements in striatal metabolism persisted, possibly accounting for the amotivation and anhedonia in these abusers (Wang et al., 2004). These results suggest that, though protracted abstinence may reverse some of the METH-induced alterations in brain function, other deficits persist. The documentation of METH-induced neurotoxicity in serotonin neurons and associated aggression in animals stimulated a recent investigation of the effects of METH abuse on SERTs in humans and relationships to clinical phenotypes (Sekine et al., 2006). This study with [11C](+)McN-5652 revealed that the SERT density in global brain regions (for example, the midbrain, thalamus, caudate, putamen, cerebral cortex, and cerebellum) was significantly lower in abusers of METH than in controls, and this reduction was inversely correlated with the duration of METH use. Furthermore,

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statistical parametric mapping analyses indicated that the density in the orbitofrontal, temporal, and anterior cingulate areas was closely associated with the magnitude of aggression in abusers of METH. The authors concluded that protracted abuse of METH may reduce the density of the SERT in the brain, leading to elevated aggression, even in abusers who are currently abstinent. METHYLENEDIOXYMETHAMPHETAMINE (MDMA) Methylenedioxymethamphetamine (MDMA; also called ecstasy) is a popular recreational drug that is toxic to serotonin neurons in laboratory animals (Ricaurte et al., 1988; McCann et al., 2001). It potently releases serotonin and DA from their vesicular storage sites (for review, see Huether et al., 1997). Similar to METH and other substituted amphetamines, excitotoxicity and oxidative stress may account in part for its neurotoxicity (Quinton and Yamamoto, 2006). Due to its increased use and the potential for neurotoxicity, neuroimaging studies in users of MDMA have been used to evaluate toxicity in the human MDMA user. There are several recent reviews of neuroimaging studies of MDMA (Reneman et al., 2006; Thomasius et al., 2006; Cowan, 2007). The controversies, gaps in knowledge, and methodological challenges associated with PET studies to determine whether or not MDMA is neurotoxic in humans have been discussed (Lyvers, 2006). Most PET studies have been directed to understanding its potential for damaging serotonergic neurons. Positron emission tomography-18FDG studies to examine changes in brain function after long-term use of MDMA report a global reduction in 18FDG uptake rates that is most pronounced in the striatum. Reductions tended to be correlated with cumulative MDMA doses, suggesting that younger MDMA users may be more vulnerable to MDMA-induced neurotoxicity (Obrocki et al., 2002). Early studies using [11C]McN5652 to examine SERT density in users of MDMA reported that heavy use of MDMA is associated with neurotoxic effects on serotonin neurons, that women may be more susceptible than men, and that MDMA-induced changes in several brain regions of female ex-MDMA users are reversible (Reneman et al., 2001). More recent studies have confirmed reductions in SERTs in MDMA users during early abstinence in 30 current MDMA users, 29 former MDMA users, 29 drug-naïve comparisons, and 29 polydrug users (Buchert et al., 2004). In the users of MDMA, SERT availability as assessed by [11C]McN5652 was significantly reduced in the mesencephalon, thalamus, left caudate, hippocampus, occipital cortex, temporal lobes, and posterior cingulate gyrus. Reduction was more pronounced in female than in male users, and there was no significant difference between the MDMA

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users and the other groups. These findings support the hypothesis of MDMA-induced protracted alterations of the serotonergic system and indicate that the reduced availability of SERT, as measured by PET, might be reversible. Similar findings were reported in another study in which two different radiotracers, [11C]McN5652 and [11C]DASB, were compared in 23 abstinent users of MDMA and 19 non-MDMA controls (McCann et al., 2005). Comparisons in 15 regions of interest demonstrated that the two different tracers gave comparable results showing that reductions occurred in selected cortical and subcortical structures. Exploratory correlational analyses suggested that SERT measures recover with time, and that loss of the SERTs is directly associated with MDMA use intensity. The possibility that decreases in SERT levels are an artifact of tracer kinetic model used for [11C]McN5652 was evaluated in 30 current, 29 former users of ecstasy, 29 drug-naïve comparisons, and 28 polydrug controls using a model that is less sensitive to the effect of statistical noise (Buchert et al., 2006). The equilibrium specific-to-nonspecific partition coefficient V3 was obtained voxel-wise by application of the simplified reference tissue method (SRTM), showed SERT reductions in the striatum and in the thalamus in current users of ecstasy. This was corroborated by volume-of-interest– based analysis confirming previous reports and indicating that reduced SERT binding potential is not an artifact of tracer kinetic modeling. However, SRTM analysis did not confirm previous finding of SERT reductions in neocortical brain areas. ALCOHOL The neurochemical mechanisms by which alcohol produces its acute and chronic effects are complex and not well understood. However, there is evidence that alcohol reinforcement is mediated by an activation of γ -aminobutyric acid (GABA)-A receptors, release of opioid peptides, release of DA, inhibition of glutamate receptors, and interaction with serotonin systems, making these systems of special relevance in understanding the effects of alcohol on the brain (Koob et al., 1998). Many different radiotracers including 18FDG as well as others with specificity for different neurotransmitter systems have been used to examine the acute and chronic effects of alcohol on brain metabolism and brain neurotransmitter activity in normal individuals, individuals with an alcohol addiction, and individuals at risk (reviewed in Volkow et al., 2003). Neuroimaging has also been used to study alcohol toxicity (reviewed in Mann et al., 2001). Positron emission tomography measures of brain glucose metabolism using 18FDG have shown that individuals with an alcohol addiction and individuals who are

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not addicted respond differently to an alcohol challenge. Individuals with an alcohol addiction show a smaller behavioral response and a larger metabolic response than normal individuals (reviewed in Volkow et al., 2003). Different responsivity between individuals with an alcohol addiction and a comparison group was also seen for the lorazepam (a benzodiazepine drug that, like alcohol, also enhances GABA transmission) challenge, indicating altered GABA-BZR function in individuals with an alcohol addiction (reviewed in Volkow et al., 2003). The effects of an acute challenge with an intoxicating dose of alcohol (0.75 g/kg) on brain glucose metabolism were measured in normal healthy individuals with 18FDG and PET and produced substantial decreases in occipital cortex and increases in left temporal cortex similar to previous studies with lorazepam (Volkow, Wang, Overall, et al., 1997) that has been interpreted to reflect alcohol-induced decreases on brain GABA-BZR activity. Building on evidence that alcohol has effects on the GABA, PET and SPECT imaging have shown decreased benzodiazepine receptor levels in individuals with an alcohol addiction and in controls with [11C]flumazenil (Gilman et al., 1996) and [123I]iomazenil (Abi-Dargham, et al., 1998). A recent study designed to test the hypothesis that alcohol dependence is associated with reduced benzodiazepine receptor function showed that although alcohol dependence is associated with decreased midazolam-induced time asleep, there is no difference in receptor occupancy by midazolam (as measured with [11C]flumazenil) in individuals who were dependent upon alcohol relative to a control group. This was not predicted and may be accounted for by a difference in GABABDZ subunit profile (Lingford-Hughes et al., 2005). Gender has also been studied as a variable in the acute effects of alcohol by comparing changes in brain glucose metabolism during alcohol intoxication (0.75 g/kg) in healthy male and female controls (Wang et al., 2003). The magnitude of the alcohol-induced change in brain metabolism was significantly larger in male (–25 ± 6%) than in female (–14 ± 11%; p < .005) individuals; in contrast, the self-reports for the perception of intoxication were significantly greater in females than in males. This study shows a markedly blunted sensitivity to the effects of acute alcohol on brain glucose metabolism in females. Blunted metabolic responses could reflect other effects of alcohol, for which the regional metabolic signal may be hidden within the large decrements in metabolism that occur during alcohol intoxication. In a recent study in normal healthy individuals, two relatively low doses of alcohol (0.25 g/kg and 0.5 g/kg, or 5–10 mM in total body water) significantly decreased whole-brain glucose metabolism (10% and 23%, respectively) while not affecting cognitive performance (Volkow, Wang, Franceschi, et al., 2006). This contrasts with previous results showing that a 13% reduction in brain metabolism by lorazepam was associated with

significant cognitive impairment. This seemingly paradoxical finding where the same degree of metabolic decrease produces cognitive impairment for lorazepam and not for alcohol raises the possibility that the large brain metabolic decrements during alcohol intoxication could reflect a shift in the substrate for energy utilization. Infact there is new evidence that blood-borne acetate, which is markedly increased during intoxication, is a substrate for energy production by the brain (Waniewski and Martin, 1998). Imaging studies have also examined the relationship of gender and chronic alcohol toxicity, following up on the general belief that women are more vulnerable to alcohol’s toxic effects than men. However, whereas males with an alcohol addiction have consistently shown reductions in brain glucose metabolism relative to comparison subjects, a PET study with 18FDG in 10 recently detoxified females with an alcohol addiction reported no differences between individuals with an alcohol addiction and female controls (Wang et al., 1998). These results do not support a higher toxicity for the effects of alcohol in the female brain, as assessed with regional brain glucose metabolism. However, the authors point out that the severity of alcohol use in these females with an alcohol addiction was less than that of the males with an alcohol addiction previously investigated in PET studies. Another study comparing males and females with an alcohol addiction suggests that alcohol has a differential effect on GABA-BZR in men and women (Lingford-Hughes et al., 2000). Postmortem studies have also documented significant reductions in D2 receptors in the nucleus accumbens and amygdala in individuals with an alcohol addiction when compared with controls (Tupala et al., 2001; Tupala et al., 2003). Dopamine D2 receptor measurements as assessed with PET predominantly reflect postsynaptic receptors (Volkow et al., 1996), which are mostly located in GABA cells, suggesting involvement of these cells in the ventral striatum of individuals with an alcohol addiction. The DA D2 receptor is one of the DA receptor subtypes involved in transmitting DA’s reinforcing signals (Nowak et al., 2000). This has been documented in a variety of ways. For example, D2 receptor antagonist drugs decrease reinforcing responses to alcohol in rodents (Pfeffer and Samson, 1986) and in humans (Ahlenius et al., 1973). Also, studies have shown differences in D2 receptor levels between rat strains that differ in their preferences for alcohol (Stefanini et al., 1992; McBride et al., 1993), and D2 receptor knockout mice exhibit reduced reinforcing responses to alcohol (T.J. Phillips et al., 1998). Moreover, overexpression of D2 receptor in NAc markedly reduces alcohol intake (Thanos et al., 2001), even in selectively bred P rats who prefer alcohol (Thanos et al., 2004). A recent PET/[11C]raclopride study comparing DA D2 receptor levels in subregions of the striatum in indi-

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viduals with an alcohol addiction versus a control group provides evidence for reduced receptor levels throughout the different subregions of the human striatum (limbic [ventral], sensorimotor, and associative) (Martinez et al., 2005). This same study also reported a decrease in amphetamine-induced DA release in ventral striatum in individuals with an alcohol addiction compared to a control group further supporting decrements in brain DA activity in individuals with an alcohol addiction. These findings replicate previous studies documenting lower DA D2 receptors in ventral striatum in individuals with an alcohol addiction than in controls (Heinz et al., 2004; Martinez et al., 2005). For one of these studies, the low D2 receptors in ventral striatum were associated with alcohol craving (Heinz et al., 2004). A simultaneous assay by PET of pre- and postsynaptic markers of DA neurotransmission (with 6-[18F]fluoroDOPA as a marker of dopamine synthesis and [18F]des methoxyfallypride to map DA D2/D3 receptors) in the same individuals indicated that a striatal DA deficit correlated with alcohol craving, which was associated with a high relapse risk in a 6-month follow-up of these patients (Heinz, Siessmeier, et al., 2005). In humans, differences in D2 receptor availability in individuals with no alcohol addiction are associated with differences in sensitivity to the intoxicating effects of alcohol (Yoder et al., 2005). Thus, the low D2 receptor availability in ventral striatum in individuals with an alcohol addiction in conjunction with reduced DA release and synthesis could compound their vulnerability for alcohol abuse. We note that the literature contains inconsistencies with imaging and postmortem studies reporting on measures of baseline D2 receptors in striatum in individuals with an alcohol addiction, with some studies showing no changes (Guardia et al., 2000; Kuikka et al., 2000; Repo et al., 1999) whereas others (including our laboratory) reporting decreases (Hietala et al., 1994; Volkow et al., 1996; Volkow, Wang, Maynard, et al., 2002; Tupala et al., 2003; Heinz et al., 2004; Martinez et al., 2005). The discrepancy could reflect, among others, the fact that many of the earlier imaging studies, including our own, did not distinguish the dorsal from the ventral striatum and reported the averaged values of both regions. Alternatively, differences could reflect patient characteristics such as age of patients, chronicity of drinking, early- versus late-onset alcoholism, stage of withdrawal, ethnicity, gender, and comorbidity with smoking. An early SPECT study with [123I]β -CIT (a nonselective radiotracer that measures SERT concentration in the brain stem) reported a 30% decrease in availability of brain-stem SERTs in individuals with an alcohol addiction (Heinz et al., 1998). However, a recent PET study with [11C]DASB, a selective radiotracer for the SERT, showed no difference in transporter availability between

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individuals with an alcohol addiction (parsed into a group of aggressive and nonaggressive sybtypes) and a control group (Brown et al., 2007). A recent PET study highlighting the relationship between alcohol dependence and the endogenous opioid system used the mu-opioid receptor subtype selective radiotracer [11C]carfentanil to show a strong functional relationship between alcohol craving, mood, and muOR binding in specific brain regions (right dorsal lateral PFC, right anterior frontal cortex, and right parietal cortex) in men who were dependent upon alcohol (Bencherif et al., 2004). Similarly, another study with [11C]carfentanil in patients who were abstaining from alcohol reported an increase in mu-opiate receptors in the ventral striatum, including the nucleus accumbens, which correlated with the severity of alcohol craving (Heinz, Reimold, et al., 2005). These findings are consistent with the moderate effectiveness of mu-opiate receptor active drug naltrexone in reducing the risk of relapse among some individuals with an alcohol addiction (Soyka and Roesner, 2006). 18 FDG and other PET tracers have been used to probe the recovery of brain function and brain neurotransmitter activity in individuals with an alcohol addiction after alcohol withdrawal. Decrements in brain glucose metabolism were reported to partially recover in individuals with an alcohol addiction, particularly during the first 16–30 days after withdrawal (Volkow et al., 1994). Dopamine transporter levels, though reported in one study to be lower in individuals with an alcohol addiction than in controls, have been reported to recover to near-normal levels after abstinence as determined with SPECT and [123I]β -CIT (Laine et al., 1999). However a PET study reported normal DAT levels in individuals with an alcohol addiction (Volkow et al, 1996). The discrepancy may relate to the time interval between the study and the last use of alcohol because the DATs are subject to rapid up- and down-regulation in response to drug challenge (Zahniser and Doolen, 2001). Positron emission tomography with [11C]raclopride measuring DA D2 receptor levels in individuals with an alcohol addiction tested within 6 weeks of detoxification and then retested 1–4 months later while alcohol free showed the absence of significant recovery during alcohol detoxification (Volkow, Wang, Franceschi, et al., 2002). These findings suggest that low DA D2 receptor availability in individuals with an alcohol addiction is not due to alcohol withdrawal and may reflect a predisposing factor. In another PET study, [11 C]dihydrotetrabenazine, a radiotracer for the type 2 vesicular monoamine transporter (VMAT2) that has been reported to be insensitive to up- and down-regulation (Vander Borght et al., 1995), was reported to be reduced in males with a severe alcohol addiction (Gilman et al., 1998). This indicates that nigrostriatal monoaminergic terminals are reduced and suggests that the dam-

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aging effects of severe chronic alcoholism on the central nervous system are more extensive than previously considered. NICOTINE AND TOBACCO SMOKE The effects of nicotine and tobacco smoke on brain function, blood flow, and neurochemistry have been studied using a variety of imaging techniques (reviewed in Volkow et al., 2003; McClernon and Gilbert, 2004). The pharmacokinetics of nicotine itself have been measured using [11C]nicotine in humans revealing rapid uptake into the brain reaching peak uptake at 2–4 minutes after intravenous injection and clearing with a half-life between 22 minutes for thalamus and 36 minutes for temporal cortex (reviewed in Volkow, Fowler, et al., 1999). This is consistent with the rapid onset of its pharmacological effects in humans and the frequency of cigarette smoking. However, there is growing appreciation for the role of the nonnicotine chemical components of tobacco and the reinforcing sensory stimulation provided by smoking a cigarette that contribute to smoking behavior and addiction (Rose, 2006). Although [11C]nicotine provides valuable information on nicotine pharmacokinetics, its uptake is dominated by nonspecific binding. This has led to the development of radiotracers such as 2- and 6-[18F]fluoro A85380 and [125I]5-iodo A 85380 based on α4β2 agonist A 85380 that binds predominantly to the α4β2 nicotinic acetylcholine receptor subtype (Ding and Fowler, 2005; Horti and Villemagne, 2006) and to the initiation of measures of neuronal nicotinic receptor (nAChR) occupancy by smoking one or more cigarettes and nAChR levels in smokers who were recently abstinent. Smoking a full cigarette (or more) resulted in more than 88% receptor occupancy and was accompanied by a reduction in cigarette craving. Thus, daily smoking almost completely saturates the nAChR throughout the day, suggesting that smoking may alleviate withdrawal symptoms by maintaining nAChRs in the desensitized state (Brody et al., 2006). A SPECT study with [125I]5-iodo-A 85380 recently documented abnormally high levels of α4β2 in the brains of smokers during early abstinence (6.8 ± 1.9 days) (Staley et al., 2006), consistent with the observation of elevated α4β2 nAChR in smokers’ brains postmortem (Perry et al., 1999). Neuronal nicotinic receptor levels correlated with the days since last cigarette and the urge to smoke to relieve withdrawal symptoms may affect the ability of smokers to maintain abstinence. The hypothesis that some of the effects of smoking cigarettes in humans are mediated through nicotine activation of opioid, and DA neurotransmission has also been investigated using the radiotracers [11C]carfentanil and [11C]raclopride, which label mu-opioid and DA D2 receptors, respectively (D.J. Scott et al., 2007) under conditions where the radiotracer was injected and individ-

uals smoked two denicotinized cigarettes followed by two nicotinized cigarettes. Smokers had significantly lower baseline mu-opioid receptor levels than nonsmokers during the denicotinized cigarette part of the study. Parametric maps corresponding to low and high nicotine smoking periods showed that smoking an average cigarette was associated with the activation of DA D2 and mu-opioid release as evidenced by the reductions of DA D2 and mu-opioid receptor availability from the denicotinized to the nicotinized conditions. There were no differences in DA D2 receptor levels between nonsmokers and smokers that is similar to a recent PET study with [123I]-IBZM (Yang et al., 2006). The ability of cigarette smoking to cause DA release was also documented in another study with [11C]raclopride that showed that the magnitude of the release was comparable to that found in studies that used similar methods to examine the effects of other addictive drugs (Brody et al., 2004). Positron emission tomography studies were the first to document low brain monoamine oxidase A and B (MAO-A and -B) in smokers relative to nonsmokers and former smokers (Fig. 49.1) (reviewed in Fowler et al., 2005). The average reductions in MAO-A and -B are 30% and 40%, respectively. Positron emission tomography studies confirmed early reports that nicotine does not inhibit MAO, that smoking a single cigarette does not produce a measurable change in brain MAOB in nonsmokers, and that an overnight cigarette abstinence for smokers does not produce a measurable recovery of brain MAO activity (Fowler et al., 2005, and references therein). Low brain MAO in smokers may be one of the mechanisms by which smoking contributes to some of the behavioral and epidemiological features of smoking, including the decreased risk of Parkinson’s disease in smokers (W.K. Scott et al., 2005) and an increased rate of smoking in patients with psychiatric and substance use disorders (Kalman et al., 2005). Reduced brain MAO activity would be predicted to spare biogenic amines such as DA, serotonin, and NE and to reduce the production of hydrogen peroxide, a by-product from MAO-catalyzed oxidation and a potential source of free radicals. Both of these effects would be predicted to have therapeutic benefit in neurological and psychiatric disorders. Thus, there is biochemical rationale for the neuroprotective effect of tobacco smoke and for the selfmedication hypothesis. Recently, L-deprenyl showed efficacy in smoking cessation (George et al., 2003). In addition, a nonselective MAO inhibitor, 2,3,6-trimethylbenzoquinone, has been isolated from flue-cured tobacco leaves (Khalil et al., 2000) and shown to possess neuroprotective properties (Castagnoli et al., 2003). Positron emission tomography studies of brain function, as measured with 18FDG, documented reversible changes in brain metabolism during different stages of nicotine dependence (overnight abstinence vs. 2-week exposure to denicotinized cigarettes + nicotine patches vs. 2 weeks after returning to the regular cigarette) and

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highlight the likely role of thalamic gating and striatal reward and corticolimbic regulatory pathways in maintaining cigarette addiction (Rose et al., 2007). Similarly, recent measures of the effects of smoking on cerebral blood flow with O-15 water revealed that smoking affects regional cerebral blood flow (rCBF) not only in areas of the brain rich in nicotinic cholinergic receptors but also in areas implicated in the rewarding effects of drugs of abuse (Zubieta et al., 2005). In this same study, the craving for a cigarette in chronic smokers has been correlated with elevation in regional metabolism in the right hippocampus, an area involved in associating environmental cues with drugs, and in the left dorsal anterior cingulate, which has been implicated in drug craving and relapse to drug-seeking behavior, similar to an earlier study with FDG (Brody et al., 2002). These regional brain activations and associations with craving are similar to findings with other addictive substances. An interesting study recently reported that the administration of patch nicotine decreased gender differences in brain metabolism between men and women performing a continuous performance task or a competition and retaliation task (Fallon et al., 2005). OPIATES Mu, delta, and kappa opioid receptors are the physiological targets of endogenous and exogenous opioids. There are a number of PET radiotracers for imaging and quantifying these receptors (Lever, 2007). [11C]carfentanil that is selective for the mu subtype is the most widely used, specifically in studies of the opioid receptors. Others such as [11C]diprenorphine (nonselective) and [18F]cyclofoxy (nonselective) are also available for studies of receptor availability, and other subtype selective opioid receptor radiotracers are under development (Lever, 2007). We also note that a large fraction of the PET research on opioid receptors is related to studies of the neurobiology of pain (Sprenger et al., 2005). Although neuroimaging has not been applied to studies of abuse of prescription pain medications per se, we note that abuse of pain medications, most notably the opiates, is one of the most rapidly growing areas of drug abuse. Over the past several years, PET has been used to study opiate abuse in current heroin abusers, in individuals treated with opiate agonists such as methadone, and in those undergoing opiate withdrawal. Parameters measured include brain metabolism in abusers of opiates, neuroanatomical correlates of craving, opiate receptor occupancy with treatment drugs and during withdrawal, and DA receptor levels. Briefly, these studies showed that, similar to other addictions, abusers of opiates have lower DA D2 receptors relative to a control group; that individuals addicted to opiates have a blunted response to prototypical human rewards; and

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that craving is associated with activations of blood flow in the prefrontal cortical regions (reviewed in Volkow et al., 2003). Methadone substitution is one of the main ways to treat opiate addiction, and it has been shown that its use improves health and social outcome. However, little is known about methadone pharmacology, including the degree to which it occupies opioid receptors at the doses required to suppress withdrawal symptoms. A recent study examined the relationship between methadone dose and occupation of brain opioid receptors using [11C]diprenorphine and PET, comparing a group of eight individuals who were dependent on opioids and stable on their substitute methadone (18–90 mg daily) and eight healthy controls (Melichar et al., 2005). Surprisingly, no difference in [11C]diprenorphine binding was found between the groups, and there was no relationship between methadone dose and receptor occupancy. Methadone also did not block [11C]diprenorphine binding in rats. This report contrasts to an earlier study with [18F]cyclofoxy showing that methadone administration modestly but significantly (19%–32%) reduces the uptake of [18F]cyclofoxy (Kling et al., 2000). Potential reasons for this discrepancy were discussed (Melichar et al., 2005) and include differences in radiotracer characteristics, possible receptor internalization, and up-regulation of opioid receptors after chronic dosing. The authors suggested that the lack of a measurable occupancy of opioid receptor by methadone is evidence that efficacy occurs at very low levels of opioid receptor occupancy. Buprenorphine is a relatively new and effective treatment of opioid dependence. Following earlier studies showing occupancy of mu-opioid receptors by buprenorphine (Zubieta et al., 2000), a recent PET study with [11C]carfentanil examined the duration of receptor occupancy by buprenorphine, measuring occupancy at different times after buprenorphine administration. Plasma buprenorphine concentration, withdrawal symptoms, and blockade of the effects of hydromorphone were also recorded. Relative to placebo, mu-opioid receptor occupancy was 30%, 54%, 67%, and 82% at 4, 28, 52, and 76 hours, respectively, after buprenorphine. Moreover mu-opioid receptor availability correlated with plasma buprenorphine levels, withdrawal symptoms, and hydromorphone blockade. Together with a previous study (Greenwald et al., 2003), this study showed that mu-opiate receptor occupancy by buprenorphine is long lasting, that receptor availability as measured with PET predicts changes in pharmacokinetic and pharmacodynamic measures and that buprenorphine (unlike methadone) occupies about 50%–60% or the mu-opioid receptors at doses required to suppress withdrawal symptoms. Nalmefene is a long-acting opioid antagonist that is used in the treatment of alcoholism and other disorders (Mason et al., 1999). Similar to the study with buprenorphine, [11C]carfentanil was used to determine

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the relationship between nalmefene plasma concentration and central mu-opioid receptor occupancy. Central mu-opioid receptor occupancy was measured at four time points (3, 26, 50, 74 hours) after a clinically effective dose (20 mg, orally) either as a single dose or after repeated dosing over 7 days (Ingman et al., 2005). Both nalmefene dosings resulted in a very high occupancy at mu-opioid receptors (87%–100%), and the decline in the brain receptor occupancy was similar after both dosings but clearly slower than the decline in the plasma concentration of nalmefene or metabolites. High nalmefene occupancy (83%–100%) persisted at 26 hours after the dosings, consistent with slow dissociation of the drug from mu-opioid receptors. This study supports the rationale of administering nalmefene when needed and suggests that once-daily dosing is sufficient to achieve a high mu-opioid receptor occupancy. MARIJUANA Marijuana is the most widely used illegal substance in the United States, and thus the nature of its effects on the brain is of major importance. However, there are surprisingly few studies applying neuroimaging methods to the effects of marijuana abuse on the human brain (for reviews, see Lindsey et al., 2003; Volkow et al., 2003; Quickfall and Crockford, 2006). The main psychoactive substance of marijuana is delta9-tetrahydrocannibinol (THC), which has been postulated to exert its psychoactive effects through interactions with cannabinoid receptors that are highly localized in the cerebellum and hippocampus (Herkenham et al., 1990). A SPECT ligand for the cannabinoid receptor (Gatley et al., 1998) has recently been labeled with 124I for PET studies in a patient with schizophrenia, though the long half-life of 124I (4.17 days) is limiting because of radiation exposure (Berding et al., 2006). A number of PET radiotracers have been synthesized and evaluated and though most have not demonstrated sufficient brain uptake and specificity for translation to humans, [18F]MK9470, a selective high-affinity inverse agonist, has recently been evaluated and shows promise in human studies (Burns et al., 2007). There is a clear need to make advances in this area not only because of the intrinsic importance of this abundant receptor in the brain that is the target of the most widely abused drug but also because the central cannabinoid receptor is an important target for drug research and development, including drugs to treat obesity. Marijuana smoking increases brain blood flow in a number of paralimbic brain regions (for example, orbital frontal lobes, insula, temporal poles) and in anterior cingulate and cerebellum. In contrast, rCBF decreased in temporal regions that are sensitive to auditory attention effects. This is consistent with speculation that

the intoxicating and mood-related effects of marijuana may be mediated by brain regions showing increases in rCBF, whereas impaired cognitive function during intoxication may be associated with brain regions showing decreases in rCBF (O’Leary et al., 2000). Studies on the effects of marijuana intoxication on regional brain glucose metabolism reported differences in the patterns of response between abusers and nonabusers. Whereas marijuana increased cerebellar metabolism in all patients, it increased metabolism in anterior cingulate gyrus and in OFC only in the abusers but not in the controls (reviewed in Volkow et al., 2003). Frequent marijuana users at baseline show substantially lower brain blood flow (as measured with O-15 water) than controls in a large region of posterior cerebellum (which is linked to an internal timing system), indicating altered brain function may underlie alterations of time sense, which is common following marijuana smoking (Block et al., 2000). Expanding on this, the effects of marijuana on brain perfusion and internal timing were assessed in occasional and chronic marijuana users who performed a paced counting task during the PET study (Ponto et al., 2004). The study showed that smoking marijuana increased rCBF in the ventral forebrain and cerebellar cortex and appears to accelerate a cerebellar clock altering self-paced behaviors. Recent PET studies also show that smokers who were abstinent with marijuana (25 days) have persistent deficits in blood flow in prefrontal brain regions that are the regions responsible for executive cognitive functioning even though they do not differ from controls in the performance of a modified version of the Stroop task (Eldreth et al., 2004). The authors speculated that users of marijuana recruit an alternative neural network as a compensatory mechanism during performance of this task and that prefrontal deficits may be a common denominator in the evolution of maladaptive behaviors such as substance abuse and other neuropsychiatric disorders. Consistent with this is a recent study in which measurement of brain blood flow in heavy users of marijuana during performance of a gambling task revealed greater activation in the left cerebellum and less activation in the right lateral OFC and the right dorsolateral PFC (DLPFC) and impaired decision making compared to the control group (Bolla et al., 2005). Specifically, the heavy users of marijuana may focus on only the immediate reinforcing aspects of a situation (that is, getting high) while ignoring the negative consequences. Poor decision making could make an individual more prone to addictive behavior and more resistant to treatment. VULNERABILITY The question of why some people who experiment with drugs become addicted whereas others do not is im-

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portant in the context of understanding mechanisms underlying addictive behavior. The finding of low DA D2 receptors in individuals who are addicted raise important mechanistic questions: (1) In the absence of drug addiction, does an individual’s baseline level of DA D2 receptors influence the behavioral response to a stimulant drug? (2) Does short-term exposure to a stimulant drug change DA D2 receptor levels and, if so, do these changes persist after protracted withdrawal? (3) Can environmental changes affect DA D2 receptor levels? and (4) Are high DA D2 receptors protective in individuals at risk? These questions have been addressed through imaging studies in normal individuals who were not abusing drugs in whom the confounds of neurobiological changes due to prolonged drug exposure are eliminated and in laboratory animals. Although individuals addicted to cocaine, METH, heroin, or alcohol as a group have significant decrements in DA D2 receptors, there is considerable overlap in receptor values with those from individuals who are not addicted (reviewed in Volkow et al., 2003). This large variability among individuals formed the basis for a study that showed that healthy individuals who did not abuse drugs with low DA D2 receptors found an intravenous dose of the stimulant drug methylphendiate pleasant, but those with high DA D2 receptor levels found it aversive (Volkow et al., 1999). This supports the notion that individuals with low DA receptors may have an understimulated reward system and, as a result, they perceive a pleasurable sensation when subjected to a drug-induced elevation in DA. It follows that an individual who takes a drug and finds it pleasant is more likely to repeat the behavior. This finding was recently reinforced in a preclinical PET study with [11C]raclopride that demonstrated that nucleus accumbens D2/D3 receptor availability predicts trait impulsivity and cocaine reinforcement in rats (Dalley et al., 2007). Reduced DA D2 receptors in abusers of cocaine raise an important question as to the extent to which these reductions preceded the use of cocaine. Although it is not possible to obtain this information in humans, studies in monkeys have addressed this question by imaging DA D2 receptors at baseline and through a 1-year course of cocaine administration followed by a 1-year abstinence period, tracking receptor levels throughout with PET (Nader et al., 2006). This study showed that D2 receptor availability decreased by 15%–20% within 1 week of initiating self-administration and remained reduced by approximately 20% during 1 year of exposure. Decreases persisted for up to 1 year of abstinence in some monkeys. Monkeys with higher baseline DA D2 receptor levels self-administered less cocaine, providing evidence for a predisposition to self-administer cocaine based on D2 receptor availability, and demonstrated a rapid decrease in DA D2 receptor level following cocaine. This supports the notion that biological

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vulnerability (that is, low DA D2 receptors at the outset) as well as cocaine-induced vulnerability (cocaineinduced reductions in DA D2 receptors) could predispose an individual to cocaine administration. Highlighting the impact of environmental factors on DA D2 receptor availability, this same group assessed the effect of changing the social environment of monkeys on DA D2 receptor availability and on cocaine self-administration using PET (Morgan et al., 2002). Individually housed monkeys had a baseline PET scan to assess DA D2 receptor levels and were given access to cocaine. Whereas DA D2 receptor level did not differ among individually housed animals, social housing increased the DA D2 receptors in the dominant, but not the subordinate, monkeys. In parallel, cocaine use decreased in the dominant animals and increased in the subordinate animals. This study, which occurred over a 3-month time frame, puts forth the notion that DA D2 receptor level can change within the time frame of normal social activities (Nader and Czoty, 2005). In animals, repeated exposure to stimulant drugs leads to an enhanced drug-induced psychomotor response and increased DA release that has been postulated to confer vulnerability to drug addiction or drug-induced psychosis in humans. A recent PET study with [11C]raclopride determined whether brief exposure to amphetamine (three oral doses—0.3 mg/kg—on days 1, 3, and 5) in normal healthy individuals in a laboratory setting would alter DA release, producing behavioral and neurochemical sensitization (Boileau et al., 2006). Dopamine release in response to amphetamine was measured on the first exposure (day 1) and at 14 days and 1 year after the third exposure with [11C]raclopride binding. Consistent with a sensitization-like phenomenon, 14 and 365 days after the third dose of amphetamine, there was a greater psychomotor response and increased DA release relative to the initial dose. Moreover, high novelty-seeking and impulsivity personality traits predicted proneness to sensitization. This study with only limited amphetamine exposure demonstrated that sensitization to stimulants achieved in healthy men in the laboratory, that it is associated with enhanced DA release, and that the phenomenon persists for at least 1 year. Predisposition to alcoholism is likely an interaction between genetic and environmental factors that confer vulnerability and protection. Individuals with an alcohol addiction have low levels of DA D2 receptors in striatum, and increasing D2 receptor levels in laboratory animals reduces alcohol consumption (Thanos et al., 2001). A recent study with [11C]raclopride to measure dopamine D2 receptors and 18FDG to measure brain glucose metabolism compared individuals without an alcohol addiction with a positive family history of alcoholism with individuals without an alcohol addiction with a negative family history (Volkow, Wang, Begleiter, et al., 2006). Dopamine D2 receptor levels were signifi-

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cantly higher for the family positive group. In addition, significant associations between D2 receptors and metabolism in frontal regions involved with emotional reactivity and executive control suggest that high levels of D2 receptors could protect against alcoholism by regulating circuits involved in inhibiting behavioral responses and in controlling emotions. On the other hand, a PET study that measured changes in DA in striatum induced by amphetamine found no differences as a function of family history of alcoholism (Munro et al., 2006). OUTLOOK In spite of the increasing reliance of the biomedical sciences, including substance abuse research, on molecular imaging, the development of new radiotracers remains a slow and even rate-limiting process. For example, we still need good radiotracers for many neurotransmitters and neurotransmitter subtypes (including the cannabinoid receptor, the opioid receptor subtypes [kappa and delta], the glutamate and GABA systems, and others, including cellular signaling processes). However, even the familiar radiopharmaceuticals that are the backbone of imaging sciences are the product of enormous effort and even serendipity. Yet the value of radiopharmaceuticals in almost every area of clinical research is of such enormous importance that it justifies a more focused effort in identifying the impediments and in setting scientific and medical priorities. There are a number of urgent requirements to be able to develop radiotracers that can visualize and quantify a single biochemical process in the human body where all of the chemical reactions of life are occurring. These include research in chemistry, training of chemists, advances in molecular design, and the targeting and streamlining of translation of new developments to humans. In addition, as nuclear imaging is combined with other modalities and with measures of genetics and behavior, the need for advanced postprocessing, and quantification and statistical analysis of large datasets, becomes imperative in order to extract meaningful relationships between brain chemistry and behavior.

ACKNOWLEDGMENT This work was performed in part at Brookhaven National Laboratory under contract DE-AC02-98CH10886 with the U.S. Department of Energy and was supported by its Office of Biological and Environmental Research and by the National Institutes of Health.

REFERENCES Abi-Dargham, A., Krystal, J.H., Anjilvel, S., Scanley, B.E., Zoghbi, S., Baldwin, R.M., Rajeevan, N., Ellis, S., Petrakis, I.L., Seibyl, J.P., Charney, D.S., Laruelle, M., and Innis, R.B. (1998) Altera-

tions of benzodiazepine receptors in type II alcoholic subjects measured with SPECT and [123I]iomazenil. Am. J. Psychiatry 155(11):1550–1555. Ahlenius, S., Carlsson, A., Engel, J., Svensson, T., and Sodersten, P. (1973) Antagonism by alpha methyltyrosine of the ethanolinduced stimulation and euphoria in man. Clin. Pharmacol. Ther. 14:586–591. Balster, R.L., and Schuster, C.R. (1973) Fixed-interval schedule of cocaine reinforcement: effect of dose and infusion duration. J. Exp. Anal. Behav. 20(1):119–129. Barr, A.M., Panenka, W.J., MacEwan, G.W., Thornton, A.E., Lang, D.J., Honer, W.G., and Lecomte, T. (2006) The need for speed: an update on MAMP addiction. J. Psychiatry Neurosci. 31: 301– 313. Bencherif, B., Wand, G.S., McCaul, M.E., Kim, Y.K., Ilgin, N., Dannals, R.F., and Frost, J.J. (2004) Mu-opioid receptor binding measured by [11C]carfentanil positron emission tomography is related to craving and mood in alcohol dependence. Biol. Psychiatry 55(3): 255–262. Berding, G., Schneider, U., Gielow, P., Buchert, R., Donnerstag, F., Brandau, W., Knapp, W.H., Emrich, H.M., and Müller-Vahl, K. (2006) Feasibility of central cannabinoid CB1 receptor imaging with [124I]AM281 PET demonstrated in a schizophrenic patient. Psychiatry Res. 147(2/3):249–256. Block, R.I., O’Leary, D.S., Hichwa, R.D., Augustinack, J.C., Ponto, L.L., Ghoneim, M.M., Arndt, S., Ehrhardt, J.C., Hurtig, R.R., Watkins, G.L., Hall, J.A., Nathan, P.E., and Andreasen, N.C. (2000) Cerebellar hypoactivity in frequent marijuana users. Neuroreport 11:749–753. Boileau, I., Dagher, A., Leyton, M., Gunn, R.N., Baker, G.B., Diksic, M., and Benkelfat, C. (2006) Modeling sensitization to stimulants in humans: an [11C]raclopride/positron emission tomography study in healthy men. Arch. Gen. Psychiatry 63(12):1386– 1395. Bolla, K.I., Eldreth, D.A., Matochik, J.A., and Cadet, J.L. (2005) Neural substrates of faulty decision-making in abstinent marijuana users. NeuroImage 26(2):480–492. Brody, A.L., Mandelkern, M.A., London, E.D., Childress, A.R., Lee, G.S., Bota, R.G., Ho, M.L., Saxena, S., Baxter, L.R., Jr., Madsen, D., and Jarvik, M.E. (2002) Brain metabolic changes during cigarette craving. Arch. Gen. Psychiatry 59(12):1162–1172. Brody, A.L., Mandelkern, M.A., London, E.D., Olmstead, R.E., Farahi, J., Scheibal, D., Jou, J., Allen, V., Tiongson, E., Chefer, S.I., Koren, A.O., and Mukhin, A.G. (2006) Cigarette smoking saturates brain alpha 4 beta 2 nicotinic acetylcholine receptors. Arch. Gen. Psychiatry 63(8):907–915. Brody, A.L., Olmstead, R.E., London, E.D., Farahi, J., Meyer, J.H., Grossman, P., Lee, G.S., Huang, J., Hahn, E.L., and Mandelkern, M.A. (2004) Smoking-induced ventral striatum dopamine release. Am. J. Psychiatry 161(7):1211–1218. Brown, A.K., George, D.T., Fujita, M., Liow, J.S., Ichise, M., Hibbeln, J., Ghose, S., Sangare, J., Hommer, D., and Innis, R.B. (2007) PET [11C]DASB imaging of serotonin transporters in patients with alcoholism. Alcohol Clin. Exp. Res. 31(1):28–32. Buchert, R., Thiele, F., Thomasius, R., Wilke, F., Petersen, K., Brenner, W., Mester, J., Spies, L., and Clausen, M. (2006) Ecstasy-induced reduction of the availability of the brain serotonin transporter as revealed by [11C](+)McN5652-PET and the multi-linear reference tissue model: loss of transporters or artifact of tracer kinetic modelling? J. Psychopharmacol. November 8 [Epub ahead of print]. Buchert, R., Thomasius, R., Wilke, F., Petersen, K., Nebeling, B., Obrocki, J., Schulze, O., Schmidt, U., and Clausen, M. (2004) A voxel-based PET investigation of the long-term effects of “Ecstasy” consumption on brain serotonin transporters. Am. J. Psychiatry 161(7):1181–1189.

49: PET AND SPECT IMAGING IN SUBSTANCE ABUSE RESEARCH Burns, H.D., Van Laere, K., Sanabria-Bohórquez, S., Hamill, T.G., Bormans, G., Eng, W.S., Gibson, R., Ryan, C., Connolly, B., Patel, S., Krause, S., Vanko, A., Van Hecken, A., Dupont, P., De Lepeleire, I., Rothenberg, P., Stoch, S.A., Cote, J., Hagmann, W.K., Jewell, J.P., Lin, L.S., Liu, P., Goulet, M.T., Gottesdiener, K., Wagner, J.A., de Hoon, J., Mortelmans, L., Fong, T.M.,and Hargreaves, R.J. (2007) [18F]MK-9470, a positron emission tomography (PET) tracer for in vivo human PET brain imaging of the cannabinoid1 receptor. Proc. Natl. Acad. Sci. USA 104(23):9800–9805. Castagnoli, K., Petzer, J.B., Steyn, S.J., van der Schyf, C.J., and Castagnoli, N., Jr. (2003) Inhibition of human MAO-A and MAO-B by a compound isolated from flue-cured tobacco leaves and its neuroprotective properties in the MPTP mouse model of neurodegeneration. Inflammopharmacology 11(2):183–188. Chang, L., and Haning, W. (2006) Insights from recent positron emission tomographic studies of drug abuse and dependence. Curr. Opin. Psychiatry 19(3):246–252. Childress, A.R., Mozley, P.D., McElgin, W., Fitzgerald, J., Reivich, M., and O’Brien, C.P. (1999) Limbic activation during cueinduced cocaine craving. Am. J. Psychiatry 156(1):11–18. Cowan, R.L. (2007) Neuroimaging research in human MDMA users: a review. Psychopharmacology (Berl) 189(4):539–556. Dalley, J.W., Fryer, T.D., Brichard, L., Robinson, E.S., Theobald, D.E., Laane, K., Pena, Y., Murphy, E.R., Shah, Y., Probst, K., Abakumova, I., Aigbirhio, F.I., Richards, H.K., Hong, Y., Baron, J.C., Everitt, B.J., and Robbins, T.W. (2007) Nucleus accumbens D2/3 receptors predict trait impulsivity and cocaine reinforcement. Science 315(5816):1267–1270. Ding, Y.S., and Fowler, J.S. (2005) New-generation radiotracers for nAChR and NET. Nucl. Med. Biol. 32(7):707–718. Eldreth, D.A., Matochik, J.A., Cadet, J.L., and Bolla, K.I. (2004) Abnormal brain activity in prefrontal brain regions in abstinent marijuana users. NeuroImage 23(3):914–920. Fallon, J.H., Keator, D.B., Mbogori, J., Taylor, D., and Potkin, S.G. (2005) Gender: a major determinant of brain response to nicotine. Int. J. Neuropsychopharmacol. 8(1):17–26. Fowler, J.S., Ding, Y.S., and Volkow, N.D. (2003) Radiotracers for positron emission tomography imaging. Semin. Nucl. Med. 33(1): 14–27. Fowler, J.S., and Ido, T. (2002) Initial and subsequent approach for the synthesis of 18FDG. Semin. Nucl. Med. 32(1):6–12. Fowler, J.S., Logan, J., Volkow, N.D., and Wang, G.J. (2005) Translational neuroimaging: positron emission tomography studies of monoamine oxidase. Mol. Imaging Biol. 7(6):377–387. Fowler, J.S., and Volkow, N.D. (2004) Neuroimaging in substance abuse research. In: Charney, D.S., and Nestler, E.J., eds. Neurobiology of Mental Illness, 2nd ed. New York: Oxford University Press, pp. 740–752. Fowler, J.S., Volkow, N.D., Wang, G.J., Ding, Y.S., and Dewey, S.L. (1999) PET and drug research and development. J. Nucl. Med. 40(7): 1154–1163. Gatley, S.J., Lan, R., Volkow, N.D., King, P., Wong, C.T., Gifford, A.N., Pyatt, B., and Makriyannis, A. (1998) Imaging the brain marijuana receptor: development of a radioligand that binds to cannabinoid CB1 receptors in vivo. J. Neurochem. 70:417–423. Gatley, S.J., Volkow, N.D., Wang, G.J., Fowler, J.S., Logan, J., Ding, Y.S., and Gerasimov, M. (2005) PET imaging in clinical drug abuse research. Curr. Pharm. Des. 11(25):3203–3219. George, T.P., Vessichio, J.C., and Termine, A. (2003) A preliminary, placebo controlled trial of selegiline hydrochloride for smoking cessation. Biol. Psychiatry 53:136–143. Gilman, S., Koeppe, R.A., Adams, K., Johnson-Greene, D., Junck, L., Kluin, K.J., Brunberg, J.B., Martorello, S., and Lohman, M. (1996) Positron emission tomographic studies of cerebral benzodiazepine-receptor binding in chronic alcoholics. Ann. Neurol. 40:163–171.

841

Gilman, S., Koeppe, R.A., Adams, K.M., Junck, L., Kluin, K.J., Johnson-Greene, D., Martorello, S., Heumann, M., and Bandekar, R. (1998) Decreased striatal monoaminergic terminals in severe chronic alcoholism demonstrated with (+)[11C]dihydrotetrabenaz ine and positron emission tomography. Ann. Neurol. 44(3): 326–333. Gorelick, D.A., Kim, Y.K., Bencherif, B., Boyd, S.J., Nelson, R., Copersino, M., Endres, C.J., Dannals, R.F., and Frost, J.J. (2005) Imaging brain mu-opioid receptors in abstinent cocaine users: time course and relation to cocaine craving. Biol. Psychiatry 57(12): 1573–1582. Grant, S., London, E.D., Newlin, D.B., Villemagne, V.L., Liu, X., Contoreggi, C., Phillips, R.L., Kimes, A.S., and Margolin, A. (1996) Activation of memory circuits during cue-elicited cocaine craving. Proc. Natl. Acad. Sci. USA 93(21):12040–12045. Greenwald, M.K., Johanson, C.E., Moody, D.E., Woods, J.H., Kilbourn, M.R., Koeppe, R.A., Schuster, C.R., and Zubieta, J.-K. (2003) Effects of buprenorphine maintenance dose on mu-opioid receptor availability, plasma concentrations, and antagonist blockade in heroin-dependent volunteers. Neuropsychopharmacology 28:2000–2009. Guardia, J. Catafau, A.M., Batlle, F., Martin, J.C., Segura, L. Gonzalvo, B., Prat, G., Carrio, I., and Casas, M. (2000) Striatal dopaminergic D(2) receptor density measured by [(123)I]iodobenzamide SPECT in the prediction of treatment outcome of alcohol-dependent patients. Am. J. Psychiatry 157:127–129. Heinz, A., Ragan, P., Jones, D.W., Hommer, D., Williams, W., Knable, M.B., Gorey, J.G., Doty, L., Geyer, C., Lee, K.S., Coppola, R., Weinberger, D.R., and Linnoila, M. (1998) Reduced central serotonin transporters in alcoholism. Am. J. Psychiatry 155:1544– 1549. Heinz, A., Reimold, M., Wrase, J., Hermann, D., Croissant, B., Mundle, G., Dohmen, B.M., Braus, D.F., Schumann, G., Machulla, H.J., Bares, R., and Mann, K. (2005) Correlation of stable elevations in striatal mu-opioid receptor availability in detoxified alcoholic patients with alcohol craving: a positron emission tomography study using carbon 11-labeled carfentanil. Arch. Gen. Psychiatry 62(1):57–64. Heinz, A., Siessmeier, T., Wrase, J., Buchholz, H.G., Grunder, G., Kumakura, Y., Cumming, P., Schreckenberger, M., Smolka, M. N., Rosch, F., Mann, K., and Bartenstein, P. (2005) Correlation of alcohol craving with striatal dopamine synthesis capacity and D2/3 receptor availability: a combined [18F]DOPA and [18F]DMFP PET study in detoxified alcoholic patients. Am. J. Psychiatry 162(8): 1515–1520. Heinz, A., Siessmeier, T., Wrase, J., Hermann, D., Klein, S., Grusser, S.M., Flor, H., Braus, D.F., Buchholz, H.G., Grunder, G., Schreckenberger, M., Smolka, M.N., Rosch, F., Mann, K., and Bartenstein, P. (2004) Correlation between dopamine D(2) receptors in the ventral striatum and central processing of alcohol cues and craving. Am. J. Psychiatry 161:1783–1789. Herkenham, M., Lynn, A.B., Little, M.D., Johnson, M.R., Melvin, L.S., de Costa, B.R., and Rice, K.C. (1990) Cannabinoid receptor localization in brain. Proc. Natl. Acad. Sci. USA 87:1932–1936. Hietala, J., West, C., Syvalahti, E., Nagren, K., Lehikoinen, P., Sonninen, P., and Ruotsalainen, U. (1994) Striatal D2 dopamine receptor binding characteristics in vivo in patients with alcohol dependence. Psychopharmacology (Berl) 116:285–290. Horti, A.G., and Villemagne, V.L. (2006) The quest for Eldorado: development of radioligands for in vivo imaging of nicotinic acetylcholine receptors in human brain. Curr. Pharm. Des. 12(30): 3877–3900. Huether, G., Zhou, D., and Rüther, E. (1997) Causes and consequences of the loss of serotonergic presynapses elicited by the consumption of 3,4-methylenedioxy methamphetamine (MDMA, “ecstasy”) and its congeners. J. Neural Transm. 104:771–794.

842

SUBSTANCE ABUSE DISORDERS

Ingman, K., Hagelberg, N., Aalto, S., Nagren, K., Juhakoski, A., Karhuvaara, S., Kallio, A., Oikonen, V., Hietala, J., and Scheinin, H. (2005) Prolonged central mu-opioid receptor occupancy after single and repeated nalmefene dosing. Neuropsychopharmacology 30(12):2245–2253. Jacobsen, L.K., Staley, J.K., Malison, R.T., Zoghbi, S.S., Seibyl, J.P., Kosten, T.R., and Innis, R.B. (2000) Elevated central serotonin transporter binding availability in acutely abstinent cocainedependent patients. Am. J. Psychiatry 157:1134–1140. Kalman, D., Morissette, S.B., and George, T.P. (2005) Co-morbidity of smoking in patients with psychiatric and substance use disorders. Am. J. Addict. 14(2):106–123. Khalil, A.A., Steyn, S., and Castagnoli, N. (2000) Isolation and characterization of monoamine oxidase inhibitor from tobacco leaves. Chem. Res. Toxicology 13:31–35. Kim, S.J., Lyoo, I.K., Hwang, J., Sung, Y.H., Lee, H.Y., Lee, D.S., Jeong, D.U., and Renshaw, P.F. (2005) Frontal glucose hypometabolism in abstinent methamphetamine users. Neuropsychopharmacology 30(7):1383–1391. Kling, M.A., Carson, R.E., Borg, L., Zametkin, A., Matochik, J.A., Schluger, J., Herscovitch, P., Rice, K.C., Ho, A., Eckelman, W.C., and Kreek, M.J. (2000) Opioid receptor imaging with positron emission tomography and [(18)F]cyclofoxy in long-term, methadonetreated former heroin addicts. J. Pharmacol. Exp. Ther. 295(3): 1070–1076. Koob, G.F., Roberts, A.J., Schulteis, G., Parsons, L.H., Heyser, C.J., Hyytia, P., Merlo-Pich, E., and Weiss, F. (1998) Neurocircuitry targets in ethanol reward and dependence. Alcohol Clin. Exp. Res. 22(1):3–9. Kuikka, J.T.Y., Repo, E., Bergstrom, K.A., Tupala, E., and Tiihonen, J. (2000) Specific binding and laterality of human extrastriatal dopamine D2/D3 receptors in late onset type 1 alcoholic patients. Neurosci. Lett. 292:57–59. Kung, H.F., Kung, M.P., and Choi, S.R. (2003) Radiopharmaceuticals for single-photon emission computed tomography brain imaging. Semin. Nucl. Med. 33(1):2–13. Laine, T.P., Ahonen, A., Torniainen, P., Heikkila, J., Pyhtinen, J., Rasanen, P., Niemela, O., and Hillbom, M. (1999) Dopamine transporters increase in human brain after alcohol withdrawal. Mol. Psychiatry 4(2):104–105, 189–191. Lecchi, M., Ottobrini, L., Martelli, C., Del Sole, A., and Lucignani, G. (2007) Instrumentation and probes for molecular and cellular imaging. Q. J. Nucl. Med. Mol. Imaging 51(2):111–126. Lever, J.R. (2007) PET and SPECT imaging of the opioid system: receptors, radioligands and avenues for drug discovery and development. Curr. Pharm. Des. 13(1):33–49. Lindsey, K.P., Gatley, S.J., and Volkow, N.D. (2003) Neuroimaging in drug abuse. Curr. Psychiatry Rep. 5(5):355–361. Lingford-Hughes, A. (2005) Human brain imaging and substance abuse. Curr. Opin. Pharmacol. 5(1):42–46. Lingford-Hughes, A.R., Acton, P.D., Gacinovic, S., Boddington, S.J., Costa, D.C., Pilowsky, L.S., Ell, P.J., Marshall, E.J., and Kerwin, R.W. (2000) Levels of gamma-aminobutyric acid-benzodiazepine receptors in abstinent, alcohol-dependent women: preliminary findings from an 123I-iomazenil single photon emission tomography study. Alcohol Clin. Exp. Res. 24(9):1449–1455. Lingford-Hughes, A.R., Wilson, S.J., Cunningham, V.J., Feeney, A., Stevenson, B., Brooks, D.J., and Nutt, D.J. (2005) GABAbenzodiazepine receptor function in alcohol dependence: a combined 11C-flumazenil PET and pharmacodynamic study. Psychopharmacology (Berl) 180(4):595–606. London, E.D., Berman, S.M., Voytek, B., Simon, S.L., Mandelkern, M.A., Monterosso, J., Thompson, P.M., Brody, A.L., Geaga, J. A., Hong, M.S., Hayashi, K.M., Rawson, R.A., and Ling, W. (2005) Cerebral metabolic dysfunction and impaired vigilance in recently abstinent methamphetamine abusers. Biol. Psychiatry 58(10):770–778.

London, E.D., Simon, S.L., Berman, S.M., Mandelkern, M.A., Lichtman, A.M., Bramen, J., Shinn, A.K., Miotto, K., Learn, J., Dong, Y., Matochik, J.A., Kurian, V., Newton, T., Woods, R., Rawson, R., and Ling, W. (2004) Mood disturbances and regional cerebral metabolic abnormalities in recently abstinent methamphetamine abusers. Arch. Gen. Psychiatry 61(1):73–84. Lyvers, M. (2006) Recreational ecstasy use and the neurotoxic potential of MDMA: current status of the controversy and methodological issues. Drug Alcohol Rev. 25(3):269–276. Mann, K., Agartz, I., Harper, C., Shoaf, S., Rawlings, R.R., Momenan, R., Hommer, D.W., Pfefferbaum, A., Sullivan, E.V., Anton, R.F., Drobes, D.J., George, M.S., Bares, R., Machulla, H.J., Mundle, G., Reimold, M., and Heinz, A. (2001) Neuroimaging in alcoholism: ethanol and brain damage. Alcohol Clin. Exp. Res. 25(5 Suppl ISBRA):104S–109S. Martinez, D., Broft, A., Foltin, R.W., Slifstein, M., Hwang, D-R., Huang, Y., Perez, A., Frankel, W.G., Cooper, T., Kleber, H.D., Fischman, M.W., and Laruelle, M. (2004) Cocaine dependence and d2 receptor availability in the functional subdivisions of the striatum: relationship with cocaine-seeking behavior. Neuropsychopharmacology 29:1190–1202. Martinez, D., Gil, R., Slifstein, M., Hwang, D.R., Huang, Y., Perez, A., Kegeles, L., Talbot, P., Evans, S., Krystal, J., Laruelle, M., and Abi-Dargham, A. (2005) Alcohol dependence is associated with blunted dopamine transmission in the ventral striatum. Biol. Psychiatry 58(10):779–786. Mason, B.J., Salvato, F.R., Williams, L.D., Ritvo, E.C., and Cutler, R.B. (1999) A double-blind, placebo-controlled study of oral nalmefene for alcohol dependence. Arch. Gen. Psychiatry 56(8): 719–724. McBride, W.J., Chernet, E., Dyr, W., Lumeng, L., and Li, T.K. (1993) Densities of dopamine D2 receptors are reduced in CNS regions of alcohol-preferring P rats. Alcohol 10:387–390. McCann, U.D., Ricaurte, G.A., and Molliver, M.E. (2001) “Ecstasy” and serotonin neurotoxicity: new findings raise more questions. Arch. Gen. Psychiatry 58:907–908. McCann, U.D., Szabo, Z., Seckin, E., Rosenblatt, P., Mathews, W.B., Ravert, H.T., Dannals, R.F., and Ricaurte, G.A. (2005) Quantitative PET studies of the serotonin transporter in MDMA users and controls using [11C]McN5652 and [11C]DASB. Neuropsychopharmacology 30(9):1741–1750. McClernon, F.J., and Gilbert, D.G. (2004) Human functional neuroimaging in nicotine and tobacco research: basics, background, and beyond. Nicotine Tob. Res. 6(6):941–959. Melichar, J.K., Hume, S.P., Williams, T.M., Daglish, M.R., Taylor, L.G., Ahmad, R., Malizia, A.L., Brooks, D.J., Myles, J.S., Lingford-Hughes, A., and Nutt, D.J. (2005) Using [11C]diprenorphine to image opioid receptor occupancy by methadone in opioid addiction: clinical and preclinical studies. J. Pharmacol. Exp. Ther. 312(1):309–315. Morgan, D., Grant, K.A., Gage, H.D., Mach, R.H., Kaplan, J.R., Prioleau, O., Nader, S.H., Buchheimer, N., Ehrenkaufer, R.L., and Nader, M.A. (2002) Social dominance in monkeys: dopamine D2 receptors and cocaine self-administration. Nat. Neurosci. 5(2): 169–174. Munro, C.A., McCaul, M.E., Oswald, L.M., Wong, D.F., Zhou, Y., Brasic, J., Kuwabara, H., Kumar, A., Alexander, M., Ye, W., and Wand, G.S. (2006) Striatal dopamine release and family history of alcoholism. Alcohol Clin. Exp. Res. 30(7):1143–1151. Nader, M.A,. and Czoty, P.W. (2005) PET imaging of dopamine D2 receptors in monkey models of cocaine abuse: genetic predisposition versus environmental modulation. Am. J. Psychiatry 162(8): 1473–1482. Nader, M.A., Morgan, D., Gage, H.D., Nader, S.H., Calhoun, T.L., Buchheimer, N., Ehrenkaufer, R., and Mach, R.H. (2006) PET imaging of dopamine D2 receptors during chronic cocaine selfadministration in monkeys. Nat. Neurosci. 9(8):1050–1056.

49: PET AND SPECT IMAGING IN SUBSTANCE ABUSE RESEARCH Nowak, K.L., McBride, W.J., Lumeng, L., Li, T.K., and Murphy, J. M. (2000) Involvement of dopamine D2 autoreceptors in the ventral tegmental area on alcohol and saccharin intake of the alcohol-preferring P rat. Alcohol Clin. Exp. Res. 24:476–483. Obrocki, J., Schmoldt, A., Buchert, R., Andresen, B., Petersen, K., and Thomasius, R. (2002) Specific neurotoxicity of chronic use of ecstasy. Toxicol. Lett. 127(1-3):285–297. O’Leary, D.S., Block, R.I., Flaum, M., Schultz, S.K., Boles, Ponto, L.L., Watkins, G.L., Hurtig, R.R., Andreasen, N.C., and Hichwa, R.D. (2000) Acute marijuana effects on rCBF and cognition: a PET study. Neuroreport 11:3835–3841. Perry, D.C., Davila-Garcia, M.I., Stockmeier, C.A., and Kellar, K.J. (1999) Increased nicotinic receptors in brains from smokers: membrane binding and autoradiography studies. J. Pharmacol. Exp. Ther. 289(3):1545–1552. Pfeffer, A.O., and Samson, H.H. (1986) Effect of pimozide on home cage ethanol drinking in the rat: dependence on drinking session length. Drug Alcohol Depend. 17:47–55. Phillips, P.E., Stuber, G.D., Heien, M.L., Wightman, R.M., and Carelli, R.M. (2003) Subsecond dopamine release promotes cocaine seeking. Nature 422:614–618. Phillips, T.J., Brown, K.J., Burkhart-Kasch, S., Wenger, C.D., Kelly, M.A., Rubinstein, M., Grandy, D.K., and Low, M.J. (1998) Alcohol preference and sensitivity are markedly reduced in mice lacking dopamine D2 receptors. Nat. Neurosci. 1:610–615. Ponto, L.L., O’Leary, D.S., Koeppel, J., Block, R.I., Watkins, G.L., Richmond, J.C., Ward, C.A., Clermont, D.A., Schmitt, B.A., and Hichwa, R.D. (2004) Effect of acute marijuana on cardiovascular function and central nervous system pharmacokinetics of [(15)O]water: effect in occasional and chronic users. J. Clin. Pharmacol. 44(7):751–766. Quickfall, J., and Crockford, D. (2006) Brain neuroimaging in cannabis use: a review. J. Neuropsychiatry Clin. Neurosci. 18(3): 318–332. Quinton, M.S., and Yamamoto, B.K. (2006) Causes and consequences of methamphetamine and MDMA toxicity. AAPS J. 8(2):E337– E347. Reneman, L., Booij, J., de Bruin, K., Reitsma, J.B., de Wolff, F.A., Gunning, W.B., den Heeten, G.J., and van den Brink, W. (2001) Effects of dose, sex, and long-term abstention from use on toxic effects of MDMA (ecstasy) on brain serotonin neurons. Lancet 358(9296):1864–1869. Reneman, L., de Win, M.M., van den Brink, W., Booij, J., and den Heeten, G.J. (2006) Neuroimaging findings with MDMA/ecstasy: technical aspects, conceptual issues and future prospects. J. Psychopharmacol. 20(2):164–175. Repo, E., Kuikka, J.T., Bergstrom, K.A., Karhu, J., Hiltunen, J., and Tiihonen, J. (1999) Dopamine transporter and D2-receptor density in late-onset alcoholism. Psychopharmacology (Berl) 147: 314–318. Ricaurte, G.A., Forno, L.S., Wilson, M.A., DeLanney, L.E., Irwin, I., Molliver, M.E., and Langston, J.W. (1988) (+/−)3,4-Methylenedioxymethamphetamine selectively damages central serotonergic neurons in nonhuman primates. JAMA 260:51–55. Ritz, M.C., Lamb, R.J., Goldberg, S.R., and Kuhar, M.J. (1987) Cocaine receptors on dopamine transporters are related to selfadministration of cocaine. Science 237(4819):1219–1223. Rolls, E.T. (2000) The orbitofrontal cortex and reward. Cereb. Cortex 10(3):284–294. Rose, J.E. (2006) Nicotine and nonnicotine factors in cigarette addiction. Psychopharmacology (Berl) 184(3-4):274–285. Rose, J.E., Behm, F.M., Salley, A.N., Bates, J.E., Coleman, R.E., Hawk, T.C., and Turkington, T.G. (2007) Regional brain activity correlates of nicotine dependence. Neuropsychopharmacology 32(12):2441–2452. Scott, D.J., Domino, E.F., Heitzeg, M.M., Koeppe, R.A., Ni, L., Guthrie, S., and Zubieta, J.K. (2007) Smoking modulation of

843

mu-opioid and dopamine D2 receptor-mediated neurotransmission in humans. Neuropsychopharmacology 32(2):450–457. Scott, W.K., Zhang, F., Stajich, J.M., Scott, B.L., Stacy, M.A., and Vance, J.M. (2005) Family-based case-control study of cigarette smoking and Parkinson disease. Neurology 64(3):442–447. Sekine, Y., Iyo, M., Ouchi, Y., Matsunaga, T., Tsukada, H., Okada, H., Yoshikawa, E., Futatsubashi, M., Takei, N., and Mori, N. (2001) Methamphetamine-related psychiatric symptoms and reduced brain dopamine transporters studied with PET. Am. J. Psychiatry 158:1206–1214. Sekine, Y., Minabe, Y., Ouchi, Y., Takei, N., Iyo, M., Nakamura, K., Suzuki, K., Tsukada, H., Okada, H., Yoshikawa, E., Futatsubashi, M. and Mori, N. (2003) Association of dopamine transporter loss in the orbitofrontal and dorsolateral prefrontal cortices with methamphetamine-related psychiatric symptoms. Am. J. Psychiatry 160(9):1699–1701. Sekine, Y., Ouchi, Y., Takei, N., Yoshikawa, E., Nakamura, K., Futatsubashi, M., Okada, H., Minabe, Y., Suzuki, K., Iwata, Y., Tsuchiya, K.J., Tsukada, H., Iyo, M., and Mori, N. (2006) Brain serotonin transporter density and aggression in abstinent methamphetamine abusers. Arch. Gen. Psychiatry 63(1):90–100. Soyka, M., and Roesner, S. (2006) New pharmacological approaches for the treatment of alcoholism. Expert Opin. Pharmacother. 7(17):2341–2353. Sprenger, T., Berthele, A., Platzer, S., Boecker, H., and Tolle, T.R. (2005) What to learn from in vivo opioidergic brain imaging? Eur. J. Pain 9(2):117–121. Staley, J.K., Krishnan-Sarin, S., Cosgrove, K.P., Krantzler, E., Frohlich, E., Perry, E., Dubin, J.A., Estok, K., Brenner, E., Baldwin, R.M., Tamagnan, G.D., Seibyl, J.P., Jatlow, P., Picciotto, M.R., London, E.D., O’Malley, S., and van Dyck, C.H. (2006) Human tobacco smokers in early abstinence have higher levels of beta2* nicotinic acetylcholine receptors than nonsmokers. J. Neurosci. 26(34): 8707–8714. Stefanini, E., Frau, M., Garau, M.G., Garau, B., Fadda, F., and Gessa, G.L. (1992) Alcohol-preferring rats have fewer dopamine D2 receptors in the limbic system. Alcohol Alcohol. 27:127–130. Thanos, P.K., Taintor, N.B., Rivera, S.N., Umegaki, H., Ikari, H., Roth, G., Ingram, D.K., Hitzemann, R., Fowler, J.S., Gatley, S.J., Wang, G.J., and Volkow, N.D. (2004) DRD2 gene transfer into the nucleus accumbens core of the alcohol preferring and nonpreferring rats attenuates alcohol drinking. Alcohol Clin. Exp. Res. 28:720–728. Thanos, P.K., Volkow, N.D., Freimuth, P., Umegaki, H., Ikari, H., Roth, G., Ingram, D.K., and Hitzemann, R. (2001) Overexpression of dopamine D2 receptors reduces alcohol self-administration. J. Neurochem. 78:1094–1103. Thomasius, R., Zapletalova, P., Petersen, K., Buchert, R., Andresen, B., Wartberg, L., Nebeling, B., and Schmoldt, A. (2006) Mood, cognition and serotonin transporter availability in current and former ecstasy (MDMA) users: the longitudinal perspective. J. Psychopharmacol. 20(2):211–225. Tupala, E., Hall, H., Bergstrom, K., Mantere, T., Rasanen, P., Sarkioja, T., and Tiihonen, J. (2003) Dopamine D2 receptors and transporters in type 1 and 2 alcoholics measured with human whole hemisphere autoradiography. Hum. Brain Mapp. 20:91–102. Tupala, E., Hall, H., Bergstrom, K., Sarkioja, T., Rasanen, P., Mantere, T., Callaway, J., Hiltunen, J., and Tiihonen, J. (2001) Dopamine D(2)/D(3)-receptor and transporter densities in nucleus accumbens and amygdala of type 1 and 2 alcoholics. Mol. Psychiatry 6:261–267. Vander Borght, T., Kilbourn, M., Desmond, T., Kuhl, D., and Frey, K. (1995) The vesicular monoamine transporter is not regulated by dopaminergic drug treatments. Eur. J. Pharmacol. 294(2/3): 577–583. Volkow, N.D., Chang, L., Wang, G.-J., Fowler, J.S., Franceschi, D., Sedler, M.J., Gatley, S.J., Hitzemann, R., Ding, Y.S., Wong, C.,

844

SUBSTANCE ABUSE DISORDERS

and Logan J. (2001) Higher cortical and lower subcortical metabolism in detoxified methamphetamine abusers. Am. J. Psychiatry 158:383–389. Volkow, N.D., Chang, L., Wang, G-J., Fowler, J.S., Franceschi, D., Sedler, M., Gatley, S.J., Miller, E., Hitzemann, R., Ding, Y.S., and Logan, J. (2001) Loss of dopamine transporters in methamphetamine abusers recovers with protracted abstinence. J. Neurosci. 21(23):9414–9418. Volkow, N.D., Wang, G.J., Fowler, J.S., Logan, J., Gatley, S.J., Gifford, A., Hitzemann, R.,Ding, Y.S., and Pappas, N. (1999) Prediction of reinforcing responses to psychostimulants in humans by brain dopamine D2 receptor levels. Am. J. Psychiatry 156(9):1440–1443. Volkow, N.D., and Fowler, J.S. (2000) Addiction, a disease of compulsion and drive: involvement of the orbitofrontal cortex. Cereb. Cortex 10:318–325. Volkow, N.D., Fowler, J.S., Ding, Y.S., Wang, G-J., and Gatley, S.J. (1999) Imaging the neurochemistry of nicotine actions: studies with positron emission tomography. Nicotine Tob. Res. 1(Suppl 2):S127–S132; discussion S139–S140. Volkow, N.D., Fowler, J.S., and Wang, G-J. (2003) Positron emission tomography and single-photon emission computed tomography in substance abuse research. Semin. Nucl. Med. 33(2): 114–128. Volkow, N.D., Fowler, J.S., and Wang, G-J. (2004) The addicted human brain viewed in the light of imaging studies: brain circuits and treatment strategies. Neuropharmacology 47(Suppl 1):3–13. Volkow, N.D., Fowler, J.S., Wolf, A.P., Hitzemann, R., Dewey, S., Bendriem, B., Alpert, R., and Hoff, A. (1991) Changes in brain glucose metabolism in cocaine dependence and withdrawal. Am. J. Psychiatry 148(5):621–626. Volkow, N.D., Wang, G-J., Begleiter, H., Porjesz, B., Fowler, J.S., Telang, F., Wong, C., Ma, Y., Logan, J., Goldstein, R., Alexoff, D., and Thanos, P.K. (2006) High levels of dopamine D2 receptors in unaffected members of alcoholic families: possible protective factors. Arch. Gen. Psychiatry 63(9):999–1008. Volkow, N.D., Wang, G-J., Fischman, M.W., Foltin, R., Fowler, J.S., Franceschi, D., Franceschi, M., Logan, J., Gatley, S.J., Wong, C., Ding, Y.S., Hitzemann, R., and Pappas, N. (2000) Effects of route of administration on cocaine induced dopamine transporter blockade in the human brain. Life Sci. 67(12):1507–1515. Volkow, N.D., Wang, G-J, Fowler, J.S., Hitzemann, R., Angrist, B., Gatley, S.J., Logan, J., Ding, Y.S., and Pappas, N. (1999) Association of methylphenidate-induced craving with changes in right striato-orbitofrontal metabolism in cocaine abusers: implications in addiction. Am. J. Psychiatry 156:19–26. Volkow, N.D., Wang, G-J., Fowler, J.S., Logan, J., Gatley, S.J., Hitzemann, R., Chen, A.D., Dewey, S.L., and Pappas, N. (1997) Decreased striatal dopaminergic responsiveness in detoxified cocaine-dependent subjects. Nature 386(6627):830–833. Volkow, N.D., Wang, G-J., Fowler, J.S., Logan, J., Hitzemann, R., Ding, Y.S., Pappas, N., Shea, C., and Piscani, K. (1996) Decreases in dopamine receptors but not in dopamine transporters in alcoholics. Alcohol Clin. Exp. Res. 20:1594–1598. Volkow, N.D., Wang, G-J., Fowler, J.S., Logan, J., Jayne, M., Franceschi, D., Wong, C., Gatley, S.J., Gifford, A.N., Ding, Y.S., and Pappas, N. (2002) “Nonhedonic” food motivation in humans involves dopamine in the dorsal striatum and methylphenidate amplifies this effect. Synapse 44(3):175–180. Volkow, N.D., Wang, G-J., Franceschi, D., Fowler, J.S., Thanos, P.P., Maynard, L., Gatley, S.J., Wong, C., Veech, R.L., Kunos, G., and Li, T.K. (2006) Low doses of alcohol substantially decrease glucose metabolism in the human brain. Neuroimage 29(1):295– 301. Volkow, N.D., Wang, G-J., Hitzemann, R., Fowler, J.S., Overall, J.E., Burr, G., and Wolf, A.P. (1994) Recovery of brain glucose metabolism in detoxified alcoholics. Am. J. Psychiatry 151(2): 178–183.

Volkow, N.D., Wang, G-J., Ma, Y., Fowler, J.S., Wong, C., Ding, Y.S., Hitzemann, R., Swanson, J.M., and Kalivas, P. (2005) Activation of orbital and medial prefrontal cortex by methylphenidate in cocaine-addicted subjects but not in controls: relevance to addiction. J. Neurosci. 25(15):3932–3939. Volkow, N.D., Wang, G-J., Maynard, L., Fowler, J.S., Jayne, B., Telang, F., Logan, J., Ding, Y.S., Gatley, S.J., Hitzemann, R., Wong, C., and Pappas, N. (2002) Effects of alcohol detoxification on dopamine D2 receptors in alcoholics: a preliminary study. Psychiatry Res. 116(3):163–172. Volkow, N.D., Wang, G-J., Overall, J.E., Hitzemann, R., Fowler, J.S., Pappas, N., Frecska, E., and Piscani, K. (1997) Regional brain metabolic response to lorazepam in alcoholics during early and late alcohol detoxification. Alcohol Clin. Exp. Res. 21(7): 1278– 1284. Volkow, N.D., Wang, G-J., Fischman, M., Foltin, R., Fowler, J.S., Abumrad, N.N., Vitkun, S., Logan, J., Gatley, S.J., Pappas, N., Hitzemann, R., and Shea, C.E. (1997) Relationship between subjective effects of cocaine and dopamine transporter occupancy. Nature 386(6627):827–830. Volkow, N.D., Wang, G-J., Telang, F., Fowler, J.S., Logan, J., Childress, A.R., Jayne, M., Ma, Y., and Wong, C. (2006) Cocaine cues and dopamine in dorsal striatum: mechanism of craving in cocaine addiction. J. Neurosci. 26(24):6583–6588. Wang, G-J., Volkow, N.D., Chang, L., Miller, E., Sedler, M., Hitzemann, R., Zhu, W., Logan, J., Ma, Y., and Fowler, J.S. (2004) Partial recovery of brain metabolism in methamphetamine abusers after protracted abstinence Am. J. Psychiatry 161(2):242– 248. Wang, G-J., Volkow, N.D., Fowler, J.S., Cervany, P., Hitzemann, R.J., Pappas, N.R., Wong, C.T., and Felder, C. (1999) Regional brain metabolic activation during craving elicited by recall of previous drug experiences. Life Sci. 64(9):775–784. Wang, G-J., Volkow, N.D., Fowler, J.S., Franceschi, D., Wong, C.T., Pappas, N.R., Netusil, N., Zhu, W., Felder, C., and Ma, Y. (2003) Alcohol intoxication induces greater reductions in brain metabolism in male than in female subjects. Alcohol Clin. Exp. Res. 27(6):909–917. Wang, G-J., Volkow, N.D., Fowler, J.S., Pappas, N.R., Wong, C.T., Pascani, K., Felder, C.A., and Hitzemann, R.J. (1998) Regional cerebral metabolism in female alcoholics of moderate severity does not differ from that of controls. Alcohol Clin. Exp. Res. 22(8):1850–1854. Waniewski, R.A., and Martin, D.L. (1998) Preferential utilization of acetate by astrocytes is attributable to transport, J. Neurosci. 18:5225–5233. Wilson, J.M., Kalasinsky, K.S., Levey, A.I., Bergeron, C., Reiber, G., Anthony, R.M., Schmunk, G.A., Shannak, K., Haycock, J.W., and Kish, S.J. (1996) Striatal dopamine nerve terminal markers in human, chronic methamphetamine users. Nat. Med. 2:699– 703. Wong, D.F., Kuwabara, H., Schretlen, D.J., Bonson, K.R., Zhou, Y., Nandi, A., Brasic, J.R., Kimes, A.S., Maris, M.A., Kumar, A., Contoreggi, C., Links, J., Ernst, M., Rousset, O., Zukin, S., Grace, A.A., Lee, J.S., Rohde, C., Jasinski, D.R., Gjedde, A., and London, E.D. (2006) Increased occupancy of dopamine receptors in human striatum during cue-elicited cocaine craving. Neuropsychopharmacology 31(12):2716–2727. Yang, Y.K., Yao, W.J., McEvoy, J.P., Chu, C.L., Lee, I.H., Chen, P.S., Yeh, T.L., and Chiu, N.T. (2006) Striatal dopamine D2/D3 receptor availability in male smokers. Psychiatry Res. 146(1): 87–90. Yoder, K.K., Kareken, D.A., Seyoum, R.A., O’Connor, S.J., Wang, C., Zheng, Q.H., Mock, B., and Morris, E.D. (2005) Dopamine D(2) receptor availability is associated with subjective responses to alcohol. Alcohol Clin. Exp. Res. 29:965–970. Zahniser, N.R., and Doolen, S. (2001) Chronic and acute regulation of Na+/Cl- -dependent neurotransmitter transporters: drugs, sub-

49: PET AND SPECT IMAGING IN SUBSTANCE ABUSE RESEARCH strates, presynaptic receptors, and signaling systems. Pharmacol. Ther. 92(1):21–55. Zhu, J.P.Q., Xu, W., and Angulo, J.A. (2006) MAMP-induced cell death: selective vulnerability in neuronal subpopulations of the striatum in mice. Neuroscience 140:607–622. Zubieta, J.K., Gorelick, D.A., Stauffer, R., Ravert, H.T., Dannals, R.F., and Frost, J.J. (1996) Increased mu opioid receptor binding detected by PET in cocaine-dependent men is associated with cocaine craving. Nat. Med. 2(11):1225–1229.

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Zubieta, J., Greenwald, M.K., Lombardi, U., Woods, J.H., Kilbourn, M.R., Jewett, D.M., Koeppe, R.A., Schuster, C.R., and Johanson, C.E. (2000) Buprenorphine-induced changes in mu-opioid receptor availability in male heroin-dependent volunteers: a preliminary study. Neuropsychopharmacology 23:326–334. Zubieta, J.K., Heitzeg, M.M., Xu, Y., Koeppe, R.A., Ni, L., Guthrie, S., and Domino, E.F. (2005) Regional cerebral blood flow responses to smoking in tobacco smokers after overnight abstinence. Am. J. Psychiatry 162(3):567–577.

50 Brain Reward and fMRI P. READ MONTAGUE

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Questions about brain reward representations and neurobiological substrates of reward and reward processing form one of the broadest areas of neuroscience. The reason for this breadth derives from the fact that reward pursuit is one of the primary functions of a mobile creature, and so it is not surprising that the neural machinery devoted to reward processing is vast, multileveled, and related to every aspect of human cognition. Three decades ago, experiments on reward representation and processing focused almost exclusively on animal studies, and since that time, this work has evolved dramatically up and down. It has extended down to networks of identified molecular interactions (e.g., Hyman et al., 2006) and up to circuits underlying reward-guided choice and decision making in nonuman primates (e.g., Montague, Hyman, et al., 2004; Morris et al., 2004; Morris et al., 2006; Schultz, 2007). In this chapter, we focus on brain reward systems in humans using functional magnetic resonance imaging (fMRI) as the neural probe of choice and restrict our focus further to approaches in this area that lean on either computational modeling of brain reward systems or neuroeconomic probes during decision making. This chapter is taken almost verbatim from Montague (2007) in Functional Neurology. Any discussion of reward processing in humans must first clarify the very broad use of the term reward and the kinds of stimuli, behavioral acts, internal mental states, and so on that can act as rewards for humans. More specifically, one must first specify what qualifies as a reward and why, and identify the quantitative settings in which rewards are defined and pursued. It is our general perspective here that by examining the way that rewards guide valuation and decision making, we can clarify and differentiate the uses of the term. NEUROECONOMIC APPROACHES TO REWARD PROCESSING Webster’s New Millennium™ Dictionary of English defines neuroeconomics as “the study of the brain in making economic decisions, esp. to build a biological model of decision-making in economic environments.” This same dictionary account of the word lists its birth date as the year 2002. The question on many scientists’ minds, 846

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especially those interested in how any nervous system makes a decision, is just how different is neuroeconomics from behavioral and neuroscience research that has been going on for the last 50 years? Well, in terms of the issues raised, it is not, but in terms of its focus and future outlook, it is indeed opening new areas of inquiry. From the neuroscience side, neuroeconomics stands on the shoulders of a lot of behavioral and neural evidence derived from creatures ranging from fruit flies to humans. However, many issues in decision making and its neural and computational underpinnings, though not uniquely human, take a certain form in humans that is not always directly comparable in model systems such as rodents and fruit flies. Also, as alluded to, much of the work taking place in neuroeconomics has natural connections to computational neuroscience and, through that connection, to practical applications in psychiatry, neurology, and beyond. Last, it is altogether possible that the term neuroeconomics is unnecessarily limiting, and for neuroscientists should be thought of as “decision neuroscience” in the same manner that we naturally accept the term molecular neuroscience. Efficiency and the Reward-Harvesting Problem There are two natural neuroeconomics. The first, let’s call it neuroeconomics I, addresses the way that neural tissue is built, sustains itself through time, and processes information efficiently. Neuroeconomics II concerns itself with the behavioral algorithms running on such neural tissue. This review focuses on neuroeconomics II but begins by highlighting important unanswered issues that arise in neuroeconomics I, and the most important issue is the efficient use of energy. Modern-day computing devices generate an enormous amount of wasted heat, devoting only a small fraction of their thermal degrees of freedom to the computing itself. The wasted heat derives from many sources, but mainly from a design luxury not available to any evolved biological computers—a wall socket, that is, an ongoing and seemingly inexhaustible source of energy. Modern computers do not have to consider how to obtain their next volt or whether the program they are running is more efficient than some other equivalent way to solve the problem at hand. Without these worries troubling

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their design, modern computers compute with extremely high speed and accuracy, and they communicate information internally at high rates. All these features contribute to the generation of entropy (Montague, 2006). But most important, a modern computer’s life has never depended on making choices about differentially allocating power to computing speed, energy usage, precision, or algorithm efficiency. This example provides a dramatic contrast to the computing economics of evolved biological systems. In contrast to the example above, biological computers run on batteries that they must recharge using the behavioral strategies at their disposal; consequently, neural hardware and neural software of real creatures never had the option to be grossly inefficient (e.g., Bialek, 1987; Laughlin, 1994). This latter observation is beguiling because it seems so obvious, but it has crafted remarkable efficiency into the nervous system wherever we have been able to look closely, including visual processing (Barlow, 1961; Atick, 1992; Barlow, 2001; Simoncelli and Olshausen, 2001). The human brain runs on about 20–25 watts, representing 20%–25% of an 80- to 100-watt basal power consumption. All the processes that the brain controls—vision, audition, olfaction, standing, running, digestion, and so on—must share this extremely small energy consumption rate. No matter how one divides this energy consumption among ongoing neural computations, an unavoidable conclusion arises: evolved nervous systems compute with an almost freakish efficiency (e.g., Levy and Baxter, 1996; Laughlin et al., 1998; Laughlin, 2001; Attwell and Laughlin, 2001; Laughlin, 2004). To be this efficient, biological computing devices must take account of investments—efficiencies in the operation of their parts and the algorithms running on those parts—and returns (expected increases in fitness). Collectively, these issues constitute what we call neuroeconomics I, the efficient operation of neural tissue. In the visual system, this kind of question has blossomed into a rich area of investigation that falls under the heading “natural visual statistics” approach to vision (or some congener of this name). The central idea is that the neural representations (processing strategies and organizational principles) in the visual system represent a “matching” of the encoding strategy in vision to the natural statistical structure present in the input “signals” (Ruderman, 1994; for review, see Simoncelli and Olshausen, 2001). This efficiency perspective is important because it has not been applied systematically to the problem of harvesting rewards (Fig. 50.1A). Figure 50.1 does not do justice to the complexities of a creature wandering about and deciding where it should search for prey or whether such searches are worth it. It is a deeply economic problem, but it depends on the statistics of likely reward distributions in the world, and it depends on the inter-

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nal states and goals of the creature: a creature’s internal state changes the way it processes and values external stimuli. The idea of quantifying the statistics of external reward and variables related to internal state is implicit to work on optimal foraging—how an animal should choose to search to maximize its net return on some food or prey (Smith, 1982; Kamil et al., 1987; see Krebs et al., 1978, for a classic example). In summary, the “natural statistics of reward-harvesting” depends on (1) the internal “signals” of the organism type, (2) the possible redundancies latent in these signals, and (3) the way that both “match” the statistics of external stimuli and behavioral options. It is just a harder problem. Why Should Heat Measures Correlate with Cognitive Variables? The above efficiency perspective also invites and answers broadly an important question that arises in the context of modern neuroimaging experiments: Why should “heat measures” (fMRI measures) taken from small volumes of neural tissue encode information about the computations being carried out nearby? (Fig. 50.1B) The broad answer is efficiency. One should expect an extremely efficient device to couple the dynamics of ongoing power demands directly to the computations it is performing. In the most efficient scenario (generally impossible to achieve), the dynamics of metabolic demand in a small volume of neural tissue would be exactly equivalent to the computations carried out by that volume. These demand measures would exist across a range of time and space scales; therefore, one should not expect a measurement as crude as fMRI to detect all of them. Nevertheless, efficiency hypotheses provide some insight into why “heat measures” should relate in any sensible way to cognition. If neuroeconomics (as defined above) is to produce a truly biological account of decision making, then it must descend further into the efficient mechanisms that compose the nervous system. In short, it must reconnect deeply with neuroscience and take more seriously the styles of computation required to implement efficient behavioral algorithms in real neural tissue. The incipient steps of neuroeconomics have in large part tested decision making in humans and nonhuman primates with fMRI, positron emission tomography (PET), or single-unit electrophysiology as the neural probes of choice. But the really important connections will come when detailed mechanisms can be reconnected with the interesting behavioral and imaging work. The second neuroeconomics, neuroeconomics II, chooses as its starting point behavioral algorithms and neural responses associated broadly with decision making and the kinds of valuations that underlie it. And it is explicitly here where portions of economics and neuroscience are beginning to find fruitful common ground. In particular, they find much common ground in computa-

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FIGURE 50.1 Efficient representations and their coupling to brain responses. (A) Reward harvesting is a complex problem that depends on processing cues from the world efficiently to “harvest prey” (circles) that may be difficult to find or catch. External sensory cues are only part of the problem. As indicated, the other source of signal originates within the creature seeking the rewards—the collection of “internal” signals that define its needs and goals. These variables can change dramatically the value of external stimuli. An efficient nervous system should contain representations that match the inter-

nal needs of the creature to the external signals that meet those needs. This is clearly a complex and dynamic problem. (B) Because of their dependence on local changes in blood flow and other proxies for metabolic demand, current non-invasive imaging approaches to human brain function (PET and fMRI) implicitly draw a relationship (not an equivalence) between cognitive variables and something akin to a “heat” measure. PET: positron emission tomography; fMRI: functional magnetic resonance imaging.

tional models or explanations grounded in an area called reinforcement learning (RL) (Sutton and Barto, 1998).

ment, and an internal teaching signal that depends on both (Sutton and Barto, 1998). Biologically, RL models have provided insight into the computations distributed by midbrain dopamine (DA) neurons, an important neuromodulatory system involved in reward processing and decision making related to reward harvesting (see Daw and Doya, 2006, for a recent review). We review the essence of these models here before showing their application to imaging experiments in humans. Modeling work on midbrain DA neurons has progressed dramatically over the last decade, and the research community is now equipped with a collection of computational models that depict very explicitly the kinds of information thought to be constructed and broadcast by this system (Montague et al., 1993; Montague and Sejnowski, 1994; Montague et al., 1996; Schultz et al.,

Reward-Harvesting, Reinforcement Learning (RL) Models, and Dopamine As outlined above, the problem of efficiently harvesting rewards from the real world is a complex task that depends on signals inside and outside the organism. In short, a creature needs efficient internal representations that match its collection of internal needs to the external signals that meet those needs. One approach to these problems is called reinforcement learning (RL), a modeling approach that casts the reward-harvesting problem explicitly as an interaction between the internal needs of the creature, the external signals from the environ-

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1997; Dayan and Balleine, 2002; Daw and Doya, 2006; for overall review, see Montague, McClure, et al., 2004; for application to addiction, see Redish, 2004). These models arose initially to account for detailed singleunit electrophysiology in midbrain DA neurons recorded while primates carry out simple learning and decisionmaking tasks (Ljungberg et al., 1992; Quartz et al., 1992; Montague et al., 1994, 1996) or to account for decision making in honeybees equipped with similar neurons (Montague et al., 1995). A large subset of the midbrain DA neurons participate in circuits that learn to value and to predict future rewarding events, especially the delivery of primary rewards such as food, water, and sex (Montague et al., 1996; Schultz et al., 1997; Schultz, 1998; Schultz and Dickinson, 2000; Waelti et al., 2001; Dayan and Abbott, 2001; Montague and Berns, 2002; Bayer and Glimcher, 2005; also see Delgado et al., 2000). Collectively, these findings have motivated a specific computational hypothesis suggesting that DA neurons emit reward prediction errors encoded in modulations in their spike output (Montague and Sejnowski, 1994; Montague et al., 1996; Schultz et al., 1997). This hypothesis is strongly supported by the timing and amplitude of burst and pause responses in the spike trains of these neurons (Quartz et al., 1992; Montague and Sejnowski, 1994; Montague et al., 1996; Schultz et al., 1997; Waelti et al., 2001; Montague, McClure, et al., 2004; Bayer and Glimcher, 2005). In recent years, this work has evolved significantly, and this model is correct for a subset of transient responses, but clearly not all transient responses (Ikemoto and Panksepp, 1999; Redgrave et al., 1999; theory to explain anomalies: Kakade and Dayan, 2002; also see: Morris et al., 2006; Redgrave and Gurney, 2006). Also, the model does not account at all for slow changes in DA levels that would be detectable with methods such as microdialysis. The complaints about the theory ride on top of the reward prediction error hypothesis, that is, they posit extra information being carried by DA transients. The most coherent theoretical account is that by Kakade and Dayan (2002) and posits an extra “bonus” signal for exploration encoded in dopaminergic transients, an idea followed up on by Redgrave and Gurney (2006). Despite these open issues, the reward prediction error hypothesis for rapid changes in dopaminergic spike activity continues to explain an important part of the repertoire of responses available to these neurons (Fig. 50.2). In words, increases in spike activity (from background rates) mean “things are better than expected,” decreases mean “things are worse than expected,” and no change means “things are just as expected.” In this interpretation, this system is always emitting information to downstream neural structures because even no change in firing rate carries meaning. The reward prediction error (RPE) takes the following form:

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RP error = current reward + γ (next reward prediction) − (current reward prediction), where γ is a scaling factor between 0 and 1 and represents a way to weight the near-term future more heavily than the distant future. For our purposes, two aspects of this equation are critical: (1) The system uses “forward models” to produce an online estimate of the next reward prediction, which is constantly combined with the current experienced reward and current reward prediction. (2) The predictions and their comparison across time represent an underlying value function stored in the animal’s brain. To see this, we write the model as: RP error = current reward + γ V (next internal state) − V (current internal state). Here, the function V, called a value function, is written as a function of the internal state of the animal. In this expression, valuation takes the form of a value function that associates with each internal state a number, its “value,” which represents the total reward that can be expected (on average) from that state into the distant future (reviewed in Montague, McClure, et al., 2004; Daw and Doya, 2006). This kind of stored value is like a long-term judgment; it “values” each state. And it is these values that can be updated through experience and under the guidance of reinforcement signals like the DA reward prediction error. Notice one important fact implicit here—the values are silent, stored numbers. There is no natural way to read out values directly; therefore, experiments on valuation must tease out the underlying value functions indirectly (Fig. 50.3). The RPE signal highlighted above is exactly the learning signal used in the temporal difference (TD) algorithm familiar to the machine learning field (Kaelbling et al., 1996; Sutton and Barto, 1998). In this computer science context, the learning signal is called the TD error and is used in dual modes (1) to learn better predictions of future rewards and (2) to choose actions that lead to rewarding outcomes. This dual use of the TD error signal is called an actor-critic system (Fig. 50.3). We use the terms TD error and reward prediction error interchangeably. When used as a learning signal, the RPE can be used to improve predictions of the value of the states of the organisms using simple Hebbian (correlational) learning rules (Montague et al., 1995; Montague et al., 1996; Schultz et al., 1997). A collection of adaptive weights (w) used to represent these predicted values are updated directly in proportion to this TD error— that is, the weights change (Δw) in proportion to the (signed) reward prediction error: Δw a TD error

(learning rule).

FIGURE 50.2 Dopamine transients encode prediction errors in expected value of future reward. (A) Dopamine spike activity and expected value of future reward. During training, each visual cue predicted reward 2 seconds later (recordings from alert monkey), but with differing expected values. The expected value of the future reward (probability p of reward × magnitude m of reward) was (left to right) 0 ml (p = 1 × m = 0 ml), 0.025 ml (p = 0.5 × m = 0.05 ml), 0.075 ml (p = 0.5 × m = 0.15 ml), 0.15 ml (p = 1.0 × m = 0.15 ml), and 0.25 ml (p = 0.5 × m = 0.50 ml). Bin width is 10 ms. Single dopamine neurons spike activity is shown at top with their overlying spike histograms. Spike histograms over 57 neurons are shown at bottom (adapted from Tobler et al., 2005). The TD error signal rt + γ V(St+1) − V(St) accounts for exactly this pattern of change with learning, where St is the state of the animal at time t. It also accounts for changes in firing when the timing of reward is changed because

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this changes dramatically the expected value of reward at the trained time. (B) Spike modulation in dopamine neurons carries reward prediction error. (Top panel) Dopamine neuron increases its spiking rate at the unexpected delivery of a rewarding fluid (spike histogram on top, individual spike trains beneath). (Middle panel) After repeated pairings of visual cue (CS) with fluid reward delivery 1 second later, the transient modulation to reward delivery (R) drops back into baseline and transfers to the time of the predictive cue (CS). (Bottom panel) On catch trials, omission of reward delivery causes pause response in dopamine neuron at the time that reward delivery should have occurred based on previous training. (Traces recorded from alert monkey; adapted from Schultz et al., 1997; Montague and Berns, 2002.) The TD error signal rt + γV(St+1) − V(St) accounts for exactly this pattern of change with learning, where St is the state of the animal at time t.

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(2005) quantified precisely dopaminergic spiking behavior during reward-dependent saccade experiments in alert monkeys and concluded that these neurons indeed encode a quantitative RPE signal. To be clear about the scope of this model, it applies strictly to rapid transients in spike rates in the 50–250 millisecond range and does not apply to other timescales of dopaminergic modulation that may well carry other information important for cognitive processing and behavioral control. For example, the model is agnostic with regard to baseline DA levels or even fluctuations on slightly slower timescales such as minutes to hours. Consequently, the model would not account for microdialysis results whose measurements lie in these temporal regimes. 50.3 Hypothesized relationships of actor–critic models to dopamine neuron spike output. Value function information (across states and through time) and reward information combine linearly at the level of dopamine neurons. This combination, if encoded in spike modulations, means that changes in activity encode RPEs δ(t). This signal is a signed quantity and can be used in target neural structures for learning and action choice. (Adapted from Montague et al., 1996; Montague, Hyman, and Cohen, 2004; also see McClure et al., 2003.)

FIGURE

The congruence of the TD error signal to measured dopaminergic spike activity is quite remarkable. The TD model predicts that the expected value (probability of reward × magnitude of reward) of the delivered reward will be encoded in the transient modulation of DA spike activity. This feature can be seen in Figure 50.2A for conditioned cues that predict different expected values for future rewards. In this figure, each cue predicted fluid delivery 2 seconds into the future, and the amounts listed above each cue are the expected value of that delivery, that is, the probability of delivery × magnitude. The results reproduced here show dopaminergic neuron activity after overtraining on the displayed visual cues (Tobler et al., 2005). As shown in Figure 50.2B, the model also predicts important temporal features of spike activity changes during conditioning tasks. For example, the unexpected delivery of food and fluid rewards causes burst responses in these neurons (R in Fig. 50.2B). If a preceding sensory cue, such as a light or sound, consistently predicts the time and expected value of the future reward, two dramatic changes occur as learning proceeds: (1) the transient response to reward delivery drops back to baseline firing levels and (2) a transient response occurs at the time of the earliest predictive sensory cue (CS in middle panel, Fig. 50.2B). However, the system keeps track of the expected time of reward delivery; if reward is not delivered at the expected time after the predictive cue, the firing rate decreases dramatically at the expected time of reward. Recent experiments by Bayer and Glimcher

Reward Prediction Error Model Guides fMRI Experiments in Humans Passive and active conditioning tasks The RPE model has now been extended to fMRI experiments in humans. Numerous reward expectancy experiments have now been carried out that probe human blood oxygen level dependent (BOLD) responses that correlate with RPEs (Knutson et al., 2000; Berns et al., 2001; Knutson et al., 2001; McClure, Berns, and Montague, 2003; O’Doherty et al., 2003; O’Doherty et al., 2004; for reviews, see O’Doherty, 2004; Montague et al., 2006). This work consistently demonstrates a BOLD response in the ventral striatum and ventral parts of the dorsal striatum that correlate with a TD error expected throughout the task in question (Fig. 50.4A). One extremely important finding by O’Doherty et al. (2004) is that the BOLD-encoded RPE signals can be dissociated in the dorsal and ventral striatum according to whether an action is required for the acquisition of the reward. This finding is depicted in Figure 50.4B. For passive tasks, the RPE is evident not only in ventral striatum and in active tasks; it is evident in both, but with a strong component in the dorsal striatum (Fig. 50.4B). These findings and the model-based analysis that uncovered them suggest that stimulus– response learning typical of actor–critic circuits in humans may be associated with activation in the dorsal striatum. Reward Prediction Error Signals Tracked During Sequential Decision Making The decision task shown in Figure 50.5 (see also COLOR FIGURE 50.5 in separate insert) is a modification of a task meant to test a theory of decision making under uncertainty called melioration (Herrnstein and Prelec, 1991; Egelman et al., 1998). This task can be envis-

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FIGURE

50.4 Actor and critic signals in humans detected by fMRI. (A) A simple conditioning task reveals a TD-like prediction-error signal (critic signal; see Fig. 50.3) encoded in hemodynamic responses in the human brain. On a normal training trial, a cue (light gray arrowhead) is followed by the passive delivery of pleasant-tasting juice (dark gray arrowhead) while subjects are scanned (TR = 2 seconds). After training on these contingencies, catch trials were randomly interleaved, and the reward delivery was delayed. Reward reliability continued at 100%, only the time of delivery was changed. The TD model predicts a negative prediction error at the time juice was expected but not delivered and a positive prediction error at the (unexpected) delayed time. At these moments, the expected value of reward deviates positively and negatively from that learned during training. Taking hemodynamic delays into account (~4 seconds), a prediction

error of each polarity (positive and negative) can be seen in the ventral putamen during a surprising catch trial. The thin line is the average hemodynamic response during a normal trial, and the dashed line is the average hemodynamic response during a catch trial (original data from McClure, Berns, and Montague, 2003). (B) Identification of potential actor response in dorsal striatum (see Fig. 50.3). A conditioning task is carried out in two modes requiring (1) a button press (an action) and (2) no action at all. The dorsal striatum—a region involved in action selection—responds only during the mode where action is required and shows no response when an action is not required. This is the first demonstration of an actor response detected in the human brain. (Legend adapted from Montague, Hyman, and Cohen, 2004, Fig. 4; original data from O’Doherty et al., 2004). fMRI: functional magnetic resonance imaging.

aged as a simple way to model real-world choices, where the rewards from a choice change as that choice is sampled. In Figure 50.5, the payoff functions for each choice (A or B) change as a function of the fraction of choices allocated to button A in the last 20 choices (Li et al., 2006; also see Daw and Doya, 2006, for review). As choice A is selected, the individual is moved to the right on the x axis (fraction allocated to A increases), and so choosing A (red) near the crossing point in the curves causes the returns from subsequent choices to A to decrease, whereas the returns from B increase (magnified in inset). The reward functions model a common scenario encountered by creatures in the real world. Imagine a bee sampling one flower type repeatedly while ignoring a second flower that it might also sam-

ple. All things being equal, as the flower is sampled, its nectar returns decrease (analogue to A, red) whereas the other unsampled flower (analogue to B, blue) type refills, thereby increasing its nectar return the next time it is sampled. A decision model like an actor–critic architecture (Fig. 50.3) that uses a TD error signal as its input gets stuck sampling near such crossing points because this is a stable point for the dynamics of the model (explained in the appendix of Montague and Berns, 2002). Behaviorally, humans do indeed get stuck near the crossing point; however, these data show that a “TD regressor” for the entire 250-choice experiment identifies a strong neural correlate of TD error in the putamen (right panel of Fig. 50.5). Figure 50.5B shows that the model also captures the choice behavior exhib-

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50.5 Actor–critic signals during sequential two-choice decision task. (A) Neural correlate of reward prediction error during sequential choice task. (Left) Two-choice task with returns encoded by centrally placed slider bar. (Middle) Inset shows the average behavior of a temporal difference (TD)-error-driven actor–critic model near the crossing point in the reward function. The colored arrows (see COLOR FIGURE 50.5 in separate insert) show what happens when red (A) or blue (B) is chosen, and they indicate the direction that the participants move along the x axis. The inset shows how these functions model one typical real-world occurrence for simple choices—choosing to sample A (red) tends to decrease returns from A while the unsampled returns from B increase, like flowers refilling with nectar while they are not being sampled. An actor–critic model will tend to stick near crossing points (explained in Montague and Berns, 2002). (Right) The hemodynamic correlate of a TD error signal throughout the entire 250 choices in this task is shown at two levels of significance (.001 and .005 [random effect]; N = 46; y = 12 mm). The payoff functions for this task are modified from a task originally proposed by Herrnstein and Prelec (1991) to test a theory of choice called melioration (adapted almost verbatim from

Li et al., 2006). (B) Actor–critic model captures choice behavior. Participant decisions were predicted using a reinforcement learning model with two different methods to determine the probability to choose an action (ε-greedy method and sigmoid method). For both methods, we assume that participants maintained independent estimates of the reward expected for each choice, A and B, and updated these values based on experienced rewards using a choice-dependent TD-error (that is, the Rescorla-Wagner learning algorithm). Choices were assumed to be (1) probabilistically related to choice values according to a sigmoid function (softmax method, green curve) or (2) have a fixed probability of 1-ε/ 2 for choice associated with bigger weight (ε-greedy method, pink curve). Decisions were binned (x axis) based on predicted likelihood that subjects would choose A. Y values indicate the actual average allocation to A for all choices within each bin. Linear regression shows there is a strong correlation between predicted and actual choices. (MS: r = 0.97, RO: r = 0.99, FR: r = 0.97, PR: r = 0.97 for softmax method; MS: r = 0.97, RO: r = 0.99, FR: r = 0.95, PR: r = 0.99 for ε-greedy method). (Adapted almost verbatim from Li et al., 2006.) MS: Matching Shoulder; RO: Rising Optimum; FR: Flat Return; PR: Pseudorandom.

ited by humans on this task. Here, the model is the simple actor–critic architecture illustrated in Figure 50.3 and using a sigmoid decision function (“softmax” function) that takes the TD error as input. In Figure 50.13, we illustrate how neural correlates of components of computational models (here the “TD regressor”) can be identified during reward-guided decision tasks (see Montague, McClure, et al., 2004; Daw and

Doya, 2006; Montague et al., 2006; Lohrenz et al., 2007; Chiu et al., 2008). On this simple two-choice decision task, the computational model is a central component in the identification of hemodynamic responses that correlate with the TD error signal (see “RL correlates” in Fig. 50.5). The procedure for identifying these RL correlates is straightforward. For each individual, we model the TD error sig-

FIGURE

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nal throughout the entire task, use this model to generate a sequence of choices using the actor–critic choice model shown in Figure 50.3, and extract three parameters (learning rate and two initial weights for each button) that minimize the difference between the predicted sequence of choices and the individual’s measured sequence of choices. This is done separately for each individual. The fitted parameters that produce the best behavioral match are used to compute the TD error signal throughout the entire experiment (250 choices). This best-fit TD error is idiosyncratic for each individual because individuals generate different sequences of choices on the task. The best-fit TD error signal is then convolved with the hemodynamic response function to produce the predicted hemodynamic response for the TD error (see Fig. 50.13 for illustration). The predicted hemodynamic response is then entered into a standard general linear model regression with the measured MR data (Friston et al., 1994; Ashburner and Friston, 1999), and regions of the brain that show the same hemodynamic profile are identified using t tests. This is the “RL correlate” shown in Figure 50.5 in the putamen. In contrast to this method, the TD correlate shown in Figure 50.4A is a fluctuation measured directly in the average hemodynamic response (McClure, Berns, and Montague, 2003; O’Doherty et al., 2003; O’Doherty et al., 2004). All details of the fitting procedures can be found clearly in Li et al. (2006). Anticipation of Secondary Reward (Money) Also Activates Striatum

cortical areas. Some of the earliest work in this area using fMRI was carried out by Breiter and colleagues and others (Breiter et al., 1997; Thut et al., 1997; Breiter et al., 2001). This group recorded responses to cocaine injections and found pronounced activation in the orbitofrontal cortex and the nucleus accumbens among a collection of reward-related regions. Early work by Knutson and colleagues also showed pronounced activation of the nucleus accumbens, but this group showed accumbal activations anticipating the receipt of reward (money) (Knutson et al., 2000; Knutson et al., 2001; see Figure 50.6). In addition, they found that the peak accumbal responses correlated with the amount of money received. Delgado et al. (2000) and Elliott et al. (2003) also identified, early on, large striatal responses to monetary rewards and punishments. Collectively, this work was important in establishing the possibility that more sophisticated reward processing was taking place at the level of the striatum. It is now almost paradigmatic that one can make such an assertion, but these reward-processing experiments using a noninvasive probe that could look “deep enough” into the human brain helped motivate more serious consideration of the striatum as a region involved intimately in reward processing. Prior to this time, the striatum was considered to be a brain region primarily (but not exclusively) involved in the selection and sequencing of motor behaviors (for review, see Wickens, 1993). HARVESTING REWARDS FROM OTHER AGENTS

In this chapter, we are focusing on model-based approaches to reward processing as detected by fMRI; however, human reward responses generate very consistent activations across a common set of subcortical and

We have now seen consistent fMRI-detectable responses to reward delivery, anticipation of reward delivery, and the sequential delivery of rewards predicated on a se-

FIGURE 50.6 Anticipation of reward activates striatum. Hemodynamic response to reward delivery grows with time from a cue until

reward is delivered. The peak response scales with the amplitude of the monetary reward. (Adapted from Knutson et al., 2001.)

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quence of actions. Many of these results were guided, either in their design or interpretation, by reinforcement learning models of reward processing and decision making, or at least were motivated in part by these models. As with any model-based approach, the model is always too simple an account of the reality exposed by the experiments, but it is not a stretch to claim that the reinforcement learning models have significantly structured our arguments and approaches to the vast array of problems associated with adaptively defining procuring rewards. We turn now to a class of behavior most important for humans—harvesting rewards through interaction with other humans. It is in this domain that the idea of a reward signal becomes most abstract, and in the case of empathy and norm enforcement (see Figs. 50.15, 50.16), rewards (both signs) can pass from one individual to another without any exchange of material between the two individuals. This is the sense in which fairness norms and deviations from them form a true common currency within and across individual humans. Although we cannot yet compute the exchange rates of such currencies across individuals, we can indeed see their impact. We start with fairness games derived from the behavioral and experimental economic fields. It is a rather intuitive claim that fairness between two humans is equivalent in some currency to a trade where both parties feel satisfied with the outcome without being coerced to feel this way. Almost by construction, the idea of fairness implies some understood norm of what is expected from another human when an exchange is carried out. In addition, we all recognize that the idea of a fair exchange between individuals extends well beyond the exchange of material goods (Camerer, 2003). Despite these expansive possibilities, fairness, like many other social sentiments, can be operationalized and probed with mathematically portrayed games (or staged interactions) played with other humans (Camerer, 2003; Camerer and Fehr, 2006). Economic Games Expose Fairness Norms and Abstract Prediction Error Responses In exchanges with other humans, efficient reward harvesting—in the form of immediate rewards, favors, or future promises of either—requires an agent to be able to model his or her partner and future interactions with that partner. An individual lacking this modeling capacity is literally incapable of protecting his or her own interests in interactions with others (Camerer and Fehr, 2006). It is well known that mental illness in many forms debilitates one’s capacity to interact and exchange fruitfully with other humans, and such incapacities are one important part of human cognition that psychiatry seeks to repair. Consequently, it is particularly important to be able to probe brain responses during active social exchanges among humans and place the results into

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some quantitative framework. Currently, neuroimaging work in this area has been focused on two-person interactions (Rilling et al., 2002; de Quervain et al., 2004; Rilling et al., 2004a, 2004b; King-Casas et al., 2005; Singer et al., 2006; Tomlin et al., 2006), with one notable exception: using a social conformity experiment in the style of Asch (Asch, 1951; Berns et al., 2005). One particularly fruitful approach has been the use of economic exchange games. Figure 50.7 illustrates the Ultimatum Game, probably better termed “take-itor-leave-it.” Player X is endowed with an amount of money (or some other valuable resource) and offers a split of this endowment to player Y, who can either accept or reject the offer. If player Y accepts, both players walk away with money; however, if player Y rejects, then no one gets anything. A “rational agent” account of this game would predict that player Y should accept all nonzero offers (Guth et al., 1982; also see Camerer, 2003; Fig. 50.7). Humans reject at a rate of about 50% at roughly a 70:30 to 80:20 split. The data in figure 50.7B (right panel) show a 50% rejection rate at around 70:30 (adapted from Camerer and Fehr, 2006). The reader might stop to “simulate” what they might accept or reject. Notice that the rejection rate changes when the number of responders increases—the presence of second responder causes both responders to accept a poorer split from the proposer. This game and others like it (Rilling et al., 2002) probe fairness norms and in the context of fMRI show that deviations from fairness norms act like rewards and punishments and even change behaviors and brain responses quite significantly (Rilling et al., 2002; Sanfey et al., 2003; Rilling et al., 2004a; King-Casas et al., 2005). Figure 50.8 shows a bilateral insula response to unfair offers from other humans (deviation from fairness norm shown in Fig. 50.7B), a finding consistent with its responses to negative emotional outcomes (Phillips et al., 1997; Damasio et al., 2000; Sanfey et al., 2003). This response was found to be diminished for a given level of unfairness if individuals played on a computer (Sanfey et al., 2003). Of course, negative emotions may follow the neural signal flagging a deviation from the fairness norm, but the important point here is that in the economic game, it is easy to quantify the norm. Damage to the insula is consistent with its role in computing deviations from norms if we allow that norms are continually being updated by experience (Dani and Montague, 2007). In chronic smokers, damage to the insula appears to create a state where smokers do not generate feelings that they need to smoke—they find it subjectively easier to avoid relapse after quitting (Naqvi et al., 2007). They may have lost their ability to compare their norms to their internal state or to link such comparison to negative emotional states, which becomes the proximate motivating mechanism to smoke again. The Ultimatum Game is particularly clarifying in suggest-

FIGURE 50.7 Two-person economic games expose fairness norms. (A) Exchange games between humans engage internal models of others, which may simulate interactions forward for a variable number of exchanges. These interactions evolved in the context of social exchange where multiple encounters were not only likely but were the norm. On these grounds, it is not unreasonable to expect such games to engender models of others that simulate multiple iterations with a partner. (B) Ultimatum game (take-it-or-leave-it). On-shot game where a player starts with a fixed amount of money and offers some split

(here, 60:40) to the partner. If the partner accepts, both players walk away with money (take it). If the player rejects the offer, neither player gets anything (leave it). A rational agent should accept any nonzero offers (Guth et al., 1982; also see Camerer, 2003), but, in fact, the human rejection rate is 50% at 80:20 split, and, as illustrated here, will change as the number of responders increases. One interpretation of these results is that humans possess well-established fairness norms (Fehr and Schmidt, 1999).

FIGURE 50.8 Insula responds to norm violation in a fairness game. Average hemodynamic responses of the right (R.) and left (L.) insula to the revelation of the proposer’s offer in an ultimatum game. Traces are separated by the fairness of the proposer’s offer. On this particular version, $10 was split between the players in integral dol-

lar amounts. The behavior showed that offers less than or equal to $2 from a human partner were treated as unfair, that is, rejected at a rate of ∼50%. dIPFC = dorso-lateral prefrontal cortex; ACC = anterior cingulate cortex. (Adapted from Sanfey et al., 2003, and data kindly provided by the authors.)

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ing these possibilities and useful because the possibilities are easily put into a quantitative model. The exact answer awaits future work. The Ultimatum Game gives a one-shot probe of norms and norm violation, but without any reputations forming between the interacting humans. In normal life, reputations built with another human form the basis of relationships with others—another area where mental illness can have devastating consequences. However, reputation formation, like one-shot fairness norms, can also be operationalized and turned into a quantitative probe for social interactions. Figures 50.9 (see also COLOR FIGURE 50.9 in separate insert) and 50.10 show fMRI data from a trust game carried out in a large cohort (N = 100) of interacting humans. This particular game is a multiround version of a game first suggested by Camerer and Weigelt (1988) but given its name and current form by Berg et al. (1995). Here, we show a multiround adaptation of this game, where two players play

10 rounds of pay–repay cycles (Fig. 50.9). One important difference with the one-shot Ultimatum Game is that reputations form between the players (see KingCasas et al., 2005, for details on reputation formation in this game). They develop a model of their partner’s likely response to giving too little or too much money— in short, they form a shared norm of what is expected of one another and respond briskly (good or bad) when that norm is violated. A number of new results have been discovered using this game while scanning both interacting brains (Montague et al., 2002); however, here, we emphasize just one: a RPE-like signal in the caudate nucleus that occurs on the “intention” to change the level of trust on the next round of play (Fig. 50.10). In early rounds (rounds 3–4), this signal appears in the trustee’s caudate nucleus at the revelation of the investor’s decision, but in later rounds (rounds 7–8), it occurs before the investor’s decision is revealed. So the signal trans-

50.9 Multiround trust game: harvesting rewards from other humans. (A) On each round, one player called the investor is endowed with $20 and can send (“trust”) the other player (called the trustee) any fraction of this amount. The amount sent is tripled en route to the trustee, who then decides what fraction of the tripled amount to repay. Players execute 10 rounds of this pay–repay cycle. Players maintain their respective roles throughout the entire task,

permitting the development of reputations with one another. (B) Timeline for events in the multiround trust game. Outcome screens are revealed simultaneously to both players; both interacting brains were scanned simultaneously (see King-Casas et al., 2005; multiround trust game is a variation on the game proposed by Camerer and Weigelt, 1988; Berg et al., 1995).

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50.10 Correlates of reciprocity and future intentions (trustee brain). (Left brain inset) Bilateral ventral caudate nucleus activation identified by contrasting the brain response to positive reciprocity and negative reciprocity (see King-Casas et al., 2005). Reciprocity is defined as relative differences in across-round payment between the players. For example, neutral reciprocity means that one player’s fractional change in available money sent was followed by the same fractional change in available money sent by the partner. Positive reciprocity means that the partner responded with a greater fractional change in money sent, and negative reciprocity means that the partner responded with a lesser fractional change in money sent. Contrasting brain responses to positive and negative reciprocity identified the ventral caudate nucleus. (medium gray and black traces) Average time series in the identified caudate region in early rounds

(top; rounds 3–4) and later rounds (bottom; rounds 7–8). The traces have been separated according to the trustee’s next move but are shown here at the time that the investor’s decision is revealed to both players. The trustee’s next move does not happen for ~22 seconds, so this response correlates with the trustee’s intention to increase (black trace) or decrease (medium gray trace) their repayment in the near future. Notice the difference between the intention to increase (black trace) and decrease (medium gray trace) repayment shifts 14 seconds earlier as trials progress and reputations build. This shift means that in later rounds (7–8), this signal difference is occurring before the investor’s decision is revealed. This is a shift analogous to that seen in simpler conditioning experiments (see Fig. 50.2). (Adapted from King-Casas et al., 2005; Tomlin et al. 2006.)

fers from reacting to the investor’s choice to anticipating the investor’s choice. The response shows up in a strongly dopaminoceptive structure (caudate) and exhibits exactly the temporal transfer expected for a RPE signal (Fig. 50.2 and Supplementary Online Materials [SOM]; King-Casas et al., 2005). A very clever use of a single-shot version of the trust game by Delgado and colleagues shows that the caudate signals can be dramatically modulated by information about the moral character (“moral priors”) of one’s partner (Delgado et al., 2005; Fig. 50.11). Once again, we see that reward-processing systems can flexibly and rapidly adapt their function to the problem at hand and can integrate a wide array of information that shows up as measurable changes in BOLD responses. The flexibility of the reward-harvesting systems can also be illustrated by experiments using information about “what might have happened” to generate measurable dynamic responses

in the same reward-processing structures (caudate and putamen). Lohrenz and colleagues have used a market investment game to track fictive error signals, a type of signal related to the ongoing difference between what one “might have earned” and what one “actually earned” (Lohrenz et al., 2007; Figs. 50.12–50.14) (see also COLOR FIGURE 50.14 in separate insert). These investigators show that the brain tracks fictive outcomes using the same reward pathways that generate and distribute reward prediction error signals—ongoing differences between what was expected and what was experienced. So real experience and fictive experience can generate reward error signals, both of which appear to influence an individual’s next choice in the investment game (Lohrenz et al., 2007). This game is particularly useful because it might be used to explore brain responses in drug addicts, where the capacity to allow negative out-

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FIGURE 50.11 The influence of moral priors on striatal reward responses to revealed trust. (A) Single-shot trust task was played multiple times, but brain responses and behavior were altered by “moral priors” about one’s partner. Three partners were used: good, neutral, and bad (“suspect moral character,” according to the authors of the study). Players were shown a picture and read a “cover story” about the moral character of their opponent. Players consistently chose to trust the “good” partner more. (B) The authors of the study describe the outcome best: “As expected from previous studies, acti-

vation of the caudate nucleus differentiated between positive and negative feedback, but only for the ‘neutral’ partner. Notably, it did not do so for the ‘good’ partner and did so only weakly for the ‘bad’ partner, suggesting that prior social and moral perceptions can diminish reliance on feedback mechanisms in the neural circuitry of trial-and-error reward learning.” Here, we show the average time series in the caudate at the time the outcome is revealed. The responses illustrate clearly the influence of the “moral prior” on measured responses. (Adapted from Delgado et al., 2005.)

comes that “might happen” to influence drug-taking habits appears to be severely diminished or lost altogether. While chronic smokers generate neural error signals associated with what “might” happen to them, these signals appear to be ignored in a way consonant with addicts’ drug use in the clear presence of negative outcomes that might occur or positive outcomes that may be foregone (Chiu et al., 2008).

related with fictive reward error signals (Lohrenz et al., 2007; Figs. 50.12–50.14). This remarkable range of “rewarding” dimensions illustrates a very basic point that we made much earlier—that is, the signal source that controls the reward input to striatum/midbrain system defines implicitly the current goal of the creature and thus the external stimulus or internal state that the creature values at the moment. It is reasonable to hypothesize that in humans, reward-harvesting machinery has the capacity to be redeployed in pursuit of literally any representation that can control the reward function r(t) as depicted in Figure 50.3. This is a powerful way to flexibly control a creature’s behavior and to induce cognitive innovation. A new idea or concept gains control of the reward function r(t), and the reward-harvesting machinery that we share with every other vertebrate on the planet takes over, computes RPEs and other quantities (Kakade and Dayan, 2002), and directs learning and decision making for some time. It is now clear why the brain must have a way to gate and filter the kinds of representations (probably intimately dependent on prefrontal cortex) allowed to govern reward-harvesting

Common currencies: From fairness to pain We have now reviewed evidence that reward processing in the human brain can be tracked using fMRI across a wide spectrum of stimuli or internal states that qualify as rewarding. In Figure 50.4, a passive and active conditioning experiment using fruit juice as the “reward” generated hemodynamic responses in the striatum (caudate and putamen) that correlated with a prediction error in the expected value of juice delivery. From primary rewards such as sugar water, we extended to sequential decision making, social exchange with other humans, and the influence of “moral biases” in these exchanges, and we even illustrated fMRI-detectable signals that cor-

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50.12 Fictive errors and the neural substrates of “what might have been.” A market investment task where market history is shown as decisions are made. Participants are shown their total available (lower left box) and the fractional percentage change from the last choice (lower right box). Participants move a centrally placed slider bar at each decision point (vertical gray lines) to indicate the fraction of their total to commit into the market (ranging from 0% to 100% in 10% increments). The “riskless” choice in this game is to “cash out” (0% invested). After the bet is placed, the market fluctuates to the next decision point—at that moment, if the market goes up, then all higher bets were better (higher gains); if it goes down,

then all lower bets were better (smaller losses). This task was used to track the behavioral and neural influence of “what might have been” (fictive error signal over gains)—that is, the ongoing temporal difference between the best that “might have been” gained and the actual gain. Figure 50.13 shows how such a signal was tracked during this experiment. Twenty equally spaced decisions were made per market, and 20 markets were played (adapted from Lohrenz et al., 2007; Chiu et al., 2008). In behavioral regressions, other than the last bet and the market fluctuation, this “fictive error over gains” was the best predictor of changes in the participants’ next bet, showing that it had measurable neural and behavioral influence.

machinery (Miller and Cohen, 2001), and why ideas about RPEs and gating in the prefrontal cortex should be taken seriously and be mathematically extended (O’Reilly et al., 1999; O’Reilly et al., 2002—DA gating hypothesis). We close our chapter on brain reward and fMRI by touching lightly upon very recent work exploring another rewarding dimension—punishment, that is, why humans are motivated to punish and the proximate brain responses and behavioral contexts that surround

the desire to punish. This is an important area, in part because the “valuation function issue” surrounding punishment of other humans relates directly to the nature of social norms, their enforcement, and the way that they would encourage or discourage particular kinds of social structures. This is an area where brain reward processing intersects with the way that humans organize themselves and others into institutions. Two of the more interesting experiments in this area are illustrated in Figures 50.15 and 50.16. Figure 50.15

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50.13 Building a regressor for fictive errors. To track the “fictive error over gains,” we computed the fictive error over gains at each decision point where a gain was earned. The time between decisions is a free variable, and so normally the time of decision occurs at irregular time intervals. For display purposes, we have shown decisions on regular time intervals, but otherwise, these data were taken from a participant in the experiment. The fictive error over gains is then convolved with a hemodynamic response function (impulse re-

sponse) to produce the hemodynamic response dynamic predicted for the fictive error signal. This trace is best fit to the hemodynamic response in each measured voxel, where the free parameter at hand is the height of the response function b. Using standard statistical methods, we identified the voxels whose measured signal correlates best with this expected response dynamic throughout the entire decision-making task. This method amounted to seeking a temporal pattern of blood flow changes that matched the fictive error signal.

is a two-part experiment that addresses the way that norm violations in one domain (fairness in an exchange with another human) translates into brain responses related to another domain (empathic responses to pain in others). Following the theme of this chapter, it is not surprising that reward circuitry is again engaged. In Figure 50.15, an individual witnesses two other individuals playing a game of cooperation/defection (sequential prisoner’s dilemma game; Singer et al., 2006). As illustrated, one of the players is a confederate who has been told to play fairly or unfairly. The individual, after watching the game transpire, is then put in a scanner and allowed to watch the confederate receive a painful stimulus. In earlier work (Singer et al., 2004), these same investigators had helped to identify brain responses (using fMRI) that correlate with empathizing with observed pain in others. In this experiment, males and females showed empathy-related fMRI responses when

observing pain being delivered to a “fair” confederate. However, for “unfair” confederates, the male brains diverged significantly from the female brains. Male brains showed dramatically reduced responses in empathyrelated regions and showed activation in reward-related areas (nucleus accumbens). Even more remarkably, the nucleus accumbens response correlated with the male individuals’ reported desire for revenge as subjectively reported (see Singer et al., 2006, for details and Fig. 50.16B). These are revealing findings in that the neural signatures correspond quite well with a behavioral account that casts males as norm enforcers (Singer et al., 2006). Figure 50.16A agrees with these general findings, but it shows an experiment that directly tested brain responses correlating with the act of punishment and not merely the desire to punish. These investigators (de Quervain et al., 2004) used PET imaging and an ultimatum game to probe directly neural responses associ-

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FIGURE 50.14 Separable neural responses for reward prediction error and fictive error. The fictive error signal (Figs. 50.12, 50.13) and the experiential error signal (version of a temporal difference [TD] error signal) are sometimes colinear and must be mathematically separated. This figure shows those activations (at the prescribed statistical threshold) associated with the TD error alone, the fictive error

ated with monetary punishment of an unfair player. The results showed a clear activation in dorsal striatum of male brains to punishment of another human who is perceived as “bad,” a defector that has abused trust in an exchange with another human.

FIGURE 50.15 Common currencies crossing domain boundaries: from fairness to pain. A two-part experiment showing how norm violation in one domain (deviation from fairness in a sequential prisoner’s dilemma game) is “credited” and paid for in another domain

alone, and both. The fictive error is computed as explained in Figure 50.13. At each decision, the experiential error is taken as the differ∼ ence between the z-scored bet b (proxy for expected value of return) ∼ and the actual return b rt. Here, rt is the market as defined in Figure 50.13 (relative fractional change in the price; adapted from Lohrenz et al., 2007; also see Montague et al., 2006; Chiu et al., 2008).

Valuation Diseases The reinforcement learning models of reward processing in the brain are clearly incomplete and oversimplified. Two things are clear from single unit recordings in DA neurons in the midbrain: (1) they are capable of

(experience of pain) (Singer et al., 2006). (A, B) After playing the economic game (a sequential prisoner’s dilemma game fairly or unfairly), the participants observed the confederates receiving a painful stimulus. (cont. on next page)

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50.15 (continued) (C) Males and females exhibited brain responses in empathy-related areas like the anterior cingulate cortex and frontal-insular cortex, both shown here (see Singer et al., 2006, for details). (D) Male brains demonstrated dramatically reduced empathyrelated responses when they viewed unfair players receiving pain but

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50.16 Reward responses and the punishment of norm violators. (A) In an ultimatum game where punishment is possible, the desire to punish activates caudate nucleus (PET experiment using O15 water; de Quervain et al., 2004). Activation in dorsal striatum of male brains to punishment of another human who is perceived as “bad”; a defector that has abused trust in an exchange with another human. This activation scaled with the participants’ desire to punish a perceived offender. These responses are consistent with these brains treating the punishment of a defector like a reward. (B) Correlation between the subjective desire for revenge (in male brains) toward an unfair player (in Fig. 50.15) and the nucleus accumbens (N. acc.) activation. PET: positron emission tomography.

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showed increased activation during this time in reward-related areas. These reward responses correlated with the males subjectively reported desire for revenge toward the players perceived as unfair (Fig. 50.16B).

encoding in their spike rate a reward prediction error signal for summed future reward (Montague et al., 1996; Schultz et al., 1997; reviewed in Schultz, 1998), and (2) they also communicate a host of other responses not related to this class of error signal (Schultz, 1998). We reviewed previously some of the evidence showing that the model was incomplete. Nevertheless, it has provided a way to understand error signals recorded in the striatum using fMRI across a wide array of task demands. In fact, a temporal difference reinforcement learning model has been applied by Redish (2004) to explain a number of features of drug addiction. The essence of that model is that drugs of abuse generate an unpredicted increase in DA that causes overvaluation of cues associated with drug taking. Cast this way, addiction becomes a valuation disease caused by drug-induced DA increases that cannot be learned by the underlying value function. The underlying value function grows without bound (Redish, 2004), which means that the value of drug-predicting cues grows without bound. Ironically, this RL perspective links drug addiction to movement disorders (for example, Parkinson’s disease) and might suggest novel treatment strategies or research approaches. In Parkinson’s disease, DA neurons are reduced to ∼10% of their normal number by some unknown set of pathological processes. The reward prediction errors generated by such a small number of DA neurons run into a serious signal-to-noise problem. Fluctuations in dopaminergic activity in these few remaining neurons produce an extremely noisy prediction error signal, which would be difficult for downstream neural targets to interpret— they would have difficulty inferring “real” fluctuations from the increased noise level in the few remaining cells.

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Consequently, it is difficult to read out differences in the values of the underlying state space—what this means practically is that all behavioral options or internal mental states would appear to have the same value as the current state. In this case, downstream decision-making mechanisms “see” that no other state is any more valuable than the current state, and they would naturally want to remain in that state. The most efficient choice to make is to freeze in the current state in the face of a flat value function. In this depiction, Parkinson’s disease becomes a kind of “rational freezing disease” under the influence of a very noisy DA-encoded prediction error system. So the RL framework, which gave us a way to understand the wide range of reward tasks in humans, also provides a new way to connect addiction and movement disorders under a common computational framework. We expect efforts along these lines to progress in neurology and psychiatry and would expect computational psychiatry and computational neurology to be reasonable subfields emerging in the coming years.

REFERENCES Asch, S.E. (1951) Effects of group pressure upon the modification and distortion of judgment. In: Guetzkow, H., ed. Groups, Leadership and Men. Pittsburgh, PA: Carnegie Press, pp. 177–190. Ashburner, J., and Friston, K.J. (1999) Nonlinear spatial normalization using basis functions. Hum. Brain Mapp. 7:254–266. Atick, J.J. (1992) Could information-theory provide an ecological theory of sensory processing? Network 3:213–251. Attwell, D., and Laughlin, S.B. (2001) An energy budget for signalling in the grey matter of the brain. J. Cereb. Blood Flow Metab. 21:1133–1145. Barlow, H.B. (1961) Possible principles underlying the transformation of sensory messages. In: Rosenblith, W., ed. Sensory Communication. Cambridge, MA: MIT Press, pp. 217–234. Barlow, H.B. (2001) Redundancy reduction revisited. Network: Computation in Neural Systems 12:241–253. Bayer, H.M., and Glimcher, P.W. (2005) Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron 47(1):129–141. Berg, J., Dickhaut, J., and McCabe, K. (1995) Trust, reciprocity, and social history. Games Econ. Behav. 10:122–142. Berns, G.S., Chappelow, J., Zink, C.F., Pagnoni, G., Martin-Skurski, M.E., and Richards, J. (2005) Neurobiological correlates of social conformity and independence during mental rotation. Biol. Psychiatry 58:245–253. Berns, G.S., McClure, S.M., Pagnoni, G., and Montague, P.R. (2001) Predictability modulates human brain response to reward. J. Neurosci. 21:2793–2798. Bialek, W. (1987) Physical limits to sensation and perception. Ann. Rev. Biophys. Biophys. Chem. 16:455–478. Breiter, H.C., Aharon, I., Kahneman, D., Dale, A., and Shizgal, P. (2001) Functional imaging of neural responses to expectancy and experience of monetary gains and losses. Neuron 30:619– 630. Breiter, H.C., Gollub, R.L., Weisskoff, R.M., Kennedy, D.N., Makris, N., Berke, J.D., et al. (1997) Acute effects of cocaine on human brain activity and emotion. Neuron 19:591–611. Camerer, C.F. (2003) Behavioral Game Theory. Princeton, NJ: Princeton University Press. Camerer, C.F., and Fehr, E. (2006) When does “economic” man dominate social behavior? Science 311:47–52.

Camerer, C.F., and Weigelt, K. (1988) Reputation and corporate strategy: a review of recent theory and applications. Strategic Management Journal 9:443–454. Chiu, P.H., Lohrenz, T.M., and Montague, P.R. (2008) Smokers’ brains compute but ignore a fictive error signal in a sequential investment game. Nat. Neurosci. 11:514–520. Damasio, A.R., Grabowski, T.J., Bechara, A., Damasio, H., Ponto, L.L., Parvizi, J., and Hichwa, R.D. (2000) Subcortical and cortical brain activity during the feeling of self-generated emotions. Nat. Neurosci. 3:2978–2986. Dani, J.A., and Montague, P.R. (2007) Disrupting addiction through the loss of drug-associated internal states. Nat. Neurosci. 10: 403–404. Daw, N.D., and Doya, K. (2006) The computational neurobiology of learning and reward. Curr. Opin. Neurobiol. 16(2):199– 204. Dayan, P. (1992) The convergence of TD (lambda) for general lambda. Machine Learn. 8:341–362. Dayan, P., and Abbott, L.F. (2001) Theoretical Neuroscience. Cambridge, MA: MIT Press. Dayan, P., and Balleine, B.W. (2002) Reward, motivation and reinforcement learning. Neuron 36:285–298. de Quervain, D.J., Fischbacher, U., Treyer, V., Schellhammer, M., Schnyder, U., et al. (2004) The neural basis of altruistic punishment. Science 305:1254–1258. Delgado, M.R., Frank, R.H., and Phelps, E.A. (2005) Perceptions of moral character modulate the neural systems of reward during the trust game. Nat. Neurosci. 8:1611–1618. Delgado, M.R., Nystrom, L.E., Fissell, C., Noll, D.C., and Fiez, J.A. (2000) Tracking the hemodynamic responses to reward and punishment in the striatum. J. Neurophysiol. 84:3072–3077. Egelman, D.M., Person, C., and Montague, P.R. (1998) A computational role for dopamine delivery in human decision-making. J. Cogn. Neurosci. 10:623–630. Elliott, R., Newman, J.L., Longe, O.A., and Deakin, J.F. (2003) Differential response patterns in the striatum and orbitofrontal cortex to financial reward in humans: a parametric functional magnetic resonance imaging study. J. Neurosci. 23(1):303–307. Fehr, E., and Schmidt, K.M. (1999) A theory of fairness, competition, and cooperation. Quarterly J. Econ. 114:817–868. Friston, K.J., Jezzard, P., and Turner, R. (1994) The analysis of functional MRI time-series. Hum. Brain Mapp. 1, 153–171. Guth, W., Schmittberger, R., and Schwarze, B. (1982) An experimental analysis of ultimatum bargaining. J. Econ. Behav. Organ. 3:367–388. Herrnstein, R.J., and Prelec, D. (1991) Melioration: a theory of distributed choice. J. Econ. Perspect. 5:137–156. Hyman, S.E., Malenka, R.C., and Nestler, E.J. (2006) Neural mechanisms of addiction: the role of reward-related learning and memory. Annu. Rev. Neurosci. 29:565–598. Ikemoto, S., and Panksepp, J. (1999) The role of nucleus accumbens dopamine in motivated behavior: a unifying interpretation with special reference to reward-seeking. Brain Res. Rev. 31:6–41. Kaelbling, L.P., Littman, M.L., and Moore, AW. (1996) Reinforcement learning: a survey. J. Artif. Intellig. Res. 4:237–285. Kakade, S., and Dayan, P. (2002) Dopamine: generalization and bonuses. Neural Networks 15: 549–559. Kamil, A.C., Krebs, J.R., and Pulliam, H.R. (1987) Foraging Behavior. New York: Plenum Press. King-Casas, B., Tomlin, D., Anen, C., Camerer, C.F., Quartz, S.R., and Montague, P.R. (2005) Getting to know you: reputation and trust in a two-person economic exchange. Science 308:78–83. Knutson, B., Fong, G.W., Adams, C.M., Varner, J.L., and Hommer, D. (2001) Dissociation of reward anticipation and outcome with event-related fMRI. Neuroreport 12:3683–3687. Knutson, B., Westdorp, A., Kaiser, E., and Hommer, D. (2000) FMRI visualization of brain activity during a monetary incentive delay task. NeuroImage 12:20–27.

50: BRAIN REWARD AND fMRI Krebs, J.R., Kacelnik, A., and Taylor, P. (1978) Tests of optimal sampling by foraging great tits. Nature 275:27–31. Lau, B., and Glimcher, P.W. (2005) Dynamic response-by-response models of matching behavior in rhesus monkeys. J. Exp. Anal. Behav. 84(3):555–579. Laughlin, S.B. (1994) Matching coding, circuits, cells, and molecules to signals. General principles of retinal design in the fly’s eye Prog. Retinal Eye Res. 13:165–196. Laughlin, S.B. (2001) Energy as a constract on the coding and processing of sensory information. Curr. Opin. Neurobiol. 11(4):475– 480. Laughlin, S.B. (2004) The implications of metabolic energy requirements in the representation of information in neurons. In: Gazzaniga, M.S., ed. The Cognitive Neurosciences III. Cambridge MA: MIT Press, pp. 187–196. Laughlin, S.B., de Ruyter van Stevenick, R.R., and Anderson, J.C. (1998) The metabolic cost of neural information. Nat. Neurosci. 1(1):36–41. Levy, W.B., and Baxter, R.A. (1996) Energy efficient neural codes. Neural Comp. 8(3):531–543. Li, J., McClure, S.M., King-Casas, B., and Montague, P.R. (2006) Policy adjustment in a dynamic economic game. PloS One, 1:e103. Ljungberg, T., Apicella, P., and Schultz, W. (1992) Responses of monkey dopamine neurons during learning of behavioral reactions. J. Neurophysiol. 67(1):145–163. Lohrenz, T., McCabe, K., Camerer, C.F., and Montague, P.R. (2007) Neural signature of fictive learning signals in a sequential investment task. Proc. Natl. Acad. Sci. USA 104:9493–9498. McClure, S.M., Berns, G.S., and Montague, P.R. (2003) Temporal prediction activates human striatum. Neuron 38:339–346. McClure, S.M., Daw, N., and Montague, P.R. (2003) A computational substrate for incentive salience. Trends Neurosci. 26(8): 423–428. Miller, E.K., and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annu. Rev. Neurosci. 24:167–202. Montague, P.R. (2006) Why Choose This Book? New York: Penguin Group. Montague, P.R. (2007) Neuroeconomics: A view from neuroscience. Functional Neurology 22(4):219–234. Montague, P.R., and Berns, G.S. (2002) Neural economics and the biological substrates of valuation. Neuron 36:265–284. Montague, P.R., Berns, G.S., Cohen, J.D., McClure, S.M., Pagnoni, G., et al. (2002) Hyperscanning: simultaneous fMRI during linked social interactions. NeuroImage 16(4):1159–1164. Montague, P.R., Dayan, P., Nowlan, S.J., Pouget, A., and Sejnowski, T.J. (1993) Using aperiodic reinforcement for directed self-organization. Adv. Neural Info. Proc. Systems 5:969–976. Montague, P.R., Dayan, P., Person, C., and Sejnowski, T.J. (1995) Bee foraging in uncertain environments using predictive Hebbian learning. Nature 377:725–728. Montague, P.R., Dayan, P., and Sejnowski, T.J. (1996) A framework for mesencephalic dopamine systems based on predictive Hebbian learning. J. Neurosci. 16(5):1936–1947. Montague, P.R., Dayan, P., and Sejnowski, T.J. (1994) Foraging in an uncertain environment using predictive Hebbian learning. Adv. Neural Info. Proc. Systems 6:598–605. Montague, P.R., Hyman, S.E., and Cohen, J.D. (2004) Computational roles for dopamine in behavioural control. Nature 431: 760–767. Montague, P.R., King-Casas, B., and Cohen, J.D. (2006) Imaging valuation models in human choice. Annu. Rev. Neurosci. 29:417– 448. Montague, P.R., McClure, S.M., Baldwin, P.R., Phillips, P.E.M., Budygin, E.A., et al. (2004) Dynamic gain control of dopamine delivery in freely moving animals. J. Neurosci. 24(7):1754–1759. Montague, P.R., and Sejnowksi, T.J. (1994) The predictive brain: temporal coincidence and temporal order in synaptic learning mechanims. Learn. Memory 1(1):1–33.

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Morris, G., Arkadir, D., Nevet, A., Vaadia, E., and Bergman, H. (2004) Coincident but distinct messages of midbrain dopamine and striatal tonically active neurons. Neuron 43(1):133–143. Morris, G., Nevet, A., Arkadir, D., Vaadia, E., and Bergman, H. (2006) Midbrain dopamine neurons encode decisions for future action. Nat. Neurosci. 9(8):1057–1063. Naqvi, N.H., Rudrauf, D., Damasio, H., and Bechara, A. (2007) Damage to the insula disrupts addiction to cigarette smoking. Science 315:531–534. O’Doherty, J.P. (2004) Reward representations and reward-related learning in the human brain: insights from neuroimaging. Curr. Opin. Neurobiol. 14(6):769–776. O’Doherty, J.P., Dayan, P., Friston, K., Critchley, H., and Dolan, R.J. (2003) Temporal difference models and reward related learning in the human brain. Neuron 38:329–337. O’Doherty, J.P., Dayan, P., Schultz, J., Deichmann, R., Friston, K., and Dolan, R.J. (2004) Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science 304:452–454. O’Doherty, J.P., Deichmann, R., Critchley, H.D., and Dolan, R.J. (2002) Neural responses during anticipation of a primary taste reward. Neuron 33(5):815–826. O’Reilly, R.C., Braver, T.S., and Cohen, J.D. (1999) A biologicallybased neural network model of working memory. In: Miyake, A., and Shah, P., eds., Models of Working Memory: Mechanisms of Active Maintenance and Executive Control. New York: Cambridge University Press, pp. 375–411. O’Reilly, R.C., Noelle, D.C., Braver, T.S., and Cohen, J.D. (2002) Prefrontal cortex and dynamic categorization tasks: representational organization and neuromodulatory control. Cereb. Cortex 12:246–257. Phillips, M.L., Young, A.W., Senior, C., Brammer, M., Andrew, C., Calder, A.J., et al. (1997) A specific neural substrate for perceiving facial expressions of disgust. Nature 389:495–498. Quartz, S., Dayan, P., Montague, P.R., and Sejnowski, T. (1992) Expectation learning in the brain using diffuse ascending connections. Soc. Neurosci. Abst. 18:1210. Redgrave, P., and Gurney, K. (2006) The short-latency dopamine signal: a role in discovering novel actions? Nat. Rev. Neurosci. 7: 967–975. Redgrave, P., Prescott, T.J., and Gurney, K. (1999) Is the short-latency dopamine response too short to signal reward error? Trends Neurosci. 22:146–151. Redish, A.D. (2004) Addiction as a computational process gone awry. Science 306:1944–1947. Rilling, J.K., Gutman, D.A., Zeh, T.R., Pagnoni, G., Berns, G.S., and Kilts, C.D. (2002) A neural basis for social cooperation. Neuron 35:395–405. Rilling, J.K., Sanfey, A.G., Aronson, J.A., Nystrom, L.E., and Cohen, J.D. (2004a) The neural correlates of theory of mind within interpersonal interactions. NeuroImage 22:1694–1703. Rilling, J.K., Sanfey, A.G., Aronson, J.A., Nystrom, L.E., and Cohen, J.D. (2004b) Opposing BOLD responses to reciprocated and unreciprocated altruism in putative reward pathways. Neuroreport 15:2539–2543. Ruderman, D.L. (1994) The statistics of natural images. Network 5:517–548. Sanfey, A.G., Loewenstein, G., McClure, S.M., and Cohen, J.D. (2006) Neuroeconomics: cross-currents in research on decision-making. Trends Cog. Sci. 10(3):108–116. Sanfey, A.G., Rilling, J.K., Aronson, J.A., Nystrom, L.E., and Cohen, J.D. (2003) The neural basis of economic decision-making in the Ultimatum Game. Science 300:1755–1758. Schultz, W., and Dickinson, A. (2000) Neuronal coding of prediction errors. Annu. Rev. Neurosci. 23:473–500. Schultz, W. (1998) Predictive reward signal of dopamine neurons. J. Neurophysiol., 80:1–27. Schultz, W. (2007) Multiple dopamine functions at different time courses. Annu. Rev. Neurosci. 30:259–288.

866

SUBSTANCE ABUSE DISORDERS

Schultz, W., Dayan, P., and Montague, P.R. (1997) A neural substrate of prediction and reward. Science 275:1593–1599. Simoncelli, E., and Olshausen, B.A. (2001) Natural image statistics and neural representation Annu. Rev. Neurosci. 24:1193–1215. Singer, R., Seymour, B., O’Doherty, J., Kaube, H., Dolan, R.J., and Frith, C.D. (2004) Empathy for pain involves the affective but not sensory components of pain. Science 303:1157–1162. Singer, T., Seymour, B., O’Doherty, J.P., Stephan, K.E., Dolan, R.J., and Frith, C.D. (2006) Empathic neural responses are modulated by the perceived fairness of others. Nature 439:466–469. Smith, J.M. (1982) Evolution and the Theory of Games. Cambridge, UK: Cambridge University Press. Sutton, R.S., and Barto, A.G. (1998) Reinforcement Learning. Cambridge, MA: MIT Press.

Thut, G., Schultz, W., Roelcke, U., Nienhusmeier, M., Missimer, J., Maguire, R.P., and Leenders, K.L. (1997) Activation of the human brain by monetary reward. Neuroreport 8:1225–1228. Tobler, P.N., Fiorillo, C.D., and Schultz, W. (2005) Adaptive coding of reward value by dopamine neurons. Science 307:1642–1645. Tomlin, D., Kayali, M.A., King-Casas, B., Anen, C., Camerer, C.F., Quartz, S.R., and Montague, P.R. (2006) Agent-specific responses in the cingulate cortex during economic exchanges. Science 312: 1047–1050. Waelti, P., Dickinson, A., and Schultz, W. (2001) Dopamine responses comply with basic assumptions of formal learning theory. Nature 412:43–48. Wickens, J. (1993) A Theory of the Striatum. Oxford, UK: Pergamon Press.

51 Principles of the Pharmacotherapy of Addictive Disorders CHARLES P. O’BRIEN

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The modern definition of addiction emphasizes uncontrolled drug use rather than tolerance and physical dependence as essential features of the disorder. It is generally recognized that addiction has strong hereditary influences and, once established, behaves as a chronic brain disorder with relapses and remissions over the long term (McLellan et al., 2000). Tolerance, a finding commonly present in addiction, is produced by homeostatic neuroadaptations to repeated drug exposure that diminish the pharmacological response (American Psychiatric Association [APA], 1994). Physical dependence is a state manifested by withdrawal symptoms that occur when drug taking is terminated or significantly reduced and reflects a “rebound” in unopposed neuroadaptations to repeated drug exposure. Thus, withdrawal symptoms are generally opposite in direction to initial drug effects (O’Brien, 2005b). It is important to note that tolerance and withdrawal symptoms occur commonly among patients who are not addicted, especially those treated for chronic pain, and who are treated with any of the common medications to which the body adapts. These include medications for high blood pressure, anxiety, depression, and pain. Indeed, the fear of producing addiction leads to the undertreatment of pain (Stalnikowicz et al., 2005) and needless suffering despite the availability of effective pain medication (Foley, 1997). Neuroimaging studies in human patients and findings from animal models of addiction suggest that more persistent neuroadaptations contribute other features of addiction, including craving, loss of control, and even denial. Addictive agents produce euphoria by acutely activating brain reward pathways that have evolved to ensure survival, which largely explains the compelling nature of drug reward. Repeated exposure to addictive agents disrupts neurotransmitter systems (Dackis and O’Brien, 2005b), alters gene expression (Nestler, 2004), and even distorts neuronal morphology in reward-related brain regions (Robinson and Kolb, 2004), suggesting that these agents chronically dysregulate reward pathways. With active drug use, euphoria alternates with

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craving to establish a cycle of addiction that becomes increasingly entrenched and uncontrollable, despite medical and psychosocial hazards. Craving can be precipitated by environmental cues, stress, and exposure to a small dose of the addictive agent. Cue-induced craving has been associated with limbic activation in a large number of human neuroimaging studies utilizing positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) (Dackis and O’Brien, 2005b), and this pernicious and persistent phenomenon might be reversed by agents that dampen limbic activation. Human neuroimaging studies also demonstrate reductions in frontal metabolism with stimulant, opioid, and alcohol dependence, whereas animal studies indicate that chronic exposure to several addictive agents (for example, opioids, stimulants, nicotine) dysregulates reward function (Koob et al., 2004). These findings support a biological basis for addiction and are guiding neuronal strategies that target specific clinical components of addiction. The clinical data fit best when addiction is considered to be a syndrome characterized by compulsive drugseeking behavior that impairs psychosocial functioning or damages health. Whereas initial drug use is voluntary, once addicted, the individual is beset by strong urges to continue or to resume drug taking. Even after detoxification and long periods of abstinence, relapse frequently occurs despite sincere efforts to avoid further drug use. People or situations previously associated with drug use elicit involuntary reactions and may provoke relapse (Wikler, 1973; O’Brien, 1975). The biological mechanisms for these apparently reflex patterns are suggested by data from animal models at the neurochemical level (Chapter 45) and the molecular level (Chapter 38). At the clinical level, conditioned cues (people, places, and things) produce intense craving through involuntary limbic activation, leading to self-destructive drug use even after long periods of abstinence. A key point for the clinician to realize is that the proneness to relapse is based on changes in brain function that continue for months or years after the last use of the

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drug. Of course, these changes in brain function interact with environmental factors such as social stress and situational triggers. If tolerance and withdrawal symptoms were the only elements of addictive illness, treatment would simply consist of detoxification, a process that allows the body to cleanse itself while receiving descending doses of a medication that reduces withdrawal symptoms (O’Brien, 2006). If drug taking does not resume, homeostatic mechanisms will gradually readapt to the absence of the drug (LeBlanc et al., 1969), and tolerance will be diminished or lost. We now know that detoxification is, at best, a first step in treatment and that simply achieving a drug-free state is not the most significant accomplishment. The more difficult aspect is prevention of relapse to drug-taking behavior. PRINCIPLES OF RELAPSE PREVENTION As our understanding of the chronic nature of addictive disorders improved, it became apparent that treatment should be based on a chronic disease model such as diabetes or asthma rather than an acute disease model such as pneumonia. Although the shift from an acute or short-term treatment model to a chronic model is still in progress, there is considerable resistance to this change (McLellan et al., 2000). There are two steps in addiction treatment: detoxification and prevention of relapse. In the United States, the health care system has traditionally paid for detoxification but not for longterm relapse prevention (Dackis and O’Brien, 2005b) that is essential to attaining a favorable clinical outcome. As a chronic disorder, addiction requires long-term treatment that is usually measured in months and years. The strategies for preventing relapse have traditionally involved counseling or psychotherapy, and more recently included pharmacotherapies that target clinical components of addictive illness. When psychiatric disorders co-occur with addiction, they must be treated concomitantly and preferably by the same treatment team. In this chapter, we focus on medication for the primary addictive disorder, but counseling and medication of comorbid disorders are equally important. This chapter focuses on the principles involved in pharmacotherapy, but the reader is referred to the extensive scientific literature on the evidence-based counseling procedures that should be employed along with medication (Volpicelli et al., 2001). By the time a person with an addiction presents for treatment, there are usually numerous complicating interpersonal, occupational, legal, and medical problems that affect the prognosis and clinical presentation. The typical patient evolves from drug user to abuser to dependent or addicted person over a period of years. During this time, it is common for social, occupational, fam-

ily, medical, and legal problems to develop. The Addiction Severity Index (McLellan et al., 1980; Cacciola et al., 2007) contains seven classes of variables that are assessed in a structured interview to obtain a severity rating. Those patients who rank at the severe level only on quantity of drugs used and not on other dimensions have a reasonably good prognosis. In contrast, those with severe psychosocial complications scoring high in the nondrug areas have a poor prognosis and are likely to relapse regardless of their level of drug use severity (Woody et al., 1984). MANAGEMENT OF COEXISTING MENTAL DISORDERS Psychiatric disorders commonly coexist with addictive disorders. These include anxiety disorders, psychotic disorders, and affective disorders such as depression. Although some of these dual diagnosis cases are simply a coincidental occurrence of common disorders, the overlap is greater than would be expected by chance based on population prevalence (Kessler et al., 1996). There are three kinds of possible relationships, and each probably occurs in different groups of drug users. A preexisting psychiatric disorder could increase the likelihood of initiating drug use as an attempt at self-medicating the psychiatric symptoms (Woody et al., 1974; Khantzian, 1985). Second, chronic drug taking could produce changes in the brain and in social interactions that predispose to the development of psychiatric disorders. This latter hypothesis is supported by the observation that many of the psychiatric symptoms associated with addictive disorders begin after the addictive process and resolve spontaneously after several weeks of abstinence from drugs of abuse (Schuckit et al., 1997). Finally, addictive and psychiatric illness may present together as independent disorders. Although substance-induced psychiatric disorders may resolve spontaneously with abstinence, independent psychiatric disorders must be stabilized with appropriate medications. DETOXIFICATION It is unfortunate that the majority of persons who are drug dependent are merely treated with detoxification and little or no long-term follow-up care. This is not logical, but it is a fact of the current health care system in the United States (McLellan et al., 2005). Detoxification is actually performed by the patient’s own metabolic processes. Thus, it can be accomplished voluntarily (although not necessarily safely) through sheer willpower by ceasing drug use or involuntarily when a person with an addiction is incarcerated or placed in a treatment program where access to drugs is denied. The

51: PRINCIPLES OF THE PHARMACOTHERAPY OF ADDICTIVE DISORDERS

withdrawal syndrome from opiate addiction can be very uncomfortable, but it is not life threatening unless the patient has preexisting medical problems. The symptoms consist of sweating, muscle aches, cramps, nausea, diarrhea, vomiting, tearing of the eyes, rhinorrhea, tremors, tachycardia, and other signs of autonomic nervous system hyperactivity. The discomfort has been compared to a bad case of the flu. Several sorts of treatment of these symptoms are available. Withdrawal from sedatives, alcohol, and stimulants is considered below. Replacing the drug of dependence or using another drug in the same category in gradually decreasing doses is a direct way to block withdrawal symptoms. As in all forms of detoxification, transfer from a short-acting drug such as heroin to a longer-acting drug such as methadone provides a smooth transition to the drug-free state. By appropriate dosing, detoxification can be achieved with minimal discomfort. A recent innovation for opiate dependence involves using the partial agonist buprenorphine as a transition to the drug-free state. The patient can be switched from dependence on heroin or methadone to buprenorphine, which is then stopped with few or no withdrawal symptoms. Buprenorphine was approved by the Food and Drug Administration (FDA) in 2002 as a treatment for opiate dependence. The same principles apply in the detoxification from nicotine dependence and from sedative (alcohol) dependence, except the untreated sedative withdrawal syndrome is much more dangerous than that of opiates or nicotine. Stimulant withdrawal has not traditionally been treated by detoxification regimens, even though it is associated with poor clinical outcome. In the treatment of patients dependent on alcohol or other sedatives, appropriate detoxification is critical because the sedative withdrawal syndrome is potentially life threatening. Whereas the acute administration of alcohol and sedatives increases γ -aminobutyric acid (GABA) and decreases glutamate pathways, the reverse occurs with chronic exposure, producing a GABA-deficiency state and glutamate hyperactivity that increases the risk of seizures during withdrawal (Dackis and O’Brien, 2003). There is evidence that sensitization to alcohol withdrawal symptoms occurs, so repeated withdrawals become progressively more severe while the treatment of withdrawal symptoms may retard the sensitization process (Brown et al., 1988). Benzodiazepines effectively suppress the withdrawal syndrome, and with proper attention to electrolytes and vitamins, the vast majority of patients can be safely eased into the alcohol-abstinent state in preparation for a long-term rehabilitation program. Symptoms of nicotine withdrawal can be diminished by nicotine replacement therapy including chewing gum, patch, or nasal spray. Nicotine gum and nicotine patch do not achieve the peak plasma levels seen with cigarettes, and thus they do not produce the same magnitude

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of nicotine’s subjective effects. Comparisons with placebo treatment show large benefits for nicotine replacement at 6 weeks, but the effect diminishes with time. The withdrawal syndrome from stimulants such as cocaine and amphetamine consists of hypersomnia, hyperphagia, bradycardia, and a number of depressive symptoms that usually resolve over several days. Interestingly, cocaine withdrawal symptoms appear to be predictive of treatment outcome. Kampman and colleagues (2002) measured cocaine withdrawal symptoms in several trials using the Cocaine Selective Severity Assessment. They found that more withdrawal symptoms in patients at the start of treatment accurately predicted their poorer outcome following treatment. Given these findings, the pharmacological reversal of cocaine withdrawal symptoms with agents like modafinil may improve clinical outcome (Dackis, 2005). Patients with heavy marijuana use also develop a physical dependence and may present for treatment when they are unable to stop daily use on their own (Haney, 2005). The symptoms consist of irritability, anxiety, marijuana craving, decreased quality and quantity of sleep, and decreased food intake. Various medications have been tried to alleviate these symptoms, and some clinicians have reported success with dronabinol, the oral form of delta 9 tetra hydro cannabinol, but clinical trials are absent (Haney et al., 2004). Detoxification by Suppression of Autonomic Hyperactivity For opiate detoxification, methadone is not always available due to legal limitations, and buprenorphine may be undesirable because it is an opiate partial agonist. Clonidine, a nonopiate that reverses opiate withdrawal, is an alternative option in these instances. Lofexidine, a similar medication, is currently in clinical trials as an aid to opiate detoxification. These a 2 agonists act as autoreceptors and produce presynaptic inhibition of locus coeruleus activity, effectively reducing the large adrenergic component of opioid withdrawal (Gerra et al., 2001). Thus, clonidine and lofexidine have found a place in the clinic for treating the symptoms of opioid withdrawal. Rapid Detoxification for Opiate Addiction Because persons who are opiate addicts are often afraid to detoxify, there have been efforts to make the process more rapid and less frightening so as to improve the transition to the protection of an opiate antagonist. These efforts began in the 1980s and progressed to the present fad of rapid detoxification while under general anesthesia. A mixture of medications that is typically kept confidential as a “trade secret” is used, but the known commonalities are as follows: After induction

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of general anesthesia, detoxification is precipitated by an opiate antagonist such as naloxone or naltrexone or a combination of the two; opiates are displaced from their receptors and metabolized, but the patient is not aware of withdrawal symptoms while anesthetized; in some cases, naltrexone may be implanted subcutaneously (L. Gooberman, personal communication, Seminar at University of Pennsylvania, 4/12/97) to prevent relapse to opiate use for varying periods of time after the procedure. The patient is awakened after 6–8 hours and is considered detoxified. This procedure is expensive and carries the risks of general anesthesia. A randomized controlled comparison of rapid detoxification under anesthesia versus buprenorphine detoxification was conducted, and there was no apparent advantage for the procedure under anesthesia (Collins et al., 2005). At this time, there is no evidence that speed of detoxification has any long-term advantage over the usual procedure over several days. Whatever the method, relapse after detoxification is very common. MEDICATIONS FOR PREVENTION OF RELAPSE The treatment of patients with an addiction must always be individualized. This requires a complete evaluation so that coexisting medical, psychiatric, and social problems can be addressed as needed. There are, however, common elements to treatment programs. Treatments for addictive disorders may begin with detoxification, but the key to successful treatment is long-term prevention of relapse by behavioral and pharmacological means. Usually these approaches should be combined, but the insistence on behavioral treatment alone and the avoidance of medication remain a significant weakness in many treatment programs. The types of medication that have shown efficacy in combination with behavioral therapy in the prevention of relapse can be classified as agonists (including partial agonists), antagonists, and anticraving medications that work through a variety of mechanisms. Vaccines are an experimental approach that is currently being evaluated in clinical trials (Sofuoglu and Kosten, 2006). Agonists and Partial Agonists The first use of an agonist for the treatment of addiction was reported by Vincent Dole (Dole and Nyswander, 1965), who demonstrated that daily methadone treatment could transform the behavior of patients with an opiate addiction. Opiates, which are derivates of the opium poppy, and opioids, which may be peptides or synthetic compounds, activate opiate receptors that are located throughout the nervous system as well as in the endocrine, cardiovascular, gastrointestinal, and other systems of the body. The behavioral effects of opiates

include intense euphoria and calming. The user becomes satisfied and relaxed, a state quite different from the euphoric excitement produced by stimulants. Among the other effects of opiates is the activation of an endogenous pain control system, so a person in severe pain experiences relaxation and relief of severe pain. Although opiates produce prompt physical dependence with repeated use, addiction seldom occurs in patients receiving opiates and opioids for relief of pain (Adams et al., 2006). Of course, prescription opiates and opioids can be abused, and it is the responsibility of the physician to provide humane pain relief to patients in need while exercising caution to reduce the likelihood that the prescribed medication will be obtained by deliberate abusers. The use of heroin or other opiates purchased on the street for the purpose of obtaining a “high” has a significant risk of producing addiction. Currently, it is estimated that there are over one million heroin and other opiate addicts in the United States, and the purity of heroin sold on the street is at an historic high. Much is known about the mechanisms involved in opiate dependence, resulting in a wider variety of effective medications than are found for other types of addiction. Detoxification is not applicable for those patients who are opioid dependent who prefer maintenance using methadone or buprenorphine (Kreek, 1992). In the mid1960s, Dole and Nyswander (1965) found that methadone given in a level dose could be used to stabilize patients who were addicted to opiates, block withdrawal symptoms, and reduce or eliminate the craving for heroin. This discovery opened the way for the medical treatment of addictive disorders (Dole and Nyswander, 1965). Methadone has a slow onset by the oral route. It is a long-acting mu-opiate receptor agonist that largely prevents reward or euphoria if the patient “slips” and takes a dose of an opiate. The mechanism for preventing euphoria is based on cross-tolerance in which tolerance (insensitivity) acquired by the use of one drug in a category conveys tolerance to all drugs in that category. Of course, the maintenance dose of methadone must be adjusted to the purity of heroin on the street. A dose of heroin significantly higher in opioid equivalents than the maintenance dose of methadone would override the cross-tolerance effect. Patients can be maintained for many years on a properly adjusted dose of methadone. Craving for opioids is diminished or absent, and patients are able to engage in constructive activities. Cognition and alertness are not impaired, and complex tasks including higher education can be accomplished (Kreek, 1992). Currently, about 200,000 people formerly addicted to illegal opioids are being maintained on methadone in the United States. Those with significant psychosocial problems require counseling or psychotherapy in addition to the medication. A major change in the treatment of opiate addiction in the United States came in 2000, when legislation was

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enacted that made it possible to treat persons with an addiction to opiates in a doctor’s office rather than requiring a specialized methadone clinic. The medication that was intended for this treatment is buprenorphine. This medication is a partial agonist at the mu receptor and an antagonist at kappa receptors (Bickel and Amass, 1995). As a partial agonist, buprenorphine produces limited opiate effects, and thus overdose is rare. Because of its affinity for the mu receptor, buprenorphine effectively prevents the effects of other opiates and opioids, thus reducing the likelihood that heroin will be used. Patients treated with buprenorphine become dependent on it, as with methadone and levo-alpha-acetylmethadyl (LAAM), but the withdrawal symptoms from buprenorphine are quite mild. A limitation of buprenorphine is the ceiling on opiate agonist effects giving a maximal efficacy of about 40–50 mg of methadone. Persons with an addiction using large doses of street heroin may find that buprenorphine is not sufficiently potent to block withdrawal or drug craving. After 2 years of debate over how many restrictions to place on the prescribing of this medication, buprenorphine was approved in 2002 as a Schedule III opioid. Prescribing is limited to physicians who take extra training and obtain certification. The rules initially limited doctors to no more than 30 patients per physician. Recently, the limit was raised to 100 because experience and monitoring over the past 4 years has found very little abuse. An important reason may be the fact that buprenorphine is marketed in combination with the opiate antagonist naloxone in a 4:1 ratio of buprenorphine to naloxone. When the medication is taken sublingually, the naloxone is poorly absorbed, and the agonist effects of buprenorphine are not blocked. If a person who wishes to obtain euphoria injects the combination either intravenously or intramuscularly, the naloxone acts as a powerful antagonist, blocking the mu-opioid effects and producing minimal desirable effects, possibly even mild withdrawal, depending on the prior state of the patient (Mendelson et al., 1999). Another approved opiate agonist that can be used for maintenance is LAAM. This drug has long-acting metabolites that block withdrawal and craving for over 72 hours, and it need be taken only 2 to 3 times per week. Use of LAAM is now a second-line therapy due to the finding of prolonged QT interval corrected (QTc) on cardiograms and the risk of serious cardiac rhythm abnormalities (Marsch et al., 2005). A similar agonist principle is the use of nicotine replacement therapy in the treatment of tobacco use disorder. The administration of nicotine as a patch, gum, or nasal spray can replace the nicotine received through smoking, thus blocking withdrawal symptoms. The nicotine can be stopped after 1 to 2 weeks without discomfort, although craving may return. The nicotine can be continued as a maintenance for extended

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periods, as is the case with methadone. The levels obtained via a nicotine patch usually do not produce the pleasant responses achieved through smoking, and there are usually no withdrawal symptoms on stopping the patch. Theoretically, smokers should be able to switch their nicotine dependence from administration via smoking to nicotine delivered by patch, chewing gum, or nasal spray. Although some smokers continue to chew nicotine gum for many months after giving up cigarettes, most stop nicotine replacement after a few weeks. The tendency to relapse may be strong, and thus it is important to teach patients behavioral techniques to resist the urge to smoke. An interesting combination that showed some efficacy in clinical trials is the combination of nicotine and mecamylamine to prevent relapse to smoking. It was hypothesized that stimulation of receptors by an agonist and an antagonist would be more effective, and the side effects of the two drugs would tend to cancel each other out (Rose et al., 2001). The clinical data on this combination have been mixed, and more studies are needed. A very recent medication that applies the partial agonist principle in the treatment of tobacco use disorder is varenicline (Foulds, 2006). This is an α4 β2 nicotinic receptor partial agonist that has been reported to relieve cigarette craving and to result in a significantly higher rate of abstinence at 52 weeks (23%) than placebo (10.3%) or bupropion (14.6%) in company-sponsored doubleblind trials (Jorenby et al., 2006). Although agonist treatment is effective in opioid and nicotine addiction, agonists have not been found effective in patients addicted to stimulants. Experiments using methylphenidate or dextro-amphetamine as agonists for cocaine and methamphetamine addiction have not been successful (Gorelick et al., 2004). Similarly, benzodiazepine treatment for alcohol or sedative dependence is ineffective. It is unclear why agonist treatment does not work in patients addicted to these substances. The pharmacological reversal of clinically significant neuroadaptations has long been employed with detoxification regimens, and the normalization of more persistent neuroadaptations might identify agents with anticraving action (O’Brien, 2005a). In addition to chronic neuroadaptations in reward-related pathways, prefrontal cortical dysregulation has been demonstrated in stimulant, opioid, and alcohol dependence (Dackis and O’Brien, 2005a) and is now viewed as a core component of addiction that contributes to poor impulse control, reduced motivation, and denial in individuals with an addiction (Dackis and O’Brien, 2005a). Consequently, agents that enhance prefrontal cortical metabolism hold promise in the treatment of addiction. Antagonist Treatment Advances in understanding how opioids interact with opiate receptors to produce their pharmacological effects

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led to the development of specific antagonists that have high affinity for these receptors but do not activate the chain of cellular events producing opioid drug effects. Naltrexone is an antagonist that has great affinity for mu-opiate receptors and significant but less affinity for delta and kappa opiate receptors. Unlike methadone, it has no agonist effects, so there are no opioid calming or other subjective effects. When first introduced, naltrexone was thought to be an ideal medication for heroin addiction because it occupied opiate receptors and blocked the effects of subsequent heroin injections. Experience has shown that most persons addicted to heroin prefer methadone because it provides mild opioid-reinforcing effects that are absent in naltrexone. Thus, naltrexone has been used very little except for white-collar individuals with an addiction to opiates such as physicians, nurses, and individuals with a history of opioid addiction recently released from prison on probation (Cornish et al., 1997). The effects of blocking opiate receptors probably depend on the degree of tonic activation of the endogenous opioid system. Some normal volunteers given naltrexone experience nausea and dysphoria, while others experience no reaction. Although long-term blockade of opiate receptors might be expected to produce impairment of neuroendocrine function, remarkably few effects have been noted even in patients who have taken naltrexone daily for several years. In 2006, a slow-release (depot) injectable preparation of naltrexone was given FDA approval and made available for prescription. Paradoxically, it was approved only for alcoholism because it was discovered in animal models that alcohol activated endogenous opioids (Altshuler et al., 1980), and blocking opiate receptors with naltrexone was found to improve treatment for alcoholism (Volpicelli et al., 1990; Volpicelli et al., 1992). Of course, the depot form of naltrexone is also effective for the treatment of opioid addiction (Comer et al., 2006), and clinical trials are under way that will eventually lead to FDA approval for that indication in addition to alcoholism. Thus, opiate receptor antagonists have been found to be effective in the treatment of opiate addiction and alcoholism. The availability of a depot form is expected to significantly improve the adherence to medication for this treatment method. Response to naltrexone is similar across all patients with an addiction to opiates because the medication blocks the site of major drug effect. For patients with an alcohol addiction, however, there is great variability. Some patients with an alcohol addiction report that alcohol stimulation is blocked and rehabilitation is greatly aided by the medication. Others report little or no effect. A recent development is the discovery of a functional variant in the mu-opiate receptor gene that is a main target of naltrexone. The variant is an A to G substitution at position 118 of Exon 1 and results in a receptor with reported greater affinity for beta endorphin

(Bond et al., 1998). Individuals with this allele have been found to perceive greater stimulation from a given dose of alcohol (Ray and Hutchison, 2004), and the stimulation was found to be blocked by naltrexone pretreatment (Ray, personal communication). A retrospective analysis of patients with an alcohol addiction in a naltrexone clinical trial found that those with the G allele did poorly when randomized to placebo but had a significantly better outcome when randomized to naltrexone (Oslin et al., 2003). This finding was replicated in another clinical trial (Anton et al., 2008) but not in a third (Gelernter et al., 2007). Blockade of Euphoria There are different mechanisms whereby medications can block or diminish the euphoria produced by drugs of abuse. Antagonist treatment prevents the addictive agent from effectively binding to brain receptors that mediate the euphoric response. This is best illustrated by naltrexone treatment in opiate dependence because the mechanism of opiate euphoria results from the stimulation of mu-opiate receptors. The mechanism of stimulant euphoria is not well understood, so it has been more difficult to develop medications to block this essential clinical phenomenon. An alternative means of diminishing drug euphoria involves the agonist approach. Opiate agonists block euphoria by cross tolerance. Thus, a steady dose of methadone not only satisfies the drive to obtain opiates but also produces cross tolerance to all other opiates and opioids. If a patient on methadone decides to try to get high anyway, an injection of heroin will result in little or no euphoria (Kreek, 1992). Levo-alpha-acetylmethadyl works in a similar fashion. Buprenorphine, as a partial agonist with very strong affinity for mu receptors, has both the cross-tolerance effect and a blocking effect as it deprives the injected opiate of access to mu receptors (Comer et al., 2005). Nicotine replacement therapy for smokers can reduce the pleasure of smoking by a cross-tolerance mechanism similar to that of methadone for heroin euphoria. Modafinil, a medication that retards sleep onset, has been shown to block cocaine-induced euphoria in three human laboratory studies of predominately male cocaine users (Dackis et al., 2003; Malcolm et al., 2006; Hart et al., 2008). The mechanism of this blockade is unknown. Other medications block cocaine reward in animal (but not yet reliably demonstrated in human) studies by increasing GABA inhibitory effects on reward pathways such as ventral tegmental–ventral striatal dopamine (DA) pathways. These include medications such as topiramate (Johnson et al., 2004; Kampman et al., 2004), vigabatrin (Brodie et al., 2005), and baclofen (Weerts et al., 2007). Animal models suggest that this GABA-enhancing mechanism may block the rewarding effects of other drugs as well as cocaine.

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Medications That Produce an Aversive Response Until 1995, disulfiram was the only medication available to prevent relapse to uncontrolled drinking in detoxified persons with an alcohol addiction. This medication blocks the metabolism of alcohol, causing the accumulation of acetaldehyde, a noxious by-product. The resulting acetaldehyde reaction is so unpleasant that it effectively prevents patients from consuming any alcohol. Disulfiram has a place in the pharmacopeia of medications for alcoholism, but its usefulness is limited. Despite treatment contracts and even legal coercion, most persons with an alcohol addiction will not take disulfiram regularly, and randomized clinical trials have not shown disulfiram to be efficacious (Fuller et al., 1986). Aversive conditioning has also been tried by timing an injection of emetine to produce vomiting while presenting the smell and taste of alcohol (Childress et al., 1985). Short-term success has been reported, but the technique has never become widespread. Anticraving Medications Acamprosate, a completely different medication that appears to decrease the desire for alcohol, was developed in Europe and has been available in the United States since 2004. Acamprosate appears to reduce the longlasting neuronal hyperexcitability that follows chronic alcohol use (Anton, O’Malley, et al., 2006). The mechanisms are unclear but may include alterations in glutamate receptor gene expression. This medication suppresses the intake of alcohol in rats and, as with naltrexone, activity in the animal model predicts clinical efficacy. In double-blind studies, acamprosate has been shown to increase the likelihood of continuous abstinence in patients with an alcohol addiction and to shorten the period of drinking if the patient “slips” and consumes some alcohol. The opiate receptor antagonist naltrexone has been reported in several clinical trials to reduce alcohol craving (O’Brien, 2005b) as well as alcohol reward. Human laboratory studies of alcohol priming in nontreatment seeking patients with an alcohol addiction demonstrated a reduction in alcohol craving and alcohol drinking in spite of the alcohol priming drink in participants who were not seeking treatment (O’Malley et al., 2002). Preclinical data have also shown an effect of alcohol on serotonergic systems. This has motivated trials using medications affecting that system. Ritanserin, a 5hydroxytryptamine-2 (5-HT2) receptor antagonist, was found to be no more effective than placebo in the treatment of alcoholism (Johnson et al., 1996). Ondansetron, a 5-HT3 antagonist, was found to reduce drinking in early-onset patients with an alcohol addiction alone (Johnson et al., 2000) and in combination with naltrexone (Ait-Daoud et al., 2001). Specific craving

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studies have not been addressed with the serotonergic medications. STIMULANT ADDICTION Stimulant use tends to occur in epidemics. In the United States, cocaine use peaked during 1985 with 8.6 million occasional users and 5.8 million regular users. More than 23 million Americans are estimated to have used cocaine at some time, but the number of current users declined steadily to 2.9 million in 1988 and further to 1.5 million in 1995. Lifetime prevalence rates peaked at 2.7% in 2002 (Volkow, 2004). Unfortunately, the number of frequent users (at least weekly) has remained steady since 1991 at about 600,000. The pharmacological effects of this drug in humans have been observed in the laboratory. Cocaine produces a dose-related increase in wakefulness, improved performance on tasks of vigilance and alertness, sexual arousal, and a sense of self-confidence and well-being. This is accompanied by increased heart rate and blood pressure. Higher doses produce a brief euphoria followed by a desire for more drug. Involuntary motor activity, stereotyped behavior, and paranoia may occur. Irritability, personality change, and increased risk of violence are found among heavy chronic users. The half-life of cocaine in plasma is about 50 minutes, but inhalant (crack) users typically desire more cocaine after 10 to 30 minutes. Intranasal and intravenous use also results in briefer euphoria than would be predicted by plasma cocaine levels, suggesting that a declining plasma concentration is associated with termination of the high and increased craving for cocaine. This theory is supported by PET imaging studies using 11C-labeled cocaine that show that the time course of subjective euphoria parallels the uptake and displacement of the drug in the corpus striatum (Chapter 49). Addiction is the most common complication of cocaine use although some users, especially those using intranasally, can continue intermittent use for years. Others become compulsive users despite elaborate methods to maintain control. Stimulants tend to be used much more irregularly than opiates, nicotine, and alcohol. Binge use is very common, and a binge may last for hours to days, terminating only when supplies of the drug are exhausted or when use is interrupted by behavioral toxicity such as hallucinations. Cocaine Sensitization Sensitization, a consistent finding in animal studies of cocaine and other stimulants, has not been clearly demonstrated in humans with an addiction to cocaine. Sensitization is typically measured by increased behavioral

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hyperactivity when the same dose is given daily to an animal. In human cocaine users, sensitization for euphoric effects of cocaine is not typically seen. To the contrary, some experienced users report requiring more cocaine over time to obtain euphoria, that is, tolerance. In the laboratory, tachyphylaxis (rapid tolerance) has been observed with reduced effects when the same dose was given repeatedly in one session. Because not all animals show behavioral sensitization to cocaine, and not all human cocaine users become addicted, it is possible that the failure to sensitize predisposes one to cocaine addiction. Sensitization in humans has been linked to paranoid, psychotic manifestations of cocaine use. This idea is based on the fact that binge-limited paranoia begins after long-term cocaine use (mean interval, 35 months) in vulnerable users (Satel and Edell, 1991). Thus, repeated administration may be required to sensitize the patient to experience paranoia. The phenomenon of kindling has also been invoked to explain cocaine sensitization. Subconvulsive doses of cocaine given repeatedly will eventually produce seizures in rats (Post et al., 1987). This observation has been compared to electrical kindling of seizures and may underlie the gradual development of paranoia. Cocaine users experience intense craving when exposed to cocaine-related cues, which typically include the neighborhood where they have used cocaine, the sight of cocaine, cocaine paraphernalia, and cash. This response has been measured in the laboratory when abstinent users of cocaine are shown video scenes associated with cocaine use (Ehrman et al., 1992). The conditioned response consists of physiological arousal and increased drug craving. Cue-induced craving is a pernicious phenomenon that leads directly to relapse in patients with an addiction, even after long periods of abstinence. Medications that block limbic activation in response to cocaine cues may prove effective against this pernicious phenomenon. Relapse prevention is usually the major challenge encountered by clinicians who treat patients with an addiction to cocaine. Effective rehabilitation programs use individual and group psychotherapy based on the principles of Alcoholics Anonymous and/or behavioral treatments such as those based on reinforcing cocaine-free urine tests using vouchers that can be exchanged for goods and services (Alterman and McLellan, 1993; Higgins et al., 1994). These programs produce improvement and varying periods of abstinence, but the risk of relapse remains after months or years of abstinence. Numerous studies have been conducted on medications that might aid in the rehabilitation of individuals with an addiction to cocaine. A detailed review would not be useful because most are no longer used. Among those medications still under study for possible approval

by the FDA as a treatment for stimulant addiction are modafinil (Dackis et al., 2005) and disulfiram (Carroll et al., 1998). Buprenorphine, a partial opioid agonist, has been found to reduce cocaine self-administration in monkeys (Mello et al., 1989), but studies in patients who were dependent upon cocaine have yielded mixed results. A recent controlled study of buprenorphine in a population of combined patients who were dependent on both opiates and cocaine showed a positive effect in reducing the use of cocaine and opiates (Montoya et al., 2004). The results were consistent with the hypothesis that buprenorphine is effect for cocaine only in higher doses, 16 mg or greater. Studies in animals have consistently shown that enhancement of GABA activity reduces cocaine selfadministration (Roberts et al., 1996). Preliminary results from clinical trials using baclofen, a GABA-B agonist, and topiramate, which activates GABA-A receptors, suggest that this approach may reduce cocaine use in humans as well (Shoptaw et al., 2003). Studies in patients with cocaine and methamphetamine addictions using vigabatrin, an inhibitor of GABA transaminase, are just beginning (Brodie et al., 2005). Another recent novel approach uses modafinil, a drug that produces alerting via a complex mechanism involving enhanced glutamate activity. A controlled study reported that modafinil-treated patients significantly reduced their use of cocaine when compared to placebotreated patients (Dackis et al., 2005). Modafinil is currently under intense investigation as a first-line treatment for cocaine dependence. Other Stimulants Amphetamine, dextroamphetamine, methamphetamine, phenmetrazine, methylphenidate, and diethylpropion all produce behavioral activation similar to that of cocaine. Amphetamines increase synaptic DA levels primarily by stimulating presynaptic DA release rather than by blockade of reuptake at the DA transporter, as is the case with cocaine. Intravenous or smoked methamphetamine is an important drug of abuse in the western half of the United States, and it produces an abuse/dependence syndrome similar to that of cocaine. Paranoid psychosis is more common with amphetamine abuse. In some sections, methamphetamine abuse has reached epidemic proportions, and there are intensive efforts to develop behavioral and medication treatments for this serious addiction (Rawson et al., 2000). A different picture arises when oral stimulants are prescribed in a weight reduction program. These drugs do reduce appetite and weight on a short-term basis, but the effects diminish over time as tolerance develops. In rodents, there is a rebound of appetite and weight

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gain when amphetamine use is stopped. In humans who are obese, weight loss after amphetamine treatment is usually temporary. Anorectic medications, therefore, are not considered to be a treatment for obesity by themselves, but rather a short-term adjunct to behavioral treatment programs. It is noteworthy that drug abuse manifested by drug-seeking behavior occurs in only a small proportion of patients given stimulants to facilitate weight reduction. Cannabinoids (Marijuana) Cannabis is a plant that has been cultivated for the production of hemp fiber and for presumed medicinal and psychoactive properties of the plant’s products. The smoke from burning cannabis contains 61 different cannabinoids, but virtually all of the psychoactive effects of smoked marijuana can be produced by one of them, Δ-9-tetrahydrocannabinol. In the United States, marijuana is the most commonly used illicit drug. Usage peaked during the late 1970s, when about 60% of high school seniors reported having used marijuana and about 10% reported daily use. Lifetime use declined to 40% and daily use to 2% in the mid-1990s, but 2005 data for 12th graders was 45% lifetime prevalence and for 29- to 30-year-olds, 60% lifetime prevalence (Johnston, 2006). The actions of cannabis in the brain are becoming better understood. A cannabinoid receptor has been identified (Devane et al., 1988) and cloned (Matsuda et al., 1990), and two subtypes have been identified. These receptors are widely dispersed throughout the brain and in certain other organs. High densities occur in the cerebral cortex, hippocampus, striatum, and cerebellum (Herkenham, 1993). An arachadonic acid derivative has been identified as an endogenous ligand and named anandamide (Devane et al., 1992). The effects of marijuana depend on the route of administration, the dose, the experience of the user, and the setting in which it is used. Changes in mood, perception, and motivation are reported by most users. The giddiness and relaxed feeling called a “high” lasts about 2 hours. During this time, there is impairment of cognitive functions, perception, reaction time, learning, and memory. Impairment of coordination and eye-tracking behavior has been reported to persist for several hours beyond the perception of a high. Anxiety reactions may occur, especially with higher doses and with oral rather than smoked marijuana. Although there is no convincing evidence that marijuana can produce a schizophrenic-like syndrome, there are numerous clinical reports that marijuana use can precipitate a relapse in patients recovering from a schizophrenic episode. Marijuana has also been reported to produce an amotivational syndrome. This is not an offi-

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cial diagnosis, but it has been used to describe individuals who withdraw from social activities and show little interest in school, work, or other goal-directed activity. When heavy marijuana use accompanies these symptoms, the drug is often cited as the cause. There are no data that demonstrate a causal relationship, although most authorities recommend that treatment of such patients include cessation of marijuana use. There is no evidence that marijuana damages brain cells or produces any permanent functional changes, and heavy marijuana users show gradual improvement in mental state after stopping its use. This is consistent with animal data indicating impairment of maze learning that persists for weeks after the last dose of the drug. Tolerance to the effects of marijuana has been demonstrated in humans and animals (Jones et al., 1981). Withdrawal symptoms and signs are not typically seen in clinical populations, but some patients report compulsive frequent marijuana use. In 2002, over 280,000 people entered treatment for cannabis dependence (National Institute on Drug Abuse, 2007). There is no specific treatment for marijuana dependence at this time, but cannabinoids receptor antagonists are logical candidates for investigation. The withdrawal syndrome does not require medication unless persistent signs of depression are present. Prevention of relapse is accomplished by behavioral treatments such as those used in the treatment of alcoholism or cocaine addiction (Stephens et al., 2002). Several beneficial effects of marijuana have been described. These include reduction of nausea, musclerelaxing effects, anticonvulsant effects, and reduction of intraocular tension for the treatment of glaucoma. There are also clinical reports asserting that marijuana stimulates appetite and reverses the muscle wasting seen in acquired immune deficiency syndrome and other conditions. When it is taken as a medication rather than as a recreational drug, the psychoactive effects are also present and may impair normal occupational functions. At present, there are insufficient data to claim that cannabinoids are superior to standard treatments, but some controlled studies are in progress. A major problem in assessing the medicinal use of smoked marijuana is the uncertain delivery of multiple substances and variable doses. With the cloning of cannabinoid receptors and the discovery of an endogenous ligand, it is hoped that derivatives of cannabinoids with medicinal uses will be developed. Hallucinogenic Drugs Drugs that primarily produce perceptual, thought, or mood disturbances at low doses, with minimal effects on memory and orientation, are classed as hallucinogenic drugs. Examples are lysergic acid diethylamide (LSD),

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phencyclidine (PCP), methylenedioxymethamphetamine (MMDA, “ecstasy”), and a variety of anticholinergic drugs (atropine, benztropine). Lysergic acid diethylamide was discovered in 1945, but experimental and recreational use peaked in the 1960s and 1970s and then declined. During the 1990s, use again increased. In 1993, 11.8% of college students reported some use of these drugs during their lifetime, and the increase was most striking in younger cohorts beginning in the eighth grade. Lysergic acid diethylamide is the most potent hallucinogenic drug, producing significant psychedelic effects with a total dose of as little as 25–50 mg. Thus, it is over 3,000 times more potent than mescaline. In humans, the effects of hallucinogenic drugs are variable even in the same individual at different times. In addition to the dose of the drug, individual variables and the setting in which the drug is given are important. At doses of 100 micrograms, LSD produces perceptual distortions and hallucinations; mood changes, including elation, paranoia, or depression; intense arousal; and sometimes a feeling of panic. Signs of LSD ingestion include pupillary dilation, increased blood pressure and pulse, flushing, salivation, lacrimation, and hyperreflexia. The user typically reports prominent visual effects. Colors seem more intense; shapes may appear altered, and the user may focus attention on unusual items such as the pattern of hairs on the back of his or her hand. Claims have been made about the potential of these drugs for enhancing psychotherapy and for treating addictions and other mental disorders. These claims have not been supported by controlled treatment outcome studies; thus, there is no current indication for these drugs as medications. Medical attention may be sought when an unpleasant reaction occurs. A “bad trip” usually consists of severe anxiety, although at times it is marked by intense depression and suicidal thoughts. The bad trip from LSD may be difficult to distinguish from reactions to anticholinergic drugs and PCP. There are no documented toxic fatalities from LSD use, but fatal accidents and suicides have occurred during or shortly after the trip. Prolonged psychotic reactions lasting 2 days or more may occur after the ingestion of a hallucinogen. Schizophrenic episodes may be precipitated in susceptible individuals, and there is some evidence that chronic use of these drugs is associated with the development of persistent psychotic disorders (McLellan et al., 1979). When a user is brought to the emergency room after a bad trip, the severe agitation can be ameliorated with benzodiazepines (that is, diazepam 20 mg orally) or simply “talked down” by reassurance. Neuroleptic medications (DA receptor antagonists) should be avoided as they may intensify the experience. A particularly trou-

bling aftereffect of the use of LSD and other similar drugs is the occurrence of episodic visual disturbances in a small proportion of former users. These are called flashbacks, and they resemble the experiences of prior LSD trips. There is now an official diagnostic category called the hallucinogen persisting perception disorder (HPPD) (APA, 1994). The symptoms include false fleeting perceptions in the peripheral fields, flashes of color, geometric pseudohallucinations, and positive afterimages (Abraham and Aldridge, 1993). The visual disorder appears stable in half of the cases and thus represents an apparently permanent alteration of the visual system. These symptoms may be precipitated by stress, fatigue, emergence into a dark environment, marijuana use, neuroleptic use, and anxiety states. Methylenedioxymethamphetamine Methylenedioxymethamphetamine (MDMA) and methylenedioxyamphetamine (MDA) are phenylethylamines that have stimulant as well as psychedelic effects. Known as “ecstasy,” MDMA in the past was recommended by some psychotherapists as an aid to gaining insight, although no data exist to support this contention. The drug became popular during the 1980s on some college campuses because of testimonials that it enhances selfknowledge. The acute effects are dose-dependent and include tachycardia, dry mouth, jaw clenching, muscle aches, and, at higher doses, visual hallucinations, agitation, hyperthermia, and panic attacks. Animal data showing degeneration of serotonergic nerve cells and axons have been reported (Ricaurte et al., 1985). In humans, cerebrospinal fluid of individuals with chronic MDMA use has been found to have low levels of serotonin metabolites, but brain studies similar to those reported in animals have not been done. Some residual effects have been reported (Bolla et al., 1998), and there is no evidence that the claimed benefits of MDMA actually occur. Phencyclidine Phencyclidine (PCP) is available throughout the United States through illicit channels. It was originally developed as an anesthetic in the 1950s but was abandoned because of a high frequency of postoperative delirium with hallucinations. It was classed as a dissociative anesthetic because, in the anesthetized state, the patients remain conscious, with staring gaze, flat facies, and rigid muscles. As little as 0.05 mg/kg produces emotional withdrawal, concrete thinking, and bizarre responses to projective psychological testing. The symptoms produced by PCP include catatonic posturing and resemble the symptoms of schizophrenia. Abusers taking higher doses may exhibit hostile or assaultive behavior. Anes-

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thetic effects increase with the dosage, and stupor or coma may occur with muscular rigidity, rhabdomyolysis, and hyperthermia. Patients who are intoxicated and in the emergency room may change quickly from aggressive behavior to coma, with elevated blood pressure and enlarged, nonreactive pupils. Phencyclidine binds with high affinity to sites located in the cortex and limbic structures, resulting in blocking of N-methyl-D-aspartic acid (NMDA)-type glutamate receptors. Lysergic acid diethylamide and other psychedelics do not bind to these receptors. There is evidence that NMDA receptors are involved in ischemic neuronal death caused by high levels of excitatory amino acids. Thus, there is interest in potentially therapeutic analogues of PCP that also block NMDA channels but with fewer psychotic effects. There are no specific treatments for hallucinogenic drug abuse. Patients frequently have to be admitted to the hospital because of brief psychotic episodes, but the most difficult aspect of treatment is the long-term prevention of relapse. Inhalants Anesthetic gases such as nitrous oxide or halothane are sometimes taken by medical personnel to produce a “high.” Nitrous oxide used in whipping cream canisters may be abused by food service employees. Nitrous oxide produces euphoria and analgesia followed by loss of consciousness. Compulsive use and chronic toxicity are rarely reported, but there are obvious risks of overdosage associated with the abuse of this anesthetic. Chemicals that are volatile at room temperature and produce abrupt changes in mental state when inhaled are abused by some groups in specific parts of the United States. Examples include toluene (from airplane glue), kerosene, gasoline, carbon tetrachloride, amyl nitrate, and nitrous oxide. Each substance has a characteristic pattern. Solvents such as toluene are typically used by children beginning at age 12. The child places the material in a plastic bag and inhales the vapors. After several minutes of inhalation, dizziness and intoxication occur. Aerosol sprays containing fluorocarbon propellants are used in a similar fashion. Prolonged exposure or daily use may result in damage to several organ systems. Clinical problems include cardiac arrhythmias, bone marrow depression, cerebral degeneration, and damage to liver, kidney, and peripheral nerves. Cardiac arrhythmias and death have occasionally been attributed to inhalant abuse. Amyl nitrate was used in the past for the treatment of angina because it produces dilation of smooth muscle and relieves coronary artery constriction. In recent years, amyl nitrate and butyl nitrate have been used to relax smooth muscle and enhance orgasm, particularly by male

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homosexuals. Sold as room deodorizers, these nitrates can produce the feeling of a “rush,” flushing, and dizziness. Adverse effects include palpitations, postural hypotension, and headache progressing to loss of consciousness.

DEVELOPMENTAL THERAPEUTICS The Vaccine Approach Immunization against the effects of an abused drug was first tested using morphine. Monkeys were immunized with morphine-6-hemisuccinate-BSA (bovine serum albumin), and the resultant morphine antibodies were found to reduce self-administration of heroin but not cocaine (Killian et al., 1978). Recently, active immunization with a new, stable cocaine conjugate has been found to suppress cocaine- but not amphetamineinduced locomotor activity and stereotyped behavior in rats (Rocio et al., 1995). Brain levels of cocaine were also lowered by the antibodies, and rats and mice were found to reduce intravenous cocaine self-administration after passive transfer of cocaine antibodies (Fox et al., 1996; Kantak et al., 2000). A clinical trial involving 34 patients showed that the vaccine caused few side effects and produced dose-related levels of antibodies (Kosten et al., 2002). Recent studies have shown further improvement in the vaccine, but additional studies involving dose-response relationships to clinical response are necessary (Martell et al., 2005). In spite of cocaine antibodies, relapse may still be possible by using a high dose of the drug or by taking a different stimulant.

CLOSING COMMENTS Medications that target discrete clinical phenomena of addiction, such as euphoria, withdrawal, and craving, are being developed as adjunctive treatments that may significantly improve clinical outcome. The development of these agents has been greatly facilitated by research revealing the underlying neuronal mechanisms of these phenomena. Although the many types of drug use disorders have common aspects, there are also many differences that must be specifically addressed with different pharmacological strategies. In addition, all patients require a full evaluation and tailored treatment plans that take their unique set of problems into account. It is especially important to identify and stabilize co-occurring medical and psychiatric disorders in the addicted population. Approved medications that target cardinal features of addiction are now available for some addictive disorders, and more will certainly be developed through continued research. When viewed in the context of chronic disease, the current treatments for addiction are

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quite successful (O’Brien and McLellan, 1996; McLellan et al., 2000). Long-term treatment is accompanied by improvements in physical status as well as in mental, social, and occupational functions. REFERENCES Abraham, H.D., and Aldridge, A. (1993) Adverse consequences of lysergic acid diethylamide. Addiction 88:1327. Adams, E.H., Breiner, S., Cicero, T.J., Geller, A., Inciardi, J.A., Schnoll, S.H., et al. (2006) A comparison of the abuse liability of tramadol, NSAIDs, and hydrocodone in patients with chronic pain. J. Pain Symptom Manage. 31:465–476. Ait-Daoud, N., Johnson, B.A., Javors, M., Roache, J.D., and Zanca, N.A. (2001) Combining ondansetron and naltrexone treats biological alcoholics: corroboration of self-reported drinking by serum carbohydrate deficient transferrin, a biomarker. Alcohol Clin. Exp. Res. 25:847–849. Alterman, A.I., and McLellan, A.T. (1993) Inpatient and day hospital treatment services for cocaine and alcohol dependence. J. Subst. Abuse Treat. 10:269–275. Altshuler, H.L., Phillips, P.A., and Feinhandler, D.A. (1980) Alteration of ethanol self-administration by naltrexone. Life Sci. 26: 679–688. American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Anton, R., Couper, D., Swift, R., Pettinati, H., Goldman, D., and Oraczi, G. (2008) An evaluation of the mu opiate receptor gene as a predictor of response to naltrexone in the treatment of alcoholism? Results from the COMBINE study. Arch. Gen. Psychiatry 65:135–144. Anton, R., O’Malley, S., Ciraulo, D., Cisler, R., Couper, D., Donovan, D., et al. (2006) Combined pharmacotherapies and behavioral interventions for alcohol dependence—The COMBINE Study: a randomized controlled trial. JAMA 295(17):2003–2007. Bickel, W.K., and Amass, L. (1995) Buprenorphine treatment of opioid dependence: a review. Exper. Clin. Psychopharmacol. 3(4): 477–489. Bolla, K., McCann, U., and Ricaurte, G. (1998): Memory impairment in abstinent MDMA (“ecstasy”) users. Neurology 51(6): 1532–1537. Bond, C., LaForge, K., Tian, M., Melia, D., Shengwen, Z., Borg, L., et al. (1998) Single-nucleotide polymorphism in the human mu opioid receptor gene alters b-endorphin binding and activity: Possible implications for opiate addiction. Proc. Natl. Acad. Sci. 95:9608–9613. Brodie, J.D., Figueroa, E., Laska, E.M., and Dewey, S.L. (2005) Safety and efficacy of gamma-vinyl GABA (GVG) for the treatment of methamphetamine and/or cocaine addiction. Synapse 55: 122–125. Brown, M.E., Anton, R.F., Malcolm, R., and Ballenger, J.C. (1988) Alcohol detoxification and withdrawal seizures: clinical support for a kindling hypothesis. Biol. Psychiatry 23:507–514. Cacciola, J.S., Alterman, A.I., McLellan, A.T., Lin, Y.T., Lynch, K.G. (2007) Initial evidence for the reliability and validity of a “Lite” version of the Addiction Severity Index. Drug Alcohol Depend. 87:297–302. Carroll, K.M., Nich, C., Ball, S.A., McCance, E., and Rounsavile, B.J. (1998) Treatment of cocaine and alcohol dependence with psychotherapy and disulfiram. Addiction 93:713–727. Childress, A.R., McLellan, A.T., and O’Brien, C.P. (1985) Behavioral therapies for substance abuse. Intl. J. Addictions 20(6&7): 947–969. Collins, E.D., Kleber, H.D., Whittington, R.A., and Heitler, N.E. (2005) Anesthesia-assisted vs buprenorphine- or clonidine-assisted

heroin detoxification and naltrexone induction: a randomized trial. JAMA 294:903–913. Comer, S.D., Sullivan, M.A., Yu, E., Rothenberg, J.L., Kleber, H.D., Kampman, K., et al. (2006) Injectable, sustained-release naltrexone for the treatment of opioid dependence: a randomized, placebo-controlled trial. Arch. Gen. Psychiatry 63:210–218. Comer, S.D., Walker, E.A., and Collins, E.D. (2005) Buprenorphine/ naloxone reduces the reinforcing and subjective effects of heroin in heroin-dependent volunteers. Psychopharmacology 181(4):664–675. Cornish, J.W., Metzger, D., Woody, G.E., Wilson, D., McLellan, A.T., Vandergrift, B., and O’Brien, C.P. (1997) Naltrexone pharmacotherapy for opioid dependent federal probationers. J. Subst. Abuse Treat. 14:529–534. Dackis, C.A. (2005) New treatments for cocaine abuse. Drug Discovery Today 2:79–86. Dackis, C.A., and O’Brien, C.P. (2003) The neurobiology of alcoholism. In: Gershon, S., and Soires, R., eds. Handbook of Psychiatric Disorders. New York: Marcel Dekker, pp. 563–580. Dackis, C., and O’Brien, C. (2005a) Neurobiology of addiction: treatment and public policy ramifications. Nat. Neurosci. 8:1431–1436. Dackis, C., and O’Brien, C. (2005b) Neurobiology of addiction: treatment and public policy ramifications (commentary). Nat. Neurosci. 8(11):1431–1436. Dackis, C.A., Kampman, K.M., Lynch, K.G., Pettinati, H.M., and O’Brien, C.P. (2005) A double-blind, placebo-controlled trial of modafinil for cocaine dependence. Neuropsychopharmacology 30:205–211. Dackis, C.A., Lynch, K.G., Yu, E., Samaha, F.F., Kampman, K.M., Cornish, J.W., et al. (2003) Modafinil and cocaine: a doubleblind, placebo-controlled drug interaction study. Drug Alcohol Depend. 70:29–37. Devane, W.A., Dysarz, F.A., Johnson, M.R., Melvin, L.S., and Howlett, A.C. (1988) Determination and characterization of a cannabinoid receptor in rat brain. Mol. Pharm. 34:605–613. Devane, W.A., Hanus, L., Breuer, A., Pertwee, R.G., Stevenson, L.A., Griffin, G., et al. (1992) Isolation and structure of a brain constituent that binds to the cannabinoid receptor. Science 258: 1946–1949. Dole, V.P., and Nyswander, M. (1965) A medical treatment for diacetylmorphine (heroin) addiction: a clinical trial with methadone hydrochloride. JAMA 193:80–84. Ehrman, R., Robbins, S., Childress, A.R., and O’Brien, C.P. (1992) Conditioned responses to cocaine-related stimuli in cocaine abuse patients. Psychopharmacology 107:523–529. Foley, K. (1997) Competent care for the dying instead of physicianassisted suicide. New Engl. J. Med. 336(1):54–58. Foulds, J. (2006) The neurobiological basis for partial agonist treatment of nicotine dependence: varenicline. Int. J. Clin. Pract. 60: 571–576. Fox, B.S., Kantak, K.M., Edwards, M.A., Black, K.M., Bollinger, B.K., Botka, A.J., et al. (1996) Efficacy of a therapeutic cocaine vaccine in rodent models [see comments]. Nat. Med. 2:1129–1132. Fuller, R.K., Branchey, L., Brightwell, D.R., Derman, R.M., Emrick, C.D., Iber, F.L., et al. (1986) Disulfiram treatment of alcoholism. A Veterans Administration cooperative study. JAMA 256: 1449–1455. Gelernter, J., Gueorguieva, R., Kranzler, H.R., Zhang, H., Cramer, J., Rosenheck, R., and Krystal, J.H. (2007) Opioid receptor gene (OPRM1, OPRK1, and OPRD1) variants and response to naltrexone treatment for alcohol dependence: results from the VA Cooperative Study. Alcohol Clin. Exp. Res. 31:555–563. Gerra, G., Zaimovic, A., Giusti, F., Di Gennaro, C., Zambelli, U., Gardini, S., and Delsignore, R. (2001) Lofexidine versus clonidine in rapid opiate detoxification. J. Subst. Abuse Treat. 21:11–17. Gorelick, D.A., Gardner, E.L., and Xi, Z.X. (2004) Agents in development for the management of cocaine abuse. Drugs 64: 1547–1573.

51: PRINCIPLES OF THE PHARMACOTHERAPY OF ADDICTIVE DISORDERS Haney, M. (2005) The marijuana withdrawal syndrome: diagnosis and treatment. Curr. Psychiatry Rep. 7:360–366. Haney, M., Hart, C.L., Vosburg, S.K., Nasser, J., Bennett, A., Zubaran, C., and Foltin, R.W. (2004) Marijuana withdrawal in humans: effects of oral THC or divalproex. Neuropsychopharmacology 29:158–170. Hart, C.L., Haney, M., Vosburg, S.K., Rubin, E., and Foltin, R.W. (2008) Smoked cocaine self-administration is decreased by modafinil. Neuropsychopharmacology 33:761–768. Herkenham, M.A. (1993) Localization of cannabinoid receptors in brain; relationship to motor and reward systems. Biological Basis of Substance Abuse 3:187–200. Higgins, S.T., Budney, A.J., Bickel, W.K., Badger, G.J., Foerg, F.E., and Ogden, D. (1994) Outpatient behavioral treatment for cocaine dependence: one-year outcome. Exp. Clin. Psychopharmacol. 3(2):205–212. Johnson, B.A., Ait-Daoud, N., Akhtar, F.Z., and Ma, J.Z. (2004) Oral topiramate reduces the consequences of drinking and improves the quality of life of alcohol-dependent individuals: a randomized controlled trial. Arch. Gen. Psychiatry 61:905–912. Johnson, B.A., Jasinski, D.R., Galloway, G.P., Kranzler, H., Weinrieb, R., Anton, R.F., et al. (1996) Ritanserin in the treatment of alcohol dependence—a multi-center clinical trial. Psychopharmacology 128:206–215. Johnson, B.A., Roache, J.D., Javors, M.A., DiClemente, C.C., Cloninger, C.R., Prihoda, T.J., et al. (2000) Ondansetron for reduction of drinking among biologically predisposed alcoholic patients: A randomized controlled trial [see comments]. JAMA 284: 963–971. Johnston, L. (2006). Monitoring the future 2005. In: Johnston, L., O’Malley, P., Bachman, J., and Schulenberg, J., eds. Monitoring The Future, National Survey Results on Drug Use, 1975–2005, Vol I, Secondary School Students. Bethesda, MD: National Institute on Drug Abuse, pp. 139–262. Jones, R.T., Benowitz, N.L., and Herning, R.I. (1981) Clinical review of cannabis tolerance and dependence. J. Clin. Pharmacol. 21:143S–152S. Jorenby, D.E., Hays, J.T., Rigotti, N.A., Azoulay, S., Watsky, E.J., Williams, K.E., et al. (2006) Efficacy of varenicline, an alpha4beta2 nicotinic acetylcholine receptor partial agonist, vs placebo or sustained-release bupropion for smoking cessation: a randomized controlled trial. JAMA 296:56–63. Kampman, K.M., Pettinati, H., Lynch, K.G., Dackis, C., Sparkman, T., Weigley, C., and O’Brien, C.P. (2004) A pilot trial of topiramate for the treatment of cocaine dependence. Drug Alcohol Depend. 75:233–240. Kampman, K.M., Volpicelli, J.R., Mulvaney, F., Rukstalis, M., Alterman, A.I., Pettinati, H., et al. (2002) Cocaine withdrawal severity and urine toxicology results from treatment entry predict outcome in medication trials for cocaine dependence. Addict. Behav. 27:251–260. Kantak, K., Collins, S., Lipman, E., Bond, J., Giovanoni, K., and Fox, B. (2000) Evaluation of anti-cocaine antibodies and a cocaine vaccine in a rat self-administration model. Psychopharmacology 148:251–262. Kessler, R.C., Nelson, C.B., McGonagle, K.A., Edlund, M.J., Frank, R.G., and Leaf, P.J. (1996) The epidemiology of co-occurring addictive and mental disorders: implications for prevention and service utilization. Am. J. Orthopsychiatry 66:17–31. Khantzian, E.J. (1985) the self-medication hypothesis of addictive disorders: focus on heroin and cocaine dependence. Am. J. Psychiatry 142:1259–1264. Killian, A., Bonese, K., Rothberg, R., Wainer, B., and Schuster, C. (1978) Effects of passive immunization against morphine on heroin selfadministration. Pharmacol. Biochem. Behav. 9(3):347–352. Koob, G.F., Ahmed, S.H., Boutrel, B., Chen, S.A., Kenny, P.J., Markou, A., et al. (2004) Neurobiological mechanisms in the transition

879

from drug use to drug dependence. Neurosci. Biobehav. Rev. 27:739–749. Kosten, T., Rosen, M., Bond, J., Settles, M., Roberts, J., Shields, J., et al. (2002) Human therapeutic cocaine vaccine: safety and immogenicity. Vaccine 29(8):1196–1204. Kreek, M.J. (1992). Rationale for maintenance pharmacotherapy of opiate dependence. In: O’Brien, C.P., and Jaffe, J., eds. Addictive States. New York: Raven Press, pp. 205–230. LeBlanc, A., Kalant, H., Gibbins, R., and Berman, N. (1969) Acquisition and loss of tolerance to ethanol by the rat. J. Pharmacol. Exp. Ther. 168:244. Malcolm, R., Swayngim, K., Donovan, J.L., DeVane, C.L., Elkashef, A., Chiang, N., et al. (2006) Modafinil and cocaine interactions. Am. J. Drug Alcohol Abuse 32:577–587. Marsch, L.A., Stephens, M.A., Mudric, T., Strain, E.C., Bigelow, G.E., and Johnson, R.E. (2005) Predictors of outcome in LAAM, buprenorphine, and methadone treatment for opioid dependence. Exp. Clin. Psychopharmacol. 13:293–302. Martell, B.A., Mitchell, E., Poling, J., Gonsai, K., and Kosten, T.R. (2005) Vaccine pharmacotherapy for the treatment of cocaine dependence. Biol. Psychiatry 58:158–164. Matsuda, L.A., Lolait, S.J., Brownstein, M.J., Young, A.C., Bonner, T.I. (1990) Structure of a cannabinoid receptor and functional expression of the cloned cDNA. Nature 346:561–564. McLellan, A., Luborsky, L., O’Brien, C., and Woody, G. (1980) An improved diagnostic instrument for substance abuse patients: The Addiction Severity Index. J. Nerv. Ment. Dis. 168:26–33. McLellan, A.T., Lewis, D.C., O’Brien, C.P., and Kleber, H.D. (2000) Drug dependence, a chronic medical illness: implications for treatment, insurance, and outcomes evaluation. JAMA 284:1689–1695. McLellan, A.T., Weinstein, R.L., Shen, Q., Kendig, C., and Levine, M. (2005) Improving continuity of care in a public addiction treatment system with clinical case management. Am. J. Addict. 14:426–440. McLellan, A.T., Woody, G.E., and O’Brien, C.P. (1979) Development of psychiatric illness in drug abusers. N. Eng. J. Med. 301: 1310–1314. Mello, N.K., Mendelson, J.H., Bree, M.P., and Lukas, S.E. (1989) Buprenorphine suppresses cocaine self-administration by rhesus monkeys. Science 245:859–862. Mendelson, J., Jones, R.T., Welm, S., Baggott, M., Fernandez, I., Melby, A.K., and Nath, R.P. (1999) Buprenorphine and naloxone combinations: the effects of three dose ratios in morphine-stabilized, opiate-dependent volunteers. Psychopharmacology 141:37–46. Montoya, I.D., Gorelick, D.A., Preston, K.L., Schroeder, J.R., Umbricht, A., Cheskin, L.J., et al. (2004) Randomized trial of buprenorphine for treatment of concurrent opiate and cocaine dependence. Clin. Pharmacol. Ther. 75:34–48. National Institute on Drug Abuse. (2007) Marijuana Facts. http:// www.nida.nih.gov/MarijBroch/parentpg17-18N.html#Addicted. Nestler, E.J. (2004) Molecular mechanisms of drug addiction. Neuropharmacology 47(Suppl 1):24–32. O’Brien, C.P. (1975) Experimental analysis of conditioning factors in human narcotic addiction. Pharmacological Rev. 27:535–543. O’Brien, C.P. (2005a) Anti-craving (relapse prevention) medications: possibly a new class of psychoactive medication. Am. J. Psychiatry 162:1423–1431. O’Brien, C.P. (2005b) Drug addiction and drug abuse. In: Brunton, L., ed. Goodman & Gilman’s The Pharmacological Basis of Therapeutics, 11th ed. New York: McGraw-Hill, pp. 607–627. O’Brien, C.P. (2006). Drug addiction and drug abuse. In: Brunton, L., Lazo, J., and Parker, K., eds., Goodman & Gilman’s The Pharmacological Basis of Therapeutics, 11th ed. New York: McGraw- Hill, pp. 607–627. O’Brien, C.P., and McLellan, A.T. (1996) Myths about the treatment of addiction. Lancet 347:237–240.

880

SUBSTANCE ABUSE DISORDERS

O’Malley, S.S., Krishnan-Sarin, S., Farren, C., Sinha, R., and Kreek, M.J. (2002) Naltrexone decreases craving and alcohol selfadministration in alcohol-dependent subjects and activates the hypothalamo-pituitary-adrenocortical axis. Psychopharmacology (Berl) 160:19–29. Oslin, D.W., Berrettini, W., Kranzler, H.R., Pettinati, H., Gelernter, J., Volpicelli, J.R., and O’Brien, C.P. (2003) A functional polymorphism of the mu-opioid receptor gene is associated with naltrexone response in alcohol-dependent patients. Neuropsychopharmacology 28:1546–1552. Post, R.M., Weiss, S.R.B., Pert, A., and Uhde, T.W. (1987). Chronic cocaine administration: sensitization and kindling effects. In: Fisher, S., and Uhlenhuth, E. H., eds. Cocaine: Clinical and Biobehavioral Aspects. New York: Oxford University Press, pp. 109–173. Rawson, R., Huber, A., Brethen, P., Obert, J., Gulati, V., Shoptaw, S., and Ling, W. (2000) Methamphetamine and cocaine users: differences in characteristics and treatment retention. J. Psychoactive Drugs 32:233–238. Ray, L.A., and Hutchison, K.E. (2004) A polymorphism of the muopioid receptor gene (OPRM1) and sensitivity to the effects of alcohol in humans. Alcohol Clin. Exp. Res. 28:1789–1795. Ricaurte, G., Bryan, G., Strauss, L., Seiden, L., and Schuster, C. (1985) Hallucinogenic amphetamine selectively destroys brain serotonin nerve terminals. Science 229:986–988. Roberts, D.C., Andrews, M.M., and Vickers, G.J. (1996) Baclofen attenuates the reinforcing effects of cocaine in rats. Neuropsychopharmacology 15:417–423. Robinson, T.E., and Kolb, B. (2004) Structural plasticity associated with exposure to drugs of abuse. Neuropharmacology 47(Suppl 1): 33–46. Rocio, M., Carrera, A., Ashley, J.A., Parsons, L.H., Wirsching, P., Koob, G.F., and Janda, K.D. (1995) Suppression of psychoactive effects of cocaine by active immunization. Nature 378:727–730. Rose, J.E., Behm, F.M., and Westman, E.C. (2001) Acute effects of nicotine and mecamylamine on tobacco withdrawal symptoms, cigarette reward and ad lib smoking. Pharmacol. Biochem. Behav. 68:187–197. Satel, S.L., and Edell, W.S. (1991) Cocaine-induced paranoia and psychosis proneness. Am. J. Psychiatry 148(12):1708–1711. Schuckit, M., Tipp, J., Bergman, M., Reich, W., Hesselbrock, V., and Smith, T. (1997) Comparison of induced and independent major depressive disorders in 2,945 alcoholics. Am. J. Psychiatry 154:948–957.

Shoptaw, S., Yang, X., Rotheram-Fuller, E.J., Hsieh, Y.C., Kintaudi, P.C., Charuvastra, V.C., and Ling, W. (2003) Randomized placebo-controlled trial of baclofen for cocaine dependence: preliminary effects for individuals with chronic patterns of cocaine use. J. Clin. Psychiatry 64:1440–1448. Sofuoglu, M., and Kosten, T.R. (2006) Emerging pharmacological strategies in the fight against cocaine addiction. Expert Opin. Emerg. Drugs 11:91–98. Stalnikowicz, R., Mahamid, R., Kaspi, S., and Brezis, M. (2005) Undertreatment of acute pain in the emergency department: a challenge. Int. J. Qual. Health Care 17:173–176. Stephens, R.S., Babor, T.F., Kadden, R., and Miller, M. (2002) The Marijuana Treatment Project: rationale, design and participant characteristics. Addiction 97(Suppl 1):109–124. Volkow, N. (2004) Cocaine abuse and addiction (from the director). National Institute on Drug Abuse Research Report Series. http://www.nida.nih.gov/ResearchReports/Cocaine/Cocaine.html Volpicelli, J., Pettinati, H., McLellan, A., and O’Brien, C. (2001) Combining medication and psychosocial treatment for addiction— The BRENDA approach. New York: Guilford Press. Volpicelli, J.R., Alterman, A.I., Hayashida, M., and O’Brien, C.P. (1992) Naltrexone in the treatment of alcohol dependence. Arch. Gen. Psychiatry 49:876–880. Volpicelli, J.R., O’Brien, C.P., Alterman, A.I., and Hayashida, M. (1990). Naltrexone and the treatment of alcohol dependence: initial observations. In: Reid, L.B., ed. Opioids, Bulimia, Alcohol Abuse and Alcoholism. New York: Springer-Verlag, pp. 195–214. Weerts, E.M., Froestl, W., Kaminski, B.J., and Griffiths, R.R. (2007) Attenuation of cocaine-seeking by GABA B receptor agonists baclofen and CGP44532 but not the GABA reuptake inhibitor tiagabine in baboons. Drug Alcohol Depend. 89:206–213. Wikler, A. (1973) Dynamics of drug dependence: implications of a conditioning theory for research and treatment. Arch. Gen. Psychiatry 28:611–616. Woody, G.E., McLellan, A.T., Luborsky, L., O’Brien, C.P., Blaine, J., Fox, S., et al. (1984) Severity of psychiatric symptoms as a predictor of benefits from psychotherapy: the Veterans AdministrationPenn study. Am. J. Psychiatry 141:1172–1177. Woody, G., O’Brien, C.P., and Rickels, K. (1974) Depression and anxiety in heroin addicts: a placebo-controlled study of doxepin in combination with methadone. Presented at the National Academy of Sciences/National Research Council Committee on Problems of Drug Dependence. Washington, DC: National Academy of Sciences, pp. 1160–1167.

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VER the past decade major advances have taken place at virtually every level of understanding Alzheimer’s disease (AD) and other dementias. New genetic abnormalities have been identified, pathophysiological mechanisms have been elucidated with therapeutic agents targeting these mechanisms in clinical development, and both diagnostic tests and prognostic indicators are present with new ones on the horizon. While these extraordinary advances are apparent in the research questions we ask and they way we address this disease clinically, fundamental questions remain unanswered. Any discussion of the pathophysiology and treatment of dementias must consider the function and anatomy of the normal brain. In Chapter 55, Wenk reviews the functional neuroanatomy of the different systems involved in learning and memory and the consequences of these pathways’ disruption. Complementing this discussion is Berger-Sweeney and colleagues’ review of the neurotransmitter systems involved in learning and memory in Chapter 56. In Chapter 53, Kaufer and DeKosky review the current diagnostic classifications of dementia and how they relate to the neurobiology of AD, Parkinson’s disease, dementia with Lewy bodies, and other cognitive disorders. In Chapter 57, Bobinski and colleagues discuss the neuropathological and neuroimaging findings associated with normal aging and AD. The central role of the hippocampus in early disease is reviewed. To date, neuroimaging studies provide the most likely candidates as predictors of cognitive decline and dementia in nonsymptomatic aging cohorts. Clinicopathological examination of autopsied patients who had neuropsychological testing and neuroimaging studies at different stages of cognitive impairment prior to death is invaluable for gaining a better understanding of the distinction between normal aging and AD, and of the transitional state just prior to the development of frank dementia. Perl’s review of the abnormalities in brain structures in dementia is a natural extension of the earlier chapters in this section. In Chapter 58, Perl discusses advances that have been made in determining the distinction between normal aging and dementia, and delineates the pathological lesions that are emblematic of AD and other dementias.

In Chapter 52, Hardy and colleagues describe mutations in chromosomes 21, 1, and 14 which have all been implicated in familial forms of AD. These mutations affect three different proteins: amyloid precursor protein (APP), presenilin I, and presenilin II. It has been argued that since all these mutations increase the level of AB1-42 in plasma or in cell culture systems, amyloid deposition must be the final common pathway in AD. As compelling as this analysis may be, it is still not definitive. Much of the literature has focused on the role of AB1-42 in the pathophysiology of AD. The neurotoxicity of AB is concentration-dependent and best demonstrated in cell culture systems. Assays permitting examination of human cerebrospinal fluid (CSF) measures of these components provide further support to the story of amyloid toxicity. In addition, recent attention has been paid to soluble abeta and oligomers which currently dominate the thinking in the field as toxic entities. However, the precise mechanism by which cells are killed remain to be identified. Other credible candidates for a central role in cell death include microglial activation with complement expression. It would be a mistake to dismiss the role of the neurofibrillary tangle in the pathophysiology of AD. Perl underlines the importance of tangles in the pathology of AD and implicitly raises the question of how this molecule could not have a critical role in the cognitive deficits observed in AD patients. Although this pathological element of the affected brain has received somewhat less attention than amyloid, it may still be a critical component. This possibility is strengthened when consideration is given to the fact that relatively large depositions of amyloid can occur in aged individuals who have no cognitive impairment. In contrast, largescale deposition of tangles is almost inevitably associated with cognitive impairment. Some of the earliest pathological changes in AD include tangle formation in entorhinal cortex. Lastly, there is a certain parsimony to attributing disturbed neuronal function to the deposition of intercellular pathology, such as the tangle, rather than to extracellular pathology, such as the plaque. The development of transgenic animal models further clarifies the pathophysiology of AD and establishes

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a platform for testing potential therapeutic agents. In Chapter 54, Elder reviews this field, retracing the history of the early attempts to overexpress APP without generating plaque or other AD type pathology. Barely a decade ago, mouse models began to appear that reliably mimicked human AD pathology. A concerted effort has been made to gain insight into the etiology of AD by attempting to re-create some the gene-related and/or pathophysiology-related abnormalities in animal models. Genetic manipulations have produced mice that express, overexpress, or underexpress particular genes (APP, presenilin, apolipoprotein E4) and their proteins that are implicated in the pathophysiology of AD. The most recent advances include transgenic animals with new phenotypes that include additional aspects of Alzheimer pathology. Recent presenilin-1 (PS1) and familial Alzheimer’s disease (FAD) mutants can now model agerelated neurodegenerative changes, neuronal loss, and recently age-related neurofibrillary tangles (NFTs) like inclusions. Broadening the ability to model these typical pathological features will further our understanding of AD and widen the net of targets for drug development beyond those involved exclusively in amyloid. The areas where we most urgently need advances are diagnostics and therapeutics. One of the most intriguing possibilities is that imaging techniques may yield a specific diagnostic test for AD, particularly when the illness is in its earliest stages. The chapters by Bobinski and colleagues (57) and Buchsbaum and colleagues (59) raise the possibility that the very early changes in AD may be detectable with magnetic resonance imaging (MRI) and positron emission tomography (PET), respectively. The increasing availability and accuracy of MRI give this technology a potentially broad application. The hippocampal formation may well prove to be a brain region that will provide the earliest window into the process of AD. The ability to detect abnormalities in the hippocampal formation in individuals at risk for AD and to monitor this area’s changes with illness progression may suggest that the MRI study of the hippocampus will provide a biological surrogate for the testing and development of drugs designed to alter the progression of the disease. Perhaps such a marker would provide a vehicle to conduct more expeditious clinical trials. Chapter 60 by Bergmann and Sano reviews progress underlying the therapeutics of AD. Compared to the clinical nihilism that surrounded this disease only 2 decades ago, the availability of approved drugs in two classes (cholinesterase inhibitors and N-methyl-D-aspartate [NMDA] receptor antagonist) that have beneficial effects in Alzheimer’s patients is a triumph. As Chapter 60 reports, newer treatments targeting amyloid accumulation by various mechanisms including vaccines and secretase modulation are in clinical trials at this very

moment which will test the amyloid hypothesis and may provide new hope for patients and practitioners. Development of many of these agents began with the early transgenic models described above and led to full fledged clinical trials. The availability of newer models is already providing leads for new treatment concepts targeting tau and gene. Chapters 61–63 highlight the importance of subcortical structures in dementia. Using multiple sclerosis as a paradigm, Hyde reviews in Chapter 61 the neuropsychological profile associated with neuropathological lesions observed in these patients. While deficits in working memory and executive function are not uncommon in multiple sclerosis, the more classical neuropsychological deficits in cortical syndromes such as aphasia, agnosia, and apraxia are rarely observed in these patients. Chapters 62 and 63 review two other causes of dementia, dementia with Lewy bodies and Parkinson’s disease, respectively. A chapter (65) has been added on frontotemporal dementia (FTD) in which Miller makes the compelling argument that this condition may be more common than previously recognized. FTD is the most common of early onset dementias yet a quarter of the cases occur after the 6th decade. Themes from earlier chapters describing anatomy and imaging resonate as the role of frontal lobe and executive function in clinical phenomenology so characteristic of this disease is described in this chapter. These chapters describe the phenomenology, neuroimaging findings, cognitive profiles, clinical course, genetics, pharmacological management, neurochemical deficits, and neuropathological findings associated with these dementias. While AD, dementia with Lewy bodies, and Parkinson’s disease have some common characteristics, it appears that they do represent distinct, yet possibly related, illnesses. It is hoped that further investigation into the interface between these three dementias will achieve a better understanding of their pathophysiology and optimize their treatments. Two new chapters have been added describing mild cognitive impairment by Peterson (64), and vascular dementia by Chui (66). Both highlight the growing awareness of even subtle cognitive compromise in memory as well as other domains. These chapters describe the clinical presentation of these conditions, demonstrate how cognitive and clinical profiles predict further compromise and incapacity, and address the need to develop treatment algorithms that can address even mild impairment. Taken together the work summarized in these chapters highlights the importance of cognition in mental health; provides a road map for defining conditions and understanding their phenomenology and pathology; and even provides proof that this dissection of mechanisms of impairment can enlighten our treatment of these conditions.

52 The Genetics and Pathogenesis of Alzheimer’s Disease and Related Dementias JOHN A. HARDY

The role that genetic analysis has played in dissecting the aetiology and pathogenesis of Alzheimer’s disease (AD) is the primary focus of this review. The impact of this analysis in terms of animal modeling and clinical investigations is also covered. Other dementing illnesses, including Lewy body disease, prion diseases, Worster Drought syndrome, and frontotemporal dementia, are discussed to the extent that they shed light on the pathogenesis of AD. Progress toward mechanistic therapy is outlined. INTRODUCTION In our aging societies, dementias, especially AD but also frontal temporal dementias and Lewy body disease, are increasing societal problems, afflicting perhaps 5% of those older than age 65 years and 20% of those older than 80 years. Treatment for these diseases, as in all neurodegenerative diseases, remains palliative. However, based largely on genetic analysis, we now have an outline of the pathogenic mechanisms involved in these diseases, and we also have a clearer view of the progression of the disease. This increased understanding has led to the identification of several plausible drug targets for these diseases and a general sense of optimism that mechanistic therapy may soon be available. The purpose of this review is to discuss this progress. I focus on AD and discuss other dementias to the extent to which they contribute to our understanding of AD. ALZHEIMER’S DISEASE AD is the major cause of dementia in the elderly and afflicts ∼4 million Americans (U.S. population ∼300 million). Although most cases are late onset and show familial clustering, a small proportion has onset ages

younger than age 60 years and shows autosomal dominant inheritance. It seems that all cases with early-onset, autosomal dominant AD have mutations in either the amyloid precursor protein (APP) gene or in the presenilin 1 (PSEN1) or presenilin 2 (PSEN2) genes (Rogaeva, 2002). The only currently accepted genetic risk factor for late-onset AD is the apolipoprotein E (ApoE) gene, in which the ε4 allele is risk factor and the ε2 allele is protective (Farrer et al., 1997). Although it is widely believed that there must be other genetic risk factors for late-onset disease, a recent genome screen suggested that there were unlikely to be any other alleles that had as large an effect as ApoE (Coon et al., 2007). APP and Alzheimer’s Disease The occurrence of Alzheimer pathology in Down syndrome (trisomy 21) has long been recognized, and when Glenner and Wong identified the Aβ peptide in the meninges of, first, typical Alzheimer cases (Glenner and Wong, 1984b) and then the same peptide sequence in Down syndrome (Glenner and Wong, 1984a), they commented that it was likely that the gene was on chromosome 21 and was mutated in AD. These remarkable predictions were shown to be correct with the cloning of APP and the identification of APP mutations in a few AD cases (Goate et al., 1991). Examination of cases of Down syndrome with translocations distal of the APP gene showed that these individuals, although they had the obvious features of Down syndrome, did not develop AD (Prasher et al., 1998): this made it clear that the relationship between AD and Down syndrome specifically relates to overexpression of the APP gene rather than a nonspecific relationship with the full trisomy. In general, families with APP missense mutations have typical AD with onset ages in the 50s with little variance. However, some cases, particularly those with mutations within the Aβ sequence, have a phenotype that 883

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resembles hereditary cerebral hemorrhage with amyloidosis (Dutch type) (HCHWA-D) (Levy et al., 1990). The reason for the variability in the phenotype is not clear. More recently, several families with duplications of the APP gene have been identified. Individuals with these duplications also have a variable phenotype with approximately half the duplication carriers developing hemorrhagic strokes and half developing typical AD (Rovelet-Lecrux et al., 2006). These data, of course, fit very well with the observations in Down syndrome, yet hemorrhagic stroke is rare in Down syndrome. The reason for this slight discrepancy is unclear. ApoE genotype affects the age of onset in families with APP mutations and dementia but does not affect the age of onset of hemorrhagic stroke. In dementia, essentially single copies of the ε4 allele reduce the age of onset 5 years relative to ε3 homozygotes, and ε4 homozygotes have an onset age 10 years earlier. Single copies of the ε2 allele increase the age of onset by 5 years, and ε2 homozygotes have an onset age 10 years later (Houlden et al., 1993). These general rules of thumb appear also to be true for AD in Down syndrome (Royston et al., 1994). One large gap in our current knowledge is that we have little idea about the function of APP. When it was first cloned, it was suggested to be a receptor (Kang et al., 1987), and that seems likely to be the case. But its ligand and downstream targets are not known. This means we do not know whether, in some way, Alzheimer pathogenesis relates to the normal function of APP (see below). The Presenilins A minority of families (~10%) had mutations in the APP gene. Genetic linkage analysis showed that the majority of families showed linkage to chromosome 14 (Schellenberg et al., 1992), whereas a minority, largely of Russo-German origin, showed linkage to chromosome 1 (Levy-Lahad et al., 1995). Position cloning identified the genes for the former, which are the majority (∼80%), as mutations in the PSEN1 gene (Sherrington et al., 1995), whereas the others (∼10%), including the Russo-German families, had mutations in their homologue, PSEN2 (Rogaev et al., 1995). Most of the mutations are simple missense variants, but some in frame deletions, most notably PSEN1 Δex9, have also been described. No nonsense or frameshift mutations have been identified suggesting that the mutations are not simple loss of function variants but not eliminating the possibility that the mutations lead to a partial loss of function. A very large number of families with PSEN1 and PSEN2 mutations have now been described (http://www .molgen.ua.ac.be/ADMutations/) (see Fig. 52.1). In gen-

eral, families with PSEN1 mutations have typical AD with ages of onset from 35 to 50, with some of the variability in onset age being accounted for by ApoE genotype as with APP families (Pastor et al., 2003). Families with PSEN2 mutations have a very variable onset age, and though a proportion of the variance is accounted for by ApoE genotype, much of the variance remains unexplained (Wijsman et al., 2005). Some families with PSEN1 mutations have an unusual phenotype of initial spastic paraparesis, and these families are generally characterized by have large “cotton wool” plaques rather than neuritic plaques (Crook et al., 1998). Although the reason for the difference in pathogenesis is not clear, it seems that the mutations involved are those that have the largest effect on APP processing (Houlden et al., 2000). In contrast to APP, the function of the presenilins are now well understood in outline. They are the central subunit of intramembranous proteases which are responsible for the regulated cleavage of Notch, APP, and many other type-1 membrane proteins (see Fig. 52.1). The effects of pathogenic mutations: The amyloid hypothesis of Alzheimer’s disease. In general terms, we have a clear understanding of the effects of the APP and presenilin mutations: most APP mutations and all presenilin mutations alter APP processing such that Aβ deposition is a more likely event (Scheuner et al., 1996) (see Fig. 52.2). Slightly less certain and less well studied is the possibility that some of the intra-Aβ mutations’ primary effect is on reducing the solubility of Aβ without altering the position of cleavage (Wisniewski et al., 1991). Although the general framework of the effects of the pathogenic mutations is clear, the details are not, and the precise mechanisms of the effects of the mutations on APP cleavage are not understood. γ -secretase’s action is complex and seems to involve an initial cleavage between codons 721 and 722 (Aβ 49 and Aβ50) before trimming back the sequence to final cleavage after codon 711 (Aβ 40) or 713 (Aβ 42) (Weidemann et al., 2002). Despite this uncertainty over the molecular detail of the effects of the mutations, most researchers have reached a consensus that, in general, the effects of the mutations are directly related to their effects on APP processing, and this has been the basis for the amyloid hypothesis of the disorder (Hardy and Selkoe, 2002). Recently, two groups have independently suggested an alternative: that the crucial effect is that all the mutations cause a partial inhibition of presenilin function (Sambamurti et al., 2006; Shen and Kelleher, 2007). They point out that γ -secretase has many vital functions and is involved in the processing of many type-1 membrane proteins beyond APP including Notch cleav-

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52.1 A diagram of the central structure of γ -secretase with APP in the active site of Presenilin 1 (PSEN1). The central role of presenilins in γ -secretase action was shown by the creation of presenilin knock out mice, which fail to metabolize the C-terminal stub of APP (De Strooper et al., 1998). The critical aspartate residues at the active site were identified by mutagenesis experiments (Wolfe et

al., 1999). The whole active γ -secretase complex containing presenilin and other accessory proteins has been reconstituted in yeast (Edbauer et al., 2003). The structure of PSEN1 is derived from Laudon et al. (2005). This diagram was drawn by Richard Crook with advice from Wim Annaert.

age but that APP is the major substrate in terms of expression. They argue that all the pathogenic mutations may act to inhibit γ -secretase either directly in the case of presenilin mutations, or indirectly through the effects of mutations in, or increased dose of, its major substrate. This argument fits equally well with the genetic data as the amyloid hypothesis, but it seems less likely when one considers the admittedly inconclusive evidence suggesting a neurotoxicity of Aβ and also when one considers the analogy with the other plaque and tangle diseases, Worster Drought syndrome, and some prion dementias. In these latter diseases there are amyloid deposits, tangles, and cell death; and in these the pathogenic mutations are, as in AD, in the extracellular deposited amyloid protein. This analogy suggests that the route to cell death directly involves the deposited protein. Neither of these arguments against the presenilin inhibition hypothesis of AD is conclusive, and this hypothesis remains a credible alternative. As detailed above, most, but not all, researchers would acknowledge that the most likely mechanism leading

to AD in the early-onset kindreds and in Down syndrome is the amyloid hypothesis. However, the applicability of the amyloid hypothesis to late-onset AD is much more widely debated (see below).

FIGURE

Late-Onset Alzheimer’s Disease Apolipoprotein ε. The only established risk factor for late onset disease is the ApoE ε4 (Corder et al., 1993). A single copy of the ε4 allele appears to shift the risk curve for developing AD forward by 5 years, in general, in Down syndrome (Royston et al., 1994), in families with APP mutations (Houlden et al., 1993), and in families with presenilin mutations (Pastor et al., 2003; Wijsman et al., 2005). Being the homozygote for the ε4 allele shifts the risk curves forward by 10 years, and it seems likely that a single copy of the ε2 allele shifts the curve back by 5 years and two copies, back by 10 years (Corder et al., 1993; Farrer et al., 1997). However, the increase in familial clustering encoded at the ApoE ε locus is widely believed not to be sufficient to account for more than a modest proportion of the total famil-

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FIGURE 52.2 A simplistic diagram showing APP processing. APP processing occurs through two alternative pathways (Haass et al., 1992). In the first pathway, APP is cleaved at codon 671 by the enzyme β - secretase (BACE; Vassar et al., 1999) and then by γ -secretase. This pathway releases Aβ. In the second pathway, α-secretase cleavage occurs within the Aβ sequence, predominantly at residue 682 by a mixture of ADAM 10 and ADAM 17 (Asai et al., 2003) followed by γ -secretase cleavage. This yields a fragment designated p3 (Haass et al., 1992). The APP670/1 mutation potentiates BACE cleavage yielding more total Aβ (Cai et al., 1993; Citron et al., 1995; Vassar et al, 1999). Some of the mutations in the APP sequence, particularly the APP692 mutation, inhibit the α-secretase cleavage, indi-

rectly causing more flux through a β cleavage pathway (De Jonghe et al., 1998). APP mutations close to the C-terminal of the Aβ sequence marginally alter the final length of a proportion ofAβ causing an increase in the proportion of Aβ 42 (Suzuki et al., 1994). Presenilin mutations have essentially the same effect (Scheuner et al., 1996). The approximate positions of mutations are indicated by the ovals and strength and number of the arrows illustrates the amount of flux through the pathway. The γ -secretase cleavage is a more complex event than conveyed in the diagram (see text and Weidemann et al., 2002).

ial clustering, leading to the belief that there is likely to be on the order of ∼5 other genetic risk loci (Daw et al., 2000).

than the odds ratios > 3.5 reported for the ApoE ε4 locus. This finding is consistent with the first reports of a whole genome study in AD, which clearly identified the ApoE ε4 locus (Coon et al., 2007), but found nothing else before the sample was fractionated by ApoE ε genotype (Reiman et al., 2007). There are many possible explanations for this—the coverage of the whole genome chip arrays is not complete, and this methodology would not pick up genes that had many different risk alleles—but the simplest explanation is that there are no other alleles of major effect. This would suggest that the rest of the risk of disease is predisposed to by common alleles with low risk ratios (> 1.5) or by rare variants with large effect size but low population attributable risk, as well, of course, by environmental influences and chance. The recent success of the dissection of type II diabetes by whole-genome association

Are there other Alzheimer risk genes? Extensive study using linkage approaches and candidate gene association studies has so far failed to give consistent proof that any of the other candidates are involved in the aetiology of the disease. The Alzgene website (http://www .alzforum.org/res/com/gen/alzgene/default.asp) keeps a continually updated meta-analysis of genes that have been extensively tested for involvement (Bertram et al., 2007). Only two genes, ACE and IL1B, presently (July 2007) pass the criteria of 95% confidence intervals not including unity when the initial report is excluded and the analysis is confined to a single ethnic group (the standard practice in meta-analysis). Both of these have reported odds ratios of between 1.1 and 1.2: far lower

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studies suggests that that the best initial approach to this problem is through the pooling of the data from several large studies to achieve very large sample sizes. One particularly plausible risk gene is the APP gene because we know from the example of Down syndrome and the APP duplication families that increases of expression of 50% (three copies of the gene) give disease with ages of onset in the 50s. This means that if there are alleles in the general population with a relative expression level increased by 25%, when homozygote, these, too, would be associated with disease onset at the same age, and presumably, slightly lower expression alleles would be associated with a higher-onset age. In addition, in the other protein deposition disorders where autosomal dominant genes have been found, genetic variability in the expression of the same protein has shown a robust association with the sporadic disease (Singleton et al., 2004). Recently two studies have reported such an association (Brouwers et al., 2006; Guyant-Maréchal et al., 2007), and genetic linkage analysis has also suggested that chromosome 21 may be involved (Wavrant-De Vrieze et al., 1999): however, a recent and thorough analysis failed to confirm this association (Nowotny et al., 2007); so even with this plausible candidate, strict genetic evidence for involvement is lacking. Does the amyloid hypothesis apply to late-onset Alzheimer’s disease? Parsimony would suggest that the overall mechanism of disease in late-onset disease would be generally similar to the mechanism in the autosomal dominant kindreds. However, this point has rightly been much more extensively debated than the mechanism of pathogenesis of the autosomal dominant kindreds. A major gap in our knowledge is a precise understanding of the functions of APP. From the perspective of the amyloid hypothesis, one worrying suggestion is that amyloid deposition is a damage-response mechanism. One known function of APP is in the blood clotting cascade (Smith et al., 1990), and one intriguing suggestion is that amyloid deposition is a physiological response to microhemorrhaging (Cullen et al., 2006): certainly, there is extensive, though not incontrovertible, evidence that plaque formation occurs centered on blood vessel walls (Miyakawa et al., 1982; Kumar-Singh et al., 2005). In such a scheme, the amyloid deposition may initially, at least, have a damage-response role (Atwood et al., 2002), though such an idea is difficult to reconcile with the development of the disease in the autosomal dominant kindreds. Some have suggested that this damage response role underlies the side-effect profile of the amyloid vaccine (see below). This debate will be helped as we develop an understanding of the role of APP and as we identify and understand more risk factor genes. Most important, how-

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ever, it will be resolved when/if we develop treatments for the disorder. INSIGHTS FROM OTHER DEMENTING DISEASES Although AD is easily the most prevalent dementing disease, other rarer dementias offer useful comparators. These include dementia with Lewy bodies, prion disease, Worster Drought syndrome (British dementia), and frontal temporal dementia with tangles (F T DP-17 T). Dementia with Lewy Bodies The nosological separations of dementia with Lewy bodies from AD and from Parkinson’s disease have proved extremely difficult (McKeith et al., 1996). In some cases of AD, including those with APP mutations (Lantos et al., 1994), Down syndrome (Lippa et al., 1999), and presenilin (Lippa et al., 1998) mutations, there are a variable number of Lewy bodies whose presence has become much more clear with the advent of first ubiquitin, and later α-synuclein staining. This observation suggests that Lewy formation, like tangle formation, can be a downstream pathology to APP mismetabolism (Hardy, 2003). Individuals with large numbers of cortical Lewy bodies have a dementing phenotype that, on a group though not on an individual level, is distinguishable from typical AD in having a fluctuating course and some parkinsonian features. This latter phenotype, unsurprisingly, overlaps with that in individuals who present with Parkinson’s disease and later develop dementia (Lippa et al., 2007). Parkinson’s disease and Parkinson’s dementia can occasionally be caused by αsynuclein mutations (Polymeropoulos et al., 1997), including gene duplications (Singleton et al., 2003), and the sporadic diseases show a genetic association with the α-synuclein haplotype (Farrer et al., 2001). Insights into Alzheimer’s disease. The nosological confusion between AD and dementia with Lewy Bodies is likely to obscure a rather simple and revealing underlying biology. As is true for prion (see below), tau (see below), and APP (see above), α-synuclein deposition is influenced by the α-synuclein haplotype (Singleton et al., 2004). In addition, as is true for tau, α-synuclein deposition is also increased by APP mismetabolism (Masliah et al., 2000; Masliah et al., 2001). These data suggest that α-synuclein can be downstream of APP mismetabolism in an analogous way to tau (see Fig. 52.3). Experimental support for this notion has come from transgenic experiments which show that α-synuclein deposition in transgenic mice is hastened by an APP transgene in an analogous manner to tau deposition (Masliah et al., 2001) (see Fig. 52.3 and below). From

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52.3 The proposed relationship between Aβ and tau and αsynuclein and between Alzheimer’s disease and dementia with Lewy bodies (Hardy et al., 1998; Hardy, 2003). The genetic data on British

dementia and the prion diseases suggest that the cognate proteins (ABri and prion) can behave in a similar way to Aβ 42.

a treatment perspective, the implication of overlap between AD and dementia with Lewy bodies is that one might expect both syndromes to respond to anti-Aβ therapies but differently to antitau and antisynuclein therapies.

Lewy body pathology (Hsiao et al., 1992) indicating that these pathologies can also be secondary to a prion aetiology as they are to an Aβ aetiology. Also, genetic variability in prion expression contributes to the risk of the sporadic disease, with high expressors being at higher risk for disease in a broadly analogous way to the way in which APP expression can cause AD (Mead et al., 2001). Perhaps most interesting has been the recent demonstration that extracts of Alzheimer brain amyloid (but not synthetic Aβ) can precipitate plaque pathology in APP transgenic mice (Meyer-Luehmann et al., 2006), suggesting that the difference between the prion diseases’ infectivity and the spread of Alzheimer pathology in AD is, at its basis, a quantitative difference and not a qualitative difference. Perhaps all these diseases of β -sheet protein deposition are diseases of pathologic templating (Hardy, 2005).

Prion Disease A full description of prion diseases is beyond the scope of this chapter (see Prusiner, 2001). Prion diseases fall into three classes: hereditary, acquired (infectious, iatrogenic, cannibalistic), and sporadic. At the center of these aetiologies is the prion protein: mutations in the prion gene cause the hereditary disorder. A pathologic conformation of the protein is the infectious agent in the human- and animal-acquired forms of the disease, and genetic variability in the prion gene contributes to the risk of the sporadic disease. Insights into Alzheimer’s disease. There are a number of interesting parallels between prion diseases and AD. First, the obvious similarity that both disorders involve abnormal aggregates of the cognate protein. Some forms of prion diseases involve extracellular depositions of the prion protein as plaques that have a superficial resemblance to the amyloid plaques of AD. However, there are other, perhaps deeper, parallels. Some of the hereditary prion diseases have secondary tangle and

Worster Drought Syndrome (British Dementia) Worster Drought syndrome (Worster-Drought et al., 1933) (now unfortunately redesignated as British dementia) refers to a large English family that has a plaque and tangle disease that, before immunostaining, was considered to be a form of either early-onset AD or hereditary prion disease. The disease is caused by a stop codon mutation at the C-terminus of a type 2 membrane protein (ABri). This frameshift mutation adds

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23 nonsense amino acids to the protein (Vidal et al., 1999). Furin cleavage of the 34 terminal amino acids yields an amyloidogenic peptide that is deposited as a congophilic angiopathy and neuritic plaque (Kim et al., 1999). Insights into Alzheimer’s disease. Tangles are the secondary pathology in this disease as it is in AD. The importance of this disease for AD is that it shows that the deposition of a completely unphysiological amyloidogenic peptide can lead to plaque and tangle disease. Through the manipulation of the ABri sequence in mouse transgenics and a replacement of the pathological ABr sequence with either Aβ 42 or Aβ 40, McGowan and colleagues (McGowan et al., 2005) showed that Aβ 42 was essential for deposition to occur. Frontal Temporal Dementia (FTD) with Parkinsonism Linked to Chromosome 17 with Tangles (FTDP-17 T: Pick’s Disease) and Other “Tangle-Only” Diseases Hereditary FTD has long been recognized as a comparatively rare cause of morbidity and mortality, but its nosology has been extremely difficult. In the last 10 years, genetic analysis has considerably clarified this difficult issue. So far, three genes have been found, though it is likely that there are others. A nonsense mutation in CHMP2b probably explains the disease in a single Danish family (Skibinski et al., 2005), but the majority of families showed genetic linkage to chromosome 17 markers (Foster et al., 1997). About half of these families had tau pathology (Spillantini et al., 1998)—either tangles, Pick bodies, or wispy tau filaments—and about half of them had ubiquitin positive inclusions (Mackenzie and Feldman, 2005). Initially these were grouped together as a single entity, FTDP17 (Foster et al., 1997), but we now know they are unrelated diseases despite their clinical and genetic linkage similarities. Those with tau pathology have mutations in the tau (MAPT) (Hutton et al., 1998; Poorkaj et al., 1998) gene whereas those with ubiquitin inclusions have mutations in the progranulin (PGRN) gene (Baker et al., 2006; Cruts et al., 2006), and have the ribonucleic acid (RNA) binding protein, TDP-43 (Neumann et al., 2006) as the central protein in their inclusions. In this chapter, only the pathogenesis of those dementias with MAPT mutations will be discussed because these offer insight into AD. Two types of MAPT mutations have been discovered: missense changes that decrease the binding of tau to microtubules and increase tau’s propensity to aggregate (Hong et al., 1998) and splicing mutations that increase the inclusion of exon 10 in the protein (Hutton et al., 1998). Exon 10 encodes one of the four microtubule binding domains, so this form of the protein is commonly described as 4-repeat tau.

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Interestingly, the sporadic tangle diseases (including progressive supranuclear palsy; Baker et al., 1999), corticobasal degeneration (Houlden et al., 2001), and Parkinson’s dementia complex of Guam (Poorkaj et al., 2001) show a genetic association with the MAPT gene. The MAPT haplotype that shows association with progressive supranuclear palsy and corticobasal degeneration (CBD) (designated H1c in Europeans; Pittman et al., 2005) is that which shows greatest expression of 4-repeat tau (Myers et al., 2007). The simplest way of thinking of this is to consider these diseases as the same disorder as FTDP-17T, but separated from it by an accident of nosology, because both their pathological and clinical features also overlap with this latter disorder. Mice with MAPT transgenes containing FTDP-17T mutations develop tangles and cell loss clearly implicating tau dysfunction in neuronal cell death (Lewis et al., 2000). Insights into Alzheimer’s disease. The importance of FTDP-17 in our understanding of the pathogenesis of cell death in AD is clear. The fact that tau mutations cause tangles and cell death suggests that this is likely the same cell death pathway as the predominant pathway in AD. This suggestion is strengthened by the observation that crossing mutant APP transgenic mice with such MAPT mice leads to an augmentation of the tangle pathology without altering the amyloid pathology (Lewis et al., 2001). This observation is consistent with the view that Aβ is upstream of MAPT in AD (see Fig. 52.3) and is thus also consistent with the amyloid hypothesis of the disorder (Hardy and Selkoe, 2002). Also consistent with this view are observations that reducing tau levels reduces Aβ toxicity on cells (Rapoport et al., 2002) and decreases the behavioral decrements induced by Aβ overexpression in transgenic mice (Roberson et al., 2007). In addition, some (Myers et al., 2005), though not all, studies (Mukherjee et al., 2007) have reported that the same H1c MAPT haplotype that shows an association with progressive supranuclear palsy and corticobasal degeneration shows a weaker association with AD suggesting that increased expression of 4-repeat tau increases the likelihood of developing AD (Myers et al., 2007). Genetics Based Clinical Progress in Alzheimer’s Disease If we are to develop mechanism-based therapies for AD, then we will want to be able to diagnose the disease accurately and early, and we will want to be able to monitor whether therapies are having beneficial effects. In both of these areas, use of the families with autosomal dominant disease has proven extremely useful because of the predictable nature of the disease.

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Such families have been used extensively to determine the earliest clinical symptoms of the disease (Fox et al., 1998). However, possibly the most promising techniques for assessing preclinical change and the rate of progression of disease are imaging techniques: two different and complementary approaches are being used: magnetic resonance imaging (MRI) registration (Freeborough et al., 1996) and positron emission tomography (PET) amyloid imaging (Klunk et al., 2004). MRI registration is a technique for measuring atrophy as a change in volume in a single person over time (Freeborough et al., 1996), and its use has shown that detectable hippocampal atrophy begins about 6 years before clinical symptoms of disease are apparent and that a more generalized atrophy is detectable about 3 years before the onset of clinical symptoms (Ridha et al., 2006). The analysis also showed that the global rate was relatively similar between persons at the same stage of the development of disease but that the rate of atrophy increased as the disease spread to affect different brain regions (Chan et al., 2003). The clinical utility of the approach was shown when it was used to assess the effects of Aβ immunization when it showed the unexpected outcome that brain volume was decreased by the immunization (Fox et al., 2005) although it remains unclear as to whether this reflected a reduction in brain mass or was caused by loss of amyloid or a change in brain water balance (Fox et al., 2005; Gilman et al., 2005). PET amyloid imaging has recently been developed using radiolabeled, Pittsburgh Compound B (PIB), an analogue of thioflavin S (Klunk et al., 2004). This compound allows imaging of amyloid deposition in vivo and has shown that this deposition process begins many years (∼10) before clinical symptoms appear in presenilin mutation carriers (Klunk et al., 2007) and, when combined with MR registration, that the rate of atrophy correlates with the amyloid load (Edison et al., 2007). Animal Models and Experimental Therapeutics The genetic findings outlined above have enabled the creation of transgenic mice that model parts of the disease process. Mice with mutant APP transgenes develop plaques (Games et al., 1995) but no tangles, little cell loss (Takeuchi et al., 2000), and only subtle behavioral changes (Hsiao et al., 1996): crossing in presenilin mice increased this pathology but did not change its basic pattern (Duff et al., 1996; Borchelt et al., 1997). These mice have, therefore, been extremely useful in developing anti-amyloid therapies (Duff and Suleman, 2004). As one example among many, the amyloid immunization therapy came directly from such mouse experiments (Schenk et al., 1999; Bard et al., 2000). Mice with mutant MAPT genes develop tangles and extensive cell loss (Lewis et al., 2000), and have been useful in develop-

ing antitangle therapies (Noble et al., 2005). Mice with mutant APP and mutant MAPT genes have increased tangle formation, and such mice could be used to explore the relationship between the pathologies (Lewis et al., 2000; Oddo et al., 2003) although this important relationship has not yet been extensively explored. These mice and the mechanistic understanding we have developed offer a plethora of molecular targets for intervention (see Golde, 2006). The amyloid therapeutic approach that has attracted the most attention has been the amyloid vaccine approach. This approach was borne out of the surprising observation that immunization of APP transgenic mice led to the partial clearance of plaque deposits and almost immediate improvement of the APP transgenic mice on behavioral testing (Schenk et al., 1999; Morgan et al., 2000; Golde, 2006). Clinical trials of amyloid immunization were stopped after a small proportion of patients who received the test, but not the control immunization, developed meningioencephalitis for reasons that are unclear (Nicoll et al., 2003; Gilman et al., 2005). Although this trial could be seen as hopeful in that it clearly showed that amyloid plaques could be cleared (Nicoll et al., 2003) from the Alzheimer brain, because the trial was aborted, it has remained unclear whether this has beneficial behavioral consequences. It is also unclear whether the meningioencephalitis was merely an unfortunate side effect or whether it reflected an unanticipated role for Aβ in the pathological brain. Thus, this trial has been seen by amyloid optimists as useful proof of principle (Schenk, 2004) and by amyloid pessimists as a harbinger of other likely unsuccessful trials (Atwood et al., 2003). Many potential therapies have passed the test of working in the transgenic mice: in most cases, human trials are either under way or in the planning stage. If they work, they will be a powerful validation of the pathologic gene through transgenic animals to test therapies as a route to treat all neurologic diseases. If none of them work, then it should cause us to reevaluate all of our assumptions, not just about the amyloid hypothesis, but also about this whole approach to disease. CONCLUSION Genetic analysis of AD has led to a widespread belief that we have a basic understanding of the pathogenesis of the disease. It has also led to the development of animal models that appear to replicate aspects of this pathogenesis as well as to the identification of credible molecular targets for therapy. Finally, it has helped in the accurate characterization of the prodrome and clinical course of the disease. However, though there have been many successful therapies in the mouse models of the disease, none has yet shown utility in clinical trials. Although patients with AD are undoubtedly better treated

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then they were 15 years ago, the only direct benefit to patients from this gene-based approach to research to date has been the availability of genetic testing in the kindreds with APP and presenilin mutations.

ACKNOWLEDGMENTS The author’s laboratory is supported by the Medical Research Council. Thanks to Richard Crook for Figure 1.

REFERENCES Asai, M., Hattori, C., Szabo, B., et al. (2003) Putative function of ADAM9, ADAM10, and ADAM17 as APP alpha-secretase. Biochem. Biophys. Res. Commun. 301(1):231–235. Atwood, C.S., Bishop, G.M., Perry, G., and Smith, M.A. (2002) Amyloid-beta: a vascular sealant that protects against hemorrhage? J. Neurosci. Res. 70(3):356. Atwood, C.S., Perry, G., and Smith, M.A. (2003) Cerebral hemorrhage and amyloid-beta. Science 299:1014. Baker, M., Litvan, I., Houlden, H., et al. (1999) Association of an extended haplotype in the tau gene with progressive supranuclear palsy. Hum. Mol. Genet. 8(4):711–715. Baker, M., Mackenzie, I.R., Pickering-Brown, S.M., Gass, J., et al. (2006) Mutations in progranulin cause tau-negative frontotemporal dementia linked to chromosome 17. Nature 442(7105): 916–919. Bales, K.R., Verina, T., Cummins, D.J., Du, Y., et al. (1999) Apolipoprotein E is essential for amyloid deposition in the APP(V717F) transgenic mouse model of Alzheimer’s disease. Proc. Natl. Acad. Sci. USA 96(26):15233–15238. Bard, F., Cannon, C., Barbour, R., et al. (2000) Peripherally administered antibodies against amyloid beta-peptide enter the central nervous system and reduce pathology in a mouse model of Alzheimer disease. Nat. Med. 6(8):916–919. Bertram, L., McQueen, M.B., Mullin, K., Blacker, D., and Tanzi, R.E. (2007) Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat. Genet. 39(1):17–23. Borchelt, D.R., Ratovitski, T., van Lare, J., et al. (1997) Accelerated amyloid deposition in the brains of transgenic mice coexpressing mutant presenilin 1 and amyloid precursor proteins. Neuron 19(4): 939–945. Brouwers, N., Sleegers, K., Engelborghs, S., et al. (2006) Genetic risk and transcriptional variability of amyloid precursor protein in Alzheimer’s disease. Brain 129(Pt 11):2984–2991. Cai, X.D., Golde, T.E., and Younkin, S.G. (1993) Release of excess amyloid beta protein from a mutant amyloid beta protein precursor. Science 259(5094):514–516. Chan, D., Janssen, J.C., Whitwell, J.L., et al. (2003) Change in rates of cerebral atrophy over time in early-onset Alzheimer’s disease: longitudinal MRI study. Lancet 362(9390):1121–1122. Citron, M., Teplow, D.B., and Selkoe, D.J. (1995) Generation of amyloid beta protein from its precursor is sequence specific. Neuron 14(3):661–670. Coon, K.D., Myers, A.J., Craig, D.W., et al. (2007) A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer’s disease. J. Clin. Psychiatry 68(4):613–618. Corder, E.H., Saunders, A.M., Strittmatter, W.J., et al. (1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261(5123):921–923. Crook, R., Verkkoniemi, A., Perez-Tur, J., et al. (1998) A variant of Alzheimer’s disease with spastic paraparesis and unusual plaques due to deletion of exon 9 of presenilin 1. Nat. Med. 4(4):452–455.

891

Cruts, M., Gijselinck, I., van der Zee, J., et al. (2006) Null mutations in progranulin cause ubiquitin-positive frontotemporal dementia linked to chromosome 17q21. Nature 442(7105):920–924. Cullen, K.M., Kocsi, Z., and Stone, J. (2006) Microvascular pathology in the aging human brain: evidence that senile plaques are sites of microhaemorrhages. Neurobiol. Aging 27(12):1786–1796. Daw, E.W., Payami, H., Nemens, E.J., et al. (2000) The number of trait loci in late-onset Alzheimer disease. Am. J. Hum. Genet. 66(1):196–204. De Jonghe, C., Zehr, C., Yager, D., et al. (1998) Flemish and Dutch mutations in amyloid beta precursor protein have different effects on amyloid beta secretion. Neurobiol. Dis. 5(4):281–286. De Strooper, B., Saftig, P., Craessaerts, K., et al. (1998) Deficiency of presenilin-1 inhibits the normal cleavage of amyloid precursor protein. Nature 391(6665):387–390. Duff, K., Eckman, C., Zehr, C., et al. (1996) Increased amyloidbeta42(43) in brains of mice expressing mutant presenilin 1. Nature 383(6602):710–713. Duff, K., and Suleman, F. (2004) Transgenic mouse models of Alzheimer’s disease: how useful have they been for therapeutic development? Brief Funct. Genomic Proteomic. 3(1):47–55. Edbauer, D., Winkler, E., Regula, J.T., Pesold, B., Steiner, H., and Haass, C. (2003) Reconstitution of gamma-secretase activity. Nat. Cell Biol. 5(5):486–488. Edison, P., Archer, H.A., Hinz, R., et al. (2007) Amyloid, hypometabolism, and cognition in Alzheimer disease: an [11C]PIB and [18F]FDG PET study. Neurology 68(7):501–508. Farrer, L.A., Cupples, L.A., Haines, J.L., et al. (1997) Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium. JAMA 278(16): 1349–1356. Farrer, M., Maraganore, D.M., Lockhart, P., et al. (2001) alphasynuclein gene haplotypes are associated with Parkinson’s disease. Hum. Mol. Genet. 10(17):1847–1851. Foster, N.L., Wilhelmsen, K., Sima, A.A., Jones, M.Z., D’Amato, C.J., and Gilman, S. (1997) Frontotemporal dementia and parkinsonism linked to chromosome 17: a consensus conference. Ann. Neurol. 41(6):706–715. Fox, N.C., Black, R.S., Gilman, S., Rossor, M.N., et al. (2005) Effects of Abeta immunization (AN1792) on MRI measures of cerebral volume in Alzheimer disease. Neurology 64(9):1563–1572. Fox, N.C., Warrington, E.K., Seiffer, A.L., Agnew, S.K., and Rossor, M.N. (1998) Presymptomatic cognitive deficits in individuals at risk of familial Alzheimer’s disease. A longitudinal prospective study. Brain 121(Pt 9):1631–1639. Freeborough, P.A., Woods, R.P., and Fox, N.C. (1996) Accurate registration of serial 3D MR brain images and its application to visualizing change in neurodegenerative disorders. J. Comput. Assist. Tomogr. 20(6):1012–1022. Games, D., Adams, D., Alessandrini, R., et al. (1995) Alzheimertype neuropathology in transgenic mice overexpressing V717F beta-amyloid precursor protein. Nature 373(6514):523–527. Gilman, S., Koller, M., Black, R.S., et al. (2005) Clinical effects of Abeta immunization (AN1792) in patients with AD in an interrupted trial. Neurology 64(9):1553–1562. Glenner, G.G., and Wong, C.W. (1984a) Alzheimer’s disease and Down’s syndrome: sharing of a unique cerebrovascular amyloid fibril protein. Biochem. Biophys. Res. Commun. 122(3):1131–1135. Glenner, G.G., and Wong, C.W. (1984b) Alzheimer’s disease: initial report of the purification and characterization of a novel cerebrovascular amyloid protein. Biochem. Biophys. Res. Commun. 120(3):885–890. Goate, A., Chartier-Harlin, M.C., Mullan, M., et al. (1991) Segregation of a missense mutation in the amyloid precursor protein gene with familial Alzheimer’s disease. Nature 349(6311): 704–706.

892

DEMENTIA

Golde, T.E. (2006) Disease modifying therapy for AD? J. Neurochem. 99(3):689–707. Guyant-Maréchal, L., Rovelet-Lecrux, A., Goumidi, L., et al. (2007) Variations in the APP gene promoter region and risk of Alzheimer disease. Neurology 68:684–687. Haass, C., Schlossmacher, M.G., Hung, A.Y., et al. (1992) Amyloid beta-peptide is produced by cultured cells during normal metabolism. Nature 359(6393):322–324. Hardy, J. (2003) The relationship between Lewy body disease, Parkinson’s disease, and Alzheimer’s disease. Ann. N. Y. Acad. Sci. 991:167–170. Hardy, J. (2005) Expression of normal sequence pathogenic proteins for neurodegenerative disease contributes to disease risk: “permissive templating” as a general mechanism underlying neurodegeneration. Biochem. Soc. Trans. 33(Pt 4):578–581. Hardy, J., Duff, K., Gwinn-Hardy, K., Perez-Tur, J., and Hutton, M. (1998) Genetic dissection of Alzheimer’s disease and related dementias: amyloid and its relationship to tau. Nat. Neurosci. 1(5): 355–358. Hardy, J., and Selkoe, D.J. (2002) The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297(5580):353–356. Hong, M., Zhukareva, V., Vogelsberg-Ragaglia, V., et al. (1998) Mutation-specific functional impairments in distinct tau isoforms of hereditary FTDP-17. Science 282(5395):1914–1917. Houlden, H., Baker, M., McGowan, E., et al. (2000) Variant Alzheimer’s disease with spastic paraparesis and cotton wool plaques is caused by PS-1 mutations that lead to exceptionally high amyloid-beta concentrations. Ann. Neurol. 48(5):806–808. Houlden, H., Baker, M., Morris, H.R., et al. (2001) Corticobasal degeneration and progressive supranuclear palsy share a common tau haplotype. Neurology 56(12):1702–1706. Houlden, H., Collinge, J., Kennedy, A., et al. (1993) Apolipoprotein E genotype and Alzheimer’s disease. Alzheimer’s Disease Collaborative Group. Lancet 342(8873):737–738. Hsiao, K., Chapman, P., Nilsen, S., et al. (1996) Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science 274(5284):99–102. Hsiao, K., Dlouhy, S.R., Farlow, M.R., et al. (1992) Mutant prion proteins in Gerstmann-Straussler-Scheinker disease with neurofibrillary tangles. Nat. Genet. 1(1):68–71. Hutton, M., Lendon, C.L., Rizzu, P., et al. (1998) Association of missense and 5'-splice-site mutations in tau with the inherited dementia FTDP-17. Nature 393(6686):702–705. Janus, C., Pearson, J., McLaurin, J., et al. (2000) A beta peptide immunization reduces behavioural impairment and plaques in a model of Alzheimer’s disease. Nature 408(6815):979–982. Kang, J., Lemaire, H.G., Unterbeck, A., et al. (1987) The precursor of Alzheimer’s disease amyloid A4 protein resembles a cell-surface receptor. Nature 325(6106):733–736. Kim, S.H., Wang, R., Gordon, D.J., et al. (1999) Furin mediates enhanced production of fibrillogenic ABri peptides in familial British dementia. Nat. Neurosci. 2(11):984–988. Klunk, W.E., Engler, H., Nordberg, A., et al. (2004) Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann. Neurol. 55(3):306–319. Klunk, W.E., Price, J.C., Mathis, C.A., et al. (2007) Amyloid deposition begins in the striatum of presenilin-1 mutation carriers from two unrelated pedigrees. J. Neurosci. 27(23):6174–6184. Kumar-Singh, S., Pirici, D., McGowan, E., et al. (2005) Dense-core plaques in Tg2576 and PSAPP mouse models of Alzheimer’s disease are centered on vessel walls. Am. J. Pathol. 167(2):527–543. Lantos, P.L., Ovenstone, I.M., Johnson, J., Clelland, C.A., Roques, P., and Rossoor, M.N. (1994) Lewy bodies in the brain of two members of a family with the 717 (Val to Ile) mutation of the amyloid precursor protein gene. Neurosci. Lett. 172(1/2): 77–79.

Laudon, H., Hansson, E.M., Melen, K., et al. (2005) A ninetransmembrane domain topology for presenilin 1. J. Biol. Chem. 280(42):35352–35360. Levy, E., Carman, M.D., Fernandez-Madrid, I.J., Power, M.D., et al. (1990) Mutation of the Alzheimer’s disease amyloid gene in hereditary cerebral hemorrhage, Dutch type. Science 248(4959): 1124–1126. Levy-Lahad, E., Wijsman, E.M., Nemens, E., et al. (1995) A familial Alzheimer’s disease locus on chromosome 1. Science 269(5226): 970–973. Lewis, J., Dickson, D.W., Lin, W.L., et al. (2001) Enhanced neurofibrillary degeneration in transgenic mice expressing mutant tau and APP. Science 293(5534):1487–1491. Lewis, J., McGowan, E., Rockwood, J., et al. (2000) Neurofibrillary tangles, amyotrophy and progressive motor disturbance in mice expressing mutant (P301L) tau protein. Nat. Genet. 25(4):402–405. Lippa, C.F., Duda, J.E., Grossman, M., et al. (2007) DLB and PDD boundary issues: diagnosis, treatment, molecular pathology, and biomarkers. Neurology 68(11):812–819. Lippa, C.F., Fujiwara, H., Mann, D.M., et al. (1998) Lewy bodies contain altered alpha-synuclein in brains of many familial Alzheimer’s disease patients with mutations in presenilin and amyloid precursor protein genes. Am. J. Pathol. 153(5):1365–1370. Lippa, C.F., Schmidt, M.L., Lee, V.M., and Trojanowski, J.Q. (1999) Antibodies to alpha-synuclein detect Lewy bodies in many Down’s syndrome brains with Alzheimer’s disease. Ann. Neurol. 45(3):353–357. Mackenzie, I.R., and Feldman, H.H. (2005) Ubiquitin immunohistochemistry suggests classic motor neuron disease, motor neuron disease with dementia, and frontotemporal dementia of the motor neuron disease type represent a clinicopathologic spectrum. J. Neuropathol. Exp. Neurol. 64(8):730–739. Masliah, E., Rockenstein, E., Veinbergs, I., et al. (2000) Dopaminergic loss and inclusion body formation in alpha-synuclein mice: implications for neurodegenerative disorders. Science 287(5456): 1265–1269. Masliah, E., Rockenstein, E., Veinbergs, I., et al. (2001) Beta-amyloid peptides enhance alpha-synuclein accumulation and neuronal deficits in a transgenic mouse model linking Alzheimer’s disease and Parkinson’s disease. Proc. Natl. Acad. Sci. USA 98(21): 12245–12250. McGowan, E., Pickford, F., Kim, J., et al. (2005) Abeta42 is essential for parenchymal and vascular amyloid deposition in mice. Neuron 47(2):191–199. McKeith, I.G., Galasko, D., Kosaka, K., et al. (1996) Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology 47(5):1113–1124. Mead, S., Mahal, S.P., Beck, J., Campbell, T., Farrall, M., Fisher, E., and Collinge, J. (2001) Sporadic—but not variant—CreutzfeldtJakob disease is associated with polymorphisms upstream of PRNP exon 1. Am. J. Hum. Genet. 69(6):1225–1235. Meyer-Luehmann, M., Coomaraswamy, J., Bolmont, T., et al. (2006) Exogenous induction of cerebral beta-amyloidogenesis is governed by agent and host. Science 313(5794):1781–1784. Miyakawa, T., Shimoji, A., Kuramoto, R., and Higuchi, Y. (1982) The relationship between senile plaques and cerebral blood vessels in Alzheimer’s disease and senile dementia. Morphological mechanism of senile plaque production. Virchows Arch. B Cell Pathol. Incl. Mol. Pathol. 40:121–129. Morgan, D., Diamond, D.M., Gottschall, P.E., et al. (2000) A beta peptide vaccination prevents memory loss in an animal model of Alzheimer’s disease. Nature 408(6815):982–985. Mukherjee, O., Kauwe, J.S., Mayo, K., Morris, J.C., and Goate, A.M. (2007) Haplotype-based association analysis of the MAPT locus in late onset Alzheimer’s disease. BMC Genet. 8:3.

52: GENETICS AND PATHOGENESIS OF ALZHEIMER’S DISEASE AND RELATED DEMENTIAS Myers, A.J., Kaleem, M., Marlowe, L., et al. (2005) The H1c haplotype at the MAPT locus is associated with Alzheimer’s disease. Hum. Mol. Genet. 14(16):2399–2404. Myers, A.J., Pittman, A.M., Zhao, A.S., et al. (2007) The MAPT H1c risk haplotype is associated with increased expression of tau and especially of 4 repeat containing transcripts. Neurobiol. Dis. 25(3):561–570. Neumann, M., Sampathu, D.M., Kwong, L.K., et al. (2006) Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science 314(5796):130–133. Nicoll, J.A., Wilkinson, D., Holmes, C., Steart, P., Markham, H., and Weller, R.O. (2003) Neuropathology of human Alzheimer disease after immunization with amyloid-beta peptide: a case report. Nat. Med. 9(4):448–485. Noble, W., Planel, E., Zehr, C., et al. (2005) Inhibition of glycogen synthase kinase-3 by lithium correlates with reduced tauopathy and degeneration in vivo. Proc. Natl. Acad. Sci. USA 102(19): 6990–6995. Nowotny, P., Simcock, X., Bertelsen, S., et al. (2007) Association studies testing for risk for late-onset Alzheimer’s disease with common variants in the beta-amyloid precursor protein (APP). Am. J. Med. Genet. B Neuropsychiatr. Genet. 144(4):469–474. Oddo, S., Caccamo, A., Shepherd, J.D., et al. (2003) Triple-transgenic model of Alzheimer’s disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron 39(3): 409–421. Pastor, P., Roe, C.M., Villegas, A., et al. (2003) Apolipoprotein epsilon4 modifies Alzheimer’s disease onset in an E280A PS1 kindred. Ann. Neurol. 54(2):163–169. Pittman, A.M., Myers, A.J., Abou-Sleiman, P., et al. (2005) Linkage disequilibrium fine mapping and haplotype association analysis of the tau gene in progressive supranuclear palsy and corticobasal degeneration. J. Med. Genet. 42(11):837–846. Polymeropoulos, M.H., Lavedan, C., Leroy, E., et al. (1997) Mutation in the alpha-synuclein gene identified in families with Parkinson’s disease. Science 276(5321):2045–2047. Poorkaj, P., Bird, T.D., Wijsman, E., et al. (1998) Tau is a candidate gene for chromosome 17 frontotemporal dementia. Ann. Neurol. 43(6):815–825. Poorkaj, P., Tsuang, D., Wijsman, E., et al. (2001) TAU as a susceptibility gene for amyotropic lateral sclerosis–parkinsonism dementia complex of Guam. Arch. Neurol. 58(11):1871–1878. Prasher, V.P., Farrer, M.J., Kessling, A.M., et al. (1998) Molecular mapping of Alzheimer-type dementia in Down’s syndrome. Ann. Neurol. 43(3):380–383. Prusiner, S.B. (2001) Shattuck lecture—neurodegenerative diseases and prions. N. Engl. J. Med. 344(20):1516–1526. Rapoport, M., Dawson, H.N., Binder, L.I., Vitek, M.P., and Ferreira, A. (2002) Tau is essential to beta-amyloid-induced neurotoxicity. Proc. Natl. Acad. Sci. USA 99(9):6364–6369. Reiman, E.M., Webster, J.A., Myers, A.J., et al. (2007) GAB2 alleles modify Alzheimer’s risk in APOE epsilon4 carriers. Neuron 54(5): 713–720. Ridha, B.H., Barnes, J., Bartlett, J.W., et al. (2006) Tracking atrophy progression in familial Alzheimer’s disease: a serial MRI study. Lancet Neurol. 5(10):828–834. Roberson, E.D., Scearce-Levie, K., Palop, J.J., et al. (2007) Reducing endogenous tau ameliorates amyloid beta-induced deficits in an Alzheimer’s disease mouse model. Science 316(5825):750– 754. Rogaev, E.I., Sherrington, R., Rogaeva, E.A., et al. (1995) Familial Alzheimer’s disease in kindreds with missense mutations in a gene on chromosome 1 related to the Alzheimer’s disease type 3 gene. Nature 376(6543):775–778. Rogaeva, E. (2002) The solved and unsolved mysteries of the genetics of early-onset Alzheimer’s disease. Neuromolecular Med. 2(1): 1–10.

893

Rovelet-Lecrux, A., Hannequin, D., Raux, G., et al. (2006) APP locus duplication causes autosomal dominant early-onset Alzheimer disease with cerebral amyloid angiopathy. Nat. Genet. 38(1): 24–26. Royston, M.C., Mann, D., Pickering-Brown, S., et al. (1994) Apolipoprotein E epsilon 2 allele promotes longevity and protects patients with Down’s syndrome from dementia. Neuroreport 5(18): 2583–2585. Sambamurti, K., Suram, A., Venugopal, C., Prakasam, A., Zhou, Y., Lahiri, D.K., and Greig, N.H. (2006) A partial failure of membrane protein turnover may cause Alzheimer’s disease: a new hypothesis. Curr. Alzheimer Res. 3(1):81–90. Schellenberg, G.D., Bird, T.D., Wijsman, E.M., et al. (1992) Genetic linkage evidence for a familial Alzheimer’s disease locus on chromosome 14. Science 258(5082):668–671. Schenk, D. (2004) Hopes remain for an Alzheimer’s vaccine. Nature 431(7007):398. Schenk, D., Barbour, R., Dunn, W., et al. (1999) Immunization with amyloid-beta attenuates Alzheimer-disease-like pathology in the PDAPP mouse. Nature 400(6740):173–177. Scheuner, D., Eckman, C., Jensen, M., et al. (1996) Secreted amyloid beta-protein similar to that in the senile plaques of Alzheimer’s disease is increased in vivo by the presenilin 1 and 2 and APP mutations linked to familial Alzheimer’s disease. Nat. Med. 2(8): 864–870. Shen, J., and Kelleher, R.J., III. (2007) The presenilin hypothesis of Alzheimer’s disease: evidence for a loss-of-function pathogenic mechanism. Proc. Natl. Acad. Sci. USA 104(2):403–409. Sherrington, R., Rogaev, E.I., Liang, Y., et al. (1995) Cloning of a gene bearing missense mutations in early-onset familial Alzheimer’s disease. Nature 375(6534):754–760. Singleton, A., Myers, A., and Hardy, J. (2004) The law of mass action applied to neurodegenerative disease: a hypothesis concerning the etiology and pathogenesis of complex diseases. Hum. Mol. Genet.13(Spec No 1):R123–R126. Singleton, A.B., Farrer, M., Johnson, J., et al. (2003) alpha-Synuclein locus triplication causes Parkinson’s disease. Science 302(5646): 841. Skibinski, G., Parkinson, N.J., Brown, J.M., et al. (2005) Mutations in the endosomal ESCRTIII-complex subunit CHMP2B in frontotemporal dementia. Nat. Genet. 37(8):806–808. Smith, R.P., Higuchi, D.A., Broze, G.J., Jr. (1990) Platelet coagulation factor XIa-inhibitor, a form of Alzheimer amyloid precursor protein. Science 248(4959):1126–1128. Spillantini, M.G., Bird, T.D., and Ghetti, B. (1998) Frontotemporal dementia and Parkinsonism linked to chromosome 17: a new group of tauopathies. Brain Pathol. 8(2):387–402. Suzuki, N., Cheung, T.T., Cai, X.D., et al. (1994) An increased percentage of long amyloid beta protein secreted by familial amyloid beta protein precursor (beta APP717) mutants. Science 264(5163): 1336–1340. Takeuchi, A., Irizarry, M.C., Duff, K., et al. (2000) Age-related amyloid beta deposition in transgenic mice overexpressing both Alzheimer mutant presenilin 1 and amyloid beta precursor protein Swedish mutant is not associated with global neuronal loss. Am. J. Pathol. 157(1):331–339. Vassar, R., Bennett, B.D., Babu-Khan, S., et al. (1999) Beta-secretase cleavage of Alzheimer’s amyloid precursor protein by the transmembrane aspartic protease BACE. Science 286(5440):735–741. Vidal, R., Frangione, B., Rostagno, A., et al. (1999) A stop-codon mutation in the BRI gene associated with familial British dementia. Nature 399(6738):776–781. Wavrant-De Vrieze, F., Crook, R., Holmans, P., et al. (1999) Genetic variability at the amyloid-beta precursor protein locus may contribute to the risk of late-onset Alzheimer’s disease. Neurosci. Lett. 269:67–70.

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DEMENTIA

Weidemann, A., Eggert, S., Reinhard, F.B.M., et al. (2002) A novel ε-cleavage within the transmembrane domain of the Alzheimer amyloid precursor protein demonstrates homology with Notch processing. Biochem. 41:2825–2835. Wijsman, E.M., Daw, E.W., Yu, X., et al. (2005) APOE and other loci affect age-at-onset in Alzheimer’s disease families with PS2 mutation. Am. J. Med. Genet. B Neuropsychiatr. Genet. 132(1): 14–20. Wisniewski, T., Ghiso, J., and Frangione, B. (1991) Peptides homologous to the amyloid protein of Alzheimer’s disease containing a

glutamine for glutamic acid substitution have accelerated amyloid fibril formation. Biochem. Biophys. Res. Commun. 180(3): 1528. Wolfe, M.S., Xia, W., Ostaszewski, B.L., Diehl, T.S., Kimberly, W.T., and Selkoe, D.J. (1999) Two transmembrane aspartates in presenilin1 required for presenilin endoproteolysis and gamma-secretase activity. Nature 398(6727):513–517. Worster-Drought, C., Hill, T.R., and McMenemey, W.H. (1933) Familial presenile dementia with spastic paralysis. J. Neurol. Psychopath. 14:27–34.

53 Diagnostic Classifications: Relationship to the Neurobiology of Dementia DANIEL I. KAUFER

A N D

STEVEN T. DEKOSKY

The diagnostic classification of dementia bridges two levels of analysis. Clinically defined syndromes based on typical signs and symptoms occupy one level, and neuropathologically based criteria derived from retrospective correlations between characteristic structural brain alterations and clinical features form the other. A common approach to classifying degenerative dementias entails identifying associations between specific clinical and pathological features to define probabilistic categories (probable and possible) of clinical diagnostic certainty. Although a neuropathologically based classification of dementia is more objective, such information is usually not available in a clinical setting. Moreover, neuropathological hallmarks of neurodegenerative dementias are usually present before overt clinical signs and symptoms become manifest. These points highlight the need for systematic longitudinal clinical assessment and for prospective clinical validation of neuropathological diagnostic criteria. Accurate clinical characterization and differentiation of dementia syndromes is essential to guiding laboratory diagnostic evaluation and identifying genetic and other biological diagnostic markers and, ultimately, disease-specific interventions. DEMENTIA: CLINICAL OVERVIEW Definition of Dementia Dementia refers to an acquired and persistent syndrome of intellectual impairment, reflecting a variety of disease processes (Cummings and Benson, 1992). As defined in Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV), the two essential diagnostic features of dementia are (1) memory and other cognitive deficits and (2) an impairment in social and occupational functioning (American Psychiatric Association [APA], 2000). Delirium and any primary psychiatric disorder that could account for the symptoms must be excluded.

Neuropsychiatric symptoms often accompany dementia and are incorporated into the specific diagnostic criteria for some dementing illnesses, such as Lewy body dementia (LBD) and frontotemporal dementia (FTD). Although memory impairment is the sine qua non of Alzheimer’s disease (AD; the most common cause of dementia in middle and late life), other intellectual or neuropsychiatric disturbances may be the initial or predominant clinical manifestation of a dementia syndrome. DSM-IV requires compromise in social and occupational roles, and this imparts a measure of ecological validity to the diagnosis of dementia. Discrepancies between this criterion and population-based cutoff scores on neuropsychological tests between normal and dementia may reflect individual differences in real-world competence related to age, educational level, cultural background, or medical and psychiatric comorbidity. With emerging biomarkers heralding the era of preclinical diagnosis, the distinction between a pathological disease state and clinical syndrome that jointly define a specific dementia will need to become more explicit. Dementia Versus Delirium Delirium (acute confusional state or encephalopathy) is a common syndrome of acquired cognitive dysfunction. Key clinical features distinguishing delirium from dementia are the primary attentional deficits associated with the former and the chronic nature of the latter. The defining characteristics of delirium are a disturbance in consciousness, attentional deficits, brief duration of symptoms, and fluctuation in symptoms over time (APA, 2000). Initial diagnosis of a dementia cannot be made reliably in the presence of delirium. In general, dementia syndromes involve functionally, metabolically, or neurochemically mediated impairment of cognitive functioning associated with structural brain alterations. By contrast, delirium states typically reflect functional brain deficits that can occur in the absence of structural lesions. 895

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This distinction is more relative than absolute, reflecting a dynamic balance between cerebral, functional, and structural perturbations. Individuals with dementia are more susceptible to delirium-producing insults and metabolic derangements that, if unattended, may exacerbate the underlying dementia or ultimately result in death. Potential reversibility is not an inherent feature of dementia as it is for delirium. Reversibility is determined principally by the nature, severity, and duration of the pathophysiologic insult or agent, as well as age of the patient.

53.1 Degenerative and Nondegenerative Dementias TABLE

Degenerative Amyloid/tau pathology Alzheimer’s disease

α-synuclein pathology Parkinson’s disease (dementia) Dementia with Lewy bodies Multisystem atrophy Tau pathology Frontotemporal dementia

PATHOLOGICAL CLASSIFICATION Etiologies Etiologies of dementia may be divided into two broad categories: degenerative and nondegenerative (Table 53.1). The first category primarily reflects pathophysiologic processes that are intrinsic to the central nervous system (CNS). Whether a dementia involves degenerative or nondegenerative processes or a combination of the two, individual factors (such as education, gender, agerelated changes, preexisting brain disease, environmental exposures, and medical and psychiatric comorbidity) may influence the clinical expression of the dementing process. Nondegenerative dementias, sometimes referred to as acquired or secondary dementias, are a heterogeneous group of disorders reflecting diverse etiologies: vascular, endocrine, traumatic, demyelinating, neoplastic, infectious, inflammatory, hydrocephalic, systemic, nutritional deficiency, and toxic conditions. Well-defined derangements of cerebral metabolism that result in highly specific cellular degeneration, as exemplified by inherited leukodystrophies and genetically determined heavy metal accumulation disorders (for example, Wilson’s disease), occupy a transitional category of metabolic dementias. Degenerative Dementias: Overview Neurodegenerative disorders account for the vast majority of adult-onset dementias. Most occur in late life and involve aberrant protein processing that is under variable genetic control (Table 53.2) (Martin, 1999; Pruisner, 2001). Four major classes of pathological protein-related neurodegenerative dementias are (1) amyloidopathies, (2) α-synucleinopathies, (3) tauopathies, and (4) trinucleotide repeat disorders. In many cases, familial and sporadic forms of a specific disorder have been described, representing the existence of disease-causing genetic mutations and other genetic factors that modify the risk. Exemplifying our expanding knowledge of such proteinmisfolding or mismetabolizing disorders, a new class of disorders referred to as trans-activation-response (TAR)

Progressive supranuclear palsy Corticobasal degeneration Trinucleotide repeat Huntington’s disease Spinocerebellar ataxias Toxic/metabolic disorders

Nondegenerative Vascular dementias Multiple cortical infarcts Binswanger’s disease Lacunar state Infectious dementia HIV dementia Whipple’s disease Neurosyphilis Demyelinating dementia Multiple sclerosis Miscellaneous dementias Symptomatic hydrocephalus Heavy metal (storage) disorders Dementia syndrome of depression

Wilson’s disease (copper)

Deficiencies (vitamin B12, niacin)

Hallevorden–Spatz syndrome (iron)

Endocrinopathies (thyroid, etc.)

Leukodystrophy Metachromatic leukodystrophy Prion-related dementiasa Creutzfeldt–Jakob disease

Chronic alcohol/drug abuse Wernicke–Korsakoff syndrome Marchiafava–Bignami disease Industrial/environmental toxins

Gerstmann–Straussler– Scheinker syndrome

Vasculitides (systemic and CNS)

Fatal familial insomnia (thalamic dementia)

Lupus erythematosus

Variant Creutzfeldt–Jakob disease (BSE)

Sjogren’s disease

aInherited, sporadic, and directly transmissable forms. BSE: bovine spongiform encephalopathy; CNS: central nervous system; HIV: human immunodeficiency virus.

deoxyribonucleic acid (DNA)-binding protein 43 (TDP43) proteinopathies have been described in association with ubiquitin-positive, tau-negative inclusions that are present in FTD and motor neuron disease (Neumann et al., 2006; Neumann et al., 2007) (see Fig. 53.1). Amyloidopathies In AD, autosomal dominant mutations in three distinct genes (presenilin 1 and 2 and the amyloid precursor protein) account for less than 5% of all cases. Genetic polymorphism of the apolipoprotein E gene modulates the risk of developing AD. The E4 allelic variant (one of 3 ApoE alleles: E2, E3, or E4) is associated with higher risk, and the E2 allele may be associated with lower risk.

53: DIAGNOSTIC CLASSIFICATIONS TABLE

897

53.2 Prevalence and Pathological Features of Selected Degenerative Dementias

Disease Alzheimer’s disease

Prevalencea 4,000,000

Genetic Factors (chrom. #) (F = familial, S = sporadic)

Abnormal Proteins

Pathological Features

F: APP (21), PS1 (14),

β -Amyloid

Amyloid (neuritic) plaques,

PS2 (1)

Tau (phosphorylated)

Neurofibrillary tangles

α-Synuclein

Lewy bodies (brain stem),

S: apolipoprotein E (19) Parkinson’s disease

500,000

F: α-synuclein (4)

loss of pigmented neurons

Parkin (recessive) S: CYP2D6 Dementia with Lewy bodies

100,000 (est.)

Parkinson’s disease with dementia

F: SNCA (α-Synuclein)

α-Synuclein

Lewy bodies (diffuse),

S: apolipoprotein E (19)

± b -Amyloid, ± Tau

Lewy neurites, ± neuritic plaques, ± neurofibrillary tangles

Frontotemporal dementia

45,000

F: tau (17); progranulin (17)

Tau, TDP-43

Huntington’s disease

30,000

F: Huntingtin (4)

Huntingtin

S: ? Progressive supranuclear palsy

15,000 10,000

F: ?

Tau

400

Midbrain atrophy, globose neurofibrillary tangles

α-Synuclein

Glial and neuronal

F: Prion protein gene

Prion protein

Amyloid plaques

S: ?

(β-pleated sheet)

(prion protein)

F: ? S: ?

Creutzfeldt–Jakob disease

Striatal and cortical atrophy, intraneuronal inclusions

S: ? Multisystem atrophy

Frontotemporal atrophy ± tau or TDP-43 inclusions

S: ?

inclusions

Estimated prevalence in the United States (2000). Sources: Martin (1999), Pruisner (2001), Baker et al. (2006).

a

53.1 Clinical syndromes in relation to protein pathology. The spectral relationship between cognitive and motor syndromes in selected neurodegenerative disorders is schematically illustrated. Most cases of DLB and PDD have concomitant amyloid pathology. FTD clinical syndromes are associated primarily with either tau or TDP43 protein pathology. TDP-43 pathology is associated with “pure” FTD, “pure” MND, and the combination of FTD and MND. AD: Alzheimer’s disease; CBD: corticobasal degeneration; DLB: dementia with Lewy bodies; FTD: frontotemporal dementia; MND: motor neuron disease; PDD: Parkinson’s disease with dementia; PSP: progressive supranuclear palsy.

FIGURE

Routine clinical testing for genotype, however, is not recommended (Plassman and Breitner, 1996; Mayeux et al., 1999; Knopman et al., 2001). Despite the genetic diversity of AD, the pathological features are similar. These include the extracellular accumulation of β -amyloid (Aβ) plaques and the intracellular accumulation of neurofibrillary tangles in selected brain regions (The National Institute on Aging and the Reagan Institute Working Group, 1997). The former derive from alternative proteolytic processing of the amyloid-precursor protein (APP), whereas the latter accrue from hyperphosphorylation and extensive cross linking of the microtubule-associated protein tau, which normally stabilizes the neuronal cytoskeleton. Reduced levels of the synthetic enzyme for acetylcholine (choline acetyltransferase) and severe cell loss in basal forebrain cholinergic nuclei are pathological concomitants of AD; but recent evidence suggests that though functional alterations in cholinergic neurotransmission occur early in the course, structural cholinergic deficits do not become prominent until later stages of the disease process (Davis et al., 1999; DeKosky et al., 2002). The topographic distribution and spread of neurofibrillary tangles is the basis for pathologically staging AD (Braak and Braak, 1991; Delacourte et al., 1999). All known genetic mutations underlying familial forms of AD cause aberrant

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processing of Aβ, and other evidence suggests that amyloid pathology may have a preeminent etiological role (Selkoe, 2000). Although the primary etiology of sporadic AD remains controversial and may well be multifactorial, amyloid mismetabolism remains central to the pathological cascade. Prion-related diseases are unique in that they may arise as either a genetically determined, infectiously transmitted, or sporadic disorder (Pruisner, 2001). Creutzfeldt– Jakob disease (CJD), the most common prion disorder, occurs by all these mechanisms, whereas fatal familial insomnia (thalamic dementia) and Gerstmann–Straussler– Scheinker syndrome are only associated with a dominantly inherited mutation in the prion protein gene. Infectious transmission represents less than 1% of all cases of prion diseases, typically resulting from direct contact with contaminated instruments or tissue. There is, however, the potential for widespread transmission, as suggested by the 100 or so cases of human variant CJD (bovine spongiform encephalopathy) that have occurred in the United Kingdom. Pathological alteration of the normal prion protein results in a conformational shift from a primarily α-helical to a mostly β-pleatedsheet structure that tends to form amyloid deposits. The altered form of the prion protein is rendered infectious by inducing a similar conformational change in other normal prion proteins. This process underlies the protean and rapidly progressive clinical manifestations of CJD. The previous designation of cerebrospinal fluid (CSF) protein 14–3-3 as a “gold standard” diagnostic marker for CJD (Knopman et al., 2001) has been questioned, with current efforts focusing on diffusion-weighted magnetic resonance imaging (MRI) and serum biomarkers in addition to 14–4-3 (Shiga et al., 2004).

α-Synucleinopathies Parkinson’s disease (PD) is defined by the presence of αsynuclein-containing intracytoplasmic inclusions (Lewy bodies) that accumulate in the substantia nigra and other pigmented nuclei of the brain stem. Dementia with Lewy bodies (DLB), a recently defined class of degenerative dementia, is characterized by brain stem and cortical Lewy bodies and abnormal neurofilaments (Lewy-related neurites) in the CA2–3 region of the hippocampus (McKeith et al., 1996; Perry et al., 1996). Lewy body pathology is seen in 15%—25% of all dementia cases, most commonly in conjunction with pathological features of AD (that is, amyloid plaques), referred to as the Lewy body variant of AD by some authors (Hansen et al., 1990) and as mixed AD/DLB by others. Three pathological subtypes of DLB based on the topographical distribution of Lewy bodies are recognized: (1) brain-stem predominant, (2) limbic (transitional), and (3) neocortical. Neurotransmitter deficits

in DLB include the loss of dopaminergic neurons from the substantia nigra, as in PD, and more severe reductions in neocortical cholinergic markers compared to AD (Tiraboschi et al., 2000; Bohnen et al., 2003). Multisystem atrophy (MSA) refers to a degenerative parkinsonian disorder with variable associated features, including autonomic, cerebellar, and pyramidal tract dysfunction. Three clinical variants of MSA are recognized: (1) striatonigral degeneration (SND), (2) Shy– Drager syndrome (SDS), and (3) olivopontocerebellar atrophy (OPCA; Wenning et al., 1994). All have a common pathological substrate of α-synuclein-containing glial cytoplasmic inclusions that are variably distributed in the cortex and subcortical regions, cerebellum, spinal cord, and dorsal root ganglia (Penney, 1995; Tu et al., 1998). Consensus diagnostic criteria for MSA have suggested two main forms, based on the predominant clinical feature: (1) MSA—Parkinson (MSA-P) or (2) MSA—cerebellar (MSA-C) (Gilman et al., 1999). Previously described cases of SND and SDS are classified as MSA-P, and sporadic OPCA is referred to as MSA-C. Tauopathies Frontotemporal dementia (FTD) is a spectrum of clinicopathological disorders and is divided into three main types: (1) Pick’s disease, (2) non-Pick’s FTD, and (3) FTD with motor neuron disease (The Lund and Manchester Groups, 1994; McKhann et al., 2001). These FTD variants are virtually indistinguishable with respect to dementia symptoms and gross pathological changes. Microscopic alterations (ballooned neurons and tau-positive Pick bodies) define Pick’s disease and are associated with other pathological features common to all three variants: selective frontal-temporal cortical atrophy and neuronal loss, widespread astrocytic gliosis, and a variable degree of spongiform changes. An autosomal dominant mutation on chromosome 17 has been identified as one cause of familial FTD that is typically associated with extrapyramidal motor signs (Wilhelmsen et al., 1994; Yamaoka et al., 1996). Mutations in a gene coding for microtubule associated tau (MAPT) protein on chromosome 17 have been associated with familial cases of FTD, usually with parkinsonian features (Hong et al., 1998). Abnormal structure or altered splicing of the MAPT gene results in impaired binding of tau protein to microtubules and its subsequent polymerization into neurofibrillary tangles. The most common form of familial FTD is associated with mutations in the progranulin gene that, like the MAPT gene, is also located on chromosome 17 (Baker et al., 2006). Two other degenerative dementias classified as tauopathies are progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD), which exhibit pathological features that overlap with those of FTD (Feany et

53: DIAGNOSTIC CLASSIFICATIONS

al., 1996; Litvan et al., 1996; Sergeant et al., 1999). Progressive supranuclear palsy is distinguished by the presence of globose neurofibrillary tangles (distinct from those of AD) composed of aggregated tau protein and accompanied by neuronal loss and gliosis in the subthalamic nucleus, globus pallidus, substantia nigra, and other subcortical nuclei. The pathological hallmarks of CBD are large, achromatic neurons and astrocytic plaques; these tend to be asymmetrically distributed in posterior cortical areas and subcortical regions affected in PSP. A specific tau polymorphism is common to PSP and CBD (Houlden et al., 2001). TDP-43 Proteinopathies Although a number of familial cases of FTD were associated with MAPT mutations on chromosome 17, it has been known that other familial cases of FTD were not associated with tau pathology. Recent work has identified TDP-43 as the major component of pathologic inclusions associated with FTD cases that are taunegative, including sporadic and familial forms of the disease (Neumann et al., 2006, 2007). TDP-43 is also a pathologic hallmark of amyotrophic lateral sclerosis (ALS), a form of motor neuron disease, providing a common link between FTD and ALS. The prominent role of TDP-43 in different forms of FTD, including non-tau-sporadic and familial forms, and FTD associated with motor neuron disease, has led to a recent revision to the classification of FTD-associated disorders (Cairns et al., 2007). Trinucleotide repeats. Huntington’s disease (HD) is somewhat unique in that all cases are inherited in an autosomal dominant pattern. In HD, a disease-causing mutation in the huntingtin gene located on chromosome 4 results in an abnormally long cytosine-adenosineguanine (CAG) trinucleotide repeat sequence (Huntington’s Disease Research Collaborative Group, 1993). An abnormal form of huntingtin protein is deposited in neurons in vulnerable areas of the brain. A higher number of trinucleotide repeats is associated with younger age of onset. Spinocerebellar ataxias are another class of neurodegenerative disorders characterized by inherited trinucleotide repeat sequences; dementia is a variable feature. PATHOPHYSIOLOGY Neurotransmitter Systems There are two general types of central neurotransmitter systems: (1) local or interneuron neurotransmitters, such as γ -aminobutyric acid (GABA) and neuropeptides, and (2) projection neurotransmitters, including acetylcholine, dopamine, serotonin, and norepinephrine (Cummings

899

and Coffey, 1994). The principal excitatory (glutamate) and inhibitory (GABA) neurotransmitters of the CNS mediate neuronal information transfer in local corticalcortical and cortical-subcortical circuits. Aberrant or dysregulated activation of excitatory amino acid transmitter receptors for glutamate and N-methyl-D-aspartate (NMDA) can trigger a pathological cascade resulting in toxic levels of intracellular calcium. Excitotoxic mechanisms have been hypothesized to play a role in a wide range of neurological disorders by precipitating neurotoxic neuronal death in specific systems (Lipton and Rosenberg, 1994). Classic neurotransmitters have been associated most closely with cognitive and neuropsychiatric symptoms in dementia. Collectively, cholinergic and monoaminergic projection systems regulate the excitatory and inhibitory tone of multiple cortical and subcortical neural circuits, exerting a modulatory influence on cognitive processes, mood, emotional states, and goal-directed behavior (Mesulam, 1990; Cooper et al., 1991; Cummings and Coffey, 1994). Disruption of these projection systems contributes to cognitive dysfunction (for example, of attention, memory, language) and neuropsychiatric symptoms (for example, depression, apathy, psychosis) in AD and other dementing illnesses. Efforts to relieve symptoms in AD by augmenting cholinergic function may have beneficial neuropsychiatric as well as cognitive effects (Cummings and Kaufer, 1996), but they are limited by neuronal death, synapse loss, and metabolic dysfunction induced by neurofibrillary tangles (DeKosky and Scheff, 1990; DeKosky, 1995). Neuroimaging Structural imaging techniques (computed tomography [CT]) and MRI are useful in the evaluation and differential diagnosis of dementing disorders (Knopman et al., 2001). Mass lesions, cerebrovascular disease, demyelination, and focal or regionally selective atrophy are associated with some degenerative dementias. Quantitative MRI methods also show promise in the differential diagnosis of dementia and in preclinical detection of early AD (Kaufer et al., 1997; Jack et al., 1999). In addition to gross structural alterations, underlying metabolic or cerebral perfusion derangements may be detectable by MRI spectroscopy or with functional neuroimaging techniques (Pritchard and Brass, 1992). Functional imaging based on quantitative radioactive tracer measurements of cerebral blood perfusion with single photon emission computed tomography (SPECT) or brain glucose metabolism with positron emission tomography (PET) may identify regional cerebral functional abnormalities that parallel the distribution of pathology in selected diseases. Alzheimer’s disease is typically associated with functional deficits in temporal and parietal lobe areas, whereas FTD is characterized by decreased

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metabolism or perfusion in frontal and anterior temporal lobe regions (Miller et al., 1991). Functional imaging techniques with radioactive tracers to assess the functional integrity of striatal dopamine and cardiac sympathetic (norepinephrine) terminals have also been recognized as having diagnostic utility in DLB (McKeith et al., 2005). Hypoperfusion on SPECT scan or glucose hypometabolism on PET scan in the occipital lobes in conjunction with abnormalities in temporal and parietal patterns shows promise for distinguishing DLB from AD (Lobotesis et al., 2000; Minoshima et al., 2001). Although functional imaging is not recommended for routine use in the diagnosis of dementia (Knopman et al., 2001), PET imaging for diagnosing or confirming dementia highlights has potential utility as an ancillary clinical diagnostic tool (Silverman et al., 2001). Burgeoning research applications of PET include the advent of in vivo amyloid imaging with Pittsburgh Compound B (Klunk et al., 2004) and other putative tracers for preclinical AD (Small et al., 2006), as well as distinguishing AD and FTD (Foster et al., 2007). In particular, neuroimaging for detection of disease-specific proteins (DeKosky and Marek, 2003) will be utilized in specific diagnosis, assessing pharmacologic interventions, and in preclinical detection (Mintun et al., 2006). CLINICAL SYNDROMES Functional Classification: Cortical and Subcortical Neurodegenerative processes selectively involve topographically or functionally related neural systems. For example, pathological involvement in AD is concentrated in medial temporal, limbic, and temporal-parietal association cortices, whereas FTD primarily affects frontal and anterior temporal neocortical and limbic-related regions. By contrast, HD, PD, and PSP are degenerative disorders in which subcortical brain regions, particularly the striatum, are the principal loci of pathological alterations. Although the anatomical regions and functional systems affected by various degenerative dementias are relatively well characterized, the determinants of selective vulnerability underlying specific disease processes are poorly understood. A systematic approach to the differential diagnosis of dementia is aided by recognition of two distinctive patterns of clinical features: cortical and subcortical (Cummings and Benson, 1992). Cerebral cortical areas represent functional domains that are interconnected in modular serial and parallel networks subserving specific information processing functions (Mesulam, 1990). Structural or functional disturbances in these cortically based networks may produce deficits in instrumental intellectual skills including memory, language, or visuospatial functions. Anatomically, the striatum (caudate and putamen), globus pallidus, anterior and medial thalamus, and substantia nigra are interconnected with frontal

cortical regions in a series of circuits with motor and neurobehavioral affiliations (Alexander et al., 1986; Cummings, 1993). In contrast to the specific nature of intellectual disturbances in a cortical dementia, a subcortical dementia entails more diffuse impairment of mental functioning, including dilapidated thinking, cognitive slowing, memory retrieval deficits, and executive dysfunction (for example, impaired judgment and planning). Subcortical dementia is frequently associated with extrapyramidal dysfunction. Parkinson’s disease, HD, and PSP, as well as subcortical vascular disease, white matter diseases, and hydrocephalus, all exhibit clinical symptoms that reflect involvement of the basal ganglia and interconnected structures (Albert et al., 1974; Cummings and Benson, 1984). Although the cortical-subcortical functional classification of dementia does not strictly correlate with regions affected by pathology, it provides a useful heuristic differential diagnostic framework. Differential Diagnosis The differential diagnosis of dementia outlined below derives from the cortical-subcortical dichotomy but emphasizes elementary clinical features as the organizing principle (Fig. 53.2; Table 53.3). The first major branch point of this classification is based on attention versus memory deficits. If memory deficit is a primary feature, further distinction is based on the type of memory disturbance (learning vs. retrieval). The nonspecific initial manifestations of some dementias are addressed by inclusion under multiple headings. The American Academy of Neurology practice parameter details guidelines for the clinical evaluation of dementia (Knopman et al., 2001). Isolated Cognitive or Psychiatric Symptoms The initial manifestations of a dementia may include only neuropsychiatric symptoms or an isolated cognitive impairment (for example, memory, language, or visuospatial disturbance) in the absence of significant attentional or memory disturbances. Depending on the clinical circumstances, a CT or MRI brain scan may be indicated to rule out a primary CNS process (for example, neoplasm, stroke, subdural hematoma). Frontotemporal dementia may present with primarily neuropsychiatric manifestations, often beginning with disinhibited personality changes or depressive symptoms (Miller et al., 1991). Two clinical subtypes of FTD may also present as isolated language disturbances involving either expressive (primary progressive aphasia) or receptive (semantic dementia) linguistic functions (Neary et al., 1999). Initial manifestations of DLB may include prominent visual hallucinations and fluctuating attentional disturbances in the absence of a frank dementia (McKeith et al., 1996; McKeith et al., 2005).

53: DIAGNOSTIC CLASSIFICATIONS TABLE

901

53.3 Clinico-anatomical Features of Selected Degenerative Dementias

Etiology

Clinical Features

Alzheimer’s

Memory deficit (L)

disease Frontotemporal dementia

Neuroimaging Findings MRI (M)/PET (P)

Anatomical Correlates Medial temporal, nucleus basalis

Hippocampal atrophy (M)

Aphasia, apraxia, agnosia

Temporal and parietal neocortex

↓ Temporal-parietal (P)

Memory deficit (R)

Dorsolateral prefrontal cortex

Frontal-temporal atrophy (M)

Speech/language disorders

Frontal/temporal neocortex (left)

↓ Frontal-temporal (P)

Disinhibition

Orbitofrontal cortex (right)

Hyperorality (Kluver–Bucy)

Amygdala/anterior temporal cortex

Dementia with

Memory deficit (L or R)

Medial temporal, prefrontal cortex

↓ Temporal-parietal-occipital

Lewy bodies

Fluctuating attention

Reticular activating system (?)

(P)

Extrapyramidal signs

Substantia nigra

↓ striataldopamine binding

Psychosis (hallucinations)

Temporal cortex, striatum (?)

(P)

Progressive

Supranuclear gaze palsy

Midbrain

Midbrain atrophy (M)

supranuclear

Dysarthria/dysphagia

Bulbar cranial nerves

↓ Frontal-thalamic (P)

palsy

Gait/balance disturbances, axial rigidity

Globus pallidus, subthalamic nucleus, substantia nigra

Corticobasal

Unilateral limb signs (dystonia, myoclonus)

Subthalamic nucleus, thalamus, globus pallidus

Cortical sensory loss, apraxia, alien hand

Parietal/frontal neocortex (focal and asymmetric)

Rigidity, gaze palsy (late)

Midbrain

Huntington’s

Memory deficit (R)

Frontal-striatal (caudate)

Caudate atrophy (M)

disease

Executive dysfunction

Frontal-striatal (caudate)

↓ Striatal-frontal (P)

Choreiform movements

Putamen, subthalamic nucleus, globus pallidum

Creutzfeldt–

Memory deficit (L or R)

Medial temporal/frontal-striatal

Diffusion-weighted hyperintensities (M)

Jakob disease

Ataxia, myoclonus

Cerebellar, basal ganglia

↓ Multifocal/diffuse (P)

Language disturbances

Frontal-temporal

degeneration

Focal or asymmetric cortical atrophy (M) ↓ Cortical (focal or asymmetric) (P)

L: learning deficit; R: retrieval deficit; MRI: magnetic resonance imaging; PET: positron emission tomography (glucose metabolism).

The fluctuating level of consciousness in DLB may mimic a delirium, but it is distinguished by its persistent nature and the absence of metabolic disturbances. Focal, asymmetric degenerative syndromes can produce isolated language or visuospatial disturbances, as in the initial stages of CBD (Mesulam, 1982; Rinne et al., 1994; Caselli, 1995). Mild cognitive impairment (MCI) is characterized by short-term memory deficits (amnestic form) in the absence of other cognitive deficits or functional impairment (Petersen et al., 1999). Up to 50% of individuals classified as having MCI will develop AD within 5 years, underscoring the importance of MCI as a risk factor or potential diagnostic marker for AD and as an entry point for therapeutic intervention (Petersen et al., 2001). Clinico-pathological data suggest that neurofibrillary tangle pathology is commonly present in amnestic MCI (Markesbery et al., 2006). Cerebrospinal fluid studies in MCI indicate that an “AD-like” pattern of lower-than-normal Aβ and elevated tau or phospho-tau predicts conversion to AD in 90% of such cases (Hansson et al., 2006). Importantly, absence of these CSF changes was associ-

ated with less than 10% of these cases not converting to AD, indicating that amnestic MCI is not invariably AD, and careful evaluation and longitudinal follow-up are necessary. Memory Deficit: Learning versus Retrieval The ability to learn new information is strongly dependent on the integrity of the hippocampus and related medial temporal lobe limbic circuits; a deficit in the ability to form new memory traces is referred to as anterograde amnesia. The inability to recall previously learned information, referred to as retrograde amnesia, is dependent in part on frontal lobe and related subcortical circuits. In learning and retrieval types of memory disorders, spontaneous recall is impaired. Clinically, a retrieval memory deficit is distinguished from a deficit in learning by the ability to recognize target stimuli from a learning trial (for example, a word list) after a delay, either with the aid of cues (cued recall) or from among choices that include target and nontarget stimuli (Cummings and Benson, 1992).

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FIGURE 53.2 Differential diagnosis of dementia. R/O: “Rule out”; AIDS: acquired immunodeficiency syndrome; AD: Alzheimer’s disease; CBD: corticobasal degeneration; CJD: Creutzfeldt–Jakob disease; CNS: central nervous system; DLB: dementia with Lewy bodies; EPS: extrapy-

Learning Deficit: Differential Diagnosis Impaired learning (anterograde amnesia) is also referred to as an amnestic syndrome; head trauma, Korsakoff’s syndrome, herpes encephalitis, and hypoxia are among the most common causes. Alzheimer’s disease may present with memory impairment only (that is, MCI) and should be considered as a provisional diagnosis in the absence of other identifiable aetiologies. If AD is the cause, memory functions will continue to decline and other cortically based cognitive disturbances, such as executive, language, and visuospatial disturbances, will emerge. Laboratory screening for aberrant metabolic factors (that is, thyroid function and vitamin B-12 level) and a CT or MRI brain scan to evaluate possible CNS lesions should be pursued to rule out alternative etiologies, particularly those that may be reversible. Vascular dementia (VaD) syndromes usually manifest focal or lateralized neurologic signs. Dementia with Lewy bodies may involve either a learning or retrieval type of memory impairment; concomitant delirium-like features and extrapyramidal signs may help distinguish DLB from AD (Mega et al., 1996), although AD is frequently a concomitant diagnosis. Alzheimer’s disease is the prototypic cortical dementia, principally involving neocortical association areas and related medial temporal lobe structures, with relative

ramidal signs; FTD: frontotemporal dementia; HIV: human immunodeficiency virus; HD: Huntington’s disease; MCI: mild cognitive impairment; MSA: multisystem atrophy; NPH: normal-pressure hydrocephalus; PSP: progressive supranuclear palsy; VaD: vascular dementia.

preservation of primary motor and sensory areas. In addition to progressive short-term memory loss, core symptoms are “cortical” deficits: aphasia, apraxia, and agnosia (McKhann et al., 1984). Visuospatial dysfunction and word-finding difficulties are common early manifestations. Apathetic indifference, diminished insight or lack of awareness of deficits, and impaired abstract thinking frequently accompany the core neuropsychological deficits. Focal neurological signs are usually absent early on; extrapyramidal motor dysfunction, myoclonus, or seizures may develop late in the course. If extrapyramidal symptoms emerge concurrently with cognitive problems, the diagnosis of DLB must be considered. National Institute for Neurological and Communication Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable AD include age of onset between 40 and 90 years, deficits in two or more cognitive domains, progression of deficits for at least 6 months, undisturbed consciousness, and the absence of another reasonable diagnosis (McKhann et al., 1984). Possible AD is reserved for cases that, in addition to meeting the above criteria, have an atypical clinical presentation or have another brain-based disorder that is not thought to contribute significantly to the clinical manifestations. Increasing knowledge of biomarkers as early indicators of incipi-

53: DIAGNOSTIC CLASSIFICATIONS

ent disease has led to the proposal of research criteria for AD that include only amnestic disorder and the presence of a biomarker of AD (Dubois et al., 2007). Retrieval Deficit: Differential Diagnosis Some clinical syndromes of dementia with retrieval memory deficits are accompanied by extrapyramidal signs, reflecting dysfunction in one or more frontal-subcortical circuits. A retrieval type of memory deficit in association with other features of a “subcortical” dementia characterizes acquired immune deficiency syndrome (AIDS)related cognitive impairment. Two types of dementiarelated syndromes, based on severity, have been proposed and clinically validated: (1) human immunodeficiency virus (HIV)-1-associated dementia complex (ADC) and (2) HIV-1-associated minor cognitive/motor disorder (The Dana Consortium on Therapy for HIV Dementia and Related Cognitive Disorders, 1996). Testing for HIV should be pursued if appropriate risk factors are present in conjunction with relevant signs and symptoms. Frontotemporal dementia is associated with extrapyramidal signs (for example, familial FTD-17) or features of motor neuron disease in 10%–20% of cases (The Lund and Manchester Groups, 1994; Cairns et al., 2007). In cases where depression is prominent, a history of depression is present, and signs of other neurological disorders are lacking, the possibility of dementia associated with depression (pseudodementia or dementia syndrome of depression) may warrant a diagnostic “challenge” with antidepressants (Caine, 1981). In cases where depression is accompanied by significant cognitive deficits, antidepressant therapy may relieve the mood disturbance and reveal an underlying dementia, most commonly AD. Extrapyramidal features may also be present in VaD syndromes, particularly those due to multiple lacunar infarcts or diffuse and severe periventricular white matter ischemia (Binswanger’s disease). Normal-pressure hydrocephalus (NPH) produces a rapidly progressive and potentially reversible subcortical dementia accompanied by incontinence and gait disturbance. Computed tomography or MRI typically shows ventricular enlargement out of proportion to the degree of cortical gyral atrophy, but clinical correlation is essential. Clinical symptoms, particularly the gait disturbance, may resolve with a ventriculo-peritoneal shunt; shorter duration and an identifiable etiology (for example, meningitis, subdural hematoma) may predict a better response to shunting; Graff-Radford et al., 1989). Vascular dementia is a heterogeneous syndrome with multiple clinical presentations, depending on lesion type and location (Roman et al., 1993). Infarctions in the territory of large cerebral vessels produce characteristic syndromes of higher intellectual dysfunction, such as aphasias, neglect, or visuospatial difficulties, with or without

903

motor signs, depending on the regions and the extent of brain damage. The occurrence of a single stroke may predict subsequent cognitive decline that is not accompanied by further clinically apparent strokes (Moroney et al., 1996). The pathological mechanism of progressive dementia in this context remains unclear. Diffuse or multifocal small vessel ischemic disease can result in dementia arising from multiple lacunar infarcts. This form of VaD is associated with a preponderance of lesion sites in the frontal lobe white matter or basal ganglia, implicating disruption of frontal-subcortical circuit pathways as the relevant pathological mechanism (Ishii et al., 1986). More diffuse involvement of subcortical white matter secondary to small vessel ischemia (so-called Binswanger’s disease) also functionally disconnects cortical and subcortical regions. Vascular dementia occurs more commonly as a mixed dementia syndrome in conjunction with AD than in isolation (Bennett et al., 2005, 2006). National Institute for Neurological Disorders and Stroke-Association Internationale pour la Recherche et l’Enseignement en Neurosciences (NINDS-AIRENS) diagnostic criteria for probable VaD (Roman et al., 1993) include the presence of dementia, focal neurological signs, relevant cerebrovascular lesions on brain imaging, and an imputed relationship between the dementia syndrome and the cerebrovascular lesions. This relationship must either reflect onset of dementia within 3 months of a stroke, abrupt cognitive deterioration, or fluctuating stepwise progression. Possible VaD is used when the 3-month time requirement is not met. Validation studies for the NINDS-AIRENS and other criteria for VaD have generally shown low sensitivity (Knopman et al., 2001). A genetically determined VaD syndrome, cerebral autosomal dominant arteriopathy with subcortical infarctions and leukoencephalopathy (CADASIL), has been described and linked to Notch3 mutations on chromosome 19 (Tournier-Lasserve et al., 1993; Joutel et al., 1996). Typically, CADASIL presents in early to middle adulthood and is associated with multiple subcortical infarcts and confluent subcortical white matter ischemic changes of the Binswanger’s type and (in contrast to other VaD syndromes) is independent of vascular risk factors. Extrapyramidal signs in conjunction with retrieval memory deficits are central features of many degenerative dementing illnesses. Huntington’s disease typically presents in early to middle adulthood with choreiform movements and behavior and personality changes, including irritability, depression, and impulsivity (Folstein, 1989; Shoulson, 1990). Early-onset cases are more commonly associated with paternal inheritance, seizures, and parkinsonian features. Parkinson’s disease is the prototypical extrapyramidal syndrome characterized by resting tremor, bradykinesia, limb rigidity, and postural imbalance. Frank depression and dementia occur in 30%– 40% of individuals who are affected (Cummings and

904

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Benson, 1992); with longer duration of the PD, dementia may be over 50%. Consensus diagnostic criteria for DLB (McKeith et al., 1996) require dementia, one or more core features (fluctuating attention, extrapyramidal signs, visual hallucinations), and supportive clinical features (for example, sensitivity to neuroleptics, frequent falls). These provide a probabilistic clinical diagnosis of DLB. Probable DLB is used when two or more of the core features are present with dementia, and possible DLB refers to a dementia syndrome with one of the core features. A prospective validation study by Lopez and colleagues (2002) suggested that consensus diagnostic criteria for DLB have high specificity but low sensitivity, particularly when concomitant AD pathological features are present. Recently revised criteria for DLB (McKeith et al., 2005) identify two other clinical features as “suggestive”: rapid-eye-movement (REM) sleep behavior disorder and neuroleptic sensitivity. Either of these two features counts as a core feature if at least one other core feature is present. The revised DLB criteria also include provisions for a probabilistic basis for the pathological diagnosis of DLB based on the predominance of cortical and limbic Lewy bodies relative to the density of neurofibrillary tangles. This addition to the criteria explicitly addresses the problem of overlapping etiologies. Although the consensus criteria view DLB and PD dementia (PDD) as separate disorders, another recent study (Apaydin et al., 2002) observed limbic and neocortical Lewy bodies to be the best predictor of dementia in PDD. The similarities between DLB and PDD are evident in diagnostic criteria for PDD (Emre et al., 2007) and have been suggested to form a spectrum of “Lewy body disorders” distinguished primarily by the predominant initial clinical features (Lippa et al., 2007). Progressive supranuclear palsy is distinguished from PD by the absence of a resting tremor, the presence of axial (neck and trunk) rigidity, more severe speech and swallowing difficulties, a greater degree of gait and balance impairment, and limitation in voluntary downward gaze (supranuclear gaze palsy) (Collins et al., 1995). Midbrain atrophy on MRI may be a helpful diagnostic sign (Oba et al., 2005; Reich, 2006). Corticobasal degeneration is a rare disorder that may present with unilateral or asymmetric signs of rigidity, myoclonus, apraxia (manifested as “alien hand” phenomena, which refers to a limb that feels “foreign” and may act in an autonomous manner; Riley et al., 1990; Rinne et al., 1994). Other features include visuospatial (nondominant hemisphere) or language (dominant hemisphere) dysfunction and extrapyramidal motor signs akin to those of PSP. Multisystem atrophy is a group of parkinsonian dementia syndromes that respond poorly to dopaminergic therapy. Compared to PD, striatonigral degeneration (SND) is distinguished by the absence of a resting tremor, symmetrical motor signs, more severe autonomic dys-

function, and more rapid functional decline. The presence of laryngeal stridor and pyramidal tract signs (for example, Babinski sign) may also help distinguish SND from PD. Cognitive function in SND is relatively preserved, although executive deficits are characteristically observed on formal neuropsychological testing (Robbins et al., 1992). Patients with SND may initially respond to levodopa to a limited degree, but the duration of benefit is typically short lived, and treatment is not well tolerated in many cases. Shy–Drager syndrome is distinguished by early, severe dysautonomia, including orthostatic hypotension, urinary problems, constipation, impotence, and sweating. Orthostatic hypotension may be particularly disabling and can be exacerbated by levodopa and other dopaminergic drugs. Sporadic OPCA is distinguished primarily by dysarthria and ataxia in association with marked cerebellopontine atrophy on structural brain imaging. Parkinsonian motor signs and dysautonomia are variably present. Impaired saccadic eye movements and vertical gaze palsy may also occur. Sporadic OPCA, viewed as a form of MSA, is typically distinguished from hereditary forms of OPCA, which are a subtype of spinocerebellar ataxia. Sporadic CJD occurs in approximately 4 out of 1,000,000 adults aged 60 years or older (Pruisner, 2001). The initial clinical presentation is often nonspecific and may include ataxia or other elementary neurological signs. Disease progression is relentless, with the average duration from symptom onset to death being approximately 9 months. In addition to dementia, language disturbances and myoclonic jerking of the limbs are common features. A CSF test result of 14–3-3 protein may aid the diagnosis, but the specificity of this test is controversial (Knopman et al., 2001; Pruisner, 2001). A periodic spike discharge pattern on electroencephalogram (EEG) often develops later in the course, and recent studies have called attention to the presence of multifocal subcortical signal hyperintensities on diffusionweighted MRI imaging (Mittal et al., 2002). SUMMARY AND FUTURE DIRECTIONS Current classifications of dementia involve mapping the intersection of clinical and neuropathological features. Although the NINCDS-ADRDA diagnostic criteria for AD have been well validated, probabilistic diagnostic classifications for VaD and DLB have not (Knopman et al., 2001). There is significant clinical and pathological overlap among disorders (Langa et al., 2004), where the boundaries between syndromes may be more accurately represented along a spectrum of clinical-pathological features, as depicted in Figure 53.1. Clinical diagnostic heterogeneity within such overlap zones reflects the variable clinical expression of underlying pathological substrates. Increased information about genetic and envi-

53: DIAGNOSTIC CLASSIFICATIONS

ronmental contributions to dementia risk and etiology should yield a more precise, neurobiologically based differential diagnosis. Eventually, preclinical detection of AD and other degenerative dementias should be possible, along with prophylactic therapies that slow or stop the emergence of dementia symptoms. As fundamental mechanisms of aberrant protein processing in neurodegenerative disorders become elucidated, more definitive diagnostic and therapeutic approaches to dementing disorders will converge.

REFERENCES Albert, M.L., Feldman, R.G., and Willis, A.L. (1974) The “subcortical dementia” of progressive supranuclear palsy. J. Neurol. Neurosurg. Psychiatry 37:121–130. Alexander, G.E., Delong, M.R., and Strick, P.L. (1986) Parallel organization of functional circuits linking basal ganglia and cortex. Annu. Rev. Neurosci. 9:357–381. American Psychiatric Association. (2000) Diagnostic and Statistical Manual of Mental Disorders, 4th ed., text rev. Washington, DC: Author. Apaydin, H., Ahlskog, E.A., Parisi, J.E., Boeve, B.F., and Dickson, D.W. (2002) Parkinson disease neuropathology: Later-developing dementia and loss of the levodopa response. Arch. Neurol. 59: 102–112. Baker, M., Mackenzie, I.R., Pickering-Brown, S.M., et al. (2006) Mutations in progranulin cause tau-negative frontotemporal dementia linked to chromosome 17. Nature 442:916–919. Bennett, D.A., Schneider, J.A., Arvanitakis, Z., et al. (2006) Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology 66:1837–1844. Bennett, D.A., Schneider, J.A., Bienias, J.L., Evans, D.A., and Wilson, R.S. (2005) Mild cognitive impairment is related to Alzheimer disease pathology and cerebral infarctions. Neurology 64:834–841. Bohnen, N.I., Kaufer, D.I., Hendrickson, R., et al (2003) Cortical cholinergic function is more severely affected in parkinsonian dementia than Alzheimer’s disease: an in vivo positron emission tomography study. Arch. Neurol. 60:1745–1748. Braak, H., and Braak, E. (1991) Neuropathological staging of Alzheimer-related staging. Acta Neuropathol. 82:239–259. Caine, E. (1981) Pseudodementia. Current concepts and future directions. Arch. Gen. Psychiatry 38:1359–1364. Cairns, N.J., Bigio, E.H., Mackenzie, I.R., et al. (2007) Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: consensus of the Consortium for Frontotemporal Lobar Degeneration. Acta Neuropathol. (Berl) 114:5–22. Caselli, R.J. (1995) Focal and asymmetric cortical degeneration syndromes. Neurologist 1:1–19. Collins, S.J., Ahlskog, E., Parisi, J.E., and Maraganore, D.M. (1995) Progressive supranuclear palsy: neuropathologically based diagnostic clinical criteria. J. Neurol. Neurosurg. Psychiatry 58:167– 173. Cooper, J.R, Roth, R.H., and Bloom, F.E. (1991) The Biochemical Basis of Neuropharmacology, 6th ed. New York: Oxford University Press. Cummings, J.L. (1993) Frontal-subcortical circuits and human behavior. Arch. Neurol. 50:873–880. Cummings, J.L. (2000) Cholinesterase-inhibitors: a new class of psychotropic compounds. Am. J. Psychiatry 157:4–15. Cummings, J.L., and Benson, D.F. (1984) Subcortical dementia. Arch. Neurol. 41:874–879. Cummings, J.L., and Benson, D.F. (1992) Dementia: A Clinical Approach, 2nd ed. Boston: Heinemann-Butterworths.

905

Cummings, J.L., and Coffey, C.E. (1994) Neurobiological basis of behavior. In Coffey, C.E., and Cummings, J.L., eds. Textbook of Geriatric Neuropsychiatry. Washington, DC: American Psychiatric Press, pp. 72–96. Cummings, J.L., and Kaufer, D.I. (1996) Neuropsychiatric aspects of Alzheimer’s disease: the cholinergic hypothesis revisited. Neurology 46:876–883. The Dana Consortium on Therapy for HIV Dementia and Related Cognitive Disorders. (1996) Clinical confirmation of the American Academy of Neurology algorithm for HIV-1-associated cognitive/motor disorder. Neurology 47:1247–1253. Davis, K.L., Mohs, R.C., Marin, D., et al. (1999) Cholinergic changes and synaptic alterations in Alzheimer’s disease. JAMA 281: 1401–1406. DeKosky, S.T. (1995) Searching for the holy grail: what is the structural correlate of cognition? Neurobiol. Aging 16:298–300. DeKosky, S.T., Ikonomovic, M.D., Styren, S.D., et al. (2002) Upregulation of choline acetylcholinestrase activity in hippocampus and frontal cortex of elderly subjects with mild cognitive impairment. Ann. Neurol. 51:145–155. DeKosky, S.T., and Marek, K. (2003) Looking backward to move forward: Early detection of neurodegenerative disorders. Science 302:830–834. DeKosky, S.T., and Scheff, S.W. (1990) Synapse loss in frontal cortex biopsies in Alzheimer’s disease: correlation with cognitive severity. Ann. Neurol. 27:457–464. Delacourte, A., David, J.P., Sergeant, N., et al. (1999) The biochemical pathway of neurofibrillary degeneration in aging and Alzheimer’s disease. Neurology 52:1158–1165. Dubois, B., Feldman, H.H., Jacova, C., et al. (2007) Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDSADRDA criteria. Lancet Neurol. 6:734–746. Emre, M., Aarsland, D., Brown, R., et al. (2007) Clinical diagnostic criteria for dementia associated with Parkinson’s disease. Mov. Disord. 22:1689–1707. Feany, M.B., Mattiace, L.A., and Dickson, D.W. (1996) Neuropathologic overlap of progressive supranuclear palsy, Pick’s disease, and corticobasal degeneration. J. Neuropathol. Exp. Neurol. 55:53–67. Folstein, S. (1989) Huntington’s Disease. Baltimore: Johns Hopkins University Press. Foster, N.L., Heidebrink, J.L., Clark, C.M., et al. (2007) FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain 130:2616–2635. Gilman, S., Low, P.A., Quinn, N, et al. (1999) Consensus statement on the diagnosis of multiple system atrophy. J. Neurol. Sci. 163: 94–98. Graff-Radford, N.R., Godersky, J.C., and Jones, M.P. (1989) Variables predicting surgical outcome in symptomatic hydrocephalus in the elderly. Neurology 39:1601–1604. Hansen, L., Salmon, D., Galasko, D., et al. (1990) The Lewy body variant of Alzheimer’s disease: a clinical and pathological entity. Neurology 40:1–8. Hansson, O., Zetterberg, H., Buchhave, P., Londos, E., Blennow, K., and Minthon, L. (2006) Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol. 5:228–234. Hong, M., Zhukareva, V., Vogelsberg-Ragalia, V., et al. (1998) Mutation-specific functional impairments in distinct isoforms of hereditary FTDP-17. Science 282:1914–1917. Houlden, H., Baker, M., Morris, H.R., et al. (2001) Corticobasal degeneration and progressive supranuclear palsy share a common tau haplotype. Neurology 56:1702–1706. Huntington’s Disease Research Collaborative Group. (1993) A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington’s disease chromosomes. Cell 72:971–983. Ishii, N., Nishihara, Y., and Imamura, T. (1986) Why do frontal lobe symptoms predominate in vascular dementia with lacunes? Neurology 36:340–345.

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Jack, C.R., Petersen, R.C., Xu, Y.C., et al. (1999) Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 52:1397–1403. Joutel, A., Corpechot, C., Ducros, A., et al. (1996) Notch3 mutations in CADASIL, a hereditary adult-onset condition causing stroke and dementia. Nature 383:707–710. Kaufer, D.I., and Cummings J.L. (1996) Delirium and dementia: an overview. In: Feinberg, T., and Farah, M., eds. Behavioral Neurology and Neuropsychology. New York: McGraw-Hill, pp. 499–520. Kaufer, D.I., Itti, L., Miller, B.L., Fairbanks, L., Li, J., Kushi, J, Fishman, J., and Cummings, J.L. (1997) Midline cerebral morphometry distinguishes frontotemporal dementia and Alzheimer’s disease. Neurology 48:978–985. Klunk, W.E., Engler, H., Nordberg, A., et al. (2004) Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann. Neurol. 55:306–319. Knopman, D.S., DeKosky, S.T., Cummings, J.L., et al. (2001) Practice parameter: diagnosis of dementia (an evidence-based review). Neurology 56:1143–1153. Langa, K.M., Foster, N.L., and Larson, E.B. (2004) Mixed dementia: emerging concepts and therapeutic implications. JAMA 292: 2901–2908. Lippa, C.F., Duda, J.E., Grossman, M., et al. (2007) DLB and PDD boundary issues: diagnosis, treatment, molecular pathology, and biomarkers. Neurology 68:812–819. Lipton, S.A., and Rosenberg, P.A. (1994) Excitatory amino acids as a final common pathway for neurological disorders. N. Engl. J. Med. 330:613–622. Litvan, I., Agid, Y., Calne, D., et al. (1996) Clinical research criteria for the diagnosis of progressive supranuclear palsy (Steele-RichardsonOlszewski syndrome): report of the NINDS-SPSP international workshop. Neurology 47:1–9. Lobotesis, K., Fenwick, J.D., Phipps, A., et al. (2000) Occipital hypoperfusion on SPECT in dementia with Lewy bodies but not AD. Neurology 56:643–649. Lopez, O.L., Becker, J.T., Kaufer, D.I., Hamilton, R.L., Sweet, R.A., Klunk, W., and DeKosky, S.T. (2002) Research evaluation and diagnosis of dementia with Lewy bodies. Arch. Neurol. 59:43–47. The Lund and Manchester Groups. (1994) Clinical and neuropathological criteria for frontotemporal dementia: the Lund and Manchester Groups. J. Neurol. Neurosurg. Psychiatry 57:416–418. Markesbery, W.R., Schmitt, F.A., Kryscio, R.J., Davis, D.G., Smith, C.D., and Wekstein, D.R. (2006) Neuropathologic substrate of mild cognitive impairment. Arch. Neurol. 63:38–46. Martin, J.B. (1999) Molecular basis of the neurodegenerative disorders. N. Engl. J. Med. 340:1970–1980. Mayeux, R., Saunders, A.M., Shea, S., et al. (1999) Utility of the apolipoprotein E genotype in the diagnosis of Alzheimer’s disease. Alzheimer’s Disease Centers Consortium on Apolipoprotein E and Alzheimer’s disease. N. Engl. J. Med. 338:506–511. McKeith, I.G., Dickson, D.W., Lowe, J., et al. (2005) Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 65:1863–1872. McKeith, I.G., Galasko, D., Kosaka, K., et al. (1996) Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology 47:1113–1124. McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., and Stadlan, E.M. (1984) Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of the Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology 34:939–944. McKhann, G. M., Albert, M. S., Grossman, M., et al. (2001) Clinical and pathological diagnosis of frontotemporal dementia: Report of the Work Group on Frontotemporal Dementia and Pick’s Disease. Arch. Neurol. 58:1803–1809.

Mega, M.S., Masterman, D.L., Benson, D.F., et al. (1996) Dementia with Lewy bodies: reliability and validity of clinical and pathologic criteria. Neurology 47:1403–1409. Mesulam, M.-M. (1982) Slowly progressive aphasia without generalized dementia. Ann. Neurol. 11:592–598. Mesulam, M.-M. (1990) Large scale neurocognitive networks and distributed processing for attention, language, and memory. Ann. Neurol. 28:597–613. Miller, B.L., Cummings, J.L., Vilanueva-Meyer, J., Boone, K., Mehringer, C.M., Lesser, I.M., and Mena, I. (1991) Frontal lobe degeneration: clinical, neuropsychological, and SPECT characteristics. Neurology 41:1374–1382. Minoshima, S., Foster, N.L., Sima, A.A.F., et al. (2001) Alzheimer’s disease versus dementia with Lewy bodies: cerebral metabolic distinction with autopsy confirmation. Ann. Neurol. 50:358–365. Mintun, M.A., Larossa, G.N., Sheline, Y.I., et al. (2006) [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology 67:446–452. Mittal, S.J., Farmer, P., Kalina, P., Kingsley, P.B., and Halperin, J. (2002) Correlation of diffusion-weighted magnetic resonance imaging with neuropathology in Creutzfeldt-Jakob disease. Arch. Neurol. 59:128–134. Moroney, J.T., Bagiella, E., Desmond, D.W., et al. (1996) Risk factors for incident dementia after stroke. Role of hypoxic and ischemic disorders. Stroke 27:1283–1289. The National Institute on Aging, and the Reagan Institute Working Group on the Diagnostic Criteria for the Neuropathological Assessment of Alzheimer’s Disease. (1997) Consensus recommendations for the post-mortem diagnosis of Alzheimer’s disease. Neurobiol. Aging 18:S1–S2. Neary, D., Snowden, J.S., Gustafson, L., et al. (1999) Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 51:1546–1554. Neumann, M., Kwong, L.K., Sampathu, D.M., Trojanowski, J.Q., and Lee, V.M. (2007) TDP-43 proteinopathy in frontotemporal lobar degeneration and amyotrophic lateral sclerosis: protein misfolding diseases without amyloidosis. Arch. Neurol. 64:1388– 1394. Neumann, M., Sampathu, D.M., Kwong, L.K., et al. (2006) Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science 314:130–133. Oba, H., Yagishita, A., Terada, H., et al. (2005) New and reliable MRI diagnosis for progressive supranuclear palsy. Neurology 64:2050–2055. Penney, J.B. (1995) Multiple systems atrophy and nonfamilial olivopontocerebellar atrophy are the same disease. Ann. Neurol. 37: 553–554. Perry, R., McKeith, I.G., and Perry, E. (1996) Dementia with Lewy Bodies: Clinical, Pathological and Treatment Issues. Cambridge, UK: Cambridge University Press. Petersen, R.C., Smith, G.E., Waring, S.C., et al. (1999) Mild cognitive impairment: clinical characteristics and outcome. Arch. Neurol. 56:303–308. Petersen, R.C., Stevens, J.C., Ganguli, M., Tangalos, E., Cummings, J.L., and DeKosky, S.T. (2001) Practice parameter: early detection of dementia: mild cognitive impairment (an evidence-based review). Neurology 56:1133–1142. Plassman, B.L., and Breitner, J.C.S. (1996) Recent advances in the genetics of Alzheimer’s disease and vascular dementia with an emphasis on gene-environment interactions. J. Am. Geriatr. Soc. 44:1242–1250. Prichard, J.W., and Brass, L.M. (1992) New anatomical and functional imaging methods. Ann. Neurol. 32:395–400. Pruisner, S.B. (2001) Shattuck lecture—Neurodegenerative diseases and prions. N. Engl. J. Med. 344:1516–1526. Reich, S.G. (2006) Can mid-sagittal MRI be used to diagnose progressive supranuclear palsy? Nat. Clin. Pract. Neurol. 2:12–13.

53: DIAGNOSTIC CLASSIFICATIONS Riley, D.E., Lang, A.E., Lewis, A., Resch, L., Ashby, P., Hornykiewicz, O., and Black, S. (1990) Cortical-basal ganglionic degeneration. Neurology 40:1203–1212. Rinne, J.R., Lee, M.S., Thompson, P.D., and Marsden, C.D. (1994) Corticobasal degeneration. A clinical study of 36 cases. Brain 117:1183–1196. Robbins, T.W., James, M., Lange, K.W., et al. (1992) Cognitive performance in multisystem atrophy. Brain 115:271–291. Roman, G.C., Tatemichi, T.K., Erkinjuntti, T., et al. (1993) Vascular dementia: diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology 43:250–260. Selkoe, D. (2000) Toward a comprehensive theory for Alzheimer’s disease. Hypothesis: Alzheimer’s disease is caused by the cerebral accumulation and cytotoxicity of amyloid beta-protein. Ann. N. Y. Acad. Sci. 924:17–25. Sergeant, N., Wattez, A., and Delacourte, A. (1999) Neurofibrillary degeneration in progressive supranuclear palsy and corticobasal degeneration: tau pathologies with exclusively “exon 10” isoforms. J. Neurochem. 72:1243–1249. Shiga, Y., Miyazawa, K., Sato, S., et al. (2004) Diffusion-weighted MRI abnormalities as an early diagnostic marker for CreutzfeldtJakob disease. Neurology 63:443–449. Shoulson, I. (1990) Huntington’s disease: cognitive and psychiatric features. Neuropsychiatry Neuropsychol. Behav. Neurol. 3:15–22. Silverman, D.H.S., Small, G.W., Chang, C.Y., et al. (2001) Positron emission tomography in evaluation of dementia: regional brain metabolism and long-term outcome. JAMA 286:2120–2127.

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Small, G.W., Kepe, V., Ercoli, L.M., et al. (2006) PET of brain amyloid and tau in mild cognitive impairment. N. Engl. J. Med. 355: 2652–2663. Snowden, J.S., Pickering-Brown, S.M., Mackenzie, I.R., et al. (2006) Progranulin gene mutations associated with frontotemporal dementia and progressive non-fluent aphasia. Brain 129:2808–2810. Tiraboschi, P., Hansen, L.A., Alford, M., et al. (2000) Cholinergic dysfunction in diseases with Lewy bodies. Neurology 54:407–411. Tournier-Lasserve, E., Joutel, A., Melki, J., et al. (1993) Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy maps to chromosome 19q12. Nat. Genet. 3:256–259. Tu, P.H., Galvin, J.E., Baba, M., et al. (1998) Glial cytoplasmic inclusions in white matter oligodendrocytes of multiple system atrophy brains contain insoluble α -synuclein. Ann. Neurol. 44: 415–422. Wenning, G.K., Ben-Schlomo, Y., Magalhaes, M., et al. (1994) Clinical features and natural history of multiple system atrophy in 100 cases. Brain 117:835–845. Wilhelmsen, K.C., Lynch, T., Pavlou, E., Higgins, M., and Nygaard, T.G. (1994) Localization of disinhibition-dementia-parkinsonismamyotrophy complex to 17q21–22. Am. J. Hum. Genet. 55:1159– 1165. Yamaoka, L.H., Welsh-Bohmer, K.A., Hulette, C.M., et al. (1996) Linkage of frontotemporal dementia to chromosome 17: Clinical and neuropathological characterization of phenotype. Am. J. Hum. Genet. 59:1306–1312.

54 Transgenic Models of Dementias GREGORY A. ELDER

GENERAL CONSIDERATIONS

Methods for Generating Transgenic Organisms

Requirements for a Transgenic Model

In mice, two general techniques exist for introducing genetic modifications. The first to be developed generates transgenic animals by pronuclear injection. A onecell embryo at the pronuclear stage is injected with a transgene containing the gene of interest. Transgenes typically consist of plasmid deoxyribonucleic acid (DNA) in which a complementary deoxyribonucleic acid (cDNA) for the protein of interest is linked to a heterologous promoter that drives expression. Natural or artificial introns are often included to allow the primary transcript to be spliced that generally enhances messenger ribonucleic acid (mRNA) stability and a polyadenylation sequence is added to allow proper mRNA processing. Alternatively bacterial, plasmid, or yeast artificial chromosomes may be injected that have the advantage of being able to accommodate even large genes. The injected transgene integrates randomly, typically at a single site and in multiple copies. Because there is no corresponding allele on the homologous chromosome opposite the integration site, these mice are referred to as “hemizygous” rather than “heterozygous.” The mouse typically contains its own endogenous version of the gene of interest; therefore, the transgene is in most cases expressed on top of the expression of the endogenous mouse gene leading to an overexpression system. A second technique, rather than introducing a foreign transgene, modifies an existing gene in the mouse. This approach uses specialized cells termed embryonic stem (ES) cells that are cell lines derived from early-stage mouse embryos. These lines can be maintained indefinitely in vitro in an undifferentiated state yet retain the capacity that when injected back into a mouse embryo, they can mix with the endogenous cells of the embryo and contribute to all tissues of the developing mouse including the germ line. The gene of interest is modified in ES cells by introducing a targeting vector that consists of a modified version of the endogenous gene. In ES cells, the targeting vector recombines with the homologous endogenous gene, thereby introducing the modification of interest. Modified ES cells are injected into a blastocyst-stage mouse embryo that generates a

Animal models offer the opportunity to model human diseases allowing testing of therapeutic strategies as well as investigation of disease course and underlying pathophysiology in a manner that is impractical or unethical in humans. Transgenic technologies introduce genetic modifications into animals. Their use for disease modeling therefore requires that a genetic lesion be associated with a disease or at least that a hypothesis regarding the disorder exists that can be modeled by a genetic modification. Successful modeling also requires that the transgenic organism can exhibit the essential features of the human disease be it pathological, physiological, or behavioral. Transgenic Organisms Transgenic technology exists for many organisms, including fish, flies, and worms as well as mammalian species including mice, rats, sheep, and pigs. Modeling in invertebrates such as Drosophila or C. elegans or in vertebrates such as zebra fish offers advantages including the degree of experimental control and the relatively short life span of the organisms. They suffer the disadvantage though of being far removed phylogenetically from mammals. Although efforts to model human neurodegenerative diseases in these systems continue, they have had less impact than models using mammalian systems and are not discussed further. The interested reader is however referred to several recent reviews that have discussed transgenic modeling of Alzheimer’s disease in Drosophila and C. elegans (Link, 2005; Wu and Luo, 2005) and invertebrate modeling of human tauopathies (Gotz et al., 2007). Among vertebrates, mice have become by far the species of choice. Transgenic modeling in mice is relatively inexpensive. Mice also have a relatively short life span, and the techniques for performing genetic modifications in them are well developed. Although transgenic rats exist, this technology is not as widely available as for mice.

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chimeric mouse containing endogenous blastocyst cells as well as ES cells. Successful integration of the ES cells into the germ line allows the genetic modification to be propagated as part of the mouse genome, creating stable transgenic lines. Embryonic stem cell technology has been most commonly used to produce null mutants or gene “knockouts.” However it can also be used to modify endogenous mouse genes down to the level of creating single nucleotide changes, producing what are known as “knockin” mice. In contrast to pronuclear injection where multiple copies of a transgene insert randomly in the genome, with ES cell–based methods the native mouse gene is modified in its normal chromosomal location. Thus, though in pronuclear injection a transgene is typically overexpressed and often misexpressed spatially and temporally due to its coupling to a heterologous promoter, with homologous recombination the altered gene is expressed at normal levels with a normal temporal and spatial expression pattern. ALZHEIMER’S DISEASE Alzheimer’s disease (AD) is the most common cause of senile dementia in the United States and Europe, accounting for some 50%–80% of cases. Alzheimer’s disease may in many ways be regarded as the ideal disease for modeling in transgenic systems. It first has a well-recognized pathology, consisting of senile plaques and neurofibrillary tangles (NFTs). The major components of plaques and tangles are well defined, consisting of accumulations of β-amyloid (Aβ) peptide in plaques and hyperphosphorylated forms of tau in NFTs. It has other well-recognized pathological features, including neuronal and synaptic loss, dystrophic neurites, and the presence of reactive astrocytes and activated microglia, all changes that can be modeled in the mouse. Alzheimer’s disease also has a well-defined behavioral phenotype, including memory impairments that can be modeled in the mouse as well. Perhaps most important, though, most cases occur sporadically, there are families in which the disease is inherited in an autosomal dominant fashion. These cases of familial Alzheimer’s disease (FAD) mimic the sporadic disease clinically and pathologically except for a typically earlier age of onset. Mutations in three genes, the amyloid precursor protein (APP), presenilin-1 (PS1) and presenilin-2 (PS2) have been identified as causes of FAD (Ertekin-Taner, 2007). Transgenic Models Based on Overexpression of APP FAD Mutants In AD, the 39-42 amino acid Aβ peptide deposits in senile plaques. Various in vitro and in vivo studies have

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demonstrated that Aβ can be neurotoxic. The amyloid cascade hypothesis postulates that Aβ production sets off a chain of events in AD brain that eventually leads to cell death (Selkoe, 2001). The Aβ peptide itself is derived from processing of a larger precursor protein known as APP. The amyloid hypothesis was greatly bolstered by the finding that mutations in APP can cause FAD. Modeling in transgenic mice has been vigorously pursued based on the amyloid hypothesis and has been the subject of several recent reviews (Codita et al., 2006; Games et al., 2006; McGowan et al., 2006). Early attempts at generating transgenic models in the mouse before the discovery of FAD mutations focused on overexpressing wild-type APP in transgenic mice by pronuclear injection using a variety of promoters. However, none of these efforts produced anything that looked like an amyloid plaque or other recognizable AD-type pathology. It was not until 1995 and 1996 with the reports of PDAPP (Games et al., 1995) and Tg2576 (Hsiao et al., 1996) mice that models mimicking many of the features of human AD began to appear. These mice are described in some detail because they illustrate a general approach that would prove successful in the hands of many investigators and for other neurodegenerative diseases as well. In the first report, Games et al. (1995) used the platelet derived growth factor-β (PDGF) promoter to drive a splicible human APP minigene capable of expressing all three major APP isoforms and containing an FAD mutation at codon 717 in which a valine was mutated to a phenylalanine (V717F). The PDGF promoter was chosen because, despite its name, it was known to be highly expressed in the central nervous system (CNS) and to drive strong expression of exogenous transgenes in neurons. In the line that was generated (termed PDAPP because of the PDGF promoter plus APP), 40 copies of the transgene integrated, resulting in an ≈18fold elevation of APP RNA and ≈10-fold elevation of human APP protein, both compared to the endogenous mouse APP. Proportionate increases in human Aβ were seen as well. PDAPP mice exhibited age-dependent amyloid deposition in brain parenchyma with the appearance of thioflavin-S positive plaques, including compacted plaques with dense cores that were highly reminiscent of those seen in human AD. Dystrophic neuritis, reactive astrocytes, and activated microglia were all found near plaques. Plaque deposition was minimal at 6 months of age, but readily apparent by 9 months and increased dramatically by 12–15 months (Reilly et al., 2003). PDAPP mice were subsequently shown to develop age-related learning defects (Chen et al., 2000) and synapse loss (Dodart et al., 2000). Hsiao et al. (1996) independently took a relatively similar approach overexpressing a human APP minigene containing the APP695 form, which is the isoform most

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highly expressed in neurons. The transgene contained the “Swedish” FAD mutation (K670N/M671L) and was driven by the hamster prion (PrP) promoter that drives expression widely in the nervous system. These mice, termed Tg2576 mice, expressed human APP at levels greater than five-fold above those of the endogenous mouse APP. Aβ 40 and 42 levels increased in an agedependent manner without any change in expression of full-length APP. As in PDAPP mice, Tg2576 mice exhibited an age-dependent deposition of amyloid, resulting in thioflavin-S positive plaques that exhibited the essential features of senile plaques in AD, including gliosis and dystrophic neurites. In Tg2576 mice, plaque amyloid was first clearly seen by 11–13 months, eventually becoming widespread in cortical and limbic structures. Water maze learning was found to be normal in 3-month-old animals but impaired in 9- to 10-monthold mice. The Tg2576 mouse line has been made widely available and is currently the most utilized transgenic model of AD. Subsequently, many other transgenic lines were developed using relatively similar approaches to those taken for developing PDAPP and Tg2576 mice (reviewed in Codita et al., 2006; Games et al., 2006; McGowan et al., 2006), relying on typically strong promoters to drive expression of APP transgenes containing one or sometimes multiple FAD mutations. Common features of the models were the production of Aβ containing plaques, dystrophic neurites, and gliosis. Cognitive and behavioral deficits were also common (Games et al., 2006). Many other electrophysiological, neurochemical, and neuropathological changes that model aspects of AD in humans have also been reported. Although the models exhibit many similarities, they differ in certain aspects, one being the time of onset of plaque deposition. TgCRND8 mice that express multiple APP mutations exhibit plaques by 3 months of age (Chishti et al., 2001). The APP23 line, in which a thy1 promoter was used to drive expression of the APP Swedish mutation, is notable for its prominent cerebrovascular amyloid deposition (Calhoun et al., 1999). PDAPP and Tg2576 mice indeed differ in certain aspects—among them, Tg2576 mice increase production of both Aβ40 and Aβ42, whereas in PDAPP mice, Aβ42 is selectively increased (Hsiao et al., 1996; Fryer et al., 2003). In Tg2576 mice most amyloid is found in dense cored plaques with relatively few of the diffuse deposits found in PDAPP mice. Tg2576 mice are also known for their giant plaques (Sasaki et al., 2002) and exhibit more congophilic angiopathy (Fryer et al., 2003), the latter being largely absent in PDAPP mice. Variations between lines likely reflect the different promoters used to drive expression, the different mutations or combinations of mutations and the genetic backgrounds on which the transgenes have been maintained. PDAPP mice, for example, have been mostly studied on

a highly mixed C57BL6/DBA/Swiss-Webster background. By contrast, Tg2576 mice have been typically studied on a mixed C57BL6/SJL background, and the Tg2576 transgene has been difficult to move off this background. Indeed, the Tg2576 transgene leads to early death when present on an FVB/N background (Hsiao et al., 1995). Transgenic Mice Expressing Presenilin-Associated FAD Mutations Presenilin-1 (PS1) was discovered in the search for an early-onset FAD gene associated with chromosome 14 (Ertekin-Taner, 2007). More than 160 mutations in PS1 have been linked to FAD, and mutations in PS1 are the most commonly recognized cause of early-onset FAD. Shortly after PS1’s discovery, a related gene was identified on chromosome 1 (Ertekin-Taner, 2007). Mutations in this gene, now called presenilin 2 (PS2), although a less common cause than PS1 also result in FAD. Functionally, presenilins are best known for their role in the γ -secretase cleavage of many transmembrane proteins including APP (Vetrivel et al., 2006). Presenilin FAD mutations in particular shunt APP processing towards the more amyloidogenic Aβ42 species (Vetrivel et al., 2006), an observation that can be been seen as further support for the amyloid hypothesis. A variety of PS1 FAD mutant lines have been generated using many of the same promoters used to create APP lines, including PDGF (Duff et al., 1996) and PrP (Borchelt et al., 1996; Citron et al., 1997). Some PS2 FAD mutant lines also exist. Several PS1 FAD mutations have also been knocked in to the endogenous mouse PS1 gene (Flood et al., 2002; Guo et al., 1999; Nakano et al., 1999). Presenilin FAD mutant mice have consistently shown selective elevations of Aβ42 with little if any effect on Aβ40. When crossed with plaque-forming APP lines, the PS1 FAD mutants cause earlier and more extensive plaque deposition (Borchelt et al., 1996; Holcomb et al., 1998), although single transgenic PS1 or PS2 mice have never been observed to exhibit plaque formation. Although PS1/APP bigenic mice have been frequently studied, the parental presenilin lines have been less studied likely due to their lack of a more robust AD pathology. However, PS1 and PS2 FAD mutant lines show exaggerated hippocampal damage following kainite induced excitotoxicity (Guo et al., 1999; Grilli et al., 2000; Schneider et al., 2001), and PS1 FAD mutants render animals more sensitive to trimethyltin-induced hippocampal damage (Kassed et al., 2003). Lesioning of the perforant path also induces excessive neuronal loss in the entorhinal cortex in mice harboring the deltaE9 PS1 FAD mutant (Lazarov et al., 2006). Increased protein oxidation and lipid peroxidation have also been reported in PS1 FAD mutant brain (Mohmmad Abdul et al., 2004; Schuessel et al., 2006), and several studies

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have documented impaired hippocampal neurogenesis in adult PS1 FAD mutant mice (Wen et al., 2004; Chevallier et al., 2005). One study has reported agerelated neurodegenerative changes and neuronal loss in a PS1 FAD mutant line (Chui et al., 1999), and recently age-related NFT-like inclusions were described in a PS1 knockin line (Tanemura et al., 2006). Thus, presenilin FAD mutant mice exhibit a phenotype. What is less apparent is why they fail to exhibit the full range of AD related changes in mice given the potency of the mutations in humans. Relevance as Models of Alzheimer’s Disease The success of transgenic models such as PDAPP and Tg2576 have depended on the overexpression of APP transgenes containing FAD-associated mutations. In one sense, the models are problematic because of their reliance on overexpressed proteins. One might argue that overexpression of any protein becomes toxic at some level and that it is hardly surprising that overexpression of an amyloidogenic protein at some level causes amyloid deposits. Yet there is no evidence for APP overexpression in sporadic AD. It is also interesting to compare these overexpression models to APP knockin mice in which the Swedish mutation was introduced into the mouse APP gene (Reaume et al., 1996). These mice should represent the most authentic model of human FAD in the mouse and because the three amino acid differences between mouse and human in the Aβ region were modified as well, they produce human Aβ. In these mice, though Aβ production is increased, no amyloid plaques or any substantial neuropathology develops. The models have also been troubled by the difficulty of producing the full spectrum of AD pathology including neuronal loss and NFTs. Despite extensive amyloid deposition, PDAPP and Tg2576 exhibit no neuronal loss (Irizarry et al., 1997a, 1997b). APP23 mice show very modest losses of CA1 pyramidal cells (about 15%) (Calhoun et al., 1998) but far below that observed in AD. More substantial neuronal loss has been reported in mice expressing multiple PS1 and APP mutations. In one study (Schmitz et al., 2004), APP transgenic mice expressing APPSwe and V717I-London were crossed with mice harboring the PS1 M146L mutation and a 35% loss of hippocampal neurons was reported. In another study, two APP (APPSwe/APPLondon) mutations expressed from transgenes were crossed onto a mouse line that had two presenilin FAD mutations (M233T/L235P) knocked in to the mouse PS1 gene. Besides amyloid pathology, extensive neuronal loss (> 50%) occurred in the hippocampus. Finally, recently three APP and two PS1 FAD mutations were combined to create a 5X FAD mutant mouse, and neuronal loss was observed (Oakley et al., 2006). Thus, neuronal loss

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can be induced in the mouse but only, it would seem, by combining multiple mutations that are individually sufficient to cause disease in humans. A second problem with the models has been the general difficulty of inducing NFT-like pathology. Neurofibrillary tangles are recognized by their propensity to label with certain histological stains, including thioflavin-S and Congo red, and by being ultrastructurally composed of paired helical filaments (PHF). Hyperphosphoryated forms of tau are found in NFTs, and conformationally altered tau epitopes appear that can be recognized by specific antibodies. PDAPP mice accumulate phosphorylated tau epitopes within dystrophic neurites but only in animals older than 14 months of age (Masliah et al., 2001). Within these neurites, 12–15 nm filaments can be found but no PHF and no lesions with the histological staining properties of NFTs. Various hypotheses have been advanced for the difficulty of inducing NFT-like lesions in the mouse including differences between human and mouse tau and the shorter life span of the mouse. Recently, mice have been produced that exhibit NTFlike lesions and plaques by combining FAD mutations with mutant forms of tau associated with a distinct form of dementia known as frontotemporal dementia with parkinsonian features (FTDP-17). Although clinically distinct from AD (see below), FTDP-17 cases exhibit NFTs like those found in AD, and mutations in tau cause a subset of FTDP-17 cases. Lewis et al. (2001) first crossed a transgenic line known as JNPL3 that expresses the P301L mutation associated with FTDP-17 with Tg2576 mice. Singly transgenic JPNL3 mice were known to develop NFT-like lesions and the bigenic progeny called TAPP mice exhibited NFTs and amyloid plaques. More recently, Oddo et al. (2003) generated a triple transgenic model (3xTg-AD) by coinjecting independent transgenes harboring APPSwe and the P301L FTDP-17 mutation into fertilized eggs harvested from homozygous PS1M146V knockin mice. The resulting transgenic lines thus express mutations in APP and tau from exogenous transgenes on a background of a PS1 FAD mutation expressed from the endogenous mouse gene. With aging, these mice had increased Aβ40 and Aβ42 levels, accumulated intraneuronal Aβ, and exhibited amyloid plaques and NFTlike lesions that could be immunostained by antibodies that recognize conformationally altered tau epitopes. Amyloid plaques appeared by 6 months of age and preceded tau pathology that was not evident until about 1 year of age. 3xTg-AD mice also developed agedependent synaptic dysfunction, including altered longterm potentiation and deficits in memory (Oddo et al., 2003; Billings et al., 2005). These mice thus exhibit a broader spectrum of AD pathology. The question again arises, however: are they models of AD? The mice do exhibit the much-sought-

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after plaques with tangle pathology. They, however, represent a composite of two distinct diseases that do not naturally occur together. Plaque development is almost certainly driven by the APP and PS1 FAD mutations, with tangle-like pathology driven by the tau mutation. Indeed, in 3xTg-AD mice, the pathologies arise in spatially distinct patterns with Aβ deposition initiating in neocortex and progressing to hippocampus, and tau pathology beginning in hippocampus and progressing to neocortex. It does appear, however, that the mutations do interact, as in TAPP mice, NFTs are found in regions that rarely or never exhibit NFTs in single transgenic JNPL3 animals. In addition, intracerebral injections of anti-Aβ antibodies into the hippocampus of 3xTg-AD mice not only reduced extracellular and intracellular accumulation of Aβ but also resulted in clearance of early tau pathology, although later-stage lesions were resistant (Oddo et al., 2004). These studies thus show that modulating Aβ affects tau pathology and suggest that tau pathology may be induced by Aβ generation. This notion has also been supported by recent studies showing that behavioral deficits in APP FAD mutant mice were reduced when endogenous tau was removed by breeding the APP transgene onto a tau null background (Roberson et al., 2007). Uses of Transgenic Models to Study AD Pathophysiology: Effects of Different Species of Aβ In vitro Aβ 42 promotes fibril formation more strongly than Aβ 40. Recently, the relative plaque forming ability of Aβ 40 and Aβ 42 was investigated in vivo by generating transgenic mice that selectively express either Aβ 40 or Aβ 42 (McGowan et al., 2005). These mice were created by fusing Aβ 40 and Aβ 42 peptide sequences to the C-terminus of the BRI protein. BRI is a transmembrane protein that undergoes a constitutive cleavage near its C-terminal end that releases a soluble 23 amino acid peptide. Aβ 40 or Aβ 42 selective expression systems were created by replacing the 23 amino acid native BRI peptide with human Aβ 40 or Aβ 42 sequences. Interestingly, BRI-Aβ 42 mice accumulated insoluble Aβ 42 and with aging developed amyloid plaques, diffuse deposits, and extensive congophilic angiopathy. By contrast, BRI-Aβ 40 mice developed no amyloid pathology at any age. Aβ 40 is found in plaque amyloid and is especially common in vascular amyloid. These studies are thus consistent with models suggesting that Aβ 42 is required to “seed” parenchymal and vascular deposits of Aβ 40. Transgenic mice have also been used to assess factors that affect patterns of amyloid deposition. Interestingly, though a number of FAD mutations in APP reside near the β and γ -secretase cleavage sites, other mutations lie within the Aβ domain itself. These latter mutations typically do not produce substantial parenchymal deposition in the form of plaques but rather result in exten-

sive vascular deposits. One such mutation is E693Q also known as the Dutch mutation rather than resulting in AD causes a hereditary form of recurrent intracerebral hemorrhage. Herzig et al. (2004) developed transgenic lines that expressed human wild-type APP, APP-Dutch, or APPDutch crossed with a PS1 FAD mutant. These lines exhibited different ratios of Aβ 40/42, with APP Dutch being greater than wild-type APP, which was in turn greater than APP-Dutch/ PS1. The high ratio of Aβ 40/42 in the APP-Dutch mice resulted in extensive congophilic angiopathy with essentially no parenchymal deposition. By contrast, APP-Dutch/ PS1 with nearly half the Aβ 40/42 ratio of APP-Dutch mice developed parenchymal plaques with little vascular deposition, and wildtype APP mice with intermediate Aβ 40/42 ratios had mixed parenchymal and vascular deposition. These results, though not inconsistent with the notion that Aβ 42 is necessary as a seed for amyloid deposition in either compartment, suggest that Aβ 40 promotes vascular deposition while Aβ 42 shifts deposition towards parenchymal amyloid. Other studies (Cheng et al., 2004) have found, however, that transgenic mice harboring a distinct 693 mutation (E693G/Arctic) combined with APP Swedish and Indiana mutations develop prominent parenchymal plaque deposits with little congophilic angiopathy despite high Aβ 40/42 ratios. Thus, some other property of mutations at the 693 site besides their effect on Aβ 40/42 ratios must also influence parenchymal versus vascular deposition. The Rise of the Aβ Oligomer The original amyloid hypothesis regarded Aβ deposited in plaque amyloid as the toxic material. However, subsequently it became clear that plaque counts correlate relatively poorly with the level of cognitive decline and that NFTs, in fact, correlate more strongly than plaques with the degree of dementia. This led to a reevaluation of what form of amyloid might constitute the most toxic species, and recently soluble forms of Aβ have been proposed as the more toxic species. Soluble Aβ species are toxic in cell culture systems (Walsh and Selkoe, 2007). APP transgenic mice have provided strong circumstantial support for their toxicity in vivo by showing that many pathological and functional changes in these mice occur before plaque pathology. For example, a series of studies in PDAPP mice have shown that volume loss and other anatomic changes in the dentate gyrus are present in 100-day-old mice well before plaque deposition (Redwine et al., 2003; Wu et al., 2004). Tg2576 mice also exhibit electrophysiological and behavioral changes months before plaque deposition (Jacobsen et al., 2006). Behavioral and electrophysiological changes have been described in other lines of APP mice before amyloid deposition as well

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(Holcomb et al., 1998; Hsia et al., 1999; Moechars et al., 1999), and in Tg2576 mice, axonal swellings may be present for up to a year before amyloid deposition (Stokin et al., 2005). Indeed, recently a 56-kDa oligomeric Aβ species was identified in Tg2576 mice (Lesne et al., 2006). Levels of this species that has been termed Aβ*56 correlates strongly with the degree of memory impairment in Tg2576 mice; and when injected into rats, Aβ*56 also disrupts cognitive functioning. The finding of pathophysiological changes in PS1 FAD mutant mice (see above) that have elevated Aβ but no plaques is also consistent with a toxic role for soluble forms of Aβ. Aβ Immunization as a Therapeutic Strategy in Alzheimer’s Disease APP transgenic animals have been widely used to study factors that affect Aβ deposition. For example, the role that apolipoprotein ε4 (ApoE4) and its various isoforms play in the development of plaque pathology has been extensively studied using ApoE4 transgenic and knockout mice (Bales et al., 1997; Holtzman et al., 2000; Fagan et al., 2002). Studies examining how dietary cholesterol affects plaque pathology (Refolo et al., 2001) have formed part of the basis for the interest in statins as a potential AD treatment. Indeed, APP transgenic mice have been used for a range of preclinical studies evaluating factors that influence plaque pathology ranging from inflammatory modulators, metal chelators, and natural products that bind Aβ to lifestyle factors including exercise, environmental enrichment, caloric restriction, and even wine consumption (Adlard et al., 2005; Lazarov et al., 2005; Patel et al., 2005; Games et al., 2006; Wang et al., 2006). However, nowhere have transgenic mice played a larger role than in the development of immunotherapy as a potential treatment for AD. Indeed, though the initial impetus for immune approaches came from in vitro studies showing that anti-Aβ antibodies could prevent fibril formation as well as disaggregate preformed fibrils (Solomon et al., 1996), without studies in transgenic mice demonstrating their potential effectiveness in vivo, it seems unlikely that these approaches would have ever made their way into human trials. These studies have recently been extensively reviewed by Morgan (2006). Schenk et al. (1999) first investigated Aβ vaccination in vivo. They initially immunized 6-week-old PDAPP mice (well before the age of plaque deposition in this line) with an Aβ vaccine injected on a monthly basis for 11 months. The mice developed high titers of anti-Aβ antibodies and at 12 months of age showed dramatic reductions in plaque loads. In a second set of studies, 11-month-old mice (after the onset of plaque deposition) were given monthly injections and were examined at 15 and 18 months. At both ages, plaque burdens were dramatically reduced, raising the hope that Aβ vacci-

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nation might be beneficial even after parenchymal deposits are present. Subsequent studies confirmed the beneficial effect of Aβ immunotherapy in other transgenic lines, also showing that active immunization could reverse memory deficits in APP and PS/APP mice (Janus et al., 2000; Morgan, 2006). How active immunization works remains uncertain. Schenk et al. (1999) proposed that anti-Aβ antibodies might coat amyloid deposits and promote phagocytosis by microglia and other immune cells. Later studies found, however, that immunization also induces massive increases in plasma Aβ (DeMattos et al., 2001), suggesting that vaccination might induce movement of Aβ from brain into what has been referred to as a peripheral sink for Aβ. A third possibility is that anti-Aβ antibodies directly impede new fibril formation. Subsequently, it was found that passive immunization by administering anti-Aβ antibodies peripherally also reduces amyloid deposition (Dodart et al., 2002; Kotilinek et al., 2002). Indeed, multiple studies have shown that even short-term administration of anti-Aβ antibodies improves performance in tests of learning and memory. Interestingly, improvements occur even though no detectible effect is seen on deposits of plaque amyloid, providing further support for the notion that a soluble pool of Aβ may be critical for toxicity. Whatever its mechanism of action, studies in transgenic mice were sufficiently compelling that Aβ immunization was taken into clinical trials in humans. Although phase 1 studies indicated good immunological responses and tolerability of the vaccine, phase 2 studies in patients with AD were halted due to the appearance of an autoimmune meningoencephalitis in some patients (Orgogozo et al., 2003). Although these initial studies were ultimately disappointing, a retrospective analysis found that those patients with the highest anti-Aβ titers had significantly less cognitive decline than those with low titers (Hock et al., 2003), suggesting that Aβ immunization remains a viable strategy if autoimmune side effects can be overcome. Passive immunization strategies remain attractive, as well, due to the greater control over antibody levels that can be achieved, although some studies in transgenic mice have suggested that adoptive transfer may cause more congophilic angiopathy (Morgan, 2006). Although effective immunomodulatory strategies remain a goal rather than a reality, attempts to develop safer active or passive immunization strategies continue and will without doubt continue to make use of transgenic models. TAUOPATHY-ASSOCIATED DEMENTIAS Besides AD, hyperphosphorylated forms of tau accumulate in NFTs in the absence of plaques in a number of neurodegenerative diseases including Pick’s disease,

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progressive supranuclear palsy, corticobasal degeneration, and FTD. Frontotemporal dementia cases present clinically with often prominent behavioral disturbances or isolated language defects and relatively preserved memory, initially. Some cases also exhibit parkinsonian features (FTDP). Pathologically, atrophy—especially frontotemporal—is prominent with neuronal loss, NFTs, and sometimes spongioform change. Frontotemporal dementia is a less common form of dementia than AD, accounting for 5%–7% of cases in some autopsy series. Like AD, most cases occur sporadically. However, in some families with FTDP, the disease is caused by mutations in the tau gene on chromosome 17 (FTDP-17) (Haugarvoll et al., 2007). Mutations— including exonic point mutations that alter the protein coding sequence as well as intronic mutations that affect splicing or the level of tau expression—have all been identified. In addition to FTDP, tau mutations cause clinical syndromes resembling progressive supranuclear palsy, corticobasal degeneration, Pick’s disease, and a disease known as progressive subcortical gliosis. Tau is a microtubule binding protein that undergoes a complex transcriptional and posttranscriptional regulation producing multiple isoforms (Mandelkow et al., 2007). Tau’s only known function is to bind to microtubules, leading to their stabilization. Binding occurs through a microtubule binding domain, and tau isoforms can be broadly divided into those that contain three or four repeats of this domain. Phosphorylation reduces tau binding to microtubules. In AD as well as in human tauopathies, tau becomes hyperphosphoryated, and conformationally altered epitopes appear that can be recognized by specific antibodies. In addition, phosphorylated forms of tau that are normally found in axons become redistributed to the somato-dendritic compartment. Transgenic Models of Tauopathies Transgenic modeling of tauopathies has been approached in a manner very similar to that which was successful for AD. Tau transgenes containing FTDP-17 mutations have been typically overexpressed using strong promoters. JPNL3 mice (Lewis et al., 2000) were mentioned briefly above. In these mice, the mouse PrP promoter was used to express the four repeat form of human tau containing the P301L mutation associated with FTDP17. Hemizygous mice expressed human tau at levels approximately equal to the endogenous mouse tau, leading to about a twofold increase in total tau. JPNL3 mice exhibited marked tangle-like pathology and gliosis in brain as well as spinal cord, with neuronal loss in both regions. In addition to neuronal inclusions, filamentous accumulations of tau occurred in astrocytes and oligodendrocytes (Lin et al., 2003a). These lesions stained with Congo red and thioflavin-S as well as other

stains that recognize human NFTs and also, like human NFTs, reacted with anti-tau antibodies that see phosphorylated as well as conformationally altered tau epitopes. Insoluble forms of tau not normally detected in mouse brain accumulated, and a mixture of 10–20 nm diameter straight as well as wavy filaments was visible by electron microscopy, though no true PHFs were found (Lin et al., 2003b). JNPL3 mice developed a progressive motor disorder that became evident as early as 6½ months of age in hemizygous mice and 4½ months in homozygous mice. The motor disorder was associated with a nearly 50% reduction of spinal motor neurons, peripheral nerve degeneration, and neurogenic atrophy. As a control for tau overpression itself, mice were created with the same PrP promoter driving expression of human wild-type tau. These mice exhibited no clinical phenotype, and though neurons in the hippocampus and other regions stained with antibodies that recognize conformationally altered tau epitopes, these neurons did not develop NFTs (Lewis et al., 2000). Subsequently, many transgenic lines have been made expressing FTDP-17 associated tau mutations under a variety of promoters that drive expression in neurons and glia (reviewed in Gotz et al., 2007). A common feature of these models has been the induction of filamentous tau pathology in neurons and glia that, unlike transgenic AD models, has been readily associated with neuronal loss. Behavioral impairments have been reported, and motor neuron disease has been common, the latter a feature also frequently found in association with human FTD. Differences between models almost certainly reflect variables such as the promoter utilized, the tau isoform expressed, the transgene integration site, and the genetic backgrounds on which the studies were conducted. As with AD models, questions arise as to whether the disturbances primarily result from the FTDP-17 mutations or could be caused by tau overexpression itself, and indeed a number of studies have shown that overexpression of wild-type human tau can lead to clinical and pathological effects in transgenic mice. Ishihara et al. (1999), for example, used the mouse PrP promoter to overexpress the shortest form of human tau, known as T44, that is most prominently expressed during fetal development. The mice that were created had total tau elevations of 5- to 15-fold in most CNS regions. Young mice exhibited motor weakness, and nonfilamentous tau aggregates could be detected in neurons that stained with phosphorylation and conformation-dependent tau antibodies that recognize NFTs. However, only old mice (18–20 months) developed mature lesions that exhibited the staining properties of NFTs (Ishihara et al., 2001). Similarly, transgenic mice expressing human tau from a P1 artificial chromosome on a mouse tau–/– background accumulated hyperphosphorylated tau at 6 months of age but only developed thioflavin-S positive lesions at 15 months (Andorfer et al., 2003).

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Other studies (Spittaels et al., 1999; Probst et al., 2000) have observed that even modest 1.5-fold overexpression of wild-type human tau under the control of the thy-1 promoter induced a redistribution of phosphorylated tau into the cell body and the appearance of conformation-dependent tau epitopes but without the development of lesions having the staining properties of NFTs. Interestingly, though, it is less prone to induce NFT-like lesions, wild-type tau seems more prone to induce axonal spheroids than FDTP-17 mutant tau (Terwel et al., 2005). Expression of human wild-type tau from the mouse Tα1 α-tubulin promoter that is active in glial cells and neurons has also been reported to induce a glial pathology resembling the astrocytic plaques of corticobasal degeneration (Higuchi et al., 2002). Thus, overexpression of wild-type human tau can clearly cause neuropathology, although its propensity to induce NFT-like lesions seems less than FTDP-17 mutant tau. These effects of wild-type tau may, however, be physiologically relevant in that a number of FTDP-17 mutants involve noncoding mutations and, in some cases, missense mutations that result in relative overexpression of certain tau isoforms (Haugarvoll et al., 2007). Implications for Pathophysiology and Treatment of Human Tauopathies Although intracellular inclusions like NFTs might intuitively seem to be toxic, recently it has been suggested that the inclusions found, for example, in Huntington’s disease may actually be neuroprotective (Ross and Poirier, 2005). In one set of very informative studies, transgenic mice in which tau expression could be regulated were used to examine the relationship between NFT pathology and neuronal dysfunction. In these studies, transgenic mice were created using the tetracycline (tet)-off inducible system (Ramsden et al., 2005; Santacruz et al., 2005). The tetracycline-operon response element (TRE) was used to drive the four repeat form of human tau harboring the P301L FTDP-17 mutation. On a second transgene, the calcium calmodulin kinase II (CaMKII) promoter was used to drive expression of the tet-off transactivator (rTA). Due to the specificity of the CaMKII promoter, these mice expressed high levels of transgenic tau principally in forebrain regions. In the nonrepressed state, transgenic tau levels were increased 7–13-fold relative to endogenous mouse tau, and after treatment with doxycycline that turns transgene expression off, levels fell to approximately 15% of their maximum levels (though still about 2.5-fold above endogenous mouse tau). Without doxycycline suppression, mice in the highest expressing line (rTg4510) developed NFT-like lesions at 4 to 5 months of age in cortex and hippocampus with accumulation of abnormally phosphorylated tau and a 60% loss of CA1 py-

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ramidal neurons. With aging, extensive neurodegeneration occurred in cortical and limbic structures, leading to gross forebrain atrophy and reduced brain weight. Spatial memory deficits were apparent by 2.5 to 4 months of age before NFTs appeared. Interestingly, no motor deficits were detected in rTg4510 mice, likely reflecting the predominately forebrain expression pattern of the transgene. When 2½-month-old mice were treated with doxycycline and examined at 4 months, the number of NFTs did not change, suggesting that transgene suppression stopped new NFTs from developing without clearing old ones. However, when animals at 4 months of age or older were treated, NFTs continued to accumulate despite transgene suppression, arguing that NFT formation had become transgene independent. Yet despite continued NFT accumulation in the doxycycline-treated animals, brain weight and neuronal numbers stabilized. In addition, both young and old mice treated with doxycycline improved their performance on the Morris water maze, even with relatively short-term treatments. These findings argue that NFT formation is not necessary for neurodegeneration, and indeed, cognitive impairment in the absence of NFT formation has also been found in other lines of FTDP-17 transgenic mice (Gotz et al., 2007). This dissociation appears to be true for glial pathology as well, as when the P301L mutation was expressed using an oligodendrocyte-specific promoter, myelin disruption and impaired axonal transport preceded the appearance of thioflavin-S stained inclusions in oligodendrocytes (Higuchi et al., 2005). Thus, spatial memory deficits and neuronal loss can be temporally separated from NFT formation, and progressive NFT formation does not necessarily lead to neurodegeneration. Instead of implicating a direct toxic role for NFTs, such observations suggest the existence of a toxic preNFT tau species, offering an interesting parallel to the story of soluble Aβ species. Indeed, recent studies have identified a multimeric species of tau in tau transgenic mice as well as cases of human FTDP-17 and AD (Berger et al., 2007). These tau multimers have been suggested to be responsible for toxicity, although besides a toxic gain of function, it remains possible that imbalances in tau isoforms or altered microtubule binding by tau mutants may lead to a loss of function as well (Ballatore et al., 2007). Whatever the basis for the effect, studies in rTg4510 transgenic mice argue that neuronal dysfunction can be reversed, suggesting that in human tauopathies— including AD—there may be a phase of the disease that is reversible. Modulation of tau phosphorylation has attracted attention as one therapeutic strategy, and protein kinase inhibitors exist that can be administered orally and penetrate the blood–brain barrier (Gotz et al., 2007). Synthetic analogs of one such inhibitor—K252a, a

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non-specific protein kinase inhibitor—has been tested in JNPL3 mice and shown to reduce soluble hyperphosphorylated tau as well as delay or prevent development of severe motor impairments (Le Corre et al., 2006), thus offering important preclinical support for this approach to treating human tauopathies. OTHER DEMENTIAS Dementia occurs in the context of many other neurodegenerative disorders. One group of disorders that includes Parkinson’s disease, diffuse Lewy body disease, and multiple system atrophy is characterized by cytoplasmic inclusions in neurons and glial cells called Lewy bodies. Lewy bodies contain high levels of the protein α-synuclein, and missense mutations as well as triplication of the α-synuclein gene have been identified in families with autosomal dominant Parkinson’s disease. Transgenic mice that overexpress wild-type or mutant α-synuclein have been made using a variety of neuronal and glial promoters (Fernagut and Chesselet, 2004). Ubiquitin and α-synuclein positive inclusions have been induced by wild-type and mutant α-synuclein, with the extent of pathology generally correlating with transgene expression level. Motor disorders have been common in these mice, although the models have been somewhat disappointing in the lack of dopaminergic cell loss. British and Danish familial dementias are caused by mutations in a gene on chromosome 13 known as BRI2. Pathologically, the disorders exhibit amyloid plaques composed of BRI protein rather than Aβ. Attempts to model these disorders in transgenic mice have been recently reviewed (Pickford et al., 2006). Prion diseases are also associated with dementia and exhibit amyloid plaques containing prion protein. These diseases, though mostly sporadic, also exist in familial forms, and some transgenic mouse models have been created (Li et al., 2007). Dementia is also associated with Huntington’s disease, and a number of transgenic Huntington’s models have been developed (Walker, 2007). CONCLUSIONS Transgenic models now dominate approaches to animal modeling of human neurodegenerative diseases. The models are in one sense limited by their requirement for a genetic modification. However, the existence of familial forms for most of the common human senile dementias has allowed transgenic models to be created that reproduce the most critical aspects of the disease pathology. These models have improved understanding of disease pathogenesis and have led to new therapeutic approaches. They will, without doubt, continue to play central roles for years to come in preclinical testing

and as tools for developing insight into the biological basis of human dementias. REFERENCES Adlard, P.A., Perreau, V.M., Pop, V., and Cotman, C.W. (2005) Voluntary exercise decreases amyloid load in a transgenic model of Alzheimer’s disease. J. Neurosci. 25:4217–4221. Andorfer, C., Kress, Y., Espinoza, M., de Silva, R., Tucker, K.L., Barde, Y.A., Duff, K., and Davies, P. (2003) Hyperphosphorylation and aggregation of tau in mice expressing normal human tau isoforms. J. Neurochem. 86:582–590. Bales, K.R., Verina, T., Dodel, R.C., Du, Y., Altstiel, L., Bender, M., Hyslop, P., Johnstone, E.M., Little, S.P., Cummins, D.J., Piccardo, P., Ghetti, B., and Paul, S.M. (1997) Lack of apolipoprotein E dramatically reduces amyloid beta-peptide deposition. Nat. Genet. 17:263–264. Ballatore, C., Lee, V.M., and Trojanowski, J.Q. (2007) Tau-mediated neurodegeneration in Alzheimer’s disease and related disorders. Nat. Rev. Neurosci. 8:663–672. Berger, Z., Roder, H., Hanna, A., Carlson, A., Rangachari, V., Yue, M., Wszolek, Z., Ashe, K., Knight, J., Dickson, D., Andorfer, C., Rosenberry, T.L., Lewis, J., Hutton, M., and Janus, C. (2007) Accumulation of pathological tau species and memory loss in a conditional model of tauopathy. J. Neurosci. 27:3650–3662. Billings, L.M., Oddo, S., Green, K.N., McGaugh, J.L., and LaFerla, F.M. (2005) Intraneuronal abeta causes the onset of early Alzheimer’s disease-related cognitive deficits in transgenic mice. Neuron 45:675–688. Borchelt, D.R., Thinakaran, G., Eckman, C.B., Lee, M.K., Davenport, F., Ratovitsky, T., Prada, C.M., Kim, G., Seekins, S., Yager, D., Slunt, H.H., Wang, R., Seeger, M., Levey, A.I., Gandy, S.E., Copeland, N.G., Jenkins, N.A., Price, D.L., Younkin, S.G., and Sisodia, S.S. (1996) Familial Alzheimer’s disease-linked presenilin 1 variants elevate Abeta1-42/1-40 ratio in vitro and in vivo. Neuron 17:1005–1013. Calhoun, M.E., Burgermeister, P., Phinney, A.L., Stalder, M., Tolnay, M., Wiederhold, K.H., Abramowski, D., Sturchler-Pierrat, C., Sommer, B., Staufenbiel, M., and Jucker, M. (1999) Neuronal overexpression of mutant amyloid precursor protein results in prominent deposition of cerebrovascular amyloid. Proc. Natl. Acad. Sci. USA 96:14088–14093. Calhoun, M.E., Wiederhold, K.H., Abramowski, D., Phinney, A.L., Probst, A., Sturchler-Pierrat, C., Staufenbiel, M., Sommer, B., and Jucker, M. (1998) Neuron loss in APP transgenic mice. Nature 395:755–756. Chen, G., Chen, K.S., Knox, J., Inglis, J., Bernard, A., Martin, S.J., Justice, A., McConlogue, L., Games, D., Freedman, S.B., and Morris, R.G. (2000) A learning deficit related to age and betaamyloid plaques in a mouse model of Alzheimer’s disease. Nature 408:975–979. Cheng, I.H., Palop, J.J., Esposito, L.A., Bien-Ly, N., Yan, F., and Mucke, L. (2004) Aggressive amyloidosis in mice expressing human amyloid peptides with the Arctic mutation. Nat. Med. 10: 1190–1192. Chevallier, N.L., Soriano, S., Kang, D.E., Masliah, E., Hu, G., and Koo, E.H. (2005) Perturbed neurogenesis in the adult hippocampus associated with presenilin-1 A246E mutation. Am. J. Pathol. 167:151–159. Chishti, M.A., Yang, D.S., Janus, C., Phinney, A.L., Horne, P., Pearson, J., Strome, R., Zuker, N., Loukides, J., French, J., Turner, S., Lozza, G., Grilli, M., Kunicki, S., Morissette, C., Paquette, J., Gervais, F., Bergeron, C., Fraser, P.E., Carlson, G.A., GeorgeHyslop, P.S., and Westaway, D. (2001) Early-onset amyloid deposition and cognitive deficits in transgenic mice expressing a double mutant form of amyloid precursor protein 695. J. Biol. Chem. 276:21562–21570.

54: TRANSGENIC MODELS Chui, D.H., Tanahashi, H., Ozawa, K., Ikeda, S., Checler, F., Ueda, O., Suzuki, H., Araki, W., Inoue, H., Shirotani, K., Takahashi, K., Gallyas, F., and Tabira, T. (1999) Transgenic mice with Alzheimer presenilin 1 mutations show accelerated neurodegeneration without amyloid plaque formation. Nat. Med. 5:560–564. Citron, M., Westaway, D., Xia, W., Carlson, G., Diehl, T., Levesque, G., Johnson-Wood, K., Lee, M., Seubert, P., Davis, A., Kholodenko, D., Motter, R., Sherrington, R., Perry, B., Yao, H., Strome, R., Lieberburg, I., Rommens, J., Kim, S., Schenk, D., Fraser, P., St George Hyslop, P., and Selkoe, D.J. (1997) Mutant presenilins of Alzheimer’s disease increase production of 42-residue amyloid beta-protein in both transfected cells and transgenic mice. Nat. Med. 3:67–72. Codita, A., Winblad, B., and Mohammed, A.H. (2006) Of mice and men: more neurobiology in dementia. Curr. Opin. Psychiatry 19: 555–563. DeMattos, R.B., Bales, K.R., Cummins, D.J., Dodart, J.C., Paul, S. M., and Holtzman, D.M. (2001) Peripheral anti-A beta antibody alters CNS and plasma A beta clearance and decreases brain A beta burden in a mouse model of Alzheimer’s disease. Proc. Natl. Acad. Sci. USA 98:8850–8855. Dodart, J.C., Bales, K.R., Gannon, K.S., Greene, S.J., DeMattos, R.B., Mathis, C., DeLong, C.A., Wu, S., Wu, X., Holtzman, D.M., and Paul, S.M. (2002) Immunization reverses memory deficits without reducing brain Abeta burden in Alzheimer’s disease model. Nat. Neurosci. 5:452–457. Dodart, J.C., Mathis, C., Saura, J., Bales, K.R., Paul, S.M., and Ungerer, A. (2000) Neuroanatomical abnormalities in behaviorally characterized APP(V717F) transgenic mice. Neurobiol. Dis. 7:71–85. Duff, K., Eckman, C., Zehr, C., Yu, X., Prada, C.M., Perez-tur, J., Hutton, M., Buee, L., Harigaya, Y., Yager, D., Morgan, D., Gordon, M.N., Holcomb, L., Refolo, L., Zenk, B., Hardy, J., and Younkin, S. (1996) Increased amyloid-beta42(43) in brains of mice expressing mutant presenilin 1. Nature 383:710–713. Ertekin-Taner, N. (2007) Genetics of Alzheimer’s disease: a centennial review. Neurol. Clin. 25:611–667. Fagan, A.M., Watson, M., Parsadanian, M., Bales, K.R., Paul, S.M., and Holtzman, D.M. (2002) Human and murine ApoE markedly alters A beta metabolism before and after plaque formation in a mouse model of Alzheimer’s disease. Neurobiol. Dis. 9:305–318. Fernagut, P.O., and Chesselet, M.F. (2004) Alpha-synuclein and transgenic mouse models. Neurobiol. Dis. 17:123–130. Flood, D.G., Reaume, A.G., Dorfman, K.S., Lin, Y.G., Lang, D.M., Trusko, S.P., Savage, M.J., Annaert, W.G., De Strooper, B., Siman, R., and Scott, R.W. (2002) FAD mutant PS-1 gene-targeted mice: increased A beta 42 and A beta deposition without APP overproduction. Neurobiol. Aging 23:335–348. Fryer, J.D., Taylor, J.W., DeMattos, R.B., Bales, K.R., Paul, S.M., Parsadanian, M., and Holtzman, D.M. (2003) Apolipoprotein E markedly facilitates age-dependent cerebral amyloid angiopathy and spontaneous hemorrhage in amyloid precursor protein transgenic mice. J. Neurosci. 23:7889–7896. Games, D., Adams, D., Alessandrini, R., Barbour, R., Berthelette, P., Blackwell, C., Carr, T., Clemens, J., Donaldson, T., Gillespie, F., Guido, T., Hagoplan, S., Johnson-Wood, K., Khan, K., Lee, M., Lelbowitz, P., Lieberburg, I., Little, S., Masliah, E., McConlogue, L., Montoya-Zavala, M., Mucke, L., Paganini, L., Pennlman, E., Power, M., Schenk, D., Seubert, P., Snyder, B., Wadsworth, S., Wolozin, B., and Zhao, J. (1995) Alzheimer-type neuropathology in transgenic mice overexpressing V717F beta-amyloid precursor protein. Nature 373:523–527. Games, D., Buttini, M., Kobayashi, D., Schenk, D., and Seubert, P. (2006) Mice as models: transgenic approaches and Alzheimer’s disease. J. Alzheimers Dis. 9:133–149. Gotz, J., Deters, N., Doldissen, A., Bokhari, L., Ke, Y., Wiesner, A., Schonrock, N., and Ittner, L.M. (2007) A decade of tau transgenic animal models and beyond. Brain Pathol. 17:91–103.

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Grilli, M., Diodato, E., Lozza, G., Brusa, R., Casarini, M., Uberti, D., Rozmahel, R., Westaway, D., St George-Hyslop, P., Memo, M., and Ongini, E. (2000) Presenilin-1 regulates the neuronal threshold to excitotoxicity both physiologically and pathologically. Proc. Natl. Acad. Sci. USA 97:12822–12827. Guo, Q., Sebastian, L., Sopher, B.L., Miller, M.W., Ware, C.B., Martin, G.M., and Mattson, M.P. (1999) Increased vulnerability of hippocampal neurons from presenilin-1 mutant knock-in mice to amyloid beta-peptide toxicity: central roles of superoxide production and caspase activation. J. Neurochem. 72:1019–1029. Haugarvoll, K., Wszolek, Z.K., and Hutton, M. (2007) The genetics of frontotemporal dementia. Neurol. Clin. 25:697–715. Herzig, M.C., Winkler, D.T., Burgermeister, P., Pfeifer, M., Kohler, E., Schmidt, S.D., Danner, S., Abramowski, D., Sturchler-Pierrat, C., Burki, K., van Duinen, S.G., Maat-Schieman, M.L., Staufenbiel, M., Mathews, P.M., and Jucker, M. (2004) Abeta is targeted to the vasculature in a mouse model of hereditary cerebral hemorrhage with amyloidosis. Nat. Neurosci. 7:954–960. Higuchi, M., Ishihara, T., Zhang, B., Hong, M., Andreadis, A., Trojanowski, J., and Lee, V.M. (2002) Transgenic mouse model of tauopathies with glial pathology and nervous system degeneration. Neuron 35:433–446. Higuchi, M., Zhang, B., Forman, M.S., Yoshiyama, Y., Trojanowski, J.Q., and Lee, V.M. (2005) Axonal degeneration induced by targeted expression of mutant human tau in oligodendrocytes of transgenic mice that model glial tauopathies. J. Neurosci. 25: 9434–9443. Hock, C., Konietzko, U., Streffer, J.R., Tracy, J., Signorell, A., Muller-Tillmanns, B., Lemke, U., Henke, K., Moritz, E., Garcia, E., Wollmer, M.A., Umbricht, D., de Quervain, D.J., Hofmann, M., Maddalena, A., Papassotiropoulos, A., and Nitsch, R.M. (2003) Antibodies against beta-amyloid slow cognitive decline in Alzheimer’s disease. Neuron 38:547–554. Holcomb, L., Gordon, M.N., McGowan, E., Yu, X., Benkovic, S., Jantzen, P., Wright, K., Saad, I., Mueller, R., Morgan, D., Sanders, S., Zehr, C., O’Campo, K., Hardy, J., Prada, C.M., Eckman, C., Younkin, S., Hsiao, K., and Duff, K. (1998) Accelerated Alzheimer-type phenotype in transgenic mice carrying both mutant amyloid precursor protein and presenilin 1 transgenes. Nat. Med. 4:97–100. Holtzman, D.M., Bales, K.R., Tenkova, T., Fagan, A.M., Parsadanian, M., Sartorius, L.J., Mackey, B., Olney, J., McKeel, D., Wozniak, D., and Paul, S.M. (2000) Apolipoprotein E isoform-dependent amyloid deposition and neuritic degeneration in a mouse model of Alzheimer’s disease. Proc. Natl. Acad. Sci. USA 97:2892– 2897. Hsia, A.Y., Masliah, E., McConlogue, L., Yu, G.Q., Tatsuno, G., Hu, K., Kholodenko, D., Malenka, R.C., Nicoll, R.A., and Mucke, L. (1999) Plaque-independent disruption of neural circuits in Alzheimer’s disease mouse models. Proc. Natl. Acad. Sci. USA 96: 3228–3233. Hsiao, K., Chapman, P., Nilsen, S., Eckman, C., Harigaya, Y., Younkin, S., Yang, F., and Cole, G. (1996) Correlative memory deficits, abeta elevation, and amyloid plaques in transgenic mice. Science 274:99–102. Hsiao, K.K., Borchelt, D.R., Olson, K., Johannsdottir, R., Kitt, C., Yunis, W., Xu, S., Eckman, C., Younkin, S., Price, D., Iadecola, C., Clark, B., and Carlson, G. (1995) Age-related CNS disorder and early death in transgenic FVB/N mice overexpressing Alzheimer amyloid precursor proteins. Neuron 15:1203–1218. Irizarry, M.C., McNamara, M., Fedorchak, K., Hsiao, K., and Hyman, B.T. (1997a) APPSw transgenic mice develop age-related A beta deposits and neuropil abnormalities, but no neuronal loss in CA1. J. Neuropathol. Exp. Neurol. 56:965–973. Irizarry, M.C., Soriano, F., McNamara, M., Page, K.J., Schenk, D., Games, D., and Hyman, B.T. (1997b) Abeta deposition is associated with neuropil changes, but not with overt neuronal loss in

918

DEMENTIA

the human amyloid precursor protein V717F (PDAPP) transgenic mouse. J. Neurosci. 17:7053–7059. Ishihara, T., Hong, M., Zhang, B., Nakagawa, Y., Lee, M.K., Trojanowski, J.Q., and Lee, V.M. (1999) Age-dependent emergence and progression of a tauopathy in transgenic mice overexpressing the shortest human tau isoform. Neuron 24:751–762. Ishihara, T., Zhang, B., Higuchi, M., Yoshiyama, Y., Trojanowski, J.Q., and Lee, V.M. (2001) Age-dependent induction of congophilic neurofibrillary tau inclusions in tau transgenic mice. Am. J. Pathol. 158:555–562. Jacobsen, J.S., Wu, C.C., Redwine, J.M., Comery, T.A., Arias, R., Bowlby, M., Martone, R., Morrison, J.H., Pangalos, M.N., Reinhart, P.H., and Bloom, F.E. (2006) Early-onset behavioral and synaptic deficits in a mouse model of Alzheimer’s disease. Proc. Natl. Acad. Sci. USA 103:5161–5166. Janus, C., Pearson, J., McLaurin, J., Mathews, P.M., Jiang, Y., Schmidt, S.D., Chishti, M.A., Horne, P., Heslin, D., French, J., Mount, H.T., Nixon, R.A., Mercken, M., Bergeron, C., Fraser, P.E., St George-Hyslop, P., and Westaway, D. (2000) A beta peptide immunization reduces behavioural impairment and plaques in a model of Alzheimer’s disease. Nature 408:979–982. Kassed, C.A., Butler, T.L., Navidomskis, M.T., Gordon, M.N., Morgan, D., and Pennypacker, K.R. (2003) Mice expressing human mutant presenilin-1 exhibit decreased activation of NF-kappaB p50 in hippocampal neurons after injury. Mol. Brain Res. 110: 152–157. Kotilinek, L.A., Bacskai, B., Westerman, M., Kawarabayashi, T., Younkin, L., Hyman, B.T., Younkin, S., and Ashe, K.H. (2002) Reversible memory loss in a mouse transgenic model of Alzheimer’s disease. J. Neurosci. 22:6331–6335. Lazarov, O., Peterson, L.D., Peterson, D.A., and Sisodia, S.S. (2006) Expression of a familial Alzheimer’s disease-linked presenilin-1 variant enhances perforant pathway lesion-induced neuronal loss in the entorhinal cortex. J. Neurosci. 26:429–434. Lazarov, O., Robinson, J., Tang, Y.P., Hairston, I.S., KoradeMirnics, Z., Lee, V.M., Hersh, L.B., Sapolsky, R.M., Mirnics, K., and Sisodia, S.S. (2005) Environmental enrichment reduces Abeta levels and amyloid deposition in transgenic mice. Cell 120:701– 713. Le Corre, S., Klafki, H.W., Plesnila, N., Hubinger, G., Obermeier, A., Sahagun, H., Monse, B., Seneci, P., Lewis, J., Eriksen, J., Zehr, C., Yue, M., McGowan, E., Dickson, D.W., Hutton, M., and Roder, H.M. (2006) An inhibitor of tau hyperphosphorylation prevents severe motor impairments in tau transgenic mice. Proc. Natl. Acad. Sci. USA 103:9673–9678. Lesne, S., Koh, M.T., Kotilinek, L., Kayed, R., Glabe, C.G., Yang, A., Gallagher, M., and Ashe, K.H. (2006) A specific amyloidbeta protein assembly in the brain impairs memory. Nature 440: 352–357. Lewis, J., Dickson, D.W., Lin, W.L., Chisholm, L., Corral, A., Jones, G., Yen, S.H., Sahara, N., Skipper, L., Yager, D., Eckman, C., Hardy, J., Hutton, M., and McGowan, E. (2001) Enhanced neurofibrillary degeneration in transgenic mice expressing mutant tau and APP. Science 293:1487–1491. Lewis, J., McGowan, E., Rockwood, J., Melrose, H., Nacharaju, P., Van Slegtenhorst, M., Gwinn-Hardy, K., Paul Murphy, M., Baker, M., Yu, X., Duff, K., Hardy, J., Corral, A., Lin, W.L., Yen, S.H., Dickson, D.W., Davies, P., and Hutton, M. (2000) Neurofibrillary tangles, amyotrophy and progressive motor disturbance in mice expressing mutant (P301L) tau protein. Nat. Genet. 25: 402–405. Li, A., Piccardo, P., Barmada, S.J., Ghetti, B., and Harris, D.A. (2007) Prion protein with an octapeptide insertion has impaired neuroprotective activity in transgenic mice. Embo. J. 26:2777– 2785. Lin, W.L., Lewis, J., Yen, S.H., Hutton, M., and Dickson, D.W. (2003a) Filamentous tau in oligodendrocytes and astrocytes of

transgenic mice expressing the human tau isoform with the P301L mutation. Am. J. Pathol. 162:213–218. Lin, W.L., Lewis, J., Yen, S.H., Hutton, M., and Dickson, D.W. (2003b) Ultrastructural neuronal pathology in transgenic mice expressing mutant (P301L) human tau. J. Neurocytol. 32:1091– 1105. Link, C.D. (2005) Invertebrate models of Alzheimer’s disease. Genes Brain Behav. 4:147–156. Mandelkow, E., von Bergen, M., Biernat, J., and Mandelkow, E.M. (2007) Structural principles of tau and the paired helical filaments of Alzheimer’s disease. Brain Pathol. 17:83–90. Masliah, E., Sisk, A., Mallory, M., and Games, D. (2001) Neurofibrillary pathology in transgenic mice overexpressing V717F betaamyloid precursor protein. J. Neuropathol. Exp. Neurol. 60:357– 368. McGowan, E., Eriksen, J., and Hutton, M. (2006) A decade of modeling Alzheimer’s disease in transgenic mice. Trends Genet. 22: 281–289. McGowan, E., Pickford, F., Kim, J., Onstead, L., Eriksen, J., Yu, C., Skipper, L., Murphy, M.P., Beard, J., Das, P., Jansen, K., Delucia, M., Lin, W.L., Dolios, G., Wang, R., Eckman, C.B., Dickson, D.W., Hutton, M., Hardy, J., and Golde, T. (2005) Abeta42 is essential for parenchymal and vascular amyloid deposition in mice. Neuron 47:191–199. Moechars, D., Dewachter, I., Lorent, K., Reverse, D., Baekelandt, V., Naidu, A., Tesseur, I., Spittaels, K., Haute, C.V., Checler, F., Godaux, E., Cordell, B., and Van Leuven, F. (1999) Early phenotypic changes in transgenic mice that overexpress different mutants of amyloid precursor protein in brain. J. Biol. Chem. 274: 6483–6492. Mohmmad Abdul, H., Wenk, G.L., Gramling, M., Hauss-Wegrzyniak, B., and Butterfield, D.A. (2004) APP and PS-1 mutations induce brain oxidative stress independent of dietary cholesterol: implications for Alzheimer’s disease. Neurosci. Lett. 368:148–150. Morgan, D. (2006) Immunotherapy for Alzheimer’s disease. J. Alzheimers Dis. 9:425–432. Nakano, Y., Kondoh, G., Kudo, T., Imaizumi, K., Kato, M., Miyazaki, J.I., Tohyama, M., Takeda, J., and Takeda, M. (1999) Accumulation of murine amyloidbeta42 in a gene-dosage-dependent manner in PS1 “knock-in” mice. Eur. J. Neurosci. 11:2577–2581. Oakley, H., Cole, S.L., Logan, S., Maus, E., Shao, P., Craft, J., GuillozetBongaarts, A., Ohno, M., Disterhoft, J., Van Eldik, L., Berry, R., and Vassar, R. (2006) Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J. Neurosci. 26:10129–10140. Oddo, S., Billings, L., Kesslak, J.P., Cribbs, D.H., and LaFerla, F.M. (2004) Abeta immunotherapy leads to clearance of early, but not late, hyperphosphorylated tau aggregates via the proteasome. Neuron 43:321–332. Oddo, S., Caccamo, A., Shepherd, J.D., Murphy, M.P., Golde, T.E., Kayed, R., Metherate, R., Mattson, M.P., Akbari, Y., and LaFerla, F.M. (2003) Triple-transgenic model of Alzheimer’s disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron 39:409–421. Orgogozo, J.M., Gilman, S., Dartigues, J.F., Laurent, B., Puel, M., Kirby, L.C., Jouanny, P., Dubois, B., Eisner, L., Flitman, S., Michel, B.F., Boada, M., Frank, A., and Hock, C. (2003) Subacute meningoencephalitis in a subset of patients with AD after Abeta42 immunization. Neurology 61:46–54. Patel, N.V., Gordon, M.N., Connor, K.E., Good, R.A., Engelman, R.W., Mason, J., Morgan, D.G., Morgan, T.E., and Finch, C.E. (2005) Caloric restriction attenuates Abeta-deposition in Alzheimer transgenic models. Neurobiol. Aging 26:995–1000. Pickford, F., Coomaraswamy, J., Jucker, M., and McGowan, E. (2006) Modeling familial British dementia in transgenic mice. Brain Pathol. 16:80–85.

54: TRANSGENIC MODELS Probst, A., Gotz, J., Wiederhold, K.H., Tolnay, M., Mistl, C., Jaton, A.L., Hong, M., Ishihara, T., Lee, V.M., Trojanowski, J.Q., Jakes, R., Crowther, R.A., Spillantini, M.G., Burki, K., and Goedert, M. (2000) Axonopathy and amyotrophy in mice transgenic for human four-repeat tau protein. Acta. Neuropathol. (Berl) 99:469–481. Ramsden, M., Kotilinek, L., Forster, C., Paulson, J., McGowan, E., SantaCruz, K., Guimaraes, A., Yue, M., Lewis, J., Carlson, G., Hutton, M., and Ashe, K.H. (2005) Age-dependent neurofibrillary tangle formation, neuron loss, and memory impairment in a mouse model of human tauopathy (P301L). J. Neurosci. 25: 10637–10647. Reaume, A.G., Howland, D.S., Trusko, S.P., Savage, M.J., Lang, D. M., Greenberg, B.D., Siman, R., and Scott, R.W. (1996) Enhanced amyloidogenic processing of the beta-amyloid precursor protein in gene-targeted mice bearing the Swedish familial Alzheimer’s disease mutations and a “humanized” Abeta sequence. J. Biol. Chem. 271:23380–23388. Redwine, J.M., Kosofsky, B., Jacobs, R.E., Games, D., Reilly, J.F., Morrison, J.H., Young, W.G., and Bloom, F.E. (2003) Dentate gyrus volume is reduced before onset of plaque formation in PDAPP mice: a magnetic resonance microscopy and stereologic analysis. Proc. Natl. Acad. Sci. USA 100:1381–1386. Refolo, L.M., Pappolla, M.A., LaFrancois, J., Malester, B., Schmidt, S.D., Thomas-Bryant, T., Tint, G.S., Wang, R., Mercken, M., Petanceska, S.S., and Duff, K.E. (2001) A cholesterol-lowering drug reduces beta-amyloid pathology in a transgenic mouse model of Alzheimer’s disease. Neurobiol. Dis. 8:890–899. Reilly, J.F., Games, D., Rydel, R.E., Freedman, S., Schenk, D., Young, W.G., Morrison, J.H., and Bloom, F.E. (2003) Amyloid deposition in the hippocampus and entorhinal cortex: quantitative analysis of a transgenic mouse model. Proc. Natl. Acad. Sci. USA 100:4837–4842. Roberson, E.D., Scearce-Levie, K., Palop, J.J., Yan, F., Cheng, I.H., Wu, T., Gerstein, H., Yu, G.Q., and Mucke, L. (2007) Reducing endogenous tau ameliorates amyloid beta-induced deficits in an Alzheimer’s disease mouse model. Science 316:750–754. Ross, C.A., and Poirier, M.A. (2005) Opinion: What is the role of protein aggregation in neurodegeneration? Nat. Rev. Mol. Cell. Biol. 6:891–898. Santacruz, K., Lewis, J., Spires, T., Paulson, J., Kotilinek, L., Ingelsson, M., Guimaraes, A., DeTure, M., Ramsden, M., McGowan, E., Forster, C., Yue, M., Orne, J., Janus, C., Mariash, A., Kuskowski, M., Hyman, B., Hutton, M., and Ashe, K.H. (2005) Tau suppression in a neurodegenerative mouse model improves memory function. Science 309:476–481. Sasaki, A., Shoji, M., Harigaya, Y., Kawarabayashi, T., Ikeda, M., Naito, M., Matsubara, E., Abe, K., and Nakazato, Y. (2002) Amyloid cored plaques in Tg2576 transgenic mice are characterized by giant plaques, slightly activated microglia, and the lack of paired helical filament-typed, dystrophic neurites. Virchows Arch. 441:358–367. Schenk, D., Barbour, R., Dunn, W., Gordon, G., Grajeda, H., Guido, T., Hu, K., Huang, J., Johnson-Wood, K., Khan, K., Kholodenko, D., Lee, M., Liao, Z., Lieberburg, I., Motter, R., Mutter, L., Soriano, F., Shopp, G., Vasquez, N., Vandevert, C., Walker, S., Wogulis, M., Yednock, T., Games, D., and Seubert, P. (1999) Immunization with amyloid-beta attenuates Alzheimer-disease-like pathology in the PDAPP mouse. Nature 400:173–177. Schmitz, C., Rutten, B.P., Pielen, A., Schafer, S., Wirths, O., Tremp, G., Czech, C., Blanchard, V., Multhaup, G., Rezaie, P., Korr, H., Steinbusch, H.W., Pradier, L., and Bayer, T.A. (2004) Hippocampal neuron loss exceeds amyloid plaque load in a transgenic mouse model of Alzheimer’s disease. Am. J. Pathol. 164:1495–1502.

919

Schneider, I., Reverse, D., Dewachter, I., Ris, L., Caluwaerts, N., Kuiperi, C., Gilis, M., Geerts, H., Kretzschmar, H., Godaux, E., Moechars, D., Van Leuven, F., and Herms, J. (2001) Mutant presenilins disturb neuronal calcium homeostasis in the brain of transgenic mice, decreasing the threshold for excitotoxicity and facilitating long-term potentiation. J. Biol. Chem. 276:11539– 11544. Schuessel, K., Frey, C., Jourdan, C., Keil, U., Weber, C.C., MullerSpahn, F., Muller, W.E., and Eckert, A. (2006) Aging sensitizes toward ROS formation and lipid peroxidation in PS1M146L transgenic mice. Free Radic. Biol. Med. 40:850–862. Selkoe, D.J. (2001) Alzheimer’s disease: genes, proteins, and therapy. Physiol. Rev. 81:741–766. Solomon, B., Koppel, R., Hanan, E., and Katzav, T. (1996) Monoclonal antibodies inhibit in vitro fibrillar aggregation of the Alzheimer beta-amyloid peptide. Proc. Natl. Acad. Sci. USA 93: 452–455. Spittaels, K., Van den Haute, C., Van Dorpe, J., Bruynseels, K., Vandezande, K., Laenen, I., Geerts, H., Mercken, M., Sciot, R., Van Lommel, A., Loos, R., and Van Leuven, F. (1999) Prominent axonopathy in the brain and spinal cord of transgenic mice overexpressing four-repeat human tau protein. Am. J. Pathol. 155: 2153–2165. Stokin, G.B., Lillo, C., Falzone, T.L., Brusch, R.G., Rockenstein, E., Mount, S.L., Raman, R., Davies, P., Masliah, E., Williams, D.S., and Goldstein, L.S. (2005) Axonopathy and transport deficits early in the pathogenesis of Alzheimer’s disease. Science 307: 1282–1288. Tanemura, K., Chui, D.H., Fukuda, T., Murayama, M., Park, J.M., Akagi, T., Tatebayashi, Y., Miyasaka, T., Kimura, T., Hashikawa, T., Nakano, Y., Kudo, T., Takeda, M., and Takashima, A. (2006) Formation of tau inclusions in knock-in mice with familial Alzheimer disease (FAD) mutation of presenilin 1 (PS1). J. Biol. Chem. 281:5037–5041. Terwel, D., Lasrado, R., Snauwaert, J., Vandeweert, E., Van Haesendonck, C., Borghgraef, P., and Van Leuven, F. (2005) Changed conformation of mutant tau-P301L underlies the moribund tauopathy, absent in progressive, nonlethal axonopathy of tau4R/2N transgenic mice. J. Biol. Chem. 280:3963–3973. Vetrivel, K.S., Zhang, Y.W., Xu, H., and Thinakaran, G. (2006) Pathological and physiological functions of presenilins. Mol. Neurodegener. 1:4. Walker, F.O. (2007) Huntington’s disease. Lancet 369:218–228. Walsh, D.M., and Selkoe, D.J. (2007) A beta oligomers—a decade of discovery. J. Neurochem. 101:1172–1184. Wang, J., Ho, L., Zhao, Z., Seror, I., Humala, N., Dickstein, D.L., Thiyagarajan, M., Percival, S.S., Talcott, S.T., and Pasinetti, G.M. (2006) Moderate consumption of Cabernet Sauvignon attenuates Abeta neuropathology in a mouse model of Alzheimer’s disease. FASEB J. 20:2313–2320. Wen, P.H., Hof, P.R., Chen, X., Gluck, K., Austin, G., Younkin, S. G., Younkin, L.H., DeGasperi, R., Gama Sosa, M.A., Robakis, N.K., Haroutunian, V., and Elder, G.A. (2004) The presenilin-1 familial Alzheimer disease mutant P117L impairs neurogenesis in the hippocampus of adult mice. Exp. Neurol. 188:224–237. Wu, C.C., Chawla, F., Games, D., Rydel, R.E., Freedman, S., Schenk, D., Young, W.G., Morrison, J.H., and Bloom, F.E. (2004) Selective vulnerability of dentate granule cells prior to amyloid deposition in PDAPP mice: digital morphometric analyses. Proc. Natl. Acad. Sci. USA 101:7141–7146. Wu, Y., and Luo, Y. (2005) Transgenic C. elegans as a model in Alzheimer’s research. Curr. Alzheimer Res. 2:37–45.

55 Functional Neuroanatomy of Learning and Memory GARY L. WENK

INTRODUCTION TO MULTIPLE MEMORY SYSTEMS The predominant theme in recent studies of the neuroanatomy of human learning and memory has been that memory does not rely upon a single system of the brain but is composed of many separate systems that can function independent of each other (Mishkin and Appenzeller, 1987; Zola-Morgan and Squire, 1993; Mishkin and Murray, 1994). The dissociations between different types of memory abilities reflect the nature and organization of this distributed system of brain regions. The classic distinctions between long- and short-term memory have evolved into more complicated dichotomies organized around the concepts of declarative (or explicit) and nondeclarative (or implicit) memory systems (Squire, 1992; Schacter and Tulving, 1994). Declarative memories include factual knowledge, such as the multiplication tables and the ability to recognize specific objects, and the events or episodes in one’s life. Declarative memories can be acquired quickly within a single learning experience and can be expressed as explicit statements of knowledge. Declarative memories are primarily associated with the medial temporal lobe structures, including the hippocampus and related entorhinal, perirhinal, and parahippocampal cortices. In contrast, nondeclarative memories are usually acquired more slowly across many learning sessions, with a few notable exceptions, such as taste aversion, and are closely tied to the original learning situation. Nondeclarative memories include a broad range of nonconscious abilities, such as skills or habits controlled by the striatum (Knowlton et al., 1996), and motor responses to classically conditioned stimuli such as the eye-blink reflex organized by the cerebellum (Krupa et al., 1993). Simple reflexes organized by the brain stem and spinal cord that respond to peripheral stimuli are also considered types of nondeclarative memory. Finally, the ability to recall recently acquired information following presentation of some component of the memory, that is, priming, is another type of nondeclarative memory that is thought to require the neocortex (Tulving and Schacter, 1990). These structures are clearly involved 920

in the acquisition of memories. Recent evidence suggests that our long-term memories are ultimately stored in the cortical and subcortical neuronal networks that originally mediated the experience, that is, association cortex and higher-order secondary cortex (Squire, 1992; Roland and Gulyas, 1994) as well as the hippocampus (Rolls, 2000). These distinctions of locus of function have been based upon studies of experimental animals that have been given specific and discrete lesions to the related brain structures mentioned above, as well as upon studies of patients who were amnestic. Finally, it must always be kept in mind that the same brain structure or cortical region may participate in different kinds of learning and memory and that some types of memories require the activation of many different brain regions. APPROACHES TO THE STUDY OF THE NEUROANATOMY OF MEMORY SYSTEMS: LESION ANALYSES VERSUS STIMULATION VERSUS RECORDING STUDIES The analysis of the effects of lesions is probably the oldest, and still most widely used, approach to the problem of structure–function analyses and the determination of the neuroanatomy of memory systems in the brain. In humans, the behavioral effects of lesions resulting from head injury, tumors, vascular accidents, or neurosurgery are compared to the behavior of normal patients on a variety of standardized behavioral tasks. Similar research has been completed using nonhuman species such as primates and rodents, with the fundamental difference that the brain lesions are more precisely produced and more discrete in their effects upon behavior. Lesions are typically produced by one of the following methods: aspirating small regions out of the brain; electrolytic lesioning, that is, the passing of electric currents into the specific brain region; heating or cooling of the tissue to produce transient inactivation of the region; or the injection of selective neurotoxins into specific brain regions that may be selectively vulnerable to the action of these toxins. Although brain lesions

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are relatively easy to produce, the interpretation of their effects can be quite difficult and requires that the experimenter have a thorough understanding of the consequences of each type of manipulation: nonspecific effects of the lesion, transynaptic degeneration of nearby brain regions, effects of the subsequent cell loss upon neuroinflammatory processes, and so on. Lesions can produce a variety of effects upon behavior that make interpretation difficult. For example, lesions can alter performance in tasks that are sensitive to learning and memory because the critical brain region for that function has been damaged or destroyed, or because that brain region was initially responsible for inhibiting a specific behavior that has now been released from inhibition. Lesions can also cause the expression of the expected behavior to be disorganized so that the patient cannot reliably perform the task in an appropriate manner. Stimulation of the brain nonspecifically by electrical current, or specifically by the application of pharmacological agents, can produce one of the following responses: (1) a relatively specific and discrete effect, such as the activation of a small muscle group, a change in body temperature, or activation of a specific neural system or (2) an overall activating effect, such as the aggression response following stimulation of the amygdala or feeding behavior following stimulation of the lateral hypothalamus. Determining which of the above effects of the stimulation might underlie a particular behavior is often quite difficult. The advantage of stimulation studies using recently designed minimal stimulation techniques, over the lesion analyses, however, is that one is working with an intact, functioning, and relatively normal neural system. Recording the brain’s neural activity, either electrical or chemical, and interpreting these studies presents a unique series of challenges. Electrophysiological recordings using in-dwelling electrodes can provide instantaneous information on the relationship between the activity of individual neurons, or groups of neurons, within a specific brain region and selected behaviors. The simultaneous recording of the activity of hundreds of neurons can provide information on how neurons interact with each other to produce specific behaviors. The combination of these techniques can provide valuable insights on brain regions involved in specific types of memory. Neuroimaging studies have been used to confirm the results obtained using these methods and extend them by monitoring multiple regions in the healthy or injured brain. Electrophysiological methods, however, do not allow the determination of the neurotransmitter identity of the neural system being recorded, that is, whether the neurons are acetylcholinergic, dopaminergic, serotonergic, and so on. The determination of the release of specific neurotransmitter substances, for example by microdialysis or by using a push–pull cannula, provides important information on the specificity of the neurotrans-

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mitter changes within a particular neural system, but it cannot provide information on instantaneous changes in neuronal activity. Neuroimaging methods can be used to monitor selected aspects of the behavior of specific neurotransmitter systems, such as receptor density and metabolite levels that can then be related to specific mnemonic abilities. Taken together, these approaches have provided considerable insights into the ways in which memory systems are distributed and organized within the human brain. The following sections present information on the specific brain systems involved in our ability to learn and remember. MIDLINE DIENCEPHALON STRUCTURES Medial Dorsal Thalamus A role for the medial dorsal thalamic nucleus in memory has been based upon the finding that this region is consistently injured in alcoholic Korsakoff’s syndrome. This syndrome is associated with a severe anterograde and retrograde amnesia. Patients typically have normal nondeclarative or implicit memory but impaired declarative memory. Patients with medial dorsal thalamic damage following cerebrovascular infarctions also demonstrate significant memory impairments (Winocur et al., 1984; Graff-Radford et al., 1990). Well-circumscribed lesions of this thalamic region can impair performance in a delayed nonmatching to sample task in monkeys (Aggleton and Mishkin, 1983) and rats (Mumby and Pinel, 1994). In addition, when the medial dorsal nucleus (and mammillary bodies) are damaged following administration of the antithiamine drug pryithiamine, rats demonstrate significant impairments on a variety of tasks that require learning and memory (Mair et al., 1991). A recent positron emission tomography (PET) study was conducted (Andreasen et al., 1999) to investigate the activity of the medial dorsal thalamus when patients intentionally recalled a specific past personal experience. The silent recall of a consciously retrieved episodic memory produces activation of the left medial dorsal thalamus. This region may therefore assist in the initiation and monitoring of the conscious retrieval of episodic memories. The prefrontal cortex efferents of the medial dorsal thalamus are so extensive that they have been used to define the region (Fuster, 1997). Functional magnetic resonance imaging (fMRI) studies have demonstrated that the human thalamus is involved in verbal memory (Crespo-Facorro et al., 1999) and sequence learning (Rauch et al., 1998). Mammillary Nucleus Damage to the mammillothalamic tracts that connect the anterior nucleus of the thalamus with the mammillary

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bodies located in the posterior hypothalamus also produces a memory impairment (Malamut et al., 1992). The mammillary bodies are a component of the extended hippocampal system; anterograde and retrograde memories are affected following injury to this system (Gilboa et al., 2006). Degeneration of the mammillary bodies is also sometimes reported in patients with Korsakoff’s syndrome (Victor et al., 1989). In monkeys, bilateral lesions of the mammillary bodies impair memory (Aggleton and Mishkin, 1985). Two famous clinical cases demonstrate the difficulty in interpreting the consequences of thalamic nucleus versus mammillary nucleus injury in humans. Patient N.A. was a U.S. Air Force radar technician when his barracks roommate accidentally thrust a miniature fencing foil through his right nostril. The foil pierced the cribriform plate and passed into the left medial dorsal nucleus. Computed tomography (CT) scans confirmed that N.A. also has bilateral injury to the mammillothalamic tracts (Squire et al., 1989). N.A. has a slight retrograde amnesia and profound anterograde amnesia. As might be predicted from the above discussion, N.A. has difficulty with declarative but not nondeclarative memories; that is, he can learn motor skills but cannot remember recent events. In contrast, patient B.J. presented with a nearly identical memory disorder (Dusoir et al., 1990) following injury to only the mammillary bodies produced by having a snooker cue thrust through his left nostril. Rats with lesions of the mammillary bodies show similar impairments. Rats show a spatial learning deficit following damage of this structure that may be specific to remembering one or more places over a given time (Sziklas and Petrides, 2000). THE BASAL FOREBRAIN REGION The basal forebrain region contains a population of large cholinergic (Ch) neurons within the medial septal area (MSA) that send an efferent projection to the hippocampus, and within the nucleus basalis of Meynert (NBM) that innervates the entire cortical mantle, olfactory bulbs, and amygdala (Wenk and Olton, 1987). Interest in this brain region followed the suggestion that a decline in the number of Ch cells may be responsible for some of the cognitive impairments associated with aging and Alzheimer’s disease (AD) (Coyle et al., 1983). Behavioral deficits associated with lesions of the NBM were initially interpreted as being the result of impairments in learning and memory abilities (for a review, see Olton and Wenk, 1987). The possibility that forebrain Ch systems might not always play a role in the neural processes that underlie memory was initially demonstrated in an elegant study by Dunnett and colleagues (1987) that found that the degree of destruction of NBM Ch neurons did not correlate with the degree of impair-

ment in a spatial memory task. Subsequent studies concluded that NBM Ch neurons may be important for specific aspects of attention (Olton et al., 1988; Robbins et al., 1989; Muir et al., 1992; Wenk, 1993, 1997). More recent studies have confirmed that the Ch projection to neocortex is involved in the control of attention (Everitt and Robbins, 1997; Sarter et al., 2005). Electrophysiological evidence has also implicated NBM Ch cells in attentional processes. Attention to biologically relevant stimuli was associated with an increase in the activity of basal forebrain neurons in primates (Richardson and DeLong, 1991; Wilson and Rolls, 1990). Single units within the NBM and the nucleus of the diagonal band of Broca were selectively responsive to visual or auditory stimuli that were associated with the expectation of food reward (Wilson and Rolls, 1990). Overall, then, the corticopetal NBM Ch system may be involved in the control of shifting attention to potentially relevant, and brief, sensory stimuli that predict a biologically relevant event, such as the availability of a food reward. In contrast, MSA Ch efferents to the hippocampus may play a more direct role in the neural processes that underlie learning and memory. However, the influence of MSA Ch cells may be task dependent. For example, selective Ch lesions impaired performance in a delayed nonmatching to position operant task (M.P. McDonald et al., 1997) but did not impair performance in the Morris water maze (Berger-Sweeney et al., 1994). MEDIAL TEMPORAL LOBE Overall, the medial temporal region is critical for the development of declarative memories that are required for the long-term storage and conscious recall of specific events or episodes and factual knowledge. Recent lesion analysis studies have confirmed that the severity and nature of declarative memory impairments depend upon the location and extent of injury to specific regions within the temporal lobe. Although injury to the hippocampus can impair declarative memory abilities, the combined destruction of the hippocampus, entorhinal cortices, and parahippocampal gyrus produces far more severe and long-lasting impairments. Lesion analyses have demonstrated that these various regions are involved in controlling different aspects of mnemonic ability (Murray, 1996). Hippocampus The hippocampus may mediate the representation of spatial and temporal memories by association of stimuli from all sensory modalities. The kinds of memories that the hippocampus stores have also been referred to as relational, that is, information on how specific objects

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or events, existing in some spatial or temporal arrangement, are related to each other (Eichenbaum et al., 1994). The key aspect of these kinds of memories is that they are relational, flexible, and permit creative behavior (Nadel, 1996). The hippocampus is critical for encoding information about an animal’s environment and the episodes that occur within those environments. In so doing, it forms and stores representations of spaces and spatial contexts; these are called cognitive maps (O’Keefe and Nadel, 1978). Experimental support for these ideas has come from many different approaches to the study of hippocampal function (Eichenbaum et al., 1992). For example, in rats and monkeys, hippocampal neurons increase their firing rate when the animal moves into a specific location in its immediate environment (O’Keefe and Nadel, 1978). These “place field” cells contribute information about the place and time when a memory occurs that becomes part of the context of the memory (Smith and Mizumori, 2006). The cognitive map theory of hippocampal function suggests that discrete and selective lesions of the hippocampus will produce a deficit in place learning or exploration of a novel environment (Nadel, 1996). Functional magnetic resonance imaging studies on humans have confirmed that the hippocampus is active during contextdependent tasks (Nadel et al., 2000) and inferential tasks where the patient integrates previously learned information to perform successfully under novel conditions (Greene et al., 2006). Historically, it has been assumed that the hippocampus also temporarily stores information that has been recently obtained and that is useful for the current task at hand or is destined for long-term storage elsewhere. Recent evidence, however, obtained from patients with temporal lobe injury (for example, H.M.) suggests that the hippocampus may also store information for many years. Entorhinal and Parahippocampal Cortices Combined lesions of the entorhinal and parahippocampal cortices impair performance on tasks that require learning and memory almost as seriously as large temporal lobe lesions that include these structures and the hippocampus as well (Zola-Morgan, Squire, Amaral, and Suzuki, 1989b; Suzuki et al., 1993; Zola-Morgan et al., 1994). This fact is better appreciated when one considers that these structures are a critical route for cortical sensory information entering the hippocampus (Insausti et al., 1987). Surprisingly, the bilateral destruction of the entorhinal cortex alone produced only a transient impairment in a delay-dependent form of memory, that is, the delayed nonmatch to sample task (Leonard et al., 1995). Impaired performance in this task was longer lasting when the parahippocampal gyrus was also included with the entorhinal lesion (Zola-Morgan, Squire, Amaral, and Suzuki, 1989b; Suzuki et al., 1993). This

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delayed nonmatch to sample task is the most sensitive task that is used to demonstrate memory impairments related to the function of the entorhinal cortex. It is a recognition task that requires the animal to distinguish between a novel object and an object seen prior to a delay period. New pairs of objects are used on each trial. Overall, the perirhinal and entorhinal cortical areas are important for stimulus recognition memory and stimulus-stimulus associations across sensory modalities (Murray, 1996). These ventral temporal cortical areas are probably more important for the consolidation of long-term memories for facts and events, that is, semantic knowledge, than are the amygdala and hippocampus (Squire, 1992; Murray, 1996). Recent studies using fMRI techniques also implicate an interaction between activity within the parahippocampal cortex and hippocampus during the retrieval of autobiographical events (Maguire et al., 2001) and remote memories (Squire and Bayey, 2007). Amygdala The amygdala mediates the memory of affective or emotional information and may encode memories for the emotional significance of events (LeDoux, 1993). This type of memory has been given the name valence memory (Nadel, 1996). Support for this concept comes from electrophysiological studies of the activity of amygdala neurons and from studies of the effects of discrete lesions. Amygdala neurons respond most vigorously to stimuli that have affective salience; that is, they predict whether a stimulus will be positively or negatively rewarding (Nishijo et al., 1988). Recent investigations of the primate amygdala are consistent with this hypothesis; amygdala neurons transmit information about a large array of complex sensory, particularly visual in primates, stimuli. This information is processed to allow facial recognition (Gothard et al., 2007). Animals with lesions of the amygdala are impaired in tasks that require a distinction between responses to stimuli that are, or are not, associated with a food reward (R.J. McDonald and White, 1993). However, amygdala lesions do not impair performance in tasks that only require delay-dependent forms of memory, such as in a delayed nonmatch to sample task (Zola-Morgan, Squire, and Amaral, 1989a). The amygdala also seems to code the relative magnitude of the reward (Kesner and Williams, 1995; Rolls et al., 1999). Therefore, the amygdala probably is important for remembering information that is associated with a particular affect. It most likely contributes this information to the adjacent hippocampal system to enhance the consolidation and remembrance of information that is of particular importance to the animal—for example, that certain sensory cues predict significant reward or danger (Aggleton, 2001).

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CEREBELLUM

PREFRONTAL CORTEX

The cerebellum has traditionally been considered to be dedicated to motor functions and is required for the acquisition and expression of the conditioned response (Christian and Thompson, 2005). Its connectivity and phylogenetic development patterns suggest that it also plays a role in higher cognitive processes (Lee and Thompson, 2006). The cerebellum is responsible for implicit memories of sensorimotor learning. The classic example of learning that is controlled by the cerebellum is the eye-blink response (Desimone, 1992; Krupa et al., 1993). Rabbits will blink their eyes in response to an air puff directed to the cornea. When this air puff is repeatedly paired with a tone, the rabbit will learn to blink in response to the tone. Rabbits with cerebellar lesions do not acquire this association. Damage to the cerebellum can impair other learned sensorimotor responses, such as the ability to perform complex motor skills that have been well rehearsed—for example, skiing, golfing, playing musical instruments, speech, or the control of eye movements (Glickstein and Yeo, 1990).

The prefrontal cortex influences our memory for the temporal order of events rather than the actual memory of those events. Operationally, the neurons within this brain region may control neuronal activity in premotor and motor cortex to inhibit temporally inappropriate behaviors (Narayanan and Laubach, 2006). Therefore, monkeys with lesions of the prefrontal cortex are impaired in a delayed nonmatching to sample task when the sample objects recur again and again across each trial. To perform this task, the monkey must remember which object was seen most recently, inhibit the same response, and therefore choose the other object. In contrast, prefrontal lesions do not impair performance of this task when novel objects are used on each trial. In this instance, the monkey need only recall that an object is novel (never been seen before) and choose that object. Studies using PET suggest that the prefrontal cortex is active during word encoding and that it coordinates its function with the dorsal hippocampus (Leube et al., 2001). Finally, it has become clear that a neural circuit comprising the prefrontal cortex and various limbic structures, in particular the amygdala, normally implements the self-regulation of emotions.

BASAL GANGLIA The basal ganglia are thought to play a critical role in motor planning and movement sequencing. Studies using fMRI have shown that the basal ganglia may modulate activity in the thalamus during working memory–guided movement sequencing. The globus pallidus may contribute to the planning and temporal organization of motor sequencing (Menon et al., 2000). The caudate nucleus may be responsible for memories of motor responses (for example, estimates of the distance that one moved a lever) as well as habit learning (for example, patterns of specific movements). This type of learning is more gradual than that established by the hippocampus and requires repeated associations of the stimuli to be learned (Knowlton et al., 1996). In addition to habit learning, the caudate may be critical for remembering the spatial relationship of objects with regard to oneself, that is, egocentric memory (Kesner et al., 1993). This is in contrast to the type of memory that may be organized by the hippocampus, that is, memory for the spatial relation of objects in relation to each other (Kesner et al., 1993). In support of this concept, recent studies have shown that neurons in the caudate are active when a monkey is picking up a piece of food or manipulating objects within its environment (Rolls et al., 1983). Connections between the striatum and prefrontal cortex may enable behavioral flexibility that involves extradimensional shifts, particularly for learning and memory of visual cue and response information (Ragozzino et al., 2002; Eschenko and Mizumori, 2007).

ANTERIOR CINGULATE Multiple functions that underlie memory have been associated with the anterior cingulate gyrus, perhaps the most important being attention (Posner and Rothbart, 1998). Not surprisingly, healthy elderly adults who demonstrate a dysfunction in attention have decreased activation of this brain region (Milham et al., 2002; Pardo et al., 2007). Single neuron activity recorded during training suggests that the rabbit anterior cingulate cortex cAC is part of an attentional mechanism detecting coincidence between temporally related environmental stimuli (Weible et al., 2003).

ACKNOWLEDGMENT Preparation of this chapter was supported in part by the National Institute of Aging, RO1 AG030331.

REFERENCES Aggleton, J.P. (2001) The Amygdala. Oxford, UK: Oxford University Press. Aggleton, J.P., and Mishkin, M. (1983) Memory impairments following restricted medial thalamic lesions. Exp. Brain Res. 52: 199–209. Aggleton, J.P., and Mishkin, M. (1985) Mammillary body lesions and visual recognition in monkeys. Exp. Brain Res. 58:190–197.

55: FUNCTIONAL NEUROANATOMY OF LEARNING AND MEMORY Andreasen, N.C., O’Leary, D.S., Paradiso, S., Cizadla, T., Arndt, S., Watkins, G.L., Ponto, L.L., and Hichwa, R.D. (1999) The cerebellum plays a role in conscious episodic memory retrieval. Hum. Brain Mapp. 8:226–234. Berger-Sweeney, J., Heckers, S., Mesulam, M.M., Wiley, R.G., Lappi, D.A., and Sharma, M. (1994) Differential effects on spatial navigation of immunotoxin-induced cholinergic lesions of the medial septal area and nucleus basalis magnocellularis. J. Neurosci. 14: 4507–4519. Christian, K.M., and Thompson R.F. (2005) Long-term storage of an associative memory trace in the cerebellum. Behav. Neurosci. 119:526–537. Coyle, J.T., Price, D.L., and DeLong, M.R. (1983) Alzheimer’s disease: a disorder of cortical cholinergic innervation. Science 219: 1184–1190. Crespo-Facorro, B., Paradiso, S., Andreasen, N.C., O’Leary, D.S., Watkins, G.L., Boles Ponto, L.L., and Hichwa, R.D. (1999) Recalling word lists reveals cognitive dysmetria in schizophrenia: a positron emission tomography study. Am. J. Psychiatry 156:386–392. Desimone, R. (1992) The physiology of memory: recordings of things past. Science 258:245–246. Dunnett, S.B., Whishaw, I.Q., Jones, G.H., and Bunch, S.T. (1987) Behavioral, biochemical and histochemical effects of different neurotoxic amino acids injected into nucleus basalis magnocellularis of rats. Neuroscience 20:653–669. Dusoir, H., Kapur, N., Byrnes, D.P., McKinstry, S., and Hoare, R.D. (1990) The role of diencephalic pathology in human memory disorder. Brain 113:1695–1706. Eichenbaum, H., Otto, T., and Cohen, N.J. (1992) Review: the hippocampus—what does it do? Behav. Neural Biol. 57:2–36. Eichenbaum, H., Otto, T., and Cohen, N.J. (1994) Two functional components of the hippocampal memory system. Behav. Brain Sci. 17:449–518. Eschenko, O., and Mizumori, S.J.Y. (2007) Memory influences on hippocampal and striatal neural codes: effects of a shift between task rules. Neurobiol. Learn. Memory 87:495–509. Everitt B.J., and Robbins T.W. (1997) Central cholinergic systems and cognition. Annu. Rev. Psychol. 48:649–684. Fuster, J. M. (1997) The Prefrontal Cortex: Anatomy, Physiology, and Neuropsychology of the Frontal Lobe, 3rd ed. Philadelphia: Lippincott–Raven. Gilboa, A., Winocur, G., Rosenbaum, R.S., Poreh, A., Gao, F.Q., Black, S.E., Westmacott, R., and Moscovitch, M. (2006) Hippocampal contributions to recollection in retrograde and anterograde amnesia. Hippocampus 16:966–980. Glickstein, M., and Yeo, C. (1990) The cerebellum and motor learning. J. Cogn. Neurosci. 2:69–80. Gothard, K.M., Battaglia, F.P., Erickson, C.A., Spitler, K.M., and Amaral, D.G. (2007) Neural responses to facial expression and face identity in the monkey amygdala. J. Neurophysiol. 97:1671– 1683. Graff-Radford, N.R., Tranel, D., Van Hoesen, G.W., and Brandt, J. (1990) Diencephalic amnesia. Brain 113:1–25. Greene, A.J., Gross, W.L., Elsinger, C.L., and Rao, S.M. (2006) An fMRI analysis of the human hippocampus: inference, context, and task awareness J. Cogn. Neurosci. 18:1156–1173. Insausti, R., Amaral, D.G., and Cowan, W.M. (1987) The entorhinal cortex of the monkey: II. cortical afferents. J. Comp. Neurol. 264:356–395. Kesner, R.P., Bolland, B.L., and Dakis, M. (1993) Memory for spatial locations, motor responses, and objects: triple dissociation among the hippocampus, caudate nucleus, and extrastriate visual cortex. Exp. Brain Res. 93:462–470. Kesner, R.P., and Williams, J.M. (1995) Memory for magnitude of reinforcement: dissociation between the amygdala and hippocampus. Neurobiol. Learn. Mem. 64:237–244.

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Knowlton, B.J., Mangels, J.A., and Squire, L.R. (1996) A neostriatal habit learning system in humans. Science 273:1399–1402. Krupa, D.J., Thompson, J.K., and Thompson, R.F. (1993) Localization of a memory trace in the mammalian brain. Science 260: 989–991. LeDoux, J.E. (1993) Emotional memory systems in the brain. Behav. Brain Res. 58:69–79. Lee, K.H., and Thompson, R.F. (2006) Multiple memory mechanisms in the cerebellum? Neuron 51:680–682. Leonard, B.W., Amaral, D.G., Squire, L.R., and Zola-Morgan, S. (1995) Transient memory impairment in monkeys with bilateral lesions of the entorhinal cortex. J. Neurosci. 15:5637–5659. Leube, D.T., Erb, M., Grodd, W., Bartels, M., and Kircher, T.T. (2001) Differential activation in parahippocampal and prefrontal cortex during word and face encoding tasks. Neuroreport 12: 2773–2777. Maguire, E.A., Vargha-Khadem, F., and Mishkin M. (2001) The effects of bilateral hippocampal damage on fMRI regional activations and interactions during memory retrieval. Brain 124:1156–1170. Mair, R.G., Knoth, R.L., Rabehenuk, S.A., and Langlais, P.J. (1991) Impairment of olfactory, auditory, and spatial serial reversal learning in rats recovered from pyrithiamine induced thiamine deficiency. Behav. Neurosci. 105:360–374. Malamut, B.L., Graff-Radford, N., Chawluk, J., Grossman, R.I., and Guy, R.C. (1992) Memory in a case of bilateral thalamic infarction. Neurology 42:163–169. McDonald, M.P., Wenk, G.L., and Crawley, J.N. (1997) Analysis of galanin and galanin antagonist, M40, on delayed non-matching to position performance in rats lesioned with the cholinergic immunotoxin 192 IgG-saporin. Behav. Neurosci. 111:552–563. McDonald, R.J., and White, N.M. (1993) A triple dissociation of memory systems: hippocampus, amygdala, and dorsal striatum. Behav. Neurosci. 107:3–22. Menon, V., Anagnoson, R.T., Glover, G.H., and Pfefferbaum, A. (2000) Basal ganglia involvement in memory-guided movement sequencing. Neuroreport 11:3641–3645. Milham, M.P., Erickson, K.I., Banich, M.T., Kramer, A.F., Webb, A., Wszalek, T., and Cohen, N.J. (2002) Attentional control in the aging brain: insights from an fMRI study of the Stroop task. Brain Cogn. 49:277–296. Mishkin, M., and Appenzeller, T. (1987) The anatomy of memory. Sci. Am. 256:80–89. Mishkin, M., and Murray, E.A. (1994) Stimulus recognition. Curr. Opin. Neurobiol. 4:200–206. Muir, J.L., Dunnett, S.B., Robbins, T.W., and Everitt, B.J. (1992) Attentional functions of the forebrain cholinergic systems: effects of intraventricular hemicholinium, physostigmine, basal forebrain lesions and intracortical grafts on a multiple-choice serial reaction time task. Exp. Brain Res. 89:611–622. Mumby, D.G., and Pinel, J.P.J. (1994) Rhinal cortex lesions and object recognition in rats. Behav. Neurosci. 108:11–18. Murray, E.A. (1996) What have ablation studies told us about the neural substrates of stimulus memory? Semin. Neurosci. 8:13–22. Nadel, L. (1996) The hippocampus: selective functions in memory. In: Ono, T., McNaughton, B.L., Molotchnikoff, S., Rolls, E.T., and Nishijo, H., eds. Perception, Memory, Emotion: Frontiers in Neuroscience. Oxford, UK: Elsevier, pp. 305–317. Nadel, L., Samsonovich, A., Ryan, L., and Moscovitch, M. (2000) Multiple trace theory of human memory: Computational, neuroimaging, and neuropsychological results. Hippocampus 10:352–368. Narayanan, N.S., and Laubach, M. (2006) Top-down control of motor cortex ensembles by dorsomedial prefrontal cortex. Neuron 52:921–931. Nishijo, H., Ono, T., and Nishino, H. (1988) Single neuron responses in amygdala of alert monkey during complex sensory stimulation with affective significance. J. Neurosci. 8:3570–3583.

926

DEMENTIA

O’Keefe, J., and Nadel, L. (1978) The Hippocampus as a Cognitive Map. Oxford, UK: Clarendon Press. Olton, D.S., and Wenk, G.L. (1987) Dementia: Animal models of the cognitive impairments produced by degeneration of the basal forebrain cholinergic system. In: Meltzer, H.Y., ed. Psychopharmacology: The Third Generation of Progress. New York: Raven Press, pp. 941–953. Olton, D.S., Wenk, G.L., Church, R.M., and Meck, W.H. (1988) Attention and the frontal cortical cortex as examined by simultaneous temporal processing. Neuropsychology 26:307–318. Pardo, J.V., Lee, J.T., Sheikh, S.A., Surerus-Johnson, C., Shah, H., et al. (2007) Where the brain grows old: Decline in anterior cingulate and medial prefrontal function with normal aging. Neuroimage 35:1231–1237. Posner, M.I., and Rothbart, M.K. (1998) Attention, self-regulation and consciousness. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 353: 1915–1927. Ragozzino, M.E., Ragozzino, K.E., Mizumori, S.J.Y., and Kesner, R.P. (2002) Role of the dorsomedial striatum in behavioral flexibility for response and visual cue discrimination learning. Behav. Neurosci. 116:105–115. Rauch, S. L., Whalen, P. J., Curran, T., McInerney, S., Heckers, S., and Savage, C. R. (1998) Thalamic deactivation during early implicit sequence learning: a functional MRI study. Neuroreport 9:865–870. Richardson, R.T., and DeLong, M.R. (1991) Functional implications of tonic and phasic activity changes in nucleus basalis neurons. In: Richardson, R.T., ed. Activation to Acquisition: Functional Aspects of the Basal Forebrain Cholinergic System. Boston: Birkhauser, pp. 135–166. Robbins, T.W., Everitt, B.J., Marston, H.M., Wilkinson, J., Jones, G.H., and Page, K.J. (1989) Comparative effects of ibotenic acidand quisqualic acid-induced lesions of the substantia innominata on attentional function in the rat: further implications for the role of the cholinergic neurons in the nucleus basalis in cognitive processes. Behav. Brain Res. 35:221–224. Roland, P.E., and Gulyas, B. (1994) Visual imagery and visual representation. Trends Neurosci. 17:281–297. Rolls, E.T. (2000) Memory systems in the brain. Annu. Rev. Psychol. 51:599–630. Rolls, E.T., Critchley, H.D., Browning, A.S., Hernadi, A., and Lenard, L. (1999) Responses to the sensory properties of fat of neurons in the primate orbitofrontal cortex. J. Neurosci. 19: 1532–1540. Rolls, E.T., Thorpe, S.J., and Maddison, S.P. (1983) Responses of striatal neurons in the behaving monkey. 1. Head of the caudate nucleus. Behav. Brain Res. 7:179–210. Sarter, M., Hasselmo, M.E., Bruno, J.P. and Givens, B. (2005) Unraveling the attentional functions of cortical cholinergic inputs: interactions between signal-driven and cognitive modulation of signal detection. Brain Res. Rev. 48:98–111. Schacter, D.L., and Tulving, E. (1994) Memory Systems. Cambridge, MA: MIT Press. Smith, D.M., and Mizumori, S.J.Y. (2006) Hippocampal place cells, context and episodic memory. Hippocampus 16:716–729.

Squire, L.R. (1992) Declarative and nondeclarative memory: multiple brain systems supporting learning and memory. J. Cogn. Neurosci. 4:232–243. Squire, L.R., Amaral, D.G., Zola-Morgan, S., Kritchevsky, M., and Press, G. (1989) Description of brain injury in the amnesic patient N.A. based on magnetic resonance imaging. Exp. Neurol. 105:23–35. Squire, L.R., and Bayey, P.J. (2007) The neuroscience of remote memory. Curr. Opin. Neurobiol. 17:185–196. Suzuki, W., Zola-Morgan, S., Squire, L.R., and Amaral, D.G. (1993) Lesions of the perirhinal and parahippocampal cortices in the monkey produce long-lasting memory impairment in the visual and tactual modalities. J. Neurosci. 13:2430–2451. Sziklas, V., and Petrides, M. (2000) Selectivity of the spatial learning deficit after lesions of the mammillary region in rats. Hippocampus 10:325–328. Tulving, E., and Schacter, D.L. (1990) Priming and human memory systems. Science 247:301–306. Victor, M., Adams, R.D., and Collins, G.H. (1989) The WernickeKorsakoff Syndrome and Related Neurological Disorders Due to Alcoholism and Malnutrition, 2nd ed. Philadelphia: F.A. Davis. Weible, A.P., Weiss, C., and Disterhoft, J.F. (2003) Activity profiles of single neurons in caudal anterior cingulate cortex during trace eyeblink conditioning in the rabbit. J. Neurophysiol. 90:599–612. Wenk, G.L. (1993) A primate model of Alzheimer’s disease. Behav. Brain Res. 57:117–122. Wenk, G.L. (1997) The nucleus basalis magnocellularis cholinergic system: 100 years of progress. Neurobiol. Learn. Mem. 67:85–95. Wenk, G.L., and Olton, D.S. (1987) Basal forebrain cholinergic neurons and Alzheimer’s disease. In: Coyle, J.T., ed. Animal Models of Dementia: A Synaptic Neurochemical Perspective. New York: Alan R. Liss, pp. 81–101. Wilson, F.A.W., and Rolls, E.T. (1990) Neuronal responses related to the novelty and familiarity of visual stimuli in the substantia innominata, diagonal band of Broca and periventricular region of the primate basal forebrain. Exp. Brain Res. 80:104–120. Winocur, G., Oxbury, S., Roberts, R., Agnetti, V., and Davis, D. (1984) Amnesia in a patient with bilateral lesions to the thalamus. Neuropsychology 22:123–143. Zola-Morgan, S., and Squire, L.R. (1993) Neuroanatomy of memory. Annu. Rev. Neurosci. 16:547–563. Zola-Morgan, S., Squire, L.R., and Amaral, D.G. (1989a) Lesions of the amygdala that spare adjacent cortical regions do not impair memory or exacerbate the impairment following lesions of the hippocampal formation. J. Neurosci. 9:1922–1936. Zola-Morgan, S., Squire, L.R., Amaral, D.G., and Suzuki, W. (1989b) Lesions of perirhinal and parahippocampal cortex that spare the amygdala and the hippocampal formation produce severe memory impairment. J. Neurosci. 9:4355–4370. Zola-Morgan, S., Squire, L.R., and Ramus, S.J. (1994) Severity of memory impairment in monkeys as a function of locus and extent of damage within the medial temporal lobe memory system. Hippocampus 4:483–495.

56 Neurochemical Systems Involved in Learning and Memory JOANNE BERGER-SWEENEY, LAURA R. SCHAEVITZ,

A N D

KARYN M. FRICK

During the past decades, considerable experimental evidence has linked specific neurotransmitter systems to learning and memory processes. Although acetylcholine (ACh) and glutamate have been most extensively studied in relation to memory, considerable evidence also links γ -aminobutyric acid (GABA), dopamine (DA), norepinephrine (NE), and serotonin (5-HT) to memory. Recently, it has become clear that studying the individual contribution of classical neurotransmitters to memory processes is not a feasible approach to studying the neurochemistry of memory because of numerous interactions among transmitters and of modulation by neuroactive peptides, steroid hormones, and trophic factors. The insights gained from studying neurotransmitters related to learning and memory are particularly relevant to the study of dementia. Dementia is characterized by a progressive, irreversible deterioration of higher cognitive functions, including learning and memory (Coyle et al., 1984). Failure of neurotransmission, particularly in regions of the brain such as the hippocampus and neocortex, is likely to be a fundamental defect responsible for cognitive impairments in dementia. Additionally, it has become increasingly clear that cognitive impairments, including alterations in learning and memory, are prominent features of numerous neurological and psychiatric disorders, such as Parkinson’s and Huntington’s diseases and schizophrenia. Pharmacological treatments that improve motor deficits in Parkinson’s and Huntington’s and positive psychiatric symptoms in schizophrenia still leave some higher cognitive functions impaired, such as learning and memory. Understanding the neurochemistry of learning and memory, therefore, is a first step toward relating the symptoms of dementia to underlying biochemical processes.

CONSIDERABLE EVIDENCE SUGGESTS THAT CHOLINERGIC NEURONS PLAY A CRITICAL ROLE IN ACQUISITION AND ATTENTIONAL PROCESSES Pharmacological studies in numerous species, using a variety of experimental paradigms, have linked ACh to learning and memory processes. In general, cholinergic agonists (for example, physostigmine) improve memory, whereas cholinergic antagonists (for example, scopolamine) impair memory (Bartus et al., 1985) (Table 56.1). Centrally-acting cholinergic agonists improve memory; however, peripherally administered agonists, which do not cross into the central nervous system (CNS), do not improve memory, suggesting that the effects of cholinergic compounds on memory are likely mediated through central mechanisms. Moreover, the dose of a given drug administered to an animal is critical in determining the magnitude and direction of the mnemonic effect; the same compound can either improve or impair memory, depending on the dose administered. Muscarinic and nicotinic receptors are thought to mediate cholinergic effects on learning and memory (Jones et al., 1999; Dani and Bertrand 2007). Classic lesion studies have identified populations of cholinergic neurons and projections that are critical for learning and memory. These neurons are located in the basal forebrain and project to the hippocampus and neocortex. The basal forebrain region includes the medial septal area (MSA) and the vertical limb of the diagonal band of Broca (dbB), which project primarily to the hippocampus, and the horizontal limb of the dbB and nucleus basalis magnocellularis (nBM), which project to the neocortex. Lesions of the MSA and nBM in rodents impair performance on a variety of mnemonic tasks, including spatial reference and working memory

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TABLE

56.1 Life Cycles and Pharmacological Characteristics of Six Classical Neurotransmitters

Neurotransmitter

Synthetic Pathway

Degradative Pathway

Acetylcholine (ACh)

Choline and acetyl CoA → ACh ↑ ChAT

ACh → Choline and acetic acid ↑ AChE

Glutamate

Glutamine → Glutamate ↑ Glutaminase Aspartate → Glutamate

Glutamate → Glutamine Glutamate → GABA ↑ GAD

Glucose → Glutamate

Primary CNS Receptor Subtypes

Common Agonists

Common Antagonists

Muscarinic: M1, M2, M3, M4, M5

Muscarine

Scopolamine

Oxotremorine

Atropine

Nicotinic: a(2–10) β(2–4)

Carbachol Physostigmine

Pirenzepine mecamylamine

Nicotine

Bungarotoxin

Ionotrophic: NMDA (1, 2A–D) AMPA (GluR1–3) Kainate

Kainic, ibotenic, and quisqualic acids

D-AP5

NMDA

Metabotropic: mGluR1–8

MK-801

AMPA

PCP

DHPG

AIDA

Ketamine

L-AP4 GABA

Dopamine

Glutamate → GABA ↑ GAD

L-tyrosine

L-DOPA

Norepinephrine

→ L-DOPA ↑ tyrosine hydroxylase

→ DA ↑ DOPA decarboxlase

Dopamine → NE ↑ Dopamine β -hydroxylase

GABA → succinic semialdehyde ↑ GABA transaminase

GABA–A: a(1–6), β(1–3), γ (1–3), δ, ε, θ, ρ(1–3)

Muscimol

Bicuculline

Baclofen

Picrotoxin

GABA–B (1–2)

Benzodiazepines

Phaclofen

Barbiturates

Flumazenil

Reuptake

D1, D2, D3, D4, D5

Amphetamine

Reserpine

Cocaine

Neuroleptics

Dopamine → Norepinephrine ↑ DA β -hydroxylase

SKF38393

SCH23390

Dopamine → DOPAC ↑ MAO

Quinpirole

SCH39166

Dopamine → HVA ↑ COMT and MAO

Apomorphine

Raclopride

Deprenyl

Haloperidol

Reuptake

a1(A,B,D), a2(A–C)

Amphetamine

Reserpine

NE → Epinephrine ↑ PNMT

β1, β2, β3

Epinephrine

Phentolamine

Tricyclic antidepressants

Propranolol

Clonidine

Yohimbine

NE → MHPG and VMA ↑ COMT and MAO Serotonin

Tryptophan → 5-HTP ↑ tryptophan hydroxylase 5-HTP → 5-HT ↑ amino acid decarboxylase

Guanfacine

Reuptake

5-HT1(A–F)

LSD

Reserpine

5-HT → 5-HIAA ↑ MAO and aldehyde dehydrogenase

5-HT2(A–C)

Anxiolytics

Clozapine

5-HT3, 5-HT4, 5-HT5A, 5-HT5B

Sumatriptan

Clomipramine

5-HT6, 5-HT7

Imipramine

Antidepressants

Fluoxetine (Prozac)

Methiothepin

5-HT → Melatonin (pineal)

Source: Largely from Cooper et al., 1996; Siegel et al., 1999; Nestler et al., 2001. Note: ↑ denotes the action of an enzyme on the substrate to the upper left of the arrow. For further information on the above or on the anatomical projections of the above listed systems, see Nestler et al. (2001). 5-HT: serotonin; 5-HIAA: 5-hydroxyindoleacetic acid; 5-HTP: 5-hydroxytryptophan; ACh: acetylcholine; AChE: acetylcholinesterase; ACPD: aminocyclopentyl dicarboxylic acid; AIDA: 1-aminoindan-1,5 dicarboxylic acid; AMPA: α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid; ChAT: choline acetyltransferase; CNS: central nervous system; CoA: coenzyme A; COMT: catechol-O-methyltransferase; D-AP5: D-2-amino-5 phosphonopentanoate; DA: dopamine; DHPG: 3,5-dihydroxyphenylglycine; DOPAC: dihydroxyphenylacetic acid; GABA: γ -aminobutyric acid; GAD: glutamic acid decarboxylase; HVA: homovanillic acid; L-AP4: L-2-amino-4-phosphonopropionic acid; LSD: lysergic acid diethylamide; MAO: monoamine oxidase; MHPG: 3-methoxy-4-hydroxyphenlglycol; NE: norepinephrine; NMDA: N-methyl-D-aspartate; PCP: phencyclidine; PNMT: phenylethanolamine N-methyltransferase; VMA: vanillylmandelic acid.

56: NEUROCHEMICAL SYSTEMS INVOLVED IN LEARNING AND MEMORY

tasks such as the Morris water maze and T-maze alternation. Reference memory and working memory, a dichotomy used extensively in the rodent literature, refer to information to be remembered across trials (reference memory) or for a single trial (working memory) (Olton et al., 1979). The critical flaw in the early lesion studies was the use of nonspecific lesion techniques. Many studies used electrolytic lesions (which destroy neurons as well as fibers of passage) or excitotoxins such as ibotenic acid (which spare fibers of passage but kill cholinergic and noncholinergic neurons). More specific lesion techniques, such as the immunotoxin 192 IgG saporin, produce selective cholinergic lesions of the basal forebrain. In general, the deficits seen on spatial memory tasks following 192 IgG saporin lesions are considerably less robust than those observed after nonspecific toxin lesions (Baxter and Chiba, 1999). This finding has led many investigators to question the link between the cholinergic system and memory. Recent studies document impairments following either developmental or adult 192 IgG saporin lesions in tasks designed to measure attention, suggesting that basal forebrain cholinergic neurons may be involved in attentional processes. Furthermore, basal forebrain cholinergic neurons appear critical in reorganizing cortical representations of behaviorally important sensory stimuli and may regulate the cortical plasticity necessary for laying down a memory trace (Rasmusson, 2000). Thus, ACh may contribute more to the acquisition and processing of sensory information than to the retention of this information. It is noteworthy that acetylcholinerase inhibitors, which prevent the enzymatic breakdown of acetylcholine, are the most widely prescribed pharmacological treatments for Alzheimer’s disease (Musial et al., 2007). These drugs improve, albeit temporarily and only moderately, cognitive impairments in a significant number of patients with Alzheimer’s disease. GLUTAMATE IS INVOLVED IN LONG-TERM POTENTIATION, A PUTATIVE MECHANISM OF LEARNING AND MEMORY The excitatory amino acid glutamate is the most abundant amino acid in the CNS. However, glutamate was not identified as a neurotransmitter until the early 1980s because of its multiple roles in the CNS, including involvement in fatty acid synthesis, ammonia regulation, and as a precursor for GABA. Glutamate receptors are widespread throughout the CNS but are particularly concentrated in the hippocampus and neocortex. The most obvious connection between glutamate and memory is glutamate’s involvement in long-term potentiation (LTP), an artificially induced form of lasting neuronal plasticity originally observed in the hippocampus

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(Bliss and Lømo, 1973). Long-term potentiation is a putative mechanism of associative learning because its three main characteristics—cooperativity, associativity, and input specificity—closely resemble D.O. Hebb’s postulation that a synapse linking two cells will be strengthened if the two cells are active simultaneously (Hebb, 1949). N-methyl-D-aspartate (NMDA)-dependent LTP involves induction (in which the initial increase in synaptic potentiation occurs) and maintenance (in which the increase persists for a prolonged period). To induce LTP, a postsynaptic membrane must first be depolarized by the binding of glutamate to postsynaptic αamino-3-hydroxy-5 methylisoxazole-4-proprionic acid (AMPA) receptors. This depolarization releases a Mg2+ blockade of postsynaptic NMDA channels that occurs normally at the resting potential. Glycine and serine act as coagonists at NMDA receptors. Removal of the Mg2+ blockade allows an influx of Ca2+ into the postsynaptic terminal, which activates a cascade of Ca2+-dependent kinases that leads eventually to potentiation of the postsynaptic neuron. To maintain this potentiation, increased presynaptic glutamate release is required, which involves an unidentified retrograde messenger (MacDonald et al., 2006). In one of the first links between NMDA receptors and memory it was shown that D-AP5, an NMDA channel blocker, impairs spatial reference memory in rats tested in the Morris water maze (Morris, 1986). Doses sufficient to impair memory also block LTP, suggesting that intact LTP is required for performance of the task. Recent attention has focused on drugs that facilitate AMPA receptor-mediated transmission in the hippocampus (Bannerman et al., 2006). Drugs that facilitate the induction of LTP in vivo improve the retention of several types of memory in rats as well as in aged humans. Together, these studies suggest that pharmacological blockade of LTP results in memory impairment, whereas facilitation of LTP results in memory enhancement. Knockout studies in mice have offered further insight into the function of the Ca2+ ionophore in dendrites, related AMPA and NMDA receptors, and control of intraneuronal kinases important in the initiation of LTP. Mice with a deletion of a portion of the NMDA gene restricted to the CA1 region of the hippocampus exhibit impaired LTP and impaired spatial reference memory in the Morris water maze. Kinases important for LTP initiation, such as α-calcium calmodulin-dependent kinase II (CaMKII), may be under activity-dependent local translational control (L. Wu et al., 1998). Mutations of CaMKII or the fyn tyrosine kinase impair LTP initiation and spatial water-maze learning. Also, the maintenance of LTP putatively involves kinases that are different from those involved in LTP initiation. Cyclic adenosine monophosphate (cAMP)-dependent protein kinase A (PKA) and mitogen-activated protein kinases (MAPKs) are involved in LTP maintenance and can

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activate transcriptional factors, such as cAMP response element binding (CREB) proteins that activate immediate- and late-response genes. These genes then putatively regulate structural and functional alterations in the neuron that can serve as a substrate for long-term storage of information and may serve as a physical substrate for neuronal plasticity. However, spatial learning can occur even if LTP is completely blocked pharmacologically, a result that highlights the fact that the connection between LTP and memory has yet to be firmly established. Nevertheless, much recent research has been devoted to developing glutamatergic-based drugs to enhance cognition in normal aging and Alzheimer’s disease (Knopman, 2006). GABAERGIC INHIBITION IN THE SEPTOHIPPOCAMPAL SYSTEM CAN PROFOUNDLY INFLUENCE MEMORY GABA is the primary inhibitory neurotransmitter in the CNS. Its distribution is ubiquitous in the brain, and cell bodies are prominent in several regions involved in learning and memory including the neocortex, nBM, medial septum, hippocampus, striatum, and amygdala. In the medial septum, GABAergic neurons interact extensively with cholinergic neurons, and both of these cell populations send projections to and receive them from the hippocampus. Because the GABAA receptor complex has multiple binding sites, there are several ways to modulate the GABAergic system pharmacologically. This chloride channel complex includes five major binding sites: GABA (opens the channel), barbiturates (decrease the frequency of channel opening and increase opening duration), benzodiazepines (BDZs; increase the frequency of channel opening), picrotoxin (blocks the channel), and steroids (Sieghart, 2006). The GABAB receptor is a simple ion channel (K+ or Ca2+) and is not modulated by the aforementioned compounds. Breen and McGaugh (1961) first demonstrated GABAergic modulation of memory by showing that posttraining peripheral administration of picrotoxin enhanced maze learning in rats. Posttraining peripheral injection of the GABAA antagonist bicuculline also produces a dose-dependent improvement of passive avoidance retention. Conversely, peripheral injection of the GABAA agonist muscimol impairs passive avoidance retention. The effects of direct intraseptal modulation of the GABAA receptor are consistent with those of peripheral injections (Walsh and Stackman, 1992). In general, pre- and posttraining facilitation of GABAA activation with muscimol or the BDZ agonist chlordiazepoxide impairs memory on a wide variety of tasks including T-maze alternation, the radial arm maze, and the Morris water maze. These infusions also disrupt cholinergic function in the septum and hippocampus. This detrimental effect on memory is particularly interesting in light of the amnesic side effects observed in humans

treated with BDZs to relieve anxiety. Conversely, antagonizing the BDZ site can reverse the amnesic effects of several BDZs in humans and rats. Several neuroactive steroids also modulate the GABAA receptor and affect memory via GABAergic mechanisms. Facilitation of GABAB activity with the agonist baclofen impairs spatial memory and decreases hippocampal cholinergic function, suggesting similar mnemonic and neurochemical consequences of modulating the two GABA receptors. Interestingly, recent work suggests that the cognitive effects of intraseptal cholinergic agonist treatment are not due to increased ACh release but to increased septohippocampal GABA signaling (M. Wu et al., 2000). Such an increase would reduce GABAergic neurotransmission in the hippocampus, thereby disinhibiting hippocampal pyramidal neurons and allowing for increased excitatory plasticity. The amygdala is also important for the retention of some aversively motivated tasks, and GABAergic mechanisms in this structure may modulate aversive learning. Similar to peripheral injections, intra-amygdala infusion of bicuculline or picrotoxin enhances passive avoidance retention, whereas infusion of muscimol or baclofen impairs retention. It is possible that the amygdala and septohippocampal GABAergic systems interact to affect anxiety and fear and their relationship to memory formation and storage. DOPAMINERGIC FUNCTION IN THE PREFRONTAL CORTEX IS CRITICAL FOR WORKING MEMORY Most catecholaminergic neurons originate in discrete nuclei in the brain stem that project widely to the neocortex, limbic system, and striatum. In addition to the striatum, dopaminergic neurons in the ventral tegmental area and substantia nigra project to the prefrontal cortex, anterior cingulate cortex, perirhinal and entorhinal cortices, basal forebrain, hippocampus, and amygdala. Many studies have examined the effects of peripheral injection of dopaminergic compounds on learning and memory. However, the results are inconsistent, depending on the drug and the task used, as well as on whether the injection is given pre- or posttraining. Peripheral treatments generally disrupt non-mnemonic parameters such as motor function (for example, increased latency to respond) and appetitive behavior, making it difficult to dissociate the effects of dopaminergic compounds on memory from performance effects. Injections of dopaminergic compounds directly into the CNS suggest that DA modulates memory in part through an interaction with ACh in the septohippocampal system (Decker and McGaugh, 1991). Intraseptal injection of the DA antagonist haloperidol increases hippocampal ACh turnover; similar increases in ACh turnover can be produced by intraseptal or ventral tegmental injections of the DA toxin 6-hydroxydopamine

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(6-OHDA). These results suggest that the dopaminergic input to the septum inhibits septohippocampal cholinergic activity. Thus, decreasing septal dopaminergic function may improve memory. Indeed, septal 6-OHDA lesions (with desmethylimipramine [DMI] to protect noradrenergic neurons) enhance spatial memory in several tasks, and this improvement is correlated with increased septohippocampal cholinergic activity. Even more compelling is the role of dopaminergic projections to the prefrontal cortex (PFC) in working memory. Monkeys with bilateral lesions of the PFC are severely impaired on spatial working memory tasks, whereas they are unimpaired on object recognition tasks. Humans with PFC damage show similar memory deficits. Specific dopaminergic lesions of the dorsolateral PFC made by injections of 6-OHDA and DMI result in mnemonic deficits in monkeys similar to those in monkeys with cortical ablations (Brozoski et al., 1979), suggesting a specific role of prefrontal DA in working memory. Peripheral administration of the DA precursor L-DOPA or the DA agonist apomorphine improves the mnemonic performance of the monkeys whose DA is depleted. Prefrontal cortex injections of D1 receptor antagonists in monkeys impair memory in an oculomotor delayedresponse task without affecting sensory or motor functions (Sawaguchi and Goldman-Rakic, 1991), further implicating the dopaminergic system in working memory function. Recent pharmacological, cellular, and electrophysiological studies in rodents provide evidence that DA can not only mediate plasticity and improve working memory, but can also enhance spatial, reversal, and incentive learning (El-Ghundi et al., 2007). Some evidence implicates reduced DA function in the cognitive impairments common in several neurodegenerative diseases. Dopaminergic drugs may improve aspects of working memory in individuals with these diseases, as well as in normal individuals (Chamberlain et al., 2006). Patients with Parkinson’s disease and schizophrenia commonly exhibit working memory deficits, which is interesting given that reduced DA function in the PFC has been observed in both disorders. Increasing DA levels in patients with schizophrenia using amphetamine or in patients with Parkinson’s disease using L-DOPA improves their performance on tests of working memory. The PFC may also be particularly vulnerable to deterioration with increasing age. Aged rats and aged monkeys exhibit a significant loss of DA from the PFC, a finding that is correlated with spatial working memory deficits. NOREPINEPHRINE AFFECTS MEMORY THROUGH AROUSAL STATES AND MODULATION OF ACETYLCHOLINE AND DOPAMINE The widespread noradrenergic projections from locus coeruleus (LC) to the neocortex have been implicated

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in general arousal and attentional states. Noradrenergic fibers originating in the brain stem are divided into two pathways: dorsal and ventral. The ventrally located cell bodies innervate the brain stem and hypothalamus. Dorsally located cell bodies are contained in the LC and innervate the spinal cord, cerebellum, amygdala, septum, hippocampus, and the entire cerebral cortex. Reciprocal connections also project from LC to the PFC. Norepinephrine (NE) has the highest affinity for α2 andrenergic receptors in the neocortex, which are coupled to G-proteins that inhibit cAMP pathways. Several studies have failed to observe a direct effect of noradrenergic modulation on memory. For instance, in rodents, NE depletion has little effect on a variety of memory tasks including the radial arm maze and passive avoidance tasks. Other studies in rats and monkeys suggest that α2 agonists can improve working memory in aged animals and catecholamine-depleted animals. These improvements appear to be restricted to cognitive functions related to the PFC, such as working memory, given that these agonists do not affect spatial reference memory or recognition memory (Ramos and Arnste, 2007). Although most work relating NE to memory focuses on PFC, a recent study suggests that noradrenergic projections to hippocampus may influence LTP (Schimanski et al., 2007). In addition, because most types of memory storage involve arousal and focused attention, the LC’s involvement in these processes points towards NE as a modulator of memory function. The LC can modify septohippocampal cholinergic function and, therefore, NE can modulate memory function indirectly (Decker and McGaugh, 1991). Intraseptal injection of NE increases hippocampal ACh turnover and alters the hippocampal theta rhythm. This relationship between NE and ACh appears to be reciprocal; muscarinic stimulation of the hippocampus inhibits NE synthesis and release, whereas cholinergic depletion increases NE synthesis and release. In addition, nicotine can increase the turnover of NE in the hippocampus and ACh can activate the LC. Behaviorally, neither an LC lesion nor administration of the cholinergic antagonist scopolamine affects retention of active avoidance training alone; however, when the two treatments are combined, they produce a severe deficit. Thus, NE and ACh appear to act synergistically to affect some types of memory. Recent evidence suggests that reductions in NE levels are correlated with deficits in hippocampal LTP. The LC’s projections to the PFC also may be indirectly involved in memory. In monkeys and humans, PFC lesions lead to increased distractibility and increased susceptibility to interference by irrelevant stimuli, effects that likely contribute to the observed working memory impairments. The PFCs of patients with attention-deficit/ hyperactivity disorder are smaller and less active than those of age-matched controls, and these patients exhibit working memory and attentional impairments, further

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supporting a role for the PFC in attention. The α2 agonist clonidine significantly ameliorates mnemonic and attentional deficits in young NE-depleted monkeys, suggesting that NE in the PFC may affect memory by reducing interference by distracting or irrelevant stimuli. Because DA is also involved in PFC-dependent tasks, it is likely that NE and DA interact in this area to affect working memory (Ramos and Arnste, 2007). SEROTONIN INFLUENCES MEMORY AND LONG-TERM POTENTIATION Almost all serotonergic cell bodies are located in the medial brain-stem region as discrete nuclei termed the dorsal and medial raphé nuclei. Projections from these cell bodies extend to virtually all areas of the CNS including the amygdala, thalamus, hypothalamus, olfactory bulb, striatum, basal forebrain, hippocampus, and all regions of the cortex. Its ubiquitous nature and multifaceted functions have made discrete cause-and-effect relationships concerning serontonin’s (5-HT’s) role in learning and memory difficult to determine (Meneses, 1999). However, characterization of new 5-HT receptor subtypes, as well as new chemical probes that can act with relative specificity toward these receptors, have assisted in this endeavor. Studies in knockout mice and antisense tools also have opened new areas of investigation. Depletion of 5-HT in certain brain regions, in particular the hippocampus, can impair memory (Buhot et al., 2000). Furthermore, depletion of tryptophan (the amino acid precursor to 5-HT) in the diet of otherwise healthy individuals is correlated with an acute and reversible loss of learning and memory functions. Conversely, 5-HT depletion in PFC in rats is associated with increased plasticity in pyramidal neurons, which in turn potentiates short-term memory. Of the many 5-HT receptors, 5-HT1A, 5-HT4, and 5HT5 receptors have been associated most consistently with learning and memory (e.g., Malleret et al., 1999). Pharmacological studies, as well as studies in receptor knockout mice, suggest that the 5-HT1A receptors play a role in passive avoidance retention. The 5-HT4 receptors modulate LTP and long-term depression (LTD). Pharmacological studies, as well as those using receptor antisense oligonucleotides, point to a critical role of 5-HT6 receptors in enhancing spatial memory in the Morris water maze. 5-HT7 may also play a role in learning and memory, but this role remains unclear, as 5-HT7 knockout mice are impaired in contextual fear conditioning but not spatial reference memory in a Barnes maze (Roberts et al., 2004). Some of these changes may take place not via LTP/LTD mechanisms, but by synaptic plasticity and sensory input reorganization, as has been noted in the cholinergic system (Cassel and Jeltsch, 1995).

In addition, 5-HT may influence memory via interactions with the gaseous neurotransmitter nitric oxide (NO). eNOS knockout mice exhibit improved Morris water maze performance and decreased 5-HT turnover in hippocampus and neocortex, suggesting a link between NO and 5-HT. Some behavioral changes might be related to extraneuronal processes, such as blood flow, which NO and 5-HT regulate. Evidence for this 5HT/NO interaction is bolstered by experiments involving 5-HT1B receptor knockout mice that also show enhanced spatial memory similar to that seen in eNOS knockout mice. It remains to be seen whether this improvement is due specifically to enhanced spatial learning or is a by-product of eNOS alterations of other brain functions that contribute to performance of this task. VARIOUS NEUROACTIVE PEPTIDES CAN ALSO MODULATE MEMORY A growing number of peptides have been shown to modulate synaptic plasticity and learning and memory. Many peptides coexist with a variety of classical neurotransmitters and modulate their release in brain regions associated with learning and memory. Examples include ACh and galanin in the septum, GABA and somatostatin in the cortex and hippocampus, and NE and neurotensin in the LC. Several peptides modulate memory including opioids, galanin, oxytocin, vasopressin, neuropeptide Y, cholecystokinin, somatostatin, insulin, neurokinin, and substance P. Administration of opiate agonists impairs memory, whereas administration of opiate antagonists enhances memory (Decker and McGaugh, 1991). This appears to be true for peripheral administration as well as for intracranial injections. However, intracranial infusions reveal a dissociation between the septohippocampal and amygdalar systems, which are both innervated by opiate peptides. Appetitively motivated tasks testing working memory are affected by intraseptal opiate infusions but not by intra-amygdala infusions, whereas aversively motivated avoidance tasks testing reference memory are affected only by intra-amygdala infusions. In the septum, infusion of the opioid receptor agonist β-endorphin decreases hippocampal ACh turnover, and this effect is blocked by the opioid receptor antagonist naltrexone. This result may be due to activation of septal GABAergic interneurons, which inhibit cholinergic neurons that project to the hippocampus. In the amygdala, NE depletion blocks the facilatory effects of naloxone on a passive avoidance task, suggesting an interaction between NE and opioids. Moreover, the naloxone-induced improvements in avoidance and Y-maze discrimination tasks are blocked by injection of noradrenergic β-receptor antagonists injected directly into the amygdala, but not

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into the striatum or cortex, indicating that NE receptors in the amygdala interact with opiate peptides to affect these types of memory. The neuromodulatory peptide galanin (along with neuropeptide Y) modulates hippocampal function and plays a key role in memory. Galanin impairs a variety of learning and memory tasks including those testing spatial learning, retention, and consolidation (Givens et al., 1992; Wrenn and Crawley, 2001). The inhibitory effects may result from alterations in functional synapses and/or neurotransmitter release in the hippocampus. They may also be mediated through interactions with monoamines. Galanin is colocalized with 5-HT in the dorsal raphé, as well as with NE in the LC, and ACh in the septum. Hence, galanin may modulate the effects of the monoamines and influence cognitive processes via these interactions. The neurohypophyseal hormones oxytocin and vasopressin affect memory antagonistically. Vasopressin facilitates memory consolidation and retrieval in rats tested in a variety of avoidance tasks, whereas oxytocin impairs memory in these tasks. The septohippocampal system and raphé nuclei appear to be important for the memory-consolidating effects of these peptides, whereas the amygdala is involved in effects on retrieval (de Wied, 1984). In addition, basal forebrain cholinergic neurons are also innervated by substance P, which enhances retention of passive avoidance if injected into the septum or nBM. The potential importance of substance P to hippocampal-dependent learning and memory is suggested by the fact that knockout mice missing the substance P receptor neurokinin 3 exhibit cognitive deficits in passive avoidance as well as spatial water maze. NEUROTROPHIC FACTORS AFFECT LEARNING AND MEMORY VIA MODULATION OF THE CHOLINERGIC AND GLUTAMATERGIC SYSTEMS Learning and memory are processes that likely include chemical and morphological changes in neurons (Kandel, 2001). It is therefore not surprising that neurotrophic factors, which regulate synaptic modeling and influence neuronal survival, are implicated in learning and memory processes. The first neurotrophic factor was discovered in the peripheral nervous system in the early 1950s (Levi-Montalcini, 1987). This growth-promoting substance was termed nerve growth factor (NGF). Since then, other closely related neurotrophins have been discovered, including brain-derived neurotrophic factor (BDNF) and neurotrophins-3 and -4/5 (NT-3, NT-4/5). Three high-affinity receptors appear to be the principal receptors involved in signal transduction. These highaffinity receptors are all transmembrane tyrosine kinases (Trks): TrkA (binds NGF), TrkB (binds BDNF),

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and TrkC (binds NT-3). NT-4/5 binds to either TrkA or TrkB. All four neurotrophins can also bind a low-affinity receptor termed p75 or NGFR. The hippocampus and neocortex, the main targets of cholinergic innervation from the basal forebrain, contain the highest levels of NGF, BDNF, and NT-3 messenger ribonucleic acids (mRNA) in the mammalian brain. These four trophic factors are target derived and are retrogradely transported to cholinergic projection neuron cell bodies where they appear to interact with receptors on the neurons. Behavioral studies examining animals missing a single neurotrophin or its receptor, as well as animals in which a single neurotrophin has been reintroduced, indicate that all neurotrophic factors play important roles in learning and memory. Early studies indicated that NGF modulates learning and memory by promoting the survival of basal forebrain cholinergic neurons. Nerve growth factor infusion directly into the brain of rats with transections of the fimbria-fornix, a lesion that results in extensive degeneration of septohippocampal cholinergic neurons and severe spatial memory deficits, significantly reduces septohippocampal cholinergic deterioration and spatial memory deficits induced by the lesion. Similar effects have been demonstrated throughout the basal forebrain. More recent studies indicate that intracranial NGF infusions reduce deficits in memory tasks associated with the age-related loss of basal forebrain cholinergic neurons. The improvement to memory in aging animals has been mirrored in recent clinical trials in which patients with Alzheimer’s disease showed some cognitive improvement following treatment with NGF (Williams et al., 2006). Brain-derived neurotrophic factor, the most abundant neurotrophin in the brain, NT-3, and NT-4/5 all appear to affect learning and memory by modulating LTP (Yamada et al., 2002). Brain-derived neurotrophic factor and TrkB are localized to glutamatergic synapses and may affect synaptic consolidation through immediate early gene signalling cascades. Expression of BDNF and TrkB mRNA increase after spatial and contextual learning. Further, BDNF mRNA levels are up-regulated following exercise, and this increase is correlated with improved cognitive function in several species. Interestingly, heterozygous BDNF knockout mice exhibit impaired LTP and spatial learning, and both of these deficits can be rescued by BDNF. Similarly, a conditional knockout of NT-3 and a knockout of NT-4/5 exhibit impaired LTP, as well as deficits in several hippocampal and amygdala-dependent learning and memory tasks. Despite the tremendous potential of neurotrophins to improve cognitive function in normal patients and patients with dementia, technical problems with drug delivery continue to be a limiting factor in their clinical use (Arancio and Chao, 2007).

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STEROID RECEPTORS IN HIPPOCAMPUS AND NEOCORTEX LIKELY MEDIATE STEROID EFFECTS ON MEMORY THROUGH A VARIETY OF MECHANISMS Steroid hormones, such as estrogens, progestins, and androgens, profoundly affect the function of the hippocampus and neocortex. Receptors for all three of these hormones are found throughout both brain regions, and evidence exists to suggest that all three can modulate hippocampal and cortical function. For example, in female rodents, progesterone modulates hippocampal synaptogenesis, and acute, but not chronic, treatment with progesterone improves spatial and objectrecognition memory. Testosterone deprivation impairs spatial working memory in male rats, and testosterone replacement can reverse these deficits (Sandstrom, Kim, and Wasserman, 2006). However, the vast majority of research has focused on estrogens. Estradiol, the most potent form of estrogen, regulates hippocampal dendritic branching and synaptogenesis, enhances membrane excitability and LTP, promotes neurogenesis, and stimulates the activation of numerous intracellular signaling cascades (Woolley, 2007). Estrogens can bind to nuclear (ERα and ERβ) and nonnuclear receptors (identities unknown, possibly associated with the plasma membrane) to influence long- and short-term neural plasticity. Through receptor binding and interactions with modulators such as growth factors, estrogens promote gene transcription, thereby influencing neuronal structure and function. However, directly linking these alterations to memory modulation has proven to be a challenge. Estrogens released around the time of birth organize female and male hippocampi differently and lead to sex-dependent differences in spatial learning in adulthood. In adulthood, estrogens continue to influence spatial memory: for example, some studies in rodents show subtle variations in spatial memory across the estrous cycle. Other studies find that estradiol treatment improves various types of memory in young and aged female rodents. Estradiol may exert its effects on memory through a variety of mechanisms, including interactions with neurotransmitter systems. For example, estradiol can influence hippocampal excitability by altering cholinergic function in the basal forebrain (Gibbs & Gabor, 2003). Within the hippocampus, estradiol decreases BDNF expression and GABAergic neurotransmission in inhibitory interneurons, leading to disinhibition of pyramidal neurons and formation of new dendritic spines (Segal & Murphy, 2001). Although these alterations are likely the result of estradiol binding to nuclear estrogen receptors, the rapidity of some of estradiol’s effects on neural function suggest a critical role for nonnuclear receptors in modulating memory. Data indicating that estradiol is produced locally in the hippocampus present an intriguing new method for rapid estradiol action. For example, estradiol rapidly activates intracellular

signal transduction cascades such as the mitogen activated protein kinase (MAP kinase) cascade, and recent data indicate that an estradiol-induced increase in MAPK signaling is necessary for estradiol to improve hippocampal-dependent object memory. Further, this effect can be mediated exclusively by estradiol binding to the plasma membrane, suggesting that memory can be modulated by membrane-associated mechanisms separate from binding to traditional estrogen receptors. CONCLUSIONS It should be clear from this brief review that several neurochemical systems are intricately involved in learning and memory processes. Pharmacological studies have provided information about the mnemonic consequences of augmentation or reduction of specific systems, as well as about receptors and secondary and tertiary messenger systems involved in these effects. Lesion studies have provided detailed information about the anatomical distribution of these neurochemical systems and about the alterations in mnemonic processes that result from the absence of a particular transmitter or transmitters. Recent studies have highlighted interactions among transmitters and neuromodulators, making it clear that no neurochemical system influences memory in isolation. In the hippocampus, for example, ACh, glutamate, GABA, NE, 5-HT, peptides, NGF, and hormones all play a role in determining the nature of spatial memories that will be formed and subsequently retrieved. Future investigations will likely continue to focus on the elaborate interplay among transmitters and modulators in learning and memory processes and the specific plastic mechanisms that underlie these effects. Because disturbances of multiple transmitter systems may produce the complex cognitive dysfunction associated with dementia, understanding the intricate interactions among neurochemicals in the brain will be essential for designing effective treatments for dementia.

REFERENCES Arancio, O., and Chao, M.V. (2007) Neurotrophins, synaptic plasticity and dementia. Curr. Opin. Neurobio. 17:325–330. Bartus, R.T., Dean, R.L., Pontecorvo, M.J., and Flicker, C. (1985) The cholinergic hypothesis: a historical overview, current perspective, and future directions. Ann. N.Y. Acad. Sci. 444:332–358. Baxter, M.G., and Chiba, A.A. (1999) Cognitive functions of the basal forebrain. Curr. Opin. Neurobiol. 9:178–183. Bannerman, D.M., Rawlins, J.N., and Good, M.A. (2006) The drugs don’t work—or do they? Pharmacological and transgenic studies of the contribution of NMDA and GluR-A-containing AMPA receptors to hippocampal-dependent memory. Psychophamacology 188:552–566. Bliss, T.V.P., and Lømo, T. (1973) Long-lasting potentiation of synaptic transmission in the dentate area of the anaesthetized rabbit

56: NEUROCHEMICAL SYSTEMS INVOLVED IN LEARNING AND MEMORY following stimulation of the perforant path. J. Physiol. 232: 331–356. Breen, R.A., and McGaugh, J.L. (1961) Facilitation of maze learning with posttrial injections of picrotoxin. J. Comp. Physiol. Psychol. 54:495–501. Brozoski, T.J., Brown, R.M., Rosvold, H.E., and Goldman, P.S. (1979) Cognitive deficit caused by regional depletion of dopamine in prefrontal cortex of rhesus monkey. Science 205:929–932. Buhot, M.C., Martin, S., and Segu, L. (2000) Role of serotonin in memory impairment. Ann. Med. 32:210–221. Cassel, J.C., and Jeltsch, H. (1995) Serotonergic modulation of cholinergic function in the central nervous system: cognitive implications. Neuroscience 69:1–41. Chamberlain, S.R., Muller, U., Robbins, T.W., and Sahakian B.J. (2006) Neuropharmacological modulation of cogntition. Curr. Opin. Neurol. 19:607–612. Cooper, J.R., Bloom, F.E., and Roth, R.H. (1996) The Biochemical Basis of Neuropharmacology, 7th ed. New York: Oxford University Press. Coyle, J.T., Singer, H., McKinney, M., and Price, D. (1984) Neurotransmitter specific alterations in dementing disorders: insights from animal models. J. Psychiatr. Res. 18:501–512. Dani, J.A., and Bertrand, D. (2007) Nicotinic acetylcholine receptors and nicotinic cholinergic mechanisms of the central nervous system. Ann. Rev. Pharmacol. Toxicol. 47:699–729. Decker, M.W., and McGaugh, J.L. (1991) Role of interactions between the cholinergic system and other neuromodulatory systems in learning and memory. Synapse 7:151–168. de Wied, D. (1984) Neurohypophyseal hormone influences on learning and memory processes. In: Lynch, G., McGaugh, J.L., and Weinberger, N.M., eds. Neurobiology of Learning and Memory. New York: Guilford Press, pp. 289–312. El-Ghundi, M., O’Dowd, B.F., and George, S.R. (2007) Insights into the role of dopamine receptor systems in learning and memory. Rev. Neurosci. 18:37-66. Ellis, K.A., and Nathan, P.J. (2001) The pharmacology of human working memory. Int. J. Neuropsychopharmacol. 4:299–313. Feng, R., Rampon, C., et al. (2001) Deficient neurogenesis in forebrain-specific presenilin-1 knockout mice is associated with reduced clearance of hipppocampal memory traces. Neuron 32: 911–926. Gibbs, R.B., and Gabor, R. (2003) Estrogen and cognition: Applying preclinical findings to clinical perspectives. J. Neurosci. Res. 74: 637–643. Givens, B.S., Olton, D.S., and Crawley, J.N. (1992) Galanin in the medial septal area impairs working memory. Brain Res. 582:71–77. Hebb, D.O. (1949) The Organization of Behavior. New York: John Wiley & Sons. Henderson, V.W., Paganini-Hill, A., Emanuel, C.K., Dunn, M.E., and Buckwalter, J.G. (1994) Estrogen replacement therapy in older women. Comparisons between Alzheimer’s disease cases and nondemented control subjects. Arch. Neurol. 51:896–900. Jones, S., Sudweeks, S., and Yakel, J.L. (1999) Nicotinic receptors in the brain: correlating physiology with function. Trends Neurosci. 22:555–561. Kandel, E.R. (2001) The molecular biology of memory storage: a dialogue between genes and synapses. Science 294:1030–1038. Knopman, D.S. (2006) Current treatment of mild cognitive impairment and Alzheimer’s disease. Curr. Neurol. Neurosci. Rep. 6: 365–371. Levi-Montalcini, R. (1987) The nerve growth factor 35 years later. Science 237:1154–1162. MacDonald, J.F., Jackson, M.F., and Beazely, M.A. (2006) Hippocampal long-term synaptic plasticity and signal amplification of NMDA receptors Crit. Rev. Neurobiol. 18:71–84. Malleret, G., Hen, R., Guillou, J.L., Segu, L., and Buhot, M.C. (1999) 5-HT1B receptor knock-out mice exhibit increased exploratory

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activity and enhanced spatial memory performance in the Morris water maze. J. Neurosci. 19(14):6157–6168. McEwen, B.S. (2001) Tracking the estrogen receptor in neurons: implications for estrogen-induced synapse formation. Proc. Natl. Acad. Sci. USA 98:7093–7100. Meneses, A. (1999) 5-HT system and cognition. Neurosci. Biobehav. Rev. 23:1111–1125. Morris, R.G.M. (1986) Selective impairment of learning and blockade of long-term potentiation by an N-methyl-D-aspartate receptor antagonist, AP5. Nature 319:774–776. Musial, A., Bajda, M., and Malawska, B. (2007) Recent developments in cholinesterase inhibitors for Alzheimer’s disease treatment. Curr. Med. Chem. 14:2654–2679. Nestler, E.J., Hymam, S.E., and Malenka, R.C. (2001) Molecular Neuropharmacology. New York: McGraw-Hill Medical Publishing. Olton, D.S., Becker, J.T., and Handelmann, G.E. (1979) Hippocampus, space, and memory. Behav. Brain Sci. 2:313–365. Ramos, B.P., and Arnste, A.F. (2007) Adrenergic pharmacology and cognition: focus on the prefrontal cortex. Pharmacol. Ther. 113: 523–536. Rasmusson, D.D. (2000) The role of acetylcholine in cortical synaptic plasticity. Behav. Brain Res. 115:205–218. Roberts, A.J., Krucker, T., Levy, C.L., Slanina, K.A., Sutcliffe, J.F., and Hedlund, P.B. (2004) Mice lacking 5-HT receptors show specific impairments in contextual learning. Eur. J. Neurosci. 19:1913–1922. Sandstrom, N.J., Kim, J. H., and Wasserman, M.A. (2006) Testosterone modulates performance on a spatial working memory task in male rats. Horm. Behav. 50:18–26. Sawaguchi, T., and Goldman-Rakic, P.S. (1991) D1 dopamine receptors in prefrontal cortex: involvement in working memory. Science 251:947–950. Schimanski, L.A., Ali, D.W., Baker, G.B., and Nquyen, P.V. (2007) Impaired hippocampal LTP in inbred mouse strains can be rescued by beta-adrenergic receptor activation. Eur. J. Neurosci. 25: 1589–1598. Segal, M., and Murphy, D. (2001) Estradiol induces formation of dendritic spines in hippocampal neurons: functional correlates. Horm. Behav. 40, 156–159. Siegel, G.W., Agranof, B.W., Albers, R.W., Fisher, S.K., and Uhler, M.D., eds. (1999) Basic Neurochemistry: Molecular, Cellular, and Medical Aspects, 6th ed. New York: Lippincott-Raven. Sieghart, W. (2006) Structure, pharmacology, and function of GABAA recptor subtypes. Adv. Pharmacol. 54:231–63. Walsh, T.J., and Stackman, R.W. (1992) Modulation of memory by benzodiazepine-acetylcholine interactions. In: Levin, E.D., Decker, M.W., and Butcher, L.L., eds. Neurotransmitter Interactions and Cognitive Function. Boston: Birkhauser, pp. 312–328. Williams, B.J., Eriksdotter-Jonhagen, M., and Granholm, A.C. (2006) Nerve growth factor in treatment and pathogenesis of Alzheimer’s disease. Prog. Neurobiol. 80:114–128. Woolley, C.S. (2007) Acute effects of estrogen on neuronal physiology. Annu. Rev. Pharmacol. Toxicol. 47:657–680. Wrenn, C.C., and Crawley, J.N. (2001) Pharmacological evidence supporting a role for galanin in cognition and affect. Prog. Neuropsychopharmacol. Biol. Psychiatry 25:283–299. Wu, L., Wells, D., Tay, J., Mendis, D., Abbott, M.A., Barnitt, A., Quinlan, E., Heynen, A., Fallon, J.R., and Ritchter, J.D. (1998) CPEB-mediated cytoplasmic polyadenylation and the regulation of experience-dependent translation of alpha-CaMKII and mRNA at synapses. Neuron 21:1129–1139. Wu, M., Shanabrough, M., Leranth, C., and Alreja, M. (2000) Cholinergic excitation of septohippocampal GABA but not cholinergic neurons: implications for learning and memory. J. Neurosci. 20:3900–3908. Yamada, K., Mizuno, M., and Nabeshima, T. (2002) Role for brainderived neurotrophic factor in learning and memory. Life Sci. 70:735–744.

57 Neuropathological and Neuroimaging Studies of the Hippocampus in Normal Aging and in Alzheimer’s Disease E F F I E M . M I T S I S , M AT T H E W B O B I N S K I , M I R O S L AW B R Y S , LIDIA GLODZIK-SOBANSKA, SUSAN DESANTI, YI LI, BYEONG-CHAE KIM, LISA MOSCONI,

This chapter was revised by Effie M. Mitsis, PhD, from an earlier version written and published in this textbook by the NYU group.

Recent estimates suggest that Alzheimer’s disease (AD), the most common type of dementia seen after age 60 years, affects an estimated 15 million people worldwide. In the year 2000, there were 4.5 million people with AD in the U.S. population, and prevalence projections estimate that this number will increase by threefold to 13.2 million people by the year 2050 (Hebert et al., 2003). Other data show that for every patient with dementia, there are approximately eight individuals with no dementia with cognitive deterioration adversely affecting their quality of life (Larrabee and Crook, 1994). Prevalence rates for individuals older than age 65 years with mild cognitive impairment (MCI), considered a prodromal stage of AD, range between 3% for a neuropsychologically defined amnestic subtype (Ganguli et al., 2004; Manly et al., 2005) to as high as 25% when all cognitive subtypes of MCI are considered (Manly et al., 2005). Therefore, with respect to the above estimates, a staggering number of elderly persons with mild to severe cognitive impairments, perhaps 10– 20 million, can be expected in the next 35 years, representing a great human and economic toll. Cross-sectional and longitudinal studies commonly observe subtle declines in cognitive functioning associated with aging, and the underlying brain anatomy and physiological mechanisms responsible for these age-related declines in cognition are becoming better understood. 936

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Neuropathology and structural neuroimaging studies consistently point to the hippocampal formation as a key structure in understanding age-related cognitive changes, particularly memory impairments. Neuropathology studies identify the neurons of the hippocampal formation, which includes the entorhinal cortex (EC), hippocampus, and subiculum, as the most vulnerable to the age-related deposition of neurofibrillary tangles (NFT; Braak and Braak, 1991), a diagnostic feature of AD, with synaptic dysfunction (Braak and Braak, 1991), synaptic loss (Scheff et al., 2007), and neuronal loss leading to gross atrophy (Hyman et al., 1984; Gomez-Isla et al., 1996; Bobinski et al., 1997). Moreover, for many elderly patients with MCI, NFT deposition in the hippocampal formation is a relatively focal phenomenon (Giannakopoulos et al., 1994). With the progression of clinical symptoms, there is a correlated progression of the neuropathology with increasing involvement of the neocortex (Braak and Braak, 1991). Similarly, in-vivo neuroimaging studies have demonstrated anatomically specific volume reductions in the hippocampus of patients with MCI (Convit et al., 1997; Jack et al., 1999; De Santi et al., 2001; Jack et al., 2005; van de Pol et al., 2007). As a group, patients with MCI are at increased risk to develop symptoms of AD within a few years. Longitudinal neuroimaging studies show that hippocampal volume and measures of delayed verbal recall are accurate predictors of future dementia in patients with MCI. In neuropathology and neuroimaging studies, the dementia symptoms of AD are associated with hippocampal formation and neocortical pathology. Magnetic resonance imaging (MRI)

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studies in patients with AD have shown that cortical atrophy occurs in defined sequences as the disease progresses, which is comparable to the pattern of NFT accumulation seen in cross-section at autopsy (Thompson, 2003). Severe EC and hippocampal atrophy is consistently found in patients with mild AD (Jack et al, 1992; Convit et al., 1997), whereas volume reductions in cortical regions are apparent in the more advanced stages of disease (Convit et al., 1997). As our ability to detect the anatomic changes in the hippocampal formation improves, so does our ability to detect patients at increased risk for AD. Improved early detection of AD-related brain changes will be of value in future therapeutic studies examining patients with MCI and possibly even patients at earlier preclinical stages. The purpose of this chapter is threefold: (1) to describe the normal anatomy of the hippocampal formation and the sites vulnerable to neuropathological changes in normal aging and AD; particular emphasis will be placed on the hippocampus proper, with descriptions using histological criteria and the gross landmarks visible with in-vivo structural neuroimaging; (2) to briefly review relationships between hippocampal formation damage and neuropsychological performances; and (3) to present data that support the hypothesis that hippocampal formation atrophy occurs early in the natural history of AD and actually precedes neocortical involvement. HIPPOCAMPAL FORMATION NEUROANATOMY The hippocampal formation is one of the major parts of the allocortex (a phylogenetically older cortex that is part of the rhinencephalon). It consists of the hippocampus proper (hippocampus), dentate gyrus, subicular complex, and EC (Rosene and Van Hoesen, 1987; Amaral and Insausti, 1990). General Boundaries of the Hippocampus In the human brain, the hippocampus proper is particularly well developed, occupying the temporal lobe in the floor of the temporal (inferior) horn of the lateral ventricle. The hippocampus is known for its seahorselike appearance, and much of its gross anatomy can be viewed in vivo with MRI. The length of the hippocampus is about 4 to 5 cm, with a maximal width of about 2 cm and a maximal height of about 1.5 cm (Duvernoy, 1988). The boundaries of the hippocampus vary along its rostrocaudal length. To illustrate these boundaries at four levels along the hippocampal length, we will use in-vivo T1-weighted MRI scans and postmortem sections stained with cresyl violet (Fig. 57.1A–H). Note that the numbers in brackets in the text correspond to those indicated in

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the figures. Figures 57.1A and 57.1B represent the anterior hippocampus at the level of the amygdaloid body. At this level the hippocampus 〈1〉 is bounded dorsally by the amygdala 〈2〉, laterally by the temporal horn 〈3〉, inferiorly by the subiculum 〈4〉 and the white matter of the parahippocampal gyrus (PG) 〈5〉, and medially by the ambient cistern 〈6〉. The PG 〈5〉 is bounded laterally by the collateral sulcus 〈7〉 and inferiorly by the entorhinal 〈8〉 and transentorhinal cortices. At this level, the EC extends medially to cover the ambiens 〈9〉 and semilunar gyri 〈10〉. The boundary between the hippocampus and the amygdala is somewhat indistinct. However, using sagittal views, which are readily obtained with MRI, the visual separation between amygdala and hippocampus can be facilitated (Convit et al., 1999). More posteriorly, at the level of the hippocampal head (also referred to as the pes hippocampus or uncus) (Fig. 57.1C, D), the hippocampus 〈11〉 is more complex in shape. Posterior levels of the hippocampus have the shape of a figure eight lying on its side with the temporal horn 〈3〉 laterally; the uncal sulcus 〈11〉, the white matter of the PG, and the subiculum 〈4〉 inferiorly; the choroid plexus of the temporal horn 〈3a〉 superiorly; and the ambient cistern 〈6〉 medially. The PG is bounded inferiorly and medially by the tentorium cerebelli 〈12〉 and laterally by the collateral sulcus. The entorhinal cortex at this level is bounded mainly between the collateral sulcus and the medial aspect (uncus) of the PG. Figures 57.1E and 57.1F represent the level of the body of the hippocampus. At this level the lateral and superior hippocampus boundaries are the temporal horn 〈3〉 and choroid plexus of the lateral ventricle. The inferior boundary is the subiculum 〈4〉 and the white matter of the PG 〈5〉. On the dorsal and medial border of the hippocampus is the fimbria (Fi) 〈13〉, which is made up of white matter fibers that extend posteriorly to form the fornix. The cerebrospinal fluid space medial to the body of the hippocampus is the transverse fissure of Bichat 〈14〉, which bounds the dentate gyrus medially and separates the subiculum 〈4〉 from the thalamus (lateral geniculate level) 〈15〉 over the length of the body and tail of the hippocampus. Figures 57.1G and 57.1H represent the tail of the hippocampus at the level of the splenium of the corpus callosum 〈17〉. At this level, the hippocampus 〈1〉 is inferior and lateral to the fornix 〈16〉 and the splenium of the corpus callosum. The Hippocampus The individual fields of the hippocampus can be pictured as a stacked bundle of tissue strips running rostrocaudally in the temporal lobe. The distinctive C shape of the hippocampus is present when the bundled strips fold over each other mediolaterally, as seen in the midportion or body of the hippocampus (Fig. 57.1F). On

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57.2 Postmortem histological slice and corresponding highresolution coronal magnetic resonance image through the hippocampal body depicting the alveus and the stratum oriens (SO); stratum pyramidale of the CA1 (CA1); a multistrata layer composed of the stratum radiatum, lacunosum, and moleculare of the cornu Ammonis and the molecular layer of the dentate gyrus (MS); sector CA4 (CA4); and the granule layer of the dentate gyrus (DGg).

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more rostral sections, the hippocampus bends sharply in a medial and then in a caudal direction. The more rostral levels of the hippocampal structure are more complex, mostly due to a varied number of rostrocaudal flexures. At caudal levels (hippocampal tail), the hippocampus bends dorsally and ascends toward the splenium. As part of allocortex, the cornu Ammonis (hippocampus proper) has three major layers: (1) the stratum oriens, (2) the stratum pyramidale, and (3) a layer that blends the strata radiatum, lacunosum, and moleculare. Aspects of these layers can be appreciated using MRI (Fig. 57.2). On the basis of types of the pyramidal neurons, the cornu Ammonis can be divided into four sectors: CA1 to CA4. Subicular Complex The subicular complex is divided into three parts: the subiculum proper, presubiculum, and parasubiculum. Subicular complex subdivisions consist of two layers: (1) the molecular layer and (2) the pyramidal layer. In the presubiculum, a layer interposed between the molecular and the pyramidal layers, the parvopyramidal layer, is distinguished. Entorhinal Cortex The EC and the transentorhinal cortex form a major part of the anterior PG. Phylogenetically, they are relatively old structures. Based on histology and connectivity, the EC is transitional between the hippocampus and the neocortex. The term entorhinal cortex was introduced by Brodmann (1909) as a synonym for his area 28. Subsequent studies divided the entorhinal cortex into many fields (Vogt and Vogt, 1919; Braak, 1972) and increased the number to as many as 23 different fields (Rose, 1927). Recent cytoarchitectonic studies showed that parcellation of the entorhinal cortex in humans is largely parallel to that in the monkey and distinguishes

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only eight different fields (Amaral et al., 1987; Insausti et al., 1995). However, to date, little is known about the physiological function and the consequences of pathology in these fields. The EC is made up of six layers (Amaral and Insausti, 1990; Insausti et al., 1995). Layer II is one of the most outstanding and distinguishing areas of the EC and is made up of islands of large, modified pyramidal and stellate cells. Compared with the neocortex, one of the most characteristic features of the EC in all species is the absence of an internal granular layer. In its place is an acellular layer of dense fibers called the lamina dissecans. The EC is adjacent to the more lateral perirhinal cortex (areas 35 and 36 of Brodmann). There is no clearcut border between area 35 and the EC, and these two fields appear to have an obliquely oriented boundary, where the deep layers of the EC extend somewhat more laterally than the superficial layers. This distinctly angled border between area 35 and the EC has been emphasized by Braak (1980), who has labeled the region of overlap the transentorhinal cortex. With serial coronal MRI sections, one may reliably identify gyral landmarks that are approximate boundaries for the EC region. These landmarks include, on the medial surface, the semilunar gyrus and the gyrus semianularis. The lateral boundary is approximated at anterior levels by the rhinal sulcus and posteriorly by the collateral sulcus. Hippocampal Formation Connections The EC, the gateway to the hippocampus, receives massive synaptic input from neocortical association areas and less pronounced input from primary sensory areas (Van Hoesen, 1982; Suzuki and Amaral, 1994). In addition, it receives input from many subcortical regions, including the midbrain raphé nuclei, the ventral tegmental area, the locus coeruleus, the septum, the thalamus and hypothalamus, the amygdala, the magnocellular basal forebrain nuclei, and the claustrum (Insausti et al., 1987). The EC provides the major source of afferent information to the hippocampus via the perforant path (Witter and Amaral, 1991). The predominant component of the perforant path has been regarded as the projection from the stellate layer II neurons of the EC that synapses in the molecular layer on the dendrites of the granular cells of the dentate gyrus. In the classical model of the trisynaptic circuit, this is the first link, followed by the mossy fiber connections to CA3 pyramidal cells and completed by the Schaffer collateral input to CA1. This simplified circuit diagram has been modified recently as it has been shown that there is actually a second distinct projection from the entorhinal cortex, the alternative perforant pathway, that contributes fibers to all the hippocampal fields and to the subiculum (Witter and Amaral, 1991). The alternative

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perforant pathway is formed by projection from neurons of layers II and III of the EC to the subiculum, CA1, CA2, and CA3. Much hippocampal output is also directed back to the EC and neocortex directly from CA1 and via relays in the subiculum. Thus, the EC occupies the key position with respect to gating the interactions, output as well as input, between the hippocampus and the rest of the brain.

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Cerebrospinal fluid (CSF) marks the boundary of the hippocampus over a large surface area. This includes the temporal horn and a complex of CSF containing fissures and cisterns. Figures 57.3A and 57.3B (see also COLOR FIGURE 57.3B in separate insert) depict the orientation of the transverse fissure relative to the hippocampus, PG, thalamic structures, and ventricular CSF in three orthogonal planes. These CSF landmarks are of particular interest for in-vivo imaging, as they provide high-contrast boundaries between the hippocampus and surrounding structures such as the thalamus. In addition, increases in these CSF spaces reflect regional tissue atrophy, and they are therefore of interest in the clinical evaluation. In the coronal view (see Fig. 57.3A, top panel), the lateral boundaries of the transverse fissure of Bichat (also known as the lateral transverse fissure [LTF]) is the medial aspect of the dentate gyrus (DG) and the Fi. The coronal view best permits separation of the choroidal fissure (CF) and hippocampal fissure (HF) extensions of the LTF. In the horizontal or axial view, the LTF begins at the posterior border of the pes hippocampus or uncus (Un) (Fig. 57.3A, middle panel). Medially, the LTF communicates with the

B 57.3 (A) Schematic representations of coronal (top panel), axial (middle panel), and sagittal (bottom panel) views of the hippocampal region. A: ambient cistern; CA: cornu Ammonis; CF: choroids fissure recess; CP: cerebral peduncle; DG: dentate gyrus; Ent: entorhinal cortex; Fi: fimbria; H: hippocampus; HF: hippocampal fissure; LGB: lateral geniculate body; LTF: lateral tranverse fissure; LV: lateral ventricle; PG: parahippocampal gyrus; Pul: pulvinar; S: subiculum; and Un: uncus. (B) The magnetic resonance imaging scans were obtained on a General Electric Advantage 1.5T imager using a spoiled gradient echo sequence of 35/9/1 (TR/TE/excitations), a 60 degree flip angle, an 18 cm field of view, and a 256 × 128 acquisition matrix. We obtained 124 contiguous coronal images with a slice thickness of 1.3 mm. On 56 of these images, using a twofold image magnification to aid in region drawing (pixel size = 0.35 mm), we outlined and coded in yellow (see Figure 57.3B in color insert) the hippocampal fissures. Also, the cerebrospinal fluid (CSF) of the lateral ventricle was outlined and coded in red. The top panel shows 3 of the 56 slices coded. All 56 coronal images and the coded regions were reformatted and displayed as 5 mm contiguous slices in a negative angulation axial plane (middle panel) and in a sagittal plane (bottom panel). The reformatted axial images and sagittal images depict the anatomical relationship of the two CSF compartments.

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ambient cistern kAl, which borders the cerebral peduncles kCPl. The coronal and sagittal planes (Fig. 57.3A, bottom panel) of section permit identification of the structures bounding the ventral surface of the transverse fissure, namely, the subiculum of the PG, as well as the identification of those thalamic structures bounding the dorsal margin, the lateral geniculate body (LGB), and the pulvinar (Pul). NEUROPATHOLOGY Hippocampal Atrophy in Alzheimer’s Disease Impairment of memory is one of the earliest features of AD. Clinical symptoms slowly increase in severity and are accompanied by personality changes, deterioration of language functions, and involvement of the extrapyramidal motor system (Reisberg et al., 1982). Disease severity is associated with a hierarchy of pathological changes progressing from the EC and hippocampus to involvement of the neocortex (Braak and Braak, 1991). Hippocampal atrophy rates, detectable on MRI up to 5 years prior to clinical expression of the disease (Fox et al., 1999; Schott et al., 2003), may be considered a surrogate marker for disease progression and predict progressive cognitive decline (Jack et al., 2000; Barnes et al., 2004; Jack et al., 2005; Mungas et al., 2005) even in aging individuals without subjective memory complaint and with normal baseline scores on cognitive tasks (den Heijer et al., 2006). After disease onset, the spreading sequence of neocortical atrophy mirrors the progressive spread of amyloid plaques and NFT in the brain (Braak and Braak, 1997). Postmortem histopathological studies show that the hippocampal formation, especially the entorhinal and transentorhinal cortices, is one of the earliest and most severely affected structures in AD (Hyman et al., 1984; Braak and Braak, 1991). Morphological studies of the hippocampal formation reveal neurofibrillary changes and granulovacuolar degeneration of neurons, synaptic and neuronal loss, and amyloid β deposition in plaques and vascular walls (Ball et al., 1985; Braak and Braak, 1991). Neurofibrillary degeneration and the loss of projection neurons responsible for the majority of afferent and efferent connections of the hippocampal formation cause the disruption of intrahippocampal connections and functional isolation of the hippocampal formation from other parts of the memory system (Hyman et al., 1984). Neuronal loss in the hippocampal formation appears to be a major component of the memory impairment seen in AD (Hyman et al., 1984; Bobinski et al., 1997). Neurofibrillary degeneration has been put forth as a cause of neuronal loss and atrophy of the hippocampal formation (Hyman et al., 1984; Davies et al., 1992; Bobinski et al., 1996; Bobinski et al., 1997). The later onset of amyloid deposits in the hippocampal for-

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mation subdivisions and the topographical differences in distribution and number suggest that amyloid and neurofibrillary changes develop independently (Bouras et al., 1994). The impact of amyloid deposits on hippocampal formation atrophy is not known. The severe atrophy of the hippocampal formation in AD is found, to a similar extent, in cellular and fiber layers (Bobinski et al., 1995; Bobinski et al., 1996). Our detailed volumetric study of the hippocampal formation showed marked volume losses in the pyramidal layer of the cornu Ammonis (61%), in the stratum radiatum (74%), and in the lacunosum/moleculare (66%) in patients severely affected by AD compared to normal controls (Bobinski et al., 1995). The volumetric loss of the pyramidal layer reflects the loss of pyramidal cells, whereas the decrease in the volume of the stratum radiatum and lacunosum/moleculare encompasses the loss of (1) apical dendrites of the pyramidal cells and (2) the perforant fibers and Schaffer collaterals. In the subicular complex, patients severely affected by AD also showed a 68% volumetric loss of the pyramidal layer. This volume loss is a direct effect of loss of cell bodies and perineuronal processes. The atrophy of the apical dendrites of pyramidal cells, and of the dense network of fibers running through the molecular layer of the subicular complex, probably accounts for the 54% decrement in the volume of this layer. The DG is the only hippocampal subdivision that does not manifest a significant volumetric decrement relative to controls. The granular layer is mostly spared in the course of AD and is affected by neurofibrillary pathology only in latestage AD (Braak and Braak, 1991). In this study, neuronal counts were not made in the EC. In another pathological study (Bobinski et al., 1995), the volume of the hippocampal formation subdivisions was examined for their relationship to the stage (as determined by the Functional Assessment Staging [FAST] procedure scale) and the duration of AD. Using the FAST scale, the following significant relationships were observed with regional volume measures: CA1 (r52.79), subiculum (r52.75), and EC (r52.62) (Fig. 57.4; see also COLOR FIGURE 57.4 in separate insert). Over the estimated duration of clinically manifest AD, calculations projected an overall decrease of 60% in the volume of the hippocampal formation. These volumetric decreases in the cornu Ammonis, subicular complex, and EC were 64%, 70%, and 51%, respectively. These cross-sectionally derived results suggest that changes occur in the hippocampal formation and most of its structural components throughout the course of AD (Fig. 57.5). Determination of the subvolumes of the whole hippocampal formation and estimation of the total number of neurons, NFT, and amyloid deposits in these volumes enabled analysis of the relationships between pathological lesions, neuronal number, and volume of

FIGURE 57.4 Schematic drawings of histologically derived volumes of the hippocampus and subicular complex. (A) is the average normal control and (B) is the average Alzheimer’s disease (AD) patient.

FIGURE 57.5 Scattergram plotting volume of CA1 with disease duration.

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the hippocampal subdivisions (Bobinski et al., 1996). Specifically, the volume in the hippocampus proper, as determined by either histological criteria or postmortem MRI studies, correlated linearly with number of neurons (r5.91; Fig. 57.6). This finding, as well as the observation that the volume of the hippocampus as determined by MRI reflects the actual size of the structure (Bobinski et al., 2000), is of particular relevance to in-vivo neuroimaging. These data support the contention that in-vivo neuroimaging measures of atrophy reflect actual histological damage and neuronal loss (see below). Alzheimer’s Disease–Related Neuronal Loss Neuronal loss in the hippocampal formation in AD has been described by many authors. However, NFT lesions account for only a small proportion of hippocampal neuronal loss (Kril et al., 2002). The EC, CA1, and subiculum are consistently affected severely, whereas the granular layer of the DG is generally spared (Davies et al., 1992; West et al., 1994; Gomez-Isla et al., 1996). Studies of the hippocampus proper show that the number of subdivisions showing neuronal loss depends to a great extent on the duration of the illness and/or the clinical stage of AD in the patients investigated (Bobinski et al., 1997). For those individuals clinically least affected, significant neuronal loss was observed in the CA1 and subiculum. For the patients with more severe AD, significant neuronal loss was observed in CA1, CA2, CA3, CA4, and the subiculum. Recent studies of the EC add to our understanding by demonstrating clear evidence for early neuronal loss (Gomez-Isla et al., 1996). Moreover, neuronal loss correlates with the percentage of neurons with neurofibrillary changes among all neurons (r5.73) (Bobinski et al., 1996). This suggests that neu-

57.6 Scattergram depicting the relationship between hippocampal volume and hippocampal neuronal counts in Alzheimer’s disease (AD) patients and controls.

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rofibrillary pathology is a possible etiological factor in neuronal and volumetric loss in the hippocampal formation of patients with AD. On the other hand, no significant relationships were found between either neuronal counts or volumes of the hippocampal formation subdivisions and the numerical density of plaques, or the total number of plaques, or the area occupied by amyloid, or the density of vessels with amyloid angiopathy. Therefore, the data indicate that unlike tangle pathology, plaque pathology may not be associated with neuronal loss. Despite the complex connectivity in the hippocampal formation, neurofibrillary pathology and neuronal loss appear to develop in a structure-specific fashion. Braak and Braak (1991) described a staging scheme of neurofibrillary changes in the brain based on the temporal and topographical distribution of these lesions. According to these authors, neurofibrillary changes develop first in the transentorhinal cortex and then in the EC (transentorhinal stages). Further progression involves CA1, the subiculum, and CA4, then sectors CA2 and CA3 of the cornu Ammonis and the parvopyramidal layer of the presubiculum. This was referred to as the limbic stage of pathology. The changes in the dentate gyrus and all isocortical association areas (neocortex) appear in the last stage of this classification, the isocortical stages. These observations have been extended to include specific layers in the hippocampal formation (Thal et al., 2000). The first abnormally phosphorylated tau is located in perikarya and dendrites of layer II neurons of the entorhinal and transentorhinal cortices. Next, it appears in the pyramidal layer of CA1 and subiculum, then in the stratum radiatum and oriens, and finally in the outer molecular layer of the DG, which is the perforant pathway target zone. The involvement of the

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stratum oriens, together with the stratum radiatum and the outer molecular layer of the DG, is seen almost exclusively in individuals with dementia (Thal et al., 2000). West et al. (1994), who, using unbiased stereological techniques, estimated the total number of neurons in several hippocampal formation subdivisions, also reported structure-specific neuronal loss in AD. Among normal controls they found neuronal losses in two subdivisions, the hilus (CA4) and the subiculum. In the AD group they also observed additional loss of neurons in CA1. Therefore, the pathology of AD does not simply reflect an acceleration of normal aging. The regional pattern of neuronal loss in AD is qualitatively and quantitatively different from that observed in normal aging. Selective vulnerability of the CA1 sector is supported by observation of marked neuronal loss in the limbic stages (Braak’s stage III and IV) (Rossler et al., 2002). Compared to stage I, the number of pyramidal neurons in CA1 was reduced by 33% in stage IV and by 51% in stage V. In the subiculum, significant neuronal loss was found only in stage V (22%). In a detailed stereology study performed on brains of patients with moderate to severe AD and normal controls, we examined the number of neurons and NFT in the hippocampus (Bobinski et al., 1997). The CA1 sector was severely affected by neurofibrillary pathology and neuronal loss. In this sector there was a profound loss of neurons (86%), and 71% of the surviving neurons were affected by neurofibrillary changes. The subiculum showed somewhat less pathology: the neuronal loss was 68%, and 52% of surviving neurons were affected by neurofibrillary pathology. Other structures, such as CA2, CA3, and CA4, are much less affected by neuronal loss (75%, 53%, and 55%, respectively) and neurofibrillary pathology (33%, 26%, and 28% of surviving neurons, respectively). Finally, the granular layer of the DG was the only hippocampal subdivision without significant neuronal loss over the course of AD. This surprising finding may reflect a unique lack of vulnerability of these cells or may be related to increased cellular plasticity in this region. In the AD group, only 4% of the neurons in the granular layer of the DG showed neurofibrillary changes. Overall, these results support the hypothesis that there is a selective pattern of neuronal vulnerability in AD. Postmortem studies have documented the presence of NFT in the EC and transentorhinal cortex of elderly individuals with no dementia (Hof et al., 1992). In the brains of patients with early-stage AD, neurofibrillary changes are always detectable in the EC and transentorhinal cortex. Consequently, pathology limited to the EC and transentorhinal cortex may represent a clinically silent phase of the disease (Hof et al., 1992). Neurons of layers II and IV are particularly susceptible to degeneration. Eventually during the course of AD, virtu-

ally all neurons in layer II contain NFT (Hirano and Zimmerman, 1962; Kemper, 1978; Hyman et al., 1984; Mann and Esiri, 1989; Braak and Braak, 1991). Layer II is also the first cortical layer showing ghost tangles (clusters of extracellular filaments that are remnants of a degenerated neuron) (Braak and Braak, 1991). Layer IV is affected after layer II. Only a comparatively few NFT are found in layers III and V, and these usually develop late in the course of AD (Braak and Braak, 1991). It has been suggested that the degeneration of much of the neuronal architecture of the EC destroys a large functional part of hippocampal input and output, and that this destruction results in the memory and cognitive deficits associated with the early stages of AD (Hyman et al., 1984). In a detailed stereological study, GomezIsla et al. (1997) found that patients with very mild cognitive impairment (Clinical Dementia Rating [CDR] = 0.5) had 32% fewer neurons in the EC than controls. In layer II, neuronal loss reached 60%. In severe dementia cases (CDR53), the total number of neurons in layer II decreased by 90% and in layer IV by 70%. Moreover, neuronal numbers were negatively correlated with tangle and plaque densities. This study showed that significant neuronal loss in layer II of the EC distinguished even very mild AD from nondemented aging (Gomez-Isla et al., 1996). In summary, modern stereological techniques have recently shown that CA1 of the hippocampus and layers II and IV of the EC are the most vulnerable to AD pathology and are potentially specific for AD (West et al., 1994; Gomez-Isla et al., 1996). There is growing evidence suggesting that more than one mechanism of neuronal loss occurs in AD (GomezIsla et al., 1997; Broe et al., 2001; Rossler et al., 2002). Apoptosis has been suggested to play a role in AD (de la Monte et al., 1998; Broe et al., 2001). Almost one fourth of the remaining neurons in AD show abnormal nuclear morphology and deoxyribonucleic acid (DNA) fragmentation (Broe et al., 2001). In addition, there is no correlation between apoptotic morphology and tau deposition, suggesting that non-NFT-related neuronal degeneration plays a significant role in AD. Hippocampal Formation Pathology in Normal Aging Studies of normal elderly persons typically show that NFT accumulation in the EC and/or hippocampus dramatically increases with increasing age (Price et al., 1991; Arriagada et al., 1992; Giannakopoulos et al., 1994; Langui et al., 1995; Price et al., 2001). Specifically, a pattern of early hippocampal formation NFT deposition (Hubbard et al., 1990; Giannakopoulos et al., 1994; Giannakopoulos et al., 2003), with relative sparing of the neocortex (Price et al., 1991; Arriagada et al., 1992; Ulrich, 1985), is found in studies of elderly individuals

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with no dementia (normal and MCI). It is informative that strong age relationships remain despite methodological differences in patient recruitment, cognitive evaluation, staining procedures, and anatomical sampling. These differences across studies appear more likely to affect the relative numbers of patients affected rather than the pattern of brain region change. For example, Giannakopoulos et al. (1994) examined 1131 brains of elderly person who were normal and mildly affected but with no dementia derived from a hospital-based medical and surgical service. They observed NFT in the CA1 of the hippocampus in 25% of the sample. By comparison, NFT was uncommon in these patients in the superior frontal (4%) and occipital cortices (3%). Langui et al. (1995) examined the EC and hippocampus from 167 brains of normal patients. The diagnosis of normal was based on clinical notes; no cognitive testing was performed. They observed that AD changes (NFT or senile plaques) were found in less than 20% of patients younger than age 60 years, in over 80% of those between 60 and 80 years, and in nearly 100% of the 56 patients older than age 80 years. The predominant form of pathology was the NFT, either alone or frequently in combination with senile plaques. Only 2% of normal brains showed senile plaques in the absence of NFT. A recent longitudinal study that followed a small cohort of elderly individuals (age range 74–95 years, median age 85 years) who were cognitively intact at time of death found relatively low burdens of AD neuropathology, with 87% of the sample (34 out of 39 patients) having a Braak stage < IV (Knopman et al., 2003). Summarizing several other studies that examined the hippocampal formation along with neocortical sites, patients with no dementia appear to show a strong age-related tendency toward NFT accumulation that is concentrated in the hippocampal formation (Morris et al., 1991; Price et al., 1991; Arriagada et al., 1992). Although senile plaques also tend to accumulate with age, typically they accumulate at later ages and have a preference for the neocortex rather than the hippocampal formation (Arriagada et al., 1992; Giannakopoulos et al., 1994). In a recently proposed model, neurofibrillary changes occur in all persons during aging but affect relatively few neurons before 85 to 90 years and are insufficient to cause significant neuronal loss or cognitive impairment (Price et al., 2001). With a substantial amyloid burden, the amount of neurofibrillary change increases during the preclinical stage of AD. There is still insufficient neuronal degeneration to produce detectable cognitive impairment, but autopsied cases in this stage generally meet pathological criteria for AD. Further amyloid deposition and accelerated neurofibrillary change result in significant neuronal dysfunction and death and associated MCI (Price et al., 2001).

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These data, which support the Braak model, suggest that age-associated hippocampal formation lesions are the earliest lesions associated with AD. Moreover, it appears that in association with these early lesions, there is a reduction in the volume of the affected tissue, thus making this observation a target for early diagnosis using in-vivo neuroimaging. It was reported that normal elderly individuals with NFT lesions in the hippocampus showed hippocampal volume reductions compared with normal age-matched elderly persons without NFTs (de la Monte, 1989). It therefore appears that the inverse relationship between NFT deposition and hippocampal volume extends throughout the range of normal to severely demented AD. Such neuropathology findings have encouraged the more comprehensive in-vivo examination of the hippocampal formation in aging and AD. To date, longitudinal in-vivo imaging studies are becoming an important bridge between clinical and neuropathology based staging models (Mosconi, Tsui, et al., 2007). NEUROPSYCHOLOGY Systematic research with monkeys and rats and related research with humans has identified structures and connections important for memory in the medial temporal lobe and the midline diencephalon. These important structures within the medial temporal lobe are the hippocampus, the subicular complex, and the adjacent and anatomically related entorhinal, perirhinal, and parahippocampal cortices (Mishkin, 1978; Moss et al., 1981; Zola-Morgan et al., 1994). The amygdaloid contribution to memory is modest (Zola-Morgan et al., 1989). Studies of the medial temporal lobe in monkeys showed that the severity of memory impairment depended on the locus and the extent of medial temporal lobe damage (Zola-Morgan et al., 1994). Damage limited to the hippocampus produced mild memory impairment (ZolaMorgan and Squire, 1986). When the damage was increased to include the adjacent entorhinal and parahippocampal cortices, more severe memory impairment was produced. Finally, when the above lesion was extended rostrally to include the more anterior aspects of the EC and the perirhinal cortex, the memory impairment was even greater (Zola-Morgan et al., 1989; ZolaMorgan et al., 1993; Zola-Morgan et al., 1994). These findings suggest that whereas damage to the hippocampus proper produces measurable memory impairment, a substantial part of the severe memory impairment produced by large medial temporal lobe lesions in humans and monkeys can be attributed to damage to the entorhinal, perirhinal, and parahippocampal cortices adjacent to the hippocampus. Selective hippocampal lesions produce memory storage deficits while preserving immediate recall, remote recall (historical memories), and intelligence (Squire,

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1992). Some evidence exists that the measures most sensitive to hippocampal integrity, such as secondary memory tasks emphasizing delayed recall, are somewhat resistant to longitudinal decline over short study intervals in normal aging (Colsher and Wallace, 1991). These observations have led to the successful use of delayed recall tasks in the clinical differentiation of persons with normal aging from patients with no dementia but with MCI who are considered at risk for AD (Welsh et al., 1991; Blacker et al., 2007; for a detailed review, see Twamley et al., 2006). There is a general consensus among the numerous studies that have used delayed recall tasks to investigate neuropsychological function in AD that episodic memory decline is an early and prominent feature of AD, with declines occurring years before significant cognitive and behavioral changes required for a diagnosis of AD. Neuroimaging studies investigating the relationship between neuropathology and cognitive changes have demonstrated that atrophy primarily of the hippocampus correlates with episodic memory impairment in AD (de Leon et al., 1997), with subsequent decline in other cognitive domains consistent with the spread to neocortical regions of the underlying neuropathology. In summary, the pathological and neuropsychological data offer excellent justification for examining the integrity of the hippocampal formation as a potentially informative anatomy for evaluation of the transition between normal aging, MCI, and AD-related memory decline. However, efficient memory functioning is not simply based on the integrity of the hippocampal formation. Many different locations of brain damage have been associated with memory dysfunctions (Mesulam, 1990), and generalized atrophic changes that are known to occur in normal-aged individuals may also contribute to memory changes (de Leon et al., 1984). Consequently, the determination of meaningful brain–memory relationships in aging humans requires qualitative and quantitative characterization of the cognitive deficits, as well as examination of the anatomical specificity of any statistically significant brain-memory relationship.

ing studies regarding the involvement of the hippocampus. All studies report hippocampal atrophy relative to age-matched controls. These results initially were reflected in indirect measures including qualitative ratings of the amount of CSF accumulating in the hippocampal fissures (de Leon et al., 1988; de Leon et al., 1989; de Leon et al., 1993; de Leon et al., 1997); linear two-dimensional estimates of hippocampal width (Scheltens et al., 1992; Jobst et al., 1994); measures of medial temporal lobe gray matter volume (Stout et al., 1996); the size of the suprasellar cistern (Aylward et al., 1996); and the distance between the right and left Un (see de Leon et al., 1994, for review). Subsequently, direct measures of hippocampal volume loss were employed with the advent of new and more sophisticated MRI sequences, as well as the use of precise and validated volumetric methods (Seab et al., 1988; Jack et al., 1992; Convit et al., 1993; Ikeda et al., 1994; Lehericy et al., 1994; Convit, de Leon, Hoptman, et al., 1995; Convit et al., 1997; Jack et al., 1997; Insausti et al., 1998; Laakso et al., 1998; Bobinski et al., 1999; Goncharova et al., 2001). However, before hippocampal atrophy can be considered a diagnostic marker for early (preclinical) AD, several lines of investigation need to be developed further. Specifically, we need to improve our understanding of the prevalence and severity of hippocampal atrophy over the stages of AD and as a function of age, gender, and genetic factors. The diagnostic specificity of hippocampal atrophy for AD needs to be established, and the relationship between the imaging-determined atrophy and neuropathological features of the disease needs to be validated. Results from more recent longitudinal studies of normal aging show that MCI and AD has begun to demonstrate that structural imaging has potential to predict outcome and that hippocampal and medial temporal lobe changes appear to be the most important predictors of future decline (Glodzik-Sobanska et al., 2005).

NEUROIMAGING STUDIES

The decline from normal to MCI and AD has been investigated mainly by MRI studies. These studies have shown, overall, that the rate of medial temporal lobe (MTL) volume reduction correlates with the decline from normal to MCI (Rusinek et al., 2003; Jack et al., 2004). Cross-sectional and longitudinal studies show that imaging the hippocampal formation alterations is of use in the evaluation of age-related memory changes, and in the prediction of future dementia and a diagnosis of AD. Moreover, these in-vivo data support the Braak model. In this model, the earliest stages of AD are marked by selective involvement of the EC followed by hippocampal changes, and finally by progressive neocortical

In the late 1980s and early 1990s, several laboratories reported that the hippocampal region could be reliably studied with structural neuroimaging (de Leon et al., 1988; Seab et al., 1988; de Leon et al., 1989; Press et al., 1989; Kesslak et al., 1991; de Leon et al., 1993). This advance was partly facilitated by the availability of MRI. Thus, numerous research efforts were directed away from more general markers of brain atrophy (ventricular size and cortical atrophy) to anatomically better-defined regional assessments. In the AD literature, a growing consensus exists among in-vivo neuroimag-

CROSS-SECTIONAL HIPPOCAMPAL STUDIES OF NORMAL AGING AND ALZHEIMER’S DISEASE

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pathology. Recent studies using in-vivo MRI imaging techniques demonstrate the pattern and rate of regional atrophy, with tissue losses of 20%–50% in regions of the hippocampal formation corresponding to the CA1 and subiculum in patients with AD (Frisoni et al., 2006). Importantly, these CA1 and subicular involvements were associated with an increased risk for conversion from MCI to AD (Apostolova et al., 2006). In another study (Apostolova et al., 2006), comparing patients with amnestic MCI and patients with mild AD demonstrated that patients with mild AD have significantly greater bilateral atrophy of the lateral hippocampus an area corresponding to the CA1 region and in the right hippocampus in areas corresponding to the CA2 and CA3 subfields. These findings are in agreement with pathological observations of damage to the hippocampus proper in AD (Bobinski et al., 1995; Bobinski et al., 1997; Schonheit et al., 2004). Memory decline with aging is closely associated with hippocampal formation integrity. One published MRI study followed a large cohort of normal individuals until the onset of dementia including AD and showed an association between hippocampal and amygdala volumes during normal aging and shorter times until onset of dementia on average 6 years later (den Heijer et al., 2006). The risk for dementia was threefold increased per 1 standard deviation (SD) decrease in hippocampal volumes, and twofold increased per 1 SD decrease in amygdala volumes (den Heijer et al., 2006). The distinction between whether memory loss is part of normal aging or a pathological state was explored in a cross-sectional study of younger and older adults using a functional MRI protocol that was specifically developed to perform regional analysis of the hippocampal formation (Small et al., 2002). To determine the frequency of age-related hippocampal decline in the elderly group, the hippocampal circuit of each older patient was compared to the youngest age group using a multivariate linear regression, where the independent variables were the four hippocampal subregions and the dependent variable was group. Patients were then dichotomized into those in which the hippocampal signal did not significantly differ from the younger age group and those who had at least one hippocampal subregion showing significant decline in signal. The findings from this study showed that function in two hippocampal subregions—the subiculum and the DG— declines normally with age, whereas function in the EC was found to decline pathologically (Small et al., 2002). Similarly, entorhinal glucose utilization reductions were found to predict the decline from normal aging to MCI (de Leon et al., 2001). Moreover, this study showed that reduced hippocampal metabolism followed the EC changes among subjects that showed cognitive decline. An early computed tomography (CT)-based study of a large cohort (405 patients) showed that hippocam-

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pal atrophy was significantly more prevalent in all clinical groups compared with controls (de Leon et al., 1997). Seventy-eight percent of the MCI group, 84% of the mild AD group, and 96% of the moderate to severe AD groups showed hippocampal atrophy. Hippocampal atrophy was shown in 29% of controls. Normal controls showed striking age dependence for hippocampal atrophy, whereas the cognitively impaired groups showed prevalence rates independent of age. Numerous studies have demonstrated the ability of MRI-based volumetric measurements of the hippocampal formation to differentiate between patients with AD and normal controls (Fig. 57.7). Hippocampal formation atrophy has been shown to be one of the most robust and consistently documented findings (Jack et al., 1992; Convit et al., 1997; de Leon et al., 1997; Jack et al., 1997; Laakso et al., 1998).Recently, there has been increased interest in identifying patients at the earliest stages of AD so that effective treatment, when available, can be initiated. Therefore, neuroimaging studies have been performed on patients with no dementia who are at increased risk for AD, including those with family history of AD or the apolipoprotein (ApoE) genotype, and patients with no dementia with mild MCI. The hippocampus size is significantly reduced in patients with MCI compared with normal controls (Convit, de Leon, Tarshish, et al., 1995; Convit et al., 1997; de Leon et al., 1997; Laakso et al., 1998). The volume of the hippocampus is decreased by 11% to 15% in patients with MCI and by 12% to 35% in patients with AD compared to normal controls (Juottonen et al., 1998; Bobinski et al., 1999; De Santi et al., 2001; Du et al., 2001; Glodzik-Sobanska et al., 2005). With the observation that transentorhinal/EC rather than hippocampus is the site of the earliest pathological changes, several studies demonstrated significant volume loss of this region in patients with MCI compared with normal controls (Killiany et al., 2000; Xu et al., 2000; Du et al., 2001; Pennanen et al., 2004; Devanand et al., 2007). Entorhinal cortex was found to be smaller than normal by 13% in MCI and by 27% to 40% in AD (Juottonen et al., 1998; Bobinski et al., 1999; Du et al., 2001). These considerable differences in the degree of hippocampal and entorhinal atrophy probably result from different measuring methods and different subjects (severity of impairment). In our recent validation study, we showed that very accurate volumetric measurements of the whole hippocampal formation can be obtained by using an MRI protocol (Bobinski et al., 2000). Strong correlations were found between MRI and histological measurements for the hippocampus (r5.97), hippocampus/subiculum (r5.95), and hippocampus/PG (r5.89). Moreover, strong correlations between MRI subvolumes and neuronal counts were found for the hip-

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FIGURE 57.7 Axial magnetic resonance imaging scan depicting the hippocampal area from a normal control subject (left) and an age-matched Alzheimer’s disease (AD) patient (right). Black arrows mark the boundary of the hippocampus; white arrows point to the region of the hippocampal fissure.

pocampus (r5.90) and the hippocampus/subiculum subvolume (r5.84), suggesting the anatomical validity of MRI volume measurements. LONGITUDINAL STUDIES PREDICTING THE DEVELOPMENT OF DEMENTIA The results of many cross-sectional studies of hippocampal atrophy showed that hippocampal changes frequently occur in patients with MCI and thereby may predict the development of symptoms consistent with the course of AD. In our pioneering CT-based studies, 72% of patients with MCI and 4% of controls deteriorated to receive the diagnosis of AD (de Leon et al., 1989; de Leon et al., 1993). The results of this study pointed to the need for longitudinal study of the temporal relation between hippocampal atrophy, neocortical atrophy, and the development of intellectual dysfunction. As only 4% of our normal elderly sample deteriorated to dementia, while 15% had baseline hippocampal atrophy, this study also suggested that to carefully evaluate the predictive risk of hippocampal atrophy, we must also (1) extend the period of observation beyond 4 years, (2) use more sensitive indices of hippocampal integrity, and (3) use more fine-grained assessments of neuropsychological performance. Subsequent longitudinal studies confirmed and extended our results (Jack et al., 1999; Jack et al., 2000; Dickerson et al., 2001; Killiany et al., 2002). The annual rate of hippocampal atrophy was reported to be 3% in MCI and 3.5% in AD group (Jack et al., 2000). Our studies show that the medial temporal lobe atrophy rate measured with the regional boundary shift method over a 2-year interval was the most significant predictor of decline, in a group of initially healthy individuals who converted to MCI or AD at the 6-year followup. Overall prediction accuracy was 89% (Rusinek et al., 2003). Not all patients with MCI decline to clinical AD. It is estimated that 50%–70% will convert to AD (Kluger et al., 1999). Heterogeneity among patients with MCI

may be related to several factors, APoE status being one of them. Polymorphism of the APOE gene is a significant risk factor for developing late-onset AD (Corder et al., 1993). The ε4 allele confers an increased risk of developing AD and lowers the age at onset in a dosedependent fashion, whereas the ε2 allele is protective. Annual hippocampal atrophy is significantly different in AD patients with (9.8%) and without the APoE ε4 allele (7%) (Mori et al., 2002). Many studies demonstrated that hippocampal and entorhinal volumes accurately predict future conversion of MCI to AD (Jack et al., 1999; Jack et al., 2000; Killiany et al., 2000; Dickerson et al., 2001; Killiany et al., 2002; Jack et al., 2004). We reported the first evidence that EC glucose use reductions in normal elderly persons, as measured by positron emission tomography (PET), uniquely predict conversion to MCI (Fig. 57.8) (de Leon et al., 2001), and that in MCI and AD metabolism reductions exceed volume losses (De Santi et al., 2001). Using a newly developed automated hippocampal sampling procedure, we demonstrated that hippocampal glucose metabolic rate is a sensitive preclinical predictor of future cognitive impairment, as well as a longitudinal correlate of the decline from normal aging (Mosconi, 2005). More recently, fluorodeoxyglucose (FDG) PET imaging was used longitudinally to predict and monitor cognitive decline from normal aging (Mosconi, Tsui, et al., 2007). Baseline hippocampal glucose metabolic rates predicted decline from normal to AD with 81% accuracy, from normal to other dementias with 77% accuracy, and from normal to MCI with 71% accuracy. Greater rates of hippocampal and cortical glucose metabolic rates were found in the declining as compared to the nondeclining normal patients. Reduced hippocampal glucose metabolic rate was associated with a shorter duration of survival time as normal (Mosconi, Brys, et al., 2007). Numerous cross-sectional and longitudinal neuroimaging AD studies confirm the involvement of the MTL structures previously described in the neuropathologic literature. Furthermore, structural imaging has demonstrated potential to predict future decline in normal

A

B 57.8 Fluorodeoxyglucose-positron emission tomography (FDG-PET) images in a longitudinal study (baseline and follow-up) demonstrating the region of the entorhinal cortex (arrows) in two normal elderly subjects, one of whom remained normal at the 3-year follow-up (A) and the other who declined to mild cognitive impairment (MCI) (B). Note the decrease in FDG uptake in the entorhinal cortex of the patient who declined at MCI.

FIGURE

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individuals and in individuals with MCI, and hippocampal and MTL changes appear to be the most important regional predictors. In the first published prediction study (de Leon et al., 1989), the hippocampal atrophy qualitatively assessed at baseline was present in more than 90% of 48 patients who had MCI who developed dementia over a 3-year period. Only 19% of patients with MCI whose condition did not worsen had atrophy. Our replication study that applied the same axial image acquisition protocol and the same visual rating scale confirmed the ability of qualitative hippocampal atrophy assessment to predict further evolution to AD at the 4-year followup. The baseline assessment of hippocampal atrophy predicted decline with 91% accuracy (de Leon et al., 1993). The results showed that MTL atrophy was sufficient to predict conversion to AD 3 to 4 years in advance. In summary, consistent with pathological findings, MR studies point to the hippocampus and EC as the first sites for atrophic changes in AD. Entorhinal cortex glucose metabolism reductions predict the transition between normal aging and MCI, and hippocampal volume is a useful predictor of future dementia from MCI. Positron emission tomography MCI studies have identified patterns of hypometabolism in the parietotemporal and posterior cingulate cortex that are also associated with the MCI transition to AD. The temporal relationships between EC, hippocampus, and neocortical hypometabolism are under investigation (see Mosconi et al., 2004, for review). RELATIONSHIP BETWEEN HIPPOCAMPAL ATROPHY AND MEMORY IN NORMAL AGING Memory tests that involve medial temporal lobe structures for execution are the best indices of early cognitive impairment. Among normal controls, hippocampal volume correlates with delayed memory performance but not with primary or immediate memory performance (Golomb et al., 1994). Moreover, after a followup interval of 4 years, we observed in this same elderly cohort that smaller baseline hippocampal volumes were predictive of disproportionately greater reductions in delayed recall performance (Golomb et al., 1996). These results suggest that hippocampal atrophy may play an important independent role in contributing to the memory loss experienced by many aging adults. Several longitudinal studies showed that the volume of hippocampal formation decreases with age, with annual rates of volume loss ranging from 1.55% to 2.1% (Kaye et al., 1997; Jack et al., 2000). A very strong inverse correlation was found between hippocampal volume and age among normal patients older than age 60 (r52.93) but not among individuals aged 40–60 (Mu et al., 1999). On the other hand, the volume of the EC does not correlate with age (Insausti et al., 1998).

THE ANATOMIC SPECIFICITY OF HIPPOCAMPAL VOLUME LOSS IN PATIENTS AT RISK FOR ALZHEIMER’S DISEASE The early diagnosis of AD continues to be difficult and requires experience and skill (McKhann et al., 1984). Therefore, many studies have explored the role of noninvasive imaging as a potential aid in the early diagnosis of AD, such as MRI measures of the hippocampus and EC. Research shows that measures of the hippocampus or the EC are significantly different in patients with mild AD versus controls. However, there is less agreement about which of these structures is more useful in differentiating patients with AD in the preclinical stage of disease (Juottonen et al., 1998; Bobinski et al., 1999; Xu et al., 2000; Killiany et al., 2002). Our early study on anatomical specificity demonstrated that the hippocampal volume separated normal controls from patients with MCI, correctly classifying 74% (Convit, de Leon, Tarshish, et al., 1995). In addition, measurement of the fusiform gyrus volume uniquely improved the ability of hippocampal volume measurement to separate patients with MCI from patients with AD from 74% to 80%. Our cross-sectional data showed that, within the temporal lobe, specific hippocampal volume reductions separated the group at risk for AD from the normal group. By the time impairments are sufficient to allow a diagnosis of AD to be made, in addition to the medial temporal lobe volume reductions, the lateral temporal lobe is showing volume reductions, most saliently involving the fusiform gyrus. Using a longitudinal approach, Jack et al. (2004) measured annualized rates of change in the volume of hippocampus, EC, whole brain, and ventricles with serial MRI measurements in a relatively large sample (N = 160) of normal elderly individuals with MCI and patients with probable AD. They found that atrophy rates in the four structures were greater among normal elderly patients who converted to MCI or AD than among those who remained stable, greater among patients with MCI who converted to AD than among those who remained stable, and greater among individuals with fast-progressing AD as compared to those with slow-progressing AD. The MRI changes were related to disease progression rather than to disease stage at baseline. To address the issue of early involvement of the EC, we measured the hippocampal and superior temporal gyrus volumes as well as the validated landmark method for the EC (Bobinski et al., 1999). In a series of univariate logistic regression models, measurement of the EC correctly classified 100% of the control and 87.5% of the AD group. Measurement of the hippocampus classified 87.5% of the control group and 75% of the AD group. In addition, regression models showed superiority of the entorhinal measures over the hippocampal measures in overall classification accuracy. Other

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studies confirmed our early observations regarding the superiority of entorhinal measurement over hippocampus measurement in differentiating persons with mild AD from normal controls (Juottonen et al., 1998; Killiany et al., 2002). Subsequently, studies showed that EC accurately differentiates normal controls from those destined to develop dementia and those destined to develop MCI, as well as differentiating patients with MCI and patients with AD (Dickerson et al., 2001; Du et al., 2001; Killiany et al., 2002; Devanand et al., 2007). Hippocampal volumes may be valuable not only in distinguishing individuals with AD from normal controls but also in identifying individuals with AD neuropathology who have yet to demonstrate dementia or even clinically evident memory impairment. Based on data from the Nun Study, Gosche et al. (2002) showed that hippocampal volumes from postmortem MRI studies distinguished Braak stages III and IV from Braak stages II and below among patients with no dementia. Moreover, among patients who were cognitively intact, the hippocampus distinguished those in Braak stage II from those in stage I or below. The strong correlation between antemortem hippocampal volume and Braak stage (r52.63) was confirmed by another group (Jack et al., 2002). DIFFERENTIAL DIAGNOSIS Magnetic resonance imaging techniques have been used to examine diagnostic specificity of different dementing illnesses. Alzheimer’s disease is the most common cause of late-life dementia, accounting for 70%–80% of cases. Vascular dementia is the second most common cause of dementia, often occurring together with AD and therefore making accurate differential diagnosis between the two difficult. Other causes of dementia include frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB). Although MTL atrophy is found in patients with AD who have FTD, regional patterns differentiate these two disorders. Frisoni and colleagues (1996) demonstrated that frontal atrophy, enlargement of the left temporal horn, and sparing of the MTL region characterized FTD, whereas more severe MTL loss was typical for AD. Comparison of hippocampal and EC volume loss between patients with AD and those with FTD revealed greater extent of hippocampal atrophy in the AD group. Comparison of patients with AD and patients with vascular dementia has shown a consistent pattern of more severe hippocampal atrophy in AD (Barber et al., 2000). No specific pattern of atrophy has been observed in AD as compared to vascular dementia (Barber et al., 2000; O’Brien et al., 2001; Varma et al., 2002). However, hippocampus and EC correctly discriminate between patients with AD and those with subcortical ischemic

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vascular dementia (SIVD). Volume losses of the hippocampus and entorhinal complex are less severe in SIVD than in AD (Du et al., 2002). Hippocampal volume distinguishes 82% of patients with SIVD from normal controls and 63% of patients with SIVD from patients with AD. Adding global cerebral changes to hippocampus substantially improves the classification to 96% between patients with SIVD and normal controls and to 83% between patients with SIVD and those with AD. Entorhinal cortex does not improve the discrimination when added to hippocampus (Du et al., 2002). Larger volumes of the whole temporal lobe, the hippocampus, and amygdala (Barber et al., 2000) and smaller putamen volumes (Cousins et al., 2003) distinguish patients who have DLB from patients with AD. There are no studies comparing MCI with other degenerative diseases; therefore, the ability of MRI to discriminate between AD at the MCI stage and other dementing illnesses remains unanswered. AUTOMATED IMAGE ANALYSIS METHODS Improved MRI resolution has allowed for precise volumetry of individual MTL structures and new techniques, such as voxel-based morphometry (VBM), have facilitated more rapid image analysis (Glodzik-Sobanska et al., 2005). Voxel-based morphometry is an automated method of measuring atrophy of the entire brain. Whereas volumetric studies use the region of interest (ROI) method, which depends upon the expertise of an imaging technician outlining preselected structures in a series of sections on a computer screen, VBM objectively maps gray matter density changes, on a voxelby-voxel basis, in the entire brain. Automated techniques such as VBM have been developed to enable automatic analyses of whole-brain structural MRI scans to avoid shortcomings associated with the ROI method (that is, preselected regions and the inherent difficulties associated with reliance upon inter- and intraindividual variability in placement of ROIs). Voxel-based morphometry has been applied in numerous studies in AD and has been recently applied in individuals with MCI (Rombouts et al., 2000; Baron et al., 2001; Chetelat et al., 2002; Busatto et al., 2003; Pennanen et al., 2005). In addition to “classic” MTL pathology, the VBM method of whole-brain analysis has captured different foci of interest such as posterior cingulate and generally diffuse cerebral atrophy between patients with AD and healthy controls. In what may be the first study to use VBM in individuals with MCI (Chetelat et al., 2002), extensive gray matter loss involving hippocampal and infero-lateral temporal regions was found in MCI relative to age-matched controls with greater gray matter loss found in patients with AD than in patients with MCI in superior and posterior brain,

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primarily involving the posterior polymodal association cortex. Other automated procedures such as brain boundary shift integral (BSI), developed for the assessment of global cerebral atrophy rate was also designed to overcome the problems of intra- and interobserver reliability with manual measurement. This method involves computation of change in whole brain volume using a registration and subtraction of two scans. Summary data with this method, comparing 11 patients with AD and 11 matched healthy controls, demonstrated a median volume reduction of 12.3 mL compared to 0.3 mL for controls. Although the annualized rate of atrophy with this method (< 1%) is less than that for hippocampal volume, it has yielded excellent discrimination between patients with AD and controls. Serial annual MRI scans over a 5- to 8-year period, with subsequent analysis of atrophy rate with BSI, demonstrated that patients who are symptom free and at risk for dementia (from families with early-onset AD) have significantly greater rate of global brain atrophy than controls (1% per year vs. 0.24%) (Fox et al., 2001). The semiautomated method has been shown to be superior to volumetric measurement. A 1% increase in atrophy rate, as measured with hippocampal BSI, was associated with an 11-fold increase in the odds of AD diagnosis, whereas for the same manually measured rate, the odds increased only threefold (Barnes et al., 2004). We recently published longitudinal findings using regional brain boundary shift analysis and spatial coregistration to determine whether rate of medial temporal lobe atrophy over the initial time interval of a 6-year, three time-point longitudinal study is predictive of future memory decline in 45 healthy, elderly patients (Rusinek et al., 2003). After 6 years of observations, 32 patients remained healthy and 13 showed cognitive decline and received a diagnosis of MCI (n = 9) or mild to severe AD (n = 4). MTL atrophy rate, through its interactions with sex and age, was the most significant predictor of decline. The overall accuracy of prediction was 89% (in 40 of 45 patients), with 91% specificity (in 29 of 32 patients) and 85% sensitivity (in 11 of 13 patients). An annual MTL atrophy rate of 0.7% best enabled the separation of patients who were declining from patients who were nondeclining. As per our knowledge, we demonstrated for the first time that increased MTL atrophy rate is predictive of future memory decline in healthy, elderly volunteer patients (Rusinek et al., 2003). Longitudinal studies such as these reveal the importance and time course of increased rates of global and regional atrophy. With longitudinal assessment, the issue of atrophy rate stability arises. In a healthy elderly population, the atrophy rate is low and relatively constant over time, whereas in patients with AD, cerebral atrophy rate is greater and accelerates with disease progression (see Glodzik-Sobanska et al., 2005). As estimated with

BSI, change in whole-brain atrophy rate was 0.31% per year (Chan et al., 2003). New imaging techniques that allow assessment of tissue integrity on a microstructural level (MTI-facilitating indirect assessment of proteins and membranes; diffusion-weighted imaging—reflecting direction and magnitude of water diffusion) may shed light on early, global, and regional changes. These newer approaches have not yet provided enough data to offer diagnostic conclusions, but they have already shown promise in revealing new anatomic damage and better characterization of tissue volume loss. CONCLUSIONS In-vivo techniques not only have shed a new light on the pathogenesis of AD, but they also appear to be of descriptive value over the clinical course of AD and stand ready to contribute to an increased understanding of MCI. The data indicate that visually detected hippocampal changes appear early in the natural history of AD and are progressive. Such changes are relatively uncommon in normal elderly persons. However, when such atrophic changes are present, they are associated with mild memory deficits. The data suggest that in individuals who are mildly impaired, clinically recognizable hippocampal atrophy appears to be related to the AD process, as it predicts with high sensitivity and specificity the decline to AD levels of cognitive performance (de Leon et al., 1989; de Leon et al., 1993). This conclusion is supported in part by postmortem studies that show AD-related pathology in the hippocampal formation of patients with MCI (Price et al., 1991). Moreover, it is universally observed at postmortem examination that hippocampal atrophy occurs in AD. We now extend these observations in vivo by showing a remarkably high frequency of hippocampal atrophy among individuals with probable AD and MCI. The imaging data also show the consistent and necessary involvement of the lateral temporal lobe in the statistical classification of patients with AD relative to patients with MCI. Overall, in patients with no dementia, these findings now permit the identification of brain changes that indicate increased risk for AD. It is anticipated that future therapeutic studies will probably use brain imaging measures as a surrogate markers of cognitive decline, which are relatively free of educational and cultural bias, for selection purposes and as outcome measures.

REFERENCES Amaral, D.G., and Insausti, R. (1990) Hippocampal formation. In: Paxinos, G., ed. The Human Nervous System. San Diego, CA: Academic Press, pp. 711–755.

57: HIPPOCAMPUS IN AGING AND ALZHEIMER’S DISEASE Amaral, D.G., Insausti, R., and Cowan, W.M. (1987) The entorhinal cortex of the monkey: I. Cytoarchitectonic organization. J. Comp. Neurol. 264:326–355. Apostolova, L.G., Dinov, I.D., Dutton, R.A., Hayashi, K.M., Toga, A.W., Cummings, J.L., and Thompson, P.M. (2006) 3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer’s disease. Brain 129:2867–2873. Apostolova, L.G., Dutton, R.A., Dinov, I.D., Hayashi, K.M., Toga, A.W., Cummings, J.L., and Thompson, P.M. (2006) Conversion of mild cognitive impairment to Alzheimer disease predicted by hippocampal atrophy maps. Arch. Neurol. 63:693–699. Arriagada, P.V., Marzloff, K., and Hyman, B.T. (1992) Distribution of Alzheimer-type pathologic changes in nondemented elderly individuals matches the pattern in Alzheimer’s disease. Neurology 42:1681–1688. Aylward, E.H., Rasmusson, D.X., Brandt, J., Raimundo, L., Folstein, M., and Pearlson, G.D. (1996) CT measurement of suprasellar cistern predicts rate of cognitive decline in Alzheimer’s disease. J. Int. Neuropsychol. Soc. 2:89–95. Ball, M.J., Hachinski, V., Fox, A., Kirshen, A.J., Fisman, M., Blume, W., Kral, V.A., and Fox, H. (1985) A new definition of Alzheimer’s disease: a hippocampal dementia. Lancet 5:14–16. Barber, R., Ballard, C., McKeith, I.G., Gholkar, A., and O’Brien, J.T. (2000) MRI volumetric study of dementia with Lewy bodies: a comparison with AD and vascular dementia. Neurology 54: 1304–1309. Barnes, J., Scahill, R.I., Boyes, R.G., Frost, C., Lewis, E.B., Rossor, C.L., Rossor, M.N., and Fox, N.C. (2004) Differentiating AD from aging using semiautomated measurement of hippocampal atrophy rates. Neuroimage 23:574–581. Baron, J.C., Chetelat, G., Desgranges, B., Perchey, G., Landeau, B., de la Sayette, V., and Eustache, F. (2001) In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer’s disease. Neuroimage 14:298–309. Blacker, D., Lee, H., Muzikansky, A., Martin, E.C., Tanzi, R., McArdle, J.J., Moss, M., and Albert, M. (2007) Neuropsychological measures in normal individuals that predict subsequent cognitive decline. Arch. Neurol. 64:862–871. Bobinski, M., de Leon, M.J., Convit, A., De Santi, S., Wegiel, J., Tarshish, C.Y., Saint-Louis, L.A., and Wisniewski, H.H. (1999) MRI of entorhinal cortex in mild Alzheimer’s disease. Lancet 353:38–40. Bobinski, M., de Leon, M.J., Wegiel, J., De Santi, S., Convit, A., Saint Louis, L.A., Rusinek, H., and Wisniewski, H.M. (2000) The histological validation of postmortem magnetic resonance imaging-determined hippocampal volume in Alzheimer’s disease. Neuroscience 95:721–725. Bobinski, M., Wegiel, J., Tarnawski, M., Reisberg, B., de Leon, M.J., Miller, D.C., and Wisniewski, H.M. (1997) Relationships between regional neuronal loss and neurofibrillary changes in the hippocampal formation and duration and severity of Alzheimer’s disease. J. Neuropathol. Exp. Neurol. 56:414–420. Bobinski, M.J., Wegiel, J., Wisniewski, H.M., Tarnawski, B., Bobinski, M., Reisberg, B., de Leon, M.J., and Miller, D.C. (1996) Neurofibrillary pathology—correlation with hippocampal formation atrophy in Alzheimer disease. Neurobiol. Aging 17: 909–919. Bobinski, M., Wegiel, J., Wisniewski, H.M., Tarnawski, M., Reisberg, B., Mlodzik, B., de Leon, M.J., and Miller, D.C. (1995) Atrophy of hippocampal formation subdivisions correlates with stage and duration of Alzheimer disease. Dementia 6:205–210. Bouras, C., Hof, P.R., Giannakopoulos, P., Michel, J.P., and Morrison, J.H. (1994) Regional distribution of neurofibrillary tangles and senile plaques in the cerebral cortex of elderly patients: a quantitative evaluation of a one-year autopsy population from a geriatric hospital. Cereb. Cortex 4:138–150. Braak, H. (1972) Zur pigmentoarchitektonic der Grosshirnrinde des Menschen [ ]. I. Regio entorhinalis. Z. Zellforsch. 127:407–438.

953

Braak, H. (1980) Architectonics of the Human Telencephalic Cortex. Berlin: Springer-Verlag. Braak, H., and Braak, E. (1991) Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 82:239–259. Braak, H., and Braak, E. (1997) Diagnostic criteria for neuropathologic assessment of Alzheimer’s disease. Neurobiol. Aging 18: S85–S88. Brodmann, K. (1909) Vergleichende lokalisationslehre der grosshirnrinde in ihren prinzipien dargestellt auf grund des zellenbaues [ ]. Leipzig, Germany: Barth. Broe, M., Shepherd, C.E., Milward, E.A., and Halliday, G.M. (2001) Relationship between DNA fragmentation, morphological changes and neuronal loss in Alzheimer’s disease and dementia with Lewy bodies. Acta Neuropathol. 101:616–624. Busatto, G.F., Garrido, G.E., Almeida, O.P., Castro, C.C., Camargo, C.H., Cid, C.G., Buchpiguel, C.A., Furuie, S., and Bottino, C.M. (2003) A voxel-based morphometry study of temporal lobe gray matter reductions in Alzheimer’s disease. Neurobiol. Aging 24: 221–231. Chan, D., Janssen, J.C., Whitwell, J.L., Watt, H.C., Jenkins, R., Frost, C., Rossor, M.N., and Fox, N.C. (2003) Change in rates of cerebral atrophy over time in early-onset Alzheimer’s disease: longitudinal MRI study. Lancet 362:1121–1122. Chetelat, G., Desgranges, B., De La Sayette, V., Viader, F., Eustache, F., and Baron, J.C. (2002) Mapping gray matter loss with voxelbased morphometry in mild cognitive impairment. Neuroreport 13:1939–1943. Clark, R.F., and Goate, A.M. (1993) Molecular genetics of Alzheimer’s disease. Arch. Neurol. 50:1164–1172. Colsher, P.L., and Wallace, R.B. (1991) Longitudinal application of cognitive function measures in a defined population of community-dwelling elders. Ann. Epidemiol. 1:215–230. Convit, A., de Leon, M.J., Golomb, J., George, A.E., Tarshish, C.Y., Bobinski, M., Tsui, W., De Santi, S., Wegiel, J., and Wisniewski, H.M. (1993) Hippocampal atrophy in early Alzheimer’s disease: anatomic specificity and validation. Psychiatr. Q. 64:371–387. Convit, A., de Leon, M.J., Hoptman, M.J., Tarshish, C., De Santi, S., and Rusinek, H. (1995) Age-related changes in brain. I. Magnetic resonance imaging measure of temporal lobe volumes in normal subjects. Psychiatr. Q. 66:343–355. Convit, A., de Leon, M.J., Tarshish, C., De Santi, S., Kluger, A., Rusinek, H., and George, A. (1995) Hippocampal volume losses in minimally impaired elderly. Lancet 345:266. Convit, A., de Leon, M.J., Tarshish, C., De Santi, S., Tsui, W., Rusinek, H., and George, A.E. (1997) Specific hippocampal volume reductions in individuals at risk for Alzheimer’s disease. Neurobiol. Aging 18:131–138. Convit, A., McHugh, P.R., Wolf, O.T., de Leon, M.J., Bobinski, M., De Santi, S., Roche, A., and Tsui, W. (1999) MRI volume of the amygdala: a reliable method allowing separation from the hippocampal formation. Psychiatry Res. Neuroimag. 90:113–123. Corder, E.H., Saunders, A.M., Strittmatter, W.J., Schmechel, D.E., Gaskell, P.C., Small, G.W., Roses, A.D., Haines, J.L., and Pericak-Vance, M.A. (1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261:921–923. Cousins, D.A., Burton, E.J., Burn, D., Gholkar, A., McKeith, I.G., and O’Brien, J.T. (2003) Atrophy of the putamen in dementia with Lewy bodies but not Alzheimer’s disease: an MRI study. Neurology 61:1191–1195. Davies, D.V., Horwood, N., Isaacs, S.L., and Mann, D.M.A. (1992) The effect of age and Alzheimer’s disease on pyramidal neuron density in the individual fields of the hippocampal formation. Acta Neuropathol. 83:510–517. de la Monte, S.M. (1989) Quantitation of cerebral atrophy in preclinical and end-stage Alzheimer’s disease. Ann. Neurol. 25:450– 459.

954

DEMENTIA

de la Monte, S.M., Sohn, Y.K., Ganju, N., and Wands, J.R. (1998) P53- and CD95-associated apoptosis in neurodegenerative diseases. Lab. Invest. 78:401–411. de Leon, M.J., Convit, A., Wolf, O.T., Tarshish, C.Y., De Santi, S., Rusinek, H., Tsui, W., Kandil, E., Scherer, A.J., Roche, A., Imossi, A., Thorn, E., Bobinski, M., Caraos, C., Lesbre, P., Schlyer, D., Poirier, J., Reisberg, B., and Fowler, J. (2001) Prediction of cognitive decline in normal elderly subjects with 2-(18F)fluoro-2deoxy-D-glucose/positron-emission tomography (FDG/PET). Proc. Natl. Acad. Sci. USA 98:10966–10971. de Leon, M., deSanti, S., Zinkowski, R., Mehta, P., Pratico, D., Segal, S., Clark, C., Kerkman, D. D., Debernardi, J., Li, J., Lair, L., Reisber, B., and Tsui, W. (2004) MRI and CSF studies in the early diagnosis of Alzheimer’s disease. J. Inter. Med. 256:205–223. de Leon, M.J., George, A.E., Convit, A., De Santi, S., Golomb, J., Tarshish, C., Rusinek, H., Ferris, S.H., Bobinski, M., and Arena, L. (1994) MR measurement of the medial temporal lobe changes in Alzheimer disease: The case for the interuncal distance. Am. J. Neuroradiol. 15:1286–1290. de Leon, M.J., George, A.E., Ferris, S.H., Christman, D.R., Fowler, J.S., Gentes, C., Brodie, J., Resiberg, B., and Wolf, A.P. (1984) Positron emission tomography and computed tomography assessments of the aging human brain. J. Comput. Assist. Tomogr. 8:88–94. de Leon, M.J., George, A.E., Golomb, J., Tarshish, C., Convit, A., Kluger, A., De Santi, S., McRae, T., Ferris, S.H., Reisberg, B., Ince, C., Rusinek, H., Bobinski, M., Quinn, B., Miller, D.C., and Wisniewski, H.M. (1997) Frequency of hippocampal formation atrophy in normal aging and Alzheimer’s disease. Neurobiol. Aging 18:1–11. de Leon, M., Mosconi, L., Blennow, S., DeSanti, S., Zinkowski, R., Mehta, P., Pratico, D., Tsui, W., Saint Louis, L., Sobanska, L., Brys, M., Li, Y., Rich, K., Rinne, J., and Rusinek, H. (2007) Imaging and CSF studies in the preclinical diagnosis of Alzheimer’s disease. Ann. N. Y. Acad. Sci. 1097:114–145. de Leon, M.J., George, A.E., Stylopoulos, L.A., Smith, G., and Miller, D.C. (1989) Early marker for Alzheimer’s disease: the atrophic hippocampus. Lancet 2:672–673. de Leon, M.J., Golomb, J., George, A.E., Convit, A., Tarshish, C.Y., McRae, T., De Santi, S., Smith, G., Ferris, S.H., Noz, M., and Rusinek, H. (1993) The radiologic prediction of Alzheimer’s disease: the atrophic hippocampal formation. Am. J. Neuroradiol. 14:897–906. de Leon, M.J., McRae, T., Tsai, J.R., George, A.E., Marcus, D.L., Freedman, M., Wolf, A.P., and McEwen, B. (1988) Abnormal cortisol response in Alzheimer’s disease linked to hippocampal atrophy. Lancet 2:391–392. den Heijer, T., Geerlings, M.I., Hoebeek, F.E., Hofman, A., Koudstaal, P.J., and Breteler, M.M. (2006) Use of hippocampal and amygdalar volumes on magnetic resonance imaging to predict dementia in cognitively intact elderly people. Arch. Gen. Psychiatry 63: 57–62. De Santi, S., de Leon, M.J., Rusinek, H., Convit, A., Tarshish, C.Y., Boppana, M., Tsui, W.H., Daisley, K., Wang, G.J., and Schlyer, D. (2001) Hippocampal formation glucose metabolism and volume losses in MCI and AD. Neurobiol. Aging 22:529–539. Devanand, D.P., Pradhaban, G., Liu, X., Khandji, A., De Santi, S., Segal, S., Rusinek, H., Pelton, G.H., Honig, L.S., Mayeux, R., Stern, Y., Tabert, M.H., and de Leon, M.J. (2007) Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease. Neurology 68:828–836. Dickerson, B.C., Goncharova, I., Sullivan, M.P., Forchetti, C., Wilson, R.S., Bennett, D.A., Beckett, L.A., and Detoledo-Morrell, L. (2001) MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease. Neurobiol. Aging 22: 747–754.

Du, A.T., Schuff, N., Amend, D., Laaskso, M.P., Hsu, Y.Y., Jagust, W.J., Yaffe, K., Kramer, J.H., Reed, B., Norman, D., Chui, H.C., and Weiner, M.W. (2001) Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 71: 441–447. Du, A.T., Schuff, N., Laakso, M.P., Zhu, X.P., Jagust, W.J., Yaffe, K., Kramer, J.H., Miller, B.L., Reed, B.R., Norman, D., Chui, H.C., and Weiner, M.W. (2002) Effects of subcortical ischemic vascular dementia and AD on entorhinal cortex and hippocampus. Neurology 58:1635–1641. Duvernoy, H.M. (1988) The Human Hippocampus: An Atlas of Applied Anatomy. Munich, Germany: J.F. Bergmann Verlag. Fox, N.C., Crum, W.R., Scahill, R.I., Stevens, J.M., Janssen, J.C., and Rossor, M.N. (2001) Imaging of onset and progression of Alzheimer’s disease with voxel-compression mapping of serial magnetic resonance images. Lancet 358:201–205. Fox, N.C., Scahill, R.I., Crum, W.R., and Rossor, M.N. (1999) Correlation between rates of brain atrophy and cognitive decline in AD. Neurology 52:1687–1689. Frisoni, G.B., Beltramello, A., Geroldi, C., Weiss, C., Bianchetti, A., and Trabucchi, M. (1996) Brain atrophy in frontotemporal dementia. J. Neurol. Neurosurg. Psychiatry 61:157–165. Frisoni, G.B., Sabattoli, F., Lee, A.D., Dutton, R.A., Toga, A.W., and Thompson, P.M. (2006) In vivo neuropathology of the hippocampal formation in AD: a radial mapping MR-based study. Neuroimage 32:104–110. Ganguli, M., Dodge, H.H., Shen, C., and DeKosky, S.T. (2004) Mild cognitive impairment, amnestic type: an epidemiologic study. Neurology 63:115–121. Giannakopoulos, P., Herrmann, F.R., Bussiere, T., Bouras, C., Kovari, E., Perl, D.P., Morrison, J.H., Gold, G., and Hof, P.R. (2003) Tangle and neuron numbers, but not amyloid load, predict cognitive status in Alzheimer’s disease. Neurology 60:1495–1500. Giannakopoulos, P., Hof, P.R., Mottier, S., Michel, J.P., and Bouras, C. (1994) Neuropathological changes in the cerebral cortex of 1258 cases from a geriatric hospital: retrospective clinicopathological evaluation of a 10-year autopsy population. Acta Neuropathol. 87:456–468. Glodzik-Sobanska, L., Rusinek, H., Mosconi, L., Li, Y., Zhan, J., De Santi, S., Convit, A., Rich, K.E., Brys, M., and de Leon, M.J. (2005) The role of quantitative structural imaging in the early diagnosis of Alzheimer’s disease. Neuroimaging Clin. N. Am. 15: 803–826. Golomb, J., Kluger, A., de Leon, M.J., Ferris, S.H., Convit, A., Mittelman, M.S., Cohen, J., Rusinek, H., De Santi, S., and George, A. (1994) Hippocampal formation size in normal human aging: a correlate of delayed secondary memory performance. Learn. Mem. 1:45–54. Golomb, J., Kluger, A., de Leon, M.J., Ferris, S.H., Mittelman, M.S., Cohen, J., and George, A.E. (1996) Hippocampal formation size predicts declining memory performance in normal aging. Neurology 47:810–813. Gomez-Isla, T., Hollister, R., West, H., Mui, S., Growdon, J.H., Petersen, R.C., Parisi, J.E., and Hyman, B.T. (1997) Neuronal loss correlates with but exceeds neurofibrillary tangles in Alzheimer’s disease. Ann. Neurol. 41:17–24. Gomez-Isla, T., Price, J.L., McKeel, D.W., Jr., Morris, J.C., Growdon, J.H., and Hyman, B.T. (1996) Profound loss of layer II entorhinal cortex neurons occurs in very mild Alzheimer’s disease. J. Neurosci. 16:4491–4500. Goncharova, I.I., Dickerson, B.C., Stoub, T.R., and Detoledo-Morrell, L. (2001) MRI of human entorhinal cortex: a reliable protocol for volumetric measurement. Neurobiol. Aging 22:737–745. Gosche, K.M., Mortimer, J.A., Smith, C.D., Markesbery, W.R., and Snowdon, D.A. (2002) Hippocampal volume as an index of

57: HIPPOCAMPUS IN AGING AND ALZHEIMER’S DISEASE Alzheimer neuropathology: findings from the Nun Study. Neurology 58:1476–1482. Hebert, L.E., Scherr, P.A., Bienias, J.L., Bennett, D.A., and Evans, D.A. (2003) Alzheimer disease in the US population: prevalence estimates using the 2000 census. Arch. Neurol. 60:11119–11122. Hirano, A., and Zimmerman, H.M. (1962) Alzheimer’s neurofibrillary changes. Arch. Neurol. 7:227–242. Hof, P.R., Bierer, L.M., Perl, D.P., Delacourte, A., Buee, L., Bouras, C., and Morrison, J.H. (1992) Evidence for early vulnerability of the medial and inferior aspects of the temporal lobe in an 82year-old patient with preclinical signs of dementia: regional and laminar distribution of neurofibrillary tangles and senile plaques. Arch. Neurol. 49:946–953. Hubbard, B.M., Fenton, G.W., and Anderson, J.M. (1990) A quantitative histological study of early clinical and preclinical Alzheimer’s disease. Neuropathol. Appl. Neurobiol. 16:111–121. Hyman, B.T., Van Hoesen, G.W., Damasio, A.R., and Barnes, C.L. (1984) Alzheimer’s disease: cell-specific pathology isolates the hippocampal formation. Science 225:1168–1170. Ikeda, M., Tanabe, H., Nakagawa, Y., Kazui, H., Oi, H., Yamazaki, H., Harada, K., and Nishimura, T. (1994) MRI-based quantitative assessment of the hippocampal region in very mild to moderate Alzheimer’s disease. Neuroradiology 36:7–10. Insausti, R., Amaral, D.G., and Cowan, W.M. (1987) The entorhinal cortex of the monkey: III. Subcortical afferents. J. Comp. Neurol. 264:396–408. Insausti, R., Juottonen, K., Soininen, H., Insausti, A.M., Partanen, K., Vainio, P., Laakso, M.P., and Pitkanen, A. (1998) MR volumetric analysis of the human entorhinal, perirhinal, and temporopolar cortices. Am. J. Neuroradiol. 19:659–671. Insausti, R., Tunon, T., Sobreviela, T., Insausti, A.M., and Gonzalo, L.M. (1995) The human entorhinal cortex: a cytoarchitectonic analysis. J. Comp. Neurol. 355:171–198. Jack, C.R., Dickson, D.W., Parisi, J.E., Xu, Y.C., Cha, R.H., O’Brien, P.C., Edland, S.D., Smith, G.E., Boeve, B.F., et al. (2002) Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology 58:750–757. Jack, C.R., Petersen, R.C., O’Brien, P.C., and Tangalos, E.G. (1992) MR-based hippocampal volumetry in the diagnosis of Alzheimer’s disease. Neurology 42:183–188. Jack, C.R., Petersen, R.C., Xu, Y., O’Brien, P.C., Smith, G.E., and Ivnik, R.J. (2000) Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology 55: 484–489. Jack, C.R., Jr., Petersen, R.C., Xu, Y., O’Brien, P.C., Smith, G.E., Ivnik, R.J., Boeve, B.F., Tangalos, E.G., and Kokmen, E. (2000) Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology 55:484–489. Jack, C.R., Petersen, R.C., Xu, Y.C., O’Brien, P.C., Smith, G.E., Ivnik, R.J., Boeve, B.F., Waring, S.C., Tangalos, E.G., and Kokmen, E. (1999) Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 52:1397–1403. Jack, C.R., Petersen, R.C., Xu, Y.C., Waring, S.C., O’Brien, P.C., Tangalos, E.G., Smith, G.E., Ivnik, R.J., and Kokmen, E. (1997) Medial temporal atrophy on MRI in normal aging and very mild Alzheimer’s disease. Neurology 49:786–794. Jack, C. R., Jr., Shiung, M.M., Gunter, J.L., O’Brien, P.C., Weigand, S.D., Knopman, D.S., Boeve, B.F., Ivnik, R.J., Smith, G.E., Cha, R.H., Tangalos, E.G., and Petersen, R.C. (2004) Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology 62:591–600. Jack, C.R., Jr., Shiung, M.M., Weigand, S.D., O’Brien, P.C., Gunter, J.L., Boeve, B.F., Knopman, D.S., Smith, G.E., Ivnik, R.J., Tangalos, E.G., and Petersen, R.C. (2005) Brain atrophy rates predict subsequent clinical conversion in normal elderly and amnestic MCI. Neurology 65:1227–1231.

955

Jobst, K.A., Smith, A.D., Szatmari, M., Esiri, M.M., Jaskowski, A., Hindley, N., McDonald, B., and Molyneux, A.J. (1994) Rapidly progressing atrophy of medial temporal lobe in Alzheimer’s disease. Lancet 343:829–830. Juottonen, K., Laakso, M.P., Insausti, R., Lehtovirta, M., Pitkanen, A., Partanen, K., and Soininen, H. (1998) Volumes of the entorhinal and perirhinal cortices in Alzheimer’s disease. Neurobiol. Aging 19:15–22. Kaye, J.A., Swihart, T., Howieson, D., Dame, A., Moore, M.M., Karnos, T., Camicioli, R., Ball, M., Oken, B., and Sexton, G. (1997) Volume loss of the hippocampus and temporal lobe in healthy elderly persons destined to develop dementia. Neurology 48:1297–1304. Kemper, T.L. (1978) Senile dementia: a focal disease in the temporal lobe. In: Nandy, E., ed. Senile Dementia: A Biomedical Approach. New York: Elsevier, pp. 105–113. Kesslak, J.P., Nalcioglu, O., and Cotman, C.W. (1991) Quantification of magnetic resonance scans for hippocampal and parahippocampal atrophy in Alzheimer’s disease. Neurology 41:51–54. Killiany, R.J., Gomez-Isla, T., Moss, M., Kikinis, R., Sandor, T., Jolesz, F., Tanzi, R., Jones, K., Hyman, B., and Albert, M.S. (2000) Use of structural magnetic resonance imaging to predict who will get Alzheimer’s disease. Ann. Neurol. 47:430–439. Killiany, R.J., Hyman, B.T., Gomez-Isla, T., Moss, M.B., Kikinis, R., Jolesz, F., Tanzi, R., Jones, K., and Albert, M.S. (2002) MRI measures of entorhinal cortex vs. hippocampus in preclinical AD. Neurology 58:1188–1196. Kluger, A., Ferris, S.H., Golomb, J., Mittelman, M.S., and Reisberg, B. (1999) Neuropsychological prediction of decline to dementia in nondemented elderly. J. Geriatr. Psychiatr. Neurol. 12:168–179. Knopman, D.S., Parisi, Salviati, A., Floriach-Robert, M., Boeve, B.F., Ivnik, R.J., Smith, G.E., Dickson, D.W., Johnson, K.A., Petersen, L.E., McDonald, W.C., Braak, H., and Petersen, R.C. (2003) Neuropathology of cognitively normal elderly. J. Neuropathol. Exp. Neurol. 62:1087–1095. Kril, J.J., Patel, S., Harding, A.J., and Halliday, G.M. (2002) Neuron loss from the hippocampus of Alzheimer’s disease exceeds extracellular neurofibrillary tangle formation. Acta Neuropathol. 103:370–376. Laakso, M.P., Soininen, H., Partanen, K., Lehtovirta, M., Hallikainen, M., Hanninen, T., Helkala, E.-L., Vainio, P., and Riekkinen, P.J., Sr. (1998) MRI of the hippocampus in Alzheimer’s disease: sensitivity, specificity, and analysis of the incorrectly classified subjects. Neurobiol. Aging 19:23–31. Langui, D., Probst, A., and Ulrich, J. (1995) Alzheimer’s changes in non-demented and demented patients: a statistical approach to their relationships. Acta Neuropathol. 89:57–62. Larrabee, G.J., and Crook, T.H. (1994) Estimated prevalence of ageassociated memory impairment derived from standardized tests of memory function. Int. Psychogeriat. 6:95–104. Lehericy, S., Baulac, M., Chiras, J., Pierot, L., Martin, N., Pillon, B., Deweer, B., Dubois, B., and Marsault, C. (1994) Amygdalohippocampal MR volume measurements in the early stages of Alzheimer disease. Am. J. Neuroradiol. 15:929–937. Manly, J.J., Bell-McGinty, S., Tang, M.X., Schupf, N., Stern, Y., and Mayeux, R. (2005) Implementing diagnostic criteria and estimating frequency of mild cognitive impairment in an urban community. Arch. Neurol. 62:1739–1746. Mann, D.M.A., and Esiri, M.M. (1989) The pattern of acquisition of plaques and tangles in the brains of patients under 50 years of age with Down syndrome. J. Neurol. Sci. 89:169–179. McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., and Stadlan, E.M. (1984) Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA work group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology 34:939–944.

956

DEMENTIA

Mesulam, M.M. (1990) Large-scale neurocognitive networks and distributed processing for attention, language, and memory. Neurol. Prog. 28(5):597–613. Mishkin, M. (1978) Memory in monkeys severely impaired by combined but not by separate removal of amygdala and hippocampus. Nature 273:297–298. Mori, E., Lee, K., Yasuda, M., Hashimoto, M., Kazui, H., Hirono, N., and Matsui, M. (2002) Accelerated hippocampal atrophy in Alzheimer’s disease with apolipoprotein E epsilon4 allele. Ann. Neurol. 51:209–214. Morris, J.C., McKeel, D.W., Storandt, M., Rubin, E.H., Price, J.L., Grant, E.A., Ball, M.J., and Berg, L. (1991) Very mild Alzheimer’s disease: informant-based clinical, psychometric, and pathological distinction from normal aging. Neurology 41:469–478. Mosconi, L. (2005) Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur. J. Nucl. Med. Mol. Imaging 32:486–510. Mosconi, L., Brys, M., Glodzik-Sobanska, L., De Santi, S., Rusinek, H., and de Leon, M.J. (2007) Early detection of Alzheimer’s disease using neuroimaging. Exp. Gerontol. 42:129–138. Mosconi, L., De Santi, S., Rusinek, H., Convit, A., and de Leon, M.J. (2004) Magnetic resonance and PET studies in the early diagnosis of Alzheimer’s disease. Expert Rev. Neurother. 4:831– 849. Mosconi, L., Tsui, W.H., Pupi, A., De Santi, S., Drzezga, A., Minoshima, S., and de Leon, M.J. (2007) (18)F-FDG PET database of longitudinally confirmed healthy elderly individuals improves detection of mild cognitive impairment and Alzheimer’s disease. J. Nucl. Med. 48:1129–1134. Moss, M., Mahut, H., and Zola-Morgan, S. (1981) Concurrent discrimination learning of monkeys after hippocampal, entorhinal, or fornix lesions. J. Neurosci. 3:227–240. Mu, Q., Xie, J., Wen, Z., Weng, Y., and Shuyun, Z. (1999) A quantitative MR study of the hippocampal formation, the amygdala, and the temporal horn of the lateral ventricle in healthy subjects 40 to 90 years of age. Am. J. Neuroradiol. 20:207–211. Mungas, D., Harvey, D., Reed, B.R., Jagust, W.J., DeCarli, C., Beckett, L., Mack, W.J., Kramer, J.H., Weiner, M.W., Schuff, N., and Chui, H.C. (2005) Longitudinal volumetric MRI change and rate of cognitive decline. Neurology 65:565–571. O’Brien, J.T., Paling, S., Barber, R., Williams, E.D., Ballard, C., McKeith, I.G., Gholkar, A., Crum, W.R., Rossor, M.N., and Fox, N.C. (2001) Progressive brain atrophy on serial MRI in dementia with Lewy bodies, AD, and vascular dementia. Neurology 56:1386–1388. Paykel, E.S., Brayne, C., Huppert, F.A., Gill, C., Barkley, C., Gehlhaar, E., Beardsall, L., Girling, D.M., Pollitt, P., and O’Connor, D. (1994) Incidence of dementia in a population older than 75 years in the United Kingdom. Arch. Gen. Psychiatry 51:325–332. Pennanen, C., Kivipelto, M., Tuomainen, S., Hartikainen, P., Hanninen, T., Laakso, M.P., Hallikainen, M., Vanhanen, M., Nissinen, A., Helkala, E.L., Vainio, P., Vanninen, R., Partanen, K., and Soininen, H. (2004) Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol. Aging 25:303–310. Pennanen, C., Testa, C., Laakso, M.P., Hallikainen, M., Helkala, E. L., Hanninen, T., Kivipelto, M., Kononen, M., Nissinen, A., Tervo, S., Vanhanen, M., Vanninen, R., Frisoni, G.B., and Soininen, H. (2005) A voxel based morphometry study on mild cognitive impairment. J. Neurol. Neurosurg. Psychiatry 76:11–14. Petrella, J.R., Coleman, R.E., and Doraiswamy, P.M. (2003) Neuroimaging and early diagnosis of Alzheimer disease: a look to the future. Radiology 226:315–336. Press, G.A., Amaral, D.G., and Squire, L.R. (1989) Hippocampal abnormalities in amnesic patients revealed by high-resolution magnetic resonance imaging. Nature 341:54–57. Price, J.L., Davis, P.B., Morris, J.C., and White, D.L. (1991) The distribution of tangles, plaques and related immunohistochemi-

cal markers in healthy aging and Alzheimer’s disease. Neurobiol. Aging 12:295–312. Price, J.L., Ko, A.I., Wade, M.J., Tsou, S.K., McKeel, D.W., and Morris, J.C. (2001) Neuron number in the entorhinal cortex and CA1 in preclinical Alzheimer disease. Arch. Neurol. 58:1395–1402. Reisberg, B., Ferris, S.H., de Leon, M.J., and Crook, T. (1982) The global deterioration scale for assessment of primary degenerative dementia. Am. J. Psychiatry 139:1136–1139. Rombouts, S.A., Barkhof, F., Witter, M.P., and Scheltens, P. (2000) Unbiased whole-brain analysis of gray matter loss in Alzheimer’s disease. Neurosci. Lett. 285:231–233. Rose, M. (1927) Die sog, Riechrinde beim Menschen und beim Affem. II. Teil des “Allocortex bei Tier und Mensch” [ ]. J. Psychol. Neurol. 34:261–401. Rosene, D.L., and Van Hoesen, G.W. (1987) The hippocampal formation of the primate brain: a review of some comparative aspects of cytoarchitecture and connections. In: Jones, E.G. and Peters, A., eds. Cerebral Cortex. New York: Plenum Press, pp. 345–456. Rossler, M., Zarski, R., Bohl, J., and Ohm, T.G. (2002) Stagedependent and sector-specific neuronal loss in hippocampus during Alzheimer’s disease. Acta Neuropathol. 103:363–369. Rusinek, H., De Santi, S., Frid, D., Tsui, W., Tarshish, C., Convit, A., et al. (2003) Regional brain atrophy rate predicts future cognitive decline: 6-year longitudinal MR imaging study of normal aging. Radiology 229:691–696. Rusinek, H., Endo, Y., De Santi, S., Frid, D., Tsui, W.H., Segal, S., Convit, A., and de Leon, M.J. (2004) Atrophy rate in medial temporal lobe during progression of Alzheimer disease. Neurology 63:2354–2359. Scheff, S.W., Price, D.A., Schmitt, F.A., DeKosky, S.T., and Mufson, E.J. (2007) Synaptic alterations in CA1 in mild Alzheimer disease and mild cognitive impairment. Neurology 68:1501–1508. Scheltens, P., Leys, D., Barkhof, F., Huglo, D., Weinstein, H.C., Vermersch, P., Kuiper, M., Steinling, M., Wolters, E.C., and Valk, J. (1992) Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal aging: diagnostic value and neuropsychological correlates. J. Neurol. Neurosurg. Psychiatry 55:967–972. Schoenberg, B.S. (1986) Epidemiology of Alzheimer’s disease and other dementing disorders. J. Chronic Dis. 39:1095–1104. Schonheit, B., Zarski, R., and Ohm, T. G. (2004) Spatial and temporal relationships between plaques and tangles in Alzheimerpathology. Neurobiol. Aging 25:697–711. Schott, J.M., Fox, N.C., Frost, C., Scahill, R.I., Janssen, J.C., Chan, D., Jenkins, R., and Rossor, M.N. (2003) Assessing the onset of structural change in familial Alzheimer’s disease. Ann. Neurol. 53:181–188. Seab, J.P., Jagust, W.S., Wang, S.F.S., Roos, M.S., Reed, B.R., and Budinger, T.F. (1988) Quantitative NMR measurements of hippocampal atrophy in Alzheimer’s disease. Magn. Reson. Med. 8:200–208. Small, S.A., Tsai, W.Y., DeLaPaz, R., Mayeux, R., and Stern, Y. (2002) Imaging hippocampal function across the human life span: is memory decline normal or not? Ann. Neurol. 51:290–295. Squire, L.R. (1992) Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans. Psychol. Rev. 99: 195–231. Stout, J.C., Jernigan, T.L., Archibald, S.L., and Salmon, D.P. (1996) Association of dementia severity with cortical gray matter and abnormal white matter volume in dementia of Alzheimer type. Arch. Neurol. 53:742–749. Suzuki, W.A., and Amaral, D.G. (1994) Perirhinal and parahippocampal cortices of the macaque monkey: cortical afferents. J. Comp. Neurol. 350:497–533. Thal, D.R., Holzer, M., Rub, U., Waldmann, G., Gunzel, S., Zedlick, D., and Schober, R. (2000) Alzheimer-related tau-pathology in the perforant path target zone and in the hippocampal stratum

57: HIPPOCAMPUS IN AGING AND ALZHEIMER’S DISEASE oriens and radiatum correlates with onset and degree of dementia. Exp. Neurol. 163:98–110. Thompson, L.K. (2003) Unraveling the secrets of Alzheimer’s betaamyloid fibrils. Proc. Natl. Acad. Sci. USA, 100:383–385. Twamley, E.W., Ropacki, S.A., and Bondi, M.W. (2006) Neuropsychological and neuroimaging changes in preclinical Alzheimer’s disease. J. Int. Neuropsychol. Soc. 12:707–735. Ulrich, J. (1985) Alzheimer changes in nondemented patients younger than sixty-five: possible early stages of Alzheimer’s disease and senile dementia of Alzheimer type. Ann. Neurol. 17:273–277. van de Pol, L.A., van der Flier, W.M., Korf, E.S., Fox, N.C., Barkhof, F., and Scheltens, P. (2007) Baseline predictors of rates of hippocampal atrophy in mild cognitive impairment. Neurology 69: 1491–1497. Van Hoesen, G.W. (1982) The parahippocampal gyrus: new observations regarding its cortical connections in the monkey. Trends Neurosci. 5:345–350. Varma, A.R., Adams, W., Lloyd, J.J., Carson, K.J., Snowden, J.S., Testa, H.J., Jackson, A., and Neary, D. (2002) Diagnostic patterns of regional atrophy on MRI and regional cerebral blood flow change on SPECT in young onset patients with Alzheimer’s disease, frontotemporal dementia and vascular dementia. Acta Neurol. Scand. 105:261–269. Vogt, C., and Vogt, O. (1919) Allgemeinere Ergebnisse unserer Hirnforschung [ ]. J. Psychol. Neurol. 25:279–462. Welsh, K., Butters, N., Hughes, J., Mohs, R., and Heyman, A. (1991) Detection of abnormal memory decline in mild cases of

957

Alzheimer’s disease using CERAD neuropsychological measures. Arch. Neurol. 48:278–281. West, M.J., Coleman, P.D., Flood, D.G., and Troncoso, J.C. (1994) Differences in the pattern of hippocampal neuronal loss in normal ageing and Alzheimer’s disease. Lancet 344:769–772. Witter, M.P., and Amaral, D.G. (1991) Entorhinal cortex of the monkey: V. Projections to the dentate gyrus, hippocampus, and subicular complex. J. Comp. Neurol. 307:437–459. Xu, Y., Jack, C.R., O’Brien, P.C., Kokmen, E., Smith, G.E., Ivnik, R.J., Boeve, B.F., Tangalos, R.G., and Petersen, R.C. (2000) Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD. Neurology 54:1760–1767. Zola-Morgan, S., and Squire, L.R. (1986) Memory impairment in monkeys following lesions limited to the hippocampus. Behav. Neurosci. 2:155–160. Zola-Morgan, S., Squire, L.R., and Amaral, D.G. (1989) Lesions of the amygdala that spare adjacent cortical regions do not impair memory or exacerbate the impairment following lesions of the hippocampal formation. J. Neurosci. 9:1922–1936. Zola-Morgan, S., Squire, L.R., Clower, R.P., and Rempel, N.L. (1993) Damage to the perirhinal cortex exacerbates memory impairment following lesions to the hippocampal formation. J. Neurosci. 13:251–265. Zola-Morgan, S., Squire, L.R., and Ramus, S.J. (1994) Severity of memory impairment in monkeys as a function of locus and extent of damage within the medial temporal lobe memory system. Hippocampus 4:483–495.

58 Abnormalities in Brain Structure on Postmortem Analysis of Dementia DANIEL P. PERL

In the absence of reliable biological markers for the clinical evaluation of any of the major dementing disorders, the autopsy continues to play a critical role in establishing the definitive diagnosis for patients who suffer from dementia. Furthermore, in the absence of a truly valid animal model for the major disorder associated with dementia, Alzheimer’s disease (AD), postmortem tissues derived from patients with this disease continue to play an invaluable role for researchers investigating a wide variety of aspects of this condition. Over the past two decades, major advances have been made in identifying relevant changes in brain structure related to the presence of various dementing disorders as well as recognizing those changes that occur in the course of the normal aging process. NORMAL AGING Traditionally, it has been taught that normal aging is accompanied by a modest degree of loss of neurons in several regions of the brain. However, the extent of that loss is currently being reassessed using the techniques of systematic nonbiased sampling (stereology). Preliminary data using these nonbiased sampling techniques indicate that such neuronal losses in normal aging are difficult to verify in most regions studied (for review see Peters et al., 1998). Additional studies of this kind will be required to confirm if this impression is correct. Neurofibrillary tangles and senile plaques, lesions to be discussed in detail in “Alzheimer’s Disease,” are frequently seen in relatively small numbers in the entorhinal cortex, hippocampus, and even neocortex of brains obtained from individuals of advanced age with normal cognitive function. In general, the extent of these lesions in the normal elderly, though variable, is considerably less than that found in patients with clinically apparent AD. However, the distinction between normal-aged individuals and those with mild cognitive impairment can involve subtle distinctions.

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ALZHEIMER’S DISEASE Any of the grossly visible alterations in brain structure that can be seen in patients with AD are entirely nonspecific in nature and overlap extensively with those encountered in brain specimens derived from elderly individuals who had shown normal cognitive function during life. In general, the brain of any individual older than age 60 years shows some increase in fibrous tissue within the leptomeninges, particularly involving the parasaggital regions over the vertex of the cerebral hemispheres. This age-related fibrosis produces a variable degree of whitening and opacification of the membranes. The degree of this change in patients with AD is indistinguishable from that seen in elderly patients with no dementia. Most brain specimens derived from patients with AD show some degree of cerebral cortical atrophy. This atrophy is most notable in the frontotemporal association cortex and tends to spare primary motor, sensory, and visual areas. Once again, in elderly patients, particularly those of advanced age, there is extensive overlap between brain weight and measures of cortical atrophy between age-matched individuals with normal cognitive function and those with AD. Indeed, the overlap is so extensive that brain weight or cortical thickness measured on the brain specimen of any individual cannot be reliably employed to predict the presence of dementia (Terry, 1986). When taken as a group, such differences were difficult to establish on a statistical basis. However, it should be noted that in cases of AD of presenile onset (that is, arbitrarily set at an onset younger than 65 years), comparisons of brain weight or degree of cortical atrophy with age-matched controls reveal a clear and obvious difference upon gross inspection of the brain. The loss of brain tissue associated with AD generally leads to a symmetrical dilatation of the lateral ventricles (hydrocephalus ex vacuo). Again, based on this finding, one cannot accurately distinguish between age-matched normals and persons with AD. However, grossly visible

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atrophy of the hippocampus, with selective dilatation of the temporal horn, does represent a reasonably reliable clue, upon dissection of the brain, that the specimen will ultimately show microscopic evidence of AD. Similarly, the absence of this finding indicates that other explanations for the underlying cause of dementia will likely need to be sought. Microscopic Changes The histopathological evaluation of the brain tissues of victims of AD reveals a series of morphological alterations upon which the neuropathological diagnosis is based. Once again, virtually all of these alterations may also be encountered, to some degree, in the brains of elderly patients who during life had demonstrated normal cognitive function. Some of these changes do not correlate with the extent of cognitive loss, whereas for others, the distinction between AD and normal aging involves complex evaluation regarding the extent and distribution of the particular abnormality. Indeed, correlations between the extent and distribution of such lesions are currently undergoing detailed scientific study using brain specimens derived from individuals in large cohorts of elderly patients who have undergone rigorous longitudinal neuropsychological studies. Neurofibrillary Tangles In his initial description of the disease that would eventually bear his name, Alois Alzheimer (1907) identified the presence of abnormal fibrous inclusions within the neuronal perikaryal cytoplasm. These inclusions are referred to as Alzheimer neurofibrillary tangles, and they are one of the cardinal microscopic lesions associated with the disease. It is difficult to specifically visualize the neurofibrillary tangle using hematoxylin and eosin, the traditional morphological histological stain of pathology. In general, a variety of silver impregnation stains, such as the modified Bielschowski or Gallyas techniques, or the fluorochrome dye thioflavin S, are typically employed to better visualize and quantify these changes. With better characterization of the protein constituents of the neurofibrillary tangle, immunohistochemical approaches have also been widely used for this purpose. These have mostly employed antibodies to abnormally phosphorylated tau (see below) (Yen et al., 1987; Dickson et al., 1988; Iwatsubo et al., 1994). Because these techniques require either specialized equipment (in the case of the thioflavin S stain) or experienced histotechnologists (in the case of silver impregnation stains), many anatomical pathologists in general practice are usually unable to evaluate properly brain specimens submitted for the diagnosis of AD. Such specimens are best referred to specialized neuropathology laboratories with

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the experience and facilities needed to evaluate various neurodegenerative disorders. Using these special stains, within neurons with a pyramidal perikaryal shape, such as the large neurons of the CA1 sector of the hippocampus and the layer V neurons of the association cortex, the neurofibrillary tangle appears as parallel aggregates of thickened fibrils that frequently surround the nucleus and extend Fig. 58.1). When neurons toward the apical dendrite (Fig with a more rounded configuration are involved by a neurofibrillary tangle, such as neurons of the substantia nigra and locus coeruleus, the inclusion appears as interweaving swirls of fibers and here they are referred to as globoid tangles. The vast majority of neurons that contain a neurofibrillary tangle, based on light microscopic and ultrastructural examination, appear to be morphologically intact. However, particularly in areas of the brain with severe neurofibrillary tangle formation, one will encounter examples of tangles lying free in the neuropil and without any associated host neurons. Such structures are referred to as extracellular or ghost tangles and are thought to represent tangle-bearing neurons that have died, leaving the tangle as a remnant that the brain cannot effectively remove. The nature of the neurofibrillary tangle has been the subject of considerable research over the past several decades, and much has been learned about its structural components. Ultrastructurally, the neurofibrillary tangle is composed of parallel skeins of abnormal fibrils that measure 10 nm in diameter. The fibrils are paired and wound in a helical fashion having a regular periodicity of 80 nm (Kidd, 1963; Wisniewski et al., 1976). Based on these observations, such structures are generally referred to as paired helical filaments (PHF). It took many years to decipher the biochemical nature of these abnormal fibrils because they are extremely resistant to solubilization. The primary constituent of the

FIGURE 58.1 Alzheimer’s disease in the hippocampus (CA1). Modified Bielschowski stain shows neurofibrillary tangles and senile plaques.

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neurofibrillary tangle is a microtubule-associated protein called tau. The tau within neurofibrillary tangles is abnormally phosphorylated, with phosphate groups attached to specific sites on the molecule (Lee et al., 1991). The neurofibrillary tangle also contains a number of other protein constituents such as ubiquitin (Perry et al., 1987; Love et al., 1988), cholinesterases (Mesulam and Moran, 1987), and β -amyloid (Aβ; see below) (Hyman et al., 1989), the major constituent of the amyloid accumulations seen in senile plaques and leptomeningeal and cerebral cortical blood vessels (see below). The pattern of distribution of neurofibrillary tangles present in cases of AD is, for the most part, rather distinct and predictable. Severe involvement is seen in the layer II neurons of the entorhinal cortex, the CA1 and subicular regions of the hippocampus, the amygdala, and the deep layers (layers V and superficial VI) of the neocortex (Morrison and Hof, 1997). Studies have shown that the extent and distribution of neurofibrillary tangles in cases of AD do correlate with the degree of dementia and the duration of illness (Arriagada et al., 1992; Hof et al., 1995). This suggests that this neuronal alteration does have some direct impact on the functioning capacity of the individual who is affected. However, it is clear that other factors contribute to the clinical features of the disease. It is important to recognize that though the neurofibrillary tangle is one of the cardinal histopathological features of AD, this neuropathological alteration may also be encountered in association with a large variety of other disease states (Wisniewski et al., 1979). These include disorders such as postencephalitic parkinsonism, post-traumatic dementia or dementia pugalistica, type C Niemann–Pick disease, and amyotrophic lateral sclerosis/parkinsonism dementia complex of Guam. It remains unclear why diseases with such a wide range of underlying etiological mechanisms should all show this one particular neuronal abnormality.

plaque has a central core of Aβ protein arranged in a radial fashion and is surrounded by a corona of abnormally formed neurites or neuronal processes (either dendrites or axons). The abnormal or dystrophic neurites stain strongly with the same silver impregnation stains (Fig. 58.2) used to identify the neurofibrillary tangles, and ultrastructurally these structures contain dense bodies, membranous profiles, and packets of paired helical filaments. In the periphery of the neuritic plaque, one may also commonly encounter one or two microglial cells and, less frequently, reactive astrocytes. With the availability of immunohistochemical techniques using antibodies raised against portions of the Aβ protein, it has been recognized that focal diffuse deposits of this amyloid protein may occur in the cerebral cortex in the absence of accompanying dystrophic neurites (Yamaguchi et al., 1989). Such diffuse deposits of Aβ are now referred to as diffuse plaques. Diffuse plaques are commonly encountered in the brains of elderly individuals and can be seen in relatively large numbers in the absence of any associated evidence of cognitive impairment (Gentleman et al., 1989; Morris et al., 1996; Wolf et al., 1999). A third form of plaque has also been identified, consisting of a dense core of Aβ that may or may not be accompanied by a small number of surrounding dystrophic neurites. Such plaques are generally referred to as burned-out or end-stage plaques and are considered to be the remnants of what was once a neuritic plaque (Wisniewski et al., 1982). Because all neuropathological observations of such lesions are, by their very nature, cross-sectional with respect to time, these interpretations are best thought of as speculation. The Aβ protein is derived from a larger amyloid precursor protein (APP), which is a highly conserved transmembrane glycoprotein (Kang et al., 1987). The Aβ portion of the precursor protein is formed through the

Senile Plaque The other major histopathological alteration encountered in patients suffering from AD is the senile or neuritic plaque. Senile plaques are relatively complex lesions but are defined by the presence of a central core accumulation of a 4 kD protein with a β -pleated sheet configuration referred to as Aβ or β –amyloid (Masters et al., 1985; Kang et al., 1987; Beyreuther and Masters, 1990). The β -pleated sheet configuration of the protein confers on the molecule the ability to bind the planar dye Congo Red and produce birefringence when illuminated by polarized light, the physical definition of an amyloid. Several different forms of plaque are associated with brain aging and AD, and at times the nomenclature employed in the literature can be confusing. The neuritic

FIGURE 58.2 Alzheimer’s disease in the neocortex. Modified Bielschowski stain shows senile or neuritic plaques.

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action of two secretases, which split the amino and carboxyl terminals of the 4 kD segment that then accumulates in the tissues (Selkoe et al., 1996; Selkoe, 1998, 2001). The carboxyl end cleavage is ragged, with longer forms (having a total of 42 or 43 amino acids) tending to be deposited within the senile plaques and a shorter form (containing 40 amino acids) tending to accumulate within the leptomeningeal and cerebral cortical blood vessels in the form of congophilic angiopathy (see below) (Prelli et al., 1988). Senile plaques have been shown to accumulate a number of other proteins, for example, heparan sulfate glycoproteins (Maresh et al., 1996; Snow et al., 1996; Castillo et al., 1997), apolipoprotein ε4 (Namba et al., 1991; Dickson et al., 1997; Nishiyama et al., 1997), complement proteins (Dickson and Rogers, 1992; Rogers et al., 1992; McGeer et al., 1994), and alpha-1-antichymotrypsin (Abraham et al., 1990). Congophilic Angiopathy Not only does Aβ accumulate in the form of senile plaque cores, there is also a tendency for this molecule to accumulate in the walls of the cerebral blood vessels. This phenomenon is referred to as congophilic angiopathy. The vessels that become involved by this process are the small arteries and arterioles of the leptomeninges and those of the gray matter of the cerebral cortex. It has been found that the shorter forms of the Aβ polypeptide, that is, the 1–40 form, predominates in these deposits (Prelli et al., 1988). These accumulations do not appear to exert any deleterious effect on the function of these vessels, although with a severe degree of involvement the vessel becomes prone to spontaneous intraparenchymal rupture, with focal accumulation of blood in the brain tissues. Such hemorrhages are not generally encountered in and around the lenticular nuclei and thalamus, such as that seen as a consequence of uncontrolled systemic hypertension. The hemorrhages associated with congophilic angiopathy tend to occur in the frontal and occipital white matter and may also be multiple. Due to their more isolated location, such lesions are commonly referred to as lobar hemorrhages.

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also are seen in lesser numbers in the neurons of the remainder of the CA1 hippocampal region. Ultrastructurally, they are described as a membrane-bound structure with a clear vacuolar matrix containing an electrondense central granule (Hirano et al., 1968). These central granules stain darkly with silver impregnation stains and are decorated with antibodies directed against phosphorylated neurofilaments tubulin, tau, and ubiquitin (Kahn et al., 1985; Dickson et al., 1987; Ikegami et al., 1996). Little is known about the nature of these lesions or their significance. They may clearly be seen in brain specimens derived from elderly individuals with normal cognitive function. However, two studies have shown that the presence of large numbers of such lesions in the boundary zone between the CA1 and CA2 regions of the caudal aspect of the hippocampus correlates well with a diagnosis of AD (Tomlinson and Kitchener, 1972; Ball and Lo, 1977). Eosinophilic rod-like inclusions, or Hirano bodies, are encountered within the CA1 region of the hippocampus. These intensely eosinophilic lesions were first identified by Asao Hirano in his pioneering clinico-neuropathological studies of amyotrophic lateral sclerosis/parkinsonism– dementia complex of Guam and are now commonly referred to as Hirano bodies (Hirano, 1994). In this disease, confined to the native population of Guam, large numbers of such lesions are commonly encountered. Subsequently, similar inclusions in lesser numbers were noted in some but not all cases of AD. Finally, such lesions may also be identified in the brains of normal-aged individuals with intact cognition, but typically there are very few of these lesions in such specimens. Hirano bodies have a distinct ultrastructural appearance consisting of parallel fibers that interweave in a regular crossing pattern that is strongly reminiscent of the appearance of a tweed fabric. Immunohistochemical studies have revealed the presence of epitopes of actin, tropomyosin, and vinculin in these bodies (Goldman, 1983; Galloway, Perry, and Gambetti, 1987; Galloway, Perry, Kosik, and Gambetti, 1987). At the present time, the Hirano body appears to be a nonspecific alteration, and its significance is unknown. Synaptic Loss

Granulovacuolar Degeneration/Eosinophilic Rod-Like Inclusions (Hirano Bodies) Granulovacuolar degeneration was first identified by Simchowitz in 1911. This poorly understood lesion consists of small vacuoles measuring 2–4 mm in diameter, each containing a small, dense basophilic granule, which typically measures approximately 1 mm in diameter. These granule-containing vacuoles are encountered almost exclusively within the perikaryal cytoplasm of pyramidal neurons of the hippocampus, most typically at the junction between the CA2 and CA1 sectors. They

Studies by Masliah and Terry (Masliah et al., 1989; Terry et al., 1991; Masliah and Terry, 1993; Masliah et al., 1993) and by Scheff and coworkers (Scheff and Price, 1993; Scheff et al., 1993; DeKosky et al., 1996; Scheff and Price, 1998; Scheff et al., 2001) have shown that a substantial loss of synaptic profiles occurs in the brains of patients with AD. This has been investigated using quantification of immunohistochemical markers against synaptic proteins such as synaptophysin and by quantitative electron microscopy. Masliah and coworkers have shown a mean decrease of 45% in the

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amount of staining of presynaptic boutons in cases of AD, representing a dramatic loss in these critical elements that support cell-to-cell communication (Masliah et al., 1989). These coauthors have argued that this loss constitutes the major morphological counterpart to cognitive loss in AD and that it correlates highly with the degree of functional impairment (Terry et al., 1991). Diagnostic Criteria for Alzheimer’s Disease In the absence of a specific clinical and/or laboratory diagnostic test for AD, it is correctly stated that one cannot make a definitive clinical diagnosis of this disorder, and confirmation at autopsy is ultimately required. This places the burden of establishing the definitive diagnosis on the neuropathologist. In the majority of cases, particularly those with severe impairment at the end stage of the disease, that task is relatively straightforward, and the brain specimen typically demonstrates extensive and widespread involvement by virtually all of the lesions described above. However, in a significant number of cases, either the extent of involvement by these lesions or the presence of other superimposed pathological processes makes the establishment of a clearcut diagnosis problematic. Panels of neuropathologists with expertise in the evaluation of such cases have been convened over the years with the task of articulating usable criteria for establishing a neuropathological diagnosis of AD. Over the years, three major criteria have been proposed by groups of pathologists with expertise in AD, and each has been employed with variable success. The first such criterion was articulated by a group of neuropathologists organized by the National Institute on Aging (NIA) and the American Association of Retired Persons (AARP). The results of their deliberations became known in the literature as the NIA/AARP or Khachaturian Criteria after the organizer of the group, Dr. Zaven Khachaturian (Khachaturian, 1985). The Khachaturian Criteria sought to establish an approach to the diagnosis of AD based on the use of an age-related senile plaque score that was determined by the density of senile plaques in the neocortex. For example, in individuals dying between the ages of 66 and 75 years, more than 10 neocortical plaques per microscopic field with a total area of 1 mm2 were required for the diagnosis of AD. However, for individuals dying at an age older than 75 years, 15 plaques per microscopic field were required to establish the diagnosis. This approach attempted to deal with the reality that some elderly individuals could have overtly intact cognitive function yet still show a moderate degree of senile plaque formation in the cerebral cortex. The second major effort to introduce criteria for the diagnosis of AD was carried out by the Consortium to

Establish a Registry for Alzheimer’s Disease (CERAD) (Mirra et al., 1991). This group developed a protocol aimed at standardizing the approach for assessing the density of senile plaques in a semiquantitative fashion. They also sought a method to standardize the collection of other measures of the extent of AD-related lesions. For establishing a neuropathological diagnosis, the CERAD group also employed an age-related senile plaque score (plaque density), expressed as being possible, probable, or definite AD. Whether a case is considered possible, probable, or definite relates to the extent of plaque formation in regard to the age of the patient plus information on whether dementia was present on clinical evaluation. Most recently, consensus recommendations have emerged from the National Institute on Aging/Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer’s Diseases (Hyman and Trojanowski, 1997). The so-called NIA/ Reagan Institute recommendations endorse the use of the CERAD approach for standardized semiquantitative assessments of senile plaque densities and also suggest that the extent and distribution of neurofibrillary tangles present (using the Braak and Braak [1991] stages; see below) be added to the diagnostic assessment. The overall assessment is expressed in terms of a low, medium, or high probability that the dementia present was related to AD. EARLY-STAGE VERSUS LATE-STAGE ALZHEIMER’S DISEASE Until relatively recently, the vast majority of the neuropathological literature related to clinico-pathological correlation tended to involve descriptions of the end stages of AD. Because patients with AD do not typically die as a direct consequence of the disease itself, most patients tend to survive to its advanced stages. They tend to linger on in a severely impaired condition for a variable amount of time until a superimposed infection or another disorder emerges to serve as the cause of death. Accordingly, the brain specimen from such a patient will typically demonstrate a severe, widely distributed burden of neurodegenerative lesions. Typically, in the final years of their illness, such patients will have deteriorated so severely that they are completely noncommunicative and are virtually unable to be tested using standard neuropsychological batteries. The brain specimens of such terminal patients will typically show a heavy burden of neurofibrillary tangles and senile plaques. This situation is particularly prevalent among relatively young patients with AD, the patients likely to be diagnosed and followed longitudinally by research groups interested in AD. Accordingly, such patients are likely to be involved in a variety of research studies and even-

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tually undergo autopsy and donation of the brain for use in postmortem studies. Indeed, over the years, the overwhelming proportion of published studies that use postmortem tissues have involved end-stage patients. However, it must be recognized that AD is a slowly progressive condition that takes many years, perhaps a decade or more, to progress to clinical stages where a diagnosis can first be made. This is generally followed by many years of further progression from early to middle stages of the disorder. Because AD is a distinctly age-related disorder, it is anticipated that a proportion of elderly patients would actually die in the early stages of AD related to the presence of other disease states, frequently before the diagnosis was formally suggested. It is clear that the incidence and prevalence of AD are strongly correlated with advanced age and that the vast majority of cases are encountered after the age of 80. Recognizing that advanced age, with its inherent frailties and multiple medical comorbidities, leads to a high death rate, it would therefore be anticipated that many elderly individuals would die of unrelated causes while also passing through the early clinical stages of AD. Additionally, it would be anticipated that some elderly individuals would die during the period when the disease was just starting but had not had enough time to produce a sufficient number of lesions to attract clinical attention, neuropsychological workup, and eventual diagnosis. What happens when such a patient comes to a neuropathologist for diagnostic evaluation? It is clear that in many of these cases, the neuropathological changes found would be considered to be part of normal aging. Over the years, many such cases were described, and a literature emerged in which partial expression of the neuropathology of AD was considered a normal counterpart of the aging process and was thought to be separable from AD. More recently, a number of laboratories have begun to look in a disciplined fashion at the progressive development of the lesions of AD. One of the major objectives of such work has been to clarify the nature of the earliest morphological features of the disease. What appears to be a reproducible pattern for the sequential development of the disease has begun to emerge. This work has come predominantly from the laboratories of several cortical neuroanatomists who have recognized the importance of specific underlying cortical pathways in defining the spread of the lesions as the disease progresses. The work, among others, of Pearson and colleagues (1985), Van Hoesen and Hyman (1990), Morrison and Hof (1997), and Braak and Braak (1991) has made major contributions. This has culminated in a proposed sequence by Eva and Heiko Braak of the progression of AD in six stages of increasing involvement of the brain. Stages 1 and 2 show relatively selective involvement by neurofibrillary tangles in the transentrohinal cortex. This

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is followed by stages 3 and 4, with increasing limbic lobe involvement, followed by two final stages (5 and 6) with a more typical widespread pattern of involvement in the neocortex. The Braak and Braak stages were developed by evaluating the pattern of neurodegenerative changes present in a series of 83 brain specimens derived from elderly individuals. The stages were constructed by looking at the comparative extent and distribution of lesion development in the brains used in the study, but no associated clinical data were available from the patients from whom these specimens were obtained. Despite this obvious weakness, the Braak and Braak stages have been quite useful and, for the most part, have provided a format for the morphologist to use in evaluating the relative stage of development of the disease. A small number of research groups have now begun to enroll relatively large cohorts of elderly individuals who demonstrate intact cognitive function and follow them longitudinally over a period of years. In advanced age, some individuals will retain undiminished cognitive capacities, while others will begin to show deterioration, presumably related in some cases to the development of AD. If the cohort is sufficiently large and of advanced age, a significant proportion of deaths will occur each year due to a number of common age-related medical conditions. With an active autopsy procurement program, after several years a number of brain specimens derived from such normal or individuals who were mildly impaired can be collected and made available for study. This has been the design of several ongoing studies, such as the Religious Order Study at Rush-Presbyterian–St. Luke’s (Mufson et al., 2000; Kordower et al., 2001; Mitchell et al., 2002), the Nun Study at the University of Kentucky (Snowdon et al., 2000; Gosche et al., 2002; Riley et al., 2002), the Memory and Aging Study at Washington University, St. Louis (Price and Morris, 1999; Morris and Price, 2001; Morris et al., 2001; Price et al., 2001), and the Jewish Home for the Aged Study at the Mount Sinai School of Medicine (Haroutunian et al., 1998; Davis et al., 1999; Bussiere et al., 2002). Such study groups have begun to publish reports on aspects of early AD and have provided important clinico-pathological correlational data. These studies have shown that neurofibrillary tangles and senile plaques correlate with the degree of dementia in patients with mild AD.

DEMENTIA WITH LEWY BODIES (DIFFUSE CORTICAL LEWY BODY DISEASE) In 1817, James Parkinson, in his classic essay on shaking palsy, noted that the disease that now bears his name left the intellect unimpaired (Parkinson, 1955). Despite the validity of his otherwise remarkably precise clinical de-

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scription of the disease, it is now known that dementia is a common consequence of this disorder, particularly when it affects elderly individuals. Some studies have shown that more than 50% of patients with Parkinson’s disease will eventually develop significant cognitive impairment (Pirozzolo et al., 1993). Extrapyramidal clinical features are also commonly encountered in patients with AD (Molsa et al., 1984). Some neuropathological studies have shown that approximately one-fourth of patients with a progressive dementia considered consistent with a clinical diagnosis of AD show at autopsy significant numbers of neurofibrillary tangles and senile plaques but also demonstrate degeneration of the dopaminergic neurons of the substantia nigra, pars compacta in association with Lewy bodies in remaining pigmented neurons (Ditter and Mirra, 1987). In such cases, a varying number of weakly eosinophilic spherical cytoplasmic inclusions are also noted in cerebral cortical neurons. Such inclusions stain prominently with antibodies raised against ubiquitin and α-synuclein and are referred to as cortical Lewy bodies. The use of such immunohistochemical approaches has allowed the ready identification of large numbers of cases of dementia associated with both nigral and cortical Lewy bodies (Dickson, 1999). To further confuse matters, it is now recognized that at autopsy, virtually all cases of Parkinson’s disease show some degree of cortical Lewy body formation (Hughes et al., 1992). This has led to considerable disagreement and controversy regarding how such cases should be categorized diagnostically. Some have claimed that dementia with Lewy bodies is a distinct and separable clinical and neuropathological entity that is actually quite common, and a consensus conference has proposed specific clinical and neuropathological diagnostic criteria for this condition (McKieth et al., 1996; Lowe and Dickson, 1997). We have pointed out that cases that begin with extrapyramidal features and subsequently develop dementia are virtually indistinguishable neuropathologically from those cases that present with dementia and then show neuropsychiatric and extrapyramidal features (Perl et al., 1998). Indeed, of 76 pathologically established Parkinson’s disease cases examined at the United Kingdom Brain Bank, four met the proposed neuropathological diagnostic criteria for dementia with Lewy bodies (Hughes et al., 1992). For these and other reasons, we have raised concerns about considering dementia with Lewy bodies as a distinct clinical entity and have noted that the extensive overlap between AD and Parkinson’s disease is far greater than one would anticipate by chance alone (Perl et al., 1998). This has led to the suggestion that such overlap may represent common pathogenetic mechanisms affecting a variety of specific vulnerable neuronal populations. These disagreements remain unresolved and continue to be the subject of active investigation and discussion.

OTHER CAUSES OF DEMENTIA Multi-Infarct Dementia Stroke, in the form of brain infarction, is a relatively common disorder in elderly individuals. Indeed, studies have shown that the incidence of clinically apparent brain infarction is about 3 times greater among individuals 75 years of age or older than among individuals younger than 65 years of age. A neuropathological study performed many years ago indicated that over 30% of brain specimens from individuals dying at older than 90 years of age evaluated neuropathologically showed evidence of either acute or healed infarcts in the cerebral hemispheres (Peress et al., 1972). Of the patients in this series who had been noted to be diabetic, the incidence was approximately 50%. In cases in which there is cumulative destruction of vital cerebral structures, such as occurs as a result of multiple cerebral infarctions, clinical evidence of cognitive impairment may be noted. In such cases, the term multi-infarct dementia is commonly employed. Traditionally, this term is reserved for cases in which the cerebrovascular lesions alone are thought to be responsible for the cognitive failure. In our experience, such cases are relatively rare. In the Mount Sinai/Bronx Veterans Administration Alzheimer’s Disease Research Center brain bank repository, only 7% of dementia cases coming to neuropathological evaluation were diagnosed as multi-infarct dementia. Of course, patients with AD, particularly those of advanced age, may commonly suffer from superimposed cerebral infarction. In such cases, it may be difficult for the neuropathologist to determine the relative importance of the infarctive lesion or lesions in producing the relative extent of cognitive failure shown in any patient of this type. Such cases are generally referred to as mixed dementia and should not be considered examples of true multi-infarct dementia. In multi-infarct dementia, the extent and distribution of the infarcts present show considerable case-tocase variability. As a general rule, the lesions are multiple, bilateral, and of varying age, typically involving the cerebral cortex, basal ganglia, and/or subcortical white matter. In most cases, one of these general areas will be predominantly involved. In our experience, multiple cerebral cortical areas of infarction represent the most commonly encountered pattern. As a general rule, the total combined volume of cerebral cortical tissue destruction is almost invariably in excess of 50 ml. Infarctions involving the basal ganglia leading to dementia tend to be smaller than their cerebral cortical counterparts, frequently representing multiple lacunar infarcts, each less than 1 cm in greatest dimension. Such lesions are virtually always bilateral, and involvement of the thalamus is very common (Fig. 58.3). These lesions

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58.3 Gross appearance of a brain with multi-infarct dementia showing several bilateral lacunar infarcts.

FIGURE

represent a consequence of arteriosclerotic disease of the proximal middle cerebral artery and its lenticulostriate perforating branches. Multi-infarct dementia with lacunar and cerebral cortical involvement is also a common pattern of distribution. In a very small number of cases of multi-infarct dementia, the infarctive process selectively involves the subcortical white matter. Such lesions produce widespread demyelinization, with relative sparing of the overlying cerebral cortex. The ensuing dementia is thought to represent a cortical disconnection syndrome. Such cases are usually referred to as subacute arteriosclerotic encephalopathy or Binswanger’s disease, and this is apparently the rarest form of multi-infarct dementia (Caplan and Schoene, 1978; Caplan, 1995). Frontotemporal Lobar Degeneration (FTLD) In patients with presenile onset of dementia (that is, prior to age 65 years), there is a significant proportion of cases that show a clearly demonstrable pattern of cerebral degeneration that selectively involves the frontal and temporal lobes. Such cases are categorized, in general, as examples of frontotemporal lobar degeneration (FTLD). Within this group, there has emerged a rather complex subclassification based on associated clinical features (such as motor neuron disease, parkinsonism, etc.), molecular pathology, and the presence or absence of specific accompanying neuropathologic features (for example, Pick bodies, ubiquitinated intraneuronal inclusions, etc.). This is a rapidly expanding area as new cases are reported and analyzed. Cases of FTLD in all forms tend to share clinical features that are referred to as frontotemporal dementia that includes a nonfluent aphasia with notable deficits in speech production and semantic dementia (preservation of episodic memory—that is, recollections of day-to-day

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events), and profoundly impaired semantic memory— that is, the understanding of the meaning of verbal and visual stimuli. Poor judgment, disinhibition, and other problems with executive function are also noted in such patients. Neuropathologists have begun to classify cases of FTLD into those with tau-immunopositive inclusions and those with ubiquitin immunopositive inclusions (FTLD-U). The classic FTLD tau-positive disorder is Pick’s disease. Pick’s disease is characterized neuropathologically by striking frontotemporal atrophy, with relative sparing of the remainder of the cerebral cortex and the presence of Pick bodies, characteristic inclusions in affected neurons. In its classic presentation, Pick’s disease is characterized by emotional and behavioral changes indicative of temporal lobe and amygdala pathology. These patients may show many characteristics of the Kluver– Bucy syndrome, with apathy, hyperorality, and changes in sexual and eating habits. Dementia may be profound. Some cases of Pick’s disease may be clinically indistinguishable from AD. Grossly, the brain with Pick’s disease typically shows strikingly severe “knife-edge” atrophy of the frontotemporal cortex (lobar atrophy). The parietal and occipital cortices typically have a normal appearance, with a sharp boundary between the affected and unaffected regions. Symmetrical dilatation of the lateral ventricles is obvious in fully evolved cases, with particularly striking enlargement of the temporal horns. This reflects extensive loss of tissue through severe involvement of the hippocampus and amygdala. Brain weights of these patients are commonly below 1,000 g. In the affected cortex, one usually finds severe neuronal loss with accompanying reactive gliosis. The few remaining neurons are somewhat swollen and contain a large, spherical inclusion body within the perikaryal cytoplasm. Such inclusions stain prominently with silver impregnation stains (Fig. 58.4). They are best seen in the hippocampus but, to a variable extent, may also be seen in other areas of involved cortex. In regions with severe neuronal loss, it may be difficult to identify any characteristic inclusions, although swollen (“ballooned”) neurons with clear chromatolytic cytoplasm (so-called Pick cells) may be encountered. The cytoplasm of such cells generally does not stain with silver stains, although faint argyrophilia may be seen. When neocortical Pick bodies are more extensive, they tend to involve layers II and VI, a pattern of distribution that is strikingly different from the laminar distribution pattern observed in the neurofibrillary tangles of AD (Hof et al., 1994). Pick bodies in the neocortex may be superficially confused with cortical Lewy bodies, as both lesions are spherical and may be argyrophilic (cortical Lewy bodies tend to be more weakly argyrophilic). Although both inclusions show immunoreactivity to ubiquitin, Pick bodies stain strongly with antitau antibodies, while cor-

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FIGURE 58.4 Pick’s disease in the hippocampus. Modified Bielschowski stain shows numerous Pick bodies in pyramidal cells.

tical Lewy bodies do not (Love et al., 1988; Lowe et al., 1988). Finally, anti-α-synuclein immunostaining marks cortical Lewy bodies prominently but fails to delineate Pick bodies. Ultrastructural studies have shown the Pick body to be a non-membrane-bound inclusion consisting of a randomly arranged accumulation of straight filaments measuring 14–16 nm in diameter and of variable length (Murayama et al., 1990). These filaments are admixed with a variable amount of twisted filaments having a periodicity and diameter distinctly different from those of the paired helical filaments of AD neurofibrillary tangles. In the hippocampus there may be dramatic involvement of the large pyramidal neurons of the CA1 region by Pick bodies. Smaller similar lesions are also typically encountered in the small neurons of the dentate fasciculus. Most recently, immunohistochemical preparations using antitau antibodies have shown the presence of glial cytoplasmic inclusions in Pick’s disease (Iwatsubo et al., 1994). It should be noted that some cases of Pick’s disease show, in addition to Pick bodies, neurofibrillary tangles and even senile plaques. In such Pick’s disease cases with superimposed AD-related pathology, the clinical presentation and other neuropathological features appear to be no different than those seen in more typical Pick’s disease. Finally, the molecular nature of the tau accumulation seen in Pick’s disease is distinctly different from that of AD (Delacourte et al., 1996). The tau encountered in AD migrates on a Western blot to reveal three major bands (at 55, 66, and 69 kD), whereas the tau associated with Pick’s disease shows only two major bands (at 55 and 66 kD). It has been suggested that this observation may serve as a molecular means for differentiating the two diseases. Finally, recent investigations into other forms

of FTLD (see below) have led to the suggestion that this entity be called frontotemporal lobar degeneration with Pick bodies (FTLD with Pick bodies) (Cairns et al., 2007). Those FTLD-U cases are characterized by the presence of ubiquitin immunopositive intraneuronal inclusions that are tau negative and α-synuclein negative (Josephs, 2007). Such frontotemporal lobar degeneration with ubiquitin positive inclusions (FTLD-U) may be seen with or without associated motor neuron disease. Recently, the protein that is ubiquitinated in these inclusions has been identified as TAR-DNA binding protein 43 (TDP-43) (Neumann, et al., 2006). Of interest is that TDP-43 immunoreactive inclusions have also been identified in motor neurons of sporadic cases of amyotrophic lateral sclerosis. Frontotemporal lobar degeneration with ubiquitin positive inclusions may also be linked to mutations to several other proteins, such as progranulin and valsolin-containing protein. This has led to a rather complex approach to classification for which, as further cases are identified and studied, additional modifications will be needed (Cairns et al., 2007). Frontotemporal Dementia and Parkinsonism Linked to Chromosome 17 (FTDP-17) An additional form of frontotemporal dementia has been identified that is associated with clinical parkinsonism. Approximately 60% of such cases show evidence of familial clustering, typically with an autosomal dominant inheritance pattern. Studies of such families have demonstrated linkage to chromosome 17q21–22. Because these cases show evidence of accompanying parkinsonism, the nosologic term frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17) has been introduced (Spillantini et al., 1998). Clinically, such cases may demonstrate a wide variety of manifestations. Many show the clinical features typical of frontotemporal dementia with a loss of frontal lobe executive functions, hyperorality, stereotyped and perseverative behaviors, a progressive paucity of speech but preserved spatial orientation. The disease typically begins in the 50s, although cases have been reported with onset in the 30s to the 70s. Inappropriate behavior and impulsivity are also common. Prominent psychiatric symptoms similar to those of schizophrenia have also been reported, including auditory hallucinations, delusions, and paranoia. Judgment is impaired, as well as planning and reasoning capabilities. In the later phases of the disease, a more profound global dementia occurs that may often be difficult to separate from that of AD. Signs of parkinsonism, including bradykinesia, limb rigidity, and postural instability, are evident in most cases. Typically, these features do not respond to 3,4-dihydroxyphenylalanine (L-DOPA) therapy. Motor weakness accompanied by muscular wasting in

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the limbs, and fasciculations has also been reported in some cases. A relatively small number of morphological descriptions have been reported in documented cases of FTDP17 (Hulette et al., 1999). Such cases typically show evidence of cerebral cortical atrophy of the frontal and temporal lobes as well as of the amygdala and basal ganglia. In the involved areas, there is evidence of rather severe neuronal loss with accompanying gliosis. In most cases, there is relative sparing of the hippocampus and substantia nigra. In those areas of involvement, tauimmunoreactive intraneuronal inclusions are seen with the appearance of neurofibrillary tangles, as well as taupositive inclusions in glial cells. Typically, stains for Aβ accumulation are negative. To make the situation even more confusing, some cases of FTDP-17 have been reported with Pick bodies. At present, it remains unclear to what extent such FTDP-17 cases represent a substrate of progressive dementia and/or parkinsonism, particularly when encountered in a familial setting. This also appears to be a situation where the more one looks, the more one finds. Prion-Related Diseases (Creutzfeldt–Jakob Disease, Gerstmann–Straussler–Scheinker Syndrome, Fatal Familial Insomnia) Creutzfeldt–Jakob disease (CJD) is an extremely rare form of rapidly progressive dementia. It is seen sporadically and in familial clusters throughout the world. Patients show evidence of a rapidly advancing dementia typically associated with motor disturbances, a characteristic electroencephalographic pattern (so-called triphasic waves), and myoclonic jerks. The disease is invariably fatal, with patients typically dying within a year of onset. Although AD may be confused with CJD at its initial presentation, this characteristically rapid course readily distinguishes CJD from the much more slowly progressive AD. Creutzfeldt–Jakob disease is characterized neuropathologically by neuronal loss, intense reactive gliosis, and spongiform changes. The extent of neuronal loss and the accompanying gliosis correlate well with the length of the illness, generally reflecting the attentiveness of supporting nursing care provided to the patient. Intracerebral inoculation of homogenates of the brain tissue of patients with CJD into nonhuman primates has produced a similar syndrome following a prolonged incubation period and serves as the basis for considering this condition to be transmissible (Gibbs et al., 1968). The nature of the transmissible agent is an abnormally folded protein (PrP protein) that is capable of initiating replication in the host and is referred to generically as a prion (Prusiner, 1991). Owing to the potentially infectious nature of affected tissues, organs from suspected patients with CJD (cornea, kidney, etc.) should not be employed for transplantation

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since they are capable of transmitting disease iatrogenically (Gajdusek et al., 1977). Gerstmann–Strausler–Scheinker syndrome is an extremely rare disorder (approximately 2–5 cases/100 million population) that is also a prion-related condition. Clinically, it is characterized by cerebellar ataxia, dysmetria, hyporeflexia, and a positive Babinski sign. Neuropathological examination shows prominent plaque-like amyloid deposits in the molecular layer of the cerebellum. The amyloid protein that accumulates is composed of PrP protein and not Aβ, as is seen in AD. Gerstmann– Strausler–Scheinker syndrome is inherited in an autosomal dominant fashion, and in most cases a proline to leucine substitution is found at the 102 codon of the PrP molecule (Hsiao et al., 1989). Fatal familial insomnia (FFI) is also an extremely rare prion-related disorder and in most cases is related to mutations of the 129 codon of the PrP molecule (Gambetti et al., 1995). Patients with FFI show prominent disturbances in sleep–wake cycles, hallucinations, ataxia, myoclonus, dysarthria, and pyramidal signs. This disorder is also invariably fatal, typically with a course of less than 1 year. Neuropathological features include prominent neuronal loss with astrocytosis and spongiform changes localized particularly to the thalamus. Posttraumatic Dementia (Dementia Pugalistica) The clinical studies of Critchley (1957) and the cliniconeuropathological findings of Corselis (Corsellis and Brierly, 1959; Corsellis et al., 1973) have helped to characterize a progressive dementing disorder that develops as a consequence of the delayed effects of severe repeated head trauma. This disorder, referred to as posttraumatic dementia, punch drunk syndrome, or dementia pugalistica, is classically encountered in retired boxers, although additional cases are reported following other forms of severe trauma to the head. In a study of 250 randomly selected retired boxers in Great Britain, 26 showed clinical evidence of a posttraumatic encephalopathic condition characterized by extrapyramidal signs, frequently accompanied by a variable extent of dementia (Roberts et al., 1990). Typically, the progression of the dementia was rather slow. However, in some cases, there was such marked functional impairment that institutional placement was required. Neuropathological examination of patients with dementia pugalistica typically shows thinning and perforation of the septum pellucidum, depigmentation of the substantia nigra, and rather extensive neurofibrillary tangle formation in the frontotemporal cerebral cortex. The distribution of tangles in the cortex predominates in layers II and III, compared to layer V, a pattern that is the reverse of that seen in AD (Hof et al., 1992). Although this condition was classically described by Corselis as being free of senile plaque formation, the sensitive im-

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munohistochemical procedures developed subsequently showed rather dramatic Aβ accumulation (Roberts et al., 1991). Parkinsonian symptoms are related to profound loss of the pigmented neurons in the substantia nigra; however, Lewy bodies are not encountered. Dementia pugalistica is a poorly understood entity, and the pathogenetic mechanisms responsible for progressive neurodegeneration following repeated blows to the head remain entirely obscure.

REFERENCES Abraham, C.R., Shirahama, T., and Potter, H. (1990) Alpha 1-antichymotrypsin is associated solely with amyloid deposits containing the beta-protein. Amyloid and cell localization of alpha 1antichymotrypsin. Neurobiol. Aging 11:123–129. Alzheimer, A. (1907) Ueber eine eigenartige erkrankung der hirnrinde [About a peculiar disease of the cerebral cortex]. Z. Gesamte Neurol. Psychiat. 18:177–179. Arriagada, P.V., Growdon, J.H., Hedley-White, T., and Hyman, B.T. (1992) Neurofibrillary tangles and not senile plaques parallel duration and severity of Alzheimer’s disease. Neurology 42:1681–1688. Ball, M.J., and Lo, L. (1977) Granulovacuolar degeneration in the ageing brain and in dementia. J. Neuropathol. Exp. Neurol. 36: 474–487. Beyreuther, K., and Masters, C.L. (1990) Nomenclature of amyloid A4 proteins and their precursors in Alzheimer’s disease and Down’s syndrome. Neurobiol. Aging 11:66–68. Braak, H., and Braak, E. (1991) Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. (Berl) 82:239– 259. Bussiere, T., Friend, P.D., Sadeghi, N., Wicinski, B., Lin, G.I., Bouras, C., Giannakopoulos, P., Robakis, N.K., Morrison, J.H., Perl, D.P., and Hof, P.R. (2002) Stereologic assessment of the total cortical volume occupied by amyloid deposits and its relationship with cognitive status in aging and Alzheimer’s disease. Neuroscience 112:75–91. Cairns, N.J., Bigio, E.H., Mackenzie, I.R.A., Neumann, M., Lee, V.M.Y., Hatanpaa, K.J., et al. (2007) Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: consensus of the consortium for frontotemporal lobar degeneration. Acta Neuropathol. 114:5–22. Caplan, L.R. (1995) Binswanger’s disease–revisited. Neurology 45: 626–633. Caplan, L.R., and Schoene, W.C. (1978) Clinical features of subcortical arteriosclerotic encephalopathy (Binswanger disease). Neurology 28:1206–1215. Castillo, G.M., Ngo, C., Cummings, J., Wight, T.N., and Snow, A.D. (1997) Perlecan binds to the beta-amyloid proteins (A beta) of Alzheimer’s disease, accelerates A beta fibril formation, and maintains A beta fibril stability. J. Neurochem. 69:2452–2465. Corsellis, J.A.N., and Brierly, J.B. (1959) Observations on the pathology of insidious dementia following head injury. J. Mental. Sci. 105:715–720. Corsellis, J.A.N., Bruton, C.J., and Freeman-Browne, D. (1973) The aftermath of boxing. Psychol. Med. 3:270–303. Critchley, M. (1957) Medical aspects of boxing particularly from a neurological standpoint. Br. Med. J. 1:357. Davis, K.L., Mohs, R.C., Marin, D., Purohit, D.P., Perl, D.P., Lantz, M., Austin, G., and Haroutunian, V. (1999) Cholinergic markers in elderly patients with early signs of Alzheimer disease. JAMA 281:1401–1406. DeKosky, S.T., Scheff, S.W., and Styren, S.D. (1996) Structural correlates of cognition in dementia: quantification and assessment of synapse change. Neurodegeneration 5:417–421.

Delacourte, A., Robitaille, Y., Sergeant, N., Buee, L., Hof, P.R., Wattez, A., Laroche Cholette, A., Mathieu, J., Chagnon, P., and Gauvreau, D. (1996) Specific pathological Tau protein variants characterize Pick’s disease. J. Neuropathol. Exp. Neurol. 55:159–168. Dickson, D.W. (1999) Tau and synuclein and their role in neuropathology. Brain Pathol. 9:657–661. Dickson, D.W., Farlo, J., Davies, P., Crystal, H., Fuld, P., and Yen, S.H. (1988) Alzheimer’s disease. A double-labeling immunohistochemical study of senile plaques. Am. J. Pathol. 132:86–101. Dickson, D.W., Ksiezak-Reding, H., Davies, P., and Yen, S.H. (1987) A monoclonal antibody that recognizes a phosphorylated epitope in Alzheimer neurofibrillary tangles, neurofilaments and tau proteins immunostains granulovacuolar degeneration. Acta Neuropathol. (Berl) 73:254–258. Dickson, D.W., and Rogers, J. (1992) Neuroimmunology of Alzheimer’s disease: a conference report. Neurobiol. Aging 13:793–798. Dickson, T.C., Saunders, H.L., and Vickers, J.C. (1997) Relationship between apolipoprotein E and the amyloid deposits and dystrophic neurites of Alzheimer’s disease. Neuropathol. Appl. Neurobiol. 23:483–491. Ditter, S.M., and Mirra, S.S. (1987) Neuropathologic and clinical features of Parkinson’s disease in Alzheimer’s disease patients. Neurology 37:754–760. Gajdusek, D.C., Gibbs, C.J., Jr., Asher, D.M., Brown, P., Diwan, A., Hoffman, P., Nemo, G., Rohwer, R., and White, L. (1977) Precautions in medical care of, and in handling materials from, patients with transmissible virus dementia (Creutzfeldt-Jakob disease). N. Engl. J. Med. 297:1253–1258. Galloway, P.G., Perry, G., and Gambetti, P. (1987) Hirano bodies contain actin and actin-associated proteins. J. Neuropathol. Exp. Neurol. 46:185–199. Galloway, P.G., Perry, G., Kosik, K., and Gambetti, P. (1987) Hirano bodies contain tau protein. Brain Res. 403:337–340. Gambetti, P., Parchi, P., Petersen, R.B., Chen, S.G., and Lugaresi, E. (1995) Fatal familial insomnia and familial Creutzfeldt-Jakob disease: clinical, pathological and molecular features. Brain Pathol. 5:43–51. Gentleman, S.M., Bruton, C., Allsop, D., Lewis, S.J., Polak, J.M., and Roberts, G.W. (1989) A demonstration of the advantages of immunostaining in the quantification of amyloid plaque deposits. Histochemistry 92:355–358. Gibbs, C.J., Jr., Gajdusek, D.C., Asher, D.M., Alpers, M.P., Beck, E., Daniel, P.M., and Matthews, W.B. (1968) Creutzfeldt-Jakob disease (spongiform encephalopathy): transmission to the chimpanzee. Science 161:388–389. Goldman, J.E. (1983) The association of actin with Hirano bodies. J. Neuropathol. Exp. Neurol. 42:146–152. Gosche, K.M., Mortimer, J.A., Smith, C.D., Markesbery, W.R., and Snowdon, D.A. (2002) Hippocampal volume as an index of Alzheimer neuropathology: findings from the Nun Study. Neurology 58:1476–1482. Haroutunian, V., Perl, D.P., Purohit, D.P., Marin, D., Khan, K., Lantz, M., Davis, K.L., and Mohs, R.C. (1998) Regional distribution of neuritic plaques in the nondemented elderly and subjects with very mild Alzheimer disease. Arch. Neurol. 55:1185–1191. Hirano, A. (1994) Hirano bodies and related neuronal inclusions. Neuropathol. Appl. Neurobiol. 20:3–11. Hirano, A., Dembitzer, H.M., Kurland, L.T., and Zimmerman, H.M. (1968) The fine structure of some intraganglionic alterations. Neurofibrillary tangles, granulovacuolar bodies and “rodlike” structures as seen in Guam amyotrophic lateral sclerosis and parkinsonism-dementia complex. J. Neuropathol. Exp. Neurol. 27:167–182. Hof, P.R., Bierer, L.M., Purohit, D.P., Carlin, L., Schmeidler, J.M., Davis, K.L., and Perl, D.P. (1995) Neurofibrillary tangles correlate with dementia severity in Alzheimer’s disease. Arch. Neurol. 52:81–88. Hof, P.R., Bouras, C., Buee, L., Delacourte, A., Perl, D.P., and Morrison, J.H. (1992) Differential distribution of neurofibrillary

58: ABNORMALITIES IN BRAIN STRUCTURE ON POSTMORTEM ANALYSIS tangles in the cerebral cortex of dementia pugilistica and Alzheimer’s disease cases. Acta Neuropathol. (Berl) 85:23–30. Hof, P.R., Bouras, C., Perl, D.P., and Morrison, J.H. (1994) Quantitative neuropathologic analysis of Pick’s disease cases: cortical distribution of Pick bodies and coexistence with Alzheimer’s disease. Acta Neuropathol. (Berl) 87:115–124. Hsiao, K., Baker, H.F., Crow, T.J., Poulter, M., Owen, F., Terwilliger, J.D., Westaway, D., Ott, J., and Prusiner, S.B. (1989) Linkage of a prion protein missense variant to Gerstmann-Straussler syndrome. Nature 338:342–346. Hughes, A.J., Daniel, S.E., Kilford, L., and Lees, A.J. (1992) Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: a clinico-pathological study of 100 cases. J. Neurol. Neurosurg. Psychiatry 55:181–184. Hulette, C.M., Pericak-Vance, M.A., Roses, A.D., Schmechel, D.E., Yamaoka, L.H., Gaskell, P.C., Welsh-Bohmer, K.A., Crowther, R.A., and Spillantini, M.G. (1999) Neuropathological features of frontotemporal dementia and parkinsonism linked to chromosome 17q21–22 (FTDP-17): Duke Family 1684. J. Neuropathol. Exp. Neurol. 58:859–866. Hyman, B.T., and Trojanowski, J.Q. (1997) Consensus recommendations for the postmortem diagnosis of Alzheimer’s disease from the National Institute on Aging and the Reagan Institute working group on diagnostic criteria for the neuropathological assessment of Alheimer’s disease. J. Neuropathol. Exp. Neurol. 56: 1095–1097. Hyman, B.T., Van Hoesen, G.W., Beyreuther, K., and Masters, C.L. (1989) A4 amyloid protein immunoreactivity is present in Alzheimer’s disease neurofibrillary tangles. Neurosci. Lett. 101:352–355. Ikegami, K., Kimura, T., Katsuragi, S., Ono, T., Yamamoto, H., Miyamoto, E., and Miyakawa, T. (1996) Immunohistochemical examination of phosphorylated tau in granulovacuolar degeneration granules. Psychiatry Clin. Neurosci. 50:137–140. Iwatsubo, T., Hasegawa, M., and Ihara, Y. (1994) Neuronal and glial tau-positive inclusions in diverse neurologic diseases share common phosphorylation characteristics. Acta Neuropathol. (Berl) 88:129–136. Josephs, K. (2007) Frontotemporal lobar degeneration. Neurologic Clinics 25:683–696. Kahn, J., Anderton, B.H., Probst, A., Ulrich, J., and Esiri, M.M. (1985) Immunohistological study of granulovacuolar degeneration using monoclonal antibodies to neurofilaments. J. Neurol. Neurosurg. Psychol. 48:924–926. Kang, J., Lemaire, H.G., Unterbeck, A., Salbaum, J.M., Masters, C.L., Grzeschik, K.H., Multhaup, G., Beyreuther, K., and Muller Hill, B. (1987) The precursor of Alzheimer’s disease amyloid A4 protein resembles a cell-surface receptor. Nature 325:733–736. Khachaturian, Z.S. (1985) Diagnosis of Alzheimer’s disease. Arch. Neurol. 42:1097–1105. Kidd, M. (1963) Paired helical filaments in electron microscopy of Alzheimer’s disease. Nature 197:192–193. Knopman, D.S., Mastri, A.R., Frey, W.H., Sung, J.H., and Rustan, T. (1990) Dementia lacking distinctive histologic features: a common non-Alzheimer degenerative dementia. Neurology 40:251– 256. Kordower, J.H., Chu, Y., Stebbins, G.T., DeKosky, S.T., Cochran, E.J., Bennett, D., and Mufson, E.J. (2001) Loss and atrophy of layer II entorhinal cortex neurons in elderly people with mild cognitive impairment. Ann. Neurol. 49:202–213. Lee, V.M.Y., Balin, B.J., Otvos, L., Jr., and Trojanowski, J.Q. (1991) A major subunit of paired helical filaments and derivatized forms of normal tau. Science 251:675–678. Love, S., Saitoh, T., Quijada, S., Cole, G.M., and Terry, R.D. (1988) Alz-50, ubiquitin and tau immunoreactivity of neurofibrillary tangles, Pick bodies and Lewy bodies. J. Neuropathol. Exp. Neurol. 47:393–405. Lowe, J., Blanchard, A., Morrell, K., Lennox, G., Reynolds, L., Billett, M., Landon, M., and Mayer, R.J. (1988) Ubiquitin is a common

969

factor in intermediate filament inclusion bodies of diverse type in man, including those of Parkinson’s disease, Pick’s disease, and Alzheimer’s disease, as well as Rosenthal fibres in cerebellar astrocytomas, cytoplasmic bodies in muscle, and mallory bodies in alcoholic liver disease. J. Pathol. 155:9–15. Lowe, J., and Dickson, D. (1997) Pathological diagnostic criteria for dementia associated with cortical Lewy bodies: review and proposal for a descriptive approach. J. Neural Transm Suppl. 51:111–120. Maresh, G.A., Erezyilmaz, D., Murry, C.E., Nochlin, D., and Snow, A.D. (1996) Detection and quantitation of perlecan mRNA levels in Alzheimer’s disease and normal aged hippocampus by competitive reverse transcription-polymerase chain reaction. J. Neurochem. 67:1132–1144. Masliah, E., Mallory, M., Hansen, L., DeTeresa, R., and Terry, R.D. (1993) Quantitative synaptic alterations in the human neocortex during normal aging. Neurology 43:192–197. Masliah, E., and Terry, R. (1993) The role of synaptic proteins in the pathogenesis of disorders of the central nervous system. Brain Pathol. 3:77–85. Masliah, E., Terry, R.D., DeTeresa, R.M., and Hansen, L.A. (1989) Immunohistochemical quantification of the synapse-related protein synaptophysin in Alzheimer disease. Neurosci. Lett. 103: 234–239. Masters, C.L., Multhaup, G., Simms, G., Pottgiesser, J., Martins, R.N., and Beyreuther, K. (1985) Neuronal origin of a cerebral amyloid: neurofibrillary tangles of Alzheimer’s disease contain the same protein as the amyloid of plaque cores and blood vessels. EMBO J. 4:2757–2763. McGeer, P.L., Rogers, J., and McGeer, E.G. (1994) Neuroimmune mechanisms in Alzheimer disease pathogenesis. Alzheimer Dis. Assoc. Disord. 8:149–158. McKieth, I.G., Galasko, D., Kosaka, K., Perry, E.K., Dickson, D.W., Hansen, L.A., Salmon, D.P., Lowe, J., Mirra, S.S., and Byrne, E.J. (1996) Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology 47:1113–1124. Mesulam, M.M., and Moran, M.A. (1987) Cholinesterases within neurofibrillary tangles related to age and Alzheimer’s disease. Ann. Neurol. 22:223–228. Mirra, S.S., Heyman, A., McKeel, D., et al. (1991) The consortium to establish a registry for Alzheimer’s disease (CERAD). Part II. Standardization of the neuropathologic assessment of Alzheimer’s disease. Neurology 41:479–486. Mitchell, T.W., Mufson, E.J., Schneider, J.A., Cochran, E.J., Nissanov, J., Han, L.Y., Bienias, J.L., Lee, V.M., Trojanowski, J.Q., Bennett, D.A., and Arnold, S.E. (2002) Parahippocampal tau pathology in healthy aging, mild cognitive impairment, and early Alzheimer’s disease. Ann. Neurol. 51:182–189. Molsa, P.K., Marttila, R.J., and Rinne, U.K. (1984) Extrapyramidal signs in Alzheimer’s disease. Neurology 34:1114–1116. Morris, J.C., and Price, A.L. (2001) Pathologic correlates of nondemented aging, mild cognitive impairment, and early-stage Alzheimer’s disease. J. Mol. Neurosci. 17:101–118. Morris, J.C., Storandt, M., McKeel, D.W., Jr., Rubin, E.H., Price, J.L., Grant, E.A., and Berg, L. (1996) Cerebral amyloid deposition and diffuse plaques in “normal” aging: evidence for presymptomatic and very mild Alzheimer’s disease. Neurology 46: 707–719. Morris, J.C., Storandt, M., Miller, J.P., McKeel, D.W., Price, J.L., Rubin, E.H., and Berg, L. (2001) Mild cognitive impairment represents early-stage Alzheimer disease. Arch. Neurol. 58:397–405. Morrison, J.H., and Hof, P.R. (1997) Life and death of neurons in the aging brain. Science 278:412–419. Mufson, E.J., Ma, S.Y., Cochran, E.J., Bennett, D.A., Beckett, L.A., Jaffar, S., Saragovi, H.U., and Kordower, J.H. (2000) Loss of nucleus basalis neurons containing trkA immunoreactivity in individuals with mild cognitive impairment and early Alzheimer’s disease. J. Comp. Neurol. 427:19–30.

970

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Murayama, S., Mori, H., Ihara, Y., and Tomonaga, M. (1990) Immunocytochemical and ultrastructural studies of Pick’s disease. Ann. Neurol. 27:394–405. Namba, Y., Tomonaga, M., Kawasaki, H., Otomo, E., and Ikeda, K. (1991) Apolipoprotein E immunoreactivity in cerebral amyloid deposits and neurofibrillary tangles in Alzheimer’s disease and kuru plaque amyloid in Creutzfeldt-Jakob disease. Brain Res. 541: 163–166. Neumann, M., Sampathu, D.M., Kwong, L.K., Truax, A.C., Micsenyi, M.C., Chou, T.T., et al. (2006) Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science 314: 130–133. Nishiyama, E., Iwamoto, N., Ohwada, J., and Arai, H. (1997) Distribution of apolipoprotein E in senile plaques in brains with Alzheimer’s disease: investigation with the confocal laser scan microscope. Brain Res. 750:20–24. Parkinson, J. (1955) An essay on the shaking palsy. London, 1817. In: Critchley, M., ed. James Parkinson (1755–1824). London: Macmillan, pp. 145–218. Pearson, R.C.A., Esiri, M.M., Hiorns, R.W., Wilcock, R.W., and Powell, T.P.S. (1985) Anatomical correlates of the distribution of the pathological changes in the neocortex in Alzheimer’s disease. Proc. Natl. Acad. Sci. USA 82:4531–4534. Peress, N.S., Kane, W.C., and Aronson, S.M. (1972) Central nervous system findings in a tenth decade autopsy population. Prog. Brain Res. 40:473–483. Perl, D.P., Olanow, C.W., and Calne, D. (1998) Alzheimer’s disease and Parkinson’s disease: distinct entities or extremes of a spectrum of neurodegeneration? Ann. Neurol. 44:S19–S31. Perry, G., Friedman, R., Shaw, G., and Chau, C. (1987) Ubiquitin is detected in neurofibrillary tangles and senile plaque neurites of Azheimer’s disease brains. Proc. Natl. Acad. Sci. USA 84:3033– 3036. Peters, A., Morrison, J.H., Rosene, D.L., and Hyman, B.T. (1998) Are neurons lost from the primate cerebral cortex during normal aging? Cereb. Cortex 8:295–300. Pirozzolo, F.J., Swihart, A.A., Rey, G.J., Mahurin, R., and Jankovic, J. (1993) Cognitive impairments associated with Parkinson’s disease and other movement disorders. In: Jankovic, J., and Tolosa, E., eds. Parkinson’s Disease and Other Movement Disorders. Baltimore: Williams & Wilkins, pp. 493–510. Prelli, F., Castano, E., Glenner, G.G., and Frangione, B. (1988) Differences between vascular and plaque core amyloid in Alzheimer’s disease. J. Neurochem. 51:648–651. Price, J.L., Ko, A.I., Wade, M.J., Tsou, S.K., McKeel, D.W., and Morris, J.C. (2001) Neuron number in the entorhinal cortex and CA1 in preclinical Alzheimer disease. Arch. Neurol. 58:1395–1402. Price, J.L., and Morris, J.C. (1999) Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Ann. Neurol. 45:358–368. Prusiner, S.B. (1991) Molecular biology of prion diseases. Science 252:1515–1522. Riley, K.P., Snowdon, D.A., and Markesbery, W.R. (2002) Alzheimer’s neurofibrillary pathology and the spectrum of cognitive function: findings from the Nun Study. Ann. Neurol. 51:567–577. Roberts, G.W., Allsop, D., and Bruton, C. (1990) The occult aftermath of boxing. J. Neurol. Neurosurg. Psychiatry 53:373–378. Roberts, G.W., Gentleman, S.W., Lynch, A., and Draham, D.I. (1991) Beta A4 amyloid protein deposition in brain after head trauma. Lancet 338:1422–1423. Rogers, J., Cooper, N.R., Webster, S., Schultz, J., McGeer, P.L., Styren, S.D., Civin, W.H., Brachova, L., Bradt, B., Ward, P., et al. (1992) Complement activation by beta-amyloid in Alzheimer disease. Proc. Natl. Acad. Sci. USA 89:10016–10020.

Scheff, S.W., and Price, D.A. (1993) Synapse loss in the temporal lobe in Alzheimer’s disease. Ann. Neurol. 33:190–199. Scheff, S.W., and Price, D.A. (1998) Synaptic density in the inner molecular layer of the hippocampal dentate gyrus in Alzheimer disease. J. Neuropathol. Exp. Neurol. 57:1146–1153. Scheff, S.W., Price, D.A., and Sparks, D.L. (2001) Quantitative assessment of possible age-related change in synaptic numbers in the human frontal cortex. Neurobiol. Aging 22:355–365. Scheff, S.W., Sparks, L., and Price, D.A. (1993) Quantitative assessment of synaptic density in the entorhinal cortex in Alzheimer’s disease. Ann. Neurol. 34:356–361. Selkoe, D.J. (1998) The cell biology of beta-amyloid precursor protein and presenilin in Alzheimer’s disease. Trends Cell. Biol. 8:447–453. Selkoe, D.J. (2001) Alzheimer’s disease: genes, proteins, and therapy. Physiol. Rev. 81:741–766. Selkoe, D.J., Yamazaki, T., Citron, M., Podlisny, M.B., Koo, E.H., Teplow, D.B., and Haass, C. (1996) The role of APP processing and trafficking pathways in the formation of amyloid beta-protein. Ann. N.Y. Acad. Sci. 777:57–64. Simchowicz, T. (1911) Histologische studien über die senile dementz [Histologic studies of senile dementia]. Histol. und Histopathol Arbeiten Åber die Grosshirnrinde 4:267–444. Snow, A.D., Nochlin, D., Sekiguichi, R., and Carlson, S.S. (1996) Identification in immunolocalization of a new class of proteoglycan (keratan sulfate) to the neuritic plaques of Alzheimer’s disease. Exp. Neurol. 138:305–317. Snowdon, D.A., Greiner, L.H., and Markesbery, W.R. (2000) Linguistic ability in early life and the neuropathology of Alzheimer’s disease and cerebrovascular disease. Findings from the Nun Study. Ann. N.Y. Acad. Sci. 903:34–38. Spillantini, M.G., Bird, T.D., and Ghetti, B. (1998) Frontotemporal dementia and Parkinsonism linked to chromosome 17: a new group of tauopathies. Brain Pathol. 8:387–402. Terry, R.D. (1986) Interrelations among the lesions of normal and abnormal aging of the brain. Prog. Brain Res. 70:41–48. Terry, R.D., Masliah, E., Salmon, D.P., Butters, N., Deteresa, R., Hill, R., Hansen, L.A., and Katzman, R. (1991) Physical basis of cognitive alterations in Alzheimer’s disease: synapse loss is the major correlate of cognitive impairment. Ann. Neurol. 30:572–580. Tomlinson, B.E., and Kitchener, D. (1972) Granulovacuolar degeneration of hippocampal pyramidal cells. J. Pathol. 106:165–185. Van Hoesen, G.W., and Hyman, B.T. (1990) Hippocampal formation: anatomy and the patterns of pathology in Alzheimer’s disease. Prog. Brain Res. 83:445–457. Wisniewski, H.M., Narang, H.K., and Terry, R.D. (1976) Neurofibrillary tangles of paired helical filaments. J. Neurol. Sci. 27:173–181. Wisniewski, H.M., Vorbrodt, A.W., Moretz, R.C., Lossinsky, A.S., and Grundke-Iqbal, I. (1982) Pathogenesis of neuritic (senile) and amyloid plaque formation. Exp. Brain Res. Suppl. 5: 3–9. Wisniewski, K., Jervis, G.A., Moretz, R.C., and Wisniewski, H.M. (1979) Alzheimer neurofibrillary tangles in diseases other than senile and presenile dementia. Ann. Neurol. 5:288–294. Wolf, D.S., Gearing, M., Snowdon, D.A., Mori, H., Markesbery, W.R., and Mirra, S.S. (1999) Progression of regional neuropathology in Alzheimer disease and normal elderly: findings from the Nun study. Alzheimer Dis. Assoc. Disord. 13:226–231. Yamaguchi, H., Hirai, S., Morimatsu, M., Shoji, M., and Nakazato, Y. (1989) Diffuse type of senile plaques in the cerebellum of Alzheimer-type dementia demonstrated by beta protein immunostain. Acta. Neuropathol. 77:314–319. Yen, S.H., Dickson, D.W., Crowe, A., Butler, M., and Shelanski, M.L. (1987) Alzheimer’s neurofibrillary tangles contain unique epitopes and epitopes in common with the heat-stable microtubule associated proteins tau and MAP2. Am. J. Pathol. 126:81–91.

59 Functional Brain Imaging Studies in Dementia MONTE S. BUCHSBAUM, ADAM BRICKMAN, JING ZHANG,

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ERIN A. HAZLETT

The underlying pathophysiological mechanisms resulting in dementia may result from a variety of causes ranging from the relatively well-understood interruptions of blood flow of vascular dementia to the less wellcharacterized alterations of Alzheimer’s disease (AD), Pick’s disease, and alcoholic dementia. The clinical diagnosis of dementia in ICD-10 requires a decline in memory and thinking sufficient to impair personal activities of daily living. Similarly, the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV; American Psychiatric Association, 1994) requires memory impairment and one or more other cognitive disturbances including aphasia, apraxia, agnosia, and disturbance of executive functioning sufficient to cause impairment in social or occupational function. The criteria of dual cognitive impairment, always including memory deficit, tend to suggest that (1) dementia is associated with two brain sites of involvement (for example, temporal lobe memory operations and frontal lobe executive dysfunction) or that (2) good memory function depends on the coordination of more than one brain area, leading to the frequent association of memory loss with other cognitive dysfunctions in diseases with general cerebral effects. This coordination of multiple brain regions involved in the strategy of memory may draw especially on frontal lobe resources. The heterogeneous manifestations of cognitive loss, the confounding effects of executive dysfunction on all cognitive ability, and the widely prevalent comorbidity of central nervous system (CNS) diseases in the elderly make the diagnosis of dementia and its subtypes problematic. As increasingly specific and effective drugs to treat AD, Parkinson’s disease, the pseudodementia of depression, and other dementing illnesses are developed, the differential diagnosis of these varieties of dementia will be increasingly critical for good psychiatric care and scientific pharmacotherapy. Functional brain imaging is providing a key tool for mapping the compromised brain areas, assessing regional effects of medication treatment, and even selecting behavioral therapies to exploit undamaged brain resources. This review focuses

on the important advances made in positron emission tomography (PET) studies of brain metabolism in dementing illnesses over the past 10 years. There are other useful reviews that cover the earlier literature (Arnold and Kumar, 1993; Herholz, 1995; Messa et al., 1995). THE 18F-FLUORODEOXYGLUCOSE METHOD AND POSITRON EMISSION TOMOGRAPHY STUDIES IN DEMENTIA The final common path for the bioenergetics of all neurochemical processes in the brain is glucose use. Fluorodeoxyglucose (FDG) uptake parallels energy consumption (Sokoloff et al., 1977; Hertz and Peng, 1992) that can be quantitatively determined with PET (typically presented as a relative glucose metabolic rate) and is sensitive to the effects of pharmacological treatments in dementia (for example, donepezil) (Teipel et al., 2006) and individual differences in pharmacological response (Buchsbaum, Potkin, Marshall, et al., 1992; Buchsbaum, Potkin, Siegel, et al., 1992). Studies with nuclear magnetic resonance imaging (MRI) phosphorous spectroscopy and PET have suggested that “glucose metabolism is reduced early in AD (reflecting decreased basal synaptic functioning) and is unrelated to a rate limitation in glucose delivery [or] abnormal glucose metabolism” (Murphy et al., 1993, p. 341). Fluorodeoxyglucose metabolic rates are stable over time (Bartlett et al., 1988; Maquet et al., 1990; Bartlett et al., 1991; Wang et al., 1994) with most subjects showing whole brain metabolic variability below 10%. Because individuals differ widely in whole brain metabolic rate, regional differences are often best assessed when data are converted to a relative metabolic rate by dividing by a standard brain area (most commonly the average whole brain glucose metabolic rate). Relative rates are usually more statistically powerful in demonstrating the effects of cognitive and perceptual tasks or patterns of regional decrease (for example, temporal but not occipital decreases in AD compared to the regional pattern in normal subjects). 971

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However, relative measures may be less reliable in following patients over time than the absolute metabolic rate in two situations: (1) a patient who loses metabolic rate uniformly across the brain would show no relative change on a follow-up scan and (2) large metabolic rate decreases across the cortex (lowering the whole brain metabolic rate) would create large apparent subcortical increases even if subcortical structures remained entirely unchanged over time. The ability to calculate absolute metabolic rates is a significant advantage of PET with FDG over such alternative approaches as functional MRI (fMRI) or cerebral blood flow studies, which do not yield absolute units. However, the latter two approaches offer advantages in the ease with which many behavioral tasks can be administered for the detailed examination of cognitive change; fMRI yields values in individuals being evaluated for dementia that are modestly correlated with the relative metabolic rate (34% of variance shared; r = 0.58) (Gonzalez et al., 1995). NORMAL AGING AND AGE-RELATED MEMORY IMPAIRMENT Frontal Lobe Deficits in Aging and Memory The cortical atrophy of age may be more pronounced in the frontal lobe (Coffey et al., 1992), and cognitive decline has been related to the gradual loss of cortical neurons. Because the frontal lobe is important in executive functioning—the sequencing and controlling of tasks—and has the most pronounced reciprocal connections to other cortical areas of any cortical area (Stuss and Benson, 1986), its decline could lead to changes in the cortical areas where cognitive tasks are carried out and the efficiency with which tasks are executed. Functional imaging studies have tended to demonstrate the activation of frontal (Tulving et al., 1994; Kapur et al., 1995) or frontal and temporal areas (Grady et al., 1995). These findings suggest that combined frontal/temporal deficits may be a common feature of dementia. Metabolic Changes With Age And Dementia Because there are systematic changes with age, it is important to differentiate age-related change and dementiarelated change. Most studies using PET have demonstrated a significant age-associated decrease in cerebral glucose metabolism (A. Martin et al., 1991; Loessner et al., 1995; Moeller et al., 1996; Buchsbaum and Hazlett, 1997; Hazlett et al., 1998). Although a few other studies found age-related functional change to be more marked in the temporal lobe (Takada et al., 1992) or unchanged with age (Tempel and Perlmutter, 1992). Although many regions have been implicated, ageassociated metabolic decreases in the frontal lobe have

been consistently reported (Loessner et al., 1995; Buchsbaum and Hazlett, 1997; Hazlett et al., 1998), during task (Hazlett et al., 1998; Reuter-Lorenz et al., 2000) and resting states (De Santi et al., 1995; Kuhl et al., 1982; Loessner et al., 1995). Consistent with a frontal aging hypothesis, we have previously shown an age-associated shift from anterior regions to more posterior regions of the frontal lobe in normal individuals performing a verbal learning task (Hazlett et al., 1998; Brickman et al., 2003). Moreover, in a review of functional neuroimaging studies of normal aging, Cabeza (2001) described consistent findings of either lower activation or absent activation in older normal adults compared to younger adults during tasks of episodic encoding or semantic retrieval. Areas of the frontal lobe were particularly involved, including anterior cingulate/medial frontal lobe (Brodmann areas 24 and 32), dorsolateral prefrontal cortex (Brodmann areas 44, 45, and 46), orbital frontal lobe (Brodmann area 47), and lateral frontal lobe (Brodmann areas 6, 8, and 10). Our own studies have shown similar findings (Hazlett et al., 1998). Specifically, we used coregistered FDG-PET and MRI to characterize brain function in 70 healthy volunteers aged 20–87. All volunteers performed a verbal memory task (Serial Verbal Learning Task) during the PET scan. Frontal activity showed an age-related decline that remained significant after statistical control for atrophy measured on coregistered MRI. Analyses of young and old subgroups matched on memory performance revealed that young good performers activated frontal regions, whereas old good performers relied on occipital regions. Although activating different cortical regions, good performers of all ages used the same cognitive strategy—semantic clustering. Hazlett et al. (1998) concluded that age-related functional change may reflect dynamic reallocation in a network of brain areas, not merely anatomically fixed neuronal loss or diminished capacity to perform. The eventual diagnostic fate of these memory-impaired volunteers with no dementia will be of interest in understanding cognitive decline with age. The cognitive impairments of elderly monkeys also seem to be mediated by the prefrontal cortex (Gallagher and Rapp, 1997). The pattern of relative frontal decline that appears to be a common characteristic of normal aging may provide a background that interacts with the imaging characteristics and behavioral expression of each of the dementing illnesses described below. ALZHEIMER’S DISEASE Regional Neuropathology in Alzheimer’s Disease Neuropathological confirmation is necessary to ultimately confirm the diagnosis of AD; changes in association areas are more severe than those in the primary

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sensory and motor cortices and may be more severe in temporal regions (Pearson et al., 1985; Rogers and Morrison, 1985; Lewis et al., 1987; Van Hoesen and Damasio, 1987; Hof et al., 1990; Hof and Morrison, 1990; Arnold et al., 1991; Hof and Morrison, 1994). Regional Metabolic Changes in Alzheimer’s Disease In probable AD, single photon emission tomography (SPECT) and PET studies have revealed decreases in glucose metabolic rate that are relatively greater in temporal and parietal than frontal lobes and may precede full development of AD behaviorally (Fig. 59.1) or structurally (Fig. 59.2). Moreover, the finding in imaging studies that AD tends not to affect primary sensory areas provides a striking parallel to the findings of neuropathological studies (Jagust et al., 1988; McGeer et al., 1990; Buchsbaum et al., 1991; Kumar et al., 1991; Nyback et al., 1991; DeCarli et al., 1992; Jobst et al., 1992; Pearlson et al., 1992; Jagust et al., 1993; Minoshima et al., 1995; Valladares-Neto et al., 1995; Sakamoto et al., 2002). Ratios between metabolic rates in major brain areas have proved more effective than the absolute metabolic rate in a single area for discriminating patients and controls (Heiss et al., 1991; Azari et al., 1993; Jagust et al., 1993; Mielke et al., 1993, 1994). In difficult diagnostic cases where cerebral infarction versus AD needs to be discriminated, FDG-PET and SPECT may be valuable (Fig. 59.3). Even if the clinical onset is progressive, suggesting AD, FDG-PET, and other forms of neuroimaging can demonstrate unambiguous infarction (Sarangi et al., 2000). It has been found that FDG-PET is more sensitive than SPECT in separating normal elderly individuals from patients when areas in the temporoparietal and posterior cingulate were used (Herholz et al., 2002). Single photon emission tomography visually inspected was also found superior to anatomical MRI for AD and multi-infarct dementia (Honda

59.1 Positron emission tomography scans from a normal elderly patient, a patient with no dementia with memory impairment, and a patient with probable Alzheimer’s disease (AD). Bilateral temporal lobe metabolic decrease is clearly visible in the patient with AD.

FIGURE

FIGURE 59.2 A PET scan and a MRI scan from a 66-year-old woman with gradual onset of difficulty remembering recent events such as wrapping presents and placing an ironed shirt on a hanger. Neuropsychological tests indicate a parietal lobe deficit and memory impairment. The MRI scan is normal for age, but the PET scan shows an asymmetrical parietal deficit consistent with a cognitive deficit. PET: positron emission tomography; MRI: magnetic resonance imaging.

et al., 2002). In the hippocampus, FDG was also found to separate normal elderly persons, those with mild cognitive impairment, and patients with AD more accurately than MRI-assessed volumetric loss (De Santi et al., 2001). Changes on FDG-PET scans appear closely related to histopathological change observed in subsequent postmortem exam and indicate the validity of PET in the differential diagnosis of dementias. Negative correlations were observed between postmortem regional neurofibrillary tangle density and a prospectively obtained relative metabolic rate with PET (DeCarli et al., 1992; Mielke et al., 1996). In a large study, 22 individuals with difficult-to-characterize memory loss or dementia using clinical criteria received PET, and ultimate pathological confirmation of AD was achieved in 12. The sensitivity of the clinical diagnosis was 63%, while that

FIGURE 59.3 Differential diagnosis in dementia. Cerebrovascular disease shows a single very low metabolic area; Alzheimer’s disease shows a typical bitemporal soft-edged metabolic decrease; head injury shows a single discrete, limited hypometabolic area.

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of the PET criteria of bitemporal decrease visually assessed was 93%, indicating the value of PET as a diagnostic tool in memory loss (Hoffman et al., 2000). Visual ratings of FDG-PET showed superior sensitivity to clinical evaluation (0.84 vs. 0.76) and superior specificity (0.74) when compared to the clinical initial evaluation and final evaluation 4 years later (0.58 and 0.63) when evaluated against postmortem findings (Jagust et al., 2007). Statistical mapping techniques have also been confirmed as effective in diagnosing AD and in the differential diagnosis of Alzheimer’s (n = 34) and frontotemporal dementia (n = 14) (Higdon et al., 2004) in a sample of patients with imaging and postmortem confirmation. Further, though FDG-PET was slightly better, when voxel-by-voxel statistical mapping was used diagnostic sensitivity and specificity of PET and SPECT were similar (Nihashi et al., 2007). Although this literature suggests that as a diagnostic tool PET is superior to an initial clinical evaluation and more specific than clinical evaluation at a follow-up several years later, its clinical utility (as opposed to scientific validity) must be judged against a standard of selecting treatments. Although the differential treatment of AD with cholinesterase inhibitors and cerebrovascular disease with anticoagulants is established, the measurable cognitive improvement in AD is not large. In a useful review of neurotransmitter deficits in dementia, Huey et al. (2006) concluded that patients with frontotemporal dementia show deficiencies in the serotonin (e.g., Lanctot et al., 2007) and dopamine neurotransmitter systems while the acetylcholine system appears relatively intact. Thus, patient trials of antidementia drugs would appear to profit from functional neuroimaging because of its greater specificity than clinical diagnosis and good agreement with postmortem diagnosis. The lack of specificity in drug trials could lead to a diminution of effect size with underestimation of efficacy. Further, because many inpatients with dementia are treated with low-dose risperidone, a dopamine and serotonin blocker, separating vascular, Alzheimer, and frontotemporal dementia with FDG imaging might have a larger clinical impact than currently appreciated. Prediction of Development of Alzheimer’s Disease Progression from mild cognitive impairment to AD has been observed longitudinally with FDG-PET (see reviews in Pakrasi and O’Brien, 2005; Prvulovic et al., 2005; Uttner et al., 2006). Hippocampal hypometabolism predicted decline from normal to AD with 81% accuracy, which was confirmed in two cases by postmortem examination (Mosconi et al., 2005; de Leon et al., 2007). For cortical areas, patients with frontotemporal, thalamic, and cingulate changes were more likely to progress to having AD (Hunt et al., 2007). FDG-PET was superior to cerebrospinal fluid (CSF)-phospho-tau in predicting conversion to dementia in patients with mild cognitive impairment (Fellgiebel et al., 2007).

REGIONAL fMRI AND 015 CHANGES IN ALZHEIMER’S DISEASE Functional MRI studies in AD have consistently demonstrated altered patterns of activation in the medial temporal lobe (hippocampus) and neocortex during memory encoding compared with healthy controls (S.A. Small et al., 1999; Rombouts et al., 2000; Machulda et al., 2003; Sperling et al., 2003). Greater medial temporal lobe activation during a memory encoding task was present in a subgroup of individuals with mild cognitive impairment who demonstrated cognitive decline 2½ years after scanning, compared with a subgroup that remained clinically stable (Dickerson et al., 2004). Greater hippocampal activation predicted greater degree and rate of subsequent cognitive decline over 5.9 years of followup after scanning (S.L. Miller et al., 2007). Greater taskrelated increase in the fusiform and inferior frontal region in patients with AD than normals has also been found (Anderson et al., 2007). These findings suggest that increased activation of medial temporal lobe regions including the hippocampus and frontal lobes may reflect a compensatory response to AD pathology. AMALOID AND PLAQUE IMAGING IN ALZHEIMER’S DISEASE Amyloid deposits can be visualized in patients using Pittsburgh Compound B (Klunk et al., 2004) and other compounds (for a review, see Nordberg, 2007). Although this is primarily a structural imaging technique, its greater inclusion of frontal abnormalities, similarities in pattern to FDG uptake, and potential responsiveness to blood flow suggest its mention here. Frontotemporal Dementia Primary progressive aphasia, a progressive loss of language with sparing of other cognitive domains, is considered a variant of frontotemporal dementia (FTD). A longitudinal study found a markedly asymmetrical left superior and middle temporal lobe circumscribed area of hypometabolism expanding in a 1-year follow-up (Uttner et al., 2006). In patients with FDG with incontinence, right-hemispheric hypometabolic clusters were found in the premotor/anterior cingulate cortex and the putamen/claustrum/insula (Perneczky et al., 2008). Subtypes of Alzheimer’s Disease In AD, large individual differences, especially in cortical brain areas affected, as well as in neuropsychological deficit and rate of clinical progression, are characteristic. In a novel analysis, the coefficient of variation of the global metabolic pattern was found to be higher in patients with AD than normal controls (Volkow et al.,

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2002). Three major explanations may be proposed for this heterogeneity: (1) the existence of subtypes due to differing genetic and/or environmental interactions with predilections for varying anatomical areas and resulting symptom patterns; (2) parietal, frontal, and temporal metabolic decreases, often surprisingly asymmetrical, merely reflect variable regional expressions of a common underlying diffuse pathological process; (3) cross-sectional studies reveal different stages of progression from a pathological process initiated in the medial temporal lobe that spreads transynaptically through the corticocortical projections to the lateral temporal, frontal, and parietal lobes (e.g., Morrison, 1993). Most patients with AD show sparing of the visual regions on PET imaging; however, a subgroup with prominent visual symptoms including simultagnosia, visual agnosia, and Balint’s syndrome (visual inattention, oculomotor apraxia, and optic ataxia) showed marked metabolic decreases in the parietal and occipital cortex including the primary visual area (Pietrini et al., 1996; Nestor et al., 2003). A subsample of these patients had the diagnosis of AD confirmed at autopsy, suggesting that concurrent cerebrovascular disease was not important in these symptoms. Another behavioral subgroup of patients with AD with delusional misidentification syndrome (Mentis et al., 1995) shared the delusion that their husbands, wives, or physicians were impostors or that similar events had happened in the past. False beliefs in doubles and duplicates have been termed reduplicative paramnesias and include the Capgras syndrome. These patients showed lower metabolic rates in the orbitofrontal and neighboring cingulate gyrus regions than a comparison group of patients with AD without these symptoms. Reduplicative paramnesia has been seen after closed head injury, cerebral infarcts, and a variety of other neurological conditions (for a review, see Mentis et al., 1995), with a preponderance of focal lesions in frontal and temporal regions. The role of the frontal lobe in mnemonic organization and time sequencing would appear to be important in this disorder, as the reduplicated person is not typically an unrecognized stranger (as may appear in advanced AD) but rather an intimate companion as a quite accurate copy. Patients with AD and with apathy also have reduced medial frontal and anterior cingulate activity (Benoit et al., 2002). Information about the Apolipoprotein ε4 (ApoE4) allele may be a valuable way of subtyping patients with AD. Relatives with no dementia at risk for AD (G.W. Small et al., 1995) and patients with AD (Mosconi et al., 2008) with the E4 allele showed lower FDG-PET metabolic rates than individuals without the E4 allele. Somewhat random variation in the cortical area that is affected first in a progressive global brain illness could be related to the specific symptoms of a particular patient with AD. For example, the finding that patients with lower left-sided metabolism tend to show greater verbal intellectual impairment, whereas those with right

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hypometabolism show visuospatial impairments (Foster et al., 1983; Haxby et al., 1985; Koss et al., 1985; Grady et al., 1986; Haxby et al., 1986), would be consistent with this hypothesis (although Ober et al., 1991, did not show left–right hemisphere differentiation in visuoconstructive performance). The finding that right–left asymmetries of baseline and follow-up PET scans remain highly correlated over time (Mielke et al., 1994) suggests, however, that a regional predilection of the disease may occur with symptomatic subtypes. The presence of a stable factor structure would also tend to refute the random cortical area decrease hypothesis and support functional and etiological subgroups. Because factor analysis of metabolic rate in multiple brain areas requires large samples, there are only two such reports; one found parieto-temporal, paralimbic, left hemisphere, and frontoparietal factors (Grady et al., 1990), and the other found frontostriatal, central-occipital, fronto-striataltemporal-occipital, striato-temporoparietal, and mesial temporal-mesial frontal factors (Ichimiya et al., 1994). Although the factor structures are not entirely similar, they provide some data supporting the idea that AD does not strike random patches of cortex. Anatomically limited factors (frontostriatal, centro-occipital, and mesial temporal) showed no correlation with the Mini-Mental State Examination (MMSE) or clinical global dementia ratings, whereas the factors with wide weighting in the frontal, temporal, and parietal regions showed significant correlations (Ichimiya et al., 1994). This supports the important role of frontal connections with many other areas in the development of dementia; there appears to be no single anatomical lesion that alone yields high dementia rating scores. A potentially important subgrouping variable for AD is age of onset. Earlier age of onset has been associated with less subcortical and more widespread cortical metabolic loss (Ichimiya et al., 1994; Sakamoto et al., 2002). Progression of the illness may also account for variation in the PET metabolic decreases (Fig. 59.1). Metabolic rates in posterior cingulate, hippocampus, and temporal association areas (Schroder et al., 2001; Desgranges et al., 2002) and parietal regions (Santens et al., 2001) are significantly correlated with MMSE scores. Memory function in AD assessed by the selective reminding test was significantly correlated with hippocampal perfusion (Rodriguez et al., 2000). A longitudinal study indicated that decreases in the frontal lobe were most marked (Alexander et al., 2002), perhaps consistent with AD first striking the temporal lobe and then, once patients are identified, progressively affecting the frontal lobe. Cognitive Tasks in Alzheimer’s Disease Given that the defining behavioral characteristic of dementia is memory deficit, and given that activation with memory tasks has been well demonstrated with functional imaging, memory paradigms seem particularly

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useful in functional imaging in AD and other dementias. However, most investigators have used a resting condition. Higher test–retest reliability over a short interval for an activation task than in a resting condition was found in normal patients and patients with dementia (Duara et al., 1987). Six studies compared patients and normals and used a task salient for the hallmark behavioral memory deficit of AD during the uptake period (Miller et al., 1987; Buchsbaum et al., 1991; Kessler et al., 1991; Duara et al., 1992; Kessler et al., 1996; Valladares-Neto et al., 1995). These studies found the same temporo/parietal and frontal metabolic decreases during activation that were found in the resting studies. Duara et al. (1992) made a rigorous test of the differential power of resting versus activation conditions to identify patients and found them to be similar. Grady et al. (1993) used a face-matching task that did not have a memory component and observed the usual middle tempora/parietal decreases in AD across the face task and a control sensorimotor task. Surprisingly, at the occipital pole and in frontal premotor cortex, there was significantly greater activation in patients with mild to moderate AD. The authors interpreted this to suggest that patients with AD may have an increased attentional load during the face-matching task and are apparently still able to activate frontal regions. These results could indicate that early in the disease the initial temporal lobe decrease is relatively well fixed across resting, nonmemory, and memory tasks, but that frontal and sensory areas that are less completely affected can still be brought into play by the patient. Task studies in patients with more severe dementia might show the frontal deficits becoming more fixed. Although it could be argued that imaging under resting conditions makes comparability across studies more feasible, an activation task condition may be no more or less problematic than the resting state. In a recent article, Andreasen termed the so-called resting state random episodic silent thinking (REST) (Andreasen et al., 1995). They reviewed which cognitive activities may be activated in rest and presented data on which brain areas may be associated with memory activities at rest. Such strategic shifts in memory access involving the frontal lobe would clearly confound the interpretation of rest activities, especially early in the course of AD, when compensatory frontal activity (Grady et al., 1993) may occur. Memory tasks that stress a vulnerable system may be especially useful in high-risk studies that attempt to predict which patients with mild memory disturbance or which unaffected relatives of patients with AD will ultimately receive a diagnosis of AD. An analogy with highrisk studies of offspring of patients with schizophrenia could prove instructive. In such studies, more difficult versions of attentional tasks such as the continuous performance task were required to identify patients who would go on to develop schizophrenia, whereas easier

versions of the task, which show marked abnormalities in patients with manifest schizophrenia, did not elicit abnormal performance in the patients with preschizophrenia (Cornblatt and Erlenmeyer-Kimling, 1985). Course of Illness in Alzheimer’s Disease Serial scans of patients with AD from first memory impairment to end-stage illness could demonstrate an atrophic region restricted to the hippocampus that spreads to involve sequentially the lateral temporal lobe, the parietal lobe, and finally frontal cortex (Morrison, 1993). Alternatively, either lateral temporal, frontal, or parietal atrophy directly following hippocampal atrophy might appear, indicating global cortical change or random patchy cortical atrophy unrelated to rate of progression. To differentiate these possibilities, a data set would need methodologically consistent images and a sufficient sample size to allow testing of subgroup hypotheses. Although longitudinal studies in large samples of patients are lacking, PET studies have tended to find a wider range of cortical areas involved. Metabolic changes preceded neuropsychological changes in some patients with early-onset AD (Haxby et al., 1986). Restudy of a small sample of six patients 15 months apart demonstrated that progression in the parietal lobe was greater than in the frontal lobe (Jagust et al., 1988); this finding could reflect progression in a largely parietaldeficit subgroup, but the sample size and follow-up duration are small. Two studies have suggested that low frontal activity may predict more rapid decline. Decreased flow on SPECT predicted rapid decline in a longitudinal study (Hanyu et al., 1995), and frontal reduction in FDG-PET studies was associated with a more rapid clinical course (Mann et al., 1992). In addition, left prefrontal metabolic rate was the best predictor of premorbid function (Alexander et al., 1997). Although not a predictor of decline, changes in frontal and left temporal, but not whole hemisphere, measures of regional cerebral blood flow were correlated with changes in scores on the MMSE (Sachdev et al., 1997). Thus, a decline in frontal activity seems more closely linked to change in the clinical course early in the illness than a decline in activity in occipital cortical areas, a finding not inconsistent with the temporal to frontal to generalized cortical decrease pattern hypothesized by Morrison (1993), but longer-term follow-up is clearly necessary. Generalized decreases in cortical glucose metabolism in late-onset AD and more focal frontal and temporoparietal deficits in early-onset cases have been found (Mielke et al., 1991). Almost all of these studies suggest a more severe metabolic impairment in patients with early-onset disease, which may suggest a more virulent course. The lack of follow-up in these studies leaves unresolved the issue of regional progression, although they do support the view of a heterogeneous disorder.

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PICK’S DISEASE Pick’s disease is a rare dementing disorder with greater metabolic decrease and atrophy of the frontal lobe (Fig. 59.4) than other brain regions and correspondingly greater personality change in its early stages than in AD. Stereotypic behavior is common in Pick’s disease and frontotemporal degeneration (Shigenobu et al., 2002). Pathological changes (Dickson, 1998) consist of intraneuonal inclusions (Pick bodies). In a study of an autopsyconfirmed case of dementia with Pick’s disease (Friedland et al., 1993), the patient was scanned 4 years after the onset of illness, which was characterized by problems in understanding spoken language and agitation; the appearance of visual hallucinations was noted in the year of the PET scan. The greatest relative decrease (13%) was in the right frontal lobe in comparison with control values (0.90 vs. 1.03), whereas right temporal cortex was actually relatively greater than in controls (1.04 vs. 1.01). Specific reduction of frontal metabolic activity has been seen in other recent studies (Lieberman et al., 1998). Decreased frontal function, usually bilateral and combined with temporal lobe decreases, is seen in frontotemporal lobar degeneration (Schumann et al., 2000). In studies of Fahr’s disease, a frontal lobe/hyperkinetichypotonic syndrome, reductions in metabolic rate in the frontal lobe and in the putamen, globus pallidus, and temporal regions have been observed (Hempel et al., 2001). Differentiation of AD and frontotemporal dementia demonstrated greater parietal loss in AD but similar temporal findings (Santens et al., 2001).

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whereas smaller infarcts may show up less clearly on MRI. Scanning with FDG-PET may be valuable in the differential diagnosis (Figs. 59.3 and 59.5). In an important study, patients who had vascular dementia on clinical diagnosis and no cortical infarcts on MRI scans were studied (Sultzer et al., 1995). Frontal metabolic rates were lower in patients with infarcts in the basal ganglia and thalamus or anterior periventricular white matter abnormalities, whereas temporal metabolic rates were lower in individuals with posterior white matter change. This suggests that a disruption of frontostriatal and frontothalamic connections may be important in these remote cortical metabolic change patterns. Sultzer et al. (1995) noted that the PET images in their patients were similar to those seen in AD. With different treatments for vascular and Alzheimer’s dementia, this differentiation is important. In a population of vascular, AD, mixed, and frontotemporal dementia, PET showed greater sensitivity and specificity in identifying the different types of early dementia, especially in detecting AD (sensitivity 44%, specificity 83%), than SPECT (Dobert et al., 2005).

SUBCORTICAL DEMENTIA Parkinson’s Disease

Quite similar localization in PET and anatomical MRI may be seen with large, complete cerebral infarcts,

Patients with Parkinson’s disease and dementia may show temporoparietal PET changes similar to those seen in AD in comparison to patients with no dementia (Peppard et al., 1992). Patients with Parkinson’s disease without dementia showed the greatest differences from normals in posterior regions—primary visual, visual association, and parietal cortex—with no significant frontal lobe decrease (Eberling et al., 1994). In a rare study in which a PET scan was available for a patient initially diagnosed

59.4 Pick’s disease. Marked frontal decrease extends from the lower arrow to the upper arrow, with a relatively sharp margin bilaterally. The interhemispheric fissure is prominent.

FIGURE 59.5 Cerebrovascular disease. Left: isolated thalamic lacunar infarct associated with deja vue. Right: Multiple areas of marked decrease in metabolic rate associated with severe dementia.

VASCULAR DEMENTIA

FIGURE

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as having AD but found to have only Parkinson’s disease at autopsy, a temporoparietal decrease in metabolic rate was found, but frontal decreases were more marked than in a comparison group of patients with AD alone (Schapiro et al., 1993). Patients with diffuse Lewy body disease and AD had a temporoparietal-frontal pattern of metabolic decrease similar to that found in AD (Yong et al., 2007) but with decreases in primary visual areas as well (Albin et al., 1996). These patterns suggest that the dementia of Parkinson’s disease, like other dementias, usually is characterized by a widespread reduction in cortical metabolic rate, often involving frontal and temporal regions. Huntington’s Disease Huntington’s disease occurs in adulthood, sometimes first appearing as a psychiatric illness, a dementia, or a motor disorder. It is an autosomal dominant condition possibly associated with CAG repeats on chromosome

4 (Berrios et al., 2001) and affects the basal ganglia, causing a dramatic disappearance of the caudate and putamen on FDG-PET images (Dierks et al., 1999) (Figure 59.6). Presymptomatic gene carriers have significant decreases in caudate and putamen FDG metabolic rates as well as increases in occipital cortex (Feigin et al., 2001; Ciarmiello et al., 2006). ALCOHOLIC KORSAKOFF’S DEMENTIA Patients with Korsakoff’s syndrome showed FDG-PET decreases in the cingulate and precuneate areas (Joyce et al., 1994), and these differences were maintained even after correction for (CSF volume as measured on computed tomography (CT). Acute effects of alcohol appear primarily in the cortex (Volkow et al., 1990), but long-term effects after 6–8 weeks of abstinence were seen in the cingulate and orbitofrontal cortex (Volkow et al., 1997). Anterior temporal and frontal decreases have also been observed in detoxified patients with alcoholic organic mental disorders (P.R. Martin et al., 1992). OTHER DEMENTIAS Patients with myotonic dystrophy, a disease with autosomal dominant inheritance, show characteristic changes in muscle, heart, and the endocrine system as well as cerebral involvement. They often have associated organic personality disorders but tend not to show memory deficits as prominently as patients with AD do. Fluorodeoxyglucose-PET has shown significant metabolic decreases in the frontal cortex and lentiform nucleus of patients with myotonic dystrophy rather than in temporal areas, as frequently seen in AD (Mielke et al., 1993). In Creutzfeldt–Jakob disease, widespread metabolic decreases are noted that may appear in occipital, cerebellar, frontal, and perisylvian regions, unlike AD or Pick’s disease (Matochik et al., 1995; Henkel et al., 2002). IS CHRONIC SCHIZOPHRENIA A DEMENTING ILLNESS?

FIGURE 59.6 Huntington’s disease. Top row: A patient’s metabolic rate in the caudate and putamen is close to white matter values. Middle row: A normal volunteer shows the caudate and putamen clearly. Bottom row: Enlarged view of the striatal region with the caudate nucleus marked. Note near absence of uptake in caudate in Huntington’s disease.

Dementia praecox, an early name for schizophrenia and the gradual appearance of deficits in executive function and memory with progressive impairment in social or occupational function, certainly characterizes many patients with schizophrenia. Schizophrenia shares the pattern of temporal and frontal decreases in metabolic rate seen in AD and other dementias (for reviews of the more than 40 PET and regional cerebral blood flow studies, see Williamson, 1987; Buchsbaum, 1990; Andreasen

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et al., 1992; Chua and McKenna, 1995; Buchsbaum and Hazlett, 1998). Occipital metabolism, typically spared from decrease in AD, is often similarly spared or even elevated in patients with schizophrenia. Schultz et al. (2002) examined the relationship between age and cerebral blood flow (015-PET) in 49 unmedicated patients with schizophrenia during a resting condition and found negative correlations in anterior cingulate, frontal and parietal cortex bilaterally. The finding of reduced function in the anterior cingulate and frontal lobe with aging is consistent with previous findings in healthy individuals. However, the reduced regional cerebral blood flow (rCBF) observed in the parietal regions may be unique to schizophrenia. A study of elderly patients with schizophrenia with chronic illness and extended hospital stays indicates that a substantial number of them met clinical criteria for dementia, with global cognitive impairment (Davidson et al., 1995). Patients with AD and patients with schizophrenia who had the same level of overall cognitive impairment based on the MMSE showed different patterns of disabilities (Davidson et al., 1996). The patients with schizophrenia performed more poorly than the patients with AD on the naming and constructional praxis tests but were less impaired on the delayed recall measure. Thus, rapid forgetting of new information distinguishes AD from normal aging and also from the cognitive impairments of chronic schizophrenia (Welsh et al., 1991; Welsh et al., 1992). The evidence from this line of research suggests that the neural mechanisms underlying dementia in late-life schizophrenia and AD are dissimilar. Neurodegeneration (neuron loss, neurofibrillary tangles, astrocytosis, microgliosis) has generally not been found in elderly patients with schizophrenia (Falke et al., 2000). However, aspects of dementia, including disorganization, negative symptoms, and psychoticism, all correlated with blood flow in the cerebellum, suggesting a communality with the dementia of schizophrenia conceptualized as cognitive dysmetria (Kim et al., 2000). And like patients with AD, patients with schizophrenia showed frontal decrease (Carter et al., 1998), and frontal and hippocampal activation was seen on PET scans during memory tasks (Carter et al., 1998; Crespo-Facorro et al., 2001).

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visual inspection of the scans (Fig. 59.7) (Minoshima et al., 1995; Burdette et al., 1996; Schroder et al., 2001; Alexander et al., 2002; Herholz et al., 2002; Sakamoto et al., 2002; Shigenobu et al., 2002). The technique has the advantage of being able to explore the entire brain systematically in the search for specific areas of metabolic change, but its successful application requires that the region of change be in a similar pixel location in most patients. This requires the assumption that the same anatomical brain area is affected in most patients and the methodology to allow individual brains to be aligned so that the same anatomical areas in each patient appear at the same Cartesian coordinates. The first assumption, reviewed above, is met for AD, although clinical subtypes and individual variation cause slightly different areas in temporal and parietal lobes to be affected, sometimes asymmetrically (Ishii et al., 2001); if the centers of areas with the lowest FDG uptake fail to line up, t test comparisons may not be significant for the group. The second methodological requirement can be met through stable head positioning (Ruttimann et al., 1995) and image warping to align brains to the same coordinates (Fig. 59.8). The results of pixel-by-pixel analyses in AD demonstrate bilateral temporal and parietal change and, to a much lesser extent, medial temporal metabolic decreases with no frontal lobe change, perhaps suggesting that changes outside the lateral temporal cortex may be too variable in position to appear in aligned images. Images can be computed for each individual showing how far each voxel value is from the mean of a control group (typically

COMPUTER METHODS IN DEMENTIA IMAGE ANALYSIS Significance Probability Mapping and Dementia Subtyping Voxel-by-voxel mapping of brain imaging, first described as significance probability mapping by Bartels and Subach (1976) and later as statistical parametric mapping (Friston et al., 1991), is a useful adjunct to

FIGURE 59.7 Statistical comparison of normal (n = 47) and AD (n = 37) positron emission tomography scans after coregistration with MRI, brain extraction from skull and scalp, and 12-parameter standardizing to the shape of the normal brain. The image background is the Montreal Neurological Institute average anatomical MRI brain. Superimposed are patches which indicate areas where t tests reach or exceed p < .05, two-tailed (1.99) for a decrease. Note the lower relative metabolic rate in the temporal and parietal lobes in AD. AD: Alzheimer’s disease; MRI: magnetic resonance imaging.

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59.8 MRI scan in a normal elderly patient and a patient with AD. Top row: Unaltered FDG-PET scan. Second row: Brain extracted to remove FDG uptake in scalp and scatter. Third row: Images warped to adjust width (x), length (y) and height (z), x, y, and z position and x, y, and z tilt to standard Montreal Neurological Institute anatomical MRI brain created by averaging patients together. Bottom left: Normal patient image (left) and AD patient image (right) placed together before standardization. Bottom right: Normal patient image (left) and AD patient image (right) placed together after standardization. Note the low metabolism in the temporal lobe. Images are now sufficiently similar in shape so that they can be used in statistical analysis. MRI: Magnetic resonance imaging; AD: Alzheimer’s disease; FDG: fluorodeoxyglucose; PET: positron emission tomography.

FIGURE

FIGURE 59.10 Significance probability mapping of individual patient with AD and age-matched patient. Patient has extensive areas of temporal lobe decrease not found in typical patient not meeting criteria for AD or MCI. Insert box: Patient with schizophrenia shows frontal decrease in contrast to AD and normal. AD: Alzheimer’s disease; MCI: mild cognitive impairment.

expressed as Z scores and indicating the number of standard deviations the patient is from the control group). Human viewers tend to have better performance in diagnostic experiments when viewing these statistical images (Shidahara et al., 2006), and this is illustrated in Figures 59.9 and 59.10. Regional Area Measurements

FIGURE 59.9 Individual patient with AD showing comparison with 70 normal volunteers. Black patches mark areas where patient is more than two standard deviations below the group normal. The bitemporal (long arrows) and biparietal (short arrows) decreases indicate the characteristic AD pattern. Light gray patches are areas where relative metabolic rate is above normal and show preservation of parts of the primary occipital cortex striatum and thalamus. Unsmoothed data shows maximum scanner resolution and 6-mm smoothing preserves areas of abnormality and eliminates many small regions which may have appeared due to noise and cortical folding patterns. AD: Alzheimer’s disease.

Although whole slice significance probability maps can survey the entire brain, smaller areas such as the superior temporal gyrus or the hippocampus may have variable positions with respect to the outer brain margin and may be more accurately analyzed by tracing them on the MRI and assessing these values on PET. Tracing the hippocampus (Fig. 59.11) on each patient’s coregistered MRI scan may minimize this variation, allow medial temporal change to be visualized, and greatly improve patient/normal difference determination, as wisely done by some investigators (De Santi et al., 2001). This time-consuming process may be speeded up by the point-counting method, which yields the anatomical volume accurately (MacFall et al., 1994; Keshavan et al., 1995); with coregistered PET, a volumetric metabolic rate method may also be obtained. In our experience, the point-counting method is approximately sixto eightfold faster than outlining methods, but it has been little employed in quantification.

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with very low metabolic rates, hypermetabolic compensation by remaining neurons, or to merely closer packing of neurons, a supposition not clearly supported by most microscopic tissue examination. Further, two forms of analysis suggest that this anatomical change is not the sole reason for metabolic decrease. Cortical atrophy on MRI scans was used in analysis of covariance with regional CSF estimates as covariates to demonstrate that the degree of metabolic decrease in AD was much greater than expected on the basis of brain atrophy alone (Smith et al., 1992). An MRI-based partial volume correction procedure did not remove differences between patients and controls and enhanced rather than diminished correlations between regional glucose metabolic rate and neuropsychological test performance (Meltzer et al., 1996). The significance of relative metabolic rate decreases with age in the frontal lobes of men were preserved in eight of nine brain areas after partial volume correction (Yanase et al., 2005). These studies suggest the value of coregistered MRI templates with functional imaging and indicate that metabolic data offer additional information rather than merely duplicating the information provided by structural imaging. SUMMARY

59.11 Top: Coronal section of the temporal lobe with the hippocampus traced. Bottom: Three-dimensional visualization of the hippocampus based on 50–70 coronal sections in the same patients shown in Figure 57.6. Light gray areas are t tests where patients with AD have lower values than normal controls. AD: Alzheimer’s disease.

FIGURE

Sulcal Enlargement, Structural Shrinkage, and Metabolic Rate The characteristic sulcal widening associated with cortical shrinkage seen in dementias opens areas of the cerebral cortex to CSF, which is inactive metabolically. With the 4–6 mm resolution of PET, these sulcal areas are not fully resolved, and the cortical mantle could thus reflect an apparent reduction in metabolic rate per unit area of the slice image whereas the actual cortical metabolic rate per unit area of gray matter was unchanged. This would be possible if the cortical shrinkage was due exclusively or largely to loss of histological contents

In the dementia literature, general parallels are observed between data provided by functional imaging and by neuropathological studies. The two approaches converge in suggesting that processes involving the temporal and frontal lobes together are often associated with dementia. Findings in the primary sensory cortex or the occipital and parietal lobes without temporal or frontal involvement are less likely to be associated with dementia. Although neuropathology supplies microscopic detail and quantitative cell counts, quite obviously it cannot in itself be useful as a prognostic measure. Structural resolution with MRI provides gross anatomical resolution but does not reveal regional cortical deficits or correlations with behavioral dysfunction. Combined functional/structural brain imaging strategies are clearly necessary for precise assessment of the functional neuroanatomy. Techniques that examine relationships between metabolic rates in brain regions through correlation coefficients or path analysis may be especially promising for understanding the network of cortical communication that is diminished in dementia (Mentis et al., 1994; Horwitz et al., 1995). Older studies, which lacked high-resolution coregistered anatomical templates and were performed with PET instruments of lower resolution than are currently available, may have been unable to discern the function of key regions for the illness or assess the contribution of sulcal enlargement in the cortex to measures of metabolic rate. New prospective studies are needed to take advantage of the dramatically better resolution imaging now available

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and to accumulate samples of adequate size to facilitate an understanding of the biological heterogeneity of AD and other dementias. Longitudinal observation of the progression of dementia will allow us to determine whether these diffuse brain deficits follow a specific neuroanatomical program (for example, medial temporal, lateral temporal, frontal in AD) or attack cortical regions in a random and diffuse manner, with symptoms resulting from the particular neuroanatomical deficit but not being etiologically informative.

ACKNOWLEDGMENTS The authors thank the Charles A. Dana Foundation for supporting their study of normal aging and acknowledge support of NIH Anatomy and function of the thalamus in schizophrenia MH60023.

REFERENCES Albin, R.L., Minoshima, S., D’Amato, C.J., Frey, K.A., Kuhl, D.A., and Sima, A.A. (1996) Fluoro-deoxyglucose positron emission tomography in diffuse Lewy body disease. Neurology 47:462– 466. Alexander, G.E., Chen, K., Pietrini, P., Rapoport, S.I., and Reiman, E.M. (2002) Longitudinal PET evaluation of cerebral metabolic decline in dementia: a potential outcome measure in Alzheimer’s disease treatment studies. Am. J. Psychiatry 159:738–745. Alexander, G.E., Furey, M.L., Grady, C.L., et al. (1997) Association of premorbid intellectual function with cerebral metabolism in Alzheimer’s disease: implications for the cognitive reserve hypothesis. Am. J. Psychiatry 154:165–172. American Psychiatric Association. (1994) Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: Author. Anderson, K.E., Brickman, A.M., Flynn, J., Scarmeas, N., Van Heertum, R., Sackeim, H., et al. (2007) Impairment of nonverbal recognition in Alzheimer disease: a PET O-15 study. Neurology 69:32– 41. Andreasen, N., O’Leary, D.S., Cizadlo, T., et al. (1995) Remembering the past: two facets of episodic memory explored with positron emission tomography. Am. J. Psychiatry 152:1576 –1585. Andreasen, N.C., Rezai, K., Alliger, R., et al. (1992) Hypofrontality in neuroleptic-naive patients and in patients with chronic schizophrenia. Assessment with xenon 133 single-photon emission computed tomography and the Tower of London. Arch. Gen. Psychiatry 49:943–958. Arndt, S., Rajarethinam, R., Cizadlo, T., O’Leary, D., Downhill, J., and Andreasen, N.C. (1996) Landmark-based registration and measurement of magnetic resonance images: a reliability study. Psychiatry Res. 67:145–154. Arnold, S.E., Hyman, B.T., Flory, J., Damasio, A.R., and Van Hoesen, G.W. (1991) The topographical and neuroanatomical distribution of neurofibrillary tangles and neuritic plaques in the cerebral cortex of patients with Alzheimer’s disease. Cereb. Cortex 1: 103–116. Arnold, S.E., and Kumar, A. (1993) Reversible dementias. Med. Clin. North Am. 77:215–230. Azari, N.P., Pettigrew, K.D., Schapiro, M.B., et al. (1993) Early detection of Alzheimer’s disease: a statistical approach using positron emission tomographic data. J. Cereb. Blood Flow Metab. 13:438– 447. Bartels, P., and Subach, J. (1976) Significance probability mappings and automated interpretation of complex pictorial scenes. In: Preston, E., and Onoe, M., eds. Digital Processing of Biomedical Imagery. New York: Academic Press, pp. 101–114.

Bartlett, E., Brodie, J., Wolf, A., Christman, D., Laska, E., and Meissner, M. (1988) Reproducibility of cerebral glucose metabolic measurements in resting human subjects. J. Cereb. Blood Flow Metab. 8:502–512. Bartlett, E.J., Barouche, F., Brodie, J.D., et al. (1991) Stability of resting deoxyglucose metabolic values in PET studies of schizophrenia. Psychiatry Res. 40:11–20. Benoit, M., Koulibaly, P.M., Migneco, O., Darcourt, J., Pringuey, D.J., and Robert, P.H. (2002) Brain perfusion in Alzheimer’s disease with and without apathy: a SPECT study with statistical parametric mapping analysis. Psychiatry Res. 114:103–111. Berrios, G.E., Wagle, A.C., Markova, I.S., et al. (2001) Psychiatric symptoms and CAG repeats in neurologically asymptomatic Huntington’s disease gene carriers. Psychiatry Res. 102:217–225. Brickman, A.M., Buchsbaum, M.S., Shihabuddin, L., Hazlett, E.A., Borod, J.C., and Mohs, R.C. (2003) Striatal size, glucose metabolic rate, and verbal learning in normal aging. Brain Res. Cogn. Brain Res. 17:106–116. Buchsbaum, M., and Hazlett, E. (1998) Positron emission tomography studies of abnormal glucose metabolism in schizophrenia. Schizophr. Bull. 24:343–364. Buchsbaum, M.S. (1990) Frontal lobes, basal ganglia, temporal lobes—three sites for schizophrenia? Schizophr. Bull. 16:377–378. Buchsbaum, M.S., and Hazlett, E.A. (1997) Functional brain imaging and aging in schizophrenia. Schizophr. Res. 27:129–141. Buchsbaum, M.S., Kesslak, J.P., Lynch, G., et al. (1991) Temporal and hippocampal metabolic rate during an olfactory memory task assessed by positron emission tomography in patients with dementia of the Alzheimer type and controls. preliminary studies. Arch. Gen. Psychiatry 48:840–847. Buchsbaum, M.S., Potkin, S., Marshall, J., et al. (1992) Effects of clozapine and thiothixene on glucose metabolic rate in schizophrenia. Neuropsychopharmacology 6:155–163. Buchsbaum, M.S., Potkin, S.G., Siegel, B.V. Jr., et al. (1992) Striatal metabolic rate and clinical response to neuroleptics in schizophrenia. Arch. Gen. Psychiatry 49:966 –974. Burdette, J.H., Minoshima, S., Vander Borght, T., Tran, D.D., and Kuhl, D.E. (1996) Alzheimer disease: improved visual interpretation of PET images by using three-dimensional stereotaxic surface projections. Radiology 198:837–843. Cabeza, R. (2001) Cognitive neuroscience of aging: contributions of functional neuroimaging. Scand. J. Psychol. 42:277–286. Carter, C.S., Perlstein, W., Ganguli, R., Brar, J., Mintun, M., and Cohen, J.D. (1998) Functional hypofrontality and working memory dysfunction in schizophrenia. Am. J. Psychiatry 155:1285– 1287. Chua, S.E., and McKenna, P.J. (1995) Schizophrenia—a brain disease? A critical review of structural and functional cerebral abnormality in the disorder. Br. J. Psychiatry 166:563–582. Ciarmiello, A., Cannella, M., Lastoria, S., Simonelli, M., Frati, L., Rubinsztein, D.C., et al. (2006) Brain white-matter volume loss and glucose hypometabolism precede the clinical symptoms of Huntington’s disease. J. Nucl. Med. 47:215–222. Coffey, C.E., Wilkinson, W.E., Parashos, I.A., et al. (1992) Quantitative cerebral anatomy of the aging human brain: a cross-sectional study using magnetic resonance imaging. Neurology 42: 527– 536. Cornblatt, B.A., and Erlenmeyer-Kimling, L. (1985) Global attentional deviance as a marker of risk for schizophrenia: specificity and predictive validity. J. Abnorm. Psychol. 94:470– 486. Crespo-Facorro, B., Wiser, A.K., Andreasen, N.C., et al. (2001) Neural basis of novel and well-learned recognition memory in schizophrenia: a positron emission tomography study. Hum. Brain. Mapp. 12:219–231. Davidson, M., Harvey, P.D., Powchik, P., et al. (1995) Severity of symptoms in chronically institutionalized geriatric schizophrenic patients. Am. J. Psychiatry 152:197–207.

59: FUNCTIONAL BRAIN IMAGING STUDIES Davidson, M., Harvey, P., Welsh, K.A., Powchik, P., Putnam, K.M., and Mohs, R.C. (1996) Cognitive functioning in late-life schizophrenia: a comparison of elderly schizophrenic patients and patients with Alzheimer’s disease. Am. J. Psychiatry 153:1274 – 1279. DeCarli, C., Atack, J., Ball, M., et al. (1992) Post-mortem regional neurofibrillary tangle densities but not senile plaque densities are related to regional cerebral metabolic rates for glucose during life in Alzheimer’s disease patient. Neurodegeneration 1:113– 121. de Leon, M.J., Mosconi, L., Blennow, K., DeSanti, S., Zinkowski, R., Mehta, P.D., et al. (2007) Imaging and CSF studies in the preclinical diagnosis of Alzheimer’s disease. Ann. N.Y. Acad. Sci. 1097:114–145. DeQuardo, J.R., Bookstein, F.L., Green, W.D., Brunberg, J.A., and Tandon, R. (1996) Spatial relationships of neuroanatomic landmarks in schizophrenia. Psychiatry Res. 67:81–95. De Santi, S., de Leon, M., Convit, A., et al. (1995) Age-related changes in brain: II. Positron emission tomography of frontal and temporal lobe glucose metabolism in normal subjects. Psychiatry Q. 66:357–370. De Santi, S., de Leon, M.J., Rusinek, H., et al. (2001) Hippocampal formation glucose metabolism and volume losses in MCI and AD. Neurobiol. Aging 22:529–539. Desgranges, B., Baron, J.C., Lalevee, C., et al. (2002) The neural substrates of episodic memory impairment in Alzheimer’s disease as revealed by FDG-PET: relationship to degree of deterioration. Brain 125:1116–1124. Dickerson, B.C., Salat, D.H., Bates, J.F., Atiya, M., Killiany, R.J., Greve, D.N., et al. (2004) Medial temporal lobe function and structure in mild cognitive impairment. Ann. Neurology 56:27–35. Dickson, D.W. (1998) Pick’s disease: a modern approach. Brain Pathol. 8:339–354. Dierks, T., Linden, D.E., Hertel, A., et al. (1999) Multimodal imaging of residual function and compensatory resource allocation in cortical atrophy: a case study of parietal lobe function in a patient with Huntington’s disease. Psychiatry Res. 90:67–75. Dobert, N., Pantel, J., Frolich, L., Hamscho, N., Menzel, C., and Grunwald, F. (2005) Diagnostic value of FDG-PET and HMPAO-SPET in patients with mild dementia and mild cognitive impairment: metabolic index and perfusion index. Dement. Geriatr. Cogn. Disord. 20:63–70. Duara, R., Barker, W.W., Chang, J., Yoshii, F., Loewenstein, D.A., and Pascal, S. (1992) Viability of neocortical function shown in behavioral activation state PET studies in Alzheimer disease. J. Cereb. Blood Flow Metab. 12:927–934. Duara, R., Gross-Glenn, K., Barker, W.W., et al. (1987) Behavioral activation and the variability of cerebral glucose metabolic measurements. J. Cereb. Blood Flow Metab. 7:266–271. Eberling, J.L., Richardson, B.C., Reed, B.R., Wolfe, N., and Jagust, W.J. (1994) Cortical glucose metabolism in Parkinson’s disease without dementia. Neurobiol. Aging 15:329–335. Falke, E., Han, L.Y., and Arnold, S.E. (2000) Absence of neurodegeneration in the thalamus and caudate of elderly patients with schizophrenia. Psychiatry Res. 93:103–110. Feigin, A., Leenders, K.L., Moeller, J.R., et al. (2001) Metabolic network abnormalities in early Huntington’s disease: an [(18)F]FDG PET study. J. Nucl. Med. 42:1591–1595. Fellgiebel, A., Scheurich, A., Bartenstein, P., and Muller, M.J. (2007) FDG-PET and CSF phospho-tau for prediction of cognitive decline in mild cognitive impairment. Psychiatry Res. 155:167–171. Foster, N.L., Chase, T.N., Fedio, P., Patronas, N.J., Brooks, R.A., and Di Chiro, G. (1983) Alzheimer’s disease: focal cortical changes shown by positron emission tomography. Neurology 33:961– 965. Friedland, R.P., Koss, E., Lerner, A., et al. (1993) Functional imaging, the frontal lobes, and dementia. Dementia 4:192–203.

983

Friston, K.J., Frith, C., Liddle, P., and Frackowiak, R. (1991) Plastic transformation of PET images. J. Comput. Assist. Tomogr. 15: 634–659. Gallagher, M., and Rapp, P.R. (1997) The use of animal models to study the effects of aging on cognition. Annu. Rev. Psychol. 48: 339–370. Gonzalez, R.G., Fischman, A.J., Guimaraes, A.R., et al. (1995) Functional MR in the evaluation of dementia: correlation of abnormal dynamic cerebral blood volume measurements with changes in cerebral metabolism on positron emission tomography with fludeoxyglucose F 18. Am. J. Neuroradiol. 16:1763–1770. Grady, C.L., Haxby, J.V., Horwitz, B., et al. (1993) Activation of cerebral blood flow during a visuoperceptual task in patients with Alzheimer-type dementia. Neurobiol. Aging 14:35– 44. Grady, C.L., Haxby, J.V., Schapiro, M.B., et al. (1990) Subgroups in dementia of the Alzheimer type identified using positron emission tomography. J. Neuropsychiatry Clin. Neurosci. 2:373–384. Grady, C.L., Haxby, J.V., Schlageter, N.L., Berg, G., and Rapoport, S.I. (1986) Stability of metabolic and neuropsychological asymmetries in dementia of the Alzheimer type. Neurology 36:1390– 1392. Grady, C.L., McIntosh, A.R., Horwitz, B., et al. (1995) Age-related reductions in human recognition memory due to impaired encoding. Science 269:218–221. Hanyu, H., Nakano, S., Abe, S., Arai, H., Iwamoto, T., and Takasaki, M. (1995) [Longitudinal study of neuropsychological and cerebral blood flow changes in Alzheimer-type dementia]. Nippon Ronen Igakkai Zasshi 32:728–735. Haxby, J.V., Duara, R., Grady, C.L., Cutler, N.R., and Rapoport, S.I. (1985) Relations between neuropsychological and cerebral metabolic asymmetries in early Alzheimer’s disease. J. Cereb. Blood Flow Metab. 5:193–200. Haxby, J.V., Grady, C.L., Duara, R., Schlageter, N., Berg, G., and Rapoport, S.I. (1986) Neocortical metabolic abnormalities precede nonmemory cognitive defects in early Alzheimer’s-type dementia. Arch. Neurol. 43:882–885. Hazlett, E., Buchsbaum, M., Mohs, R., et al. (1998) Age-related shift in brain region allocation during successful memory performance. Neurobiol. Aging 19:437– 445. Heiss, W.D., Szelies, B., Kessler, J., and Herholz, K. (1991) Abnormalities of energy metabolism in Alzheimer’s disease studied with PET. Ann. N.Y. Acad. Sci. 640:65–71. Hempel, A., Henze, M., Berghoff, C., Garcia, N., Ody, R., and Schroder, J. (2001) PET findings and neuropsychological deficits in a case of Fahr’s disease. Psychiatry Res. 108:133–140. Henkel, K., Zerr, I., Hertel, A., et al. (2002) Positron emission tomography with [(18)F]FDG in the diagnosis of Creutzfeldt-Jakob disease (CJD). J. Neurol. 249:699–705. Herholz, K. (1995) FDG PET and differential diagnosis of dementia. Alzheimer Dis. Assoc. Disord. 9:6–16. Herholz, K., Schopphoff, H., Schmidt, M., et al. (2002) Direct comparison of spatially normalized PET and SPECT scans in Alzheimer’s disease. J. Nucl. Med. 43:21–26. Hertz, L., and Peng, L. (1992) Energy metabolism at the cellular level of the CNS. Can. J. Physiol. Pharmacol. 70:S145–S157. Higdon, R., Foster, N.L., Koeppe, R.A., DeCarli, C.S., Jagust, W.J., Clark, C.M., et al. (2004) A comparison of classification methods for differentiating fronto-temporal dementia from Alzheimer’s disease using FDG-PET imaging. Stat. Med. 23:315–326. Hof, P.R., Cox, K., and Morrison, J.H. (1990) Quantitative analysis of a vulnerable subset of pyramidal neurons in Alzheimer’s disease: I. Superior frontal and inferior temporal cortex. J. Comp. Neurol. 301:44–54. Hof, P.R., and Morrison, J.H. (1990) Quantitative analysis of a vulnerable subset of pyramidal neurons in Alzheimer’s disease: II. Primary and secondary visual cortex. J. Comp. Neurol. 301: 55–64.

984

DEMENTIA

Hof, P., and Morrison, J. (1994) The cellular basis of cortical disconnection in Alzheimer’s disease and related dementing conditions. In: Terry, R., Katzman, R., and Bick, K., eds. Alzheimer Disease. New York: Raven Press, pp. 197–229. Hoffman, J.M., Welsh-Bohmer, K.A., and Hanson, M., et al. (2000) FDG PET imaging in patients with pathologically verified dementia. J. Nucl. Med. 41:1920–1928. Honda, N., Machida, K., Hosono, M., Matsumoto, T., Matsuda, H., Oshima, M., et al. (2002) Interobserver variation in diagnosis of dementia by brain perfusion SPECT. Radiat. Med. 20: 281–289. Horwitz, B., McIntosh, A.R., Haxby, J.V., et al. (1995) Network analysis of PET-mapped visual pathways in Alzheimer type dementia. Neuroreport 6:2287–2292. Huey, E.D., Putnam, K.T., and Grafman, J. (2006) A systematic review of neurotransmitter deficits and treatments in frontotemporal dementia. Neurology 66:17–22. Hunt, A., Schonknecht, P., Henze, M., Seidl, U., Haberkorn, U., and Schroder, J. (2007) Reduced cerebral glucose metabolism in patients at risk for Alzheimer’s disease. Psychiatry Res. 155: 147–154. Ichimiya, A., Herholz, K., Mielke, R., Kessler, J., Slansky, I., and Heiss, W.D. (1994) Difference of regional cerebral metabolic pattern between presenile and senile dementia of the Alzheimer type: a factor analytic study. J. Neurol. Sci. 123:11–17. Ishii, K., Willoch, F., Minoshima, S., et al. (2001) Statistical brain mapping of 18F-FDG PET in Alzheimer’s disease: validation of anatomic standardization for atrophied brains. J. Nucl. Med. 42:548–557. Jagust, W.J., Eberling, J.L., Richardson, B.C., et al. (1993) The cortical topography of temporal lobe hypometabolism in early Alzheimer’s disease. Brain Res. 629:189–198. Jagust, W.J., Friedland, R.P., Budinger, T.F., Koss, E., and Ober, B. (1988) Longitudinal studies of regional cerebral metabolism in Alzheimer’s disease. Neurology 38:909–912. Jagust, W., Reed, B., Mungas, D., Ellis, W., and Decarli, C. (2007) What does fluorodeoxyglucose PET imaging add to a clinical diagnosis of dementia? Neurology 69:871–877. Jobst, K.A., Smith, A.D., Barker, C.S., et al. (1992) Association of atrophy of the medial temporal lobe with reduced blood flow in the posterior parietotemporal cortex in patients with a clinical and pathological diagnosis of Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 55:190–194. Joyce, E.M., Rio, D.E., Ruttimann, U.E., et al. (1994) Decreased cingulate and precuneate glucose utilization in alcoholic Korsakoff’s syndrome. Psychiatry Res. 54:225–239. Kapur, S., Craik, F.I., Jones, C., Brown, G.M., Houle, S., and Tulving, E. (1995) Functional role of the prefrontal cortex in retrieval of memories: a PET study. Neuroreport 6:1880–1884. Keshavan, M.S., Anderson, S., Beckwith, C., Nash, K., Pettegrew, J.W., and Krishnan, K.R. (1995) A comparison of stereology and segmentation techniques for volumetric measurements of lateral ventricles in magnetic resonance imaging. Psychiatry Res. 61: 53–60 Kessler, J., Ghaemi, M., Mielke, R., Herholz, K., and Heiss, W.D. (1996) Visual versus auditory memory stimulation in patients with probable Alzheimer’s disease. A PET study with 18 FDG. Ann. N.Y. Acad. Sci. 777:233–238. Kessler, J., Herholz, K., Grond, M., and Heiss, W.D. (1991) Impaired metabolic activation in Alzheimer’s disease: a PET study during continuous visual recognition. Neuropsychologia 29:229– 243. Kim, J.J., Mohamed, S., Andreasen, N.C., et al. (2000) Regional neural dysfunctions in chronic schizophrenia studied with positron emission tomography. Am. J. Psychiatry 157:542–548. Klunk, W.E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D.P., et al. (2004) Imaging brain amyloid in Alzheimer’s

disease with Pittsburgh Compound-B. Ann. Neurology 55:306– 319. Koss, E., Friedland, R.P., Ober, B.A., and Jagust, W.J. (1985) Differences in lateral hemispheric asymmetries of glucose utilization between early- and late-onset Alzheimer-type dementia. Am. J. Psychiatry 142:638– 640. Kuhl, D.E., Metter, E.J., Riege, W.H., and Phelps, M.E. (1982) Effects of human aging on patterns of local cerebral glucose utilization determined by the [18F]fluorodeoxyglucose method. J. Cereb. Blood Flow Metab. 2:163–171. Kumar, A., Schapiro, M.B., Grady, C., et al. (1991) High-resolution PET studies in Alzheimer’s disease. Neuropsychopharmacology 4:35– 46. Lanctot, K., Herrmann, N., Ganjavi, H., Black, S., Rusjan, P., Houle, S., et al. (2007) Serotonin-1A receptors in frontotemporal dementia compared to controls. Psychiatry Res. 156(3):247–250. Leenders, K.L., Perani, D., Lammertsma, A.A., et al. (1990) Cerebral blood flow, blood volume and oxygen utilization. Normal values and effect of age. Brain 113:27– 47. Lewis, D.A., Campbell, M.J., Terry, R.D., and Morrison, J.H. (1987) Laminar and regional distributions of neurofibrillary tangles and neuritic plaques in Alzheimer’s disease: a quantitative study of visual and auditory cortices. J. Neurosci. 7:1799–1808. Lieberman, A.P., Trojanowski, J.Q., Lee, V.M., et al. (1998) Cognitive, neuroimaging, and pathological studies in a patient with Pick’s disease. Ann. Neurol. 43:259–265. Loessner, A., Alavi, A., Lewandrowski, K.U., Mozley, D., Souder, E., and Gur, R.E. (1995) Regional cerebral function determined by FDG-PET in healthy volunteers: normal patterns and changes with age. J. Nucl. Med. 36:1141–1149. MacFall, J.R., Byrum, C.E., Parashos, I., et al. (1994) Relative accuracy and reproducibility of regional MRI brain volumes for pointcounting methods. Psychiatry Res. 55:167–177. Machulda, M.M., Ward, H.A., Borowski, B., Gunter, J.L., Cha, R.H., O’Brien, P.C., et al. (2003) Comparison of memory fMRI response among normal, MCI, and Alzheimer’s patients. Neurology 61:500–506. Mann, U.M., Mohr, E., Gearing, M., and Chase, T.N. (1992) Heterogeneity in Alzheimer’s disease: progression rate segregated by distinct neuropsychological and cerebral metabolic profiles. J. Neurol. Neurosurg. Psychiatry 55:956–959. Maquet, P., Dive, D., Salmon, E., von Frenckel, R., and Franck, G. (1990) Reproducibility of cerebral glucose utilization measured by PET and the [18F]-2-fluoro-2-deoxy-d-glucose method in resting, healthy human subjects. Eur. J. Nucl. Med. 16:267–273. Martin, A., Friston, K., Colebatch, J., and Frackowiak, R. (1991) Decreases in regional cerebral blood flow with normal aging. J. Cereb. Blood Flow Metab. 11:684 – 689. Martin, P.R., Rio, D., Adinoff, B., et al. (1992) Regional cerebral glucose utilization in chronic organic mental disorders associated with alcoholism. J. Neuropsychiatry Clin. Neurosci. 4:159–167. Matochik, J.A., Molchan, S.E., Zametkin, A.J., Warden, D.L., Sunderland, T., and Cohen, R.M. (1995) Regional cerebral glucose metabolism in autopsy-confirmed Creutzfeldt-Jakob disease. Acta Neurol. Scand. 91:153–157. McGeer, E.G., Peppard, R.P., McGeer, P.L., et al. (1990) 18Fluorodeoxyglucose positron emission tomography studies in presumed Alzheimer cases, including 13 serial scans. Can. J. Neurol. Sci. 17:1–11. Meguro, K., Yamaguchi, S., Yamazaki, H., et al. (1996) Cortical glucose metabolism in psychiatric wandering patients with vascular dementia. Psychiatry Res. 67:71–80. Meltzer, C.C., Zubieta, J.K., Brandt, J., Tune, L.E., Mayberg, H.S., and Frost, J.J. (1996) Regional hypometabolism in Alzheimer’s disease as measured by positron emission tomography after correction for effects of partial volume averaging. Neurology 47: 454 – 461.

59: FUNCTIONAL BRAIN IMAGING STUDIES Mentis, M.J., Salerno, J., Horwitz, B., et al. (1994) Reduction of functional neuronal connectivity in long-term treated hypertension. Stroke 25:601–607. Mentis, M.J., Weinstein, E.A., Horwitz, B., et al. (1995) Abnormal brain glucose metabolism in the delusional misidentification syndromes: a positron emission tomography study in Alzheimer disease. Biol. Psychiatry 38:438– 449. Messa, C., Fazio, F., Costa, D.C., and Ell, P.J. (1995) Clinical brain radionuclide imaging studies. Semin. Nucl. Med. 25:111–143. Mielke, R., Herholz, K., Fink, G., Ritter, D., and Heiss, W.D. (1993) Positron emission tomography in myotonic dystrophy. Psychiatry Res. 50:93–99. Mielke, R., Herholz, J., Grond, M., Kessler, J., and Heiss, W. (1991) Differences in regional cerebral glucose metabolism between presenile and senile dementia of Alzheimer type. Neurobiol. Aging 13:93–98. Mielke, R., Herholz, K., Grond, M., Kessler, J., and Heiss, W.D. (1992) Severity of vascular dementia is related to volume of metabolically impaired tissue. Arch. Neurol. 49:909–913. Mielke, R., Herholz, K., Grond, M., Kessler, J., and Heiss, W.D. (1994) Clinical deterioration in probable Alzheimer’s disease correlates with progressive metabolic impairment of association areas. Dementia 5:36– 41. Mielke, R., Schroder, R., Fink, G.R., Kessler, J., Herholz, K., and Heiss, W.D. (1996) Regional cerebral glucose metabolism and postmortem pathology in Alzheimer’s disease. Acta Neuropathol. 91:174 –179. Miller, J.D., de Leon, M.J., Ferris, S.H., et al. (1987) Abnormal temporal lobe response in Alzheimer’s disease during cognitive processing as measured by 11C-2-deoxy-d-glucose and PET. J. Cereb. Blood Flow Metab. 7:248–251. Miller, S.L., Fenstermacher, E., Bates, J., Blacker, D., Sperling, R.A., and Dickerson, B.C. (2007) Hippocampal activation in adults with mild cognitive impairment predicts subsequent cognitive decline. J. Neurol. Neurosurg. Psychiatry. Sept 10 [Epub ahead of print] Minoshima, S., Frey, K.A., Koeppe, R.A., Foster, N.L., and Kuhl, D.E. (1995) A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18FDG PET. J. Nucl. Med. 36:1238 –1248. Moeller, J., Ishikawa, T., Dhawan, V., et al. (1996) The metabolic topography of normal aging. J. Cereb. Blood Flow Metab. 16: 385–398. Morrison, J.H. (1993) Differential vulnerability, connectivity, and cell typology. Neurobiol. Aging 14:51–54; discussion 55–56. Mosconi, L., De Santi, S., Brys, M., Tsui, W.H., Pirraglia, E., Glodzik-Sobanska, L., et al. (2008) Hypometabolism and altered cerebrospinal fluid markers in normal apolipoprotein E E4 carriers with subjective memory complaints. Biol. Psychiatry 63(6): 609– 618. Mosconi, L., Tsui, W.H., De Santi, S., Li, J., Rusinek, H., Convit, A., et al. (2005) Reduced hippocampal metabolism in MCI and AD: automated FDG-PET image analysis. Neurology 64:1860– 1867. Murphy, D.G., Bottomley, P.A., Salerno, J.A., et al. (1993) An in vivo study of phosphorus and glucose metabolism in Alzheimer’s disease using magnetic resonance spectroscopy and PET. Arch. Gen. Psychiatry 50:341–349. Murphy, D.G., DeCarli, C., McIntosh, A.R., et al. (1996) Sex differences in human brain morphometry and metabolism: an in vivo quantitative magnetic resonance imaging and positron emission tomography study on the effect of aging. Arch. Gen. Psychiatry 53:585–594. Nestor, P.J., Caine, D., Fryer, T.D., Clarke, J., and Hodges, J.R. (2003) The topography of metabolic deficits in posterior cortical atrophy (the visual variant of Alzheimer’s disease) with FDGPET. J. Neurol. Neurosurg. Psychiatry 74:1521–1529.

985

Nihashi, T., Yatsuya, H., Hayasaka, K., Kato, R., Kawatsu, S., Arahata, Y., et al. (2007) Direct comparison study between FDG-PET and IMP-SPECT for diagnosing Alzheimer’s disease using 3D-SSP analysis in the same patients. Radiat. Med. 25:255–262. Nordberg, A. (2007) Amyloid imaging in Alzheimer’s disease. Curr. Opin. Neurol. 20:398– 402. Nordberg, A., Lilja, A., Lundqvist, H., et al. (1992) Tacrine restores cholinergic nicotinic receptors and glucose metabolism in Alzheimer patients as visualized by positron emission tomography. Neurobiol. Aging 13:747–758. Nyback, H., Nyman, H., Blomqvist, G., Sjogren, I., and StoneElander, S. (1991) Brain metabolism in Alzheimer’s dementia: studies of 11C-deoxyglucose accumulation, CSF monoamine metabolites and neuropsychological test performance in patients and healthy subjects. J. Neurol. Neurosurg. Psychiatry 54:672– 678. Ober, B.A., Jagust, W.J., Koss, E., Delis, D.C., and Friedland, R.P. (1991) Visuoconstructive performance and regional cerebral glucose metabolism in Alzheimer’s disease. J. Clin. Exp. Neuropsychol. 13:752–772. Pakrasi, S., and O’Brien, J.T. (2005) Emission tomography in dementia. Nucl. Med. Comm. 26:189–196. Pearlson, G.D., Harris, G.J., Powers, R.E., et al. (1992) Quantitative changes in mesial temporal volume, regional cerebral blood flow, and cognition in Alzheimer’s disease. Arch. Gen. Psychiatry 49: 402– 408. Pearson, R.C., Esiri, M.M., Hiorns, R.W., Wilcock, G.K., and Powell, T.P. (1985) Anatomical correlates of the distribution of the pathological changes in the neocortex in Alzheimer disease. Proc. Natl. Acad. Sci. USA 82:4531– 4534. Peppard, R.F., Martin, W.R., Carr, G.D., et al. (1992) Cerebral glucose metabolism in Parkinson’s disease with and without dementia. Arch. Neurol. 49:1262–1268. Perneczky, R., Diehl-Schmid, J., Forstl, H., Drzezga, A., May, F., and Kurz, A. (2008) Urinary incontinence and its functional anatomy in frontotemporal lobar degenerations. Eur. J. Nucl. Med. Mol. Imaging 35(3):605–610. Pietrini, P., Furey, M.L., Graff-Radford, N., et al. (1996) Preferential metabolic involvement of visual cortical areas in a subtype of Alzheimer’s disease: clinical implications. Am. J. Psychiatry 153: 1261–1268. Poon, L. (1985) Differences in human memory with aging: nature, causes, and clinical implications. In: Birren, J., and Schaie, K., eds. Handbook of the Psychology of Aging. New York: Van Nostrand Reinhold, pp. 427– 462. Prvulovic, D., Van de Ven, V., Sack, A.T., Maurer, K., and Linden, D.E. (2005) Functional activation imaging in aging and dementia. Psychiatry Res. 140:97–113. Reuter-Lorenz, P., Jonides, J., Smith, E., Hartley, A., Miller, A., Marshuetz, C., et al. (2000) Age differences in frontal lateralization of verbal and spatial working memory revealed by PET. J. Cogn. Neurosci. 12:174–187. Rodriguez, G., Vitali, P., Calvini, P., et al. (2000) Hippocampal perfusion in mild Alzheimer’s disease. Psychiatry Res. 100:65–74. Rogers, J., and Morrison, J.H. (1985) Quantitative morphology and regional and laminar distributions of senile plaques in Alzheimer’s disease. J. Neurosci. 5:2801–2808. Rombouts, S.A., Barkhof, F., Veltman, D.J., Machielsen, W.C., Witter, M.P., Bierlaagh, M.A., et al. (2000) Functional MR imaging in Alzheimer’s disease during memory encoding. Am. J. Neuroradiol. 21:1869–1875. Ruttimann, U.E., Andreason, P.J., and Rio, D. (1995) Head motion during positron emission tomography: is it significant? Psychiatry Res. 61:43–51. Sachdev, P., Gaur, R., Brodaty, H., et al. (1997) Longitudinal study of cerebral blood flow in Alzheimer’s disease using single photon emission tomography. Psychiatry Res. 68:133–141.

986

DEMENTIA

Sakamoto, S., Ishii, K., Sasaki, M., et al. (2002) Differences in cerebral metabolic impairment between early and late onset types of Alzheimer’s disease. J. Neurol. Sci. 200:27–32. Salmon, E., Maquet, P., Sadzot, B., Degueldre, C., Lemaire, C., and Franck, G. (1991) Decrease of frontal metabolism demonstrated by positron emission tomography in a population of healthy elderly volunteers. Acta Neurol. Belg. 91:288–295. Santens, P., De Bleecker, J., Goethals, P., et al. (2001) Differential regional cerebral uptake of (18)F-fluoro-2-deoxy-d-glucose in Alzheimer’s disease and frontotemporal dementia at initial diagnosis. Eur. Neurol. 45:19–27. Sarangi, S., San Pedro, E.C., and Mountz, J.M. (2000) Anterior choroidal artery infarction presenting as a progressive cognitive deficit. Clin. Nucl. Med. 25:187–190. Schapiro, M.B., Pietrini, P., Grady, C.L., et al. (1993) Reductions in parietal and temporal cerebral metabolic rates for glucose are not specific for Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 56:859–864. Schroder, J., Buchsbaum, M.S., Shihabuddin, L., et al. (2001) Patterns of cortical activity and memory performance in Alzheimer’s disease. Biol. Psychiatry 49:426– 436. Schultz, S.K., O’Leary, D.S., Boles Ponto, L.L., Arndt, S., Magnotta, V., Watkins, G.L., et al. (2002) Age and regional cerebral blood flow in schizophrenia: age effects in anterior cingulate, frontal, and parietal cortex. J. Neuropsychiatry Clin. Neurosci. 14:19–24. Schumann, G., Halsband, U., Kassubek, J., et al. (2000) Combined semantic dementia and apraxia in a patient with frontotemporal lobar degeneration. Psychiatry Res. 100:21–29. Shidahara, M., Inoue, K., Maruyama, M., Watabe, H., Taki, Y., Goto, R., et al. (2006) Predicting human performance by channelized Hotelling observer in discriminating between Alzheimer’s dementia and controls using statistically processed brain perfusion SPECT. Ann. Nucl. Med. 20:605–613. Shigenobu, K., Ikeda, M., Fukuhara, R., et al. (2002) The Stereotypy Rating Inventory for frontotemporal lobar degeneration. Psychiatry Res. 110:175–187. Small, G.W., Mazziotta, J.C., Collins, M.T., et al. (1995) Apolipoprotein E type 4 allele and cerebral glucose metabolism in relatives at risk for familial Alzheimer disease. JAMA 273:942–947. Small, G.W., Okonek, A., Mandelkern, M.A., et al. (1994) Age-associated memory loss: initial neuropsychological and cerebral metabolic findings of a longitudinal study. Int. Psychogeriatr. 6:23–44; discussion 60–62. Small, S.A., Perera, G.M., DeLaPaz, R., Mayeux, R., and Stern, Y. (1999) Differential regional dysfunction of the hippocampal formation among elderly with memory decline and Alzheimer’s disease. Ann. Neurol. 45:466– 472. Smith, G.S., de Leon, M.J., George, A.E., et al. (1992) Topography of cross-sectional and longitudinal glucose metabolic deficits in Alzheimer’s disease. pathophysiologic implications. Arch. Neurol. 49:1142–1150. Sokoloff, L., Reivich, M., Kennedy, C., et al. (1977) The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J. Neurochem. 28: 897–916. Sperling, R.A., Bates, J.F., Chua, E.F., Cocchiarella, A.J., Rentz, D.M., Rosen, B.R., et al. (2003) fMRI studies of associative encoding in young and elderly controls and mild Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 74:44 –50. Stuss, D., and Benson, D. (1986) The Frontal Lobes. New York: Raven Press. Sultzer, D.L., Mahler, M.E., Cummings, J.L., Van Gorp, W.G., Hinkin, C.H., and Brown, C. (1995) Cortical abnormalities

associated with subcortical lesions in vascular dementia. Clinical and position emission tomographic findings. Arch. Neurol. 52: 773–780. Takada, H., Nagata, K., Hirata, Y., et al. (1992) Age-related decline of cerebral oxygen metabolism in normal population detected with positron emission tomography. Neurol. Res. 14:128–131. Teipel, S.J., Drzezga, A., Bartenstein, P., Moller, H.J., Schwaiger, M., and Hampel, H. (2006) Effects of donepezil on cortical metabolic response to activation during (18)FDG-PET in Alzheimer’s disease: a double-blind cross-over trial. Psychopharmacology 187: 86–94. Tempel, L.W., and Perlmutter, J.S. (1992) Vibration-induced regional cerebral blood flow responses in normal aging. J. Cereb. Blood Flow Metab. 12:554 –561. Tulving, E., Kapur, S., Craik, F., Moscovitch, M., and Houle, S. (1994) Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings. Proc. Natl. Acad. Sci. USA 91:2016–2020. Uttner, I., Mottaghy, F.M., Schreiber, H., Riecker, A., Ludolph, A.C., and Kassubek, J. (2006) Primary progressive aphasia accompanied by environmental sound agnosia: a neuropsychological, MRI and PET study. Psychiatry Res. 146:191–197. Valladares-Neto, D.C., Buchsbaum, M.S., Evans, W.J., et al. (1995) EEG delta, positron emission tomography, and memory deficit in Alzheimer’s disease. Neuropsychobiology 31:173–181. Van Hoesen, G., and Damasio, A. (1987) Neural correlates of cognitive impairment in Alzheimer’s disease. In: Mountcastle, V., Plum, F., and Geiger, S., eds. Handbook of Physiology: The Nervous System, Vol. V, Higher Functions of the Brain. Bethesda, MD: American Physiological Society, pp. 871–898. Volkow, N.D., Hitzemann, R., Wolf, A.P., et al. (1990) Acute effects of ethanol on regional brain glucose metabolism and transport. Psychiatry Res. 35:39–48. Volkow, N.D., Wang, G.J., Overall, J.E., et al. (1997) Regional brain metabolic response to lorazepam in alcoholics during early and late alcohol detoxification. Alcohol Clin. Exp. Res. 21:1278– 1284. Volkow, N.D., Zhu, W., Felder, C.A., et al. (2002) Changes in brain functional homogeneity in subjects with Alzheimer’s disease. Psychiatry Res. 114:39–50. Wang, G.J., Volkow, N.D., Wolf, A.P., Brodie, J.D., and Hitzemann, R.J. (1994) Intersubject variability of brain glucose metabolic measurements in young normal males. J. Nucl. Med. 35:1457– 1466. Welsh, K., Butters, N., Hughes, J., Mohs, R., and Heyman, A. (1991) Detection of abnormal memory decline in mild cases of Alzheimer’s disease using CERAD neuropsychological measures. Arch. Neurol. 48:278–281. Welsh, K.A., Butters, N., Hughes, J.P., Mohs, R.C., and Heyman, A. (1992) Detection and staging of dementia in Alzheimer’s disease. Use of the neuropsychological measures developed for the Consortium to Establish a Registry for Alzheimer’s disease. Arch. Neurol. 49:448– 452. Williamson, P. (1987) Hypofrontality in schizophrenia: a review of the evidence. Can. J. Psychiatry 32:399– 404. Yanase, D., Matsunari, I., Yajima, K., Chen, W., Fujikawa, A., Nishimura, S., et al. (2005) Brain FDG PET study of normal aging in Japanese: effect of atrophy correction. Eur. J. Nucl. Med. Mol. Imaging 32:794 –805. Yong, S.W., Yoon, J.K., An, Y.S., and Lee, P.H. (2007) A comparison of cerebral glucose metabolism in Parkinson’s disease, Parkinson’s disease dementia and dementia with Lewy bodies. Eur. J. Neurol. 14(12):1357–1362.

60 Principles of the Pharmacotherapy of Dementia CHRISTINE BERGMANN

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The awareness of cognitive loss and dementia has grown dramatically in the past 10 years, leading to routine diagnosis of many of these diseases, including the most common, Alzheimer’s disease (AD). Alzheimer’s disease is a neurodegenerative condition characterized by progressive cognitive and functional deterioration with an estimated prevalence of over 4 million in the United States. Treatments for AD have been the focus of considerable research. In the past decade, five treatments, representing two classes of drugs, have been approved. Currently, over 160 registered trials in the United States are recruiting patients for the treatment of AD, and many others have been completed and reported. This chapter reviews the pharmacology underlying the currently approved treatments; describes completed trials representing mechanisms and hypotheses identified by clinical observations, epidemiological findings, and basic science; and surveys ongoing clinical trials evaluating new possible mechanisms. We begin by reviewing currently approved medications for the treatment of dementia. Next, we describe strategies that target amyloid, the current most likely mechanism for intervention. Many different mechanisms of action have been proposed based on laboratory data, animal models, and clinical observation; we present the results of clinical trials testing these mechanisms. CHOLINESTERASE INHIBITORS After its release into the synaptic cleft, the neurotransmitter acetylcholine is degraded rapidly by the hydrolytic activity of cholinesterases. In the human brain, the most prominent enzyme involved in acetylcholine hydrolysis in acetylcholinesterase. Additional evidence suggests that butyrylcholinesterase can also hydrolyze acetylcholine in the human brain and may be involved in cholinergic transmission (Mesulam et al., 2002). Reductions in the activities of acetylcholinesterase and choline acetyltransferase, enzymes involved in the synthesis and degradation of acetylcholine, were found in brain tissues from patients with AD (Davies and Maloney,

MARY SANO

1976). Butyrylcholinesterase constitutes only a small percentage of brain cholinesterase activity in normal aging but has been shown to be increased to 30% in the brains of patients with AD (Mesulam and Geula, 1994). These findings led to the cholinergic hypothesis of AD. According to this hypothesis, the destruction of cholinergic neurons in the basal forebrain and the resulting deficit in central cholinergic transmission contribute substantially to the cognitive deficits and behavioral symptoms observed in patients suffering from AD (Bartus et al., 1982). Inhibition of cholinesterases leads to an increase of acetylcholine concentration in the synaptic cleft and is thought to enhance cholinergic transmission and ameliorate cholinergic deficit. Four cholinesterase inhibitors are available: tacrine, donepezil, rivastigmine, and galantamine. Of these, the first commercially available cholinesterase inhibitor, tacrine, is now rarely used because of its hepatotoxic side effects in 40% of all patients (Watkins et al., 1994). The three second-generation cholinesterase inhibitors, donepezil, rivastigmine, and galantamine, are approved for the treatment of AD and are considered the standard of care by the American Academy of Neurology (Doody et al., 2001). Donepezil and galantamine are selective inhibitors of acetylcholinesterase, whereas rivastigmine also inhibits butyrylcholinesterase (Cutler et al, 1998). This class of medications was originally approved for the treatment of patients with mild to moderate disease, and in 2007 the indication for donepezil was expanded to severe AD. Systematic reviews of all available randomized, doubleblind, multicenter, placebo-controlled studies by the Cochrane Collaboration showed moderate benefits of cholinesterase inhibitors on cognitive, behavioral, and functional symptoms for donepezil (Birks and Harvey, 2003), rivastigmine (Birks et al., 2000), and galantamine (Loy and Schneider, 2004). Clinical benefits from the cholinesterase inhibitors were also reported by several other meta-analyses (Ritchie et al., 2004; Whitehead et al., 2004; Takeda et al., 2006), whereas another systematic review questioned the scientific basis for recommendations of cholinesterase inhibitors for treatment 987

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of AD, raising issues of methodology and clinical relevance of outcome measures (Kaduszkiewicz et al., 2005). Despite this controversy, the ability to affect cognitive outcome has been robust. Most recently, a trial of donepezil for patients with severe AD and agitation found that there was a modest cognitive benefit, even though no behavioral benefit was observed (Howard et al., 2007). Memantine Glutamate represents the main excitatory neurotransmitter in the central nervous system, and a physiological level of glutamate-receptor activity is essential for normal brain function (Kornhuber and Weller, 1997). Glutamate excitotoxicity mediated through excessive activation of N-methyl-D-aspartate (NMDA) receptors is believed to play a role in the neuronal cell death observed in AD and other neurodegenerative diseases by causing increases in intracellular calcium that then triggers downstream events that cause cell death (Hynd et al., 2004). Thus, NMDA-receptor antagonists may have a therapeutic potential for neuronal protection from glutamate-mediated neurotoxicity. Memantine is a low-to-moderate affinity, voltagedependent, noncompetitive NMDA receptor antagonist with rapid gating kinetics (Danysz et al., 2000). Its fast on/off kinetics and low-to-moderate affinity are key to memantine’s action because it ameliorates the effects of excessive glutamate while preserving the physiologic activation of NMDA receptors required for learning and memory. Like other NMDA receptor antagonists, memantine at high concentrations can inhibit mechanisms of synaptic plasticity that are believed to underlie learning and memory, but studies have shown that at lower, clinically relevant concentrations memantine actually promotes synaptic plasticity and preserves or enhances memory in animal models of AD (Johnson and Kotermanski, 2006). However, it is not a cholinesterase inhibitor and therefore offers a different target from the cholinesterase inhibitors that previously were the only approved treatment for AD. Memantine was approved in the United States for treatment of moderate to severe AD in 2003. Systematic reviews of all available randomized, double-blind, multicenter, placebo-controlled studies by the Cochrane Collaboration showed that memantine treatment resulted in significant benefits compared with placebo in cognitive, functional, and behavioral assessments in the treatment group compared to placebo in patients with moderate to severe AD (AreosaSastre et al., 2005). Memantine does not affect the inhibition of acetylcholinesterase by cholinesterase inhibitors, and an openlabel European trial indicated that tolerability was not affected when donepezil or other cholinesterase inhibitors were administered to patients already receiving memantine or vice versa (Hartmann and Moebius, 2003;

Tariot et al., 2004). Memantine is usually well tolerated, although adverse effects, including confusion, insomnia, and headache, occurred in a small percentage of the study participants (Tariot et al., 2004). Modulation of Aβ Production

β -amyloid (Aβ) peptides are proteolytic fragments of a larger protein termed amyloid precursor protein (APP) which consists of a large extramembranous region, a transmembrane region, and a small cytosolic C-terminal tail (Kang et al., 1987). β -amyloid is generated from APP by sequential cleavages by two proteases termed β - and γ -secretase. β -amyloid is secreted constitutively by normal cells (Haass et al., 1992) and can be detected in plasma and cerebrospinal fluid (CSF) of normal individuals (Seubert et al., 1992). Amyloid precursor protein is also cleaved by another protease termed α-secretase that precludes Aβ generation because the cleavage site within the Aβ sequence produces a small nonamyloidogenic peptide termed p3 (Esch et al., 1990). Nonneuronal cells preferentially use α-secretase at the expense of β -secretase cleavage whereas neurons predominately use β -secretase cleavage and thus generate mostly Aβ (Simons et al., 1996). β -secretase (BACE-I) was cloned in 1999 (Vassar et al., 1999). BACE-I knockout mice were found to have a normal phenotype, while they abolished Aβ generation (Luo et al., 2001), making BACE-I a major focus of drug discovery efforts ever since. γ -secretase was found to be a protein complex composed of presenilin, nicastrin, PEN2, and APH1, with presenilin providing the active core of the secretase complex (review in De Strooper, 2003). A major concern regarding potential side effects of γ -secretase inhibitors comes from the identification of several γ secretase substrates other than APP, including Notch-1 (De Strooper et al., 1999). Safety and tolerability of a γ -secretase inhibiting compound (LY450139) not affecting Notch-1 by Eli Lilly was recently tested in healthy volunteers (Siemers et al., 2005) and patients with AD (Siemers et al., 2006). The compound was well tolerated and reduced plasma Aβ levels but failed to reduce CSF Aβ. A larger study testing the effect of LY450139 on cognition is currently under way. Aβ Immunotherapy Active immunization with Aβ attenuates AD-like pathology in a transgenic mouse model of AD (Schenk et al., 1999). Passive immunization with antibodies against Aβ also reduces amyloid deposition (Bard et al., 2000), and both forms of immunization against Aβ reduce learning deficits of APP transgenic mice (Janus et al., 2000; Morgan et al., 2000). The exact underlying mechanism to explain how antibodies reduce Aβ deposition in the brain is unclear. Multiple injections of an Aβ1–42

60: PRINCIPLES OF PHARMACOTHERAPY

synthetic peptide (AN1792 by Elan Pharmaceuticals) demonstrated safety and tolerability in a phase I trial (Gilman et al., 2005). In the phase II trial of AN1792, 372 patients with mild to moderate AD were randomized to receive either intramuscular injections of AN1792 or placebo. Among those receiving AN1792, 19.7% developed the predetermined concentration of the Aβspecific antibody (Bayer et al., 2005). Unfortunately, 18 (6%) patients treated with AN1792 (and none of the placebo group) developed meningoencephalitis, a result that led to prompt discontinuation of the trial. Of the 18 patients with meningoencephalitis, 12 recovered to baseline within several weeks whereas 6 developed longterm neurological or cognitive sequelae (Orgogozo et al., 2003). All study participants were followed longitudinally after cessation of the trial. No significant differences were found between treatment and placebo groups on performance in cognitive testing, although a small subset of the antibody-responder patients had a significantly slower cognitive decline than the antibody nonresponders (Hock et al., 2003). These patients were found to have greater brain volume decreases on neuroimaging analysis than nonresponders, and this decrease in brain volume was associated with better cognitive performance (Fox et al., 2005). In brain autopsies of a subset of patients from this clinical trial, both with and without meningoencephalitis, areas of apparent clearing of amyloid plaques in the cerebral cortex were observed, with an abundance of Aβ-immunoreactive microglia cells (Nicoll et al., 2003; Ferrer et al., 2004; Masliah et al., 2005). The cases of meningoencephalitis did not correlate with the presence or concentration of Aβ antibody titers, and this concentration is now believed to be caused by a T-cell response against Aβ (Monsonego et al., 2003). Currently, there are two phase I clinical trials of active immunization under way using either Aβ derivatives or an Aβ fragment coupled to a carrier (Schenk et al., 2004). Passive administration of an Aβ-specific humanized monoclonal antibody is currently undergoing a phase II clinical trial in patients with AD. A potential caveat to this form of therapy might be the finding of a study with APP transgenic mice with high levels of cerebral amyloid angiopathy in which passive Aβ immunization caused local microhemorrhages associated with amyloid-bearing vessels (Pfeifer et al., 2002). Another approach to vaccination, which avoids the use of anti-Aβ antibodies and thus circumvents the risk of meningoencephalitis, was demonstrated in APP transgenic mice by immunizing them with the random aminoacid copolymer glatiramer acetate (Frenkel et al., 2005). Glatiramer acetate, which has been successfully used to treat patients with multiple sclerosis, was shown to activate microglial cells, which lead to Aβ clearance without causing encephalitis. Studies in humans are under way.

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ANTI-INFLAMMATORY DRUGS Although inflammation is not considered a hallmark of AD, deposition of Aβ in form of plaques causes a potentially pathological immune response. Senile plaques are often surrounded by activated astrocytes and microglial cells and can also induce activation of the complement cascade (McGeer and McGeer, 2001). Cyclooxygenase (COX) enzymes mediate the conversion of arachidonic acid to prostaglandins, which are crucial components of the proinflammatory process. The main target of nonsteroidal anti-inflammatory drugs (NSAIDs) is COX enzymes. The inducible COX isoform, COX2, is up-regulated in brains of patients with AD (Yasojima et al., 1999), indicating that NSAIDs might be beneficial in AD by reducing neurotoxic inflammation. A subset of NSAIDs have been found to lower Aβ levels independently of COX enzyme activity, apparently by directly modeling γ -secretase activity that enzymatically cleaves Aβ from its larger precursor protein (Weggen et al., 2001). One agent that is particularly effective in modulating γ -secretase activity and ultimately in selective Aβ–42 lowering in animal models is flurizan (Tarenflurbil). In a phase II study, the agent had no effect on cognitive outcomes in mild to moderate AD. Secondary analyses including only patients with mild AD identified a trend toward benefit at the highest dose (800 mg) (Wilcock et al., 2007). This prompted modulation of a phase III study to determine efficacy in this selected population. Epidemiological studies show a reduced prevalence of AD among chronic users of NSAIDS (McGeer and McGeer, 2007). Transgenic animal studies are clearly providing the rational support for the data derived from the epidemiological studies (Cole et al., 2004). Unfortunately many of the recent long-term, prospective, randomized, double-blind, placebo-controlled clinical trials of NSAIDS in patients with AD have produced negative results and had high drop-out rates because of gastrointestinal side effects (Ho et al., 2006). Because selective COX2 inhibitors have a reduced rate of gastrointestinal side effects, they have been used in clinical trials of patients with AD. Early clinical trials of COX2 inhibitors have not succeeded in reducing cognitive or behavioral deficits in patients either with AD (Aisen et al., 2003) or with mild cognitive impairment (Thal et al., 2005). Selective COX2 inhibitors have recently been shown to increase the risk of cardiovascular events (Mukherjee et al., 2001), which resulted in the withdrawal of some of these drugs from the market and the early termination of several clinical trials, including a trial of dementia prevention with naproxen and celecoxib in AD. At the time the trial was halted, both naproxen and celecoxib were associated with trends toward increased risk of dementia (ADAPT Research Group et al., 2007).

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COMPLEMENTARY AND ALTERNATIVE MEDICINES IN THE TREATMENT OF DEMENTIA Alternative medicines may have potential beneficial results in treating dementia and related symptoms as well as slowing disease progression. Primary mechanisms of action include modifications in neurotransmitter synthesis, inhibition of neurotransmitter reuptake, enzymeinduced neurotransmitter breakdown, and antioxidant activity. Unfortunately, many studies of alternative medicines in dementia are inconclusive and characterized by methodological deficiencies such as small sample sizes and inadequate controls. Extracts of the leaves of the maidenhair tree, Ginkgo biloba, have long been used in China, and more recently in several European countries, as a traditional medicine for various disorders of health. Although some recent trials of Ginkgo biloba showed inconsistent results (Kanowski et al., 1996; Le Bars et al., 1997; van Dongen et al., 2000), a published meta-analysis of clinical studies of Ginkgo biloba showed inconsistent and unconvincing evidence of improvement in cognition and functional activities (Birks et al., 2007). A natural cholinesterase inhibitor, huperzine A, has been isolated from a Chinese herb. Huperzine has been found to improve memory in a small study of short duration (Zhang et al., 2002); other trials are under way. Several small studies using extracts of the herbs melissa officinalis or salvia lavandulaefolia found slight improvement in cognitive function or behavioral symptoms in the treatment groups (Ballard et al., 2002; Akhondzadeh et al., 2003a; Akhondzadeh et al., 2003b; Perry et al., 2003). Several epidemiologic studies showed a protective effect of increased fish consumption and ω-3 fatty acid intake for the development of AD (Barberger-Gateau et al., 2002; Morris et al., 2003). Meta-analysis of all available biological, epidemiological and observational data suggested a protective effect of ω-3 fatty acids (Lim et al., 2006), but so far only one randomized clinical trial of ω-3 fatty acids showed a positive effect, and only in patients with very mild AD (Freund-Levi et al., 2006). Further trials are in progress. Levacecarnine is the most common natural short-chain acetyl carnitine ester of L-carnitine and functions physiologically as a shuttle between the cytoplasm and mitochondria for long-chain fatty acids. In animal studies, it has been reported to protect central and peripheral nervous system synapses in neurodegenerative and ageing models and to improve cognitive deficits in aged rats (Barnes et al., 1990). In a meta-analysis, levacecarnine showed some evidence of effect on clinical global impression; however, the authors concluded that the evidence is currently inadequate to recommend its routine use in clinical practice (Hudson and Tabet, 2003). Another therapeutical strategy is to reduce Aβ neurotoxcitity by attenuation of Aβ –metal ion interactions. β -amyloid accumulation and toxicity are influenced by

zinc and copper ions (Bush et al., 1994). These metals are enriched in Aβ deposits, and their removal results in the solubilization of Aβ. The antibiotic clioquinol, which is a copper-zinc chelator, increases the solubilization of Aβ in the AD plaque from postmortem human brain tissue, reduces hydrogen peroxide generation from Aβ, and results in a significant decrease in brain Aβ deposition in a transgenic mouse model of AD (Cherny et al., 2001). In a short-term clinical trial, Ritchie et al. (2003) reported that clioquinol therapy significantly slowed the rate of cognitive decline in a subset of patients with AD, as compared with that in controls. The slowing of cognitive decline in patients treated with clioquinol was seen only in those who were more severely affected. A meta-analysis of the use of clioquinol for AD, however, came to the conclusion that trials of longer duration are needed before any recommendations about the use of clioquinol can be given (Jenagaratnam and McShane, 2006). Clinical trials using the antioxidant idebenone had mixed results (Senin et al., 1992; Weyer et al., 1997; Thal et al., 2003). Two other antioxidants, the curry spice curcumin and coenzyme Q10, have been shown to destabilize Aβ fibrils in vitro (Ono et al., 2004; Ono et al., 2005). A population-based cohort study found better cognition in elderly Asian patients with high curcumin consumption (Ng et al., 2006); a clinical trial is currently under way (Ringman et al., 2005). As of yet, there are no clinical trials using coenzyme Q10 in patients with AD. Several observational studies have shown that moderate consumption of wine is associated with a lower incidence of AD (Truelsen et al., 2002; Luchsinger and Mayeux, 2004). Wine is enriched in antioxidant compounds with potential neuroprotective activities. Resveratrol, a polyphenol that occurs in abundance in grapes and red wine, is used by the plant to defend itself against fungal and other attacks. In the early 1990s, the presence of resveratrol was detected in red wine. It is hypothesized to afford antioxidant and neuroprotective properties (Miller and Rice-Evans, 1995) and therefore to contribute to the beneficial effects of red wine consumption on neurodegeneration (Savaskan et al., 2003; Han et al. 2004). Additionally, resveratrol is thought to facilitate the utilization of electrons in the nonmitochondrial portions of the cell (Fauconneau et al., 1997). In a recent study, it was shown that resveratrol promotes intracellular degradation of Aβ via a mechanism that involves the proteasome (Marambaud et al., 2005). Resveratrol does not influence the Aβ producing enzymes and therefore does not inhibit Aβ generation. A small clinical trial of resveratrol in patients with AD has shown encouraging results (Blass and Gibson, 2006); a larger clinical trial is currently under way. However, clinical trials to evaluate treatment of AD with antioxidant supplements or with food containing

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large amounts of antioxidants have so far failed to show clinically significant benefits. Modification of Cardiovascular Risk Factors as a Treatment of Dementia Traditionally, AD has been thought to be a primary neurodegenerative disorder and not of vascular origin. However, in recent years, epidemiologic studies have identified risk factors for vascular disease that are also associated with cognitive impairment and AD (Breteler, 2000). Cardiovascular risk factors are highly prevalent in the elderly population and rarely exist in isolation. Diabetes mellitus, hypertension, hyperlipidemia, and coronary artery disease often coexist, and this constellation of cardiovascular risk factors has been found to increase the risk for cognitive decline, vascular dementia, and AD (Luchsinger and Mayeux, 2004). The risk of AD has been found to increase with the number of vascular risk factors present in an individual (Luchsinger et al., 2005). Cell culture and transgenic animal experiments have shown that an increased cholesterol concentration causes an increased generation of AD plaques (Refolo et al., 2000) whereas cholesterol depletion inhibits Aβ formation in vitro and in vivo (Fassbender et al., 2001). Elevated cholesterol is associated with a higher plaque load in patients with AD (Kivipelto et al., 2002), and patients with AD with hypercholesterolemia suffer from more rapid cognitive decline (Evans et al., 2004). Some early epidemiological studies have suggested that statins reduce the risk of AD by as much as 60%–70% (Jick et al., 2000; Wolozin et al., 2000). However, a metaanalysis of recent studies showed statins do not exert a beneficial effect on the risk of dementia and AD (Zhou et al., 2007). A post hoc analysis of pooled data from three clinical trials of patients with AD randomized to galantamine or placebo and also taking a statin or not showed no association between the use of statins and cognitive function; there was also no interaction between statins and galantamine in their effect on cognition (Winblad et al., 2007). Preliminary results from a double-blind, placebocontrolled, randomized clinical trial of atorvastatin in patients with mild to moderate AD demonstrated a significant benefit on a cognitive measure compared to placebo (Sparks et al., 2005). This benefit was more prominent among individuals with elevated cholesterol levels and higher scores on memory testing at study entry time (Sparks et al., 2006). However, patients in this study were selected regardless of lipid levels, and some may have had cardiovascular risk-reduction benefit; the observed benefit may have derived from this etiology rather than by affecting AD pathology. Two other multicenter trials to examine the effect of statins on slowing the clinical progression of AD are ongoing, and

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both are recruiting only patients with normal lipid levels. Thus, if a benefit is seen it may be distinct from a cardiovascular risk reduction. Recruitment is complete in both, and these 18-month trials may have results in 2008. Hypertension is a well-known risk factor for cardiovascular disease and stroke, and thus for vascular dementia. Recent evidence demonstrated that there is a vascular contribution to AD (De La Torre, 2004), although it is not clear if the contribution is simply an added deficit within the clinical profile or if it contributes to the pathophysiology of AD. Observational studies provide support for the association between hypertension and cognitive deficit, including AD; however, they are confounded by many variables, including interventions with various mechanisms of action and changing treatment guidelines. In fact, a systematic review found the relation of blood pressure to cognitive function and dementia is both complex and inconsistent, differing by the age at which blood pressure was ascertained (middle age or old age), whether having treated or untreated hypertension, and in cross-sectional verses longitudinal studies (Qiu et al., 2005). It is worth noting that these observational studies often include few or no very old subjects (age ≥85), making extrapolation to this population difficult. The successful effect of antihypertensive medication in containing stroke rates provides hope for similar effects on the prevention of cognitive decline and dementia. Observational studies addressing the relationship of the treatment of hypertension and cognitive decline had mixed results. In several longitudinal cohort studies, individuals treated with antihypertensive drugs showed a decreased risk for cognitive decline (Tzourio et al., 1999) or less evident increased risk of cognitive decline and dementia due to hypertension (Elias et al., 1993; Launer et al., 2000). Several trials in which the primary outcome was a measure of cardiovascular risk reduction added a cognitive assessment. In several trials, there were either only benefits in a subset of trial participants (Skoog et al., 2005) or only with long-term use of antihypertensive medication (Cervilla et al., 2000). In one large trial, active therapy with antihypertensive medication decreased the incidence of dementia by 50% over two years (Forette et al., 1998), and another trial in elderly patients with probable AD showed that the mean decline on the Mini Mental State Examination (MMSE) score was much lower in the group on brain-penetrating angiotensin converting enzyme (ACE) inhibitors than in the control group (Ohrui et al., 2004). Diabetes mellitus has been shown to be associated with changes in cognition; however, the finding of an association between diabetes and AD has been inconsistent (Biessels et al., 2006). In type 1 diabetes, cognitive deficits include mild slowing of mental speed and a diminished mental flexibility (Brands et al., 2005). In type 2 diabetes, cognitive impairment mainly affects learning

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and memory, mental speed, and flexibility (Allen et al., 2004). The association between diabetes mellitus and AD is particularly strong among carriers of the apolipoprotein ε4 (ApoE4) allele (Peila et al., 2002) and in patients treated with insulin (Ott et al., 1999; Mogi et al., 2004). Brain atrophy in elderly patients with diabetes mellitus is more severe in patients treated with insulin (Ushida et al., 2001). A likely explanation is that only severe cases of diabetes mellitus require insulin treatment. One observational study demonstrated that women with diabetes mellitus had a fourfold increased risk of a major cognitive decline on a verbal fluency test after 4 years compared to women without diabetes mellitus (Kanaya et al., 2004), and improved glucose control as measured by glycohemoglobin could ameliorate this decline. There was no significant difference in cognitive test performance at baseline or followup in men regardless of glucose tolerance status or glycohemoglobin level. A study of a cohort of elderly Mexican Americans showed that one third of the study participants were identified as having type 2 diabetes at baseline, and 58.3% of these diabetics were using either oral antidiabetic medications or insulin or a combination of both. During a 2-year period, there was significantly less physical and cognitive decline among patients receiving treatment with antidiabetic medications compared to those without treatment (Wu et al., 2003). Combination therapy of antidiabetic agents appeared to be more effective than monotherapy in preventing the decline in physical and cognitive functioning for patients. No randomized, double-blind, placebo-controlled clinical trials of tighter blood glucose control and cognitive decline or incident dementia have been reported, but one large clinical trial addressing these questions is currently under way. There is substantial epidemiologic evidence that cardiovascular risk factors such as hypertension, hyperlipidemia, and diabetes mellitus are associated with cognitive decline, vascular dementia, and perhaps AD. However, at present the exact mechanisms by which these cardiovascular risk factors may increase the risk of cognitive decline and dementia and their relative importance in the pathogenesis of AD are unknown. In this context, further studies to elucidate these mechanisms are needed. Additionally, the incidence of cognitive decline, vascular dementia, and AD should constitute a major outcome measure of future trials comparing different antihypertensive, cholesterol-lowering, and antidiabetic drugs to determine the best clinical strategy for prevention of dementia. HORMONAL TREATMENT OF DEMENTIA Systematic meta-analyses of cohort and case-control studies have reported estrogen use to be associated with a

reduction in the risk of developing AD of approximately 30% (LeBlanc et al., 2001). However, randomized clinical trials have failed to find any clinically meaningful evidence of benefit in treating patients with preexisting mild-to-moderate AD with estrogen, and the Cochrane review concluded that hormone replacement therapy is not indicated in patients with AD (Hogervorst et al., 2002). The Women’s Health Initiative Memory Study, a primary prevention trial, examined the possible benefit of hormone replacement therapy in reducing the incidence or delaying the time of onset of dementia (Shumaker et al., 2004). Adverse outcomes led to the study being terminated early. Treatment was linked to an increased risk of stroke and coronary artery disease and actually increased the risk of dementia (Hazard ratio: 1.76; 95% confidence interval [CI]: 1.19–2.60). ANTIOXIDANTS AND VITAMINS The free radical hypothesis of aging proposes that free radical reaction that damages cells are the primary mechanism by which aging occurs (Harman, 1956). Surrogate markers of injury attributable to free radicals are present in patients with AD, particularly near plaque and tangle sites (Grünblatt et al., 2005). Vitamins C and E have been found to protect from oxidative deoxyribonucleic acid (DNA) damage (Huang et al., 2000), and vitamin E protects nerve cells from Aβ peptide toxicity (Behl et al., 1992). Several population-based prospective observational studies that have used questionnaires to monitor the intake of vitamins C and E on the risk of developing dementia had mixed results (Boothby and Doering, 2005). A placebo-controlled, clinical trial of vitamin E and selegiline in patients with moderately advanced AD was conducted by the Alzheimer’s Disease Cooperative Study (Sano et al., 1997). Patients in the vitamin E group were treated with 2000 IU (1342 alpha-tocopherol equivalents) vitamin E per day. The results indicated that vitamin E may slow functional deterioration, leading to nursing home placement. Another clinical trial with vitamin E was conducted in patients with mild cognitive impairment with the primary endpoint being the time to development of possible or probable AD (Petersen et al., 2005). There were no significant differences in the rate of progression to AD between the vitamin E and placebo groups. Despite the lack of high-level evidence to support an association between cognitive benefits or decreased incidence of AD with vitamin C and E use, the use of these vitamins has become commonplace in clinical practice. Unfortunately, there are also safety concerns with the use of vitamin E. A clinical trial of longterm vitamin E supplementation studying the effects on cardiovascular events and cancer not only showed that vitamin E does not prevent cancer or major cardiovas-

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cular events, but that it also increases the risk of heart failure (Lonn et al., 2005). A meta-analysis of randomized controlled trials examining the potential dose– response relationship between vitamin E supplementation and total mortality showed dose-dependent and significantly increased all-cause mortality with the use of vitamin E (Miller et al., 2005). Recent recommendations are therefore not to advocate the use of vitamin E in individuals at risk of or affected by AD (Ames and Ritchie, 2007). Elevated plasma homocysteine levels are a risk factor for cardiovascular disease and stroke and may be related to an increased risk of AD (Seshadri et al., 2002). Deficiencies of folic acid and vitamins B12 and B6 intake increase homocysteine plasma levels. Folic acid and vitamins B12 are needed for the conversion of homocysteine to methionine, and vitamin B6 is needed for the conversion of homocysteine to cysteine. High dietary intake of folic acid and vitamin B12 and B6 decreased homocysteine levels in adults (Homocysteine Lowering Trialists’ Collaboration, 2005). A recent longitudinal cohort study reported higher folate intake to decrease the risk of incident AD independent of levels of vitamin B6 and B12 (Luchsinger et al., 2007). However, meta-analyses of clinical trials addressing the influence of folic acid, vitamin B6, and vitamin B12 intake failed to show any beneficial effect on cognitive function (Malouf and Areosa Sastre, 2003; Malouf and Grimley Evans, 2003; Malouf et al., 2003). Furthermore, two recent clinical trials on folic acid and vitamins B6 and B12 failed to show any reduction of the risk of major cardiovascular events and stroke (Bonaa et al., 2006; Lonn et al., 2006). One study of supplementation over a 3-year period in older individuals with no dementia selected for their relatively high homocysteine levels indicated a favorable influence on cognitive function (Durga et al., 2007), whereas a 2-year study in older individuals not selected on homocysteine levels did not (McMahon et al., 2006). Recently reported results of a U.S. multicenter clinical trial of B vitamins and folic acid in the treatment of AD over a 10-month period failed to demonstrate a benefit and was associated with an increase in depressive symptoms (Aisen et al., 2007). In this study, patients had relatively normal homocysteine levels, suggesting that benefits of supplementation may only be observed in those with high homocysteine and low folate intake. DOPAMINERGIC ENHANCEMENT OF COGNITIVE FUNCTION The ascending dopamine (DA) system of the mammalian brain has been associated with regulation of motor output, reward-related behavior, executive functions, and short-term memory (Thierry et al., 1998). Dopaminergic

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projections to the prefrontal cortex and striatum are involved in spatial working memory functions, and striatal and amygdala ascending DA tracts are important for learning and conditioning (Goldman-Rakic, 1998). Research in experimental animals suggests that damage to the lateral prefrontal cortex in monkeys impairs spatial working memory (Brozoski et al., 1979), stimulation of DA D1 receptors by DA D1 receptor agonists can ameliorate these deficits (Cai and Arnsten, 1997). Studies in healthy humans have suggested that spatial working memory and other executive functions might be improved by administration of low doses of DA, D1, and D2 receptor agonists (Luciana et al., 1992; Mueller et al., 1998; Schuck et al., 2002). Patients with cognitive deficits caused by traumatic brain injury displayed improved performance of executive function and attention but not spatial memory (Lal et al., 1988; McDowell et al., 1998). Aphasia describes linguistic difficulties following brain lesions, most often caused by a stroke. The cortical localization of brain damage resulting in aphasia is varied. A review for the Cochrane Database failed to show any positive effects of DA receptor agonists or stimulants on treatment of aphasia poststroke (Greener et al., 2001). Stimulant drugs such as amphetamine, methamphetamine, and methylphenidate can influence DA neurotransmission by blocking reuptake at the transporter site, thereby increasing extracellular levels of DA. However stimulants also have effects at the noradrenaline and serotonin transporter sites, making attribution of possible cognitive-enhancing properties specifically to DA neurotransmission problematic (Kuczenski and Segal, 1997). Psychomotor stimulants are widely used for the treatment of attention-deficit/hyperactivity disorder (ADHD), as they have an established ability to improve attention and spatial working memory in these patients (Mehta et al., 2004) and even in young healthy volunteers (CampBruno and Herting, 1994; Elliott et al., 1997). Interestingly, these findings do not apply for elderly volunteers (Turner et al., 2003). So far, there has been only one study that attempted to separate dopaminergic and noradrenergic effects on cognitive function by comparing the effects of methylphenidate; 3,4-dihydroxyphenylalanine (L-DOPA); and desipramine (noradrenaline reuptake inhibitor) on attention and inhibition in children with ADHD. The study showed that neither a pure dopaminergic nor noradrenergic explanation is sufficient for an explanation (Overtoom et al., 2003). Dopaminergic enhancement via monoamine oxidase inhibition has also been examined. The type B monoamine oxidase inhibitor selegiline was shown to delay nursing home placement and to mildly improve subsets of neuropsychological testing (Burke et al., 1993; Sano et al., 1997; Filip and Kolibas, 1999) in patients with AD. Yet a meta-analysis came to the conclusion that there was no evidence of any meaningful clinical

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benefits and thus no justification to use selegiline in the treatment of AD (Birks and Flicker, 2003). Clinical trials with rasagiline, an irreversible type B monoamine oxidase inhibitor, are currently under way. Oxidative stress occurs when the cellular production of reactive oxygen species overwhelms the natural defense of antioxidants leading to cell death through apoptosis and necrosis and may be important in the development of dementia. Noradrenergic Modulation of Memory Ascending noradrenergic projections from the locus coeruleus to higher cortical regions are implicated in arousal and modulate cognitive functions dependent upon prefrontal cortex and associated circuitry. Working memory refers to short-term storage, and manipulation of items in memory is dependent upon prefrontal cortex activity (Baddeley, 1986). Animal studies have shown that moderate levels of noradrenaline enhance working memory, whereas higher concentrations impair this function. These findings appear attributable to dissociable effects of noradrenaline at α1- and α2a adrenoreceptors (Arnsten and Li, 2005). Long-term (emotional) memory appears to be mediated by the amygdalae, with mediotemporal structures being crucial for conditioned fear learning and fearful responses in animals (McGaugh, 2004). Augmentation of noradrenaline transmission has been shown to enhance long-term memory, whereas such effects are reversed by β blockade (van Steegeren et al., 2002; Cahill and Alkire, 2003). The lipophilic β blocker propranolol impaired working memory in multiple studies, whereas less lipophilic β blockers such as atenolol had no effect on memory, suggesting that central blockade might be necessary for modulatory effects on memory (Mueller et al., 2005). The α2 adrenoreceptor agonist clonidine was found to impair working memory in most studies (Jakala et al., 1999), whereas findings for other α agonists and selective noradrenaline reuptake inhibitors were inconsistent (Mueller et al., 2005). SEROTONERGIC MODULATION OF COGNITIVE FUNCTION Serotonin has long been implicated in a wide range of behavioral functions, especially in mood regulation, aggression, and impulsivity. In recent years, experimental studies with animals and humans have shown that serotonin may also play an important role in normal and impaired cognitive function as well as in specific human memory processes. Lowering of serotonergic activity in healthy volunteers is associated with impairment of long-term memory performance, specifically delayed recall and delayed recognition of pictures (Rowley et al., 1998; Rubinsztein et al., 2001). Studies of the effect of serotonin stimulation on memory function in healthy

volunteers have yielded inconsistent results (Schmitt et al., 2001; Harmer et al., 2002). A depressive episode is often accompanied by extensive cognitive impairment across a wide range of cognitive domains, including impairment of long-term memory functioning, executive function, attention, and concentration. Central serotonergic dysfunction is considered to be one of the neuronal substrates of depression; however, central catecholaminergic activity, the neuroendocrine system, and the immune system are also impaired. Clinical improvement of memory function in patients who were depressed was observed after treatment with selective serotonin reuptake inhibitors (SSRIs) (Richardson et al., 1994; La Pia et al., 2001). There is increasing evidence for alterations in the function of the serotonin system in AD that may be responsible for many of the behavioral aspects of the disease, including the frequent coexistence of depression. Serotonin receptor binding decreases dramatically with aging in a variety of brain regions (Sheline et al., 2002). Low serotonin has been related to cognitive deficits seen in AD (Lai et al., 2002), and serotonin dysregulation can occur separately or in conjunction with that of the cholinergic system (Buhot et al., 2000). Acute serotonin depletion caused impaired performance on memory testing in patients with AD compared to healthy elderly controls (Porter et al., 2000). There are no randomized controlled trials as of yet of the use SSRIs in patients with AD with the purpose of enhancing cognition. In frontotemporal dementia, SSRIs have been shown to mildly ameliorate behavioral symptoms such as impulsivity, carbohydrate craving, and compulsion (Swartz et al., 1997); however, they have been found to mildly impair cognitive function (Deakin et al., 2004). Recently the serotonin 5-HT4 receptor, which has been shown to increase cyclic adenosine monophosphate (cAMP) production, has also been implicated in APP processing. Specifically, it appears to stimulate αsecretase. The therapeutic potential of activation of this receptor has been advanced by the identification of receptor agonists that have been used in transgenic models to demonstrate regulation of the nonamyloidagenic precursor protein (Lezoualc’h, 2007). The development of agonists for this receptor provides a mechanism for therapeutic interventions for AD. In fact, one compound, PRX-03140, a small-molecule agonist of 5-HT4, has been described in the lay literature as having benefit in patients with AD, although the details of the trial and the true effect size has been less clear (http://www.epixpharma.com/products/prx-03140.asp). Registered trials are ongoing (NCT00384423). SUMMARY The availability of treatments for AD is now a reality, although the search continues for more effective treat-

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ments for dementia and its prodromal conditions. Some leads from epidemiologic data and early laboratory studies have proven ineffective, allowing for a more precise understanding of how to approach treatment. Further, the impact of treatments affecting common comorbidities, such as cerebrovascular and cardiovascular conditions, may have direct and indirect effects on cognition, and these benefits are being sorted out. Methodologies now exist to design and implement clinical trials to assess treatments with extended efficacy, in subjects with milder conditions, and that target potential disease etiologies. New drug classes are currently being evaluated, and any reasonable assessment of the state of the field leads to the conclusion that important results and expanding treatment options are imminent. REFERENCES ADAPT Research Group, Lyketsos, C.G., Breitner, J.C., Green, R.C., Martin, B.K., Meinert, C., Piantadosi, S., and Sabbagh, M. (2007) Naproxen and celecoxib do not prevent AD in early results from a randomized controlled trial. Neurology 68(21): 1800–1808. Aisen, P.S., Jin, S., Thomas, R.G., Sano, M., Diaz-Arrastia, R., and Thal, L. for the Alzheimer’s Disease Cooperative Study. (2007) The effect of high dose supplements to reduce homocysteine in Alzheimer’s disease: The ADCS Homocysteine Trial. International Conference on the Prevention of Dementia, Washington, DC, June 2007. Aisen, P.S., Schafer, K.A., Grundman, M., Pfeiffer, E., Sano, M., Davis, K.L., Farlow, M.R., Jin, S., Thomas. R.G., and Thal, L.J. (2003) Alzheimer’s Disease Cooperative Study. Effects of rofecoxib or naproxen vs placebo on Alzheimer’s disease progression: a randomized controlled trial. JAMA 289:2819–2826. Akhondzadeh, S., Noroozian, M., Mohammadi, M., Ohadinia, S., Jamshidi, A.H., and Khani, M. (2003a) Melissa officinalis extract in the treatment of patients with mild to moderate Alzheimer’s disease: a double-blind, randomized, placebo controlled trial. J. Neurol. Neurosurg. Psychiatry 74:863–866. Akhondzadeh, S., Noroozian, M., Mohammadi, M., Ohadinia, S., Jamshidi, A.H., and Khani, M. (2003b) Salvia officinalis extract in the treatment of patients with mild to moderate Alzheimer’s disease: a double-blind, randomized and placebo controlled trial. J. Clin. Pharm. Ther. 28:53–59. Allen, K.V., Frier, B.M., and Strachan, M.W.J. (2004) The relationship between type 2 diabetes and cognitive dysfunction: longitudinal studies and their methodological limitations. Eur. J. Pharmacol. 490:169–175. Ames, D., and Ritchie, C. (2007) Antioxidants and Alzheimer’s disease: time to stop feeding vitamin E to dementia patients? Int. Psychogeriatr. 19:1–8. Areosa-Sastre, A., McShane, R., and Sherriff, F. (2005) Memantine for dementia. Cochrane Database Syst. Rev. (2):CD003154. Arnsten, A.F., and Li, B.M. (2005) Neurobiology of executive functions: catecholamine influences on prefrontal cortical functions. Biol. Psychiatry 57:1377–1384. Baddeley, A. (1986) Working Memory. Clarendon: Oxford Science Publications. Ballard, C.G., O’Brien, J.T., Reichelt, K., and Perry, E.K. (2002) Aromatherapy as a safe and effective treatment of the management of agitation in severe dementia: the results of a double-blind, placebocontrolled trial with Melissa. J. Clin. Psychiatry 63:553–558. Barberger-Gateau, P., Letenneur, L., Deschamps, V., Peres, K., Dartigues, J.F., and Renaud, S. (2002) Fish, meat and risk of dementia: cohort study. Br. Med. J. 325:932–933.

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Bard, F., Cannon, C., Barbour, R., Burke, R.L., Games, D., Grajeda, H., Guido, T., Hu, K., Huang, J., Johnson-Wood, K., Khan, K., Kholodenko, D., Lee, M., Lieberburg, I., Motter, R., Nguyen, M., Soriano, F., Vasquez, N., Weiss, K., Welch, B., Seubert, P., Schenk, D., and Yednock, T. (2000) Peripherally administered antibodies against amyloid-β enter the central nervous system and reduce pathology in a mouse model of Alzheimer’s disease. Nature Med. 6:916–919. Barnes, C.A., Markowska, A.L., Ingram, D.K., Kametani, H., Spangler, E.L., Lemken, V.J., and Olton, D.S. (1990) Acetyl-L-carnitine 2: effects on learning and memory performance of aged rats in simple and complex mazes. Neurobiol. Aging 11:499–506. Bartus, R.T., Dean, R.L. III, Beer, B., and Lippa, A.S. (1982) The cholinergic hypothesis of geriatric memory dysfunction. Science 217:408–414. Bayer, A.J., Bullock, R., Jones, R.W., Wilkinson, D., Paterson, K.R., Jenkins, L., Millais, S.B., and Donoghue, S. (2005) Evaluation of the safety and immunogenicity of synthetic Aβ 42 (AN 1792) in patients with AD. Neurology 64:94–101. Behl, C., Davis, J., Cole, G.M., and Schubert, D. (1992) Vitamin E protects nerve cells from amyloid-beta toxicity. Biochem. Biophys. Res. Commun. 186:944–950. Biessels, G.J., Staekenborg, S., Brunner, E., Brayne, C., and Scheltens, P. (2006) Risk of dementia in diabetes mellitus: a systematic review. Lancet Neurol. 5(1):64–74. Birks, J., Grimley, and Evans, J. (2007) Ginkgo biloba for cognitive impairment and dementia (Cochrane Review). Cochrane Database Syst Rev. (2):CD003120. Birks, J.S., and Harvey, R. (2003) Donepezil for dementia due to Alzheimer’s disease. Cochrane Database Syst. Rev.:CD001190. Birks, J., and Flicker, L. (2003) Selegiline for Alzheimer’s disease. Cochrane Database Syst. Rev.:CD000442. Birks, J.S., Iakovidou, V., and Tsolaki, M. (2000) Rivastigmine for Alzheimer’s disease. Cochrane Database Syst. Rev.:CD001191. Blass, J.P., and Gibson, G.E. (2006) Correlations of disability and biologic alterations in Alzheimer brain and test of significance by a therapeutic trial in humans. J. Alzheimers Dis. 9:207–218. Bonaa, K.H., Njolstad, I., Ueland, P.M., Schirmer, H., Tverdal, A., Steigen, T., Wang, H., Nordrehaug, J.E., Arnesen, E., Rasmussen, K., NORVIT Trial Investigators. (2006) Homocysteine lowering and cardiovascular events after acute myocardial infarction. N. Eng. J. Med. 354(15):1578–1588. Boothby, L.A., and Doering, P.L. (2005) Vitamin C and vitamin E for Alzheimer’s disease. Ann. Pharmacother. 39:2073–2030. Brands, A.M., Biessels, G.J., De Haan, E.H., Kappelle, L.J., and Kessels, R.P. (2005) The effects of type 1 diabetes on cognitive performance: a meta-analysis. Diabetes Care 28:726–735. Breteler, M.M.B. (2000) Vascular risk factors for Alzheimer’s disease: an epidemiologic perspective. Neurobiol. Aging 21:153–160. Brozoski, T.J., Brown, R.M., Rosvold, H.E., and Goldman, P.S. (1979) Cognitive deficit caused by regional depletion of dopamine in prefrontal cortex of the rhesus monkey. Science 205: 929–932. Buhot, M.C., Martin, S., and Segu, L. (2000) Role of serotonin in memory impairment. Ann. Med. 32:210–221. Burke, W.J., Roccaforte, W.H., Wengel, S.P., Bayer, B.L., Ranno, A.E., and Willcockson, N.K. (1993) L-deprenyl in the treatment of mild dementia of the Alzheimer type: results of a 15-month trial. J. Am. Geriatr. Soc. 41:1219–1225. Bush, A.I., Pettingell, W.H., Multhaup, G., Paradis, M.,Vonsattel, J.P., Gusella, J.F., Beyreuther, K., Masters, C.L., and Tanzi, R.E. (1994) Rapid induction of Alzheimer Aβ amyloid formation by zinc. Science 265:1464–1467. Cahill, L., and Alkire, M.T. (2003) Epinephrine enhancement of human memory consolidation: interaction with arousal at encoding. Neurobiol. Learn. Mem. 79:194–198. Cai, J.X., and Arnsten, A.F. (1997) Dose-dependent effects of the dopamine D1 receptor agonists A77636 or SKF81297 on spatial

996

DEMENTIA

working memory in aged monkeys. J. Pharmacol. Exp. Ther. 283:183–189. Camp-Bruno, J.A., and Herting, R.L. (1994) Cognitive effects of milacemide and methylphenidate in healthy young adults. Psychopharmacology 115:46–52. Cervilla, J.A., Prince, M., Joels, S., Lovestone, S., and Mann, A. (2000) Long-term predictors of cognitive outcome in a cohort of older people with hypertension. Br. J. Psychiatry 177:66–71. Cherny, R.A., Atwood, C.S., and Xilinas, M.E. (2001) Treatment with a copper-zinc chelator markedly and rapidly inhibits β -amyloid accumulation in Alzheimer’s disease transgenic mice. Neuron 30: 665–676. Cole, G.M., Morihara, T., Lim, G.P., Yang, F., Begum, A., and Frautschy, S.A. (2004) NSAID and antioxidant prevention of Alzheimer’s disease: lessons from in vitro and animal models. Ann. N.Y. Acad. Sci. 1035:68–84. Cutler, N.R., Polinsky, R.J., Sramke, J.J., Enz, A., Jhee, S.S., Mancione, L., Hourani, J., and Zolnouni, P. (1998) Dose-dependent CSF acetylcholinesterase inhibition by SDZ ENA 713 in Alzheimer’s disease. Acta Neurol. Scand. 97:244–250. Danysz, W., Parsons, C.G., Moebius, H.J., Stoeffler, A., and Quack, G. (2000) Neuroprotective and symptomatological action of memantine relevant for Alzheimer’s disease-a unified glutamatergic hypothesis on the mechanism of action. Neurotoxicity Res. 2:85–98. Davies, P., and Maloney, A.J. (1976) Selective loss of central cholinergic neurons in Alzheimer’s disease. Lancet. 2(8000):1403. Deakin, J.B., Nestor, P.J., Hodges, J.R., and Sahakian, B.J. (2004) Paroxetin does improve symptoms and impairs cognition in frontotemporal dementia: a double-blind randomized controlled trial. Psychopharmacology 172:400–408. De La Torre, J.C. (2004) Is Alzheimer’s disease a neurodegenerative or vascular disorder? Data, dogma and dialectics. Lancet Neurol. 3:184–190. De Strooper, B. (2003) APH-1, PEN2, nicastrin with presenilin generate an active γ-secretase complex. Neuron 38:9–12. De Strooper, B., Annaert, W., Cupers, P., Saftig, P., Craessaerts, K., Mumm, J.S., Schroeter, E.H., Schrijvers, V., Wolfe, M.S., Ray, W.J., Goate, A., and Kopan, R. (1999) A presenilin-1-dependent gamma-secretase-like protease mediates release of Notch intracellular domain. Nature 398(6727):518–522. Doody, R.S., Stevens, J.C., Beck, C., Dubinsky, R.M., Kaye, J.A., Gwyther, L., et al. (2001) Practice parameter: management of dementia (an evidence-based review). Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 56:1154–1156. Durga, J., van Boxtel, M.P., Schouten, E.G., Kok, F.J., Jolles, J., Katan, M.B., et al. (2007) Effect of 3-year folic acid supplementation on cognitive function in older adults in the FACIT trial: a randomised, double blind, controlled trial. Lancet 369(9557): 208–216. Elias, M.F., Wolf, P.A., D’Agostino, R.B., Cobb, J., and White, L.R. (1993) Untreated blood pressure level is inversely related to cognitive functioning: The Framingham Study. Am. J. Epidemiol. 6:353–364. Elliott, R., Sahakian, B.J., Matthews, K., Bannerjea, A., Rimmer, J., and Robbins, T.W. (1997) Effects of methylphenidate on spatial working memory and planning in healthy young adults. Psychopharmacology 131:196–206. Esch, F.S., Keim, P.S., Beattie, E.C., Blacher, R.W., Culwell, A.R., Oltersdorf, T., McClure, D., and Ward, P.J. (1990) Cleavage of amyloid beta peptide during constitutive processing of its precursor. Science 248:1122–1124. Evans, R.M., Hui, S., Perkins, A., Lahiri, D.K., Poirier, J., and Farlow, M.R. (2004) Cholesterol and APOE genotype interact to influence Alzheimer disease progression. Neurology 62: 1869–1871. Fassbender, K., Simons, M., Bergmann, C., Stroick, M., Lutjohann, D., Keller, P., Runz, H., Kuhl, S., Bertsch, T., von Bergmann, K.,

Hennerici, M., Beyreuther, K., and Hartmann, T. (2001) Simvastatin strongly reduces levels of Alzheimer’s disease beta-amyloid petides Abeta 42 and Abeta 40 in vitro and in vivo. Proc. Natl. Acad. Sci. USA 98:5856–5861. Fauconneau, B., Waffo-Teguo, P., Huguet, F., Barrier, L., Decendit, A., and Merillon, J.M. (1997) Comparative study of radical scavenger and antioxidant properties of phenolic compounds from Vitis vinifera cell cultures using in vitro tests. Life Sci. 61:2103–2110. Ferrer, I., Boada Rovira, M., Sanchez Guerra, M.L., Rey, M.J., and Costa-Jussa, F. (2004) Neuropathology and pathogenesis of encephalitis following amyloid-β immunization in Alzheimer’s disease. Brain Pathol. 14:11–20. Filip, V., and Kolibas, E. (1999) Selegiline in the treatment of Alzheimer’s disease: a long-term randomized placebo-controlled trial. Czech and Slovak Senile Dementia of Alzheimer Type Study Group. J. Psychiatry Neurosci. 24:234–243. Forette, F., Seux, M.L., Staessen, J.A., Thijs, L., Birkenhager, W.H., Babarskiene, M.R., Babeanu, S., Bossini, A., Gil-Extremera, B., Girerd, X., Laks, T., Lilov, E., Moisseyev, V., Tuomilehto, J., Vanhanen, H., Webster, J., Yodfat, Y., and Fagard, R. (1998) Prevention of dementia in randomized double-blind placebocontrolled systolic hypertension in Europe (SYST-EUR) trial. Lancet 352:1347–1351. Fox, N.C., Black, R.S., Gilman, S., Rossor, M.N., Griffith, S.G., Jenkins, L., and Koller, M. (2005) AN1792(QS-21)-201 Study. Effects of Aβ -immunization (AN 1792) on MRI measures of cerebral volume in Alzheimer disease. Neurology 64:1563–1572. Frenkel, D., Maron, R., Burt, D.S., and Weiner, H.L. (2005) Nasal vaccination with a proteosome-based adjuvant and glatiramer acetate clears β -amyloid in a mouse model of Alzheimer’s disease. J. Clin. Invest. 115:2423–2433. Freund-Levi, Y., Eriksdotter-Jonhagen, M., Cederholm, T., Basun, H., Faxen-Irving, G., Garlind, A., Vedin, I., Vessby, B., Wahlund, L.O., and Palmblad, J. (2006) Omega-3 fatty acid treatment in 174 patients with mild to moderate Alzheimer disease: OmegAD study: a randomized double-blind trial. Arch. Neurol. 63: 1402–1408. Gilman, S., Koller, M., Black, R.S., Jenkins, L., Griffith, S.G., Fox, N.C., Eisner, L., Kirby, L., Rovira, M.B., Forette, F., and Orgogozo, J.M. (2005) AN1792(QS-21)-201 Study Team. Clinical effects of Aβ immunization (AN 1792) in patients with AD in an interrupted trial. Neurology 64:1553–1562. Goldman-Rakic, P.S. (1998) The cortical dopamine system: role in memory and cognition. Adv. Pharmacol. 42:707–711. Greener, J., Enderby, P., and Whurr, R. (2001) Pharmacological treatment for aphasia following stroke. Cochrane Database Syst. Rev.:CD000424. Grünblatt, E., Schlösser, R., Fischer, P., Fischer, M.O., Li, J., Koutsilieri, E., Wichart, I., Sterba, N., Rujescu, D., Möller, H.J., Adamcyk, W., Dittrich, B., Müller, F., Oberegger, K., Gatterer, G., Jellinger, K.J., Mostafaie, N., Jungwirth, S., Huber, K., Tragl, K.H., Danielczyk, W., and Riederer, P. (2005) Oxidative stress related markers in the “VITA” and the centenarian projects. Neurobiol. Aging 26(4):429–438. Haass, C., Schlossmacher, M.G., Hung, A.Y., Vigo-Pelfrey, C., Mellon, A., Ostaszewski, B.L., Lieberburg, I., Koo, E.H., Schenk, D., Teplow, D.B., and Selkoe, D. (1992) Amyloid beta-peptide is produced by cultured cells during normal metabolism. Nature 359:322–325. Han, Y.S., Zheng, W.H., Bastianetto, S., Chabot, J.G., and Quirion, R. (2004) Neuroprotective effects of Resveratrol against betaamyloid induced neurotoxicity in rat hippocampal neurons: involvement of protein kinase C. Br. J. Pharmacol. 141:997–1005. Harman, D. (1956) Aging: a theory based on free radical and radiation chemistry. J. Gerontol. 11:298–300. Harmer, C.J., Bhagwagar, Z., Cowen, P.J., and Goodwin, G.M. (2002) Acute administration of citalopram facilitates memory consolidation in healthy volunteers. Psychopharmacol. 163:106–110.

60: PRINCIPLES OF PHARMACOTHERAPY Hartmann, S., and Moebius, H.J. (2003) Tolerability of memantine in combination with cholinesterase inhibitors in dementia therapy. Int. Clin. Psychopharmacol. 18:81–85. Ho, L., Qin, W., Stetka, B.S., and Pasinetti, G.M. (2006) Is there a future for cyclo-oxygenase inhibitors in Alzheimer’s disease? CNS Drugs 20:85–98. Hock, C., Konietzko, U., Streffer, J.R., Tracy, J., Signorell, A., MullerTillmanns, B., Lemke, U., Henke, K., Moritz, E., Garcia, E., Wollmer, M.A., Umbricht, D., de Quervain, D.J., Hofmann, M., Maddalena, A., Papassotiropoulos, A., and Nitsch, R.M. (2003) Antibodies against β -amyloid slow cognitive decline in Alzheimer’s disease. Neuron 38:547–554. Hogervorst, E., Yaffe, K., Richards, M., and Huppert, F. (2002) Hormone replacement therapy to maintain cognitive function in women with dementia. Cochrane Database Syst. Rev. (3):CD003799. Homocysteine Lowering Trialists’ Collaboration. (2005) Dosedependent effects of folic acid on blood concentrations of homocysteine: a meta-analysis of the randomized trials. Am. J. Clin. Nutr. 82:806–812. Howard, R.J., Juszczak, E., Ballard, C.G., et al. (2007) Donepezil for the treatment of agitation in Alzheimer’s disease. N. Engl. J. Med. 57:182–192. Huang, H.Y., Helzlsouer, K.J., and Appel, L.J. (2000) The effects of vitamin C and vitamin E on oxidative DNA damage: results from a randomized controlled trial. Cancer Epidemiol. Biomarkers Prev. 9:647–652. Hudson, S., and Tabet, N. (2003) Acetyl-L-carnitine for dementia. Cochrane Database for Dementia:CD003158. Hynd, M.R., Scott, H.L., and Dodd, P.R. (2004) Glutamate-mediated excitotoxicity and neurodegeneration in Alzheimer’s disease. Neurochem. Int. 45:583–595. Jakala, P., Riekkinen, M., Sirvio, J., Koivisto, E., Kejonen, K., Vanhanen, M., and Riekkinen, P., Jr. (1999) Guanfacine, but not clonidine, improves planning and working memory performance in humans. Neuropsychopharmacology 20:460–470. Janus, C., Pearson, J., McLaurin, J., Mathews, P.M., Jiang, Y., Schmidt, S.D., Chishti, M.A., Horne, P., Heslin, D., French, J., Mount, H.T., Nixon, R.A., Mercken, M., Bergeron, C., Fraser, P.E., St GeorgeHyslop, P., and Westaway, D. (2000) A beta peptide immunization reduces behavioural impairment and plaques in a model of Alzheimer’s disease. Nature 408(6815):979–982. Jenagaratnam, L., and McShane, R. (2006) Clioquinol for the treatment of Alzheimer’s disease. Cochrane Database Syst. Rev.:CD005380. Jick, H., Zornberg, G.L., Jick, S.S., et al. (2000) Statins and the risk of dementia. Lancet 356: 627–1631. Johnson, J.W., and Kotermanski, S.E. (2006) Mechanism of action of memantine. Curr. Opin. Pharmacol. 6:61–67. Kaduszkiewicz, H., Zimmermann, T., Beck-Bornholdt, H.P., and van den Bussche, H. (2005) Cholinesterase inhibitors for patients with Alzheimer’s disease: systematic review of randomized clinical trials. Br. Med. J. 331:321–327. Kanaya, A.M., Barrett-Connor, E., Gildengorin, G., and Yaffe, K. (2004) Change in cognitive function by glucose tolerance status in older adults. Arch. Intern. Med. 164:1327–1333. Kang, J., Lemaire, H.G., Unterbeck, A., Salbaum, J.M., Masters, C.L., Grzeschik, K.H., Multhaup, G., Beyreuther, K., and MullerHill, B. (1987) The precursor of Alzheimer’s disease amyloid A4 protein resembles a cell-surface receptor. Nature 325:733–736. Kanowski, S., Herrmann, W.M., Stephan, K., Wierich, W., and Hörr, R. (1996) Proof of efficacy of the ginkgo biloba special extract EGb 761 in outpatients suffering from mild to moderate primary degenerative dementia of the Alzheimer type or multi-infarct dementia. Pharmacopsychiatry 29(2):47–56. Kivipelto, M., Helkala, E.L., Laakso, M., et al. (2002) Apolipoprotein E e4 allele, elevated midlife total cholesterol level and high midlife systolic blood pressure are independent risk factors for late-life Alzheimer disease. Ann. Intern. Med. 137:149–155.

997

Kornhuber, J., and Weller, M. (1997) Psychotogenicity and N-methylD-aspartate receptor antagonism: implications for neuroprotective pharmacotherapy. Biol. Psychiatry 41:135–144. Kuczenski, R., and Segal, D.S. (1997) Effects of methylphenidate on extracellular dopamine, serotonin and norepinephrine: comparison with amphetamine. J. Neurochem. 68:2032–2037. Lal, S., Merbtiz, C.P., and Grip, J.C. (1988) Modification of function in head-injured patients with Sinemet. Brain Inj. 2(3):225–233. Lai, M.K.P., Tsang, S.W.Y., Francis, P.T., Keene, J., Hope, T., and Esiri, M.M. (2002) Postmortem serotonergic correlated of cognitive decline in Alzheimer’s disease. Neuroreport 13:1175–1178. La Pia, S., Fuschillo, C., Giorgio, D., Ciriello, R., Pinto, A., and Rivellini, M. (2001) Serotonin (5-HT)-related symptoms and fluoxetine in geriatric depression. Arch. Gerontol. Geriatr. 33(Suppl. 1): 213–225. Launer, L.J., Ross, G.W., Petrovitch, H., Masaki, K., Foley, D., White, L.R., and Havlik, R.J. (2000) Midlife blood pressure and dementia: the Honolulu-Asia aging study. Neurobiol. Aging 21: 49–55. Le Bars, P.L., Katz, M.M., Berman, N., Itil, T.M., Freedman, A.M., and Schatzberg, A.F. (1997) A placebo-controlled, double-blind, randomized trial of an extract of Ginkgo biloba for dementia. North American EGb Study Group. JAMA 278(16):1327–1332. LeBlanc, E.S., Janowsky, J., Chan, B.K., and Nelson, H.D. (2001) Hormone replacement therapy and cognition: systematic review and meta-analysis. JAMA 285:1489–1499. Lezoualc’h, F. (2007) 5-HT4 receptor and Alzheimer’s disease: the amyloid connection. Exp. Neurol. 205:325–329. Lim, W.S., Gammack, J.K., Van Niekerk, J., and Dangour, A.D. (2006) Omega 3 fatty acid for the prevention of dementia. Cochrane Database Syst. Rev.:CD005379. Lonn, E., Bosch, J., Yusuf, S., Sheridan, P., Pogue, J., Arnold, J.M., Ross, C., Arnold, A., Sleight, P., Probstfield, J., Dagenais, G.R., HOPE and HOPE-TOO Trial Investigators. (2005) Effects of long-term vitamin E supplementation on cardiovascular events and cancer: a randomized controlled trial. JAMA 293:1338– 1347. Lonn, E., Yusuf, S., Arnold, M.J., Sheridan, P., Pogue, J., Micks, M., McQueen, M.J., Probstfield, J., Fodor, G., Held, C., Genest, J., Jr., Heart Outcomes Prevention Evaluation (HOPE) 2 Investigators. (2006) Homocysteine lowering with folic acid and B vitamins in vascular disease. N. Eng. J. Med. 354:1567–1577. Loy, C., and Schneider, L. (2004) Galantamine for Alzheimer’s disease. Cochrane Database Syst. Rev.:CD001747. Luchsinger, J.A., and Mayeux, R. (2004) Cardiovascular risk factors and Alzheimer’s disease. Curr. Atheroscl. Rep. 6:261–266. Luchsinger, J.A., Reitz, C., Honig, L.S., and Mayeux, R. (2005) Aggregation of vascular risk factors and risk of incident Alzheimer disease. Neurology 65:545–551. Luchsinger, J.A., Tang, M.X., Miller, J., Green, R., and Mayeux, R. (2007) Relation of higher folate intake to lower risk of Alzheimer disease in the elderly. Arch. Neurol. 64:86–92. Luchsinger, J.A., Tang, M.X., Siddiqui, M., Shea, S., and Mayeux, R. (2004) Alcohol intake and risk of dementia. J. Am. Geriatr. Soc. 52:540–546. Luciana, M., Depue, R.A., Arbisi, P., and Leon, A. (1992) Facilitation of working memory in humans by a D2 dopamine receptor agonist. J. Cogn. Neurosci. 4:330–347. Luo, Y., Bolon, B., Kahn, S., Bennett, B.D., Babu-Khan, S., Denis, P., Fan, W., Kha, H., Zhang, J., Gong, Y., Martin, L., Louis, J.C., Yan, Q., Richards, W.G., Citron, M., and Vassar, R. (2001) Mice deficient in BACE-I, the Alzheimer’s β -secretase, have normal phenotype and abolished β -amyloid generation. Nat. Neurosci. 4:231–232. Maki, P., and Hogervorst, E. (2003) The menopause and HRT. HRT and cognitive decline. Best Pract. Res. Clin. Endocrinol. Metab. (1):105–122.

998

DEMENTIA

Malouf, M., Grimley, E.J., and Areosa, S.A. (2003) Folic acid with or without vitamin B12 for cognition and dementia. Cochrane Database Syst. Rev.:CD004514. Malouf, M., and Grimley Evans, J. (2003) The effect of vitamin B6 on cognition. Cochrane Database Syst. Rev.:CD004393. Malouf, M., and Areosa Sastre, A. (2003) Vitamin B12 for cognition. Cochrane Database Syst. Rev.:CD004326. Marambaud, P., Zhao, H., and Davies, P. (2005) Resveratrol promotes clearance of Alzheimer’s disease amyloid peptides. J. Biol. Chem. 280:37377–37382. Masliah, E., Hansen, L., Adame, A., Crews, L., Bard, F., Lee, C., Seubert, P., Games, D., Kirby, L., and Schenk, D. (2005) Aβ vaccination effects on plaque pathology in the absence of encephalitis in Alzheimer’s disease. Neurology 64:129–131. McDowell, S., Whyte, J., and D’Esposito, M. (1998) Differential effect of a dopaminergic agonist on prefrontal function in traumatic brain injury patients. Brain 121:1155–1164. McGaugh, J.L. (2004) The amygdale modulates the consolidation of memories of emotionally arousing experiences. Ann. Rev. Neurosci. 27:1–28. McGeer, P.L., and McGeer, E.G. (2001) Inflammation, autotoxicity and Alzheimer’s disease. Neurobiol. Aging 22:799–809. McGeer, P.L., and McGeer, E.G. (2007) NSAIDs and Alzheimer’s disease: epidemiological, animal model and clinical studies. Neurobiol. Aging 28:639–647. McGuiness, B., Todd, S., Passmore, P., and Bullock, R. (2006) The effects of blood pressure lowering on development of cognitive impairment and dementia in patients without apparent prior cerebrovascular disease. Cochrane Database Syst. Rev.:CD004034. McMahon, J.A., Green, T.J., Skeaff, C.M., Knight, R.G., Mann, J.I., and Williams, S.M. (2006) A controlled trial of homocysteine lowering and cognitive performance. N. Engl. J. Med. 354(26): 2764–2472. Mehta, M.A., Goodyer, I.M., and Sahakian, B.J. (2004) Methylphenidate improves working memory and set-shifting in AD/HD: relationships to baseline memory capacity. J. Child Psychol. Psychiatry 45:293–305. Mesulam, M.M., and Geula, C. (1994) Butyrylcholinesterase reactivity differentiates the amyloid plaques of aging from those of dementia. Ann. Neurol. 36:722–727. Mesulam, M., Guillotzet, A., Shaw, P., and Quinn, B. (2002) Widely spread butyrylcholinesterase can hydrolyze acetylcholine in normal and Alzheimer brain. Neurbiol. Dis. 9:88–93. Miller, E.R. 3rd, Pastor-Barriuso, R., Dalal, D., Riemersma, R.A., Appel, L.J., and Guallar, E. (2005) Meta-analysis: high-dosage vitamin E supplementation may increase all-cause mortality. Ann. Intern. Med. 142:37–46. Miller, N.J., and Rice-Evans, C.A.(1995) Antioxidant activity of resveratrol in red wine. Clin. Chem. 41(12 Pt 1):1789. Mogi, N., Umegaki, H., Hattori, A., Maeda, N., Miura, H., Kuzuya, M., Shimokata, H., Ando, F., Ito, H., and Iguchi, A. (2004) Cognitive function in Japanese elderly with type 2 diabetes mellitus. J. Diabet. Comp. 18:42–46. Monsonego, A., Zota, V., Karni, A., Krieger, J.I., Bar-Or, A., Bitan, G., Budson, A.E., Sperling, R., Selkoe, D.J., and Weiner, H.L. (2003) Increased T-cell reactivity to amyloid β protein in older humans and patients with Alzheimer’s disease. J. Clin. Inves. 112:415–422. Morgan, D., Diamond, D.M., Gottschall, P.E., Ugen, K.E., Dickey, C., Hardy, J., Duff, K., Jantzen, P., DiCarlo, G., Wilcock, D., Connor, K., Hatcher, J., Hope, C., Gordon, M., and Arendash, G.W. (2000) A beta peptide vaccination prevents memory loss in an animal model of Alzheimer’s disease. Nature 408(6815): 982–985. Morris, M.C., Evans, D.A., Bienias, J.L., Tangney, C.C., Bennett, D.A., Wilson, R.S., Aggarwal, N., and Schneider, J. (2003) Consumption of fish and n-3 fatty acids and risk of incident Alzheimer disease. Arch. Neurol. 60:940–946.

Mueller, U., von Cramon, D.Y., and Pollmann, S. (1998) D1- versus D2-receptor modulation of visuospatial working memory in humans. J. Neurosci. 18:2720–2728. Mueller, U., Mottweiler, E., and Bublak, P. (2005) Noradrenergic blockade and numeric working memory in humans. J. Psychopharmacol. 19:21–28. Mukherjee, D., Nissen, S.E., and Topol, E.J. (2001) Risk of cardiovascular events associated with selective COX-2 inhibitors. JAMA 286:954–959. Ng, T.P., Chiam, P.C., Lee, T., Chua, H.C., Lim, L., and Kua, E.H. (2006) Curry consumption and cognitive function in the elderly. Am. J. Epidemiol. 164:898–906. Nicoll, J.A., Wilkinson, D., Holmes, C., Steart, P., Markham, H., and Weller, R.O. (2003) Neuropathology of human Alzheimer disease after immunization with amyloid-β pepetide: a case report. Nature Med. 9:448–452. Ohrui, T., Tomita, N., Sato-Nakagawa, T., Matsui, T., Maruyama, M., Niwa, K., Arai, H., and Sasaki, H. (2004) Effects of brainpenetrating ACE inhibitors on Alzheimer disease progression. Neurology 63:1324–1325. Ono, K., Hasegawa, K., Haiki, H., and Yamada, M. (2004) Curcumin has potent anti-amyloidogenic effects for Alzheimer’s beta-amyloid fibrils in vitro. J. Neurosci. Res. 75:742–750. Ono, K., Hasegawa, K., Haiki, H., and Yamada, M. (2005) Preformed beta-amyloid fibrils are destabilized by coenzyme Q10 in vitro. Biochem. Biophys. Res. Commun. 330:111–116. Orgogozo, J.M., Gilman, S., Dartigues, J.F., Laurent, B., Puel, M., Kirby, L.C., Jouanny, P., Dubois, B., Eisner, L., Flitman, S., Michel, B.F., Boada, M., Frank, A., and Hock, C. (2003) Subacute meningoencephalitis in a subset of patients with AD after Aβ42 immunization. Neurology 61:46–54. Ott, A., Stolk, R.P., van Harskamp, F., Pols, H.A., Hofman, A., and Breteler, M.M. (1999) Diabetes mellitus and the risk of dementia: The Rotterdam Study. Neurology 53:1937–1942. Overtoom, C.C., Verbaten, M.N., Kemner, C., Kenemans, J.L., van Engeland, H., Buitelaar, J.K., van der Molen, M.W., van der Gugten, J., Westenberg, H., Maes, R.A., and Koelega, H.S. (2003) Effects of methylphenidate, desipramine, and L-dopa on attention and inhibition in children with attention deficit hyperactivity disorder. Behav. Brain Res. 145:7–15. Peila, R., Rodriguez, B.L., and Launer, L.J. (2002) Type 2 diabetes, ApoE gene and the risk for dementia and related pathologies. The Honolulu-Asia Aging Study. Diabetes 51:1256–1262. Perry, N.S.L., Bollen, C., Perry, E.K., and Ballard, C. (2003) Salvia for dementia therapy: review of pharmacological activity and pilot tolerability clinical trial. Pharmacol. Biochem. Behav. 75:651–659. Petersen, R.C., Thomas, R.G., Grundman, M., Bennett, D., Doody, R., Ferris, S., Galasko, D., Jin, S., Kaye, J., Levey, A., Pfeiffer, E., Sano, M., van Dyck, C.H., Thal, L.J., Alzheimer’s Disease Cooperative Study Group. (2005) Vitamin E and donepezil for the treatment of mild cognitive impairment. N. Engl. J. Med. 352: 2379–2388. Pfeifer, M., Boncristiano, S., Bondolfi, L., Stalder, A., Deller, T., Staufenbiel, M., Mathews, P.M., and Jucker, M. (2002) Cerebral hemorrhage after passive anti-Aβ immunotherapy. Science 298: 1379. Porter, R.J., Lunn, B.S., Walker, L.L., Gray, J.M., Ballard, C.G., and O’Brien, J.T. (2000) Cognitive deficit induced by acute tryptophan depletion in patients with Alzheimer’s disease. Am. J. Psychiatry 157:638–640. Qiu, C., Winblad, B., and Fratiglioni, L. (2005) The age-dependent relation of blood pressure to cognitive function and dementia. Lancet Neurol. 4:487–499. Refolo, L.M., Malester, B., LaFrancois, J., Bryant-Thomas, T., Wang, R., Tint, G.S., Sambamurti, K., Duff, K., and Pappolla, M.A. (2000) Hypercholesterolemia accelerates the Alzheimer’s amyloid pathology in a transgenic mouse model. Neurobiol. Dis. 7:321–331.

60: PRINCIPLES OF PHARMACOTHERAPY Richardson, J.S., Keegan, D.L., Bowen, R.C., Blackshaw, S.L., Cebrian Perez, S., and Dayal, N. (1994) Verbal learning by major depressive disorder patients during treatment with fluoxetine or amitriptyline. Int. Clin. Psychopharmacol. 9:35–40. Ringman, J.M., Frautschy, S.A., Cole, G.M., Masterman, D.L., and Cummings, J.L. (2005) A potential role of the curry spice curcumin in Alzheimer’s disease. Curr. Alzheimer Res. 2:131–136. Ritchie, C.W., Ames, D., Clayton, T., and Lai, R. (2004) Metaanalysis of randomized trials of the efficacy and safety of donepezil, galantamine and rivastigmine for the treatment of Alzheimer’s disease. Am. J. Geriatr. Psychiatry 12:358–369. Ritchie, C.W., Bush, A.I., Mackinnon, A., Macfarlane, S., Mastwyk, M., MacGregor, L., Kiers, L., Cherny, R., Li, Q.X., Tammer, A., Carrington, D., Mayros, C., Volitakis, I., Xilinas, M., Ames, D., Davis, S., Beyreuther, K., Tanzi, R.E., and Masters, C.L. (2003) Metal-protein attenuation with iodochlorhydroxyquin (clioquinol) targeting Aβ amyloid depostion and toxicity in Alzheimer disease: a pilot phase 2 clinical trial. Arch Neurol. 60:1685–1691. Rowley, B., Van, F., Mortimore, C., and Connell, J. (1998) Effects of acute tryptophan depletion on tests of frontal and temporal lobe function. J. Psychopharmacol. 12:A60. Rubinsztein, J., Rogers, R.D., Riedel, W.J., Mehta, M.A., Robbins, T.W., and Sahakian, B.J. (2001) Acute dietary tryptophan depletion impairs affective shifting and delayed visual recognition in healthy volunteers. Psychopharmacol. 154:319–326. Sano, M., Ernesto, C., Thomas, R.G., Klauber, M.R., Schafer, K., Grundman, M., Woodbury, P., Growdon, J., Cotman, C.W., Pfeiffer, E., Schneider, L.S., and Thal, L.J. (1997) A controlled trial of selegiline, alpha-tocopherol, or both as treatment for Alzheimer’s disease. The Alzheimer’s Disease Cooperative Study. N. Engl. J. Med. 336:1216–1222. Savaskan, E., Olivieri, G., Meier, F., Seifritz, E., Wirz-Justice, A., and Müller-Spahn, F. (2003) Red wine ingredient resveratrol protects from beta-amyloid neurotoxicity. Gerontology 49(6): 380–383. Schenk, D., Barbour, R., Dunn, W., Gordon, G., Grajeda, H., Guido, T., Hu, K., Huang, J., Johnson-Wood, K., Khan, K., Kholodenko, D., Lee, M., Liao, Z., Lieberburg, I., Motter, R., Mutter, L., Soriano, F., Shopp, G., Vasquez, N., Vandevert, C., Walker, S., Wogulis, M., Yednock, T., Games, D., and Seubert, P. (1999) Immunization with amyloid-β attenuates Alzheimer-disease-like pathology in the PDAPP mouse. Nature 400:173–177. Schenk, D., Hagen, M., and Seubert, P. (2004) Current progress in β -amyloid immunotherapy. Curr. Opin. Immunol. 16:599–606. Schmitt, J.A.J., Kruizinga, M., and Riedel, W.J. (2001) Nonserotonergic pharmacological profiles and associated cognitive effects of serotonin reuptake inhibitors. J. Psychopharmacol. 15: 173–179. Schuck, S., Bentue-Ferrer, D., Kleinermans, D., Reymann, J.M., Polard, E., Gandon, J.M., and Allain, H. (2002) Psychomotor and cognitive effects of piribedil, a dopamine agonist, in young healthy volunteers. Fundam. Clin. Pharmacol. 16:57–65. Senin, U., Parnetti, L., Barbagallo-Sangiorgi, G., Bartorelli, L., Bocola, V., Capurso, A., Cuzzupoli, M., Denaro, M., Marigliano, V., Tammaro, A.E., and Fioravanti, M. (1992) Idebenone in senile dementia of Alzheimer type: a multicentre study. Arch. Gerontol. Geriatr. 15:249–260. Seshadri, S., Beiser, A., Selhub, J., Jacques, P.F., Rosenberg, I.H., D’Agostino, R.B., Wilson, P.W., and Wolf, P.A. (2002) Plasma homocysteine as a risk factor for dementia and Alzheimer’s disease. N. Eng. J. Med. 346:476–483. Seubert, P., Vigo-Pelfrey, C., Esch, F., Lee, M., Dovey, H., Davis, D., Sinha, S., Schlossmacher, M., Whaley, J., and Swindlehurst, C. (1992) Isolation and quantification of soluble Alzheimer’s betapeptide from biological fluids. Nature 359:325–327. Sheline, Y.I., Mintun, M.A., Moerlein, S.M., and Snyder, A.Z. (2002) Greater loss of 5-HT(2A) receptors in midlife than in late life. Am. J. Psychiatry 159:430–435.

999

Shumaker, S.A., Legault, C., Kuller, L., Rapp, S.R., Thal, L., Lane, D.S., Fillit, H., Stefanick, M.L., Hendrix, S.L., Lewis, C.E., Masaki, K., Coker, L.H., Women’s Health Initiative Memory Study. (2004) Conjugated equine estrogens and incidence of probable dementia and mild cognitive impairment in postmenopausal women: Women’s Health Initiative Memory Study. JAMA 291:2947–2958. Siemers, E.R., Quinn, J.F., Kaye, J., Farlow, M.R., Porsteinsson, A., Tariot, P., Zoulnouni, P., Galvin, J.E., Holtsman, D.M., Knopman, D.S., Satterwhite, J., Gonzales, C., Dean, R.A., and May, P.C. (2006) Effects of a γ-secretase inhibitor in a randomized study of patients with Alzheimer’s disease. Neurology 66:602–604. Siemers, E.R., Skinner, M., Dean, R.A., Gonzales, C., Satterwhite, J., Farlow, M., Ness, D., and May, P.C. (2005) Safety, tolerability and changes in amyloid-β concentrations after administration of a γ-secretase inhibitor in volunteers. Clin. Neuropharmacol. 28: 126–132. Simons, M., De Strooper, B., Multhaupt, G., Tienari, P.J., Dotti, C. G., and Beyreuther, K. (1996) Amyloidogenic processing of the human amyloid precursor protein in primary cultures of rat hippocampal neurons. J. Neurosci. 16:899–908. Skoog, I., Lithell, H., Hansson, L., Elmfeldt, D., Hofman, A., Olofsson, B., Trenkwalder, P., Zanchetti, A., SCOPE Study Group. (2005) Effect of baseline cognitive function and antihypertensive treatment on cognitive and cardiovascular outcomes: study on cognition and prognosis in the elderly (SCOPE). Am. J. Hypertension 18:1052–1059. Sparks, D.L., Connor, D.J., Sabbagh, M.N., Petersen, R.B., Lopez, J., and Browne, P. (2006) Circulating cholesterol levels, apolipoprotein E genotype and dementia severity influence the benefit of atorvastatin treatment in Alzheimer’s disease: results of the Alzheimer’s Disease Cholesterol-Lowering Treatment (ADCLT) trial. Acta Neurol. Scand. 185(Suppl):3–7. Sparks, D.L., Sabbagh, M., Connor, D.J., Lopez, J., Launer, L.J., Browne, P., Wasser, D., Johnson-Traver, S., Lochhead, J., and Ziolwolski, C. (2005) Atorvastatin for the treatment of mild to moderate Alzheimer’s disease. Arch. Neurol. 62:753–757. Swartz, J.R., Miller, B.L., Lesser, I.M., and Darby, A.L. (1997) Frontotemporal dementia: Treatment response to serotonin selective reuptake inhibitors. J. Clin. Psychiatry 58:212–216. Takeda, A., Loveman, E., Clegg, A., Kirby, J., Picot, J., Payne, E., and Green, C. (2006) A systematic review of the clinical effectiveness of donepezil, rivastigmine and galantamine on cognition, quality of life and adverse effects in Alzheimer’s disease. Int. J. Geriatr. Psychiatry 21:17–28. Tariot, P.N., Farlow, M.R., Grossberg, G.T., Graham, S.M., McDonald, S., Gergel, I., for the Memantine Study Group. (2004) Memantine treatment in patients with moderate to severe Alzheimer disease already receiving treatment. JAMA 291:317–324. Thal, L.J., Ferris, S.H., Kirby, L., Block, G.A., Lines, C.R., Yuen, E., Assaid, C., Nessly, M.L., Norman, B.A., Baranak, C.C., Reines, S.A., Rofecoxib Protocol 078 Study Group. (2005) A randomized, double-blind study of rofecoxib in patients with mild cognitive impairment. Neuropsychopharmacology 30:1204–1215. Thal, L.J., Grundman, M., Berg, J., Ernstrom, K., Margolin, R., Pfeiffer, E., Weiner, M.F., Zamrini, E., and Thomas, R.G. (2003) Idebenone treatment fails to slow cognitive decline in Alzheimer’s disease. Neurology 61:1498–1502. Thierry, A.M., Pirot, S., Gioanni, Y., and Glowinski, J. (1998) Dopamine function in the prefrontal cortex. Adv. Pharmacol. 42:717–720. Truelsen, T., Thudium, D., and Gronbaek, M. (2002) Amount and type of alcohol and risk of dementia. Neurology 59:1313–1319. Turner, D.C., Robbins, T.W., Clark, L., Aron, A.R., Dowson, J., and Sahakian, B.J. (2003) Relative lack of cognitive effects of methylphenidate in elderly male volunteers. Psychopharmacology 168(4): 455–464.

1000

DEMENTIA

Tzourio, C., Dufouil, C., Ducimetiere, P., and Alperovitch, A. (1999) Cognitive decline in individuals with high blood pressure: a longitudinal study in the elderly-EVA study group. Epidemiology of vascular aging. Neurology 53:1948–1952. Ushida, C., Umegaki, H., and Hattori, A. (2001) Assessment of brain atrophy in elderly subjects with diabetes mellitus by computed tomography. Geriatr. Gerontol. Int. 1:33–37. Vassar, R., Bennett, B.D., Babu-Khan, S., Kahn, S., Mendiaz, E.A., Denis, P., Teplow, D.B., Ross, S., Amarante, P., Loeloff, R., Luo, Y., Fisher, S., Fuller, J., Edenson, S., Lile, J., Jarosinski, M.A., Biere, A.L., Curran, E., Burgess, T., Louis, J.C., Collins, F., Treanor, J., Rogers, G., and Citron, M. (1999) Beta-secretase cleavage of Alzheimer’s amyloid precursor protein by the transmembrane aspartic protease BACE. Science 286:735–741. van Dongen, M.C., van Rossum, E., Kessels, A.G., Sielhorst, H.J., and Knipschild, P.G. (2000) The efficacy of ginkgo for elderly people with dementia and age-associated memory impairment: new results of a randomized clinical trial. J. Am. Geriatr. Soc. 48(10):1183–1194. Van Steegeren, A.H., Everaerd,W., and Gooren, L.J. (2002) The effect of beta-adrenergic blockade after encoding on memory of an emotional event. Psychopharmacol. 163:202–212. Watkins, P.B., Zimmermann, H.J., Knapp, M.J., Gracon, S.I., and Lewis, K.W. (1994) Hepatotoxic effects of tacrine administration in patients with Alzheimer’s disease. JAMA 271:992–998. Weggen, S., Eriksen, J.L., Das, P., Sagi, S.A., Wang, R., Pietrzik, C.U., Findlay, K.A., Smith, T.E., Murphy, M.P., Bulter, T., Kang, D.E., Marquez-Sterling, N., Golde, T.E., and Koo, E.H. (2001) A subset of NSAIDs lower amyloidogenic Aβ 42 independently of cyclooxygenase activity. Nature 414:212–216. Weyer, G., Babej-Dolle, R.M., Hadler, D., Hofmann, S., and Herrmann, W.M. (1997) A controlled study of 2 doses of idebenone in the treatment of Alzheimer’s disease. Neuropsychobiology 36:73–82.

Whitehead, A., Perdomo, C., Pratt, R.D., Birks, J., Wilcock, G.K., and Evans, J.G. (2004) Donepezil for the symptomatic treatment of patients with mild to moderate Alzheimer’s disease: a metaanalysis of individual patient data from randomized controlled trials. Int. J. Geriatr. Psychiatry 19:624–633. Winblad, B., Jelic, V., Kershaw, P., and Amatniek, J. (2007) Effects of statins on cognitive function in patients with Alzheimer’s disease in galantamine clinical trials. Drugs Aging 24:57–61. Wilcock, G., Black, S., Hendrix, S., Zavitz, K., Laughlin, M., and Swabb, E. (2007, Aug. 25–28) Flurizan in AD: Efficacy and Safety in a 24 month Study. Paper presented at the European Federation of Neurological Societies (EFNS), Brussels, Belgium. Wolozin, B., Kellman, W., Ruosseau, P., Celesia, G.G., and Siegel, G. (2000) Decreased prevalence of Alzheimer’s disease associated with 3-hydroxy-3-methylglutaryl Coenzyme A reductase inhibitors. Arch. Neurol. 57:1439–1443. Wu, J.H., Haan, M.N., Liang, J., Ghosh, D., Gonzalez, H.M., and Herman, W.H. (2003) Impact of antidiabetic medications on physical and cognitive functioning of older Mexican Americans with diabetes mellitus: a population-based cohort study. Ann. Epidemiol. 13:369–376. Yasojima, K., Schwab, C., McGeer, E.G., and McGeer, P.L. (1999) Distribution of cyclooxygenase-1 and cyclooxygenase-2 mRNAs and proteins in human brain and peripheral organs. Brain Res. 830:226–236. Zhang, Z., Wang, X., Chen, Q., Shu, L., Wang, J., and Shan, G. (2002) Clinical efficacy and safety of huperzine alpha in treatment of mild to moderate Alzheimer disease, a placebo-controlled, double-blind, randomized trial. Chin. Med. J. 82:2231–2252. Zhou, B., Teramukai, S., and Fukushima, M. (2007) Prevention and treatment of dementia or Alzheimer’s disease by statins: a metaanalysis. Dement. Geriatr. Cogn. Disord. 23:194–201.

61 Cognitive Impairment in Demyelinating Disease THOMAS M. HYDE

Multiple sclerosis (MS) is a chronic yet episodic demyelinating disorder of the central nervous system (CNS), often involving the brain, spinal cord, and/or cranial nerves. The traditional definition includes the criteria of events “separated by time and space.” Practically speaking, this means that signs and symptoms occur, remit, and recur over a period of many years (time) in different locations in the CNS (space). The neurological manifestations are as varied as the functions of the CNS. The exact manifestations in a given case depend upon the location of the inflammatory destructive lesion(s). Common clinical features include weakness, paralysis, loss of vision, double vision, dysarthria, intention tremor, incoordination, imbalance, sensory changes, and bladder problems. Cognitive impairment can also occur and is frequently overlooked. The pattern of relapse and remission is common in the early phases of the illness. Later on, many patients convert to a chronic progressive disorder. The diagnosis of MS is made based on the clinical history and laboratory findings. The hallmark of MS is a relapsing and remitting pattern of multiple focal neurological deficits occurring over several years. Laboratory and neuroimaging studies are useful for confirmation. Traditionally, examination of the cerebrospinal fluid (CSF) is particularly helpful. During an acute flare, the CSF often shows a mild mononuclear pleocytosis and/ or elevated protein level. The gamma globulins in the CSF are synthesized within the nervous system, and in MS on gel electrophoresis form an abnormal pattern termed oligoclonal bands. Oligoclonal bands are present in the CSF of the overwhelming majority of patients with MS. Bands have also been reported in neurosyphilis and subacute sclerosing panencephalitis. The presence of bands in the CSF but not in the blood is helpful in confirming the diagnosis of MS, but often they are not present following the first episode. Modern neuroimaging and electrophysiology have increased the accuracy of diagnosis in MS. Neuroimaging studies, particularly magnetic resonance imaging (MRI), are exceedingly helpful in confirming the diagnosis of MS. In fact, MRI can reveal clinically silent plaques

throughout the nervous system. Multifocal lesions, often in the white matter and frequently with a periventricular distribution pattern, are the classic MRI finding in MS. Acute lesions can enhance on occasion with the injection of gadolinium. In addition, atrophy of white matter structures, such as the corpus callosum or medullary pyramids, often occurs later in the course of the disease. Evoked potentials, an electrophysiological measure, can also be useful in MS. Because MS is an inflammatory condition with a preference for myelinated fiber pathways, conductance along known fiber pathways is often slowed in patients with MS. Typically, visual, auditory, and somatosensory evoked potentials are measured to test the competence of signal transmission along their respective pathways in the nervous system. Taken together, laboratory studies can be a useful adjunct to the clinical history and examination in suspected cases of MS. The differential diagnosis of MS includes CNS manifestations of many systemic illnesses, including autoimmune diseases. These include systemic lupus erythematosus, Sjögren syndrome, polyarteritis nodosa, sarcoidosis, Behçet’s disease, Lyme disease, neurosyphilis, progressive multifocal leukoencephalopathy, vitamin B12 deficiency, metachromatic leukodystrophy, Fabry’s disease, adrenoleukodystrophy, lymphoma, arteriovenous malformations, and recurrent small embolic or thrombotic infarcts of the CNS (Trojano and Paolicelli, 2001). Careful histories, examinations, and laboratory studies help differentiate between these entities and MS. The epidemiology of MS has spawned a number of theories about the etiology of this disorder. The prevalence ranges from 1 to 100 per 100,000, increasing with increasing distance from the equator (Weinshenker, 1996; Kurtzke, 2000). The gradient is less prominent but present in the Southern Hemisphere. Individuals of northern European ancestry are at highest risk (Weinshenker, 1996). Individuals who migrate from a high-risk to a low-risk latitude retain some of the risk of their place of birth, especially if they migrate after 15 years of age (Dean, 1967). In addition, there have been reports of “epidemics” of MS theoretically ascribed to the immi1001

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gration of individuals from high-risk areas (Kurtzke and Hyllested, 1985). Taken together, these findings support a transmissible environmental factor in the etiology of MS. Many environmental factors have been proposed for MS, yet none has been clearly and reproducibly established. Genetic factors also play a role in the genesis of MS. The disease occurs in relatives of patients with MS with a frequency 10–50 times greater than that in the general population, with the highest risk occurring in siblings (Sadovnick et al., 1988). Twin studies also support a heritable factor in the etiology of MS. There is an eightfold greater risk in monozygotic twins compared to dizygotic twins (Ebers et al., 1986; Sadovnick et al., 1993). The pattern of genetic transmission does not follow that of strict Mendelian inheritance. Additionally, an increased risk in family members of index cases is not strict evidence of a genetic factor because family members share environmental risk factors in addition to genes. However, the discrepancy between dizygotic and monozygotic twins is the strongest evidence for a genetic predisposition toward the development of MS. In all likelihood, MS is caused by the effects of environmental factor(s) acting upon individuals with a genetic susceptibility towards this illness. Recently, two separate groups have reported that variations in the interleukin 7 receptor alpha chain gene influence the risk of multiple sclerosis (Gregory et al., 2007; Lundmark et al., 2007). The first citation relied upon data from four independent family-based or casecontrol data sets. Moreover, the latter group also found altered expression of the genes encoding for the interleukin 7 receptor alpha chain and its ligand (interleukin 7) in the CSF of individuals with MS. As more sophisticated techniques become widely employed, the precise nature of the genetic factors influencing risk for MS should be forthcoming in the near future. Women are more at risk of developing MS than men, in some studies up to 3 times more so (Baum and Rothschild, 1981). The risk of disease is highest between 20 and 40 years of age and then declines. Many late-life cases might represent reactivation of dormant or clinically silent disease that began decades before clinical presentation. Neuropathology studies suggest that clinically silent MS may be more common than was previously believed (Gilbert and Sadler, 1983). Understanding the role of gender and age may ultimately help unravel the environmental and genetic factors that underlie MS. COGNITIVE IMPAIRMENT IN MULTIPLE SCLEROSIS Cognitive impairment can appear anytime during the clinical course of MS, although it most often appears later in the illness. Cognitive impairment is often overlooked, especially in its early stages, because of the dra-

matic and more obvious elemental neurological deficits of most patients with MS. Between 40% and 65% of all patients with MS develop significant levels of cognitive disability (Rao, Leo, Bernardin, et al., 1991; DeSousa et al., 2002). Several large studies have placed the incidence in community-based patients with MS at around 50% (LaRocca, 1984). In nursing home populations of patients with MS, which might be expected to have a greater frequency of cognitive impairment, only about 50% were thought to be impaired although the scale employed was not very sophisticated or detailed (Buchanan et al., 2001). Ascertainment bias is a significant issue when assessing the frequency of cognitive impairment in the MS patient population. The frequency varies, depending upon the source of the patients, the age of the patients, the duration of illness, the type of MS, and the instruments used to perform the cognitive assessment. For example, patients with the relapsing-remitting form of MS tend to have fewer cognitive deficits than those with the chronic progressive form (Heaton et al., 1985; Wishart and Sharpe, 1997). Testing for cognitive processing deficits can be extremely difficult in MS. The motor and sensory deficits make neuropsychological testing difficult and may confound the results. For example, in a patient with severe diplopia, tests relying upon the visual system may appear to reveal severe impairment. One might mistakenly interpret this as a deficit in cortical processing of visually based information, when in fact it may be due to a deficit in the more elemental aspects of the visual system. Careful neuropsychological studies must take these issues into consideration in patient selection and data interpretation. Heterogeneity of disease severity must also be considered when comparing studies. Patients who are more severely affected by MS, not surprisingly, are predisposed toward cognitive deficits. However, even in the early stages of illness, patients with MS have shown deficits in verbal memory and abstract reasoning (Amato et al., 1995). The course of illness—relapsing-remitting, primary progressive, and secondary progressive—may also play a role in the type of cognitive impairment observed. Patient populations should be carefully characterized and classified into subtypes before inclusion in a study (Peyser et al., 1990). There is no uniform pattern of cognitive impairment in patients with MS. Most commonly, deficits occur in recent memory, attention span, abstract and conceptual reasoning, and rate of information processing. Language is affected less frequently. In general, cognitive deficits in MS appear to follow a profile usually associated with so-called subcortical dementias. Memory is the most commonly impaired cognitive domain in patients with MS. Defining the nature of this memory deficit has been a work in progress. Different groups use different memory tests. Pure replications have been infrequent. In addition, definitions of

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the aspects of memory vary from group to group. In general, patients with MS show deficits both in working memory, a “prefrontal cortical task,” and episodic recall, a “mesial temporal task.” Working memory, the aspect of memory that permits the manipulation and application of information to problem solving, is also impaired in patients with MS. The frontal lobes seem to be preferentially vulnerable to the development of lesions in MS (Sperling et al., 2001; Lazeron et al., 2005). Heaton et al. (1985) found that patients with MS make more perseveration errors than controls. Using a different paradigm, Rao and Hammeke (1984) also found that patients with chronic progressive MS tend to perseverate and do not modify their problem-solving strategy even with verbal cueing. Working memory dysfunction may be more common in secondary progressive rather than primary progressive MS (Comi et al., 1995). Rovaris et al. (2000) found that a significant proportion of patients with MS perform poorly on a battery of tests of executive function and working memory. Using a wide variety of tests of executive function combined with careful exclusion criteria, Foong et al. (1997) showed that the deficits in executive function were not attributable to primary visual system abnormalities. Patients with frontal white matter lesions tend to have more working memory deficits than other MS patient groups (Arnett et al., 1994). Even early in the course of illness, patients with MS may suffer from working memory deficits (Schulz et al., 2006). As with many other aspects of the illness, only a subset of patients with MS have difficulty with concept formation, set shifting, and modification of responses and problemsolving strategies even with environmental feedback. Working memory deficits seem to be a feature primarily of the progressive rather than the relapsing-remitting form of the illness (Archibald and Fisk, 2000). In general, working memory deficits usually implicate dysfunction of the dorsolateral prefrontal cortex (Berman et al., 1995; D’Esposito and Postle, 1999). However, most studies that have associated prefrontal cortical function with working memory emphasize the role of prefrontal gray matter rather than white matter. In MS, the lesions either interrupt input to or output from the prefrontal cortex, suggesting that any working memory deficits in MS are related to disconnection of the neural network subserving working memory. Short-term memory is usually unaffected, but spontaneous and free recall is often deficient (Beatty and Monson, 1996). Fisher (1988) found impairment in general memory, verbal memory, visual memory, and delayed recall. Camp et al. (1999) also found deficits in verbal memory, whereas Rendell et al. (2007) found impairments in prospective memory. Rao et al. (1984; Rao et al., 1993) found deficiencies in immediate and delayed recall. Episodic memory, which is used for day-to-day functions such as the retrieval of appointment times, recall of lists,

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and recall of places (Rao et al., 1984; Rao, Leo, and St. Aubin-Faubert, 1989; Minden et al., 1990), is more affected than semantic memory, which is used for the retrieval of overlearned names and facts (Beatty et al., 1989; Filley et al., 1989). Automatic memory, which is involved in the most simple coding and categorization of a stimulus, is preserved, in contrast to the more effortful free and cued-recall measures in patients with MS (Grafman et al., 1991; Rao et al., 1993). Thornton and Raz (1997) conducted a meta-analysis of 36 studies investigating memory function in patients with MS. They concluded that there is significant impairment in all memory domains, not just in retrieval in long-term memory. Another group found abnormalities in reaction time, nonverbal memory, and planning (Schulz et al., 2006). Other groups have found that the primary memory deficit in patients with MS is in the learning of new information (Rao et al., 1984; Gaudino et al., 2001). Verbal memory deficits were associated with the progressive forms of MS. Retrieval failure was noted only in the progressive form of MS. Patients with MS perform normally on tests of motor learning (Rao et al., 1993). Part of the difficulty in interpreting these data is due to the variability in memory deficits in patients with MS. Rao et al. (1984) found that one third of patients with chronic progressive MS performed normally on memory testing, and only 21% were severely affected. In general, learning, recall, and effortful memory measures are abnormal in patients with MS, whereas shortterm memory capacity is unimpaired. Attention span may be abnormal in patients with MS, particularly those with progressive forms of the illness (Fisher, 1988; Filley et al., 1989; Rao, Leo, Bernardin, et al., 1991; Ron et al., 1991; Feinstein, Kartsounis, et al., 1992; Feinstein, Youl, et al., 1992; Camp et al., 1999; Sperling et al., 2001; Schulz et al., 2006). The tasks used to measure attention span vary across these studies, and some do not actually address attention as much as short-term or working memory. Visual and auditory attention are often impaired (Ron et al., 1991). In one study, attention deficits were found relatively early in the course of MS (Feinstein, Kartsounis, et al., 1992; Feinstein, Youl, et al., 1992). However, another group reported that attention deficits appeared only with an extended duration of illness (Amato et al., 2001). A more detailed investigation of attention span in different clinical subtypes of MS might help resolve these discrepancies. Attention involves a widely distributed cortical and subcortical network of interconnected structures (Mesulam, 1981). It is not surprising that at least in some patients with MS, the function of this network is disrupted. Visuospatial perception and memory also are impaired in some patients with MS (Rao, Leo, Bernardin, et al., 1991; Comi et al., 1995). It is not clear if this is due to abnormalities within the primary visual system (that are

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common in MS) or to second- and third-order deficits in complex visuospatial processing in association cortex. Parietal white matter is often the site of lesions in patients with MS (Sperling et al., 2001). Lesions in visual association cortex, particularly in the occipito-temporoparietal junction, are often implicated in visuospatial perception impairment (Cogan, 1979). Additional investigation would be useful. Cognitive processing speed is slowed in many patients with MS (Kail, 1998; Demaree et al., 1999; Archibald and Fisk, 2000; Sperling et al., 2001). Auditory and visual information processing speed are diminished in patients with MS; however, when these patients are given sufficient time, their performance rises to that of controls (Demaree et al., 1999). This is not an unexpected finding because a delay in conductance along well-recognized primary visual and auditory pathways has long been recognized as a feature of MS as a consequence of demyelination. In fact, it is the basis of the use of evoked potential measurements for the diagnosis of this disease. The use of reaction time as a measure of cognitive processing speed must be interpreted cautiously. Incoordination, weakness, and tremor may impede the speed of the motor response, whereas the speed of the conceptual formulation of the response may be within normal limits. More classic neurological syndromes of cognitive impairment, such as aphasia, agnosia, and apraxia, are rarely observed in patients with MS. This may be related to the nature of the pathology in MS. In general, MS lesions tend to be relatively small. To produce aphasia or any of the classic cortical lesion syndromes, extensive damage must occur to a precise region of cortex or to fiber pathways arising from the region. The lesions in MS rarely are that extensive, in contrast to strokes, where such syndromes are common. Cognitive functions that are subserved by a more extensive network of structures, such as memory, learning, and attention span, may be more vulnerable to the accumulated effects of small but widely distributed lesions. There has been some systematic investigation of language function in patients with MS. In general, though abnormalities in language function have been reported, they tend to be relatively mild compared to other aspects of cognitive dysfunction in patients with MS (Jambor, 1969; Heaton et al., 1985). Classic aphasia syndromes are quite rare (Olmos-Lau et al., 1977). There are very few reports of classic agnosia or apraxia. Cognitive impairment markedly alters the quality of life for patients with MS. Their activities of daily living may be severely affected in social and vocational spheres. Their ability to function independently may also be diminished. Those with cognitive deficits are less likely to be employed, are more socially withdrawn, and have greater difficulty performing routine household tasks (Rao, Leo, Ellington, et al., 1991). However, at least in

one longitudinal study of 1 year’s duration, most patients with MS, regardless of subtype, did not show significant cognitive decline (Hohol et al., 1997). MAGNETIC RESONANCE IMAGING ABNORMALITIES AND COGNITIVE IMPAIRMENT IN MULTIPLE SCLEROSIS Prior to the advent of MRI, it was difficult to perform lesion assessment with available neuroimaging techniques. With the exception of active lesions that enhance with contrast injections, MS lesions are difficult to delineate by computed tomography (CT) scan. Therefore, initial neuroimaging studies using this modality focused on ventricular size. Two groups reported that ventricular enlargement correlated with cognitive impairment in MS by CT scan (Rao et al., 1985; Rabins et al., 1986). Because ventricular enlargement is often a correlate of cerebral atrophy, such a correlation is not surprising. In a refined approach to the same issue using MRI measures, Edwards et al. (2001) found that a lower volume of cerebral white matter correlated with poorer performance on a battery of neuropsychological tests, though this group was not able to correlate ventricular enlargement as measured on MRI with poor test performance. Performance on a comprehensive measure of cognitive ability inversely correlated with global gray matter volume in patients with relapsing-remitting MS (Morgen et al., 2006). Neuroimaging studies with MRI have been invaluable in improving diagnostic accuracy in MS. Several groups have tried to correlate lesion location and number/density with cognitive deficits in patients with MS. For example, several groups have found that patients with MS who were impaired on a neuropsychological screening battery had more brain lesions on MRI than unimpaired patients (Franklin et al., 1988; Ron et al., 1991; Comi et al., 1995; Hohol et al., 1997; Rovaris et al., 1998; Camp et al., 1999; Rovaris et al., 2000). There is disagreement as to the relationship between the clinical subtype of MS, the extent of lesion load, and the degree of neuropsychological impairment (Comi et al., 1995; Hohol et al., 1997; Camp et al., 1999; Fulton et al., 1999). There appears to be a preferential involvement of frontoparietal white matter in MS by MRI analysis (Sperling et al., 2001). Cognitive dysfunction generally correlates with lesions located at the gray-white junction in the prefrontal, limbic, and association cortical regions (Charil et al., 2003). It should be noted that lesion load as measured with conventional MRI may underestimate the extent of the pathology in MS (Davie et al., 1994). Moreover, MRI measures as presently constituted do not differentiate between active inflammation and gliotic scarring. Finally, lesion expansion and regression may be more common

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in MS than clinical measures of disease activity might suggest (Isaac et al., 1988; Harris et al., 1991). So-called asymptomatic lesions may actually be symptomatic, depending upon the sensitivity and breadth of the clinical instruments employed. Nevertheless, at least in a small longitudinal study, patients with active disease as measured by lesion load on MRI scan had a fall-off in performance on neuropsychological testing, especially in tests of attention and information-processing speed. This functional deterioration was not present in patients with MS with static MRI measures (Feinstein et al., 1993). Working memory and executive function impairment may be closely correlated with lesion load in the frontal lobes. Three groups have reported that poor performance on the Wisconsin Card Sort Test is directly correlated with the severity of frontal involvement as measured on MRI scan (Swirsky-Sacchetti et al., 1992; Arnett et al., 1994; Nocentini et al., 2001). Abstraction and conceptual reasoning are most often impaired in patients with MS with a high lesion load (Rao, Leo, Haughton, et al., 1989). Working memory performance inversely correlated with prefrontal and global grey matter volume in patients who were mildly disabled with relapsing-remitting MS (Morgen et al., 2006). In a study that used multiple measures of working memory and executive function in MS, Foong et al. (1997) found that poorer performance on spatial working memory and planning tasks was correlated with the frontal lesion load in MS. However, this correlation disappeared when the result was normalized by total lesion load (Foong et al., 1997). The authors interpreted this to mean that a widespread pathology may underlie executive dysfunction in MS, not just a frontal lesion load. A similar finding was noted by two other groups (Rovaris et al., 1998; Rovaris et al., 2000; Nocentini et al., 2001). One interpretation holds that neuropsychological tests purporting to assess frontal lobe function actually depend upon a more widely distributed neural network. Alternatively, patients with a higher lesion load in the frontal cortex might be expected to have an overall increase in brain lesion load. Correcting for total brain lesion load may obscure the role of frontal lobe lesions in executive function and working memory in MS. The only way to address this issue definitively is to study that probably rare group of patients with MS with predominantly frontal lobe lesions or those with relative sparing of the frontal lobes. Verbal and visual memory deficits are correlated with lesion load in MS (Ron et al., 1991). The greater the total lesion area, the worse patients with MS perform on measures of recent memory (Rao, Leo, Haughton, et al., 1989). In addition, long-term memory deficits in patients with relapsing-remitting MS also correlate with lesion load. However, short-term memory deficits may not correlate with lesion load in this patient subset (Fulton et al., 1999). Volume loss in cerebral white matter has been

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correlated with poor performance on a test of visuospatial memory (Edwards et al., 2001). As noted previously, attention deficits are common in patients with MS. Even in patients early in their clinical course, attention deficits may already be present (Feinstein, Kartsounis, et al., 1992; Feinstein, Youl, et al., 1992; Schulz et al., 2006). Moreover, attention deficits are often associated with clinically silent and unsuspected cerebral lesions on MRI scan. Worsening attention deficits correlate closely with increasing lesion load on MRI (Hohol et al., 1997; Sperling et al., 2001). Auditory attention is impaired in individuals with a high lesion load in MS (Ron et al., 1991). However, lesion load does not correlate with attention measures by all groups (Rao, Leo, Haughton, et al., 1989). Sperling et al. (2001) found that total, frontal, and parietal lesion load all correlated with attentional performance. Other aspects of neuropsychological function have been examined in the context of lesion load on MRI scan. Abnormalities in information processing speed correlate directly with progressive increases in lesion load on MRI (Hohol et al., 1997; Fulton et al., 1999). The functional substrate of this finding might benefit from more refined anatomical distribution studies of lesion load. The corpus callosum is an easily measured white matter structure. Atrophy of the corpus callosum has been associated with poor performance on a dichotic listening task in patients with MS (Rao, Bernardin, et al., 1989). Cross-callosal pathways are essential to proper performance of this task. The degradation of fiber pathways contributing to reduced interhemispheric communication produced by MS probably underlies this finding. In addition, atrophy of the corpus callosum has been correlated with poor performance on tests of sustained attention, rapid problem solving, and mental arithmetric (Rao, Leo, Haughton, et al., 1989) and on two tests of verbal fluency, a frontal task (Nocentini et al., 2001). In a more recent study, Edwards et al. (2001) found that corpus callosum atrophy correlated with overall performance on a battery encompassing a wide variety of neuropsychological measures. Therefore, the secondary effects of MS lesions on the integrity of fiber pathways distant from the actual lesion site cannot be underestimated. This limits the value, in part, of focal lesion quantification and cognitive correlates in MS, as well as in other disorders produced by disruption of fiber pathways. TREATMENT OPTIONS FOR COGNITIVE IMPAIRMENT IN MULTIPLE SCLEROSIS There are two approaches to the treatment of cognitive impairment in MS. The first is to prevent cognitive impairment or, once it occurs, to prevent its progression. The

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second is to ameliorate or reverse preexisiting cognitive impairment with agents that enhance cognitive performance. To prevent progression in relapsing-remitting MS, regular injections of interferon β -1b (Betaseron), interferon β -1a (Avonex), and glatiramer acetate (Copaxone) have proven to be highly effective. The administration of such agents should help to slow the development of cognitive impairment or, once it occurs, slow its progression, in patients with relapsing-remitting MS. A recent study suggests that over a 1-year interval, treatment with interferon β -1b actually improved complex attention, concentration, visual learning, and recall, while other neuropsychological dimensions were unchanged. In the untreated MS control group, complex attention, verbal fluency, visual learning, and recall deteriorated, while other dimensions of cognition did not progress (Barak and Achiron, 2002). This finding suggests that prevention of disease progression not only prevents cognitive deterioration, but might also allow compensatory changes that result in cognitive enhancement. Furthermore, Rudick et al. (1999) found that interferon β -1a reduced brain atrophy by 55% during the 2nd year of a 2-year trial in patients with relapsing-remitting MS. In another study, treatment of patients with relapsingremitting MS with glatiramer acetate had no effect on sustained attention, perceptual processing, verbal and visuospatial memory, and semantic retrieval after 1 and 2 years of treatment. By contrast, in the control untreated group, mean neuropsychological test scores actually rose at 1 and 2 years. The lack of measurable decline in the control group limits the possibility of detecting a therapeutic effect of this agent at least in this patient sample (Weinstein et al., 1999). The study of the effects of these immunomodulatory therapies on cognitive dysfunction in MS clearly deserves more attention. A variety of other medications have been used to enhance cognitive function in patients with MS. Geisler et al. (1996) studied the effects of amantidine and pemoline on cognitive function in MS. Both medications are used widely to treat the fatigue that frequently occurs in patients with MS. Unfortunately, neither one improved cognitive performance over a 6-week treatment period. However, another group found that amantadine signficiantly reduced fatigue whereas pemoline did not (Krupp et al., 1995). In a more recent study, amantidine was found to improve reaction time (Sailer et al., 2000). This is not unexpected because amantidine enhances dopaminemediated motor function. Other aspects of cognitive function were not examined in this limited study. Donepezil HCl (Aricept), an acetylcholinesterase inhibitor widely used in Alzheimer’s disease to improve cognition, improved attention, memory, and executive function in a short open trial in patients with MS tested at 4 and 12 weeks (Greene et al., 2000). Another group found similar results (Christodoulou et al., 2006). Additional study should be devoted to the use of cognition-enhancing

medications in MS, especially as new agents become available. For example, modafinil, a novel nonamphetamine stimulant, has cognition-enhancing qualities that might be beneficial to patients with MS (Baranski and Pigeau, 1997). Disappointingly, modafinil did not improve fatigue in patients with MS in a large randomized doubleblind trial (Stankoff et al., 2005). Stimulated by the observation that males are less likely to develop MS than females, a trial of testosterone supplementation was undertaken in male patients with MS. Daily testosterone treatment for 12 months improved cognitive performance and slowed brain atrophy in a small pilot study (Sicotte, et al., 2007). Clearly, much more attention needs to be devoted to interventions designed to slow or reverse the cognitive deficits associated with MS. SUMMARY Cognitive impairment is much more frequently associated with MS than is widely appreciated. The cognitive domains most often affected are working memory and executive function, recall, attention, and cognitive processing speed. Although neuropsychological deficits can appear early in the course of the illness, they tend to be more common as the disease progresses. Increasing lesion load as measured on MRI scans is correlated with many measures of neuropsychological dysfunction. Cognitive processes that rely most heavily on distributed and interconnected neural networks, such as executive function, episodic memory, and encoding, may be most vulnerable to the accumulated effects of widely distributed white matter lesions. Deficits in processing speed may be the signature of the central demyelinating lesions that are the hallmark of MS. Corpus callosum atrophy, which probably reflects accumulated axonal damage and regression, is another MRI measure frequently associated with impaired cognitive processing. Primary prevention of disease progression with immunomodulatory therapy may prevent neuropsychological deterioration, at least in patients with the relapsing-remitting form of illness. Cognition-enhancing agents such as acetylcholinesterase inhibitors hold the promise of ameliorating some of the deficits incurred by patients with MS.

ACKNOWLEDGMENTS The author would like to thank Dr. Terry Goldberg for his advice and guidance in the preparation of this work, and Jamie Rosenthal for assistance in updating and revising this chapter.

REFERENCES Amato, M.P., Ponziani, G., Pracucci, G., Bracco, L., Siracusa, G., and Amaducci, L. (1995) Cognitive impairment in early-onset multiple sclerosis: pattern, predictors, and impact on everyday life in a 4 year follow-up. Arch. Neurol. 52:168–172.

61: COGNITIVE IMPAIRMENT IN DEMYELINATING DISEASE Amato, M.P., Ponziani, G., Siracusa, G., and Sorbi, S. (2001) Cognitive dysfunction in early-onset multiple sclerosis: a reappraisal after 10 years. Arch. Neurol. 58:1602–1606. Archibald, C.J., and Fisk, J.D. (2000) Information processing efficiency in patients with multiple sclerosis. J. Clin. Exp. Neuropsychol. 22:686–701. Arnett, P.A., Rao, S.M., Bernardin, L., Grafman, J., Yetkin, F.Z., and Lobeck, L. (1994) Relationship between frontal lobe lesions and Wisconsin Card Sorting Test performance in patients with multiple sclerosis. Neurology 44:420–425. Barak, Y., and Achiron, A. (2002) Effect of interferon-beta-1b on cognitive functions in multiple sclerosis. Eur. Neurol. 47:11–14. Baranski, J.V., and Pigeau, R.A. (1997) Self-monitoring cognitive performance during sleep deprivation: effects of modafinil, d-amphetamine and placebo. J. Sleep Res. 6:84–91. Baum, H.M., and Rothschild, B.B. (1981) The incidence and prevalence of reported multiple sclerosis. Ann. Neurol. 10:420–428. Beatty, W.W., Goodkin, D.E., Monson, N., and Beatty, P.A. (1989) Cognitive disturbances in patients with relapsing-remitting multiple sclerosis. Arch. Neurol. 46:1113–1119. Beatty, W.W., and Monson, N. (1996) Problems solving by patients with multiple sclerosis: comparison of performance on the Wisconsin and California Card Sorting Tests. J. Int. Neuropsychol. Soc. 2:134–140. Berman, K.F., Ostrem, J.L., Randolph, C., Gold, J., Goldberg, T.E., Coppola, R., Carson, R.E., Hersovitch, P., and Weinberger, D.R. (1995) Physiological activation of a cortical network during performance of the Wisconsin Card Sorting Test: a positron emission tomography study. Neuropsychologia 33:1027–1046. Buchanan, R.J., Wang, S., Huang, C., and Graber, D. (2001) Profiles of nursing home residents with multiple sclerosis using the minimum data set. Multiple Sclerosis 7:189–200. Camp, S.J., Stevenson, V.L., Thomapson, A.J., Miller, D.H., Borras, C., Auriacombe, S., Brochet, B., Falautano, M., Fillipi, M., HérisséDulo, L., Montalban, X., Parrcira, E., Polman, C.H., De Sa, J., and Langdon, D.W. (1999) Cognitive function in primary progressive and transitional progressive multiple sclerosis. A controlled study with MRI correlates. Brain 122:1341–1348. Charil, A., Zijdenbos, A.P., Taylor, J., Boelman, C., Worsley, K.J., Evans, A.C., and Dagher, A. (2003) Statistical mapping analysis of lesion location and neurological disability in multiple sclerosis: application to 452 data sets. NeuroImage 19:532–544. Christodoulou, C., Melville, P., Scherl, W.F., MacAllister, W.S., Elkins, L.E., and Krupp, L.B. (2006) Effects of donepezil on memory and cognition in multiple sclerosis. J. Neurol. Sci. 245:127–136. Cogan, D.G. (1979) Visuospatial dysgnosia. Am. J. Ophthalmol. 88: 361–368. Comi, G., Filippi, M., Martinelli, V., Campi, A., Rodegher, M., Alberoni, M., Siribian, G., and Canal, N. (1995) Brain MRI correlates of cognitive impairment in primary and secondary progressive multiple sclerosis. J. Neurol. Sci. 132:222–227. Davie, C.A., Hawkins, C.P., Barker, G.J., Brennan, A., Tofts, P.S., Miller, D.H., and McDonald, W.I. (1994) Serial proton magnetic resonance spectroscopy in acute multiple sclerosis lesions. Brain 117:49–58. Dean, G. (1967) Annual incidence, prevalence and mortality of multiple sclerosis in white South African-born and in white immigrants to South Africa. Br. Med. J. 2:724–730. Demaree, H.A., DeLuca, J., Gaudino, E.A., and Diamond, B.J. (1999) Speed of information processing as a key deficit in multiple sclerosis: implications for rehabilitation. J. Neurol. Neurosurg. Psychiatry 67:661–663. DeSousa, E.A., Albert, R.H., and Kalman, B. (2002) Cognitive impairments in multiple sclerosis: a review. Am. J. Alzheimers Dis. Other Demen. 17:23–29. D’Esposito, M., and Postle, B.R. (1999) The dependence of span and delayed-response performance on prefrontal cortex. Neuropsychologia 37:1303–1315.

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Ebers, G.C., Bulman, D.E., Sadovnick, A.D., Paty, D.W., Warren, S., Hader, W., Murray, T.J., Seland, T.P., Duquette, P., Grey, T., et al. (1986) A population-based study of multiple sclerosis in twins. N. Engl. J. Med. 315:1638–1642. Edwards, S.G.M., Liu, C., and Blumhardt, L.D. (2001) Cognitive correlates of supratentorial atrophy on MRI in multiple sclerosis. Acta Neurol. Scand. 104:214–223. Feinstein, A., Kartsounis, L.D., Miller, D.H., Youl, B.D., and Ron, M.A. (1992) Clinically isolated lesions of the type seen in multiple sclerosis: a cognitive, psychiatric, and MRI follow up study. J. Neurol. Neurosurg. Psychiatry 55:869–879. Feinstein, A., Ron, M., and Thompson, A. (1993) A serial study of psychometric and magnetic resonance imaging changes in multiple sclerosis. Brain 116:569–602. Feinstein, A., Youl, B., and Ron, M. (1992) Acute optic neuritis: a cognitive and magnetic resonance imaging study. Brain 115:1403–1415. Filley, C.M., Heaton, R.K., Nelson, L.M., Burks, J.S., and Franklin, G.M. (1989) A comparison of dementia in Alzheimer’s disease and multiple sclerosis. Arch. Neurol. 46:157–161. Fisher, J.S. (1988) Using the Wechsler memory scale-revised to detect and characterize memory deficits in multiple sclerosis. Clin. Neuropsychol. 2:149–172. Foong, J., Rozewicz, L., Quaghebeur, G., Davie, C.A., Kartsounis, L.D., Thompson, A.J., Miller, D.H., and Ron, M.A. (1997) Executive function in multiple sclerosis. The role of frontal lobe pathology. Brain 120:15–26. Franklin, G.M., Heaton, R.K., Nelson, L.M., Filley, C.M., and Seibert, C. (1988) Correlation of neuropsychological and MRI findings in chronic/progressive multiple sclerosis. Neurology 38:1826–1829. Fulton, J.C., Grossman, R.I., Udupa, J., Mannon, L.J., Grossman, M., Wei, L., Polansky, M., and Kolson, D.L. (1999) MR lesion load and cognitive function in patients with relapsing-remitting multiple sclerosis. Am. J. Neuroradiol. 20:1951–1955. Gaudino, E.A., Chiaravalloti, N.D., DeLuca, J., and Diamond, B.J. (2001) A comparison of memory performance in relapsingremitting, primary progressive and secondary progressive multiple sclerosis. Neuropsychiatr. Neuropsychol. Behav. Neurol. 14:32–44. Geisler, M.W., Sliwinski, M., Coyle, P.K., Masur, D.M., Doscher, C., and Krupp, L.B. (1996) The effects of amantadine and pemoline on cognitive functioning in multiple sclerosis. Arch. Neurol. 53:185–188. Gilbert, J.J., and Sadler, M. (1983) Unsuspected multiple sclerosis. Arch. Neurol. 40:533–536. Grafman, J., Rao, S., Bernardin, L., and Leo, G.J. (1991) Automatic memory processes in patients with multiple sclerosis. Arch. Neurol. 48:1072–1075. Greene, Y.M., Tariot, P.N., Wishart, H., Cox, C., Holt, C.J., Schwid, S., and Noviasky, J. (2000) A 12-week open trial of donepezil hydrochloride in patients with multiple sclerosis and associated cognitive impairments. J. Clin. Psychopharmacol. 20:350–356. Gregory, S.G., Schmidt, S., Seth, P., Oksenberg, J.R., Hart, J., Prokop, A., Caillier, S.J., Ban, M., Goris, A., Barcellos, L.F., Lincoln, R., McCauley, J.L., Sawcer, S.J., Compston, D.A., Dubois, B., Hauser, S.L., Garcia-Blanco, M.A., Pericak-Vance, M.A., Haines, J.L., for the Multiple Sclerosis Genetics Group. (2007) Interleukin 7 receptor alpha chain (IL7R) shows allelic and functional association with multiple sclerosis. Nat. Genet. 39:1083–1091. Harris, J.O., Frnak, J.A., Patronas, N., Mcarlin, D.E., and McFarland, H.F. (1991) Serial gadolinium-enhanced magnetic resonance imaging scans in patients with early, relapsing-remitting multiple sclerosis: implications for clinical trials and natural history. Ann. Neurol. 29:548–555. Heaton, R.K., Nelson, L.M., Thompson, D.S., Burks, J.S., and Franklin, G.M. (1985) Neuropsychological findings in relapsingremitting and chronic progressive MS. J. Consult. Clin. Psychol. 53:103–110. Hohol, M.J., Guttman, C.R.G., Orav, J., Mackin, G.A., Kikinis, R., Khoury, S.J., Lolesz, F.A., and Weiner, H.L. (1997) Serial neuro-

1008

DEMENTIA

psychological assessment and magnetic resonance imaging analysis in multiple sclerosis. Arch. Neurol. 54:1018–1025. Isaac, C., Li, D.K.B., Genton, M., Jardine, C., Grochowski, E., Palmer, M., Kastrukoff, L.F., Oger, J., and Paty, D.W. (1988) Multiple sclerosis: a serial study using MRI in relapsing patients. Neurology 38:1511–1515. Jambor, K.L. (1969) Cognitive functioning in multiple sclerosis. Br. J. Psychiatry 115:765–775. Kail, R. (1998) Speed of information processing in patients with multiple sclerosis. J. Clin. Exp. Neuropsychol. 20:98–106. Krupp, L.B., Coyle, P.K., Doscher, C., Miller, A., Cross, A.H., Jandorf, L., Halper, J., Johnson, B., Morgante, L., and Grimson, R (1995) Fatigue therapy in multiple sclerosis: results of a double-blind, randomized, parallel trial of amantidine, pemoline, and placebo. Neurol. 45:1956–1961. Kurtzke, J.F. (2000) Epidemiology of multiple sclerosis. Does this really point toward an etiology? Neurol. Sci. 21:383–403. Kurtzke, J.F., and Hyllested, K. (1985) Multiple sclerosis in the Faroe Islands II. Clinical update, transmission, and the nature of MS. Neurology 36:307–328. LaRocca, N.G. (1984) Psychosocial factors in multiple sclerosis and the role of stress. Ann. N.Y. Acad. Sci. 436:435–442. Lazeron, R.H.C., Boringa, J.B., Schouten, M., Uitedehaag, B.M.J., Bergers, E. Lindeboom, J. Eikelenboom, M.J., Scheltens, P.H., Barkhof, F. and Polman, C.H. (2005) Brain atrophy and lesion load as explaining parameters for cognitive impairment in multiple sclerosis. Multiple Sclerosis 11:524–531. Lundmark, F., Duvefelt, K., Iacobaeus, E., Kockum, I., Wallstrom, E., Khademi, M., Oturai, A., Ryder, L.P., Saarela, J., Harbo, H.F., Celius, E.G., Salter, H., Ollson, T. and Hillert, J. (2007) Variations in interleukin 7 receptor alpha chain (IL7R) influences risk of multiple sclerosis. Nat. Genet. 39: 1108–1113. Mesulam, M.M. (1981) A cortical network for directed attention and unilateral neglect. Ann. Neurol. 10:309–325. Minden, S.L., Moes, E.J., Orav, J., Kaplan, E., and Reich, P. (1990) Memory impairment in multiple sclerosis. J. Clin. Exp. Neuropsychol. 12:566–586. Morgen, J., Sammer, G., Courtney, S.M., Wolters, T., Melchior, H., Blecker, C.R., Oschmann, P., Kaps, M., and Vaitl, D. (2006) Evidence for a direct association between cortical atrophy and cognitive impairment in relapsing-remitting MS. NeuroImage 30:891–898. Nocentini, U., Rossini, P.M., Carlesimo, G.A., Graceffa, A., Grasso, M.G., Lupoi, D., Oliveri, M., Orlacchio, A., Pozzilli, C., Rizzato, B., and Caltagirone, C. (2001) Patterns of cognitive impairment in secondary progressive stable phase of multiple sclerosis: correlations with MRI findings. Eur. Neurol. 45:11–18. Olmos-Lau, N., Ginsberg, M.D., and Geller, J.B. (1977) Aphasia in multiple sclerosis. Neurology 27:623–626. Peyser, J.M., Rao, S.M., LaRocca, N.G., and Kaplan, E. (1990) Guidelines for neuropsychological research in multiple sclerosis. Arch. Neurol. 47:94–97. Rabins, P.V., Brooks, B.F., O’Donnell, P., Pearlson, G.D., Moberg, P., Jubelt, B., Coyle, P., Dalos, N., and Folstein, M.F. (1986) Structural brain correlates of emotional disorder in multiple sclerosis. Brain 109:585–597. Rao, S.M., Bernardin, L., Leo, G.J., Ellington, L., Ryan, S.B., and Burg, L.S. (1989) Cerebral disconnection in multiple sclerosis. Arch. Neurol. 46:918–920. Rao, S.M., Glatt, S., Hammeke, T.A., McQuillen, M.P., Khatri, B.O., Rhodes, A.M., and Pollard, S. (1985) Chronic/progressive multiple sclerosis: relationship between cerebral ventricular size and neuropsychological impairment. Arch. Neurol. 42:678–682. Rao, S.M., Grafman, J., DiGiulio, D., Mittenberg, W., Bernardin, L., Leo, G.J., Luchetta, T., and Unverzagt, F. (1993) Memory dysfunction in multiple sclerosis: its relation to working memory, semantic encoding, and implicit learning. Neuropsychology 7: 364–374.

Rao, S.M., and Hammeke, T.A. (1984) Hypothesis testing in patients with chronic progressive multiple sclerosis. Brain Cogn. 3:94–104. Rao, S.M., Hammeke, T.A., McQuillen, M.P., Khatri, B.O. and Lloyd, D. (1984) Memory disturbance in chronic progressive multiple sclerosis. Arch. Neurol. 41:625–631. Rao, S.M., Leo, G.J., Bernardin, L., and Unverzagt, F. (1991) Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology 41:685–691. Rao, S.M., Leo, G.J., Ellington, L., Nauertz, T., Bernardin, L., and Unverzagt, F. (1991) Cognitive dysfunction in multiple sclerosis. II. Impact on employment and social functioning. Neurology 41: 692–696. Rao, S.M., Leo, G.J., Haughton, V.M., St. Aubin-Faubert, P., and Bernardin, L. (1989) Correlation of magnetic resonance imaging with neuropsychological testing in multiple sclerosis. Neurology 39:161–166. Rao, S.M., Leo, G.J., and St. Aubin-Faubert, P. (1989) On the nature of memory disturbance in multiple sclerosis. J. Clin. Exp. Neuropsychol. 11:699–712. Rendell, P.G., Jensen, and Henry, J.D. (2007) Prospective memory in multiple sclerosis. J. Internat. Neurophys. Soc. 13:410–416. Ron, M.A., Callanan, M.M., and Warrington, E.K. (1991) Cognitive abnormalities in multiple sclerosis: a psychometric and MRI study. Psychol. Med. 21:59–68. Rovaris, M., Filippi, M., Falautano, M., Minicucci, L., Rocca, M. A., Martinelli, V., and Comi, G. (1998) Relations between MR abnormalities and patterns of cognitive impairment in multiple sclerosis. Neurology 50:1601–1608. Rovaris, M., Filippi, M., Minicucci, L., Iannucci, G., Santuccio, G., Possa, F., and Comi, G. (2000) Cortical/subcortical disease burden and cognitive impairment in patients with multiple sclerosis. Am. J. Neuroradiol. 21:402–408. Rudick, R.A., Fisher, E., Lee, J.-C., Simon, J., Jacobs, L., and the Multiple Sclerosis Collaborative Research Group. (1999) Use of the brain parenchymal fraction to measure whole brain atrophy in relapsing-remitting MS. Neurol. 53:1698–1704. Sadovnick, A.D. Armstrong, H., Rice, G.P.A., Bulman, D., Hashimoto, L., Paty. D.W., Hashimoto, S.A., Warren, S., Hader, W., Murray, T.J., et al. (1993) A population-based study of multiple sclerosis in twins: update. Ann. Neurol. 33:281–285. Sadovnick, A.D., Baird, P.A., and Ward, R.H. (1988) Multiple sclerosis: updated risks for relatives. Am. J. Med. Genet. 29:533– 541. Sadovnick, A.D., Ebers, G.C., Dyment, D.A., and Risch, N.J. (1996) Evidence for a genetic basis for multiple sclerosis. The Canadian Collaborative Study Group. Lancet 347:1728–1730. Sailer, M., Heinze, H.-J., Schoenfeld, M.A., Hauser, U., and Smid, H.G.O.M. (2000) Amantadine influences cognitive processing in patients with multiple sclerosis. Pharmacopsychiatry 33:28–37. Schulz, D., Kopp, B., Kunkel, A., and Faiss, J.H. (2006) Cognition in the early stage of multiple sclerosis. J. Neurol. 253:1002– 1010. Sicotte, N.L., Glesser, B.S., Tandon, V., Klutch, R., Steiner, B., Drain, A.E., Shattuck, D.W., Hull, L., Wang, H.-J., Elashoff, R.M., Swerdloff, R.S., and Voskuhl, R.R. (2007) Testosterone treatment in multiple sclerosis. Arch. Neurol. 64:683–688. Sperling, R.A., Guttman, C.R., Hohol, M.J., Warfield, S.K., Jakab, M., Parente, M. Diamond, E.L., Daffner, K.R., Olek, M.J., Orav, E.J., Kikinis, R., Jolesz, F.A., and Weiner, H.L. (2001) Regional magnetic resonance imaging lesion burden and cognitive function in multiple sclerosis. Arch. Neurol. 58:115–121. Stankoff, B., Waubant, E., Confavreux, C., Edan, G., Debouverie, M., Rumbach, L., Moreau, T., Pelletier, J., Lubetzki, C., Clanet, M., and the French Modafinil Study Group. (2005) Modafinial for fatigue in MS: a randomized placebo-controlled double-blind study. Neurol. 64:1139–1143.

61: COGNITIVE IMPAIRMENT IN DEMYELINATING DISEASE Swirsky-Sacchetti, T., Mitchell, D.R., Seward, J., Gonzales, C., Lublin, F., Knobler, R., and Field, H.L. (1992) Neuropsychological and structural brain lesions in multiple sclerosis: a regional analysis. Neurology 42:1291–1295. Thornton, A.E., and Raz, N. (1997) Memory impairment in multiple sclerosis: a quantitative review. Neuropsychology 11:357–366. Trojano, M., and Paolicelli, D. (2001) The differential diagnosis of multiple sclerosis: classification and clinical features of relapsing and progressive neurological syndromes. Neurol. Sci. 22:S98–S102.

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Weinshenker, B.G. (1996) Epidemiology of multiple sclerosis. Neurol. Clin. 14:291–308. Weinstein, A., Schwid, S.I., Schiffer, R.B., McDermott, M.P., Giang, D.W., and Goodman, A.D. (1999) Neuropsychologic status in multiple sclerosis after treatment with glatiramer. Arch. Neurol. 56:319–324. Wishart, H., and Sharpe, D. (1997) Neuropsychological aspects of multiple sclerosis: a quantitative review. J. Clin. Exp. Neuropsychol. 19:810–824.

62 Dementia with Lewy Bodies DAVID J. BURN, ELAINE K. PERRY, JOHN T. O’BRIEN, NEIL ARCHIBALD, ELIZABETA B. MUKAETOVA-LADINSKA, JOAQUIM CEREJEIRA, DANIEL COLLERTON, EVELYN JAROS, ROBERT PERRY, MARGARET A. PIGGOTT, CHRIS M. MORRIS, ANDREW MCLAREN, CLIVE G. BALLARD,

Dementia with Lewy bodies (DLB) is a primary neurodegenerative dementia sharing several clinical and pathological characteristics with Parkinson’s disease (PD). The first case reports of DLB appeared in 1961, when Okazaki published a report of two patients, aged 69 and 70 years, presenting with dementia who died shortly afterward with severe extrapyramidal rigidity. Autopsy showed Lewy body (LB) pathology in the cerebral cortex (Okazaki et al., 1961). The advent of anti-ubiquitin immunocytochemical staining methods allowed the frequency and distribution of cortical LBs to be defined more easily, and the clinico-pathological boundaries of DLB began to emerge. More recently, α-synuclein antibodies have revealed even more extensive pathological changes in DLB and have demonstrated a neurobiological link with other synucleinopathies, PD, and multiple system atrophy (MSA). Between 15% and 20% of all cases of the elderly with dementia reaching autopsy have DLB, making it the second most common cause of degenerative dementia after Alzheimer’s disease (AD). Patients with DLB have a poorer quality of life and consume more resources than patients with AD (Boström et al., 2007a, 2007b) making the impact of this dementia syndrome even more striking. Exquisite, not infrequently fatal, sensitivity to neuroleptic drugs and encouraging trial results for the use of cholinesterase inhibitors mean that an accurate diagnosis of DLB is more than merely of academic interest. This chapter reviews the clinical features, diagnosis, and investigation of DLB, together with its neuropathology, neurochemistry, and genetics. Finally, the chapter considers the management of this progressive and disabling disorder. CLINICAL FEATURES AND NATURAL HISTORY Dementia with Lewy bodies is characterized by a variable combination of fluctuating cognition, neuropsychiatric 1010

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disturbance, and parkinsonism. Autonomic dysfunction and sleep disorders may also be prominent features, the former contributing to falls. Fluctuating Cognition Variation in cognitive performance is commonly observed in many late-onset dementias. It is frustrating to carers and has a major impact upon the patient’s ability to perform everyday activities reliably. Fluctuating cognition (FC) may present in several ways, depending upon the severity and diurnal pattern. Carers of patients with DLB describe spontaneous, periodic, and transient episodes of fluctuation, affecting functional abilities (Bradshaw et al., 2004) quite different from the more prolonged, situation-dependent variability seen in AD. Fluctuation occurs in 80% or more of people suffering from DLB, 30%–60% of individuals with vascular dementia (VaD), and 20% of people with AD. Evaluation of fluctuating cognition can be difficult and requires detailed questioning of patients and carers. Several clinical scales have been validated to quantify FC in DLB such as The Clinician Assessment of Fluctuation Scale (Walker et al., 2000a) and The Mayo Fluctuations Composite Scale (Ferman et al., 2004). In the latter study, informant endorsement of three of four questions (Does the patient experience excessive daytime sleepiness? Do they sleep more than 2 hours during the day? Do their words occasionally come out jumbled? Are there times when they stare into space for long periods?) had a positive predictive value of 83% for a diagnosis of DLB versus AD. Computer-based testing systems offer an alternative method of assessing FC with measures of attention demonstrating marked variation in the DLB population (Walker et al., 2000b). This variation can be detected over very short periods of time (on a second-to-second basis), suggesting that FC arises from dysregulation of continuously active arousal systems. Fluctuating cognition may also be an important determinant of poor

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prognosis, according to a retrospective analysis of 243 autopsy-confirmed cases of DLB and Parkinson’s disease with dementia (PDD) (Jellinger et al., 2007). Psychiatric Symptoms At least 80% of patients with DLB experience some neuropsychiatric symptoms, such as visual hallucinations, auditory hallucinations, delusions, delusional misidentification, and depression (Campbell et al., 2001). Visual hallucinations are the most common symptom, with a mean frequency of 50% (range, 13%–80%) in prospective studies, compared with 20%–30% in patients with AD from a meta-analysis of standardized reports. The person with DLB typically sees adults, children, or animals of normal size, sometimes with accompanying auditory hallucinations, which are far less frequent in AD. Visual hallucinations are not only more frequent in patients with DLB compared to AD but also more persistent. Hallucinations can be quantified to monitor change using the North East Visual Hallucinations Inventory (Mosimann et al., 2008). Extrapyramidal Features Estimates of the frequency of parkinsonian features at presentation in DLB range between 10% and 78%, whereas 40%–100% of patients display extrapyramidal signs (EPS) at some stage of the illness (McKeith, Perry, et al., 1992; Gnanalingham et al., 1997; Louis et al., 1997; Del Ser et al., 2000). Differences between series are most likely to represent ascertainment bias and the variable definition of clinical phenomenology. There is no consensus on whether the parkinsonism associated with DLB differs phenotypically from that associated with PD. Interpretation of the literature is hindered by a dearth of prospective clinico-pathological data. In a review of 75 case reports of DLB published between 1961 and 1991, Lennox (1992) determined the frequency of parkinsonism to be 90%, with 50% of the patients having three or more of the following symptoms: rigidity, tremor, bradykinesia, gait disorder, and flexed posture. Reduced rest tremor, greater symmetry of signs, myoclonic jerks, and a reduced response to levodopa have all been reported in DLB, although these have not been confirmed by others (Gnanalingham et al., 1997; Louis et al., 1997). In a large international multicenter study, parkinsonism was reported in 92.4% of 120 patients with DLB (Del Ser et al., 2000). There was a small but statistically significant difference between male and female patients on the five-item Unified Parkinson’s Disease Rating Scale (UPDRS) subscore (Ballard et al., 1997), with male patients being more severely affected. Older patients with DLB tended to have higher UPDRS scores, but the difference was not statistically significant. Pa-

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tients with more severe cognitive impairment (defined as a Mini-Mental State Examination [MMSE] score, 18) had significantly more severe EPS than those with less cognitive decline using the full UPDRS part III, but when this relationship was reexamined using the fiveitem UPDRS subscore, no difference was found between the groups. This apparent disparity may be interpreted as meaning that patients with more severe dementia have difficulty understanding and executing some of the instructions. Aarsland and colleagues (2001) described more severe action tremor, rigidity, bradykinesia, difficulty arising from a chair, greater facial impassivity, and gait disturbance in 98 patients with DLB compared with 130 patients with PD. Overall, 68% of the patients with DLB had EPS. Burn and colleagues (2003) describe postural instability and gait difficulty as being significantly more common in DLB compared to PD. Significant parkinsonism was more frequent in patients with DLB (71%) than in those with AD (7%) or VaD (10%) (Ballard, O’Brien, Swann, et al., 2000). The degree of cognitive impairment had no influence on the occurrence of EPS. Patients with DLB with established parkinsonism had an annual increase in severity, assessed using the UPDRS, of 9%, a figure comparable with that seen in PD. In common with PD, progression was more rapid (49% increase in the motor UPDRS score in 1 year) in patients with DLB with early parkinsonism. A postural instability-gait difficulty (PIGD) motor phenotype is overrepresented in DLB (and dementia associated with PD) compared with PD patients with no dementia. In one cross-sectional study, 69% of 26 patients with DLB were classified as PIGD phenotype, compared with only 30% of 38 patients with PD (Burn et al., 2003). The involvement of brain-stem cholinergic nuclei, notably the pedunculopontine nucleus, may be responsible for the expression of this phenotype. A supranuclear gaze paresis has been described in DLB (Fearnley et al., 1991; de Bruin et al., 1992). In combination with cognitive impairment and falls, this may cause diagnostic confusion with progressive supranuclear palsy. It may sometimes be difficult to ascertain, however, whether the patient with DLB has a true gaze paresis, oculomotor apraxia, or is simply inattentive to the examiner’s command. Sleep disorders Rapid-eye-movement (REM) sleep behavior disorder (RBD) is a common sleep disturbance in neurodegenerative disorders (Schenck et al., 1993; Sforza et al., 1997; Olson et al., 2000). It is characterized by loss of normal skeletal muscle atonia during REM sleep with resultant motor activity and “acting out of dreams.” Patients demonstrate a variety of movements ranging from verbal outbursts to pugilistic movements and even more dramatic

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motor activity. Injuries to patients and bed partners are common. REM sleep behavior disorder can present in isolation, that is, not in association with concurrent medical diagnoses, or in the context of medical, and often neurological, disorders. The former is termed “idiopathic” and the latter “secondary.” There is a marked sex difference in reported cases of RBD. Over 85% of patients in several large case series were male (Olson et al., 2000; Schenck and Mahowald, 2002), and this male preponderance is also seen in the “secondary” neurodegenerative cases (Iranzo et al., 2006; Boeve, Silber, Parisi, et al., 2003). The reason for this difference is not clear but may reflect a less “aggressive” clinical phenotype in females, leading to fewer medical consultations (Schenck and Mahowald, 2002). The diagnosis is made on clinical grounds and careful questioning of bed partners is therefore vital. Clinical suspicion may then be backed up by video polysomnography (PSG), utilizing audiovisual footage to confirm the physical features of RBD in addition to electromyography, electro-oculography, electroencephalogram (EEG), and oxygen saturation recordings during sleep. The diagnostic criteria are summarized in Table 62.1. Estimates from prospective studies in specialist centers place the frequency of RBD at 50%–80% in DLB (Boeve et al., 2004). Prospective population-based studies are needed to assess the true incidence and prevalence of RBD in neurodegenerative disorders in general, and DLB, PD, and MSA in particular. Several studies (Wetter et al., 2000; Boeve et al., 2001; Gagnon et al., 2002; Iranzo et al., 2005) have demonstrated that RBD is common in conditions associated with the intraneuronal deposition of α-synuclein (synucleinopathies such

62.1 The Recently Published Second Edition of the International Classification of Sleep Disorders Requires the Following for the Clinical Diagnosis of RBD

TABLE

Presence of RSWA on PSG At least one of the following: sleep-related, injurious, potentially injurious, or disruptive behaviors by history (that is, dream enactment behavior) and/or abnormal REM sleep behavior documented during polysomnographic monitoring. Absence of EEG epileptiform activity during REM sleep unless RBD can be clearly distinguished from any concurrent REM sleep-related seizure disorder. The sleep disorder is not better explained by another sleep disorder, medical or neurological disorder, mental disorder, medication use, or substance use disorder. Source: Taken from: American Academy of Sleep Medicine, 2005. EEG: electroencephalogram; PSG: polysomongram; REM: rapid eye movement; RSWA: REM sleep without atonia.

as PD, MSA, and DLB), and this is in contrast to the nonsynucleinopathies such as Progressive Supranuclear Palsy (PSP) and AD (Boeve et al., 2001). This finding has been backed up by several studies in AD (Gagnon et al., 2006) that found clinically evident RBD to be uncommon in patients with AD. In their autopsy study of 15 patients with RBD and a neurodegenerative disorder (Boeve, Silber, and Ferman, 2003), 10 (66.7%) had a diagnosis of RBD predating the development of dementia or parkinsonism by a median of 10 years (range 2 to 29). The neuropathologic diagnoses were LB disease in 12 and MSA in 3. Iranzo et al. (2006) retrospectively assessed 44 consecutive patients diagnosed with idiopathic RBD for the subsequent development of neurodegenerative disorders. Twenty (45%) patients developed a neurological disorder, predominantly PD (9) and DLB (6) and mild cognitive impairment with prominent visuospatial dysfunction (4), after a mean of over 11 years from reported onset of RBD symptoms (range 5–23). The suggestion that RBD may provide an early clue to the development of “synucleinopathy” in patients who are otherwise asymptomatic may allow insight into the early pathophysiology of these conditions as well as provide better diagnostic accuracy and the potential for earlier treatment when this becomes available. For these reasons, the presence of RBD has now been included in the new consensus criteria for the diagnosis to DLB as a “suggestive” feature (McKeith et al., 2005). Autonomic Features Falls are an important feature of DLB, with over one third of patients suffering more than 20 per year (Ballard et al., 1999). One of the most common causes of falls is abnormal cardiovascular autonomic function, which may predate the onset of parkinsonism and dementia by several years or develop with other clinical features (Kaufmann et al., 2004). Orthostatic hypotension and carotid sinus hypersensitivity are common in DLB (Ballard et al., 1998) and associated with burden of hyperintense lesions on magnetic resonance imaging (MRI) brain scanning (Ballard, O’Brien, Barber, et al., 2000). Patients with DLB demonstrate impairment of sympathetic and parasympathetic function on autonomic testing (Allan et al., 2007), and these changes are associated with reduced cardiac uptake of 123I-meta-iodobenzylguanidine (MIBG), a marker of postganglionic myocardial sympathetic innervation (Oka et al., 2007). Yoshita and colleagues (2006) examined cardiac MIBG scans in 37 patients with DLB and 42 with AD compared to controls. Uptake was significantly reduced in the DLB group compared to AD and control groups. In contrast, no significant differences were found between patients with AD and controls. This suggests a possible use for cardiac MIBG scanning in differentiating DLB from AD, although further work is required. Other autonomic symptoms include urinary

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incontinence, constipation, erectile dysfunction, and eating and swallowing difficulties (Horimoto et al., 2003, Thaisetthawatkul et al., 2004). CLINICAL DIAGNOSIS Consensus clinical diagnostic criteria were first published in 1996 and were updated in 1999 and, most recently, in 2005 (Table 62.2). The criteria characterize the central feature of DLB as a progressive disorder in which episodic memory impairment is often minimal in the early stages, whereas attentional, executive, and visuospatial deficits may be disproportionately prominent (McKeith et al., 1996). The presence of two or more of three core clinical features (fluctuating attention and alertness, recurrent visual hallucinations, parkinsonism), together with the variable presence of suggestive or supportive features, indicates probable DLB. Suggestive features now included in the criteria are RBD, severe neuroleptic sensitivity, and abnormal dopamine (DA) uptake on single photon emission computed tomography (SPECT) or positron emission tomography (PET) imaging. These have a similar diagnostic weighting as the core features but require further validation before being considered sufficient for a diagnosis of probable DLB without the presence of core features. Features considered as supportive of a diagnosis of DLB (listed in Table 62.2) and discussed in this chapter lack specificity because they may also occur in a variety of other disorders (McKeith et al., 1999). When DLB presents as a primary dementia syndrome, the key differential diagnoses are AD, VaD, delirium secondary to systemic or pharmacological toxicity, prion disease, or other neurodegenerative syndromes. In these circumstances, consensus guidelines for the clinical diagnosis of DLB have been shown to have prospective diagnostic accuracy at least as good as those for AD. Their discriminating value is greatest at an early stage, suggesting that DLB should be considered in any new dementia presentation (McKeith, Ballard, et al., 2000). Inability of patients with DLB who are moderately impaired to copy pentagons accurately has been reported with a sensitivity of 88% and a specificity of 59% compared with AD, suggesting this as a useful screening test (Ala et al., 2001). As described above, EPS are strong diagnostic indicators because parkinsonism is uncommon in early AD or VaD (Ballard, O’Brien, Swann, et al., 2000). The DLB Consortium recommended that if a patient has had motor symptoms of PD for more than 1 year prior to the diagnosis of dementia, then a diagnosis of PDD is most appropriate. If mental symptoms occur within 12 months of onset of motor disability, then a primary diagnosis of DLB may be more appropriate. This approach is entirely consistent with guidelines for the clinical diagnosis of PD (Gelb et al., 1999) and, more recently, PDD (Emre et al., 2007). It should be

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remembered, however, that these different patterns of clinical presentation share similar underlying neurodegenerative pathologies, including abnormal α-synuclein deposition and formation of Lewy neurites/bodies. LB parkinsonism and DLB may thus represent a spectrum of LB syndromes. Attempts to draw absolute boundaries between them, such as the 12-month rule, are only arbitrary conventions designed to help in clinical practice because there is strong evidence that the clinical end points of DLB and PDD are similar (Mosimann et al., 2004; Mosimann et al., 2006) INVESTIGATIONS Clinical examination and investigations should establish the presence of cognitive, psychiatric, and neurological signs and exclude hematological, biochemical, or pharmacological causes. The EEG is usually abnormal in DLB, with a greater degree of background slowing compared with AD, but this is too nonspecific to be of use in an individual case. Transient slow wave (delta) activity is seen in the temporal lobes of 50% of DLB cases (18% AD) and is associated with a clinical history of loss of consciousness (Briel et al., 1999). No clinically useful laboratory tests have yet been established for the diagnosis of DLB based on plasma or cerebrospinal fluid (CSF) analysis, although CSF Ab42 levels were decreased and tau levels were normal in 11 patients with clinically diagnosed DLB, compatible with the neuropathological findings of high-plaque but low-tangle counts in the DLB brain (Kanemaru et al., 2000). Neuroimaging Structural imaging changes in dementia with lewy bodies Relatively few studies to date have investigated computed tomography (CT) or MRI changes in DLB. An initial report of eight patients diagnosed as having AD during life but with LB pathology at postmortem found more pronounced frontal lobe atrophy on CT than in pure AD cases (Förstl et al., 1993). Larger studies using MRI have failed to replicate this finding. Instead, the main structural imaging change emerging as characteristic of DLB is relative preservation of the hippocampus and medial temporal lobe compared to the reduction seen in AD (Barber et al., 2000; Whitwell et al., 2007), possibly helping to explain the preservation of mnemonic function in such cases. Although hippocampal volume is slightly reduced, by about 15% compared to controls, the reduction is considerably less than that seen in AD, with some 40% of cases having no evidence of atrophy. Patients with DLB show relatively little cortical gray matter loss when compared to patients

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62.2 Revised Criteria for the Clinical Diagnosis of Dementia with Lewy Bodies (DLB)

1. Central feature (essential for a diagnosis of possible or probable DLB) Dementia defined as progressive cognitive decline of sufficient magnitude to interfere with normal social or occupational function. Prominent or persistent memory impairment may not necessarily occur in the early stages but is usually evident with progression. Deficits on tests of attention, executive function, and visuospatial ability may be especially prominent. 2. Core features (two core features are sufficient for a diagnosis of probable DLB, one for possible DLB) Fluctuating cognition with pronounced variations in attention and alertness Recurrent visual hallucinations that are typically well formed and detailed Spontaneous features of parkinsonism 3. Suggestive features (If one or more of these is present in the presence of one or more core features, a diagnosis of probable DLB can be made. In the absence of any core features, one or more suggestive features is sufficient for possible DLB. Probable DLB should not be diagnosed on the basis of suggestive features alone.) REM sleep behavior disorder Severe neuroleptic sensitivity Low dopamine transporter uptake in basal ganglia demonstrated by SPECT or PET imaging 4. Supportive features (commonly present but not proven to have diagnostic specificity) Repeated falls and syncope Transient, unexplained loss of consciousness Severe autonomic dysfunction, for example, orthostatic hypotension, urinary incontinence Hallucinations in other modalities Systematized delusions Depression Relative preservation of medial temporal lobe structures on CT/MRI scan Generalized low uptake on SPECT/PET perfusion scan with reduced occipital activity Abnormal (low uptake) MIBG myocardial scintigraphy Prominent slow wave activity on EEG with temporal lobe transient sharp waves 5. A diagnosis of DLB is less likely In the presence of cerebrovascular disease evident as focal neurologic signs or on brain imaging In the presence of any other physical illness or brain disorder sufficient to account in part or in total for the clinical picture If parkinsonism only appears for the first time at a stage of severe dementia 6. Temporal sequence of symptoms DLB should be diagnosed when dementia occurs before or concurrently with parkinsonism (if it is present). The term Parkinson’s disease with dementia (PDD) should be used to describe dementia that occurs in the context of well-established Parkinson’s disease. In a practice setting, the term that is most appropriate to the clinical situation should be used, and generic terms such as LB disease are often helpful. In research studies in which distinction needs to be made between DLB and PDD, the existing 1-year rule between the onset of dementia and parkinsonism DLB continues to be recommended. Adoption of other time periods will simply confound data pooling or comparison between studies. In other research settings that may include clinicopathologic studies and clinical trials, both clinical phenotypes may be considered collectively under categories such as LB disease or a-synucleinopathy. From: McKeith et al., 2005. REM: rapid-eye-movement; SPECT: single photon emission computed tomography; PET: positron emission tomography; CT: computed tomography; MRI: magnetic resonance imaging; MIBG: 123I-meta-iodobenzylguanidine; EEG: electroencephalogram.

with AD (Whitwell et al., 2007). Rather, when 72 patients with DLB were compared to similar numbers with AD and age-matched controls, the most striking findings on volumetric analysis were focal atrophy of the midbrain, hypothalamus, and substantia inominata in DLB compared to a more generalized atrophy of the temporo-parietal cortex and medial temporal lobes in AD. It has been suggested that temporal lobe atrophy on MRI might be a marker of concurrent tangle pathology in DLB, although larger studies are needed to examine this issue further.

More general measures of atrophy have also been examined in DLB, with patients having a degree of ventricular enlargement similar to that seen in AD (Barber et al., 2000). The rate of volume loss over time using serial MRI has been studied, but no consistent pattern has emerged. O’Brien and colleagues (2001) found similar rates in DLB (1.4%) and AD (2.0%), though Whitwell et al. (2007) found “pure” DLB cases to have similar rates of progression to controls, with increased rates only seen in those with mixed DLB and AD pathology. White matter lesions (WML) are increased in AD and

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may contribute, together with degenerative pathology, to the severity of cognitive impairment. A similar increase has been described in DLB cases (Barber et al., 1999), although the effects on cognitive function have not yet been determined, though rates of WML progression over time are similar in DLB to AD (Burton et al., 2006). Functional imaging changes in dementia with Lewy bodies There have been several studies investigating PET and SPECT changes in DLB. Positron emission tomography studies of glucose metabolism and SPECT investigations using blood flow markers such as Tc-HMPAO have demonstrated many similarities to the patterns seen in AD (Donnemiller et al., 1997; Defebvre et al., 1999; Ishii et al., 1999; Lobotesis et al., 2001). Pronounced biparietal hypoperfusion is seen together with variable deficits in frontal and temporal lobes, which again are usually symmetric. Biparietal hypoperfusion in DLB is even more extensive than in patients with AD matched for age and dementia severity, particularly in Brodmann area 7, an area that mediates important aspects of visuospatial function. Similar patterns of hypoperfusion in the parieto-occipital cortex are seen in patients with DLB and PDD and differ from those in AD (Firbank et al., 2003). Pronounced hypoperfusion in this area may underpin the pronounced visuospatial impairments characteristic of DLB. Occipital hypometabolism on PET and hypoperfusion on PET and SPECT have been strongly associated with DLB and appear to affect primary visual cortex as well as visual association areas (Brodmann areas 17–19). In contrast, temporal lobe perfusion is relatively preserved, paralleling the findings from structural imaging studies described above. Minoshima and colleagues (2001) reported a sensitivity of 90% and a specificity of 80% for occipital hypometabolism in separating DLB from AD, although only 11 DLB cases were studied. In a larger SPECT study, occipital hypoperfusion had reasonable specificity (86%) in distinguishing DLB from AD and controls, although sensitivity was lower at 64% (Lobotesis et al., 2001). Labeling of muscarinic acetylcholine receptors using 123I-iodo-quinuclidinyl-benzilate (QNB) has shown an increase in 123I-QNB binding in the right occipital lobe in DLB and right and left occipital lobes in PDD using SPECT imaging (Colloby et al., 2006). It is uncertain whether such occipital changes are related to the occurrence of visual hallucinations. Studies using PET and SPECT have also investigated changes in the dopaminergic and cholinergic systems. Donnemiller and colleagues (1997) found significant reductions in DLB but not AD in striatal binding of β carbomethoxy-iodophenyl-tropane (CIT), a ligand with high affinity for the dopamine transporter (DAT), using

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PET. One disadvantage of CIT is that imaging has to be delayed until 24 hours postinjection. A ligand with faster imaging kinetics, FP (fluoropropyl)-CIT, is now commercially available in many countries and demonstrates DAT reductions even in patients with early PD. The results of several trials have demonstrated the clinical utility of FP-CIT SPECT in the diagnosis of DLB (Z. Walker et al., 2002; O’Brien et al., 2004). A large, multicenter phase III trial of the technique has been completed (McKeith et al., 2007). Comparing DLB and nonDLB dementia (predominantly AD), abnormal scans had a sensitivity of 77.7% for detecting clinically probable DLB, with a specificity of 90.4% for excluding nonDLB dementia and an overall diagnostic accuracy of 85.7%. Evidence of abnormal DAT activity in the basal ganglia on FP-CIT SPECT scanning has now been incorporated into the Consensus Criteria for DLB as a suggestive feature. In addition, O’Brien et al. (2004) and Z. Walker et al. (2004) have shown that the pattern of abnormality on FP-CIT SPECT is different in PD and DLB, with more marked reduction of dopaminergic uptake in the caudate head in DLB and PDD compared to PD. In contrast, patients with PD demonstrate greater asymmetry of uptake in the posterior putamina. The lack of asymmetry on FP-CIT SPECT imaging in DLB may help to explain the symmetrical motor features often seen in DLB as well as the association between symmetrical parkinsonism and dementia. Reduced DA D2 receptor density in basal ganglia using 123I iodobenzamide has also been reported in DLB (Z. Walker et al., 1997). Neuropsychological Assessment Increased variability Dementia with Lewy bodies is characterized by increased variability in performance on cognitive tasks, within and between patients and when compared to age-matched controls and patients with AD (Ballard, O’Brien, Gray, et al., 2001; Ballard, O’Brien, Morris, et al., 2001; Collerton et al., 2005). This variability is particularly evident in executive and attentional tasks. Too few studies have compared DLB with PD or VaD to allow a clear pattern to emerge. This may partly reflect the more variable pathology of DLB, but it is also a feature of the fluctuations that characterize the disease process itself. The effects of these fluctuations are reflected not only in an increase in the variance of scores in DLB groups, but also in the conflicting findings reported on the same tasks.

Differences in performances on specific tasks In terms of group differences, patients with DLB always do worse than age-matched controls on neuropsycholog-

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ical tasks, with particularly poor performance on visual perceptual and learning tasks, visual semantic tasks, and praxis tasks. Simple global measures of performance (for example, the MMSE) are usually equivalent to those of patients with AD of comparable severity, perhaps reflecting the insensitivity of these measures to attentional impairments. Patients with DLB tend to perform better than patients with AD on verbal memory and orientation tasks. Performance on visual tasks, particularly recognition tasks, is consistently more impaired than in AD (for detailed reviews, see Simard et al., 2000; Lambon et al., 2001; Collerton et al., 2005). The pattern is reversed in comparisons with PD, with patients with DLB generally performing worse in all areas except visual and motor tasks. Effects of progression on the disease process Neuropsychological changes as DLB progresses are not well characterized, though differences from AD appear to be particularly pronounced in the early stages and lessen as the disease progresses. Rate of progression, as evidenced by change in global cognitive measures such as the MMSE or Cambridge Cognitive Examination (CAMCOG), is equivalent to or faster than that seen in AD and VaD, with a decline of 4–5 MMSE points per year (Simard et al., 2000; Ballard, O’Brien, Morris, et al., 2001; Johnson et al., 2005). Clinical utility of neuropsychological assessment Given that similar tasks have produced different results in different studies, and that effect sizes in comparison with patient groups are generally below 1, single test performances cannot be used in isolation to distinguish between DLB and other dementing illnesses. Patterns of performance on verbal and visuospatial tasks can be used to reliably classify prediagnosed groups of patients with DLB, AD, and VaD. Although the predictive value of test results in the general dementia population is not established, preliminary results are encouraging (Tiraboschi et al., 2006). At present, the major utility of the neuropsychological assessment of DLB is in defining the effects of this variable disease on the individual patient, to allow the development of evidence-based rehabilitative or compensatory strategies and to monitor progression in that patient. NEUROPATHOLOGY Described as the neuropathological hallmark of PD by Friedrich Lewy in 1912, Lewy bodies were first associated with dementia in 1961 by Okazaki et al. Lewy bodies are spherical, intracytoplasmic, eosinophilic, neuronal inclusions with a dense hyaline core and a clear halo.

On electron microscopy (EM), they are composed of a core of filamentous and granular material surrounded by radially oriented filaments 10–20 nm in diameter. Subcortical LBs are easily seen using conventional hematoxylin and eosin staining. The presence of LBs in pigmented brain stem nuclei, and in the substantia nigra (SN) in particular, coupled with neuronal loss and gliosis, constitute the characteristic pathological findings in the prototypic LB disease, PD. Cortical LBs lack the characteristic core and halo appearance of their brain-stem counterparts and were difficult to detect until the late 1980s, when anti-ubiquitin immunocytochemical staining methods allowed their frequency to be determined (Lennox and Lowe, 1997). Ubiquitin antibodies also identified Lewy neurites (LNs) in the hippocampal CA2/3 region of DLB, which were absent in AD. More recently, the presynaptic protein α-synuclein was shown to be a major component of cortical and subcortical LBs and neurites (Spillantini et al., 1997). α -synuclein antibodies label greater numbers of cortical and hippocampal CA2/3 LNs and intraneuronal inclusions than ubiquitin, including fine granular and diffuse deposits and LBs, indicating that accumulation of α -synuclein precedes its ubiquitination (Spillantini et al., 1998; Gómez-Tortosa, Newell, et al., 2000). α-Synuclein antibodies have also identified novel nonubiquitinated inclusions in hippocampal pyramidal cells of patients with DLB. Purified LBs contain full-length as well as partially truncated forms and high molecular aggregates of α -synuclein (Baba et al., 1998). Using EM, immunoreactivity to α-synuclein is associated with filaments 5– 10 nm wide and 50–700 nm long (Baba et al., 1998). α -synuclein is a widespread neuronal presynaptic protein found in the central nervous system, Schwann cells, cultured oligodendrocytes, platelets, and CSF. Monomeric α -synuclein exists in equilibrium between free and plasma membrane- or vesicle-bound states (McLean et al., 2000). One of α -synuclein protein’s crucial functions in vivo is the protection of the nerve terminals against injury via cooperation with cystein string protein (CSPα and soluble N-Ethylmaleimide-sensitive factor (NSF) (Bonini and Giasson, 2005). This may play a role in the prevention of neuronal neurodegeneration because α -synuclein abolishes the lethality and neurodegeneration caused by deletion of CSPα and maintains soluble NSF attachment receptor (SNARE) complex assembly (Chandra et al., 2005). Over-expression of α -synuclein in neuronal cell lines results in changes in membrane fluidity and changes cellular fatty acid uptake and metabolism (Sharon et al., 2003; Castagnet et al., 2005; Golovko et al., 2005), with the earliest defects being inhibition of endoplasmic reticulum-associated degeneration (Cooper et al., 2006). Its self-aggregation and filament formation is extensively modulated by environmental factors (Uversky, 2007).

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Prior to assembly into filaments, α -synuclein protein may undergo a transition from a random coil to a β -pleated sheet conformation (Serpell et al., 2000). In vitro studies show that α -synuclein is more likely to self-aggregate when it is overexpressed (Stefanova et al., 2002) or in the presence of some coadjuvant factors (for example, amyloid protein, metal ions, trifluorethanol, septons, heparin, agrin, oxidative stress, low pH, proteosomal inhibition, constituents of chromatin, etc.). The overexpression of α -synuclein also results in selective nigral DA neuronal loss, restricted to the embryogenesis (Wakamatsu et al., 2007). Post-translational modifications of α -synuclein (for example, phosphorylation, nitration, lipoxidation) also promote fibril formation (Fujiwara et al., 2002; Dalfó and Ferrer, 2008). Phosphorylation of this protein is present in 26% of the elderly human brains and is found in LBs, LNs, white matter axons, and dot-like structures similar to argyrophilic grains. Nitrated α -synuclein is found in cortical LBs and dystrophic neurites in SN and hippocampal neurons that show diffuse cytoplasmic staining (Gómez-Tortosa et al., 2002), suggesting that nitration may be a prerequisite for α -synuclein aggregation. Diffuse presence of nitrated α -synuclein has now been described in the frontal lobe in Pick’s disease in the absence of LB formation (Dalfó et al., 2006). The presence of a large number of other neuronal proteins within LBs may provide further clues to their formation. Cytoskeletal proteins, such as neurofilaments, and microtubules are thought to become trapped within the α -synuclein fibrillary aggregates. The presence of ubiquitin, a cofactor in the ubiquitin-proteasome system of intracellular proteolysis, and catalytic enzymes are considered part of a cell stress response to eliminate abnormal and damaged proteins from cells. Most recently, chaperone proteins, like parkin (a ubiquitinprotein ligase), torsin A, and heat shock proteins (for example, HSP70) known to participate in refolding misfolded proteins and/or directing proteins towards degradation have been also localized in brain stem and cortical LBs and neurites (McNaught and Jenner, 2001; Uryu et al., 2006; Leverenz et al., 2007). These findings, together with the evidence that in the SN of patients with PD, the ubiquitin-proteasome pathway is impaired, have been interpreted to indicate that altered protein handling leads to accumulation of damaged α -synuclein within LBs and to neuronal degeneration (McNaught and Jenner, 2001). In the hippocampus of patients with DLB and patients with PD, axon pathology involves not only α - but also β - and γ -synuclein (Galvin et al., 1999). Antibodies to β -synuclein reveal accumulations of vesicles in presynaptic mossy fiber terminals of the hippocampal hilus, and antibodies to γ -synuclein detect axonal spheroid-like structures in the dentate molecular layer. Animal and tissue culture studies suggest that β -synuclein may be

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neuroprotective. Thus, the formation of LBs and motor function deficits are significantly ameliorated in α - and β -synuclein bigenic mice compared to single α -synuclein transgenic mice (Hashimoto et al., 2001; Fan et al., 2006). In tissue culture, the overexpression of β -synuclein directly inhibits α -synuclein aggregation and protofibrillar formation of α -synuclein (Hashimoto et al., 2001; Uversky et al., 2002; Park and Lansbury, 2003). This has been further confirmed in vitro, with β -synuclein dimmers blocking the aggregation of α -synuclein into ringlike oligomers, and also disrupting the already formed α -synuclein aggregates (Tsigelny et al., 2007). In contrast, the overexpression of β -synuclein mutants (P123H and V70M) enhances lysosomal pathology (Wei et al., 2007), and this may play a role in stimulating neurodegeneration. Although γ -synuclein inhibits α -synuclein aggregation (Uversky et al., 2002), its role in neuroprotection is not well understood. Neuropathological Criteria for DLB High cortical senile plaque counts are found in the majority of patients with DLB, but their composition differs from those found in pure AD. When present, the dystrophic neurites decorating plaques in DLB are α synuclein immunoreactive and seldom tau immunoreactive. In 80%–90% of DLB cases, there is no evidence of significant neocortical tau pathology, paired helical filaments, or neurofibrillary tangles (Harrington et al., 1994). Whether or not DLB is considered to be a variant of AD depends upon the pathological definition of AD being used. When using the 1996 DLB criteria (which required only the presence of LB for the pathologic diagnosis) and the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) criteria for AD (a definition of AD that is heavily dependent upon plaque density), 77% of the cases would fulfill both diagnoses. By contrast, 80%–90% of cases would fail to fulfill definitions of AD requiring supra-threshold numbers of neocortical neurofibrillary tangles (E.K. Perry, Smith, et al., 1990). These findings, alongside with clinical studies showing clinical diagnostic accuracy for DLB to be higher in patients with low-burden AD pathology (Del Ser et al., 2001; Lopez et al., 2002; Merdes et al., 2003), have resulted in a recent revision of the neuropathological criteria for diagnosing DLB (McKeith et al., 2005). This combines the National Institute on Aging (NIA)/Reagan criteria and the modified Consensus DLB guidelines, based on semiquantitative assessment of α -synuclein pathology. Thus, these revised criteria acknowledge that a pathological diagnosis of both diseases should be made on a probabilistic basis, taking into account the extent and the contribution of the different pathological findings (Table 62.3). Neuropathological assessment of clinical cases of DLB should evaluate Lewy and AD-type pathology to pro-

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DEMENTIA TABLE 62.3 Assessment of Likelihood of LB and Alzheimer Pathologies to Be Associated with DLB Clinical Syndrome

Lewy Body Pathology

Alzheimer-Type Pathology NIA-Reagan Low (BST 0-II)

NIA-Reagan Intermediate (BST III-IV)

NIA-Reagan High (BST V-VI)

Brain-stem predominant

Low

Low

Low

Limbic (transitional)

High

Intermediate

Low

Diffuse neocortical

High

High

Intermediate

From: Mckeith et al., 2005. DLB: dementia with Lewy bodies; BST: Braak stage; NIA: National Institute on Aging.

vide a degree of likelihood (high, intermediate, or low) that α -synuclein pathology is underlying the clinical syndrome. A diagnosis of DLB becomes less likely as ADrelated pathology, staged by NIA/Reagan criteria, increases. According to the new revised criteria, DLB and pure AD will be pathologically distinct in the majority of cases. The validity of the newly proposed criteria still needs to be tested in clinico-neuropathological studies. Clinico-pathological Correlations Cognitive and neuropsychiatric correlations The relationship between cognitive impairment and neuropathological features characteristic for DLB is not clear. In DLB and PDD, severity of cognitive impairment is positively correlated with the density of cortical LBs in frontal and temporal lobes and with the density of LNs in the hippocampal CA2 field, though not with LB density in anterior cingulate cortex (Gómez-Tortosa et al., 1999; Hurtig et al., 2000). However, the contribution of AD pathology (when analyzed according to Braak stages) seems, in some instances, to prevail over the LB staging (Welsman et al., 2007). Fluctuating cognition, in contrast, shows no correlation with LB density in either neocortical, paralimbic, or nigral areas (Gómez-Tortosa et al., 1999). The nucleus basalis of Meynert shows more profound neuron loss in DLB than in AD, as well as extensive LB/α -synuclein pathology, and is therefore likely to contribute significantly to the cognitive decline in DLB (Lippa et al., 1999). Noncognitive changes in DLB appear to be independent of the presence of LBs. No significant regional differences in LB densities have been reported between cases with and without cognitive fluctuation, hallucinations, delusions, recurrent falls (Gómez-Tortosa, Irizarry et al., 2000), and delusional misidentification (Förstl et al., 1994). Neuropathological studies in patients with DLB and well-formed visual hallucinations (VH) have demonstrated high LB densities in the amygdala and parahippocampus, with early hallucinations relating to higher densities in parahippocampal and inferior temporal cortices (Harding et al., 2002). A higher burden of LBs in

the amygdala and in frontal, temporal, and parietal neocortex is also present in patients with PD with VH (Papapetropoulos et al., 2006). However, these findings have not been replicated in a recent DLB study (Yamamoto et al., 2007). Depression, frequently reported in DLB, appears not to be associated with cortical and subcortical LBs (Samuels et al., 2004). However, lateonset major depression appears to be related to the frequent presence of LB pathology (Sweet et al., 2004), whereas presence of LBs in the amygdala in AD increases significantly the risk of developing major depression (odds ratio [OR] = 8.56) (Lopez et al., 2006). Neurological correlations The density of LB in the SN does not differ significantly between cases starting with parkinsonism and those evolving initially with dementia (Gómez-Tortosa et al., 1999). Mild or moderate neuron loss in SN has been found to be restricted to DLB cases without parkinsonism, whereas DLB cases with parkinsonism have shown neuron loss in the ventrolateral tier of SN of similar severity to that seen in PD. Brain-stem LBs seem to underlie the presence of essential tremor in some patients with DLB and PD (Louis et al., 2006). Other features Although the increased falls reported in DLB may be multifactorial, it is likely that more widespread brain-stem involvement of nondopaminergic nuclei is a contributing factor. Degeneration of the predominantly cholinergic pedunculopontine nucleus and minimal involvement of the SN and locus coeruleus (LC), harboring LBs and LNs but no overt neuronal loss, is a likely candidate because neuronal loss in this structure has been associated with postural instability (Zweig et al., 1989). Pathologic studies in RBD have suggested dysfunction of one or several brain-stem neuronal pathways. Candidate sites include the SN, LC-subcoeruleus complex, pedunculopontine, dorsal vagus and dorsal raphé nucleus, and the gigantocellular reticular nucleus (Uchiyama et al., 1995; Turner et al., 2000). These nuclei utilize a

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number of neurotransmitters including dopminergic, noradrenergic, cholinergic, and serotoninergic connections, all of which may play a role in the development of RBD. Eisensehr and colleagues (2003) demonstrated abnormalities in DAT SPECT in patients with subclinical and clinically evident RBD, with increasing severity of abnormality in those patients with overt RBD. These changes are similar to those seen in idiopathic PD. Unfortunately, the numbers of cases in which pathological information is available is small, and more work is necessary to elucidate these complex interactions further. The pathological correlates for autonomic dysfunction in DLB are likely to be similar to those in cases with pure autonomic failure, where pathology includes neuronal loss, LB, and LN in autonomic nuclei of the brain stem, intermediolateral cell columns of the spinal cord, and sympathetic and parasympathetic ganglia. Indeed, a recent pathological study suggests that the common presence of α -synuclein aggregates in peripheral autonomic neurons and adrenal glands may represent an early presymptomatic phase in the development of LB disorders (Minguez-Castellanos et al., 2007; Fumimura et al., 2007). Carotid sinus hypersensitivity, consisting of falls and dizziness, is highly prevalent in DLB and other neurodegenerative disorders, including AD and PD. The neuropathological correlate of this is hyperphosphorylated tau in tyrosine hydroxylase-containing neurons (catecholaminergic neurons), in the absence of neuronal loss (Miller et al., 2007). NEUROCHEMISTRY Dementia with Lewy bodies has more severe and widespread cholinergic deficits than AD, but postsynaptic receptor coupling is intact; and though DA loss is not as great in DLB as in PD, the “compensatory” changes in the DA system that occur in PD are absent in DLB.

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Clinical differences between AD and DLB/PDD reflect distinct neurochemical profiles underlying specific symptoms and having treatment implications such as response to cholinesterase inhibitors and levodopa, and neuroleptic sensitivity. The Dopaminergic System Presynaptic dopaminergic measures Reduced SN neuron density and low DA concentration in the caudate nucleus were early reports in DLB (E.K. Perry, Marshall, Perry, et al., 1990; R.H. Perry, Irving, et al., 1990; Marshall et al., 1994). Subsequently, DA concentration and DATs have been shown to be reduced in posterior striatum even in DLB cases with no EPS (Piggott et al., 1999; Piggott et al., in press) (Fig. 62.1). Dopamine loss in DLB is less selectively focused on the posterior putamen than in PD, and the caudate is more affected (Piggott et al., 1999). This reflects the pattern of SN neuron loss, with relative sparing of the medial SN in PD. Substantia nigra and DAT loss in DLB are also more symmetric between hemispheres than in PD (Ransmayr et al., 2001; O’Brien et al., 2004; Z. Walker et al., 2004). Dopamine transporter loss affecting caudate and putamen rostrocaudally in DLB has been shown in vivo (Z. Walker et al., 2004; Colloby et al., 2005), and imaging DAT by SPECT and PET can assist differentiation of DLB from AD (Hu et al., 2000; O’Brien et al., 2004; Z. Walker et al., 2007), and such an abnormal scan is now part of the Consensus Criteria as a suggestive feature (McKeith et al., 2007). Reduced nigrostriatal DA is the most likely substrate for the parkinsonism of DLB. It may be that moderate reduction in dopaminergic input results in more severe EPS in DLB than it would in PD because there is a lack of compensatory changes such as increased turn-

62.1 Dopamine transporter density (fmol 125I PE 2I/mg tissue) in striatum from cases of PD without dementia, PDD, DLB with EPS later, DLB without EPS, AD, and normal elderly control tissue. Source: Piggot et al., in press.

FIGURE

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over of DA and up-regulation of D2 receptors, which occur in PD (Piggott et al., 1999). Nigrothalamic DA is also likely to be reduced in DLB. The thalamus receives DA via nigro-caudate collaterals, which show depleted DAT immunoreactivity in the 1-methyl-4-phenyl-1,2,3,6tetrahydropyridine (MPTP)-treated monkey model of PD (Freeman et al., 2001). Other neurotransmitter system changes probably contribute to the movement disorder of DLB, as evidenced by the axial predominance and relative levodopa resistance (Bonelli et al., 2004).

et al., 2007). Reduced temporal cortical D2 density correlated with cognitive decline but not with hallucinations or delusions, suggesting neuroleptic use would have a deleterious effect on cognition. Dopamine D1 and D3 receptors in the striatum were not altered in DLB in a postmortem study mainly involving cases with little or no parkinsonism (Piggott et al., 1999). The Cholinergic System

Postsynaptic dopaminergic measures

Presynaptic changes

Striatal DA D2 receptor density is up-regulated in PD without dementia by > 70% (Piggott et al., 1999) and is doubled in thalamus (Piggott, Ballard, Dickinson, et al., 2007). In DLB there is a slight reduction (↓17%) in D2 density in the striatum (Piggott et al., 1999), with D2 density lowest in cases that had severe neuroleptic sensitivity and slightly higher in cases tolerant of neuroleptics (Piggott et al., 1998); it may be that cases with lower D2 density are more at risk of sudden catastrophic receptor blockade by the D2 antagonist action of neuroleptics. Failure to up-regulate D2 receptors in DLB could be due to intrinsic striatal pathology, with β -amyloid (Aβ) and synuclein pathology reported (Duda et al., 2002), or perhaps to deficits in other systems, for example in thalamo-striatal afferents or the cholinergic system. In the thalamus there is lower D2 binding in all regions in DLB without EPS; in DLB with EPS there is limited, slight but significant up-regulation in two nuclei only; whereas in PDD cases moderate, significant up-regulation occurs in the motor ventrointermedius nucleus alone (Piggott, Ballard, Dickinson, et al., 2007). Thalamic D2 receptor binding in DLB and PDD does not vary with cognitive decline or visual hallucinations but is significantly higher with increased EPS (Piggott, Ballard, Dickinson, et al., 2007). In DLB and PDD there is higher thalamic D2 binding in cases with FC, particularly in the reticular nucleus (Piggott, Ballard, Dickinson, et al., 2007). Inhibitory D2 receptors located on reticular nucleus γ -aminobutyric acid (GABA)ergic neurons (also inhibitory) will therefore help maintain thalamic and cortical activity, thus enabling fluctuations. In an environment of reduced transmitter concentration, higher D2 receptors can amplify small transmitter changes leading to variations in consciousness and attention. Similarly, nicotinic receptors were higher in some thalamic nuclei in cases with FC (Pimlott et al., 2006) (see below), possibly suggesting that combined cholinergic and dopaminergic therapy is required to treat FC in DLB. In temporal cortex in DLB and PDD, D2 receptors are significantly reduced (> 40%) and are also reduced in DLB cases with concomitant Alzheimer pathology, but are not reduced in pure AD (Piggott, Ballard, Rowan,

Presynaptic cholinergic cortical activities are generally more reduced than in AD, and there are also losses in the striatum and in the projection from the pedunculopontine nucleus to the thalamus. As in AD, there is consistent involvement of the nucleus basalis of Meynert, but with LB pathology and more extensive cell loss (Tiraboschi et al., 2000). In the cortex, choline acetyltransferase (ChAT) and acetyl cholinesterase (AChE) (the synthesizing and degrading enzymes of acetylcholine) losses determined postmortem exceed those in AD (in which they are particularly pronounced in the hippocampus) and are apparent early in the disease course (E.K. Perry, Kerwin, et al., 1990; E.K. Perry, Marshall, Kerwin, et al., 1990; Tiraboschi et al., 2002). Cholinergic losses are correlated with cognitive decline in DLB (E.K. Perry, Marshall, Perry, et al., 1990; Samuel et al., 1997; Tiraboschi et al., 2002), and in PD (E.K. Perry et al., 1985; Mattila et al., 2001; Bohnen et al., 2006). Choline acetyltransferase deficits are greater in some visual cortical areas in DLB cases with visual hallucinations compared to those without (E.K. Perry, Kerwin, et al., 1990; Ballard, Piggott, et al., 2000). Neocortical binding to nicotinic acetylcholine receptors (nAChRs) containing α4 and β 2 subunits (α4* and β2*) is reduced in DLB and AD (E.K. Perry, Smith, et al., 1990; Gotti et al., 2006), but unlike AD, in DLB there is an apparent correlation between this nAChR deficit and cortical ChAT reduction (Reid et al., 2000). Somewhat surprisingly, nAChR binding is relatively preserved in the temporal cortex (and in thalamus) in cases of DLB with FC (Ballard, Court, et al., 2002; Pimlott et al., 2006). Because patients with FC are able to be more alert some of the time, the neurotransmitter systems must be capable of reaching the higher level of awareness. When cholinergic losses are severe, a higher density of nicotinic receptors may enable small transmitter fluctuations to lead to variations in consciousness and attention. Whether cortical α7* receptors are reduced generally in DLB is equivocal (Reid et al., 2000; Gotti et al., 2006), but it is most likely to occur in DLB cases with hallucinations (Court et al., 2001). In the striatum nAChRs are more reduced in DLB and PD than in AD, notably α6*, α4*, β2*, and β3* sub-

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types (Gotti et al., 2006). Reduced nAChR binding in striatum (partly on dopaminergic terminals) is as severe in DLB as in PD (E.K. Perry et al., 1995; Gotti et al., 2006), perhaps indicating that loss of these receptors occur at an early stage of nigrostriatal degeneration (E.K. Perry et al., 1995). In contrast, α4*β 2* nAChRs were not generally reduced in the thalamus in DLB (although there were reductions in PD), significant deficits only being observed in cases without FC (Pimlott et al., 2006). Reduced α7 receptor binding has been noted in the thalamic reticular nucleus in DLB (and in AD), a region innervated by cholinergic neurons from the basal forebrain (Court et al., 1999). Loss of nAChRs in DLB is likely to reflect reduced cholinergic innervation (cortex and thalamus), dopaminergic innervation (striatum), and also attenuation of pre- and postsynaptic receptors on glutamatergic, GABAergic, and serotonergic neurons. Muscarinic receptor changes Postsynaptically, there is less neuronal damage in DLB than in AD (Tiraboschi et al., 2000; O’Brien et al., 2001). Type 1 cortical muscarinic receptors (M1), unchanged or slightly reduced in severe AD and with defective coupling, have been reported to be up-regulated in temporal and parietal cortex in DLB (E.K. Perry, Smith, et al., 1990; Ballard, Piggott, Johnson, et al., 2000) and higher in frontal cortex in PDD and DLB compared to AD (Warren et al., 2008). M1 up-regulation in temporal cortex in DLB is associated with delusions (Ballard, Piggott, Johnson, et al., 2000). Coupling to G protein– second-messenger systems is preserved in DLB compared to AD in temporal cortex (E.K. Perry et al., 1998) and in frontal cortex (Warren et al., 2008). In contrast, immunohistochemical M1 expression is reduced in selected subfields of hippocampus (Shiozaki et al., 2001). Unlike in cortex, striatal M1 receptor binding is reduced, in parallel with D2 receptors, in DLB (M1 and D2 are distributed mainly on the same population of striatal projection neurons) (Piggott et al., 2003). M2 receptor binding was higher in cingulate cortex compared to controls, and higher M2 and M4 cingulate binding was associated with visual hallucinations (Teaktong et al., 2005). M4 receptors are raised in cingulate in DLB with FC (Teaktong et al., 2005), and in the insular cortex with the symptom of delusions, whereas in thalamus M4 receptors are reduced in DLB (Warren et al., 2007). Cholinesterase inhibitor therapy may be particularly successful in DLB for a constellation of reasons, including up-regulated, efficiently coupled cortical M1 receptors, severely reduced acetylcholine, little or no cortical atrophy or tangle burden, the potential for higher function to be stabilized in patients with FC, and low M1 receptors in striatum avoiding worsening EPS.

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Serotonin LB pathology and neuron loss have been reported in the raphé nucleus in DLB (Langlais et al., 1993), but not always (Benarroch et al., 2005), and reduced serotonin (5-HT) has been reported in striatum and cortex in DLB (Langlais et al., 1993; E.K. Perry et al., 1993; Ohara et al., 1998). Serotonin transporter binding is reduced (70%) in temporal and parietal cortex in DLB, and 5-HT2A receptors are reduced by 50% in putamen in PD (Piggott et al., 2000), with 5-HT2A receptors also reduced in temporal cortex in DLB and PDD (Cheng et al., 1991). Depression is a frequent symptom in PD and DLB, but a link between serotonin loss and depression remains to be clarified. There is no evidence that selective serotonin reuptake inhibitors are effective in depression in PD (Ghazi-Noori et al., 2003), and patients with untreated PD with depression showed no differences in CSF serotonin metabolites compared to patients without depression (Kuhn et al., 1996). Patients with DLB with a history of major depression actually had relatively higher serotonin transporter binding in parietal cortex than cases without (Ballard, Johnson, et al., 2002). There is however an increase in the numbers of 5-HT1A receptors in temporal cortex in DLB and PDD with depression (Sharp et al., in preparation), and in PD 5-HT1A receptors are increased in frontal and temporal cortex compared to controls (although any relationship to depression was not assessed in this study) (Chen et al., 1998). Treatment of depression in DLB may be more efficacious with a 5-HT1A antagonist. Greater preservation of serotonergic function may be related to behavioral and psychological symptoms in DLB. Patients with visual hallucinations show a relative preservation of 5HT markers and also have markedly reduced cholinergic parameters (Cheng et al., 1991; E.K. Perry, Marshall, Kerwin, et al., 1990; E.K. Perry et al., 1993). Glutamate Excitatory amino acid transmission occurs between several components of the basal ganglia circuit, which are likely to be affected in DLB, and excitotoxic mechanisms are implicated in the progress of neurodegenerative diseases. In PD there is increased excitatory output from the subthalamic nucleus, and glutamate antagonists have been used therapeutically. However, investigations of glutamate markers have been few, with no change in glutamate transporter protein in cortex in two DLB cases (H.L. Scott et al., 2002), no change in N-methyl-D-aspartate (NMDA) receptor immunoreactivity in entorhinal cortex and hippocampus (Thorns et al., 1997), and no reduction in glutamate in CSF (Molina et al., 2005). Glutamate receptor (GluR)2/3 α -amino-3-hydroxy-5-methyl-4-isoxasolepropionic

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acid (AMPA) receptor immunoreactivity was decreased in entorhinal cortex and hippocampus (Thorns et al., 1997), and group I metabotropic GluRs (mGluRs) were reduced in DLB (Albasanz et al., 2005), but these reductions were in cases with Alzheimer pathology. Further studies are needed to determine the extent of GLuR changes in DLB. GABA Although anxiety and insomnia are common complaints in DLB, and GABAergic systems are likely affected, there are few published reports of GABAergic changes. Selective dendritic derangement of GABAergic medium spiny neurons in the caudate have been reported and suggested to be linked to disrupted executive function (Zaja-Milatovic et al., 2005; Zaja-Milatovic et al., 2006). However, there was no change in benzodiazepine binding (GABA-A receptor) in the striatum in DLB (Suzuki et al., 2002), and no difference in GABA CSF concentration between controls and DLB (Molina et al., 2005). Noradrenaline Degeneration of the LC has been reported in PD and suggested to be linked to symptoms of mood disorder and subtle cognitive change (Cash et al., 1987), and this loss is more extensive in PDD (Cash et al., 1987; Zweig et al., 1993) and DLB (Leverenz et al., 2001; Szot et al. 2006). Locus coeruleus neuron loss correlates with cognitive decline, and there was evidence of compensation in the remaining LC neurons (Szot et al., 2006). α2 adrenergic receptor density was increased slightly in DLB in frontal cortex (Leverenz et al., 2001). In DLB and AD, there was reduced α1D and α2C adrenergic receptor messenger ribonucleic acid (mRNA) in hippocampus (Szot et al., 2006). Noradrenaline system changes in limbic areas may contribute to depression and to behavioral symptoms such as aggression and pacing, in cortex to cognitive decline, and in basal ganglia to movement disorder; but in the main, these relationships are still to be investigated. GENETICS Owing to the similarities between the clinical and pathological manifestations of DLB with AD and PD, it is not surprising that the search for genes that are associated with AD and PD has been used to identify genetic associations with DLB. One report of presumed autosomal dominant DLB (though not according to consensus criteria) in a 67-year-old woman who developed parkinsonism and then dementia, together with her two sons, may indicate a strong genetic basis (Wakabayashi et al., 1998). The relatively late onset of DLB and a

poor family history may be one reason why so few DLB families have been identified to date. Alzheimer’s Disease Genes in Dementia with Lewy Bodies Because of the association of the e4 allele of the apolipoprotein ε4 (ApoE4) gene on chromosome 19 and AD, and the presence of Aβ in DLB, several groups have reported genotyping studies. In DLB, the e4 allele frequency is elevated in a manner analogous to that found in AD. In PD, no association is observed with ApoE4. There are, however, subtle differences in the ApoE4 allele frequencies between AD and DLB, with a higher e2 allele frequency and a reduced frequency of the e4/4 genotype in DLB. Differences in the ApoE4 frequencies may account for some of the differences between the two diseases in terms of clinical presentation and pathology, but it is unlikely that one single genetic determinant accounts for the differences between DLB and AD. Apolipoprotein ε4 is associated with both senile plaques (SPs) and neurofibrillary tangles (NFTs), and a biochemical effect of the ApoE4 genotype in AD has been proposed (Strittmatter et al., 1993). However, DLB appears not to show a dose-dependant correlation of SP or NFT counts with ApoE4 allele dose, and given the markedly reduced NFT counts seen in DLB compared with AD, this may suggest that ApoE4 does not play a major role in NFT formation. Recent work indicates potentially four other major loci for AD alone, with regions on chromosomes 4, 6, 12, and 20 being of interest. A recent series of wholegenome scans identified loci on chromosomes 1, 5, 6, 9, 10, 12, 19, 21, and X that appear to associate with AD. One locus on chromosome 12 has been suggested to be due to the α2-macroglobulin gene. In DLB, our studies have not shown an association with this locus. Others have, however, suggested that the chromosome 12 locus involved in AD is actually in the immediate pericentromeric region of chromosome 12 and may associate with the low-density lipoprotein receptor-like protein or the transcription factor LBP-1c (Taylor et al., 2001). Several studies have eliminated the low-density receptor-like protein in AD and also in DLB. The strongest association with the chromosome 12 locus may be in late-onset dementia families with pathological evidence of DLB rather than AD (W.K. Scott et al., 2000). The butyrylcholinesterase gene K variant (BCHE K) is also a risk factor for AD in conjunction with ApoE4, increasing the risk of AD 18-fold compared to the ApoE4 allele alone. Current studies do not, however, indicate a role for BCHE in specifying the risk of DLB. Variation at BCHE may have a bearing on the suggestion that patients with DLB are more likely to respond to cholinergic therapy than patients with AD (see next page). Patients with DLB who are homozygous for the K allele

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are significantly better at performing an attentional task than wild-type or heterozygous individuals. Cholinesterase inhibitors are, however, ineffective in BCHE-K homozygotes, probably because these individuals are at ceiling performance, though wild-type and heterozygous individuals benefit from this treatment since the inhibition of butyrylcholinesterase (and acetylcholinesterase) brings acetylcholine levels to those of BCHE-K homozygotes. Screening at the BCHE locus for mutations with reduced activity could therefore be used to identify individuals who are likely to have a good response to cholinergic therapy. No associations have been found with DLB with polymorphisms in the genes for presenilin 1, presenilin 2, and α -1 antichymotrypsin. These genes are therefore unlikely to have a major influence on the pathogenesis of DLB. Parkinson’s Disease Genes in Dementia with Lewy Bodies Much of the genetics of PD has focused on a candidate gene approach in disease association studies, perhaps because of the assumption that the majority of PD is sporadic. Mutations in the cytochrome P450 gene CYP2D6 (debrisoquine 4-hydroxylase) and related enzymes have been extensively studied because of the suggestion that PD may be due to an environmental toxin interacting with a specific gene. Elevated frequencies of the common CYP2D6 mutant allele, CYP2D6B, have been inconsistently found among patients compared with controls. Study of the CYP2D6 gene in DLB has been equally controversial, with one report suggesting findings similar to those in PD, with an increased frequency of the B allele (Saitoh et al., 1995) and one study showing no association (Bordet et al., 1994). A candidate gene approach to the study of genetic influences in PD has focused upon the dopaminergic system. It would be of interest to ascertain the status of these genes in DLB, given the dopaminergic dysfunction and pathology seen in DLB. An association of the N-acetyltransferase (NAT) 2 gene locus with familial PD is also of interest given its role in xenobiotic metabolism and the suggested role of these enzymes in detoxifying DA metabolites (Bandmann et al., 1997). Our own studies, however, do not suggest any association with the NAT2 locus and DLB. Mitochondrial mutations are found in DLB at similar levels to those found in AD and PD, arguing that they may be an acquired function of neurodegeneration, though still potentially capable of accelerating the disease process. There is a higher frequency of allele 2 of the DA receptor D3 gene (DRD3) in patients with PD with hallucinations compared to those without hallucinations (Goetz et al., 2001). Unlike AD, there is no significant difference between the frequencies of allele 2 homozy-

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gotes and heterozygotes and no association with ApoE4. The DRD3 receptor may thus be a factor involved in hallucinations and may merit study in DLB. α -Synuclein has previously been identified as a major component of SP in AD, and this prompted study of the role of the gene in AD. To date, no mutations or associated polymorphisms have been linked to AD. The identification of mutations in α -synuclein (Polymeropoulos et al., 1996) and of the protein in LB will no doubt provide an impetus to search for other mutations in PD and also to search for associations with DLB. No simple association has been found with the synuclein gene in PD and DLB. More sophisticated investigations of the α -synuclein gene in PD have revealed a possible haplotype linked to the disease, and studies are currently under way in DLB to determine if this is also the case. Other proteins that are implicated in the genetic aetiology of PD could potentially be associated with the pathogenesis of DLB. Synphilin, an α -synuclein interacting protein, is present in the PD brain in LBs (Engelender et al., 1999) but does not appear to associate with disease risk in either PD (Bandopadhyay et al., 2001) or DLB (C.M. Morris, unpublished observations). MANAGEMENT Establishing an accurate and timely diagnosis is fundamental to planning management and treatment interventions in DLB. This, in turn, relies on acquiring a detailed clinical history supplemented by relevant examinations and investigations (see above). It is then necessary to identify key symptoms and evaluate their significance. A problem list of cognitive, psychiatric, and motor disabilities needs to be established in addition to the usual assessments of functioning, risk, and carer burden. Until safe and effective medications become available, the mainstay of clinical management is to educate patients and carers about the nature of the symptoms of DLB and suggest strategies to cope with them. Interventions can be targeted for each of the three core symptoms. Strategies for cognitive symptoms include orientation and memory prompts and attentional cues. For psychiatric symptoms, options include explanation, education, reassurance, and targeted behavioral interventions (Collerton and Dudley, 2004). Motor impairments may benefit from physiotherapy and mobility aids. There are no disease-modifying pharmacological therapies for DLB. Better understanding of the neurobiology of synuclein may lead to the development of novel therapeutic interventions applicable to a diverse group of neurodegenerative disorders including DLB, PD, and MSA, but until then, only symptomatic treatments are available. Alleviation of psychosis, cognitive deficits, and affective and motor symptoms may be required but can be extremely difficult because treatment introduced for

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one set of symptoms may lead to deterioration in others. In particular, patients treated with antipsychotic medication, especially those with high D2 receptor antagonism, can experience an exacerbation of parkinsonian symptoms. Further, approximately 50% of all patients who receive neuroleptics experience life-threatening adverse effects, termed neuroleptic sensitivity (McKeith, Fairbairn, et al., 1992). This is characterized by sedation, immobility, rigidity, postural instability, falls, and increased confusion. Deterioration can be rapid, and patients are unable to maintain adequate fluid and food intake. The reaction is associated with a poor outcome and a two- to threefold increase in mortality. Because of these concerns, managing patients with DLB with psychotic symptoms is often complex (McKeith, Galasko, et al., 1995). Factors exacerbating psychosis should be identified and excluded. For patients being treated with antiparkinsonian drugs, dose reduction or even withdrawal should be considered, at least on a trial basis. Empirically, drugs for PD could be reduced or withdrawn in the following order: anticholinergics, amantadine, l-deprenyl (selegiline), DA agonists, and levodopa preparations. If there is no improvement, then a cautious trial of an antipsychotic agent may be considered. Functional impairment in DLB is related to the degree of parkinsonism (McKeith et al., 2006), suggesting that antiparkinsonian therapy has an important role in the management of DLB. 3,4-dihydroxyphenylalanine (L-DOPA) is generally well tolerated in DLB and can still produce worthwhile benefit, although motor responsiveness is generally less than that observed in PD (Bonelli et al., 2004; Molloy et al., 2005). Younger DLB cases may be likely to respond to dopaminergic treatment. The use of levodopa was not associated with any adverse cognitive or neuropsychiatric effects after 3 months of treatment in one study (Molloy et al., 2006). Treatment of RBD lacks a double-blind, placebocontrolled evidence base. Clonazepam has been reported as effective and well tolerated (Olson et al., 2000) in suppressing the motor features but does not restore REMsleep atonia (Lapierre and Montplaisir, 1992). Melatonin has also proved beneficial, with control of symptoms or significant improvement being noted in 10 of 14 patients who had failed to respond to clonazepam or were unable to tolerate therapeutic doses (Boeve, Silber, Ferman, et al., 2003). Further work is needed to investigate the potential role of cholinesterase inhibitors and dopaminergic therapies as treatment strategies for RBD. Following initial positive case reports of the use of newer atypical antipsychotics in DLB, further case studies indicate that neuroleptic sensitivity does occur, especially as the dose is increased (McKeith, Ballard, et al., 1995; Burke et al., 1998; Z. Walker, Grace, et al., 1999). Quetiapine does not appear to significantly worsen motor symptoms in a recent, small placebo-controlled trial of 36 patients with DLB (Kurlan et al., 2007) but was not associated with significant improvement in psy-

chiatric or cognitive outcome measures. Until more robust clinical trials are completed, specific recommendations are limited, but overall, atypical antipsychotics are probably safer than traditional agents in DLB. Low dosing may be more important than the use of any specific drug. A rational, effective, and safer alternative to treating DLB may be to compensate for the cholinergic deficits previously described by the use of cholinesterase inhibitors. Open studies have shown improvements in cognitive and noncognitive symptoms with donepezil and rivastigmine, without significant deterioration in motor function (Shea et al., 1998). Apathy, anxiety, impaired attention, hallucinations, delusions, sleep disturbance, and cognitive test performance are the most frequently cited treatment-responsive symptoms. Improvements are generally reported as greater than those achieved with similar doses of these drugs in AD, and a recent openlabel study found evidence of sustained efficacy after 2 years of treatment (Grace et al., 2001). A multicenter, randomized, placebo-controlled trial of rivastigmine in DLB confirmed these observational studies (McKeith, Spano, et al., 2000). A total of 120 patients with DLB were treated with daily doses of rivastigmine of up to 12 mg or placebo for 20 weeks. Patients had a clinical diagnosis of probable and possible DLB and an MMSE score of greater than 10. Approximately twice as many patients on rivastigmine (63.4%) as on placebo (30.0%) showed at least a 30% improvement from baseline in DLB-typical psychiatric symptoms. Patients also showed improvements on computer-based tests of attention. Adverse effects were similar to those observed with the drug in AD and to those reported for other cholinesterase inhibitors. Parkinsonian symptoms did not worsen on treatment, although emergent tremor was noted in a small number of treated patients. Similar findings have been noted in two trials of cholinesterase inhibitors in patients with PDD. The largest (Emre et al., 2004) was a randomized multicenter placebocontrolled trial of rivastigmine, at doses of 3 mg–12 mg, in over 500 patients, using dementia rating scales (Alzheimer’s Disease Assessment Scale – Cognitive subscale [ADAS-cog] and Clinician’s Global Impression of Change subscale [ADAS-CGIC]), cognitive function, and behavioral symptoms (neuropsychiatric inventory, MMSE, Cognitive Drug Research power of attention tests, clock drawing and verbal fluency) as primary and secondary outcome measures, respectively. There was a moderate but significant benefit in the treatment group compared to placebo but at the expense of adverse side effects such as nausea, vomiting, and worsening tremor (10%). Smaller studies, also in PDD (Aarsland et al., 2002; Ravina et al., 2005), have demonstrated similar benefits with donepezil. Head-to-head studies between cholinesterase inhibitors have not been performed to permit advice on which drug should be used first line in the management of DLB and PDD.

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Cholinesterase inhibitors should therefore probably be the first choice for symptomatic treatment of the core symptoms of DLB, particularly because they do not carry the adverse risks associated with neuroleptic agents. Further large-scale trials in patients with DLB and PDD are required to support this proposal. CONCLUSION DLB is now established as a commonly occurring clinical syndrome accounting for up to 1 in 6 cases of dementia in older people. Recognition of cases with the characteristic clinical symptoms of attentional deficits, visuoperceptual abnormalities, visual hallucinations, fluctuating arousal, and parkinsonism is associated with a high probability of LB pathology and diagnostic accuracy. Unfortunately, a substantial number of cases do not present with such clearly recognizable clinical features and this appears often to be due to the co-existence of significant cortical Alzheimer pathology. The clinician must therefore adopt a high index of suspicion for cases with less florid presentations (possible DLB) and pursue these further by specific inquiry about suggestive clinical features and use of appropriate neuroimaging techniques. Lack of hippocampal atrophy, reduced perfusion of occipital cortex, and reduced striatal dopamine re-uptake are all supportive of a DLB diagnosis compared with AD, which is the usual differential. No other biomarkers have yet been established as useful in the diagnosis of DLB. When the term DLB was adopted in 1996, it was done so “as a generic term for such cases, because it acknowledges the presence of LB without specifying their relative importance in symptom formation.” Although this remark was made predominantly with respect to other degenerative and vascular pathologies, it also holds true in relation to LB themselves. Clinico-pathological correlations between LB and LN density and severity of clinical features are infrequent, consistent with recent opinion that these are end-stage and possibly cytoprotective lesions. Neurotoxic species of a -synuclein have not yet been identified but may well comprise small oligomeric aggregates at the synaptic level. This has major implications for targeting drug development, and further work in this area must be a research priority. The symptomatic and possibly even neuroprotective value of cholinesterase inhibition in the treatment of DLB also needs to be further explored further in large multicenter trials. Levodopa responsiveness of the parkinsonism associated with DLB is poorly documented, and controlled studies are also clearly needed. REFERENCES Aarsland, D., Ballard, C., McKeith, I., Perry, R.H., and Larsen, J.P. (2001) Comparison of extrapyramidal signs in dementia with Lewy

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bodies and Parkinson’s disease. J. Neuropsychiatry Clin. Neurosci. 13:374–379. Aarsland, D., Laake, K., Larsen, J.P., and Janvin, C. (2002) Donepezil for cognitive impairment in Parkinson’s disease: a randomised controlled study. J. Neurol. Neurosurg. Psychiatry 72:708–712. Ala, T.A., Hughes, L.F., Kyrouac, G.A., Ghobrial, M.W., and Elble, R.J. (2001) Pentagon copying is more impaired in dementia with Lewy bodies than in Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 70:483– 488. Albasanz, J.L., Dalfó, E., Ferrer, I., and Martin, M. (2005) Impaired metabotropic glutamate receptor/phospholipase C signaling pathway in the cerebral cortex in Alzheimer’s disease and dementia with Lewy bodies correlates with stage of Alzheimer’s-diseaserelated changes. Neurobiol. Dis. 20:685–693. Allan, L.M., Ballard, C.G., Allen, J., Murray, A., Davidson, A.W., McKeith, I.G., and Kenny, R.A. (2007) Autonomic dysfunction in dementia. J. Neurol. Neurosurg. Psychiatry 78(7):671–677. American Academy of Sleep Medicine. (2005) The International Classification of Sleep Disorders: Diagnostic and Coding Manual, 2nd ed. Westchester, IL. Baba, M., Nakajo, S., Tu, P.H., Tomita, T., Nakaya, K., Lee, V.M., Trojanowski, J.Q., and Iwatsubo, T. (1998) Aggregation of alpha-synuclein in Lewy bodies of sporadic Parkinson’s disease and dementia with Lewy bodies. Am. J. Pathol. 152:879–884. Ballard, C., Johnson, M., Piggott, M., et al. (2002) A positive association between 5HT re-uptake binding sites and depression in dementia with Lewy bodies. J. Affect. Dis. 69:219–223. Ballard, C.G., Court, J.A., Piggott, M., et al. (2002) Disturbances of consciousness in dementia with Lewy bodies associated with alteration in nicotinic receptor binding in the temporal cortex. Conscious. Cogn. 11:461– 474. Ballard, C.G., McKeith, I., Burn, D., Harrison, R., O’Brien, J., Lowery, K., Campbell, M., Perry, R., and Ince, P. (1997) The UPDRS scale as a means of identifying extrapyramidal signs in patients suffering from dementia with Lewy bodies. Acta Neurol. Scand. 96:366–371. Ballard, C.G., O’Brien, J., Barber, B., et al. (2000) Neurocardiovascular instability, hypotensive episodes and MRI lesions in neurodegenerative dementia. Ann. N.Y. Acad. Sci. 903:442– 445. Ballard, C.G., O’Brien, J., Gray, A., Cormack, F., Ayre, G., Rowan, E., Thompson, P., Bucks, R., McKeith, I., Walker, M., and Tovee, M. (2001) Attention and fluctuating attention in patients with dementia with Lewy bodies and Alzheimer’s disease. Arch. Neurol. 58:977–982. Ballard, C.G., O’Brien, J., Morris, C.M., Barber, R., Swann, A., Neill, D., and McKeith, I. (2001) The progression of cognitive impairment in dementia with Lewy bodies, vascular dementia and Alzheimer’s disease. Int. J. Geriatr. Psychiatry 16:499–503. Ballard, C.G., O’Brien, J., Swann, A., Neill, D., Lantos, P., Holmes, C., Burn, D., Ince, P., Perry, R., and McKeith, I. (2000) One year follow-up of parkinsonism in dementia with Lewy bodies. Dement. Geriatr. Cogn. Disord. 11:219–222. Ballard, C.G., Piggott, M., Johnson, M., Cairns, N.J., Perry, R., McKeith, I., Jaros, E., O’Brien, J., Holmes, C., and Perry, E. (2000) Delusions associated with elevated muscarinic binding in dementia with Lewy bodies. Ann. Neurol. 48:868–876. Ballard, C.G., Shaw, F., Lowery, K., McKeith, I., and Kenny, R. (1999) The prevalence, assessment and associations of falls in dementia with Lewy bodies and Alzheimer’s disease. Dement. Geriatr. Cogn. Disord. 10:97–103. Ballard, C.G., Shaw, F., McKeith, I., and Kenny, R. (1998) High prevalence of neurovascular instability in neurodegenerative dementias. Neurology 51:1760–1762. Bandmann, O., Vaughan, J., Holmans, P., Marsden, C.D., and Wood, N.W. (1997) Association of slow acetylator genotype for N-acetyl transferase 2 with familial Parkinson’s disease. Lancet 350:1136– 1139. Bandopadhyay, R., de Silva, R., Khan, N., Graham, E., Vaughan, J., Engelender, S., Ross, C., Morris, H., Morris, C., Wood, N.W.,

1026

DEMENTIA

Daniel, S., and Lees, A. (2001) No pathogenic mutations in the synphilin-1 gene in Parkinson’s disease. Neurosci. Lett. 307: 125–127. Barber, R., Ballard, C.G., McKeith, I.G., Gholkar, A., and O’Brien, J.T. (2000) MRI volumetric study of dementia with Lewy bodies: a comparison with AD and vascular dementia. Neurology 54: 1304–1309. Barber, R., Gholkar, A., Scheltens, P., Ballard, C.G., McKeith, I.G., and O’Brien, J.T. (1999) Medial temporal lobe atrophy on MRI in dementia with Lewy bodies. Neurology 52:1153–1158. Benarroch, E.E., Schmeichel, A.M., Low, P.A., Boeve, B.F., Sandroni, P., and Parisi, J.E. (2005) Involvement of medullary regions controlling sympathetic output in Lewy body disease. Brain 128:338–344. Boeve, B., Silber, M., and Ferman, T. (2004) REM sleep behavior disorder in Parkinson’s disease and dementia with Lewy bodies. J. Ger. Psychiatry Neurol. 17:146–157. Boeve, B.F., Dickson, D.W., Olson, E.J., Shepard, J.W., Silber, M.H., Ferman, T.J., Ahlskog, J.E., and Benarroch, E.F. (2006) Insights into REM sleep behavior disorder pathophysiology in brainstempredominant Lewy body disease. Sleep Med. 8:60–64. Boeve, B.F., Silber, M.H., and Ferman, T.J. (2003) Melatonin for treatment of REM sleep behavior disorder in neurologic disorders: results in 14 patients. Sleep Med. 4: 281–284. Boeve, B.F., Silber, M.H., Ferman, T.J., Kokmen, E., Smith, G.E., Ivnik, R.J., Parisi, J.E., Olson, E.J., and Petersen, R.C. (1998) REM sleep behavior disorder and degenerative dementia: an association likely reflecting Lewy body disease. Neurology 51:363–370. Boeve, B.F., Silber, M.H., Ferman, T.J., Lucas, J.A., and Parisi, J.E. (2001) Association of REM sleep behavior disorder and neurodegenerative disease may reflect an underlying synucleinopathy. Mov. Disord. 16:622–630. Boeve, B.F., Silber, M.H., Parisi, J.E., Dickson, D.W., Ferman, T.J., Benarroch, E.E., Schmeichel, A.M., Smith, G.E., Petersen, R.C., Ahlskog, J.E., Matsumoto, J.Y., Knopman, D.S., Schenck, C.H., and Mahowald, M.W. (2003) Synucleinopathy pathology and REM sleep behavior disorder plus dementia or parkinsonism. Neurology 61(1):40 – 45. Bohnen, N.I., Kaufer, D.I., Hendrickson, R., et al. (2006) Cognitive correlates of cortical cholinergic denervation in Parkinson’s disease and parkinsonian dementia. J. Neurology 253:242–247. Bonelli, S.B., Ransmayr, G., Steffelbauer, M., Lukas, T., Lampl, C., and Deibl, M. (2004) L-dopa responsiveness in dementia with Lewy bodies, Parkinson’s disease with and without dementia. Neurology 63:376–378. Bonini, N.M., and Giasson, B.I. (2005) Snaring the function of alpha-synuclein. Cell 123(3):359–361. Bordet, R., Broly, F., Destee, A., and Libersa, C. (1994) Genetic polymorphism of cytochrome P450 2D6 in idiopathic Parkinson’s disease and diffuse Lewy body disease. Clin. Neuropharmacol. 17:484 – 488. Boström, F., Jonsson, L., Minthon, L., and Londos, E. (2007a) Patients with Lewy body dementia have more impaired quality of life than patients with Alzheimer’s disease. Alzheimers Dis. Assoc. Disord. 21:150–154. Boström, F., Jonsson, L., Minthon, L., and Londos, E. (2007b) Patients with Lewy body dementia use more resources than those with Alzheimer’s disease. Int. J. Ger. Psychiat. 22:713–719. Bradshaw, J., Slaing, M., Hopwood, M., Anderson, V., and Brodtmann, A. (2004) Fluctuating cognition in dementia with Lewy bodies and Alzheimer’s disease is qualitatively distinct. J. Neurol. Neurosurg. Psychiatry 75(3):382–387. Briel, R.C., McKeith, I.G., Barker, W.A., Hewitt, Y., Perry, R.H., Ince, P.G., and Fairbairn, A.F. (1999) EEG findings in dementia with Lewy bodies and Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 66:401– 403. Burke, W.J., Pfeiffer, R.F., and McComb, R.D. (1998) Neuroleptic sensitivity to clozapine in dementia with Lewy bodies. J. Neuropsychiatry Clin. Neurosci. 10:227–229.

Burn, D.J., Rowan, E.N., Minett, T., et al. (2003) Extrapyramidal features in Parkinson’s disease with and without dementia and dementia with Lewy bodies: a cross-sectional comparative study. Mov. Disord. 18: 884–889. Burton, E.J., McKeith, I.G., Burn, D.J., Firbank, M.J., O’Brien, J.T. (2006) Progression of white matter hyperintensities in Alzheimer disease, dementia with Lewy bodies, and Parkinson disease dementia: a comparison with normal ageing. Am. J. Geriatr. Psychiatry 14(10):842–849. Campbell, S., Stephens, S., and Ballard, C. (2001) Dementia with Lewy bodies: clinical features and treatment. Drugs Ageing 18: 397– 407. Cash, R., Dennis, T., L’Heureux, R., Raisman, R., Javoy-Agid, F., and Scatton, B. (1987) Parkinson’s disease and dementia: norepinephrine and dopamine in locus ceruleus. Neurology 37:42– 46. Castagnet, P.I., Golovko, M.Y., Barceló-Coblijn, G.C., et al. (2005) Fatty acid incorporation is decreased in astrocytes cultured from alpha-synuclein gene-ablated mice. J. Neurochem. 94(3):839– 849. Chandra, S., Gallardo, G., Fernández-Chacón, R., et al. (2005) Alphasynuclein cooperates with CSP alpha in preventing neurodegeneration. Cell 123(3):383–396. Chen, C.P., Alder, J.T., Bray, L., Kingsbury, A.E., Francis, P.T., and Foster, O.J. (1998) Post-synaptic 5-HT1A and 5-HT2A receptors are increased in Parkinson’s disease neocortex. Ann. N.Y. Acad. Sci. 861:288–289. Cheng, A.V., Ferrier, I.N., Morris, C.M., et al. (1991) Cortical serotonin-S2 receptor binding in Lewy body dementia, Alzheimer’s and Parkinson’s diseases. J. Neurol. Sci. 106:50–55. Collerton, D., Burn, D., McKeith, I., and O’Brien, J. (2003) Systematic review and meta-analysis show that dementia with Lewy bodies is a visual-perceptual and attentional-executive dementia [erratum appears in Dement. Geriatr. Cogn. Disord. 2005;19(1):56]. Dement. Geriatr. Cogn. Disord. 16: 229–237. Collerton, D., and Dudley, R. (2004) A cognitive behavioural framework for the treatment of distressing visual hallucinations in older people. Behav. Cogn. Psychother. 32:443– 455. Collerton, D., Perry, E., and McKeith, I. (2005) Why people see things that are not there. A novel perception and attention deficit model for recurrent complex visual hallucinations. Behav. Brain Sci. 28:737–794. Colloby, S.J., Pakrasi, S., Firbank, M.J., Perry, E.K., Piggott, M.A., et al. (2006) In vivo SPECT imaging of muscarinic acetylcholine receptors using (R,R) 123I-QNB in dementia with Lewy bodies and Parkinson’s disease dementia. NeuroImage 33(2):423– 429. Colloby, S.J., Williams, E.D., Burn, D.J., Lloyd, J.J., McKeith, I.G., and O’Brien, J.T. (2005) Progression of dopaminergic degeneration in dementia with Lewy bodies and Parkinson’s disease with and without dementia assessed using 123I-FP-CIT SPECT. Eur. J. Nucl. Med. Mol. Imag.32:1176–1185. Cooper, A.A., Gitler, A.D., Cashikar, A., et al. (2006) Alpha-synuclein blocks ER-Golgi traffic and Rab1 rescues neuron loss in Parkinson’s models. Science 313(5785):324 –328. Court, J., Spurden, D., Lloyd, S., et al. (1999) Neuronal nicotinic receptors in dementia with Lewy bodies and schizophrenia: abungarotoxin and nicotine binding in the thalamus. J. Neurochem. 73:1590 –1597. Court, J.A., Ballard, C.G., Piggott, M.A., Johnson, M., O’Brien, J. T., Holmes, C., Cairns, N., Lantos, P., Perry, R.H., Jaros, E., and Perry, E.K. (2001) Visual hallucinations are associated with lower a-bungarotoxin binding in dementia with Lewy bodies. Pharmacol. Biochem. Behav. 70:571–579. Del Ser, T., Hachinski, V., Merskey, H., and Munoz, D.G. (2001) Clinical and pathologic features of two groups of patients with dementia with Lewy bodies: Effect of coexisting Alzheimer-type lesion load. Alzheimer Dis. Assoc. Disord. 15:31– 44. Dalfó, E., and Ferrer, I. (2008) Early a-synuclein lipoxidation in neocortex in Lewy bodies diseases. Neurobiol. Aging 29(3):408– 417.

62: DEMENTIA WITH LEWY BODIES Dalfó, E., Martinez, A., Muntane, G., and Ferrer, I. (2006) Abnormal a-synuclein solubility, aggregation and nitration in the frontal cortex in Pick’s disease. Neurosci. Lett. 400:125–129. de Bruin, V.M., Lees, A.J., and Daniel, S.E. (1992) Diffuse Lewy body disease presenting with supranuclear gaze palsy, parkinsonism, and dementia: a case report. Mov. Disord. 7:355–358. Defebvre, L.J., Leduc, V., Duhamel, A., et al. (1999) Technetium HMPAO SPECT study in dementia with Lewy bodies. J. Nucl. Med. 40:956 –962. Del Ser, T., McKeith, I., Anand, R., Cicin-Sain, A., Ferrara, R., and Spiegel, R. (2000) Dementia with Lewy bodies: findings from an international multicentre study. Int. J. Geriatr. Psychiatry 15:1034 –1045. Donnemiller, E., Heilmann, J., Wenning, G.K., et al. (1997) Brain perfusion scintigraphy with 99mTc-HMPAO or 99mTc-ECD and 123 I-beta-CIT single-photon emission tomography in dementia of the Alzheimer-type and diffuse Lewy body disease. Eur. J. Nucl. Med. 24:320 –325. Duda, J.E., Giasson, B.I., Mabon, M.E., Lee, V.M., and Trojanowski, J.Q. (2002) Novel antibodies to synuclein show abundant striatal pathology in Lewy body diseases. Ann. Neurol. 52:205–210. Eisensehr, I., Linke, R., Tatsch, K., et al. (2003) Increased muscle activity during rapid eye movement sleep correlates with decrease of striatal presynaptic dopamine transporters. IPT and IBZM SPECT imaging in subclinical and clinically manifest idiopathic REM sleep behavior disorder, Parkinson’s disease, and controls. Sleep 26:507–512. Emre, M., Aarsland, D., Albanese, A., et al. (2004) Rivastigmine for dementia associated with Parkinson’s disease. N. Engl. J. Med. 351:2509–2518. Emre, M., Aarsland, D., Brown, R., et al. (2007) Clinical diagnostic criteria for dementia associated with Parkinson’s disease. Mov. Disorder 22(12):1689–1707. Engelender, S., Kaminsky, Z., Guo, X., et al. (1999) Synphilin-1 associates with α -Synuclein and promotes the formation of cytosolic inclusions. Nat. Genet. 22:110–114. Fan, Y., Limprasert, P., Murray, I.V., Smith, A.C., Lee, V.M., Trojanowski, J.Q., Sopher, B.L., La and Spada, A.R. (2006) Beta-synuclein modulates a -synuclein neurotoxicity by reducing alpha-synuclein protein expression. Hum. Mol. Genet. 15:3002– 3010. Farde, L., Suhara, T., Nyberg, S., Karlsson, P., Nakashima, Y., Hietala, J., and Halldin, C. (1997) A PET study of [11C]FLB 457 binding to extrastriatal D2-dopamine receptors in healthy subjects and antipsychotic drug-treated patients. Psychopharmacology 133:396– 404. Fearnley, J.M., Revesz, T., Brooks, D.J., Frackowiak, R.S., and Lees, A.J. (1991) Diffuse Lewy body disease presenting with a supranuclear gaze palsy. J. Neurol. Neurosurg. Psychiatry 54:159–161. Ferman, T.J., Boeve, B.F., Smith, G.E., Silber, M.H., Kokmen, E., Petersen, R.C., and Ivnik, R.J. (1999) REM sleep behaviour disorder and dementia: Cognitive differences when compared with AD. Neurology 52:951–957. Ferman, T.J., Smith, G.E., Boeve, B.F., Ivnik, R.J., Petersen, R.C., Knopman, D., Graff-Radford, N., Parisi, J., and Dickson, D.W. (2004) DLB fluctuations: specific features that reliably differentiate from AD and normal ageing. Neurology 62:181–187. Firbank, M.J., Colloby, S.J., Burn, D.J., McKeith, I.G., and O’Brien, J.T. (2003) Regional cerebral blood flow in Parkinson’s disease with and without dementia. NeuroImage 20:1309–1319. Förstl, H., Burns, A., Levy, R., and Cairns, N. (1994) Neuropathological correlates of psychotic phenomena in confirmed Alzheimer’s disease. Br. J. Psychiatry 165:53–59. Förstl, H., Burns, A., Luthert, P., et al. (1993) The Lewy-body variant of Alzheimer’s disease. Clinical and pathological findings. Br. J. Psychiatry 162:385–392. Freeman, A., Ciliax, B., Bakay, R., et al. (2001) Nigrostriatal collaterals to thalamus degenerate in parkinsonian animal models. Ann. Neurol., 50:321–329.

1027

Fujiwara, H., Hasegawa, M., Dohmae, N., et al. (2002) a -Synuclein is phosphorylated in synucleinopathies. Nat. Cell Biol. 4:160 –164. Fumimura, Y., Ikemura, M., Saito, Y., Sengoku, R., Kanemura, K., et al. (2007) Analysis of the adrenal gland is useful for evaluating pathology of the peripheral autonomic nervous system in Lewy body disease. J. Neuropathol. Exp. Neurol. 66:354 –362. Gagnon, J.F., Bedard, M.A., Fantini, M.L., Petit, D., Panisset, M., Rompre, S., Carrier, J., and Montplaisir, J. (2002) REM sleep behaviour disorder and REM sleep without atonia in Parkinson’s disease. Neurology 59:585–589. Gagnon, J.F., Petit, D., Fantini, M.L., Pompre, S., Gauthier, S., Panisset, M., Robillard, A., and Montplaisir, J. (2006) REM sleep behaviour disorder and REM sleep without atonia in probable Alzheimer’s disease. Sleep 29(10):1321–1325. Galvin, J.E., Uryu, K., Lee, V.M., and Trojanowski, J.Q. (1999) Axon pathology in Parkinson’s disease and Lewy body dementia hippocampus contains alpha-, beta-, and gamma-synuclein. Proc. Natl. Acad. Sci. USA 96:13450–13455. Gelb, D.J., Oliver, E., and Gilman, S. (1999) Diagnostic criteria for Parkinson’s disease. Arch. Neurol. 56:33–39. Ghazi-Noori, S., Chung, T.H., Deane, K., Rickards, H., and Clarke, C.E. (2003) Therapies for depression in Parkinson’s disease. Cochrane Database Sys. Rev.:CD003465. Gnanalingham, K.K., Byrne, E.J., Thornton, A., Sambrook, M.A., and Bannister, P. (1997) Motor and cognitive function in Lewy body dementia: comparison with Alzheimer’s and Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 62:243–252. Gnanalingham, K.K., Smith, L.A., Hunter, A.J., Jenner, P., and Marsden, C.D. (1993) Alterations in striatal and extrastriatal D-1 and D-2 dopamine receptors in the MPTP-treated common marmoset: an autoradiographic study. Synapse 14:184 –194. Goetz, C.G., Burke, P.F., Leurgans, S., Berry-Kravis, E., Blasucci, L.M., Raman, R., and Zhou, L. (2001) Genetic variation analysis in Parkinson disease patients with and without hallucinations: casecontrol study. Arch. Neurol. 58:209–213. Golovko, M.Y., Faergeman, N.J., Cole, N.B., et al. (2005) Alphasynuclein gene deletion decreases brain palmitate uptake and alters the palmitate metabolism in the absence of alpha-synuclein palmitate binding. Biochemistry 44(23):8251–8259. Gómez-Tortosa, E., Gonzalo, I., Newell, K., et al. (2002) Patterns of protein nitration in dementia with Lewy bodies and striatonigral degeneration. Acta Neuropathol. 103(5):495–500. Gómez-Tortosa, E., Irizarry, M.C., Gomez-Isla, T., and Hyman, B.T. (2000) Clinical and neuropathological correlates of dementia with Lewy bodies. Ann. N.Y. Acad. Sci. 920:9–15. Gómez-Tortosa, E., Newell, K., Irizarry, M.C., Albert, M., Growdon, J.H., and Hyman, B.T. (1999) Clinical and quantitative pathologic correlates of dementia with Lewy bodies. Neurology 53:1284– 1291. Gómez-Tortosa, E., Newell, K., Irizarry, M.C., Sanders, J.L., and Hyman, B.T. (2000) Alpha-synuclein immunoreactivity in dementia with Lewy bodies: morphological staging and comparison with ubiquitin immunostaining. Acta Neuropathol. (Berl) 99:352–357. Gotti, C., Moretti, M., Bohr, I., et al. (2006) Selective nicotinic acetylcholine receptor subunit deficits identified in Alzheimer’s disease, Parkinson’s disease and dementia with Lewy bodies by immunoprecipitation. Neurobiol. Dis. 23:481– 489. Grace, J., Daniel, S., Stevens, T., Shankar, K.K., Walker, Z., Byrne, E.J., Butler, S., Wilkinson, D., Woolford, J., Waite, J., and McKeith, I.G. (2001) Long-term use of rivastigmine in patients with dementia with Lewy bodies: An open label trial. Int. Psychogeriatr. 13:199–205. Harding, A.J., Broe, G.A., and Halliday, G.M. (2002) Visual hallucinations in Lewy body disease relate to Lewy bodies in the temporal lobe. Brain 125:391– 403. Harrington, C.R., Perry, R.H., Perry, E.K., Hurt, J., McKeith, I.G., Roth, M., and Wischik, C.M. (1994) Senile dementia of Lewy body type and Alzheimer type are biochemically distinct in terms

1028

DEMENTIA

of paired helical filaments and hyperphosphorylated tau protein. Dementia 5:215–228. Hashimoto, M., Rockenstein, E., Mante, M., Mallory, M., and Masliah, E. (2001) Beta-synuclein inhibits alpha-synuclein aggregation: a possible role as an anti-parkinsonian factor. Neuron 32:213–223. Horimoto, Y., Matsumoto, M., Akatsu, H., Ikari, H., Kojima, K., Yamamoto, T., Otsuka, Y., Ojika, K., Ueda, R., and Kosaka, K. (2003) Autonomic dysfunctions in dementia with Lewy bodies. J. Neurol. 250(5):530–533. Hu, X.S., Okamura, N., Arai, H., et al. (2000) 18F-fluorodopa PET study of striatal dopamine uptake in the diagnosis of dementia with Lewy bodies. Neurology 55:1575–1577. Hurtig, H.I., Trojanowski, J.Q., Galvin, J., Ewbank, D., Schmidt, M.L., Lee, V.M., Clark, C.M., Glosser, G., Stern, M.B., Gollomp, S.M., and Arnold, S.E. (2000) Alpha-synuclein cortical Lewy bodies correlate with dementia in Parkinson’s disease. Neurology 54:1916–1921. Iranzo, A., Molinuevo, J.L., Santmaria, J., Serradell, M., Marti, M.J., Valldeoriola, F., and Tolosa, E. (2006) Rapid-eye-movement sleep behaviour disorder as an early marker for a neurodegenerative disorder: a descriptive study. Lancet Neurol. 5:572–577. Iranzo, A., Santamaria, J., Rye, D.B., Valldeoriola, F., Marti, M.J., Munoz, E., Vilaseca, I., and Tolosa, E. (2005) Characteristics of idiopathic REM sleep behaviour disorder and that associated with MSA and PD. Neurology 65:247–252. Ishii, K., Yamaji, S., Kitagaki, H., Imamura, T., Hirono, N., and Mori, E. (1999) Regional cerebral blood flow difference between dementia with Lewy bodies and AD. Neurology 53:413– 416. Jellinger, K.A., Wenning, G.K., and Seppi, K. (2007) Predictors of survival in dementia with Lewy bodies and Parkinson dementia. Neurodegener. Dis. 4:428– 430. Johnson, D.K., Morris, J.C., and Galvin, J.E. (2005) Verbal and visuospatial deficits in dementia with Lewy bodies. Neurology 65: 1232–1238. Kaasinen, V., Nagren, K., Hietala, J., Oikonen, V., Vilkman, H., Farde, L., Halldin, C., and Rinne, J.O. (2000) Extrastriatal dopamine D2 and D3 receptors in early and advanced Parkinson’s disease. Neurology 54:1482–1487. Kanemaru, K., Kameda, K., and Yamanouchi, H. (2000) Decreased CSF amyloid b42 and normal tau levels in dementia with Lewy bodies. Neurology 54:1875–1876. Kaufmann, H., Nahm, K., Purohit, D., and Wolfe, D. (2004) Autonomic failure as the initial presentation of Parkinson disease and dementia with Lewy bodies. Neurology 63:1093–1095. Kenny, R.A., Shaw, F.E., O’Brien, J.T., Scheltens, P.H., Kalaria, R., and Ballard, C. (2004) Carotid sinus syndrome is common in dementia with Lewy bodies and correlates with deep white matter lesions. J. Neurol. Neurosurg. Psychiatry 75(7):966–971. Kuhn, W., Muller, T., Gerlach, M., et al. (1996) Depression in Parkinson’s disease: biogenic amines in CSF of “de novo” patients. J. Neural Trans. 103:1441–1445. Kurlan, R., Cummings, J., Raman, R., and Thal, L. (2007) Quetiapine for agitation or psychosis in patients with dementia and parkinsonism. For the Alzheimer’s Disease Cooperative Study Group Neurology 68(17):1356–1363. Lambon, R.M.A., Powell, J., Howard, D., Whitworth, A.B., Garrard, P., and Hodges, J.R. (2001) Semantic memory is impaired in both dementia with Lewy bodies and Alzheimer’s disease: a comparative neuropsychological study and literature review. J. Neurol. Neurosurg. Psychiatry 70:149–156. Langlais, P.J., Thal, L., Hansen, L., Galasko, D., Alford, M., and Masliah, E. (1993) Neurotransmitters in basal ganglia and cortex of Alzheimer‘s disease with and without Lewy bodies. Neurology 43:1927–1934. Lapierre, O., and Montplaisir, J. (1992) Polysomnographic features of REM sleep behavior disorder: development of a scoring method. Neurology 42:1371–1374.

Lennox, G.G. (1992) Lewy body dementia. Baillieres Clin. Neurol. 1:653–676. Lennox, G.G., and Lowe, J.S. (1997) Dementia with Lewy bodies. Baillieres Clin. Neurol. 6:147–166. Leverenz, J., Umar, I., Wang, Q., et al. (2007) Proteomic identification of novel proteins in cortical Lewy bodies. Brain Pathol. 17: 139– 145. Leverenz, J.B., Miller, M.A., Dobie, D.J., Peskind, E.R., and Raskind, M.A. (2001) Increased alpha 2-adrenergic receptor binding in locus coeruleus projection areas in dementia with Lewy bodies. Neurobiol. Aging 22:555–561. Lippa, C.F., Smith, T.W., and Perry, E. (1999) Dementia with Lewy bodies: choline acetyltransferase parallels nucleus basalis pathology. J. Neural Transm. 106:525–535. Lobotesis, K., Fenwick, J., Phipps, A., Ryman, A., Swann, A., Ballard, C., McKeith, I.G., and O’Brien, J.T. (2001) Occipital hypoperfusion on SPECT in dementia with Lewy bodies but not AD. Neurology 56:643–649. Lopez, O.L., Becker, J.T., Kaufer, D.I., et al. (2002) Research evaluation and prospective diagnosis of dementia with Lewy bodies. Arch. Neurol. 59:43– 46. Lopez, O.L., Becker, J.T., Sweet, R.A., et al. (2006) Lewy bodies in the amygdala increase risk for major depression in subjects with Alzheimer disease. Neurology 67(4):660–665. Louis, E.D., Klatka, L.A., Liu, Y., and Fahn, S. (1997) Comparison of extrapyramidal features in 31 pathologically confirmed cases of diffuse Lewy body disease and 34 pathologically confirmed cases of Parkinson’s disease. Neurology 48:376–380. Louis, E.D., Vonsattel, J.P., and Honig, L.S. (2006) Neuropathologic findings in essential tremor. Neurology 66(11):1756–1759. Marshall, E.F., Perry, E.K., Perry, R.H., McKeith, I.G., Fairbairn, A.F., and Thompson, P. (1994) Dopamine metabolism in postmortem caudate nucleus in neurodegenerative disorders. Neurosci. Res. Commun. 14:17–25. Mattila, P.M., Roytta, M., Lonnberg, P., Marjamaki, P., Helenius, H., and Rinne, J.O. (2001) Choline acetytransferase activity and striatal dopamine receptors in Parkinson’s disease in relation to cognitive impairment. Acta Neuropath. 102:160–166. McKeith, I., O’Brien, J., Walker, Z., Tatsch, K., Booji, J., et al. (2007) Sensitivity and specificity of dopamine transporter imaging with 123I-FP-CIT SPECT in dementia with Lewy bodies: a phase III, multicentre study Lancet Neurol. 6(4):305– 313. McKeith, I.G., Ballard, C.G., and Harrison, R.W. (1995) Neuroleptic sensitivity to risperidone in Lewy body dementia. Lancet 346: 699. McKeith, I.G., Ballard, C.G., Perry, R.H., et al. (2000) Prospective validation of consensus criteria for the diagnosis of dementia with Lewy bodies. Neurology 54:1050–1058. McKeith, I.G., Burn, D., O’Brien, J., Perry, R., and Perry, E.K. (2002) Dementia with Lewy bodies. In: Davis, K.L., Charney, D., Coyle, J.T., and Nemeroff, C., eds. Neuropsychopharmacology: The 5th Generation of Progress. Philadelphia: Lippincott, Williams & Wilkins, pp. 1301–1315. McKeith, I.G., Dickson, D.W., Lowe, J., et al. (2005) Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 65(12):1863–1872. McKeith, I.G., Fairbairn, A., Perry, R., Thompson, P., and Perry, E. (1992) Neuroleptic sensitivity in patients with senile dementia of Lewy body type. Br. Med. J. 305:673– 678. McKeith, I.G., Galasko, D., Kosaka, K., et al. (1996) Consensus guidelines for the clinical and pathological diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology 47:1113–1124. McKeith, I.G., Galasko, D., Wilcock, G.K., and Byrne, E.J. (1995) Lewy body dementia—diagnosis and treatment. Br. J. Psychiatry 167:709–717.

62: DEMENTIA WITH LEWY BODIES McKeith, I.G., Perry, E.K., and Perry, R. (1999) Report of the second dementia with Lewy body international workshop. Neurology 53:902–905. McKeith, I.G., Perry, R.H., Fairbairn, A.F., Jabeen, S., and Perry, E.K. (1992) Operational criteria for senile dementia of Lewy body type (SDLT). Psychol. Med. 22:911–922. McKeith, I.G., Rowan, E., Askew, K., Naidu, A., Allen, L., Barnett, N., Lett, D., Mosimann, U.P., Burn, D., and O’Brien, J.T. (2006) More severe functional impairment in dementia with Lewy bodies than Alzheimer disease is related to extrapyramidal motor dysfunction. Am. J. Ger. Psychiat. 14(7):582–588. McKeith, I.G., Spano, P.F., Del Ser, T., Emre, M., Wesnes, K., Anand, R., Cicin-Sain, A., Ferrara, R., and Spiegel, R. (2000) Efficacy of rivastigmine in dementia with Lewy bodies: a randomised, doubleblind, placebo-controlled international study. Lancet 356:2031– 2036. McLean, P.J., Kawamata, H., Ribich, S., and Hyman, B.T. (2000) Membrane association and protein conformation of alpha-synuclein in intact neurons. Effect of Parkinson’s disease-linked mutations. J. Biol. Chem. 275(12):8812–8816. McNaught, K.S., and Jenner, P. (2001) Proteasomal function is impaired in substantia nigra in Parkinson’s disease. Neurosci. Lett. 297:191–194. Merdes, A.R., Hansen, L.A., Jeste, D.V., et al. (2003) Influence of Alzheimer pathology on clinical diagnosis accuracy in dementia with Lewy bodies. Neurology 60:1586–1690. Miller, V.M., Kenny, R.A., Slade, J.Y., Oakley, A.E., and Kalaria, R.N. (2007) Medullary autonomic pathology of carotid sinus hypersensitivity. Neuropathol. Appl. Neurobiol. [Epub ahead of print]. Minguez-Castellanos, A., Chamorro, C.E., Escamilla-Sevilla, F., et al. (2007) Do alpha-synuclein aggregates in autonomic plexuses predate Lewy body disorders?: A cohort study. Neurology 68:2012– 2018. Minoshima, S., Foster, N.L., Sima, A.A., Frey, K.A., Albin, R.L., and Kuhl, D.E. (2001) Alzheimer’s disease versus dementia with Lewy bodies: cerebral metabolism distinction with autopsy confirmation. Ann. Neurol. 50:358–365. Molina, J.A., Gomez, P., Vargas, C., et al. (2005) Neurotransmitter amino acid in cerebrospinal fluid of patients with dementia with Lewy bodies. J. Neural Transm. 112:557–563. Molloy, S., McKeith, I.G., O’Brien, J.T., and Burn, D.J. (2005) The role of levodopa in the management of dementia with Lewy bodies. J. Neurol. Neurosurg. Psychiatry 76:1200–1203. Molloy, S., Rowan, E.N., McKeith, I.G., O’Brien, J.T., and Burn, D.J. (2006) The effect of levodopa on cognitive function in Parkinson’s disease with and without dementia and dementia with Lewy bodies. J. Neurol. Neurosurg. Psychiatry 77:1323–1328. Mosimann, U., Rowan, E., Partington, C., Collerton, D., et al. (2006) Characteristics of visual hallucinations in Parkinson’s disease dementia and dementia with Lewy bodies. Am. J. Geriatr. Psychiatry 14:154–160. Mosimann, U.P., Collerton, D., Dudley, R., Meyer, T.D., Graham, G., Dean, J.L., Bearn, D., Killen, A., Dickinson, L., Clarke, M.P., and McKeith, I.G. (2008) A semi-structured interview to assess visual hallucinations in older people. Int. J. Geriatr. Psychiatry [Epub ahead of print]. Mosimann, U.P., Mather, G., Wesnes, K.A., O’Brien, J.T., Burn, D.J., and McKeith, I.G. (2004) Visual perception in Parkinson disease dementia and dementia with Lewy bodies. Neurology 63:2091–2096. O’Brien, J.T., Colloby, S., Fenwick, J., Williams, E.D., Firbank, M., Burn, D., et al. (2004) Dopamine transporter loss visualized with FP-CIT SPECT in the differential diagnosis of dementia with Lewy bodies. Arch. Neurol. 61:919–925. O’Brien, J.T., Paling, S., Barber, R., et al. (2001) Progressive brain atrophy on serial MRI in dementia with Lewy bodies, AD, and vascular dementia. Neurology 56:1386–1388.

1029

O’Brien, J.T., Paling, S., Barber, R., Williams, E.D., Ballard, C., McKeith, I.G., Gholkar, A., Crum, W.R., Rossor, M.N., and Fox, N.C. (2001) Progressive brain atrophy on serial MRI in dementia with Lewy bodies, AD and vascular dementia. Neurology 56: 1386–1388. Ohara, K., Kondo, N., and Ohara, K. (1998) Changes of monoamines in post-mortem brains from patients with diffuse Lewy body disease. Pro. Neuro-Psychopharm. Biol. Psychiatry 22: 311–317. Oka, H., Yoshioka, M., Morita, M., Onouchi, K., Suzuki, M., Ito, Y., Hirai, T., Mochio, S., and Inoue, K. (2007) Reduced cardiac 123I-MIBG uptake reflects cardiac sympathetic dysfunction in Lewy body disease. Neurology 69(14):1460 –1465. Okazaki, H., Lipton, L.S., and Aronson, S.M. (1961) Diffuse intracytoplasmic ganglionic inclusions (Lewy type) associated with progressive dementia and quadraparesis in flexion. J. Neurol. Neurosurg. Psychiatry 20:237–244. Olson, E.J., Boeve, B.F., and Silber, M.H. (2000) Rapid eye movement sleep behaviour disorder: demographic, clinical and laboratory findings in 93 cases. Brain 123:331–339 Papapetropoulos, S., McCorquodale, D.S., Gonzalez, J., Jean-Gilles, L., and Mash, D.C. (2006) Cortical and amygdalar Lewy body burden in Parkinson’s disease patients with visual hallucinations. Parkinsonism Rel. Disord. 12:253–256. Park, J.Y., and Lansbury, P.T., Jr. (2003) Beta-synuclein inhibits formation of alpha-synuclein protofibrils: a possible therapeutic strategy against Parkinson’s disease. Biochemistry 42: 3696–3700. Perry, E.K., Court, J., Goodchild, R., Griffiths, M., Jaros, E., Johnson, M., Lloyd, S., Piggott, M., Spurden, D., Ballard, C., McKeith, I., and Perry, R. (1998) Clinical neurochemistry: developments in dementia research based on brain bank material. Journal of Neural Transmission (Budapest) 105:915–933. Perry, E.K., Curtis, M., Dick, D.J., et al. (1985) Cholinergic correlates of cognitive impairment in Parkinson’s disease: comparisons with Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 48:413–421. Perry, E.K., Kerwin, J., Perry, R.H., Irving, D., Blessed, G., and Fairbairn, A. (1990) Cerebral cholinergic activity is related to the incidence of visual hallucinations in senile dementia of Lewy body type. Dementia 1:2– 4. Perry, E.K., Marshall, E., Kerwin, J., et al. (1990) Evidence of a monoaminergic-cholinergic imbalance related to visual hallucinations in Lewy body dementia. J. Neurochem. 55:1454 –1456. Perry, E.K., Marshall, E., Perry, R.H., et al. (1990) Cholinergic and dopaminergic activities in senile dementia of Lewy body type. Alzheimer Dis. Assoc. Disord. 4:87–95. Perry, E.K., Marshall, E., Thompson, P., et al. (1993) Monoaminergic activities in Lewy body dementia: relation to hallucinosis and extrapyramidal features. J. Neural Transm. – Parkinson’s Dis. Dement. Sect. 6:167–177. Perry, E.K., Morris, C.M., Court, J.A., et al. (1995) Alteration in nicotine binding sites in Parkinson’s disease, Lewy body dementia and Alzheimer’s disease: possible index of early neuropathology. Neuroscience 64:385–395. Perry, E.K., Smith, C.J., Court, J.A., and Perry, R.H. (1990) Cholinergic nicotinic and muscarinic receptors in dementia of Alzheimer, Parkinson and Lewy body types. J. Neural Transm. – Parkinson’s Dis. Dement. Sect. 2:149–158. Perry, R.H., Irving, D., Blessed, G., Fairbairn, A., and Perry, E.K. (1990) Senile dementia of Lewy body type. A clinically and neuropathologically distinct form of Lewy body dementia in the elderly. J. Neurol. Sci. 95:119–139. Piggott, M.A., Ballard, C.G., Burn, D.J., Rowan, E., McKeith, I.G., Perry, R.H., Jaros, E., Perry, E.K. (in press) Dopamine transporter loss in Dementia with Lewy bodies and Parkinson’s Disease Dementia. Piggott, M.A., Ballard, C.G., Dickinson, H.O., McKeith, I.G., Perry, R.H., and Perry, E.K. (2007) Thalamic D2 receptors in dementia

1030

DEMENTIA

with Lewy bodies, Parkinson’s disease, and Parkinson’s disease dementia. Int. J. Neuropsychopharm. 10(2):231–244. Piggott, M.A., Ballard, C.G., Rowan, E., Holmes, C., McKeith, I.G., Jaros, E., Perry, R.H., and Perry, E.K. (2007) Selective loss of dopamine D2 receptors in temporal cortex in dementia with Lewy bodies, association with cognitive decline. Synapse 61(11):903–911. Piggott, M., Goodchild, R., Johnson, M., Ballard, C., and Perry, E. (2000, April) Serotonin receptor changes in dementing diseases of the elderly. Paper presented at the International Psychogeriatrics Association, Newcastle. Piggott, M.A., Marshall, E.F., Thomas, N., et al. (1999) Striatal dopaminergic markers in dementia with Lewy bodies, Alzheimer’s and Parkinson’s diseases: rostrocaudal distribution. Brain 122: 1449–1468. Piggott, M.A., Owens, J., O’Brien, J., et al. (2003) Muscarinic receptors in basal ganglia in dementia with Lewy bodies, Parkinson’s disease and Alzheimer’s disease. J. Chem. Neuroanat. 25:161–173. Piggott, M.A., Perry, E.K., Marshall, E.F., et al. (1998) Nigrostriatal dopaminergic activities in dementia with Lewy bodies in relation to neuroleptic sensitivity: comparisons with Parkinson’s disease. Biol. Psychiatry 44:765–774. Pimlott, S.L., Piggott, M., Ballard, C., McKeith, I., Perry, R., Kometa, S., Owens, J., Wyper, D., and Perry, E. (2006) Thalamic nicotinic receptors implicated in disturbed consciousness in dementia with Lewy bodies. Neurobiol. Dis. 21(1):50–56. Polymeropoulos, M.H., Higgins, J.J., Golbe, L.I., and Nussbaum, R.L. (1996) Mapping of a gene for Parkinson’s disease to chromosome 4q21-q23. Science 274:1197–1198. Ransmayr, G., Seppi, K., Donnemiller, E., et al. (2001) Striatal dopamine transporter function in dementia with Lewy bodies and Parkinson’s disease. Eur. J. Nucl. Med. 28:1523–1528. Ravina, B., Putt, M., Siderowf, A., et al. (2005) Donepezil for dementia in Parkinson’s disease: a randomised, double blind, placebo controlled, crossover study. J. Neurol. Neurosurg. Psychiatry 76:934–939. Reid, R.T., Sabbagh, M.N., Corey-Bloom, J., Tiraboschi, P., and Thal, L.J. (2000) Nicotinic receptor losses in dementia with Lewy bodies: comparisons with Alzheimer’s disease. Neurobio. Aging 21: 741–746. Saitoh, T., Xia, Y., Chen, X., Masliah, E., Galasko, D., Shults, C., Thal, L.J., Hansen, L.A., and Katzman, R. (1995) The CYP2D6B mutant allele is overrepresented in the Lewy body variant of Alzheimer’s disease. Ann. Neurol. 37:110–112. Samuel, W., Alford, M., Hofstetter, C.R., and Hansen, L. (1997) Dementia with Lewy bodies versus pure Alzheimer disease: differences in cognition, neuropathology, cholinergic dysfunction, and synapse density. J. Neuropath. Exp. Neurol. 56:499–508. Samuels, S.C., Brickman, A.M., Burd, J.A., Purohit, A.C., Quereshi, P.Q., and Serby, M. (2004) Depression in autopsy-confirmed dementia with Lewy bodies and Alzheimer’s disease. Mt. Sinai J. Med. 71:55–62. Schenck, C.H., Hurwitz, T.D., and Mahowlad, M.W. (1993) Normal and abnormal REM sleep regulation: REM sleep behaviour disorder: an update on a series of 96 patients and a review of the world literature. J. Sleep Res. 2:224–231. Schenck, C.H., and Mahowald, M.W. (2002) REM sleep behaviour disorder: clinical, developmental and neuroscience perspectives 16 years after its formal identification in sleep. Sleep 25:120 –138. Scott, H.L., Pow, D.V., Tannenberg, A.E., and Dodd, P.R. (2002) Aberrant expression of the glutamate transporter excitatory amino acid transporter 1 (EAAT1) in Alzheimer’s disease. J. Neurosci. 22:RC206. Scott, W.K., Grubber, J.M., Conneally, P.M., Small, G.W., Hulette, C.M., Rosenberg, C.K., Saunders, A.M., Roses, A.D., Haines, J.L., and Pericak-Vance, M.A. (2000) Fine mapping of the chromosome 12 late-onset Alzheimer disease locus: potential genetic and phenotypic heterogeneity. Am. J. Hum.Genet. 66:922–932.

Serpell, L.C., Berriman, J., Jakes, R., Goedert, M., and Crowther, R.A. (2000) Fiber diffraction of synthetic alpha-synuclein filaments shows amyloid-like cross-beta conformation. Proc. Natl. Acad. Sci. USA 97:4897– 4902. Sforza, E., Krieger, J., and Petiau, C. (1997) REM sleep behaviour disorder: clinical and physiopathological findings. Sleep Med. Rev. 1:57– 69. Sharon, R., Bar-Joseph, I., Frosch, M.P., et al. (2003) The formation of highly soluble oligomers of alpha-synuclein is regulated by fatty acids and enhanced in Parkinson’s disease. Neuron 37(4): 583–595. Sharp, S.I., Ballard, C.G., Ziabreva, I., Piggott, M.A., Perry, R.H., Perry, E.K., McKeith, I.G., Aarsland, D., Ehrt, U., Larsen, J.-P., and Paul T. Francis. Serotonin 1A receptor levels associated with depression in patients with Dementia with Lewy bodies and Parkinson’s disease dementia. Manuscript submitted for publication. Shea, C., MacKnight, C., and Rockwood, K. (1998) Donepezil for treatment of dementia with Lewy bodies: a case series of nine patients. Int. Psychogeriatr. 10:229–238. Shinotoh, H., Aotsuka, A., Ota, T., Tanaka, N., Fukushi, K., Nagatsuka, S., Tanada, S., and Ivie, T. (2001) Brain cholinergic function in dementia with Lewy bodies and Alzheimer’s disease measured by PET. Abstracts, Proc 5th Int Conference on Progress in PD and AD:74. Shiozaki, K., Iseki, E., Hino, H., and Kosaka, K. (2001) Distribution of M1 muscarinic acetylcholine receptors in the hippocampus of patients with Alzheimer’s disease and dementia with Lewy bodies-an immunohistochemical study. J. Neurol. Sci. 193:23–28. Shiozaki, K., Iseki, E., Uchiyama, H., et al. (1999) Alterations of muscarinic acetylcholine receptor subtypes in diffuse Lewy body disease: relation to Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry 67:209–213. Simard, M., van Reekum, R., and Cohen, T. (2000) A review of the cognitive and behavioural symptoms in dementia with Lewy bodies. J. Neuropsychiatry Clin. Neurosci. 12:425– 450. Spillantini, M.G., Crowther, R.A., Jakes, R., Hasegawa, M., and Goedert, M. (1998) Alpha-synuclein in filamentous inclusions of Lewy bodies from Parkinson’s disease and dementia with Lewy bodies. Proc. Natl. Acad. Sci. USA 95:6469–6473. Spillantini, M.G., Schmidt, M.L., Lee, V.M., Trojanowski, J.Q., Jakes, R., and Goedert, M. (1997) Alpha-synuclein in Lewy bodies. Nature 388:839–840. Stefanova, N., Emgård, M., Klimaschewski, L., et al. (2002) Ultrastructure of alpha-synuclein-positive aggregations in U373 astrocytoma and rat primary glial cells. Neurosci Lett. 323(1):37– 40. Strittmatter, W.J., Saunders, A.M., Schmechel, D., Pericak-Vance, A.M., Enghild, J., Salvesen, G.S., and Roses, A.D. (1993) Apolipoprotein E: high avidity binding to b-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer’s disease. Proc. Natl. Acad. Sci. USA 90:1977–1981. Suzuki, M., Desmond, T.J., Albin, R.L., and Frey, K.A. (2002) Striatal monoaminergic terminals in Lewy body and Alzheimer’s dementias. Ann. Neurol. 51:767–771. Sweet, R.A., Hamilton, R.I., Butters, M.A., Mulsant, B.H., Pollock, B.G., Lewis, D.A., Lopez, O.I., DeKosky, S.T., and Reynolds, C.F. (2004) Neuropathologic correlates of late-onset major depression. Neuropsychopharmacology 29:2242–2250. Szot, P., White, S.S., Greenup, J.L., Leverenz, J.B., Peskind, E.R., and Raskind, M.A. (2006) Compensatory changes in the noradrenergic nervous system in the locus ceruleus and hippocampus of postmortem subjects with Alzheimer’s disease and dementia with Lewy bodies. J. Neurosci. 26:467– 478. Taylor, A.E., Yip, A., Brayne, C., Easton, D., Evans, J.G., Xuereb, J., Cairns, N., Esiri, M.M., and Rubinsztein, D.C. (2001) Genetic association of an LBP-1c/CP2/LSF gene polymorphism with late onset Alzheimer’s disease. J. Med. Genet. 38:232–233. Teaktong, T., Piggott, M.A., McKeith, I.G., Perry, R.H., Ballard, C., and Perry, E. (2005) Muscarinic M2 and M4 receptors in ante-

62: DEMENTIA WITH LEWY BODIES rior cingulate cortex: relation to neuropsychiatric symptoms in dementia with Lewy bodies. Behav. Brain Res. 161:299–305. Thaisetthawatkul, P., Boeve, B.F., Benarroch, E.E., Sandroni, P., Ferman, T.J., Petersen, R., and Low, P.A. (2004) Autonomic dysfunction in dementia with Lewy bodies. Neurology 62:1804–1809. Thorns, V., Mallory, M., Hansen, L., and Masliah, E. (1997) Alterations in glutamate receptor 2/3 subunits and amyloid precursor protein expression during the course of Alzheimer’s disease and Lewy body variant. Acta Neuropathol. 94:539–548. Tiraboschi, P., Hansen, L.A., Alford, M., et al. (2000) Cholinergic dysfunction in diseases with Lewy bodies. Neurology 54:407– 411. Tiraboschi, P., Hansen, L.A., Alford, M., et al. (2002) Early and widespread cholinergic losses differentiate dementia with Lewy bodies from Alzheimer disease. Arch. Gen. Psychiatry 59:946 –951. Tiraboschi, P., Salmon, D.P., Hansen, L.A., Hofstetter, R.C., Thal, L.J., and Corey-Bloom, J. (2006) What best differentiates Lewy body from Alzheimer’s disease in early stage dementia. Neurology 129:729 –735. Tsigelny, I.F., Bar-On, P., Sharikov, Y., Crews, L., Hashimoto, M., Miller, M., Keller, S.H., Platoshyn, O., Yuan, J.X.-Y., and Masliah, E. (2007) Dynamics of a-synuclein aggregation and inhibition of pore-like oligomer development by b-synuclein. FEBS J. 274: 1862–1877. Turner, R.S., D’Amato, C.J., Chervin, R.D., and Blaivas, M. (2000) The pathology of REM sleep behavior disorder with comorbid Lewy body dementia. Neurology 55:1730–1732. Uchiyama, M., Isse, K., Tanaka, K., et al. (1995) Incidental Lewy body disease in a patient with REM sleep behavior disorder. Neurology 45:709–712. Uryu, K., Richter-Landsberg, C., and Welsh, W. (2006) Convergence of heat shock protein 90 with ubiquitin in filamentous alphasynuclein inclusions of alpha-synucleinopathies. Am. J. Pathol. 168:947–961. Uversky, V. (2007) Neuropathology, biochemistry and biophysics of a-synuclein aggregation. J. Neurochem. 103:17–37. Uversky, V.N., Li, J., Souillac, P., Millett, I.S., Doniach, S., Jakes, R., Goedert, M., and Fink, A. (2002) Biophysical properties of the synucleins and their propensities to fibrillate: inhibition of alphasynuclein assembly by beta and gamma-synucleins. J. Biol. Chem. 277:11970–11978. Wakabayashi, K., Hayashi, S., Ishikawa, A., Hayashi, T., Okuizumi, K., Tanaka, H., Tsuji, S., and Takahashi, H. (1998) Autosomal dominant diffuse Lewy body disease. Acta Neuropathol. (Berl) 96:207–210. Wakamatsu, M., Ashii, A., Iwata, S., Sakagami, J., Ukai, Y., Ono, M., Kanbe, D., Muramatsu, S., Kobayashi, K., Iwatsubo, T., and Yoshimoto, M. (2007) Selective nigral dopamine neurons induced by overexpression of truncated human a-synuclein in mice. Neurobiol Aging 29(4):574 –585. Walker, M.P., Ayre, G.A., Cummings, J.L., Wesnes, K., McKeith, I.G., O’Brien, J.T., and Ballard, C.G. (2000a) The Clinician Assessment of Fluctuation and the One Day Fluctuation Assessment Scale. Two methods to assess fluctuating confusion in dementia. Br. J. Psychiatry 177:252–256. Walker, M.P., Ayre, G.A., Cummings, J.L., Wesnes, K., McKeith, I.G., O’Brien, J.T., and Ballard, C.G. (2000b) Quantifying fluctuation in dementia with Lewy bodies, Alzheimer’s disease, and vascular dementia. Neurology 54:1616–1624. Walker, Z., Grace, J., Overshot, R., Satarasinghe, S., Swan, A., Katona, C.L., and McKeith, I.G. (1999) Olanzapine in dementia with Lewy bodies: a clinical study. Int. J. Geriatr. Psychiatry 14: 459– 466. Walker, Z., Costa, D.C., Ince, P., McKeith, I.G., and Katona, C.L. (1999) In-vivo demonstration of dopaminergic degeneration in

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dementia with Lewy bodies. Lancet 354:646 – 647. Walker, Z., Costa, D.C., Janssen, A.G., Walker, R.W., Livingstone, G., and Katona, C.L. (1997) Dementia with Lewy bodies: a study of post-synaptic dopaminergic receptors with iodine-123 iodobenzamide single-photon emission tomography. Eur. J. Nucl. Med. 24:609– 614. Walker, Z., Costa, D.C., Walker, R.W., Lee, L., Livingston, G., Jaros, E., Perry, R., McKeith, I.G., and Katona, C.L. (2004) Striatal dopamine transporter in dementia with Lewy bodies and Parkinson disease A comparison. Neurology 62:1568 –1572. Walker, Z., Costa, D.C., Walker, R.W.H., et al. (2002) Differentiation of dementia with Lewy bodies from Alzheimer’s disease using a dopaminergic presynaptic ligand. J. Neurol. Neurosurg. Psychiatry 73:134 –140. Walker, Z., Jaros, E., Walker, R.W.H., Lee, L., Costa, D.C., Livingston, G., Ince, P.G., Perry, R., McKeith, I., and Katona, C.L.E. (2007) Dementia with Lewy bodies: a comparison of clinical diagnosis, FP-CIT single photon emission computed tomography imaging and autopsy. J. Neurol. Neurosurg. Psychiatry 78(11):1176 –1181. Warren, N.M., Piggott, M.A., Lees, A.J., and Burn, D.J. (2007) Muscarinic receptors in the thalamus in progressive supranuclear palsy and other neurodegenerative disorders. J. Neuropathol. Exp. Neurol. 66(5):399– 404. Warren, N.M., Piggott, M.A., Lees, A.J., Perry, E.K., and Burn, D.J. (2008) Intact coupling of M1 receptors and preserved M2 and M4 receptors in the cortex in progressive supranuclear palsy: contrast with other dementia. J. Chem. Neuroanat. 35(3):268–274. Wei, J., Fujita, M., Nakai, M., Waragai, M., Watabe, K., Akatsu, H., Rockenstein, E., Masliah, E., and Hashimoto, M. (2007) Enhanced lysosomal pathology caused by b-synuclein mutants linked to dementia with Lewy bodies. J. Biol. Chem. 282:28904–28914. Welsman, D., Cho, M., Taylor, C., Adams, A., Thal, L.J., and Hansan, L.A. (2007) In dementia with Lewy bodes, Braak stage determines phenotype, not Lewy body distribution. Neurology 69:356–359. Wetter, T.C., Collado-Seidel, V., Pollmacher, T., Yassouridis, A., and Trenkwalder, C. (2000) Sleep and periodic leg movement patterns in drug-free patients with Parkinson’s disease and multiple system atrophy. Sleep 23:361–367. Whitwell, J.L., Weigand, S.D., Shiung, M.M., Boeve, B.F., Ferman, T.J., et al. (2007) Focal atrophy in dementia with Lewy bodies on MRI: a distinct pattern from Alzheimer’s disease. Brain 130: 708–719. Yamamoto, R., Iseki, E., Murayama, N., Minegishi, M., Marui, W., Togo, T., Katsuse, O., Kosaka, K., Kato, M., Iwatsubo, T., and Arai, H. (2007) Correlation in Lewy pathology between the claustrum and visual areas in brains of dementia with Lewy bodies. Neurosci Lett. 415:219–224. Yoshita, M., Taki, J., Yokoyama, K., Noguchi-Shinohara, M., Matsumoto, Y., Nakajima, K., and Yamada, M. (2006) Value of 123I-MIBG radioactivity in the differential diagnosis of DLB from AD. Neurology 66:1850–1854. Zaja-Milatovic, S., Keene, C.D., Montine, K.S., Leverenz, J.B., Tsuang, D., and Montine, T.J. (2006) Selective dendritic degeneration of medium spiny neurons in dementia with Lewy bodies. Neurology 66:1591–1593. Zaja-Milatovic, S., Milatovic, D., Schantz, A.M., et al. (2005) Dendritic degeneration in neostriatal medium spiny neurons in Parkinson disease. Neurology 64:545–547. Zweig, R.M., Cardillo, J.E., Cohen, M., Giere, S., and Hedreen, J.C. (1993) The locus ceruleus and dementia in Parkinson’s disease. Neurology 43:986 –991. Zweig, R.M., Jankel, W.R., Hedreen, J.C., Mayeux, R., and Price, D.L. (1989) The pedunculopontine nucleus in Parkinson’s disease. Ann. Neurol. 26:41– 46.

63 Dementia in Parkinson’s Disease MARTIN GOLDSTEIN

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Parkinson’s disease (PD) is an age-related neurodegenerative disorder that is clinically characterized primarily by motor dysfunction. The cardinal features are resting tremor, rigidity, bradykinesia, and gait dysfunction with postural disturbances. Pathologically, the hallmark of PD is degeneration of dopaminergic (DA-ergic) neurons in the substantia nigra pars compacta (SNc), intracellular protein aggregates in affected neurons known as Lewy bodies (LBs), and a consequent loss of DA-ergic input to the striatum as well as other basal ganglia, thalamic, and cerebral regions (Olanow et al., 2001). Although interest has traditionally focused on motor dysfunction, nonmotor features are increasingly recognized as intrinsic components of PD phenomenology (Poewe, 2007). Among the most important of these nonmotor features is cognitive dysfunction, which is common (Caballol et al., 2007) and can progress to meet clinical criteria of dementia (Goldmann Gross et al., 2008). Indeed, PD-related cognitive disturbances can profoundly affect occupational and social adaptation (Alpert et al., 1990; Dubinsky et al., 1991; Goetz et al., 1995), comprise a major source of disability (Ahlskojg, 2007; Green and Camicioli, 2007), worsen prognosis (Goetz et al., 1995; Aarsland et al., 1996; Litvan, 1998; Aarsland et al., 2000), and shorten survival (Ebmeir et al., 1990a; Louis et al., 1997; Fernandez and Lapane, 2002; Levy, Tang, Louis, et al., 2002). To enhance awareness and clarify terminology, the Movement Disorder Society recently introduced standardized diagnostic criteria (Emre et al., 2007) and assessment strategies (Dubois et al., 2007) that hopefully will be incorporated into the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-V). This review focuses on PD-related cognitive dysfunction and contrasts the clinical, neuropsychological, and pathological features of the dementia that occurs in PD with those associated with other major neurodegenerative disease states. NOSOLOGY Although Parkinson’s disease with dementia (PDD) is a common clinical term, its emergence as a well-defined syndrome remains incomplete, and clinicopathologic definitions remain poorly operationalized (McKeith, 2007). 1032

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Even nosologic characterization of cognitive dysfunction in PD represents a layered challenge. First, cognitive dysfunction in PD can be multifactorial, as detailed in Figure 63.1. Second, standard treatments for PD can negatively affect cognitive function. Third, comorbidity with other age-associated dementias (for example, cerebrovascular disease, Alzheimer’s disease, etc.) is common and can be significant (Leibson et al., 2006). Fourth, the distinction between PDD and dementia with Lewy bodies (DLB) can be difficult (Boeve, 2007); indeed, the distinction between PDD and DLB is somewhat arbitrary, and it remains unclear if they are different disorders or merely variations of a single disease spectrum (Lippa et al., 2007). EPIDEMIOLOGY Parkinson’s disease is the second most common neurodegenerative disorder after Alzheimer’s disease (AD), affecting up to 1% of individuals older than the age of 60 years (Tanner and Goldman, 1996; Khandhar and Marks, 2007). In his original monograph, James Parkinson noted that cognition and behavior were unaffected (Parkinson, 1817). The presence of cognitive disturbances in PD was recognized by Charcot (1877) (who was also the first to apply the term Parkinson’s disease), and it is now known that cognitive dysfunction commonly occurs in PD (Caballol et al., 2007; Goldmann Gross et al., 2008). Indeed, up to 90% of patients with PD eventually develop cognitive deficits, and a large percentage of these patients progress to frank dementia (Aarsland et al., 2003). Epidemiologic recognition that cognitive dysfunction, including dementia, is widely prevalent in PD has been a principal driving force for the increasing attention that has focused on the nonmotor aspects of PD (McKeith, 2007). Indeed, long-term follow-up studies of patients with PD indicate that dementia and other non-DA features are the primary source of disability (Hely et al., 2005). The reported incidence and prevalence of cognitive dysfunction in PD vary considerably. This is likely at least in part due to heterogeneities of the patient populations studied, the methodology used to assess cognitive function, and the criteria for diagnosing dementia that

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63.1 Multi-factorial conversion of Parkinson’s disease to Parkinson’s disease with dementia.

FIGURE

were employed (Brown and Marsden, 1984; Boyd et al., 1991; Ebmeier et al., 1991; Pillon et al., 1991; Emre et al., 2007). For example, PDD prevalence has conventionally been studied in hospital clinic–based populations, which consequently limits the generalizability of the data (Emre et al., 2007). Prevalence of dementia among patients with PD was long thought to be about 25% (McKeith, 2007), an estimate influenced by the predominance of movement disorder clinic settings of many studies. However, patients with PD with cognitive impairment may be cared for at a memory clinic or in an institutional care setting and are thus excluded from movement disorder clinic–based prevalence estimates (McKeith, 2007), yielding an artifactually low estimate of PDD. Also, early studies often did not distinguish patients with PDD from patients with DLB (Cummings et al., 1988; Emre et al., 2007), perhaps correctly. Further, PD-related dementia has historically been defined using criteria developed for AD, which may be insensitive to the dementia that occurs in PD and again yielding artificially low prevalence estimates. These types of confounds should be reduced by the establishment of PDD-specific diagnostic criteria (Emre et al., 2007). Nonetheless, despite epidemiologic challenges, data indicate that intellectual impairment meeting standardized criteria for dementia is common in PD, particularly in the later stages of the disease (Elizan et al., 1986; Ebmeier et al., 1991; Biggins et al., 1992; Lieberman, 1998; Caballol et al., 2007; Goldmann Gross et al., 2008). In a seminal review, Cummings (1988) analyzed 27 studies representing over 4,000 patients with PD and found a mean dementia prevalence of 40%. Mayeux et al. (1992) performed a community-based population study and found that 41.3% of patients with PD had dementia (Mayeux et al., 1992). In a meta-analysis,

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Aarsland et al. (2005) noted that there was a dementia prevalence of 31.5% among patient populations with PD. They further determined that up to 4% of dementia cases in the general population were due to PDD (Aarsland et al., 2005). They estimated the prevalence of PDD in the general population aged 65 and older to be 0.2%–0.5% (Aarsland et al., 2005). Other studies have reported prevalence rates for dementia among patients with PD of 48% (Hobson and Meara, 2004), 23% (Athey et al., 2005), and 22% (de Lau et al., 2005). Interestingly, even among patients with newly diagnosed PD, the dementia prevalence has been reported as being up to 17% (Foltynie et al., 2004; Kang et al., 2005). Overall, estimates place the prevalence of dementia in PD at 6 times that of age-matched controls (Mayeux et al., 1992; Poewe, 2006; Emre et al., 2007; McKeith, 2007). Due to the higher mortality rate of PDD relative to patients with PD (Levy, Tang, Louis, et al., 2002), the extent of dementia may be underestimated by prevalence surveys (Mayeux et al., 1990; Marder et al., 1991). More informative data is therefore derived from longitudinal studies affording incidence estimates (Emre et al., 2007). Community-based studies have reported yearly dementia incidence rates of approximately 10% among patients with PD, and relative risks of developing dementia up to 5.9% in comparison to patients with no PD (Aarsland et al., 2001; Hobson et al., 2005; Rippon and Marder, 2005). In a controlled longitudinal study of the incidence of dementia among patients with PD, Biggins et al. (1992) found that 19% of patients with PD developed dementia over a 4½-year period. Patients with PD who developed dementia tended to be older at time of disease onset and to have a longer duration of PD than those who did not develop dementia. Similar results have been reported in a longitudinal cohort study (Williams-Gray et al., 2007), a case-control study (Rajput et al., 1984), and a hospital-based study (Mayeux et al., 1990). Cumulative incidence rates for dementia among patients with PD in carefully performed studies have been reported to be as high as 80% (Aarsland et al., 2003; Burton et al., 2004). Reid et al. (1996) prospectively followed patients with newly diagnosed PD to assess dementia incidence. They observed that 28% of patients developed dementia after 5 years (Reid et al. 1996). Aarsland et al. (2003) found a 78% cumulative prevalence of dementia in PD after 8 years. In this study, a prominent age effect was observed, with dementia prevalence increasing from 12.4% in the 50- to 59-year age group, to 68.7% in those older than 80 years of age. The mean time course from the onset of PD to development of dementia varies in different studies, ranging between 3 years (WilliamsGray et al., 2007) and 10 years from diagnosis (Hughes et al., 2000; Aarsland et al., 2003). This corresponded to an annual dementia incidence of 30.0 per 1,000 person-years (Williams-Gray et al., 2007).

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DEMENTIA

Although more contemporary prevalence rates of PDD are high in comparison to older studies, they may still underestimate the extent of cognitive impairment in PD. Potential confounds include sampling problems, lack of appropriate controls, use of variable diagnostic criteria, and failure to consider premorbid intelligence. Also, patients with PD are traditionally managed by neurologists who focus on motor dysfunction and place less emphasis on the detection and reporting of behavioral phenomenology. NEUROPATHOLOGY AND PATHOPHYSIOLOGY OF PDD Although the precise pathophysiology of cognitive dysfunction in PD remains incompletely understood, scientific advances are yielding increasing insights (Calabresi et al., 2006). It was long thought that much, if not all, dementia in PD was coincidental with brain aging or concomitant AD. However, the realization that patients with PD have a much higher risk of developing dementia than age-matched controls made this theory inadequate (McKeith, 2007). That PDD can incorporate a dysexecutive syndrome, an amnestic “Alzheimer-like” profile (less common), and/or a DLB-like pattern further suggests multifactorial contributors to the development of PDD. The characteristic neuropathologic feature of PD is degeneration of nigro-striatal DA-ergic neurons coupled with intracellular proteinaceous inclusions known as LBs (Agid et al., 1987; Jellinger, 1987). Within the SNc there is specific involvement of ventro-lateral neurons with relative sparing of DA neurons in the more medial ventral tegmental area (Fearnley and Lees, 1991). With the advent of ubiquitin and α-synuclein staining, it is now appreciated that pathology in PD is extensive (Uversky, 2007). Neuronal loss, frequently associated with LBs, can be found in epinephrine neurons of the locus coeruleus (LC), cholinergic (ACh-ergic) neurons of the nucleus basalis of Meynert (NBM), serotonin neurons of the midline raphé, in the olfactory areas, and in multiple regions of the cerebral hemisphere, brain stem, spinal cord, and peripheral autonomic system (Braak et al., 2006a; Braak et al., 2006b). Indeed, recent studies by Braak and colleagues (Braak et al., 2003; Braak, et al., 2006a) suggest that degeneration in non-DA-ergic regions of the lower brain stem (dorsal motor nucleus of the vagus) and olfactory system precede DA-ergic pathology. Lewy body pathology in cortical and mesocortical regions is thought to represent the principal pathological correlate of dementia in PD (Hurtig et al., 2000; Emre et al., 2007). Parkinson’s disease with dementia can also be associated with AD-type pathology (that is, senile plaques [SPs] and neurofibrillary tangles [NFTs])

FIGURE 63.2 Converging neuropathologic relationship of Parkinson’s disease with dementia (PDD) and dementia with Lewy bodies (DLB).

that occurs more frequently than in the general populations; McKeith (2007) has suggested a pathologic probability matrix, depicted in Figure 63.2, to help conceptualize these different pathologic processes. Cognitive Impairment Secondary to Nigro-Striatal-Frontal Dysfunction The primary pathologic defect of PD, nigro-striatal DA neuron loss, can lead to dysfunction in striato-frontal loops yielding a variety of cognitive defects (Zgaljardic et al., 2003; Owen, 2007). Although detailed understanding of how nigro-striatal-frontal pathophysiology produces PD-related cognitive impairment remains elusive, broad categories of executive dysfunction represent the core cognitive feature of PD (Alexander et al., 1986; Cummings, 1995; Tinaz et al., 2008). Parkinson’s disease–related cognitive dysfunction suggests involvement of each of the major prefrontal cortico-subcortical circuit domains. For example, PDD phenomenology includes semantic, working memory, and task control deficiencies (implicating dorsolateral prefrontal dysfunction), inhibitory dyscontrol (implicating orbitofrontal dysfunction), and initiative/agency failure (implicating medial frontal dysfunction), among other defects (Cummings, 1995; Mesulam, 2000; Frank et al., 2007). Functional neuroimaging offers significant potential for elucidating the specific frontostriatal substrates that underlie the individual PDD clinical features (Monchi et al., 2007). Neurotransmitter Systems Implicated in PD-Related Neuropsychiatric Dysfunction Extensive efforts have been made to characterize neurotransmitter profiles associated with cognitive impairment in PD (Francis and Perry, 2007). Dopamine and

63: DEMENTIA IN PARKINSON’S DISEASE

non-DA systems are affected in PD, including serotonergic (Ser-ergic) neurons in the median raphé, noradrenergic (norepinephrine [NE]-ergic) neurons in the LC, and ACh-ergic neurons in the NBM (Agid et al., 1987; Braak et al., 2006a: Braak et al., 2006b). Speculations as to the basis of such multitransmitter system pathology include excitotoxic damage in targets of the subthalamic nucleus whose glutamatergic neurons are overactive in PD (Rodriguez et al., 1998). Dopamine system The reduction in striatal DA secondary to degeneration of SNc DA neurons correlates with, and to a large extent is responsible for, the motor abnormalities that characterize PD. It should be appreciated that the SNc also provides DA-ergic innervation to the entire basal ganglia complex, and portions of the thalamus and cerebral cortex, particularly frontal areas (Parent et al., 2000; Smith and Kieval, 2000). Increasing attention is being devoted to the role of DA depletion in nonmotor aspects of PD, including sleep disturbance, affective dysregulation, and cognitive impairment (Bédard et al., 1998; Brooks and Piccini, 2006; Calabresi et al., 2006; Chaudhuri et al., 2006; Cropley et al., 2006). Extensive animal model, neuropathologic, neurophysiologic, and functional neuroimaging data indicate that DA systems are involved in a myriad of neuropsychological functions, and that DA depletion as occurs in PD can lead to a variety of behavioral disorders (El-Ghundi et al., 2007). The negative symptomatology of schizophrenia (for example, apathy, affective blunting, cognitive slowing) that is thought to be related to DA inhibition offers potential insights into the pathophysiology of dementia in PD (Fournet et al., 2000). Dopamine excess can also be associated with multiple cognitive and behavioral derangements (for example, schizophrenia, amphetamine-induced psychosis, etc.) (Taylor et al., 1990; Zahrt et al., 1997; Goldman-Rakic, 1998, 1999). In PD, DA depletion and iatrogenic DA excess represent potential contributors to the neuropsychiatric dysfunction that can be seen in this disorder (Burn and Troster, 2004). Norepinephrine (NE) system The NE system is involved in multiple cognitive and affective functions (Ramos and Amsten, 2007). Many psychotropic agents function via noradrenergic mechanisms, and abnormal increases and decreases in NE activity can adversely affect cognitive function (Ordway and Klimek, 2001). Norepinephrine activity changes in the prefrontal cortex can especially affect prefrontally mediated executive processes (Arnsten et al., 1999; Birnbaum et al., 1999). Extensive data implicate noradrenergic alterations in PD as a contributing factor that leads

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to neurobehavioral and cognitive dysfunction in PD (Agid et al., 1987; Brooks, 1998; Emre, 2003; Bosboom et al., 2004). Serotonin (5-HT) system Considerable data implicate 5-HT systems in affective regulation, impulse control, and aggression (Wrase et al., 2006). Derangements of 5-HT system function have been detected in PD (Kish, 2003; Kish et al., 2008), with the potential to significantly contribute to neuropsychological dysfunction in these domains (Chamberlain et al., 2006; Alex and Pehek, 2007). Further, decarboxylase activity in 5-HT neurons may facilitate conversion of exogenously administered levodopa (LD) to DA (Yamada et al., 2007) and thereby perhaps contribute to cognitive dysfunction associated with changes in DA availability. For all of these reasons, there has been increasing interest in the role of 5-HT in the neurobehavioral features of PD. Cholinergic (ACh) system Cholinergic systems play a crucial role in cognitive function, especially memory processes (Cooper et al., 1992). Cholinergic system involvement in the pathogenesis of cognitive dysfunction in AD has directed attention to these systems in patients with PDD (Contestabile et al., 2007), where prominent degeneration is detected in the NBM, the primary source of cholinergic input to the cerebral cortex. The dynamic relationship between DA and ACh has long been a focus of pathophysiologic attention in PD (Calabresi et al., 2006; Schliebs and Arendt, 2006), prompting the early introduction of anticholinergic agents as a treatment for PD. Indeed, such therapies have long been known to adversely affect cognitive function, and these drugs are contraindicated in patients with PD with cognitive dysfunction (Olanow et al., 2001). Interest in the ACh–DA balance has been renewed, with the increasing focus on cognitive dysfunction in PD and the identification of numerous cholinergic neuronal subtypes that might have different functional effects (Calabresi et al., 2006). In fact, cholinergic deficits may be more pronounced in PD than in AD and may occur at an earlier stage of the disease (Bohnen and Frey, 2007). Recent data have demonstrated the clinical utility of cholinesterase inhibitors for PDD (Emre et al., 2004; Cummings and Winblad, 2007). Cognitive Dysfunction Secondary to Iatrogenic Complications of PD Medications used to treat PD have complex cognitive effects that remain incompletely understood. Antiparkinsonian drugs can improve and adversely influence cognitive function.

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Anti-ACh agents Anticholinergic activity can impair cognitive function and even cause delirium, especially in the elderly (Koller, 1984; Van Spaendonck et al., 1993; Bédard et al., 1999). Anti-ACh agents (for example, benztropine, trihexyphenidyl) have been long known to be associated with cognitive impairment in PD. For example, in a controlled study of patients with PD, 2 weeks of treatment with the anti-ACh agent trihexyphenidyl caused executive deficits (Bédard et al., 1999), and 4 months of treatment resulted in impaired short-term memory (Cooper et al., 1992). As these drugs typically have minimal antiparkinsonian effects (mostly acting only on tremor), they are rarely employed in the modern era and contraindicated in patients with impaired cognitive functions and the elderly (Olanow et al., 2001). Dopamine agents Dopaminergic anti-PD agents have complicated effects on cognitive performance (Molloy et al., 2006; Schultz, 2007a, 2007b). In the early stages of PD, LD can potentially improve select cognitive functions, with variable reports of improvement in wakefulness, verbal fluency, working memory, conditional learning, and cognitive sequencing, as well as reductions in perseveration and global bradyphrenia (Gotham et al., 1988; Cooper et al., 1992; Owen, Roberts, et al., 1993; Cools, 2006; McNamara and Durso, 2006). It has been suggested that one of the ways that LD might ameliorate some high-level cognitive deficits in PD is by inducing increased perfusion to the dorsolateral prefrontal cortex (Cools et al., 2001b; Cools et al., 2002). However, DA-ergic agents also have the potential to cause a wide range of neurobehavioral abnormalities especially when used in more advanced stages of the illness, at higher dosages, and/or in the elderly (Cools et al., 2001b; Olanow et al., 2001; Cools, 2006). Anti-PD surgery Surgical treatments are now widely employed in the management of patients with advanced PD (Olanow and Brin, 2001). Striking clinical benefits have been observed in patients who have failed medical therapy, particularly with disability related to motor complications. Ablative lesions for PD (for example, pallidotomy and thalamotomy) have been largely replaced by deep brain stimulation (DBS) because of the increased safety of the latter and a reduced risk of inducing side effects associated with brain lesions (particularly bilateral brain lesions). However, DBS typically involves multiple needle passes through the brain to precisely identify the desired brain target and can induce cognitive impairment, especially in those with preexisting dysfunction (Appleby

et al., 2007). Neuropsychological screening to exclude patients with cognitive impairment is now recommended. Ablative procedures Cognitive dysfunction following surgical lesions relate to the site and size of the lesion, and whether procedures are performed bilaterally or unilaterally (Lombardi et al., 2000; Trépanier et al., 2000). Nonlateralizing attentional and hemisphere-specific impairments of frontostriatal cognitive function can follow unilateral ablative procedures (Trépanier et al., 2000). A dysexecutive syndrome coupled with behavioral changes of a “frontal nature” has been reported in up to 30% of patients with PD following unilateral pallidotomy (Trépanier et al., 1998). Left-sided pallidotomy is associated with impaired verbal learning and verbal fluency, whereas rightsided pallidotomy causes a loss of visuospatial constructional abilities, which frequently persist (Trépanier et al., 2000). Reports of adverse effects are even more common after bilateral pallidotomy (Parkin et al., 2002), which can include a wide range of neuro-behavioral dysfunctions including affective (depression), comportmental (for example, abulia), impulse control (for example, obsessive–compulsive disorder [OCD]), and assorted cognitive disturbances (for example, apraxias) as well as dysphagia, and dysphonia. Accordingly, physicians have been reluctant to recommend bilateral pallidotomies even to patients who are cognitively intact and with bilateral PD symptoms (Ghika et al., 1999; Olanow and Brin, 2001). Deep brain stimulation (DBS). Deep brain stimulation has become the surgical procedure of choice for PD (Olanow et al., 2001). High-frequency stimulation simulates the effect of a lesion without necessitating the production of a destructive lesion (Obeso et al., 2001). Deep brain stimulation also permits the performance of bilateral procedures with relative safety, and the targeting of relevant brain structures such as the subthalamic nucleus (STN) that physicians have been reluctant to lesion because of the risk of a potentially fatal hemiballismus (Obeso et al., 2001). This procedure also permits periodic readjustment of stimulator settings to maximize benefits and minimize adversity, and stimulation can be stopped in the case of undesired adverse events. Cognitive aspects of DBS represent an area of intense study for a variety of reasons. First, DBS has become an important therapy for PD. Second, DBS carries the potential for multifactorial cognitive complications (Voon et al., 2006). For example, immediate cognitive sequelae can result from the multiple needle passes through the frontal lobes required to precisely identify the target site and to place the permanent electrode. More important, however, are the ongoing neuro-behavioral effects asso-

63: DEMENTIA IN PARKINSON’S DISEASE

ciated with continued stimulation, which, though widely commented upon, remain poorly defined (Appleby et al., 2007). For example, stimulation in the region of the STN can lead to profound depression with increased suicide rates, transient periods of uproarious laughter, and impulse control dysfunction (see below). Finally, the evolving application of DBS for the treatment of a range of neuropsychiatric disorders such as depression and OCD (Wichamann and DeLong, 2006) has further prompted curiosity about the neurobehavioral effects of stimulating a variety of brain targets. Immediate and evolving long-term cognitive effects of PD can be complicated by any preexisting neurobehavioral dysfunction; this has prompted recommendations that neuropsychological assessment be an essential component of evaluation for a DBS procedure (Okun et al., 2007). Unilateral thalamic stimulation is relatively well tolerated (Woods et al., 2001), but this procedure is now rarely employed because superior results are obtained with DBS-STN or globus pallidus pars interna (GPi). The cognitive effects of unilateral or bilateral DBS-GPi remain somewhat controversial (Ardouin et al., 1999; Fields et al., 1999; Saint-Cyr et al., 2000). One group found no evidence of impairment following bilateral DBS-GPi on a full battery of neuropsychological tests (Fields et al., 1999). In fact, they reported significant improvement in delayed recall, as well as subjective anxiolysis. In contrast, another study observed deterioration in lexical fluency following DBS-GPi (Ardouin et al., 1999). Relative to DBS-STN, patients who have DBS-GPi have been noted to have a higher suicide rate (Appleby et al., 2007). Nonetheless, in a study of patients with DBS-GPi, Rodrigues et al. (2007) found improved quality of life measures, including cognition. Deep brain stimulation-STN has emerged as the predominant surgical treatment modality, and there is increasing focus on the cognitive sequelae for this procedure (Aybek et al., 2007). An early study investigating cognitive aspects of DBS-STN found improved performance on the random number generation test, Wisconsin Card Sorting Test, and on paced serial addition and missing digit tests, but that performance worsened conditional associative learning (Jahanshahi et al., 2000). Morrison et al. (2000) designed a neuropsychological program to try to distinguish the cognitive effects of surgical implantation from stimulation in patients undergoing bilateral DBS-STN. In a study of 17 patients, they demonstrated that the surgical procedure itself adversely affected attention and concentration and tended to adversely affect verbal learning, naming, and verbal fluency (Morrison et al., 2004). No detectable adverse effects on cognition or depression were associated with stimulation (Morrison et al., 2004). Pillon et al. (2000) also tried to discriminate the acute effects on cognition of surgical implantation from those of chronic STN stimulation. They reported no impairment of memory

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or executive functions for up to 6 months after DBS surgery but did find mild impairment in lexical fluency at 12 months (Pillon et al., 2000). They also noted small but significant improvements in psychomotor speed and working memory when the stimulator was turned on compared to when it was turned off. Saint-Cyr and colleagues (2000) reported significant declines in multiple cognitive processes (working memory, speed of mental processing, bimanual motor speed and coordination, set switching, phonemic fluency, long-term consolidation of verbal material, and encoding of visuospatial material) in the first year after surgery, particularly in older patients with bilateral DBS-STN. In trying to interpret these studies, it is important to realize that (a) there are variations in surgical technique and in the number of needle passes required to identify the target, (b) the precise location of the electrode is not known with precision, (c) stimulation of different sites within the same brain target can lead to opposite effects (that is, though stimulation in the ventral pallidum improves parkinsonian features, stimulation in the dorsal GPi can worsen them), and (d) stimulation has the potential to affect distant as well as near brain regions. Parsons et al. (2006) performed a quantitative metaanalysis to better ascertain the cognitive consequences of DBS-STN. Analyzing studies published between 1990 and 2006, the investigators found small declines in executive functions, verbal learning, and memory; moderate declines were only reported in semantic and phonemic verbal fluency. Changes in verbal fluency were not related to patient age, disease duration, stimulation parameters, or change in DA-ergic therapy after surgery. York et al. (2007) investigated cognitive and other neuropsychiatric outcomes at 6 months in patients who had bilateral DBS-STN compared to those who received best medical treatment. Compared to controls, patients who had DBS-STN demonstrated significant declines in verbal memory and inhibition of a dominant response, with trends for declines in verbal fluency, verbal longterm recall, and set-shifting. Patients who had DBS-STN demonstrated no significant changes in depression or anxiety scores, but one patient who had DBS developed dementia over 6 months compared to none of the PD controls. This data prompted the study authors to recommend counseling candidates for DBS-STN about the risk of mild linguistic and executive cognitive declines associated with the procedure. Conflicting results obviously may reflect differences in patient population, neural target for stimulation, laterality, and status of the stimulator at the time of neurobehavioral evaluation. Of particular interest are case reports of patients who experienced profound depression with suicidal ideations following STN stimulation (Burkhard et al., 2004; Appleby et al., 2007) and a possible role of STN in impulse control disorders (Wichamann and DeLong, 2006; Hardesty and Sackeim, 2007).

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Further studies are required to better inform us about the neurophysiologic and neurobehavioral consequences of DBS. RELATIONSHIP OF PDD TO OTHER NEURODEGENERATIVE COGNITIVE DISORDERS Nosologic classification of the neurodegenerative dementias represents an evolving construct, as progressively improving clinical, pathologic, and mechanistic understanding emerges. Diagnostic classification has historically been influenced by what type of patients a physician is likely to see. For example, a patient with dementia and parkinsonism might be diagnosed as having “Alzheimer disease with parkinsonism” in a memory disorder clinic but with “PD-dementia” in a movement disorder clinic. The neuropathologist who finds pathological evidence consistent with PD and AD may also struggle to provide an exact diagnosis and may be understandably prejudiced by the clinical history in providing a final diagnosis. In these instances, the pathology report may represent less of a diagnostic “gold standard” than simply a reflection of the clinical orientation of the physicians, who in turn were hoping to be informed by pathologic findings (Perl et al., 1998). Multidisciplinary neuroscientific insights have generated increasing interest in the commonalities between PDD and other neurodegenerative cognitive disorders, and the question as to whether they are separate diseases or merely part of a spectrum of neurodegeneration (Love, 2005; Metzler-Baddeley, 2007). Clinical and neuropathologic overlap of PDD, AD with parkinsonism, and DLB have especially driven hypotheses regarding their respective relationships and the possibility of a common underlying neurodegenerative process (Perl et al., 1998; Galvin, 2006). For example, many patients diagnosed during life with PDD demonstrate classic degenerative changes in the SNc postmortem but also show NFTs and SPs sufficient to make a diagnosis of AD and/or diffuse cortical LBs consistent with DLBrelated pathology (Byrne et al., 1987; Perl et al., 1998; Noe et al., 2004; Burn, 2006a, 2006b). These pathologic admixtures, along with their corresponding clinical overlap, have prompted consideration of the possibility that these disorders comprise various cognitive-motor permutations of a neurodegenerative spectrum, with consequent implications for nosologic classification. Although such theorizing, and their empiric bases, remain an evolving process, it is useful to briefly review currently known pathologic relationships among PD and other major neurodegenerative cognitive disorders to clinico-pathologically contextualize PD-related cognitive dysfunction. Table 63.1 provides a summary of the pathologic findings among the major neurodegenerative cognitive disorders (Boeve, 2007).

63.1 Neurodegenerative Cognitive Disorders and Associated Dysfunctional Proteins TABLE

Dysfunctional Protein

Neurodegenerative Syndrome

Amyloid

AD

(amyloidopathies)

Down syndrome

Tau

AD

(tauopathies)

Pick’s disease CBGD PSP FTDP-17 with mutation in the microtubule-associated protein tau (FTDP-17 MAPT)

α-synuclein

PDD

(synucleinopathies)

DLB MSA

TAR DNA-binding protein 43 FTLD ubiquitin-positive inclusions (TDP-43) (FTLD-U) huntingtin

HD

Adapted from Boeve (2003). AD: Alzheimer’s disease; CBGD: cortico basal ganglionic degeneration; PSP: progressive supranuclear palsy; PDD: Parkinson’s disease with dementia; DLB: dementia with Lewy bodies; MSA: multiple system atrophy; FTLD: frontotemporal lobar dementia; HD: Huntington’s disease.

PD and AD Although AD and PD are relatively common disorders of the elderly, the overlap of clinical and pathological features between the two conditions exceeds that which would be expected to occur by chance alone (Perl et al., 1998), further driving interest in potentially unifying their pathogenic mechanisms. That said, there exist fundamental differences in the patterns of evolution of AD and PD dementias that support their clinicopathologic individualization (Stern et al., 1998). Patients with PD have increased risk of developing dementia, and there is increased frequency of parkinsonian motor features in patients with AD. There is increased risk of AD in siblings of patients with PDD compared with siblings of matched normal patients (Marder et al., 1999). Traumatic brain injury, hypertension, and diabetes are risk factors for the development of AD (Schofield et al., 1997), but not for PDD (Levy, Tang, Cote, et al., 2002). Spectrum conceptualizations of neurodegenerative cognitive disorders have driven increasing interest in the relationship between the cognitive profiles of PDD and AD (Bronnick et al., 2007). Parkinsonism in AD Numerous clinical studies have reported on the presence of parkinsonian features in patients with AD (Chui et al., 1985; Mayeux et al., 1985; Kurlan et al., 2000). In these cases, AD-related parkinsonian motor abnormal-

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ities are usually characterized by rigidity and bradykinesia rather than resting tremor (Mitchell, 1999; Kurlan et al., 2000). As with cognitive dysfunction in PD, the prevalence of AD-related parkinsonian features is likely to be underestimated because most reports come from AD clinics focusing primarily on cognitive function and without expertise in movement disorders. Reports of the prevalence of parkinsonism in patient populations with AD vary considerably, with some extending to 90%, particularly in studies performed by movement disorder specialists (Molsa et al., 1984; Lippa et al., 1998; Mitchell, 1999). For example, in one study conducted by investigators with PD expertise, 92% (n = 143) of patients with AD were found to have extrapyramidal signs (Molsa et al., 1984). In a 66-month prospective longitudinal study, extrapyramidal features developed in 36% of patients with mild AD (n = 44) who were preselected on the basis of not having motor dysfunction at baseline; this compared to 5% (n = 58) in agematched controls (Morris et al., 1989). Parkinsonian motor features can be detected at any stage of the ADrelated dementia process (Morris et al., 1989). Neuropsychological overlap and distinctions between AD and PD In general, cognitive impairment is more extensive in AD than in PDD. Although executive dysfunction is the core feature of PDD, anterograde amnesia is the hallmark of AD (McKeith, 2007). However, despite their respective relative cortical versus subcortical bases, there is significant overlap in the cognitive profiles of PDD and AD

FIGURE 63.3 Cognitive profile of Parkinson’s disease with dementia (PDD) compared with Alzheimer’s disease (AD).

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(Bronnick et al., 2007; McKeith, 2007), as depicted in Figure 63.3. Investigators have attempted to determine if there exists a meaningful distinction in the cognitive profile of patients with AD complicated by parkinsonism (ADP) versus AD without parkinsonism. In a study comparing these groups matched for age, education, and disease duration, patients with ADP, relative to their AD counterparts, were more impaired on tests of shortterm learning and memory, orientation, naming, verbal fluency, and construction, but not on tests of long-term memory, abstract reasoning, or verbal comprehension (Richards, Bell, et al., 1993). Such data suggest that parkinsonism within the context of AD may be a useful marker for a cognitive deficit profile distinct from that characterizing AD uncomplicated by parkinsonism, representing in part a mixture of PDD and AD pathology. Pathological overlap and distinctions: evidence of PD changes in AD, and AD changes in PD Postmortem studies provide evidence of pathologic overlap between PD and AD, with numerous reports documenting a high prevalence of neuropathological features of PD in patients diagnosed antemortem with AD (Byrne et al., 1987; Perl et al., 1998; Noe et al., 2004; Burn, 2006a, 2006b). In the Morris et al. (1989) study of patients with AD with extrapyramidal motor signs described above, postmortem nigral changes consistent with PD-related pathology were identified in addition to expected AD changes. In another study, 18 of 40 consecutively presenting patients with “autopsy-confirmed” AD also had neurodegenerative changes in the SN consistent

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with a diagnosis of PD (Leverenz and Sumi, 1986). Ditter and Mira (1987) studying 20 consecutively presenting patients with “pathologically confirmed” AD observed that 55% also had nigral degeneration with LBs in the SNc consistent with a pathological diagnosis of PD. In another study, 23% of patients with AD specifically selected because they met the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) clinical and neuropathological criteria for “definite AD” had PD-consistent changes in the SN at postmortem (Hulette et al., 1995). Studies in patients clinically diagnosed with PD show parallel evidence of AD-related pathology. For example, an autopsy study of 36 patients with “autopsy-proven” PD noted SPs and NFTs consistent with a pathological diagnosis of AD in 42% of patients (Boller et al., 1980). Alzheimer’s disease-related pathologic changes were more severe in patients with PD with dementia than in patients with PD with no dementia, and the frequency of AD pathology was 6 times higher than that expected in an age-matched control population (Boller et al., 1980). Another study compared the prevalence of AD pathology in patients with dementia and patients with no dementia with “pathologically proven” PD and in agematched controls. Senile plaques and NFTs sufficient to make a diagnosis of AD were present in 75% of the PD group and in 94% of those patients with PDD (Gaspar and Gray, 1984). In sum, there exists significant clinical and pathological overlap between PD and AD, but the overall etiologic significance of this remains unknown. Parkinsonian Spectrum Processes A group of disorders termed “Parkinson’s plus” or “atypical Parkinsonism” comprise syndromes marked by more widespread degeneration than is seen with PD (usually striatum and pallidum in addition to SNc) combined with a variety of additional motor and nonmotor features (cerebellar degeneration, eye movement disorders, autonomic dysfunction). In general, atypical parkinsonian syndromes are characterized by early-onset speech and gait disturbance, axial greater than appendicular rigidity, relative absence of tremor, and a poor response to LD (Olanow et al., 2001). They include multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and cortico basal ganglionic degeneration (CBGD). Each of these include variable parkinsonian and cognitive features (Litvan, Agid, Calne, et al., 1996; Schneider et al., 1997; Kertesz et al., 2000; Wenning et al., 2000). The cognitive profiles associated with each of these syndromes tend to manifest distinctive neuropsychological patterns (Lauterbach, 2004; Robbins et al., 1994). Dementia with Lewy bodies (DLB) has become the preferred term used to describe the dementia that occurs in association with parkinsonian features and diffusely

distributed cortical LBs (McKeith et al, 1996; McKeith, 2007). Dementia with Lewy bodies is now thought to be the second most frequent neuropathologically diagnosed degenerative dementia (Aarsland, 2002; Ransmayr, 2002). Dementia with Lewy bodies is a clinically defined syndrome consisting of a predominantly dysexecutive dementia, prominent visual hallucinations, and fluctuating sensorium in addition to parkinsonian motor features (McKeith, 2007). The presence of cognitive dysfunction characterized by at least two of three core features qualifies for a diagnosis of probable DLB, which in turn is 90% predictive of LB pathology at autopsy (McKeith et al., 2005; McKeith, 2007). Other common features include depression, rapid-eye-movement (REM) behavior sleep disorder (RBD), prominent gait instability, and syncope (McKeith et al., 1996; Aarsland, 2002; Ransmayr, 2002). Dementia with Lewy bodies is pathologically characterized by widely distributed cortical and subcortical (SNc, LC, dorsal vagal nucleus, NBM) LBs, in association with nigral degeneration and AD-type lesions (McKeith et al., 1996; Verny and Duyckaerts, 1998). Neurochemical findings include marked reductions of cortical acetylcholine and nigro-striatal DA (McKeith et al., 1996; McKeith et al., 2004). Mean age at disease onset ranges between 60 and 68 years; mean disease duration averages 6 to 7 years (McKeith et al., 2004). Males are more frequently affected than females (McKeith et al., 2004). A key, though somewhat arbitrary, differential diagnostic feature distinguishing PDD and DLB is the temporal sequence of the onset of motor and cognitive dysfunction: dementia occurring prior to, or within 1 year after the onset of PD features is diagnosed as DLB, whereas dementia developing more than 1 year after the onset of PD is diagnosed as PDD (McKeith et al., 2005). This is known as the “one year rule.” Many question the legitimacy of the “one year rule” as a principal nosologic distinction between DLB and PDD (Lippa et al., 2007). The absence of empiric foundation for a diagnostic rule that categorizes a dementia beginning 11 months after PD diagnosis as DLB but one beginning 13 months later as PDD seems somewhat contrived and raises the question of whether they are not in fact a part of the same neurodegenerative disorder. The cognitive dysfunction of DLB is usually more severe than the dementia of PDD, particularly for prefrontally mediated (Downes et al., 1998) and visual processing tasks (McKeith, 2007). For example, a recent study by Mondon et al. (2007) attempted to compare cognitive profiles of PDD and DLB. Despite global similarities in cognitive performances, patients with DLB consistently had worse performance on tasks requiring higher-order visuospatial processing. In contrast to the general trend in PDD, psychosis can occur in DLB regardless of DA-ergic treatment (McKeith et al., 2005). Approximately 75% of patients with DLB

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experience hallucinations, and more than 50% suffer from delusions (Aarsland et al., 2001). In a study by Aarsland and colleagues (2000) comparing DLB, PDD, and PD without dementia, delusions and hallucinations were most common in the DLB group (57% and 76%, respectively), followed by the PDD group (29% and 54%, respectively), and finally the PD without dementia group (7% and 14%, respectively). Patients with DLB are reported to be exquisitely sensitive to neuroleptics, though historically this issue may have been exaggerated (Aarsland et al., 2005). In sum, there is striking clinical, pathological, and biochemical overlap among DLB, PDD, and AD with parkinsonism. It remains to be determined whether DLB represents a discrete nosological entity or merely an anticipated intermediary on the neurodegenerative spectrum between PD and AD. Boeve (2007) published an

TABLE

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exhaustive review of parkinsonian spectrum neurodegenerative processes; see Table 63.2 for an inventory of characteristic features. RISK FACTORS FOR DEVELOPMENT OF COGNITIVE DYSFUNCTION IN PD Genetic Genetic factors have been implicated in the aetiology of PD. Several different genetic mutations have been identified in small numbers of patients with autosomal dominant and recessive forms of familial PD (De Marco et al., 2008; Kahle, 2008). Of particular note are mutations in LRRK2 gene that are found not only in earlyonset familial cases, but also in older patients with no family history and with clinical and pathologic fea-

63.2 Features of Other Neurodegenerative Cognitive Disorders Presenting with Parkinsonism

Disorder DLB

Parkinsonian Findings Masked facies, stooped posture, reduced arm swing similar to PD and PDD, but tremor less asymmetric and more postural than resting. Features tend to develop after cognitive features.

Principal Cognitive Features • severe progression of mixed subcortical and cortical features • visual hallucinations • fluctuating sensorium • neuroleptic sensitivity

CBGD

Markedly asymmetric rigidity (dystonia), often with coexisting jerky tremor, myoclonus; parkinsonism is minimally levodopa responsive.

Cortical dysfunction as reflected by at least one of the following: • focal or asymmetric ideomotor apraxia • alien limb phenomenon • cortical sensory loss • visual or sensory hemineglect • constructional apraxia • apraxia of speech or nonfluent aphasia

PSP

Parkinsonism with early gait impairment and postural instability, impaired vertical eye movements, wide-eyed stare, reduced eye-blink frequency, axial greater than appendicular rigidity.

Early onset of cognitive impairment including at least two of the following: apathy, impairment in abstract thought, decreased verbal fluency, utilization or imitation behavior, or frontal release signs.

MSA

Parkinsonism with early speech and balance impairment, axial rigidity, minimal asymmetry; minimal LD responsivity in the striatonigral variant (MSA-P); ataxia and spasticity prominent in the olivopontocerebellar atrophy variant (MSA-C); orthostatic hypotension and autonomic dysfunction prominent in the Shy–Drager syndrome variant.

• variable

FTLD-P17 AD+p

Variable parkinsonism, sometimes LD responsive, often similar findings to those in CBGD. Parkinsonism tends to be later in course; rigidity, bradykinesia, tremor (resting or postural) most obvious.

• overall milder / more subtle / more gradual progression

mixed dysexecutive • anterograde amnesia • dysnomia

Source: Adapted from Boeve, 2007. DLB: dementia with Lewy bodies; CBGD: cortico basal ganglionic degeneration; PSP: progressive supranuclear palsy; MSA: multisystem atrophy; FTLD-P17: frontotemporal lobar dementia with parkinsonism associated with chromosome 17 mutation; AD+p: Alzheimer’s Disease with parkinsonism; PDD: Parkinson’s disease with dementia; LD: levodopa.

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tures typical of sporadic PD. First-degree relatives of patients with sporadic PD also have an increased risk of developing PD (Warner and Schapira, 2003). As for PDD specifically, genetic data is sparse. A positive family history of parkinsonism or dementia imposes a modest increase in the chance that a patient with PD will convert to PDD (Marder et al., 1990; Schrag et al., 1998). Genetic predisposition for PDD has only been systematically studied for apolipoprotein ε4 (ApoE4) genotypes, with conflicting results (Emre et al., 2007). A positive correlation of E2 or E4 alleles with PDD was reported in some studies (Harhangi et al., 2000; Parsian et al., 2002; de Lau et al., 2005) whereas a negative association with E4 was found in others (Koller et al., 1995; Inzelberg et al., 1998; Camicioli et al., 2005). Dementia has been reported in familial forms of PD characterized by PARK1 (Zarranz et al., 2004) and PARK8 (Wszolek et al., 1997) genes, whereas PDD is rare in those familial PD forms characterized by PARK2, PARK6, and PARK7 genes (Emre et al., 2007). Age Significant interactions exist between age, age at time of PD onset, and PD-associated cognitive deterioration (Richards, Stern, et al., 1993; Marder et al., 1995; Glatt et al., 1996; Schrag et al., 1998; Graham and Sagar, 1999; Emre et al., 2007). Several studies have demonstrated that in PD, advancing age is associated with a faster rate of development of extrapyramidal motor dysfunction, more severe gait and postural instability, decreased LD responsivity, and more profound cognitive impairment including dementia (Levy, 2007). In general, it appears that age and overall disease severity are synergistic risk factors for developing dementia in PD (Levy, Schupf, et al., 2002; Levy, 2007). It was previously inferred that the apparently low incidence of cognitive deficits in patients with young-onset PD may relate to their ability to compensate for PD-related degenerative changes (Dubois et al., 1990). However, a study by Aarsland, Kvaloy, et al. (2007) found that, after adjusting for age, age at PD onset does not influence the risk for later dementia development. Education Level As in AD, education level correlates inversely with cognitive decline in PD (Glatt et al., 1996; Cohen et al., 2007; Verbaan et al., 2007). Although the association between high educational attainment and lower risk of developing cognitive dysfunction suggests the potential for education to modulate cognitive performance in PD, interpretation of such findings is complicated by multiple potential confounds (Ngandu et al., 2007). For example, a potential association of greater academic achievement with higher premorbid cognitive performance would

imply greater cognitive reserve capacity, with consequent resilience to the neurodegenerative dementia processes (Ngandu et al., 2007). Environmental Exposure Epidemiological studies have noted an inverse correlation between smoking and PD, with epidemiologic studies consistently demonstrating that smokers have a seemingly reduced risk of developing PD (Morens et al., 1995). By contrast, Levy, Tang, Cote, et al. (2002) noted a positive association between smoking and dementia in patients with PD; in particular, current smoking was more strongly associated with incident dementia than past smoking. Type, Severity, and Levodopa Responsivity of Motor Symptoms There is a strong correlation between the severity of parkinsonian motor signs and the severity of cognitive deficits (Ebmeier et al., 1990b; Richards, Stern, et al., 1993; Marder et al., 1995; Glatt et al., 1996; Levy, Schupf, et al., 2002). Motor deficit and advanced age have a particularly synergistic effect on the risk of developing cognitive impairment: Levy, Schupf, et al. (2002) found that patients with older age and high severity of motor symptoms had a relative risk of incident dementia of 9.7% compared with a younger age/lower severity group. In general, akinetic-rigid forms of PD are associated with a higher risk of dementia (Ebmeier et al., 1991; Emre et al., 2007; Williams-Gray et al., 2007). Akineticrigid forms of PD are characterized by features that classically do not respond to LD including axial, gait, posture, balance, facial reactivity, and speech disturbances (Elizan et al., 1986; Emre et al., 2007). Aarsland et al. (2004) further found that LD-unresponsive features are associated with accelerated cognitive decline. Levy and colleagues (2000) found that speech impairment, bradykinesia, and axial instability had the strongest associations with incident dementia in PD. A cross-sectional study by Burn et al. (2003) found an overrepresentation of the postural instability gait difficulty (PIGD) motor subtype to be present in 88% of patients with PDD compared with 38% of patients with PD without dementia. In the PD group, tremor dominant (TD) and PIGD subtypes were evenly represented compared to the predominant PIGD pattern in PDD (Burn et al., 2003). This observation was further supported by a prospective follow-up study of 40 patients with PD where 25% of those with the PIGD subtype developed dementia, compared with none who had TD or indeterminate phenotypes (Burn et al., 2006). Williams-Gray et al. (2007) also observed that in a cohort of patients with PD, those who did not have a TD PD phenotype at baseline had a greater risk of developing dementia. It should

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be appreciated that patients with the PIGD subtype are also more likely to have an atypical parkinsonism and to have a more aggressive rate of decline in motor features as well (Emre et al., 2007). In contrast, tremor dominance at presentation has been associated with relative cognitive resilience and a reduced risk of developing dementia (Elizan et al., 1986). In fact, Alves and colleagues (2006) found that dementia did not occur among patients with persistent TD subtype, and patients with TD subtype at baseline did not develop dementia unless they transitioned to PIGD subtype. Patients who suffer from dystonic dyskinesias have been variably associated with increased risk for PDD (Emre et al., 2007). Perceptual Disturbance (Hallucinations) Visual hallucinations (VH) are a marker for increased risk of the subsequent development of dementia in patients with PD (Mayeux et al., 1992; Stern et al., 1993; Marder et al., 1995; Aarsland et al., 2003). RamirezRuiz et al. (2007) found that 45% of patients with PD and no dementia who experienced hallucinations developed dementia over the course of a 1-year period. In the same study, more than 80% of patients with PD with no dementia who had hallucinations had mild cognitive impairment (MCI) compared to only 30% of patients with PD with no dementia who did not have hallucinations (Ramirez-Ruiz et al., 2007). Cognitive functions involving higher visual processing, including visual memory, were especially affected in those with hallucinations. Sleep Disturbance Sleep disturbances with excessive daytime sleepiness (EDS) are common in PD (Brodsky et al., 2003), with multiple potential complicating influences on cognitive and affective function. Excessive daytime sleepiness has been reported to be a risk factor for the development of dementia in a patient with PD (Gjerstad et al., 2007). REM behavior disorder (RBD), a parasomnia frequently reported in PD, may also be a risk factor for dementia (Sinforiani et al., 2006). For example, patients with PD with concomitant RBD show significantly worse performance on neuropsychological tests measuring episodic verbal memory, executive functions, and visuoperceptual processing compared to patients with PD without RBD (Vendette et al., 2007). In a consecutive series of RBD patients, 10 of 25 with PD had dementia (Olson et al., 2000). Although there have been longitudinal studies demonstrating that RBD is a risk factor for PD (Schenck et al., 1996), there have not been similar studies with respect to PDD. It should be appreciated that RBD is also commonly seen in other synucleinopathies that are associated with dementia such as DLB and MSA.

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CLINICAL FEATURES OF PDD Cognitive Profile Cognitive dysfunction in PD can range from exquisitely subtle changes requiring sensitive neuropsychological instruments to detect, to frank dementia where the patient requires continuous supervision to ensure safety. When slight, the patient, caregivers, and even experienced clinicians may not recognize the presence of any cognitive problem (Marjama-Lyons and Koller, 2001). Although onset is typically insidious, progression to dementia is usually inexorable, with mean annual rate of decline in Mini-Mental State Examination (MMSE) score ranging from 1 to 4.5 points (Aarsland et al., 2004; Burn et al., 2006). Recognition that dementia becomes increasingly prevalent in PD populations over time prompted the need to develop standardized criteria for diagnosing PDD (McKeith, 2007). A Movement Disorder Society Task Force (MDSTF) charged with this responsibility recently reported its findings (Emre et al., 2007). Based on an extensive literature review, this group recently published a definitive compilation of the neuropsychiatric profile characterizing PDD. We here briefly review the characteristic features of PDD, which are inventoried in Table 63.3. Early stages: Sentinel neuropsychological deficits Although Graham and Sagar (1999) suggested the existence of a “motor-only” stage of PD characterized by progressive motor dysfunction in the absence of cognitive impairment, neuropsychological deficits can be noted in the vast majority of patients even in the early stages of the disease (Pirozzolo et al., 1982; Taylor et al., 1990; Cooper et al., 1991; Janvin et al., 2005; Lewis et al., 2005; Williams-Gray et al., 2007). Cognitive deficits in early PD are marked by significant heterogeneity among a variety of different cognitive domains, including executive, linguistic, memory, and complex visual (Taylor et al., 1990; Cooper et al., 1991; Dubois and Pillon, 1997; Cools et al., 2001a; Janvin et al., 2005; Lewis et al., 2005; Williams-Gray et al., 2007). Although the relationship between the initial deficit pattern and the subsequent dementia remains to be clarified (Emre et al., 2007), data derived from prospective studies suggest that certain deficit patterns may herald later cognitive decline (Mahieux et al., 1998; Janvin et al., 2005). For example, a longitudinal community-based epidemiological study of patients with PD showed that baseline performance on verbal fluency tasks was significantly associated with subsequent incident dementia (Jacobs et al., 1995). Results of several other studies also suggest that poor performance on tests of verbal fluency may be a distinct characteristic of the “preclinical” phase of dementia in PD (Emre et al., 2007). As mentioned

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63.3 Clinical Features of PDD

Core features

• insidious onset • slow progression • impairment in more than one cognitive domain • deficits severe enough to impair daily life (social, occupational, or personal care) • impairment independent of that attributable to motor or autonomic symptoms

Associated clinical features

• cognitive features: 

impaired attention ■





impaired executive functions ■

especially initiation, planning, concept formation, rule finding, set shifting

■

deficient set maintenance

■

reduced mental speed (bradyphrenia)

impaired visuo-spatial functions ■





may fluctuate during the day and from day to day

deficient performance on tasks requiring visual-spatial orientation, perception, or construction

impaired memory function ■

reduced recent memory

■

poor performance on free recall tasks

■

recognition usually better than free recall

linguistic dysfunction ■

dysnomia

■

impaired complex comprehension

• perceptual disturbances 

hallucinations: mostly visual, usually complex, formed objects

• thought content disturbance 

delusions

• mood dysregulation 

depression



anxiety

• comportmental features: 

apathy: decreased spontaneity; reduced motivation, interest, and effortful behavior



changes in personality

• excessive daytime sleepiness

(under Epidemiology), Williams-Gray et al. (2007) longitudinally followed a community-based cohort of patients with newly diagnosed idiopathic PD. Although 10% developed dementia at a mean of 3.5 years from diagnosis, 57% showed some evidence of cognitive impairment. Deficits attributable to frontostriatal dysfunction was the predominant deficit among the group with no dementia; however, the most important clinical predictors of subsequent global cognitive decline (following correction for age) were impaired performance on neuropsychological tasks thought to be mediated by posterior cortical substrates, including semantic fluency and visuospatial functions (especially visuomotor construction) (Williams-Gray et al., 2007). Neuropsychological studies of PD emphasize the early prominence of dysexecutive features (Mahieux et al., 1998). For example, patients with early PD demonstrate impaired learning of novel tasks requiring internally driven processing (that is, set acquisition) (Taylor and Saint-Cyr, 1995). Reduced working memory in early PD can manifest as nonspecific bradyphrenia (Wilson et al., 1980; Cooper and Sagar, 1993a; Cooper et al., 1994) and prolonged decision making in tasks with high cognitive load (Zimmermann, et al., 1992). Retrieval deficits and impaired abstraction have also been observed in the early stages of PD (Dubois and Pillon, 1998), although in contrast to PD, these patients are frequently improved by cuing, suggesting a more fundamental problem with retrieval rather than encoding of memory. The presence of MCI in a patient with PD (Foltynie et al., 2002) has prompted research to determine if a sentinel dementia profile can be defined that represents a sentinel pattern for PDD as has been considered in AD. For example, Janvin et al. (2006) investigated whether certain MCI patterns are harbingers for subsequent dementia development in PD. Janvin et al. (2006) longitudinally tracked patients with PD with intact cognition and with various MCI subtypes and found 62% of patients with PD with MCI, compared to 20% of patients with PD who were cognitively intact, developed dementia. Single-domain nonamnesic MCI and multidomain slightly impaired MCI were associated with PDD development, while amnesic MCI subtype was not (Janvin et al., 2006). This pattern is distinct from the natural history of AD, where amnesic MCI has been identified as a principal sentinel for AD conversion (Mariani et al., 2007). These findings may have important therapeutic implications for treatment of dementia in PD where MCI may turn out to be a more reliable index of future disability than it has in AD.

Source: Adapted from Emre et al. (2007).

PDD cognitive profile Executive dysfunction. Extensive evidence indicates that executive dysfunction constitutes a central characteristic

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of PDD (Emre et al., 2007). Neuropsychological assays sensitive to frontal lobe dysfunction (for example, tests of planning, working memory, set maintenance, set shifting, impulse control, conflict detection, etc.) reveal progressive executive failure in PD (Van Spaendonck et al., 1993). Further, the executive dysfunction of PD gives rise to secondary impairments in multiple other cognitive domains (for example, memory retrieval impairment due to failure of ancillary executive processes) (Pillon et al., 1993). Importantly, the presence of dominant executive dysfunction constitutes a key clinical feature distinguishing PDD from AD dementia (Cahn-Weiner et al., 2002). Attention is a core executive function that is disrupted in PD (Ballard et al., 2002). Because many attentional assessment instruments confound attention with other executive processes and motor speed, methodologic issues complicate interpretation of attentional studies in PD (Emre et al., 2007). Nonetheless, based on reports from several studies (e.g., Ballard et al., 2002), it seems clear that attentional impairment represents a core attribute of PDD, with prominent tendency for fluctuation in concentration that is distinct from other cortical neurodegenerative disorders such as AD (Cahn-Weiner et al., 2002; Emre et al., 2007). Patients with PD also demonstrate excessive dependence on external cues for task initiation, struggling to perform motor and cognitive tasks that require utilization of an internal strategy (Hsieh et al., 1995; Berger et al., 1999). Consequently, patients with PD require increased processing time to formulate task goals (set acquisition) (Owen et al., 1992; Dubois and Pillon, 1998). Dependence on external cues to execute a serial learning strategy appears to also correlate with motor dysfunction, primarily bradykinesia (Berger et al., 1999). Patients with PD develop progressive deficiency implementing efficient and accurate task control operations (Owen et al., 1992; Dubois and Pillon, 1998). Impaired attentional set-shifting ability (Cools et al., 2001a; Woodward et al., 2002) becomes prominent with PD progression. Impaired set shifting has been suggested to underlie the difficulty patients with PD manifest in performing bimanual simultaneous motor tasks (Horstink et al., 1990). It appears that the difficulty is more in initiating a response set for a new relevant dimension rather than in disengaging from a previously reinforced category (Brown and Marsden, 1988; Owen, Roberts, et al., 1993; Partiot et al., 1996). Set-shifting impairment in particular is associated with motor severity (particularly rigidity) as inventoried by the Unified Parkinson’s Disease Rating Scale (UPDRS) (Van Spaendonck et al., 1996). Because of diminished set acquisition and set-shifting proficiency, patients with PDD frequently experience a progressive diminution in multitasking capacity (Brown et al., 1993). Concept formation (that is, abstract inductive reasoning) can be tested using a variety of neuropsychological

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instruments (for example, Conceptualization subscale of the Mattis Dementia Rating Scale [DRS], Similarities subtest of the Wechsler Adult Intelligence Scale [WAIS], Raven’s Progressive Matrices [RPM], and Wisconsin Card Sorting Test [WCST]) (Dubois et al., 2007; Emre et al., 2007). Patients with PDD show consistently impaired performance on such measures compared to patients with PD with no dementia (Paolo et al., 1996; Van Spaendonck et al., 1996; Marié et al., 1999; Emre et al., 2007). Several studies have contrasted the executive functions in PDD and AD (e.g., Cahn-Weiner et al., 2002). Although select data indicate that patients with PDD are no more perseverative than patients with AD on WCST performance (Paolo et al., 1996), it is likely that set shifting and other dysexecutive features yield increased vulnerability to perseveration in PD (Cools et al., 1984; Owen et al., 1992; Downes et al., 1993). Compared to patients with AD, patients with PDD commit more total errors on the WCST, but not on any other index of performance (Paolo et al., 1996). Patients with PDD have also been noted to perform worse than patients with AD on the RPM (Starkstein et al., 1996). Although performing better on memory subscores, patients with PDD are noted to perform worse than patients with AD on select executive function DRS subscales (Aarsland et al., 2003). Linguistic dysfunction. Several studies have documented verbal fluency deficits in PDD (Emre et al., 2007), especially those employing the DRS, where verbal fluency assessment constitutes a large portion of the Initiation and Perseveration subscale (Aarsland et al., 2003; Paolo et al., 1995). However, data are heterogeneous regarding phonemic or semantic vulnerability predominance (Piatt et al., 1999; Noe et al., 2004). With the exception of prosody, overall linguistic function is less impaired in PDD than in AD (Cummings et al., 1988), where dysnomia in particular is a fundamental hallmark. Learning and memory impairment. Memory impairment is the presenting problem in approximately two thirds or fewer of patients with PDD (compared to 94% with DLB and 100% with AD) (Noe et al., 2004). Several types of learning and memory impairment plague patients with PD, evolving with disease stage progression (Owen, Beksinska, et al., 1993), with neuropsychological studies of memory function in PDD yielding variable and sometimes inconsistent results (Emre et al., 2007). Phenomenologic and methodologic complexities contribute to this variability. Phenomenologically, many memory functions are dependent on executive processes and are consequently directly vulnerable to PD-related frontostriatal dysfunction (Pillon et al., 1993). Methodologically, neuropsychological assays of memory functions often involve executive processes intrinsic to those memory processes being measured and are therefore not solitary probes of memory function.

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Reports suggest that anterograde memory function, mediating short-term and recent memory capacities, progressively dwindles with PD progression (Sullivan et al., 1989). Encoding and storage abilities per se are relatively spared in PD (Sullivan and Sagar, 1991; Pillon et al., 1996). However, PD-related attentional reduction, with secondarily deleterious effects on storage, especially contributes to impaired new memory formation when conducted within the context of interfering stimuli (Sullivan and Sagar, 1991; Cooper and Sagar, 1993a; Marié et al., 1999). Retrograde memory performance is especially vulnerable to the effects of progressive failure of ancillary executive processes essential to long-term memory performance. Memory-affecting executive processes vulnerable to PD-related degeneration include internally driven search strategies (Buytenhuijs et al., 1994), information retrieval (Dubois and Pillon, 1998), and dating capacity (Sagar, Cohen, et al., 1988). It is important to note, however, that evidence for dysexecutive-related mechanisms of memory dysfunction in PD primarily derives from studies of patients with PD with no dementia who demonstrate preserved recognition memory and performance enhancement when given retrieval cues (Emre et al., 2007), thereby suggesting preservation of memory function per se. However, patients with PD who meet criteria for a formal diagnosis of dementia are in fact impaired on cued recall tasks (Pillon et al., 1993; Higginson et al., 2005), including recognition deficits for verbal (Noe et al., 2004; Higginson et al., 2005) and nonverbal stimuli (Noe et al., 2004), suggesting primary memory failure (Whittington et al., 2000) at least at the later stages of the dementia process. Working memory, which consists of the ability to scan, manipulate, and/or process newly registered information, becomes increasingly impaired in PD (Owen, Iddon, et al., 1997; Fournet et al., 2000; Hoppe et al., 2000). Because working memory relies on a complex interdependence of multiple executive (attention, set maintenance, task control operations, etc.) and memory functions, coordinated by a complex frontally based neural network, it is not surprising that working memory would decompensate under the weight of the PD-related frontostriatal pathology. Patients with PD are capable of schema learning but require more practice than controls to achieve comparable levels of performance (Soliveri et al., 1992). Learning of conditional associations by trial and error also becomes impaired (Sprengelmeyer et al., 1995). Over time, procedural learning deficits become increasingly prominent as well (Saint-Cyr et al., 1988; Ferraro et al., 1993; Pascual-Leone et al., 1993; Haaland et al., 1997; Sarazin et al., 2001). Several studies have attempted to identify those memory features which distinguish PDD and AD. Although results have been frequently inconsistent, data overall indicate that verbal and visual memory are overall less impaired in PDD than in AD (Kuzis et al., 1999; CahnWeiner et al., 2002; Higginson et al., 2005).

Visuospatial dysfunction. Visuospatial deficits have long been noted to complicate PD (Bowen et al., 1972). The mechanism underlying visuospatial impairment has not been well-delineated (Bradley et al., 1989), and it is not clear if these deficits are independent of attentional (M.J. Wright et al., 1990; Filoteo and Maddox, 1999) and/or other executive impairments (Brown and Marsden, 1986; Brown and Marsden, 1988; Growdon et al., 1990; Raskin et al., 1992; Bondi et al., 1993; Berry et al., 1999; Blanchet et al., 2000). Overall, patients with PDD have more impaired visuo-perceptual function than patients with PD with no dementia (Mosimann et al., 2004), and patients with PDD tend to perform worse than patients with AD in many visuo-perceptual domains (Mosimann et al., 2004). Dyspraxia. Praxis assessment necessarily involves assaying multiple cognitive and even motor domains (for example, executive, visuospatial, visuomotor control, fine motor, etc.). Consequently, it is not surprising that patients with PDD typically perform poorly on praxis assessments, especially those involving drawing/construction (Emre et al., 2007). For example, patients with PDD show significantly impaired performance on the Clock Drawing Test and other design construction tasks, with layered deficits of planning, organization, and visuomotor control (Cahn-Weiner et al., 2003; Cormack et al., 2004). Overall, data suggest that visuomotor praxis is more impaired in PDD than AD (Cormack et al., 2004; Emre et al., 2007). Neuropsychiatric Dysregulation Psychiatric disturbances developing within the context of PD can be multifactorial in their genesis and complex in their consequences. The same, or closely related, mechanisms generating cognitive impairment in PD can also yield affective dysregulation, thought content derangement, perceptual disturbance, impulse dyscontrol, and comportmental dysregulation (Taylor et al., 1990; Weintraub and Hurtig, 2007; Weintraub and Potenza, 2006). In turn, psychiatric phenomenology can (1) aetiologically contribute to, (2) exacerbate, and/or (3) complicate the management of PD-related cognitive dysfunction. Psychiatric disturbances complicating PD even without dementia can be extensive. For example, Pacchetti et al. (2005), studying 289 consecutive outpatients with PD, found 18% had hallucinations, 7% had hallucinations plus “confusion,” and 4% had hallucinations plus delusions. Another investigation by Aarsland, Brønnick, and Her (2007) exhaustively explored the profile of neuropsychiatric symptoms in PDD. In this study of over 500 patients with PDD using the Neuropsychiatric Inventory (NPI), they found that 89% of patients had least one neuropsychiatric symptom. The most common symptoms were depression (58%), apathy (54%), anxiety (49%), and hallucinations (44%). Patients with PD with

63: DEMENTIA IN PARKINSON’S DISEASE

psychosis and agitation symptom clusters had the lowest MMSE, highest UPDRS, and highest caregiver distress scores (Aarsland, Brønnick, and Her, 2007). Psychotic symptoms can be aggravated by DA-ergic medications and accordingly limit the ability to use these medications to better control PD motor features. The prominence of psychotic symptoms complicating PD has prompted formulation of standardized diagnostic criteria for these features (Ravina et al., 2007). We briefly review core neurospychiatric dysregulation complicating the neurobehavioral profile of PDD. Mood dysregulation: Depression and anxiety Depressed mood is common in PD, with prevalence rates approximating 50% (Dooneief et al., 1992). Major depression has been reported to occur in 13% of patients with PDD (Aarsland et al., 2001). Depression within the context of PD may represent the most complexly layered affective dysregulation. As depicted in Figure 63.4, depression in PD can be a consequence of multiple possible aetiologic mechanisms. It has long been debated if depression in PD is related to endogenous or exogenous mechanisms. It is not surprising that patients who have a chronic, progressive, neurodegenerative condition might become depressed. Alternatively, neurodegeneration with involvement of multiple monoamine neurotransmitter systems might cause depression as an inherent component of the PD process. New concepts are also emerging. Although it has long been appreciated that the masked facies of PD can mimic depression, data suggest a more insidious effect than mere mimicry. If facial expression is constrained by an impaired capacity to recruit facial mimetic muscles, brain regions involved in affective responsivity may be similarly restrained. Another hypothetical mechanism by which masked facies can reflect or be causative of depression invokes the evolving concept of mirror neurons. This concept hypothesizes that an inability to “mirror” the socioemotional facial expressions of others can have an impact

FIGURE

63.4 Depressogenic mechanisms in Parkinson’s disease.

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on the activation of socioemotionally relevant mirror neuron functioning. As in other clinical contexts, depression can itself cause secondary cognitive dysfunction (for example, pseudodementia). Patients who are depressed can appear to have dementia but remain cognitively intact, which can be readily recognized after treatment of the depression. On the other hand, patients with PD with depression tend to be more cognitively impaired on tests of memory function and language fluency than patients with PD without comorbid depression matched for age, education, gender, age at disease onset, disease duration, and disease severity (Tröster, Paolo, et al., 1995; Tröster, Stalp, et al., 1995). Thus, depression might also occur as a consequence of the dementia process. Parkinsonian motor and cognitive features include many that phenomenologically suggest depression, including affective blunting, bradyphrenia, and apathy (Koller, 1984). Further, typical neurovegetative indices of depression (for example, sleep disturbance, appetite) can be deranged by PD, and so their reliability as markers of affective dysregulation is compromised. Therefore, an essential component of PD clinical evaluation is a comprehensive affective assessment that includes probing the patient’s subjective experience to confirm whether or not a dysthymic state exists. Although PDassociated depression typically appears as a psychomotor retardation due to PD-related masking and bradykinesia, the subjective experience can include significant agitated depression-type features. In general, the pattern and severity of depression appear to be significantly influenced by the severity of motor dysfunction and degree of overall functional disability (Gotham et al., 1986a; Brown et al., 1988). Mood swings frequently accompany the motor fluctuations associated with LD treatment, with depression being more pronounced during off periods. Depression has been reported to occur in approximately two thirds of patients with PD with motor fluctuations, with consequent impact on patient quality of life (Nissenbaum et al., 1987). Therefore interventions designed to reduce motor fluctuations may be helpful in ameliorating PDrelated depression (Olanow et al., 2001) and consequent depression-related cognitive complications. Subjective anxiety appears to occur at similar rates as dysphoria, and the two disturbances are often comorbid (Menza et al., 1993; Emre et al., 2007). Anxiety can also be more prominent in off periods. Indeed, some patients with PD suffer severe panic episodes confined to off episodes that can be dramatically relieved by manipulation of pharmacotherapy for PD. Anxiety tends to be more pronounced in patients with PDD; however, objective irritability appears to be less prevalent than in other neurodegenerative dementias (Engelborghs et al., 2005). Apathy is another common mood disturbance in PD. Prevalence rates in PDD have been reported to be as

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high as 54% (Aarsland, Brønnick, and Her, 2007), compared to frequencies of 17% in patient populations with PDD with no dementia (Aarsland et al., 2001). Hallucinations Perceptual disturbances or hallucinations commonly complicate PD (Fénelon et al., 2000, 2006), and occur in up to 65% of patients with PDD (Aarsland, Brønnick, and Her, 2007; Williams et al., 2007). Visual hallucinations occur at least twice as frequently as auditory hallucinations (Emre et al., 2007). They are predominantly composed of visual images that are typically complex, formed, and represent real (animals, people) but nonthreatening objects (Fénelon et al., 2000; Mosimann et al., 2006). Patients with PDD generally retain insight regarding the hallucinatory nature of the perceptual derangement until more advanced stages (Aarsland, Brønnick, and Her, 2007). In many instances the hallucinations are more disturbing to family members than to patients. In more advanced cases, patients may develop hallucinations in association with paranoid ideations, particularly involving marital infidelity. PD-associated hallucinations can be multifactorial in origin (Holroyd et al., 2001). They may occur spontaneously or be induced by LD and other DA-ergic medications. Dopamine agonists in particular can induce hallucinations, even in the early stages of the disease (Rascol et al., 2000; Olanow et al., 2001). Cortical LBs and prominent cholinergic deficits are frequent postmortem findings in patients with PD who experience hallucinations with or without dementia (Aarsland et al., 2001; Assal and Cummings, 2002). Parkinsonism associated with prominent hallucinations should prompt consideration of underlying DLB pathology (Williams et al., 2007). Visual hallucinations tend to be associated with multiple cognitive deficits, including frontal dysfunction and memory deterioration (Ozer et al., 2007). Santangelo et al. (2007) studied cognitive function in patients with PD in a 2-year study, comparing those with hallucinations at baseline, those who developed hallucinations during the course of follow-up, and those who remained hallucination free throughout the study. Cognitive performance significantly declined in all three groups, but at end point, patients with PD who had hallucinations scored significantly lower than those who did have hallucinations on phonological and semantic fluency tasks, immediate free recall, and go/no-go tasks (Santangelo et al., 2007). Hallucinations and poor phonological fluency independently predicted the later development of diffuse cognitive impairment (Santangelo et al., 2007). Visual hallucinations are reported to occur with similar frequency and severity in PDD and DLB (Emre et al., 2007), contrasting with significantly lower prevalence rates in AD (Hirono et al., 1999).

The development of hallucinations can restrict the ability to adequately treat patients with PD, as higher doses of DA-ergic medications can induce/aggravate hallucinatory behavior and cognitive impairment. Treatment with atypical neuroleptics such as quetiapine or clozapine, even in very low doses (for example, 12.5–50 mg) can provide dramatic benefit for patients with PD and permit higher doses of LD to be employed to treat parkinsonian motor features. Most studies have shown that clozapine is more effective than quetiapine, but typically the latter is tried first to avoid the risk of agranulocytosis and the need for periodic monitoring required with clozapine. Atypical neuroleptics are frequently associated with sedation and may cause worsening parkinsonism. Thought content disturbance Disturbances of thought content, sometimes rising to the level of delusionality, can complicate PD (Aarsland et al., 1999; Aarsland et al., 2001; Holroyd et al., 2001). In general, delusions are less common than hallucinations in PDD, although the two are often comorbid (Emre et al., 2007). Although occurring in up to 17% of patients with PD in general (Aarsland et al., 1999; Marsh et al., 2004), the frequency of delusions in PDD is reported to be up to 30% (Aarsland, Brønnick, and Her, 2007), generally lower than prevalence rates reported in DLB (Aarsland et al., 2001). However, Mosimann et al. (2006) observed that there was a similar frequency, content, and severity of delusions over time in PDD and DLB; paranoid and “phantom boarder” type are among the most common in PDD and DLB (Aarsland et al., 2001). Impulse dyscontrol Impulse control disorders (ICDs) including pathological gambling, hypersexuality, and varied compulsions (for example, eating, shopping) have recently been described in patients with PD (Weintraub and Potenza, 2006; Voon and Fox, 2007). Intrinsic PD pathology and iatrogenic effects (especially treatment with DA-ergic agents) are thought to contribute to impulse control impairment (Pontone et al., 2006; Pagonabarraga et al., 2007; Mamikonyan et al., 2008). Risk factors include young age, dopamine agonists particularly in high doses, and preexisting depression or an ICD (Dodd et al., 2005; Voon and Fox, 2007). Impulse control disorders have now been described in association with multiple DA agonists (pramipexole, ropinirole, pergolide) and appear to be a class effect (Mamikonyan et al., 2008). How DA agonists lead to ICDs is not known, but it is fascinating that DA is known to be closely linked to reward (Schultz, 1998). It has been speculated that DA agonists might induce ICDs through activation of specific DA receptor subtypes, but it is possible that DA agonists act by restoring DA-ergic tone that permits ex-

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pression of their baseline personality. In that context, however, it is noteworthy that these problems are not typically seen with LD. In contrast, LD has been associated with a DA dysregulation syndrome and a condition known as “punding” where patients repeatedly perform meaningless activities such as gathering and assembling and disassembling objects (Evans et al., 2004). These in turn have not been described with DA agonists. Further studies are required to determine the precise frequency of ICDs in PD in comparison to the general public; such studies must take into account that there is now more ready access to gambling (for example, Internet, more widely accessible casinos) and that the risk of pathologic gabling (PG) is greater in individuals who are retired or have a disabling illness (Weintraub and Potenza, 2006). Impulse control disorders can represent an especially delicate management challenge when they occur within the context of PDD. CLINICAL ASSESSMENT Traditional clinical inventories including the MMSE and UPDRS remain the staples of routine cognitive assessment in PD and have a reasonably adequate capacity to identify major cognitive and affective dysfunction (Starkstein and Merello, 2007). However, there has been evolving need to formulate more sensitive and detailed assessment strategies that are more specifically focused on the problems that occur in PD. Consequently, the MDSTF has recently published a practice guideline of methodologies for diagnosing dementia in PD (Dubois et al., 2007); we review these below. Routine Examination The MMSE has long been used as a screening instrument for dementia in community-based samples (Folstein et

TABLE

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al., 1975; Wells et al., 1992). However, the MMSE is not a particularly sensitive instrument for PD, where deficits primarily affect executive domains, particularly in the early stages of the illness. Thus, for instance, a patient with PD with an MMSE score of 27 may have considerably more cognitive impairment than would be expected for an individual in the general population. The MDSTF has developed guidelines for routine office-based assessment that augment the MMSE by adding domainspecific screening tasks (Dubois et al., 2007); see Table 63.4 for a summary inventory of these assessments. Neuropsychological Assessment Neuropsychologic testing provides a standardized method for gauging cognitive dysfunction that can be used as a baseline for future evaluations, aid in differential diagnosis, and inform treatment planning (Litvan, Agid, Goetz, et al., 1996; Litvan, Mega, et al., 1996). Unlike an office-based clinical screen, standardized neuropsychological testing establishes precise, objective measurements. Patient scores on cognitive tests are compared to a standardized, “expectable” reference value derived from normative data sets that control for such factors as gender, age, and education. With population-based and patient-specific reference points in mind, the typical neuropsychological evaluation measures a wide array of skills. Overlearned skills and novel problem-solving abilities are assessed. Because most neuropsychological instruments de facto test more than one cognitive skill (for example, attentional capacity impacts other directed measures of cognitive functions), assessment batteries typically rely on a combination of measures within and across cognitive domains to systematically eliminate confounds. Pattern analysis serves to highlight salient findings in building a cognitive profile while providing context for excluding erroneous scores or discrepancies. Qualitative behavioral observations throughout the assessment offer valuable additional data regarding factors such as

63.4 MDSTF Guidelines for Office-based Screening of PD-related Cognitive Deficits

Cognitive Domain

Method of Evaluation

Pass/Fail Criteria

General intellectual functioning

MMSE

Cut-off score for impairment: < 26

Mental tracking

Months of the year in reverse order

Omission of two or more months, incorrect sequencing of months, or failure to carry out task within 90 seconds

Lexical verbal fluency

Number of words beginning with “s” generated within 60 seconds

Fewer than 10 items

Clock Drawing Test (“set hands to ‘ten past two’”)

Inability to insert the correct clock-face numbers or hands pointing to an incorrect time

Constructional praxis

MMSE intersecting pentagons

Copy should include two pentagons which overlap

Memory

MMSE 3-word recall

Failure to recall all three words suggests the existence of a memory storage or memory retrieval problem

Planning/organization

Source: Adapted from Dubois et al. (2007). MDSTF: Movement Disorder Society Task Force; PD: Parkinson’s disease; MMSE: Mini-Mental State Examination.

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anxiety and compensatory strategies, which can negatively affect test validity. Neuropsychological test inventory See Table 63.5 for a summary inventory of MDSTFrecommended neurospsychological assays applicable to characterizing PDD. Test interpretation A formal diagnosis of PDD is generally conferred when the following criteria are met: (1) impaired cognitive function representing a decline from premorbid ability, (2) memory impairment in addition to impairment of at least one other cognitive domain, (3) deficit severity sufficient to impair functioning in daily life, and (4) presence of at least one associated behavioral feature (for example, apathy, hallucinations, excessive daytime sleepiness) (Dubois et al., 2007). Deficits in only one cognitive domain (for example, memory or executive dysfunction) may justify a diagnosis of MCI but do not satisfy criteria for a formal dementia diagnosis. Likewise, cognitive decline that has yet to cause functional disability does not fall into the category of dementia per se. Neuroimaging Structural and functional neuroimaging modalities can be helpful in clarifying the aetiology, and possibly informing the management, of cognitive dysfunction in PD (Sawle et al., 1994; Brooks, 2000). Although practice guidelines continue to evolve regarding its utilization, neuroimaging has become a valuable diagnostic tool in evaluating cognitive dysfunction in general. The ability of neuroimaging to aid in the differential diagnosis of cognitive dysfunction arising within the context of parkinsonism is manifold. In addition to detecting imagingspecific features of parkinsonism, patients presenting with a combination of cognitive dysfunction and parkinsonian motor signs often possess layered comborbid neuropathology. In addition to the age-related multiple syndromes that are capable of producing admixtures of cognitive and motor dysfunction, patients need to be screened for the presence, and relative contributions, of neurodegenerative, cerebrovascular, neoplastic, hemorrhagic, and other pathologies that might cause or contribute to the cognitive dysfunction.

Structural imaging Computed tomography (CT). Computed tomography has diagnostic utility for the urgent evaluation of acute mental status changes that arise within the context of parkinsonism and/or dementia. However, magnetic

resonance imaging (MRI) has supplanted CT as the structural imaging modality of choice, as it provides superior ability to visualize brain structures and pathology, particularly in the posterior fossa. An exception is Fahr’s disease, an idiopathic syndrome manifest by calcification in the basal ganglia, which can present with parkinsonism and can best be detected on CT. Computed tomography is also valuable for the identification of disorders associated with calcium deposits and hemorrhage. Magnetic resonance imaging (MRI). Many pathologic problems that contribute to the development of cognitive/ extrapyramidal motor syndromes can be detected on MRI. Magnetic resonance imaging is also especially valuable for evaluating the distribution and severity of cerebrovascular disease, neoplasia, subdural hematomas, hydrocephalus, prion diseases, and so on, which could contribute to parkinsonism and dementia. Magnetic resonance imaging can be useful in the differential diagnosis of the atypical parkinsonisms (Hauser and Olanow, 1994). Magnetic resonance imaging studies demonstrate pronounced low-signal abnormalities in the striatum on T2-weighted MRI images in patients with atypical parkinsonism (Olanow, 1992) that can help distinguish these conditions from PD. These changes are due to iron accumulation and reflect neurodegeneration in the striatum that is not typically found in idiopathic PD. Cerebellar and brain-stem atrophy are features of olivoponto cerebellar atrophy (OPCA) or MSA-cerebellar type (MSA-C) (Bhattacharya et al., 2002). Bilateral symmetric highsignal abnormalities in the globus pallidus and SN pars reticulate on T1-weighted MRI are indicative of exposure to manganese, which in high concentration has the potential to cause a form of parkinsonism (Olanow, 2004). Serial volumetric T1-weighted MRI images in patients with PD demonstrate a significant loss of brain volume compared to age-matched controls (Hu et al., 2001). Atrophy of the substantia innominata, measured on coronal thin-section T2-weighted MR images, can reflect degeneration of the NBM that is pronounced in patients with AD and PDD (Hanyu et al., 2002). Burton et al. (2004) performed a cross-sectional study to determine if a specific pattern of cerebral atrophy is associated with PDD. Using voxel-based morphometry (VBM), the investigators found reduced gray matter volume in patients with PDD relative to controls in bilateral temporal and occipital lobes as well as in right frontal, left parietal, and some subcortical regions. In contrast, patients with PD without dementia showed only reduced gray matter volume primarily in the frontal lobe compared with controls. In another VBM MRI study, Beyer, Janvin, et al. (2007) found gray matter reductions in frontal, parietal, limbic, and temporal lobes in patients with PDD compared with PD patients with no dementia. In patients with PD with MCI and no dementia, reduced

TABLE

63.5 Neuropsychological Tests Commonly Used to Evaluate Cognitive Functioning in PD

Cognitive Domain

Neuropsychological Test

Global intellectual functioning

Mattis DRS

Estimated level of premorbid cognitive ability

North American Adult Reading Test (NART-R) Shipley Institute of Living Skills Vocabulary (WAIS-III)

Executive functions

Working memory

Digit Span Spatial Span (CANTAB, WMS-III) Letter-Number Sequencing (WMS-III)

Conceptualization

Similarities, Matrix Reasoning (WAIS-III) Wisconsin Card Sort Test Tower of London

Set activation

Verbal Fluency (FAS, Animal Naming)

Set shifting

TMT

Set maintenance

Stroop Test Odd Man Out Test

Motor function

Memory

Speed

Finger-tapping test

Dexterity

Grooved Pegboard

Strength

Hand Dynamometer

Verbal memory

California Verbal Learning Test Logical Memory (WMS-III)

Visual memory

Family Pictures (WMS-III) Visual Reproduction (WMS-R)

Language

Boston Naming Test North American Reading Test (NART-R)

Visual and spatial skills

Visuoconstructive

Copy of the Clock Visual-Motor Integration

Visuospatial

Judgment of Line Orientation Cube Analysis (VOSP) Hooper Visual Organization Test

Visuoperceptual

Benton Facial Recognition Fragmented Letters (VOSP)

Neuropsychiatric

Apathy

Marin Apathy Scale Frontal Systems Behavior Scale

Depression

MADRS Hamilton Depression Inventory Geriatric Depression Scale

Anxiety

Beck Anxiety Inventory YBOCS

Visual hallucination

PPQ

Psychosis

SCID NPI

Caregiver rating scales

ABAS-II Frontal Systems Behavior Scale, caregiver survey

Source: Adapted from Dubois et al. (2007).

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gray matter was detected in left frontal and both temporal lobes (Beyer, Janvin, et al., 2007). Finally, Matsui and colleagues (2007) used diffusion tensor imaging (DTI) to compare fractional anisotropy (FA) values between patients with PD with and without dementia. The PDD group showed significant FA reduction in the bilateral posterior cingulate bundles compared with PD patients with no dementia, and FA values in the left posterior cingulate bundle correlated with several cognitive parameters (Matsui et al., 2007). While no significant volumetric differences were observed in one study of PDD in comparison with DLB (Burton et al., 2004), a more recent study detected more pronounced cortical atrophy in temporal, parietal, and occipital cortical regions in patients with DLB than in patients with PDD despite similarities in the severity of the dementia (Beyer, Larsen, et al., 2007). In sum, MRI is useful in evaluating the patient with PDD but does not permit specific diagnosis of PDD versus other neurodegenerative dementias.

Functional imaging Nuclear: Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET). As with structural neuroimaging, functional imaging can also provide useful information in patients with cognitive and motor dysfunction. Single photon emission computed tomography (SPECT) and positron emission tomography (PET) each offers the potential to image blood flow and perfusion (for example, H215O), metabolic activity (for example, flouro-deoxyglucose [FDG]), and measures of nigro-striatal function including markers of presynaptic DA transporter (carbomethoxy-iodophenyltropane [CIT]), postsynaptic DA receptors, and decarboxylase activity (F-dopa uptake) (Brooks, 1999; Hu et al., 2000). Striatal β -CIT SPECT and FD-PET provide a quantitative measure of nigro-striatal function and can be used for diagnosis of PD and for monitoring disease progression (Sawle et al., 1994; Brooks, 1998; Marek et al., 1998; Ito et al., 1999; Rakshi et al., 1999; Brooks and Samuel, 2000). Positron emission tomography studies have a greater signal-to-noise ratio than SPECT and are generally thought to be more accurate but are less widely available. FD-PET and β -CIT SPECT reveal reduced striatal uptake in patients with PD (Brooks, 1998; Marek et al., 1998). Changes are most pronounced in the posterolateral striatum, the primary projection target of affected nigral neurons, and tend to be asymmetric. FD-PET studies have been used to investigate differences in global DA-ergic function in patients with PD with and without dementia, as well as in normal controls (Ito et al., 2002). No changes in imaging markers of nigrostriatal function were detected between patients with PDD and PD patients without dementia with equivalent parkinsonian motor disability in one study (Ito et al.,

2002). In another, patients with PDD demonstrated a greater reduction in 18F-dopa uptake in the ventral striatum and midbrain, as well as reduced uptake in anterior cingulate regions in comparison to patients with PD with no dementia (Rakshi et al., 1999). These results suggested that dementia in PD is associated with impaired mesolimbic and ventrostriatal DA-ergic function (Ito et al., 2002). Positron emission tomography studies have also been reported to show reduced uptake of 5-HT and noradrenergic markers in patients with PDD compared to patients with PD with no dementia (Brooks, 1998). In patients with PD, 18FDG-PET studies demonstrate hypometabolism in posterior parietal and temporal cortical regions (Hu et al., 2000). In addition, H215O-PET studies reveal reduced blood flow in prefrontal areas during performance on tasks that recruit frontostriatal circuits in comparison with age-matched healthy controls (Cools et al., 2002). However, in patients with earlystage PD with no dementia who performed as well as normal controls on a planning task, perfusion studies showed normal frontal lobe activation during the planning phase despite abnormal processing within the basal ganglia (Dagher et al., 2001). By contrast, patients demonstrated enhanced hippocampal activity; the investigators speculated this could represent a shift to the declarative memory system as a compensation for insufficient working memory capacity within the frontostriatal system (Dagher et al., 2001). Parkinson’s disease–associated derangement of basal ganglia outflow might thus partially underlie the dysexecutive features that are frequently observed in this group of patients (Owen et al., 1998). In general, a variety of frontal, temporal, and parietal metabolic changes have been reported in PDD (Kuhl et al., 1984; Peppard et al., 1992; Vander-Borght et al., 1997), similar to changes reported in AD (Foster et al., 1984) and DLB (Hu et al., 2000), even when LB pathology is restricted to the brain stem (Turjanski and Brooks, 1997). Finally, in comparison to patients with PD, patients with PDD and patients with DLB show decreased metabolism in the inferior and medial frontal lobes bilaterally, and in the right parietal lobe. In contrast, in comparison with patients with PDD, patients with DLB had a greater decrease in metabolic activity in the anterior cingulate region (Yong et al., 2007). Magnetic Resonance Spectroscopy (MRS). The diagnostic utility of magnetic resonance spectroscopy (MRS) derives from its capacity to provide a “chemical biopsy” of a focal region of brain parenchyma. Magnetic resonance spectroscopy can be used to assay neuronal integrity and determine abnormal levels of various markers associated with particular pathogenic processes. Proton MRS (1H MRS) in particular has been used to detect cortical dysfunction in PD and has been correlated with neuropsychological measures (Hu et al., 1999). Early studies in patients with PD found increased cerebral

63: DEMENTIA IN PARKINSON’S DISEASE

lactate levels, a nonspecific MRS marker of metabolic alterations and neuropathology, and even greater increases in those with PDD (Bowen et al., 1995; Brooks, 1999; Hu et al., 2000). A significant reduction in N-acetyl aspartate (NAA), an MRS marker of neuronal integrity, has been found in temporo-parietal regions of patients with PD (Taylor-Robinson et al., 1999). These changes correlate with measures of global cognitive decline independent of motor impairment (Hu et al., 1999). Summerfield et al. (2002) found decreased NAA in the occipital lobes in PDD as compared to PD. Bowen et al. (1995) found that in comparison to healthy controls, there was increased lactate/NAA ratio in the occipital lobes in PD, and even more so in patients with PDD, suggesting impaired oxidative metabolism, particularly in PDD (Bowen et al., 1995). Another potential marker for assessing cognitive decline in PD is 31P-MRS, which is useful for assaying the neuronal bioenergetic state. Significant changes in the inorganic phosphate (Pi)/adenosine triphosphate (ATP) ratio, signifying impaired cellular energy and metabolism, have been found in temporo-parietal cortex of patients with PD compared with controls (Hu et al., 2000). These changes were found to correlate with estimated reductions in cognitive functions. Magnetic resonance spectroscopy studies of patients with PD may thus provide markers of current and possibly future cognitive impairment (Hu et al., 1999, 2000). Functional MRI (fMRI). Functional MRI has become the principal methodology for functional brain mapping and is finding increasing application as a tool for investigating cognitive function in PD. Novel neuropsychological activation paradigms and integrated cognitivemotor-autonomic measurement techniques are being developed to more thoroughly study differences in neuronal activity and metabolism in patients with PD and patients with PDD (Dagher and Nagano-Saito, 2007). A full discussion of this area is beyond the scope of this chapter, but it is anticipated that fMRI will provide insight into cognitive and other neuropsychiatric disorders in patients with PD. Electroenecephalography No specific electroencephalogram (EEG) pattern identifies patients with PD or PDD. However, patients with PDD have been reported to have slower baseline EEG background activity than patients with PD with no dementia (Neufeld et al., 1994). Significant decreases in relative alpha power have also been reported in PDD compared to PD (Sinanovic et al., 2005). A positive correlation between EEG frequency and MMSE scores has also been reported (Sinanovic et al., 2005). Abnormal EEG patterns of spike bursts and suppression raises the possibility of dementia due to prion disease or advanced AD.

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Nuclear cardiac scanning A number of investigators have applied cardiac nuclear scanning to investigate markers that might potentially distinguish PDD from other neurodegenerative dementias (Emre et al., 2007). Cardiac uptake of metaiodobenzylguanidine (MIBG), a marker for noradrenergic transporters, is reduced in patients with PD and patients with DLB (Orimo et al., 1999; Satoh et al., 1999) due to degeneration of postganglionic sympathetic fibers (Orimo et al., 1999). Future studies are needed to determine if there are different patterns in patients with PD and patients with PDD. Cardiac MIBG has been shown to be useful for the differentiation of PD from MSA (Braune et al., 1999) and PSP (Yoshita, 1998) because cardiac MIBG uptake usually remains normal in these conditions. MANAGEMENT We summarize below a step-wise algorithm for managing patients with PDD (Cooper et al., 1992; SaintCyr et al., 1993; Goetz and Stebbins, 1995; Tröster, Paolo, et al., 1995; Graham et al., 1997; Bédard et al., 1999; Rascol et al., 2000; Marjama-Lyons and Koller, 2001; Olanow et al., 2001; Wilson et al., 2002; Alexopoulos et al., 2005; Cummings and Winblad, 2007; Liepelt et al., 2007): 1. Screen for and treat reversible comorbid conditions, for example: a. metabolic b. endocrine c. nutritional d. infectious e. toxic 2. Eliminate or minimize iatrogenic etiologic and/or exacerbating agents—These agents can potentiate confusion and other DA-ergic side effects, including hallucinations, particularly in patients with advanced PD with preexisting cognitive vulnerabilities: a. non-PD agents i. sedatives, hypnotics ii. other central nervous system active agents b. PD agents—remove in the following order i. anticholinergics ii. amantadine iii. monoamine oxidase-B inhibitors (for example, selegiline) iv. dopamine agonists 3. Optimize LD— If the patient still has impaired cognitive function despite the above measures, it is appropriate to gradually lower the LD dose to see if this provides any improvement in cognitive function. It may be preferable to compromise motor control to find an LD dose that does not worsen mental function.

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4. Treat sleep dysregulation. 5. Treat mood dysregulation. 6. Low-dose atypical neuroleptic medications if mental picture is confounded by psychotic signs (hallucinations, delusions, comportmental dysregulation) (see Weintraub and Hurtig, 2007, for a detailed review). Note that these drugs are good for the treatment of hallucinations but typically are not helpful for the treatment of confusion or cognitive impairment. 7. Acetylcholinesterase-inhibitor (AChase-I) trial a. As in AD, acetylcholinesterase inhibitors may provide benefits for patients with PD, primarily by temporarily slowing cognitive degeneration. Rivastigmine and Aricept have been shown to improve cognitive dysfunction and to reduce the rate of decline, but benefits have been modest. Rivastigmine is now available in a transdermal patch formulation for the treatment of PDD. (see Table 63.6 for a summary of relevant clinical trials of acetylcholinesteraseinhibitors [AChaseI] use in PDD.) 8. assess for and implement environmental/behavioral interventions to ensure adequate a. safety and supervision b. daily structured activities c. caregiver support There is considerable interest in testing the value of acetylcholinesterase inhibitors in patients with PD with MCI. Although results have been inconclusive in patients with AD, there are reasons to suspect that results are more likely to be positive in patients with PD. First, it is not clear that patients in the general population with MCI have or will develop a neurodegenerative process. In contrast, patients with PD already have a neurodegenerative process in which the large majority will go on to develop cognitive dysfunction in the

TABLE

later stages of the disease. In addition, the cholinergic deficit in PD is more severe than it is in AD and develops at an earlier stage of the disease. For these reasons, there is some optimism that treatment of MCI in PD will prevent or delay the development of PDD. PROGNOSIS If there are reversible or exacerbating influences that are amenable to some of the above interventions, then select patients with PDD can improve and/or stabilize for sustained time periods. For most, the dementia inexorably advances, eventually contributing to significantly increased morbidity and mortality (Marder et al., 1991; Louis et al., 1997). An analysis by Jellinger et al. (2007) summarized many important prognostic features. In a retrospective analysis of 243 autopsy-confirmed cases of PDD and DLB, the average age at symptom onset was 67, and median survival was 5 years from symptom onset. Older age at symptom onset, fluctuating cognition, early-onset hallucinations, and comorbid AD pathology predicted shorter survival (Jellinger et al., 2007). In contrast, initial parkinsonism without or with delayed onset of dementia is associated with improved survival. When adjusted for age, gender, and AD comorbidity, early dementia onset was identified as the best predictor of poor outcome (Jellinger et al., 2007). Although great progress has been made in recent years in treating the motor features of PD, this review reveals the extensive interest in the nonmotor and non-DA-ergic features of PD, and enhanced awareness of their frequency and potential to cause disability for patients with PD and their caregivers (Olanow et al., in press). As stated, the majority of patients with PD develop cognitive dysfunction and more than one half of patients

63.6 Placebo-controlled Trials of Cholinesterase Inhibitors in PDD

Study

N started/ N completed

Duration (weeks)

AChase-I

Diagnosis

Outcome

Aarsland, 2002

14/12

20

donepezil

PDD

no change in mean UPDRS score

Leroi et al., 2004

16/10

18

donepezil

PDD

no treatment effect for change in NPI score

Emre et al., 2004

541/410

24

rivastigmine

PDD

positive treatment effect for change in NPI score; positive treatment effect for fewer hallucinations as adverse event

Ravina et al., 2005

22/19

10

donepezil

PDD

no treatment effect for change in BPRS total score or BPRS psychosis subscale score

Source: Adapted from Weintraub and Hurtig, 2007. AChase-I: Cholinesterase-inhibitor; PDD: Parkinson’s disease with dementia; UPDRS: Unified Parkinson’s Disease Rating Scale; NPI: Neuropsychiatric Inventory; BPRS: Brief Psychiatric Rating Scale.

63: DEMENTIA IN PARKINSON’S DISEASE

will ultimately develop dementia. Indeed, it is now appreciated that dementia is the most important cause of disability for patients with advanced PD and is the most common cause of nursing home placement (Goetz and Stebbins, 1993; Aarsland et al., 2000; Weintraub et al., 2004). It is hoped that with the advent of new insights into the nature of the cognitive dysfunction and neuropsychiatric problems that occur in PD, soon there will be innovative neuroprotective and restorative therapies that will minimize and even prevent the development of these problems.

REFERENCES Aarsland, D. (2002) Dementia with Lewy bodies. Tidsskr. Nor Laegeforen. 122(5):525–529. Aarsland, D., Andersen, K., Larsen, J.P., et al. (2001) Risk of dementia in Parkinson’s disease: a community-based, prospective study. Neurology 56:730–736. Aarsland, D., Andersen, K., Larsen, J.P., et al. (2004) The rate of cognitive decline in Parkinson’s disease. Arch. Neurol. 61: 1906– 1911. Aarsland, D., Andersen, K., Larsen, J.P., Lolk, A.L., and KraghSorensen, P. (2003) Prevalence and characteristics of dementia in Parkinson disease: an 8-year prospective study. Arch. Neurol. 60:387–392. Aarsland, D., Ballard, C., Larsen, J.P., and McKeith, I. (2001) A comparative study of psychiatric symptoms in dementia with Lewy bodies and Parkinson’s disease with and without dementia. Int. J. Geriatr. Psychiatry 16(5):528–536. Aarsland, D., Brønnick, K., and Her, U. (2007) Neuropsychiatric symptoms in patients with Parkinson’s disease and dementia: frequency, profile and associated care giver stress. J. Neurol. Neurosurg. Psychiat. 78(1):36–42. Aarsland, D., Kvaloy, J.T., Andersen, K., et al. (2007) The effect of age of onset of PD on risk of dementia. J. Neurol. 254(1): 38–45. Aarsland, D., Larsen, J.P., Lim, N.G., Janvin, C., Karlsen, K., Tandberg, E., and Cummings, J.L. (1999) Range of neuropsychiatric disturbances in patients with Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 67(4):492– 496. Aarsland, D., Larsen, J.P., Tandberg, E., and Laake, K. (2000) Predictors of nursing home placement in Parkinson’s disease: a population-based, prospective study. J. Am. Geriatr. Soc. 48(8): 938–942. Aarsland, D., Perry, R., Larsen, J.P., McKeith, I.G., O’Brien, J.T., Perry, E.K., Burn, D., and Ballard, C.G. (2005) Neuroleptic sensitivity in Parkinson’s disease and parkinsonian dementias. J. Clin. Psychiatry 66(5):633–637. Aarsland, D., Tandberg, E., Larsen, J.P., and Cummings, J.L. (1996) Frequency of dementia in Parkinson’s disease. Arch. Neurol. 53(6):538–542. Aarsland, D., Zaccai, J., and Brayne, C. (2005) A systematic review of prevalence studies of dementia in Parkinson’s disease. Mov. Disord. 20:1255–1263. Agid, Y., Javoy-Agid, F., and Ruberg, M. (1987) Biochemistry of neurotransmitters in Parkinson’s disease. In: Marsden, C.D., and Fahn, S., eds. Movement Disorders 2: Neurology, Vol. 7. London: Butterworths, pp. 166–230. Ahlskojg, J.E. (2007) Beating a dead horse: dopamine and Parkinson disease. Neurology 69(17):1701–1711. Albert, M.L., Feldman, R.G., and Willis, A.L. (1974) The “subcortical dementia” of progressive supranuclear palsy. J. Neurol. Neurosurg. Psychiatry 37(2):121–130.

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Alex, K.D., and Pehek, E.A. (2007) Pharmacologic mechanisms of serotonergic regulation of dopamine neurotransmission. Pharmacol. Ther. 113(2):296–320. Alexander, G.E., DeLong, M.R., and Strick, P.L. (1986) Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu. Rev. Neurosci. 9:357–381. Alexopoulos, G.S., Jeste, D.V., Chung, H., et al. (2005) The expert consensus guideline series. Treatment of dementia and its behavioral disturbances. Introduction: methods, commentary, and summary. Postgrad. Med. Jan (Spec No): 6–22 Alpert, M., Rosen, A., Welkowitz, J., and Lieberman, A. (1990) Interpersonal communication in the context of dementia. J. Commun. Disord. 23(4/5):337–346. Alves, G., Larsen, J.P., Emre, M., Wentzel-Larsen, T., and Aarsland, D. (2006) Changes in motor subtype and risk for incident dementia in Parkinson’s disease. Mov. Disord. 21:1123–1130. Anthony, J.C., LeResche, L., Niaz, U., von Korff, M.R., and Folstein, M.F. (1982) Limits of the “Mini-Mental State” as a screening test for dementia and delirium among hospital patients. Psychol. Med. 12(2):397– 408. Appleby, B.S., Duggan, D.S., Regenberg, A., and Rabins, P.V. (2007) Psychiatric and neuropsychiatric adverse events associated with deep brain stimulation: A meta-analysis of ten years’ experience. Mov. Disord. 22(12):1722–1728. Ardouin, C., Pillon, B., Peiffer, E., Bejjani, P., Limousin, P., Damier, P., Arnulf, I., Benabid, A.L., Agid, Y., and Pollak, P. (1999) Bilateral subthalamic or pallidal stimulation for Parkinson’s disease affects neither memory nor executive functions: a consecutive series of 62 patients. Ann. Neurol. 46(2):217–223. Arnsten, A.F., Mathew, R., Ubriani, R., Taylor, J.R., and Li, B.M. (1999) Alpha-1 noradrenergic receptor stimulation impairs prefrontal cortical cognitive function. Biol. Psychiatry 45(1):26–31. Assal, F., and Cummings, J.L. (2002) Neuropsychiatric symptoms in the dementias. Curr. Opin. Neurol. 15(4):445– 450. Athey, R.J., Porter, R.W., and Walker, R.W. (2005) Cognitive assessment of a representative community population with Parkinson’s disease (PD) using the Cambridge Cognitive Assessment-Revised (CAMCOG-R). Age Ageing 34:268–273. Aybek, S., Gronchi-Perrin, A., Berney, A., et al. (2007) Long-term cognitive profile and incidence of dementia after STN-DBS in Parkinson’s disease. Mov. Disord. 22(7):974–981. Ballard, C.G., Aarsland, D., McKeith, I., et al. (2002) Fluctuations in attention: PD dementia vs DLB with parkinsonism. Neurology 59:1714–1720. Baronti, F. (2002) [Psychological and cognitive problems in Parkinson disease—therapeutic possibilities] [German]. Schweiz. Rundsch. Med. Prax. 91(10):411– 417. Bédard, M.A., el Massioui, F., Malapani, C., Dubois, B., Pillon, B., Renault, B., and Agid, Y. (1998) Attentional deficits in Parkinson’s disease: partial reversibility with naphtoxazine (SDZ NVI085), a selective noradrenergic alpha 1 agonist. Clin. Neuropharmacol. 21(2):108–117. Bédard, M.A., Pillon, B., Dubois, B., Duchesne, N., Masson, H., and Agid, Y. (1999) Acute and long-term administration of anticholinergics in Parkinson’s disease: specific effects on the subcortico-frontal syndrome. Brain Cogn. 40(2):289–313. Bejjani, B.P., Damier, P., Arnulf, I., et al. (1999) Transient acute depression induced by high-frequency deep brain stimulation. N. Engl. J. Med. 340:1476–1480. Berding, G., Odin, P., Brooks, D.J., Nikkhah, G., Matthies, C., Peschel, T., Shing, M., Kolbe, H., van Den Hoff, J., Fricke, H., Dengler, R., Samii, M., and Knapp, W.H. (2001) Resting regional cerebral glucose metabolism in advanced Parkinson’s disease studied in the off and on conditions with [(18)F]FDG-PET. Mov. Disord. 16(6):1014–1022. Berger, H.J., van Es, N.J., van Spaendonck, K.P., Teunisse, J.P., Horstink, M.W., van’t Hof, M.A., and Cools, A.R. (1999) Rela-

1056

DEMENTIA

tionship between memory strategies and motor symptoms in Parkinson’s disease. J. Clin. Exp. Neuropsychol. 21(5):677–684. Bergman, J., and Lerner, V. (2002) Successful use of donepezil for the treatment of psychotic symptoms in patients with Parkinson’s disease. Clin. Neuropharmacol. 25(2):107–110. Berry, E.L., Nicolson, R.I., Foster, J.K., Behrmann, M., and Sagar, H.J. (1999) Slowing of reaction time in Parkinson’s disease: the involvement of the frontal lobes. Neuropsychologia 37(7):787– 795. Beyer, M.K., Janvin, C.C., Jan, P., Larsen, J.P., and Dag Aarsland, D. (2007) A magnetic resonance imaging study of patients with Parkinson’s disease with mild cognitive impairment and dementia using voxel-based morphometry. J. Neurol. Neurosurg. Psychiatry 78:254–259. Beyer, M.K., Larsen, J.P., and Aarsland, D. (2007) Gray matter atrophy in Parkinson disease with dementia and dementia with Lewy bodies. Neurology 69:747–754. Bhattacharya, K., Saadia, D., Eisenkraft, B., Yahr, M.D., Olanow, W., Drayer, B., and Kaufmann, H. (2002) Brain magnetic resonance imaging in multiple system atrophy and Parkinson’s disease. A diagnostic algorithm. Arch. Neurol. 59:835–842. Biggins, C.A., Boyd, J.L., Harrop, F.M., Madeley, P., Mindham, R.H., Randall, J.I., and Spokes, E.G. (1992) A controlled, longitudinal study of dementia in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 55(7):566–571. Birnbaum, S., Gobeske, K.T., Auerbach, J., Taylor, J.R., and Arnsten, A.F. (1999) A role for norepinephrine in stress-induced cognitive deficits: alpha-1-adrenoceptor mediation in the prefrontal cortex. Biol. Psychiatry 46(9):1266–1274. Blanchet, S., Marie, R.M., Dauvillier, F., Landeau, B., Benali, K., Eustache, F., and Chavoix, C. (2000) Cognitive processes involved in delayed non-matching-to-sample performance in Parkinson’s disease. Eur. J. Neurol. 7(5):473– 483. Boeve, B. (2003) Diagnosis and management of the non-Alzheimer dementias. In: Noseworth, J.W., ed. Neurological Therapeutics. London: Martin Dunitz, pp. 2826–2854. Boeve, B.F. (2007) Parkinson-related dementias. Neurol. Clin. 25(3): 761–781. Bohnen, N.I., and Frey, K.A. (2007) Imaging of cholinergic and monoaminergic neurochemical changes in neurodegenerative disorders. Mol. Imaging Biol. 9(4):243–257. Boller, F., Mizutani, T., Roessmann, U., and Gambetti, P. (1980) Parkinson disease, dementia and Alzheimer disease: clinicopathological correlations. Ann. Neurol. 7:329–335. Boller, F., Passafiume, D., Keefe, N.C., Rogers, K., Morrow, L., and Kim, Y. (1984) Visuospatial impairment in Parkinson’s disease. Role of perceptual and motor factors. Arch. Neurol. 41(5): 485– 490. Bondi, M.W., Kaszniak, A.W., Bayles, K.A., and Vance, K.T. (1993) Contribution of frontal system dysfunction to memory and perceptual ability in Parkinson’s disease. Neuropsychology 7:89–102. Bosboom, J.L., Stoffers, D., and Wolters, E. Ch. (2004) Cognitive dysfunction and dementia in Parkinson’s disease. J. Neural Transm. 111(10/11):1303–1315. Bowen, B.C., Block, R.E., Sanchez-Ramos, J., Pattany, P.M., Lampman, D.A., Murdoch, J.B., and Quencer, R.M. (1995) Proton MR spectroscopy of the brain in 14 patients with Parkinson disease. Am. J. Neuroradiol. 16(1):61–68. Bowen, F.P., Hoehn, M.M., and Yahr, M.D. (1972) Parkinsonism: alterations in spatial orientation as determined by a route-walking test. Neuropsychologia 10(3):355–361. Bowen, F.P., Kamienny, R.S., Burns, M.M., and Yahr, M. (1975) Parkinsonism: effects of levodopa treatment on concept formation. Neurology 25(8):701–704. Boyd, J.L., Cruickshank, C.A., Kenn, C.W., Madeley, P., Mindham, R.H., Oswald, A.G., Smith, R.J., and Spokes, E.G. (1991) Cognitive impairment and dementia in Parkinson’s disease: a controlled study. Psychol. Med. 21(4):911–921.

Braak, H., Del Tredici, K., Rub, U., et al. (2003) Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol. Aging 24(2):197–211. Braak, H., Muller, C.M., Rub, U., et al. (2006a) Pathology associated with sporadic Parkinson’s disease--where does it end? J. Neural Transm. Suppl. (70):89–97. Braak, H., Rub, U., and Del Tredici, K. (2006b) Cognitive decline correlates with neuropathological stage in Parkinson’s disease. J. Neurol. Sci. 248(1/2):255–258. Bradley, V.A., Welch, J.L., and Dick, D.J. (1989) Visuospatial working memory in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 52(11):1228–1235. Braune, S., Reinhardt, M., Schnitzer, R., Riedel, A., and Lucking, C.H. (1999) Cardiac uptake of [123I]MIBG separates Parkinson’s disease from multiple system atrophy. Neurology 53:1020– 1025. Brodsky, M.A., Godbold, J., Roth, T., and Olanow, C.W. (2003) Sleepiness in Parkinson’s disease: a controlled study. Mov. Disord. 18:668–672. Bronnick, K., Emre, M., Lane, R., Tekin, S., and Aarsland, D. (2007) Profile of cognitive impairment in dementia associated with Parkinson’s disease compared with Alzheimer’s disease. J. Neurol. Neurosurg. Psychiatry. 78(10):1064–1068. Brooks, D.J. (1998) The early diagnosis of Parkinson’s disease. Ann. Neurol. 44(3 Suppl 1):S10–S18. Brooks, D.J. (1999) Functional imaging of Parkinson’s disease: is it possible to detect brain areas for specific symptoms? J. Neural. Transm. Suppl. 56:139–153. Brooks, D.J. (2000) Morphological and functional imaging studies on the diagnosis and progression of Parkinson’s disease. J. Neurol. 247(Suppl 2):II11–II18. Brooks, D.J., and Piccini, P. (2006) Imaging in Parkinson’s disease: the role of monoamines in behavior. Biol. Psychiatry 59(10): 908–918. Brooks, D.J., and Samuel, M. (2000) The effects of surgical treatment of Parkinson’s disease on brain function: PET findings. Neurology 55(12 Suppl 6):S52–S59. Brown, R.G., and Marsden, C.D. (1984) How common is dementia in Parkinson’s disease? Lancet 2(8414):1262–1265. Brown, R.G., and Marsden, C.D. (1986) Visuospatial function in Parkinson’s disease. Brain 109(Pt 5):987–1002. Brown, R.G., and Marsden, C.D. (1988) Internal versus external cues and the control of attention in Parkinson’s disease. Brain 111(Pt 2):323–345. Brown, R.G., and Marsden, C.D. (1990) Cognitive function in Parkinson’s disease: from description to theory. Trends Neurosci. 13(1):21–29. Brown, R.G., Jahanshahi, M., and Marsden, C.D. (1993) The execution of bimanual movements in patients with Parkinson’s, Huntington’s and cerebellar disease. J. Neurol. Neurosurg. Psychiatry 56(3):295–297 [comment in: J. Neurol. Neurosurg. Psychiatry (1994) 57(1):126]. Brown, R.G., MacCarthy, B., Gotham, A.M., Der, G.J., and Marsden, C.D. (1988) Depression and disability in Parkinson’s disease: a follow-up of 132 cases. Psychol. Med. 18(1):49–55. Brown, R.G., Marsden, C.D., Quinn, N., and Wyke, M.A. (1984) Alterations in cognitive performance and affect-arousal state during fluctuations in motor function in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 47(5):454 – 465. Burkhard, P.R., Vingerhoets, F.J., Berney, A., Bogousslavsky, J., Villemure, J.G., and Ghika, J. (2004) Suicide after successful deep brain stimulation for movement disorders. Neurology 63(11):2170–2172. Burn, D.J. (2006a) Cortical Lewy body disease and Parkinson’s disease dementia. Curr. Opin. Neurol. 19:572–579. Burn, D.J. (2006b) Parkinson’s disease dementia: what’s in a Lewy body? J. Neural Transm. Suppl. 70:361–365.

63: DEMENTIA IN PARKINSON’S DISEASE Burn, D.J., Rowan, E.N., Allan, L.M., Molloy, S., O’Brien, J.T., and McKeith, I.G. (2006) Motor subtype and cognitive decline in Parkinson’s disease, Parkinson’s disease with dementia, and dementia with Lewy bodies J. Neurol. Neurosurg. Psychiatry 77: 585–589. Burn, D.J., Rowan, E.N., Minnett, T., et al. (2003) Extrapyramidal features in Parkinson’s disease with and without dementia and dementia with Lewy bodies: a cross-sectional comparative study. Mov. Disord. 18:884–889. Burn, D.J., and Troster, A.I. (2004) Neuropsychiatric complications of medical and surgical therapies for Parkinson’s disease. J. Geriatr. Psychiatry Neurol. 17(3):172–180. Burton, E.J., McKeith, I.G., Burn, D.J., Williams, E.D., and O’Brien, J.T. (2004) Cerebral atrophy in Parkinson’s disease with and without dementia: a comparison with Alzheimer’s disease, dementia with Lewy bodies and controls. Brain 127(4):791–800. Buytenhuijs, E.L., Berger, H.J., Van Spaendonck, K.P., Horstink, M.W., Borm, G.F., and Cools, A.R. (1994) Memory and learning strategies in patients with Parkinson’s disease. Neuropsychologia 32(3):335–342. Byrne, E.J., Lowe, J., Godwin-Austen, R.B., Arie, T., and Jones, R. (1987) Dementia of Parkinson’s disease associated with diffuse cortical Lewy bodies. Lancet 1:501. Caballol, N., Picconi, M.J., and Tolosa, E. (2007) Cognitive dysfunction and dementia in Parkinson disease. Mov. Disord. (Suppl 17):S358–S366. Cahn-Weiner, D.A., Grace, J., Ott, B.R., Fernandez, H.H., Friedman, J.H. (2002) Cognitive and behavioral features discriminate between Alzheimer’s and Parkinson’s disease. Neuropsychiatry Neuropsychol. Behav. Neurol. 15:79–87. Cahn-Weiner, D.A., Williams, K., Grace, J., Tremont, G., Westervelt, H., and Stern, R.A. (2003) Discrimination of dementia with Lewy bodies from Alzheimer disease and Parkinson disease using the clock drawing test. Cogn. Behav. Neurol. 16:85–92. Calabresi, P., Picconi, B., Parnetti, L., and DiFilippo, M. (2006) A convergent model for cognitive dysfunctions in Parkinson’s disease: the critical dopamine-acetylcholine synaptic balance. Lancet Neurol. 5(11):974–983. Camicioli, R., Rajput, A., Rajput, M., et al. (2005) Apolipoprotein E-ε4 and catechol-O-methyltransferase alleles in autopsy-proven Parkinson’s disease: relationship to dementia and hallucinations. Mov. Disord. 20:989–994. Chamberlain, S.R., Muller, U., Robbins, T.W., and Sahakian, B.J. (2006) Neuropharmacological modulation of cognition. Curr. Opin. Neurol. 19(6):607–612. Charcot, J.M. (1877) Leçons sur les Maladies du Système Nerveux Faites à la Salpétrière. Recueillies par Bourneville. Tome I, 3rd ed. Paris: pp. 155–188. Chaudhuri, K.R., Healy, D.G., and Schapira, A.H. (2006) Nonmotor symptoms of Parkinson’s disease: diagnosis and management. Lancet Neurol. 5(3):235–245. Chow, T.W., Miller, B.L., Hayashi, V.N., and Geschwind, D.H. (1999) Inheritance of frontotemporal dementia. Arch. Neurol. 56(7):817–822. Chui, H.C., Teng, E.L., Henderson, V.W., and Moy, A.C. (1985) Clinical subtypes of dementia of the Alzheimer type. Neurology 35:1544–1550. Cohen, O.S., Vakil, E., Tanne, D., Nitsan, Z., Schwartz, R., and Hassin-Baer, S. (2007) Educational level as a modulator of cognitive performance and neuropsychiatric features in Parkinson disease. Cogn. Behav. Neurol. 20(1):68–72. Contestabile, A., Ciani, E, and Contestabile, A (2007) The place of choline acetyltransferase activity measurement in the “cholinergic hypothesis” of neurodegenerative diseases. Neurochem. Res. 33(2): 318–327. Cools, A.R., van den Bercken, J.H., Horstink, M.W., van Spaendonck, K.P., and Berger, H.J. (1984) Cognitive and motor

1057

shifting aptitude disorder in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 47(5):443– 453. Cools, R. (2006) Dopaminergic modulation of cognitive functionimplications for L-DOPA treatment in Parkinson’s disease. Neurosci. Biobehav. Rev. 30(1):1–23. Cools, R., Barker, R.A., Sahakian, B.J., and Robbins, T.W. (2001a) Enhanced or impaired cognitive function in Parkinson’s disease as a function of dopaminergic medication and task demands. Cereb. Cortex 11(12):1136–1143. Cools, R., Barker, R.A., Sahakian, B.J., and Robbins, T.W. (2001b) Mechanisms of cognitive set flexibility in Parkinson’s disease. Brain 124(Pt 12):2503–2512. Cools, R., Stefanova, E., Barker, R.A., Robbinson, T.W., and Owen, A.M. (2002) Dopaminergic modulation of high-level cognition in Parkinson’s disease: the role of the prefrontal cortex revealed by PET. Brain 125(Pt 3):584–594. Cooper, J.A., and Sagar, H.J. (1993a) Encoding deficits in untreated Parkinson’s disease. Cortex 29(2):251–265. Cooper, J.A., and Sagar, H.J. (1993b) Incidental and intentional recall in Parkinson’s disease: an account based on diminished attentional resources. J. Clin. Exp. Neuropsychol. 15(5):713–731. Cooper, J.A., Sagar, H.J., Doherty, S.M., Jordan, N., Tidswell, P., and Sullivan, E.V. (1992) Different effects of dopaminergic and anticholinergic therapies on cognitive and motor function in Parkinson’s disease. A follow-up study of untreated patients. Brain 115(Pt 6):1701–1725. Cooper, J.A., Sagar, H.J., Jordan, N., Harvey, N.S., and Sullivan, E.V. (1991) Cognitive impairment in early, untreated Parkinson’s disease and its relationship to motor disability. Brain 114(Pt 5): 2095–2122. Cooper, J.A., Sagar, H.J., Tidswell, P., and Jordan, N. (1994) Slowed central processing in simple and go/no-go reaction time tasks in Parkinson’s disease. Brain 117(Pt 3):517–529. Cormack, F., Aarsland, D., Ballard, C., and Tovee, M.J. (2004) Pentagon drawing and neuropsychological performance in Dementia with Lewy bodies, Alzheimer’s disease, Parkinson’s disease and Parkinson’s disease with dementia. Int. J. Geriatr. Psychiatry 19:371–377. Critchley, H. (2005) Neural mechanisms of autonomic, affective, and cognitive integration. J. Comparative Neurol. 493(1):154–166. Cropley, V.L., Fujita, M., Innis, R.B., and Nathan, P.J. (2006) Molecular imaging of the dopaminergic system and its association with human cognitive function. Biol. Psych. 59(10):898–907. Cummings, J., and Winblad, B. (2007) A rivastigmine patch for the treatment of Alzheimer’s disease and Parkinson’s disease dementia. Expert Rev. Neurother. 7(11):1457–1463. Cummings, J.L. (1988) Intellectual impairment in Parkinson’s disease: clinical, pathologic, and biochemical correlates. J. Geriatr. Psychiatry Neurol. 1:24–36. Cummings, J.L. (1995) Anatomic and behavioral aspects of frontalsubcortical circuits. Ann. N.Y. Acad. Sci. 15(769):1–13. Cummings, J.L., Darkins, A., Mendez, M., Hill, M.A., and Benson, D.F. (1988) Alzheimer’s disease and Parkinson’s disease: comparison of speech and language alterations. Neurology 38:680–684. Dagher, A., and Nagano-Saito, A. (2007) Functional and anatomical magnetic resonance imaging in Parkinson’s disease. Mol. Imaging Biol. 9(4):234–242. Dagher, A., Owen, A.M., Boecker, H., and Brooks, D.J. (2001) The role of the striatum and hippocampus in planning: a PET activation study in Parkinson’s disease. Brain 124(Pt 5):1020–1032. de Lau, L.M., Schipper, C.M., Hofman, A., Koudstaal, P.J., and Breteler, M.M. (2005) Prognosis of Parkinson disease: risk of dementia and mortality: the Rotterdam Study. Arch. Neurol. 62: 1265–1269. De Marco, E.V., Tarantino, P., Rocca, F.E., et al. (2008) Alphasynuclein promoter haplotypes and dementia in Parkinson’s disease. Am. J. Med. Genet. B Neuropsychiatr. Genet. 147(3):403– 407.

1058

DEMENTIA

Ditter, S.M., and Mirra, S.S. (1987) Neuropathologic and clinical features of Parkinson’s disease in Alzheimer’s disease patients. Neurology 37:754–760. Dodd, M.L., Klos, K.J., Bower, J.H., Geda, Y.E., Josephs, K.A., and Ahlskog, J.E. (2005) Pathological gambling caused by drugs used to treat Parkinson disease. Arch. Neurol. 62(9):1377–1381. Dooneief, G., Mirabello, E., Bell, K., Marder, K., Stern, Y., and Mayeux, R. (1992) An estimate of the incidence of depression in idiopathic Parkinson’s disease. Arch. Neurol. 49(3):305–307. Downes, J.J., Priestley, N.M., Doran, M., Ferran, J., Ghadiali, E., and Cooper, P. (1998) Intellectual, mnemonic, and frontal functions in dementia with Lewy bodies: a comparison with early and advanced Parkinson’s disease. Behav. Neurol. 11(3):173–183. Downes, J.J., Sharp, H.M., Costall, B.M., Sagar, H.J., and Howe, J. (1993) Alternating fluency in Parkinson’s disease. An evaluation of the attentional control therapy of cognitive impairment. Brain 116(Pt 4):887–902. Dubinsky, R.M., Gray, C., Husted, D., Busenbark, K., Vetere-Overfield, B., Wiltfong, D., Parrish, D., and Koller, W.C. (1991) Driving in Parkinson’s disease. Neurology 41(4):517–520. Dubois, B., Burn, D., Goetz, C., et al. (2007) Movement Disorder Society Task Force practical strategies for the diagnosis of Parkinson’s disease dementia. Mov. Disord. 22:2314–2324. Dubois, B., and Pillon, B. (1997) Cognitive deficits in Parkinson’s disease. J. Neurol. 244(1):2–8. Dubois, B., and Pillon, B. (1998) Cognitive and behavioral aspects of movement disorders. In: Jankovic, J., and Tolosa, E., eds. Parkinson’s Disease and Movement Disorders. Baltimore: Williams & Wilkins, pp. 837–858. Dubois, B., Pillon, B., Sternic, N., Lhermitte, F., and Agid, Y. (1990) Age-induced cognitive disturbances in Parkinson’s disease. Neurology 40(1):38–41. Ebmeier, K.P., Calder, S.A., Crawford, J.R., Stewart, L., Besson, J.A., and Mutch, W.J. (1990a) Clinical features predicting dementia in idiopathic Parkinson’s disease: a follow-up study. Neurology 40(8):1222–1224. Ebmeier, K.P., Calder, S.A., Crawford, J.R., Stewart, L., Besson, J.A., and Mutch, W.J. (1990b) Mortality and causes of death in idiopathic Parkinson’s disease: results from the Aberdeen whole population study. Scott. Med. J. 35(6):173–175. Ebmeier, K.P., Calder, S.A., Crawford, J.R., Stewart, L., Cochrane, R.H., and Besson, J.A. (1991) Dementia in idiopathic Parkinson’s disease: prevalence and relationship with symptoms and signs of parkinsonism. Psychol. Med. 21(1):69–76. Ebmeier, K.P., Potter, D.D., Cochrane, R.H., Crawford, J.R., Stewart, L., Calder, S.A., Besson, J.A., and Salzen, E.A. (1992) Event related potentials, reaction time, and cognitive performance in idiopathic Parkinson’s disease. Biol. Psychol. 33(1):73–89. El-Ghundi, M., O’Dowd, B.F., and George, S.R. (2007) Insights into the role of dopamine receptor systems in learning and memory. Rev. Neurosci. 18(1):37–66. Elizan, T.S., Sroka, H., Maker, H., Smith, H., and Yahr, M.D. (1986) Dementia in idiopathic Parkinson’s disease. Variables associated with its occurrence in 203 patients. J. Neural. Transm. 65(3/4): 285–302. Emre, M. (2003) What causes mental dysfunction in Parkinson’s disease? Mov. Disord. 18(Suppl 6):S63–S71. Emre, M., Aarsland, D., Albanese, A., et al. (2004) Rivastigmine for dementia associated with Parkinson’s disease. N. Engl. J. Med. 351(24):2509–2518. Emre, M., Aarsland, D., Brown, R., et al. (2007) Clinical diagnostic criteria for dementia associated with Parkinson’s disease. Mov. Disord. 22:1689–1707. Engelborghs, S., Maertens, K., Nagels, G., et al. (2005) Neuropsychiatric symptoms of dementia: cross-sectional analysis from a prospective, longitudinal Belgian study. Int. J. Geriatr. Psychiatry 20:1028–1037.

Evans, A.H., Katzenschlager, R., Paviour, D., et al. (2004) Punding in Parkinson’s disease: its relation to the dopamine dysregulation syndrome. Mov. Disord. 19:397–405. Factor, S.A., Feustel, P.J., Friedman, J.H., Comella, C.L., Goetz, C.G., Kurlan, R., Parsa, M., Pfeiffer, R., and the Parkinson Study Group. (2003) Longitudinal outcome of Parkinson’s disease patients with psychosis. Neurology 60:1756–1761. Fearnley, J.M., and Lees, A.J. (1991) Ageing and Parkinson’s disease: substantia nigra regional selectivity. Brain 114:2283–2301. Fénelon, G., Goetz, C.G., and Karenberg, A. (2006) Hallucinations in Parkinson disease in the prelevodopa era. Neurology 66: 93–98. Fénelon, G., Mahieux, F., Huon, R., and Ziegler, M. (2000) Hallucinations in Parkinson’s disease: prevalence, phenomenology, and risk factors. Brain 123:733–745. Fernandez, H.H., and Lapane, K.L. (2002) Predictors of mortality among nursing home residents with a diagnosis of Parkinson’s disease. Med. Sci. Monit. 8(4):CR241–CR246. Ferraro, F.R., Balota, D.A., and Connor, L.T. (1993) Implicit memory and the formation of new associations in nondemented Parkinson’s disease individuals and individuals with senile dementia of the Alzheimer type: a serial reaction time (SRT) investigation. Brain Cogn. 21(2):163–180. Fields, J.A., Troster, A.I., Wilkinson, S.B., Pahwa, R., and Koller, W.C. (1999) Cognitive outcome following staged bilateral pallidal stimulation for the treatment of Parkinson’s disease. Clin. Neurol. Neurosurg. 101(3):182–188. Filoteo, J.V., and Maddox, W.T. (1999) Quantitative modeling of visual attention processes in patients with Parkinson’s disease: effects of stimulus integrality on selective attention and dimensional integration. Neuropsychology 13(2):206–222. Folstein, M.F., Folstein, S.E., and McHugh, P.R. (1975) “Mini-mental state.” A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 12(3):189–198. Foltynie, T., Brayne, C., and Barker, R.A. (2002) The heterogeneity of idiopathic Parkinson’s disease. J. Neurol. 249:138–145. Foltynie, T., Brayne, C.E., Robbins, T.W., and Barker, R.A. (2004) The cognitive ability of an incident cohort of Parkinson’s patients in the UK. The CamPaIGN study. Brain 127:550–560. Foster, N.L., Chase, T.N., Mansi, L., et al. (1984) Cortical abnormalities in Alzheimer’s disease. Ann. Neurol. 16:649–654. Fournet, N., Moreaud, O., Roulin, J.L., Naegele, B., and Pellat, J. (2000) Working memory functioning in medicated Parkinson’s disease patients and the effect of withdrawal of dopaminergic medication. Neuropsychology 14(2):247–253. Francis, P.T., and Perry, E.K. (2007) Cholinergic and other neurotransmitter mechanisms in Parkinson’s disease, Parkinson’s disease dementia, and dementia with Lewy bodies. Mov. Disor. Suppl 17:S351–S357. Frank, M.J., Scheres, A., and Sherman, S.J. (2007) Understanding decision-making deficits in neurological conditions: insights from models of natural action selection. Philos. Trans. R Soc. Lond. B Biol. Sci. 362(1485):1641–1654. Galvin, J.E. (2006) Cognitive change in Parkinson disease. Alzheimer Dis. Assoc. Disord. 20(4):302–310. Gaspar, P., and Gray, F. (1984) Dementia in idiopathic Parkinson’s disease: a neuropathological study of 32 cases. Acta Neuropathol. 64:43–52. Gelb, D.J., Oliver, E., and Gilman, S. (1999) Diagnostic criteria for Parkinson disease. Arch. Neurol. 56:33–39. Gemmell, H.G., Sharp, P.F., Smith, F.W., Besson, J.A., Ebmeier, K.P., Davidson, J., Evans, N.T., Roeda, D., Newton, R., and Mallard, J.R. (1989) Cerebral blood flow measured by SPECT as a diagnostic tool in the study of dementia. Psychiatry Res. 29(3): 327–329. Ghika, J., Ghika-Schmid, F., Fankhauser, H., Assal, G., Vingerhoets, F., Albanese, A., Bogousslavsky, J., and Favre, J. (1999) Bilateral

63: DEMENTIA IN PARKINSON’S DISEASE contemporaneous posteroventral pallidotomy for the treatment of Parkinson’s disease: neuropsychological and neurological side effects. Report of four cases and review of the literature. J. Neurosurg. 91(2):313–321; comment in: J. Neurosurg. 2000 92(3):509. Giladi, N., Treves, T.A., Paleacu, D., Shabtai, H., Orlov, Y., Kandinov, B., Simon, E.S., and Korczyn, A.D. (2000) Risk factors for dementia, depression, and psychosis in long-standing Parkinson’s disease. J. Neural Transm. 10:759–771. Gjerstad, M.D., Boeve, B., Wentzel-Larsen, T., et al. (2007) Occurrence and clinical correlates of REM sleep behavior disorder in patients with Parkinson’s disease over time. J. Neurol. Neurosurg. Psychiatry 79(4):387–391. Glatt, S.L., Hubble, J.P., Lyons, K., Paolo, A., Troster, A.I., Hassanein, R.E., and Koller, W.C. (1996) Risk factors for dementia in Parkinson’s disease: effect of education. Neuroepidemiology 15(1):20–25. Goetz, C.G., and Stebbins, G.T. (1993) Risk factors for nursing home placement in advanced Parkinson’s disease. Neurology 43(11): 2227–2229. Goetz, C.G., and Stebbins, G.T. (1995) Mortality and hallucinations in nursing home patients with advanced Parkinson’s disease. Neurology 45(4):669–671. Goldmann Gross, R., Siderowf, A., and Hurtig, H.I. (2008) Cognitive impairment in Parkinson’s disease and dementia with Lewy bodies: a spectrum of disease. Neurosignals 16(1):24–34. Goldman-Rakic, P.S. (1998) The cortical dopamine system: role in memory and cognition. Adv. Pharmacol. 42:707–711. Goldman-Rakic, P.S. (1999) The physiological approach: functional architecture of working memory and disordered cognition in schizophrenia. Biol. Psychiatry46(5):650–661. Gotham, A.M., Brown, R.G., and Marsden, C.D. (1986a) Depression in Parkinson’s disease: a quantitative and qualitative analysis. J. Neurol. Neurosurg. Psychiatry 49(4):381–389. Gotham, A.M., Brown, R.G., and Marsden, C.D. (1986b) Levodopa treatment may benefit or impair “frontal” function in Parkinson’s disease. Lancet 2(8513):970–971. Gotham, A.M., Brown, R.G., and Marsden, C.D. (1988) “Frontal” cognitive function in patients with Parkinson’s disease “on” and “off” levodopa. Brain 111(Pt 2):299–321. Graham, J.M., Grunewald, R.A., and Sagar, H.J. (1997) Hallucinosis in idiopathic Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 63(4):434 – 440. Graham, J.M., and Sagar, H.J. (1999) A data-driven approach to the study of heterogeneity in idiopathic Parkinson’s disease: identification of three distinct subtypes. Mov. Disord. 14(1):10–20. Green, T., and Camicioli, R. (2007) Depressive symptoms and cognitive status affect health-related quality of life in older patients with Parkinson’s disease. J. Am. Geriatr. Soc. 55(11):1888–1890. Growdon, J.H., Corkin, S., and Rosen, T.J. (1990) Distinctive aspects of cognitive dysfunction in Parkinson’s disease. Adv. Neurol. 53:365–376. Haaland, K.Y., Harrington, D.L., O’Brien, S., and Hermanowicz, N. (1997) Cognitive-motor learning in Parkinson’s disease. Neuropsychology 11(2):180–186. Hanyu, H., Asano, T., Sakurai, H., Tanaka, Y., Takasaki, M., and Abe, K. (2002) MR analysis of the substantia innominata in normal aging, Alzheimer disease, and other types of dementia. Am. J. Neuroradiol. 23(1):27–32; comment in: Am. J. Neuroradiol. 23(1):33–34. Hardesty, D.E., and Sackeim, H.A. (2007) Deep brain stimulation in movement and psychiatric disorders. Biol. Psychiatry 61(7):831– 835. Harhangi, B.S., de Rijk, M.C., van Duijin, C.M., Van Vroeckhoven, C., Hofman, A., and Breteler, M.M.B. (2000) APOE and the risk of PD with or without dementia in a population-based study. Neurology 54:1272–1276. Harrington, D.L., Haaland, K.Y., Yeo, R.A., and Marder, E. (1990) Procedural in memory in Parkinson’s disease: impaired motor

1059

but not visuoperceptual learning. J. Clin. Exp. Neuropsychol. 12(2):323–339. Hauser, R.A., and Olanow, C.W. (1994) MRI of neurodegenerative diseases. J. Neuroimaging 4:146 –158. Hay, J.F., Moscovitch, M., and Levine, B. (2002) Dissociating habit and recollection: evidence from Parkinson’s disease, amnesia and focal lesion patients. Neuropsychologia 40(8):1324–1334. Hely, M.A., Morris, J.G., Reid, W.G., and Trafficante, R. (2005) Sydney Multicenter Study of Parkinson’s Disease: non-L-doparesponsive problems dominate at 15 years. Mov. Disord. 20: 190–199. Henderson, J.M., Gai, W.P., Hely, M.A., Reid, W.G., Walker G.L., and Halliday, G.M. (2001) Parkinson’s disease with late Pick’s dementia. Mov. Disord. 16(2):311–319. Higginson, C.I., Wheelock, V.L., Carroll, K.E., and Sigvardt, K.A. (2005) Recognition memory in Parkinson’s disease with and without dementia: evidence inconsistent with the retrieval deficit hypothesis. J. Clin. Exp. Neuropsychol. 27:516 –528. Hirono, N., Mori, E., Tanimukai, S., et al. (1999) Distinctive neurobehavioral features among neurodegenerative dementias. J. Neuropsychiatry Clin. Neurosci. 11:498–503. Hobson, P., Gallacher, J., and Meara, J. (2005) Cross-sectional survey of Parkinson’s disease and parkinsonism in a rural area of the United Kingdom. Mov. Disord. 20:995–998. Hobson, P., and Meara, J. (2004) Risk and incidence of dementia in a cohort of older subjects with Parkinson’s disease in the United Kingdom. Mov. Disord. 19:1043–1049. Holroyd, S., Currie, L., and Wooten, G.F. (2001) Prospective study of hallucinations and delusions in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 70(6):734–738. Hoppe, C.D., Muller, U.D., Werheid, K.D., Thone, A.D., and von Cramon, Y.D. (2000) Digit Ordering Test: clinical, psychometric, and experimental evaluation of a verbal working memory test. Clin. Neuropsychol. 14(1):38 –55. Horstink, M.W., Berger, H.J., van Spaendonck, K.P., van den Bercken, J.H., and Cools, A.R. (1990) Bimanual simultaneous motor performance and impaired ability to shift attention in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 53(8):685– 690. Hovestadt, A., de Jong, G.J., and Meerwaldt, J.D. (1987) Spatial disorientation as an early symptom of Parkinson’s disease. Neurology 37(3):485– 487. Hsieh, S., Lee, C.Y., and Tai, C.T. (1995) Set-shifting aptitude in Parkinson’s disease: external versus internal cues. Psychol. Rep. 77(1):339–349. Hu, M.T., Taylor-Robinson, S.D., Chaudhuri, K.R., Bell, J.D., Labbe, C., Cunningham, V.J., Koepp, M.J., Hammers, A., Morris, R.G., Turjanski, N., and Brooks, D.J. (2000) Cortical dysfunction in non-demented Parkinson’s disease patients: a combined (31)PMRS and (18)FDG-PET study. Brain 123(Pt 2):340–352. Hu, M.T., Taylor-Robinson, S.D., Chaudhuri, K.R., Bell, J.D., Morris, R.G., Clough, C., Brooks, D.J., and Turjanski, N. (1999) Evidence for cortical dysfunction in clinically non-demented patients with Parkinson’s disease: a proton MR spectroscopy study. J. Neurol. Neurosurg. Psychiatry 67(1):20–26. Hu, M.T., White, S.J., Chaudhuri, K.R., Morris, R.G., Bydder, G.M., and Brooks, D.J. (2001) Correlating rates of cerebral atrophy in Parkinson’s disease with measures of cognitive decline. J. Neurol. Transm. 108(5):571–580. Hughes, T.A., Ross, H.F., Musa, S., et al. (2000) A 10-year study of the incidence of and factors predicting dementia in Parkinson’s disease. Neurology 54:1596–1602. Hulette, C., Mirra, S., Wilkinson, W., et al. (1995) The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part IX. A prospective cliniconeuropathologic study of Parkinson’s features in Alzheimer’s disease. Neurology 45:1991–1995. Hulette, C.M., Pericak-Vance, M.A., Roses, A.D., Schmechel, D.E., Yamaoka, L.H., Gaskell, P.C., Welsh-Bohmer, K.A., Crowther,

1060

DEMENTIA

R.A., and Spillantini, M.G. (1999) Neuropathological features of frontotemporal dementia and parkinsonism linked to chromosome 17q21-22 (FTDP-17): Duke Family 1684. J. Neuropathol. Exp. Neurol. 58(8):859–866. Hurtig, H.I., Trojanowski, J.Q., Galvin, J., et al. (2000) Alphasynuclein cortical Lewy bodies correlate with dementia in Parkinson’s disease. Neurology 54:1916 –1921. Inzelberg, R., Chapman, J., Treves, T.A., et al. (1998) Apolipoprotein E4 in Parkinson disease and dementia: new data and metaanalysis of published studies. Alzheimer Dis. Assoc. Disord. 12:45– 48. Ito, K., Morrish, P.K., Rakshi, J.S., Uema, T., Ashburner, J., Bailey, D.L., Friston, K.J., and Brooks, D.J. (1999) Statistical parametric mapping with 18F-dopa PET shows bilaterally reduced striatal and nigral dopaminergic function in early Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 66(6):754–758. Ito, K., Nagano-Saito, A., Kato, T., Arahata, Y., Nakamura, A., Kawasumi, Y., Hatano, K., Abe, Y., Yamada, T., Kachi, T., and Brooks, D.J. (2002) Striatal and extrastriatal dysfunction in Parkinson’s disease with dementia: a 6-[18F]fluoro-L-dopa PET study. Brain 125(Pt 6):1358–1365. Jacobs, D.M., Marder, K., Cote, L.J., Sano, M., Stern, Y., and Mayeux, R. (1995) Neuropsychological characteristics of preclinical dementia in Parkinson’s disease. Neurology 45(9):1691–1696; comment in: Neurology 1997 48(2):546–547. Jahanshahi, M., Ardouin, C.M., Brown, R.G., Rothwell, J.C., Obeso, J., Albanese, A., Rodriguez-Oroz, M.C., Moro, E., Benabid, A.L., Pollak, P., and Limousin-Dowsey, P. (2000) The impact of deep brain stimulation on executive function in Parkinson’s disease. Brain 123(Pt 6):1142–1154. Jahanshahi, M., Brown, R.G., and Marsden, C.D. (1993) A comparative study of simple and choice reaction time in Parkinson’s, Huntington’s and cerebellar disease. J. Neurol. Neurosurg. Psychiatry 56(11):1169–1177. Janvin, C.C., Aarsland, D., and Larsen, J.P. (2005) Cognitive predictors of dementia in Parkinson’s disease: a community-based, 4-year longitudinal study. J. Geriatr. Psychiatry Neurol. 18:149–154. Janvin, C.C., Larsen, J.P., Aarsland, D., and Hugdahl, K. (2006) Subtypes of mild cognitive impairment in Parkinson’s disease: progression to dementia. Mov. Disord. 21(9):1343–1349. Jellinger, K. (1987) The pathology of parkinsonism. In: Marsden, C.D., and Fahn, S., eds. Movement Disorders 2. London: Butterworths, pp. 124–165. Jellinger, K.A. (2007) Morphological substrates of parkinsonism with and without dementia: a retrospective clinico-pathological study. J. Neural Transm. Suppl.(72):91–104. Jellinger, K.A., Wenning, G.K., and Seppi, K. (2007) Predictors of survival in dementia with Lewy bodies and Parkinson dementia. Neurodegen. Dis. 4(6):428– 430. Kahle, P.J. (2008) α-Synucleinopathy models and human neuropathology: similarities and differences Acta Neuropathol (Berl) 115(1):87–95. Kang, G.A., Bronstein, J.M., Masterman, D.L., Redelings, M., Crum, J.A., and Ritz, B. (2005) Clinical characteristics in early Parkinson’s disease in a central California population-based study. Mov. Disord. 20:1133–1142. Kertesz, A., Martinez-Lage, P., Davidson, W., and Munoz, D.G. (2000) The corticobasal degeneration syndrome overlaps progressive aphasia and frontotemporal dementia. Neurology 55:1368– 1375. Khandhar, S.M., and Marks, W.J. (2007) Epidemiology of Parkinson’s disease. Dis. Mon. 53(4):200–205. Kish, S.J. (2003) Biochemistry of Parkinson’s disease: is a brain serotonergic deficiency a characteristic of idiopathic Parkinson’s disease? Adv. Neurol. 91:39– 49. Kish, S.J., Tong, J., Hornykiewicz, O., Rajput, A., Chang, L.J., Guttman, M., and Furukawa, Y. (2008) Preferential loss of sero-

tonin markers in caudate versus putamen in Parkinson’s disease. Brain 131(Pt 1):120–131. Koller, W.C. (1984) Disturbance of recent memory function in parkinsonian patients on anticholinergic therapy. Cortex 20(2):307–311. Koller, W.C., Glatt, S.L., Hubble, J.P., et al. (1995) Apolipoprotein E genotypes in Parkinson’s disease with and without dementia. Ann. Neurol. 37:242–245. Korczyn, A.D. (2001) Dementia in Parkinson’s disease. J. Neurol. 248(Suppl 3):III1–III4. Kuhl, D.E., Metter, E.J., and Riege, W.H. (1984) Patterns of local cerebral glucose utilisation determined in Parkinson’s disease by the 18F-fluorodeoxyglucose method. Ann. Neurol. 15:419–424. Kurlan, R., Richard, I.H., Papka, M., and Marshall, F. (2000) Movement disorders in Alzheimer’s disease: more rigidity of definitions is needed. Mov. Disord. 15(1):24–29. Kuzis, G., Sabe, L., Tiberti, C., Merello, M., Leiguarda, R., and Starkstein, S.E. (1999) Explicit and implicit learning in patients with Alzheimer disease and Parkinson disease with dementia. Neuropsychiatry Neuropsychol. Behav. Neurol. 12:265–269. Lauterbach, E.C. (2004) The neuropsychiatry of Parkinson’s disease and related disorders. Psychiatr. Clin. North Am. 27(4):801–825. Lavernhe, G., Pollak, P., Brenier, F., Gaio, J.M., Hommel, M., Pellat, J., and Perret, J. (1989) Alzheimer’s disease and Parkinson’s disease: neuropsychological differentiation [French]. Rev. Neurol. (Paris) 145(1):24–30. Lees, A.J., and Smith, E. (1983) Cognitive deficits in the early stages of Parkinson’s disease. Brain 106:257–270. Leibson, C.L., Maraganore, D.M., Bower, J.H., et al. (2006) Comorbid conditions associated with Parkinson’s disease: a population-based study. Mov. Disord. 22(7):1054–1055. Leverenz, J., and Sumi, S.M. (1986) Parkinson’s disease in patients with Alzheimer’s disease. Arch. Neurol. 43:662– 664. Levin, B.E., Llabre, M.M., and Weiner, W.J. (1989) Cognitive impairments associated with early Parkinson’s disease. Neurology 39:557–561. Levy, G. (2007) The relationship of Parkinson disease with aging. Arch. Neurol. 64(9):1242–1246. Levy, G., Schupf, N., Tang, M.X., Cote, L.J., Louis, E.D., Mejia, H., Stern, Y., and Marder, K. (2002) Combined effect of age and severity on the risk of dementia in Parkinson’s disease. Ann. Neurol. 51(6):722–729. Levy, G., Tang, M.X., Cote, L.J., Louis, E.D., Alfaro, B., Mejia, H., Stern, Y., and Marder, K. (2000) Motor impairment in PD: relationship to incident dementia and age. Neurology 55(4):539–544. Levy, G., Tang, M.X., Cote, L.J., Louis, E.D., Alfaro, B., Mejia, H., Stern, Y., and Marder, K. (2002) Do risk factors for Alzheimer’s disease predict dementia in Parkinson’s disease? An exploratory study. Mov. Disord. 17(2):250–257. Levy, G., Tang, M.X., Louis, E.D., et al. (2002) The association of incident dementia with mortality in PD. Neurology 59:1708–1713. Lewis, S.J.G., Foltynie, T., Blackwell, A.D., Robbins, T.W., Owen, A.M., and Barker, R.A. (2005) Heterogeneity of Parkinson’s disease in the early clinical stages using a data driven approach. J. Neurol. Neurosurg. Psychiatry 76:343–348. Lieberman, A. (1998) Managing the neuropsychiatric symptoms of Parkinson’s disease. Neurology 50(Suppl 6):S33–S38; discussion S44–S48. Liepelt, I., Maetzler, W., Blaicher, H.P., Gasser, T., and Berg, D. (2007) Treatment of dementia in parkinsonian syndromes with cholinesterase inhibitors. Dement. Geriatr. Cogn. Disord. 23(6):351–367. Lippa, C.F., Dud, J.E., Grossman, M., et al. (2007) DLB and PDD boundary issues: diagnosis, treatment, molecular pathology, and biomarkers. Neurology 68(11):812–819. Lippa, C.F., Smith, T.W., and Swearer, J. (1998) Dementia with parkinsonism: Alzheimer’s disease is more common than dementia with Lewy bodies. Am. J. Alzheimer’s Dis. Demen. 13(5):229– 235.

63: DEMENTIA IN PARKINSON’S DISEASE Litvan, I. (1998) Parkinsonism-dementia syndromes. In: Jankovic, J., and Tolosa, E., Eds. Parkinson’s Disease and Movement Disorders. Baltimore: Williams & Wilkins, pp. 819–836. Litvan, I., Agid, Y., Calne, D., et al. (1996) Clinical research criteria for the diagnosis of progressive supranuclear palsy (SteeleRichardson-Olszewski syndrome): report of the NINDS-SPSP international workshop. Neurology 47:1–9. Litvan, I., Agid, Y., Goetz, C., Jankovic, J., Wenning, G.K., Brandel, J.P., Lai, E.C., Verny, M., Mangone, C.A., and Pearce, R.K. (1996) Accuracy of clinical criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome). Neurology 46(4):922–930. Litvan, I., Mega, M.S., Cummings, J.L., and Fairbanks, L. (1996) Neuropsychiatric aspects of progressive supranuclear palsy. Neurology 47(5):1184–1189. Lombardi, W.J., Gross, R.E., Trepanier, L.L., Lang, A.E., Lozano, A.M., and Saint-Cyr, J.A. (2000) Relationship of lesion location to cognitive outcome following microelectrode-guided pallidotomy for Parkinson’s disease: support for the existence of cognitive circuits in the human pallidum. Brain 123(Pt 4):746–758. Louis, E.D., Marder, K., Cote, L., Tang, M., and Mayeux, R. (1997) Mortality from Parkinson disease. Arch. Neurol. 54(3):260–264. Love, S. (2005) Neuropathological investigation of dementia: a guide for neurologists. J. Neurol. Neurosurg. Psychiatry 76(Suppl 5): v8–v14. Mahieux, F., Fenelon, G., Flahault, A., Manifacier, M.J., Michelet, D., and Boller, F. (1998) Neuropsychological prediction of dementia in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 64:178–183. Mamikonyan, E., Siderowf, A.D., Duda, J.E., Potenza, M.N., Horn, S., Stern, M.B., and Weintraub, D. (2008) Long-term follow-up of impulse control disorders in Parkinson’s disease. Mov. Disord. 23(1):75–80. Marder, K. (2002) Donepezil for cognitive impairment in Parkinson’s disease: a randomized controlled trial. Curr. Neurol. Neurosci. Rep. 2(5):390–391. Marder, K., Flood, P., Cote, L., and Mayeux, R. (1990) A pilot study of risk factors for dementia in Parkinson’s disease. Mov. Disord. 5(2):156–161. Marder, K., Leung, D., Tang, M., Bell, K., Dooneief, G., Cote, L., Stern, Y., and Mayeux, R. (1991) Are demented patients with Parkinson’s disease accurately reflected in prevalence surveys? a survival analysis. Neurology 41(8):1240–1243. Marder, K., Tang, M.X., Alfaro, B., Mejia, H., Cote, L., Jacobs, D., Stern, Y., Sano, M., and Mayeux, R. (1998) Postmenopausal estrogen use and Parkinson’s disease with and without dementia. Neurology 50(4):1141–1143. Marder, K., Tang M.X., Alfaro, B., Mejia, H., Cote, L., Lovis, E., Stern, T., and Mayeux, R. (1999) Risk of Alzheimer’s disease in relatives of a Parkinson’s disease patient with and without dementia. Neurology 52(4):719–724. Marder, K., Tang, M.X., Cote, L., Stern, Y., and Mayeux, R. (1995) The frequency and associated risk factors for dementia in patients with Parkinson’s disease. Arch. Neurol. 52(7):695–701. Marek, K.L., Innis, R.B., and Seibyl, J. (1998) Assessment of Parkinson’s disease progression with b-CIT and SPECT imaging. Mov. Disord. 13(Suppl 2):238–230. Mariani, E., Monastero, R., and Mecocci, P. (2007) Mild cognitive impairment: a systematic review. J. Alzheimers Dis. 12(1):23–35. Marié, R.M., Barre, L., Dupuy, B., Viader, F., Defer, G., and Baron, J.C. (1999) Relationships between striatal dopamine denervation and frontal executive tests in Parkinson’s disease. Neurosci. Lett. 260(2):77–80. Marié, R.M., Barre, L., Rioux, P., Allain, P., Lechevalier, B., and Baron, J.C. (1995) PET imaging of neocortical monoaminergic terminals in Parkinson’s disease. J. Neural. Transm. Park. Dis. Dement. Sect. 9(1):55–71.

1061

Marjama-Lyons, J.M., and Koller, W.C. (2001) Parkinson’s disease. Update in diagnosis and symptom management. Geriatrics 56(8): 24–25, 29–30, 33–35. Marsh, L., Williams, J.R., Rocco, M., Grill, S., Munro, C., and Dawson, T.M. (2004) Psychiatric comorbidities in patients with Parkinson disease and psychosis. Neurology 63:293–300. Matsui, H., Nishinaka, K., Oda, M., et al. (2007) Dementia in Parkinson’s disease: diffusion tensor imaging. Acta Neurol. Scand. 116(3):177–181. Mayeux, R., Chen, J., Mirabello, E., Marder, K., Bell, K., Dooneief, G., Cote, L., and Stern, Y. (1990) An estimate of the incidence of dementia in idiopathic Parkinson’s disease. Neurology 40(10): 1513 –1517. Mayeux, R., Denaro, J., Hemenegildo, N., Marder, K., Tang, M.X., Cote, L.J., and Stern, Y. (1992) A population-based investigation of Parkinson’s disease with and without dementia. Relationship to age and gender. Arch. Neurol. 49(5):492–497. Mayeux, R., Stern, Y., Rosenstein, R., Marder, K., Hauser, A., Cote, L., and Fahn, S. (1998) An estimate of the prevalence of dementia in idiopathic Parkinson’s disease. Arch. Neurol. 45(3):260–262. Mayeux, R., Stern, Y., and Spanton, S. (1985) Heterogeneity in dementia of the Alzheimer type: evidence of subgroups. Neurology 35:453–461. McGeer, P.L., Itagaki, S., Boyes, B.E., and McGeer, E.G. (1988) Reactive microglia are positive for HLA-DR in the substantia nigra of Parkinson’s and Alzheimer’s disease brains. Neurology 38: 1285–1291. McKeith, I. (2007) Dementia with Lewy bodies and Parkinson’s disease with dementia: where two worlds collide. Practical Neurology 7:374 –382. McKeith, I., Mintzer, J., Aarsland, D., et al. (2004) Dementia with Lewy bodies. Lancet Neurol. 3:19–28. McKeith, I.G., Dickson, D.W., Lowe, J., et al. (2005) Consortium on DLB: Diagnosis and management of dementia with Lewy bodies: third report of the DLB consortium. Neurology 65:1863–1872. McKeith, I.G., Galasko, D., Kosaka, K., et al. (1996) Consensus guidelines for the clinical and pathological diagnosis of dementia with Lewy bodies: report of the consortium on DLB international workshop. Neurology 47:1113–1124. McKeith, I.G., Grace, J.B., Walker, Z., Byrne, E.J., Wilkinson, D., Stevens, T., and Pery, E.K. (2000) Rivastigmine in the treatment of dementia with Lewy bodies: preliminary findings from an open trial. Int. J. Geriatr. Psychiatry 15(5):387–392. McNamara, P., and Durso, R. (2006) Neuropharmacological treatment of mental dysfunction in Parkinson’s disease. Behav. Neurol. 17(1):43–51. Menza, M.A., Robertson, H.D., and Bonapace, A.S. (1993) Parkinson’s disease and anxiety: comorbidity with depression. Biol. Psychiatry 34:465– 470. Mesulam, M.M. (2000) Behavioral neuroanatomy. In: M.M. Mesulam, ed. Principles of Behavioral and Cognitive Neurology. New York: Oxford University Press, pp. 1–120. Metzler-Baddeley, C. (2007) A review of cognitive impairments in dementia with Lewy bodies relative to Alzheimer’s Disease and Parkinson’s Disease with Dementia. Cortex 43(5):583–600. Mitchell, S.L. (1999) Extrapyramidal features in Alzheimer’s disease. Age Ageing 28(4):401–409. Molloy, S.A., Rowan, E.N., O’Brien, J.T., McKeith, I.G., Wesnes, K., and Burn, D.J. (2006) Effect of levodopa on cognitive function in Parkinson’s disease with and without dementia and dementia with Lewy bodies. J. Neurol. Neurosurg. Psychiatry 77(12): 1323–1328. Molsa, P.K., Marttila, R.J., and Rinne, U.K. (1984) Extrapyramidal signs in Alzheimer’s disease. Neurology 34:1114 –1116. Monchi, O., Petrides, M., Mejia-Constain, B., et al. (2007) Cortical activity in Parkinson’s disease during executive processing depends on striatal involvement. Brain 130(Pt 1):233–244.

1062

DEMENTIA

Mondon, K., Gochard, A., Marqué, A., et al. (2007) Visual recognition memory differentiates dementia with Lewy bodies and Parkinson’s disease dementia. J. Neurol. Neurosurg. Psychiatry 78: 738–741. Morens, D.M., Grandinetti, A., Reed, D., et al. (1995) Cigarette smoking and protection from Parkinson’s disease: false association or etiologic clue? Neurology 45:1041–1051. Morris, J.C., Drazner, M., Fulling, K., et al. (1989) Clinical and pathological aspects of parkinsonism in Alzheimer’s disease. Arch. Neurol. 46:651–657. Morrison, C.E., Borod, J.C., Brin, M.F., Raskin, S.A., Germano, I.M., Weisz, D.J., and Olanow, C.W. (2000) A program for neuropsychological investigation of deep brain stimulation (PNIDBS) in movement disorder patients: program development and preliminary data. Neuropsychiatry Neuropsychol. Behav. Neurol. 13: 204 –219. Morrison, C.E., Borod, J., Perrine, K., et al. (2004) Neuropsychological functioning following bilateral subthalamic nucleus stimulation in Parkinson’s disease. Arch. Clin. Neuropsychology 19(2): 165–181. Mosimann, U.P., Mather, G., Wesnes, K.A., O’Brien, J.T., Burn, D.J., and McKeith, I.G. (2004) Visual perception in Parkinson disease dementia and dementia with Lewy bodies. Neurology 63: 2091– 2096. Mosimann, U.P., Rowan, E.N., Partington, C.E., et al. (2006) Characteristics of visual hallucinations in Parkinson disease dementia and dementia with lewy bodies. Am. J. Geriatr. Psychiatry 14:153–160. Nasreddine, Z.S., Loginov, M., Clark, L.N., Lamarche, J., Miller, B.L., Lamontagne, A., Zhukareva, V., Lee, V.M., Wilhelmsen, K.C., and Geschwind, D.H. (1999) From genotype to phenotype: a clinical pathological, and biochemical investigation of frontotemporal dementia and parkinsonism (FTDP-17) caused by the P301L tau mutation. Ann. Neurol. 45(6):704–715. Neufeld, M.Y., Blumen, S., Aitkin, I., Parmet, Y., and Korczyn, A.D. (1994) EEG frequency analysis in demented and nondemented parkinsonian patients. Dementia 5:23–28. Ngandu, T., von Strauss, E., Helkala, E.L., et al. (2007) Education and dementia: What lies behind the association? Neurology 69:1442–1450. Nissenbaum, H., Quinn, N.P., Brown, R.G., Toone, B., Gotham, A.M., and Marsden, C.D. (1987) Mood swings associated with the “on-off” phenomenon in Parkinson’s disease. Psychol. Med. 17(4):899–904. Noe, E., Marder, K., Bell, K.L., Jacobs, D.M., Manly, J.J., and Stern, Y. (2004) Comparison of dementia with Lewy bodies to Alzheimer’s disease and Parkinson’s disease with dementia. Mov. Disord. 19:60–67. Obeso, J.A., Olanow, C.W., Rodriguez-Oroz, M.C., et al. (2001) Deep-brain stimulation of the subthalamic nucleus or the pars interna of the globus pallidus in Parkinson’s disease. The DeepBrain Stimulation for Parkinson’s Disease Study Group. N. Eng. J. Med. 345(13):956–963. Okun, M.S., Rodriguez, R.L., Mikos, A., Miller, K., Kellison, I., Kirsch-Darrow, L., Wint, D.P., Springer, U., Fernandez, H.H., Foote, K.D., Crucian, G., and Bowers, D. (2007) Deep brain stimulation and the role of the neuropsychologist. Clin. Neuropsychol. 21(1):162–189. Olanow, C.W., Lang, A.E., and Stocchi, F. (in press) The non-motor and non-dopamine features of Parkinson’s disease. London: WileyBlackwell Press. Olanow, C.W. (1992) Magnetic resonance imaging in parkinsonism. Neurol. Clin. North Am. 10(2):405–420. Olanow, C.W. (2004) Manganese-induced parkinsonism and Parkinson’s disease. Ann. N.Y. Acad. Sci. 1012:209–223. Olanow, C.W., and Brin, M.F. (2001) Surgery for Parkinson’s disease: a physician’s perspective. Adv. Neurol. 86:421– 433.

Olanow, C.W., Brin, M., and Obeso, J.A. (2000) The role of deep brain stimulation as a surgical treatment for Parkinson’s disease. Neurology 55(Suppl 6):60–66. Olanow, C.W., Good, P.F., and Perl, D.P. (1999) Evidence of damage to the globus pallidus pars interna and pedunculopontine nucleus in Parkinson’s disease: implications for neuroprotection. Soc. Neurosci. Abstr. 25:1342. Olanow, C.W., and Tatton, W.G. (1999) Etiology and pathogenesis of Parkinson’s disease. Annu. Rev. Neurosci. 22:123–144. Olanow, C.W., Watts, R.L., and Koller, W.C. (2001) An algorithm (decision tree) for the management of Parkinson’s disease: treatment guidelines. Neurology 56(11 Suppl 5):S1–S88. Olson, E.J., Boeve, B.F., and Silber, M.H. (2000) Rapid eye movement sleep behaviour disorder: demographic, clinical and laboratory findings in 93 cases. Brain 123:331–339. Ordway, G.A., and Klimek, V. (2001) Noradrenergic pathology in psychiatric disorders: postmortem studies. CNS Spectr. 6(8):697–703. Orimo, S., Ozawa, E., Nakade, S., Sugimoto, T., and Mizusawa, H. (1999) (123)I-metaiodobenzylguanidine myocardial scintigraphy in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 67:189– 194. Owen, A.D., Schapira, A.H., Jenner, P., and Marsden, C.D. (1997) Indices of oxidative stress in Parkinson’s disease, Alzheimer’s disease and dementia with Lewy bodies. J. Neural. Transm. Suppl. 51:167–173. Owen, A.M. (2007) Cognitive dysfunction in Parkinson’s disease: the role of frontostriatal circuitry. Neuroscientist 10(6):525–537. Owen, A.M., Beksinska, M., James, M., Leigh, P.N., Summers, B.A., Marsden, C.D., Quinn, N.P., Sahakian, B.J., and Robbins, T.W. (1993) Visuospatial memory deficits at different stages of Parkinson’s disease. Neuropsychologia 31(7):627– 644. Owen, A.M., Doyon, J., Dagher, A., Sadikot, A., and Evans, A.C. (1998) Abnormal basal ganglia outflow in Parkinson’s disease identified with PET. Implications for higher cortical functions. Brain 121(Pt 5):949–965. Owen, A.M., Iddon, J.L., Hodges, J.R., Summers, B.A., and Robbins, T.W. (1997) Spatial and non-spatial working memory at different stages of Parkinson’s disease. Neuropsychologia 35(4): 519–532. Owen, A.M., James, M., Leigh, P.N., Summers, B.A., Marsden, C.D., Quinn, N.P., Lange, K.W., and Robbins, T.W. (1992) Frontostriatal cognitive deficits at different stages of Parkinson’s disease. Brain 115(Pt 6):1727–1751. Owen, A.M., Roberts, A.C., Hodges, J.R., Summers, B.A., Polkey, C.E., and Robbins, T.W. (1993) Contrasting mechanisms of impaired attentional set-shifting in patients with frontal lobe damage or Parkinson’s disease. Brain 116(Pt 5):1159–1175. Ozer, F., Meral, H., Lutfu, H., et al. (2007) Cognitive impairment patterns in Parkinson’s disease with visual hallucinations. J. Clin. Neurosci. 14(8):742–746. Pacchetti, C., Manni, R., Zangaglia, R., Mancini, F., Marchioni, E., Tassorelli, C., Terzaghi, M., Ossola, M., Martignoni, E., Moglia, A., and Nappi, G. (2005) Relationship between hallucinations, delusions, and rapid eye movement sleep behavior disorder in Parkinson’s disease. Mov. Disord. 20:1439–1448. Pagonabarraga, J., Garcia-Sanchez, C., Llebaria, G., Pascual-Sedano, B., Gironell, A., and Kulisevsky, J. (2007) Controlled study of decision-making and cognitive impairment in Parkinson’s disease. Mov. Disord. 22(10):1430–1435. Paolo, A.M., Axelrod, B.N., Troster, A.I., Blackwell, K.T., and Koller, W.C. (1996) Utility of a Wisconsin card sorting test short form in persons with Alzheimer’s and Parkinson’s disease. J. Clin. Exp. Neuropsychol. 18:892–897. Paolo, A.M., Troster, A.I., Glatt, S.L., Hubble, J.P., and Koller, W.C. (1995) Differentiation of the dementias of Alzheimer’s and Parkinson’s disease with the dementia rating scale. J. Geriatr. Psychiatry Neurol. 8(3):184–188.

63: DEMENTIA IN PARKINSON’S DISEASE Parent, A., Sato, F., Wu, Y., et al. (2000) Axonal collateralization as a general principle of organization in the basal ganglia. Trends Neurosci. 23:20–27. Parkin, S.G., Gregory, R.P., Scott, R., Bain, P., Silburn, P., Hall, B., Boyle, R., Joint, C., and Aziz, T.Z. (2002) Unilateral and bilateral pallidotomy for idiopathic Parkinson’s disease: a case series of 115 patients. Mov. Disord. 17(4):682– 692. Parkinson, J. (1817) An Essay on the Shaking Palsy. London: Whitingham and Rowland. Parsian, A., Racette, B., Goldsmith, L.J., and Perlmutter, J.S. (2002) Parkinson’s disease and apolipoprotein E: possible association with dementia but not age at onset. Genomics 79:458–461. Parsons, T., Rogers, S., Braaten, A., Woods, S., and Tröster, A. (2006) Cognitive sequelae of subthalamic nucleus deep brain stimulation in Parkinson’s disease: a meta-analysis. Lancet Neurol. 5(7):578–588. Partiot, A., Verin, M., Pillon, B., Teixeira-Ferreira, C., Agid, Y., and Dubois, B. (1996) Delayed response tasks in basal ganglia lesions in man: further evidence for a striato-frontal cooperation in behavioural adaptation. Neuropsychologia 34(7):709 –721. Pascual-Leone, A., Grafman, J., Clark, K., Stewart, M., Massaquoi, S., Lou, J.S., and Hallett, M. (1993) Procedural learning in Parkinson’s disease and cerebellar degeneration. Ann. Neurol. 34(4): 594–602. Peppard, R.F., Martin, W.R.W., Carr, G.D., et al. (1992) Cerebral glucose metabolism in Parkinson’s disease with and without dementia. Arch. Neurol. 49:1262–1268. Perl, D.P., Olanow, C.W., and Calne, D. (1998) Alzheimer’s disease and Parkinson’s disease: distinct entities or extremes of a spectrum of neurodegeneration? Ann. Neurol. 44(3):19–31. Piatt, A.L., Fields, J.A., Paolo, A.M., Koller, W.C., and Tröster, A.I. (1999) Lexical, semantic, and action verbal fluency in Parkinson’s disease with and without dementia. J. Clin. Exp. Neuropsychol. 21(4):435–443. Pillon, B., Deweer, B., Agid, Y., and Dubois, B. (1993) Explicit memory in Alzheimer’s disease, Huntington’s disease, and Parkinson’s disease. Arch. Neurol. 50:374–379. Pillon, B., Ardouin, C., Damier, P., Krack, P., Houeto, J.L., Klinger, H., Bonnet, A.M., Pollak, P., Benabid, A.L., and Agid, Y. (2000) Neuropsychological changes between “off” and “on” STN or GPi stimulation in Parkinson’s disease. Neurology 55(3):411–418. Pillon, B., Dubois, B., and Agid, Y. (1991) Severity and specificity of cognitive impairment in Alzheimer’s, Huntington’s, and Parkinson’s diseases and progressive supranuclear palsy. Ann. N.Y. Acad. Sci. 640:224 –227. Pillon, B., Ertle, S., Deweer, B., Sarazin, M., Agid, Y., and Dubois, B. (1996) Memory for spatial location is affected in Parkinson’s disease. Neuropsychologia 34(1):77–85. Pirozzolo, F.J., Hansch, E.C., Mortimer, J.A., Webster, D.D., and Kuskowski, M.A. (1982) Dementia in Parkinson disease: a neuropsychological analysis. Brain Cogn. 1(1):71–83. Poewe, W. (2006) The natural history of Parkinson’s disease. J. Neurol. 253(Suppl 7):VII2–VII6. Poewe, W. (2007) Dysautonomia and cognitive dysfunction in Parkinson’s disease. Mov. Disord. 22(Suppl 17):S374–S378. Pontone, G., Williams, J.R., Bassett, S.S., and Marsh, L. (2006) Clinical features associated with impulse control disorders in Parkinson disease. Neurology 67(7):1258–1261. Rabins, P.V., and Folstein, M.F. (1983) The dementia patient: evaluation and care. Geriatrics 38(8):99–103, 106. Rajput, A.H., Offord, K.P., Beard, C.M., and Kurland, L.T. (1984) Epidemiology of parkinsonism: incidence, classification and mortality. Ann. Neurol. 16:278–283. Rakshi, J.S., Uema, T., Ito, K., Bailey, D.L., Morrish, P.K., Ashburner, J., Dagher, A., Jenkins, I.H., Friston, K.J., and Brooks, D.J. (1999) Frontal, midbrain and striatal dopaminergic function in early and advanced Parkinson’s disease. A 3D [(18)F]dopa-PET study. Brain 122(Pt 9):1637–1650.

1063

Ramirez-Ruiz, B., Junque, C., Marti, M.J., Valldeoriola, F., and Tolosa, E. (2007) Cognitive changes in Parkinson’s disease patients with visual hallucinations. Dement. Geriatr. Cogn. Disord. 23(5): 281–288. Ramos, B.P., and Amsten, A.F. (2007) Adrenergic pharmacology and cognition: focus on the prefrontal cortex. Pharmacol. Ther. 113(3): 523–536. Ransmayr, G. (2002) [Dementia with Lewy bodies] [German]. Wien Med. Wochenschr. 152(3/4):81–84. Rascol, O., Brooks, D.J., Korczyn, A.D., et al. (2000) A five year study of the incidence of dyskinesia in patients with early Parkinson’s disease who were treated with ropinirole or levodopa. N. Engl. J. Med. 342:1484 –1491. Raskin, S.A., Borod, J.C., and Tweedy, J.R. (1992) Set-shifting and spatial orientation in patients with Parkinson’s disease. J. Clin. Exp. Neuropsychol. 14(5):801–821. Ravina, B., Marder, K., Fernandez, H.H., et al. (2007) Diagnostic criteria for psychosis in Parkinson’s disease: report of an NINDS, NIMH work group. Mov. Disord. 22(8):1061–1068. Reid, W.G.J., Hely, M.A., Morris, J.G.L., et al. (1996) A longitudinal study of Parkinson’s disease: clinical and neuropsychological correlates of dementia. J. Clin. Neurosci. 3:327–333. Richards, M., Bell, K., Dooneief, G., Marder, K., Sano, M., Mayeux, R., and Stern, Y. (1993) Patterns of neuropsychological performance in Alzheimer’s disease patients with and without extrapyramidal signs. Neurology 43(9):1708–1711. Richards, M., Stern, Y., Marder, K., Cote, L., and Mayeux, R. (1993) Relationships between extrapyramidal signs and cognitive function in a community-dwelling cohort of patients with Parkinson’s disease and normal elderly individuals. Ann. Neurol. 33(3):267–274. Ring, H.A., Bench, C.J., Trimble, M.R., Brooks, D.J., Frackowiak, R.S., and Dolan, R.J. (1994) Depression in Parkinson’s disease. A positron emission study. Br. J. Psychiatry 165(3):333–339. Rinne, J.O., Laine, M., Kaasinen, V., Norvasuo-Heila, M.K., Nagren, K., and Helenius, H. (2002) Striatal dopamine transporter and extrapyramidal symptoms in frontotemporal dementia. Neurology 58(10):1489–1493. Rippon GA, and Marder KS (2005) Dementia in Parkinson’s disease. Adv. Neurol. 96:95–113. Robbins, T.W., James, M., Owen, A.M., Lange, K.W., Lees, A.J., Leigh, P.N., Marsden, C.D., Quinn, N.P., and Summers, B.A. (1994) Cognitive deficits in progressive supranuclear palsy, Parkinson’s disease, and multiple system atrophy in tests sensitive to frontal lobe dysfunction. J. Neurol. Neurosurg. Psychiatry 57(1):79–88. Rodrigues, J.P., Walters, S.E., Watson, P., Stell, R., and Mastaglia, F.L. (2007) Globus pallidus stimulation improves both motor and nonmotor aspects of quality of life in advanced Parkinson’s disease. Mov. Disord. 22(13):1866–1870. Rodriguez, M.C., Obeso, J.A., and Olanow, C.W. (1998) Subthalamic nucleus-mediated excitotoxicity in Parkinson’s disease: a target for neuroprotection. Ann. Neurol. 44(3):175–188. Rosler, M. (2002) The efficacy of cholinesterase inhibitors in treating the behavioural symptoms of dementia. Int. J. Clin. Pract. Suppl. 127:20–36. Sagar, H.J. (1987) Clinical similarities and differences between Alzheimer’s disease and Parkinson’s disease. J. Neural. Transm. Suppl. 24:87–99. Sagar, H.J., Cohen, N.J., Sullivan, E.V., Corkin, S., and Growdon, J.H. (1988) Remote memory function in Alzheimer’s disease and Parkinson’s disease. Brain 111(Pt 1):185–206. Sagar, H.J., Sullivan, E.V., Gabrieli, J.D., Corkin, S., and Growdon, J.H. (1988) Temporal ordering and short-term memory deficits in Parkinson’s disease. Brain 111(Pt 3):525–539. Saint-Cyr, J.A., Taylor, A.E., and Lang, A.E. (1988) Procedural learning and neostriatal dysfunction in man. Brain 111(Pt 4): 941–959.

1064

DEMENTIA

Saint-Cyr, J.A., Taylor, A.E., and Lang, A.E. (1993) Neuropsychological and psychiatric side effects in the treatment of Parkinson’s disease. Neurology 43(12 Suppl 6):S47–S52. Saint-Cyr, J.A., Trépanier, L.L., Kumar, R., Lozano, A.M., and Lang, A.E. (2000) Neuropsychological consequences of chronic bilateral stimulation of the subthalamic nucleus in Parkinson’s disease. Brain 123(Pt 10):2091–2108. Santangelo, G., Trojano, L., Vitale, C., et al. (2007) A neuropsychological longitudinal study in Parkinson’s patients with and without hallucinations. Mov. Disord. 22(16):2418–2425. Sarazin, M., Deweer, B., Merkl, A., Von Poser, N., Pillon, B., and Dubois, B. (2002) Procedural learning and striatofrontal dysfunction in Parkinson’s disease. Mov. Disord. 17(2):265–273. Sarazin, M., Deweer, B., Pillon, B., Merkl, A., and Dubois, B. (2001) [Procedural learning and Parkinson disease: implication of striatofrontal loops] [French]. Rev. Neurol. (Paris) 157(12):1513–1518. Satoh, A., Serita, T., Seto, M., et al. (1999) Loss of 123I-MIBG uptake by the heart in Parkinson’s disease: assessment of cardiac sympathetic denervation and diagnostic value. J. Nucl. Med. 40:371–375. Sawle, G.V., Playford, E.D., Burn, D.J., Cunningham, V.J., and Brooks, D.J. (1994) Separating Parkinson’s disease from normality. Discriminant function analysis of fluorodopa F 18 positron emission tomography data. Arch. Neurol. 51(3):237–243. Schenck, C.H., Bundlie, S.R., and Mahowald, M.W. (1996) Delayed emergence of a parkinsonian disorder in 38% of 29 older men initially diagnosed with idiopathic rapid eye movement sleep behaviour disorder. Neurology 46:388–393. Schliebs, R., and Arendt, T. (2006) The significance of the cholinergic system in the brain during aging and in Alzheimer’s disease. J. Neural Transm. 113(11):1625–1644. Schneider, J.A., Watts, R.L., Gearing, M., et al. (1997) Corticobasal degeneration: neuropathologic and clinical heterogeneity. Neurology 48:959–969. Schofield, P.W., Tang, M., Marder, K., Bell, K., Dooneief, G., Chun, M., Sano, M., Stern, Y., and Mayeux, R. (1997) Alzheimer’s disease after remote head injury: an incidence study. J. Neurol. Neurosurg. Psychiatry 62(2):119–124. Schrag, A., Ben-Shlomo, Y., Brown, R., Marsden, C.D., and Quinn, N. (1998) Young-onset Parkinson’s disease revisited—clinical features, natural history, and mortality. Mov. Disord. 13(6):885–894. Schultz, W. (1998) Predictive reward signal of dopamine neurons. J. Neurophysiol. 80:1–27. Schultz, W. (2007a) Behavioral dopamine signals. Trends Neurosci. 30(5):203–210. Schultz, W. (2007b) Multiple dopamine functions at different time courses. Annu. Rev. Neurosci. 30:259–288. Sinanovic, O., Kapidzic, A., Kovacevic, L., Hudic, J., and Smajlovic, D. (2005) EEG frequency and cognitive dysfunction in patients with Parkinson’s disease. Med. Arch. 59:286–287. Sinforiani, E., Zangaglia, R., Manni, R., et al. (2006) REM sleep behavior disorder, hallucinations, and cognitive impairment in Parkinson’s disease. Mov. Disord. 21:462– 466. Smith, Y., and Kieval, J.Z. (2000) Anatomy of the dopamine system in the basal ganglia. Trends Neurosci. 23:28–33. Snowden, M.B., Bowen, J.D., Hughes, J., and Larson, E.B. (1995) Study of Alzheimer’s dementia patients with parkinsonian features. J. Geriatr. Psychiatry Neurol. 8(3):154–158. Soliveri, P., Brown, R.G., Jahanshahi, M., and Marsden, C.D. (1992) Effect of practice on performance of a skilled motor task in patients with Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 55(6):454 – 460. Sprengelmeyer, R., Canavan, A.G., Lange, H.W., and Homberg, V. (1995) Associative learning in degenerative neostriatal disorders: contrasts in explicit and implicit remembering between Parkinson’s and Huntington’s diseases. Mov. Disord. 10(1):51–65. Sroka, H., Elizan, T.S., Yahr, M.D., Burger, A., and Mendoza, M.R. (1981) Organic mental syndrome and confusional states in Par-

kinson’s disease. Relationship to computerized tomographic signs of cerebral atrophy. Arch. Neurol. 38(6):339–342. Starkstein, S., and Merello, M. (2007) The Unified Parkinson’s Disease Rating Scale: Validation study of the mentation, behavior, and mood section. Mov. Disord. 22(15):2156–2161. Starkstein, S.E., Sabe, L., Petracca, G., et al. (1996) Neuropsychological and psychiatric differences between Alzheimer’s disease and Parkinson’s disease with dementia. J. Neurol. Neurosurg. Psychiatry 61:381–387. Stern, Y., Marder, K., Tang, M.X., and Mayeux, R. (1993) Antecedent clinical features associated with dementia in Parkinson’s disease. Neurology 43(9):1690–1692; comment in: Neurology 1994 44(8):1553. Stern, Y., Tang, M.X., Jacobs, D.M., Sano, M., Marder, K., Bell, K., Dooneief, G., Schofield, P., and Cote, L. (1998) Prospective comparative study of the evolution of probable Alzheimer’s disease and Parkinson’s disease dementia. J. Int. Neuropsychol. Soc. 4(3): 279–284. Stuss, D.T., and Benson, D.F. (1986) The Frontal Lobes. New York: Raven Press. Sullivan, E.V., and Sagar, H.J. (1989) Nonverbal recognition and recency discrimination deficits in Parkinson’s disease and Alzheimer’s disease. Brain 112(Pt 6):1503–1517. Sullivan, E.V., and Sagar, H.J. (1991) Double dissociation of shortterm and long-term memory for nonverbal material in Parkinson’s disease and global amnesia. A further analysis. Brain 114(Pt 2): 893–906. Sullivan, E.V., Sagar, H.J., Gabrieli, J.D., Corkin, S., and Growdon, J.H. (1989) Different cognitive profiles on standard behavioral tests in Parkinson’s disease and Alzheimer’s disease. J. Clin. Exp. Neuropsychol. 11(6):799–820. Summerfield, C., Gomez-Anson, B., Tolosa, E., et al. (2002) Dementia in Parkinson disease: a proton magnetic resonance spectroscopy study. Arch. Neurol. 59:1415–1420. Tang, M.X., Jacobs, D., Stern, Y., Marder, K., Schofield, P., Gurland, B., Andrews, H., and Mayeux, R. (1996) Effect of oestrogen during menopause on risk and age at onset of Alzheimer’s disease. Lancet 348(9025):429–432; comment in: A.C.P. J Club. 1997 126(1):21; Lancet 1996 348(9025):420–421; Lancet 1996 348(9033):1027–1028; discussion 1029–1030. Tanner, C.M., and Goldman, S.M. (1996) Epidemiology of Parkinson’s disease. Neurol. Clin. 14:317–335. Taylor, A.E., and Saint-Cyr, J.A. (1990) Depression in Parkinson’s disease: reconciling physiological and psychological perspectives. J. Neuropsychiatry Clin. Neurosci. 2(1):92–98. Taylor, A.E., and Saint-Cyr, J.A. (1995) The neuropsychology of Parkinson’s disease. Brain Cogn. 28(3):281–296. Taylor, A.E., Saint-Cyr, J.A., and Lang, A.E. (1990) Memory and learning in early Parkinson’s disease: evidence for a “frontal lobe syndrome.” Brain Cogn. 13(2):211–232. Taylor-Robinson, S.D., Turjanski, N., Bhattacharya, S., Seery, J.P., Sargentoni, J., Brooks, D.J., Bryant, D.J., and Cox, I.J. (1999) A proton magnetic resonance spectroscopy study of the striatum and cerebral cortex in Parkinson’s disease. Metab. Brain Dis. 14(1): 45–55. Tinaz, S., Schendan, H.E., and Stern, C.E. (2008) Fronto-striatal deficit in Parkinson’s disease during semantic event sequencing. Neurobiol. Aging 29(3):397– 407. Trépanier, L.L., Kumar, R., Lozano, A.M., Lang, A.E., and SaintCyr, J.A. (2000) Neuropsychological outcome of GPi pallidotomy and GPi or STN deep brain stimulation in Parkinson’s disease. Brain Cogn. 42(3):324–347. Trépanier, L.L., Saint-Cyr, J.A., Lozano, A.M., and Lang, A.E. (1998) Neuropsychological consequences of posteroventral pallidotomy for the treatment of Parkinson’s disease. Neurology 51(1):207–215. Tröster, A.I., Paolo, A.M., Lyons, K.E., Glatt, S.L., Hubble, J.P., and Koller, W.C. (1995) The influence of depression on cognition in

63: DEMENTIA IN PARKINSON’S DISEASE Parkinson’s disease: a pattern of impairment distinguishable from Alzheimer’s disease. Neurology 45(4):672–676. Tröster, A.I., Stalp, L.D., Paolo, A.M., Fields, J.A., and Koller, W.C. (1995) Neuropsychological impairment in Parkinson’s disease with and without depression. Arch. Neurol. 52(12):1164–1169. Turjanski, N., and Brooks, D.J. (1997) PET and the investigation of dementia in the parkinsonian patient. J. Neurol. Transm. Suppl. 51:37–48. Uversky, V.N. (2007) Neuropathology, biochemistry, and biophysics of alpha-synuclein aggregation. J. Neurochem. 103(1):17–37. Van Spaendonck, K.P., Berger, H.J., Horstink, M.W., Buytenhuijs, E.L., and Cools, A.R. (1993) Impaired cognitive shifting in parkinsonian patients on anticholinergic therapy. Neuropsychologia 31(4):407– 411. Van Spaendonck, K.P., Berger, H.J., Horstink, M.W., Buytenhuijs, E.L., and Cools, A.R. (1996) Executive functions and disease characteristics in Parkinson’s disease. Neuropsychologia 34(7):617– 626. Vander-Borght, T., Minoshima, S., Giordani, B., et al. (1997) Cerebral metabolic differences in Parkinson’s and Alzheimer’s disease matched for dementia severity. J. Nucl. Med. 38:797–802. Vendette, M., Gagnon, J.F., Decary, A., et al. (2007) REM sleep behavior disorder predicts cognitive impairment in Parkinson disease without dementia. Neurology 69(19):1843–1849. Verbaan, D., Marinus, J., Visser, M., van Rooden, S.M., Stiggelbout, A.M., Middelkoop, H.A., and van Hilten, J.J. (2007) Cognitive impairment in Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry 78(11):1182–1187. Verny, M., and Duyckaerts, C. (1998) Dementia with Lewy bodies. Ann. Med. Interne (Paris) 149(4):209–215. Voon, V., and Fox, S.H. (2007) Medication-related impulse control and repetitive behaviors in Parkinson disease. Arch. Neurol. 64(8): 1089–1096. Voon, V., Kubu, C., Krack, P., Houeto, J.L., and Tröster, A.I. (2006) Deep brain stimulation: neuropsychological and neuropsychiatric issues. Mov. Disord. 21(Suppl 14):S305–S327. Warner, T.T., and Schapira, A.H.V. (2003) Genetic and environmental factors in the aetiology of Parkinson’s disease. Ann. Neurol. 53:516–523. Weintraub, D., and Hurtig, H.I. (2007) Presentation and management of psychosis in Parkinson’s disease and dementia with Lewy bodies. Am. J. Psychiatry 164:1491–1498. Weintraub, D., Moberg, P.J., Duda, J.E., Katz, I.R., and Stern, M.B. (2004) Effect of psychiatric and other nonmotor symptoms on disability in Parkinson’s disease. J. Am. Geriatr. Soc. 52(5):784–788. Weintraub, D., and Potenza, M.N. (2006) Impulse control disorders in Parkinson’s disease. Curr. Neurol. Neurosci. Rep. 6(4):302– 306. Wells, J.C., Keyl, P.M., Chase, G.A., Aboraya, A., Folstein, M.F., and Anthony, J.C. (1992) Discriminant validity of a reduced set of Mini-Mental State Examination items for dementia and Alzheimer’s disease. Acta Psychiatr. Scand. 86(1):23–31. Wenning, G.K., Ben-Shlomo, Y., Hughes, A., et al. (2000) What clinical features are most useful to distinguish definite multiple system atrophy from Parkinson’s disease? J. Neurol. Neurosurg. Psychiatry 68:434 – 440. Werber, E.A., and Rabey, J.M. (2001) The beneficial effect of cholinesterase inhibitors on patients suffering from Parkinson’s disease and dementia. J. Neural. Transm. 108(11):1319–1325. Whittington, C.J., Podd, J., and Kan, M.M. (2000) Recognition memory impairment in Parkinson’s disease: power and meta-analyses. Neuropsychology 14: 233–246. Wichamann, T., and DeLong, M.R. (2006) Deep brain stimulation for neurologic and neuropsychiatric disorders. Neuron 52(1):197–204. Williams, D.R., Warren, J.D., and Lees, A.J. (2007) Using the presence of visual hallucinations to differentiate Parkinson’s disease from atypical Parkinsonism. J. Neurol. Neurosurg. Psychiatry

1065

http://jnnp.bmj.com/cgi/rapidpdf/jnnp.2007.124677v1. Williams-Gray, C.H., Foltynie, T., Brayne, C.E., et al. (2007) Evolution of cognitive dysfunction in an incident Parkinson’s disease cohort. Brain 130(Pt 7):1787–1798. Wilson, R.S., Kaszniak, A.W., Klawans, H.L., and Garron, D.C. (1980) High speed memory scanning in parkinsonism. Cortex 16(1):67–72. Wilson, R.S., Mendes De Leon, C.F., Barnes, L.L., Schneider, J.A., Bienias, J.L., Evans, D.A., and Bennett, D.A. (2002) Participation in cognitively stimulating activities and risk of incident Alzheimer disease. JAMA 287(6):742–748. Woods, S.P., Fields, J.A., Lyons, K.E., Koller, W.C., Wilkinson, S.B., Pahwa, R., and Troster, A.I. (2001) Neuropsychological and quality of life changes following unilateral thalamic deep brain stimulation in Parkinson’s disease: a one-year follow-up. Acta Neurochir. (Wien) 143(12):1273–1277; discussion 1278. Woodward, T., Bub, D., and Hunter, M. (2002) Task switching deficits associated with Parkinson’s disease reflect depleted attentional resources. Neuropsychologia 40(12):1948. Wrase, J., Reimold, M., Puls, I., Kienast, T., and Heinz, A. (2006) Serotonergic dysfunction: brain imaging and behavioral correlates. Cogn. Affect Behav. Neurosci. 6(1):53–61. Wright, M.J., Burns, R.J., Geffen, G.M., and Geffen, L.B. (1990) Covert orientation of visual attention in Parkinson’s disease: an impairment in the maintenance of attention. Neuropsychologia 28(2):151–159. Wright, S.L., and Persad, C. (2007) Distinguishing between depression and dementia in older persons: neuropsychological and neuropathological correlates. J. Geriatr. Psychiatry Neurol. 20(4):189–198. Wszolek, Z.K., Vieregge, P., Uittis, R.J., et al. (1997) German-Canadian Family (Family A) with parkinsonism, amyotrophy, and dementia: longitudinal observation. Parkinsonism Rel. Disord. 3:125–136. Yamada, H., Aimi, Y., Nagatsu, I., et al. (2007) Immunohistochemical detection of L-DOPA-derived dopamine within serotonergic fibers in the striatum and the substantia nigra pars reticulata in Parkinsonian model rats. Neurosci. Res. 59(1):1–7. Yong, S.W., Yoon, J.K., An, Y.S., and Lee, P.H. (2007) A comparison of cerebral glucose metabolism in Parkinson’s disease, Parkinson’s disease dementia and dementia with Lewy bodies. Eur. J. Neurology 14(12):1357–1362. York, M.K., Dulay, M., Macias, A., et al. (2007) Cognitive declines following bilateral subthalamic nucleus deep brain stimulation for the treatment of Parkinson’s disease. J. Neurol. Neurosurg. Psychiatry http://jnnp.bmj.com/cgi/rapidpdf/jnnp.2007.118786v1. Yoshita, M. (1998) Differentiation of idiopathic Parkinson’s disease from striatonigral degeneration and progressive supranuclear palsy using iodine-123 meta-iodobenzylguanidine myocardial scintigraphy. J. Neurol. Sci. 155:60–67. Zahrt, J., Taylor, J.R., Mathew, R.G., and Arnsten, A.F. (1997) Supranormal stimulation of D1 dopamine receptors in the rodent prefrontal cortex impairs spatial working memory performance. J. Neurosci. 17(21):8528–8535. Zareparsi, S., Wirdefeldt, K., Burgess, C.E., Nutt, J., Kramer, P., Schalling, M., and Payami, H. (1999) Exclusion of dominant mutations within the FTDP-17 locus on chromosome 17 for Parkinson’s disease. Neurosci. Lett. 272(2):140–142. Zarranz, J.J., Alegre, J., Gémez-Esteban, J., et al. (2004) The new mutation, E46K, of α-synuclein causes Parkinson and Lewy body dementia. Ann. Neurol. 55:164 –173. Zgaljardic, D.J., Borod, J.C., Foldi, N.S., and Mattis, P. (2003) A review of the cognitive and behavioral sequelae of Parkinson’s disease: relationship to frontostriatal circuitry. Cogn. Behav. Neurol. 16(4):193–210. Zimmermann, P., Sprengelmeyer, R., Fimm, B., and Wallesch, C.W. (1992) Cognitive slowing in decision tasks in early and advanced Parkinson’s disease. Brain Cogn. 18(1):60–69.

64 Mild Cognitive Impairment BRENDAN J. KELLEY

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Mild cognitive impairment (MCI) defines a population experiencing cognitive decline in excess of that associated with normal cognitive changes of aging, but which does not reach the threshold of the earliest clinical features of dementia. In general, there is minimal if any impact on the individual’s daily activities. Mild cognitive impairment initially referred to memory impairment with preserved nonmemory cognitive performance, but more recently the term has been expanded to include other (nonmemory) cognitive domains. Most research has focused on the amnestic (memory predominant) form of MCI, a likely precursor of Alzheimer’s disease (AD). Over the past decade, research has demonstrated the MCI criteria to be reliable, and some data regarding patient outcomes has been established. Investigation of factors that may predict progression from MCI to AD remains an active area of research. Neuropathological studies have confirmed findings intermediate between those of AD and normal aging. Brain structural and functional neuroimaging documents a transitional state (between normal and AD) in MCI. One clinical trial suggested that donepezil may provide symptomatic benefit for a limited period of time in MCI, although most randomized clinical trials have been essentially negative. We discuss the implications of MCI for clinical practice and future research. INTRODUCTION AND CONCEPTUAL FRAMEWORK Clinicians are frequently asked to evaluate the importance of a patient’s forgetfulness. Elderly individuals who feel that their memory has changed are frequently (and understandably) concerned about developing AD. Neurodegenerative conditions such as AD are characterized by insidious onset and gradually progressive decline. The proposal of a “latent” stage of disease during which neuropathological changes occur but with subclinical or mild functional manifestations would seem reasonable. Mild cognitive impairment attempts to identify these “partially symptomatic” individuals who may be slightly forgetful but with preservation of other cognitive and functional abilities (Petersen et al., 1999; Petersen, Doody, et al., 2001; Petersen, 2003a). 1066

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Although superficially simple, the construct and clinical relevance of MCI has several important implications. Cognitive Changes of Normal Aging Discussion of MCI implies knowledge about the cognitive changes associated with normal aging. Characterization of these cognitive changes has remained an area of active research, without general agreement on the nature or degree of impairment or the neuropathological substrate of those impairments. Consequently, characterization of the early changes of MCI remains difficult (Ivnik et al., 1999). Normative data for the performance of elderly individuals on a variety of neuropsychological tests exist (Sliwinski et al., 1996; Petersen, 2003a). However, some argue that these normative values are contaminated by the inclusion of persons who would meet current definitions of MCI, and consequently they reflect more impairment than should be expected as a consequence of normal aging (Sliwinski et al., 1996). It is unclear how large an effect this may have on the normative values, or precisely how one would exclude such patients without prior knowledge of where the cutoff should exist. Although research efforts continue to more precisely delineate the cognitive changes associated with normal aging, clinical judgment remains the most reliable means to assess MCI at present. Dementia Also implicit to this discussion is a general agreement upon the definition of dementia. The general features that define dementia in the Diagnostic and Statistical Manual 3rd ed., rev. (DSM-III-R) remain a useful reference point (American Psychiatric Association [APA], 1987). These require memory impairment beyond that associated with normal aging and impairment of at least one other cognitive domain such as attention, language, visuospatial skills, or problem solving. These cognitive deficits are of sufficient severity to compromise daily functional activities and do not occur in the setting of altered sensorium such as delirium or an acute confusional state. In the DSM-III-R definition, memory impairment is an essential feature of dementia. Although this is true

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of many dementias, it is conceivable that patients with frontotemporal dementia or Lewy body dementia might present with significant impairment of nonmemory cognitive domains (and relatively spared memory functioning) early in the disorder. A more general definition of dementia as cognitive decline of sufficient severity to compromise a person’s daily function might be more inclusive of non-Alzheimer’s dementia subtypes.

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of the importance of the early diagnosis of dementia has grown, a more general construct of MCI and of specific subtypes of MCI has emerged. The general framework of MCI as the prodromal phase of a degenerative disease has remained a core concept to this evolving construct. DIAGNOSTIC CRITERIA

Proposed Benefit for Early Detection of Dementia Clinical and research efforts to define and to detect MCI presume a benefit to the earlier diagnosis of degenerative disease. In the context of the aging of the world’s population (Sloane et al., 2002), degenerative dementias represent an issue of growing global concern and hold a looming burden on healthcare resources. One major strategy for addressing this potential crisis involves delaying the onset and/or progression of these diseases. Early diagnosis then becomes paramount in trying to prevent subsequent disability. In a clinical context, detection of MCI may identify individuals at a greater risk of subsequent transition to AD and provide clinicians the opportunity to counsel these patients more effectively. Along these lines, the American Academy of Neurology (AAN) practice parameter addressing MCI concluded that persons with memory impairment who meet criteria for MCI are at increased risk of progressing to clinically probable AD and should be counseled and followed accordingly (Petersen, Stevens, et al., 2001). Ideally, identification of these individuals would allow for intervention to reduce the risk of progression to dementia at a stage where cognitive impairment has remained mild. At present, no such treatment exists. Candidate treatments include cholinesterase inhibitors, antioxidants, anti-inflammatory agents, and nootropics among others (Geda and Petersen, 2001).

The original criteria for MCI, designed to characterize the early stages of an AD-like process, were thus centered on memory impairment (Petersen et al., 1999). As discussed above, the construct of MCI has expanded to include many other types of intermediate cognitive impairment that may be precursors to a variety of dementing disorders. Figure 64.1 shows the diagnostic algorithm currently being used by the National Institute on Aging (NIA)–sponsored Alzheimer’s Disease Centers Program and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to diagnose MCI (Mueller et al., 2005). It should be emphasized that these criteria for MCI are clinical. Although neuropsychological testing may be helpful in characterizing the cognitive deficits in individuals having MCI, attempts to define arbitrary cutoffs on neuropsychological measures to |retrospectively identify individuals with MCI have demonstrated that application of these cutoff values in the absence of clinical judgment results in an unstable diagnostic paradigm and eliminates the predictive value of the MCI diagnosis (Ritchie et al., 2001). An international conference on diagnostic criteria helped to translate these findings into a clinical construct useful for primary care practitioners because these are the individuals most likely to first encounter persons in this mild range of cognitive impairment (Petersen, 2004; Winblad et al., 2004).

HISTORICAL CONTEXT Earlier cognitive investigations of older individuals had focused on those cognitive changes associated with normal aging. Terms such as aging-associated cognitive decline (AACD), age-associated memory impairment (AAMI), benign senescent forgetfulness, and late-life forgetfulness have been variably applied to these changes (Gauthier et al., 2006). By contrast, the MCI construct refers to an abnormal process, with the intent of identifying individuals in the prodromal stages of a dementing condition. By definition, it is fundamentally different from normal aging. Early MCI criteria focused on individuals having memory impairment (amnestic MCI) with the aim of identifying the prodromal state of AD. As our understanding

FIGURE 64.1 Algorithm for diagnosing and subtyping mild cognitive impairment. From Petersen, 2004. Reprinted by permission.

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CLINICAL DIAGNOSIS AND MCI SUBTYPES Clinical Diagnosis of MCI The importance of an accurate clinical history, preferably corroborated by an informant who knows the patient well, has remained paramount to the diagnosis of MCI. The first criterion for the diagnosis of MCI involves a cognitive concern on the part of the patient or an informant (Daly et al., 2000). Although these individuals are typically mildly affected and are aware of their deficits, corroboration by an informant is quite useful (Daly et al., 2000). The second criterion requires objective demonstration of cognitive impairment relative to age- and education-adjusted expectations (Ivnik et al., 1992; Smith et al., 1996). Some high-functioning patients who fall within the normal range of memory function may in fact have experienced a decline from their baseline level of function, and in these individuals, it may be appropriate to diagnose MCI. The combination of history, mental status exam, neuropsychological testing, and any additional information available is then used to determine whether the patient’s cognitive function is normal or compatible with dementia. If the patient has no dementia but has experienced a decline in cognitive function, and if most daily activities have been preserved, the patient can be designated as having MCI. Once an individual has been diagnosed as having MCI, the clinician evaluates whether a memory impairment is present. Screening memory tests such as a word list with a delayed recall component or more detailed neuropsychological testing can be useful to document memory functioning. As discussed above, though no particular reference point for normal aging is entirely accurate, normative data based upon patients of similar demographic characteristics may be useful. Patients with MCI tend to fall 1.5 standard deviations below their age- and education-matched expectations on measures of learning and recall, but it must again be emphasized that these are only guidelines and not cutoff scores for MCI. A screening mental status examination, such as the Mini-Mental State Examination (MMSE), Modified MiniMental State (3MS) Examination, and Kokmen Short Test of Mental Status (Folstein et al., 1975; Teng and Chui, 1987; Kokmen et al., 1991), should be administered in addition to the general neurological examination. However, these screening examinations are often insensitive in the MCI range of cognitive function. Patients with MCI may score in the 26 to 28 range on the MMSE, which is typically reported as normal. A mental status exam instrument without a significant memory component will not accurately differentiate patients with relatively isolated memory impairment from those experiencing normal aging. Consequently, the clinician may

consider augmenting the screening cognitive instrument with an additional memory test (Knopman and Ryberg, 1989; Petersen, 1991). Subtypes of MCI If a memory impairment is present, then the subtype of MCI is amnestic MCI (aMCI). Neuropsychological testing can further aid in determining whether other cognitive domains such as language, executive function, or visuospatial skills are also impaired. If the individual has an isolated memory difficulty, the MCI subtype would be aMCI-single domain. If another cognitive domain is impaired in addition to memory, then the MCI subtype is aMCI-multiple domain. Analogously, if the patient is determined to have cognitive impairment in the MCI range (not normal, no dementia) but without a significant memory impairment, the clinician then determines which cognitive domains are impaired (Fig. 64.1). Nonamnestic MCI (naMCI) is subtyped similarly to aMCI, with single domain (naMCIsingle domain) or multiple domain (naMCI-multiple domain) designations. The goal of such subtyping in clinical practice is to accurately describe the individual’s clinical syndrome. Evaluation Physical examination and medical laboratory tests similar to those used in the evaluation of dementia may identify medical issues that could affect cognitive function. Although depression can often be differentiated from AD, it may present with subtle memory impairment in its early stages, and clinicians should remain attuned to possible psychiatric etiologies as well. Mild cognitive impairment is a clinical diagnosis, and although neuropsychological testing alone does not establish the diagnosis of MCI, it can be suggestive in the appropriate clinical context (Petersen, 2000). The neuropsychological testing battery must include sufficiently difficult learning and recall tasks to help to differentiate patients with MCI from those experiencing normal aging. Figure 64.2 illustrates typical neuropsychological testing profiles of individuals with MCI, normal aging, and very mild clinically probable Alzheimer’s disease (Clinical Dementia Rating Scale [CDR] 0.5). On measures of general cognitive function such as the MMSE and full scale IQ, the individual with MCI performs more similar to a normal elderly patient, whereas memory function on delayed verbal recall (Logical Memory II) and nonverbal delayed recall (Visual Reproductions II) more closely resembles mild AD (Petersen et al., 1999). After describing the patient’s symptom complex, the clinician attempts to determine the etiology of these symptoms. Similar to evaluation of the etiology of

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FIGURE 64.2 Cognitive profiles comparing individuals having mild cognitive impairment with performance of normal patients and patients with AD. The Mini-Mental State Exam (MMSE) and Full Scale IQ represent measures of general intellectual function (top two panels). Measures of verbal memory function (Logical Memory II) and nonverbal memory function (Visual Reproductions II) are shown in the bottom two panels. From Petersen et al., 1999. Reprinted by permission.

dementia, historical, neuroimaging, or laboratory data may suggest the cause of MCI is of a degenerative, vascular, psychiatric, or traumatic etiology or secondary to a medical illness. The clinician then uses this available data to classify the MCI syndrome by likely etiology: degenerative (gradual onset, insidious progression), vascular (abrupt onset, stepwise decline, vascular risk factors, history of strokes, transient ischemic attack [TIAs]), psychiatric (depressed mood or anxiety), or secondary to concomitant medical disorders (for example, congestive heart failure, diabetes mellitus, systemic cancer).

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progression exists within the literature, due in part to variation in the definition and operationalization of the MCI criteria. Epidemiologic studies, particularly those that retrofitted neuropsychological criteria to existing databases, have reported variable rates of progression, with some studies reporting lower progression rates (Daly et al., 2000; Aggarwal et al., 2005; Gauthier et al., 2006; Fischer et al., 2007). In the large clinical trials studying MCI, progression rates have varied from 5%–16% per year (Petersen et al., 2005). Despite the variability in the precise rate of progression reported, all of these studies have reported progression rates far higher than the population incidence figures for AD of 1%–2% per year. The data from longitudinal studies suggests that individuals meeting criteria for MCI, particularly aMCI of a degenerative etiology, progress to dementia at a rate of 10% per year. The majority of individuals having aMCI of a degenerative etiology progress to AD. A large prospectively designed trial conducted in Germany reported that patients with MCI diagnosed using the criteria in Figure 64.1 progressed to dementia at rates of 7.2%– 10.2% per year (Busse et al., 2006). In this study, some patients improved from MCI to normal (approximately 5% per year), but a subset who initially improved subsequently declined, implying instability of the clinical course during progression to dementia. The vast majority of dementia cases were believed to represent AD. For patients presenting for evaluation of a cognitive concern in a typical neurology practice, the progression rate is likely to be in the 10%–15% per year range for those meeting the criteria for aMCI. Community studies enrolling more heterogeneous patient populations suggest that in those populations the rates to be lower, perhaps in the 8%–10% per year range. It is important to

OUTCOMES Combining the clinical MCI subtype with the presumed etiology, the clinician can make a reliable prediction about the outcome of the MCI syndrome as illustrated in Figure 64.3. It should be acknowledged that part of the construct illustrated in Figure 64.3 is theoretical and not yet validated at this time. Amnestic MCI of a degenerative etiology is very likely to progress to AD, and the AAN has endorsed this construct in its practice parameter (Petersen, Stevens, et al., 2001). The corresponding outcomes of patients having naMCI subtypes are currently under investigation. Patients diagnosed with aMCI using the criteria outlined in Figure 64.1 and having a presumed degenerative etiology will progress to dementia (usually AD) at a rate of 10%–15% per year (Petersen et al., 1999; Petersen et al., 2005). Some variability in the reported rate of

FIGURE 64.3 Predicted outcome of mild cognitive impairment subtypes according to presumed etiology. Adapted from Petersen, 2003a. Reprinted by permission.

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inform patients that a small fraction of individuals with MCI will improve and that others may remain clinically stable for many years. Thus, though MCI (and particularly aMCI) of a presumed degenerative etiology identifies individuals at increased risk of developing dementia, the diagnosis of MCI is not deterministic of progression to dementia. A progression rate of 10%–12% per year is probably a reasonably accurate estimate to use in counseling patients. PREDICTORS OF PROGRESSION Identification of clinical, genetic, and surrogate biomarker factors that may aid in identifying patients with MCI likely to progress to dementia or AD more rapidly than others remains a major area of research interest. In addition to the obvious benefit in counseling patients and family members, those designing clinical trials of potential therapeutics would like to stratify patients to enroll those at increased risk of progressing to AD within the time frame of the study. Several potential predictors of progression have emerged: (1) clinical severity, (2) Apolipoprotein ε4 (ApoE4) carrier status, (3) MRI hippocampal volumes, (4) cerebrospinal fluid (CSF) and plasma biomarkers, (5) fluorodeoxyglucose (FDG)-positron emission tomography (FDG-PET), and (6) ligand-bound PET imaging. Although very preliminary, the predictive value of several plasma signaling proteins recently reported to be dysregulated in AD (Ray et al., 2007) will likely be investigated in the near future. Clinical Severity Individuals with more severe memory impairment progress to AD more rapidly than those having less severe memory impairment. This may account for some of the variability observed in the clinical trials to be discussed later and for some of the variability in the epidemiologic data. Individuals having the aMCI-multiple domain subtype will probably progress more rapidly than those having aMCI-single domain. A recent study reported that individuals with aMCI-multiple domain subtype actually had poorer overall survival than individuals with aMCI-single domain subtype (Hunderfund et al., 2006).

Apolipoprotein ε Genotype The genetic features of MCI are similar to those of clinically probable AD. Apolipoprotein ε4 carrier status is a recognized risk factor for the development of AD (Corder et al., 1993). Apolipoprotein ε4 carrier status has been demonstrated to have predictive value for progression from MCI to AD in several studies, including the Alzheimer’s Disease Cooperative Study (ADCS) MCI Treatment Trial and the Religious Order Study (Petersen et al., 1995; Tierney et al., 1996; Aggarwal et al., 2005). Apolipoprotein ε4 carrier status correlates with more rapid progression of hippocampal atrophy on magnetic resonance imaging (MRI) in adults who are cognitively normal as well (Jak et al., 2007). Although ApoE4 carrier status may predict a higher rate of progression to AD among those diagnosed with aMCI, it is not currently recommended for routine clinical use (Farrer et al., 1997). MRI Volumetric Studies A great deal of data exist regarding volumetric analyses of structural MRI as a predictor of progression from MCI to AD. Hippocampal atrophy was shown to be a prominent and important predictor of subsequent progression from MCI to dementia and AD (Jack et al., 1999) (Fig. 64.4). Volumetric measurements of entorhinal cortex volume, whole-brain volume, and ventricular volume have also shown utility (Jack et al., 2005). An analysis employing a combined measurement of entorhinal and hippocampal volume reported a small but detectable predictive utility for this combined measurement independent of age and cognitive variables (Devanand et al., 2007). Another study suggests that subjective visual assessments of the hippocampal formation may provide predictive utility as well (DeCarli et al., 2007). An investigation of the longitudinal rate of hippocampal atrophy identified several baseline characteristics (age, worse baseline cognitive performance, ApoE4 carrier status, and baseline hippocampal volumes) predicted a higher rate of hippocampal atrophy over the subsequent 2 years (van de Pol et al., 2007). Evaluating the usefulness of volumetric assessments has been complicated by the variable algorithms used to segment MRI volumes as well as variability in the

FIGURE 64.4 Coronal magnetic resonance imaging showing degrees of hippocampal atrophy in normal (left), mild cognitive impairment (middle), and Alzheimer’s disease (right) patients.

64: MILD COGNITIVE IMPAIRMENT

populations studied. Although some studies have demonstrated a small added predictive value, the magnitude of this among patients having less readily detectable cognitive impairment has yet to be determined. The ADNI is intended, in part, to address these issue (Mueller et al., 2005). CSF and Plasma Biomarkers Cerebrospinal fluid and plasma biomarkers are in the early stages of development. Some studies have suggested that CSF measures of beta-amyloid (Aβ) and tau may aid in differentiating patients with MCI from those experiencing normal aging (Galasko et al., 1997; Galasko et al., 1998; Growdon, 1999), and others have suggested that these markers may have utility in predicting progression from MCI to AD (Sunderland et al., 1999; Stefani et al., 2006). A multinational study found that baseline CSF levels of tau phosphorylated at threonine 231, but not total tau protein levels, correlated with cognitive decline and conversion from MCI to AD (Buerger et al., 2002). This was confirmed by another study investigating several biomarkers longitudinally (Brys et al., 2007). Pathological studies in AD reported a correlation between neocortical neurofibrillary pathology and tau phosphorylated at threonine 231 (p-tau231) but not tau phosphorylated at threonine 181 (p-tau181) (Buerger et al., 2006). A study investigating the utility of CSF concentrations of Aβ 1–42, total tau (T-tau), and p-tau181 in predicting progression from MCI to AD over a 4year observation window reported a sensitivity of 95% and specificity of 83% using the combination of elevated T-tau and lowered Aβ 1–42 (Hansson et al., 2006). A similarly designed study that used a 2-year observation window reported sensitivity and specificity of 70%– 80% for p-tau231 and for the ratios of T-tau/Aβ42/40 and T-tau/Aβ42/40, suggesting that these biomarkers may have predictive value even when investigated in a 2-year trial (Brys et al., 2007). The obvious hope is that biochemical markers associated with AD pathology may augment clinical insights to provide improved prediction of the likelihood of progression from MCI to AD at the earliest possible stage. Although CSF biomarkers continue to be explored in large clinical trials (such as ADNI; Mueller et al., 2005), the currently available data are insufficient to recommend the use of CSF biomarkers in evaluation of MCI. A recent report on the dependence of CSF Aβ levels upon time of day and activity may imply that careful design of the conditions under which CSF is collected may make predictions based upon the measurements of these biomarkers more robust (Bateman et al., 2007). Study of plasma Aβ levels is less well developed, but this or another plasma biomarker may prove useful in the future (van Oijen et al., 2006; Graff-Radford et al., 2007).

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FDG-PET Imaging Some evidence suggests that metabolic changes in the brain may precede structural changes in AD and, therefore, metabolic functional imaging might detect pathological changes at an earlier point than structural neuroimaging. Clearly, this would provide valuable prognostic information directly relevant to individuals having MCI. Investigations of FDG-PET have reported FDG-PET changes suggestive of evolving AD among patients who were cognitively normal genetically predisposed to develop AD (Small et al., 1995; Reiman et al., 1996). Further, several studies indicate that AD patterns of PET at the MCI stage predict progression to AD (Anchisi et al., 2005; Drzezga et al., 2005). Although intuitive, this technique requires further validation before it could be recommended for routine clinical use. Ligand-bound FDG-PET Recently, imaging techniques that attempt in vivo identification of proteins implicated in AD pathology have been developed. Such imaging techniques could potentially have prognostic value in predicting progression of MCI. The Pittsburgh compound B (PiB) (Klunk et al., 2004) employs FDG bound to a ligand that binds to amyloid in an attempt to image amyloid deposition in the brain. Initial studies have suggested utility in distinguishing between patients who are normal, patients with MCI, and patients with AD. The limited data available investigating this compound in MCI indicate three patterns: PiB retention similar to that of patients who are normal, PiB retention mimicking patients with AD, and intermediate patterns. The clinical meaning of the three subgroups that these patterns of uptake define has not yet been defined, and only very limited longitudinal data are available regarding the outcome of these patients with MCI. It must also be acknowledged that PiB retention is not specific to amyloid deposition related to AD and that increased PiB retention has also been reported in cerebral amyloid angiopathy (Johnson et al., 2007; Lockhart et al., 2007). 2-(1-[6-[(2-[18F]fluoroethyl)(methyl)amino]amino]2-naphthyl]ethylidene)malononitrile (FDDNP), developed at University of California at Los Angeles (UCLA), is a ligand-bound FDG tracer that labels amyloid and tau proteins. This agent theoretically labels neuritic elements in the brain, including neuritic plaques and neurofibrillary tangles (NFTs) (Small et al., 2006). By labeling amyloid and tau, FDDNP may be less specific for amyloid pathology but may prove more sensitive at imaging the total pathological burden. Again, these data are very preliminary, and longitudinal studies of FDDNP, PiB, and other ligand-bound agents will be needed to quantify and validate their performance (Ryu and Chen, 2008).

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NEUROPATHOLOGICAL CORRELATES The neuropathological substrate of MCI, particularly aMCI of presumed degenerative etiology, continues to be a topic of active research and debate. Some investigators contend that in patients with aMCI the neuropathological substrate of AD is already in place and, therefore, we should diagnose these patients as having AD (Markesbery et al., 2006). In support of this, a Washington University study asserted that AD exists neuropathologically in MCI (Morris et al., 2001). However, investigators at Washington University did not use MCI as a clinical designation and, therefore, likely see only patients at a more clinically advanced stage than MCI. Further, this study did not include autopsy data from patients at the MCI stage or even the CDR 0.5 stage. Most patients had progressed clinically to CDR 1 by the time of autopsy. Thus, these data are perhaps more correctly viewed as an outcome study, rather than a crosssectional study of patients with mild degrees of cognitive impairment. As such, it would be reasonably expected that their neuropathological data demonstrate AD. Several studies have reported on the neuropathology of patients who died with the clinical classification of MCI (Bennett et al., 2005; Petersen et al., 2006). Pathological data in the Religious Order Study demonstrated an intermediate pathology between the neuropathological changes of normal aging and those of very early AD (Bennett et al., 2005). These investigators reported that a combination of neuropathological findings, including neurodegeneration and vascular pathology, contributed to the clinical picture of MCI. A recent Mayo Clinic study found neuropathologic features intermediate between changes of normal aging and AD in patients who died though their clinical classification was aMCI (Petersen et al., 2006). Most of these patients had some degree of medial temporal lobe pathology, usually NFTs, but only sparse diffuse plaques in the neocortex. They had mostly low NIA-Reagan scores for the probability of meeting neuropathology criteria for AD. A study from the University of Kentucky reported pathological findings similar to those of early AD among patients with aMCI (Markesbery et al., 2006). These investigators acknowledged that the patients with MCI may have been more clinically advanced than in other studies, and that the patients with AD used for comparison were in the early clinical stages of AD. A second study from Mayo investigated the pathological outcomes of patients with aMCI. As predicted, the majority of patients had progressed to AD. However, as many as 20% had other types of dementing disorders such as frontotemporal dementia, dementia with Lewy bodies, progressive supranuclear palsy, and vascular dementia, although taken singly, each of these disorders was uncommon (Fig. 64.5) (Jicha et al., 2006).

FIGURE 64.5 Neuropathological outcome of subjects with history of mild cognitive impairment. From Petersen, 2007b. Reprinted by permission.

Therefore, although most aMCI cases progress to AD, some develop other clinical syndromes. In summary, the actual pathologic substrate of most patients with aMCI appears to be one of evolving AD. That is, the full AD neuropathologic spectrum is not present at the MCI stage, but many incipient features are evolving. EPIDEMIOLOGICAL DATA REGARDING MCI There are a number of cohort studies that have investigated MCI prospectively (Lopez et al., 2003). However, due to MCI being a relatively recently defined construct, several epidemiological studies were already under way without having been designed to incorporate MCI criteria. Various attempts have been made to “retrofit” MCI criteria into these already designed studies, with variable success. These considerations likely account for the substantial variability in reported prevalence figures. Table 64.1 shows the reported prevalence rates for MCI and other related constructs (such as AACD) among studies that retrofitted MCI criteria to ongoing longitudinal studies, as well as newer studies employing MCI criteria prospectively. Among studies using current MCI criteria prospectively, the reported prevalence rates have generally been about 12%–18% among patients with no dementia older than age 65 years. As would be expected, lower rates are reported when the entire population, including patients with dementia, serves as the denominator (Unverzagt et al., 2001; Bennett et al., 2002). These figures depend somewhat on the specific subtype of MCI studied and the methods used to operationalize the MCI criteria. For example, using a neuropsychological algorithm to define MCI, prevalence figures are quite variable (Ritchie et al., 2001), likely reflecting the arbitrary selection of the neuropsychological instruments and the

64: MILD COGNITIVE IMPAIRMENT TABLE

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64.1 Selected MCI Epidemiology/Cohort Studies Prevalence %

Reference

Population

Number of Participants

Retrospective/ Prospective

Diagnosis Clinical/Algorithmic

CIND

AACD

MCI

9

3-5

Busse et al., 2006

Germany

980

P

A

Graham et al., 1997

Canada

2,914

R

C

17

5

Unverzagt et al., 2001

African American, Indianapolis, IN

351

P

C

23

12

Bennett et al., 2002

Catholic clergy

798

P

C

Ritchie et al., 2001

France

833

R

A

Lopez et al., 2003

Multicenter

927

P

C

18

Hanninen et al., 2002

Finland

806

P

A

5

Boeve et al., 2003

Rochester, MN

111

P

C

12

Petersen et al., 2007

Rochester, MN

1,704

P

C

16

Jungwirth et al., 2005

Austria

592

P

A

24

Di Carlo et al., 2007

Italy

2,768

R

A

Das et al., 2007

India

745

P

C

14

Luck et al., 2007

Germany

3,327

P

C

15

26 21

9.5

3

16

CIND: cognitive impairment not demented; AACD: aging-associated cognitive decline; MCI: mild cognitive impairment.

arbitrary definition of cutoff scores. Some studies have implied longitudinal instability of the MCI construct, although this instability may simply have reflected the test–retest variability of the neuropsychological instruments that had been used to define MCI (Ritchie et al., 2001; Larrieu et al., 2002), rather than instability of the clinically defined MCI construct described here. Clearly, the numerous methodological considerations of these various studies complicate the interpretation of the available epidemiologic data on MCI. Overall, the data in Table 64.1 indicate that the prevalence of MCI is probably in the 12%–15% range among individuals 65 years and older, with an incidence in the range of 1% per year. These figures are similar to those reported for AD.

viduals in whom specific targeted therapies could be investigated. For the reasons discussed above, aMCI may provide a potential target for interventions directed towards the prodromal stage of AD. Symptomatic Treatment in AD Five drugs have been approved by the FDA for the treatment of clinically probable AD, although only four are commonly used. Three of these four are acetylcholinesterase inhibitors, used in response to research indicating a cholinergic deficit in AD (Bowen et al., 1976; Davies and Maloney, 1976; Petersen, 1977; Whitehouse et al. 1981). In the past decade, acetylcholinesterase inhibitors have been shown to be effective at modulating the symptoms of AD and currently form the mainstay of treatment in clinically probable AD.

TREATMENT There is no Food and Drug Administration (FDA)approved treatment intervention for MCI. Given the discussion above, one would not expect an overall treatment indication of MCI any more than one would expect an overall indication for dementia. Analogous to the subtyping of dementia into diseases such as AD, vascular dementia, frontotemporal dementia, and so on, subtyping of MCI may identify populations at risk of progressing to specific dementia subtypes, thereby identifying indi-

Disease Modifying Treatment in AD Considerable research supports a role of oxidative damage in the pathophysiology of AD, and some epidemiologic data suggest that antioxidants may be associated with a lower incidence of AD (Goodwin et al., 1983; Gale et al., 1996; La Rue et al., 1997; Perrig et al., 1997; Morris et al., 1998). A clinical trial of patients with moderate AD reported a benefit for vitamin E and selegiline in slowing the progression of moderate AD

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(Sano et al., 1997). Following that study, an AAN practice parameter recommended that vitamin E at 1000 IU twice daily be considered as a treatment to slow the progression of AD (Doody et al., 2001). Recent metaanalyses that raised concerns of an increased risk of death among those taking greater than 400 IU per day of supplemental vitamin E (Miller et al., 2005) have cooled enthusiasm for recommending this treatment, although the applicability of those meta-analysis findings to typical AD patients is unclear.

meet criteria for dementia. The primary outcome measure was clinical progression to AD. The study planners projected a progression rate of 10%–15% per year for the patients with aMCI and powered the study to detect a reduction in that rate of 33%. The patients with aMCI progressed to AD at a rate of 16% per year in this study, similar to the design projection. Neither of the two active treatment arms reduced the risk of progression to AD over the entire 3 years of the study. However, donepezil did reduce the risk of progression to AD for the first 12 months of the study in all patients, and this effect persisted up to 24 months among ApoE4 carriers. In analyzing this data, it should be noted that of the 214 conversions from aMCI to AD encountered in the trial, 76% were ApoE4 carriers. There was no treatment effect for vitamin E. The secondary outcome measures generally corroborated these primary outcome findings regarding the risk and rate of progression from aMCI to AD. Of the 214 conversions to dementia, 212 were diagnosed with possible or probable AD, indicating that the aMCI criteria were quite specific in identifying individuals at higher risk for developing AD. The authors of this study concluded that although donepezil could not be generally recommended for the treatment of aMCI, clinicians should discuss the potential role of this medication with patients on an individual basis. Although there is no FDA-approved treatment for MCI, the off-label use of donepezil could be considered for treatment of aMCI on an individualized basis. On the basis of this study, the authors did not advocate using ApoE4 genotyping with the aim of identifying individuals having a higher likelihood of a clinical progression to AD at an earlier stage in the disease process, in accord with the many consensus panels that have argued against this type of testing. As the first clinical trial to show the ability of an intervention to delay the onset of clinical AD, this was an important study that provides evidence for the conceptual framework and feasibility of attempts to intervene at the MCI stage.

CLINICAL TRIAL DATA IN MCI Five major drug trials investigating compounds used for the symptomatic treatment of AD in MCI populations have taken place. These are summarized in Table 64.2. Taken together, these trials enrolled 4,000–5,000 patients in numerous centers around the world. Unfortunately, none has been notably positive, with one possible exception (Petersen, 2003b). The numerous possible reasons for this outcome are discussed later. Donepezil and Vitamin E Trials The ADCS enrolled 769 patients with aMCI among 69 centers in the United States and Canada and (Petersen et al., 2005). Patients were randomized to three treatment groups: donepezil (10 mg per day), vitamin E (2,000 IU per day), or placebo. All participants received a multivitamin. Each patient was followed with clinical evaluations every 6 months for up to 3 years. The entry criteria included those outlined in Figure 64.1 for aMCI, a score on the MMSE of 24 or greater, and performance 1.5 to 2 standard deviations below education-adjusted normative values on a modified version of the Wechsler Memory Scale– Revised Logical Memory II subtest. These criteria ensured that the patients were sufficiently memory impaired to be close to transitioning to AD, yet did not

TABLE

64.2 MCI Clinical Trials

Sponsor

Compound

ADCS

Donepezil

Number Enrolled

Duration (years)

769

3

Primary Outcome

Progression Rate

Result

AD

16%

Partially

Vitamin E

Reference Petersen et al., 2005

Positive

Johnson and Johnsona

Galantamine

2048

2

CDR 1

5%

Negative

Gold et al., 2004

Novartis

Rivastigmine

1018

4

AD

5%

Negative

Feldman et al., 2007

Merck

Rofecoxib

1457

3-4

AD

5%

Negative

Thal et al., 2005

Two trials. AD: Alzheimer’s disease; ADCS: Alzheimer’s Disease Cooperative Study; CDR: Clinical Dementia Rating Scale. a

64: MILD COGNITIVE IMPAIRMENT

Galantamine Johnson and Johnson sponsored two studies investigating the impact of galantamine on the progression from aMCI to AD (Gold et al., 2004). These multinational studies assessed the rate of progression from aMCI to AD using progression on the CDR from 0.5 to 1 as their primary end point. This important distinction, using progression on the CDR rather than clinical criteria for AD, renders the results of the study more difficult to interpret. For example, a patient may progress from aMCI to AD while remaining at the CDR level of 0.5, which could result in decreased sensitivity due to the study design. These two trials enrolled 2,048 patients in total, among whom 43% were ApoE4 carriers. Overall, 13% on galantamine progressed from aMCI to AD (vs. 18% in the placebo group) in one trial and 17% of the galantamine group progressed (vs. 21% of the placebo group) in the second trial. Although this trend in favor of galantamine was present, neither trial reached statistical significance. Magnetic resonance imaging was performed on many of the participants, with a suggestion that galantamine may have reduced the rate of wholebrain atrophy over the 2-year study period. Thus, although there were no significant treatment effects in these trials, there was some suggestion of a drug effect, possibly corroborated with MRI volumetric measures. Both studies showed a greater number of deaths in the galantamine treated groups relative to placebo, necessitating a warning about this possibility. It is possible that fewer than expected deaths occurred in the placebo groups, but this is uncertain. Rivastigmine Novartis investigated its acetylcholinesterase inhibitor rivastigmine (Feldman et al., 2007) in a 3-year study that enrolled 1,018 patients with aMCI and assessed progression from aMCI to AD. This multinational study had many of the same features as the ADCS but encountered difficulties with the operationalizing diagnostic criteria and neuropsychological measures. The study was conducted across 14 countries and required multiple translations of the neuropsychological instruments employed. Further, this study enrolled patients at a milder stage than that in the ADCS trial of donepezil (Petersen, 2007a). Likely as a consequence of these operational difficulties, the conversion rate was much lower than expected, necessitating extension of the study to 4 years to achieve an adequate number of events. Over the 4-year time period, 17.3% of patients taking rivastigmine progressed to AD compared to 21.4% of patients on placebos. Although the difference was in the predicted direction, it did not reach statistical significance. Similarly, there was no significant difference between treatment arms in the various neuropsycho-

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logical measures used as secondary end points. Another criticism of the study design was that ApoE4 genotyping was performed in only a subset of patients, which did not allow this important stratifying variable to be included in the data analysis. The investigators speculated that the inclusion criteria (which were different from those used in the donepezil trial) as well as the exclusion of patients having symptoms of depression at baseline may have contributed to the lower-thananticipated observed conversion rate of 5% per year. It should be noted that despite the low conversion rate, nearly all patients who progressed to dementia were diagnosed with AD. Rofecoxib Merck sponsored a large trial of the Cyclooxygenase-2 (COX 2) inhibitor rofecoxib in patients with aMCI (Thal et al., 2005). This 2-year trial enrolled 1,457 patients and used progression from aMCI to AD as the primary outcome measure. The observed progression rate was lower than anticipated, necessitating extension of the study to 3–4 years. This study reported annual conversion rates to AD of 6.4% in the rofecoxib group and 4.5% for the placebo group, achieving statistical significance (p = .011) in favor of the placebo group. The cognitive measures used as secondary outcomes did not corroborate the finding of the primary outcome, and consequently the authors tended to dismiss the significance of the finding in favor of placebo. The authors identified several factors that correlated with an increased risk of progression to AD, including lower MMSE score, ApoE4 carrier status, age, gender, and prior use of ginkgo biloba. Including these measures in a multivariate prediction model, the statistical significance of the primary outcome was no longer present. The investigators in this trial had modified the memory inclusion criteria, accepting a lesser degree of impairment than in other MCI studies. It is unclear if this design resulted in a more mildly affected study population overall, but it may have contributed to the low observed conversion rate. It is uncertain whether the findings of this study suggest that use of rofecoxib increased the rate of progression to AD, or whether this finding was simply spurious. In either case, it did not demonstrate the predicted benefit. Discussion of Available Clinical Trial Data Considered together, these trials allow some important conclusions. Many factors likely contributed to the variability in rate of progression from aMCI to AD among these clinical trials, including differences in the patient populations recruited and, importantly, the operationalization of the aMCI criteria and the primary outcome measures (Petersen, 2007a). Pertinent to the multina-

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tional trials, translation of the evaluative instruments and cultural variability as to what constitutes dementia or AD or aMCI may have had a significant impact on the trial outcomes. Due to differing normative expectations of daily functioning, the clinical threshold for a diagnosis of dementia or AD varies widely among cultures. Extending this reasoning, one would expect these cultural differences to be magnified in making the more subtle clinical determination of aMCI. Although multinational clinical trials present opportunities to investigate an intervention in a wider population, logistical difficulties relevant to studies in aMCI and AD may have hampered the ability to produce reliable results. These studies varied in the implementation procedures used to satisfy the memory criteria of the aMCI diagnosis. These seemingly harmless differences in cutoff scores, when used as inclusion criteria, may significantly affect the composition of the study groups. For example, defining milder degrees as inclusion criteria for patients with aMCI may result in very mild aMCI and possibly patients who were normal (which would have been in the control group of another trial) being included in the treatment groups, resulting in a lower than expected conversion rate. Because ApoE4 carrier status is a strong predictor of progression to AD among aMCI populations, the variable ApoE4 carrier rates among these studies are another important factor that likely influenced the outcomes. All of these trials used conversion to AD as a primary outcome measure, but they differed in the method by which this end point was determined. In addition to cultural differences in the clinical diagnosis of AD, these studies also varied as to how the primary outcome measure was operationalized. One study used a change in the CDR to determine conversion to AD, whereas others used clinical diagnosis of AD by the investigators to determine this end point. Because these studies rely upon identification and definition of subtle phenomenon of the incipient stages of AD, seemingly innocuous differences in implementation criteria may lead to significant impacts on outcome measures. A few important points relevant to the construct of aMCI emerge from these studies. First, although the overall progression rate ranged from 5% to 16%, all of these rates are much higher than the population incidence rate for AD of 1%–2%. The rate of 16% per year in the ADCS donepezil trial far exceeds this general population rate by severalfold. Even the “least successful” trial employing aMCI criteria identified a population that was at 2 or 3 times the risk of developing AD when compared to the general population. Therefore, although the treatments studied were essentially ineffective, the trials themselves documented the success and utility of using aMCI criteria to enroll a population enriched for individuals at higher risk of developing AD during the time frame of a clinical trial. As disease-modifying treat-

ments for AD move into clinical trials, the ability to identify a group of patients likely to progress at an accelerated rate would provide an excellent clinical substrate for testing compounds targeting the underlying disease process. These clinical trials confirm that the aMCI construct does identify such individuals. MCI IN CLINICAL PRACTICE Ultimately, the clinical utility of MCI as a diagnostic entity will be determined by its usefulness for clinicians in caring for and counseling patients. Most literature to date has investigated the aMCI subtype of a degenerative etiology, a likely prodrome of AD. Therefore, this discussion primarily pertains to that clinical subtype. In 2001, the AAN endorsed the construct of MCI (Petersen, Stevens, et al., 2001). This evidence-based practice parameter found sufficient evidence to encourage clinicians to identify and evaluate patients in their practices for the diagnosis of MCI. Based on many of the data discussed above, these individuals are at increased risk of developing dementia in the future and should be counseled appropriately. Although no disease-modifying treatment currently exists, therapeutic interventions may become available for these patients in the future. In the years since the publication of this practice parameter, a tremendous increase in the available data regarding MCI has occurred and consequently, the practice parameter will likely be updated in the near future. As older individuals represent a continually increasing segment of U.S. society, the number of patients presenting with subtle cognitive concerns will increase, as will the demands, desires, and concerns of these individuals. Clinicians will require a diagnostic framework in which to evaluate, classify, and ultimately treat these individuals. If one accepts the premise that individuals pass through a stage of “partial symptoms” en route to developing a degenerative dementia such as AD, then the construct of MCI provides such a framework. It must be noted that diagnostic classifications such as MCI are arbitrary. The distinctions between categories such as MCI and clinically probable AD are artificial when considered in the context of the gradual evolution of AD. Nevertheless, this terminology addresses the need to communicate clearly and effectively with our patients and with each other. The clinical designation of aMCI can be quite useful in characterizing people who do not meet diagnostic criteria for AD or dementia and avoids the stigma that labels such as dementia or AD may carry. HOW SHOULD I COUNSEL PATIENTS HAVING MCI? It would be appropriate to place the evolving nature of the construct of MCI into context. That is, there cer-

64: MILD COGNITIVE IMPAIRMENT

tainly remains discussion in the literature regarding the precise characterization of the diagnostic criteria for MCI within the research literature. With that said, a patient who meets the criteria outlined in Figure 64.1 and whose symptoms are felt to be due to a degenerative process is likely at a 10%–15% per year risk of progressing to clinically probable AD. To the extent a patient deviates from these criteria, this prediction could be adjusted upward or downward. For example, an ApoE4 carrier (keeping in mind that ApoE4 testing is not recommended in this clinical situation) having hippocampal atrophy evident on MRI would presumably be at a higher risk of progressing more rapidly. Alternatively, an individual not carrying the ApoE4 genotype with no family history of dementia and having normal appearing hippocampal structures would presumably progress less rapidly. Of course, regular clinical reevaluation remains the best adjunct for making this determination. Discussion of the implications of the MCI diagnosis is perhaps the most important aspect of counseling at this time. Although a patient is cognitively competent, they may wish to begin planning for the future and addressing financial issues, retirement, living arrangements, and so on. As discussed above, there is no medication with an FDA-approved indication for MCI. The results from the ADCS trial provide an excellent framework for discussion of the possible use of a cholinesterase inhibitor. A 63-year-old high-functioning professional may regard the modest symptomatic benefit demonstrated in that trial as important to his or her ability to continue to function in the work environment and may be inclined towards early treatment with donepezil. Alternatively, a 75-yearold retiree primarily engaged in leisure activities may choose to defer treatment until a stage of greater impairment. As these simple caricatures illustrate, the choice of whether and when to initiate treatment with a cholinesterase inhibitor is ultimately a personal decision that must be made following a frank discussion between the clinician and patient of realistic aims and expectations. Many physicians recommend a variety of lifestyle modifications in an attempt to minimize the rate of progression, although definitive data here are limited. Frequently, physicians recommend that patients remain physically active, intellectually engaged, socially active, and that they follow a heart-healthy diet (Fratiglioni et al., 2004; Rovio et al., 2005). Although insufficient data exist to support a direct impact on progression from aMCI to AD, these lifestyle modifications may improve an older individual’s overall quality of life, irrespective of an impact on progression to AD. Some preliminary evidence suggests possible benefit for cognitive rehabilitation in patients with MCI, although large studies with meaningful long-term follow-up are lacking (Belleville, 2008). Lasty, patients may derive substantial encouragement and reassurance from the recognition that MCI is a rap-

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idly evolving topic of investigation and that they should remain in touch with their physician regarding future advancements that will likely be made in this area. FUTURE RESEARCH PROSPECTS The MCI construct has become useful in research and clinical practice and is being considered for inclusion in the next revision of the Diagnostic and Statistical Manual of Mental Disorders–V (Petersen and O’Brien, 2006). As stated earlier, the clinical value of the MCI construct ultimately will be determined by practicing clinicians. Many research efforts aim to improve the accuracy of outcome prediction for patients with aMCI. It has been demonstrated that patients carrying ApoE4 genotypes and having atrophic hippocampi on MRI will likely progress more rapidly. Cerebral metabolic patterns seen on FDG-PET and CSF biomarkers, such as phosphorylated tau and Aβ 1–42, may also provide useful prognostic data. Newer molecular imaging techniques employing PiB and FDDNP may provide valuable antemortem detection of underlying pathology associated with aMCI in the future. Studies investigating these agents in aMCI are already under way. Currently, clinical criteria (Fig. 64.1) can be used to identify patients having MCI. Consideration of the suspected etiology will then allow discussion of likely outcomes with the patient (Fig. 64.2). In the research setting, a combination of these clinical considerations, augmented with some combination of the technological measures mentioned above, will be evaluated to identify combinations that improve prognostication. Although these techniques will initially be restricted to research settings, if they are proven useful, they may be adopted into practice at tertiary care centers for the adjudication of difficult cases. A large number of agents proposed to have a diseasemodifying effect in AD are at various stages of investigation. These include nonsteroidal anti-inflammatory medications proposed to modulate the biochemical processing of amyloid, active, and passive immunization strategies and monoclonal antibodies, among others. The construct of aMCI may identify individuals more likely to benefit from these agents due to intervention occurring at a time when symptoms are minimal, and as such may play an important role in structuring the enrollment and end points of future clinical trials of such disease-modifying agents (Cummings et al., 2007). CONCLUSION Intervention for individuals likely to develop AD during an asymptomatic or minimally symptomatic state holds the greatest promise, as well as poses the greatest chal-

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DEMENTIA

lenges, for disease-modifying therapies. Most existing research supports the finding that aMCI identifies individuals likely to develop AD in the future. When disease-modifying therapies directed at AD emerge, the MCI construct may prove useful to identify individuals at an early stage in the course of the disease who stand to ben