Neuroscience of Alcohol: Mechanisms and Treatment 012813125X, 9780128131251

Table of contents :
Cover
Neuroscience of Alcohol: Mechanisms and Treatment
Copyright
List of Contributors
Preface
The Neuroscience of Alcohol: Mechanisms and Treatments
Editorial Advisors
Part I: Introductory Chapters
1 Becoming a “Successful” Drinker and a Graduate: A Sociological Perspective on Alcohol Consumption by University Students
Introduction
University as a Space–Time of Becoming
Connected Consumption: The Nexus Between Tertiary Education and Alcohol
Investigating Drinking Among University Students
University: A Time and Place to Consume Alcohol
How Space Shapes Students’ Drinking Practices
University-Based Drinking
“Becoming” a “Successful” Drinker
Developing Skills to Reduce Harm and Maximize Pleasure While Drinking
“Successful” Drinking and the University Lifestyle
Drinking: Escaping Responsibilities and Pressure
Securing the Future Through Completing a Degree
Conclusion
Mini-Dictionary of Terms
Key Facts of Sociology
Summary Points
References
2 Molecular Genetics Meets Sociology: Birth Cohort Effects on Alcohol Use and Relationship With Candidate Genes
List of Abbreviations
Alcohol Issues: How to Reconcile Heritability and Secular Fluctuations
The Original Demonstration of Genotype × Birth Cohort Interaction
Further Genotype × Birth Cohort Interactions With Candidate Genes for Social Behavior
Birth Cohorts May Live in Distinct Environments as the Society Undergoes Change
Mechanisms Behind the Genotype × Birth Cohort Interactions
Mini-Dictionary of Terms
Key Facts
Candidate Gene Studies
Oxytocin
Summary Points
Acknowledgments
References
3 Alcohol and Women: Unique Risks, Effects, and Implications for Clinical Practice
Introduction
Pathways to Alcohol Use Disorder Among Women
Morbidity, Comorbidity, and Mortality Related to Alcohol Use Disorder in Women
How Does Alcohol Affect Women Differently From Men?
Explaining Sex Differences in Neurocognitive Effects of Alcohol
Research Limitations
Improving Prevention for Girls and Women
Early Diagnosis and Treatment Tailored to Girls and Women
Barriers to Treatment for Women
Needed Cultural, Environmental, and Societal Changes
Implications for Treatment: What Is Needed to Reduce Alcohol Misuse and Addiction in Girls and Women
Mini-Dictionary of Terms
Key Facts
How Alcohol Affects Women
Summary Points
References
4 ADH and ALDH Polymorphisms in Alcoholism and Alcohol Misuse/Dependence
List of Abbreviations
Introduction
Alcohol Metabolism
Oxidative Pathway
Nonoxidative Pathways
Alcohol Dehydrogenase and Aldehyde Dehydrogenase Polymorphism
Alcohol Dehydrogenase Polymorphism
Aldehyde Dehydrogenase Polymorphism
Summary
Implication for Treatment
Mini-Dictionary of Terms
Key Facts
About Alcoholism, Alcohol Abuse, and Dependence
Summary Points
References
5 Acetaldehyde in the Brain After Ethanol Exposure: Research Progress and Challenges
List of Abbreviations
Conversion of Ethanol to Acetaldehyde
Challenges in Acetaldehyde Research
Brain Acetaldehyde in Ethanol Neurotoxicity
Acetaldehyde Adducts in the Brain
Concluding Remarks
Mini-Dictionary of Terms
Key Facts
About Acetaldehyde
Summary Points
References
6 Consequences of Ethanol Exposure on Neurodevelopment
List of Abbreviations
Introduction
Alcohol and Brain Neurodevelopment
Overview of Neurodevelopmental Events
Neurodevelopmental Alterations Induced by Alcohol
Behavioral Outcomes and Mechanisms Associated With Prenatal Alcohol Exposure
Age-Related Consequences of Prenatal Alcohol Exposure
Conclusions and Future Perspectives
Mini-Dictionary of Terms
Key Facts
Neuroplasticity
Oxidative Stress
Intellectual Disabilities
Depression
Autism
Serotonin Type 1A Receptors
Phenotype
Summary Points
References
7 Animal Models of Binge Drinking: Behavior and Clinical Relevance
List of Abbreviations
Definition and Diagnostic of Binge Drinking in Humans
Relevant Clinical Criteria for Developing Animal Models of Binge Drinking
Current Preclinical Models of Binge Drinking
Forced Administration of High Doses of Alcohol
Gavage
Intraperitoneal Injections
Inhalation of Alcohol Vapors
Forced Drinking
Voluntary Alcohol Consumption
20% Alcohol Intake in the Two-Bottle Choice Intermittent Access Model
Two-Bottle Choice Drinking-in-the-Dark Model
Two-Bottle Choice Drinking in the Dark for Rats
Operant Binge Drinking
Conclusions and Need for Future Research
Mini-Dictionary of Terms
Key Facts
Animal Models of Binge Drinking
Summary Points
Acknowledgments
References
Part II: Neurobiology
8 Prenatal Alcohol Exposure: Developmental Abnormalities in the Brain
List of Abbreviations
Introduction
Studies in Humans With Fetal Alcohol Spectrum Disorder
Structural Brain Imaging
Functional Brain Imaging
Diffusion Tensor Imaging
The Role of Animal Research in Our Understanding of Fetal Alcohol Spectrum Disorder
Prenatal Ethanol Exposure and Neuroanatomical Development: Alterations in Subcortical Structures
Prenatal Ethanol Exposure and Neuroanatomical Development: Alterations in Neocortex
Prenatal Ethanol Exposure Impacts Thickness of the Neocortex
Neocortical Circuitry Development and Prenatal Ethanol Exposure: Gene Expression and Intraneocortical Connections
Potential Mechanisms of Prenatal Ethanol Exposure–Induced Neocortical Changes
Conclusion
Mini-Dictionary of Terms
Key Facts
Fetal Alcohol Spectrum Disorders Diagnosis
Epigenetics
Summary Points
References
9 Connecting Prenatal Alcohol, Its Metabolite Acetaldehyde, and the Fetal Brain
Introduction
Alcohol: From the Mother to the Fetus
Acetaldehyde in the Fetal Environment
Acetaldehyde in the Fetal Brain
The Role of Acetaldehyde in the Effects of Alcohol on Fetal Brain Development
Connecting the Behavioral Effects of Alcohol and Acetaldehyde in the Fetus
Reinforcing Effects of Alcohol and Acetaldehyde in the Fetus
Perinatal Learning With Alcohol and Acetaldehyde
Key Facts
About Alcohol and Acetaldehyde in the Fetus
Summary Points
References
10 Fetal Alcohol Exposure and the Central Nervous Control of Breathing
Introduction
Animal Models of Alcohol Exposure during Gestation/Brain Development
Methodology to Investigate Breathing Physiology
Short- and Long-Term Respiratory Plasticity: Response to Acute Chemosensory Challenges and Long-Term Facilitation of Breathing
Rhythmogenesis
Pharmacology of the Respiratory Network After Ethanol Exposure
Conclusion
Mini-Dictionary of Terms
Key Facts
Prenatal Ethanol Exposure and Breathing Function
Summary Points
References
11 Synaptic Plasticity in the Hippocampus and Alcohol Exposure During Brain Development
Introduction
The Hippocampus
Synaptic Plasticity in the Hippocampus
Alcohol and Synaptic Plasticity During Early Development
Alcohol and Synaptic Plasticity During Adolescence
Conclusion
Key Facts
Synaptic Plasticity in the Hippocampus and Alcohol Exposure During Brain Development
Summary Points
References
12 Ethanol and Cortical Spreading Depression: The Protective Role of α-Tocopherol
List of Abbreviations
Introduction: Alcoholism and Brain Injury
Alcohol and Brain Electrical Activity
Studies of Brain Effects of Alcohol Employing the Cortical Spreading Depression Model
The α-Tocopherol Protective Interaction With Ethanol on the Brain
Can the CSD Model Be Useful to the Study of Neural Effects of Other Drugs?
Mini-Dictionary of Terms
Key Facts
Brain Electrophysiology
Summary Points
Acknowledgments
References
13 Brain Electrophysiological Signatures in Human Alcoholism and Risk
List of Abbreviations
Introduction
Electroencephalogram Findings
Power Spectral Analysis
Coherence
Event-Related Potential Findings
Sensory Pathway (Evoked) Potentials
Sensory and Perceptual Potentials (P1)
Selective Attention (N1)
Mismatch Negativity
Error-Related Negativity
Attentional Orientation and Conflict Monitoring (N2)
Cognitive Evaluation and Processing (P3/P300)
Language Processing (N4/N400)
Event-Related Oscillation Findings
Delta and Theta Band Event-Related Oscillation Activity
Gamma Band Event-Related Oscillation Activity
Alpha and Beta Band Event-Related Oscillation Activity
Event-Related Oscillation Connectivity
Use of Electrophysiological Measures in the Treatment of Alcoholism
Electrophysiological Measures as Endophenotypes for Alcoholism
Summary and Future Directions
Mini-Dictionary OF Terms
Key Facts
Summary Points
References
14 Alcohol and Hippocampal Epileptiform Activity
List of Abbreviations
Introduction
Alcohol Effects on Synaptic Mechanisms of Epileptiform Activity
Acute Alcohol Abuse
Chronic Alcohol Abuse
Alcohol Withdrawal Syndrome
Alcohol Effects on Nonsynaptic Mechanisms of Epileptiform Activity
Acute Alcohol Abuse
Chronic Alcohol Abuse
Binge Drinking
Mini-Dictionary of Terms
Key Facts
Alcohol Abuse on Epilepsy
Synaptic Effects of Alcohol Abuse on Epilepsy
Nonsynaptic Effects of Alcohol Abuse on Epilepsy
Summary Points
Acknowledgments
References
15 Effects of Alcohol on the Corpus Callosum
List of Abbreviations
Introduction
Corpus Callosum: Pathology
Pathogenesis
Ethanol and Oxidative Damage
Cerebral Ethanol Metabolism and Reactive Oxygen Species Generation
Activation of Toll-Like Receptors
The Gut–Brain Axis
Free Iron Accumulation
MicroRNA-Associated Oxidative Stress
Toxic Lipids: The Liver–Brain Axis
Mini-Dictionary of Terms
Summary Points
Key Facts
Brain and Corpus Callosum Structure and Function
Effects of Ethanol on Corpus Callosum
Conclusion
References
16 The Role of the Lateral Habenula Circuitries in Alcohol Use Disorders
List of Abbreviations
Introduction
Neurobiology of Alcohol Addiction
The Lateral Habenula Circuits
Alcohol Modulates Glutamatergic and GABAergic Neurotransmissions in Habenulomesencephalic Circuit
Lateral Habenula Hyperactivity and Aversive Effects of Alcohol
Conclusion
Mini-Dictionary of Terms
Key Facts
About the Role of Lateral Habenula Circuits in Alcohol Use Disorder
Summary Points
References
17 Ventral Pallidum and Alcohol Addiction
List of Abbreviations
Introduction
Ventral Pallidum: Anatomy, Pharmacology, and Physiology
Ventral Pallidum and Alcohol Consumption
Ventral Pallidum and Relapse
Ventral Pallidum and Targeted Treatments for Alcohol Addiction
Conclusions
Mini-Dictionary of Terms
Key Facts
Ventral Pallidum
Summary Points
References
18 The Hyperpolarization-Activated Cyclic Nucleotide-Gated Ion Channels in the Rewarding Effects of Ethanol
List of Abbreviations
Introduction
The Hyperpolarization-Activated Cyclic Nucleotide-Gated Ionic Channels
Hyperpolarization-Activated Cyclic Nucleotide-Gated Ion Channels and Ethanol Actions
Hyperpolarization-Activated Cyclic Nucleotide-Gated Ion Channels and Cardiac Function
Hyperpolarization-Activated Cyclic Nucleotide-Gated Ion Channels as a Drug Target
Mini-Dictionary of Terms
Key Facts
Summary Points
References
19 Neuroimmune Aspects of Alcoholism and Affective Comorbidity
List of Abbreviations
Introduction
Alcohol Drinking Activates the Neuroimmune System
Neuroimmune Consequence of Modest Drinking
Neuroimmune Response to Acute Intoxication
Chronic Heavy Drinking and Neuroimmune Function
Neuroimmune Involvement in Alcohol Addiction, Withdrawal, and Abstinence
Affective Consequences of Alcohol-Induced Central Nervous System Neuroimmune Activity
Conclusions and Future Directions
Mini-Dictionary of Terms
Key Facts
Neuroimmune Signaling
Summary Points
References
20 Social Drinking and Motor Inhibition: Evidences From FMRI Go/Nogo Tasks fMRI Studies on Alcohol Effect on Inhibition
List of Abbreviations
Introduction
The Go/No-Go Task
Differential Activations Related to Alcohol Consumption Patterns in College Students
Disrupted Neural Signature of RI as a Precursor or a Consequence of Alcohol Use?
Conclusions
Mini-Dictionary of Terms
Key Facts
Heavy/Hazardous/Binge Drinking
Summary Points
References
21 Myelopathy and Neuropathy Associated With Alcoholism
List of Abbreviation
Introduction
Myelopathy
Pathogenesis
Clinical Features
Diagnosis
Treatment and Prognosis
Neuropathy
Pathogenesis
Clinical Features
Diagnosis
Treatment and Prognosis
Mini-Dictionary of Terms
Key Facts
Regarding Myelopathy and Neuropathy in Alcoholics
Summary Points
References
22 Alcohol Consumption and the Risk of Amyotrophic Lateral Sclerosis
List of Abbreviations
Introduction
Amyotrophic Lateral Sclerosis: An Overview
The Association Between Alcohol and Amyotrophic Lateral Sclerosis
Why Results Are so Conflicting and Heterogeneous?
Conclusions
Mini-Dictionary of Terms
Key Facts
Amyotrophic Lateral Sclerosis
Summary Points
References
23 Alcohol and Pain Interactions
List of Abbreviations
Introduction
Pain
Pain Signaling
Clinical Evaluation of Pain
Alcohol and Pain
Effects of Ethanol on Acute Pain
Effects of Chronic Ethanol on Pain
Treatment Options
Mini-Dictionary of Terms
Key Facts
Ethanol and Pain
Summary Points
References
24 Neurobiological Aspects of Ethanol-Derived Salsolinol
List of Abbreviations
Introduction
The Origin of SALS and Its Basal Concentrations in the Body Fluids and in the Brain
The Role of SALS in the Neurobiological Basis of Alcoholism
The Role of SALS in the Emergence of Neurological Disorders
Mini-Dictionary of Terms
Key Facts
Role of Ethanol Metabolism
Role of Stereo-Selectivity in the Effects of Salsolinol
Neurotoxicity of Salsolinol By-products
Summary Points
References
25 Brain Networks in Active Alcoholism and Enduring Recovery: Functional Magnetic Resonance Imaging, Electrophysiological S...
List of Abbreviations
Brain Networks in Active Alcoholism
Compensatory Mechanisms of Resting State Brain Network Synchrony in Long-Term Abstinent Alcoholics
Compensatory Mechanisms of Resting State Synchrony in Short-Term Abstinent Alcoholics
Differences in Resting State Synchrony Between Long-Term Abstinent Alcoholics With Versus Without Comorbid Drug Dependence
Degree of Resting State Synchrony During Early Alcohol Abstinence Predicts Subsequent Relapse
Longitudinal Study of Network RSS in STAA
LTAA With a Current Major Depressive Disorder
Resting State Synchrony in LTAA With Versus Without a Current Major Depressive Disorder
P3b Amplitude in LTAA With Versus Without a Current Major Depressive Disorder
Parallel ICA Identifies EEG Coherence Correlates of rs-fMRI Synchrony
Implications for Treatment
Conclusion
Mini-Dictionary of Terms
Key Facts
Executive Control Networks
Appetitive Drive Networks
Summary Points
References
26 Central Role of Amygdala and Hypothalamus Neural Circuits in Alcohol Withdrawal Symptom
List of Abbreviations
Introduction
Alcohol Withdrawal as a Hallmark of Physiological Dependence
Amygdala and Alcohol Withdrawal
Hypothalamus and Alcohol Withdrawal
Other Brain Regions Implicated in Alcohol Withdrawal
Mini-Dictionary of Terms
Key Facts
Summary Points
References
Part III: Psychology, Behavior, and Addiction
27 Neural Reward Processing in Human Alcoholism and Risk: A Focus on Event-Related Potentials, Oscillations, and Neuroimaging
List of Abbreviations
Introduction
Reward Circuitry
Electrophysiological Findings
ERP Findings in Alcoholism
Error-Related Paradigm
Outcome-Related Paradigm
Alcohol Cue Reactivity Paradigm
ERO Findings During Reward Processing in Alcoholism
Neuroimaging Findings
Structural Findings on Reward System in Alcoholism
Reward Related Functional MRI Findings in Alcoholism
Functional Connectivity Findings on the Reward System in Alcoholism
Resting State Functional Connectivity
Task Related Functional Connectivity
Issues and Future Directions
Mini-Dictionary of Terms
Key Facts
Summary Points
References
28 Occipito-Temporal Sensitivity and Emotional Faces in Alcohol Use Disorder
List of Abbreviations
Introduction
AUD and Emotion
Emotional Facial Expressions
Neural Correlates of EFE Identification
Brain Model of Core and Extended Regions of EFE Processing
Implications of EFE Processing Deficits
Functional Connectivity Between Core and Extended EFE Network Regions
Alcohol-Related Cues and EFE Recognition
Considerations for Future Research of AUD and EFE Processing
Conclusion
Mini-Dictionary of Terms
Key Facts
Emotional Facial Perception and Recognition
Summary Points
Acknowledgment
References
29 Alcohol and Violence in Psychopathy and Antisocial Personality Disorder: Neural Mechanisms
List of Abbreviations
Introduction
Neurobiological Mechanisms
Neurochemistry
Serotonin
Dopamine
Monoamine Oxidase-A
Neuroelectrophysiology
Structural Brain Changes
Mini-Dictionary of Terms
Key Facts
Monoamine Oxidase-A
Summary Points
References
30 Language Lateralization in Fetal Alcohol Spectrum Disorders
List of Abbreviations
Language Lateralization in Fetal Alcohol Spectrum Disorders
Fetal Alcohol Spectrum Disorder
Structural Lateralization in Fetal Alcohol Spectrum Disorders
Functional Lateralization in Fetal Alcohol Spectrum Disorders
Conclusions
Mini-Dictionary of Terms
Key Facts
Developmental Problems in Fetal Alcohol Spectrum Disorders
Summary Points
References
31 Deprivation in Rewards and Alcohol Misuse
List of Abbreviations
Deprivation in Rewards and Alcohol Misuse
Measurement of Reward Deprivation/Substance-Free Reinforcement
Demand
Substance-Free Reinforcement
Alternative Reinforcement Among Teenagers and Adolescents
Alternative Reinforcement Among College Students and Emerging Adults
Relation Between Gender and Alternative Reinforcement
Relation Between Social Context and Alternative Reinforcement
Alternative Reinforcement Among Adults
Alternative Reinforcement as a Transdiagnostic Risk Factor for Comorbid Psychopathology
Treatment Targeting Reward Deprivation
Mini-Dictionary of Terms
Key Facts
Reward Deprivation
Summary Points
References
32 Alcohol (Mis)Use in Individuals With Mild to Borderline Intellectual Disability
List of Abbreviations
Introduction
Prevalence
Prevalence of Alcohol (Mis)use and Alcohol Use Disorder
Screening and Assessment
The Neuropsychological Underpinnings of Alcohol Use Disorder
Dual Process Models of Addiction
Deficiencies in Information Processing in Problematic Drinkers With Mild to Borderline Intellectual Disability
Conclusion and Implications for Practice
Mini-Dictionary of Terms
Key Facts
Intellectual Disabilities
Summary Points
References
33 Sex, Stress, and Neuropeptides Interact to Influence Alcohol Consumption
List of Abbreviations
Introduction
Corticotropin-Releasing Hormone
Role of Corticotropin-Releasing Hormone in Alcohol Consumption and Adaptations
β-Endorphin’s Role in Alcohol Consumption
β-E, Corticotropin-Releasing Hormone, and Sex Interact to Regulate Drinking to Cope
Conclusions
Mini-Dictionary of Terms
Key Facts
Sex Differences in Alcohol Consumption
Summary Points
Implications for Treatments
References
34 Maternal Separation Stress in Fetal Alcohol Spectrum Disorders: A Case of Double Whammy
List of Abbreviations
Neurodevelopment Is a Long-Lasting Continuum Modulated by Environment
Fetal Alcohol Spectrum Disorders
Revealing Fetal Alcohol Spectrum Disorder Etiology via an Animal Model
Children With Fetal Alcohol Spectrum Disorder Face Additional Postnatal Challenges
Modeling Maternal Separation in Rodents
Implications for Treatments
Conclusion
Mini-Dictionary of Terms
Key Facts
Fetal Alcohol Spectrum Disorder
Summary Points
References
35 Impulsivity and Binge Drinking: A Neurocognitive Perspective
List of Abbreviations
Binge Drinking as a Harmful Alcohol-Consumption Pattern
A Multilevel Conceptualization of Impulsivity in Binge Drinking
One Step Beyond: Framing Future Research on Impulsivity in Binge Drinking
Mini-Dictionary of Terms
Key Facts
Cognitive Impairments in Binge Drinking
Summary Points
Acknowledgments
References
36 Acetaldehyde and Motivation
List of Abbreviations
Introduction
Acetaldehyde Has Its Own Motivational Properties
Acetaldehyde Induces an Addictive Phenotype
Endocannabinoids and Neuropeptide Y
Acetaldehyde Mediates Alcohol Motivational Properties
Conclusions
Mini-Dictionary OF Terms
Key Facts
Acetaldehyde
Summary Points
References
37 Age-Related Differences in the Appetitive and Aversive Motivational Effects of Alcohol
List of Abbreviations
Introduction
What Are the Motivational Effects of Alcohol, and How Do We Measure Them?
Do the Motivational Effects of Alcohol Change Across the Life Span?
Alcohol-Induced Taste Aversion
Alcohol-Induced Place Conditioning
Concluding Comments
Mini-Dictionary of Terms
Key Facts
Animal Models of Alcohol Use Disorders
Summary Points
References
38 Alcoholism in Bipolar Disorders: An Overview of Epidemiology, Common Pathogenetic Pathways, Course of Disease, and Impli...
List of Abbreviations
Introduction
Epidemiology
Common Pathogenetic Pathways
Genetic Factors
Neurophysiological Correlates
Psychopathological Correlates
Clinical Features, Course and Prognosis
Treatment Implications
Mini-Dictionary of Terms
Key Facts
Bipolar Disorders
Summary Points
References
39 Socio-Emotional Deficits in Severe Alcohol Use Disorders
List of Abbreviations
The Importance of Socio-Emotional Factors in Severe Alcohol Use Disorders
A Typological Review of Social Cognition in Patients with AUD
Towards a Deeper Understanding of Social Cognition in Patients with AUD
Mini-Dictionary of Terms
Key Facts
Social Cognition in Alcohol Use Disorders
Summary Points
Acknowledgments
References
40 Relapse Risks in Patients With Alcohol Use Disorders
List of Abbreviations
Introduction
Relapse as It Applies to AUD
Recovery From AUD
Biopsychosocial Model
Stages of Behavioral Change Model
Risk Of Psychological Relapse
Craving
Coping Skills
Self-Efficacy
Spirituality
Sociological (Environmental) Relapse Risks
Interpersonal Relationships
Family
Resilience for Recovery
Recovery Support to Increase Resilience
Resilience Associated With Self-Disclosure and Relapse Risks in Patients With AUD
Innate/Acquired Resilience Have a Mutually Reinforcing Relationship
Implications for Treatments
Mini-Dictionary of Terms
Key Facts
Relapse Risks in Patients with AUD
Summary Points
Acknowledgment
References
41 The Neurocognitive Effects of Alcohol Hangover: Patterns of Impairment/Nonimpairment Within the Neurocognitive Domains o...
List of Abbreviations
Introduction
What Is a Hangover?
Measuring Hangover
Organizing Research on Neurocognitive Performance During Hangover
Neurocognitive Performance During Hangover
Mini-Dictionary of Terms
Key Facts
Hangover
Blood Alcohol Concentration
Summary Points
References
Part IV: Pharmacology, Neuroactives, Molecular, and Cellular Biology
42 Neuroactive Steroids and Ethanol Exposure: Relevance to Ethanol Sensitivity and Alcohol Use Disorders Risk
List of Abbreviations
Introduction
Alcohol Affects Neuroactive Steroid Concentrations
Acute Alcohol Effects
Chronic Alcohol Effects
Neuroactive Steroids Mediate Specific Behavioral Effects of Ethanol
Neuroactive Steroids Influence Drinking Behavior in Rodents
Individual Variation in Neuroactive Steroids Contributes to Ethanol Intake in Rodents and Monkeys
Individual Variation in Neuroactive Steroids May Contribute to Alcohol Use Disorder in Humans
Conclusions
Mini-Dictionary of Terms
Key Facts
Neuroactive Steroids
Summary Points
References
43 Alcohol’s Effects on Extracellular Striatal Dopamine
List of Abbreviations
Overview of Striatal Anatomy and Function
Dopamine in the Striatum
Reward Prediction Error
Incentive Salience
Techniques for Measuring Extracellular Striatal Dopamine in Animals
Ethanol’s Acute Pharmacological Effects on Extracellular Striatal Dopamine
Effects of Alcohol Self-Administration on Extracellular Striatal Dopamine
Clinical Studies of Alcohol’s Effects on Extracellular Striatal Dopamine
Mini-Dictionary of Terms
Key Facts
Phasic Versus Tonic Dopamine Signals
Summary Points
References
44 Nicotinic Cholinergic Mechanisms in Alcohol Abuse and Dependence
List of Abbreviations
Introduction
Cholinergic Nicotinic Mechanisms in Alcohol Dependence
Nicotinic Acetylcholine Mechanisms in Alcohol Dependence With Comorbid Addictive and/or Psychiatric Disorders
Conclusions
Mini-Dictionary of Terms
Key Facts
Summary Points
Conflict of Interest
Acknowledgments
References
45 Opioid System and Alcohol Consumption
List of Abbreviations
Introduction
The Role of Endogenous Opioids and Their Receptors in Brain Reward Processes
Effects of Acute and Chronic Alcohol Intake on Opioid Peptides and Receptors
Deficiency of β-Endorphins and Alcohol Consumption
Opioid Antagonists and Alcohol Consumption
Conclusions
Mini-Dictionary of Terms
Key Facts
Summary Points
References
46 The Enkephalinergic System and Ethanol Effects
List of Abbreviations
Introduction
Ethanol and Opioid Effects on Dopaminergic Transmission: Role in Reinforcement
Acute and Chronic Ethanol Effects on Enkephalinergic Transmission
Prenatal Ethanol Effects on Enkephalinergic Transmission
Implications for Treatments
Conclusions
Mini-Dictionary of Terms
Key Facts
Alcoholism
Summary Points
References
47 Alcohol and Central Glutamate Activity: What Goes Up Must Come Down?
List of Abbreviations
Introduction
Glutamate
Metabotropic Glutamate Receptors (mGluRs)
Group I mGluRs
Group II mGluRs
Group III mGluRs
Effects of Ethanol on mGluRs
Ionotropic Glutamate Receptors
NMDARs
AMPARs
KARs
GRIDs
Effects of Ethanol on iGluRs
Glutamate-Associated Transporters
Vesicular Glutamate-Associated Transporters
Effects of Ethanol on Glutamate Transporters
The Mesocorticolimbic Reward System
Ethanol and the Mesocorticolimbic Reward System
Future Directions
Mini-Dictionary of Terms
Key Facts
Key Synaptic Components of the Glutamatergic System Include
Summary Points
Acknowledgements
References
48 Ethanol and Hippocampal Gene Expression: Linking in Ethanol Metabolism, Neurodegeneration, and Resistance to Oxidative S...
List of Abbreviations
Introduction
Metabolism of Ethanol in the Hippocampus
Chronic and Long-Term Effects of Ethanol in the Hippocampus
Acute Nontoxic Ethanol Intake, Hippocampal Gene Expression, and Antioxidant Potential
Mini-Dictionary of Terms
Key Facts
Summary Points
References
49 Stress, Alcohol, and Hippocampal Genes
List of Abbreviations
Introduction
Hippocampal Gene Expression Changes Following Exposure to Stress
Hippocampal Gene Expression Changes Following Exposure to Ethanol
Hippocampal Gene Expression Changes Following Exposure to the Combination of Stress and Ethanol
Conclusions
Mini-Dictionary of Terms
Summary Points
References
50 Genes and Alcoholism: Taste, Addiction, and Metabolism
List of Abbreviations
Introduction
Taste and Alcoholism
Alcohol Addiction
Influence of Alcoholism-Related Taste and Addiction Genes With Food Choice
Alcohol Metabolism Genes
Sociocultural Factors
Mini-Dictionary of Terms
Key Facts
Genetic Marks for Alcoholism
Summary Points
References
51 Ethanol Exposure During Development, and Brain Oxidative Stress
List of Abbreviations
Introduction
Ethanol Metabolism in the Fetal Brain
Mechanisms Underlying Fetal Brain Ethanol Toxicity
Effects of Ethanol Exposure During Development on ROS Production and Oxidative Stress
Use of Antioxidants as Therapeutic Strategies for FASD Treatment
Conclusions
Mini-Dictionary of Terms
Key Facts
FASD
Summary Points
References
52 Alcohol-Induced Oxidative Stress in the Brain: Suggested Mechanisms, Associated Disorders, and Therapeutic Strategies
List of Abbreviations
Introduction
Mechanisms of Ethanol-Induced Oxidative Stress
Brain Disorders Associated With Oxidative Stress
Therapeutic Approaches in Oxidative Stress-Related Brain Disorders
Mini-Dictionary of Terms
Key Facts
Oxidative Stress
Summary Points
References
53 Lead Exposure and Ethanol Intake: Oxidative Stress as a Converging Mechanism of Action
List of Abbreviations
Introduction
Oxidative Stress
Lead
Ethanol
Lead and Ethanol
Lead, Ethanol, and Oxidative Stress
Lead, Ethanol, Oxidative Stress, and Drug Consumption
Conclusion
Mini-Dictionary of Terms
Key Facts
Neurobehavioral Toxicology and Teratology
Summary Points
References
Part V: Alcohol and Other Addictions
54 Alcohol and Gambling Addiction
List of Abbreviations
Introduction
Alcoholism and Gambling Comorbidity, Epidemiological Data
Development Factors Related to Comorbidity Between Alcoholism and Gambling
Biological Factors Related to Alcoholism and Gambling Comorbidity
Personality Traits and Comorbidity of Alcoholism and Gambling Disorder
Impulsive and Compulsive Behavior
Emotion Regulation
Treatment Problems
Conclusion
Mini-Dictionary of Terms
Key Facts
Alcohol and Gambling Disorder
Summary Points
References
55 Neuroscience of Alcohol and Crack Cocaine Use: Metabolism, Effects and Symptomatology
List of Abbreviations
Introduction
Consumption
Alcohol and Crack Cocaine Mixture Metabolism
Cocaethylene and Its Neural System Actions
Final Considerations
Mini-Dictionary of Terms
Key Facts
Cocaethylene
Summary Points
References
56 The Impact of Ethanol Plus Caffeine Exposure on Cognitive, Emotional, and Motivational Effects Related to Social Functioning
List of Abbreviations
Caffeine as a Modulator of Ethanol Abuse Liability
The Neuromodulator Adenosine: Common Target for Ethanol and Caffeine
Social Interaction and Its Modulation by Anxiety: Impact of Caffeine–Ethanol Interaction
Social Recognition: Effect of Caffeine and Alcohol on Cognition and Memory
Conclusions and Future Directions
Mini-Dictionary of Terms
Key Facts
Caffeine Consumption
Summary Points
References
Part VI: Biomarkers and screening
57 Biomarkers of Alcohol Misuse
List of Abbreviations
Introduction
Ethanol
Indirect Biomarkers
Carbohydrate Deficient Transferrin
Gamma Glutamyltransferase
Aspartate Aminotransferase and Alanine Aminotransferase
Mean Corpuscular Volume
Direct Markers
Alternative Sampling Strategies of Interest in the Context of Follow-Up of Alcohol (Mis)use
Direct Alcohol Metabolites
Ethyl Glucuronide and Ethyl Sulfate
Phosphatidylethanol (PEth)
Fatty Acid Ethyl Esters
Implications for Patient Treatment and Follow-Up
Conclusion
Mini-Dictionary of Terms
Key Facts
Indirect Ethanol Biomarkers
Direct Ethanol Biomarkers
Summary Points
References
58 Phosphatidylethanol Homologs in Blood as Biomarkers for the Time Frame and Amount of Recent Alcohol Consumption
List of Abbreviations
Introduction
The Discovery of Phosphatidylethanol
Development of Phosphatidylethanol as an Alcohol Marker
Studies on the Synthesis and Elimination of Phosphatidylethanol After Controlled Alcohol Consumption
The Potential to use Different Phosphatidylethanol Homologs to Indicate Recentness of Alcohol Consumption
Summary and Conclusions
Mini-Dictionary of Terms
Key Facts
Phosphatidylethanol as a Direct Biomarker of Alcohol Consumption
Summary Points
Sources of Support
References
59 Metabolomics to Differentiate Alcohol Use Disorders From Social Drinkers and Alcohol-Naive Subjects
List of Abbreviations
Introduction
Alcohol Drinking and Its Detrimental Effects
Alcohol Dependence and Alcohol Use Disorder
Current Diagnostic Methods of Alcohol Use Disorder
AUD Questionnaires
Biomarkers
Metabolomics in Alcohol Use Disorders Diagnosis
Using 1H-NMR Spectroscopy in Metabolomics
Metabolomics to Investigate Alcohol Consumption in Humans
Urinary and Plasma Metabolomic Profiling to Discriminate Between Alcohol Use Disorders, Social Drinkers, and Alcohol-Naive ...
Mini-Dictionary of Terms
Key Facts
Metabolomics
Principal Component Analysis
Summary Points
References
60 Meconium Biomarkers of Prenatal Alcohol Exposure
List of Abbreviations
Introduction
Alcohol Use in Women During Pregnancy
Metabolism of Alcohol: Pregnancy, Embryo/Fetus, Neonate
Alcohol Consumption in Pregnancy and Biological Matrices
Alcohol-Related Analytes in Meconium
Fatty Acid Ethyl Esters
Ethyl Glucuronide and Ethyl Sulfate
Conclusion
Mini-Dictionary of Terms
Key Facts
About Prenatal Alcohol Use and Meconium
Summary Points
Acknowledgments
References
61 Applications of the Alcohol Use Disorders Identification Test (AUDIT) in Distinct Health Areas
Introduction
In What Context Are These Instruments Worked With? Are There Country-Related Differences?
Is the Proposed Structure of the AUDIT Valid?
What Are the Most Frequently Used Cut-Off Points?
Is It Possible to Improve the AUDIT by Changing Any Element?
Does the AUDIT Surpass Other Methods of Alcohol Consumption Screening?
Mini-Dictionary of Terms
Key Facts
Audit
Summary Points
References
62 Craving Measurement and Application of the Alcohol Craving Experience Questionnaire
List of Abbreviations
Definition of Craving
Craving Measurement
Definition and Theoretical Foundation
Temporal Reference
Psychometric Integrity
Administration Demand
Clinical Utility
Limitations and Practical Considerations
Conclusions
Mini-Dictionary of Terms
Key Facts
Craving
Alcohol Craving Experience questionnaire
Summary Points
References
Part VII: Treatments, strategies and resources
63 Negative Emotions and Alcohol Use Disorder Treatment
List of Abbreviations
Introduction
The Psychological Tension Reduction Hypothesis Model
The Psychiatric Comorbidity Model
The Neuroscientific Opponent Process Model
Concluding Remarks
Mini-Dictionary of Terms
Key Facts
Negative Emotions and Alcohol Use
Summary Points
References
64 Use of Baclofen in Alcohol Use Disorder: A Clinical Approach
List of Abbreviations
Introduction
Role of GABAB Receptors in Alcohol Use Disorder
Clinical Pharmacology of Baclofen
Clinical Efficacy of Baclofen in the Treatment of Alcohol Use Disorder
Safety Profile of Baclofen
Controversies in the Treatment of Alcohol Use Disorder With High Doses of Baclofen
Conclusions and Outlook
Mini-Dictionary of Terms
Key Facts
Alcohol-Induced Liver Disease (AILD)
Summary Points
References
65 Baclofen-Induced Neurotoxicity
List of Abbreviations
Introduction
Baclofen Prescription for Ethanol Abstinence
Baclofen Pharmacokinetics
Baclofen-Related Adverse Effects at Therapeutic Doses
Baclofen-Related Neurotoxicity in Overdose
Alterations in Baclofen Pharmacokinetics in Overdose
Management of the Baclofen-Poisoned Patient
Conclusions
Mini-Dictionary of Terms
Key Facts
GABAB Receptors
Summary Points
References
66 Treatment With Nalmefene in Alcoholism
List of Abbreviations
Introduction
Treatment Goals in Alcohol Dependence
Nalmefene for Reduction of Alcohol Consumption
Nalmefene-Licensed Population
Nalmefene Efficacy and Safety
Clinical Trials Design
Clinical Trials Results
Discussion
Conclusions
Mini-Dictionary of Terms
Key Facts
Unmet Medical Needs Supported by the Availability of Nalmefene
Summary Points
References
67 Dual Therapy for Alcohol Use Disorders: Combining Naltrexone With Other Medications
List of Abbreviations
Introduction
Naltrexone
Combinatorial Pharmacotherapeutics
Naltrexone+Prazosin
Naltrexone+Varenicline
Naltrexone+Fluoxetine
Naltrexone+Bupropion
Summary
Mini-Dictionary of Terms
Key Facts
AUD Treatment
Summary Points
References
68 The Avermectin Family as Potential Therapeutic Compounds for Alcohol Use Disorder: Implications for Using P2X4 Receptor ...
List of Abbreviations
Introduction
Overview of Purinergic P2X4 Receptors
Relationship Between P2X4Rs and Ethanol
In Vitro Evidence
In Vivo Evidence
Preclinical Investigations of Avermectins
Preclinical Ivermectin Study
Preclinical Moxidectin Study
Anti-alcohol Mechanism(s) of Avermectins
Implications for Treatments
Mini-Dictionary of Terms
Key Facts
The Burden of Alcohol Use Disorders
Summary Points
References
69 Alcohol Withdrawal Syndrome: Clinical Picture and Therapeutic Options
List of Abbreviations
Introduction
Alcohol Withdrawal: A Wide Range of Symptoms
Laboratory Parameters as Diagnostic Tools
Questionnaires: Tools to Grade Severity of Symptoms
Aspects to Bear in Mind Before Therapeutic Intervention
How to Treat
Benzodiazepines: Different Ways of Application
Beyond Benzodiazepines
Mini-Dictionary of Terms
Key Facts
Alcohol Withdrawal Syndrome
Summary Points
References
70 Resources for the Neuroscience of Alcohol
List of Abbreviations
Introduction
Summary Points
Acknowledgments
References
Index
Back Cover

Citation preview

NEUROSCIENCE OF ALCOHOL

NEUROSCIENCE OF ALCOHOL Mechanisms and Treatment

Edited by

VICTOR R. PREEDY Faculty of Life Science and Medicine, King’s College London, London, United Kingdom

Academic Press is an imprint of Elsevier 125 London Wall, London EC2Y 5AS, United Kingdom 525 B Street, Suite 1650, San Diego, CA 92101, United States 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom Copyright r 2019 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-813125-1 For Information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Nikki Levy Acquisition Editor: Joslyn Chaiprasert-Paguio Editorial Project Manager: Timothy Bennett Production Project Manager: Vijayaraj Purushothaman Cover Designer: Miles Hitchen Typeset by MPS Limited, Chennai, India

List of Contributors

Ricardo Abadie-Guedes Department of Physiology and Pharmacology, Federal University of Pernambuco, Recife, Brazil Paula Abate Laboratorio de Psicologı´a Experimental, Centro de Investigaciones Psicolo´gicas (CIPsi-CONICETUNC), Facultad de Psicologı´a, Universidad Nacional de Co´rdoba, Enfermera Gordillo esq. Enrique Barros, Ciudad Universitaria, Co´rdoba, Argentina Charles W. Abbott Interdepartmental Neuroscience Program, University of California, Riverside, CA, United States Elio Acquas Department of Life and Environmental Sciences, Centre of Excellence on Neurobiology of Addiction, University of Cagliari, Cagliari, Italy Samuel F. Acuff Department of Psychology, The University of Memphis, Memphis, TN, United States Bonnie Alberry Department of Biology, University of Western Ontario, London, ON, Canada Paula A. Albrecht Universidad Nacional de Co´rdoba, Facultad de Ciencias Quı´micas, Depto. de Farmacologı´a, Co´rdoba, Argentina; IFEC, CONICET, Haya de la Torre y Medina Allende, Ciudad Universitaria, Co´rdoba, Argentina Kiyoshi Ameno Department of Forensic Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan Jackie Andrade School of Psychology, Cognition Institute, Plymouth University, Plymouth, United Kingdom Asier Angulo-Alcalde Department of Basic Psychological Processes and Their Development, Faculty of Psychology, University of the Basque Country UPV/EHU, San Sebastian, Spain Justin J. Anker Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States Liana Asatryan Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, United States Dragan Babi´c Department of Psychiatry, University Hospital Mostar, Mostar, Bosnia and Herzegovina Jessica A. Baker Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States Alex Bekker Department of Anesthesiology, Pharmacology, Physiology, and Neuroscience, Rutgers, the State University of New Jersey, New Jersey Medical School, New Jersey, United States

Richard L. Bell Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States Susan E. Bergeson Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, United States Ranilson de Souza Bezerra Department of Biochemistry, Federal University of Pernambuco, Recife, Brazil Claudia D. Bianco Neuroscience Program, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil Joe¨l Billieux Addictive and Compulsive Behaviours Lab (ACB-Lab), Institute for Health and Behaviour, University of Luxembourg, Esch-sur-Alzette, Luxembourg Henry L. Blanton Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, United States Nadka Ivanova Boyadjieva Department of Pharmacology and Toxicology, Medical Faculty, Medical University, Sofia, Bulgaria Anna Brancato Department of Sciences for Health Promotion and Mother and Child Care “G. D’Alessandro” University of Palermo, Palermo, Italy Patricia S. Brocardo Neuroscience Program, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil; Department of Morphological Sciences, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil Salvatore Campanella Laboratory of Medical Psychology and Addictology, ULB Neuroscience Institute (UNI), Universite´ Libre de Bruxelles (ULB), Brussels, Belgium Liliana M. Cancela Universidad Nacional de Co´rdoba, Facultad de Ciencias Quı´micas, Depto. de Farmacologı´a, Co´rdoba, Argentina; IFEC, CONICET, Haya de la Torre y Medina Allende, Ciudad Universitaria, Co´rdoba, Argentina Carla Cannizzaro Department of Sciences for Health Promotion and Mother and Child Care “G. D’Alessandro” University of Palermo, Palermo, Italy Valerie Cardenas Neurobehavioral Research Inc., Kahului, HI, United States Vero´nica Casan˜as-Sa´nchez Departamento de Bioquı´mica, Microbiologı´a, Biologı´a Celular y Gene´tica & Instituto Universitario de Enfermedades Tropicales y Salud Pu´blica de Canarias, Facultad de Ciencias, Seccio´n Biologı´a, Universidad de La Laguna, Tenerife, Spain

xvii

xviii

LIST OF CONTRIBUTORS

Patricia A. Cesconetto Department of Biochemistry, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil Magali Chartier INSERM University, Paris, France

UMRS-1144,

Paris-Descartes

Lucie Chevillard INSERM UMRS-1144, Paris-Descartes University, Paris, France Adriano Chio` “Rita Levi Montalcini” Department of Neuroscience, University of Turin, Torino, Italy Doo-Sup Choi Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine, Rochester, MN, United States M. Gabriela Chotro Department of Basic Psychological Processes and Their Development, Faculty of Psychology, University of the Basque Country UPV/EHU, San Sebastian, Spain Jason M. Coates Centre for Youth Substance Abuse Research, The University of Queensland, Brisbane, Australia; School of Psychology, The University of Queensland, Brisbane, Australia Alessandra Concas Department of Life and Environment Sciences, Section of Neuroscience and Anthropology, University of Cagliari, Cagliari, Italy Jason P. Connor Centre for Youth Substance Abuse Research, The University of Queensland, Brisbane, Australia; Alcohol and Drug Assessment Unit, Department of Medicine, Princess Alexandra Hospital, Brisbane, Australia; School of Medicine, The University of Queensland, Brisbane, Australia Merce` Correa Department of Psychobiology, University Jaume I, Castello, Spain; Department of Psychology, University of Connecticut, Storrs, CT, United States Marı´a-Teresa Corte´s-Toma´s Department of Basic Psychology, University of Valencia, Valencia, Spain Victor Diego Cupertino Costa Laboratory of Experimental and Computational Neuroscience, Bioengineering Program, Biosystems Engineering Department-DEPEB, Federal University of Sa˜o Joa˜o del-Rei-MG, Brazil Daryl L. Davies Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, United States Antoˆnio-Carlos Guimara˜es de Almeida Laboratory of Experimental and Computational Neuroscience, Bioengineering Program, Biosystems Engineering Department-DEPEB, Federal University of Sa˜o Joa˜o delRei-MG, Brazil Arthur Guerra de Andrade Department of Psychiatry, Medical School, University of Sa˜o Paulo, Sa˜o Paulo, Brazil Antonio Gomes de Castro-Neto Study Group on Alcohol and other Drugs, Research Group on Biomedical Nanotechnology, Department of Pharmaceutical Sciences, Federal University of Pernambuco, Recife, Brazil Pollyanna Fausta Pimentel de Medeiros Study Group on Alcohol and other Drugs, Federal University of Pernambuco, Recife, Brazil

Rani De Troyer Laboratory University, Ghent, Belgium

of

Toxicology,

Ghent

Aurelie De Vos Laboratory University, Ghent, Belgium

of

Toxicology,

Ghent

Ashley A. Dennhardt Department of Psychology, The University of Memphis, Memphis, TN, United States Romina Deza-Ponzio Universidad Nacional de Co´rdoba, Facultad de Ciencias Quı´micas, Depto. de Farmacologı´a, Co´rdoba, Argentina; IFEC, CONICET, Haya de la Torre y Medina Allende, Ciudad Universitaria, Co´rdoba, Argentina Marco Di Nicola Institute of Psychiatry and Psychology, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Universita` Cattolica del Sacro Cuore, Rome, Italy Mario Dı´az Departamento de Biologı´a Animal, Edafologı´a y Geologı´a & Unidad Asociada de Investigacio´n ULLCSIC, “Fisiologı´a y Biofı´sica de la Membrana Celular en Patologı´as Neurodegenerativas y Tumorales”, Facultad de Ciencias, Seccio´n Biologı´a, Universidad de La Laguna, Tenerife, Spain Robert Didden Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands; Trajectum, Zwolle, The Netherlands Julian Dilley Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States Manuel Alves dos Santos Ju´nior Neuropsycho pharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Federal University of Ceara´, Fortelza, Brazil Donald M. Dougherty Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States; Department of Pharmacology, University of Texas Health Science Center, San Antonio, TX, United States Fabien D’Hondt University of Lille, CNRS, UMR 9193, SCALab - Sciences Cognitives et Sciences Affectives, Lille, France; CHU Lille, Clinique de Psychiatrie, CURE, Lille, France Fabrizio D’Ovidio “Rita Levi Montalcini” Department of Neuroscience, University of Turin, Torino, Italy Magı´ Farre´ Department of Clinical Pharmacology, Hospital Universitari Germans Trias i Pujol, Institut Germans Trias i Pujol IGTP, Universitat Auto`noma de Barcelona, Badalona, Spain Gerald F.X. Feeney Centre for Youth Substance Abuse Research, The University of Queensland, Brisbane, Australia; Alcohol and Drug Assessment Unit, Department of Medicine, Princess Alexandra Hospital, Brisbane, Australia George Fein Department of Medicine and Psychology, University of Hawaii, Honolulu, HI, United States; Neurobehavioral Research Inc., Kahului, HI, United States Vittoria Rachele Ferri Institute of Psychiatry and Psychology, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Universita` Cattolica del Sacro Cuore, Rome, Italy

LIST OF CONTRIBUTORS

Janice Froehlich Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States Mirari Gaztan˜aga Department of Basic Psychological Processes and Their Development, Faculty of Psychology, University of the Basque Country UPV/EHU, San Sebastian, Spain John Germov Faculty of Education and Arts, University of Newcastle, Callaghan, NSW, Australia Fabien Gierski Cognition Health Society Laboratory (C2SEA 6291), University of Reims Champagne-Ardenne, Reims, France

xix

Nathalie Hill-Kapturczak Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States Kelly J. Huffman Department of Psychology and Interdepartmental Neuroscience Program, University of California, Riverside, CA, United States Nhat Huynh Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, United States Baharudin Ibrahim School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia

Joana Gil-Mohapel Division of Medical Sciences, University of Victoria and Island Medical Program, Faculty of Medicine, University of British Columbia, Victoria, BC, Canada

Bruce Imbert Global Medicines Development, Indivior Inc., Richmond, VA, United States

Jose´-Antonio Gime´nez-Costa Department of Basic Psychology, University of Valencia, Valencia, Spain

Michael W. Jakowec Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States

Rueben Gonzales The University of Texas at Austin, Austin, TX, United States Emilio Gonzalez-Arnay Department of Anatomy and Pathology, University of La Laguna, Tenerife, Spain Emilio Gonza´lez-Reimers Internal Medicine Service, University Hospital of the Canary Islands, University of La Laguna, Tenerife, Spain Keshamalini Gopalsamy School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia Judith E. Grisel Department of Psychology, Neuroscience Program, Bucknell University, Lewisburg, PA, United States Rubem Carlos Arau´jo Guedes Department of Nutrition, Federal University of Pernambuco, Recife, Brazil Jose´e Guindon Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, United States Matthew J. Gullo Centre for Youth Substance Abuse Research, The University of Queensland, Brisbane, Australia; Alcohol and Drug Assessment Unit, Department of Medicine, Princess Alexandra Hospital, Brisbane, Australia Kristin M. Hamre Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States Jaanus Harro Division of Neuropsychopharmacology, Department of Psychology, Estonian Centre of Behavioural and Health Sciences, University of Tartu, Tartu, Estonia Julie Hepworth School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia; Mater Research Institute, The University of Queensland, Brisbane, QLD, Australia Karla Herna´ndez-Fonseca Departamento de Neuroquı´mica, Subdireccio´n de Investigaciones Clı´nicas, Instituto Nacional de Psiquiatrı´a Ramo´n de la Fuente, Ciudad de Me´xico Me´xico

Asuka Ito Department of Forensic Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan

Mostofa Jamal Department of Forensic Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan Luigi Janiri Institute of Psychiatry and Psychology, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Universita` Cattolica del Sacro Cuore, Rome, Italy Martin A. Javors Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States; Department of Pharmacology, University of Texas Health Science Center, San Antonio, TX, United States Je´roˆme Jeanblanc INSERM UMR1247, GRAP, CURS, University of Picardie Jules Verne, Amiens, France Sarah Jesse Department of Neurology, University of Ulm, Ulm, Germany Jorge Jua´rez Laboratory of Pharmacology and Behavior, Instituto de Neurociencias, CUCBA, Universidad de Guadalajara, Jalisco, Me´xico Chella Kamarajan Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, NY, United States Seungwoo Kang Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine, Rochester, MN, United States Dalibor Karlovi´c Department of Psychiatry, Catholic University of Croatia, University Hospital Centre Sestre Milosrdnice, Zagreb, Croatia Tara E. Karns-Wright Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States Victor Karpyak Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, MN, United States David J. Kavanagh Centre for Children’s Health Research, Institute of Health & Biomedical Innovation and School of Psychology & Counselling, Queensland University of Technology, Brisbane, Australia

xx

LIST OF CONTRIBUTORS

Sheraz Khoja Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, United States

Mara S. Mattalloni Universidad Nacional de Co´rdoba, Facultad de Ciencias Quı´micas, Depto. de Farmacologı´a, Co´rdoba, Argentina

Hiroshi Kinoshita Department of Forensic Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan

Pierre Maurage Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Universite´ catholique de Louvain, Louvain-laNeuve, Belgium

Haruki Koike Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan Nathan J. Kolla Forensic Psychiatrist, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Violence Prevention Neurobiological Research Unit, CAMH, Toronto, ON, Canada; Department of Psychiatry and Criminology, University of Toronto, Toronto, ON, Canada; Waypoint Centre for Mental Health Care, ON, Canada L. Darren Kruisselbrink Centre of Lifestyle Studies, School of Kinesiology, Acadia University, Wolfville, NS, Canada Matt G. Kushner Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States Se´verine Lannoy Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Universite´ catholique de Louvain, Louvain-laNeuve, Belgium

Jon May School of Psychology, Cognition Institute, Plymouth University, Plymouth, United Kingdom Gavan P. McNally School of Psychology, UNSW Sydney, Sydney, NSW, Australia Bruno Me´ garbane Department of Medical and Toxicological Critical Care, Lariboisie` re Hospital, INSERM UMR-S1144, Paris-Diderot University, Paris, France Milagros Me´ndez Departamento de Neuroquı´mica, Subdireccio´n de Investigaciones Clı´nicas, Instituto Nacional de Psiquiatrı´a Ramo´n de la Fuente, Ciudad de Me´xico Me´xico Lorenzo Moccia Institute of Psychiatry and Psychology, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Universita` Cattolica del Sacro Cuore, Rome, Italy

Philippe Larame´e Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada

Luz M. Molina-Martı´nez Laboratory of Pharmacology and Behavior, Instituto de Neurociencias, CUCBA, Universidad de Guadalajara, Jalisco, Me´xico

Rose Leontini School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia

Daniel J. Morgan Department of Anesthesiology, Penn State College of Medicine, Hershey, PA, United States

Annukka K. Lindell Department of Psychology and Counselling, School of Psychology and Public Health, La Trobe University, Bundoora, VIC, Australia Jo Lindsay School of Social Sciences, Faculty of Arts, Monash University, Clayton, VIC, Australia Laura Lo´pez-Cruz Department of Psychobiology, University Jaume I, Castello, Spain; Department of Psychology, University of Cambridge, Cambridge, United Kingdom Marisa Lopez-Cruzan Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States Lu Lu Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States Albert Ludolph Department of Neurology, University of Ulm, Ulm, Germany Danielle Macedo Department of Physiology and Pharmacology, Faculty of Medicine, Federal University of Ceara´, Fortaleza, Brazil Umberto Manera “Rita Levi Montalcini” Department of Neuroscience, University of Turin, Torino, Italy Marko Martinac Center for Mental Health, Mostar, Bosnia and Herzegovina Candelaria Martı´n-Gonza´lez Internal Medicine Service, University Hospital of the Canary Islands, University of La Laguna, Tenerife, Spain

A. Leslie Morrow Department of Psychiatry, Department of Pharmacology, Bowles Center for Alcohol Studies, University of North Carolina School of Medicine, Chapel Hill, NC, United States Robert Muga Department of Internal Medicine, Hospital Universitari Germans Trias i Pujol, Institut Germans Trias i Pujol IGTP, Universitat Auto`noma de Barcelona, Badalona, Spain Eva M. Mu¨ller-Oehring Neuroscience Program, Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, United States; Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States James G. Murphy Department of Psychology, The University of Memphis, Memphis, TN, United States Mickael Naassila INSERM UMR1247, GRAP, CURS, University of Picardie Jules Verne, Amiens, France Todd B. Nentwig Department of Psychology, Neuroscience Program, Bucknell University, Lewisburg, PA, United States Sudan P. Neupane Norwegian National Advisory Unit on Concurrent Substance Abuse and Mental Health Disorders, Innlandet Hospital Trust, Brumunddal, Norway; Norwegian Centre for Addiction Research (SERAF), University of Oslo, Oslo, Norway; Bowles Center for Alcohol Studies, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

LIST OF CONTRIBUTORS

Emily Nicholson Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States Isabella Panaccione Department of Neurosciences, Mental Health and Sensory Organs, Sant’Andrea Hospital, Sapienza University of Rome, Rome, Italy Arturo Panduro Department of Molecular Biology in Medicine, Civil Hospital of Guadalajara “Fray Antonio Alcalde”, Guadalajara, Mexico; Health Sciences Center, University of Guadalajara, Guadalajara, Jalisco, Mexico Esther Papaseit Department of Clinical Pharmacology, Hospital Universitari Germans Trias i Pujol, Institut Germans Trias i Pujol IGTP, Universitat Auto`noma de Barcelona, Badalona, Spain Ricardo Marcos Pautassi Instituto de Investigacio´n Me´dica M. y M. Ferreyra (INIMEC—CONICET-Universidad Nacional de Co´rdoba), Co´rdoba, Argentina; Facultad de Psicologı´a, Universidad Nacional de Co´rdoba, Co´rdoba, Argentina Alessandra T. Peana Department of Chemistry Pharmacy, University of Sassari, Sassari, Italy

and

xxi

Science and Medicine, King’s College London, London, United Kingdom Rossana Carla Rameh-de-Albuquerque Study Group on Alcohol and other Drugs, Federal University of Pernambuco, Recife, Brazil Omar Ramos-Lopez Department of Molecular Biology in Medicine, Civil Hospital of Guadalajara “Fray Antonio Alcalde”, Guadalajara, Mexico; Health Sciences Center, University of Guadalajara, Guadalajara, Jalisco, Mexico Linda Richter Director of Policy Research and Analysis, Center on Addiction, New York, NY, United States Ingrid Rivera-In˜iguez Department of Molecular Biology in Medicine, Civil Hospital of Guadalajara “Fray Antonio Alcalde”, Guadalajara, Mexico; Health Sciences Center, University of Guadalajara, Guadalajara, Jalisco, Mexico Mario Rivera-Meza Laboratory of Experimental Pharmacology, Department of Pharmacological and Toxicological Chemistry, Faculty of Chemical Sciences and Pharmacy, University of Chile, Santiago, Chile

Jose´ A. Pe´rez Departamento de Bioquı´mica, Microbiologı´a, Biologı´a Celular y Gene´tica & Instituto Universitario de Enfermedades Tropicales y Salud Pu´blica de Canarias, Facultad de Ciencias, Seccio´n Biologı´a, Universidad de La Laguna, Tenerife, Spain

John D. Roache Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States; Department of Pharmacology, University of Texas Health Science Center, San Antonio, TX, United States

O.

Pierrefiche UMR1247 INSERM GRAP, Group of Research on Alcohol and Pharmacodependencies, University Centre for Health Research, University of Picardy Jules Verne, Chemin du Thil, Amiens, France

Antoˆnio Ma´rcio Rodrigues Laboratory of Experimental and Computational Neuroscience, Bioengineering Program, Biosystems Engineering Department-DEPEB, Federal University of Sa˜o Joa˜o del-Rei-MG, Brazil

Patrizia Porcu Neuroscience Institute, National Research Council of Italy (CNR), Cittadella Universitaria, Cagliari, Italy

David J. Rohac Department of Psychology, University of California, Riverside, CA, United States

Simona Porru Department of Psychobiology, University Jaume I, Castello, Spain; Department of Life and Environmental Sciences, University of Cagliari, Cagliari, Italy Asheeta A. Prasad School of Psychology, UNSW Sydney, Sydney, NSW, Australia Victor R. Preedy Faculty of Life Science and Medicine, King’s College London, London, United Kingdom Geraldine Quintero-Platt Internal Medicine Service, University Hospital of the Canary Islands, University of La Laguna, Tenerife, Spain David Quinto-Alemany Departamento de Biologı´a Animal, Edafologı´a y Geologı´a, Facultad de Ciencias, Seccio´n Biologı´a, Universidad de La Laguna, Tenerife, Spain Shafiqur Rahman Department of Pharmaceutical Sciences, College of Pharmacy, South Dakota State University, Brookings, SD, United States Rajkumar Rajendram Department of Medicine, King Abdulaziz Medical City - Riyadh, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia; Diabetes and Nutritional Sciences Research Division, Faculty of Life

Benjamin Rolland UCBL, CRNL, INSERM U1028, CNRS UMR5292, Universite of Lyon, Lyon, France; UP-MOPHA Department, Le Vinatier Hospital Centre, University Service of Addictology of Lyon (SUAL), Bron, France Sonia Roman Department of Molecular Biology in Medicine, Civil Hospital of Guadalajara “Fray Antonio Alcalde”, Guadalajara, Mexico; Health Sciences Center, University of Guadalajara, Guadalajara, Jalisco, Mexico Lucı´a Romero-Acevedo Internal Medicine Service, University Hospital of the Canary Islands, University of La Laguna, Tenerife, Spain John D. Salamone Department of Psychology, University of Connecticut, Storrs, CT, United States Francisco Santolaria-Ferna´ndez Internal Medicine Service, University Hospital of the Canary Islands, University of La Laguna, Tenerife, Spain Luiz Eduardo Canton Santos Laboratory of Experimental and Computational Neuroscience, Bioengineering Program, Biosystems Engineering Department-DEPEB, Federal University of Sa˜o Joa˜o del-Rei-MG, Brazil

xxii

LIST OF CONTRIBUTORS

Arantza Sanvisens Department of Internal Medicine, Hospital Universitari Germans Trias i Pujol, Institut Germans Trias i Pujol IGTP, Universitat Auto`noma de Barcelona, Badalona, Spain Youssef Sari Department of Pharmacology and Experimental Therapeutics, University of Toledo, Frederic and Mary Wolfe Center, Toledo, OH, United States Simona Scheggi Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy Toni Schofield Discipline of Behavioural and Social Sciences in Health, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia Elisa Schro¨der Laboratory of Medical Psychology and Addictology, ULB Neuroscience Institute (UNI), Universite´ Libre de Bruxelles (ULB), Brussels, Belgium Tilman Schulte Neuroscience Program, Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, United States; Doctoral Program for Clinical Psychology, Palo Alto University, Palo Alto, CA, United States

Claire Tanner School of Biomedical Sciences, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia Roberta Uchoˆa Study Group on Alcohol and other Drugs, Department of Social Work, Federal University of Pernambuco, Recife, Brazil Mariliis Vaht Division of Neuropsychopharmacology, Department of Psychology, Estonian Centre of Behavioural and Health Sciences, University of Tartu, Tartu, Estonia Maria Lozanova Valcheva-Traykova Department of Medical Physics and Biophysics, Medical Faculty, Medical University, Sofia, Bulgaria Neomi van Duijvenbode Tactus, Deventer, The Netherlands; Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands; Nijmegen Institute for Scientist-Practitioners in Addiction, Radboud University Nijmegen, Nijmegen, The Netherlands Joanne E.L. VanDerNagel Tactus, Deventer, The Netherlands; Nijmegen Institute for Scientist-Practitioners in Addiction, Radboud University Nijmegen, Nijmegen, The Netherlands; Aveleijn, Borne, The Netherlands

Carla Alessandra Scorza Laboratory of Neuroscience, Department of Neurology and Neurosurgery, Federal University of Sa˜o Paulo, Sa˜o Paulo, Brazil

Miroslava Georgieva Varadinova Department of Pharmacology and Toxicology, Medical Faculty, Medical University, Sofia, Bulgaria

Fu´lvio Alexandre Scorza Laboratory of Experimental and Computational Neuroscience, Bioengineering Program, Biosystems Engineering Department-DEPEB, Federal University of Sa˜o Joa˜o del-Rei-MG, Brazil; Laboratory of Neuroscience, Department of Neurology and Neurosurgery, Federal University of Sa˜o Paulo, Sa˜o Paulo, Brazil

Germana Silva Vasconcelos Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Federal University of Ceara´, Fortelza, Brazil

Nimisha Shiwalkar Department of Anesthesiology, Pharmacology, Physiology, and Neuroscience, Rutgers, the State University of New Jersey, New Jersey Medical School, New Jersey, United States Shiva M. Singh Department of Biology, University of Western Ontario, London, ON, Canada Caren Na´dia Soares de Sousa Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Federal University of Ceara´, Fortelza, Brazil Christophe Stove Laboratory University, Ghent, Belgium

of

Toxicology,

Ghent

Saranya Sundaram Neuroscience Program, Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, United States; Doctoral Program for Clinical Psychology, Palo Alto University, Palo Alto, CA, United States Sian Supski School of Social Sciences, Faculty of Arts, Monash University, Clayton, VIC, Australia Ayaka Takakura Department of Forensic Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan Naoko Tanaka Department of Forensic Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan

Silvaˆnia Maria Mendes Vasconcelos Department of Physiology and Pharmacology, Faculty of Medicine, Federal University of Ceara´, Fortaleza, Brazil Meera Vaswani WHO Collaborative National Drug Dependence Treatment Center, All India Institute of Medical Sciences, New Delhi, India Ashley A. Vena States

University of Chicago, Chicago, IL, United

Miriam B. Virgolini Universidad Nacional de Co´rdoba, Facultad de Ciencias Quı´micas, Depto. de Farmacologı´a, Co´rdoba, Argentina; IFEC, CONICET, Haya de la Torre y Medina Allende, Ciudad Universitaria, Co´rdoba, Argentina Christine C. Wang Medical Student, University of Toronto, Toronto, ON, Canada Katheryn Wininger Neurobiology of Disease Program, Mayo Clinic College of Medicine, Rochester, MN, United States Ayako Yamashita Department of Nursing, Faculty of Human Health Sciences, Niimi College, Niimi, Japan Jiang-Hong Ye Department of Anesthesiology, Pharmacology, Physiology, and Neuroscience, Rutgers, the State University of New Jersey, New Jersey Medical School, New Jersey, United States Shin-ichi Yoshioka School of Health Science, Tottori University Faculty of Medicine, Yonago, Japan

LIST OF CONTRIBUTORS

xxiii

Ross McD. Young Alcohol and Drug Assessment Unit, Department of Medicine, Princess Alexandra Hospital, Brisbane, Australia; Faculty of Health, Queensland University of Technology, Brisbane, Australia

Paola Zuluaga Department of Internal Medicine, Hospital Universitari Germans Trias i Pujol, Institut Germans Trias i Pujol IGTP, Universitat Auto`noma de Barcelona, Badalona, Spain

Ali M. Yurasek Department of Health Education & Behavior, The University of Florida, Gainesville, FL, United States

Wanhong Zuo Department of Anesthesiology, Pharmacology, Physiology, and Neuroscience, Rutgers, the State University of New Jersey, New Jersey Medical School, New Jersey, United States

Ariane Zamoner Department of Biochemistry, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil

Preface

THE NEUROSCIENCE OF ALCOHOL: MECHANISMS AND TREATMENTS The use of alcohol is embodied within many cultures and there is evidence of its use thousands of years ago. Presently about 2 billion individuals consume alcohol in one form or another. Alcohol use is synonymous with ethanol consumption or “drinking” and is one of the world’s most common forms of addiction. However, the number of individuals who exceed governmental, institutional, or medical guidelines is of great concern. Globally there are over 3 million annual deaths associated with alcohol misuse. Alcohol alters a variety of neurological processes: from the molecular biology of the cell to memory. Used in excess, alcohol impacts adversely on the individual, family unit, and friendship communities. Moreover, there are other concerns because excessive alcohol ingestion can cause damage to virtually every organ system. These include the liver and gastrointestinal tract, musculoskeletal system, genitourinary system, and many other organs. It is, therefore, very important that those who misuse alcohol or are addicted to alcohol are diagnosed so that appropriate treatments can be initiated. In order to achieve this an understanding of the neuroscience of alcohol is necessary. However, the scientific material relating to alcohol, its misuse, and addictive properties is vast, complex, interlinked between different disciplines, and covered in a variety of sources. Finding the information in a single source leads to a greater understanding of the neuroscience of alcohol. This is addressed in The Neuroscience of Alcohol: Mechanisms, and Treatments. The book is divided into seven parts as follows:

3. Psychology, behavior, and addiction 4. Pharmacology, neuroactives, molecular, and cellular biology 5. Alcohol and other addictions 6. Biomarkers and screening 7. Treatments, strategies, and resources It has been difficult to ascribe particular chapters to sections as many chapters can be placed into two or more sections. Nevertheless, the navigation of the chapters is aided by the by the detailed index at the end of the book. The Neuroscience of Alcohol: Mechanisms, and Treatments transcends both the multiple disciplinary and intellectual divides as each chapter has: • A set of Key Facts • A Mini-Dictionary of Terms • A set of Summary Points The Neuroscience of Alcohol: Mechanisms, and Treatment is designed for research and teaching purposes. It is suitable for neurologists, health scientists, public-health workers, doctors, pharmacologists, and research scientists. The audience also includes federal, state, and local alcohol research, and services program directors. It may also be of interest to physicians leading efforts for treatment and prevention of alcohol use disorders. It is valuable as a personal reference book and also for academic libraries that cover the domains of either neurology, health sciences, or addictions. Contributions are from leading national and international experts including those from world-renowned institutions. It is suitable for undergraduates, postgraduates, lecturers, and academic professors.

1. Introductory chapters 2. Neurobiology

Victor R. Preedy King’s College London, London, England

xxv

Editorial Advisors

Dr. Vinood Patel. PhD, FRSC Reader, Department of Biomedical Sciences, University of Westminister, London, United Kingdom Dr. Rajkumar Rajendram AKC BSc (Hons) MBBS (Dist) EDIC FRCP (Edin) Consultant, Department of Internal Medicine, King Abdulaziz Medical City, Riyadh, Saudi Arabia Chairman, Medication Utilisation & Process Evaluation Subcommittee, Medication Safety Program, Ministry of the National Guard Health Affairs, King Abdulaziz Medical City, Riyadh, Saudi Arabia Department of Nutrition, Faculty of Life Sciences and Medicine, King’s College, London, United Kingdom

xxvii

C H A P T E R

1 Becoming a “Successful” Drinker and a Graduate: A Sociological Perspective on Alcohol Consumption by University Students Claire Tanner1, Jo Lindsay2, Rose Leontini3, Sian Supski2, Julie Hepworth4,5, Toni Schofield6 and John Germov7 1

School of Biomedical Sciences, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia 2School of Social Sciences, Faculty of Arts, Monash University, Clayton, VIC, Australia 3 School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia 4School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia 5Mater Research Institute, The University of Queensland, Brisbane, QLD, Australia 6 Discipline of Behavioural and Social Sciences in Health, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia 7Faculty of Education and Arts, University of Newcastle, Callaghan, NSW, Australia

INTRODUCTION

intertwined and in tension—the consumption of alcohol as a pleasurable aspect of the university lifestyle and the consumption of university education itself, culminating in the qualification. Drawing on qualitative interviews with students, we describe features of university students’ drinking. In so doing, we identify key dimensions of students’ alcohol use and their conceptualization of university as a unique space and time in one’s life course to drink. Students are known to engage in heavy drinking sessions largely tied to social activities with friends, on and off campus (Hepworth et al., 2016; Leontini et al., 2015; Supski, Lindsay, & Tanner, 2016). The “university lifestyle” is a commodity that can now be purchased and university education is presented and commonly understood as a space time for young people in transition from high school to postuniversity adulthood (Moss & Richter, 2010). We consider how students understand the university lifestyle as a space time for hedonism and the consumption of alcohol. Further, we argue that the consumption of alcohol currently embedded within the consumption

There has been significant investment and advancements in the neuroscience of alcohol. Research in this field has investigated the effects of alcohol on the brain, the role of genes in alcoholic dependence, models of different stages of the addiction cycle, and the development and testing in animal models of medications (Reilly, Noronha, & Warren, 2014). Some of this research has determined that environment plays a critical role in alcohol-seeking and consumption behaviors in animal models (McBride & Li, 1998; Spanagel, Noori, & Heilig, 2014). But there are significant limitations to what an animal study can tell us about the complex, highly variable, and contingent meanings and uses of alcohol for people in different social contexts. A sociological perspective offers critical insights into how social contexts and institutions shape alcohol use. This chapter contributes to a mature field in the sociological study of alcohol use. We consider the experience of undergraduate university students (“students”) as consumers of two key commodities that are

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00001-5

3

© 2019 Elsevier Inc. All rights reserved.

4

1. ALCOHOL CONSUMPTION BY UNIVERSITY STUDENTS

of tertiary education creates contradictions and tensions for some students as they try to simultaneously escape their future and create their futures, and become “successful” graduates through drinking and studying. For most students drinking is an expected element of the university lifestyle—a space time of “becoming,” where alcohol offers hedonism, pleasurable sociability and an escape from the responsibilities of the present and the future. Yet the purpose of undertaking university education is also to create one’s future, culminating with the achievement of a degree as a credential for professional future employment which excessive alcohol consumption can threaten.

UNIVERSITY AS A SPACE TIME OF BECOMING The framework we use to explore university drinking is shown in Fig. 1.1. The diagram illustrates the process of becoming while at university and the nexus with alcohol consumption. The concept of becoming has been frequently used in literature on youth to describe the diverse and messy transitions that characterize late modern life (Evans & Heinz, 1994; Hillman & Marks, 2002). We suggest that university provides a space time of becoming through consumption. For the students interviewed, the space time of university was characterized by a movement towards a future that was defined by its difference to the present. The anticipation of a future that could be constraining due to the expectation of participation in the paid labor market threw into relief the liberating possibilities of the present, as a unique space time in one’s life course in which to drink excessively. We posit that for students, this was a time of becoming that involved managing and resolving conflicting consumption practices associated with successfully obtaining a tertiary degree and consuming alcohol.

CONNECTED CONSUMPTION: THE NEXUS BETWEEN TERTIARY EDUCATION AND ALCOHOL Over the past two decades higher education has gradually moved toward a market-driven mode of delivery in countries such as the United Kingdom and Australia (Tomlinson, 2016). Public funding has declined and tuition fees paid by students have increased substantially, whereby universities have become increasingly commodified creating a strong consumerist ethos. Higher education has been described as a new “private good” in which students invest and work toward (Tomlinson, 2016). Yet, the university lifestyle for many students is also the experience of hedonism through heavy drinking. The suspension of everyday practices and pursuit of hedonism while drinking has been elaborated in the literature on youth dinking and the nighttime economy in particular (Griffin, Bengry-Howell, Hackley, & Szmigin, 2009; Szmigin et al., 2008). The inversion of normative practices and resistance to authority means that hedonism is confined to particular space time contexts and has been associated with liminality, with “in-between-ness” (Shields, 1991; Winchester, McGuirk, & Everett, 2005, pp. 60 61). In many ways university can be understood as a liminal space time for students—an “in-between-ness” bracketed off by school and dependence in the past and the responsibilities of the future (Banister & Piacentini, 2008). The role of alcohol in the life of university students can also be seen through the lens of hedonism. The consumption of alcohol that is embedded in the university lifestyle involves for students a suspension of the etiquettes of everyday life, liberation from the self-consciousness of sobriety and shared space-times of social celebration with other students. Importantly, not all university students engage in the hedonism that drinking offers as a part of the university lifestyle

School and dependence

Future adult responsibilities

University space/time • Becoming a graduate • Newly realized independence • University rituals of hedonism, friendship, and pleasure • Alchohol consumption

FIGURE 1.1 University as a space time of becoming and consuming alcohol. Illustrates university as a space time of transition from school to adult responsibilities and the role of alcohol. Unpublished.

I. INTRODUCTORY CHAPTERS

5

HOW SPACE SHAPES STUDENTS’ DRINKING PRACTICES

(Andersson, Sadgrove, & Valentine, 2012; HermanKinney & Kinney, 2013; Supski & Lindsay, 2016). While for those who do, there are limits placed on hedonistic time, not least the drive to achieve a degree as a credential for professional employment in the future.

INVESTIGATING DRINKING AMONG UNIVERSITY STUDENTS The data discussed in this chapter was collected as part of an Australian Research Council-funded Linkage project investigating students’ drinking patterns and harm minimization (Schofield et al., 2010). Our analysis is based on 50 qualitative interviews conducted in Melbourne and regional Victoria, Australia, across four university campuses. Participants were recruited via notices placed at campuses and email notifications sent to undergraduate students inviting them to participate. The study focused on undergraduate university students aged 18 24 (with a mean age of 20) as it is this age group that is most represented in students who drink heavily (Hepworth et al., 2016; Leontini et al., 2015). Interviews were conducted with a diverse sample of participants in order to garner insight into how differences in living situation, age, course type and level, socioeconomic background, geographic location, gender, and ethnicity shape drinking patterns and approaches to harm minimization. Demographic markers are included in Table 1.1 and after student quotes throughout (all names are pseudonyms).

UNIVERSITY: A TIME AND PLACE TO CONSUME ALCOHOL The centrality of drinking to university life was universally recognized by students (Table 1.2). The space time of university was perceived to be distinct from other space times, including high school, the family home, the paid labor market or, indeed, the future. As the quotes in Table 1.2 demonstrate, the default position for students across universities was to drink when and where possible. The theme of “opportunity” to drink emerged strongly in students’ explanations of patterns of drinking. Opportunities to drink were contingent on several factors (Fig. 1.2) including students’ commonly experiencing financial constraints. Almost all students were living on restricted budgets. In students’ descriptions, there was a common presentation of the choice to drink correlating with opportunity; if finances, time, and geographical space allowed, drinks would be consumed. For most students, making the most of one’s

TABLE 1.1 Participant Demographics Demographic descriptor

Number of participants

GENDER Female

34

Male

16

LOCATION OF UNIVERSITY CAMPUSES Regional

14

Capital city

36

HOUSING TYPE Family home

25

University residential college

11

Share house

14

UNIVERSITY DEGREE Bachelor of Arts

15

Bachelor of Arts/Law

2

Bachelor of Arts/Science

3

Bachelor of Science

10

Bachelor of Sports and Recreation

1

Bachelor of Business

4

Bachelor of Engineering

1

Bachelor of Medicine

5

Bachelor of Nursing

4

Honors (Arts)

4

PhD (Arts)

1

Total Number

N 5 50

Overview of key characteristics of study participants according to gender, location, housing and university degree. Unpublished.

space time by drinking involved choreographing nights out (Lindsay, 2009). For example, maximizing opportunities for predrinks, free drinks, and cheap drinks were common considerations shaping how, where, and what students drank.

HOW SPACE SHAPES STUDENTS’ DRINKING PRACTICES Students’ perceptions and exploitation of drinking opportunities were largely shaped by their place of residence, which presented a particular kind of space time transition. Living in a university residential college was associated with increased opportunities to drink more frequently and/or heavily, while living in shared housing or in the family home

I. INTRODUCTORY CHAPTERS

6

1. ALCOHOL CONSUMPTION BY UNIVERSITY STUDENTS

TABLE 1.2 University as a Time and Place to Drink Student characteristics

Quote

Cara, 20 years, 3rd year Arts, lives at College

Alcohol is huge in uni. Far too big [laughs]. So you come to uni and in a week there’s just like big party. You’re immediately introduced to this massive party culture.

Danielle, 21 years, 3rd year Arts, lives in the family home

If you’re out and you have the opportunity to drink and everyone else is drinking you just drink.

Andrew, 20 years, 2nd year Arts, lives at College

During the semester, [we drink] probably twice to three times a week [. . .] During the semester, at [one bar] especially, almost every night, we have formal dinners, which everyone has to be there, and they serve pretty much—yeah, they serve red and white wine. We see that as being free alcohol, so we’re pretty keen to have a couple. Then usually we go down to [another place] which is the pub [name], Wednesday nights, just because we’ve already had a bit of free alcohol, so it’s even cheaper to have a big night. It’s usually Wednesday nights.

Kayla, 23 years, 3rd year Arts/Science, lives in a share house

Alcohol is huge at university and it was a bit of a shock when I came here just how massive it is . . .so many activities are alcohol based, especially in O-Week . . . Even like the balls and stuff like that . . . it’s just huge and it’s kind of—well I come from a country town, it was big shock because people kind of buying alcohol instead of buying food so that they can go out.

Joshua, 18 years, 1st year Arts, lives in family home

The beer club is a just a bunch of uni students wanting an excuse to get smashed. The wine club is pretty much the same thing except they do that under the label of wine tastings.

James, 20 years, 1st year Arts, lives at College

Yeah, I think there’s definitely more drinking at uni than, say, school, but again, it’s a different age group. Yeah, I do think there is a little bit more drinking at uni than there would be elsewhere, but it’s mainly because you’ve just got that many people of the same age, of the same interests concentrated in one area. There’s juts more opportunities to do it. Yeah, and it’s the more people there are—and at university, there’s a lot of people—the more anonymous you feel you can be. University gives you a place where you can make a new identity for yourself, I suppose, do things that you wouldn’t have done before, so it is a different place.

FIGURE 1.2 Factors which contribute to an increase and decrease in university students’ alcohol consumption. – Drinking cultures in an university environment – Access to cheap or free drinks via university events or local venues promoting “uni” nights – Perceived safety of private housing versus public venues – Peer influence – Friends minimizing risk of harm on nights out

– Financial pressures – Family expectations, especially if living in family home – Lack of access to public transport, especially those living in regional or country areas – Study pressures – Paid work responsibilities – Accumulated experience of drinking with third-year students reporting less frequent binge drinking than first-years students

appeared to moderate consumption (Supski et al., 2016). Different styles of drinking also reflected the geographical location of students’ primary residence, with transport being a major impediment to—and perhaps a moderator of—heavy drinking among students living in outer suburbs of a city or regional areas. Work responsibilities also shaped drinking patterns. This was the case, for example, with Katherine, who lived in the family home with her parents and had a part-time job: I have a part-time job and things and that’s like—it often starts in the mornings. So I wouldn’t want to be feeling unwell for that (20 years, 2nd year Arts/Law, lives in family home)

Factors which limit alcohol use

Factors which increase alcohol use

Quotations from students that illustrate university as a time and place to drink. Unpublished.

There was also the suggestion of more subtle influences like parental expectation (e.g., to drink moderately or not at all while in their company) which shaped students’ drinking patterns. In contrast to the general presentation of parental expectations minimizing drinking, the university was perceived as providing ample and sanctioned spaces times to drink. This was due to the focus on alcohol at university occasions like balls, weekly events, orientation week rituals and activities and events organized by discipline-specific societies, such as barbecues, pub-crawls, and boat cruises. In addition, within residential colleges, there were also weekly dinners such as “high table” at

I. INTRODUCTORY CHAPTERS

“BECOMING” A “SUCCESSFUL” DRINKER

7

which alcohol was provided by residential colleges (Leontini et al., 2015).

university to drink also involved learning how to reduce the harms they experienced while drinking.

UNIVERSITY-BASED DRINKING

“BECOMING” A “SUCCESSFUL” DRINKER

University-based drinking rituals and routines were widely normalized as a key part of the university experience. However, for many students (see Kayla, Table 1.2) the extent, frequency, and form of drinking practices linked with university-based events, clubs, and programs came as some surprise, particularly in the first year of study. Students described different alcohol-related initiations and games: some with horror, others with disapproval, while others were defensive about the degree of coercion involved and emphasized their innocence and hilarity. One student described a residential college ritual in which “jaffies” (first-year students) were expected to drink heavily while being filmed, with the event later watched and cheered within the college on the basis of their level of inebriation. These collective space times for drinking existed alongside accounts of newly realized independence. In this way university life was perceived as a unique space time to develop individuality, in part, due to the anonymity afforded by being part of a larger community (of drinkers), see James, Table 1.2. Making the most of this “different” place was key and was implicitly connected to a perceived construction of university as a unique space time in one’s life course to drink excessively. Drinking was viewed as an integral part of the university “education” being purchased. For many students, the opportunities presented by

A common theme embedded in students’ accounts is the presentation of university as a real and imagined period of transition from high school student to adult/ graduate. Our findings, as illustrated by the quotes in Table 1.3, indicate that drinking is an integral part of this process that is shaped by students’ temporal and spatial transitions—although not necessarily in straightforward ways. We use the term “becoming” to capture the flexibility and future orientation of students’ accounts, particularly in their anticipation of certain types of futures, their constructions of the past, and, importantly, locations in the present (Worth, 2009). Most students drew on linear trajectories of development to describe their transitions at university. “Successful” drinking in their terms involved fitting in socially and reducing the negative consequences of heavy alcohol consumption. In the accounts outlined in Table 1.3, students privilege a development of selfknowledge through personal experience, which university fosters. Yet, in some cases, this was understood by students as also including learning to enjoy the taste of alcohol rather than just drinking to get drunk and to go out and have “fun” without having to drink. For some students learning first-hand from their own experiences drinking in public, or as witnesses to the regrettable experiences of others, was key to their “becoming” as described by Jenny. For most, however, their drinking-related learning was marked by the

TABLE 1.3 “Becoming” a “Successful” Drinker Student characteristics

Quote

Laura, 21 years, Arts Honors (4th year), lives in a share house

We don’t drink to excess as much as we used to. Like, sort of the first year, you wouldn’t come home and remember everything that happened, kind of thing. Now it’s more, you know—I don’t know, we probably, girls will probably drink about five or six or something like that.

Patrick, 19 years, 2nd year Sports/Rec, lives There have been times if I’m getting too drunk too early I like have a break and have some water at College and stuff. [Interviewer: So you’re looking after yourself more?]. . . Certainly a lot more than I was maybe a year ago, when I wasn’t as well-experienced at drinking and stuff. Danielle, 21 years, 3rd year Arts, lives in the family home

I went through a phase where it was all about going out, having some drinks and picking up. I grew out of that pretty quickly.

Jenny, 21 years, 3rd year Nursing, lives in a share house

Because everyone’s going to experience something they regret when they’re drinking and no one can stop except that person. So it may be just learning from whatever’s happened on the town with your mates. If you’ve seen it, if it’s happened to you.

Cara, 20 years, 3rd year Arts, lives at College

It seems to me when people hit about 21, 22 in their lives, sort of third year of uni, they realize that they’re over that stage and they’re just like, I just want to be able to go out and have fun rather than go out and not remember what happened. So you can definitely, in 3 or 4 years, see a definite change in people.

Quotations from students that illustrate how they understood themselves to have learnt to drink “successfully” while at university. Unpublished.

I. INTRODUCTORY CHAPTERS

8

1. ALCOHOL CONSUMPTION BY UNIVERSITY STUDENTS

expectation that their lives would change after university and by their own experiences, as described by Cara.

DEVELOPING SKILLS TO REDUCE HARM AND MAXIMIZE PLEASURE WHILE DRINKING Over the course of being at university, students’ learning about drinking involved understanding how much to drink, who to drink with, and where. All students spoke with confidence about their awareness of different space times and the impact on where they chose to drink more heavily. In general, students perceived safer spaces to be house parties and in colleges, as opposed to public spaces where strangers increased the potential risks of their own excesses. Consistent with studies on harm minimization and youth drinking more broadly, our participants described a range of strategies they used to reduce harm, including staying with close friends and/or groups of people that they could be confident would look after them, as well as planning transport, avoiding or diffusing fights, and consuming food and water while drinking (Grace, Moore, & Northcote, 2009; Hernandez, Leontini, & Harley, 2013). Students’ accounts reveal that drinking at university also taught them how to better pace their drinking, that is, to “know their limits.” What this actually meant for students did, however, differ: When we get a little bit lightheaded and we start to— maybe stumble and things like that. We generally stop after that. We don’t really completely black-out or anything. We just stop after that. (Lucy, 18 years, 1st year Science, lives in the family home) I guess if you’re spewing on the corner of the road that’s a pretty good sign [it’s time to stop]. (Patrick, 19 years, 2nd year Sports/Rec, lives at College)

Here, the becoming of responsible subjects achieved through the university experience infused students’ descriptions of patterns of excessive drinking. Consistent with other studies on youth drinking, these findings highlight that how Lucy and Patrick frame responsibility and harm is out of step with public health conceptions of responsible drinking and harm associated with intoxication (Hutton, 2012; Tutenges & Hulvej, 2009). Rather than being harms they should seek to avoid, for Lucy and Patrick, vomiting and severe loss of coordination are physical symptoms that provide a clear indication of when they should stop drinking. For them, acting responsibly as consumers of alcohol involved being responsive to those indicators in

order to prevent blacking out, which were skills they learnt by drinking.

“SUCCESSFUL” DRINKING AND THE UNIVERSITY LIFESTYLE The idea of the university lifestyle as offering a space time to drink for some students was conceived as an education: learning how to regularly drink is understood to be a critical part of an unofficial “curriculum” or university culture, with some students doing it better than others (Bewick et al., 2008; Leontini et al., 2015). Third-year students, for example, believed they had developed skills for managing their drinking compared to first-year students who were perceived to be less competent. Knowledge gained as a part of this process was experienced as empowering, and was privileged over other education sources about alcohol use, such as public health harm minimization campaigns. The findings accord with Skelton’s (2002, p. 105) approach to youth as a “time of knowing” where students are “living the present and making the most of the time they have.” Here the university lifestyle that students have invested in is educating students through lived experience about what drinking means, how to drink and with whom to drink. This unofficial education is arguably part of students’ becoming in that it involves students evolving as consumers of alcohol over the course of their studies. This finding also accords with other studies that have found students’ alcohol consumption decreases across the course of their studies, with firstyears drinking more heavily than third-years (Bewick et al., 2008). We suggest that the university lifestyle can be usefully understood as a commodity that is being invested in during the liminal space time of university for many students. It is, thus, through making the most of opportunities to drink that students believe they are evolving into more knowledgeable consumers of alcohol. Through their practices over time, they constitute themselves as experienced drinkers (Ja¨rvinen, Ellergaard, & Larsen, 2014) who are able to enjoy the pleasure, sociability and status of consumption, while also employing strategies to reduce the harms and negative consequences of heavy drinking (Grace et al., 2009). This process of becoming occurs through the acquisition of knowledge based on their own and their friends’ drinking experiences, even when these are seen as regrettable (Tutenges & Hulvej, 2009). In this way, learning how to manage drinking—and even heavy or frequent consumption—emerges as part of a drinking culture increasingly common to the university lifestyle (Hepworth et al., 2016). However, for

I. INTRODUCTORY CHAPTERS

DRINKING: ESCAPING RESPONSIBILITIES AND PRESSURE

most students there were clear tensions between the responsibility toward academic obligations and maximizing the pleasures of drinking that the space time of university provided.

DRINKING: ESCAPING RESPONSIBILITIES AND PRESSURE Drinking is like an escape. . . You feel released from all your troubles and whatever else is going on during the week. You can just have one night where you don’t care anymore. You’re out with the boys. You’re having fun. (Andrew, 20 years, 2nd year Arts, lives at College)

Andrew’s description suggests that release from responsibilities is part of the pleasure and relaxation ascribed to alcohol. Like Andrew, students described the reasons for and pleasures of drinking in evocative ways. Students spoke of drinking alcohol as increasing pleasure, describing the positive effects of intoxication as a reward after meeting school, family or work obligations (“I deserve a drink”), and as a means to “wind down,” “relax,” and “release,” and as a way of “letting your hair down.” Students also described consuming alcohol as a way of denying, coping with, and escaping the challenges and responsibilities of everyday life:

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they spoke of “escape” and having “no worries,” “cares,” or “troubles” when consuming alcohol. Alcohol was also seen to help students with loneliness and lack of confidence, especially in social interactions with others. Students commented that things were “easier” when intoxicated, they had greater “confidence meeting strangers,” “people were different,” and it was when “friendships” were made. These comments suggest that for many students, drinking is perceived as a way to escape from responsibilities of everyday life, in part through connecting with others, as Rebecca’s description of her relationship with her closest friend illustrates: If it wasn’t about the drinking, I wouldn’t have got to know a few of the very important people in my life. My best friend, she likes to party, so I accompany her to the clubs to party. . .just to be with her. . . [B]ecause of drinking and going out with her, I get to be very close to her. Now she’s my sister, she’s my very close sister, and it all roots from drinking. (21 years, 1st year Business, living in a share-house)

For many students, drinking provides a liberating alternative to family obligation, work commitments, exam timetables, and study, and, like Rebecca, an opportunity for meaningful connections with others (Fig. 1.3).

FIGURE 1.3 Dynamics of balancing studying and drinking for students. Students’ complex relationship between consuming alcohol at university and successfully completing their degree. Unpublished.

I. INTRODUCTORY CHAPTERS

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1. ALCOHOL CONSUMPTION BY UNIVERSITY STUDENTS

SECURING THE FUTURE THROUGH COMPLETING A DEGREE There were tensions between making the most of the pleasures associated with drinking and the practical realities and obligations of university life. Here, the idealization of university as a space time to drink conflicted with the prospect of failing at university and, therefore, threatening the transition out of university (see Fig. 1.3). This prospective next transition was, for many students, the test for assessing and moderating their drinking. The impact of alcohol use was measured in relation to their academic performance, as Eleanor explains: Interviewer: Do You Have Any Concerns About Drinking Alcohol? Whether [drinking is] affecting how much we remember for the course and stuff like that, and then how hard it is to concentrate in lectures and tutes the next morning. Yeah, that’s probably the main things. (19 years, 2nd year Medicine, lives at College)

For students who lived in residential colleges, where there are many more opportunities for drinking frequently and/or heavily (Leontini et al., 2015), these concerns were more pronounced, with one participant reporting that he moved out of college in order to successfully complete his final years of study. In this respect, alcohol consumption is perceived by students as both a benefit and a harm, a contradictory relationship that has been noted about young drinkers more broadly (Banister & Piacentini, 2008; Hernandez et al., 2013). On the one hand, for many students, drinking and its association with escape, freedom, belonging, self-determination, independence, and pleasure is set up in positive opposition to the grind, drudgery, and stress of responsibility and the dutiful conduct of sobriety (Colby, Colby, & Raymond, 2009). On the other hand, for those students to “make the most of time they have” (Skelton, 2002, p. 105) also means effectively balancing the opportunity to drink and other commitments, especially academic performance (see Fig. 1.3).

University is understood by students as a unique space time—a place to party and become “adult” (Colby et al., 2009). Accompanying their investment in a tertiary education, many students also invest in a university lifestyle that many perceive as setting them up for the rest of their lives socially as well as professionally (Hepworth et al., 2016; Leontini et al., 2015; Supski et al., 2016). We have argued that for many students, their “becoming” as consumers of alcohol is perceived as a form of return on their investment in the university lifestyle. Students see consumption of alcohol at university as a learning experience, which is, mostly, intensely pleasurable. Yet as we have shown, the consumption of alcohol currently embedded within the consumption of tertiary education creates deep contradictions for students as they try to simultaneously escape their responsibilities in the present and create their futures, and become successful graduates through drinking and studying. Successfully consuming both tertiary education and alcohol requires some students to manage a complex struggle in order to avoid compromising their investment in their degree.

MINI-DICTIONARY OF TERMS Space time A concept that captures the dynamic sociocultural and structural characteristics that shape what people do and the ways they do things together. Becoming A nonlinear process of individual development/ evolution. Consumption The use or purchase of goods or services, the act of ingesting food or drink. In sociology, consumption is connected to social behaviors, identities, institutions and power. Hedonism The pursuit of pleasure. Nighttime economy Economic activity that involves nighttime, alcohol-focused entertainment. University lifestyle A sociocultural experience specific to the space time of university. Responsibilized The process by which people are made responsible or imbued with a sense of responsibility. Harm minimization Strategies designed to prevent and reduce harm associated with alcohol and other drug use. Liminality A transitional period when a person moves from one socioculturally defined life-stage to another. Relational The ways in which people are interconnected.

CONCLUSION This chapter has examined the significance of alcohol at university as a commodity that is ubiquitous and normalized in the space time of undergraduates’ candidature. We found that for students the experience of university not only offers frequent occasions for drinking, but what is perceived to be a unique opportunity within a brief bracket in time while completing their education.

KEY FACTS OF SOCIOLOGY • Sociology is the study of society including social structures, institutions, cultures, and processes. • It investigates individual experiences and identities and the social factors that shape them (e.g., class, gender, ethnicity, age, socioeconomic status, power, and culture).

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REFERENCES

• It understands social meanings and behaviors to be contingent on specific sociocultural and politicoeconomic contexts. • It investigates social phenomena such as crime and law, wealth and poverty, racism, discrimination, and inequality. • Sociology uses a wide variety of qualitative and quantitative methods to collect and analyze evidence on social phenomena.

SUMMARY POINTS • For many students, university is perceived as a unique space time in one’s life course in which to drink excessively. • Many students “learn” how to drink alcohol across the course of their degree. • Consumption of alcohol is a key part of the university lifestyle students are investing in along with their degree. • Drinking is experienced by many students as pleasurable as well as harmful. • Students must manage a complex struggle between studying and consuming alcohol in order to successfully complete their degree.

References Andersson, J., Sadgrove, J., & Valentine, G. (2012). Consuming campus: Geographies of encounter at a British university. Social and Cultural Geography, 13(5), 501 515. Banister, E. N., & Piacentini, M. G. (2008). Drunk and (dis)orderly: The role of alcohol in supporting liminality. Advances in Consumer Research, 35, 311 318. Bewick, B. M., Mulhern, B., Barkham, M., Trusler, K., Hill, A., & Stiles, W. (2008). Changes in undergraduate student alcohol consumption as they progress through university. BMC Public Health, 8(1), 163 170. Colby, S. M., Colby, J., & Raymond, G. A. (2009). College versus the real world: Student perceptions and implications for understanding heavy drinking among college students. Addictive Behaviour, 34(1), 17 27. Evans, K., & Heinz, W. R. (1994). Becoming adults in England and Germany. London: Anglo-German Foundation. Grace, J., Moore, D., & Northcote, J. (2009). Alcohol, risk and harm reduction: Drinking amongst young adults in recreational settings in Perth. Perth: National Drug Research Institute. Griffin, C., Bengry-Howell, A., Hackley, C., & Szmigin, I. (2009). ‘Every time I do it I absolutely annihilate myself’: Loss of (self-) consciousness and loss of memory in young people’s drinking narratives. Sociology, 43(3), 457 476. Hepworth, J., McVittie, C., Schofield, T., Lindsay, J., Leontini, R., & Germov, J. (2016). ‘Just choose the easy option’: Students talk about alcohol use and social influence. Journal of Youth Studies, 19 (2), 251 268.

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Herman-Kinney, N., & Kinney, D. (2013). Sober as deviant: The stigma of sobriety and how some college students “stay dry” on a “wet” campus. Journal of Contemporary Ethnography, 42(1), 64 103. Hernandez, L., Leontini, R., & Harley, K. (2013). Alcohol, university students and harm minimisation campaigns: ‘A fine line between a good night out and a nightmare’. Contemporary Drug Problems, 40(2), 157 189. Hillman, K. J., & Marks, G. N. (2002). Becoming an adult: Leaving home, relationships and home ownership among Australian youth. Camberwell, VIC: Australian Council for Educational Research. Hutton, F. (2012). Harm reduction, students and pleasure: An examination of student responses to a binge drinking campaign. International Journal of Drug Policy, 23(3), 229 235. Ja¨rvinen, M., Ellergaard, C. H., & Larsen, A. G. (2014). Drinking successfully: Alcohol consumption, taste and social status. Journal of Consumer Culture, 14(3), 384 405. Leontini, R., Schofield, T., Lindsay, J., Brown, R., Hepworth, J., & Germov, J. (2015). ‘Social Stuff’ and institutional micro-processes: Alcohol use by students in Australian university residential colleges. Contemporary Drug Problems, 42(3), 171 187. Lindsay, J. (2009). Young Australians and the staging of intoxication and self-control. Journal of Youth Studies, 12(4), 371 384. McBride, W., & Li, T. (1998). Animal models of alcoholism: Neurobiology of high alcohol-drinking behavior in rodents. Critical Reviews in Neurobiology, 12(4), 339 369. Moss, D., & Richter, I. (2010). Understanding young people’s transitions in university halls through space and time. Young, 18(2), 157 176. Reilly, M., Noronha, A., & Warren, K. (2014). Perspectives on the neuroscience of alcohol from the National Institute on Alcohol Abuse and Alcoholism. Handbook of Clinical Neurology, 125, 15 29. Schofield, T., Lindsay, J., Giles, F., Hepworth, J., Germov, J., & Leontini, R. (2010). Alcohol use and harm minimisation among Australian University Students. ARC Linkage Project LIP100100471. Shields, R. (1991). Places on the margins: Alternative geographies of modernity. London: Routledge. Skelton, T. (2002). Research on youth transitions: Some critical interventions. In M. Cieslik, & G. Pollock (Eds.), Young people in risk society: The restructuring of youth identities and transitions in late modernity (pp. 100 116). Aldershot: Ashgate. Spanagel, R., Noori, H., & Heilig, M. (2014). Stress and alcohol interactions: Animal studies and clinical significance. Trends in Neurosciences, 37(4), 219 227. Supski, S., & Lindsay, J. (2016). There’s something wrong with you: How young people choose abstinence in a heavy drinking culture. Young. Available from https://doi.org/10.1177/ 1103308816654068. Supski, S., Lindsay, J., & Tanner, C. (2016). University students’ drinking as a social practice and the challenge for public health. Critical Public Health, 27(2), 228 237. Szmigin, I., Griffin, C., Mistral, W., Bengry-Howell, A., Weale, L., & Hackley, C. (2008). Re-framing ‘binge drinking’ as calculated hedonism: Empirical evidence from the UK. International Journal of Drug Policy, 19(5), 359 366. Tomlinson, M. (2016). Student perceptions of themselves as ‘consumers’ of higher education. British Journal of Sociology of Education, 38(4), 1 20. Tutenges, S., & Hulvej, R. M. (2009). ‘We got incredibly drunk. . .it was damned fun’: Drinking stories among Danish youth. Journal of Youth Studies, 12(4), 355 370. Winchester, H., McGuirk, P., & Everett, K. (2005). Schoolies week as a rite of passage: A study of celebration and control. In E. Teather (Ed.), Embodied geographies: Spaces, bodies and rites of passage (pp. 59 76). London: Taylor and Francis. Worth, N. (2009). Understanding youth transition as ‘becoming’: Identity, time and futurity. Geoforum, 40(6), 1050 1060.

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C H A P T E R

2 Molecular Genetics Meets Sociology: Birth Cohort Effects on Alcohol Use and Relationship With Candidate Genes Jaanus Harro and Mariliis Vaht Division of Neuropsychopharmacology, Department of Psychology, Estonian Centre of Behavioural and Health Sciences, University of Tartu, Tartu, Estonia

LIST OF ABBREVIATIONS CCEE CNS ECPBHS 5-HTTLPR NRG1 OXTR VMAT VMAT1

significantly different environments (Harro, 2010). It is conceivable that the factors leading to alcohol abuse vary in their level of impact between regions and countries. In turn, in any given area these factors would not be kept constant either. Alcohol consumption and related health problems are indeed subject to birth cohort effects (Kraus et al., 2015; Johnson & Gerstein, 1998; Meng, Holmes, HillMcManus, Brennan, & Meier, 2014; Pabst, Kraus, Piontek, & Mueller, 2010; Rice et al., 2003; TriasLlimo´s, Bijlsma, & Janssen, 2017). Socioeconomic factors, and alcohol-related policies, laws, and social norms are group-level exposures that vary between time periods and countries and may be associated with birth cohort effects; importantly, these effects may be gender specific (Keyes, Li, & Hasin, 2011a). Hence, it would be expected that if societal changes are brought about rapidly, birth cohort effects on alcohol use, and consequently alcohol use disorder, could be observable within a relatively brief time span. Such rapid transitions have, in recent decades, taken place in countries of Central and Eastern Europe (CCEE) that are often referred to as transition economies or transition societies, meaning that single-party rule is replaced by a parliamentary system, administrative institutions are being reorganized, a free market economy emerges instead of central planning, and a society known for shortage of everyday consumer goods is changing into a typical consumer society (Allaste & Bennett, 2013; Nugin, Kannike, & Raudsepp, 2016). Alcohol supply and use in these countries has

countries of Central and Eastern Europe central nervous system Estonian Children Personality Behaviour and Health Study 5-hydroxytryptamine (serotonin) transporter gene linked polymorphic region neuregulin-1 gene oxytocin receptor gene vesicular monoamine transporter vesicular monoamine transporter type 1 gene

ALCOHOL ISSUES: HOW TO RECONCILE HERITABILITY AND SECULAR FLUCTUATIONS Alcohol use, high-risk drinking, and alcohol use disorder are on the rise and their prevalence in populations can significantly increase within only a few years (Grant et al., 2017). It is also well known that problematic alcohol use runs in families (Plant, Orford, & Grant, 1989) and that higher alcohol consumption is predictable from an early onset of alcohol use (Lee, Young-Wolff, Kendler, & Prescott, 2012; York, Welte, Hirsch, Hoffman, & Barnes, 2004). Twin studies confirm the genetic foundation of alcohol-related behaviors (Ball & Murray, 1994), but the contributing genes have remained elusive. Among the various reasons for this apparently “missing” heritability are the gene 3 environment interactions: For a given behavior or disorder, the genetic factors should partly differ in Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00002-7

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© 2019 Elsevier Inc. All rights reserved.

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2. GENES, BIRTH COHORT EFFECTS, AND ALCOHOL

responded to societal changes rapidly and in a highly dynamic manner (Moskalewicz & Simpura, 2000).

THE ORIGINAL DEMONSTRATION OF GENOTYPE 3 BIRTH COHORT INTERACTION A few years ago, we hypothesized that birth cohort effects on alcohol use should interact with genetic variants known to affect the development of the central nervous system (CNS) and social behavior, and addressed the potential presence of interaction of genotype 3 cohort effect using a candidate gene approach in the sample of the Estonian Children Personality Behaviour and Health Study (ECPBHS). The ECPBHS is a longitudinal birth cohort study with the original sampling in 1998/1999 while the subjects were either in third or ninth grade, corresponding to average ages of nine and 15 years, respectively (Harro et al., 2001). Follow-up studies have been conducted at ages 15, 18, 25, and, for the older cohort, 33. What is important for the following discussion is that these two birth cohorts had been recruited from the same schools (54 out of the 56 schools in the region consented to the study, 25 of these were selected with the probability proportional to school size), that all students of the third and ninth grades were invited to participate, and that in both cohorts nearly 80% of the invited subjects agreed. Altogether this means that the two birth cohort samples are highly representative and that there should be minimal differential bias of selection. The first demonstration of genotype and birth cohort interaction in relation to alcohol came from the analysis of the association of the serotonin transporter gene promoter polymorphism (5-HTTLPR) genotype and alcohol use. Serotonin transporter is the key contributor to serotonergic neurotransmission throughout the brain and the promoter region of its gene contains a much-studied variable number of tandem repeats polymorphism (Lesch et al., 1996) that is associated with response of amygdala to fearful stimuli (Hariri et al., 2002). Studies on the association of the 5-HTTLPR genotype with alcohol consumption have been equivocal in their conclusions. Our analysis of the two birth cohorts from the ECPBHS has suggested a possible reason for the inconsistency in findings: Carriers of the s-allele, with higher amygdalar response to threats, have a highly variable association with alcohol use. Specifically, we found a statistically highly significant genotype 3 gender 3 birth cohort interaction effect on the age of first consumption of half a unit of alcohol (Vaht, Merena¨kk, Ma¨estu, Veidebaum, & Harro, 2014). The expected findings in this analysis were that males started to use alcohol

earlier than females, that the younger cohort had started to experiment with alcohol at more than 1 year earlier in age, and that the difference between males and females had become smaller in the younger cohort. These differences were, however, strongly dependent on the 5-HTTLPR genotype: While in the older cohort, the female s/s homozygotes were the group that started to drink alcohol later than any other group, the female 5-HTTLPR homozygotes of the younger cohort made their alcohol debut earlier than males, and, on average, at almost 3 years younger in age than their counterparts in the older cohort. Indeed, an overall impression of the many studies on the 5HTTLPR genotype is that it is more consistently associated with behavior in females and this may relate to regulation of social behavior. What could be said of societal changes is that availability of alcohol increased and attitudes toward its use became more liberal in the period between the two cohorts’ passage to their teenage years.

FURTHER GENOTYPE 3 BIRTH COHORT INTERACTIONS WITH CANDIDATE GENES FOR SOCIAL BEHAVIOR With this experience from the most studied psychiatric genotype, we addressed the possibility of genotype 3 birth cohort interaction in our next study that was on the VMAT1 Thr136Ile genotype. Storage of monoamine neurotransmitters is dependent on vesicular monoamine transporters (VMATs), and the VMAT1, only recently discovered in the CNS, has higher affinity for serotonin than VMAT2 and may be important in a number of psychiatric conditions (Lohoff, 2010). A single nucleotide polymorphism (SNP) in the human VMAT1 (rs1390938, G/A) results in substitution of isoleucine for threonine in the VMAT1 protein at position 136, and with the less common Ile variant the transport of monoamines into presynaptic vesicles is more efficient (Khalifa et al., 2012). It was found that homozygocity for the less-frequent A-allele of the VMAT1 genotype was not only associated with better mental health indicators, but also with resilience toward the reduction in mean age of beginning alcohol use: This reduction appeared on account of the G-allele carriers, in particular the G-allele homozygotes (Vaht, Kiive, Veidebaum, & Harro, 2016a). We next examined the potential role of neuregulin-1 genotype in alcohol abuse. Neuregulins are a family of proteins that have diverse functions in the development of the CNS, and neuregulin-1 has been implicated in the pathogenesis of schizophrenia (Mostaid et al., 2016). Substance abuse and addictions are common in psychotic disorders

I. INTRODUCTORY CHAPTERS

Proportion of subjects diagnosed with AUD

BIRTH COHORTS MAY LIVE IN DISTINCT ENVIRONMENTS AS THE SOCIETY UNDERGOES CHANGE

0.8

15

SLE > 3

Males Females

SLE ≤ 3

0.6

0.4

0.2

0.0 C/C

T allele carriers

C/C

T allele carriers Younger cohort

Older cohort

FIGURE 2.1 Alcohol use disorder by age 25 in both birth cohorts of the ECPBHS by the NRG1 rs6994992 genotype and exposure to stressful life events. Results of the logistic model analysis of ECPBHS alcohol use disorder (AUD) by age 25 considering factors cohort, gender, number of stressful life events (SLE) and NRG1 genotype, and all interactions. Estimated proportions (with 95% confidence intervals) of subjects diagnosed with AUD by cohort, gender, SLE and NRG1 genotype are presented. All main effects were statistically significant (P , .001, P 5 .011, P 5 .003, and P 5 .008 for gender, cohort, SLE and NRG1 genotype, respectively), indicating higher proportion of subjects diagnosed with AUD among males, in younger cohort, among subjects with SLE . 3 and C/C genotype. Statistically significant SLE by NRG1 genotype interaction effect (P 5 .008) uncovered the protective role of T allele among subjects with SLE . 3, but the opposite role among subjects with SLE # 3. The post hoc pairwise comparisons revealed statistically significantly higher proportions of subjects diagnosed with AUD among older cohort SLE . 3 females with C/C genotype compared to T allele carriers and among younger cohort SLE . 3 males with C/C genotype compared to T allele carriers (OR 5 16.73, P , .001 and OR 5 2.43, P 5 .036, respectively).

(Azorin, Simon, Adida, & Belzeaux, 2016) and the neuregulin-1 receptor ErbB4 is expressed in the serotonergic neurons in the raphe nuclei (Bean et al., 2014). The human NRG1 gene contains a functional SNP in the promoter region (rs6994992; Stefansson et al., 2002). We found that the NRG1 rs6994992 C/C homozygotes were more likely to develop alcohol use disorders, in particular if they had been exposed to a larger extent to stressful life events (Vaht et al., 2017). In the older cohort, the gene 3 environment interaction was significant only in females. In contrast, in the younger cohort similar interaction was absent in females; however, in male C/C homozygotes who had been exposed to at least four stressful life events, two thirds of the subjects had met the alcohol use disorder criteria by age 25 (Fig. 2.1). Oxytocin is a neuropeptide that is well known to coordinate aspects of the physiology of reproduction, but has recently received much attention as a mediator of affiliative behavior and social relationships (Gangestad & Grebe, 2017). Oxytocin regulates social behavior together with serotonin (Insel & Winslow, 1998) and the prosocial effects of serotonin-releasing drugs may be related to their ability to enhance oxytocin release (Kamilar-Britt & Bedi, 2015). Of the reported polymorphisms in the human oxytocin receptor gene (OXTR) the rs53576 appears as most consistently associated with individual differences in social

behavior (Gong et al., 2017). In the older cohort from the ECPBHS, males homozygous for the minor, A-allele (presumably leading to lower oxytocinergic function), had developed at an early age with more frequent alcohol consumption, and with higher probability ended up with alcohol use disorder by early adulthood (Vaht, Kurrikoff, Laas, Veidebaum, & Harro, 2016b). In the younger cohort, however, this genotype effect was absent: At age 15, no difference between genotypes in alcohol use frequency was found (Fig. 2.2), and by age 18, alcohol consumption was more frequent in the A/G heterozygotes, the A/A group rather appearing as the least frequent alcohol consumers (Fig. 2.3). Consequently, prevalence of alcohol use disorder in the younger cohort was not associated with the OXTR A/A genotype, but rather higher in male G/G homozygotes (Fig. 2.4).

BIRTH COHORTS MAY LIVE IN DISTINCT ENVIRONMENTS AS THE SOCIETY UNDERGOES CHANGE These examples of candidate gene variants being associated with alcohol measures in one birth cohort but not in the other, or even showing opposite associations, can explain some controversies in molecular genetics of behavior and suggest that differential

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2. GENES, BIRTH COHORT EFFECTS, AND ALCOHOL

FIGURE 2.2

Alcohol use at age 15 in both birth cohorts of the ECPBHS by the OXTR rs53567 genotype. Alcohol use at age 15 was OXTR genotype-dependent in males in the older cohort, but not the younger cohort of the Estonian Children Personality Behaviour and Health Study [FOXTR 3 cohort 3 gender (21,021) 5 5.1; P 5 .006]. Note the overall higher frequency of alcohol use in the younger cohort Fcohort (21,031) 5 58.6; P , .001]. Significant groupwise differences  P , .05;  P , .01; Fisher’s least significant difference (LSD) test. Data are presented as mean 6 SEM.

FIGURE 2.3 Alcohol use at age 18 in both birth cohorts of the ECPBHS by the OXTR rs53567 genotype. Alcohol use at age 18 was more frequent in the male OXTR A/A homozygotes of the older cohort, but in other comparisons rather heterosis-like associations appeared [FOXTR (2888) 5 4.6; P 5 .011; F OXTR 3 cohort (2885) 5 2.9; P 5 .058; FOXTR 3 cohort 3 gender (2879) 5 2.6; P 5 .073]. Significant and trend-like groupwise differences  P , .05;  P , .001; #P 5 .06; oP 5 .072; Fisher’s LSD test. Data are presented as mean 6 SEM.

I. INTRODUCTORY CHAPTERS

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Proportion of subjects diagnosed with AUD

MECHANISMS BEHIND THE GENOTYPE 3 BIRTH COHORT INTERACTIONS

0.8

Males Females

0.6

0.4

0.2

0.0 A/A

A/G

G/G

A/A

Older cohort

A/G

G/G

Younger cohort

FIGURE 2.4 Alcohol use disorder by age 25 in both birth cohorts of the ECPBHS by the OXTR rs53567 genotype. Results of the logistic model analysis of ECPBHS alcohol use disorder (AUD) by age 25 considering factors cohort, gender and OXTR genotype, and all interactions. Estimated proportions (with 95% confidence intervals) of subjects diagnosed with AUD by cohort, gender and OXTR genotype are presented, additionally the estimated proportions by cohorts are marked with gray line (with light gray area showing the 95% confidence interval). The effects of gender, cohort and OXTR genotype by cohort interaction were statistically significant (P , .001, P 5 .011 and P 5 .016, respectively), indicating a higher proportion of subjects diagnosed with AUD among males, in younger cohort, and the protective role of G-allele in the older cohort, but an opposite role in the younger cohort. There were also slight differences between OXTR genotypes depending on gender, but this interaction effect was not statistically significant (P 5 .143). The post hoc pairwise comparisons revealed statistically significantly higher proportions of subjects diagnosed with AUD among older cohort males with A/A genotype compared with A/G and G/G genotypes (OR 5 3.06, P 5 .014 and OR 5 2.68, P 5 .033, respectively).

response to societal changes at large are related to specific aspects of genetic background. Of course, cohort effects could be easily dismissed as rising by mere chance or biases in sample formation. If systematically appearing in samples where any selection bias is presumably low, they nevertheless may rather reflect the changes that are occurring in the environment. What could be the factors that make the birth cohort effects appear? And how do these come to interact with genetic variation? Birth cohort effects reflect the socioeconomic environment experienced by different generations. Restrictions, prices, and advertisements related to alcohol influence drinking behavior directly already at young age (Paschall, Grube, & Kypri, 2009) and this tends to predict patterns of alcohol use over the life course (Eliasen et al., 2009; Pitkanen, Lyyra, & Pulkkinen, 2005). Estonia is a representative CCEE transition society that moved away from socialism in the late-1980s and became an independent and highly liberal economy since 1991, being one of the fastest growing in the world until 2007 (World Bank, 2015). The former socialist countries missed major developments of the second half of the 20th century such as orientation towards consumerism and leisure, privatization and free market economy, diversity of lifestyles, and visibility of alternative subcultures. But this is not to say that birth cohort effects could be limited to such

regions where huge economy-related societal changes have been taking place. What is critically important is the perceived approval of drug use. Adolescents who matured in birth cohorts with low disapproval of drug use were at higher risk of using drugs during their teenage years, regardless of individual-level disapproval, perceived social norms, or perceived availability (Keyes et al., 2011b). Social norms and attitudes regarding drug use are likely to cluster in birth cohorts, and this clustering has a direct effect on drug use even after controlling for individual attitudes and perceptions of norms.

MECHANISMS BEHIND THE GENOTYPE 3 BIRTH COHORT INTERACTIONS Variation in substance abuse liability stems not only from genotypic differences and environmental circumstances, but also from their interactions; it occurs when the expression of a gene varies in different environments, or at different ages, or when the influence of the environment varies by genotype (Gunzerath & Goldman, 2003). Two principal processes whereby environmental circumstances interact with genetic influences with respect to drinking behaviors seem to

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2. GENES, BIRTH COHORT EFFECTS, AND ALCOHOL

exist (Young-Wolff, Enoch, & Prescott, 2011). First, restrictions, including social norms promoting abstinence and restricted availability of alcohol, may reduce the expression of genetic influences on drinking behaviors (Shanahan & Hofer, 2005). In environments characterized by high levels of social control, a large proportion of individuals, irrespective of genotype, are expected to exhibit low levels of drinking. One could also speculate that in such conditions the genetic contribution to alcohol use is to a significant extent through characteristics like nonconformity. Conversely, in more permissive settings, alcohol consumption would be more dependent on reward sensitivity or, if the social norms facilitate alcohol use (as it is the case in Estonia), rather the conformity. A second mechanism is that the social context can act as a stressor that potentiates the behavioral expression of genetic liability on risk for alcohol consumption and alcohol use disorder (Rende & Plomin, 1992). Genetically more influenced traits have been found to be the more variable phenotypes and environmental influences appear greater for the later-developing brain regions (Brun et al., 2009), suggesting that often the environment acts to reduce the genetically produced variability (Harro, 2010). Simple genetic effects can, on the other hand, be increased. It has been estimated that the general knowledge of harms by smoking and resultant antismoking policies have brought about cohort effects in the genetic influence on smoking (Domingue, Conley, Fletcher, & Boardman, 2016). So far the focus has been on genotypes that affect the development of the aspects of the CNS responsible for social behavior, for example, the serotonin system. Other neurochemical systems that play major roles in, for example, reward sensitivity or management of stress response, remain to be probed, and modeling analyses applied to understand better the mechanisms behind such gene 3 environment interactions that appear to be beyond the individual level, but rather societally controlled.

MINI-DICTIONARY OF TERMS Birth cohort In medical investigations this refers to a group of individuals that were born in a specified time period. Attention should be paid to, for example, the method of recruitment and in which respect the whole population is aimed to be represented. Transition society Also referred to as transition economy, it means more broadly a society rapidly changing from one formation to another, but currently is often used to mean a country which is changing from a centrally planned economy to a market economy. Genotype The genetic makeup of an individual, but usually refers to a particular gene of interest, and most often to the combination of gene alleles for a specific variant in the individuals.

Gene 3 environment interaction Gene variants matter because they may give rise to differences in gene expression and the end products, proteins. Gene expression is influenced by a large variety of environmental factors. Candidate gene A gene that has a product with a known function which makes it implicated in phenomena of interest. Serotonin A neurotransmitter in an evolutionally conserved neurochemical system, implicated in many functions but especially strongly in impulsivity and social behaviors. 5-HTTLPR A variable number of tandem repeats type of genetic polymorphism that is the most studied variation in psychiatric genetics. Many findings have been hard to reproduce, but some survive meta-analyses. Vesicular monoamine transporter Monoamine neurotransmitters such as serotonin, dopamine and noradrenaline are stored in synaptic vesicles until released into a synaptic cleft to transmit the neural message. Vesicular transporters transport the monoamines against the concentration gradient to the vesicles. Neuregulins A family of polypeptides that belong to the larger family of epidermal growth factor, like the family of proteins. Neuregulins have diverse functions in the development of the CNS. Oxytocin A small peptide acting both as a hormone and as a neurotransmitter that plays a role in various physiological functions related to reproduction.

KEY FACTS Candidate Gene Studies • Candidate gene approach refers to investigations on the role of genes known or believed to have a function that affects the phenotype of interest. • Genetic association studies often use candidate gene approach, but the principle applies to measurement of gene expression as well. • Candidate gene studies contrast to genome-wide association studies or genome-wide expression studies that make no a priori hypothesis. • Weakness of the candidate gene studies is that their scope is limited to what is already known, and it is easy to extrapolate improperly from the existing knowledge. • The latter may be one reason why many welldesigned candidate gene studies have been impossible to replicate. • A gene that has its role discovered by hypothesisfree studies in essence also becomes a candidate gene and will face the scrutiny of case control studies. • Common gene variants found to affect a physiological function are likely to interact with the environmental factors in a complex manner. • Candidate gene approach is salient in most studies of an experimental nature where the gene or its expression is modified. • In case of “plasticity genes” the candidate gene approach allows to study how the associations of gene variants can be qualitatively different in distinct settings.

I. INTRODUCTORY CHAPTERS

REFERENCES

19

Oxytocin

References

• Oxytocin is a nine-amino-acid peptide that acts both as a hormone and a neurotransmitter. • It was discovered by sir Henry Dale in 1906, and sequenced and synthetized by Vincent du Vigneaud in 1953. • This neuropeptide is produced by neurons of the supraoptic nucleus and the paraventricular nucleus of the hypothalamus. • Oxytocin is secreted into the posterior lobe of the pituitary gland (the neurohypophysis) and further to the bloodstream to act as a hormone. • As a neurotransmitter, oxytocin is transported by axon projections to a number of brain regions where is released upon excitation. • Dendritic release and action of diffused oxytocin to nearby nuclei also occurs. • The effects of oxytocin are mediated by a single type of G-protein-coupled receptor. • Oxytocin has multiple central and peripheral actions but is most often considered a messenger that helps to coordinate physiology of reproduction. • In recent years, oxytocin has become the molecule of choice to be investigated in connection with all aspects of social behavior in multiple species including humans.

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SUMMARY POINTS • This chapter discusses the gene 3 environment interactions in terms of birth cohort effects. • Alcohol use and abuse have been found to differ between birth cohorts. • However, alcohol use and alcohol use disorders have a genetic component. • Genes that are relevant to alcohol problems each have very small effects. • It is argued that if gene 3 environment interactions are responsible for the inconsistencies between genetic studies, genotypes should interact with birth cohort effects. • Using a database on two highly representative birth cohorts genotype 3 birth cohort interactions are described.

Acknowledgments Relevant research was supported by grants from the Estonian Ministry of Education and Science (IUT20-40) and the European Community 7FP grant n 602805 (Aggressotype).

I. INTRODUCTORY CHAPTERS

20

2. GENES, BIRTH COHORT EFFECTS, AND ALCOHOL

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Plant, M. A., Orford, J., & Grant, M. (1989). The effects on children and adolescents of parents’ excessive drinking: An international review. Public Health Reports, 104, 433 442. Rende, R., & Plomin, R. (1992). Diathesis-stress models of psychopathology: A quantitative genetic perspective. Applied and Preventive Psychology, 1, 177 182. Rice, J. P., Neuman, R. J., Saccone, N. L., Corbett, J., Rochberg, N., Hesselbrock, V., . . . Reich, T. (2003). Age and birth cohort effects on rates of alcohol dependence. Alcoholism: Clinical and Experimental Research, 27, 93 99. Shanahan, M. J., & Hofer, S. M. (2005). Social context in gene environment interactions: Retrospect and prospect. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 60B, 65 76. Stefansson, H., Sigurdsson, E., Steinthorsdottir, V., Bjornsdottir, S., Ghosh, S., Brynjolfsson, F., . . . Stefansson, K. (2002). Neuregulin 1 and susceptibility to schizophrenia. American Journal of Human Genetics, 71, 877 892. Trias-Llimo´s, S., Bijlsma, M. J., & Janssen, F. (2017). The role of birth cohorts in long-term trends in liver cirrhosis mortality across eight European countries. Addiction, 112, 250 258. Vaht, M., Kiive, E., Veidebaum, T., & Harro, J. (2016a). A functional vesicular monoamine transporter 1 (VMAT1) gene variant is associated with affect and the prevalence of anxiety, affective and alcohol use disorders in a longitudinal populationrepresentative birth cohort study. International Journal of Neuropsychopharmacology, 19, pyw013. Available from https://doi. org/10.1093/ijnp/pyw013. Vaht, M., Kurrikoff, T., Laas, K., Veidebaum, T., & Harro, J. (2016b). Oxytocin receptor gene variation rs53576 and alcohol abuse in a longitudinal population representative study. Psychoneuroendocrinology, 74, 333 341. Vaht, M., Laas, K., Kiive, E., Parik, J., Veidebaum, T., & Harro, J. (2017). A functional neuregulin-1 gene variant and stressful life events: Effect on drug use in a longitudinal populationrepresentative cohort study. Journal of Psychopharmacology, 31, 54 61. Vaht, M., Merena¨kk, L., Ma¨estu, J., Veidebaum, T., & Harro, J. (2014). Serotonin transporter gene promoter polymorphism (5-HTTLPR) and alcohol use in general population: Interaction effect with birth cohort. Psychopharmacology, 231, 2587 2594. World Bank. (2015). GDP growth rate. Available from ,http://data. worldbank.org/indicator/NY.GDP.MKTP.KD.ZG/countries/1WEE?display 5 graph. Accessed 30.03.15. York, J. L., Welte, J., Hirsch, J., Hoffman, J. H., & Barnes, G. (2004). Association of age at first drink with current alcohol drinking variables in a national general population sample. Alcoholism: Clinical and Experimental Research, 28, 1379 1387. Young-Wolff, K. C., Enoch, M. A., & Prescott, C. A. (2011). The influence of gene environment interactions on alcohol consumption and alcohol use disorders: A comprehensive review. Clinical Psychology Reviews, 31, 800 816.

I. INTRODUCTORY CHAPTERS

C H A P T E R

3 Alcohol and Women: Unique Risks, Effects, and Implications for Clinical Practice Linda Richter Director of Policy Research and Analysis, Center on Addiction, New York, NY, United States

INTRODUCTION

domestic violence, suicide, child abuse and neglect, sexual assault, unplanned pregnancies, sexually transmitted diseases, academic failure, lost productivity, unemployment, poverty, and homelessness (Office of the Surgeon General, 2016). Compared to boys and men, girls and women tend to have different motivations for using alcohol, progress from alcohol use to addiction at lower levels of use and more quickly, and suffer the consequences of alcohol misuse sooner and more intensely. Despite these facts, sex differences are not sufficiently taken into account in prevention, early intervention, and treatment (Foster & Richter, 2013). For example, in 2016, only 0.3% of girls and women received alcohol treatment at a specialty facility in the past year—half the rate of boys and men (Center for Behavioral Health Statistics & Quality, 2017).

Alcohol use disorder affects one in 10 adult women (Grant et al., 2016) and one in 20 underage girls (ages 12 20) in the United States (Table 3.1). Among girls this age who report any alcohol use in the past month, one in five meet diagnostic criteria for an alcohol use disorder (Table 3.2; Richter, Pugh, Peters, Vaughan, & Foster, 2016). Recent data indicate that the prevalence of alcohol use, misuse, and disorder has increased significantly more among adult females than among adult males over the past decade. There has been a 16% increase in reports of past-year alcohol use among women (vs a 7% increase among men); a 58% increase in reports of high-risk drinking among women (vs a 16% increase among men); and an 84% increase in reports of alcohol use disorder among women (vs a 35% increase among men) (Tables 3.3; Grant et al., 2017). Despite a substantial body of research demonstrating the extensive health consequences of risky drinking and alcohol use disorder, and that they can be prevented and treated effectively, they too often go unrecognized and untreated, especially among women, resulting in unnecessary pain and suffering and costly consequences. Addiction is the primary preventable contributor to some of the most common causes of death among women, including heart disease and cancer, and exacerbates many other health conditions including respiratory disease, infertility, pregnancy complications, depression, anxiety, and eating disorders. Alcohol misuse and addiction are also involved in many of the social problems women face, including

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00003-9

PATHWAYS TO ALCOHOL USE DISORDER AMONG WOMEN Certain physiological factors contribute to a person’s susceptibility to the misuse of alcohol and to the likelihood that such misuse will progress to addiction. Whether a girl or woman begins to drink alcohol is determined primarily by environmental influences; however, whether alcohol use will develop into an alcohol use disorder is determined largely by physiological and genetic factors (Heath et al., 1997). An earlier than average age of physical and sexual maturation (Wichstrøm, 2001) and a family history of alcohol use disorder (Schuckit et al., 2000) also increase the risk for alcohol use disorder among girls and women.

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© 2019 Elsevier Inc. All rights reserved.

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3. ALCOHOL AND WOMEN

TABLE 3.1 Current Drinking, Risky Drinking, and Alcohol Use Disorder Among Males and Females, Aged 12 20, in the United States by Sex, 2013 Weighted N

Past 30-day alcohol use (%)

Alcohol use disorder (%)

38,115,562

22.8

5.7

Males

19,625,058

23.0

5.9

Females

18,490,504

22.5

5.4

Total

Data adapted from Richter, L., Pugh, B. S., Peters, E., Vaughan, R. D., & Foster, S. E. (2016). Underage drinking: Prevalence and correlates of risky drinking measures among youth aged 12 20. American Journal of Drug and Alcohol Abuse, 42(4), 385 394.

TABLE 3.3 Prevalence of and Percentage Change in Alcohol Use Among Adults in the United States, by Sex, Between 2001 02 and 2012 13 2001 02 (n 5 43,093) (%)

2012 13 (n 5 36,309) (%)

% Change

65.4

72.7

11.2

Males

71.8

76.7

6.8

Females

59.6

69.0

15.8

9.7

12.6

29.9

14.2

16.4

15.5

5.7

9.0

57.9

8.5

12.7

49.4

12.4

16.7

34.7

4.9

9.0

83.7

Past 12 Months Alcohol Use Total

Past 12 Months

TABLE 3.2 Risky Drinking and Alcohol Use Disorder Among Males and Females Who Report Past 30-Day Alcohol Use, Aged 12 20, in the United States, by Sex, 2013

High-Risk Alcohol Use Total Males

Weighted N

Alcohol use disorder (%)

8,684,882

20.5

Past 12 Months

Males

4,522,205

21.4

DSM-IV Alcohol Use Disorder

Females

4,162,677

19.6

Total

Total

Data adapted from Richter, L., Pugh, B. S., Peters, E., Vaughan, R. D., & Foster, S. E. (2016). Underage drinking: Prevalence and correlates of risky drinking measures among youth aged 12 20. American Journal of Drug and Alcohol Abuse, 42(4), 385 394.

Women appear to have different neurochemical vulnerabilities to alcohol addiction relative to men. For example, the brain’s dopamine system is a critical component of the development and maintenance of addictive disorders, and sex differences have been found in the functioning of this system as well as in the GABA and NMDA receptors and other neurotransmitter systems (Agabio, Pisanu, Gessa, & Franconi, 2017; Pohjalainen, Rinne, Nagren, Syvalahti, & Hietala, 1998). Hormonal fluctuations that correspond to certain stages of a woman’s menstrual cycle, menopause, oral contraceptive use, and substitute hormonal therapy all play a role in the brain’s reward system’s response to alcohol intake (Agabio et al., 2017). As is true of males, the earlier a female begins to use alcohol, the higher the risk of developing an alcohol use disorder. Jenkins et al. (2011) found that earlyonset drinkers were three and half times more likely to meet criteria for alcohol addiction than later-onset drinkers. Other factors that are associated with an increased risk among females of developing alcohol addiction include mental health problems, other substance use, adverse life experiences, poor parental monitoring, and parental substance use.

Females

Males Females

Data adapted from Grant B. F., Chou, S. P., Saha, T. D., Pickering, R. P., Kerridge, B. T., Ruan, W. J., . . . Hasin, D. S. (2017). Prevalence of 12-month alcohol use, highrisk drinking, and DSM-IV alcohol use disorder in the United States, 2001 2002 to 2012 2013: Results from the National Epidemiologic Survey on Alcohol and Related Conditions. JAMA Psychiatry, 74(9), 911 923.

MORBIDITY, COMORBIDITY, AND MORTALITY RELATED TO ALCOHOL USE DISORDER IN WOMEN Alcohol use among women during pregnancy increases the risk of miscarriages, stillbirths, premature births, low birth-weight, congenital defects, and neonatal death; it also heightens the odds of poor cognitive skills and conduct disorders among prenatally exposed children. The most visible result of drinking during pregnancy is fetal alcohol spectrum disorder, characterized by growth deficiency, facial malformations, and cognitive deficiencies (The National Center on Addiction & Substance Abuse, 2006). Despite the strong link between prenatal alcohol exposure and adverse birth and childhood outcomes, a recent report from the US Centers for Disease Control and Prevention (CDC) found that more than three million women of reproductive age (7.3%) drink while sexually active and not using birth control. Three-quarters of women this age who say they want to get pregnant as soon as they possibly can also report that they did

I. INTRODUCTORY CHAPTERS

23

HOW DOES ALCOHOL AFFECT WOMEN DIFFERENTLY FROM MEN?

not stop drinking alcohol upon stopping birth control use (Green, McKnight-Eily, Tan, Mejia, & Denny, 2016). Alcohol use disorder in girls and women frequently cooccurs with depression, anxiety, schizophrenia, eating disorders, and other mental health conditions (Erol & Karpyak, 2015).

HOW DOES ALCOHOL AFFECT WOMEN DIFFERENTLY FROM MEN? Although women tend to drink less than men, when women drink, they experience the consequences more intensely and severely. This is due to significant differences in alcohol absorption, distribution, and metabolism between men and women that result from neurochemical, hormonal, genetic, and environmental factors (Agabio et al., 2017; Ceylan-Isik, McBride, & Ren, 2010; Erol & Karpyak, 2015). Compared to men, impairment from alcohol occurs among women at an earlier stage of drinking and after having consumed less alcohol. Women metabolize alcohol less efficiently: they have decreased activity of the enzyme alcohol dehydrogenase, which breaks down alcohol in the liver and stomach, keeping it from entering the bloodstream. Women’s bodies also generally contain less water and more fatty tissue than the bodies of men of similar size, so they maintain higher concentrations of alcohol in their blood; blood alcohol levels are higher in women than in men after ingesting the same amount of alcohol (Nolen-Hoeksema & Hilt, 2006). As a result, women tend to get intoxicated faster and have more intense hangovers than men, even when drinking the same amount of alcohol (National Institute on Alcohol Abuse & Alcoholism, 2015). They also show more cognitive impairment, sedation, and self-reported intoxication compared to men, and higher odds of alcohol-related injury (Agabio et al., 2017; Zeisser et al., 2013). Women with alcohol use disorder are at greater risk than are men for alcohol-related suicide, accidents, heart disease and other circulatory system disorders, cirrhosis of the liver, hepatitis, cancer, and fertility impairment. They tend to develop these problems sooner and at lower levels of drinking than men, and the deleterious effects of alcohol, including adverse alcohol medication interactions, become more severe as women age, relative to men (Agabio et al., 2017; Ceylan-Isik et al., 2010; National Institute on Alcohol Abuse & Alcoholism, 2000). Women also are more susceptible than men to alcohol-induced cognitive and motor skill impairment, and this may be due to the differential effects of alcohol on the structure of the female versus the male brain (Hommer, 2003). Women who engage in excessive drinking or who have an alcohol use disorder

demonstrate more damage to the brain relative to men, specifically in the areas involved in memory, motor control, and sensory perception (Ceylan-Isik et al., 2010; Erol & Karpyak, 2015; Hommer, 2003; Maynard, Barton, Robinson, Wooden, & Leasure, 2017). Maynard and colleagues (2016) found that alcohol-exposed female rats experience greater neuronal loss in the hippocampus’ dentate gyrus than male rats, and that binge alcohol use interrupts cell birth and increases cell death in female rats more than in male rats (Table 3.4). TABLE 3.4 Alcohol’s Differential Effects on Females Versus Males BIOLOGICAL FACTORS Enzyme

Gastric alcohol dehydrogenase, the metabolizing enzyme that breaks drown alcohol in the liver and stomach, is found in significantly higher concentrations in males than in females. This means that alcohol is more likely to enter the bloodstream in females relative to males, resulting in higher blood alcohol concentration levels, given the same amount of alcohol consumed over the same amount of time.

Fat to water ratio

Males have a higher ratio of muscle to fat than females and a higher fluid volume. This means that alcohol is more diluted in a man’s body than in a woman’s body, resulting in higher blood alcohol concentration levels in females than in males, given the same amount of alcohol consumed over the same amount of time.

Hormones

Fluctuations in females’ hormone levels during the course of the menstrual cycle affect the rate at which alcohol is eliminated from the body and the brain’s response to alcohol intake. This means that during certain times of her cycle, and when using oral contraceptives, a woman will be more sensitive to the intoxicating effects of alcohol.

HEALTH EFFECTS AND CONSEQUENCES Intoxication

Women tend to get intoxicated faster and have more intense hangovers than men, even when drinking the same amount of alcohol.

Cognitive and motor impairment

Women show more cognitive and motor skill impairment than men, and higher odds of alcohol-related injury.

Morbidity and mortality

Women with alcohol use disorder are at greater risk than are men for alcohol-related suicide, accidents, heart disease and other circulatory system disorders, cirrhosis of the liver, hepatitis, cancer, and fertility impairment.

I. INTRODUCTORY CHAPTERS

(Continued)

24

3. ALCOHOL AND WOMEN

TABLE 3.4 (Continued) Pregnancy complications

Alcohol use among women during pregnancy increases the risk of pregnancy complications and neonatal death, and heightens the odds of poor cognitive and behavioral outcomes for prenatally exposed children.

the research base is very limited, as women historically have been underrepresented in studies of alcohol use disorder. As a result, the underlying mechanisms that account for these differences are not well understood, nor are the optimal interventions to prevent and treat alcohol-related problems in women (Agabio et al., 2017; Erol & Karpyak, 2015).

SOCIAL CONSEQUENCES Alcohol misuse and addiction are strongly involved in many of the social and safety problems that affect women, including domestic violence, child abuse and neglect, sexual assault, unplanned pregnancies, sexually transmitted diseases, unemployment, poverty, and homelessness. Summary of alcohol’s differential effects on females versus males in terms of biological factors, health effects, and social consequences.

EXPLAINING SEX DIFFERENCES IN NEUROCOGNITIVE EFFECTS OF ALCOHOL Women are more susceptible than men to the neurotoxic effects of alcohol. Hommer, Momenan, Kaiser, and Rawlings (2001) found more significant reductions in brain volume in women (vs men) with an alcohol use disorder, even though the women generally started engaging in heavy drinking later in life and had consumed less alcohol in their lifetimes. Likewise, Momenan et al. (2012) found greater decreases in gray matter volume in the cerebral cortex of women relative to men who had an alcohol use disorder. Schweinsburg et al. (2003) found significantly lower concentrations of the metabolite N-acetylaspartate (indicative of decreased neuronal viability) in the frontal lobe gray matter of women with an alcohol use disorder relative to those without; this difference was not found in men. Clark’s (2007) study of physically healthy young women found decreased cerebral perfusion (blood flow, which reflects brain activity) in the frontal lobe, which controls executive functioning, in women with a history of an alcohol use disorder relative to women without such a history. Maynard et al. (2017) found significantly greater alcohol-induced damage to the hippocampus, and consequent cognitive impairment, in females relative to males.

RESEARCH LIMITATIONS Despite clear evidence of biological sex differences related to alcohol consumption and its consequences,

IMPROVING PREVENTION FOR GIRLS AND WOMEN To prevent alcohol use disorder, it is critical that girls and women, and the important people in their lives, understand the sex differences that influence risk and contribute to adverse consequences of alcohol misuse. The earlier prevention starts, the lower the risk of alcohol misuse and progression to alcohol use disorder. During early adolescence, prevention efforts should focus on reducing experimentation, increasing knowledge, developing accurate and healthy attitudes and beliefs about alcohol and other substance use, and helping girls navigate messages from peers and the media about the benefits of substance use. Research repeatedly shows that parents have the strongest influence over their daughters’ substance-related attitudes and behaviors. Close monitoring of girls’ friends and whereabouts, having open and honest communication, and parenting in a firm, but supportive, manner all are protective against alcohol misuse and associated problems in children. Other key sources of influence on girls’ risk for developing an alcohol use disorder include peers, physicians, teachers, clergy, and community leaders (The National Center on Addiction & Substance Abuse, 2011). Because alcohol use disorder typically emerges in young adulthood or adulthood, it is important that health care professionals, family, friends, and employers are equipped to identify signs of risk (including a family history of alcohol use disorder, a history of abuse and violence, depression, anxiety, or other mental health conditions) and to help women get the care and support they need for these problems. While any venue frequented by women offers opportunities for prevention and early intervention, including health care professionals offices, educational settings, churches, support groups, and domestic violence or homeless shelters, those offering services in these sites will require training in the prevention and identification of alcohol use disorder, and in knowing how to respond effectively. Tax and regulatory policies that aim to reduce the accessibility of alcohol to young people also are effective prevention strategies. Increasing taxes on alcohol

I. INTRODUCTORY CHAPTERS

NEEDED CULTURAL, ENVIRONMENTAL, AND SOCIETAL CHANGES

is associated with lower levels of alcohol use, particularly among young people and pregnant women (National Institute on Alcohol Abuse & Alcoholism, 2000). Limiting the density of alcohol retail outlets, prohibiting low-price alcohol promotions such as “ladies’ nights,” banning alcohol advertising on college campuses or youth-oriented magazines, and ensuring consistent enforcement of alcohol policies are effective in reducing underage and excessive drinking.

EARLY DIAGNOSIS AND TREATMENT TAILORED TO GIRLS AND WOMEN Health professionals are best positioned to educate girls and women about the risks of alcohol use, screen for signs of risk, intervene early with those who have symptoms, and refer those in need to professional treatment. Despite this, many screening and assessment tools focus on issues that are more relevant to risk in males—such as legal and job troubles rather than domestic violence or family conflict. Measures of alcohol use frequency and quantity rarely are sensitive to sex differences in metabolism and other relevant biological and sociocultural factors associated with alcohol misuse. As such, it is critical that screening and assessment tools, as well as treatment protocols, be tailored to the unique risks and vulnerabilities of women, including a reduced likelihood of seeking treatment or having social support to seek treatment, and a greater likelihood of having cooccurring mental health disorders (Ceylan-Isik et al., 2010). Sterling, Kline-Simon, Wibbelsman, Wong, & Weisner (2012) found that primary care physicians are more likely to screen boys than girls for alcohol use disorder. Likewise, McKnight-Eily et al. (2017) found that adult females were significantly less likely than adult males to be asked by health care providers about their alcohol use or advised to reduce their drinking. Given the higher risk of adverse consequences from alcohol use among women relative to men (at the same level of drinking), health professionals should routinely advise women who drink about this differential risk in the development of health problems (Agabio et al., 2017). Women are less likely to seek treatment than men (Agabio et al., 2017), but if they do seek treatment, they tend to do so sooner after developing an alcohol use disorder (Erol & Karpyak, 2015). This may be due in part to a “telescoping effect,” whereby women generally move more rapidly than men from initiation of regular alcohol use to problem use (Johnson, Richter, Kleber, McLellan, & Carise, 2005).

25

There is evidence that when treatment programs offer services that meet the needs of women, women with alcohol use disorder tend to achieve better outcomes than women who do not receive dedicated services that take into account the unique needs of women in treatment (Agabio et al., 2017). Women respond similarly to men to behavioral and medication treatments for alcohol use disorder, although they may be more likely than men to experience adverse side effects from certain medications (Erol & Karpyak, 2015).

BARRIERS TO TREATMENT FOR WOMEN Not only are women less likely than men to be screened for an alcohol use problem, diagnosed with an alcohol use disorder, seek help, receive treatment, or have treatment options tailored to their needs, but they also are more likely to face barriers to accessing and completing treatment (Brienza & Stein, 2002). Common barriers include missed diagnoses by medical professionals, lifestyle constraints such as competing responsibilities and childcare needs, limited financial resources or insurance coverage, inadequate social support, lack of knowledge about how and where to access quality treatment, and greater societal barriers such as stigma, shame, and discrimination (Agabio et al., 2017; Foster & Richter, 2013).

NEEDED CULTURAL, ENVIRONMENTAL, AND SOCIETAL CHANGES The long-existing gender gap in alcohol use and its associated harms is closing around the world, with women—especially young adult females—drinking more than they had in the past and, in some age groups, more than their male counterparts (Slade et al., 2016). A recent national study in the United States found that reports of past-year alcohol use, high-risk drinking, and alcohol use disorder all have increased over the past decade, with significantly greater increases among women than men (Grant et al., 2017). This is despite a better understanding today than ever before of the science of addiction and the harmful social and health consequences of alcohol misuse. To reduce the prevalence of risky and disordered alcohol use among women, there needs to be a sea change in the culture of drinking in which alcohol misuse no longer is glorified and promoted by the media, on college campuses, or in neighborhood bars, and where alcohol policies and regulations reflect the tremendous cost to taxpayers of the health and social consequences of alcohol misuse and addiction.

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26

3. ALCOHOL AND WOMEN

To effectively prevent alcohol misuse and disorder in girls and women, a comprehensive, long-term public health approach is needed that starts in childhood and addresses all the areas of influence on a girl or woman’s life that can increase risk. These include influences from parents, peers, schools, communities, the media, and the alcohol industry, which shape public perceptions about the norms surrounding drinking. Larger public health and public policy interventions are needed to address many of the underlying risks associated with alcohol use disorder in women, such as domestic violence, economic instability, depression and anxiety, and work and family-related stress. Policy interventions that involve increased taxes and regulation of alcohol marketing and internet sales can reduce access to, and the glorification of, excessive alcohol use. Much of the needed change lies at the feet of the health care system. Medical schools, residency training programs, licensing boards, health care providers, and insurers must work together to ensure that health care providers are well-trained and incentivized to screen for, diagnose, and treat alcohol use disorder among women. Treatment programs should accommodate the transportation and childcare needs of parenting women who face numerous hurdles to accessing and staying in treatment, and include a family component to boost both social support and the odds of treatment adherence.

IMPLICATIONS FOR TREATMENT: WHAT IS NEEDED TO REDUCE ALCOHOL MISUSE AND ADDICTION IN GIRLS AND WOMEN Effectively addressing alcohol misuse and alcohol use disorder in women requires fundamental changes in the way the public views these problems and the way the health care profession, government, and other service providers respond to them. To prevent and reduce alcohol use disorder in girls and women, a comprehensive approach is needed that addresses sexbased differences in the motivations for use, consequences of use, barriers to treatment, and treatment needs. An approach is also needed that elevates public awareness about alcohol use disorder and how best to prevent and treat it. Services that are tailored to women must be available and accessible to those who need it. Unless we commit to making significant, health-promoting changes in public policy and health care practice, addiction will continue to be a primary preventable health problem that takes a significant toll on girls, women, families, communities, and scarce government resources.

MINI-DICTIONARY OF TERMS High-risk drinking For women, drinking four or more standard drinks (a drink equals 14 g of pure alcohol) on any day at least weekly during the prior 12 months. Early-onset drinkers Those who reported using alcohol for the first time prior to age 16. Fetal Alcohol Spectrum Disorder A set of conditions that characterizes some children of women who drank alcohol during pregnancy, including growth deficiency, facial malformations, and cognitive deficiencies. Alcohol dehydrogenase A metabolizing enzyme that breaks down alcohol in the liver and stomach, keeping it from entering the bloodstream. Telescoping The phenomenon whereby women generally move more rapidly than men from initiation of regular alcohol use to an alcohol use disorder.

KEY FACTS How Alcohol Affects Women • Impairment from alcohol occurs among females at an earlier stage of drinking and after having consumed less alcohol than males. • Women metabolize alcohol less efficiently because they have decreased activity of the enzyme alcohol dehydrogenase, which breaks down alcohol in the liver and stomach, keeping it from entering the bloodstream. • Women’s bodies generally contain less water and more fatty tissue than the bodies of men of similar size, so they maintain higher concentrations of alcohol in their blood; blood alcohol levels are higher in women than in men after ingesting the same amount of alcohol. • As a result, women tend to get intoxicated faster and have more intense hangovers than men, even when drinking the same amount of alcohol. • Women also show more cognitive impairment, sedation, and self-reported intoxication compared to men, and higher odds of alcohol-related injury. • Women with alcohol use disorder are at greater risk than are men for alcohol-related suicide, accidents, heart disease and other circulatory system disorders, cirrhosis of the liver, hepatitis, cancer, and fertility impairment. • Women tend to develop these problems sooner and at lower levels of drinking than men, and the deleterious effects of alcohol, including adverse alcohol medication interactions, become more severe as women age, relative to men. • Women who engage in excessive drinking or who have an alcohol use disorder demonstrate more damage to the brain relative to men, specifically in the areas involved in memory, motor control, and sensory perception.

I. INTRODUCTORY CHAPTERS

REFERENCES

SUMMARY POINTS • The prevalence of alcohol use, misuse, and disorder has increased significantly more among adult females than among adult males over the past decade. • Despite this, alcohol misuse and disorder among women too often go unrecognized and untreated, resulting in unnecessary pain and suffering and costly consequences. • Alcohol addiction is a leading preventable contributor to some of the most common causes of death among women, including heart disease and cancer, and exacerbates many other health conditions including respiratory disease, infertility, pregnancy complications, depression, anxiety, and eating disorders. • Compared to males, females tend to have different motivations for using alcohol, progress from alcohol use to addiction at lower levels of use and more quickly, and suffer the consequences of alcohol misuse sooner and more intensely. • Sex differences are not sufficiently taken into account in addiction prevention, early intervention, and treatment.

References Agabio, R., Pisanu, C., Gessa, G. L., & Franconi, F. (2017). Sex differences in alcohol use disorder. Current Medicinal Chemistry, 24(24), 2661 2670. Available from https://doi.org/10.2174/ 0929867323666161202092908. Brienza, R. S., & Stein, M. D. (2002). Alcohol use disorders in primary care: Do gender-specific differences exist? Journal of General Internal Medicine, 17(5), 387 397. Center for Behavioral Health Statistics and Quality. (2017). 2016 National Survey on Drug Use and Health: Detailed tables. Retrieved from Substance Abuse and Mental Health Services website: ,https://www.samhsa.gov/data/sites/default/files/NSDUHDetTabs-2016/NSDUH-DetTabs-2016.pdf.. Ceylan-Isik, A. F., McBride, S. M., & Ren, J. (2010). Sex difference in alcoholism: Who is at a greater risk for development of alcoholic complication? Life Sciences, 87(5 6), 133 138. Available from https://doi.org/10.1016/j.lfs.2010.06.002. Clark, C. P. (2007). Decreased perfusion in young alcohol-dependent women as compared with age-matched controls. American Journal of Drug and Alcohol Abuse, 33(1), 13 19. Erol, A., & Karpyak, V. M. (2015). Sex and gender-related differences in alcohol use and its consequences: Contemporary knowledge and future research considerations. Drug and Alcohol Dependence, 156, 1 13. Available from https://doi.org/10.1016/j. drugalcdep.2015.08.023. Foster, S. E., & Richter, L. (2013). Substance use disorders. In R. T. Senie (Ed.), Epidemiology of women’s health (pp. 249 256). Burlington, MA: Jones and Bartlett Learning. Grant, B. F., Chou, S. P., Saha, T. D., Pickering, R. P., Kerridge, B. T., Ruan, W. J., . . . Hasin, D. S. (2017). Prevalence of 12-month alcohol use, high-risk drinking, and DSM-IV alcohol use disorder in the United States, 2001 2002 to 2012 2013: Results from the National Epidemiologic Survey on Alcohol and Related

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Conditions. JAMA Psychiatry, 74(9), 911 923. Available from https://doi.org/10.1001/jamapsychiatry.2017.2161. Grant, B. F., Saha, T. D., Ruan, W. J., Goldstein, R. B., Chou, S. P., Jung, J., . . . Hasin, D. S. (2016). Epidemiology of DSM-5 drug use disorder: Results from the national epidemiologic survey on alcohol and relation conditions-III. JAMA Psychiatry, 73(1), 39 47. Available from https://doi.org/10.1001/jamapsychiatry.2015.2132. Green, P. P., McKnight-Eily, L. R., Tan, C. H., Mejia, R., & Denny, C. H. (2016). Vital signs: Alcohol-exposed pregnancies—United States, 2011 2013. Morbidity and Mortality Weekly Report (MMWR), 65(4), 91 97. Available from https://doi.org/10.15585/mmwr. mm6504a6. Heath, A. C., Bucholz, K. K., Madden, P. A. F., Dinwiddie, S. H., Slutske, W. S., Bierut, L. J., . . . Martin, N. G. (1997). Genetic and environmental contributions to alcohol dependence risk in a national twin sample: Consistency of findings in women and men. Psychological Medicine, 27(6), 1381 1396. Hommer, D. W. (2003). Male and female sensitivity to alcoholinduced brain damage. Alcohol Research and Health, 27(2), 181 185. Hommer, D. W., Momenan, R., Kaiser, E., & Rawlings, R. R. (2001). Evidence for a gender-related effect of alcoholism on brain volumes. American Journal of Psychiatry, 158(2), 198 204. Jenkins, M. B., Agrawal, A., Lynskey, M. T., Nelson, E. C., Madden, P. A., Bucholz, K. K., & Heath, A. C. (2011). Correlates of alcohol abuse/dependence in early-onset alcohol-using women. American Journal on Addictions, 20(5), 429 434. Available from https://doi. org/10.1111/j.1521-0391.2011.00151.x. Johnson, P. B., Richter, L., Kleber, H. D., McLellan, A. T., & Carise, D. (2005). Telescoping of drinking-related behaviors: Gender, racial/ethnic and age comparisons. Substance Use and Misuse, 40 (8), 1139 1151. Maynard, M. E., Barton, E. A., Robinson, C. R., Wooden, J. I., & Leasure, J. L. (2017). Sex differences in hippocampal damage, cognitive impairment, and trophic factor expression in an animal model of an alcohol use disorder. Brain Structure and Function. Available from https://doi.org/10.1007/s00429-017-1482-3 [Epub ahead of print]. McKnight-Eily, L. R., Okoro, C. A., Mejia, R., Denny, C. H., HigginsBiddle, J., Hungerford, D., . . . Sniezek, J. E. (2017). Screening for excessive alcohol use and brief counseling of adults—17 states and the District of Columbia. Morbidity and Mortality Weekly Report, 66(12), 313 319. Available from https://doi.org/ 10.15585/mmwr.mm6612a1. Momenan, R., Steckler, L. E., Saad, Z. S., van Rafelghem, S., Kerich, M. J., & Hommer, D. W. (2012). Effects of alcohol dependence on cortical thickness as determined by magnetic resonance imaging. Psychiatry Research, 204(2 3), 101 111. Available from https:// doi.org/10.1016/j.pscychresns.2012.05.003. National Institute on Alcohol Abuse and Alcoholism. (2000). 10th special report to the U.S. Congress on alcohol and health. Retrieved from the National Institute on Alcohol Abuse and Alcoholism website: ,https://pubs.niaaa.nih.gov/publications/10report/10thspecialreport.pdf.. National Institute on Alcohol Abuse and Alcoholism. (2015). Women and alcohol. Retrieved from National Institute on Alcohol Abuse and Alcoholism website: ,https://pubs.niaaa.nih.gov/publications/womensfact/womensFact.pdf. Nolen-Hoeksema, S., & Hilt, L. (2006). Possible contributors to the gender differences in alcohol use and problems. The Journal of General Psychology, 133(4), 357 374. Office of the Surgeon General. (2016). Facing addiction in America: The Surgeon General’s report on alcohol, drugs, and health. Retrieved from U.S. Department of Health and Human Services website: ,https://addiction.surgeongeneral.gov..

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Pohjalainen, T., Rinne, J. O., Nagren, K., Syvalahti, E., & Hietala, J. (1998). Sex differences in the striatal dopamine D-2 receptor binding characteristics in vivo. American Journal of Psychiatry, 155, 768 773. Richter, L., Pugh, B. S., Peters, E., Vaughan, R. D., & Foster, S. E. (2016). Underage drinking: Prevalence and correlates of risky drinking measures among youth aged 12 20. American Journal of Drug and Alcohol Abuse, 42(4), 385 394. Available from https:// doi.org/10.3109/00952990.2015.1102923. Schuckit, M. A., Smith, T. L., Kalmijn, J., Tsuang, J., Hesselbrock, V., & Bucholz, K. (2000). Response to alcohol in daughters of alcoholics: A pilot study and a comparison with sons of alcoholics. Alcohol and Alcoholism., 35(3), 242 248. Schweinsburg, B. C., Alhassoon, O. M., Taylor, M. J., Gonzalez, R., Videen, J. S., Brown, G. G., . . . Grant, I. (2003). Effects of alcoholism and gender on brain metabolism. American Journal of Psychiatry, 160(6), 1180 1183. Slade, T., Chapman, C., Swift, W., Keyes, K., Tonks, Z., & Teesson, M. (2016). Birth cohort trends in the global epidemiology of alcohol use and alcohol-related harms in men and women: Systematic review and metaregression. BMJ Open, 6(10), e011827. Available from https://doi.org/10.1136/bmjopen-2016-011827.

Sterling, S., Kline-Simon, A. H., Wibbelsman, C., Wong, A., & Weisner, C. (2012). Screening for adolescent alcohol and drug use in pediatric health-care settings: Predictors and implications for practice and policy. Addiction Science and Clinical Practice, 7, 13. Available from https://doi.org/10.1186/1940-0640-7-13. The National Center on Addiction and Substance Abuse (CASA). (2006). Women under the influence. Baltimore, MD: Johns Hopkins University Press. The National Center on Addiction and Substance Abuse. (2011). Adolescent substance use: America’s #1 public health problem. New York: The National Center on Addiction and Substance Abuse. Wichstrøm, L. (2001). The impact of pubertal timing on adolescents’ alcohol use. Journal of Research on Adolescence, 11(2), 131 150. Zeisser, C., Stockwell, T. R., Chikritzhs, T., Cherpitel, C., Ye, Y., & Gardner, C. (2013). A systematic review and meta-analysis of alcohol consumption and injury risk as a function of study design and recall period. Alcoholism, Clinical and Experimental Research, 37 (Suppl. 1), E1 E8.

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C H A P T E R

4 ADH and ALDH Polymorphisms in Alcoholism and Alcohol Misuse/Dependence Meera Vaswani WHO Collaborative National Drug Dependence Treatment Center, All India Institute of Medical Sciences, New Delhi, India

LIST OF ABBREVIATIONS ADH ALDH CYP2E1 FAS MAF

resulting in toxic intermediates plays a causative role in alcohol metabolism. Alcohol is primarily metabolized in the liver by two rate-limiting reactions. In order to understand alcohol metabolism, it is important to discuss relevant biological mechanisms and genomic pathways. In humans, the pathways responsible for eliminating alcohol are found primarily in the liver by the following enzymes: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), cytochrome P450 (CYP2E1) and catalase (Zakhari, 2006).

alcohol dehydrogenase aldehyde dehydrogenase cytochrome P450 2E1 fetal alcohol syndrome Minor Allele Frequency

INTRODUCTION Alcohol, one of the greatest social, economic, and health problems worldwide, is a widely used psychoactive substance associated with various antisocial traits and organ dysfunctions. Alcoholism, a function of the interplay of genetic and environmental factors, is a complex trait with significant genetic influences exhibiting heterogeneity. Alcohol dependence (AD) is a serious social and public health concern globally, as it leads to development of a plethora of health complications. Development of AD, earlier considered as a lifestyle problem, is also influenced/governed by individuals’ genetic constitution. Although genomic pathways contributing to alcohol susceptibility have been intensely researched, its progress has been rather slow. Interindividual variation in alcohol absorption and metabolism is, in part, due to allelic variants in specific genes coding for alcohol-metabolizing enzymes.

OXIDATIVE PATHWAY In the oxidative pathway, 95% 98% of alcohol is metabolized to acetaldehyde by ADH. Acetaldehyde, a highly volatile and toxic by-product that can be damaging to cells and tissues, is further metabolized in the liver by ALDH into acetate which escapes into the blood where it ultimately gets oxidized into carbon dioxide (Heier, Xie, & Zimmermann, 2016). ADH and ALDH exist in multiple isozymes which differ in their kinetic properties. As acetaldehyde is toxic and differs according to functional enzymatic genetic polymorphisms, it is important to consider functional genetic polymorphisms of alcohol-metabolizing enzymes (ADH and ALDH). The microsomal system (MEOS) and catalase are also responsible for the oxidative metabolism of alcohol (Zakhari, 2006). ADH, ALDH, cytochrome P450 2E1 (CYP2E1), and catalase all contribute to oxidative metabolism of alcohol. ADH present in the cytosol converts alcohol into acetaldehyde. This reaction involves an intermediate

ALCOHOL METABOLISM Alcohol is metabolized by oxidative and nonoxidative pathways. Metabolic conversion of alcohol Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00004-0

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© 2019 Elsevier Inc. All rights reserved.

30

4. ADH AND ALDH POLYMORPHISMS IN ALCOHOLISM AND ALCOHOL MISUSE/DEPENDENCE

Peroxisomes H2O2

H2O

Ethanol mM

ADH

NAD+

1 Acetaldehyde µM

Acetate mM

3 NAD+

3 NADH

Cytosol

NADH

2

Mitochondria

Result:

CYP2E1 2 NADPH + H+ + O2

ALDH2

Circulation

Catalase

NADPH+ + 2 H2O Microsomes

1

Acetaldehyde adducts formation

2

Increase ROS formation

3

Increase NADH:NAD+ ratio

FIGURE 4.1 Oxidative pathways of alcohol metabolism. Source: From Zakhari, S. (2006). Overview: How is alcohol metabolized by the body? Alcohol Health and Research World, 29(4), 245. https://pubs.niaaa.nih.gov/publications/arh294/245-255.htm.

Tissue injury FAEE synthase

Fatty acid ethyl ester (FAEE) Ethanol

Phosphatidyl ethanol

PLD

FIGURE 4.2

Oxidative pathway of alcohol. Source: From Herna´ndez, J. A., Lo´pez-Sa´nchez R. C., & Rendo´n-Ramı´rez, A. (2016). Lipids and oxidative stress associated with ethanol-induced neurological damage, Oxidative Medicine and Cellular Longevity, 1543809.

carrier of electrons, nicotinamide adenine dinucleotide (NAD 1 ), which is reduced by two electrons to form NADH (Figs. 4.1 and 4.2).

Nonoxidative Pathways The nonoxidative metabolism of alcohol is minimal, but its products may have pathological and diagnostic relevance. Alcohol is nonoxidatively metabolized by at least two pathways. (1) Alcohol reacts with fatty acids to form molecules called fatty acid ethyl esters (FAEEs); and (2) The other nonoxidative pathway

Interferes with PLD-dependent signalling?

FIGURE 4.3 Ethanol is nonoxidatively metabolized by two pathways. A reaction catalyzed by the enzyme fatty acid ethyl ester (FAEE) synthase leads to the formation of molecules known as FAEEs. A reaction with the enzyme phospholipase D (PLD) results in the formation of a phospholipid known as phosphatidyl ethanol. Source: From Zakhari, S. (2006). Overview: How is alcohol metabolized by the body? Alcohol Health and Research World, 29(4), 245. https://pubs. niaaa.nih.gov/publications/arh294/245-255.htm.

results in the formation of a fat molecule containing phospholipid, known as phosphatidyl ethanol (Fig. 4.3). FAEEs are detectable in serum and other tissues after alcohol ingestion and persist long after alcohol is eliminated. The role of FAEEs in alcoholinduced tissue damage remains to be further evaluated. However, ethyl glucuronide, ethyl sulfate, and phosphatidyl ethanol are also formed due to nonoxidative pathways (Zakhari, 2006). Oxidative and nonoxidative pathways of alcohol metabolism are interrelated. Inhibition of alcohol oxidation by compounds that inhibit ADH, CYP2E1, and

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31

ALCOHOL DEHYDROGENASE POLYMORPHISM

TABLE 4.1 Drinking Patterns and Alcohol-Related Adverse Consequences in Different Populations Variable

High risk

Low risk

References

Drinking patterns and consequences

Caucasians

Asians

Chartier and Caetano (2010)

Heavy drinking as compared to Whites

Hispanics have higher rates

Asians have lower rates Chartier and Caetano (2010)

Health and Social problems from drinking

More in Hispanics and Black Americans

Less in Whites and Asians

Chartier and Caetano (2010)

Alcohol use disorder

High in Korean ancestry

Low in Chinese ancestry

Luczak , Wall, Cook, Shea, and Carr (2004)

catalase results in an increase in the nonoxidative metabolism and increased production of FAEEs in the liver and pancreas (Werner et al., 2002)

ALCOHOL DEHYDROGENASE AND ALDEHYDE DEHYDROGENASE POLYMORPHISM Alcoholism is a common disease resulting from the complex interaction of genetic, social, and environmental factors. It is multifactorial, polygenic disorder where complex gene gene and gene environment interactions are involved. Epidemiological studies (Table 4.1) have demonstrated that drinking patterns and the prevalence of alcohol-related adverse consequences, including alcohol use disorder (AUD), differ substantially among racial/ethnic groups (Wall, Luczak, & Sturmho¨fel, 2016). AD is a function of interplay of genetic and environmental factors where individual differences in metabolism lead to variations in risk. The pharmacokinetics of alcohol metabolism influences the risk for AD. Genetic polymorphisms, particularly those of the alcohol-metabolizing enzymes ADH and ALDH have been largely implicated in the development of AD. Genes encoding alcohol-metabolizing enzymes are among the largest genetic associations and their allelic variants contribute to interindividual variation in alcohol absorption and metabolism. In humans, ADH and ALDH have strong associations with alcoholism and are the principal enzymes which have been commonly been studied due to their relevance to alcohol metabolism (Wall, Carr, & Ehlers, 2003). Functional polymorphisms in genes encoding ADH and ALDH enzymes influence the rate of synthesis and metabolism of acetaldehyde, the toxic metabolite of alcohol. The presence/absence of these polymorphisms could modulate the probability of developing AD and confer protection/susceptibility to alcohol abuse and alcohol-related complications. The most widely studied functional polymorphisms in the alcohol-metabolic pathway are

the ADH1B (Arg47His) and ALDH2 (Glu487Lys) polymorphisms. Although the role of ADH1B and ALDH2 genes in susceptibility to alcoholism were discovered individually, they have been shown to act additively when they co-occur. The ADH1B 2 and ALDH2  2 alleles raise the levels of acetaldehyde by increasing the rate of synthesis and decreasing the rate of metabolism, respectively; thus, interacting additively, but not synergistically (Vaswani, Prasad, & Kapur, 2009).

ALCOHOL DEHYDROGENASE POLYMORPHISM ADH converting alcohol into acetaldehyde represents the initial step in alcohol metabolism. ADH1A (ADH1), ADH1B (ADH2), ADH1C (ADH3)—referred to as class 1 ADH isoforms (mainly expressed in liver and contribute about 70% of the total alcohol oxidizing capacity)—ADH4 (class II), ADH5 (class III), ADH7 (Class IV), and ADH6 (Class V) are the seven human ADH genes on chromosome 4 q21 q24 (Zakhari, 2006). ADH1B and ADH1C, known to have functional polymorphisms in their coding regions, have been studied extensively (Lee, Hoog, & Yin, 2004). Although, ADH2 and ADH3 genes are located in tandem on chromosome 4 their polymorphisms at these two loci do not occur independently (Yasunami, Kikuchi, Sarapat, & Yoshida, 1990). At the protein level, the allelic series for ADH1B is generated by a variation at two different sites at the genomic level. The ADH1B 1 allele is composed of 47Arg and 369Arg; the ADH1B 2 allele is composed of 47His and 369Arg; and the ADH1B 3 allele is composed of 47Arg and 369Cys (Vaswani et al., 2009) (Table 4.2). ADH2 (ADH1B) and ADH3 (ADH1C) on chromosome 4 and ALDH gene (ALDH2) on chromosome 12 have been reported to exhibit functional polymorphisms influencing variation in alcohol metabolism, variability in alcohol response, and differences in vulnerability for AD. However, ADH2 ( 1,  2,  3), ADH3 ( 1,  2), and ALDH2 ( 1,  2) have also been

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4. ADH AND ALDH POLYMORPHISMS IN ALCOHOLISM AND ALCOHOL MISUSE/DEPENDENCE

TABLE 4.2 Human Alcohol Dehydrogenase Isoenzymes Gene nomenclature Class

New

Former

I

ADH1A 

ADH1

ADH1B 1

ADH2 1

ADH1B 2

ADH2 2

ADH1B 3

ADH2 3

ADH1C 1

ADH3 1

ADH1C 2

ADH3 2

II

ADH4

ADH4

III

ADH5

ADH5

IV

ADH7

ADH7

V

ADH6

ADH6

associated with alcoholism and AD. (Wall et al., 2003). Pharmacokinetic and pharmacodynamic effects of alcohol and its metabolite (acetaldehyde) are important determinants that not only influence drinking behavior but vulnerability to AD as well (Chen, Peng, Wang, Tsao, & Yin 2009). Among all classes of ADH gene, ADH1B gene has largest effect size with AD. Studies have identified three alleles, ADH1B 1, ADH1B 2, and ADH1B 3 with both the  3 and  2 alleles demonstrating a protective association with AD and related phenotypes. The ADH1B and ADH1C genes have several variants with differing levels of enzymatic activity (Ehlers, Liang, & Gizer, 2012). Significant associations for the ADH1B 2 allele and AD have been found in Asian populations (Luczak, Glatt, & Wall, 2006a) as well as in European and African-American populations (Bierut et al., 2012). The functional variants of allele ADH1B 2 (His47) and ADH1B 3 (Cys369) with high enzyme activity leads to rapid conversion of alcohol to acetaldehyde. However, high enzyme activity of ADH1B 2 (ADH2 2, located in exon 3 of ADH2), resulting in an arginine to histidine amino acid change and ADH1B (ADH2, located in exon 9, harbors the ADH1B 3) resulting in an arginine to cysteine has been found to be associated with lower risk and protective association with AD (Ehlers, Liang, & Gizer, 2012). The ADH1B 2 allele codes for a higher activity enzyme as compared to ADH1B 1 allele is known to influence drinking behavior, resulting in protection from alcoholism (Vaswani et al., 2009). Disease risk associated with the ADH1B 2/  2 ALDH2 1/ 1genotype is about half of that associated with the ADH1B 1/ 2 ALDH2 1/ 1, suggesting that the protection afforded by the ADH1B 2 allele may be independent of that afforded by ALDH2 (Chen et al.,

1999). A very low frequency of ADH1B 2 (,0.001) in Indian subjects indicating a selection pressure operating against the ADH1B 2 allele could be due to its inability/redundancy to protect the Indian population from AD (Vaswani et al., 2009). ADH1C (ADH3), a highly polymorphic gene is involved in the alcohol metabolism. ADH3 1/ 1 genotype encoding for fast metabolizing enzyme metabolizes alcohol at a much faster rate resulting in rapid formation of acetaldehyde (Edenberg, 2007). Therefore, conversion of acetaldehyde to acetate needs to be at same pace to avoid the malfunctioning of proteins (that may cause acetaldehyde accumulation resulting in disease) and to maintain dynamic homeostasis (Vonlaufen, Wilson, Pirola, & Apte 2007). Based on the kinetic properties of ADH gene polymorphisms Wall et al. suggested the mechanism underlying the associations with alcoholism. Isoenzymes encoded by the ADH2 2, ADH2 3, and ADH3 1 alleles lead to fast metabolism of alcohol and subsequent rapid production of acetaldehyde compared with isoenzymes encoded by ADH2 1 and ADH3 2. This, in turn, leads to increased alcohol sensitivity and decreased levels of alcohol consumption in individuals with the ADH2 2, ADH2 3, or ADH3 1 alleles. However, protective associations of ADH2 2 in South Africans of mixed ancestry and ADH2 3 in African-American children with fetal alcohol syndrome (FAS) has been reported. The mechanism by which these alleles protect against alcoholism and FAS is based on the rapid production of acetaldehyde, increased sensitivity to alcohol, and lower levels of alcohol consumption (Wall et al., 2003). However, ADH1B 1 was found to be monomorphic, with the nearly complete absence of the ADH1B 2 allele in Indian population (Vaswani et al., 2009). Although multiple genetic markers of ADH genes have been identified for AD in different ethnic populations, Park et al. (2013) in their study on extended genetic effects of ADH cluster genes with 90 SNPs reported significant association of rs1229984 (of ADH1B) with AD. However, subsequent conditional analyses revealed that all positive associations of other ADH genes in the cluster disappeared, suggesting that rs1229984 might be the sole functional genetic marker tracking the genetic effects of the risk of AD in the ADH gene cluster region. In Irish sample, rs1229984 (Arg47His in exon3) with very low minor allele frequency (0.006) distinguished ADH1B 1 from ADH1B 2. However, despite its low frequency, this SNP showed consistent association with AD and several other endophenotypes in Caucasians (Kuo et al., 2008). Edenberg, Xuei, and Chen (2006) reported differences in allele frequency (in all seven ADH genes) in European Americans and African-Americans, where

I. INTRODUCTORY CHAPTERS

ALDEHYDE DEHYDROGENASE POLYMORPHISM

ADH4 was associated with AD in European Americans. A protective effect of ADH1B 3 has been shown to be restricted to populations of African descent (Han et al., 2005). However, earlier evidence showing ADH1B 2, ADH1C 1, and ALDH2 2 are rare outside the Asian or Native Americans, is indicative of limited involvement of these genes in Caucasian populations. Although all ADH genes except ADH7 are in high linkage disequilibrium (LD) with each other, but significant association of ADH1A, 1B, and 1C with alcohol metabolism may provide insight into the risk of AD in Caucasians. These studies highlight the importance of evaluating protective factors in different populations with high rates of AD and alcoholrelated behavior (Kuo et al., 2008). The functional variants of allele ADH1B 2 (His47) and ADH1B 3 (Cys369) have high enzyme activity and unusually rapid conversion of alcohol into acetaldehyde. These variants have markedly different frequencies in different ethnic groups. Meta-analysis for ADH1B 2 comparing homozygous versus heterozygous genotypes of ADH1B 2 with AD exhibited an odds ratio of five and two in Han-Chinese and Japanese and Europeans respectively (Whitfield, 2002). Positive association of ADH1B 3 with AD has been observed in Africans and Native Americans (Ehlers, Gilder, Harris, & Carr 2001; Wall et al., 2003). Protective effects of ADH1C 1 are inconsistent in Asians and Native Americans. With strong LD between ADH1B 2 and ADH1C 1, it is not clear whether there is an independent effect of ADH1C on AD. (Kuo et al., 2008). Earlier studies suggested that the ADH7 gene mainly expressed in the upper digestive tract has an epistatic effect with ADH1B for protection against AD in Taiwanese-Han and European populations. (Han et al., 2005; Luo, Kranzler, Zuo, Wang, Schork & Gelernter, 2006b).

ALDEHYDE DEHYDROGENASE POLYMORPHISM Ingested alcohol is mostly metabolized in the liver by the successive action of ADH and ALDH. Two isozymes of ALDH; cytosolic ALDH1 and mitochondrial ALDH2 are responsible for acetaldehyde metabolism. The most significant genetic polymorphism is in the ALDH2 gene, which results in the allelic variants: ALDH2 1 (the normal allele) and ALDH2 2 (virtually inactive) (Zakhari, 2006; Crabb, Matsumoto, Chang, & You, 2004). Acetaldehyde toxicity and its implication for alcoholism, alcohol abuse/dependence are due to deficiency of ALDH enzyme. If acetaldehyde does not metabolize, it interacts with body cells and tissues through the bloodstream and saliva (Crabb, et al.,

33

2004). High concentrations of acetaldehyde lead to adverse reactions, which in turn reduce the probability of heavy drinking. Inherited autosomal codominant individuals with heterozygous or homozygous copies of the ALDH2 2 allele show significant increase in blood acetaldehyde levels leading to severely unpleasant physiological responses referred as a “flush reaction.” The characteristic symptoms include: rapid onset skin vasodilation in the face, neck, and chest region (facial flushing), tachycardia (palpitations), headache, nausea, hypotension, pruritus (itchiness), alcohol-induced asthma, and extreme drowsiness (Zakhari, 2006; Crabb et al., 2004). The intensity of symptoms are variable among individuals with the ALDH2 2 allele in different ethnic populations (Table 4.3). Asian populations are strongly associated with this genetic variation; approximately 50% of Taiwanese, Han-Chinese, and Japanese populations have the ALDH2 2 allelic variant and demonstrate no acetaldehyde metabolizing activity (Zakhari, 2006). Therefore, alcohol expectancies may act as mediators between the biological factors determining physiological consequences of alcoholism (Wall et al., 2016). Genes that code for ALDH enzymes are located on several different chromosomes. According to Vasiliou and Nebert (2005), 19 functional genes and three pseudogenes in the ALDH gene encode ALDH isozymes, but ALDH1 (ALDH1A1, 9q21.13, cytosolic isozyme) and ALDH2 (12q24, mitochondrial isozyme) have been significantly involved in acetaldehyde oxidation. The ALDH2 gene, located on chromosome 12q24, is highly expressed in the liver and stomach where high affinity for acetaldehyde plays a central role in acetaldehyde metabolism. The significant genetic polymorphism in the ALDH2 gene results in the normal allelic variants ALDH2 1 and ALDH2 2, the latter being virtually inactive (Crabb et al., 2004; Zakhari, 2006). The single bp difference (G . A; Glu487Lys) in exon 12 causes the normal allele ALDH2 1 to become a nonfunctional allele (ALDH2 2) which codes for the inactive enzyme (Vaswani et al., 2009). ALDH2 2 encodes a deficient protein subunit with low or no activity resulting in nonmetabolism of ADH-generated acetaldehyde, leading to its accumulation in the body. Consequently, individuals carrying homozygous ALDH2 2 experience acetaldehyde buildup and heightened sensitivity to alcohol, which in turn results in lower positive and higher negative expectancies. Thus, individuals with ALDH2 2 allele are likely to drink less due to unpleasant, aversive, and nonreinforcing effects (Wall, Luczak, Orlowska, & Pandika, 2013, Wall et al., 2005). Alcohol expectancies acting as mediators between the biological factors of alcohol consumption and a person’s actual alcohol use would lead to decreased frequency of alcohol use and binge drinking. Reduced consumption,

I. INTRODUCTORY CHAPTERS

34

4. ADH AND ALDH POLYMORPHISMS IN ALCOHOLISM AND ALCOHOL MISUSE/DEPENDENCE

TABLE 4.3 Frequencies of Alleles Encoding ADH and ALDH Enzymes in Different Populations Allele

rs Number

Frequency in different populations A allele

G allele

European

0.000 0.008 0.992 1.000

Asian

0.739 0.771 0.229 0.261

Sub-Saharan African

0.000

1.000

African-American 0.000

1.000

Mexican

0.11

0.89



ADH1B 3 rs2066702

C allele

T allele

European

1.000

0.000

Asian

1.000

0.000

Sub-Saharan African

0.500 0.783 0.217 0.500

African-American 0.733

0.267

Mexican

0.97

0.03

C allele

T allele



ADH1C 1 rs698 European

0.523 0.527 0.473 0.477

Asian

0.927 0.975 0.025 0.073

Sub-Saharan African

0.938 0.958 0.042 0.062

African-American 0.800

0.200

Mexican

0.26

0.74

C allele

T allele

European

0.000

1.000

Asian

0.110 0.282 0.718 0.890

Sub-Saharan African

0.000

1.000

African-American 0.000

1.000

Mexican

0.98



ALDH2 2 rs671

0.02

dbSNP Database (www.ncbi.nlm.nih.gov/snp).

in turn, leads to fewer alcohol-related adverse consequences and alcohol-related problems (Wall et al., 2016). Luczak, Shea, Hsueh, Chang, Carr, and Wall (2006b) reported on the negative associations of ALDH2 2 with hangovers and blackouts after heavy drinking Although, ALDH2 2 protects against the development of AD, the protection is not complete. Individuals with ALDH2 2 alleles are at lower risk and, consequently, more vulnerable to alcohol-related pathologies, particularly head and neck cancers. Liver disease, pancreatitis, and Alzheimer’s disease are also consistent with the role of acetaldehyde in the pathogenesis of organ damage. Thus, the influence of

ALDH2 2 seems to change over the course of drinking; ALDH2 2 is protective at one stage of alcohol use (i.e., progression to heavy drinking) but becomes a risk factor at another stage; that is, progression to alcoholrelated medical problems (Wall et al., 2016). Prospective studies are needed to determine how gene effects may change over one’s lifespan. Because of a gene 3 gene interaction, both ALDH2 and ADH1B contribute unique protective effects on AD, and the level of protection may be even stronger in conjunction than alone (Wall, 2005; Wall et al., 2013). ALDH1A1 has two genetic variants; ALDH1A1 2 (a 17 bp deletion in the promoter region is present in many populations) and ALDH1A1 3 (a 3 bp insertion in the promoter region) is present only in populations with African descent. Although both have protective effects against AD in African-Americans (Spence et al., 2003), ALDH1A1 2 has been reported to have a protective action in Native Americans (Ehlers, Spence, Wall, Gilder, & Carr, 2004). Sensitivity to alcohol is significantly associated with functional polymorphism, Glu487Lys, and 487Lys (ALDH2 2) allele is responsible for a deficiency in ALDH2 activity. A significant variation in the allele frequency of ALDH2 polymorphism (rs671, Glu487Lys) has been observed across different populations worldwide (Table 4.3). The deficient ALDH2 2 allele is prevalent in Asian populations but extremely rare in non-Asians, and has the strongest protective association with AD (Vaswani et al., 2009). Asians who are homozygous for ALDH2 2 have almost zero risk, whereas heterozygotes are about one-third as likely to be alcoholic compared to those without this allele. According to Wall et al. (2003), the mechanism underlying this association is that the isoenzyme encoded by the ALDH2 2 allele leads to impaired conversion of acetaldehyde to acetate, causing elevated levels of acetaldehyde which, in turn, leads to greater sensitivity to alcohol and lower levels of alcohol consumption. ALDH2 1/ 1 has been reported to be monomorphic in six Indian populations (Bhaskar, et al., 2007). Vaswani et al. (2009) suggested that effects of acetaldehyde leading to higher positive expectancies in individuals with the ALDH2 1/ 2 when compared with the ALDH2 1/ 1 genotype could be due to the development of tolerance to acetaldehyde. However, their observation that ALDH2 2/ 2 individuals with low levels of alcohol consumption, but presumably with high levels of acetaldehyde, strongly implicates acetaldehyde in the causality of AD (Table 4.4). The pharmacokinetic and pharmacodynamic consequences indicate that acetaldehyde, rather than alcohol, is primarily responsible for alcohol sensitivity, suggesting that homozygosity of ALDH2 2 almost protects against AD and that the heterozygosity only

I. INTRODUCTORY CHAPTERS

35

SUMMARY

TABLE 4.4 Causes and Percentage of ADH and ALDH Alleles in Different Populations Allele 

ADH2 2

Cause

Population

References

Low rate of alcoholism

80% N/E Asians, 50%

Osier et al. (2002)

Russians, 40% Caucasians, Infrequent in Jewish 

ADH 2 2 (FAS)

Fast metabolism, increased sensitivity (low alcohol consumption)

SAMA

Viljoen, Carr, Foroud, Brooke, Ramsay, and Li (2001)

ADH2 3

Negative F/H of Alcoholism

30% AA, Low in SAMA,

Viljoen et al. (2001)

Native Americans

ADH2 3

Low risk of alcohol intake/dependence/withdrawal

AA, Japanese, Taiwanese

Osier et al. (1999)

South Western California

Wall et al. (2003)

Indian population 

ADH2 3 (FAS)

Fast metabolism

AA

Jacobson et al. (2000)

ADH3 1

Low risk of alcoholism

80% Asians and AA,

Eng, Luczak, and Wall (2007)

50% Caucasians

Li, Zhao, and Gelernter (2012b)

EA, Brazilians, AA

Luo et al. (2006a), Guindalini et al. (2005)

ADH4

Alcohol dependence

SAMA, South Africans of mixed ancestry; AA, African-American; EA, European Americans.

affords partial protection. (Chen et al., 2009). Frequencies of ALDH 1/ 2 varied from 2.5% to 13% for Japanese, from 10% to 18% for the Han-Chinese (Higuchi, Matsushita, Imazeki, Kinoshita, Takagi, & Kono, 1994), and 16% in Indians (Vaswani et al., 2009) suggest that heterozygosity can only afford partial protection, permitting other biological and socio-cultural factors to influence AD. A significant increase in heart rate, cardiac output, mean velocity of facial artery, and decrease in diastolic blood pressure in ALDH2 2 individuals compared to ALDH2 1 can be attributed to higher blood acetaldehyde levels. Thus, physiological tolerance or innate insensitivity to acetaldehyde buildup following alcohol ingestion may be crucial for the development of alcoholism in individuals homozygous for ALDH2 2. However, the mechanism of interactions between the antagonistic effects of acetaldehyde in developing alcoholism remains largely unknown (Chen et al., 2009).

SUMMARY • Alcoholism is a function of the interplay of genetic and environmental factors. ADH metabolizes alcohol to acetaldehyde; a highly volatile and toxic

by-product that can be damaging to cells and tissues and is further metabolized by ALDH into acetate, which escapes into the blood where it ultimately gets oxidized into carbon dioxide. • The pharmacokinetics of alcohol metabolism influences the risk for alcoholism. ADH and ALDH play an important role, not only in determining acetaldehyde levels and alcohol consumption, but also influence vulnerability to alcoholism. A fast ADH or slow ALDH metabolism leads to elevated acetaldehyde levels, which in turn reduces drinking alcohol. • Genetic polymorphisms of alcohol-metabolizing enzymes ADH and ALDH have been largely implicated in development of alcoholism. The two verified human “addiction genes” encoding for enzymes that catalyze consecutive steps in alcohol metabolism are ADH1B and ALDH2. Allelic variations in genes coding alcohol-metabolizing enzymes cause variation in alcohol absorption and metabolism which, in turn, contribute to variation in AD. • The role of ADH1B and ALDH2 genes in susceptibility to alcoholism has been shown to act additively when they co-occur. The ADH1B 2 and ALDH2  2 alleles raise the levels of acetaldehyde by

I. INTRODUCTORY CHAPTERS

36

•

•

•

•

4. ADH AND ALDH POLYMORPHISMS IN ALCOHOLISM AND ALCOHOL MISUSE/DEPENDENCE

increasing the rate of synthesis and decreasing the rate of metabolism, respectively; thus, interacting additively, but not synergistically A gene gene moderating effect appears to exist between ADH1B 2 and ALDH2 2. Functional variants of ADH1B 2 (His47) and ADH1B 3 (Cys369) have high enzyme activity. ADH1B 2, ADH1B 3, ADH1C 1, and ALDH2 2 alleles have protective associations with AD. Variations in the alcohol-metabolizing enzymes and the genes encoding ADH and ALDH are associated with alcoholism (alcohol-related behaviors and AUD). The ADH1B 2, ADH1C 1, and ALDH2 2 alleles with high prevalence in Asian populations and ADH1B 3 and ADH1C 1 alleles in African populations indicate their contribution to differences in AUD among other ethnic groups where individual and environmental factors play an additional important role. A gene gene moderating effect appears to exist between ADH1B 2 and ALDH2 2; effects of ADH1B 2 may be larger in people of Asian descent who also carry ALDH2 2. Thus, the protective effect seems to vary across environments, while the effects of genotypes are additive. The significant interaction effects between markers in ADH and ALDH genes suggest possible epistatic roles between alcohol-metabolizing enzymes contributing toward the risk of alcoholism.

IMPLICATION FOR TREATMENT Alcoholism is a function of the interplay of genetic and environmental factors. The pharmacokinetics of alcohol metabolism influences the risk for alcoholism. ADH and ALDH play an important role not only in determining acetaldehyde levels and alcohol consumption, but also influence vulnerability to alcoholism. Genetic polymorphisms of alcohol-metabolizing enzymes ADH and ALDH have been largely implicated in the development of alcoholism. Keeping this in mind, the treatment response would be specific for people carrying risk susceptible allele verses those carrying risk protective allele for alcoholism in ADH/ALDH genes

MINI-DICTIONARY OF TERMS • Alcoholism is the most severe form of alcohol abuse and involves the inability to manage drinking habits. It is also commonly referred to as alcohol use disorder.

• Alcohol dehydrogenase: The first enzyme which metabolizes alcohol into acetaldehyde, a highly volatile toxic by-product that can be damaging to cells. • Aldehyde dehydrogenase: This metabolizes acetaldehyde into acetate. • Oxidative pathway: This is where 95% 98% of alcohol consumed is metabolized into acetaldehyde and acetate • Nonoxidative Pathway: This is where metabolism of alcohol is minimal, but its products have pathological and diagnostic relevance.

KEY FACTS About Alcoholism, Alcohol Abuse, and Dependence • Alcohol addiction: loss of control, over consumption, compulsion to drink, and continuation despite knowledge of negative health and other consequences. • Reward and reinforcement have great impact to addiction. • Positive reinforcing effects: rewards are equated with the pleasurable effects. • Negative reinforcing effects: alleviation of an existing aversive state or alleviation of withdrawal. • Genetic variation predisposes individuals to increased craving and loss of control. • ADH2 2 and ALDH2 2 raise levels of acetaldehyde and, thus, interact additively, but not synergistically. • Ingestion of small amounts of alcohol in carriers of ADH2 2 and ALDH2 2 produces an unpleasant reaction characterized by facial flushing, headache, hypotension, palpitations, tachycardia, nausea, and vomiting in an analogous fashion.

SUMMARY POINTS • ADH metabolizes alcohol to acetaldehyde, a highly volatile and toxic by-product which can be damaging to cells and tissues • AD is a function of the interplay of genetic and environmental factors. • The pharmacokinetics of alcohol metabolism influences the risk for alcoholism. ADH and ALDH genes play an important role in influencing vulnerability to alcoholism. • The two outstanding examples of “addiction genes” which encode for enzymes that catalyze consecutive steps in alcohol metabolism are ADH1B and ALDH2. Allelic variations in genes contribute to variation in AD.

I. INTRODUCTORY CHAPTERS

REFERENCES

• Role of ADH1B and ALDH2 genes in susceptibility to alcoholism has been shown to act additively when they co-occur. • The ADH1B 2 and ALDH2  2 alleles raise the levels of acetaldehyde by increasing the rate of synthesis and decreasing the rate of metabolism, respectively; thus, interacting additively, but not synergistically. • Gene gene moderating effect appears to exist between ADH1B 2 and ALDH2 2. • The functional variants of allele ADH1B 2 (His47) and ADH1B 3 (Cys369) have high enzyme activity. • ADH1B 2, ADH1B 3, ADH1C 1, and ALDH2 2 alleles have protective associations and are rare outside Asians or Native Americans. • ADH1B 3 and ADH1C 1 alleles are common in African populations and Native Americans, where individual and environmental factors play an additional important role. • The significant interaction effects between markers in ADH and ALDH genes suggest possible epistatic roles between alcohol-metabolizing enzymes contributing toward the risk of alcoholism.

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4. ADH AND ALDH POLYMORPHISMS IN ALCOHOLISM AND ALCOHOL MISUSE/DEPENDENCE

Luo, X. G., Kranzler, H. R., Zuo, L. J., Wang, S., Schork, N. J., & Gelernter, J. (2006b). Diplotype trend regression analysis of the ADH gene cluster and the ALDH2 gene: Multiple significant associations with alcohol dependence. American Journal of Human Genetics, 78, 973 987. Osier, M. V., Pakstis, A. J., Kidd, J. R., Lee, J. F., Yin, S. J., Ko, H. C., . . . Kidd, K. K. (1999). Linkage disequilibrium at the ADH2 and ADH3 loci and risk of alcoholism. Am J of Hum Genet, 64, 1147 1157. Osier, M. V., Pakstis, A. J., Soodyall, H., Comas, D., Goldman, D., Odunsi, A., . . . Kidd, K. K. (2002). A global perspective on genetic variation at the ADH genes reveals unusual patterns of linkage disequilibrium and diversity. American Journal of Human Genetics, 71(1), 84 99. Park, B. L., Kim, J. W., Cheong, H. S., Kim, L. H., Lee, B. C., Seo, C. H., . . . Choi, I. G. (2013). Extended genetic effects of ADH cluster genes on the risk of alcohol dependence: From GWAS to replication. Human Genetics, 132(6), 657 668. Spence, J. P., Liang, T. B., Eriksson, C. J. P., Taylor, R. E., Wall, T. L., Ehlers, C. L., Carr, L. G., et al. (2003). Evaluation of aldehyde dehydrogenase 1 promoter polymorphisms identified in human populations. Alcoholism, Clinical and Experimental Research, 27, 1389 1394. Vasiliou, V., & Nebert, D. W. (2005). Analysis and update of the human aldehyde dehydrogenase (ALDH) gene family. Human Genomics, 2, 138 143. Vaswani, M., Prasad, P., & Kapur, S. (2009). Association of ADHIB and ALDH2 gene polymorphisms with alcohol dependence: A pilot study from India. Human Genomics, 3(3), 213 220. Viljoen, D. L., Carr, L. G., Foroud, T. M., Brooke, L., Ramsay, M., & Li, T. K. (2001). Alcohol dehydrogenase-2 2 allele is associated with decreased prevalence of fetal alcohol syndrome in the mixedancestry population of the Western Cape Province, South Africa. Alcoholism: Clinical and Experimental Research, 25, 1719 1722.

Vonlaufen, A., Wilson, J. S., Pirola, R. C., & Apte, M. (2007). Role of alcohol metabolism in chronic pancreatitis. Alcohol Research and Health, 30, 48 54. Wall, T. L. (2005). Genetic association of alcohol and aldehyde dehydrogenase with alcohol dependence and their mechanisms of action. Therapeutic Drug Monitoring, 27(6), 700 703. Wall, T. L., Carr, L. G., & Ehlers, C. (2003). Protective association of genetic variation in alcohol dehydrogenase with alcohol dependence in Native American Mission Indians. American Journal of Psychiatry, 160(1), 41 46. Wall, T. L., Luczak, S., Orlowska, D., & Pandika, D. (2013). Differential metabolism as an intermediate phenotype of risk for alcohol use disorder: Alcohol and aldehyde dehydrogenase variants. In J. MacKillop, & M. R. Munafo (Eds.), Genetic Influences on Addiction: An Intermediate Phenotype Approach (pp. 41 63). Cambridge, MA: MIT Press. Wall, T. L., Luczak, S. E., & Sturmho¨fel, S. H. (2016). Biology, genetics, and environment: Underlying factors influencing alcohol metabolism. Alcohol Research: Current Reviews, 38(1), 59 68. Werner, J., Saghir, M., Warshaw, A. L., Lewandrowski, K. B., Laposata, M., Iozzo, R. V., . . . Ferna´ndez-Del Castillo, C. (2002). Alcoholic pancreatitis in rats: Injury from nonoxidative metabolites of ethanol. American Journal of Physiology Gastrointestinal and Liver Physiology, 28, 3G65 73G65. Whitfield, J. B. (2002). Alcohol dehydrogenase and alcohol dependence: Variation in genotype-associated risk between populations. American Journal of Human Genetics, 71, 1247 1250. Yasunami, M., Kikuchi, I., Sarapat, A. D., & Yoshida, A. (1990). The human class I alcohol dehydrogenase gene cluster: Three genes are tandemly organized in an 80-kb-long segment of the genome. Genomics, 7, 152 158. Zakhari, S. (2006). Overview: How is alcohol metabolized by the body? Alcohol Health and Research World, 29(4), 245.

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5 Acetaldehyde in the Brain After Ethanol Exposure: Research Progress and Challenges Mostofa Jamal, Asuka Ito, Naoko Tanaka, Ayaka Takakura, Kiyoshi Ameno and Hiroshi Kinoshita Department of Forensic Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan

LIST OF ABBREVIATIONS ACH ADH CYP2E1 ALDH BBB NAD NMDA ROS DA 4-HNE MDA CNS ACH50 ACH100 ACH200 Aldh2-KO

intestine, wherein it is mostly absorbed. It eventually accumulates, primarily in the liver. Three different ethanol metabolizing enzymes, alcohol dehydrogenase (ADH), cytochrome P450 (CYP2E1), and catalase, convert ethanol to ACH in the liver (Scheme 5.1). ACH is produced by the oxidation of ethanol, chiefly by the liver enzyme ADH. During this process, an obligatory reduction of nicotinamide adenine dinucleotide (NAD) to NADH alters the hepatic intracellular redox state, and this biochemical change may contribute to the hepatotoxicity of ethanol. Some ethanol metabolism occurs in other tissues, including the brain, where ACH formation is likely low. If ACH is not efficiently metabolized in the liver, the unmetabolized ACH adversely affects every system of the body with which it comes into contact. Initially, it was believed that the brain lacks a physiologically relevant concentration of ACH, since ADH, the main ethanol-oxidizing enzyme, is not active in the rat brain (Duncan, Kline, & Sokoloff, 1976). Similar findings were reported in the mouse and human brain (Galter, Carmine, Buervenich, Duester, & Olson, 2003; Rout, 1992). In addition, peripherally formed ACH does not penetrate the brain very well owing to the abundance of aldehyde dehydrogenase (ALDH) in the brain microvasculature (Zimatkin, Rout, Koivusalo, Bu¨hler, & Lindros, 1992). However, there has since been increasing evidence that the brain is able to produce significant levels of ACH, depending on the peripheral concentrations of ethanol (Hoover & Brien, 1981;

acetaldehyde alcohol dehydrogenase cytochrome P450 aldehyde dehydrogenase blood brain barrier nicotinamide adenine dinucleotide N-methyl-D-aspartate reactive oxygen species dopamine 4-hydroxynonenal malondialdehyde central nervous system acetaldehyde 50 mg/kg acetaldehyde 100 mg/kg acetaldehyde 200 mg/kg Aldh2-knockout

CONVERSION OF ETHANOL TO ACETALDEHYDE Ethanol is one of the most addictive substances used recreationally in many countries. Ethanol intoxication is strongly linked to accidents, injuries, deaths, domestic conflict, and violence. Nevertheless, billions of people worldwide consume ethanol. Ethanoldrinking behavior shows great individual variation, mainly due to genetic variations in ethanol and acetaldehyde (ACH) metabolizing enzymes. Ethanol is a primary metabolic source of ACH. Upon consumption, ethanol travels down the digestive tract to the small

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00005-2

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5. ACETALDEHYDE IN THE BRAIN AFTER ETHANOL EXPOSURE: RESEARCH PROGRESS AND CHALLENGES

SCHEME 5.1 Oxidative pathways of ethanol metabolism in the liver. ADH, CYP2E1, and catalase all contribute to the oxidative metabolism of ethanol to generate ACH. ALDH converts ACH to acetate. NAD1 is an essential factor required for both ADH and ALDH enzymatic reactions, in which NAD1 is converted into NADH.

Jamal et al., 2003a, 2016a; Westcott, Weiner, Shultz, & Myers, 1980). ACH is likely produced in the brain in two ways. First, ACH is formed during in situ oxidation from any ethanol that reaches the brain. The enzyme catalase plays a major role in ACH formation from ethanol in the brain (Aragon, Rogan, & Amit, 1992; Jamal et al., 2007; Zimatkin, Pronko, Vasiliou, Gonzalez, & Deitrich, 2006). CYP2E1 is expressed in neuronal cells in rat and human brains, and could contribute to ethanol metabolism in the brain (Heit et al., 2013; Yadav, Dhawan, Singh, Seth, & Parmar, 2006; Zimatkin et al., 2006). Catalase generates most of the brain ACH, while CYP2E1 accounts for 15% 20% of the total ACH in the brain (Heit et al., 2013). Thus, ACH could be produced locally in the brain by ethanol metabolism via catalase and CYP2E1. Further, ADH1, ADH3, and ADH4 have been observed in several regions of animal and human brains, suggesting that these enzymes might contribute to ACH production in specific areas of the brain (Galter et al., 2003; Martı´nez et al., 2001). Second, high levels of peripherally formed ACH ( . 100 µM) could result in ACH crossing the blood brain barrier (BBB) into the brain (Tabakoff, Anderson, & Ritzmann, 1976). This possibility has been reported by several groups (Hoover & Brien, 1981; Jamal et al., 2003a; Westcott et al., 1980), but requires further clarification. We recently showed (Jamal et al., 2016a) that the systemic administration of ACH (50 200 mg/kg) in mice could cause pharmacologically significant increases in vivo in the levels of brain ACH (Table 5.1), which further supports the notion that the peripheral ACH, at certain levels, could travel across the BBB and enter the brain.

ACH only exists briefly in the brain before it is broken down into acetate by ALDH. ALDH is distributed widely in human and animal brains with regional differences between species (Pietruszko et al., 1984; Zimatkin et al., 1992). Various ALDHs exist (Edenberg, 2007); however, mitochondrial ALDH2, which plays a crucial role in the oxidation and detoxification of ACH, is of great interest due to its low Km for ACH. ALDH2 deficiency affects over one billion people globally, occurs in up to 40% of Asians, and causes build-up of toxic ACH and ethanolrelated flushing in Asians (Brooks, Enoch, Goldman, Li, & Yokoyama, 2009; Impraim, Wang, & Yoshida, 1982). Like humans carrying the deficient ALDH2 allele, ALDH2-deficient mice showed higher blood and brain ACH concentrations after ethanol administration, whereas ethanol concentrations were comparable in ALDH2-deficient and normal mice (Isse, Matsuno, Oyama, Kitagawa, & Kawamoto, 2005; Jamal et al., 2016a). Inactive ALDH2 enzyme reduces the likelihood of continued ethanol consumption and protects against developing alcoholism, particularly among Asian populations (Arolfo et al., 2009; Tu & Israel, 1995). ALDH2 2/2 2 homozygous and ALDH2 1/2 2 heterozygous individuals appear to have 99% and 66% protection against alcoholism, respectively (Chen et al., 1999; Harada, Agarwal, Goedde, Tagaki, & Ishikawa, 1982; Tu & Israel, 1995).

CHALLENGES IN ACETALDEHYDE RESEARCH ACH induces a range of toxic, pharmacological, and behavioral effects. These effects likely depend on

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CHALLENGES IN ACETALDEHYDE RESEARCH

TABLE 5.1 Concentrations of ACH (µM) in the Blood and Brain After Intraperitoneal Administration of ACH (50 200 mg/kg) in Aldh2-KO and Wild Type (WT) Mice ACH50

ACH100

ACH200

Blood ACH min

WT

Aldh2-KO

WT

Aldh2-KO

WT

Aldh2-KO

0

0

0

0

0

0

0

5

78.41 6 8.26

112.98 6 14.76

140.36 6 10.92

235.57 6 24.31

370.46 6 15.26

835.99 6 82.01

10

10.82 6 2.76

23.02 6 5.24

17.43 6 2.18

78.13 6 10.16

147.80 6 9.26

229.95 6 81.45

15

12.67 6 2.96

24.63 6 9.90

13.83 6 2.65

41.76 6 6.13

66.86 6 16.13

90.14 6 8.94

20

5.27 6 1.83

19.05 6 12.12

6.47 6 2.73

30.68 6 5.05

35.22 6 27.40

68.16 6 13.68

25

6.17 6 1.45

20.85 6 3.87

9.56 6 0.77

29.12 6 9.72

16.07 6 7.43

45.83 6 2.14

30

10.91 6 0.72

17.87 6 3.64

9.95 6 1.70

33.45 6 1.28

13.53 6 1.26

45.55 6 9.17

60

7.64 6 0.62

16.27 6 2.71

8.47 6 1.38

26.60 6 2.07

10.69 6 2.26

34.13 6 6.01

ACH50

ACH100

ACH200

Brain ACH min

WT

Aldh2-KO

WT

Aldh2-KO

WT

Aldh2-KO

0

0

0

0

0

0

0

5

23.10 6 1.23

93.10 6 8.92

115.29 6 12.07

214.00 6 9.81

307.56 6 13.06

782.91 6 93.57

10

11.55 6 2.71

47.89 6 16.14

30.10 6 7.83

60.10 6 7.83

103.59 6 26.39

208.17 6 8.35

15

5.97 6 0.76

15.07 6 3.62

18.43 6 8.26

38.18 6 2.65

44.86 6 6.34

84.19 6 11.51

12.68 6 1.74

22.75 6 2.17

13.24 6 3.92

49.94 6 13.12

8.35 6 2.40

36.66 6 7.86

20

ND

8.70 6 2.63

25

ND

10.56 6 3.29

ND

16.00 6 5.39

30

ND

11.43 6 0.70

ND

19.27 6 5.42

ND

38.25 6 2.41

60

ND

8.30 6 0.64

ND

17.45 6 4.75

ND

32.96 6 7.36

ND, Not detected.

various factors such as age, sex, genetics, the degree of ACH formation after alcohol consumption, and the duration and the number of ACH exposures. Among these factors, genetics play an important role in excess ACH accumulation after ethanol consumption. Many of the effects of ACH are similar to those of ethanol (Deitrich, 2004; Hunt, 1996, Quertemont, Tambour, & Tirelli, 2005). No data is available on ACH concentrations in the human brain after ethanol consumption under various conditions, owing to methodological and ethical issues. The main challenge associated with the study of ACH is that some of its effects are masked by those of ethanol. The effects of ethanol and ACH occur simultaneously after ethanol consumption, and data on ACH-induced effects are inconsistent because of the lack of control over ACH formation and the lack of knowledge of brain ACH concentrations required to exert effects. Another issue is that ADH converts ethanol to ACH in a reversible reaction, and could subsequently convert ACH to ethanol. Ethanol-related research has therefore focused on whether ethanolinduced effects are mediated by ethanol alone and/or by ACH. In this context, many researchers have

investigated the effects of ACH on several neurotransmitters and behaviors, by the direct administration of ACH with or without 4-methypyrazole (ADH inhibitor) or ALDH inhibitors such as cyanamide or disulfiram (which cause ACH accumulation) in laboratory animals (Foddai, Dosia, Spiga, & Diana, 2004; Jamal et al., 2016b; Jamal, Ameno, Ameno, Okada, & Ijiri, 2003b; Kuriyama, Ohkuma, Tomono, & Hirouchi, 1987; Quertemont, Tambour, Bernaerts, Zimatkin, & Tirelli, 2004). Their results confirmed that ethanol-induced neurochemical and behavioral alterations, at least in part, are caused by ACH. Thus, the direct administration of ACH appears to be an accurate method for studying the role of ACH in ethanol action in animal, since it is easier to control the amount of ACH. Aldh2knockout (Aldh2-KO) mice, a model for ALDH2 deficiency in humans, have recently attracted attraction as a model animal to examine the role played by ACH in the effects of ethanol. In humans, it is not possible to administer high doses of toxic compounds such as ACH. Nevertheless, the role of brain catalase after alcohol consumption in a human population has been examined indirectly (Koechling & Amit, 1992).

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5. ACETALDEHYDE IN THE BRAIN AFTER ETHANOL EXPOSURE: RESEARCH PROGRESS AND CHALLENGES

BRAIN ACETALDEHYDE IN ETHANOL NEUROTOXICITY After consumption, ethanol and ACH simultaneously spread to, and exert adverse effects in, almost every organ of the body within a few minutes. However, low to moderate ethanol consumption seems to provide certain health benefits (Krenz & Korthuis, 2012). The brain is one of the principal target organs of ethanol (Gohlke, Griffith, & Faustman, 2008). Excessive alcohol drinking is widely associated with brain damage. For instance, ethanol causes adaptive upregulation in the sensitivity of N-methyl-D-aspartate (NMDA)-glutamate receptor, resulting in an increased vulnerability for glutamate-induced cytotoxic response (Krystal, Petrakis, Mason, Trevisan, & D’Souza, 2003). Increased calcium influx through NMDA receptors is tightly coupled to uptake into mitochondria and causes the production of reactive oxygen species (ROS). Increased levels of ROS can impair neuronal viability by inhibiting electron transport chain function and ATP formation (Chu, Tong, & Monte, 2007; Goodlett, Horn, & Zhou, 2005). Furthermore, ethanol causes a reduction in brain weight due to regional brain atrophy (Agartz, Momenan, Rawlings, Kerich, & Hommer, 1999; Zahr, Kaufman, & Harper, 2011). ACH is considered more neurotoxic than ethanol (Sarc & Lipnik-Stangelj, 2009). The exact mechanisms underlying the neurotoxic effects of ACH remain unknown. Several mechanisms have been proposed to contribute to ACH-induced alteration of normal brain function, including alteration of cellular function (Tabakoff et al., 1976), alteration of biogenic amine metabolism (Truitt & Walsh, 1971), and generation of bioactive derivatives, such as tetrahydroisoquinolines and tetrahydropapaverine, after interaction with catecholamines (Bardsley & Tipton, 1980). Increased exposure to ACH can cause numerous adverse effects through the production of peroxides and free radicals, neural degeneration, and central nervous system depression. Although low ACH concentrations have no measurable effects, they could synergistically enhance the effects of ethanol. Ethanol and ACH inhibit the cholinergic system in human (Nordberg, Larsson, Perdahl, & Winblad, 1983) and animal brains (Jamal et al., 2009; Kuriyama et al., 1987), where the effects of ACH are more significant. Reduced cholinergic function is associated with deterioration of cognitive functioning in some neurodegenerative diseases (Dani & Bertrand, 2007). ACH inhibits extracellular glutamate in the anterior cingulate cortex (Zuo, Yang, Hao, Dong, & Wu, 2007), which could lead to memory loss. ACH enhances 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridineinduced damage to the mouse striatum, resulting in dopamine (DA) depletion (Corsini, Zuddas, Bonuccelli,

Schinelli, & Kopin, 1987; Zuddas et al., 1989). Reductions in DA content and uptake indices have been documented in Parkinson’s disease. ACH also alters astrocyte growth in cultures, which may cause birth defects in vivo (Holownia, Ledig, Mapoles, & Menez, 1996), and presumably exerts its neurotoxic effects via the activation of apoptotic pathways (Holownia, Ledig, Braszko, & Me´nez, 1999). In addition to its toxic effects, ACH mediates some behavioral effects of ethanol, such as narcosis (Aragon, Spivak, & Amit, 1991), aversion (Quintanilla, Callejas, & Tampier, 2002), conditioned place preference (Font, Aragon, & Miquel, 2006), locomotion (Quertemont et al., 2004; Tambour, Didone, Tirelli, & Quertemont, 2006), amnesia, anxiolytic effects (Quertemont et al., 2004), and reinforcement (Eriksson, 2001). The pleasant subjective effect reinforces voluntary ethanol consumption in animals (Brown, Amit, & Smith, 1980; Tampier & Quintanilla, 2002) and brain ACH content is believed to reinforce ethanol consumption. Mesolimbic DA transmission plays an important role in the positive reinforcing properties of ethanol (Pierce & Kumaresan, 2006; Wise, 2006). In contrast, peripheral ACH is aversive and prevents further ethanol drinking due to a range of unpleasant symptoms (Quertemont, 2004). Thus, the balance between ACH in the periphery and in the brain could determine the aversive and reinforcing effects of ethanol. ACH can also activate the hypothalamic pituitary adrenal axis (Cannizzaro, La Barbera, Plescia, Cacace, & Tringali, 2010; Kinoshita et al., 2001), which regulates many physiological processes, including metabolism, reproduction, growth, mood and emotions, and immune function. Several findings support the involvement of ACH in ethanol addiction (Deng & Deitrich, 2008; McBride et al., 2002).

ACETALDEHYDE ADDUCTS IN THE BRAIN Ethanol causes DNA damage in several ways, including increased cellular proliferation (Simanowski, Stickel, Maier, Ga¨rtner, & Seitz, 1995), oxidative stress (Cahill et al., 2002), and the formation of the lipid peroxidation products malondialdehyde (MDA) and 4hydroxynonenal (4-HNE) and related DNA adducts (Brooks, 1997). ACH seems to be a primary mediator of these effects (Scheme 5.2). High levels of NADH produced in the process of ethanol metabolism in the mitochondria can cause an increase in the number of superoxide (O2 ) free radicals, leading to the formation of hydroxyl radicals (OH ), lipid peroxidation, and mitochondrial DNA damage (Hoek, Cahill, & Pastorino, 2002). An increase in the levels of ROS due to ethanol oxidation leads to the formation of lipid

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MINI-DICTIONARY OF TERMS

Ethanol

AP1

CYP2E1

ADH

Protein adducts

DNA adducts MDA, 4-HNE, etc.

DNA adducts

ROS

ACH

Lipid peroxidation ALDH

mutagenesis impaired DND repair

 DNA lesions and mutations  Inhibits antioxidative defense and nuclear repair system  Inhibits methyl transfer

MMPs Acetate

SCHEME 5.2 ACH binds to DNA and proteins to form adducts, inhibits the antioxidative defense and the nuclear repair systems and inhibits DNA methylation. Ethanol is additionally metabolized via CYP2E1 to ACH, which is metabolized by ALDH2 to acetate. During these processes, ROS are formed, which increase lipid peroxidation, generate MDA and 4-HNE and increase the expression of the activator protein-1 gene (AP1) and matrix metalloproteinases (MMPs).

peroxides, which in turn cause modification of proteins and DNA, resulting in injury or damage to tissue within the brain. ACH can alter neuronal viability and DNA integrity in cultured neurons (Lamarche, Gonthier, Signorini, Eysseric, & Barret, 2004; Tong et al., 2011) and suppress DNA repair (Romero et al., 2016), which could lead to genomic instability and, therefore, a variety of neurological and neurodegenerative disorders (Subba Rao, 2007). ACH forms adducts with various proteins and DNA in the brain (Brooks & Theruvathu, 2005; Nakamura et al., 2000; Rintala et al., 2000). ACH-protein adducts have been detected in many regions of the brains in ethanol-fed rats (Rintala et al., 2000; Upadhya & Ravindranath, 2002), and in the frontal cortex and midbrain of an individual with alcoholism (Nakamura et al., 2003). ACH forms adducts with a number of cytosolic proteins including tubulins (Smith, Jennett, Sorrell, & Tuma, 1989; Tuma, Smith, & Sorrell, 1991). Tubulin is abundant in the brain cytoplasm, particularly in the cytosol (Thomas, Shashikala, & Sengupta, 2010) where most of the ACH generation takes place. ACH-tubulin adducts inhibit microtubule formation, which can damage cytoskeleton function in brain cells (Smith et al., 1989). ACH could also affect immature neuronal cells by increased 4-HNE and 8-hydroxydeoxyguanosine immunoreactivity, which reflects lipid peroxidation and DNA damage with adduct formation (Tong et al., 2011). ACH forms adducts with DA to form the potent endogenous neurotoxin salsolinol. Several data indicated a high presence of salsolinol in the Parkinsonian brain, suggesting a possible association with the disease process (Nagatsu, 1997; Naoi, Maruyama, Akao, & Yi, 2002).

CONCLUDING REMARKS Several recent studies have suggested that ACH accumulates in the brain after ethanol exposure and produces a number of effects similar to those of ethanol. However, there are still some challenges associated with the study of the effects of ACH in animal brains. Moreover, there is no data available on ACH concentrations in the human brain after alcohol consumption under various conditions, owing to its high toxicity. The role of ACH in the human brain should be elucidated in further studies. Individual genetic traits related to the ethanol metabolizing enzymes ADH and ALDH, and the toxicity of ACH are important areas of potential research. Information obtained from such research could improve understanding of ACHinduced diseases as well as assessment of potentials risks. In addition, knowledge of ACH toxicity could be of significance in the development of effective therapeutic strategies to prevent the toxic effects of ACH.

MINI-DICTIONARY OF TERMS Neurotransmitters Chemical signals released from presynaptic nerve terminals into the synaptic cleft which allow communication between neurons. Microvasculature The smallest blood vessels, including capillaries, venules, and arterioles that perfuse the body’s tissues. Blood brain barrier A highly selective semipermeable membrane barrier between the brain itself and the blood supply of the brain, which prevents most substances from moving from the blood to the brain tissue. Reinforcing effects An effect that increases the probability a response will occur. Aversive effects An unpleasant effect that is intended to induce a change in behavior.

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5. ACETALDEHYDE IN THE BRAIN AFTER ETHANOL EXPOSURE: RESEARCH PROGRESS AND CHALLENGES

DNA adducts DNA damage caused by formation of covalent adducts between chemical mutagens and DNA.

KEY FACTS About Acetaldehyde • ACH is a colorless liquid with a distinctive fruity odor. • The liver is the principal site of ACH accumulation after consumption of ethanol. • ALDH2 deficiency occurs in up to 40% of Asians, and causes a build-up of toxic ACH and ethanolrelated flushing. • When the ACH concentration becomes too high, the liver is no longer able to process and remove it efficiently; as a result, ACH may persist in other tissues, particularly the brain.

SUMMARY POINTS • ACH is a potential toxin that can accumulate in the brain after ethanol consumption. • ACH has a number of effects similar to those of ethanol, but its toxicity has received far less public attention than ethanol abuse. • This chapter provides an overview of the generation of ethanol-derived ACH and its toxic effects in the brain.

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5. ACETALDEHYDE IN THE BRAIN AFTER ETHANOL EXPOSURE: RESEARCH PROGRESS AND CHALLENGES

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C H A P T E R

6 Consequences of Ethanol Exposure on Neurodevelopment 1

Manuel Alves dos Santos Ju´nior1, Germana Silva Vasconcelos1, Caren Na´dia Soares de Sousa1, Danielle Macedo2 and Silvaˆnia Maria Mendes Vasconcelos2

Neuropsychopharmacology Laboratory, Drug Research and Development Center, Faculty of Medicine, Federal University of Ceara´, Fortelza, Brazil 2Department of Physiology and Pharmacology, Faculty of Medicine, Federal University of Ceara´, Fortaleza, Brazil

LIST OF ABBREVIATIONS 5-HT 5-HT1A CNS DNA FAS FASDs PAE

Ethanol consumption causes pathological changes in various organs across all age groups (Crews, Vetreno, Broadwater, & Robinson, 2016; Downer, Jiang, Zanjani, & Fardo, 2014; Tai et al., 2016). The consequences of ethanol exposure on neurodevelopment are a critical public health problem, mainly affecting people’s lives during their childhood and adolescence (Pinheiro et al., 2015). Thus, the purpose of this chapter is to describe the short- (childhood), middle- (adolescence), and long-term (adulthood) consequences of ethanol exposure during neurodevelopment.

5-hydroxytryptamine or serotonin serotonin type 1A central nervous system deoxyribonucleic acid fetal alcohol syndrome fetal alcohol spectrum disorders prenatal alcohol exposure

INTRODUCTION Ethanol effects in the central nervous system (CNS) are biphasic, ranging from depressant at higher doses to excitatory at low doses. Hence, smaller doses cause behavioral disinhibition and decreased anxiety, while higher doses may lead to sedation, unconsciousness, respiratory depression, coma, or even death (Brunton, Parker, Blumenthal, & Buxton, 2010; Vasconcelos et al., 2003) (Fig. 6.1). Some brain regions are more susceptible to the acute effects of ethanol, such as the prefrontal cortex, hippocampus, striatum, and amygdala (Vilpoux, Warnault, Pierrefiche, Daoust, & Naassila, 2009). These brain areas are responsible for rational judgment, memory, and movement (Fig. 6.2).

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00006-4

ALCOHOL AND BRAIN NEURODEVELOPMENT Overview of Neurodevelopmental Events Prenatal and postnatal periods in mammalian development are critical and characterized by rapid changes in neuronal organization. During these periods, environmental and genetic factors can have significant short- and long-term outcomes on the brain and one’s behavior. These factors may alter developmental processes leading to the appearance of neurological and

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6. CONSEQUENCES OF ETHANOL EXPOSURE ON NEURODEVELOPMENT

FIGURE 6.1 Effect of alcohol according to exposure dose. Main symptoms associated with the dose of exposure to alcohol. Low doses cause slight changes and high doses cause serious changes and may even cause coma and death.

Higher doses • Sedation • Unconsciousness • Respiratory depression • Coma • Death

Lower doses • Behavioral disinhibition • Decreased anxiety

FIGURE 6.2

Brain areas affected by exposure to alcohol related to rational judgment, memory, and movement. Brain areas affected by exposure to alcohol responsible by rational judgment, memory, and movement. Damages in these areas promote alterations in the people’s life such as cognitive impairment, social deficit and changes in movement.

psychiatric disorders (Rice & Barone, 2000; Workman, Charvet, Clancy, Darlington, & Finlay, 2013). The first major neurodevelopmental event is the formation of the neural tube, a process known as neurulation. In humans, this occurs between the third and fourth week of pregnancy. Neurulation is followed by the cortical neurogenesis, which occurs throughout the gestational period, and a peak of gliogenesis, accompanied by the formation of a complex neuronal arrangement which

will generate dendritic fields and synaptogenesis. Although these events differ in intensity at specific anatomical sites, they continue to occur throughout the fetal stage and in the postnatal period (Rice & Barone, 2000; Roessmann & Gambetti, 1986; Wise & Jones, 1976). The postnatal period is essential for brain development. During this stage, there is a considerable amount of cell differentiation and specialization learning. Synaptogenesis develops substantially and synaptic

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ALCOHOL AND BRAIN NEURODEVELOPMENT

density increases rapidly after birth and achieves its maximum levels up to 2 years afterward. After this stage, the brain undergoes a process of specific synaptic refinement and elimination which lasts until the middle of adolescence and originates the synaptic patterns of adults. The postnatal period is a phase of developmental reorganization and expansion of cognitive abilities and behavioral adaptations to the adult stage of life. Because it is a phase of intense changes, environmental exposure to toxicants can affect neural plasticity by altering neurodevelopment, which may lead to neurological and psychiatric disorders (Barker & Ullian, 2010; Borre et al., 2014; Herschkowitz, Kagan, & Zilles, 1997). Adolescence is considered the most decisive stage for neurodevelopment; therefore, it is the stage where children are at the highest risk for the development of cerebral alterations. Early adolescence is a fundamental stage during neurological development with various structural, neurochemical, and molecular changes occurring in response to genetic and environmental stimuli. Among these changes, it is crucial to emphasize the synaptic pruning and the formation of new neural connections, which are responsible for the process of neuroplasticity. A consequence of this intense process of synaptic modeling during adolescence is the high vulnerability to pathological injuries, ranging from stressful stimuli to drug abuse and dietary deficiencies (Glantz, Gilmore, Hamer, Lieberman, & Jarskog, 2007; Paus, Keshavan, & Giedd, 2008). During adulthood, the process of synaptic pruning and myelination evolves, so that at 20 years of age the brain reaches its maximum weight. However, the volume of white matter continues to increase until the middle of the fourth decade of life, which coincides with the peak of myelination observed at approximately 50 years of age (Dekaban, 1978). Although adulthood does not appear to be a vulnerable stage, it remains a period associated with aging disorders (Huttenlocher & Dabholkar, 1997; Sowell et al., 2003).

Neurodevelopmental Alterations Induced by Alcohol Several mechanisms are proposed to explain how alcohol produces deleterious effects on the developing brain. However, the type of damage induced depends on the dosage, time of exposure, and stage of brain development along with other maternal and genetic factors (Goodlett, Horn, & Zhou, 2005). Experimental studies have shown that prenatal exposure to alcohol affects all stages of brain development, from neurogenesis to myelination, due to its interactions with molecules that regulate brain development. Also, it is a trigger for apoptotic neurodegeneration (Goodlett et al., 2005; Riley, Infante, & Warren, 2011).

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Current evidence suggests that alcohol produces many deleterious effects. These deleterious effects are primarily observed on: (1) specific molecules that regulate critical processes in brain development (e.g., L1 cell adhesion molecule, alcohol dehydrogenase, and catalase); (2) the initial development of the midline serotonergic neurons leading to disruption of their regulatory signaling to other target brain structures; (3) gene expression, oxidative stress, and growth-factor signaling; (4) neuronal migration and proliferation; and (5) the astrocytic metabolic function of the fetus (Goodlett et al., 2005; Manzo-Avalos & SaavedraMolina, 2010) (Fig. 6.3). Prenatal alcohol exposure (PAE) disrupts brain development and subsequent cognitive, motor, and behavioral functions (Riley et al., 2011). Alcohol consumption is a potentially preventable cause of intellectual disabilities. High levels of alcohol consumption during the gestational period may result in fetal alcohol spectrum disorders (FASDs), which are considered as a set of irreversible conditions characterized by typical craniofacial dysmorphology, deficiency in prenatal and postnatal growth, CNS dysfunction and several associated malformations (Eugene Hoyme et al., 2005). Subsequent studies have investigated how exposure to ethanol during the brain development period affects brain structure, function, and behavior. Most of these studies evaluated the outcomes in different ages, prenatal or postnatal exposure, using animal models. These authors found that neurogenesis, synaptogenesis, gliogenesis, oligodendrocyte maturation, and agedependent behaviors have a temporal relationship with various mechanisms associated with molecular and biochemical changes in both rodents and humans (Clancy et al., 2007; Semple, Blomgren, Gimlin, Ferriero, & Noble-Haeusslein, 2013). Fetal ethanol exposure can lead to psychiatric illnesses, including depression, anxiety, and a reduction in cognitive abilities in humans. In this regard, a clinical study revealed that PAE causes mild adverse effects on childhood. Those children (4 5 years old) had higher levels of depressive symptomatology (O’Connor & Paley, 2006). Another report based on a long-term observation in an extended cohort of children with fetal alcohol syndrome (FAS) demonstrated a correlation of the psychopathology and intelligence impairment (Steinhausen, Willms, & Spohr, 1994). Also, studies have shown a connection between alcohol exposure during pregnancy and impaired verbal and visual spatial episodic memory performance in the offspring (du Plooy, Malcolm-Smith, Adnams, Stein, & Donald, 2016). Moreover, other features seem to be related to the outcomes in childhood besides PAE, such as maternal depression and the child’s sex (Connor & Kasari, 2000).

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6. CONSEQUENCES OF ETHANOL EXPOSURE ON NEURODEVELOPMENT

FIGURE 6.3 Alterations in fetal molecular mechanisms caused by drinking alcohol during pregnancy. Preclinical evidence point toward several important molecular alterations in the fetus that leads to the manifestations of age-related behavioral alterations.

An experimental study conducted in rats before mating until weaning of their pups, with a total duration of 50 days has provided evidence that in utero ethanol exposure produces long-lasting effects on development. This study concluded that alcohol can cause biochemical changes in the brain circuitry that relates to behavioral and neurochemical responsiveness during adulthood. The effects of daily exposure of ethanol on male and female rat pups were also evaluated. The animals displayed a phenotype of despair behavior while also showing disruption in hippocampal and striatal dopaminergic transmission (Carneiro et al., 2005). Accumulated evidence indicate that children prenatally exposed to alcohol have attentional deficits and behavioral problems similar to those who have attention deficit disorder. Also, they are significantly more intellectually impaired (Nanson & Hiscock, 1990). Although PAE is not a causal factor for the development of autistic behavior, a study reports six cases of children with FAS and who also fulfill the criteria for a diagnosis of autism (Nanson, 1992).

Behavioral Outcomes and Mechanisms Associated With Prenatal Alcohol Exposure The investigation of alcohol prenatal exposure in animals could help explain the outcomes and mechanisms underlying the neurobiology of behavioral deficits associated with FASD. In a previous study,

pregnant rats were exposed to high doses of alcohol during the equivalent to the human third trimester of pregnancy (a neonatal period in rats), as a consequence their offspring displayed anxiety-like behavior during the adolescence period. The same ethanol-exposed adolescent offspring showed increased excitatory synaptic inputs to neurons in basolateral amygdala mediated by glutamatergic transmission (Morton & Valenzuela, 2016). Based on that, a research group examined the receptor involved with the glutamatergic modulation. They found that the inhibition of serotonin type 1A (5-HT1A) receptors during the third trimester of pregnancy could play a significant role in the pathophysiology of FASD. The study indicates that ethanol exposure during the equivalent to the third trimester of pregnancy could reduce modulation of glutamatergic synaptic transmission by 5-HT1A receptors in the hippocampal CA3 region (Baculis, Diaz, & Valenzuela, 2015). Prenatal ethanol exposure may lead to behavioral deficits associated with an increase in attentional demand and locomotor activity in rodents’ offspring (Brys, Pupe, & Bizarro, 2014). These effects on the last trimester of pregnancy support the hypothesis that the outcomes of ethanol exposure depend on drug dosage, gestational timing, and the life stage of the offspring. Early gestational exposure with moderate concentrations of ethanol can cause persistent and long-lasting alterations in the behavior of mice, including

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AGE-RELATED CONSEQUENCES OF PRENATAL ALCOHOL EXPOSURE

hyperactivity and enhanced spatial memory. These findings suggest that even moderate doses of ethanol exposure in early pregnancy have long-term outcomes on the brain function and behavior in mice (Sanchez Vega, Chong, & Burne, 2013). Furthermore, the perinatal (third-trimester equivalent) exposure of animals to alcohol led to a loss of mature oligodendrocyte accompanied by persistent white matter injury (Newville, Valenzuela, Li, Jantzie, & Cunningham, 2017). Persistent deficits in social behavior are among the negative consequences associated with ethanol exposure during prenatal development (Hamilton et al., 2014). Previous findings indicate that moderate prenatal exposure to alcohol can produce deficits on the spatial response, social, and motor behavior associated with ventrolateral frontal cortex function. On the other hand, acute alcohol exposure in mice was not related to social responsiveness or motor activity, but longlasting deficits in long-term spatial memory (Houle´, Abdi, & Clabough, 2017).

AGE-RELATED CONSEQUENCES OF PRENATAL ALCOHOL EXPOSURE PAE produces alterations in neocortical development that can be transferred to the next generations. Besides that, it causes numerous stable epigenetic modifications transmitted via the male germline up to the third generation. Researchers showed that PAE could promote

decreased global deoxyribonucleic acid (DNA) methylation in the neocortex, as it disturbs DNA methylation, which can lead to modulation of gene expression in neocortical development (Abbott, Rohac, Bottom, Patadia, & Huffman, 2017). Genes with neurodevelopmental functions in PAE present methylation changes; thus, long-term differential changes in the methylation profile of animals and humans may enable early diagnostics and an opportunity to therapeutically treat FASD, which will lead to higher quality of life (Laufer, Chater-Diehl, Kapalanga, & Singh, 2017). Regardless of the consequences of prenatal exposure in any period of life, the use of alcohol can cause agerelated effects on brain development. Adolescents and the elderly are keeners to the harmful impacts of heavy alcohol use when compared to adults. Massive alcohol use may interpose significant events in the human adolescent brain development, causing cognitive functioning deficits, particularly concerning the spatial and attentional processing, with deficits persisting into young adulthood (Squeglia, Boissoneault, Van Skike, Nixon, & Matthews, 2014) (Fig. 6.4). Few investigations have clarified the mechanisms underlying the neurochemical and neurobiological alterations caused by prenatal ethanol exposure. Nonetheless, some data suggest a relationship between altered social behavior in adult offspring after being exposed to ethanol (in moderate levels) during their gestational period with changes in their structural plasticity and gene expression in the frontal cortex

Consequences

Childhood

Adolescence

Adulthood

Depressive symptoms

Anxiety

DA systems dysfunction

Intelligence impairment

Social deficits

Altered 5-HT functioning

Memory performance

Cognitive impairment

White matter injury

Attentional deficits

Drug abuse

Prenatal alcohol exposure

FIGURE 6.4 Consequences of alcohol exposure during pregnancy throughout the lifetime of the offspring. Several outcomes are shown in different stages of the offspring after being exposed to alcohol during any moment of the gestation period. The summarized points in each stage of life were found in studies with animals and humans trials. DA, Dopamine; 5-HT, 5-hydroxytryptamine or serotonin.

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6. CONSEQUENCES OF ETHANOL EXPOSURE ON NEURODEVELOPMENT

(Hamilton et al., 2010). Furthermore, alcohol exposure during any of the three-trimester equivalents leads to long-term consequences in redox status in some areas of the adult rat brain (e.g., increase the oxidative stress in the hippocampus) (Brocardo et al., 2017).

CONCLUSIONS AND FUTURE PERSPECTIVES Considering all the evidence, it seems necessary that a better understanding of the mechanisms underlying alcohol’s effects in the developing brain are needed. These future studies would lead to the discovery of new pharmacological targets to treat FASD. Currently, there are no effective treatments for FASD. On the other hand, preclinical studies in rodents have shown that thyroxine and metformin administration during the third-trimester equivalent of human pregnancy can reverse hippocampal and cognitive deficits caused by previous gestational ethanol exposure. Thus, this might be a promising treatment for FASD (TuncOzcan, Wert, Lim, Ferreira, & Redei, 2017).

MINI-DICTIONARY OF TERMS Alcohol A substance capable of crossing the blood brain barrier and exhibiting depressant effects on the CNS or even deleterious results depending on the time of exposure and the period of life of exposition. Fetal alcohol spectrum disorders A set of physical, behavioral, and cognitive disorders presented by the person whose mother drank alcohol during pregnancy. Neurodevelopment The development of the CNS from its molecular and structural aspects to functions of cognition, communication, sensory skills, motor, language, behavior, and emotions, during life. Prenatal alcohol exposure Consumption of alcohol during pregnancy. Postnatal alcohol exposure Drinking alcohol at any stage of life. Prefrontal Cortex Anterior region of the frontal lobe of the brain associated with an executive function as activities of planning, judgment, decision-making, personality and social behavior. Ventrolateral Prefrontal Cortex A region of the prefrontal cortex located in the inferior prefrontal gyrus. This region plays a crucial role in motor control, decision-making, and operational memory. Hippocampus Cerebral structure located in the temporal lobes considered the central region involved in the processes of learning and memory. Also, it is an essential area of the limbic system and plays a crucial role in spatial orientation.

KEY FACTS Neuroplasticity • Neuroplasticity is the nervous system’s ability to reorganize itself when exposed to a new situation throughout neuronal development.

• Neuroplasticity is related to the formation of new memories and learning processes as well as adaptation to injuries and traumatic events throughout adulthood. • Neuroplasticity is a coordinated, dynamic, and continuous process that allows neurons to adjust their activities to changes in their environment and new experiences. • The gray matter of the brain that can physically change due to these new neural connections development.

Oxidative Stress • Oxidative stress is a term that refers to an imbalance between the production of reactive oxygen species (ROS) by living organisms and their antioxidant defense mechanisms to remove or repair the damage caused by ROS. • Prooxidative/antioxidative imbalance in cells can cause oxidative damage of macromolecules, including proteins, lipids (such as phospholipids) and DNA. Hence, they can compromise many intracellular pathways and cellular integrity. • Oxidative stress induces neuron degeneration in the CNS.

Intellectual Disabilities • Intellectual Development Disorder or Intellectual Disability is characterized by difficulties in learning and cognitive performance, that is, limitations to solve problems and make plans, understand abstract ideas, establish social communication, and perform daily life activities. • Intelligence is assessed through standardized tests using the Intelligence Quotient. The outcome of a person with Intellectual Development Disorder in this test is 75 or less. • Genetic causes of intellectual disabilities are the most common, although perinatal and prenatal events also can be related to environmental causes.

Depression • Depression is a common and serious mental disorder characterized by a sense of extreme sadness and/or loss of interest in life activities that one already enjoys, low self-esteem, low energy, and pain without a definite cause for at least 2 weeks and that is present during the most part of situations. • It can lead to a variety of emotional and physical problems and can negatively affect a person’s family relationships and employment, and reducing functionality at work.

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REFERENCES

• Between 2% and 7% of adults with depression die by suicide. • The risk factors for depression are the family history of depression, certain medications, sudden changes in life, chronic health problems, and drug abuse.

Autism • Autism is a neurological disorder characterized by impairment of social interaction, verbal and nonverbal communication, and restricted and repetitive behavior. • Autism is a permanent condition. • Genetic and environmental factors are involved in the development of autism. • Early interventions with stimulus of behavioral, cognitive, or speech functions can help children with autism gain autonomy and social and communication skills.

Serotonin Type 1A Receptors • Serotonin receptors influence several biological and neurological processes, such as aggression, anxiety, appetite, cognition, learning, memory, mood, nausea, sleep, and thermoregulation. • The 5-HT 1A receptors are a serotonin receptor subtype located in presynaptic and postsynaptic membranes. • 5-HT 1A receptors are G-protein-coupled receptors that exert their effects through Gi/Go proteins inhibiting adenylyl cyclase as well as other second messenger cascades. They mediate both excitatory and inhibitory neurotransmission. • Probably, the 5-HT 1A receptor is one of the most investigated serotonin receptors since its activation has been implicated in the mechanism of action of anxiolytic drugs, antidepressants, and antipsychotics. • Postsynaptic 5-HT 1A receptors are found in brain regions related to mood, cognition, and memory. Given this, these receptors may be targeted in the treatment of memory disorders in schizophrenia.

Phenotype • A phenotype is a genetic term designated to aspects of biochemical or physiological characteristics, morphology, development, and behavior of an organism’s genotype. • A phenotype results from the interaction of the expression of the genetic code of an organism, its genotype, with the influence of environmental factors.

SUMMARY POINTS • This chapter focuses on the effects of PAE on neurodevelopment. • Alcohol can quickly diffuse across the placental membrane when ingested during pregnancy. • Genetic and environmental stimuli during adolescence can cause neuroplastic changes and synaptic modeling. These can lead to high vulnerability to pathological triggers. • Alcohol effects on the developing brain depend upon the dosage, gestation stage, and duration of exposure. • Drinking alcohol during pregnancy can impair cognitive, motor, social, and other behaviors. • Prenatal ethanol exposure is associated with psychiatric illness, including depression, anxiety, and a reduction in cognitive abilities in humans. • Ethanol exposure in moderate dosage during the early gestational period has long-term outcomes on the brain function and behavior in mice. • Specific epigenetic alterations caused by PAE persist into germline up to the third generation of unexposed animals. • Preclinical studies showed that thyroxine and metformin administration during pregnancy could reverse deficits caused by previous gestational ethanol exposure.

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C H A P T E R

7 Animal Models of Binge Drinking: Behavior and Clinical Relevance Je´roˆme Jeanblanc1, Benjamin Rolland2,3, Pierre Maurage4, Fabien Gierski5 and Mickael Naassila1

1

INSERM UMR1247, GRAP, CURS, University of Picardie Jules Verne, Amiens, France 2UCBL, CRNL, INSERM U1028, CNRS UMR5292, University of Lyon, Lyon, France 3UP-MOPHA Department, Le Vinatier Hospital Centre, University Service of Addictology of Lyon (SUAL), Bron, France 4Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Universite´ catholique de Louvain, Louvain-la-Neuve, Belgium 5 Cognition Health Society Laboratory (C2S-EA 6291), University of Reims Champagne-Ardenne, Reims, France

LIST OF ABBREVIATIONS BEC BD DID NIAAA

However, the National Institute on Alcoholism and Alcohol Abuse (NIAAA) defines BD as “a pattern of drinking alcohol that brings blood alcohol content to 0.08-g% or above. For the typical adult, this pattern corresponds to consuming five or more drinks (male) (American drinks, i.e., 14 g of ethanol), or four or more drinks (female), in about 2 hours” (NIAAA, 2017). Compared to the WHO definition, the NIAAA definition of BD also involves the notion of a minimum drinking speed, and underlies deliberately seeking drunkenness. Consequently, these two common definitions of BD convey subtle conceptual differences, and the epidemiological populations that they delineate do not display the same clinical profile and severity level (Rolland et al., 2017). Moreover, the typical definitions of BD do not explore the frequencies of drinking or heavy drinking, or the average amount of alcohol used during BD episodes. As the severity of BD can directly depend on these parameters, BD populations merely studied using the usual definitions are actually very heterogeneous, which raises some important scientific issues (Ceballos & Babor, 2017; Rolland & Naassila, 2017). In this regard, a recent study has shown that, compared to the WHO criteria, the NIAAA criteria for BD identifies subjects with more severe drinking patterns and alcohol aftermaths (Rolland et al., 2017).

blood ethanol concentration binge drinking drinking in the dark National Institute on Alcohol Abuse and Alcoholism

DEFINITION AND DIAGNOSTIC OF BINGE DRINKING IN HUMANS Binge drinking (BD) refers to a specific pattern of alcohol use, namely drinking large amounts of alcohol in a short period of time (Courtney & Polish, 2009). Moreover, the usual conception of BD implies that binge sequences are also interspersed by periods of abstinence (SAMHSA, 2016), which allows to distinguish BD from some other patterns of unhealthy alcohol use, in particular severe alcohol dependence (Rolland & Naassila, 2017). For this reason, BD is frequently defined as an “episodic heavy use of alcohol” (SAMHSA, 2016; WHO (World Health Organization), 2014). In the epidemiological literature, the criteria for BD are essentially based on exceeding drinking cutoffs in a short amount of time. For example, WHO defines BD as the “consumption of 60 or more grams of pure alcohol (6 1 standard drinks in most countries) on at least one single occasion at least monthly” (WHO, 2014).

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00007-6

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7. ANIMAL MODELS OF BINGE DRINKING: BEHAVIOR AND CLINICAL RELEVANCE

By contrast, in a more experimental context, the impact of BD on brain and cognitive functioning has been evaluated based on a more behavioral definition of BD. For example, a frequently used indicator of BD is the “binge score,” which is based on both the frequency of excessive consumption and the average consumption speed (Smith et al., 2017). In this context, brain damage and cognitive alterations were found to be more severe with BD compared to social drinking and to be positively correlated with the binge score and even more correlated with the number of drunkenness episodes. Such findings revealed that both the level of intoxication and drinking speed, which is possibly the most important factor, were crucial factors in BD behavior (Smith et al., 2017). Fast alcohol consumption, frequently on an empty stomach, allows ethanol to reach the blood more rapidly and increases blood alcohol levels with a life-threatening speed. “Happy hours” during which alcoholic drinks are cheaper for a limited period of time promoted BD behavior and severe intoxication (Thombs et al., 2008) and, thus, new policies emerged in order to curb BD. Inspired from human real life and the culture of happy hours, animal studies have evolved to explore the efficacy of drastically shorten the access to alcohol to mimic BD induced by the happy hours strategy. Key concerns are about some specific features of the drinking patterns, that is, drinking intensity per drinking occasion, and frequency of drinking days and periods of abstinence between binging episodes. Moreover, recent data also suggest that BD is a heterogeneous phenotype. Binge drinkers should not be considered a unitary group, but rather a population of individuals displaying specificity regarding gender and personality dimensions (Gierski et al., 2017), as well as regarding drinking motivations and impulsivity (Lannoy, Billieux, Poncin, & Maurage, 2017a). Animal models are meant to parallel the human condition; however, rodents do not readily consume sufficient amounts of ethanol to achieve pharmacologically relevant blood ethanol concentrations (BEC). Even if it is a challenge, this chapter will present new perspectives indicating that creating rodents binge drinkers is now possible. The great interest of animal models is to control every environmental parameter and, thus, it is possible to investigate which individual and environmental factors can promote voluntary BD behavior in order to identify its neurobiological factors and to explain how the speed of drinking may be the keystone factor in this behavior.

RELEVANT CLINICAL CRITERIA FOR DEVELOPING ANIMAL MODELS OF BINGE DRINKING The specific pattern of BD behavior is an important factor to consider in the development of an animal model of BD. Thus, the quantity/frequency/duration parameter is crucial. Concerning the quantity, signs of intoxication (such as motor impairment, which is the most easily visible sign of intoxication in rodents) should be achieved with a sufficient amount of alcohol consumed in a short period of time. Even though intoxication is not part of the clinical definition, pharmacologically relevant BEC need to be achieved around 1 g/L especially when taking into account the fact that rodents metabolize alcohol much more rapidly than humans (3 times faster in rats: 300 mg/kg/h and 5.5 times faster in mice: 550 mg/kg/h). Concerning frequency, it must be emphasized that dependence diagnosis has been considered as an exclusion criterion in several studies focusing on BD (Morris, Dowell, Cercignani, Harrison, & Voon, 2017). The frequency of the BD is also important since different populations of binge drinkers can be distinguished such as “frequent” or “infrequent” binge drinkers, and animals can be used either to study the impact of very few as well as repeated BD episodes. The frequency of BD and individual history are important since chronic BD for several months or years is a risk factor for alcohol addiction and, thus, it is not often clear in the clinical population recruited for BD studies, whether or not some individuals are dependent. Finally, the quantity/duration or the speed of drinking is the most important parameter since BD needs to be dissociated from only the quantity factor and, thus, from heavy drinking behavior. Teenage BD is a major health concern and, thus, using a developmental approach with animal models of BD could be very useful in order to unravel the mechanisms underlying long-term vulnerability for alcohol dependence. A large body of studies in rodents used forced and repeated (intermittent) ethanol administrations during the adolescence period in rodents (the second month of life) and has, for example, showed that increased risk for consuming alcohol at adulthood may involve the reward deficit syndrome (AlauxCantin et al., 2013). Interestingly, it has been shown that intermittent access to voluntary ethanol drinking facilitates excessive drinking when rats are then exposed to chronic intermittent ethanol vapor (Kimbrough, Kim, Cole, Brennan, & George, 2017). Thus, the frequency and pattern of alcohol drinking may play a crucial role in vulnerability to dependence.

I. INTRODUCTORY CHAPTERS

FORCED ADMINISTRATION OF HIGH DOSES OF ALCOHOL

Clinical studies have showed that BD is associated with an impairment of executive functions including inhibitory control and decision-making (Lannoy, D’Hondt, Dormal, Billieux, & Maurage, 2017b). BD is also associated with alterations in gray and white matter that are correlated with cognitive impairments (Hermens et al., 2013). Interestingly results have revealed that BD is associated with impaired performance in cognitive tasks in females more than males (Townshend & Duka, 2005). Thus, both brain alterations and cognitive impairments (e.g., in prefrontal executive functions or memory) may be observed in animal models of BD and differences linked to gender may be particularly investigated. At the somatic level, studies provided evidence that BD, independently of daily alcohol intake, can lead to more severe forms of alcoholic liver disease in younger populations (Ventura-Cots, Watts, & Bataller, 2017).

CURRENT PRECLINICAL MODELS OF BINGE DRINKING Preclinical research on alcohol use disorders also suffers from the lack of a clear definition of BD behavior. Animal models attempt to parallel the human condition and it is very interesting to note that the NIAAA definition of BD in humans is also used in different works published on animals (Crabbe, Harris, & Koob, 2011).

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One method that has been used successfully for a long time to enhance voluntary alcohol intake is the scheduling of alcohol availability (Le Magnen, 1960). When animals have unlimited access to alcohol, the consumption bouts are usually titrated over a 24-hour period and even though significant pharmacologically relevant BEC may be obtained at some points during the day, animals do not display visible signs of motor impairment. The different animal models of BD can be divided in two large categories depending on the mode of administration: forced/passive administration of high alcohol doses versus voluntary/active alcohol consumption. The features of the different animal models of BD are presented in the Table 7.1.

FORCED ADMINISTRATION OF HIGH DOSES OF ALCOHOL In this first category, animals receive high doses of alcohol solution leading to rapid elevated BEC and clear signs of intoxication.

Gavage This simple procedure consists in the insertion of a guide cannula in the esophagus of the rodents and in the injection of a certain volume and dose of an ethanol solution (usually a 10% or 20% ethanol solution in

TABLE 7.1 Adequacy of the Different Procedures With the Pathophysiology of BD

The interest of the different procedures used to study is presented regarding intoxication, frequency, duration of intoxication, motivation and physiological consequences and rated from ( ) for no to (111) for high interest. IA, intermittent access; DID, Drinking in the dark.  Indicates that gavage is not appropriate to mimic BD in rats (Livy et al., 2003).

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FIGURE 7.1 BEC profiles in rats and mice after alcohol administration using gavage of intraperitoneal injections. BEC profiles after ethanol administration as a single dose of 3.8 g/kg of a 21% ethanol solution in either by means of intragastric gavage or intraperitoneal injections in mice and rats (males and females in both groups). Source: From Livy, D.J., Parnell, S.E., & West, J.R. (2003). Blood ethanol concentration profiles: A comparison between rats and mice. Alcohol (Fayetteville, N.Y.) 29, 165 171, Alcohol, ELSEVIER.

tap water). Rapidly and through the digestive tracts, BEC will increase following a pharmacodynamics that resembles to what can be observed in humans (Yang, Long, & Faingold, 2001) reaching more than 120 mg/ dL after 30 minutes, for example, after a gavage of 1.12 g/kg of a 10% ethanol solution (Chen et al., 2013) in mice. Major differences exist between mice and rats using the gavage procedure, for example, 300 and 100 mg/dL are achieved after a gavage of 3.8 g/kg of a 21% ethanol solution in mice and rats, respectively (Livy, Parnell, & West, 2003). Mice show rapid rise and elimination rates and higher peak BEC while rats show more gradual profiles and retain ethanol in their bloodstream for longer periods (Fig. 7.1). Thus, the gavage procedure has limited interest to investigate BD (Livy et al., 2003; Walker & Ehlers, 2009) and both gavage and intraperitoneal routes may also be of lower interest to study BD in rats. A large variety of studies on liver injury is performed following such paradigm (Thompson, Nazari, Jacobs, Grahame, & McKillop, 2017) while fewer studies used it in behavioral neurosciences (Anto´n et al., 2017; Griffin, Lopez, & Becker, 2009; Karelina et al., 2017).

Intraperitoneal Injections This procedure is even easier to set up in a lab than the gavage one. Intraperitoneal injections may induce less stress than the gavage procedure. There are also large differences between rats and mice using the intraperitoneal route and again, as for gavage, the peak BEC are lower in rats versus mice (Livy et al., 2003). Most of

the time, these procedures are used acutely and sometimes subchronically with a specific schedule of administration. Single or multiple injections of alcohol has long been used to study the effect of acute intoxication in rodents. High doses around 2 g of pure ethanol/kg of body weight (g/kg) for the mice and 3 g/kg for the rats are usually tested in order to induce intoxication level, but with no sedative/hypnotic effects (measured with the loss of the righting reflex). A paradigm using two consecutive injections of alcohol 9 hours apart to mimic a double binge-like episode has been used in the laboratory of Naassila in order to determine if only two BD may be deleterious for memory and synaptic plasticity. As expected, using this procedure in adolescent rats, Silvestre de Ferron and colleagues (2015) demonstrated that only two intoxications induced by injections of 3 g/ kg of ethanol, leads to an alteration of synaptic plasticity responsible to a perturbation of memory processes. A multitude of variants of this procedure can be found in the literature. For example, Pascual, Blanco, Cauli, Min˜arro, and Guerri (2007) developed a protocol in which rats received a total of eight intraperitoneal injections following a schedule of one daily injection for 2 days in a row then 2 days off and so on until rats received the eight injections. The idea is to mimic BDlike ethanol exposure during half of the adolescent period (15 days out of the 30-day period) as observed in humans and also to introduce withdrawal-like period with the 2-day off intervals. The authors found that this pattern of alcohol injections leads to behavioral alterations (evaluated in a conditioned discrimination learning task) and is associated to brain damages linked to apoptosis and neuroinflammation. Numerous studies have now been published using this procedure (Alaux-Cantin et al., 2013; Montesinos, Pascual, Rodrı´guez-Arias, Min˜arro, & Guerri, 2016; Pascual et al., 2012).

Inhalation of Alcohol Vapors Inhalation of alcohol vapors has been developed to induce physical signs of alcohol dependence upon a procedure of long intoxication periods (usually 14 hours on/10 hours off/day and target BECs: 175 250 mg%) every day for several weeks (Le Bourhis, 1975; Le Bourhis Aufre`re, 1983; Schulteis, Markou, Cole, & Koob, 1995; Simon-O’Brien et al., 2015). These durations of intoxication seem too long to be associated to binge-like intoxication. To our knowledge, short periods of exposition to ethanol vapors have not been used to mimic BD.

Forced Drinking For this procedure, rats or mice are kept usually in their homecage and instead of having water delivered

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VOLUNTARY ALCOHOL CONSUMPTION

ad libitum, only alcohol is available. Thus, rodents have to drink the alcohol solution to survive. The scheduled high alcohol consumption is another paradigm in which availability of water is restricted and, thus, rats are also forced to drink the only available fluid for survival (Cronise, Finn, Metten, & Crabbe, 2005) All these procedures have the advantage to induce signs of alcohol intoxication and allow the researchers to observe direct consequences of binge-like intoxication. In addition, they are simple to setup in all laboratories, not expensive in equipment and rapidly generate experimental animals. Multiple types of experiments can be performed following such procedures such as genetic (Pascual et al., 2007) and behavioral studies in neurosciences, but also in study of the microbiota (Chen et al., 2015) and liver injury. However, the limitations are, firstly, the fact that the animals do not decide to consume alcohol. It is, thus, difficult or even impossible to evaluate some important parameters of drug consumption such as the motivation to consume and the seeking for the drug, for example, in a nonoperant paradigm. Finally, even though the alcohol exposure with the gavage procedure would appear at a better place regarding its face validity compared to the intraperitoneal route, it should be considered that, at least in rats, its interest is limited to mimic BD since the achieved peak BEC and alcohol elimination rate are low.

VOLUNTARY ALCOHOL CONSUMPTION On the opposite side to forced alcohol administration, voluntary alcohol consumption usually does not allow to achieve sufficient levels of BEC to induce any behavioral signs of intoxication. Nowadays, several protocols, mostly in mice and sometimes in rats, have been developed to induce high levels of BEC.

20% Alcohol Intake in the Two-Bottle Choice Intermittent Access Model In, 1973, Roy Wise described a protocol of voluntary alcohol consumption in a two-bottle choice paradigm in which rats have access to one bottle of tap water and one of alcohol (20% ethanol solution) every other day. Using this protocol, rats developed an escalation of their consumption leading to alcohol intake of more than 5 g/kg per day. This procedure found a new revival in the beginning of the 2000s with several publications (Carnicella, Amamoto, & Ron, 2009; Carnicella, Ron, & Barak, 2014; Simms et al., 2008; Simon-O’Brien et al., 2015). This procedure is normally used to study longterm alcohol consumption over a 24-hour period.

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However, it has been shown that the animals will consume a large part of their total intake only during the first hours of presentation of the alcohol bottle. Depending on the authors, the duration of this bingelike consumption is measured during the 2, 3 or 4 first hours.

Two-Bottle Choice Drinking-in-the-Dark Model The most-used model to mimic BD is the drinking in the dark (DID) procedure in which animals drink large amounts of ethanol in general during the first hours of the dark cycle either immediately upon lights out (for rats) or after 3 or 4 hours (for mice) and display BEC in excess of 0.8 g/L (Thiele, Crabbe, & Boehm, 2014). A multiple scheduled access (MSA) has been added to the DID procedure in which animals’ experience between 2and 4-hour access periods across the 12-hour dark cycle with each access period separated by 2 or more hours. However, this DID-MSA procedure has mainly been used in alcohol-preferring mice and not outbred animals, thus, it does not allow for generalization in highly heterogeneous populations. In addition for this specific protocol, a selected mouse line to show elevated alcohol consumption in the DID model has been generated by Crabbe and his colleagues (Crabbe et al., 2009). These mice can consume up to 6 kg/kg within the 4-hour period of access to the ethanol solution.

Two-Bottle Choice Drinking in the Dark for Rats Very recently, Holgate, Shariff, Mu, and Bartlett (2017) developed this DID procedure for rats in which rats drink more alcohol during the first 30 minutes than the rats used to drink using the 20% intermittent access protocol (0.81 vs 0.73 g/kg/30 min).

Operant Binge Drinking We recently developed a variant of the regular operant self-administration paradigm in rats with a very short access period to alcohol each day of the week (Jeanblanc et al., 2018; Lebourgeois, Gonza´lez-Marı´n, Jeanblanc, Naassila, & Vilpoux, 2017). After several weeks of training under a fixed ratio 3 (3 lever presses to get 0.1 mL of 20% ethanol) during 1 hour (moderate drinkers) then 30 minutes (high drinkers), we further reduced the duration of the daily sessions to only 15 minutes (binge drinkers) and we observed an increase in ethanol consumption (Fig. 7.2) leading to ethanol consumption above 1.2 g/kg with clear signs of intoxication (i.e., sedation and ataxia: loss of locomotor coordination) (Jeanblanc et al., 2018).

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The pattern of alcohol deliveries and the number of lever presses are presented in Fig. 7.3. The pattern of alcohol deliveries of the binge drinker rats clearly shows that rats display a very high speed of ethanol drinking. After several weeks of chronic daily BD, we also observed signs of withdrawal with increased motivation to consume alcohol even for highly concentrated solution (30% ethanol) and aggressive behavior and vocalizations. In this model we demonstrated that the speed of consumption is more important than the quantity of alcohol consumed to define a model of BD. Finally we also observed somatic damage in binge drinkers rats with the BD group displaying typical signs of hepatic steatosis (Fig. 7.4). More importantly, we demonstrated that our model displays a very good predictive validity because all the current treatments of alcohol use disorders (nalmefene, naltrexone, acamprosate, sodium oxybate and baclofen) were effective to reduce BD (Gonza´lez-Marı´n, Lebourgeois, Jeanblanc, Diouf, Naassila, 2018). Our operant model of BD displays better predictive validity compared with the DID one since DID mice were sensitive to the

Ethanol consumed 1 (g/kg)

effects of acamprosate and baclofen, but not naltrexone (Crabbe et al., 2017).

CONCLUSIONS AND NEED FOR FUTURE RESEARCH The choice of the animal species and the procedure of alcohol administration are crucial to set up an appropriate animal model of BD for addressing both neurobiological and behavioral aspects. Animal models using forced/passive ethanol administration are largely used to explore brain and somatic consequences of BD. The other models using voluntary intake display better face validity since they allow investigation of both the impact of the high speed of drinking and the motivational aspect BD that may, thus, be useful in order to investigate the transition to alcohol dependence. Thus, animal models of BD using voluntary intake should be preferred for future research especially because recent data indicate that this procedure can lead to very fast alcohol intake FIGURE 7.2 Limiting the duration of session promotes binge drinking in the operant paradigm. The cumulative number of lever presses are presented depending on the duration of the session 1 h, 30, and 15 min. Shortening the session duration very significantly increases the level of alcohol amount and the speed of drinking. Source: From Jeanblanc and Naassila, unpublished data.

FR3 – 20% ethanol 15 min

FR3 – 20% ethanol 30 min

0.5

FR3 – 10% ethanol 1h 0.25

15′

30′ Durations of the sessions

1h

FIGURE 7.3 Pattern of alcohol deliveries in binge drinkers (14 min access), high drinkers (30 min access), and moderate drinkers (1 h access). Each bar represents an alcohol delivery (0.1 mL of 20% ethanol solution), the total number of lever presses is also indicated on the right. Source: From Jeanblanc and Naassila, unpublished data.

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MINI-DICTIONARY OF TERMS

and even to induce both cognitive and liver damages. The combination of high speed of drinking with the possibility to study the motivational aspects in the same animal model of BD makes it an appropriate model of human BD behavior. In humans, the study of the motivation for BD is an important component in the field of research of BD. Few animal models of voluntary alcohol intoxication are available for rats; most of the models are developed with inbred mice leading to difficulties for the evaluation of interindividual vulnerability profile towards BD. Making animals binge drinkers by themselves is now possible and open new perspectives for research. Future research is also needed regarding several unexplored aspects of BD behavior such as the construct validity (brain circuits and cognitive functioning), predictive validity (efficacy of pharmacotherapies), the role of gender, the role of social interaction, and individual determinants such as impulsivity and genetic variations (Fig. 7.5).

MINI-DICTIONARY OF TERMS

FIGURE 7.4 Hepatic gross morphology after BD. Representative liver harvested from the BD group (A) showed typical signs of steatosis, with more yellow and rough surfaces comparing with those of the alcohol naı¨ve rats (B). Source: From Jeanblanc and Naassila, unpublished data.

Alcohol intermittent access Schedule of alcohol access in which subjects have access to highly (20%) concentrated ethanol solution every other day and that facilitate escalation of ethanol intake in rodents. Drinking in the dark High ethanol consumption associated with high BEC are achieved in C57BL/6J mice when mice receive 20% ethanol in place of water for 2 hours over 4 consecutive days and when ethanol is given 3 hours into the dark cycle, Operant paradigm Operant self-administration is conducted in operant chambers (Skinner boxes), where a subject is allowed to bar press on a lever in order to receive the reinforcer (ethanol). Cues such as lights alert the animal that the reinforcer is available and become conditioned stimuli (after conditioning).

FIGURE 7.5 Validity of the animal models of BD. Animal models of BD should display good face validity, construct validity and predictive validity.

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7. ANIMAL MODELS OF BINGE DRINKING: BEHAVIOR AND CLINICAL RELEVANCE

KEY FACTS Animal Models of Binge Drinking • Models of voluntary BD bring complementary information to that of models of forced intoxication • Models of BD must include high drinking speed, significant intoxication level, repeated number of intoxications and may thus potentially be able to induce dependence. • In models of voluntary BD, significant levels of blood ethanol are rarely achieved. • Models of voluntary BD mainly use inbred mice and DID and thus do not allow the study of interindividual vulnerability. • Model of BD may allow the study of the transition to dependence.

SUMMARY POINTS • This chapter reviews current data on animal models of BD. • The models that use either forced alcohol exposure (inhalation, gavage, intraperitoneal injection, liquid diet, alcohol solution as the sole source of fluid), or voluntary alcohol intake (DID, 20% alcohol intermittent access, operant self-administration) are presented. • Rodents do not readily consume a high level of ethanol to mimic BD behavior. • Speed of drinking and behavioral signs of alcohol intoxication are the keystone of good animal models of BD. • Future studies should explore the predictive validity of the models and the interindividuals features (gender, genetics).

Acknowledgments BJ and MN received a grant from the “Fonds Actions-Addictions” (http://actions-addictions.org), which is an independent French foundation supporting evidenced-based actions against addictive disorders. PM is a research associate at the Fund for Scientific Research (F.R.S. FNRS, Belgium). This chapter has been supported by a grant from the “Fonds Actions-Addictions.”

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cortex and depressive-like behavior induced by ethanol binge administration. Addiction Biology, 22, 724 741. Available from https://doi.org/10.1111/adb.12365. Carnicella, S., Amamoto, R., & Ron, D. (2009). Excessive alcohol consumption is blocked by glial cell line-derived neurotrophic factor. Alcohol (Fayetteville, N.Y.), 43, 35 43. Available from https://doi. org/10.1016/j.alcohol.2008.12.001. Carnicella, S., Ron, D., & Barak, S. (2014). Intermittent ethanol access schedule in rats as a preclinical model of alcohol abuse. Alcohol (Fayetteville, N.Y.), 48, 243 252. Available from https://doi.org/ 10.1016/j.alcohol.2014.01.006. Ceballos, F., & Babor, T. F. (2017). Binge drinking and the evolving language of alcohol research. Journal of Studies on Alcohol and Drugs, 78(4), 488 490. Chen, M. M., Palmer, J. L., Ippolito, J. A., Curtis, B. J., Choudhry, M. A., & Kovacs, E. J. (2013). Intoxication by intraperitoneal injection or oral gavage equally potentiates postburn organ damage and inflammation. Mediators of Inflammation, 2013, 971481. Available from https://doi.org/10.1155/2013/971481. Chen, P., Miyamoto, Y., Mazagova, M., Lee, K. C., Eckmann, L., & Schnabl, B. (2015). Microbiota protects mice against acute alcohol-induced liver injury. Alcoholism, Clinical and Experimental Research, 39, 2313 2323. Available from https://doi.org/10.1111/acer.12900. Courtney, K. E., & Polish, J. (2009). Binge drinking in young adults: Data, definitions, and determinants. Psychological Bulletin, 135(1), 142 156. Crabbe, J. C., Harris, R. A., & Koob, G. F. (2011). Preclinical studies of alcohol binge drinking. Annals of the New York Academy of Sciences, 1216, 24 40. Crabbe, J. C., Ozburn, A. R., Metten, P., Barkley-Levenson, A., Schlumbohm, J. P., Spence, S. E., . . . Huang, L. C. (2017). High Drinking in the Dark (HDID) mice are sensitive to the effects of some clinically relevant drugs to reduce binge-like drinking. Pharmacology Biochemistry and Behavior, 160, 55 62. Available from https://doi.org/10.1016/j.pbb.2017.08.002. Crabbe, J. C., Metten, P., Rhodes, J. S., Yu, C. H., Brown, L. L., Phillips, T. J., & Finn, D. A. (2009). A line of mice selected for high blood ethanol concentrations shows drinking in the dark to intoxication. Biological Psychiatry, 65, 662 670. Available from https://doi.org/10.1016/j.biopsych.2008.11.002. Cronise, K., Finn, D. A., Metten, P., & Crabbe, J. C. (2005). Scheduled access to ethanol results in motor impairment and tolerance in female C57BL/6J mice. Pharmacology, Biochemistry, and Behavior, 81, 943 953. Gierski, F., Benzerouk, F., De Wever, E., Duka, T., Kaladjian, A., Quaglino, V., & Naassila, M. (2017). Cloninger’s temperament and character dimensions of personality and binge drinking among college students. Alcoholism, Clinical and Experimental Research, 41(11), 1970 1979. Available from https://doi.org/ 10.1111/acer.13497. Gonza´lez-Marı´nn, M. C., Lebourgeois, S., Jeanblanc, J., Diouf, M., & Naassila, M. (2018). Evaluation of alcohol use disorders pharmacotherapies in a new preclinical model of binge drinking. Neuropharmacology, 140, 14 24. Available from https://doi.org/ 10.1016/j.neuropharm.2018.07.015. Griffin, W. C., III, Lopez, M. F., & Becker, H. C. (2009). Intensity and duration of chronic ethanol exposure is critical for subsequent escalation of voluntary ethanol drinking in mice. Alcoholism: Clinical and Experimental Research, 33, 1893 1900. Available from https://doi.org/10.1111/j.1530-0277.2009.01027.x. Hermens, D. F., Lagopoulos, J., Tobias-Webb, J., De Regt, T., Dore, G., Juckes, L., . . . Hickie, I. B. (2013). Pathways to alcohol-induced brain impairment in young people: A review. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 49, 3 17. Available from https://doi.org/10.1016/j.cortex.2012.05.021.

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C H A P T E R

8 Prenatal Alcohol Exposure: Developmental Abnormalities in the Brain 1

David J. Rohac1, Charles W. Abbott2 and Kelly J. Huffman3

Department of Psychology, University of California, Riverside, CA, United States 2Interdepartmental Neuroscience Program, University of California, Riverside, CA, United States 3Department of Psychology and Interdepartmental Neuroscience Program, University of California, Riverside, CA, United States

LIST OF ABBREVIATIONS ARND CDC DNA DTI FA FAS FASD fMRI INCs MD MRI P(0, 20, 50) pFAS PrEE S1 SWM V1

changes associated with prenatal alcohol, or ethanol exposure (PrEE) is discussed by exploring human brain imaging studies of individuals with FASD, as well as data generated from animal models. Additionally, it argues for the need for further investigation into potential mechanisms beginning with PrEE and leading to the FASD phenotype. This is important from both basic and translational science perspectives; we need to understand how PrEE alters brain development in such profound ways, and use that information to generate viable methods to effectively prevent and treat FASD. Before the broad term FASD was adopted, fetal alcohol syndrome (FAS) was first used to describe the effects of PrEE in children (Lemoine, Harousseau, Borteyru, & Menuet, 1968; Jones, Smith, Ulleland, & Streissguth, 1973). Today, this classification is reserved for the most severe PrEE-related phenotypes. Children with FAS often have prenatal and postnatal growth deficiencies, microcephaly, characteristic craniofacial dysmorphologies, and varying degrees of central nervous system dysfunction (Lemoine, et al., 1968; Jones et al., 1973; Chudley et al., 2005). Soon after the initial definition of FAS, it became apparent that lower levels of maternal drinking in pregnancy could impact the child in a less severe, yet still significant, way. Thus, the encompassing classification FASD was created to describe the range of phenotypes observed in PrEE children (Streissguth & O’Malley, 2000). Besides FAS, two additional diagnostic classifications within FASD describe the extent of damage due to PrEE. These include alcohol-related neurodevelopmental disorder (ARND) and partial FAS (pFAS). ARND, pFAS, and

alcohol-related neurodevelopmental disorder Centers for Disease Control and Prevention deoxyribonucleic acid diffusion tensor imaging fractional anisotropy fetal alcohol syndrome fetal alcohol spectrum disorders functional magnetic resonance imaging intraneocortical connections mean diffusivity magnetic resonance imaging postnatal day (#) partial fetal alcohol syndrome prenatal ethanol exposure primary somatosensory cortex spatial working memory primary visual cortex

INTRODUCTION Alcohol consumption during pregnancy is the leading known cause of preventable developmental delay and intellectual disability in the United States (Stratton, Howe, & Battaglia, 1996; Williams, Smith, & Committee on Substance Abuse, 2015). Fetal alcohol spectrum disorders (FASD) is an umbrella term used to describe a range of developmental defects that occur in an individual whose mother consumed alcohol during her pregnancy. These defects can include physical abnormalities, cognitive behavioral deficits, and learning disabilities that may impact the child throughout life. In this chapter, a range of developmental brain

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00008-8

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8. PRENATAL ALCOHOL EXPOSURE: DEVELOPMENTAL ABNORMALITIES IN THE BRAIN

TABLE 8.1 Summary of FASD Phenotypes Diagnosis

FAS

pFAS

ARND

Facial phenotype

Smooth philtrum

Smooth philtrum

Not observed

and

or

Thin vermillion order

Thin vermillion order

and

or

Small palpebral Fissures

Small palpebral Fissures

and

and/or

Low birth weight for gestational age

Low birth weight for gestational age

or

or

Decelerating weight over time

Decelerating weight over time

or

or

Low weight to height

Low weight to height

and

or

Growth retardation

CNS Decreased cranial size at birth dysfunction or

Decreased cranial size at birth

Decreased cranial size at birth

or

or

Structural brain abnormalities

Structural brain abnormalities

Structural brain abnormalities

or

or

or

Neurological signs (ex. poor motor skills, hearing loss, poor hand eye coordination, etc.)

Neurological signs (ex. poor motor skills, hearing loss, poor hand eye coordination, etc.)

Neurological signs (ex. poor motor skills, hearing loss, poor hand eye coordination, etc.)

or

or

Behavior or cognitive abnormalities and confirm alcohol exposed

Behavior or cognitive abnormalities

Other

FASD diagnosis summary. Overview of diagnostic criteria commonly used to classify FASD cases in children.

FAS range in severity from mild to most severe, and represent a set of recognizable phenotypes in three primary areas: (1) prenatal and/or postnatal growth deficiency; (2) central nervous system dysfunction; and (3) pattern of facial malformations (Riley & McGee, 2005). A summary of the common features of these classifications can be seen in Table 8.1. FASD prevalence rates in the United States are high with approximately 2% 5% of newborns impacted by prenatal alcohol exposure. Although less common, estimates of FAS births hover just below 1% (Williams et al., 2015). Recently, after years of debate on medical recommendations regarding drinking during pregnancy, the American Academy of Pediatrics stated that there is “no known safe amount of alcohol for a pregnant women to drink” (Williams et al., 2015). Unfortunately, despite this strong language, and similar statements by the Centers for Disease Control and Prevention (CDC), 18.6% of pregnant women age 35 44 continue to drink alcohol during their pregnancies (Tan, Denny, Cheal, Sniezek, & Kanny, 2015).

STUDIES IN HUMANS WITH FETAL ALCOHOL SPECTRUM DISORDER Decades ago, autopsy data revealed distinct alterations of the corpus callosum, enlarged ventricles, a reduced cerebellum, and other brain anomalies including neuronal and glial development as well as microcephaly and microencephaly in people with FASD (Clarren, Alvord, Sumi, Streissguth, & Smith, 1978: Jones et al., 1973; Peiffer, Majewski, Fischbach, Bierich, & Volk, 1979). Since these early works, human brain imaging studies have shown reduced overall brain volume and altered neuroanatomical development of brains structures, such as the corpus callosum (Bookstein, Sampson, Connor, & Streissguth, 2002; Bookstein, Streissguth, Sampson, Connor, & Barr, 2002). These results suggest that changes to brain morphology may underlie the often complex cognitive and behavioral phenotypes observed in people with FASD. The development of in vivo imaging techniques has transformed our ability to diagnose, explore, and track

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STUDIES IN HUMANS WITH FETAL ALCOHOL SPECTRUM DISORDER

changes in the brain. Magnetic resonance imaging (MRI) is a safe, noninvasive technique that can be used to study brain structure and function. Using different contrast techniques, several types of diagnostic tools have been developed, including structural MRI, functional MRI (fMRI), and diffusion tensor imaging (DTI).

Structural Brain Imaging Consistent with early autopsies, structural MRI studies repeatedly demonstrate significantly reduced overall brain volume in patients with FASD. Some studies have shown volumetric differences in white matter and gray matter, or both (Table 8.2). Structural imaging studies also confirm PrEE’s ability to disrupt normal development of the corpus callosum. Bookstein et al. (2002) found a high level of variance in the shape of the corpus callosum of FASD cases and concluded that it is a distinguishing characteristic useful for diagnosis. The neocortex is strongly implicated in FASD, as complex regulation of cognition, learning, behavior, sensorimotor integration, and sophisticated skills are often attributed to cortical function. Within the neocortex, the frontal, parietal, and temporal lobes show PrEE-related defects in cortical thickness, with either increases or decreases found in different cortical areas (Sowell et al., 2002, 2008b). In these studies, Sowell and colleagues found a reduced volume of the ventral frontal lobes of the left hemisphere of children with FASD (Sowell et al., 2002). Subsequent studies by Sowell found increased cortical thickness in both FAS cases and children with less severe diagnoses (Sowell et al., 2008b). MRI studies also demonstrate that PrEE can impact the development of the cerebellum, hippocampus, caudate nucleus, basal ganglia, and other subcortical structures (Table 8.2). Commonly observed motor and learning deficits presented in subjects with FASD suggest possible cerebellar dysfunction in response to PrEE. Imaging studies confirm this and demonstrate a significant volumetric reduction in FAS cases (Archibald et al., 2001). Additional exploration of the cerebellum reveals site-specific reductions within the anterior vermis, whereas the posterior vermis is unaffected (Sowell et al., 1996). The effects of PrEE on developing hippocampal volume in late childhood were investigated by Willoughby, Sheard, Nash, and Rovet (2008). Here, researchers found that PrEE resulted in reduced left hippocampal volume, with volume not significantly increasing with age as it did in normal, healthy subjects. Further investigation into PrEE-derived changes within developing subcortical structures revealed volumetric reductions in both the caudate nucleus and basal ganglia (Cortese et al., 2006; Archibald et al., 2001).

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Functional Brain Imaging fMRI data has shown differential patterns of cortical activation correlating with spatial memory, verbal learning, verbal working memory, and visual working memory in PrEE subjects. Early fMRI studies examining brain function in subjects with FASD investigated brain activation during a spatial working memory (SWM) task (Malisza, Allman, & Shiloff, 2005). Results from this work indicated that children and adults with FASD had greater activity in the inferior and middle-frontal cortex. These findings were extended by Spadoni et al. (2009), who showed changes in the activation patterns of FASD patients when performing similar SWM tasks, with greater activation within dorsolateral frontalparietal regions of cortex. The prefrontal cortex, which is thought to play a strong role in behavioral inhibition and impulse control, also displays differential activation in subjects with FASD. A study by Fryer in 2007 indicated that participants with FASD showed increased functional activation in the prefrontal cortex and decreased activation in the caudate nucleus during trials that required response inhibition.

Diffusion Tensor Imaging Preliminary DTI studies focused on callosal defects, which persisted into young adulthood of individuals with FAS (Ma et al., 2005). Using fractional anisotropy (FA) and mean diffusivity (MD) measures from select regions of interest in the corpus callosum, researchers were able to identify lower FA and higher MD within the splenium and genu of the corpus callosum of FAS subjects, suggesting microstructural defects. Additional studies by Sowell et al. in 2008 found lower FA in the lateral splenium, posterior cingulate, right temporal lobe, right internal capsule, and brain stem. Sowell also found that white matter density was reduced in the same areas FA was lowered. This suggests that PrEE results in disorganized fiber tracts, signified by lower FA, that may be a consequence of reductions in myelin development.

The Role of Animal Research in Our Understanding of Fetal Alcohol Spectrum Disorder Although human brain imaging studies inform us of the human condition by describing the ways in which the brain can be altered by PrEE, it is difficult to experimentally investigate how these neuroanatomical or functional changes occur. We need controlled experimental methodology to identify the biological mechanisms that generate changes in the brain. Animal models allow researchers to experimentally

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TABLE 8.2 Anatomy and Functional Results of MRI Scans of FASD Patients Structural studies Published by

Overall brain volume

Corpus Cerebellum callosum

Subcortical

Mattson, Schoenfeld, and Riley (2001)

 (Cerebral, cranial)



 Caudate, thalamus, basal ganglia, lenticular

Riley and McGee (2005)



 



Joseph, Warton, and Jacobson (2014) Swayze et al. (1997)

Small brain stem Altered hippocampus and caudate nucleus



 

Clark, Li, Conry, Conry, and Loock (2000) Archibald et al. (2001)



Sowell et al. (2008b)

 (Total vol., intracranial,



 (Intracranial vault)

 Caudate nucleus 

WM, GM, and CSF)

Riikonen, Salonen, Partanen, and Verho (1999)

nucleus, diencephalon enlarged ventricles



Sowell et al. (1996) Johnson, Swayze, Sato, and Andreasen (1996)





Bookstein et al. (2002)

 Caudate, left hippocampus Varied shape

Willoughby et al. (2008)



Autti-Ramo et al. (2002)

 (Cerebral and skull)

Chen, Coles, Lynch, and Hu (2012)



Cortese et al. (2006)



Astley et al. (2009)



Meintjes, Jacobson, and Molteno (2010)



Roussotte, Sulik, and Mattson (2012)

 (Overall vol. and cortical

Rajaprakash, Chavrakarty, Lerch, and Rovet (2014)

 (Overall and GM)

Nardelli, Lebel, Rasmussen, Andrew, and Beaulieu (2011)

 (Intracranial vault, total

 Hippocampus 

 Left caudate 



 Caudate, putamen, hippocampus

 Basal ganglia, left putamen and right

GM)

palladium

 Caudate, putamen, thalamus, amygdala,

WM and deep cortical GM)

hippocampus, globus pallidus



Yang, Phillips, and Kan (2012) Li et al. (2008)



Zhou, Lebel, and Lepage (2011)



Lebel, Roussotte, and Sowell (2011)

 (GM and WM)

 Caudate, putamen, thalamus, ventral

Treit et al. (2013)



 Basal ganglia, hippocampus, globus pallidus

diencephalon

Functional studies Spadoni et al. (2009) Fryer, Tapert, and Mattson (2007) Malisza et al. (2005)

 Dorsolateral frontal-parietal  Prefrontal cortex   Inferior and middle-frontal

Structural and functional MRI studies of subjects with prenatal alcohol exposure and their findings in select brain areas. CSF, Cerebrospinal fluid; GM, gray matter; WM, white matter.

STUDIES IN HUMANS WITH FETAL ALCOHOL SPECTRUM DISORDER

control or manipulate factors, including dosage, pattern and timing of exposure, nutritional status, maternal factors, and genetics, which aid our understanding of mechanisms of PrEE-related changes and deficits.

Prenatal Ethanol Exposure and Neuroanatomical Development: Alterations in Subcortical Structures PrEE-induced alterations of specific brain structures have been discovered using animal models of FASD. Along with neuroimaging studies in humans, animal models reveal the largest deviations within the basal ganglia, CA3 regions of the hippocampus and the corpus callosum (Abbott, Kozanian, Kanaan, Wendel, & Huffman, 2016; Godin, Dehart, Parnell, O’Leary-Moore, & Sulik, 2011; Norman, Crocker, Mattson, & Riley, 2009). Data suggest that PrEE causes a delay in the development of these structures, possibly from altered gene expression patterning in early development. Studies documenting changes to the corpus callosum confirm results from human imaging studies and show consistent abnormal development from PrEE (Livy & Elberger, 2008). Presented in Fig. 8.1, measures of the basal ganglia show reduced volume at birth, which then recovers to normal volume later in development. Analysis of the CA3 region of the hippocampus showed an initial reduction in thickness at birth with a thickening noted at later developmental stages that persists into adulthood. Finally, measures of the corpus callosum showed a significantly thinner corpus callosum at birth and at 20 days old; however, by adulthood the thickness was greater than control brains (Fig. 8.1). Similar anatomical changes have been observed in humans with FASD and may be associated with deficits in executive function (Bookstein et al., 2002).

Prenatal Ethanol Exposure and Neuroanatomical Development: Alterations in Neocortex When considering how the brain may be damaged in PrEE, we can look to phenotypes in children with FASD. The motor and cognitive behavioral issues observed in children with FASD strongly suggest that the neocortex, the brain structure responsible for complex behavior, language, fine motor skills, and highlevel cognitive processing is particularly susceptible to developmental damage caused by PrEE. During brain development, the neocortex is vulnerable to modification either through intrinsic influences, such as gene expression, or experience-dependent changes from altered sensory input or toxic exposures (El Shawa, Abbott, & Huffman, 2013; Sur & Rubenstein, 2005). Although plasticity still occurs in the adult cortex (Pons

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et al., 1991), the developing neocortex is particularly sensitive to modification from toxic exposures that can have long-lasting behavioral ramifications (Abbott et al., 2016). Indeed, reports from animal models of FASD have shown significant defects in the anatomy of the neocortex and how it is patterned in development.

Prenatal Ethanol Exposure Impacts Thickness of the Neocortex PrEE significantly impacts the developmental trajectory of the cortex in a way that alters the rate of thickening of the cortical sheet. Specifically, thickening of frontal cortex, putative primary somatosensory cortex (S1), and putative primary visual cortex (V1) along with thinning of the prelimbic cortex and putative primary auditory cortex in newborn PrEE mice has been observed (Abbott et al., 2016). During normal development, area and layer-dependent cortical thinning occurs across the neocortex, and PrEE mice show a delay in this pattern of natural cortical thinning (Abbott et al., 2016). The process of cortical thinning and pruning during development proceeds at variable rates dependent on brain region (Sowell et al., 2004), and alcohol exposure during the prenatal period seems to impact these regions differentially. However, for all cortical regions except the visual cortex, the altered cortical thickness is sustained at least until early adulthood in a mouse model of FASD (Abbott et al., 2016).

Neocortical Circuitry Development and Prenatal Ethanol Exposure: Gene Expression and Intraneocortical Connections Proper gene expression within the neocortex during development is critical for accurate targeting of intraneocortical connections (INCs), which form the circuitry that generates complex function in the animal. If gene expression is changed during cortical patterning due to exposure to a toxin such as alcohol, then development of the circuit may be derailed, leading to a disorganized, abnormal neocortex. Previous studies have demonstrated a wide range of gene expression changes due to PrEE. Specifically, work from our laboratory has shown an observable shift in the expression patterns of three specific genes: Rzrß, Cad8, and Id2 (Fig. 8.2). Additional studies, using quantitative polymerase chain reaction methods, demonstrate quantifiable changes to gene expression within rostral and caudal regions of cortex (Abbott, Rohac, Bottom, Patadia, & Huffman, 2017). In that report, our laboratory showed that PrEE can alter the epigenome, generating differential deoxyribonucleic acid (DNA) methylation in the neocortex of mice,

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8. PRENATAL ALCOHOL EXPOSURE: DEVELOPMENTAL ABNORMALITIES IN THE BRAIN

FIGURE 8.1 Select subcortical anatomical measures in PrEE mice at P0, P20, and P50. Nissl-stained coronal sections demonstrate measures of the basal ganglia (BG), CA3 of the hippocampus, and corpus callosum (CC). Measures of the BG show reduced volume at P0 (A1 vs A2), with no differences later in development (A3 A6). Analysis of the CA3 region showed an initial reduction in thickness at P0 (B1 vs B2) with a thickening noted at later developmental stages (B4 and B6 vs B3 and B5) that persists into adulthood. Finally, measures of the corpus callosum showed a significantly thinner corpus callosum at P0 (C2 vs C1) and at P20 (C4 vs C3); however, by adulthood the thickness was greater than control brains (C6 vs C5). Scale bar 5 500 µm, Control n 5 8, PrEE n 5 8 for all ages. Source: Taken with permission from Abbott, C.W., Kozanian, O.O., Kanaan, J., Wendel, K.M., & Huffman, K.J. (2016). The impact of prenatal ethanol exposure on neuroanatomical and behavioral development in mice. Alcoholism: Clinical and Experimental Research, 40(1), 122 133.

concomitant with altered gene expression. It is possible that these changes in DNA methylation perturb gene expression, leading to ectopic development of the neocortical circuit (Abbott et al., 2017). Patterned in early development, INCs form the circuitry that is paramount for proper nervous system function and rely on proper gene expression for correct developmental targeting. These connections enable complex behavior by processing sensory inputs and

motor outputs (Dye, El Shawa, & Huffman, 2011a; Dye, El Shawa, & Huffman, 2011b). PrEE disrupts the normal developmental patterning of connections within sensorimotor regions in the neocortex, as is observed in newborn mice exposed to alcohol prenatally (El Shawa et al., 2013). Connections of sensory and motor areas within neocortex have fairly restricted borders in normal, control mice. For example, the V1 receives input from nearby areas, and its connections

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FIGURE 8.2 Neocortical gene expression of Rzrß, Cad8, and Id2. 100 µm Coronal sections of P0 control and PrEE brain hemispheres following free-floating nonradioactive in situ hybridization. A1 (Control, Rzrß) section of caudal cortex, left arrow denotes lower medial expression and right arrow denotes moderate lateral expression. A2 (PrEE, Rzrß) section of caudal cortex, left arrow denotes moderate medial expression and right arrow denotes high lateral expression. B1 (Control, Rzrß) section through rostral cortex where left black arrow denotes low medial expression, white middle arrow denotes the medial boundary of Rzrß, and right arrow denotes moderate lateral expression. B2 (PrEE, Rzrß) section through rostral cortex where left black arrow denotes moderate medial expression, white middle arrow denotes the shifted medial boundary of Rzrß expression and right arrow denotes high lateral expression. C1 (Control, Cad8) section through rostral cortex where black arrow denotes the lateral boundary of Cad8 expression. C2 (PrEE, Cad8), section through rostral cortex where black arrow denotes a shifted lateral boundary of expression. D1 (Control, Id2) section through rostral cortex where black arrow denotes an absence of expression within cortical layers 3 and 4. D2 (PrEE, Id2) Section through rostral cortex where black arrow denotes an extension of the lateral expression. E1, E2, Patterns of gene expression compressed onto a coronal reconstruction of control (E1) or PrEE (E2) brains. Rzrß, diagonal line area; Cad8, crossed line area; Id2, dotted area. Dark line, cortical outline. Sections oriented dorsal (D) up and lateral (L) right. Scale bar 5 500 µm. Source: Taken with permission from El Shawa, H., Abbott, C.W., & Huffman, K.J. (2013). Prenatal ethanol exposure disrupts intraneocortical circuitry, cortical gene expression, and behavior in a mouse model of FASD. Journal of Neuroscience, 33(48), 18893 18905.

FIGURE 8.3 Somatosensory and visual INC development in control and PrEE brains at P0. Rostral caudal series of 100 µm coronal sections of P0 hemispheres following DiA (green) or DiI (red) crystal placements in putative somatosensory (B1 and B2, stars) and putative visual cortex (D1and D2, stars) of control and PrEE mouse brains. Sections were counterstained with DAPI. All arrows indicate retrogradely labeled cells. In rostral sections, DiI labeled red cells from visual cortex dye placements are seen in cortex of PrEE brains (A2, B2, C2, red cells, arrows) and other rostral regions but not in controls (A1, B1, C1). DiA-labeled green cells from somatosensory cortex dye placements were seen in abnormally caudal locations in cortex of PrEE mice (D2, E2) and not in corresponding locations in controls (D1, E1). Images oriented dorsal (D) up and lateral (L) to the right. F1 and F2: Flattened, lateral-view, reconstructions of control and PrEE brains at P0. Large red patches are DiI visual dye placements; large green patches are DiA somatosensory dye placements; small red and green dots, retrogradely labeled cell bodies. Reconstructions oriented medial (M) up and rostral (R) left. Scale bars 5 500 µm. Source: Adapted with permission from El Shawa, H., Abbott, C.W., & Huffman, K.J. (2013). Prenatal ethanol exposure disrupts intraneocortical circuitry, cortical gene expression, and behavior in a mouse model of FASD. Journal of Neuroscience, 33(48), 18893 18905.

do not overlap with connections of other primary sensory areas, such as the S1 cortex (Dye et al., 2011a, 2011b). Accordingly, in normal nonexposed mice, we observed the development of an organized cortex (Fig. 8.3, top row) with nonoverlapping connections of

primary sensory regions. However, in the cortices of PrEE mice, we observe a disorganized cortex with labeled cells found in ectopic locations (Fig. 8.3, bottom row). Specifically, somatosensory cortical connections are located in positions far caudal compared to that of

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FIGURE 8.4 Theoretical overview of PrEE’s teratogenic effects. Flowchart of how exposure to ethanol during the prenatal period can cause epigenetic changes (epigenome), resulting in altered gene expression (transcriptome) that can disrupt cortical circuitry (connectome).

normal mice, and visual cortex connections show labeled cells in far rostral positions. This extreme phenotype, where the frontal lobe is connected to the occipital lobe, is a projection pattern not seen in any healthy mammal at any time during development. Also, this development of aberrant INCs does not appear to depend on changes in inputs from the thalamus, as thalamocortical connections appear normal in PrEE mice (El Shawa et al., 2013).

Potential Mechanisms of Prenatal Ethanol Exposure Induced Neocortical Changes As described above, emerging evidence suggests that PrEE can induce epigenetic modifications that

influence features of cortical development. In a recent paper, we have described data supporting the idea that early, prenatal alcohol exposure alters DNA methylation, leading to abnormal gene expression and connections within the cortex. We have shown that the readout of this biological change is atypical animal behavior in late childhood or early adolescence. For example, PrEE leads to increased anxiety-like and depressive-like behaviors as well as poor motor skills and sensorimotor integration in mice (Abbott et al., 2017). Also, in that paper we show how these epigenetic modifications lead to heritable effects on neocortical gene expression, cortical circuitry and behavior (Fig. 8.4). As scientists who study FASD begin to understand more about the

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SUMMARY POINTS

mechanisms underlying alcohol’s teratogenic effects on the developing offspring, we will be able to generate preventative methods and therapeutic treatments for FASD.

CONCLUSION In humans, the prenatal period is a particularly sensitive time for brain development. Genetic signals pattern the embryo and input from the environment can modify this development. Alcohol has great potential to disrupt these signals by modifying the function of DNA, leading to abnormal brain development and, ultimately, deficits in cognitive function and behavior. FASD is a preventable condition and measures must be taken to not only understand the underlying biology so that treatments can be created, but increase awareness of moms-to-be and their partners that no amount of drinking in pregnancy is safe.

KEY FACTS Fetal Alcohol Spectrum Disorders Diagnosis • FASD diagnosis is heavily dependent on the admission of maternal consumption of alcohol. • Within FASD, the three main diagnostic classifications describe the extent of damage due to prenatal ethanol exposure including: • Alcohol-related neurodevelopment disorders. • Including an array of additional malformations including: cardiac, skeletal, renal, ocular and auditory symptoms. • Partial fetal alcohol syndrome. • Fetal alcohol syndrome. • Symptoms range in severity and represent a set of recognizable symptoms in three primary areas: • Prenatal and/or postnatal growth deficiency. • Central nervous system dysfunction. • A distinctive pattern of facial malformations including a thin vermillion border, smooth philtrum, and short palpebral fissure length. • The guidelines for diagnosis were developed for fetal alcohol syndrome.

MINI-DICTIONARY OF TERMS Cortical patterning The process of how the functional areas of the cerebral cortex are generated, including determining their size and shape, as well as how their spatial pattern on the surface of the cortex is established. Fractional anisotropy A measurement used in diffuse tensor imaging (DTI) that ranges from 0, isotropic (flow is equally likely in any direction), to 1, anisotropic (flow is restricted to one direction) movement of water molecules (e.g., through a fiber). Seen as a summary measure of structural integrity. Magnetic resonance imaging An imaging technology where scanners generate images of the organs in the body based on the emitted radio waves of specific atomic nuclei when exposed to a strong magnetic field. This is mainly measured through hydrogen atoms found throughout the body in water and fatty tissue. Mean diffusivity An inverse measure of membrane density calculated by generating the average measure of total diffusion within an area using DTI. Microcephaly A neonatal malformation signified by a much smaller head size compared with other babies of the same age and sex. Microencephaly A neonatal malformation producing a much smaller brain compared to other babies of the same age and sex. Quantitative polymerase chain reaction A laboratory method used to detect a specific DNA sequence in a sample and determine the actual number of copies of that sequence compared to a known standard DNA sequence. Sensorimotor integration The ability of the central nervous system to integrate multiple sources of stimuli, process, and transform those inputs into useable neural output. Spatial working memory The ability to keep spatial information active in working memory over a short period of time. Thalamocortical A nerve originating in the thalamus that acts as an input pathway to the cortex.

Epigenetics • Defined as a change in gene activity not associated with a change in gene sequence. • May include changes to DNA methylation/ acetylation, histone modifications, and miRNAmediated changes. • The epigenome is theorized to be one of the substrates, which can be modified by external experience, changing gene activity for an individual and their offspring. • One way alcohol is thought to affect the epigenome is by altering one-carbon metabolism, the primary source of methyl donors in DNA-transmethylation reactions.

SUMMARY POINTS • Alcohol consumption during pregnancy is the leading known cause of preventable developmental delay and intellectual disability in the United States. • FASD was created to describe the range of phenotypes observed in PrEE children and includes ARND, pFAS, and FAS. • Brain imaging studies and functional studies reveal system-wide alterations to anatomy and function as a result of FASD.

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8. PRENATAL ALCOHOL EXPOSURE: DEVELOPMENTAL ABNORMALITIES IN THE BRAIN

• Animal models of FASD allow researchers to experimentally control or manipulate multiple factors in order to study the wide range of effects of FASD. • Studies of animal models of FASD show changes to cortical anatomy, connectivity, gene expression, and subcortical anatomy. • PrEE can induce epigenetic modifications that can influence features of cortical development. • Key words: FASD, prenatal ethanol exposure, epigenetics, alcohol, brain development, and neocortex.

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C H A P T E R

9 Connecting Prenatal Alcohol, Its Metabolite Acetaldehyde, and the Fetal Brain M. Gabriela Chotro, Mirari Gaztan˜aga and Asier Angulo-Alcalde Department of Basic Psychological Processes and Their Development, Faculty of Psychology, University of the Basque Country UPV/EHU, San Sebastian, Spain

INTRODUCTION

CYP2E1 enzyme metabolizes the remaining fraction, and saturation of the ADH enzyme after high or chronic alcohol consumption induces increased activity of CYP2E1. During alcohol oxidation through this second pathway, acetaldehyde is generated, together with other highly reactive molecules known as oxygen radicals. Catalases are the third oxidative pathway and do not measurably contribute to the hepatic metabolism of alcohol. Excess alcohol not metabolized by this first pass through the liver is distributed through the blood stream to all body tissues, where it can also be metabolized into acetaldehyde, although at a much lower rate than in the liver (Zakhari, 2006). Due to the low affinity and reduced metabolic rate of the placental ADH, the placenta does not represent an obstacle to alcohol, which enters freely into the fetal compartment (Fig. 9.2) (Blakley & Scott, 1984; Heller & Burd, 2014). Once in the fetal circulation, alcohol reaches all tissues and organs, including the developing brain, resulting in circulation levels similar to maternal plasma (Zorzano & Herrera, 1989). Alcohol will be eliminated from fetal blood, mostly unchanged, through urinary and pulmonary excretion into the amniotic fluid, where it accumulates at concentrations often above those found in blood, which makes it an alcohol reservoir (Clarke, Steenaart, & Brien, 1986). Further, since the fetus constantly incorporates amniotic fluid by swallowing, breathing, and transdermal absorption, fetal alcohol exposure is prolonged until the drug is completely cleared (Heller & Burd, 2014). Fetal hepatic ADH activity is minimal and the amount of CYP2E1 is very low compared to the adult liver (Boleda, Farres, Guerri, & Pares, 1992; Heller &

Fetal alcohol exposure has well-documented adverse effects on brain development, although it is still uncertain whether these effects are generated by alcohol or by its metabolite, acetaldehyde. Understanding the complex factors involved in the numerous effects induced by prenatal alcohol exposure, and unfolding the connection between them, may help in finding strategies for preventing these effects, or intervening in cases of fetal alcohol exposure. In this chapter, the role of acetaldehyde, the first metabolite of alcohol, is reviewed in connection with the known effects of alcohol exposure on fetal development. Special emphasis is placed on the behavioral effects of alcohol and acetaldehyde during prenatal exposure leading to heightened alcohol intake after birth.

ALCOHOL: FROM THE MOTHER TO THE FETUS Alcohol (ethanol) is a relatively small molecule, which, after oral ingestion, is absorbed primarily in the small intestines. From there it is carried by the portal venous system to the liver where it is eliminated, mainly through reversible oxidative metabolism, and transformed into acetaldehyde (Fig. 9.1). The main enzymes involved in alcohol detoxification in the liver are alcohol dehydrogenase (ADH), CYP2E1, and catalase. Of those, ADH is the primary enzyme accounting for 90% 95% of the hepatic oxidation of alcohol. The

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00009-X

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FIGURE 9.1 Oxidative pathways of alcohol metabolism. The enzymes alcohol dehydrogenase (ADH), cytochrome P450-2E1 (CYP2E1), and catalase all contribute to oxidative metabolism of alcohol. ADH, present in the fluid of the cell (cytosol), converts alcohol (ethanol) to acetaldehyde. This reaction involves an intermediate carrier of electrons, 1 nicotinamide adenine dinucleotide (NAD), which is reduced by two electrons to form NADH. Catalase, located in cell bodies called peroxisomes, requires hydrogen peroxide (H2O2) to oxidize alcohol. CYP2E1, present predominantly in the cell’s microsomes, assumes an important role at elevated ethanol concentrations. Acetaldehyde is metabolized mainly by aldehyde dehydrogenase 2 (ALDH2) in the mitochondria to form acetate and NADH. Source: Adapted from Zakhari, S. (2006). Overview: How is alcohol metabolized by the body? Alcohol Research & Health, 29(4), 245 254.

FIGURE 9.2 Fetal alcohol and acetaldehyde disposition. This scheme shows how alcohol ingested by the mother reaches the fetus and possible fetal disposition of acetaldehyde.

Burd, 2014). Therefore, complete elimination of alcohol from the fetus and amniotic fluid relies mainly on maternal metabolism. Consequently, the level of prenatal alcohol exposure, that is, alcohol concentration and its duration, will depend on the amount of alcohol ingested by the mother and the metabolic capacity of her liver.

ACETALDEHYDE IN THE FETAL ENVIRONMENT The first and main product of alcohol oxidation, acetaldehyde, is a highly toxic and reactive molecule that in normal conditions has a very short life and is rapidly and irreversibly metabolized into acetate by the enzymes acetaldehyde dehydrogenase (ALDH)

(Fig. 9.1). The ALDH enzymes are found in many tissues, but are at their highest concentration in the liver (Crabb, Matsumoto, Chang, & You, 2004). Thus, after maternal alcohol ingestion, alcohol and acetaldehyde escaping the liver’s first pass arrive through the maternal circulation to the placenta. Unlike alcohol, acetaldehyde does not reach the fetal environment either immediately or in significant amounts (Blakley & Scott, 1984; Zorzano & Herrera, 1989). Several studies with animals after maternal administration of alcohol found acetaldehyde in the placenta, but null or minimal amounts in fetal tissues or amniotic fluid (Hayashi, Shimazaki, Kamata, Kakiichi, & Ikeda, 1991; Zorzano & Herrera, 1989). ALDH enzymes have been found in the fetal liver of humans and other mammals (Cao, Tu, & Weiner, 1989; Fakhoury, deBeaumais et al., 2009), as well as in the placenta (Blakley & Scott, 1984),

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THE ROLE OF ACETALDEHYDE IN THE EFFECTS OF ALCOHOL ON FETAL BRAIN DEVELOPMENT

although in all cases the amount and activity of ALDH is lower than in adult liver. Hence, it seems that this protective barrier against acetaldehyde is effective, at least with the amounts of acetaldehyde accumulated in maternal circulation under normal conditions and after consumption of alcohol doses below 2 4 g/kg. However, when high levels of acetaldehyde circulate in maternal blood (above 80 μM/L), acetaldehyde can be detected in fetal tissues (Zorzano & Herrera, 1989). This threshold above which placental and fetal hepatic metabolic capacity of acetaldehyde are surpassed are found either after chronic alcohol consumption, extremely high alcohol intake, or when acetaldehyde metabolism is pharmacologically manipulated (Blakley & Scott, 1984; Boleda et al., 1992; Eriksson, 2001; Guerri & Sanchis, 1985). This evidence seems to indicate that while after maternal ingestion alcohol freely enters the fetal compartment, within a moderate range of alcohol intake the fetus is relatively protected from peripheral acetaldehyde either coming from the mother or produced by the fetal liver (Clarke et al., 1986). In any case, when high concentrations of acetaldehyde are found in maternal blood circulation, the amount entering the fetal compartment would always be considerably lower than that in maternal plasma (Zorzano & Herrera, 1989).

ACETALDEHYDE IN THE FETAL BRAIN In contrast, relatively high amounts of acetaldehyde have been reported in the fetal brain (HambyMason, Chen, Schenker, Perez, & Henderson, 1997). Given that the minimal amounts of acetaldehyde that may cross the placenta are metabolized by the fetal hepatic ALDH, as well as ALDH in the blood brain barrier (Zimatkin, 1991), acetaldehyde detected inside the fetal brain must necessarily be produced in situ from alcohol (HambyMason et al., 1997). Alcohol arrives freely to the fetal brain where it is transformed into acetaldehyde by catalases, the main enzymes responsible for this transformation in both adults and the developing brain, accounting for approximately 60% of alcohol’s oxidation (HambyMason et al., 1997; Zimatkin, Pronko, Vasiliou, Gonzalez, & Deitrich, 2006). Moreover, the concentration and activity of catalases in neonatal and fetal rat brains were found to be much higher than in adults, which could partially explain the higher amount of central acetaldehyde found in the fetus brain (Delmaestro & McDonald, 1987; HambyMason et al., 1997). As in the liver, CYP2E1 activity in the adult and fetal brain is induced by acute elevated alcohol ingestion or in response to chronic drinking, and it accounts for 20% 25% of alcohol

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brain detoxification (HambyMason et al., 1997). However, in addition to acetaldehyde, it generates oxygen radicals, which are very reactive and potentially harmful molecules (Brzezinski, Boutelet-Bochan, Person, Fantel, & Juchau, 1999; Tuma & Casey, 2003). Acetaldehyde is then metabolized irreversibly to acetate by the fetal brain-ALDH enzymes (Fakhoury et al., 2009). In summary, a greater accumulation of acetaldehyde is expected in the fetal brain compared to adults at similar blood alcohol concentrations when considering the combination of all three mentioned concomitant conditions: prolonged and continuous fetal exposure to alcohol accumulated in amniotic fluid, higher activity of fetal brain catalases, and the lower expression of the ALDH enzymes in the fetal brain. On the basis of these considerations, it appears that after maternal alcohol intake, the fetus will be exposed to alcohol in the blood, brain, and amniotic fluid, while exposure to acetaldehyde is almost exclusively limited to the brain.

THE ROLE OF ACETALDEHYDE IN THE EFFECTS OF ALCOHOL ON FETAL BRAIN DEVELOPMENT Human and animal studies have revealed that the central nervous system is particularly vulnerable to the deleterious effects of prenatal alcohol exposure. Given its complexity and development throughout gestation, and even long after birth, there is no safe prenatal period for the toxic effects of alcohol and its metabolites. Many of the effects of prenatal alcohol have been shown to be attributable to the action of its main oxidation product, acetaldehyde (Eriksson, 2001). Acetaldehyde was found to induce retarded neural development and malformations matching those observed after prenatal exposure to relatively high amounts of alcohol during different stages of gestation (Sreenathan, Padmanabhan, & Singh, 1982; Webster, Walsh, McEwen, & Lipson, 1983). More recent experiments conducted at a physiological level have also shown acetaldehyde to affect neural development by disrupting cellular differentiation, neuronal growth, myelination, and by enhancing the deleterious effects of alcohol (Coutts & Harrison, 2015; Giavini, Broccia, Prati, Bellomo, & Menegola, 1992). In addition, placental formation is also negatively affected by high concentrations of acetaldehyde, altering nutrition functions fundamental for normal neurodevelopment (Lui et al., 2014). After the placenta is formed, maternal acetaldehyde does not reach the fetus but is abundantly produced in the fetal brain (Clarke et al., 1986). These amounts of acetaldehyde formed locally after

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maternal alcohol ingestion seem sufficient to be functionally relevant and to induce a wide variety of harmful effects in this vulnerable developing system (HambyMason et al., 1997). The mechanisms by which alcohol and acetaldehyde produce their harmful effects are diverse and still under investigation. The presence of alcohol in the fetal brain induces higher activity of CYP2E1 leading to the production of acetaldehyde and oxygen radicals. Both are very reactive substances that interact with other complex molecules in the cell generating hybrid compounds called adducts, a single product resulting from direct covalent chemical additions (Tuma & Casey, 2003). This, combined with the lower antioxidant capacity of the developing brain (Shim & Kim, 2013), generates an imbalance in the redox state of the neural cells inducing oxidative stress. Fetal brain tissues are particularly vulnerable to oxidative stress, which damages all components of the cell including lipids, proteins, and DNA by generating toxic adducts and disrupting their normal functioning, and in the long term, inducing cell death, contributing to the neurodegeneration observed after prenatal alcohol exposure (Tong et al., 2011; Zakhari, 2006). Further, acetaldehyde readily forms adducts with other molecules such as proteins and neurotransmitters, impairing their normal functions and inducing neurotoxicity (Tuma & Casey, 2003). Acetaldehyde also reacts with endogenous neurogenic amines such as catecholamines, generating adducts. Salsolinol, the condensation product of acetaldehyde and dopamine, is one of the most studied due to its neurotoxic effects and its involvement in the motivational effects of alcohol (Hipolito et al., 2012; Peana et al., 2017) while it has been detected in the fetal brain after chronic prenatal alcohol exposure (Mao et al., 2013). This could represent another mechanism by which acetaldehyde produces neural damage after prenatal alcohol exposure (Quertemont, Tambour, & Tirelli, 2005).

CONNECTING THE BEHAVIORAL EFFECTS OF ALCOHOL AND ACETALDEHYDE IN THE FETUS Acetaldehyde, in addition to its neurotoxic consequences, has been found to produce behavioral effects. Since many of these coincide with those of alcohol it has been suggested—and more recently demonstrated—that acetaldehyde mediates several effects of alcohol on behavior. In adult humans and animals, acetaldehyde induces motor effects including motor stimulation at low doses and sedation at high doses; memory impairing effects at high doses; and anxiolytic effects at moderate doses, while motivational effects can be

aversive or appetitive. Other consequences such as anticonvulsive and analgesic effects have not yet been tested with acetaldehyde (Quertemont et al., 2005). For the motivational effects of acetaldehyde, many studies have shown that it has differential properties depending on the dose and site of action. Elevated concentrations of peripheral acetaldehyde have been found to be highly aversive, while central acetaldehyde induces appetitive effects and appears to be responsible for the reinforcing effect that sustains alcohol consumption (Correa et al., 2012; Quertemont et al., 2005). Due to difficulties in measuring and interpreting fetal behavior, data on the prenatal effects of alcohol on behavior are scarce, and those of acetaldehyde have not yet been tested. However, indirect evidence from a few studies on alcohol or during early postnatal development may help to shed some light on this, as yet, unexplored topic. There are no reports on the fetal motor effects of acetaldehyde, but the few studies with alcohol reveal an effect of sedation in fetuses; in humans, maternal ingestion of alcohol reduced fetal breathing movements when tested 0.5 3 hours later (McLeod et al., 1983) and similar effects were described in sheep (Smith et al., 1990). A reduction of general activity was also observed in rat fetuses 1 hour after maternal administration of 1 2 g/kg alcohol (Chotro & Spear, 1997), or 4 hours after a 4 g/kg dose (Smotherman et al., 1986). Alcohol intoxication in pregnant rats also reduced the fetal motor activation induced by acute hypoxia after umbilical cord compression (Smotherman & Robinson, 1987). Although there are no data showing fetal motor stimulation with alcohol, this effect has been reported in 8- to 12-dayold rat pups during the first 5 10 minutes of alcohol intoxication, while sedation was observed 15 20 minutes later (Arias, Mlewski, Molina, & Spear, 2009); and sequestering acetaldehyde eliminated the stimulating effect of alcohol (Pautassi, Nizhnikov, Fabio, & Spear, 2011). It is possible that alcohol stimulation would be detected in fetuses if tested during the first minutes of intoxication.

REINFORCING EFFECTS OF ALCOHOL AND ACETALDEHYDE IN THE FETUS With respect to the positive reinforcing properties of alcohol and acetaldehyde in early development, in newborn rats it was found that administration of low doses of alcohol paired with an odor induced a conditioned odor preference for that smell (Petrov, Varlinskaya, & Spear, 2003). Similar appetitive responses were obtained by injecting alcohol or acetaldehyde directly into the newborn brain, but not when inhibiting brain catalases or sequestering acetaldehyde, thus, confirming the

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PERINATAL LEARNING WITH ALCOHOL AND ACETALDEHYDE

appetitive properties of central acetaldehyde in neonate rats (March, Abate, Spear, & Molina, 2013; Nizhnikov, Molina, & Spear, 2007). In prenatal stages, alcohol also appears to exert appetitive effects. When alcohol is administered to the pregnant rat during the last days of gestation (17 20), the fetus is exposed simultaneously to the chemosensory (flavor) and pharmacological properties of alcohol. This prenatal experience results in increased postnatal alcohol consumption as well as enhanced liking for the taste of alcohol when tested in infancy and adolescence (Chotro & Arias, 2003). It is generally accepted that the near-term fetus can perceive chemosensory stimuli present in the amniotic fluid during swallowing and breathing the fluid, forming associations with their aversive or appetitive consequences, which modifies postnatal responses to those stimuli (Smotherman & Robinson, 1988). Accordingly, the enhanced acceptance of alcohol found after prenatal alcohol exposure was demonstrated to be a conditioned appetitive response acquired in utero (Chotro & Arias, 2003). This prenatal experience was also found to modulate postnatal learning by retarding the acquisition of aversions and facilitating learned preferences when alcohol was the reinforcer (Arias & Chotro, 2006a, 2006b). Recently, it was demonstrated that the reinforcing effects of acetaldehyde are crucial for this prenatal appetitive learning about alcohol, since sequestering acetaldehyde was able to prevent such learning (Gaztanaga, Angulo-Alcalde, Spear, & Chotro, 2017). Additional indirect support comes from studies in which the reinforcing effects of alcohol were suppressed when blocking the endogenous opioid system, particularly the μ-opioid receptors, during prenatal alcohol exposure (Chotro & Arias, 2003; Chotro, Arias, & Laviola, 2007; Diaz-Cenzano, Gaztanaga, & Chotro, 2014). This is particularly relevant since the reinforcing and stimulating effects of central alcohol-derived acetaldehyde appear to be mediated by the μ-opioid system (Font, Lujan, & Pastor, 2013). Acetaldehyde has been found to stimulate the release of β-endorphins and salsolinol appears to induce its effects interacting with the μ-opioid receptors in the posterior ventral tegmental area, an element of the “dopamine reward pathway” (Xie, Hipolito et al., 2012). In addition to acetaldehyde, high amounts of salsolinol were found in the fetal brain after chronic alcohol exposure (Mao et al., 2013), although its behavioral effects in early ontogeny have not yet been tested.

PERINATAL LEARNING WITH ALCOHOL AND ACETALDEHYDE Although the reinforcing effects of alcohol and acetaldehyde during prenatal and neonatal stages appear

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to be clear (March et al., 2013), no evidence of the aversive effects of alcohol have yet been found until postnatal day 11 of the rat (Arias & Chotro, 2006; Pautassi, Nizhnikov, & Spear, 2009). Moreover, the same alcohol doses that are aversive for adults or 2-week-old infants are appetitive when experienced either prenatally or during the first postnatal week (Arias & Chotro, 2006; Chotro, Arias, & Spear, 2009). This developmental change in the motivational effects of alcohol could be related to the metabolic status of the developing rat at each age. As explained, the rat fetus and neonate do not generate aversive peripheral acetaldehyde due to the low or null hepatic ADH activity that begins to increase after birth and reaches the adult value by day 20 (Boleda et al., 1992) and the fetus is relatively protected from maternal acetaldehyde. Conversely, the intense activity of brain catalase that produces high levels of reinforcing acetaldehyde at fetal and neonatal stages decreases gradually with development (Delmaestro & McDonald, 1987). Thus, it seems unlikely that the fetus and the neonate have the chance to perceive the negative consequences of peripheral acetaldehyde during alcohol intoxication, while their central appetitive effects are predominant. If the perceived motivational effects of alcohol intoxication are considered to be a result of the balance between peripheral and central levels of acetaldehyde (Correa et al., 2012), this suggests that fetuses and newborns will perceive exclusively the appetitive effects of acetaldehyde, and the likelihood of perceiving its aversive properties will increase during development. This implies that fetal learning during prenatal alcohol exposure will necessarily generate appetitive responses (Fig. 9.3). This associative mechanism could underlie the enhanced liking of alcohol odor observed in two subsequent studies with newborn babies and adolescents with a history of prenatal alcohol exposure (Faas, March, Moya, & Molina, 2015; Hannigan, Chiodo, Sokol, Janisse, & Delaney-Black, 2015). Similarly, this might explain the increased alcohol consumption observed in many animal studies with prenatal alcohol exposure, along with other neurodevelopmental effects (Chotro et al., 2007). In summary, when the pregnant mother consumes alcohol, the fetus is exposed to alcohol in the blood, brain, and amniotic fluid, and to centrally formed acetaldehyde. This produces a wide range of physiological and behavioral effects that not only alter fetal neurodevelopment, but also induce changes in alcohol acceptance, which can eventually lead to alcohol abuse problems. Clinical studies show a clear relationship between prenatal alcohol and alcohol abuse in adolescents and young adults, with prenatal alcohol exposure being a good predictor of alcohol problems (Baer, Sampson, Barr, Connor, & Streissguth, 2003). More

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9. CONNECTING PRENATAL ALCOHOL, ITS METABOLITE ACETALDEHYDE, AND THE FETAL BRAIN

FIGURE 9.3 Fetal alcohol learning after maternal alcohol consumption. This scheme shows possible associative mechanisms underlying increased alcohol intake and liking after prenatal alcohol exposure.

research is needed to better identify the relative importance of each intervening factor as well as the mechanisms underlying this complex interplay between the effects of alcohol and acetaldehyde.

KEY FACTS About Alcohol and Acetaldehyde in the Fetus • Alcohol consumed by the pregnant mother crosses the placenta and reaches the fetus in similar amounts to maternal plasma, and accumulates in the amniotic fluid. • Acetaldehyde, the first oxidation metabolite of alcohol, is mainly produced in maternal liver. • Low or null amounts of maternal acetaldehyde reach the fetus after maternal alcohol ingestion, this being metabolized by the placenta and fetal liver. • The fetus, due to its hepatic metabolic immaturity, cannot produce peripheral acetaldehyde from alcohol. • Acetaldehyde is produced from alcohol in the fetal brain, mainly by catalases. • Brain acetaldehyde may produce many of the neurodevelopmental and behavioral effects of alcohol.

SUMMARY POINTS • The role of alcohol-derived acetaldehyde in relation to the known effects of prenatal alcohol exposure is reviewed.

• Alcohol ingested by the pregnant mother easily reaches the fetus, while maternal acetaldehyde does not. • Acetaldehyde is produced in the fetal brain and may be responsible for many of the effects attributed to alcohol. • Brain acetaldehyde retards development and induces neural damage through the formation of toxic adducts. • Alcohol and acetaldehyde in early development induce comparable behavioral effects and the reinforcing properties of central acetaldehyde during alcohol exposure may underlie prenatal appetitive learning producing postnatal increased alcohol intake.

References Arias, C., & Chotro, M. G. (2006a). Ethanol-induced preferences or aversions as a function of age in preweanling rats. Behavioral Neuroscience, 120(3), 710 718. Arias, C., & Chotro, M. G. (2006b). Interactions between prenatal ethanol exposure and postnatal learning about ethanol in rat pups. Alcohol, 40(1), 51 59. Arias, C., Mlewski, E. C., Molina, J. C., & Spear, N. E. (2009). Ethanol induces locomotor activating effects in preweanling Sprague Dawley rats. Alcohol, 43(1), 13 23. Baer, J. S., Sampson, P. D., Barr, H. M., Connor, P. D., & Streissguth, A. P. (2003). A 21-year longitudinal analysis of the effects of prenatal alcohol exposure on young adult drinking. Archives of General Psychiatry, 60(4), 377 385. Blakley, P. M., & Scott, W. J. (1984). Determination of the proximate teratogen of the mouse fetal alcohol syndrome. 2. Pharmacokinetics of the placental-transfer of ethanol and acetaldehyde. Toxicology and Applied Pharmacology, 72(2), 364 371. Boleda, M. D., Farres, J., Guerri, C., & Pares, X. (1992). Alcoholdehydrogenase isoenzymes in rat development. Effect of maternal ethanol-consumption. Biochemical Pharmacology, 43(7), 1555 1561.

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C H A P T E R

10 Fetal Alcohol Exposure and the Central Nervous Control of Breathing O. Pierrefiche UMR1247 INSERM GRAP, Group of Research on Alcohol and Pharmacodependencies, University Centre for Health Research, University of Picardy Jules Verne, Chemin du Thil, Amiens, France

INTRODUCTION

Compared to other drugs, ethanol appears to be the most harmful drug when taken during pregnancy being responsible for more than the double of number of effects than other drugs (European Monitoring Centre for Drugs and Drug Addiction, 2012). Importantly, these effects of ethanol cover both preand postnatal periods. However, ethanol-induced respiratory disturbances are not yet considered in this report; it is yet to be documented either at preclinical or clinical levels. Nonetheless, the effects of acute ethanol consumption on breathing in human reported respiratory depression with animal models described reduced respiratory-related nerve output activity. Some studies, but not all (Bocking et al., 1994), found that acute alcohol in pregnant ewes stopped fetal breathing movement (Watson et al., 1999a, 1999b). Acute effects of ethanol on respiratory brain areas involved inhibitions of NMDA receptors and potentiation of both glycine and GABAA receptors (Gibson & Berger, 2000), two of the cellular targets of ethanol in the brain (Costa, Savage, & Valenzuela, 2000). Furthermore, long-lasting effects of chronic ethanol exposure during gestation in animals suggested a delay in neuronal network maturation, organization, and properties that could eventually also concern the central respiratory network (Costa et al., 2000). The central respiratory network which generates and organizes rhythmic motor activity according to the organisms’ need in terms of oxygen is embedded within the brainstem. Composed of several types of respiratory rhythmic neurons, defining inspiration and expiration, this network activity is highly dependent on both excitatory and inhibitory amino acids’

Consuming alcohol during pregnancy remains an important health issue worldwide due to alcohol’s (ethanol) teratogenic effects. In western countries, 20% 25% of pregnant women drink alcohol at some time during pregnancy despite the neurophysiologic consequences of such behavior having been acknowledged by both the scientific and medical communities (Pierrefiche, Daoust, & Naassila, 2016). Chronic prenatal ethanol exposure may induce Fetal Alcohol Syndrome (FAS). This syndrome was first described in 1968 by a French pediatrician, Dr. P Lemoine. This syndrome is characterized by life-long cognitive deficits (Burd, Cotsonas-Hassler, Martsolf, & Kerbeshian, 2003), somatosensorial deficits including, but not restricted to, motor impairment, chronic neuropathic pain enhancement (Lucas et al., 2014; Noor et al., 2017), and fragmented sleep accompanied with disordered breathing (Chen, Olson, Picciano, Starr, & Owens, 2012). Besides cases of high ethanol exposure (for which prevalence may reach up to 6 9/1000 children at school age) one should consider the more numerous cases of lower levels of ethanol exposure referred to as Fetal Alcohol Spectrum Disorder (FASD) and for which incidence may reach up to 1/100 of living births (Pierrefiche et al., 2016). In other words, low to moderate ethanol consumption during gestation can also be detrimental to the future child (Meyer-Leu, Lemola, Daeppen, Deriaz, & Gerber, 2011). In 2012, the European Monitoring Centre for Drugs and Drug Addiction issued a report on drug use during pregnancy and listed the damages caused by ethanol.

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neurotransmissions and is modulated by several neurotransmitter systems. And despite the known effects of acute ethanol on NMDA and GABA receptors, there are only few preclinical investigations on the effects of ethanol exposure during brain development on the central respiratory rhythmogenesis and responses to chemosensory challenges. Additionally, drinking alcohol during pregnancy either chronically or acutely (i.e., binge drinking) is suspected to be a risk factor for sudden infant death syndrome (SIDS), (Burd, Klug, & Martsolf, 2004). Considering that the effects of exposure to ethanol during brain development are still not fully understood and that successful alcohol withdrawal during pregnancy is difficult, additional commitment in understanding the mechanisms underlying fetal neurotoxic effects of ethanol are crucial, including its impact on physiological functions.

ANIMAL MODELS OF ALCOHOL EXPOSURE DURING GESTATION/BRAIN DEVELOPMENT Several animal models testing alcohol exposure during brain development are used according to the scientific question studied. Specifically, scientists may wish to determine which period during gestation is the most sensitive to alcohol and, thus, they may restrain exposure to only part of the gestation; another question might be to reveal the effects of continuous exposure during entire gestation and/or the effects of exposure after repeated alcohol bouts (i.e., binge drinking) at some time during pregnancy; and, finally, one may be interested in the effects during only the later part of brain development which occurs postnatally in rats. Another way is to consider the clinical situation in which a woman with alcohol use disorder, is abusing alcohol before being pregnant and has tremendous difficulty to stop drinking during gestation. Here, animals should be exposed to alcohol well before mating and then during the entire period of brain development, including the postnatal period, until natural weaning (Andersen, 2003). It is this model that has been tested in most of the studies on pre- or perinatal ethanol exposure on offspring’s respiratory physiology. Specifically, female rats (Sprague-Dawley) were exposed to alcohol through a 10% ethanol (v/v) drinking solution from 1 month before mating to the 21st postnatal days of the offspring. Dehydration was limited by giving access to water every day for few hours (Dubois, Naassila, Daoust, & Pierrefiche, 2006; Dubois, Houchi, Naassila, Daoust, & Pierrefiche, 2008; Kervern, Dubois, Naassila, Daoust, & Pierrefiche, 2009). Concerning tadpoles, Lithobates catesbeiana were maintained for 8 12 weeks in pond water containing 0.15%

ethanol (Taylor, Croll, Drucker, & Wilson, 2008). Importantly, in both rodents and tadpoles, the level of ethanol exposure could be extrapolated to moderate levels in humans (Eckardt et al., 1998). Indeed, tadpoles were exposed to a level one to two times what is considered the legal limit for human blood alcohol content and pregnant dams showed a blood alcohol level at about 1 g/L (Taylor et al., 2008; Barbier et al., 2008; Dubois et al., 2008).

METHODOLOGY TO INVESTIGATE BREATHING PHYSIOLOGY The different methodologies used to investigate breathing physiology allows exploring the function from the in vivo spontaneous situation with whole-body plethysmography to ex vivo investigations using spontaneous rhythmic brainstem slices isolating the kernel of neurons dedicated to rhythmogenesis. In addition, a few decades ago an interesting intermediate animal preparation was developed by Paton J (1996) called in situ Working Heart-Brainstem Preparation (WHBP). This model consists in a decerebrated rodent sectioned below the diaphragm and superfused via the descending aorta with an oxygenated artificial cerebrospinal fluid. All types of preparations have been used in rodents for understanding the consequences and the mode of action of ethanol exposure during brain development. With the use of tadpoles, the rodent results were extended to other species than mammals. Isolated brainstem spinal cords were prepared from tadpoles and respiratory nerves were recorded. In addition, the surfacing frequency of tadpoles (their spontaneous respiratory behavior) have been measured. With these different models, the effects of ethanol exposure during brain development have been characterized on spontaneous breathing and during chemosensory challenges to evaluate the respiratory network capacity to adapt to physiological demand. In addition, the impact of ethanol exposure on rhythmogenesis, respiratory nerve motor output, and on longterm plasticity have been evaluated. The results on this topic are highly innovative in the field of alcohol research and are presented in this chapter.

SHORT- AND LONG-TERM RESPIRATORY PLASTICITY: RESPONSE TO ACUTE CHEMOSENSORY CHALLENGES AND LONG-TERM FACILITATION OF BREATHING The goal of breathing is to maintain adequate oxygenation of the tissues whatever the needs of the

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SHORT- AND LONG-TERM RESPIRATORY PLASTICITY

organism are. Accordingly, the respiratory neuronal network should be able to adapt its activity. Thus, the typical response of breathing in a low-oxygen environment could be understood as an adaptive response due to the short-term plasticity capability of the respiratory network. In this context, respiratory network responses were analyzed during low-oxygen episodes applied to either in vivo or in situ preparations of juvenile rats exposed to alcohol during prenatal and postnatal periods. Interestingly, with these two approaches, the chemosensory response to a shortlasting, low-oxygen episode was dampened. Control juvenile animals studied in vivo with plethysmography increased both respiratory frequency during hypoxia and tidal volume, defining physiological hyperventilation. Qualitatively, ethanol-exposed animals responded similarly, but at significantly lower quantitative values (Dubois et al., 2008) revealing the lack of hyperventilation. Consequently, minute ventilation during hypoxia was correctly increased only in control animals. Similarly, inspiratory inflow index (VT/Ti ratio) was significantly increased only in control animals, suggesting that pulmonary gas exchange was less efficient in ethanol-exposed animals during low-oxygen episodes. These measurements suggest that the level of oxygen in the alveolar compartment was inadequate in ethanol-exposed animals, revealing a maladaptive response to a low-oxygen environment after perinatal ethanol exposure. However, analyses of chemosensory response in vivo do not allow for a precise understanding of the nervous control of the response since there is no access to nerve or respiratory neuron activity. Therefore, chemosensory challenges were also tested with an in situ preparation allowing recordings from both phrenic and hypoglossal nerves. Under these conditions, the capacity of the respiratory network to generate gasping activity and to recover from anoxia-induced apnea was analyzed. During short-lasting anoxia, phrenic nerve frequency increased in both groups, but the response was double in control animals compared to ethanolexposed animals. Phrenic burst amplitude also increased significantly, again only in control animals. Anoxia-induced apnea started at the same time point between the two populations, but duration of apnea was shorter in the ethanol group and, consequently, gasping activity was triggered earlier in this group. More importantly was the time to recover a controllike phrenic burst of activity during re-oxygenation which was longer in ethanol-exposed animals (Dubois et al., 2008). Respiratory chemosensitivity was also tested with isolated brainstem-spinal cord preparation of bullfrog tadpoles (Taylor et al., 2008; Taylor & Brundage, 2013; Taylor, Brundage, & McLane, 2013). Central hypoxic ventilatory response was impaired

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after ethanol exposure at any stage of tadpole development (Taylor et al., 2013). Similarly hypercapniainduced increase in lung burst frequency in this model was stopped after ethanol exposure, whatever the stage of development was (Taylor et al., 2008; Taylor & Brundage, 2013). In addition, in intact tadpoles, ethanol exposure abolished the surfacing events during hypercapnia (Taylor et al., 2008), linking the results obtained at the level of central nervous system with in vivo behavior. Interestingly, impairment of respiratory response to hypercapnia resumed 6 weeks after ethanol exposure, revealing the capacity of the respiratory network to recover from a developmental exposure to a teratogen (Brundage & Taylor, 2010), at least in tadpoles. Unfortunately, we don’t have this information for mammals yet. Globally, ethanol exposure during brain development in different species impaired breathing adaptation to acute chemosensory challenges. This impairment appears early in life. Experiments in juvenile rats further suggest that the reduced response to low-oxygen episodes may be long-lasting. However it may be that such disturbances are only transient, as suggested in tadpoles (Brundage & Taylor, 2010). Table 10.1 summarizes the main results of chemosensitivity. Another interesting property of the respiratory network is the possibility to generate long-term facilitation (LTF) which is a spontaneous increase in respiratory rhythmic activity induced after repeated exposure to short-duration episodes of low-oxygen tension (Mitchell & Terada, 2011). Such long-lasting (. 1 hour) plasticity of the respiratory network, observed in several models and animal species, is supposedly a mechanism of protection of the respiratory function, to maintain upper airway patency during low-oxygen episodes. The capability of the respiratory network to generate LTF in neonatal rats after perinatal ethanol exposure using both in vitro slices and in vivo animals has been tested. In vivo, control animals submitted to three short-lasting hypoxic episodes increased tidal volume by more than 100% at 90 min posthypoxia with a 75% increase in minute-ventilation whereas ethanol-exposed animals showed approximately 50% decrease in these two parameters. Therefore, while LTF was triggered in control animals, ethanol-exposed animals showed a deep and longlasting depression of breathing, revealing abolition of a putative protective mechanism of respiration (Kervern et al., 2009). This reversion of LTF in vivo was confirmed using neonatal in vitro rhythmic brainstem slices. Similarly to the in vivo situation, 90 min after the episodes of low oxygen, control animals showed an increase in hypoglossal nerve activity whereas slices from ethanol-exposed animals showed a decrease of hypoglossal nerve activity. Importantly,

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10. FETAL ALCOHOL EXPOSURE AND THE CENTRAL NERVOUS CONTROL OF BREATHING

Main Results from the Two Species Studied

Normoxia

Rat CTL

Rat EtOH

Inspiration (s)

0.8 6 0.06

0.79 6 0.06

Expiration (s)

3.2 6 0.29

5.9 6 0.81

Respi. Frequency

17.3 6 2.2

9.9 6 1.2

19.8 6 2.6

12.5 6 3.1



Tadpole CTL

Tadpole EtOH

0.68 6 0.28

1.1 6 1.7

0.52 6 0.12 Early

0.63 6 0.24 Early

9.39 6 2.83 Late

1.53 6 0.45 Late

0.25 6 0.11# Early

No response Early

3.93 6 0.64# Late

No response Late

1.5 6 0.4 Early

0.7 6 0.3 Early

15.9 6 1.8 Late

3.4 6 1.7 Late

LOW OXYGEN Respi. Frequency

Respi. Frequency

29 6 2.6#

41.1 6 8.4 #

17.2 6 3.1 #

47.1 6 9.8#

1 Strychnine HYPERCAPNIA Inspiration (s) Expiration (s) Respi. Frequency

Plasticity

Facilitation

Depression

Early and late: stage of tadpole development; Frequency is given per min; ( ) significant from control population; # significant from controls within the population; « » not measured. Adapted from Dubois et al., 2006; Dubois et al. 2008; Kervern et al., 2009; Taylor & Brundage, 2013; Taylor et al., 2013. Only lung ventilation is described for the tadpole.

this reversion of LTF in vitro and in vivo was not due to differences in the response to each low-oxygen episode between control and ethanol-exposed animals. However, the intimate cellular mechanisms of LTF are not yet clear in control animals, while LTF failure after ethanol exposure is totally unknown and more experiments are needed to answer these questions.

RHYTHMOGENESIS Respiratory neurophysiology includes the analysis of how the brain organizes this activity in terms of neuronal sequence to produce the proper motor output for inspiration and expiration. Basically, breathing is a motor behavior generated and controlled by specific parts of the brain. It is well-known that the ensemble of neurons generating breathing activity are embedded within the brainstem in both the medulla and the pons. It entails a large network of neurons distributed along a ventrolateral column in the medulla, from the nucleus ambiguous to the limit of the pons associated with the subparabrachial nucleus (i.e., Ko¨lliker-Fuse) and the medial parabrachial nucleus (Song, Yu, & Poon, 2006) within the lateral pons. Additionally, some respiratory neurons are found in the nucleus solitarius

at the obex level. In the past few decades, precise regions within this large network have been particularly studied leading to a better understanding of the nervous control of breathing, that is, giving some hints in the nervous control of rhythm generation vs. pattern generation. For example, the so called pre-Bo¨tzinger complex, a rostral part of the ventrolateral column in the medulla, have been suggested as the kernel of respiratory rhythmogenesis (Smith, Ellenberger, Ballanyi, Richter, & Feldman, 1991) and, more recently, the retrotrapezoid nucleus, located in the ventral part of the rostral medulla that has been implicated in respiratory rhythmogenesis and, ultimately, in the control of chemosensitivity (Guyenet, Stornetta, Abbott, Depuy, & Kanbar, 2012). Importantly the central respiratory network needs to be robust since it underlies a vital physiologic function involved mainly in excitatory and inhibitory amino acids neurotransmissions for its basic rhythmogenesis rules. As such, the functioning of this network could be easily and greatly altered by ethanol exposure, either acutely or chronically. In this context, it is of interest to determine the consequences of perinatal ethanol exposure on the rhythmicity of breathing activity. The first results were obtained on rats using in vivo and in situ approaches (Dubois et al., 2006, 2008) and further results were

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RHYTHMOGENESIS

reported with in vitro spontaneous rhythmic slices (Pierrefiche et al., 2016). More recent analyses reported on rhythmic brainstem slices and other studies concerning bullfrog tadpoles. In mammals, experimental preparation used, the rhythmic activity was always slowed down after ethanol exposure (Table 10.1). For example, in rhythmic slices, recordings of the respiratory-like motor output on hypoglossal rootlets revealed an increase of the silent phase of the rhythm only, that is, the expiratory-like phase, so reducing the frequency of activity by one third (Pierrefiche et al., 2016). Burst duration, or time to peak during the burst, were unaltered. In perinatally ethanol-exposed rats, respiratory-like cycle length was longer because of a selective increase of interburst interval duration (Figs. 10.1 and 10.2). Furthermore, rhythmic activity was more unstable after ethanol due to a more

Respiratory cycle

Raw in situ phrenic nerve recording

Inspiratory phase

Expiratory phase

I

Phase II

FIGURE 10.1 Respiratory cycle and respiratory phases in rat models defined from phrenic nerve recording in situ. Phase one of expiration (I) is the postinspiratory decrementing activity of the phrenic nerve designed with the arrow. Phase two of expiration (Phase II) is the silence of phrenic nerve.

irregular interburst duration. In vivo experiments using plethysmography in unrestrained and unanesthetized animals also demonstrated a significant decrease in respiratory frequency in neonates, juvenile, and adult animals withdrawn from alcohol (Kervern et al., 2009; Dubois et al., 2006, 2008; Pierrefiche et al., 2016). Again, measuring phrenic nerve rhythmic activity together with hypoglossal nerve in situ with the WHBP (Dubois et al., 2006, 2008), a 40% decrease in burst frequency after ethanol was found. In bullfrog tadpoles, respiratory activity recorded from trigeminal and hypoglossal nerve rootlets on isolated brainstemspinal cord revealed a strong tendency to a reduction of frequency, at least in later developmental stages when analyzed in vitro or in vivo by recording the frequency of surfacing events (Taylor et al., 2008, 2013; Brundage & Taylor, 2010; Taylor & Brundage, 2013). Interestingly, in rats, further analysis of perturbations in rhythmic activity revealed that the expiratory phase was longer while duration of the inspiratory phase was unaltered. In situ, the decrease in respiratory-like frequency was due to a two-fold increase of expiratory duration on phrenic nerve recording, a value similar to in vivo measurements. Furthermore, during expiration, only the second half of the phase was increased. Interestingly, even adult animals withdrawn from alcohol for 40 days still showed a specific increase in expiration (Pierrefiche et al., 2016). Globally in rodents, perinatal ethanol exposure reduced respiratory frequency via a specific and long-lasting disturbance of the duration of part two of expiration from birth to adult. Importantly, some of these results have been repeated by Ji and his colleagues from Xinxiang Medical University in China. These authors reported that in neonatal rat rhythmic brainstem slices hypoglossal activity became irregular. Interestingly, they studied different levels of ethanol exposure and found that only the 10% group of ethanol-exposed animals showed

Spontaneous breathing

Control XIIn

Inspiration

Phr

XIIn XIIn

5s

2s

Ethanol

In vitro rhythmic slice Neonates (P7)

In situ WHBP Juvenile (P25)

93

0,5 mL 0,5 s

In vivo Plethysmography Adult withdrawn (P60)

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FIGURE 10.2 Effects of ethanol on respiratory rhythmic activity. The three different approaches used in rat models and the result of pre- and postnatal ethanol exposure on respiratory activity. Note the reduced rhythm in all cases.

94 TABLE 10.2

10. FETAL ALCOHOL EXPOSURE AND THE CENTRAL NERVOUS CONTROL OF BREATHING

Relative Efficiency of Pharmacological Agents CTL

EtOH

Preparations

NMDA

11 1

1

in vitro

AP-5

11 1

1

in vitro

GABA

11 1

1

in vitro

Diazepam

11 1

1

in vitro

Muscimol

11 1

1

in vitro

Muscimol

11 1

1

in situ

Strychnine

11 1

1111

in situ

Strychnine

1

1111

in vitro

Acute Ethanol

11 1

1111

in situ

Acute Ethanol

11 1

1111

in vitro

The different agents were tested on respiratory network activity before (CTL) and after in utero ethanol exposure (EtOH) in different preparations used in rat. Adapted from Dubois et al., 2006; Dubois et al. 2008; Kervern et al., 2009; Dubois, Kervern, Naassila, & Pierrefiche, 2013.

reduced respiratory activity and that exposure during gestation is only sufficient to observe this disturbance, confirming the results obtained by Pierrefiche et al. (2016).

PHARMACOLOGY OF THE RESPIRATORY NETWORK AFTER ETHANOL EXPOSURE As first pharmacologic agents, ethanol was tested in rats both in vitro and in situ (Table 10.2). In all experiments, the respiratory network showed sensitization to acute ethanol. In vitro acute ethanol induced a stronger inhibition of rhythmic activity after perinatal ethanol exposure (Pierrefiche et al., 2016) and, in situ, phrenic nerve as well as hypoglossal rhythmic activity were also more inhibited (Dubois et al., 2006), suggesting a long-lasting increase in sensitivity to ethanol that may be deleterious for breathing. Interestingly, using neonatal in vitro rhythmic slices, Pierrefiche et al. (2016) described a lower response to GABA application after ethanol exposure while GABAβ2 and GABAγ2 mRNA levels were unaffected. Diazepam and muscimol efficacy were also reduced (Table 10.2). Still concerning inhibitory neurotransmission, sensitivity to strychnine (an antagonist of glycine receptor) was enhanced after perinatal ethanol exposure (Pierrefiche et al., 2016). Control slices were hardly excited in the presence of strychnine whereas, after ethanol, strychnine was able to significantly increase rhythmic activity (Table 10.2). Importantly, tolerance to GABA was also observed with in situ juvenile preparation (Dubois et al., 2006) while the dampened response to chemosensory challenges in situ described above was corrected in the presence of a low concentration of strychnine (Dubois

*

nM

fmol/mg

60

800

30

400

0

*

0

Kd

CTL EtOH

Bmax

In situ binding experiment for [3H]strychnine. After ethanol exposure, Kd decreased and Bmax increased in the brainstem of in situ preparation.

FIGURE 10.3

et al., 2008). In addition, Dubois et al. (2008) measured an increase in the number of binding sites for strychnine in the medulla after ethanol exposure (Fig. 10.3). The efficacy of excitatory amino acids transmission was also reduced since NMDA bath application was inefficient after ethanol exposure, while mRNA levels for GluNR1 and GluN2B subunits of the NMDA receptor were significantly reduced in the rhythmic slices. A similar reduction in the efficacy of AP-5 was found. Ji, Wu, and Qian (2015) investigated the involvement of 5-HT2A receptors in the effects of prenatal ethanol exposure on respiratory activity using in vitro neonatal brainstem rhythmic slices. Surprisingly, in contrast to their other research (Ji, Qian, & Wu, 2015), they found a decrease in burst frequency in the group of animals exposed to alcohol at the dose of 4%, 8%, and 10% with the greatest effects at 8% ethanol. Nevertheless, the effects of ethanol were accompanied with a reduction of 5HT-2A mRNA and protein expression levels in the preBo¨tzinger area as well as tolerance to both agonist and antagonist of 5HT-2A receptors (Ji, Wu, et al., 2015; Ji, Qian, et al. 2015). These data could be

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95

KEY FACTS

5HT2C mRNA

(A) 1.6

p = .003

1.4 5HT2C/GAPDH

(B)

CTL EtOH

1.2 GAPDH

1 0.8

are still unanswered to better understand the mode of actions of ethanol during early brain development on the respiratory network. Indeed, the present study in this chapter raises the questions of which type of respiratory neurons are the most sensitive to perinatal ethanol exposure and how ethanol increases glycinergic inhibitions within the network.

0.6 5HT2C

0.4

MINI-DICTIONARY OF TERMS

0.2 0 CTL

EtOH in utero

FIGURE 10.4 mRNA levels for 5HT2C receptor measured in

rhythmic slice of rat. (A) Measurements in control (CTL) and in slices from rat models exposed prenatally to ethanol (EtOH) in utero. (B) Position of the target genes with GAPDH as reference. Unpublished data from the author.

put into perspective with previous data regarding the lack of LTF in the respiratory network, since, after ethanol, induction of long-term respiratory depression in vitro instead of LTF could be obtained after repeated applications of a 5-HT2A/2C receptor agonist. In control slices, LTF was triggered following the same drug application (Kervern et al., 2009). Additionally, it was also found in the ethanol-exposed group that mRNA levels for 5-HT2A receptors were decreased in the medulla, while those for 5-HT2C were increased (Fig. 10.4). This result was partly confirmed by Ji, Wu et al. (2015) who also reported a decrease in 5-HT2A mRNA and protein levels. Altogether, these studies describe important disturbances after ethanol exposure of breathing rhythmic activity related to a reduction in the motor output frequency generated by the respiratory network in the brainstem. However, the pharmacological targets remain to be determined.

CONCLUSION Although few preclinical studies exist on the effects of ethanol exposure during fetal life on offspring’s respiratory physiology, the results clearly show important dysfunctions of the central respiratory network. These disturbances affected both the basal rhythmogenesis properties and the capacity of the neuronal network to adapt in the short- and in long-term to low-oxygen levels. Importantly and because of the latter results, ethanol exposure during this specific period of development may be a serious risk factor for SIDS (Kervern et al., 2009). Nevertheless, many questions

Plethysmography Whole-body plethysmography is a technique for measuring respiratory parameters in conscious or anaesthetized and unrestrained or restrained animals. This method was developed for animals by Bartlett and Tenney (1970). The animal is placed into a sealed chamber and pressure variations during its ventilation are measured. From recordings, we measure tidal volume (VT, mL), inspiratory (TI, sec) and expiratory time (TE, sec) from which instantaneous breathing frequency (f, breaths/min)  and minute ventilation (V E, mL/min) as VT
f are calculated. Inspiratory inflow index An index of respiratory drive calculated from VT /TI; VT is tidal volume and TI is inspiratory duration. Gasping respiration An abnormal pattern of breathing caused by cerebral ischemia (lack of oxygen supply ang glucose), extreme hypoxia (low oxygen supply to tissue) or anoxia (depletion of oxygen). Respiratory arrest finally triggered in these conditions is interrupted by short, high amplitude inspiration characterized by gasping breathing. If such activity does not occur, death is inevitable. It is, therefore, also called “respiratory autoresuscitation.” Phrenic nerve The motor output nerve ensuring contraction of the diaphragm muscle during each inspiration. Hypoglossal nerve The motor output nerve (the twelfth cranial nerve) which innervates all the extrinsic and intrinsic muscles of the tongue, except for the palatoglossus which is involved in tongue movements. Motoneurons constituting this nerve are intermixed in the bulbar respiratory area with respiratory neurons and present comparable rhythmic activity.

KEY FACTS Prenatal Ethanol Exposure and Breathing Function • Chronic prenatal exposure to moderate levels of ethanol reduces breathing frequency in rats and breathing-related behavior in bullfrog tadpoles. • The lower frequency of breathing is long-lasting and is still observed in young adult rat offspring withdrawn from ethanol for more than a month. • The lower frequency of breathing in rats is due to a selective increase in expiratory phase. • Acute response to short-lasting hypoxia is dampened in both animal species studied. • After ethanol exposure, glycinergic inhibition is increased in mammals’ respiratory network and is responsible for a reduced response to hypoxia. • In neonatal rats, respiratory facilitation after repeated hypoxic episodes turns to depression.

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10. FETAL ALCOHOL EXPOSURE AND THE CENTRAL NERVOUS CONTROL OF BREATHING

SUMMARY POINTS • The physiology of breathing has been studied after developmental exposure to moderate levels of ethanol in rat pups and bullfrog tadpoles. • In both species, breathing was altered in several aspects and in a long-lasting manner. • In rats, breathing frequency was reduced due to a selective increase in expiratory duration, while breathing behavior was reduced in tadpoles. • In both species, the physiological response to acute low-oxygen episodes was dampened and in rats this was due to an increase in glycinergic inhibition. • In neonatal rats, the respiratory network plasticity measured as a spontaneous increase in respiratory frequency after repeated episodes of hypoxia was transformed into respiratory depression. • Cognitive deficits are induced after prenatal ethanol exposure and this chapter brings new evidence that a robust physiological function, such as breathing, might also be altered in a long-lasting manner after such exposure.

References Andersen, S. L. (2003). Trajectories of brain development: Point of vulnerability or window of opportunity? Neuroscience and Biobehavioral Reviews, 27, 3 18. Barbier, E., Pierrefiche, O., Vaudry, D., Vaudry, H., Daoust, M., & Naassila, M. (2008). Long-term alterations in vulnerability to addiction to drugs of abuse and in brain gene expression after early life ethanol exposure. Neuropharmacology, 2008(55), 1199 1211. Bartlett, D., Jr, & Tenney, S. M. (1970). Control of breathing in experimental anemia. Respiration Physiology, 10(3), 384 395. Bocking, A. D., Carmichael, L. J., Abdollah, S., Sinervo, K. R., Smith, G. N., & Brien, J. F. (1994). Effect of ethanol on immature ovine fetal breathing movements, fetal prostaglandin E2, and myometrial activity. The American Journal of Physiology, 266, R1297 R1301. Brundage, C. M., & Taylor, B. E. (2010). Neuroplasticity of the central hypercapnic ventilatory response: Teratogen-induced impairment and subsequent recovery during development. Developmental Neurobiology, 70, 726 735. Burd, L., Cotsonas-Hassler, T. M., Martsolf, J. T., & Kerbeshian, J. (2003). Recognition and management of fetal alcohol syndrome. Neurotoxicology and Teratology, 25(6), 681 688. Burd, L., Klug, M., & Martsolf, J. (2004). Increased sibling mortality in children with fetal alcohol syndrome. Addiction Biology, 9(2), 179 186. Chen, M. L., Olson, H. C., Picciano, J. F., Starr, J. R., & Owens, J. (2012). Sleep problems in children with fetal alcohol spectrum disorders. Journal of Clinical Sleep Medicine: JCSM: Official Publication of the American Academy of Sleep Medicine, 8, 421 429. Costa, E. T., Savage, D. D., & Valenzuela, C. F. (2000). A review of the effects of prenatal or early postnatal ethanol exposure on brain ligand-gated ion channels. Alcoholism, Clinical and Experimental Research, 24(5), 706 715. Dubois, C., Houchi, H., Naassila, M., Daoust, M., & Pierrefiche, O. (2008). Blunted response to low oxygen of rat respiratory network

after perinatal ethanol exposure: Involvement of inhibitory control. The Journal of Physiology, 586, 1413 1427. Dubois, C., Naassila, M., Daoust, M., & Pierrefiche, O. (2006). Early chronic ethanol exposure in rats disturbs respiratory network activity and increases sensitivity to ethanol. The Journal of Physiology, 576, 297 307. Dubois, C. J., Kervern, M., Naassila, M., & Pierrefiche, O. (2013). Chronic ethanol exposure during development: Disturbances of breathing and adaptation. Respiratory Physiology & Neurobiology, 189(2), 250 260. Eckardt, M. J., File, S. E., Gessa, G. L., Grant, K. A., Guerri, C., Hoffman, P. L., . . . Tabakoff, B. (1998). Effects of moderate alcohol consumption on the central nervous system. Alcoholism, Clinical and Experimental Research, 22, 998 1040. Gibson, I. C., & Berger, A. J. (2000). Effect of ethanol upon respiratory-related hypoglossal nerve output of neonatal rat brain stem slices. Journal of Neurophysiology, 83(1), 333 342. Guyenet, P. G., Stornetta, R. L., Abbott, S. B., Depuy, S. D., & Kanbar, R. (2012). The retrotrapezoid nucleus and breathing. Advances in Experimental Medicine and Biology, 758, 115 122. Ji, M. L., Qian, Z. B., & Wu, Y. H. (2015). Effect of prenatal alcohol exposure on rhythmic respiratory discharge activity in medullary slices of neonatal rats. Journal of Southern Medical University, 35, 598 601, Chinese. Ji, M. L., Wu, Y. H., & Qian, Z. B. (2015). Neurotoxicity of prenatal alcohol exposure on medullary pre-Bo¨tzinger complex neurons in neonatal rats. Neural Regeneration Research, 10, 1095 1100. Kervern, M., Dubois, C., Naassila, M., Daoust, M., & Pierrefiche, O. (2009). Perinatal alcohol exposure in rat induces long-term depression of respiration after episodic hypoxia. American Journal of Respiratory and Critical Care Medicine, 2009(179), 608 614. Lucas, B. R., Latimer, J., Pinto, R. Z., Ferreira, M. L., Doney, R., Lau, M., . . . Elliott, E. J. (2014). Gross motor deficits in children prenatally exposed to alcohol: A meta-analysis. Pediatrics, 134, e192 e209. Meyer-Leu, Y., Lemola, S., Daeppen, J. B., Deriaz, O., & Gerber, S. (2011). Association of moderate alcohol use and binge drinking during pregnancy with neonatal health. Alcoholism, Clinical and Experimental Research, 35, 1669 1677. Noor, S., Sanchez, J. J., Vanderwall, A. G., Sun, M. S., Maxwell, J. R., Davies, S., . . . Milligan, E. D. (2017). Prenatal alcohol exposure potentiates chronic neuropathic pain, spinal glial and immune cell activation and alters sciatic nerve and DRG cytokine levels. Brain, Behavior, and Immunity, 61, 80 95. Paton, J. F. (1996). A working heart-brainstem preparation of the mouse. Journal of Neuroscience Methods, 65, 63 68. Pierrefiche, O., Daoust, M., & Naassila, M. (2016). Use of alcohol during pregnancy in France: Another French Paradox? Journal of Pregnancy and Child Health, 3, 246. Available from https://doi. org/10.4172/2376-127X.1000246. Smith, J. C., Ellenberger, H. H., Ballanyi, K., Richter, D. W., & Feldman, J. L. (1991). Pre-Bo¨tzinger complex: A brainstem region that may generate respiratory rhythm in mammals. Science, 254, 726 729. Song, G., Yu, Y., & Poon, C.-S. (2006). Cytoarchitecture of pneumotaxic integration of respiratory and nonrespiratory information in the rat. Journal of Neuroscience., 26(1), 300 310. Taylor, B. E., Brundage, C. M., & McLane, L. H. (2013). Chronic nicotine and ethanol exposure both disrupt central ventilator responses to hypoxia in bullfrog tadpoles. Respiratory Physiology & Neurobiology, 187, 234 243. Taylor, B. E., & Brundage, C. M. (2013). Chronic but not acute ethanol exposure impairs central hypercapnic ventilator drive in bullfrog tadpoles. Respiratory Physiology & Neurobiology, 185, 533 542.

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Taylor, B. E., Croll, A. E., Drucker, M. L., & Wilson, A. L. (2008). Developmental exposure to ethanol or nicotine inhibits the hypercapnic ventilator response in tadpoles. Respiratory Physiology & Neurobiology, 160, 83 90. Watson, C. S., White, S. E., Homan, J. H., Fraher, L., Brien, J. F., & Bocking, A. D. (1999b). The adenosine A(1)-receptor antagonist 8CPT reverses ethanol-induced inhibition of fetal breathing

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C H A P T E R

11 Synaptic Plasticity in the Hippocampus and Alcohol Exposure During Brain Development O. Pierrefiche UMR1247 INSERM GRAP, Group of Research on Alcohol and Pharmacodependencies, University Centre for Health Research, University of Picardy Jules Verne, Chemin du Thil, Amiens, France

INTRODUCTION

Development of the CNS, however, does not only occur during gestation but continues until the end of adolescence (Spear, 2000). Therefore, this period also represents a sensitive time window to ethanol effects as the brain is not yet mature (Guerri & Pascual, 2010; White & Swartzwelder, 2004). The adolescent timespan drew much attention because of the prevalence of young people binge drinking (BD), that is, drinking a large amount of alcohol in a short period of time leading rapidly to drunkenness. BD is internationally defined as the consumption of five or four standard glasses of alcoholic beverages within 2 h for a man and a woman, respectively, with at least 0.8 g/L blood ethanol concentration (BEC). Importantly, between drinking episodes the subject is abstinent, making BD a repetition of high intoxicating levels of ethanol. Both preclinical and clinical data show that BD is deleterious for the CNS. Here, the main question is to determine the ethanol level threshold that induces cognitive dysfunction. Within the brain, the hippocampus is an important structure for learning and memory due to its specific neurophysiology. Ethanol is known to disturb memory through induced disturbances in the hippocampus, most notably during brain development (AlfonsoLoeches & Guerri, 2011; White & Swartzwelder, 2004). In Chapter 12, Ethanol and Cortical Spreading Depression: The Protective Role of α-Tocopherol, the disturbances of synaptic plasticity within the hippocampus after early-life ethanol exposure—either during pregnancy or adolescence—in animal models will be presented.

Ethanol is a low-weight molecule with hydrophilic and hydrophobic properties, and has great diffusion and distribution capacities within the body. Ethanol has a variety of actions in the central nervous system (CNS) resulting in psychomotor depression, motor impairment, reasoning difficulties, addiction, and deficits in new-memory formation. Consumption of alcohol (ethanol) concerns almost everyone at a different time during their lifespans. In other words, disturbances of memory by ethanol use may occur at any time. We can define three periods of ethanol exposure: (1) during gestation; (2) during adolescence/youth; and (3) during adult life. During gestation, ethanol freely crosses the placental barrier to interfere with the development of the fetus. This teratogenic property causes a large variety of disorders encompassed in fetal alcohol spectrum disorder (FASD), a continuum of symptoms from light to heavy exposure and which affects about 1% of living births. Heavy exposure to ethanol may induce fetal alcohol syndrome (FAS), internationally defined by Jones, Smith, Ulleland, and Streissguth (1973), which results in craniofacial abnormalities, general growth retardation, and some irreversible CNS dysfunctions, such as learning and memory. There is, however, mounting evidence that even light or moderate levels of ethanol exposure during fetal life may also induce similar dysfunctions. Indeed, the time-window of exposure during gestation and the threshold in the induction of deleterious effects remain important issues requiring further studies.

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00011-8

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11. SYNAPTIC PLASTICITY IN THE HIPPOCAMPUS AND ALCOHOL EXPOSURE DURING BRAIN DEVELOPMENT

THE HIPPOCAMPUS

SYNAPTIC PLASTICITY IN THE HIPPOCAMPUS

The hippocampus is bilaterally located underneath the cortex of the medial temporal lobe and belongs to the limbic system. Resembling a seahorse, its name comes from the Greek words “hippo” and “kampos” meaning, respectively, “horse” and “sea.” The hippocampus is connected to nearby structures including the presubiculum and parasubiculum and the entorhinal cortex. In mammals, the hippocampus retains similar ultrastructure and connections at cellular level with three main cellular areas, called the dentate gyrus (DG), the Cornu Ammonis field (CA, named after the horn of Amun, an ancient Egyptian god) and the subiculum. Physiologically, the entorhinal cortex provides the major input to the hippocampus reaching the DG via the perforant axonal path (Fig. 11.1). The granule cells of the DG project to the pyramidal cells of CA3, one of the CA field’s subdivisions. Axons from CA3 pyramidal cells are then projected to CA1 via the Schaefer’s collaterals. Finally, from CA1, the information reaches the subiculum which sends a major input back to the entorhinal cortex (Wible, 2013).

The hippocampus is critical for autobiographical and new-fact memories and probably allows new memories to be transferred into long-term memory. To sustain such roles, a unique physiology is required which should endow the dedicated region with a high level of plasticity. The neuronal pathway into the hippocampus is made of three excitatory glutamatergic synapses, each being capable of synaptic plasticity—a refinement of synaptic strength which provides flexibility and helps to regulate behaviors. It is then hypothesized that synaptic plasticity within the hippocampus is part of the cellular mechanisms for storing hippocampusdependent learning and memory (Malenka & Bear, 2004). Synaptic plasticity is bidirectional since synaptic strength can either be increased (long-term potentiation, LTP) relative to basal synaptic transmission, or decreased (long-term depression, LTD). Once induced, synaptic plasticity evolves with time, hence it is identified as a short-term plasticity, ranging from milliseconds to several minutes; a long-term plasticity can last several hours or days (Fig. 11.2). Only the latter form is representative of mechanisms supporting long-term memory. Different cellular mechanisms at both presynaptic and postsynaptic sites contribute to synaptic plasticity, as well as to short versus long-term forms of plasticity. Ethanol, like most drugs of abuse, is able to modulate these mechanisms. Basically, for both LTP and LTD plasticity signals, there is some NMDA dependent forms and some metabotropic glutamate (mGlu) receptors dependent forms. The former have been primarily described in the CA1 area of the hippocampus whereas the latter form is more present in the DG area. The high contribution of glutamatergic receptors permits the high level of plasticity to form new memories, but it also confers a great vulnerability since any occurring glutamate receptor abnormalities may play a role in disorders involving either glutamate receptor or synaptic plasticity at some point (Table 11.1; Johnston, 2004). Beside functional plasticity, neurogenesis, the production of new neurons, occurs in the hippocampus and participates in new learning acquisitions (Kempermann, Krebs, & Fabel, 2008). Again, ethanol is able to interfere with this process. For more details, see Fontaine, Patten, Sickmann, Helfer, & Christie, 2016 and Collingridge, Peineau, Howland, & Wang, 2010.

Alcohol and Synaptic Plasticity During Early Development FIGURE 11.1 network.

The hippocampus slice and its intrinsic neuronal

The interest to define a time-window of EtOH effects during gestation is paralleled by the time course

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SYNAPTIC PLASTICITY IN THE HIPPOCAMPUS

101

FIGURE 11.2

Schematic representation of bidirectional synaptic plasticity recorded in vitro in the hippocampus. LTP and LTD are usually induced with different electrical stimulation of the afferent pathway and starts at the 0 time point (end of stimulation). Both signals are expressed in percentage of baseline measured before plasticity induction.

TABLE 11.1

Disorders in Which GluN2B Subunit is Involved

Acquired disorders Developmental disorders Alcohol abuse

Language

Cocaine abuse

Motor impairment

Alzheimer

Learning deficits

Huntington

Autism Spectrum Disorder (ASD)

Depressive disorder

Attention deficit hyperactivity disorder (ADHD)

Chronic pain

Developmental delay Epilepsy Schizophrenia

of brain development with different cellular events taking place at discrete time points. Therefore, several studies analyzed the effects of limited exposure to ethanol during gestation. As a relative comparison between rodents and humans, the 20 21 days of gestation in rat or mice are representative of the two first trimesters of gestation in humans and rodents’ first days of life corresponds to the third trimester of human gestation (Fig. 11.3). Importantly, the hippocampus terminates its maturation postnatally in rodents. Hence, to model alcohol consumption throughout the human gestation equivalent, animal exposure during prenatal and postnatal periods is necessary. The results are summarized in Table 11.2. Before mothers know about their pregnancy, the human embryo has already passed two developmental steps. The first one is gastrulation in the third week of gestation and the second one is neurulation during the

fourth week. Two acute high doses of ethanol in mice on gestational day seven (GD7), during gastrulation or on GD8, during neurulation (BEC at 380 and 500 mg/ dL) damaged several brain region including the hippocampus (Godin et al., 2010) while learning and memory deficits occur (Minetti, Arolfo, Virgolini, Brioni, & Fulginiti, 1996; Summers, Henry, Rofe, & Coyle, 2008). Importantly, comparable cognitive deficits have also been found recently in mice with low and moderate ethanol levels (Schambra, Lewis, & Harrison, 2017; BEC at 104 mg/dL at GD7 and 177 mg/dL at GD8). Furthermore, EtOH treatment at postnatal day 7, (PND7; 2 3 2.5 g/kg s.c. 2 h apart) impaired both NMDA-dependent CA1-LTP and LTD in slices from PND30 offspring while an NMDA-independent form of LTP was still visible (Izumi et al., 2005). These results were replicated in 3-month-old mice (BEC 460 mg/dL) with memory deficits (Subbanna & Basavarajappa, 2014). Longer postnatal exposure via EtOH inhalation between PND2 9 and with a BEC of 320 395 mg/dL (Puglia & Valenzuela, 2010) reduced CA1-LTP in slices prepared immediately after exposure. However, nothing was noted if BEC reached 97 mg/dL. In contrast, no effect on LTP was reported in slices from PND45 60 animals after a PND4 9 treatment (BEC 351 mg/dL; Bellinger, Bedi, Wilson, & Wilce, 1999), although synaptic efficacy was reduced. In vivo, using PND55-70 rats, DG-LTP. was tested after exposure restricted to one trimester equivalent inducing a BEC of 91.6, 94.3, and 255.1 mg/dL for the first, second, and third trimester equivalent, respectively (Patten et al., 2013a). In males, DG-LTP was unaffected if exposure was restricted to one trimester equivalent only. In contrast, DG-LTP increased in females after

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11. SYNAPTIC PLASTICITY IN THE HIPPOCAMPUS AND ALCOHOL EXPOSURE DURING BRAIN DEVELOPMENT

FIGURE 11.3 Comparison between rat and human development.

TABLE 11.2 BEC (mg/dL)

EtOH Effects on Hippocampus Synaptic Plasticity After Exposure During Early Period of Brain Development

LTP

LTD

Behavior

Treatment

References

380

memory deficits

2 3 2.5 g/kg ip G D7

Summers et al. (2008)

500

memory deficits

2 3 2.5 g/kg ip G D8

Summers et al. (2008)

104

memory deficits

GD7

Schambra et al. (2017)

177

memory deficits

GD8

Schambra et al. (2017)

2 3 2.5 g/kg sc PND7

Izumi et al. (2005)

2 3 2.5 g/kg sc PND7

Subbanna et al. (2015)

impaired at PND30

impaired at PND30

460

impaired at 3 mo

impaired at 3 mo

320 395

CA1-LTP dec. at PND10 slices

Vapor PND2-9

Puglia and Valenzuela (2010)

97

no effect at PND10 slices

Vapor PND2-9

Puglia and Valenzuela (2010)

351

no effect in PND45-60 slices

PND4-9

Bellinger et al. (1999)

91.6

Male DG-LTP unaffected in vivo PND55 70

trimester 1

Patten et al. (2013a)

94.3

Male DG-LTP unaffected in vivo PND55-70

trimester 2

Patten et al. (2013a)

255.1

Male DG-LTP unaffected in vivo PND55-70

trimester 3

Patten et al. (2013a)

255.1

Female DG-LTP unaffected in vivo PND55-70

trimester 3

Patten et al. (2013a)

155

No effect Slices PND50-70

trimester 1

Helfer (2012)

142

DG-LTP dec no gender effect slices PND50-70

trimester 2

Helfer (2012)

314-347

No effect Slices PND50 70

trimester 3

Helfer (2012)

83

DG-LTP dec in vivo PND120-150

All gestation

Sutherland et al. (1997)

No effect CA1-LTP PND25-32 and PND 63-77 slices

All gestation

Krahl et al. (1999)

Memory deficits

7

no effect

All gestation

Savage et al. (2002)

30

no effect

All gestation

Savage et al. (2002) (Continued)

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SYNAPTIC PLASTICITY IN THE HIPPOCAMPUS

TABLE 11.2 BEC (mg/dL)

(Continued)

LTP

LTD

83

Behavior

Treatment

References

memory deficits

All gestation

Savage et al. (2002)

379-448

CA1-LTP dec in vivo PND48-80 guinea pig

learning deficits

All gestation

Richardson et al. (2002)

245

no effect on CA1-LTP in vivo PND40-80 guinea-pig

no effect

Only BGS period

Byrnes et al. (2004)

184

DG-LTP dec in vivo PND60

learning deficits

All gestation

Christie et al. (2005)

90

DG-LTP red. Slices 2-5 mo

All gestation

Brady et al., 2013

100

CA1-LTP dec. PND45-55

All gestation 1 weaning

Kervern et al. (2015)

83

DG-LTP dec in vivo PND105-140

All gestation

Varaschin et al. (2010, 2014)

87

DG-LTP inc. Female in vivo PND30-35

All gestation

Titterness and Christie (2012)

87

DG-LTP dec. male in vivo PND30-35

All gestation

Titterness and Christie (2012)

146

DG-LTP dec. male in vivo PND55-70

All gestation

Sickmann et al. (2014)

146

no effect in female

All gestation

Sickmann et al. (2014)

CA1-LTP dec male in vivo PND36

All gestation

An (2013)

CA1-LTP inc. Female in vivo PND36

All gestation

An (2013)

192

CA1-LTD no effect in male in vivo PND30-35

All gestation

Titterness and Christie (2008)

192

CA1-LTD dec female in vivo PND30-35

All gestation

Titterness and Christie (2008)

100

CA1-LTD inc. Slices male PND45-55

All gestation 1 weaning

Kervern et al. (2015)

exposure during the third trimester equivalent alone with no effect after other exposure. In contrast, only exposure during the second trimester equivalent (BEC 142 mg/dL) decreased DG-LTP without gender effects in slices from PND50 70 offspring (Helfer, White, & Christie, 2012) whereas minor changes were reported after either the first or third trimester equivalent exposure (BEC 155 and 314 347 mg/dL, respectively). Other studies tested ethanol exposure during the entire gestation or during gestation and lactation periods. A nonsignificant decrease in CA1-LTP was observed in acute slices from PND50 70 offspring after ethanol exposure throughout gestation (Swartzwelder, Farr, Wilson, & Savage, 1988), a result replicated by Tan, Berman, Abel, and Zajac (1990) in older rats (PND90 120). Using similar exposure with in vivo recordings in PND125 150 old rats, a reduction in DG-

LTP (Sutherland, McDonald, & Savage, 1997) with a BEC of 83 mg/dL was found. Exposure throughout gestation via intragastric gavage at either 4 or 6 g/kg/day did not alter CA1-LTP measured in vitro in PND25 32 adolescent and PND63 77 young-adult rats (Krahl, Berman, & Hannigan, 1999); only maximum response to input stimulation was reduced in the 6 g/kg/day group and only in the young-adult rats group. Altogether the effects of ethanol exposure during gestation in rats suggested dose-dependent and agedependent effects in inducing abnormal electrophysiology in the hippocampus associated with a tendency for LTP to be reduced. Dose-dependency of prenatal EtOH effects were tested to help with defining a threshold of EtOH exposure to trigger long-lasting deleterious effects. With 2%, 3%, or 5% ethanol consumption throughout

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11. SYNAPTIC PLASTICITY IN THE HIPPOCAMPUS AND ALCOHOL EXPOSURE DURING BRAIN DEVELOPMENT

FIGURE 11.4 Effects of EtOH during gestation on synaptic plasticity.

gestation in rats (Savage, Becher, de la Torre, & Sutherland, 2002), with BEC levels of 7, 30, and 83 mg/dL, respectively, a reduction in activitydependent potentiation of D-aspartate release from slices and in a learning task only in the 5% ethanol group was found. This study suggests that the threshold for subtle learning deficits in offspring prenatally exposed to EtOH is about 30 mg/dL (approximately 30 45 mL EtOH equivalent drinking per day; that is, one standard dose of spirituous alcohol per day). The results were extended to guinea-pigs exposed to either 3 or 4 g/kg/day via aqueous ethanol solution during gestation, including the brain-growth spurt period (Richardson, Byrnes, Brien, Reynolds, & Dringenberg, 2002). CA1-LTP recorded in vivo in PND40 80 offspring was reduced only in the 4 g/kg/day group (BEC in females from 379 to 448 mg/ dL) accompanied with learning deficits. Byrnes, Richardson, Brien, Reynolds, and Dringenberg (2004) restricted exposure to 3 g/kg/day only during the growth spurt period and found no effects on either LTP or learning (BEC 245 mg/dL in females). Still in vivo, DG-LTP was reduced together with learning capability after EtOH exposure throughout gestation in rats via a liquid diet (Christie et al., 2005; BEC 184 mg/dL). Besides these high levels of ethanol exposure, moderate exposure also produced a reduction of both DGLTP (Brady et al. 2013) and CA1-LTP (Kervern et al., 2015) in slices from either 2 5-month-olds or PND45 55 offspring, respectively. Interestingly, using different ethanol exposures the BEC in females was similarly moderate (90.5 100 mg/dL). In addition, a BEC of 83 mg/dL obtained with intermittent access for 4 hours a day to a 5% EtOH solution throughout gestation in rat (Varaschin, Akers, Rosenberg, Hamilton, & Savage, 2010; Varaschin, Rosenberg, Hamilton, & Savage, 2014) decreased DG-LTP of in vivo adult male offspring (PND105-140).

All these studies concerned male offspring, but the female brain of both humans and rodents is possibly more sensitive to alcohol, notably in terms of microcephaly or white matter integrity (Smith et al., 2017). In this context, in vivo recordings of PND30 35 offspring prenatally exposed to EtOH throughout gestation showed that DG-LTP in females was enhanced, whereas it was decreased in males (Titterness & Christie, 2012; BEC 87 mg/dL). This was replicated in males, but not in females (Sickmann et al., 2014), although the animals were older (PND55 70) and BEC was higher (146 mg/dL). Sexually dimorphic effects of EtOH on synaptic plasticity was also reported after intragastric gavage of EtOH (4 g/kg/day) from 7 days before mating until delivery (An & Zhang, 2013; An, Yang, & Zhang, 2013). In vivo recordings of PND36 offspring revealed a decrease in CA1-LTP in males and an increase in females. Moreover, depotentiation (i.e., reversion of a previously induced LTP) was enhanced in males, but absent in females. The other form of synaptic plasticity, LTD, has been much less studied. Nevertheless, Titterness and Christie (2008) showed that EtOH exposure during gestation (BEC approximately 192 mg/dL at GD15) does not affect CA1-LTD in PND30 35 male offspring, but reduced it in female offspring, revealing a sexual dimorphic effect of prenatal EtOH exposure on LTD. More recently, it was found that an enhancement of LTD in male offspring (PND45 55) after similar exposure with BEC of 100 mg/dL in females (Kervern et al., 2015). Fig. 11.4 summarizes the effects of EtOH on synaptic plasticity between males and females. In this figure we see that results obtained in female are the opposite to what is generally found in male. However, it should be noted that most of the experiments performed with female animals were done in vivo. In addition, females are possibly more sensitive to males

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105

CONCLUSION

when exposure is performed during the third trimester equivalent (i.e., during the first days of life).

Alcohol and Synaptic Plasticity During Adolescence Final maturation of the CNS does not occur before adolescence, that is, early adult life. Adolescence is characterized by final maturation of emotion, behavior, and cognition (Spear, 2000). Animal models of human adolescence are important research tools since many of the developmental, as well as physiological and behavioral changes, occurred similarly in rodents and humans, and are probably similarly underlined by a brain growth-spurt period (Fig. 11.3). Concerning the hippocampus in humans, the posterior subregions are enlarged while anterior subregions (near the amygdala) showed reduction between the age of 4 and 25 years (Gogtay et al., 2006) and myelination in the subiculum accompanies an increase in volume, most notably in males (Suzuki et al., 2005). Because the adolescent brain is still immature, consuming EtOH at that time could affect late physiological neural development. Indeed, neurobehavioral and neuroimaging studies suggest that adolescence is a period of heightened vulnerability to alcohol’s deleterious effects in particular for the cortex and the hippocampus, which are both involved in learning and memory (De Bellis et al., 2000; Nagel, Schweinsburg, Phan, & Tapert, 2005). Chronic alcohol use during adolescence in humans is associated with impairments of working memory (Sher, 2006) or fear conditioning (Stephens et al., 2005), suggesting EtOH-induced alterations in synaptic plasticity. Many studies in rodent use animal model of human binge drinking, and two main issues have been studied: (1) to demonstrate that adolescence is a critical period regarding the deleterious effects of EtOH on cognitive functions and on synaptic plasticity in the hippocampus; and (2) to determine a threshold for inducing such damages. Concerning the first, EtOH effects were compared in adolescent versus adult animals. Acquisition of spatial memory is more impaired by acute ethanol intake (1 2 g/kg i.p.) in adolescent than in adults animals (Markwiese, Acheson, Levin, Wilson, & Swartzwelder, 1998), and 5 consecutive days (2 g/kg i.p.) of ethanol treatment induce more persistent spatial memory deficits in adolescent than in adult rats, without taking gender effects into account (Sircar & Sircar, 2005; Sircar, Basak, & Sircar, 2009). Acute ethanol intake produces selective changes in ERK1/2 phosphorylation levels, a marker of plasticity, in the adolescent brain as compared to the adult, which is furthermore associated with impairment in hippocampal-dependent memory (Spanos, Besheer, & Hodge, 2012).

Concerning the second question, acute ethanol application (1 50 mM) on hippocampal adult brain slices reduces excitatory postsynaptic potentials (EPSPs) and CA1-LTP at 5 mM concentration (Blitzer, Gil, & Landau, 1990; Lovinger, White, & Weight, 1990). Similarly, in PND12-30 male rat hippocampal slices, acute ethanol reduces DG-LTP (Morrisett & Swartzwelder, 1993), NMDA current and NMDAEPSPs. Indeed, EtOH inhibits EPSPs in CA1 of juvenile rat hippocampus slice at lower concentrations than in adult slices (10 30 vs 100 mM; Pyapali, Turner, Wilson, & Swartzwelder, 1999; Swartzwelder, Wilson, & Tayyeb, 1995). Regarding synaptic plasticity, 60 mM EtOH in vitro inhibits LTP in juvenile, but not in adult, hippocampus slices (Swartzwelder et al., 1995). Chronic intermittent EtOH exposure (inhalation for 2 weeks; BEC 189 mg/dL) results also in a transient decrease of LTP in slices from PND 40 to 45 rats (Roberto, Nelson, Ur, & Gruol, 2002; BEC approximately 180 mg/dL; Sabeti and Gruol, 2008, BEC approximately 210 mg/dL) and from adult rats, but after longer repeated periods of EtOH exposure (Stephens et al., 2005). A recent study demonstrated that only two episodes of EtOH intoxication (2 “binges” 3 g/kg i.p.; BEC 197 mg/dL) transiently and selectively abolished CA1-LTD of adolescent male rat slices 48 h after treatment, associated with learning deficit (Silvestre de Ferron et al., 2015). This effect was accompanied with a higher expression of GluN2B subunit of the NMDA receptor in the synaptic cleft. Altogether, deleterious EtOH effects on hippocampal physiology via alterations of hippocampal glutamatergic (NMDA) neurotransmission and, thus, of synaptic plasticity, are part of the mechanisms of EtOHinduced memory deficits. Globally, the determination of threshold effects for EtOH exposure during adolescence have not been thoroughly studied. Concerning binge drinking, the shortest procedure is perhaps the one used by Silvestre de Ferron et al. (2015) with only two intoxications in adolescent rats.

CONCLUSION According to preclinical studies, the brain remains highly sensitive to EtOH throughout the duration of its maturation, inducing alteration in learning and memory. Indeed, there is little doubt that synaptic plasticity in the hippocampus is altered by EtOH whatever the period and mode of exposure: either acutely with binge-like drinking procedures during early- or latepregnancy or chronically throughout pregnancy, or during adolescence with repeated binging. However, a definitive picture remains difficult to establish because of the numerous models of exposure used, as well as

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the timing of exposure and BEC reached by the different paradigms. Hence, many details are still missing. For example, a threshold of how much ethanol a woman can drink during pregnancy, or on one occasion as an adolescent, is not yet clearly defined. The same is true for the moment at which EtOH consumption is the most deleterious during fetal life. Other caveats appeared recently, such as lack of knowledge about the sexual dimorphic effects of EtOH between male and female offspring or adolescent animals, as well as research on EtOH effects on LTD. Nonetheless, according to the burden of fetal alcohol exposure for the newborn and society, as well as the burden of binge-drinking during adolescence on the brain, and for the future generations, more research is warranted.

KEY FACTS Synaptic Plasticity in the Hippocampus and Alcohol Exposure During Brain Development • Consumption of alcohol during gestation alters bidirectional synaptic plasticity in the hippocampus, the cellular mechanisms of memory, in an irreversible manner. • According to preclinical studies, there is no safe period during gestation for drinking alcohol. • Alterations also exist if exposure to alcohol is during adolescence and young adult life. • All these disturbances are associated with lower learning and memory capabilities in both clinical and preclinical studies. • Mechanisms of these cellular disturbances involves at least both glutamatergic and GABAergic neurotransmissions in the hippocampus.

SUMMARY POINTS • Exposure to ethanol during brain development, either chronically or acutely in a binge manner, is deleterious for memory in both humans and animal models because ethanol alters synaptic plasticity in the hippocampus, the cellular mechanisms of learning and memory. • Specifically, LTP of the synaptic signal is depressed in the offspring prenatally exposed to ethanol, while LTD is probably increased. • Any type of exposure at any time during gestation induces such disturbances. • Preclinical studies suggest that a blood ethanol content in the dams of ca. 100 mg/dL is required to disturb hippocampus physiology.

• During adolescence, when the brain terminates maturation, similar effects of ethanol are observed although both LTP and LTD are reduced. • During adolescence, binge-type exposure needs to be repeated to cause deleterious effects, while the threshold for these effects is still unknown. • Mechanisms of ethanol’s effects involved inhibition of excitatory NMDA receptors and a possible increase in GABA-A receptors activity.

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Titterness, A. K., & Christie, B. R. (2012). Prenatal ethanol exposure enhances NMDAR-dependent long-term potentiation in the adolescent female dentate gyrus. Hippocampus, 22(1), 69 81. Varaschin, R. K., Akers, K. G., Rosenberg, M. J., Hamilton, D. A., & Savage, D. D. (2010). Effects of the cognition-enhancing agent ABT-239 on fetal ethanol-induced deficits in dentate gyrus synaptic plasticity. The Journal of Pharmacology and Experimental Therapeutics, 334(1), 191 198. Varaschin, R. K., Rosenberg, M. J., Hamilton, D. A., & Savage, D. D. (2014). Differential effects of the histamine H(3) receptor agonist methimepip on dentate granule cell excitability, paired-pulse plasticity and long-term potentiation in prenatal alcohol-exposed rats. Alcoholism, Clinical and Experimental Research, 38(7), 1902 1911. White, A. M., & Swartzwelder, H. S. (2004). Hippocampal function during adolescence: a unique target of ethanol effects. Annals of the New York Academy of Sciences, 1021, 206 220. Wible, C. G. (2013). Hippocampal physiology, structure and function and the neuroscience of schizophrenia: a unified account of declarative memory deficits, working memory deficits and schizophrenic symptoms. Behav Sci (Basel), 3(2), 298 315.

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C H A P T E R

12 Ethanol and Cortical Spreading Depression: The Protective Role of α-Tocopherol 1

Rubem Carlos Arau´jo Guedes1, Ranilson de Souza Bezerra2 and Ricardo Abadie-Guedes3

Department of Nutrition, Federal University of Pernambuco, Recife, Brazil 2Department of Biochemistry, Federal University of Pernambuco, Recife, Brazil 3Department of Physiology and Pharmacology, Federal University of Pernambuco, Recife, Brazil

LIST OF ABBREVIATIONS CSD DC ECoG EEG MEG ROS

cortical spreading depression direct-current electrocorticogram electroencephalogram magnetoencephalogram reactive oxygen species

INTRODUCTION: ALCOHOLISM AND BRAIN INJURY Alcohol consumption on a regular and gradually increasing basis is usually denoted as alcoholism. The negative effects of alcoholism on the brain are mainly due, among other mechanisms, to oxidative and free radical injury to the brain cells (Brocardo et al., 2017). The impact of redox imbalance in the brain can be substantial, as the brain uses about 20% of the body’s oxygen. This renders neurons and glial cells much more susceptible to oxidative injury (Guillemin, Essa, Song, & Manivasagam, 2017). In the past few decades, the concerns of health authorities have increased considerably regarding the negative effects of alcoholism (Topiwala et al., 2017). Compared with nondrinkers, alcohol consumers are considered at a higher risk of stroke (Fontes-Ju´nior et al., 2016), brain structure and cognitive alterations (Hendrickson et al., 2017), and

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00012-X

disturbances of brain development and function (Brocardo et al., 2017). Recent evidence suggests that ethanol administration affects brain synaptic plasticity via mechanisms that involve microglia reaction (Wong, Stowell, & Majewska, 2017). Both simple and complex brain physiological executions of motor and sensorial activity can be negatively influenced by drinking alcohol (Houle´, Abdi, & Clabough, 2017). Why do people drink alcoholic beverages? A simple answer to this question would be: “because alcohol elicits sensations of well-being and pleasure” (Guedes, Bezerra, & Abadie-Guedes, 2016). The appearance of techniques for alcohol distillation led humans to change their pattern of drinking alcoholic beverages, with increasing consumption of higher alcohol amounts in smaller volumes, which facilitated observing the negative effects of alcohol on human health. As recently suggested, ethanol metabolism in the brain appears to result in an increased amount of reactive oxygen species (ROS), which are toxic to brain tissue (Reddy et al., 2017). In this chapter, we revisit the topic, extending our previous experimental studies on the effect of ethanol ingestion on brain electrical activity as evaluated by ethanol’s action on the phenomenon known as cortical spreading depression (CSD) of brain electrical activity (Lea˜o, 1944a), which we have investigated over the past three decades (for a review, see Guedes, 2011).

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Using the CSD model, we studied the action of the antioxidant, carotenoid molecule, astaxanthin, on the brain effects of ethanol (for a review, see AbadieGuedes, Guedes, & Bezerra, 2012; Abadie-Guedes, Santos, Cahu´, Guedes, & Bezerra, 2008). In this chapter, we discuss recent findings (Abadie-Guedes, Bezerra, & Guedes, 2016) on the protective role of the antioxidant, noncarotenoid vitamin α-tocopherol (vitamin E) against the harmful action of ethanol on CSD, which is influenced by the production of ROS in the neural tissue (Netto & Martins-Ferreira, 1989). Our novel results in α-tocopherol-treated rats support a role for this antioxidant molecule in counteracting the CSD actions of both acute and chronic alcohol consumption.

ALCOHOL AND BRAIN ELECTRICAL ACTIVITY In healthy individuals, the diverse functions of the brain are executed via the production of electrical activity. Currently, electrophysiological recording techniques have been substantially improved, and electronic microchip-based integrated circuit devices enable signal digitalization and storage on computers and have definitely proved to be of great aid in diagnosing neurological disorders such as epilepsy (Asadi-Pooya, Dlugos, Skidmore, & Sperling, 2017), in conjunction with statistical or mathematical methods in some cases (Hasan, Ahamed, Ahmad, & Rashid, 2017). The noninvasive recording of brain electric activity that is performed in humans is denoted as electroencephalogram (EEG). It is currently possible to record the magnetic activity generated in the brain. This technique is termed magnetoencephalogram (MEG); MEG data have recently suggested the impairing action of ethanol on decision making (Rosen, Padovan, & Marinkovic, 2016). Some controversy still involves the possibility, raised by others (Sand et al., 2010), that alcoholdependent humans develop epilepsy. In rats, ethanol consumption has been associated with electrophysiological signs of seizures and spreading depression in the hippocampus (Bonthius et al., 2001). Regarding this scenario, we have investigated the ethanol/ spreading depression relationship in the rat neocortex (Guedes et al., 2016). Table 12.1 documents alterations in brain functional processes, which are associated to ethanol ingestion. The data collectively suggest that exposing developing rats to ethanol alters the electrophysiological activity of the brain in a longlasting manner.

STUDIES OF BRAIN EFFECTS OF ALCOHOL EMPLOYING THE CORTICAL SPREADING DEPRESSION MODEL CSD is a brain phenomenon that was first described by the Brazilian scientist Aristides A.P. Lea˜o. He was recording the electrocorticographic activity in the exposed cerebral cortex of anaesthetized rabbits when he first observed a diminution (depression) of EEG waves in response to the stimulation of a point of the cortical surface (Lea˜o, 1944a), which was accompanied by vasodilation of the cortical blood vessels (Lea˜o, 1944b) and by a direct current (DC), slow potential change in the depressed cortical point in relation to a remote reference point (Lea˜o, 1947). CSD results in neuronal and glial depolarization, with consequent brain electrical silence, which fully recovers after a few minutes. From the stimulated area, CSD gradually invades remote cortical regions, while the initially depressed point starts to recover. The recovery occurs in a similarly concentric way, which characterizes a fully reversible phenomenon. In contrast to the fast propagation of action potentials in neurons (measured in m/s), CSD propagates with a much lower velocity (measured in mm/min; Guedes et al., 2016), which indicates that CSD is a, paradoxically, very slow propagating neural phenomenon. CSD is postulated as being causally involved in important, excitabilityrelated neurological diseases such as migraines (Vinogradova, 2017), stroke, and epilepsy (Dreier et al., 2012; Lea˜o, 1972). An example of electrocorticographic activity diminution and slow potential change recording that are typical of CSD in the rat cortex is presented in Fig. 12.1. CSD has also been demonstrated in the human brain, both in vitro (Maslarova et al., 2011) and in vivo (Hartings et al., 2017). A compilation of the main features and feature-derived remarks of CSD is presented in Table 12.2. A number of nutritional and nonnutritional conditions, such as those represented by environmental, pharmacologic, and hormonal treatments, can either strengthen or weaken the ability of the brain to propagate CSD, leading to slower or faster CSD propagation in comparison with a normal brain, respectively (Guedes, 2011; Guedes et al., 2017). Therefore, the CSD velocity of propagation constitutes an interesting indicator of those changes which can be easily calculated based on the time spent by a CSD wave to pass through the distance between two cortical recording points (Fig. 12.1). The most-discussed hypotheses about CSD mechanisms include the participation of increased generation of ROS in the nervous tissue (Netto & Martins-Ferreira, 1989; Mendes-da-Silva et al., 2014). The increase in the

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STUDIES OF BRAIN EFFECTS OF ALCOHOL EMPLOYING THE CORTICAL SPREADING DEPRESSION MODEL

TABLE 12.1

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Examples of Key Features on the Effects of Ethanol Consumption on Brain Function

Species

References

Condition

Effect

Human

Squeglia, Jacobus, and Tapert (2014)

Review on studies about measurements of brain structure, function, and behavior.

Adolescent ethanol consumers show differences in brain structure, function, and behavior when compared with nondrinking controls.

Human

Can et al. (2017)

The medical records of 4701 patients with 6411 radiographically confirmed intracranial aneurysms were reviewed.

Current alcohol use was associated with rupture status compared with never drinkers. Former alcohol use was not significant.

Human

Rosen et al. (2016)

Healthy social drinkers participated in both alcohol and placebo conditions. Whole-head magnetoencephalography signals were acquired and event-related theta power was calculated.

A rostro-caudal activity gradient in the medial prefrontal cortex is modulated by task difficulty. Conflict-related theta power was selectively reduced by alcohol only under the more difficult task.

Human

Nikulin, Nikulina, Study in 12 healthy subjects after 0.8 g/kg alcohol Yamashita, Rossi, or juice in a double-blind, placebo-controlled, crossand Ka¨hko¨nen (2005) over design using simultaneous high-resolution MEG and EEG.

Alcohol significantly increased the relative power of alpha rhythm (8 10 Hz) and reduced the relative power of beta activity (17 25 Hz), but only in the eyes-closed condition.

Rat

Liu and Crews (2017) Rats received adolescent intermittent ethanol (AIE) exposure. Neural progenitor cell proliferation, differentiation, survival and maturation was determined.

AIE exposure lastingly decreased neurogenesis

Rat

Wong et al. (2017)

This paper discusses the current understanding of the alcohol exposure/microglial behavior relationship.

Rat

Brocardo et al. (2017) This study compared the effects of EtOH exposure during distinct periods of brain development on oxidative damage and antioxidant status in rats.

Early EtOH exposure increased lipid peroxidation, decreased the levels of the endogenous antioxidant glutathione.

Rat

Blaker and Yamamoto (2017)

Rats voluntarily drank 10% ethanol every other day for 4 weeks and were then exposed to a binge injection regimen of Meth (10 mg/kg injected every 2 h, for a total of 4 injections).

EtOH drinking increased inflammatory mediators involved in a synergistic interaction with Meth to increase neurotoxicity.

Transgenic mice

Rotermund et al. (2017)

To investigate the effect of αSYN on the addictive properties of chronic alcohol use, in transgenic mice expressing the human mutant [A30P]αSYN throughout the brain.

EtOH effects under operant self-administration conditions were increased. Acute ethanol injection enhanced immunostaining for the phosphorylated form of cAMP response element binding protein of αSYN transgenic mice, while in WT mice no effect was visible.

The authors reviewed the literature that links microglia to neural circuit remodeling, in the context of developmental alcohol exposure.

production of ROS is important in the context of this chapter as chronic alcohol consumption is usually associated with ROS generation in the brain (Reddy et al., 2017). Using the CSD model in the rat cortex, we investigated the effects of various paradigms of ethanol intake on CSD propagation in order to clarify the mechanisms underlying the action of ethanol on brain electrical activity. Firstly, we demonstrated that ethanol administration to adult rats by gavage for 7 days (Guedes & Frade, 1993) or longer (Abadie-Guedes et al., 2008) facilitated CSD propagation in a dose-dependent manner (Abadie-Guedes et al., 2008). The ethanolinduced augmentation of ROS in the brain (Brocardo et al., 2017) is counteracted by antioxidant molecules, such as ascorbic acid (Mendes-da-Silva et al., 2014) and carotenoids (Abadie-Guedes et al., 2008). By treating

rats with 30 μg/kg/day by gavage of a carotenoid extract from shrimp waste (shrimp heads), we were able to neutralize the accelerating action of ethanol on CSD propagation (Bezerra et al., 2005). The most abundant carotenoid present in shrimp is astaxanthin, which has strong antioxidant activity in living organisms, protecting them against oxidative injury under conditions of redox imbalance (Miki, 1991). To test the hypothesis that the large amount of astaxanthin present in the shrimp carotenoid extract could be responsible for the antagonizing action of that extract against the ethanol effect on CSD, we treated rats with pure astaxanthin. Astaxanthin dose-dependently replicated the shrimp extract effects against the ethanol action on CSD, under conditions of both chronic (Abadie-Guedes et al., 2008) and acute ethanol treatment (Abadie-Guedes et al., 2012).

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These findings support the hypothesis of an astaxanthinmediated action of the shrimp carotenoid extract against the CSD effects of ethanol.

THE α-TOCOPHEROL PROTECTIVE INTERACTION WITH ETHANOL ON THE BRAIN

FIGURE 12.1 Reduction of the electrocorticographic activity and DC potential shift that is typical of cortical spreading depression. Recordings on two points (marked as 1 and 2 on the skull diagram) of the brain cortical surface of an anaesthetized rat showing the electrocorticographic activity (E) and the slow potential (P) change that characterize cortical spreading depression (CSD). The horizontal bar under the E1 trace (left) indicates the time (1 min) of application of the CSD eliciting stimulus: a cotton ball (1 2 mm diameter) soaked in 2% KCl solution (about 270 mM). The skull diagram also shows the position of the reference electrode (Ref., on the nasal bones), as well as the place of KCl stimulus (on the frontal cortex). Vertical calibration bars (negativity upwards) equal 1 mV for the ECoG- and 10 mV for the Precordings. The vertical interrupted lines delimit the latency time for a CSD wave to spread from point 1 to point 2. We calculate the CSD velocity of propagation by dividing the interelectrode distance (d in the skull diagram) by the latency time (t), as indicated by the formula on the bottom right (unpublished record from our laboratory). TABLE 12.2

After having demonstrated the antagonizing action of carotenoids (Abadie-Guedes et al., 2008; 2012; Bezerra et al., 2005), we decided to investigate whether noncarotenoid antioxidants such as α-tocopherol would also exert a similar effect on the CSD phenomenon in ethanol-treated rats. The data (Abadie-Guedes et al., 2016) supported a “yes” answer to this question, as presented next. The antioxidant molecule known as α-tocopherol, or vitamin E, exerts its action by donating protons and, thus, neutralizing ROS in various mammalian organs, including the brain (Zakharova et al., 2017). Under two ethanol treatment protocols, namely acute (a single dose of 3 g/kg of ethanol), and chronic ethanol administration (a daily dose of 3 g/kg over 21 days), we tested α-tocopherol effects on CSD in rats of two age ranges, namely 60 80 days and 150 180 days. Substances (vehicle, ethanol, or ethanol 1 tocopherol) were administered directly into the stomach through a cannula inserted in the mouth (gavage procedure). Immediately after finishing the gavage treatment, a

Key Features and Feature-Derived Remarks of CSD

Aspect

Feature

Remarks

Brain cytoarchitectonics

CSD is observed in brain structures containing a minimal population of cell bodies, but not in fiber-only structures

CSD is a “social” phenomenon (i.e., CSD needs a minimum of cell-body population to exist)

CSD eliciting stimulus

CSD can be triggered by stimuli from electrical, mechanical, chemical, etc. origin (i.e., any type of energy)

Stimulus specificity is not required for CSD to be elicited

Functional status of the brain after CSD

One cortical area under CSD becomes functionally inactive. After a few minutes, the area recovers its function

Total reversibility is an important feature of CSD

Relationship between CSD and functional limits of the cortical areas

CSD propagation does not change appreciably, when it moves from a sensorial to a motor area, and vice-versa

CSD propagation does not depend on the function of the invaded area

CSD in different animal species

CSD has been detected from fishes to man

CSD is a very general phenomenon in the brain

CSD velocity of propagation

CSD propagates at a velocity of 2 5 mm/min

In contrast to the fast propagation of neuronal action potentials (m/s), CSD is a very slow propagating phenomenon

Lysencephalic versus gyrencephalic brains and CSD

CSD propagation faces more difficulty in the gyrencephalic, as compared with the lisencephalic brain

Gyrification of the cerebral cortex makes CSD propagation more difficult

CSD Relationship with neurological diseases

Some disorders of the nervous system share common features with CSD

The comprehension of certain neurological diseases may benefit from understanding CSD mechanisms

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113

CSD recordings in rats under acute treatment with vehicle (oil), ethanol and ethanol 1 tocopherol. Recordings of the slow potential (P) change of cortical spreading depression (CSD) on the surface of the cerebral cortex of three rats that were acutely treated (a single gavage) with vehicle (olive oil), ethanol, or ethanol 1 α-tocopherol. The horizontal bar under the P1 traces (left) indicates the time (1 min) of application of the CSD eliciting stimulus: a cotton ball (1 2 mm diameter) soaked in 2% KCl solution (about 270 mM). The skull diagram (right) shows the place of KCl stimulation, the position of the reference electrode (Ref.), on the nasal bones, as well as positions 1 and 2 of the two recording electrodes (on the parietal cortex). Vertical calibration bars (negativity upwards) are equal to 10 mV for the P-recordings. The vertical interrupted lines delimit the latency time for a CSD wave to spread from point 1 to point 2. Note the longer latency in the ethanol-treated rat, in comparison with the vehicle- and the ethanol 1 tocopherol-treated animals (based on unpublished records from our laboratory).

FIGURE 12.3 CSD recordings in three rats under chronic treatment with vehicle, ethanol, or ethanol 1 tocopherol. Recordings of the slow potential (P) change that is typical of cortical spreading depression (CSD) on the surface of the cerebral cortex of three rats that were chronically treated (a single gavage per day over 21 days) with vehicle (olive oil), ethanol, or ethanol 1 α-tocopherol. The horizontal bar under the P1 traces (left) indicates the time (1 min) of application of the CSD eliciting stimulus, which is a cotton ball (1 2 mm diameter) soaked in 2% KCl solution (about 270 mM). The skull diagram (right) shows the place of KCl stimulation, the position of the reference electrode (Ref., on the nasal bones), as well as positions 1 and 2 of the two recording electrodes (on the parietal cortex). Vertical calibration bars (negativity upwards) equal 10 mV for the Precordings. The vertical interrupted lines delimit the latency time for a CSD wave to spread from point 1 to point 2. Note the shorter latency in the ethanol-treated rat, in comparison with the vehicleand the ethanol 1 tocopherol-treated animals (unpublished record from our laboratory).

4-hours CSD recording session was initiated, and CSD episodes were elicited at 20 minute-intervals. Fig. 12.2 presents an example of the DC slow potential change of CSD that was recorded on the cerebral surface of three rats acutely treated (single gavage) with vehicle or ethanol or ethanol plus α-tocopherol. In this figure, we can observe that, in comparison with the vehicle-treated animal, acute ethanol treatment resulted in a longer latency (i.e., decelerated CSD propagation), which was reversed by α-tocopherol. Our observation is in accordance with the report from others under acute intravenous ethanol infusion (Sonn & Mayevsky, 2001). In contrast with the acute treatment, chronic ethanol administration by gavage over 21 days resulted in a shorter latency for CSD to propagate between two cortical points, as compared with the vehicle-treated controls. This CSD accelerating effect of ethanol was reversed by α tocopherol, as illustrated in the recordings presented in Fig. 12.3. These data confirmed

previous observations under similar paradigms of chronic ethanol treatment (Abadie-Guedes et al., 2008). The protective action of α-tocopherol against the effects of ethanol on CSD propagation has been quantified. The CSD velocity for each individual group is presented in Table 12.3. In both age groups, acute exposure to ethanol was associated with CSD deceleration (lower CSD velocities in comparison with the corresponding control group), while under chronic ethanol treatment, CSD was accelerated (CSD velocities higher than the respective control group). In both acute and chronic ethanol paradigms, α-tocopherol antagonized the effects of ethanol on CSD, restoring CSD velocity to levels in the control groups (Table 12.3). Our study demonstrated that α-tocopherol, which is a noncarotenoid antioxidant, counteracted ethanol action on CSD propagation in a similar way as carotenoids (Abadie-Guedes et al., 2008, 2012), suggesting that this role is not a particular property of carotenoids. The opposite CSD effects of

FIGURE 12.2

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114 TABLE 12.3

12. ETHANOL AND CORTICAL SPREADING DEPRESSION: THE PROTECTIVE ROLE OF α-TOCOPHEROL

Velocity of Cortical Spreading Depression (CSD) in Rats of Two Age-Groups (80 90 day-old and 150 180 day-old) Acute treatment

Age\treatment 80 90 days 150 180 days

Vehicle

Ethanol 1 tocopherol

Ethanol

3.4 6 0.2



3.4 6 0.1



3.2 6 0.1

3.0 6 0.1

3.1 6 0.1

2.7 6 0.2

Chronic treatment Ethanol 1 tocopherol

Age\treatment

Vehicle

Ethanol

80 90 days

3.3 6 0.1

4.1 6 0.2

3.2 6 0.1



150 180 days

4.1 6 0.2

3.5 6 0.1 3.3 6 0.1

Rats were treated per gavage with vehicle, or ethanol, or ethanol 1 tocopherol in an acute (single gavage), or chronic treatment protocol (one daily gavage over 21 days) Data are mean 6 standard deviation from 9 rats per group.  P , .05 compared with the vehicle and ethanol 1 tocopherol groups. Unpublished table adapted from our previous publication Abadie-Guedes, R., Bezerra, R. S., Guedes, R. C. A. (2016). Alpha-tocopherol counteracts the effect of ethanol on cortical spreading depression in rats of various ages, with and without ethanol abstinence. Alcoholism: Clinical and Experimental Research, 40, 728 733. Doi: 10.1111/acer.12998.

acute (CSD deceleration) and chronic ethanol (CSD acceleration) suggest different underlying mechanisms in both conditions. We postulate that ROS scavenging may be involved in the action of carotenoid (AbadieGuedes et al., 2012) and noncarotenoid antioxidants (Abadie-Guedes et al., 2016). Interestingly, ROS can modulate CSD in the rat cortex (Mendes-da-Silva et al., 2014). All of the evidence notwithstanding, the suggestion of an antioxidant-based modulation of ethanoldependent CSD effects at the cortical level deserves further investigation, devoted to clarifying their molecular mechanisms.

CAN THE CSD MODEL BE USEFUL TO THE STUDY OF NEURAL EFFECTS OF OTHER DRUGS? We believe that the CSD phenomenon represents a useful and very important model for studies on developmental and electrophysiological effects of drugs with action on the central nervous system. The complete understanding of SD mechanisms could be extremely important in helping to develop better knowledge and perhaps more effective treatments of addictions and drug misuse other than alcoholism. Considering that many of such drugs act by influencing the generation of brain electrical activity or modulating it, we consider it reasonable to predict that the CSD model can provide very important information on the understanding of how the brain functions under physiological and pathological conditions, such as alcoholism and other drug addictions. In the context of understanding the mutual relationship between drug abuse, on one side, and brain development and function, on the other, mechanistic findings obtained via the CSD phenomenon can be considered to be very helpful. As we have shown in this chapter, data from CSD modulation obtained both in

experiments on laboratory animals and observations in human patients point to the importance of this model in understanding how brain functioning may be altered by some molecules, such as ethanol, antioxidants, and other drugs of abuse. From a translational point of view, the extrapolation of the present animal data to humans can be considered as a complex task, which demands important prudence and has some limitations. Despite this, our data collectively allow the conclusion that investigation of the brain effects of alcoholism and related themes can benefit from experimental models, such as CSD. Under conditions of moderate or intense consumption of drugs of abuse, the investigation of CSD properties and the modulating action of antioxidants represents an interesting experimental strategy for analyzing the neurophysiological effects of pharmacological as well as nonpharmacological agents (Guedes et al., 2012). The importance of this point becomes evident when we consider that the abuse of several drugs nowadays intensely affects an expressive part of the human population, with negative consequences for their quality of life.

MINI-DICTIONARY OF TERMS Alpha-tocopherol (or α-tocopherol) is vitamin E. This vitamin has remarkable antioxidant properties in living organisms, neutralizing the deleterious ROS that are produced in pathological conditions, such as alcoholism. Carotenoids Are pigment molecules that, like alpha-tocopherol, have antioxidant actions in the brain, protecting it against ROS. Carotenoids must be obtained from the diet, as animals are not capable of synthesizing them. Classical migraine Also termed “migraine with aura,” is a very disabling disease whose main symptoms are sensory (usually visual) hallucinations (the aura) followed by an intense headache (migraine attack) that can last for hours. Current hypotheses suggest that the aura phenomenon could be caused by the

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REFERENCES

propagation of an episode of CSD over the occipital gyrus. After CSD, the pial blood vessels would become dilated, which would provoke the lasting headache. CSD This is a slow response produced in the brain after mechanical, electrical or chemical stimulation of a point of the brain tissue. CSD consists of the reduction of the electrical activity, which completely recovers after a few minutes. Current hypotheses point to a causal link between CSD and human neurological diseases such as epilepsy, migraine, and brain ischemia. EEG is the recording of spontaneous brain electrical activity. It is a noninvasive technique that is largely used in neurologic clinics for diagnosis of brain disorders, such as epilepsy. Formerly performed on vacuum-tube-based electronic amplifiers, EEG is currently digitalized in electronic microchip-based integrated circuit devices, and EEGs are stored and analyzed in personal computers. Epilepsy This is a very limiting neurological disease caused by the abnormally intense and uncontrolled functioning of a group of brain neurons. Epilepsy diagnosis can be done with the aid of an EEG. Uncontrolled muscle contractions (convulsions) and loss of consciousness are the main clinical signs of a generalized epileptic seizure. MEG This functional neuroimaging technique, which is noninvasive, detects and amplifies and records the brain magnetic fields associated with neuronal electrical activity. MEG uses arrays of specific detectors known as “superconducting quantum interference devices” (SQUIDs) to map brain activity. ROS This expression designates metabolic products originated from O2 that are partially reduced. ROS present higher reactivity compared with molecular O2. Examples of ROS are the superoxide anion [O22•] and hydrogen peroxide [H2O2], which are respectively formed by one- and two-electron reductions of O2. It has been postulated that neurodegenerative and excitability-related diseases are associated with excessive generation of ROS in the brain. Stroke This is the general term to designate a number of neurological focal disorders from vascular origin, which is caused by absent or deficient blood supply to a determined brain area. Stroke is a consequence of either partial/total obstruction of a blood vessel (ischemic stroke), or rupture of the vessel (hemorrhagic stroke). Usually, hemorrhagic stroke is associated with a more severe outcome than the ischemic stroke.

KEY FACTS Brain Electrophysiology • The neuronal cells of the brain are capable of producing electrical activity, and this is the way through which they exert their functions. • The noninvasive recording of brain electrical activity is called an EEG. • Neurological disorders such as epilepsy can be diagnosed with the aid of EEG. • In anaesthetized animals, brain electrical activity can be invasively recorded; after skull opening, electrodes are placed directly on the cortical surface. • Electrocorticogram (ECoG) is the term that designates the recording of electrical activity directly from the cortical surface.

• The suggestion that alcoholism is a risk factor for epilepsy derives from EEG findings in humans and ECoG analyses in animals. • In animals, the brain response known as CSD, which is evoked and propagated over the cortical tissue, can easily be studied via ECoG. • In this chapter, electrophysiological findings about tocopherol/ethanol interaction on CSD in the rat cortex are reviewed.

SUMMARY POINTS • Alcoholic beverage consumption can trigger neurological disorders or can aggravate pre-existing neurological diseases. • Brain redox imbalance is involved in the underlying pathogenic mechanisms of ethanol-induced brain diseases, including changes in the brain’s electrical activity. • Therefore, antioxidant agents might play a neuroprotective role against redox imbalance due to ethanol consumption. • We revisited the electrophysiological effects of alcohol consumption on brain function by analyzing, the phenomenon known as CSD in the rat cortex. • Alterations in CSD propagation velocity reinforce evidence of electrophysiological brain changes associated with ethanol consumption. • Our recent CSD findings in ethanol-treated rats suggest a protective effect of the antioxidant molecule α-tocopherol on CSD. • Possible underlying mechanisms of this protective action are discussed. • Studies employing the CSD model can contribute to the understanding of the alcohol consumption/ brain function/antioxidant relationship.

Acknowledgments The authors thank the Brazilian agencies CAPES (Procad/2007, Cieˆncias do Mar/2009 and BEX2036/15-0 Finance Code 001) Instituto Nacional de Neurocieˆncia Translacional (INCT No. 573604/2008-8), FINEP/RECARCINA (1650/10), CNPq (445101/2014-8, 475787/2009-9) for financial support. RCAG and RSB are Research Fellows from CNPq No. 303636/2014-9 and 303570/2009-1, respectively.

References Abadie-Guedes, R., Bezerra, R. S., & Guedes, R. C. A. (2016). Alphatocopherol counteracts the effect of ethanol on cortical spreading depression in rats of various ages, with and without ethanol abstinence. Alcoholism: Clinical and Experimental Research, 40, 728 733. Available from https://doi.org/10.1111/acer.12998. Abadie-Guedes, R., Guedes, R. C. A., & Bezerra, R. S. (2012). The impairing effect of acute ethanol on spreading depression is

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C H A P T E R

13 Brain Electrophysiological Signatures in Human Alcoholism and Risk Chella Kamarajan Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, NY, United States

LIST OF ABBREVIATIONS AUD CSD EEG ERD/ERS ERN EROs ERPs LORETA MMN

alcohol use disorders current source density electroencephalogram event-related desynchronization/synchronization error-related negativity event-related oscillations event-related potentials low-resolution brain electromagnetic tomography mismatch negativity

INTRODUCTION Ever since Hans Berger in the 1920s first recorded human electroencephalogram (EEG) (Berger, 1929), applications of this technology have been expanding to numerous fields ranging from cognitive and clinical neuroscience to brain computer interfaces and remote communications (Rosler, 2005; Schomer & da Silva, 2017; Siuly, Li, & Zhang, 2017). EEG signals provide a noninvasive, sensitive measure of brain function during ongoing mental processes or during task performance. Other well-known advantages of these measures include: (1) excellent time resolution in the range of milliseconds to examine real-time and ultra-fast neurodynamics and information processing; (2) validity of EEG measures as a direct neural activitythe summed electrical activity of neural cell assemblies; (3) superior test retest reliability within subjects and across labs; (4) relative ease of use and portability; (5) lower cost of recording systems; and (6) suitability to investigate a wide variety of neurocognitive functions and abnormalities.

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00013-1

In general, brain electrical activity is analyzed in one of three domains (Fig. 13.1): (1) continuous EEG during resting or ongoing mental states; (2) eventrelated potentials (ERPs) that are time-locked brain activity during sensory/cognitive processing; and (3) event-related oscillations (EROs) representing timeand frequency-specific brain activity during neurocognitive tasks. The clinical applications of EEG methods pervades nearly all neurocognitive domains and disorders (Schomer & da Silva, 2017), including alcoholism (for recent reviews, see Kamarajan & Porjesz, 2015; Porjesz et al., 2005; Rangaswamy & Porjesz, 2014). This chapter mainly focuses on major electrophysiological findings in individuals with alcohol use disorder (AUD) due to chronic alcohol intake as well as in highrisk (HR) offspring/relatives who are vulnerable to develop AUD and/or other related disorders, as summarized in Table 13.1. Besides, a review concerning electrophysiological changes due to acute effects of alcohol intoxication and binge or heavy/social drinking is beyond the focus of this chapter, but has been covered elsewhere (Rangaswamy & Porjesz, 2014).

ELECTROENCEPHALOGRAM FINDINGS Power Spectral Analysis Power spectral analysis quantifies signal content (magnitude) within different frequency bands. One of the salient findings is that beta rhythms (13 30 Hz), which are prevalent in the EEG during awake and alert resting state, are most useful to characterize AUD and its risk. Studies have reported increased beta

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other lower animals (cf. Kamarajan & Porjesz, 2015). Coherence has been used to examine cognitive/emotional processes, brain development, and psychopathology (Thatcher, 2012). Although it is an important measure, there are only a handful of studies on EEG coherence in AUD and HR individuals. Importantly, increased coherence in high theta band (6 7 Hz) has been shown to be a prominent finding in alcoholics (Porjesz & Rangaswamy, 2007), although findings related to other frequencies were inconsistent. In HR individuals, while increased coherence has been reported in several frequency bands (Michael, Mirza, Mukundan, & Channabasavanna, 1993), these findings were equivocal and not replicated. Future studies with refined methodologies are warranted (Kamarajan & Porjesz, 2015).

EVENT-RELATED POTENTIAL FINDINGS

power in the resting EEG of alcoholics (e.g., Costa & Bauer, 1997; Rangaswamy et al., 2002) as well as in HR offspring (Pollock, Earleywine, & Gabrielli, 1995; Rangaswamy et al., 2004), possibly suggesting neural hyperexcitability in these individuals. However, findings regarding the low-frequency EEG activity, such as delta (1 3 Hz), theta (4 7 Hz), and alpha (8 12 Hz) bands, are largely inconclusive to characterize AUD and HR individuals.

ERPs represent time-locked voltage fluctuations of the neuroelectric activity in response to a sensory, motor, or cognitive event, extracted by signal-processing methods such as filtering and trial averaging (Rugg & Coles, 1996). ERP components are identified and interpreted based on their modality (visual, auditory, somatosensory, motor), eliciting/task conditions (context, meaning, expectation, outcome), polarity (positivity or negativity), timing (latency), magnitude (amplitude), and scalp distribution or topography (frontal, parietal, etc.). Early components (up to 100 ms) index preattentive sensory reception, whereas the later components (usually those occur after 100 ms) index higher cognitive processing, such as selective attention, memory updating, semantic comprehension, and other cognitive activity. The latency (timing of occurrence of an ERP phenomenon in milliseconds) reflects neural processing time, whereas the amplitude (height of an ERP peak or trough in microvolts) indicates the magnitude or efficiency of neural resources that contributed to process a stimulus or event (Rugg & Coles, 1996). Key findings related to frequently studied ERP components in alcoholism are summarized next.

Coherence

Sensory Pathway (Evoked) Potentials

Coherence is a sensitive measure that can reveal subtle aspects about the network dynamics of the brain by quantifying functional association or “coupling” between two brain signals (Nunez, 1995). Coherence between distant brain regions is related to higher order cognitive functioning. Coherence occurs specifically in mammalian and human brain networks, and not prominent in the neural activity of invertebrates and

Brainstem evoked potentials represent the voltage changes recorded in the brain in response to a sensory stimulus, representing functional integrity of the neural pathways from the sensory organs to the processing centers in the cortex (cf. Kamarajan & Porjesz, 2015). Chronic alcoholics have been reported to have prolonged latency in the auditory brainstem potentials (Begleiter, Porjesz, & Chou, 1981). However, these

FIGURE 13.1 Brain electrophysiological methods. A typical EEG segment within 6 50 µV amplitude (A). A trial-averaged ERP waveform at Cz electrode derived from a gambling task during loss condition (B). Time frequency map showing total ERO power (µV2) (C). The dotted line at 0 ms represents the stimulus onset.

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EVENT-RELATED POTENTIAL FINDINGS

TABLE 13.1

Summary of Major Electrophysiological Findings in Alcoholics and High-Risk Offspring/Relatives Findings in Alcoholics

Findings in High-Risk Offspring/Relatives

Method/Measure

Function/Dysfunction

Resting electroencephalogram (EEG): delta power (1 3 Hz)

Integration of cerebral activity with Equivocal (both increase and decrease homeostatic processes. Increased awake reported). delta power is related to neurological and psychiatric conditions.

No significant findings reported.

Resting EEG: theta power (4 7 Hz)

May be involved in biological rhythms and cognitive states. Increased awake theta power is related to neurological and psychiatric conditions.

Equivocal (both increase and decrease reported).

No abnormal theta power found.

Resting alpha power (8 12 Hz)

Higher cognitive function and brain maturation; integrative brain function.

Equivocal (both increase and decrease reported).

Equivocal (both increase and decrease reported).

Resting EEG: beta power (12 28 Hz)

Indicative of awake and active state. Increased beta may be related to increased neural excitability.

Increased power.

Increased power.

Resting EEG: coherence

Functional connectivity between brain Increased high theta coherence; regions. Frequency-specific and region- inconclusive in other frequencies. specific coherence indicative of strength of coupling, network interaction, and brain maturation.

Tenuous findings of increased coherence in several frequency bands.

EEG/event-related oscillations (ERO): graph theoretical method

Topological properties (i.e., regions and Graph theoretical indices of EEG data connectivity) of brain networks. specific to alcoholic subjects have been elicited.

Lack of studies.

EEG trilinear modeling

Estimation of a set of spatial and Significant linkage and association spectral components of brain potentials. between trilinear component of EEG. beta band and a gamma-aminobutyric acid type A (GABAA) receptor gene (GABRA2) in Collaborative Study on the Genetics of Alcoholism (COGA) densely affected alcoholic families.

Lack of studies.

EP: auditory brainstem potentials

Integrity of sensory pathways; sensory processing.

Prolonged latencies in several auditory brainstem potential peaks.

No change in amplitude or latency.

EP: P1/P100

Basic perceptual processing of the stimulus; modulated by physical characteristics of the stimulus.

Decreased amplitudes, delayed latencies and topographic changes in visual paradigms.

No significant findings reported.

Event-related potential (ERP): N1/ N100

Attentional modulation during perceptual processing of the stimulus; selective attention.

Decreased amplitude.

Decreased amplitude.

ERP: MMN

Automatic stimulus change detection; Findings are equivocal. central auditory processing mechanism.

Findings are equivocal.

ERP: ERN/Ne

Preconscious error-detection mechanism.

Findings are equivocal.

Lack of studies.

ERP: N2/N200

Detection of response conflict (conflict monitoring); response inhibition; feedback processing.

Decreased amplitude and delayed latency.

Decreased amplitude and delayed latency.

ERP; P3/P300

Context/demand processing; stimulus significance; conscious attention; working memory.

Decreased amplitude and delayed latency.

Decreased amplitude and delayed latency.

ERP: N4/N400

Language/semantic processing; detection of incongruity in word meaning; semantic priming effects.

Decreased amplitude and delayed latency in word incongruity studies; lack of attenuation to primed words and no differentiation between primed vs. unprimed words (no priming effect).

Lack of attenuation to primed words; no differentiation between primed vs. unprimed words (no priming effect).

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(Continued) Findings in High-Risk Offspring/Relatives

Method/Measure

Function/Dysfunction

Findings in Alcoholics

ERP: dipole source modeling

Brain sources of scalp potentials. Abnormal source activity may be seen in clinical conditions.

Changes in the location of brain sources Lack of studies. for P1, N1, P2, and MMN.

ERP: current source density (CSD)

Estimation of the local radial current density and flow; spatial filtering; identification of neural sources. Changes in source activity in strength or location may suggest abnormality.

Changes in the topography and strength of activation for P3.

Changes in the topography and strength of activation for P3.

ERP: low-resolution brain electromagnetic tomography (LORETA)

Estimation of current density in voxels; identification of neural sources; patterns of activation and connectivity. Changes in current density activation level and pattern may suggest abnormality.

Changes in current density activation level and pattern for N2 and P3.

Changes in current density activation level and pattern for N2 and P3.

ERP: principal component analysis (PCA)

Decomposition of signals into orthogonal components representing distinct topographic activity patterns.

No conclusive findings.

No conclusive findings.

ERP: independent component analysis (ICA)

Decomposition of signals into a sum of temporally independent and spatially fixed components.

Changes in activation strength in ICA components for N2 and P3.

Lack of studies.

ERP: trilinear modeling

Estimation of a set of spatial and temporal components of brain potentials; simultaneous comparison of components across subjects and conditions is possible.

Significant linkage between time Lack of studies. warped P3-related trilinear components in visual oddball paradigm in COGA densely affected alcoholic families.

ERO: delta (1 3.5 Hz) power

Signal detection and decision making; context/reward processing.

Decreased evoked and total delta power during P3 response window.

ERO: theta (3.5 7.5 Hz) power

Conscious awareness; episodic Decreased evoked and total theta retrieval; recognition memory; power during N2 and P3 time window. executive control; inhibitory processing; working memory.

Decreased evoked and total theta power during N2 and P3 time window.

ERO: gamma (29 45 Hz) power

Visual perception, cognitive integrative function such as “binding,” and topdown (frontal) control during sensory processing.

Reduction in early evoked gamma power at frontal regions during target processing.

Reduction in early evoked gamma power at posterior regions during target processing.

ERO: coherence

Functional interaction and connectivity across brain regions.

Increased wavelet coherence in theta (4 8 Hz), alpha (8 13 Hz) and gamma (50 60 Hz) bands at frontal and occipital regions during 100 200 ms poststimulus of target processing.

Lack of studies.

ERO: phase synchronization

Functional interactions and connectivity Impaired synchronization and loss of across brain regions; long-range neural lateralization, most prominently in integration. alpha and lower beta frequency bands during mental rehearsal of pictures.

abnormalities are spontaneously recovered after a period of abstinence (Porjesz & Begleiter, 1985) and were not found in HR individuals (Begleiter, Porjesz, & Bihari, 1987), suggesting that these neural changes are related to the direct effects of chronic alcohol consumption.

Decreased evoked and total delta power during P3 response window.

Lack of studies.

Sensory and Perceptual Potentials (P1) The P1 component of the ERP is a positive-going potential occurring around 100 ms after the stimulus onset, and reflects basic perceptual processing of the stimulus (Rugg & Coles, 1996). Decreased P1 amplitude, delayed latency,

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EVENT-RELATED POTENTIAL FINDINGS

and topographic changes of the P1 component, particularly in visual paradigms, have been observed in chronic alcoholics, but not in HR individuals (for reviews, see Kamarajan & Porjesz, 2015; Porjesz et al., 2005; Rangaswamy & Porjesz, 2014).

Selective Attention (N1) The N1 component occurs around 100 ms after the stimulus, and represents selective attentional processing (Rugg & Coles, 1996). It has been shown that N1 can be modulated by the cognitive or emotional salience of the stimulus, and a larger N1 component is elicited for the attended and/or salient stimuli (Vogel & Luck, 2000). A diminished N1 component has been reported in alcoholics (e.g., Cohen, Ji, Chorlian, Begleiter, & Porjesz, 2002) and in their first-degree relatives (e.g., Steinhauer, Hill, & Zubin, 1987).

Mismatch Negativity Mismatch negativity (MMN) is generated when a change is automatically or preattentively detected between two streams of auditory stimuli. MMN peaks frontally within 100 250 ms poststimulus, and is typically derived by subtracting one set of stimuli from the other (e.g., standard versus deviant) (Naatanen, Paavilainen, Rinne, & Alho, 2007). In alcoholism, MMN findings are equivocal. While some studies reported larger MMN in alcoholics (e.g., Ahveninen et al., 2000) and in HR subjects (e.g., Zhang, Cohen, Porjesz, & Begleiter, 2001), others have failed to find any significant changes.

Error-Related Negativity Error-related negativity (ERN) is a large negative potential observed around 150 ms after an “incorrect” response in tasks that require “correct” identification of a stimulus presented (cf. Kamarajan & Porjesz, 2015). Changes in ERN have been reported in several disorders (for a review, see Olvet & Hajcak, 2008). Reduced ERN amplitudes have been observed during acute alcohol administration (Ridderinkhof et al., 2002) as well as in heavy drinkers (Bartholow et al., 2003), while no prominent findings are available in alcoholic or HR individuals.

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processes such as covert orienting of attention, detection of response conflict (conflict monitoring), response inhibition, and error detection (cf. Kamarajan & Porjesz, 2015). Alcoholics have shown lower N2 amplitudes in oddball tasks (Realmuto, Begleiter, Odencrantz, & Porjesz, 1993), Go/No-Go tasks (Pandey, Kamarajan, Tang, et al., 2012), and monetary gambling tasks (Kamarajan et al., 2010). Smaller N2 amplitudes in feedback trials were also associated with a greater family history density of alcohol problems (Fein & Chang, 2008).

Cognitive Evaluation and Processing (P3/P300) P3 (also known as P300) is a large positive component that generally occurs between 300 and 600 ms after the onset of a stimulus being processed (Rugg & Coles, 1996). P3 is related to the significance of a stimulus and/or cognitive event, and is considered to index a wide variety of neurocognitive processes (Polich, 2007), including context processing, attention, working memory, stimulus salience, and reward processing (Kamarajan & Porjesz, 2015). It should be noted that the most robust electrophysiological findings in alcoholism are related to the P3 component (Porjesz et al., 2005). A large body of research has established that alcoholics and HR offspring of both genders often manifest P3-related changes, viz., suppressed or lower amplitude (Fig. 13.2), changes in current source density (CSD; Nunez, 1995), and source activations (low-resolution brain electromagnetic tomography (LORETA); Pascual-Marqui, Michel, & Lehmann, 1994), as elicited under a variety of task conditions (for reviews, see Kamarajan & Porjesz, 2015; Porjesz et al., 2005; Rangaswamy & Porjesz, 2014). Since the landmark study by Begleiter, Porjesz, Bihari, and Kissin (1984), who reported smaller P3 in alcoholnaı¨ve children of alcoholics, many studies have replicated the finding under a variety of experimental conditions and samples (Porjesz et al., 2005), suggesting underlying genetic vulnerability in HR individuals. Begleiter and Porjesz (1999) postulated that P3 reduction may reflect a heritable neural disinhibition (i.e., hyperexcitability), which may be involved in the predisposition to develop alcoholism and related disorders.

Language Processing (N4/N400)

Attentional Orientation and Conflict Monitoring (N2) The N2 is a negative going wave with a frontocentral focus. It occurs between 200 and 350 ms after stimulus presentation, and is associated with several

N4 is a metric of semantic processing, which occurs around 400 ms (within 300 650 ms) with a centroparietal focus in response to semantically incongruent linguistic stimuli or words (Kutas & Van Petten, 1988). Reduced N4 amplitude during linguistic processing or

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FIGURE 13.2 ERP waveforms and topographic maps during a Go/No-Go task. Reduced P3 amplitudes were observed during response inhibition (No-Go) and execution (Go) in alcoholic individuals. Source: (A1 and A2) Adapted from Kamarajan, C., Porjesz, B., Jones, K.A., Choi, K., Chorlian, D.B., Padmanabhapillai, A., . . . Begleiter, H. (2005). Alcoholism is a disinhibitory disorder: Neurophysiological evidence from a Go/No-Go task. Biological Psychology, 69(3), 353 373 (Kamarajan, Porjesz, Jones, Choi, et al., 2005) as well as in high risk offspring. (B1 and B2) Adapted from Kamarajan, C., Porjesz, B., Jones, K.A., Chorlian, D.B., Padmanabhapillai, A., Rangaswamy, M., . . . Begleiter, H. (2005). Spatial-anatomical mapping of NoGo-P3 in the offspring of alcoholics: Evidence of cognitive and neural disinhibition as a risk for alcoholism. Clinical Neurophysiology, 116(5), 1049 1061 (Kamarajan, Porjesz, Jones, Chorlian, et al., 2005) compared to control group. For ERP findings during reward processing, see Kamarajan, C. (2018). Neural reward processing in human alcoholism and risk: A focus on event-related potentials, oscillations, and neuroimaging. In V.R. Preedy (Ed.), The neuroscience of alcohol: Mechanisms and treatment. San Diego, CA: Academic Press (Kamarajan, 2018).

a lack of attenuation to primed stimuli have been reported in alcoholics (e.g., Ceballos, Houston, Smith, Bauer, & Taylor, 2005; Roopesh et al., 2010) as well as in HR offspring/relatives (e.g., Roopesh et al., 2009; Schmidt & Neville, 1985), suggesting aberrant linguistic processing (Fig. 13.3).

EVENT-RELATED OSCILLATION FINDINGS EROs are time frequency measures of brain electrical activity that are temporally associated with a sensory and/or cognitive event (Basar, Basar-Eroglu, Karakas, & Schurmann, 1999). EROs can be classified

as: (1) “evoked,” or phase-locked oscillations; (2) “induced,” or nonphase-locked oscillations; and (3) “total,” or the summated activity of evoked and induced oscillations (Jones et al., 2006; Tallon-Baudry, Bertrand, Delpuech, & Pernier, 1996). EROs, specifically of delta, theta, and gamma band activities, have characterized cognitive dysfunction underlying alcoholism and risk, as described below.

Delta and Theta Band Event-Related Oscillation Activity Brain oscillations of low frequencies, especially delta and theta band, constitute the P3 component

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FIGURE 13.3 ERP waveforms and topographic maps during a word processing task. ERP waveform (CZ electrode) and topographic maps during primed and unprimed condition illustrating lack of N400 attenuation (circled region) to primed stimuli in alcoholics. Source: (A) Adapted from Roopesh, B.N., Rangaswamy, M., Kamarajan, C., Chorlian, D.B., Pandey, A.K., & Porjesz, B. (2010). Reduced resource optimization in male alcoholics: N400 in a lexical decision paradigm. Alcoholism: Clinical and Experimental Research, 34(11), 1905 1914 and in high risk individuals. (B) Adapted from Roopesh, B.N., Rangaswamy, M., Kamarajan, C., Chorlian, D.B., Stimus, A., Bauer, L.O., . . . Porjesz, B. (2009). Priming deficiency in male subjects at risk for alcoholism: the N4 during a lexical decision task. Alcoholism: Clinical and Experimental Research, 33(12), 2027 2036.

(Basar-Eroglu, Basar, Demiralp, & Schurmann, 1992) and are assumed to mediate a variety of cognitive processes (Basar et al., 1999). Studies have consistently found that alcoholics and their HR offspring showed decreased delta and theta ERO power during oddball, Go/No-Go, and gambling tasks (for reviews, see Kamarajan & Porjesz, 2015; Pandey, Kamarajan, Rangaswamy, & Porjesz, 2012; Porjesz et al., 2005; Rangaswamy & Porjesz, 2014) (Fig. 13.4).

Gamma Band Event-Related Oscillation Activity Gamma band (30 45 Hz) oscillatory activity during stimulus processing represents selective attention and feature binding (Tallon-Baudry et al., 1996). There are only a few studies on gamma EROs in alcoholism. Frontal gamma band response during early stimulus processing (0 150 ms poststimulus) during target processing in a visual oddball task was shown to be reduced in alcoholics (Padmanabhapillai, Porjesz, et al., 2006) and in HR offspring (Padmanabhapillai, Tang, et al., 2006), suggesting deficits in feature binding at neural level during stimulus processing (Fig. 13.5).

Alpha and Beta Band Event-Related Oscillation Activity Alcohol-induced alterations in ERO responses have been studied using event-related desynchronization/ synchronization (ERD/ERS), which measures proportional decrease/increase in event-related (poststimulus) activity relative to the baseline (prestimulus) activity. For example, acute alcohol intake decreased the alpha band ERS responses during encoding phase while increasing the ERD responses during recognition phase during an auditory memory task (Krause, 2006). Using an Alcohol Approach-Avoidance task, Korucuoglu, Gladwin, and Wiers (2014) found that acute alcohol intake in social drinkers induced ERD responses in posterior beta power while processing alcohol cues.

Event-Related Oscillation Connectivity Functional connectivity measures of brain oscillations, such as ERO coherence and phase synchrony, estimate the interlink or coupling between two distinct brain signals (Roach & Mathalon, 2008). ERO

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FIGURE 13.4

ERP waveforms and ERO power maps during a visual oddball task. ERO power changes in alcoholics (left panels, A1 A3) and HR individuals (right panels, B1 B3) during a visual oddball task. Similar to alcoholics, HR offspring manifested lower P3 amplitude, and attenuated delta and theta power relative to control subjects. Source: Adapted from Jones, K.A., Porjesz, B., Chorlian, D., Rangaswamy, M., Kamarajan, C., Padmanabhapillai, A., . . . Begleiter, H. (2006). S-transform time frequency analysis of P300 reveals deficits in individuals diagnosed with alcoholism. Clinical Neurophysiology, 117(10), 2128 2143; Rangaswamy, M., Jones, K.A., Porjesz, B., Chorlian, D.B., Padmanabhapillai, A., Kamarajan, C., . . . Begleiter, H. (2007). Delta and theta oscillations as risk markers in adolescent offspring of alcoholics. International Journal of Psychophysiology, 63(1), 3 15 (Rangaswamy et al., 2007). For ERO findings during reward processing, see Kamarajan, C. (2018). Neural reward processing in human alcoholism and risk: A focus on event-related potentials, oscillations, and neuroimaging. In V.R. Preedy (Ed.), The neuroscience of alcohol: Mechanisms and treatment. San Diego, CA: Academic Press.

FIGURE 13.5 Gamma band activity as seen in time frequency maps. Time frequency maps during target condition illustrating frontal gamma band activity (29 45 Hz) at 0 150 ms in alcoholics. Source: (A) Adapted from Padmanabhapillai, A., Porjesz, B., Ranganathan, M., Jones, K.A., Chorlian, D.B., Tang, Y., . . . Begleiter, H. (2006). Suppression of early evoked gamma band response in male alcoholics during a visual oddball task. International Journal of Psychophysiology, 60(1), 15 26 and in high risk individuals. (B) Adapted from Padmanabhapillai, A., Tang, Y., Ranganathan, M., Rangaswamy, M., Jones, K.A., Chorlian, D.B., . . . Porjesz, B. (2006). Evoked gamma band response in male adolescent subjects at high risk for alcoholism during a visual oddball task. International Journal of Psychophysiology, 62(2), 262 271.

coherence is an index of consistency in amplitude and phase modulations between two event-related signals oscillating with a specific frequency, and represent the degree of functional interactions between these signals

(cf. Kamarajan & Porjesz, 2015). On the other hand, phase synchrony methods involve quantifying alignment of phases (“phase-locking”) either across trials (“intertrial phase synchrony”) or between brain

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MINI-DICTIONARY OF TERMS

regions (“intersite phase synchrony”) (Roach & Mathalon, 2008). Connectivity studies on alcoholism are very few. Alcoholics showed impaired phase synchronization in alpha and lower beta frequency bands in a visual memory task (Sakkalis, Tsiaras, Zervakis, & Tollis, 2007). Alcoholics also displayed altered ERO coherence in theta, alpha, and gamma bands during a visual discrimination task (Ismaili, Menon, & Menon, 2012). These studies suggest that neural communication across brain regions may be impaired in alcoholism.

USE OF ELECTROPHYSIOLOGICAL MEASURES IN THE TREATMENT OF ALCOHOLISM According to Campanella, Petit, Verbanck, Kornreich, and Noel (2011), electrophysiological measures (e.g., P1 and P3 components) can guide the clinician to optimize the medication regimen tailored to a patient’s cognitive profile and adopt a kind of “personalized medicine.” In the realm of AUD outcome, Cristini, Fournier, Timsit-Berthier, Bailly, and Tijus (2003) found that the P3 amplitudes were significantly higher among alcoholics who relapsed during the 3month follow-up than in those who remained abstinent. In another study, Saletu-Zyhlarz et al. (2004) found that after 6 months of treatment, only the abstaining patients showed a normalization of brain function in terms of increase in slow-wave activity, decrease in fast-alpha, acceleration of the delta/theta centroid, and deceleration of the alpha centroid. Further, EEG-based neurofeedback has been found to be effective for treating alcoholism (e.g., Saxby & Peniston, 1995). Taken together, EEG measures may not only serve as useful prognostic indicators in alcoholism, but also can be a guide for recovery and a tool for treatment (Kamarajan & Porjesz, 2015).

ELECTROPHYSIOLOGICAL MEASURES AS ENDOPHENOTYPES FOR ALCOHOLISM Alcoholism is a complex disorder with both genetic and environmental etiology (Porjesz & Rangaswamy, 2007). Brain electrophysiological measures by themselves are highly heritable (Begleiter & Porjesz, 2006) and have been successful in identifying genes underlying neuropsychiatric disorders (Owens, Bachman, Glahn, & Bearden, 2016), including alcoholism (Rangaswamy & Porjesz, 2014). Endophenotypes are measurable traits/ variables closely related to a disease/disorder and its genotypes (Gottesman & Gould, 2003). Specifically, beta power and theta coherence of resting EEG, P3, and delta

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and theta EROs have been successfully used to identify genes involved in alcoholism and related disorders (for reviews, see Rangaswamy & Porjesz, 2008, 2014), highlighting the utility of these measures as endophenotypes in gene discovery for alcoholism and related disorders.

SUMMARY AND FUTURE DIRECTIONS This article is a succinct summary of major electrophysiological findings in individuals with alcoholism and at risk of alcoholism, who have shown changes in EEG, ERP, and ERO measures. It is also shown that these neuroelectric measures have enormous translational potential to aid in diagnosis, prevention, treatment, and rehabilitation of individuals with AUD. Further, these quantitative measures may serve as effective endophenotypes for discovering genes related to alcoholism and related disorders. However, studies using sophisticated electrophysiological techniques (e.g., phase synchrony) are still lacking in alcoholism (cf. Kamarajan & Porjesz, 2015). It is hoped that future improvements in signal-processing tools, study designs, and multimodal brain imaging (e.g., combined EEG fMRI studies) in alcoholism may lead to a better understanding of the disorder and its treatment.

MINI-DICTIONARY OF TERMS Coherence A measure of functional association between two brain regions. Current source density (CSD) A method to identify brain sources of the scalp recorded neuroelectric activity. Electroencephalogram (EEG) Brain electrical activity recorded using electrodes during either resting state or during mental processes. Endophenotype A subtype of biomarkers, which is heritable, reliably measurable and related to the characteristics or symptoms of a disorder. Error-related negativity (ERN) A negative ERP potential that represents an “incorrect” or “error” response. Event-related oscillations (ERO) Time- and frequency-specific neuroelectric activity recorded during task processing. Event-related potentials (ERPs) Trial-averaged neuroelectric activity that are time locked (aligned) to a stimulus or response event. LORETA A functional brain imaging method using current density of the EEG signals to localize source activations in threedimensional space. Mismatch negativity (MMN) A negative, frontal component which is automatically (preattentively) evoked by a deviant stimulus. N400 A negative component, occurring around 400 ms, in response to a semantically incongruent or inappropriate stimulus. P300 A large, positive ERP component that occurs around 300 ms after the onset of a stimulus or mental event during cognitive processing. Phase synchrony Measures based on phase alignment (or phase locking) of signals across trials (intertrial) or between regions (intersite).

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KEY FACTS • Brain electrophysiological measures are effective tools to understand neurocognitive processes underlying alcoholism and its risk. • Alcoholics as well as their high-risk offspring/ relatives manifest electrophysiological dysfunctions. • Increased resting EEG beta power, decreased P3 amplitudes, reduced delta and theta ERO power have been found to be the electrophysiological hallmarks of alcoholism. • Electrophysiological measures have been used as endophenotypes to identify genes associated with alcoholism and related disorders. • Applications of electrophysiological measures in diagnosis, prevention, and treatment of alcoholism are steadily expanding.

SUMMARY POINTS • Studies have found that individuals with AUD and their high-risk offspring have displayed abnormality in several electrophysiological measures. • Increased power in the beta frequencies of the resting EEG, lower P3 amplitudes, and lower ERO power in the delta and theta band have been shown as hallmark features of AUD and its risk. • Alcoholics and their offspring have also manifested changes in current source density (CSD) and source activation (LORETA) in specific brain regions at N2 and P3 time window. • Electrophysiological measures, as quantitative measures of brain function, have been used as endophenotypes to identify genes associated with AUD and related disorders. • Studies have also suggested translational applications of electrophysiological measures in diagnosis, prevention, and treatment.

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C H A P T E R

14 Alcohol and Hippocampal Epileptiform Activity

1

Victor Diego Cupertino Costa1, Luiz Eduardo Canton Santos1, Antoˆnio Ma´rcio Rodrigues1, Fu´lvio Alexandre Scorza1,2, Carla Alessandra Scorza2, Arthur Guerra de Andrade3 and Antoˆnio-Carlos Guimara˜es de Almeida1

Laboratory of Experimental and Computational Neuroscience, Bioengineering Program, Biosystems Engineering Department-DEPEB, Federal University of Sa˜o Joa˜o del-Rei-MG, Brazil 2Laboratory of Neuroscience, Department of Neurology and Neurosurgery, Federal University of Sa˜o Paulo, Sa˜o Paulo, Brazil 3Department of Psychiatry, Medical School, University of Sa˜o Paulo, Sa˜o Paulo, Brazil

LIST OF ABBREVIATIONS HF AWS EEGs GABA NMDA EA NS HEA nAChRs AW CNS IPSPs gk DG BD

hippocampal formation alcohol withdrawal syndrome electroencephalograms gamma amino-butyric acid N-methyl D-aspartate epileptiform activities nervous system hippocampal epileptiform activity nicotinic acetylcholine receptors alcohol withdrawal central nervous system postsynaptic inhibitory currents K1 conductance dentate gyrus binge drinking

INTRODUCTION Among the comorbidities associated with alcoholism, convulsions are cited as the most complex (Freedland & McMicken, 1993). Often, the seizure stories reported in clinical studies are related to alcohol withdrawal. However, seizures in the context of alcohol dependence are not necessarily due to abstinence from alcohol and may have several etiologies (Hillbom, Pieninkeroinen, & Leone, 2003). A small number of papers have addressed how specific brain regions may be responsible for alcoholinduced epilepsy and the mechanisms by which these affected sites can trigger epileptic seizures. However, Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00014-3

there are indications that the hippocampal formation (HF) is vulnerable to alcohol-induced pathological changes and is the main source of seizure activity in a variety of epileptic conditions (Germano, Sperber, Ahuja, & Moshe, 1998). Prolonged administration of ethanol, as well as alcohol withdrawal syndrome (AWS), have been shown to promote increased seizure frequency and the development of functional and neuropathological changes associated with epilepsy in the pilocarpine induction model (Scorza, Arida, Cysneiros, Priel, & de Albuquerque, 2003). Clinical data discuss the possible association between partial and complex seizure disorders and abnormal electroencephalograms (EEGs) with temporal lobe dysrhythmias, both in chronic alcoholics and in children whose mothers used alcohol during pregnancy. A 3% 21% increase in the occurrence of seizures was reported in individuals with fetal alcoholic syndrome (O’Malley & Barr, 1998; Sand et al., 2002). In addition, recent studies using animals have shown that the HF is vulnerable to alcohol-induced neuronal death, disruption of synaptic circuits, alterations in neurogenesis, and dysregulation of the expression and activities of gamma amino-butyric acid (GABA) and N-methyl D-aspartate (NMDA) receptor subunits, as well as in the mechanisms related to G protein, which is indirectly involved in the processes of excitability control (Bonthius & West, 1990; Kang, Spigelman, & Olsen, 1998), and the immunoreactivity of several subcellular mechanisms of nonsynaptic action (Santos

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et al., 2013, 2017). Each of these pathological changes in the HF may decrease the threshold for seizure and predispose an individual to epilepsy (Lothman & Bertram, 1993). Therefore, the changes promoted by alcohol abuse affect many (if not all) structures of the HF. A common fact is that in almost all cases, the literature reports the presence of seizures and epileptiform activities (EA). Thus, characterization of the alcohol effect on the nervous system (NS), especially on the hippocampus and its ability to induce EA, is a very complex task. The present chapter provides an overview of the relation between alcohol abuse and hippocampal epileptiform activity, taking into account the two main explored animal protocols used in experimental investigation, chronic and acute alcohol abuse, and the reported findings of their effects on the synaptic and nonsynaptic mechanisms.

ALCOHOL EFFECTS ON SYNAPTIC MECHANISMS OF EPILEPTIFORM ACTIVITY Although several neurotransmitters and receptors present in the hippocampus are involved in the generation of paroxysmal activities during alcohol abuse, some of them are highlighted in the literature and have a more central physiological role. These actions range from the decrease/increase in neurotransmitter concentrations due to changes in biosynthesis, degradation or transport, or the activation/inhibition of the sensitivity of several receptors (Gonzales & Hoffman, 1991). There is evidence that ethanol, by direct or indirect actions, primarily alters the neuronal communication mediated by NMDA receptors, GABAA receptors, and the nAChRs. Therefore, the main reported experimental findings of the alcohol effects on these receptors are reviewed in dependence of the animal protocol used to mimic human alcohol abuse.

Acute Alcohol Abuse The blockade of excitatory functions mediated by NMDA glutamate receptors and the enhancement of inhibitory functions mediated by GABAA receptors are the most acute alcohol mechanisms observed in slice and hippocampal cell experiments (Lovinger, White, & Weight, 1989; Reynolds, Prasad, & MacDonald, 1992). In 1989, Lovinger et al. demonstrated that acute doses of ethanol (5 100 mM) inhibited ionic currents activated by NMDA receptors in the hippocampal neurons of mice. Cohen, Martin, Morrisett, and Wilson

(1993) postulated that ethanol might have a two-phase effect. The in vitro study showed that the EA of the CA3 region of the rat hippocampus depend on the alcohol dose administered. At low concentrations (3 and 10 mM), ethanol increased the excitability of the slices. When alcohol concentrations were increased (60 300 mM), the effect was the exact opposite. It has been proposed that ethanol should have presynaptic action directly on excitatory amino acid receptors of CA3 region cells, particularly NMDA subtype receptors, to inhibit glutamate/aspartate release. This indicates that the ethanol-induced reduction in the release of these neurotransmitters can suppress glutamatergic activities and result in an increase in the threshold for the generation of EA. It is also possible that ethanol works by increasing adenosine levels in the CA3 synaptic clefts. Adenosine is also known to inhibit the release of aspartate/glutamate and, thus, to hinder the appearance of EA (Cohen et al., 1993). Although the mechanisms are not known, it is possible that alcohol inhibits induced currents, calcium influx, and toxicity promoted by NMDA receptors and their agonists (Lovinger et al., 1989). In addition, when ethanol blocks NMDA receptors, it stops the stimulation of inhibitory neurons and, consequently, impairs the inhibitory circuits in pre- and postsynaptic hippocampal pyramidal neurons (Xue et al., 2011). In these cases, glutamate acts, paradoxically, as a regulator of inhibitory tone. This effect promotes hyperexcitability of neuronal pathways, which may explain the occurrence of epileptic seizures in alcoholics. Direct effects on GABAergic receptors have also been observed. When GABAA receptors are exposed to acute doses of ethanol at concentrations of 10 50 mM, a potentiation of the inhibitory postsynaptic currents occurs. With a higher concentration (100 mM), Marszalec, Aistrup, and Narahashi (1998) noted not only the increase in postsynaptic inhibitory currents (IPSPs) measured by GABAA receptors, but also the inhibition of postsynaptic excitatory currents mediated by NMDA and AMPA receptors. Reynolds et al. (1992) have shown that in cultures of mouse hippocampal neurons, low concentrations (1 10 mM) of ethanol increase the chloride currents activated by GABA. In contrast, the threshold concentration of ethanol for the inhibition of NMDA-activated membrane currents in the same cell types was 30 mM, and significant inhibition was observed at concentrations between 50 and 100 mM. Apparently, alcohol acts very differently in various cortical regions. Interestingly, it was not able to activate all intact and viable cells subjected to its acute action, which shows that some, but not all,

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hippocampal cells demonstrate a sensitivity to chloride currents activated by GABA receptors. Ethanol has selective effects on the functionality of GABAA receptors at concentrations lower than those associated with high intoxication ( . 50 mM) that are capable of generating EA (Reynolds et al., 1992).

Chronic Alcohol Abuse There is great discussion about the convulsive activity generated by chronic alcohol ingestion. Some researchers report that seizures can occur even during intoxication, not just during AW. However, much of the work recognizes that chronic ingestion of ethanol, even at high concentrations alone, is not capable of generating convulsive activity. Instead, it leads to structural and neurochemical modifications that are capable of changing the functionality of the limbic system. Prolonged administration of alcohol in animal models has very different effects. It is not always easy to distinguish the effects related to AW from the effects of alcohol itself. However, in any case, the changes induced tend to increase cerebral excitability from an imbalance of stability between the excitatory functions, which are mediated by glutamatergic activity, and inhibitory functions, which are mediated by GABAergic activity. Under the conditions of increased excitatory activity or decreased inhibitory activity or both, alcohol alters the balance in favor of arousal and increases the chances of paroxysmal activities (Diamond & Gordon, 1997). Seizures occur in more severe cases of chronic exposure to alcohol. This effect is due to a hyperexcitability, not only of the hippocampus, but also of the entire central nervous system (CNS) (Newman, Terris, & Moore, 1995) arising from the processes of neuronal and glial swelling. Chronic ethanol ingestion also increases glutamate binding with NMDA receptors. The use of an NMDA antagonist prevents the onset of seizures, especially during AW. However, after multiple exposures, and even in the presence of an antagonist, there is a potentiation of seizures. A predisposition for the onset of seizures may also be directly related to the GABAergic system. There seems to be a consensus in the literature that chronic alcohol administration on GABAergic function has numerous effects that may vary according to different factors. The most important findings mainly involve the GABAA subtype receptors that are ionotropic mediators of rapid postsynaptic inhibition via an increase in Cl2 ion conductance. Chronic alcohol administration depresses the CNS by potentiating GABAergic

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neurotransmission. As a result, there is an intensification in the inhibition that ultimately depresses the CNS. As a subsequent compensatory mechanism, the receptor downregulation occurs, minimizing their expression in the HF. Some authors report that the hippocampus is resistant to alcohol-induced GABAergic effects, probably due to its morphology (Morrow, Herbert, & Montpied, 1992). Interestingly, Montpied et al. (1991) have shown that chronic exposure to alcohol may reduce or increase the expression of GABAA receptor subunits in various brain regions. This may explain the variation in sensitivity to the effects of ethanol. According to Bartolomei, Suchet, Barrie, and Gastaut (1997), investigating the effects of ethanoldissociated EA in the HF that occur during intoxication and after AW may not be the best way to address the effect of ethanol on the generation of seizures. This is justified because the molecular changes that serve as a framework for generating and sustaining these activities occur during chronic intoxication, which closely binds the two periods. Fig. 14.1 shows the difference between chronic and acute effects of alcohol consumption.

Alcohol Withdrawal Syndrome AWS is a state of tissue hyperexcitability that is characterized by a variety of neuropsychiatric disorders such as anxiety, fear, muscular rigidity, delirium tremens, and generalized clonic tonic seizures with epileptiform characteristics (N’Gouemo & Rogawski, 2006; Victor & Brausch, 1967). It may be associated with reduced hippocampal volume, especially during chronic exposure to alcohol. In addition to neurodegenerative and cell death processes, other functional modifications caused by processes that are compensatory to chronic alcohol use can be exacerbated during AWS. Again, the imbalance established by increased glutamatergic excitation along with decreased GABAergic inhibition caused by chronic alcohol use sets the stage for seizures, but seizures usually do not occur as long as ethanol intake continues. In the interval of 12 48 hours after abrupt withdrawal of alcohol, there is a rebound activation of NMDA and GABA receptors. At this time, brain circuits, especially in limbic and cortical areas, are prone to a state of hyperexcitability. Subliminal stimuli may trigger epileptiform seizures that are refractory to benzodiazepine anticonvulsants that are commonly used in these cases (Lovinger et al., 1989). Stepanyan et al. (2008) suggest that this refractory activity is due to the complexity of the affected neurotransmitter systems, since

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FIGURE 14.1 Chronic X synaptic effects of alcohol. This figure compares the differences between chronic and synaptic mechanisms involved in the treatment with ethanol.

benzodiazepines only modulate the GABAergic functions. These effects increase the hyperexcitability of tissues that are more sensitive to ethanol, especially the HF, resulting in seizure generation as an adaptive response of the CNS. Exposure to several continual episodes of AW (whether through sleep or any other reason) induces the overgrowth of limbic structures, as proposed by Ballenger and Post (1978). In the hippocampus of rats, the number of spikes and epileptiform events increase with repeated episodes of AW, causing spontaneous activity. These results are correlated with the duration and number of withdrawal episodes, with the onset of memory disorders, and with the prolonged reduction in the convulsive threshold (Bartolomei, 2006). Neuronal hyperexcitability caused by abstinence from chronic alcohol use seems to be related to the mechanisms of kindling. This has been demonstrated by the increase in responses evoked during abstinence (Victor & Brausch, 1967) and by the reduction in the spontaneous seizure threshold. Researchers have measured electrical activity in subcortical structures and the limbic system of animals during abstinence and have demonstrated abnormalities. Similar patterns of disturbances in EEG recordings were demonstrated in rats by. An initial delay is followed by isolated epileptiform spikes that increase in frequency and amplitude until they are organized in paroxysmal bursts and finally support epileptic discharges in the hippocampus, amygdala, thalamus, and frontal cortex regions. These abnormalities in EEG recordings occur before or concurrently with the appearance of the behavioral signs of termination and are similar in type, anatomical location, and propagation of those characterized by the EEG recordings of animals in the process of kindling (Fig. 14.2C). In addition, in experimental animal models, these electroencephalographic abnormalities are cumulative, becoming progressively

more severe with each repeated episode of abstinence (N’Gouemo & Rogawski, 2006).

ALCOHOL EFFECTS ON NONSYNAPTIC MECHANISMS OF EPILEPTIFORM ACTIVITY Alcohol directly interferes with the lipid structure of the membrane and its anchored proteins, such as ligand-dependent ionic channels or voltage-dependent channels, and modulates the actions of second messengers (Crews, Morrow, Criswell, & Breese, 1996). Alcohol-induced structural and functional changes in these nonsynaptic substrates can modify the mechanisms responsible for ionic homeostasis. These mechanisms are extremely important for neuronal signaling functions, resulting in alterations in the normal pattern of neuronal functioning and predisposing nervous tissue to numerous pathophysiologies, including epilepsy (N’Gouemo & Rogawski, 2006).

Acute Alcohol Abuse The acute intake of ethanol makes the membrane more fluid, not because it associates with the main portions of the lipid bilayer but because it binds to specialized lipid sites that interact with, and surround, the protein inclusions. In general, low concentrations of alcohol, still considered intoxicants, are sufficient to alter the passive properties of membranes, as well as the ionic conductance responsible for the generation of action potentials (Crews et al., 1996). A research group have shown that sedative (but nonanesthetic) alcohol concentrations in rats significantly reduce the potassium currents known as M-currents in CA1 pyramidal

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FIGURE 14.2 Normal, binge drinking and AWS hippocampal formations. (A) Normal HF; (B) HF submitted to the binge drinking exposure; and (C) HF after AWS.

cells. This effect seems to be selective to this type of current since it is not capable of significantly altering the other types of K1 currents. In another study, it was shown that at high concentrations (100 200 mM, lethal doses in rats) ethanol had no detectable effect on membrane potential or input resistance. According to the authors, small and variable effects on the resting membrane potential of CA1 and CA3 pyramidal cells were observed, despite the predominance of depolarization in the responsive neurons. The cell-to-cell variability and the small reported effects are in accordance with the findings that at fairly large ethanol concentrations, small effects on extracellular field potentials are observed (Crews et al., 1996) The hyperpolarization promoted by alcohol are due to elevated gk. This was confirmed via intracellular injection of the cesium ion, a K1 channel blocker, which resulted in the suppression of ethanol-induced hyperpolarization. The same effect did not occur in response to intracellular injection of Cl2, where hyperpolarizations did not follow ethanol injection (Dopico, Bukiya, & Martin, 2014). Some researchers showed that ethanol has opposite effects on the neurons of young animals (6 8 weeks) when compared to those of adult animals (25 28 weeks). In younger animal neurons, ethanol produces inhibition, for example, hyperpolarizing the membrane and

prolonging the duration of the afterhyperpolarization (AHP). In contrast, in older animal neurons, ethanol results in a disinhibitory action, such as depolarization of the membrane, a reduction in the amplitude of AHPs and IPSPs, and a decrease in spike frequency adaptations. The authors argue that this effect results from the inhibition of electrogenic pumps or possible changes in the ionic conductances promoted by ethanol in old animals. Ethanol inhibits Na1/K1 ATPase activity in synaptosomes from old animals more efficiently than in those from young animals, and this may be the key to alcohol depolarization. Another possibility is that in old animals, ethanol actually decreases the resting gk, which, in large part, controls the membrane resting potential. AHP postbursts that accompany CA3 spontaneous activities or result from the injection of depolarizing currents into the CA1 are probably generated by the activation of calciumdependent gk promoted by Ca21 ion entry into the cells during action potentials (Crews et al., 1996; Dopico et al., 2014). It was reported that ethanol decouples gap junctions in excitable tissue, such as the hippocampus, through increased junctional resistance. Therefore, ethanol is also capable of interfering with the electrical coupling between two neurons. According to some works, ethanol must decouple neuronal cells by increasing

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FIGURE 14.3 Bilayer membrane of a normal and an alcoholic neuron. This is a schematic bilayer membrane illustrating the nonsynaptic effects of a normal and an alcoholic neuron submitted to an acute treatment with ethanol.

junctional resistance and/or reducing the number of parallel gap junctions (Little, 1999). The Fig. 14.3 shows a schematic illustrating the acute nonsynaptic effects of ethanol.

Chronic Alcohol Abuse Many variables may interfere with the reported chronic actions of ethanol, such as ethanol concentration, treatment time, affected region and cell type analyzed. Ethanol acts on the major cell types of the hippocampus at distinct levels. Administration of alcohol (10% v/v) for a period of 4 weeks or less did not demonstrate any significant changes in the total number of cells or in the number of damaged cells. However, prolonged exposure of ethanol (10% v/v) increases the neuronal loss and the number of hippocampal neurons damaged. There are quantitative differences in neuronal loss in different regions of the hippocampus, and the neurotoxic effect of ethanol follows the following order: CA3 . CA1 . CA2 . CA4 . DG. After 9 months of treatment, there is a reduction of approximately 31% 37% in the number of neurons in the HF (Nixon, 2006). The thickness of the CA3 pyramidal layer is reduced in animals treated with ethanol because of the dramatic reduction in cell density. Research also showed that chronic exposure to ethanol progressively reduces the number of granular cells and that this process does not cease with AW. In parallel, throughout the neurodegenerative process, changes in neuronal plasticity throughout the HF are also delayed. Additionally, prolonged ethanol consumption potentiates cholesterol accumulation in the membrane,

promoting lipid bilayer stiffening (Crews et al., 1996). Other studies have shown that neurons present greater dendritic arborization in tissues that are subjected to chronic ethanol treatments, as shown by an increase in resistance and a decrease in membrane capacitance (Durand & Carlen, 1985). In addition to neuronal loss, chronic ethanol intake promotes changes in accessory cells to hippocampal neurons, especially astrocytes and microglia (Santos et al., 2013, 2017; Nixon, 2006). It has been demonstrated that the number of astrocytes, as well as the number and length of the fibrillar processes of these cells, is reduced after 36 weeks of ethanol treatment, mainly in the molecular stratum of the hippocampal dentate gyrus (DG) (Nixon, 2006). This relationship is also dose- and time-dependent. After 36 weeks of ethanol treatment (5% v/v), only minor changes are observed in the CA2 and DG regions of the rat hippocampus. With an increased concentration (10% v/v) and after 4 and 12 weeks of exposure to ethanol, astrocytes present hypertrophy, perhaps because they act under the control of an alcohol-altered ionic homeostasis. After 36 weeks, ethanol (10% v/v) has opposite effects; the astrocytes have finer and smaller fibrillar processes, and few swollen astrocytes are seen compared to nonalcoholic animals. In addition, there is a significant decrease in glial factor acid protein immunoreactivity after this treatment period, which is even more dramatic when the region of analysis is the DG (Nixon, 2006). Chronic exposure to ethanol also demonstrates changes in the functionality of some ion channels. It appears that sodium channels are not sensitive to the effects of ethanol; only doses well above the lethal dose to rats are able to affect such channels. On the other hand, ethanol acts on gk through the Ca21-sensitive K1

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channels (BK channels). Intracellular calcium accumulation (due to action potential firing) interferes directly with gk in the hippocampus of alcoholic animals. Thus, the effect of ethanol on Ca21 channels is not direct, but ethanol is capable of acting directly on the excitability of the HF. After 24 hours of exposure, the remaining BK channels on the membrane are less susceptible to abrupt changes, less clustered and less cohesive within the clusters (Pietrzykowski et al., 2004). According to Santos et al. (2013, 2017), EA are facilitated in the hippocampus of animals that are submitted to chronic ethanol treatments due to changes in the functionality of the Na1/K1 ATPase, in the expression of cation-chloride cotransporters (NKCC1 and KCC2), in astrocytes, microglia and cell density. All these factors may be related to the biophysical mechanisms involved in the generation of EA mediated by nonsynaptic mechanisms. Increasing the potassium concentration and removing Ca21 ions from the bath solution induce spontaneous ictal events. These events were different in animals submitted to chronic alcohol treatment in increasing concentrations. In the animals that received a lower concentration of ethanol, intense ictal

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activity was observed, with an increase in the extracellular ionic currents, as evidenced by a potentiation in the amplitude of the electrophysiological parameters. Increased expression of NKCC1 and KCC2 was also associated with this effect, especially in the cone of axonal implantation. According to some groups, the increase in NKCC1 in this region causes intense neuronal recruitment. Consequently, it can lead to a synchronization of granular hippocampal cells. In addition, the facilitation of chloride entry by the high expression of NKCC1 may increase the rate of intracellular chloride accumulation, favoring neuronal excitability, as evidenced by the decrease in interictal periods (Figs. 14.4 and 14.5) (Santos et al., 2017). Ionic accumulations caused by the increase in NKCC1 not only predispose the tissue to EA but also lead to a state of cellular swelling, which has been proposed by other researchers (Collins, Zou, & Neafsey, 1998). Confirming this hypothesis, Santos et al. (2017) used the selective NKCC1 blocker, bumetanide, to show a reduction not only in the electrophysiological parameters related to nonsynaptic EA, but also a reduction in neurodegeneration in the hippocampus of

FIGURE 14.4 Schematic representation of the nonsynaptic changes observed in the granular cells of the DG of rats submitted to long-term exposure to ethanol. These changes are directly related to the action of ethanol on the cell membrane and inflammatory processes. During these processes there is intense modification of the ionic conductance provoking hyperexcitability and increased neuronal recruitment, which facilitates the ictogenesis. In addition, the intense ionic variations during ictal events cause intense cellular swelling followed by neuronal death. Source: The scheme is courtesy of Laborato´rio de Neurocieˆncia Experimental e Computacional, Federal University of Sa˜o Joa˜o del-Rei, Brazil.

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FIGURE 14.5 Some immunohistochemical analysis of Santos’s et al. (2017) investigation. Based on immunohistochemical analysis, Santos et al. (2017) observed increased expression of ionic cotransport mechanisms (NKCC1 and KCC2) and sodium/potassium pumps (Na 1 /K 1 ATPase). These results indicate an increased susceptibility to hippocampal neurodegeneration in alcoholics. Source: Immunohistochemical images courtesy of Laborato´rio de Neurocieˆncia Experimental e Computacional, Federal University of Sa˜o Joa˜o del-Rei, Brazil. White bars indicate 2 µm.

chronically alcoholic animals. Another important modification shown in this study was the increase in the expression of the cotransporter KCC2, which has chloride extruder mechanisms and controls the intracellular accumulation of chloride, also reducing the neuronal swelling and hindering the generation and maintenance of EA. The swelling associated with [Cl2]i provides a favorable driving force for liquid Cl2 and K1 extrusion by KCC2, which would aid in recovery from swelling. These aspects could explain the increased expression of KCC2, which is dose- and timedependent on alcohol use, since overexpression of KCC2 induces the decrease in cellular swelling as a compensatory mechanism to avoid the accumulation of internal chloride (Payne, Rivera, Voipio, & Kaila, 2003). Increased KCC2 may counterbalance the increase in NKCC1 and reduce the processes of alcohol-induced swelling and degeneration. However, under conditions of high [K1]o, as in the induction protocol of nonsynaptic epileptiform events used by Santos et al. (2017),

a reversal in the functionality of KCC2 may occur, as predicted by Payne (1997) and Blaesse, Airaksinen, Rivera, and Kaila (2009). In this context and under conditions of high [K1]o, KCC2 can cause an even greater accumulation of [Cl2]i, and consequently would lead the tissue to a significantly greater synchronism. This situation was observed by Santos et al. (2017) via electrophysiological recordings of rats alcoholized for long time with a high concentration. Several studies have demonstrated a reduction in excitatory mechanisms and an insult by cellular edema with the use of furosemide, a diuretic blocker of both NKCC1 and KCC2 (Collins et al., 1998; Sripathirathan, Brown, Neafsey, & Collins, 2009). Thus, by triggering inflammatory processes and resulting in alterations in the expression of NKCC1 and KCC2 cotransporters, alcohol promotes cellular swelling that leads to tissue degeneration. In the long-term, these changes lead to the induction of hyperexcitability and hypersynchronism of neural cells, resulting in epileptic seizures that are observed in alcoholic individuals. The different alterations found by Santos et al. (2013, 2017) due to the chronic use of ethanol show that their effects are dose- and time-dependent and may cause modifications in neuronal excitability in different ways, predisposing subjects to an epileptogenic process. These findings are a contribution of basic translational research, indicating that alcoholics affected by epileptic seizures are highly susceptible to neurodegeneration. In such circumstances, the use of diuretics, such as bumetanide and furosemide, to minimize or prevent edematous processes is suggested as a clinical measure after the occurrence of seizure. A lack of intervention to reduce these effects, which make the nonsynaptic substrate conducive to seizure induction, should exacerbate the injury and lead to nonreversible conditions by neurogenesis or plasticity. Clinical research should aim to investigate nonsynaptic targets for designing new drugs (Fig. 14.6).

Binge Drinking Binge drinking (BD) refers to an episode of excessive alcohol intake in which the corresponding experimental animal model, interpreted as a subchronic model (Collins, Corso, & Neafsey, 1996), is administered ethanol daily (3 4 times/day), during 4 or 5 consecutive days, administered by gavage or gastric catheter. At each dosage, the animals are evaluated and classified according to the six-point scale of Majchrowicz (1975), and additional doses of ethanol are administered following the scoring (Collins et al., 1996; Knapp & Crews, 1999). Despite the apparent relationship with synaptic transmission via NMDA and GABA receptors, Collins

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KEY FACTS

FIGURE 14.6

Chronic nonsynaptic effects of alcohol exposure. Schematic showing the differences between a normal and alcoholic HF submitted to chronic ethanol exposure.

et al. (1998) showed that animals submitted to BD exhibited edema, neurodegeneration (in young and adult rats) (Crews et al., 2006; Nixon & Crews, 2002) and consequently, neuronal death (Obernier, White, Swartzwelder, & Crews, 2002). According to Sripathirathan et al. (2009), the neurotoxic effect of ethanol in BD animal models promotes an upregulation of the AQP4-type aquaporins in the pyramidal and granular cells of the HF. Collins and Neafsey (2012) showed a dramatic increase in the expression of aquaporins (AQP4) in animals treated with the same protocol. However, as demonstrated in other studies, status epilepticus, which capable of causing brain lesions, arising from neuronal hyperexcitability is mainly supported by the action of synaptic receptors and/or ion channels. With glial swelling, a reduction in extracellular space creates an ideal environment for neuronal hypersynchronization, generating excessive EA and neuronal death (Collins et al., 1998). These damages caused by ethanol can be generated through a metabolic pathway involving the release of polyunsaturated fatty acids, through lipid peroxidation and through oxidative stress or via a physical (mechanical) pathway or trauma and collapse of the cytoskeleton or a combination of both (Collins, et al., 1998). Finally, after testing with NMDA receptor antagonists, Collins et al (1998) concluded that the nonsynaptic regulation of cell volume is more important in neuronal degeneration due to binge alcohol abuse than the activation of synaptic pathways. Despite all the efforts, the mechanisms responsible for generating and sustaining EA in the absence of neurotransmission remain obscure. It is imperative that the stages of alcoholization of binge alcohol consumption are further investigated and that cell changes are better described in order to

understand the relationship between hippocampal damage, molecular changes, alcohol exposure time and EA caused by intoxication (Fig. 14.2B).

MINI-DICTIONARY OF TERMS Alcohol abuse Excessive consumption of alcohol. Chronic Standard of consumption or treatment in vivo. Acute Standard of treatment in vitro. Binge drinking Standard or alcohol consumption. Characterized by ingestion of high doses in a short period of time. Alcohol withdrawal syndrome Abstinence symptoms due to an abrupt withdraw of alcohol consumption. Fetal alcoholic syndrome Set of symptoms manifested by newborns whose mothers consumed ethanol during pregnancy. Nonsynaptic mechanisms All mechanisms except synapses. All of them are involved with ionic homeostasis. Synaptic mechanisms Neural communication mechanism mediated by neurotransmission. Cation-chloride cotransporters Membrane enzymatic units responsible for the cotransport of cations with chloride. Epileptiform activities Electrophysiological activities typical of subjects diagnosed with epileptic disorders.

KEY FACTS Alcohol Abuse on Epilepsy • Biphasic effects in dependence on the pattern of abuse. • Low dosage reduces excitability. • High dosage increases excitability favoring conditions for seizures. • Seizures may occur during intoxication and also withdrawal.

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• Long-term changes in hippocampal structure causes neurodegeneration.

Synaptic Effects of Alcohol Abuse on Epilepsy • Dependent on the type of abuse. • Acute abuse reduces neuronal excitability by NMDA blockage. • Acute abuse increases inhibitory GABAergic synapses. • Chronic abuse increases neuronal excitability by glutamate binding to NMDA receptors. • Chronic abuse down regulates GABAergic synapses.

Nonsynaptic Effects of Alcohol Abuse on Epilepsy • Biphasic action in dependence on the pattern of abuse. • Acute abuse increases membrane fluidity affecting ionic conductance, decoupling gap junctions and inhibiting Na1/K1 pump. • Chronic abuse increases Na1/K1 pump, NKCC1 and KCC2 expressions, promoting neuronal and glial swelling. • Ionic homeostatic changes leading to edema. • All these changes favor ictogenesis.

SUMMARY POINTS • Limbic structures are related to epileptiform activities mediated by alcohol abuse. • Hippocampus is particularly vulnerable to epileptic activity induced by alcohol. • Prolonged ethanol consumption promotes disturbances in different subcellular mechanisms in synaptic and nonsynaptic structures. • Continuous interaction of alcohol with these mechanisms leads to an imbalance of ionic homeostasis. • Uncontrolled hyperexcitability leads to reverberating mechanisms, degeneration and cell death predisposing hippocampus to sustain seizures.

Acknowledgments Support to conduct this work was provided by Fapemig (Fundac¸a˜o de Amparo a` Pesquisa do Estado de Minas Gerais), CNPq (Conselho Nacional de Desenvolvimento Cientı´fico e Tecnolo´gico), CNPq/MCT (Instituto Nacional de Neurocieˆncia Translacional), FAPESP (Fundac¸a˜o de Amparo a` Pesquisa do Estado de Sa˜o Paulo), and CAPES (Coordenac¸a˜o de Aperfeic¸oamento de Pessoal de Nı´vel Superior).

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C H A P T E R

15 Effects of Alcohol on the Corpus Callosum Emilio Gonza´lez-Reimers1, Candelaria Martı´n-Gonza´lez1, Lucı´a Romero-Acevedo1, Geraldine Quintero-Platt1, Emilio Gonzalez-Arnay2 and Francisco Santolaria-Ferna´ndez1 1

Internal Medicine Service, University Hospital of the Canary Islands, University of La Laguna, Tenerife, Spain 2 Department of Anatomy and Pathology, University of La Laguna, Tenerife, Spain

LIST OF ABBREVIATIONS BBB DAMP DNA IL MCP MEOS NADPH NFκB NLR NOD NOX PAMP PDH RNA ROS TLR TNF-α

The corpus callosum is the largest white matter tract in the brain, connecting both hemispheres. We can distinguish several regions (Fig. 15.1), namely the rostrum, genu, corpus (body), and splenium. Fibers from prefrontal areas are predominantly transmitted through the genu; those from temporoparietal areas, through the splenium, whereas thick and highly myelinated fibers transmitting visual, auditory and somatosensorial stimuli are located in the body. Subsequent progress in neuroimaging has aided in the expansion of our knowledge about the alterations of the corpus callosum. In addition to measuring the corpus callosum area and/or thickness, white matter

blood brain barrier damage associated molecular patterns desoxyribonucleic acid interleukin monocyte chemoattractant protein microsomal ethanol oxidizing system reduced nicotine adenine dinucleotide phosphate nuclear factor κB NOD like receptors nucleotide oligomerization domain NADPH oxidase pathogen associated molecular patterns pyruvate dehydrogenase ribonucleic acid reactive oxygen species toll-like receptor tumor necrosis factor α

INTRODUCTION Ethanol affects neurons and, especially, white matter (de la Monte & Kril, 2014). The degree of atrophy is related to the amount of ethanol consumed, and the intensity of brain damage seems to be region-specific; for instance, the neurons of motor areas are not affected (Kril, Halliday, Svoboda, & Cartwright, 1997). Brain atrophy and degeneration may cause cognitive impairment (Harper & Matsumoto, 2005), although, sometimes, clinical expression is subtle (Pfefferbaum, Lim, Desmond, & Sullivan, 1996).

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00015-5

FIGURE 15.1 Corpus callosum. Regions of the corpus callosum (ro, rostrum; g, genu; c, corpus; sp, splenium).

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alterations can be evaluated. Diffusion-weighted highresolution magnetic resonance, coupled with fractional anisotropy analysis assess structural alterations of the white matter, including axonal diameter, fiber density and altered myelination. Axonal integrity can be estimated by longitudinal diffusivity, whereas axial diffusivity evaluates myelin integrity (Pfefferbaum et al., 2014). In alcoholics there is a progressive atrophy of the corpus callosum (Estruch et al., 1997), accompanied by microstructural fiber changes (Pfefferbaum, Adalsteinsson, & Sullivan, 2006), down-regulation of myelin-related genes (Mayfield et al., 2002), and altered protein expression (Kashem, James, Harper, Wilce, & Matsumoto, 2007). Direct effects of ethanol, protein-calorie malnutrition, alcohol-related liver disease and hepatic encephalopathy, associated drug use, and micronutrient deficiency, are all involved in its pathogenesis.

Corpus Callosum: Pathology In a classic study, Tarnowska-Dziduszko, Bertrand, and Szpak (1995) observed callosal lesions in 57 out of 66 alcoholics aged 24 78 years. Atrophy was diffuse in seven cases, involvement of the trunk was observed in 50 cases, and genu was affected in 32 cases. The most preserved area was the splenium. Focal alterations of the myelin sheaths, perivascular areas of demyelination, spongiform degeneration, and axonal alterations including axonal loss and spindle-shaped/ spherical dilatation of axons were also observed, findings that were later confirmed by Skuja, Groma, and Smane (2012). Fibrosis and/or hyalinization of small vessels with (38 cases) or without (23 cases) narrowing of their lumen were also present, with perivascular erythrocytic extravasation in 35 cases and perivascular gliosis in 25 cases. Authors also observed cortical and white matter atrophy affecting frontal, temporal, and parietal lobes, and suggest that changes in the corpus callosum were possibly derived from atrophy of brain lobes functionally connected to them. Oishi, Mochizuki, and Shikata (1999) measured regional cerebral blood flow in 15 alcoholics (without Marchiafava Bignami disease, Wernicke Korsakoff syndrome, or any other central nervous system diseases) and 15 controls and found a relationship between frontal cortex blood flow and the thickness of the genu (and other variables related to callosal atrophy), suggesting that callosal atrophy partly depends on cortical neuronal loss (especially of the prefrontal area) and oligodendrocyte alteration with impaired myelin synthesis.

Pathogenesis Two main mechanisms explain the decreased number of axons: damage to the neuronal bodies and secondary axonal degeneration, and disruption of myelin sheaths, rendering the axons more vulnerable to the damaging effects of ethanol (Samantaray et al., 2015). A very important factor obscuring the precise role of pure ethanol toxicity is the frequently (80%) associated thiamine deficiency. Thiamine depletion plays a critical role in decreased hippocampal-frontal cortical circuit plasticity and subsequent cognitive deficiency (Vedder, Hall, Jabrouin, & Savage, 2015). Without thiamine deficiency, the negative effect of ethanol on neurogenesis is less important than that exerted on the white matter ( Kril et al., 1997). Thiamine deficiency is due to ethanol toxicity, since ethanol alters thiamine intake, absorption, and transport into brain and damages apoenzymes involved in thiamine metabolism (Thomson, Guerrini, & Marshall, 2012). Ethanol and thiamine deficiency exert additive effects in the pathogenesis of brain alterations observed in alcoholics. He, Sullivan, Stankovic, Harper, and Pfefferbaum (2007) demonstrated that callosal atrophy was more intense among rats exposed to ethanol and thiamine deprivation. Thiamine deficiency seems to be more responsible than alcohol itself in the development of cerebellar atrophy (Mulholland et al., 2005). Thiamine acts as cofactor of branched chain alpha keto-acid dehydrogenase, transketolase, pyruvate dehydrogenase (PDH), and AKGDH. Transketolase is involved in the production of reduced nicotine adenine dinucleotide phosphate (NADPH), a molecule that is essential for the synthesis of glutathione, a main antioxidant compound (Kilanczyk, Saraswat Ohri, Whittemore, & Hetman, 2016). PDH transforms pyruvate into acetylcoenzyme A, so deficiency of this enzyme disturbs energy production and also affects acetylcholine synthesis and myelin synthesis (Potter, Rowitch, & Petryniak, 2011). Alpha ketoglutarate dehydrogenase deficiency interferes with glycolysis, reducing adenosine triphosphate production (Aikawa et al., 1984), and also alters the levels of important neurotransmitters, such as aspartate, glutamate, and gamma-aminobutyric acid (Abdou & Hazell, 2015). Indeed, glutamate excitoxicity, derived from altered synthesis and transport of glutamate is a major cause of neuronal death and apoptosis in vulnerable brain areas (thalamus) in thiamine deficiency (Hazell & Butterworth, 2009). Disturbed glycolysis and lactic acidosis may damage mitochondria (Abdou & Hazell, 2015), impairing oxidative metabolism and causing cell death. In damaged mitochondria there is an imbalance between reactive oxygen species (ROS) production and

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INTRODUCTION

ROS detoxification (Lin & Beal, 2006), aggravated by the aforementioned deficiency in glutathione function. Oxidative damage is a major mediator of brain injury in thiamine deficiency. Mitochondrial damage causes neuronal death and triggers an inflammatory process, activating microglia. These cells change their phenotype and secrete proinflammatory cytokines that act on neighboring cells (astrocytes and oligodendrocytes). Astrocyte activation alters blood brain barrier (BBB) permeability and normal astrocyte-neuronal metabolite trafficking (Fig. 15.2). Oligodendrocytes are essential for myelin synthesis. Myelin is formed by 70% 85% lipids (mainly cholesterol, glycolipids, phospholipids, especially galactosylceramide), and 15% 30% proteins (Potter et al., 2011) whose expression becomes altered in ethanol-mediated corpus callosum damage. Microglia activation leads to oligodendrocyte death and myelin and axonal damage (di Penta et al., 2013). Ethanol and Oxidative Damage Thiamine deficiency is ultimately involved in myelin alterations, but also causes neuronal damage and axonal loss. These effects add to other consequences of ethanol. Ethanol delays oligodendrocyte formation and maturation (Newville, Valenzuela, Li, Jantzie, & Cunningham, 2017) and impairs de novo myelin synthesis and the expression of several oligodendrocytederived myelin-related proteins (Gnaedinger, Noronha, & Druse, 1984). It also alters membrane phospholipid content, membrane fluidity, and decreases sphingolipid synthesis (Tong et al., 2015), both in mature and immature brains (Samantaray et al., 2015), and membrane receptors for insulin-like growth factors and

insulin (Soscia et al., 2006). Myelin alterations are more intense in adolescent brains (Pascual, Pla, Min˜arro, & Guerri, 2014). The main mechanism is oxidative damage which results from an imbalance between excessive ROS production and reduced antioxidant mechanisms. The latter include cellular enzymatic pathways (superoxide dismutases, catalase and glutathione peroxidase) that may be altered by ammonia (Cagnon & Braissant, 2008) and circulating molecules (thioredoxin, metallothioneins, uric acid, bilirubin, vitamin E, vitamin C, vitamin D, vitamin A, and homocysteine-related vitamins) that may be affected in alcoholics and were recently reviewed (Gonza´lez-Reimers, Quintero-Platt, Martı´n-Gonza´lez, Romero-Acevedo, & SantolariaFerna´ndez, 2017). Several mechanisms lead to excessive ROS production (Fig. 15.3). Cerebral Ethanol Metabolism and Reactive Oxygen Species Generation Ethanol is also metabolized in the brain (Hipo´lito, Sa´nchez, Polache, & Granero, 2007). Instead of alcohol dehydrogenase, the main pathway in liver, catalase, and microsomal ethanol oxidizing system (MEOS) are operative in microglia, astrocytes, and neurons (Zimatkin & Buben, 2007). The MEOS pathway is coupled with activation of NADPH oxidase (NOX), an important source of ROS (Qin and Crews, 2012). Although some studies suggest that microglia activation might play a protective role (Marshall et al., 2013), several experiments have shown that ethanol activates microglia and up-regulates NOX, an effect that is longlasting. Astrocytes of the cortex, dentate gyrus, and FIGURE 15.2 Main consequences of thiamine deficiency. Thiamine deficiency can lead to an imbalance between reactive oxygen species (ROS) production/detoxification.

Thiamine deficiency

Lactic acidosis

Disturbed glycolysis

ROS imbalance mitochodrial damage

Neuronal death

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Glial activation

– ↑BBB permeability – Altered glial-neuronal trafficking

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forceps minor of corpus callosum were also activated. In neurons and microglia, nuclear factor κB (NFκB) expression was enhanced and ROS production increased up to sevenfold in cortex and dentate gyrus (Qin & Crews, 2012). Postmortem studies also showed increased number of cells expressing NOX in neurons, astrocytes and microglia. The increase in NFκB expression enhances synthesis of proinflammatory cytokines. Ethanol also induces the synthesis of cyclooxygenase and inducible nitric oxide synthase (Blanco, Pascual, Valles, & Guerri, 2004). This

provokes increased prostaglandin synthesis and increased production of peroxynitrite, a highly reactive compound that aggravates oxidative stress (Valle´s, Blanco, Pascual, & Guerri, 2004). This increases BBB permeability (Haorah et al., 2007) and alters mitochondrial function (Reddy, Padmavathi, Kavitha, Saradamma, & Varadacharyulu, 2013) and causes lipid, protein and desoxyribonucleic acid (DNA) damage. Mitochondrial alteration affects ROS production (Fig. 15.4). The proinflammatory cytokines secreted exacerbate ROS production, inflammation, and cellular damage.

Alcohol metabolism in the brain

Catalase pathway

MEOS pathway

Activation of NADPH-oxidase (NOX)

ROS generation

Acetaldehyde

FIGURE 15.3 Main consequences of brain ethanol metabolism. Ethanol is metabolized by the catalase and microsomal ethanol oxidizing system (MEOS) pathways in the brain. The MEOS pathway activates reduced nicotinamide adenine dinucleotide phosphate (NADPH)-oxidase (NOX), an important source of reactive oxygen species (ROS).

Ethanol

↑ROS production

Induction of COX and iNOS

↑Prostaglandins

↑ NFkB expression

↑Peroxynitrite

↑Proinflammatory cytokines

↑BBB permeability

Lipid damage

Protein damage

DNA damage

FIGURE 15.4 Ethanol and oxidative damage. Ethanol increases reactive oxygen species (ROS) production, and induces cyclooxygenase (COX) and inducible nitric oxide synthase (iNOS). Mitochondrial damage perpetuates increased ROS production and inflammation.

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INTRODUCTION

tumor necrosis factor α (TNF-α) is a potent inductor of ROS generation, and, together with interferon gamma, it also increases the synthesis of ROS (Hukkanen et al., 1995). Increased ROS production activates NFκB (Gloire, Legrand-Poels, & Piette, 2006), closing a selfperpetuating positive feedback loop. Increased ROS and proinflammatory cytokines production by activated microglia negatively affect other neurons (Yang et al., 2014). Activation of Toll-Like Receptors In alcoholics, toll-like receptors (TLRs) located in microglia and other cells become activated. Proinflammatory cytokines, glutamate (high levels of which are found in thiamine deficiency) and other molecules such as the nonhistone DNA binding protein high mobility group (see Box 15.1), released from neurons and astrocytes during inflammation, may activate TLR-3 and aggravate the inflammatory response by secreting more TNF-α, IL-6, IL-1β, and monocyte chemoattractant protein 1 (MCP-1) (Qin & Crews, 2012). Ethanol activates receptors located within the cell, such as NOD like receptors (NLRs), that detect cytosolic DAMPs or pathogen associated molecular patterns (PAMPs). Activation of NLRs leads to the formation of inflammasomes, formed by several proteins (P) that activate caspases (proinflammatory or apoptotic).

Proinflammatory caspases, such as caspase-1 induce the secretion of IL-18 and IL-1β. Astrocyte NLR-P3 inflammasome (especially at the dentate gyrus and corpus callosum) become activated by ethanol, in relation to increased mitochondrial ROS generation. These cells produce more IL-1β and IL-18 and increase inflammatory response (Alfonso-Loeches, Uren˜a-Peralta, MorilloBargues, Oliver-De La Cruz, & Guerri, 2014). Moreover, direct activation of TLR-4 by ethanol leads to increased expression of NFκB (adding to the direct effect of ROS) and secretion of proinflammatory cytokines, such as IL-1β, MCP-1and IL-6 (Zhang & Ghosh, 2001). Interestingly, TLR-4 knock-out mice are protected from the ethanol induced activation of NLR-P3, so both sensor systems (TLRs and NLRs) are necessary to orchestrate an inflammatory response (Fig. 15.5). The Gut Brain Axis Acetaldehyde increases intestinal permeability (Elamin et al., 2012), allowing Gram bacteria to reach the portal blood. Endotoxemia may overwhelm the Kupffer system and reach the systemic circulation, especially in cirrhotics (Rao, 2009). Via TLR-4 receptors (mainly), portal germs activate astrocytes to increase secretion of proinflammatory cytokines. Ethanol aids in this production, potentiating the induction of NFkB, and its binding to DNA. This proinflammatory effect is accompanied by a reduction in binding to DNA of

Insult: ethanol

TLR-4

Insult: ethanol

ASC Procaspase I

Inflammasome

NLPR3

NFkB caspase I

Procytokines

Cytokines

FIGURE 15.5

Some pathways of the innate immune response affected by ethanol. Ethanol activates cell receptors, leading to proinflammatory cytokine secretion. Proinflammatory cytokines may activate toll-like receptors closing a positive feedback cycle.

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an antiapoptotic transcription factor (the c-AMP responsive element-binding protein), especially in dentate gyrus (Bison & Crews, 2003). Cytokines produced in the liver are transported to brain and stimulate brain endothelial cells to produce additional cytokines (Erickson, Dohi, & Banks, 2012) that stimulate neuroinflammation and inhibit hippocampal neurogenesis. The global effect on neuroinflammation may be long-lasting: systemic lipopolysaccharide administration caused a marked increase in brain TNF-α levels, that remained high for 10 months, activating microglia and increasing expression of proinflammatory factors (Qin et al., 2007), an effect markedly enhanced by previous ethanol treatment (Qin et al., 2008) and in binge-drinking animal models. Free Iron Accumulation In the normal brain, iron accumulates in oligodendrocytes and serves for myelin synthesis (Rosato-Siri et al., 2017). Excessive iron disrupts white matter in patients with multiple sclerosis (Raz et al., 2015). Several mechanisms cause brain iron accumulation in alcoholics (Fig. 15.6). 1. Increased permeability of the BBB allows extravasation of red blood cells to the intersticial space, where they are destroyed, liberating heme and free iron. This causes an increase in ferritin, as a defensive mechanism against free iron. 2. Repeated microtrauma, related to the peculiar style of life of alcoholics also lead to iron deposition (Lu,

Cao, Wei, Li, & Li, 2015), that plays a major role in brain lesions after intracerebral hemorrhage, due to the marked ability of this element to generate ROS (Yang et al., 2017). Usually, hepcidin—widely distributed in brain—downregulates iron transport proteins and exerts a protective role on neuronal damage (Zhou et al., 2017). The importance of altered iron metabolism is so striking that the outcome of patients with brain bleeding can be predicted by a combination of serum iron, ferritin, and transferrin (Yang et al., 2016). Repetitive microtrauma also damage the brain leading to abnormal accumulation of a tau protein, that leads to progressive brain function impairment. (Morikawa et al., 1999). 3. Metabolism of ethanol by the MEOS system generates an increase in oxygen consumption, stimulating increased synthesis of hypoxia inducible factor 1 (Wang, Wu, Yang, Gan, & Cederbaum, 2013), that is, involved in the synthesis of TNF-α, and NO, in the induction of NOX (Yuan et al., 2011), and in iron cell accumulation by upregulation of transferrin receptor 1 (Ding et al., 2011). MicroRNA-Associated Oxidative Stress MicroRNAs may modulate the inflammatory response: an in vitro study described an inhibition of the expression of proinflammatory factors by microRNA-339-5p (Lippai, Bala, Csak, Kurt-Jones, & Szabo, 2013). Others have found that ethanol induces

FIGURE 15.6 Free iron and brain damage. Mechanisms involved in free iron deposition, that may increase oxidative damage.

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KEY FACTS

(microRNA-155) production in the cerebellum with increased TNF-α and MCP-1 secretion by cerebellar microglia (Zhang, Wei, Di, & Zhao, 2014). Toxic Lipids: The Liver Brain Axis In steatohepatitis, increased hepatocyte metabolism of lipids may lead to the formation of ceramide that provokes insulin resistance, activates proinflammatory cytokines, increases lipid peroxidation, and induces expression of ceramide genes in brain (de la Monte, Longato, Tong, DeNucci, & Wands, 2009), closing a deleterious feedback loop.

MINI-DICTIONARY OF TERMS Fractional anisotropy Measures the degree of anisotropy of water molecules. Without obstacles, water molecules diffuse freely in any direction, a pattern that may be changed by the presence of macromolecules, cell membranes, etc. If water molecules are conducted within a tube (or an axon), diffusion only occurs along the axis of this tube. Therefore, diffusion is not isotropic, but anisotropic. The degree of anisotropy can be measured, and allows to infer alterations in the axonal diameter, fiber density or myelin structure. Diffusion-weighted magnetic resonance imaging draws maps of the diffusion pattern of water molecules, allowing the detection of microstructural details of normal or altered anatomy of a given region. Apoptosis Noninflammatory programmed cell death in response to signals derived from the preapoptotic cell (intrinsic pathway) or from other cells (extrinsic pathways). Toll-like receptors Receptors that are an essential part of the innate immunity, they recognize foreign molecules mainly derived from bacteria. NOD receptors Receptors that recognize intracellular foreign molecules (viral particles or altered cytosolic proteins) DAMP damage associated molecular patterns or alarmins are molecules derived from the host cell that become altered after insults (i.e., nuclear membrane leakage, cell necrosis, heat shock, etc.). They may elicit an inflammatory reaction PAMP pathogen derived foreign molecules that generate an inflammatory response. MicroRNA small noncoding RNA molecules, located within or extracellularly. They may interfere with gene expression or promote inflammatory responses, apoptotic or antiapoptotic signals. Ceramide Membrane-bound molecules formed by fatty acids and sphingosine. They may promote lipid peroxidation, inflammation and apoptosis. Perivascular gliosis Reactive proliferation of astrocytes in response to an insult, frequently linked to inflammation-derived disturbances of the blood brain barrier. It resembles a neural equivalent of reactive fibrosis.

SUMMARY POINTS • In alcoholics, white matter atrophy is more severe than gray matter atrophy.

• Callosal atrophy depends on myelin alterations and axonal degeneration that may be secondary to neuronal damage. • Oligodendrocytes synthesize myelin, and ethanol impairs their development and function. • Ethanol alters thiamine intake, absorption, transport into brain and also damages apoenzymes involved in thiamine metabolism. • Thiamine deficiency plays an important role on white matter damage in alcoholics. • Oxidative damage is the main pathogenetic mechanism involved in white matter atrophy. It depends on an imbalance between excessive reactive oxygen species (ROS) production and altered antioxidant systems. • Main mechanisms leading to excessive ROS production include: metabolism of ethanol, activation of toll-like receptors (TLR) and nucleotide-binding oligomerization domain-like receptors (NLR), excessive cytokine production, ethanol-mediated brain accumulation of free iron, microRNA, and toxic lipids derived from liver.

KEY FACTS Brain and Corpus Callosum Structure and Function • The central nervous system consists of gray matter (neuronal bodies) and white matter (nervous tracts). • Nervous tracts connect different areas of the nervous system and are formed by axons (prolongations of neuronal bodies) covered by myelin sheaths. • Myelin is formed by complex phospholipids. It is necessary for adequate transmission of nerve signals. • Corpus callosum, the largest white matter structure of the brain, connects both brain hemispheres. • Myelin sheaths are formed by specialized glial cells called oligodendrocytes

Effects of Ethanol on Corpus Callosum • Neuronal loss and/or myelin damage may alter white matter structure and function. • Ethanol can affect gray matter, although its main effect is observed in white matter. • Ethanol directly affects oligodendrocytes, impairing myelin synthesis. • Toxic compounds derived from ethanol metabolism, mainly the so called reactive oxygen species, damage myelin sheets.

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• Myelin may be also damaged by local and systemic inflammatory mediators directly or indirectly derived from ethanol metabolism.

CONCLUSION Many mechanisms observed in alcoholics are involved in brain damage, with catastrophic consequences on brain function. Corpus callosum becomes especially affected, as we show in this chapter. Alcohol abstinence markedly improves these alterations.

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C H A P T E R

16 The Role of the Lateral Habenula Circuitries in Alcohol Use Disorders Nimisha Shiwalkar, Wanhong Zuo, Alex Bekker and Jiang-Hong Ye Department of Anesthesiology, Pharmacology, Physiology, and Neuroscience, Rutgers, the State University of New Jersey, New Jersey Medical School, New Jersey, United States

LIST OF ABBREVIATIONS AMPA AMPAR AUD CaMKII CPA CPP CTA DA EPN GABA GLT-1 IPSC LHb mPFC RMTg SM SNc VTA

(DA) levels in their target areas. However, significantly less is known about the aversion. Alcohol aversion may include the aversive effects of alcohol itself, and the aversive consequences of withdrawal from chronic repeated cycles of excessive alcohol exposure. Whereas the former may limit voluntary intake, the latter, characterized by the negative emotional disturbance during abstinence, is recognized as a major driving force for relapse drinking. The lateral habenula (LHb), an epithalamic structure, has emerged as a crucial brain region responding to aversive and stressful stimuli. LHb neurons are stimulated by aversive events, including stress, depression, disappointment, fear, and pain (Dolzani et al., 2016; Li Wang et al., 2017; Matsumoto & Hikosaka, 2007). LHb is also activated by acute alcohol and by withdrawal from chronic alcohol exposure. This chapter summarizes the current knowledge regarding the mechanisms underlying the aversive effects induced by alcohol, particularly those involving the LHb and its circuitry.

α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor alcohol use disorder calcium/calmodulin-dependent kinase II conditioned place aversion conditioned place preference conditioned taste aversion dopamine entopeduncular nucleus γ-aminobutyric acid glutamate transporter 1 inhibitory postsynaptic current lateral habenula medial prefrontal cortex rostromedial mesopontine tegmental nucleus stria medullaris substantia nigra compacta ventral tegmental area

INTRODUCTION Alcohol use disorder (AUD) accounts for the major part of neuropsychiatric disorders and contributes substantially to the global burden of diseases. AUD, like addiction to many other recreational drugs, can be defined by a compulsion to seek and take the drug, loss of control in limiting intake thereof, and the emergence of a negative emotional state when access to the drug is prevented (Koob, 2009). Alcohol has both rewarding and aversive properties. The rewarding effect is believed to be, at least in part, a result of increased activity of dopaminergic neurons in the ventral tegmental area (VTA), and increased dopamine Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00016-7

NEUROBIOLOGY OF ALCOHOL ADDICTION A significant challenge faced by researchers on alcohol is to understand the mechanisms underlying the transition from recreational alcohol use to dependency. This transition progresses through three critical stages, namely: binge/intoxication; negative affect/withdrawal; and preoccupation/anticipation which form a recurring cycle leading to dependence (Koob & Volkow,

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FIGURE 16.1 Drug addiction cycle (Batalla et al., 2017; Koob & Le Moal, 2008a, 2008b; Koob & Volkow, 2016). Addiction to a drug starts with the stage of intoxication/binge drinking characterized by rewarding effects of the drug mediated by the mesocorticolimbic system. This is followed by a stage of withdrawal symptoms resulting from the absence of the reward and is mediated by the habenulamesencephalic system. Slowly this leads to a stage of preoccupation or anticipation where there is difficulty in carrying out the executive functions of the brain, forcing the abuser toward drinking again and is mediated by the corticolimbic system.

FIGURE 16.2 Application of Solomon’s opponent-process theory to drug addiction: (C) compares the change in “a” and “b” processes due to repeated application of the same unconditioned stimulus. The primary process “a” remains the same whereas the opponent-process “b” shows a shorter onset time, increased peak, and longer decay time after repeated exposure to the same drug (B). This manifests as a decrease in the positive affective state and increase in the negative affective state associated with the drug over time (A). Source: Modified from Fig. 16.4 of Solomon, R.L., & Corbit, J.D. (1974). An opponent-process theory of motivation. I. Temporal dynamics of affect. Psychology Review, 81(2), 119 145.

2016) (Fig. 16.1). In the binge/intoxication stage, there is a rewarding response to the alcohol’s hedonic component, resulting in positive reinforcement. This is mediated, at least partly, by the mesocorticolimbic system (Batalla et al., 2017; Koob & Volkow, 2016). The intoxication stage corresponds to the first process of Solomon’s opponent-process theory of motivation (Koob and Le Moal, 2008a, 2008b; Solomon & Corbit, 1974). This theory states that the initial hedonic or pleasant reaction of alcohol use reaches tolerance over time and is replaced by a hedonic contrast (Fig. 16.2), which is fast in onset

and declines in intensity over time leading to tolerance. The second process that follows is slower in onset and characterized by an opposing, aversive, negative affective state extending into withdrawal and further strengthening over time; thereby, explaining stronger withdrawal symptoms with increasing consumption of the drug. Eventually, aversive consequences of chronic alcohol exposure and withdrawal are established as the crucial component in the development of AUD. The proposed underlying mechanism is neuroadaptations in the reward circuit to counteract the positive hedonic

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THE LATERAL HABENULA CIRCUITS

component (called “within system adaptations”) and the recruitment of anti-reward circuits (called “between system adaptations”) (Batalla et al., 2017; Koob & Volkow, 2016), such as the hypothalamic-pituitary-axis and brain stress systems. Emerging evidence indicates that the habenulomesencephalic circuit is an important determinant of the adaptations within the brain reward circuitry responsible for aversive affective behavioral symptoms.

THE LATERAL HABENULA CIRCUITS The LHb receives afferents from different limbic and basal ganglion structures (Fig. 16.3). This includes the entopeduncular nucleus (EPN) (Hong & Hikosaka, 2013; Stephenson-Jones, Kardamakis, Robertson, & Grillner, 2013), ventral pallidum (Knowland et al., 2017), lateral hypothalamus (Lecca et al., 2017; Stamatakis et al., 2016; Zhang, Hernandez, VazquezJuarez, Chay, & Barrio, 2016), lateral septum (Mirrione et al., 2014), raphe nucleus(Xiao et al., 2017), medial prefrontal cortex (mPFC) (Mathis et al., 2016;

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Mizumori & Baker, 2017), and VTA (Root, MejiasAponte, Qi, & Morales, 2014; Yoo et al., 2016), the majority of which are glutamatergic. Other neuromodulatory circuits like the reciprocal dopaminergic projection from the VTA, serotonergic projection from the raphe, and adrenergic projection from locus coeruleus also influence the functioning of the LHb. The LHb sends glutamatergic projections to the rostromedial mesopontine tegmental nucleus (RMTg) (Stamatakis & Stuber, 2012), VTA/substantia nigra compacta (SNc) (Hennigan, D’Ardenne, & McClure, 2015; Lammel et al., 2012), locus coeruleus, periaqueductal gray (Pobbe & Zangrossi, 2010), laterodorsal tegmentum (Yang et al., 2016), raphe nuclei, and medullary raphe (Batalla et al., 2017; Dolzani et al., 2016; Ootsuka, Mohammed, & Blessing, 2017; Zhou et al., 2017). Importantly, the LHb glutamatergic projections excite GABAergic RMTg neurons (Lecca et al., 2017; Stamatakis & Stuber, 2012) which, in turn, inhibit DA neurons in VTA/SNc (Hennigan et al., 2015; Lammel et al., 2012) or serotonergic neurons in the raphe (Zhou et al., 2017) and this pathway is the major contributor

FIGURE 16.3 Schematic illustration of the main connections of the Lateral Habenula (LHb) and their functions: The medial part of LHb (LHbm) receives glutamatergic inputs from the medial prefrontal cortex (mPFC), ventral tegmental area/substantia nigra compacta (VTA/SNc), and limbic regions including the lateral septum and lateral hypothalamus. The lateral part of LHb (LHbl) receives co-release of glutamate/γ-aminobutyric acid (GABA) from globus pallidus/entopeduncular nucleus. Ventral pallidum sends glutamatergic while raphe nucleus sends serotoninergic inputs to the whole LHb. Glutamatergic LHb neurons target dopaminergic neurons in the VTA/SNc, GABAergic neurons in the RMTg, interneurons as well as serotoninergic neurons in the raphe nucleus, etc. Afferent and efferent connections of the habenula are carried by the stria medularis (SM) and fasciculus retroflexus (FR), respectively. The LHb and the related circuits play crucial roles in drug addiction, aversion/reward, depression, anxiety, pain, and adaptive behaviors.

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for LHb mediated aversive response to addictive drugs (Glover, McDougle, Siegel, Jhou, & Chandler, 2016; Jhou, Fields, Baxter, Saper, & Holland, 2009).

ALCOHOL MODULATES GLUTAMATERGIC AND GABAERGIC NEUROTRANSMISSIONS IN HABENULOMESENCEPHALIC CIRCUIT In the majority of LHb neurons in rat brain slices, acute alcohol (10.8 mM) enhanced both glutamatergic and GABAergic transmissions, the two major neurotransmitters regulating the excitability of LHb neurons. The potentiation of glutamatergic transmission, however, was greater than that of the GABAergic, which contributes to the alcohol-induced excitation of LHb neurons. (Zuo, Wang, et al., 2017) (Fig. 16.4A). Noteworthy, whereas alcohol-induced acceleration of spontaneous action potential firing of LHb neurons was positively correlated with alcohol’s potentiation of excitatory postsynaptic currents, it was negatively correlated to alcohol’s potentiation of IPSCs (inhibitory postsynaptic currents) (Zuo, Fu, et al., 2017; Zuo, Wang, et al., 2017). It has been demonstrated that alcohol-induced potentiation of GABAAR-mediated

IPSCs in the LHb is limited by the presynaptic metabotropic GABA subtype B receptors (GABABRs, Fig. 16.4A). Also, application of the GABABR antagonist, SCH50911, significantly increased alcohol’s potentiation of IPSCs mediated by GABAARs in LHb. These findings support the contribution of a presynaptic GABA element in alcohol’s effects on LHb activity. The interplays of glutamatergic and GABAergic systems in the LHb-related circuits may, thereby, regulate the progression towards alcohol dependence. Enhanced glutamatergic transmission in LHb is associated with increased activity of the calcium/calmodulin-dependent kinase II (CaMKII) (Fig. 16.5) (Fink & Meyer, 2002). CaMKII phosphorylates the Serine 831 residue on the α-amino-3-hydroxy-5methyl-4-isoxazolepropionic acid receptor (AMPAR) GluA1 subunit, enhancing AMPAR activity. Increased βCaMKII activity has been shown to cause increased GluA1 trafficking to the membrane of LHb neurons, which has been linked to major depressive disorder in animal models (Li et al., 2013; Malinow, 2003). In general agreement with these findings, we recently demonstrated that withdrawal from chronic voluntary alcohol drinking leads to significant depressive-like symptoms and a substantial increase in CaMKIIAMPAR activity in the LHb and pharmacological

FIGURE 16.4 The effects of acute alcohol exposure in rats: (A) In brain slices, acute alcohol enhanced both glutamatergic and GABAergic transmissions to LHb neurons and accelerated spontaneous firing rate of LHb neurons (Fu et al., 2017; Shah et al., 2017; Zuo, Fu, et al., 2017; Zuo, Wang, et al., 2017). Single systemic injection of alcohol (1.5 g/kg, i.p.) induced conditioned taste aversion (CTA) to saccharin, increased c-fos expression (B C) (Glover et al., 2016) and the basal firing rates in the LHb (D, in vivo recording) (Tandon et al., 2017). (E) Summary of studies on CTA, conditioned place aversion (CPA) and conditioned place preference (CPP) in rats induced by acute alcohol exposure.

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FIGURE 16.5 Schematic illustration of changes in synaptic and cellular properties of LHb neurons after repeated alcohol exposure and withdrawal: The glutamatergic transmission depends primarily on the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPARs) containing GluA1. Glutamate uptake is mediated by transporters (GLT-1) on glia cells. Hyperactivity of LHb neurons during alcohol withdrawal may attribute to the following changes: (1) enhanced glutamatergic transmission; (2) increased surface expression of GluA1-containing AMPARs; (3) reduced GLT-1 expression, which elicits a hyper-glutamatergic state; (4) phosphorylation of calcium/calmodulin-dependent kinase II (CaMKII) and Ser-831 residue of GluA1 AMPARs, which strengthens postsynaptic AMPAR function; and (5) reduced M-channel expression and function. Also, alcohol-induced changes are mediated by the 5-HT2/3 receptors expressed in the glutamatergic terminal and the soma of LHb neurons. These adaptations are associated with the anxiety- and depressive-like behaviors as well as pain during alcohol withdrawal.

inhibition of AMPARs or CaMKII activity in the LHb alleviated depressive-like behaviors while reducing alcohol consumption (Li, Kang, et al., 2017). There has been a growing interest in finding the afferents to the LHb and their role in the reward circuitry. The glutamatergic inputs from the lateral hypothalamus to the LHb have been shown to contribute to aversive responses (Stamatakis et al., 2016). Similarly, the VGluT2 (Vesicular glutamate transporter-2) positive ventral pallidum, paralbumin neurons projecting to the LHb are also demonstrated to be aversive (Knowland et al., 2017). To identify the LHb inputs that are important to alcohol-related behaviors, Sheth and colleagues lesioned the stria medullaris (SM) and found an increase in voluntary alcohol consumption (Fig. 16.3) (Sheth, Furlong, Keefe, & Taha, 2017). Furthermore, alcohol-induced conditioned taste aversion (CTA) was attenuated after lesioning of: (1) the LHb, (2) the SM, or (3) the connection between the lateral hypothalamus and the LHb (Sheth et al., 2017) (Table 16.1).

Future work could determine whether, and how, these afferents contribute to the aversive effects of alcohol as well as the aversive consequences of withdrawal from chronic alcohol exposure, and whether different inputs contribute to different aspects of the aberrant behaviors.

LATERAL HABENULA HYPERACTIVITY AND AVERSIVE EFFECTS OF ALCOHOL Accumulating evidence has linked alcohol’s aversive effects with LHb hyperexcitability. An in vivo administration of a low dose (0.25 g/kg, i.p.) of alcohol to rats resulted in conditioned place aversion (CPA) and increased c-Fos expression in the LHb. Also, low concentrations (,10 mM) of alcohol substantially accelerated spontaneous firing of LHb neurons in brain slices (Fig. 16.4A) (Shah et al., 2017; Zuo, Fu, et al., 2017). In support of this, alcohol (1.5 g/kg, i.p.) induced CTA in rats is positively correlated to c-Fos

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158 TABLE 16.1 m Increase

16. THE ROLE OF THE LATERAL HABENULA CIRCUITRIES IN ALCOHOL USE DISORDERS

Effects of Manipulations of Lateral Habenula (LHb) or the Inputs to the LHb on Alcohol-Related Behaviors: k Decrease;

Phase

Treatment

Main Findings on Alcohol-Related Behaviors

Acquisition of alcohol

Lesion LHb

mAlcohol intake and blood alcohol concentrations Haack et al. (2014), (a two-bottle choice paradigm or operant selfTandon et al. (2017) administration); Blocked yohimbine-induced reinstatement of alcohol/sucrose; kAlcoholconditioned place aversion (CPA) in home cage/ an operant task.

Lesion the stria medullaris

mVoluntary alcohol intake/preference

Disconnection of the lateral hypothalamus to LHb

mVoluntary alcohol intake, without altering operant alcohol self-administration, yohimbineinduced reinstatement of alcohol selfadministration, taste preference or alcohol-CTA

Disconnection of the Ventral pallidum to LHb

Did not alter any of the alcohol-directed behaviors

Deep Brain Stimulation

kAlcohol intake/preference

Li et al. (2016)

Intra-LHb infusion

Glutamate antagonists

kAlcohol intake and depression-like behaviors

Li, Kang, et al. (2017)

M-channel activator

kAlcohol intake and anxiety-like behaviors

Kang et al. (2017)

Activator of glial glutamate transporter 1

kAlcohol intake, depressive- and anxiety-like behaviors

Kang et al. (2018)

hM4Di Inhibitory DREADDs

kAlcohol intake, depressive- and anxiety-like behaviors, and pain

Kang et al. (2017), Kang et al. (2016)

Reinstatement of alcohol

expression in the LHb (Fig. 16.4B,C) (Glover et al., 2016). In a recent study, Tandon and colleagues compared firing of LHb neurons of freely behaving rats before and after an alcohol-induced CTA to saccharin taste (Fig. 16.4D). They found that the baseline firing of LHb neurons was significantly higher after CTA induction than before. Furthermore, LHb firing evoked by cues signaling saccharin availability shifted from a pattern of primary inhibition before CTA to a primary excitation after CTA induction (Tandon, Keefe, & Taha, 2017). Together, these findings emphasize the importance of LHb activity in alcohol-induced aversion. Affective disorders such as anxiety, hyperalgesia, and depression are highly comorbid in alcoholics as aversive consequences of alcohol withdrawal and have the potential of primarily driving excessive alcohol consumption (Koob, 2003). We have observed anxiety, hyperalgesia, and depressive-like behaviors in rats withdrawn from chronic repeated cycles of alcohol administration (Kang et al., 2017; Kang, Li, & Ye, 2016; Kang, Li, Bekker, & Ye, 2018; Li, Fu, et al., 2017; Li, Kang, et al., 2017). Also increased were the glutamatergic transmission and excitability of LHb neurons. Further, the increased excitability of LHb neurons was due in part to reduced M-type K1 currents (M-currents) and M-channel expression. Intra-LHb infusion of retigabine, the M-channel opener reduced the elevated anxiety levels and alcohol intake upon resuming drinking (Kang et al., 2017).

References

Sheth et al. (2017)

As a matter of interest, LHb is reciprocally connected with the serotonergic raphe nuclei, directly and indirectly. We have shown that serotonin (5-HT) increased the glutamatergic transmission and the excitability in the majority of LHb neurons, via 5-HT2/3 receptors (Xie et al., 2016; Zuo et al., 2016). Further, both in vivo administration of alcohol and intra-LHb infusion of 5-HT increased the expression of phosphorylated GluA1 receptors and c-Fos immunoreactivity in LHb. Both the effects could be attenuated by ritanserin, a 5-HT2R antagonist (Fu et al., 2017). These findings suggest that alcohol increases local 5-HT concentration which, in turn, activates the 5-HT2 receptors and leads to phosphorylation of GluA1 receptors causing activation of LHb (Fig. 16.5). On the contrary, other studies reported that 5-HT acting on presynaptic 5-HT1B receptors blocked the excitatory inputs from EPN to LHb (Hwang & Chung, 2014; Shabel, Proulx, Trias, Murphy, & Malinow, 2012), thus, complicating the framework and demanding further detailed research. Importantly, LHb activity is also affected by the uptake of extracellular glutamate. The expression of astrocytic GLT-1 (glial glutamate transporter 1), the primary protein responsible for glutamate uptake, is significantly reduced during alcohol withdrawal (Fig. 16.5), thereby, increasing LHb excitability as well as the corresponding expression of depression and anxiety phenotypes. This expression could be rescued via administration of ceftriaxone, a compound known

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REFERENCES

to upregulate GLT-1 expression and could be counteracted by dihydrokainatic acid, a GLT-1 inhibitor, demonstrating that the phenotypes seen were due, in part, to GLT-1 modulation of synaptic glutamate uptake (Kang et al., 2018). Consistent with this, LHb GLT-1 knockout has been shown to cause depression (Cui et al., 2014). The importance of this finding carries over well to humans. Association has been found between reduced astrocytic function and depression (Miguel-Hidalgo et al., 2010; Sanacora & Banasr, 2013). Accordingly, astrocytic regulation is a promising novel target for the treatment of alcoholism due to its ability to modulate comorbid depression and anxiety. In summary, the habenulomesencephalic circuit plays a crucial role in the aversive effects of alcohol as well as the negative affective symptoms of alcohol withdrawal. Though the precise mechanisms for this linkage are not yet identified, studies emphasize a complex interaction of different systems centered on the LHb, and manipulation of these pathways can help in treating alcohol dependence and relapse.

CONCLUSION Aversive psychiatric disorders that often occur in alcoholics during forced abstinence contribute significantly to continued and relapse drinking. Acute and repeated alcohol exposure has robust and persistent effects on LHb neurons, particularly on their glutamatergic transmission. Recent findings support the hypothesis that alcohol withdrawal triggers an increase in LHb CaMKII and AMPAR activity and that CaMKII-AMPAR signaling in the LHb exemplifies a molecular basis for depression-like symptoms during alcohol withdrawal. The functional, pharmacological, or anatomical inhibition of the LHb ameliorates relapse drinking and psychiatric disorders occurring in animals withdrawn from chronic alcohol exposure. The LHb is potentially an important target for future therapies against alcohol abuse and comorbid hyperalgesia, anxiety, and depression. Though we have started to understand the neural substrates of the aversive properties of alcohol, their precise operative mechanism and relationship to aversive and seeking behavior is still in its early stages. Rapid advances in this field should lead to a better understanding of the neural circuits contributing to alcohol abuse and usher in the development of innovative treatments for AUD.

MINI-DICTIONARY OF TERMS Antagonist A compound that binds to the same receptor as the specific neurotransmitter, but does not activate the receptor.

Mesolimbic fopamine (DA) system DA neurons located in the ventral tegmental area and projecting to the Nucleus accumbens. Self-administration The voluntary consumption of a substance by controlling its delivery. Conditioned place aversion The avoidance of an environment associated with an aversive effect. Conditioned place preference The preference for an environment paired with the immediate rewarding effects of drugs.

KEY FACTS About the Role of Lateral Habenula Circuits in Alcohol Use Disorder • The lateral habenula (LHb) connects the forebrain to the midbrain. • The LHb is stimulated by aversive stimuli. • Both acute alcohol use or alcohol withdrawal increase LHb excitability and glutamate transmission. • Alcohol withdrawal is often comorbid with anxiety, hyperalgesia, and depression. • Inhibition of LHb activity or glutamate transmission ameliorates syndromes of withdrawal.

SUMMARY POINTS • This chapter focuses on the role of the lateral habenula (LHb) and its circuitries in the effects of alcohol and particularly signifies involvement of LHb activation in aversive effects of alcohol and aversive consequences of alcohol withdrawal. • The LHb projects mainly to the ventral tegmental area, Rostromedial mesopontine tegmental nucleus, and the raphe nuclei. • The LHb receives inputs primary from various limbic and basal ganglion structures. • The activity of the LHb is higher when exposed to acute alcohol and during withdrawal from chronic alcohol exposure. • LHb hyperactivity is mediated in part by adaptations in dopamine receptors or/and AMPA receptors.

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C H A P T E R

17 Ventral Pallidum and Alcohol Addiction Asheeta A. Prasad and Gavan P. McNally School of Psychology, UNSW Sydney, Sydney, NSW, Australia

LIST OF ABBREVIATIONS AcbC AcbSh BLA DBS D1 D2 LH MSN STN PVT VP VPvm VPdl VTA

In this chapter, we review VP and its contributions to various aspects of alcohol addiction. We consider the anatomy, physiology, and pharmacology of VP because these provide the key foundations upon which to understand VP. Next, we consider evidence from preclinical animal models for roles of the VP in various aspects of alcohol addiction, including consumption, taste hedonics, and relapse. Finally, we consider some treatment implications derived from these basic preclinical findings.

accumbens core accumbens shell basolateral amygdala deep brain stimulation dopamine 1 receptor dopamine 2 receptor lateral hypothalamus medium spiny neuron subthalamic nucleus paraventricular thalamus ventral pallidum ventromedial ventral pallidum dorsolateral ventral pallidum ventral tegmental area

VENTRAL PALLIDUM: ANATOMY, PHARMACOLOGY, AND PHYSIOLOGY

INTRODUCTION The ventral pallidum (VP) is located in the basal ganglia (Fig. 17.1). The VP is well positioned as the intermediary between cortical, amygdala, and striatal circuits for cognition, action and midbrain circuits for motivation and reinforcement. It is a key locus of convergence for brain circuits involved in reward learning, hedonics, and motivation. VP contributes to the self-administration of, and relapse to, various drugs of abuse, including alcohol. VP serves important roles in hedonic evaluations of natural and drug rewards, as well as in allowing environmental stimuli to direct and energize reward-seeking behavior. In recent years, our understanding has advanced so that VP is recognized as a prominent regulator of cortical, thalamic, striatal, and amygdala inputs. This is mainly due to the increased understanding of the heterogeneous organization, cellular diversity, and complex circuitries comprising VP.

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00017-9

The VP is a heterogeneous structure, segregated on its anatomy and neurochemistry. VP neurons are typically GABAergic, glutamatergic, or cholinergic neurons. They express a diversity of molecular markers, including calretinin, enkephalin, dynorphin calbindin, parvalbumin (PV), neuropeptide Y, and somatostatin, showing important roles for neuropeptide modulation of VP function (Root, Melendez, Zaborszky, & Napier, 2015). VP is also immunoreactive for both substance P and enkephalin; however, in the rodent, substance P has a more selective expression within the anatomically defined VP (Root et al., 2015). Clear VP subregions can be delineated based on expression of calbindin-d28k and neurotensin immunoreactivity. For example, the medial VP expresses neurotensin whereas the dorsal lateral VP expressed calbindin-d28k, and this delineation has important functional correlates (Root et al., 2015) (see later). However, VP neurons of the same cell class exhibit further complexity. As one example, PV neurons within the VP exist as at least two distinct subpopulations defined by their projection targets, with one subpopulation projecting to the

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FIGURE 17.1

Major afferent and efferent connectivity of the ventral pallidum as well as major cell types. Ventral pallidum receives major afferents from cortex, accumbens shell (AcbSh) and core (AcbC), paraventricular thalamus (PVT), subthalamic nucleus (STN), basolateral amygdala (BLA), and ventral tegmental area. In turn, ventral pallidum projects to subthalamic nucleus (STN), lateral hypothalamus (LH), and ventral tegmental area (VTA). These afferents and efferents are organized into discrete channels through the dorsolateral and ventromedial parts of the ventral pallidum involving at least three main classes of ventral pallidum neurons (GABA, glutamate, cholinergic).

lateral habenula (LHb) and the other to ventral tegmental area (VTA) and these two subpopulations have distinct functional correlates relevant for psychiatric disorders (Knowland et al., 2017). The VP receives major inputs from the nucleus accumbens, cortex, paraventricular thalamus (PVT), and basolateral amygdala (BLA) (Fig. 17.1). In turn, VP neurons project to many regions including the nucleus accumbens, midbrain neurons, the subthalamic nucleus (STN), the lateral hypothalamus, and the LHb. The VP can be roughly divided into rostrocaudal and medial lateral subregions (Root et al., 2015). These two are differentially associated with distinct aspects of seeking alcohol and other drugs as well as natural rewards (Leung & Balleine, 2013; Mahler et al., 2014; Prasad & McNally, 2016). These two subregions also have distinct patterns and profiles of anatomical connectivity, allowing distinct corticostriatal and amygdalostriatal circuits to interface with segregated transpallidal channels linking with distinct midbrain regions (Groenewegen, Berendse, & Haber, 1993; Zahm & Heimer, 1990) (Fig. 17.1). It is well established that the core region of the nucleus accumbens (AcbC) preferentially projects to lateral VP, whereas the shell region of the nucleus accumbens (AcbSh) preferentially projects to medial VP (Groenewegen et al., 1993; Tripathi, Prensa, Cebria´n, & Mengual, 2010; Zahm, Williams, &

Wohltmann, 1996). Accumbens projection neurons are GABAergic medium spiny neurons (MSNs) that can be subdivided into dopamine 1 (D1) or dopamine 2 (D2) receptors expressing populations that differentially regulate motivated behaviors (Lobo et al., 2010; Stefanik, Kupchik, Brown, & Kalivas, 2013). Classically, D1 MSNs project directly to the substania nigra (direct pathway), whereas D2 MSNs project to the nigra via the VP (indirect pathway). However, recent studies show that the role of VP in alcohol consumption, relapse and motivated behavior is more complex than a simple D1 versus D2 receptor input dichotomy. For example, D1 and D2 MSNs from the AcbC innervate the dorsal VP (Kupchik et al., 2015). Both MSN subtypes also innervate the ventromedial VP where approximately 50% VP neurons are innervated by both MSN populations (Creed, Pascoli, & Luscher, 2015; Kupchik et al., 2015). Stimulation of D1 and D2 input to VP can resulted in synaptic plasticity of these inputs with some evidence for opposing contributions of D1-VP and D2-VP inputs to distinct motivational consequences of drug experience. It is important to note that despite receiving extensive inputs from the nucleus accumbens, VP is more than just a passive integrator of ventral striatal inputs. In a cue-evoked, sucrose-seeking behavior task, electrophysiological recordings showed that VP neurons responded at shorter latencies to reward cues than accumbens neurons (Richard, Ambroggi, Janak, & Fields, 2016). VP neurons also project to the nucleus accumbens. Little is known about the anatomical and functional role of these VP projections to accumbens, but they are likely important for alcohol consumption and relapse to alcohol seeking. VP receives extensive inputs from the thalamus and amygdala. PVT, located in the dorsal midline thalamus, provides major glutamatergic inputs to the VP (Root et al., 2015). This input may be especially relevant to relapse to alcohol seeking because PVT lesions had no effect on alcohol consumption or responding for alcohol, but did reduce relapse to alcohol seeking after a period of extinction training (Hamlin, Clemens, Choi, & McNally, 2009). PVT neurons projecting to the VP are significantly recruited during this relapse (Perry & McNally, 2013). BLA also sends glutamatergic projection to VP. There is some evidence that these BLA inputs favor VP cholinergic neurons (Nickerson Poulin, Guerci, Mestikawy, & Semba, 2006), but they also project to other VP neuronal subtypes. The function of BLA inputs to VP function remain poorly understood. BLA neurons are active during relapse to seeking alcohol (and other drug as well as nondrug rewards) (Hamlin, Blatchford, & McNally, 2006; Hamlin, Clemens, & McNally, 2008; Hamlin, Newby, & McNally, 2007), including BLA neurons projecting

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VENTRAL PALLIDUM AND ALCOHOL CONSUMPTION

to VP (Perry & McNally, 2013). This could imply an important role for BLA inputs to VP cholinergic neurons in regulating relapse to alcohol seeking, but this remains to be established. There are three major outputs of the VP relevant to understanding its role in alcohol consumption and relapse (Fig. 17.1). First, VP is a major input to the STN. This projection is of special importance for alcohol use. STN manipulations can reduce motivation for alcohol in high-drinking rats (Lardeux & Baunez, 2007) and VP inputs to the STN contribute to the motivation to consume alcohol (Prasad & McNally, 2016). This function is shared across drug classes because high frequency stimulation or STN lesions reduces motivation for drugs of abuse, including cocaine and methamphetamine. Second, VP also projects extensively to the lateral hypothalamus, a region long implicated in reward and motivation (Marchant, Millan, & McNally, 2011) and there is evidence that this projection emerges preferentially from VP GABAergic neurons (Root et al., 2015). Interestingly, GABAergic neurons from the immediately dorsal ventral bed nucleus of the stria terminalis also project to LH where they control appetitive behavior (Jennings, Rizzi, Stam’takis, Ung, & Stuber, 2013). These VP inputs to the LH may be especially important in hedonic evaluations of alcohol (see later). Finally, the VTA and adjacent substantia nigra are key targets of VP projections. VP projections to the VTA emerge mostly from the ventromedial aspects of the VP and they contribute to the motivation to respond to, and consume, alcohol as well as different forms of relapse to alcohol seeking (Prasad & McNally, 2016).

VENTRAL PALLIDUM AND ALCOHOL CONSUMPTION The VP serves an important role in controlling consumption of alcohol and other drugs. Led by the seminal work of Kalivas and colleagues, it is well established that self-administration of ethanol, heroin, cocaine, and amphetamine all decrease extracellular levels of the inhibitory neurotransmitter GABA in the VP (Bourdelais & Kalivas, 1990; Caille & Parsons, 2004; Kemppainen, Raivio, & Kiianmaa, 2012; Kemppainen, Raivio, Nurmi, & Kiianmaa, 2010; Tang, McFarland, Cagle, & Kalivas, 2005). Alcohol consumption in animal models is due to both GABA and opioid mechanisms because VP applications of GABAA or mu-opioid receptor agonists decrease ethanol consumption whereas antagonizing these receptors increases ethanol consumption (Kemppainen et al., 2012; Kemppainen, Raivio, Suo-Yrjo, & Kiianmaa, 2011). Because the input to VP from nucleus accumbens comes from

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FIGURE 17.2 Inhibition of the nucleus accumbens (Acb) input to ventral pallidum is a key mechanism for drug reinforcement. The accumbens input to ventral pallidum releases GABA and opioids (notably, enkephalin) that bind to GABA receptors and mu-opioid receptors respectively. Alcohol, and other drugs of abuse, inhibit these accumbens inputs, depressing extracellular GABA and opioid levels in the ventral pallidum.

GABAergic MSNs that frequently co-express enkephalin (an endogenous opioid peptide acting at the muopioid receptor), and several effects of drugs of abuse are linked to GABA and opioid actions in the VP (Austin & Kalivas, 1990), these findings are often interpreted to mean that drug-induced inhibition of nucleus accumbens inputs to VP and the subsequent depression of extracellular GABA and opioid levels in the VP is a key neural mechanism for the reinforcing properties of alcohol and other drugs (Fig. 17.2) (Kalivas, Churchill, & Romanides, 1999). Indeed, consistent with the idea that a release from GABAergic inhibition in the VP underpins drug reinforcement, motivation to respond to, and consume, alcohol is increased by increasing the activity of VP neurons and can be decreased by decreasing the activity of VP neurons (Prasad & McNally, 2016). However, it is likely that this role for VP in alcohol consumption, summarized in Fig. 17.2, is more complex still. For example, the VP receives a rich and diverse set of inputs from many regions, not just the nucleus accumbens. Moreover, VP is linked to multiple features of drug reinforcement. One set of findings of particular relevance to alcohol addiction comes from work by Berridge and colleagues that identifies VP as part of an interconnected network controlling hedonic reactions to tastes (Castro, Cole, & Berridge, 2015). Caudal parts VP are important for normal hedonic responses to palatable tastes so that disruption of these parts of VP causes preferred and palatable tastes to be

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disliked and treated as aversive (Ho & Berridge, 2014). This role for VP in palatability and hedonic evaluations is due to mu-opioid systems in the VP as well as orexin inputs to VP from the lateral hypothalamus. For example, microinjections of mu-opioid receptor agonists (Smith, Tindell, Aldridge, & Berridge, 2009) or microinjections of orexin (Ho & Berridge, 2013) into the VP profoundly amplify positive hedonic responses to palatable substances, such as sucrose. This role for VP in regulating hedonic responses is important because alcohol is relatively unique among the drugs abused by humans due its oral ingestion, distinctive gustatory properties, and often strong preferences among drinkers for specific alcoholic beverages, with these preferences differing between genders and across life spans.

VENTRAL PALLIDUM AND RELAPSE In addition to its role in regulating consumption of alcohol and other drugs, VP serves a key role in controlling relapse to seeking alcohol and other drugs after a period of extinction or abstinence. It is important to note that although this role may overlap with the role of VP in alcohol consumption, it can also be dissociated from it. More interestingly, this role is shared across a variety of drugs of abuse independently of the mode of self-administration. Kalivas and colleagues were the first to establish VP as a critical node in the neural circuitry for relapse to drug seeking. The role of VP was initially revealed for psychostimulants, such as cocaine (McFarland & Kalivas, 2001; McFarland, Davidge, Lapish, & Kalivas, 2004; Tang et al., 2005; Torregrossa & Kalivas, 2008), but is well established for other drugs, including heroin (Rogers, Ghee, & See, 2008) and alcohol (Perry & McNally, 2013). Microinjections of mu-opioid receptors antagonists (Perry & McNally, 2013; Tang et al., 2005), pharmacological inactivation (McFarland et al., 2004; McFarland & Kalivas, 2001), or chemogenetic silencing (Mahler et al., 2014; Prasad & McNally, 2016) of VP prevent various forms of reinstatement of cocaine or alcohol seeking in rats. The finding that VP contributes to relapse precipitated by discrete environmental cues fits well with recent work showing that VP neurons are responsive to, and encode distinct features of, reward-related cues (Ahrens, Meyer, Ferguson, Robinson, & Aldridge, 2016; Richard et al., 2016). Much remains to be learnt about the neurocircuitry for these VP contributions to relapse. VP receives projections from numerous regions, including the cortex, Acb, PVT, STN, VTA, and BLA, and these projections differentially target the ventromedial (VPvm) and dorsolateral (VPdl) regions of VP. A variety of lines of

evidence implicate projections from AcbC to VP, which preferentially target VPdl, in reinstatement. These include prevention of relapse by pharmacological disconnection (McFarland & Kalivas, 2001) or optogenetic silencing (Khoo, Gibson, Prasad, & McNally, 2015; Stefanik et al., 2013) of the AcbC - VP pathway. The neurotransmitter GABA and neuropeptide neurotensin are important in this pathway (Torregrossa & Kalivas, 2008) as are the actions of mu-opioid receptors (Napier & Mitrovic, 1999). This evidence of a role of VP in multiple forms of reinstatement, and the roles for striatopallidal projections in other aspects of reward-seeking behavior (Leung & Balleine, 2013), support the view that cortical striatal pallidal connectivity is a key route for relapse to drug seeking across many drug classes (Kalivas & Volkow, 2005, 2011). We have mapped activated inputs to VP during context-induced reinstatement of alcohol seeking and found recruitment of not just an AcbC -VP pathway, but also of rostral BLA -VP, and PVT -VP pathways (Perry & McNally, 2013). Both BLA (Fuchs, Eaddy, Su, & Bell, 2007) and PVT (Hamlin et al., 2009) are necessary for context-induced reinstatement of alcohol seeking, but whether they achieve these roles via direct projections to the VP remains to be determined. Regardless, this convergence of activated striatal, thalamic, and amygdala inputs in VP during reinstatement of alcohol seeking, the sensitivity of these inputs (Napier & Mitrovic, 1999) as well as relapse to alcohol consumption in animal models and humans to muopioid receptor manipulations, suggests that the role for VP in relapse to alcohol seeking is likely to be more complex, and more fundamental, than simply relaying ventral striatal generated signals. The VP efferents important for reinstatement of alcohol seeking include the STN and VTA. Projections from the VP to the STN, as well as separate projections from the VP to the VTA mediate reinstatement of alcohol seeking (Prasad & McNally, 2016). As noted above, these VP output pathways also contribute to motivation to consume alcohol. The role of VP projections to STN in relapse is important because STN manipulations reduce motivation to consume alcohol as well as cocaine (Lardeux & Baunez, 2007; Pelloux & Baunez, 2013; Rouaud et al., 2010) and relapse to methamphetamine seeking (Baracz, Everett, & Cornish, 2015). Given the diversity of afferents to VP recruited during reinstatement, it is not surprising that multiple, segregated VP efferents are important for relapse. Despite being a common locus for different forms of relapse, fundamental features of these VP contributions remain poorly understood. VP consists of heterogeneous populations of GABAergic, glutamatergic, and cholinergic neurons. These neurons also express various peptides and neurotransmitters including

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MINI-DICTIONARY OF TERMS

calretinin, enkephalin, dynorphin calbindin, parvalbumin, neuropeptide Y, or somatostatin (Root et al., 2015). Adding further complexity, some of these populations are dynamically regulated by exposure to drugs of abuse, whereas others are not. The roles of these specific population(s) of VP neurons and other major VP output pathways in relapse to seeking alcohol remains to be understood.

VENTRAL PALLIDUM AND TARGETED TREATMENTS FOR ALCOHOL ADDICTION The preclinical studies show that VP serves a key role in regulating alcohol consumption as well as various forms of relapse to alcohol seeking. Within the VP, manipulations of GABA, neurotensin, D1/D2, glutamate and mu-opioid signaling affects several aspects of alcohol and other drug seeking. It is not surprising then, that VP and its associated neural networks are strong candidates for targeted treatments for alcohol addiction. Here we identify two such applications. First, mu-opioid receptor antagonists remain among the most effective pharmacotherapies for alcohol abuse (Anton et al., 2006; Connor, Haber, & Hall, 2016). The role of VP in the therapeutic efficacy of naltrexone against alcohol addictions remains poorly understood. VP and its mu-opioid receptor systems are parts of an extended neural network controlling palatability and hedonic responses. Moreover, antagonizing mu-opioid receptor systems in the VP is an effective strategy for reducing relapse to alcohol and other drugs of abuse. However, it is not known whether mu-opioid receptor antagonists achieve these antirelapse effects in animals, and derive any of their therapeutic efficacy in humans, from their effects on VP networks for hedonics. Insights into the mechanisms for naltrexone’s therapeutic efficacy against alcohol addiction would not only be of basic scientific and clinical importance, but could guide new strategies to augment this efficacy. Second, in humans, VP is part of the limbic pallidum which includes the external GP segment (GPe), and internal GP (GPi). Human studies show that the GPi is particularly susceptible to hypoxic ischemic injury caused by substance abuse. A case study using MRI showed bilateral infarcts of the internal segment of the globus pallidus (GPi) after methadone overdose. Since the overdose episode, the patient reduced craving and drug seeking for alcohol and opiates and has been abstinent for 10 years (Moussawi, Kalivas, & Lee, 2016). Deep brain stimulation (DBS) of GPi is approved by the Food and Drug Administration for treatment of Parkinson’s disease and DBS in other brain regions has been applied to the treatment of obsessive compulsive

disorders, depression and Parkinson’s disease (Graat, Figee, & Denys, 2017). There are several advantages of DBS including targeting of specific brain region, its adjustable frequency and reversibility. However, little is known about its mechanism of action as well optimal parameters for efficacy. DBS studies in animal models of drug addiction have targeted the major afferents and efferents of the VP, such as the ventral striatum and STN, but not as yet the VP itself. Nonetheless, these studies have yielded interesting findings. For example, STN DBS manipulations can reduce motivation for alcohol in high-drinking rats (Pelloux & Baunez, 2013). Ventral striatum has been targeted using DBS during extinction of an opiate conditioned place preference. High frequency (100Hz) stimulation impaired extinction learning whereas low frequencies (20Hz) enhanced extinction learning (Martı´nez-Rivera et al., 2016). Other work has mapped specific DBS protocols to reverse nucleus accumbens synaptic plasticity caused by exposure to cocaine (Creed, 2017; Creed et al., 2015).

CONCLUSIONS A strong body of preclinical research has identified roles for the VP in alcohol consumption as well as relapse to alcohol seeking. This role is shared across several drugs of abuse, most notably psychostimulants, such as cocaine. Despite occupying a key location in striatopallidal output pathways, VP is more than just a passive relay from ventral striatum. It is a complex and diverse structure allowing cortical, thalamic, amygdala, corticostriatal, and amygdalostriatal circuits to interface with distinct midbrain regions. The preclinical research reviewed here, combined with recent advances in technologies, suggest a hopeful future for clinical targeting of VP in treatment of alcohol addictions. However, there is significant functional compartmentalization and segregation within the VP that parallels its anatomical segregation into distinct circuits and channels. If the clinical benefit of this preclinical work is to be realized, then a better understanding of how these circuits and channels are organized, and how different modes of activity of groups of cells within them promote alcohol intake as well as relapse, is needed.

MINI-DICTIONARY OF TERMS Deep brain stimulation Electrical stimulation of neural tissue via surgically implanted electrodes. Extinction training The reduction in self-administration behavior where responses no longer cause delivery of alcohol.

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Relapse Return to alcohol consumption after a period of abstinence. Reinstatement An animal model of relapse-like behavior which involves the return of a previously extinguished behavior. This may be precipitated by drug-priming, reward-associated cues, contexts or stress. Self-administration Animal model of drug taking where responses (e.g., lever press) causes delivery of alcohol or another drug. Ventral striatum Collection of nuclei that include the nucleus accumbens core, nucleus accumbens shell (medial and lateral), and olfactory tubercle.

KEY FACTS Ventral Pallidum • Ventral pallidum is located in basal ganglia. • It receives inputs from cortex, amygdala, thalamus, as well as striatum and projects to ventral tegmental area, substantia nigra, subthalamic nucleus, and lateral hypothalamus. • Ventral pallidum contains distinct cell types and subregions and is organized into discrete channels. • Ventral pallidum serves a central role in regulating consumption of alcohol and other drugs of abuse. • Ventral pallidum is also a key structure controlling relapse to alcohol seeking

SUMMARY POINTS • This chapter focuses on the ventral pallidum, a basal ganglia structure, and its role in consumption and relapse to alcohol and other drug seeking as well as its potential as a therapeutic target for alcohol addiction. • The VP is a heterogeneous structure, segregated on its anatomy and neurochemistry. It receives major inputs from the nucleus accumbens, cortex, paraventricular thalamus and basolateral amygdala. In turn, VP neurons project to many regions including nucleus accumbens, midbrain neurons, the subthalamic nucleus, the lateral hypothalamus, and the lateral habenula. • A strong body of preclinical research identifies roles for VP in consumption of alcohol and other drugs. This is linked to inputs from the nucleus accumbens core. The VP also serves a key role in relapse to alcohol seeking. This role is shared across several drugs of abuse, most notably psychostimulants, such as cocaine, and is due to inputs from several brain regions (accumbens, amygdala, cortex) and outputs (ventral tegmental area subthalamic nucleus). • Inhibition of the nucleus accumbens input to ventral pallidum is a key mechanism for drug reinforcement. The accumbens input to ventral

pallidum releases GABA and opioids that bind to GABA receptors and mu-opioid receptors, respectively. Alcohol, and other drugs of abuse, inhibit these accumbens inputs, depressing extracellular GABA and opioid levels in the ventral pallidum. • Translational work identifies VP as an obvious locus for the therapeutic efficacy of naltrexone against alcohol addictions and also as a potential target for therapeutic deep brain stimulation against alcohol addictions.

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18 The Hyperpolarization-Activated Cyclic Nucleotide-Gated Ion Channels in the Rewarding Effects of Ethanol Mario Rivera-Meza Laboratory of Experimental Pharmacology, Department of Pharmacological and Toxicological Chemistry, Faculty of Chemical Sciences and Pharmacy, University of Chile, Santiago, Chile

LIST OF ABBREVIATIONS HCN Ih cAMP CNBD CNS CPP HPLC-EC NAcc VTA

hyperpolarization-activated cyclic nucleotide-gated hyperpolarization-activated current cyclic adenosine monophosphate cyclic nucleotide binding domain central nervous system conditioned place preference high-performance liquid chromatography-electrochemical detection nucleus accumbens ventral tegmental area

INTRODUCTION The ventral tegmental area (VTA) of the dopamine mesolimbic system contains dopaminergic neurons that project their axons to the nucleus accumbens (NAcc), amygdala, and prefrontal cortex. In vivo studies have shown that natural rewards such sexual pleasure and food consumption can activate the dopaminergic mesolimbic system resulting in an increase in the extracellular dopamine levels in the NAcc (Mirenowicz & Schultz, 1996). It is well established that ethanol and other drugs of abuse that elicit reward and dependence (e.g., cocaine, amphetamine, or nicotine) increase dopamine release in mesolimbic regions, showing the relevance of dopamine increase in the rewarding effects elicited by these substances and, therefore, their addictive properties. Studies performed in rats have showed that upon Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00018-0

systemic ethanol administration, an increase in extracellular dopamine levels can be seen in the NAcc (Imperato & Di Chiara, 1986). Further studies have shown that rats genetically selected for their highethanol intake will self-administer ethanol through a guide cannula implanted into the VTA (Rodd et al., 2005), highlighting the relevance of the mesolimbic system activation in the rewarding effects of ethanol. Moreover, the intravenous administration of ethanol to rats enhances the firing rate of the VTA dopaminergic neurons, which results in an increase of dopamine release in NAcc (Foddai, Dosia, Spiga, & Diana, 2004). In agreement with the relevance of dopamine in the rewarding properties of ethanol, the administration of dopamine antagonist, either systemically or locally into the NAcc, suppresses ethanol-reinforced behaviors such as ethanol intake and ethanol selfadministration (Samson, Hodge, Tolliver, & Haraguchi, 1993). In vivo microdialysis studies in alcohol-preferring UChB rats have shown lower basal levels of dopamine in the NAcc in drinker rats compared to those found in rats that do not prefer the consumption of ethanol solutions to water (Quintanilla, Tampier, Sapag, Gerdtzen, & Israel, 2007). Furthermore, the ethanolinduced release of dopamine in the NAcc of alcoholpreferring UChB rats is higher than that observed in nonpreferring rats (Bustamante et al., 2008), suggesting that differences in dopamine signaling may underlie the differential voluntary ethanol consumption showed by these lines of rats.

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© 2019 Elsevier Inc. All rights reserved.

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THE HYPERPOLARIZATION-ACTIVATED CYCLIC NUCLEOTIDE-GATED IONIC CHANNELS Dopamine neurons are recognized for showing a spontaneous activity, which is independent of their synaptic input drive (Grace & Bunney, 1983). This pacemaker activity is maintained by an inward cation depolarizing current, denominated Ih, which is activated during the membrane hyperpolarization phase (Fig. 18.1). This cationic (Na1, K1) depolarizing current, originally identified in cardiac sinoatrial node cells (Brown & Difrancesco, 1980), sets the membrane potential to further positive (depolarizing) voltages, close the activation threshold of T-calcium channels, resulting in a continuous firing of the cells (see Pape, 1996). The ion channels responsible of the Ih current were identified some decades ago (Gauss, Seifert, & Kaupp, 1998; Ishii, Takano, Xie, Noma, & Ohmori, 1999; Ludwig, Zong, Jeglitsch, Hofmann, & Biel, 1998) and were called “hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channels” due to their dual mode of activation. HCN ion channels show three

AP

major characteristics: (1) channel activation by membrane hyperpolarization (in essence correcting a hyperpolarization); (2) enhancement of channel activity because the binding of intracellular cyclic adenosine monophosphate (cAMP) to the cyclic nucleotide binding domain (CNBD); and (3) nonspecific inward permeation to Na1 and K1 ions (DiFrancesco, 1999) (Fig. 18.2). HCN channels, widely expressed in the heart and the central nervous system (CNS), are encoded by four genes (HCN1 4) showing 60% of sequence homology with each other. Studies performed in rat brain have shown that the four isoforms of HCN channels are expressed in the CNS, but their relative abundance and distribution pattern show important differences. The HCN2 isoform shows the most extensive expression and is found in the whole brain, while the HCN1 isoform is expressed mainly in the cortex and hippocampus. The expression of the HCN4 variant is more abundant in the thalamus and basal ganglia, whereas HCN3 shows the lowest relative expression among the four variants of HCN channels. Regarding the mesolimbic system, in situ hybridization and immunohistochemical studies have shown that both the HCN2 and HCN1 isoforms are expressed in NAcc, but the HCN2 variant displays the highest level of expression in the VTA (Monteggia, Eisch, Tang, Kaczmarek, & Nestler, 2000; Notomi &

20

Voltage (mV)

INa IK

–20

–60

AHP –100

0

Ih 50

100 Time (ms)

150

FIGURE 18.1

Neuronal pacemaker activity is controlled by the hyperpolarization-activated cation current (Ih). The combined action of fast sodium (INa) and delayed rectifier potassium (IK) currents are responsible for the action potential (AP). After membrane hyperpolarization (AHP), Ih current slowly depolarizes the membrane potential triggering a new AP and maintaining pacemaker activity. Source: Modified from Wechselberger M., Wright C. L., Bishop G. A., Boulant J. A. (2006). Ionic channels and conductance-based models for hypothalamic neuronal thermosensitivity. American Journal of Physiology. Regulatory, Integrative and Comparative Physiology, 291, R518 R529 (Wechselberger, Wright, Bishop, & Boulant, 2006) with permission of the publishers.

FIGURE 18.2

Structure of HCN channels. HCN channels are tetramers. One monomer is composed of six transmembrane segments including the voltage sensor (S4) and the pore region between S5 and S6. The COOH-terminal channel domain is composed of the C-linker and the cyclic nucleotide-binding domain (CNBD). Source: From Postea, O. & Biel, M. (2011). Exploring HCN channels as novel drug targets. Nature Reviews. Drug Discovery, 10, 903 914 (Postea & Biel, 2011) with permission of the publishers.

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Shigemoto, 2004). The different subunits can assemble to form functional homo- or hetero-tetramers in vitro, but the specific stoichiometry of hetero-tetramers in vivo is not completely known (Sartiani, Mannaioni, Masi, Romanelli, & Cerbai, 2017).

HYPERPOLARIZATION-ACTIVATED CYCLIC NUCLEOTIDE-GATED ION CHANNELS AND ETHANOL ACTIONS Experimental evidence supports the hypothesis that HCN channels present in dopamine neurons are targets for ethanol action. Using isolated dopamine VTA neurons from Fisher 344 rats, Brodie, Pesold, and Appel (1999) showed that incubation with ethanol (20 120 mM) increases the firing rate of VTA dopamine neurons in all tested concentrations and produced a change in the shape of the spontaneous action potential, in agreement with an enhancement of the Ih current. Several investigations have further shown that HCN blockers, such ZD7288 or cesium salts, are able to block the stimulatory effects of ethanol on Ih current and the firing rate of dopamine neurons (McDaid, McElvain, & Brodie, 2008; Okamoto, Harnett, & Morikawa, 2006). In agreement with those findings, earlier studies by Messiha (1978) showed that the systemic administration of cesium salts to ethanol preferring rats at doses of 3.0 mEq/kg/day reduced their voluntary ethanol intake for weeks. A study by Beckstead and Phillips (2009) showed that mice selectively bred for their high-ethanolinduced locomotor activity have and increased density of HCN channels in dopaminergic neurons compared to mice selected for low locomotor response to ethanol, suggesting a potential role of HCN channels in the stimulatory effects of ethanol. Another relevant finding is that the repeated exposure of mice to intoxicating levels of ethanol reduces the baseline density of HCN channels in dopamine neurons and also reduces the ability of ethanol to increase dopamine neuron firing rates (Okamoto et al., 2006). These results suggest that changes in the levels of HCN expression may be involved in the development of tolerance to ethanol effects. A computational modeling study of the activity of dopaminergic neurons in vivo, suggests that ethanol, through its effects on HCN channels, would change the firing patterns of these neurons from their basal pacemaker activity to a bursting pattern, resulting in an increase in the terminal dopamine release (Migliore, Cannia, & Canavier, 2008). An electrophysiological study in VTA slices of Wistar rats developed by Tateno and Robinson (2011), demonstrated that pharmacological concentrations of ethanol (55 mM) enhance the firing of VTA dopamine cells. These

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stimulatory effects of ethanol were reversed by the administration of the nonselective HCN blocker ZD7288. The same investigators demonstrated that these effects of ethanol on HCN channels were not restricted to dopamine neurons. Indeed, they showed that ethanol, through its action on HCN channels present in GABAergic neurons, generate important changes in the inhibitory effects exerted by GABA on VTA dopamine neurons. Further evidence demonstrating the effects of ethanol on HCN channels, was provided recently by Chen et al. (2012) using sinoatrial node cells isolated from rabbit heart. They showed that incubation of those cells with a range of concentration of ethanol able to be attained during ethanol intoxication (1 100 mM) resulted in a dose-dependent increase of the spontaneous firing of the cells; such type of effect was markedly reduced by the administration of ivabradine, a nonselective blocker of HCN channels. In a recent study, Rivera-Meza et al. (2014) developed lentiviral vectors encoding the rat gene for the HCN2 channel isoform. This lentiviral vector was administered by stereotaxic surgery into the posterior VTA (pVTA) of alcohol-preferring UChB rats that were naı¨ve for ethanol drinking, resulting in a twofold increase of HCN2 expression, measured by Western blot (Fig. 18.3). When these animals were exposed daily to a free choice paradigm between water and 5% ethanol, they showed a marked increase of 100% in their voluntary ethanol intake compared to rats treated with a control lentiviral vector (Fig. 18.4). In the same experiment, the investigators studied whether the overexpression of HCN2 could modify the rewarding effects of ethanol by measuring the ethanol-induced conditioned place preference (CPP). Results showed that animals overexpressing the HCN2 channel in the pVTA displayed a threefold increase of ethanolinduced CPP, while animals treated with the control vector did not show a significant increase (Fig. 18.5). Finally, they studied if the increased rewarding effects elicited by ethanol in the animals overexpressing HCN2 channels into the pVTA were correlated with changes on ethanol-induced dopamine release in the mesolimbic system. Results showed that rats transduced with the lentiviral vectors coding for HCN2 displayed higher levels of dopamine in the NAcc after an acute dose of ethanol (1 g/kg; i.p.) compared with those animals treated with a control lentiviral vector (Fig. 18.6). These in vivo results add further support to the hypothesis that HCN channels in the VTA are a target of ethanol or have an important role in mediating its pharmacological effects. The mechanisms by which ethanol can activate HCN channels are unknown, but considering the voltage-dependent activation of this type of ionic

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FIGURE 18.3 Lentiviral-mediated overexpression of HCN2 channels into the pVTA of UChB rats. Western blot analysis of HCN2 levels in the pVTA of UChB rats administered intra-VTA with lentiviral vectors coding for HCN2 channel (LV-rHCN2-GFP) or control (LV-GFP). Source: Modified from Rivera-Meza, M., Quintanilla, M. E., Bustamante, D., Delgado, R., Buscaglia, M., Herrera-Marschitz, M. (2014). Overexpression of hyperpolarization-activated cyclic nucleotidegated channels into the ventral tegmental area increases the rewarding effects of ethanol in UChB drinking rats. Alcoholism, Clinical and Experimental Research, 38, 911 920 with permission of the publishers.

FIGURE 18.4

Overexpression of HCN2 ion channel into the pVTA of UChB rats increases voluntary ethanol consumption. Ethanol-naı¨ve UChB rats administered intra-VTA with lentiviral vectors coding for HCN2 channel (LV-rHCN2-GFP) or control (LV-GFP) were exposed to a free choice drinking paradigm between 5% ethanol and water during 30 days. Source: Modified from Rivera-Meza, M., Quintanilla, M. E., Bustamante, D., Delgado, R., Buscaglia, M., Herrera-Marschitz, M. (2014). Overexpression of hyperpolarization-activated cyclic nucleotide-gated channels into the ventral tegmental area increases the rewarding effects of ethanol in UChB drinking rats. Alcoholism, Clinical and Experimental Research, 38, 911 920 with permission of the publishers.

FIGURE 18.5 Overexpression of HCN2 ion channel into the pVTA of UChB rats increases ethanol-induced conditioned place preference. UChB rats treated intra-VTA CPP with lentiviral vectors coding for HCN2 channel (LVrHCN2-GFP) or control (LV-GFP) and exposed to a free choice between 5% ethanol and water during 30 days were subjected to an ethanol-induced conditioned place preference study. Source: Modified from Rivera-Meza, M., Quintanilla, M. E., Bustamante, D., Delgado, R., Buscaglia, M., Herrera-Marschitz, M. (2014). Overexpression of hyperpolarization-activated cyclic nucleotide-gated channels into the ventral tegmental area increases the rewarding effects of ethanol in UChB drinking rats. Alcoholism, Clinical and Experimental Research, 38, 911 920 with permission of the publishers.

channels, it is highly probable that those mechanisms are indirect. Since HCN ionic channels activation is enhanced by the binding of intracellular cAMP to the CNBD, a plausible explanation for the activating effects of ethanol on HCN channels could be addressed to the ability of ethanol to increase

intracellular levels of cAMP (see Newton & Messing, 2006). In effect, Okamoto et al. (2006) found in mouse dopamine neurons, that ethanol facilitates the voltage gating of HCN channels in a cAMP-dependent fashion, resulting in a shift of the activation voltage of the ionic channel to more positive values. Interestingly,

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FIGURE 18.6 Overexpression of HCN2 ion channel into the pVTA of UChB rats increases the ethanol-induced release of dopamine in the NAcc. UChB rats treated intra-VTA with lentiviral vectors coding for HCN2 channel (LVrHCN2-GFP) or control (LV-GFP) and exposed to a free choice between 5% ethanol and water during 30 days were administered with a single dose of ethanol (1 g/kg). The extracellular levels of dopamine in the NAcc were measured by microdialysis coupled to HPLC-EC detection. Source: Modified from Rivera-Meza, M., Quintanilla, M.E., Bustamante, D., Delgado, R., Buscaglia, M., Herrera-Marschitz, M. (2014). Overexpression of hyperpolarization-activated cyclic nucleotide-gated channels into the ventral tegmental area increases the rewarding effects of ethanol in UChB drinking rats. Alcoholism, Clinical and Experimental Research, 38, 911 920 with permission of the publishers.

a confocal patch clamp study in oocytes has shown that HCN2 subunits display the highest sensitivity to the activating effects of intracellular cAMP binding (Kusch et al., 2011). Regarding the mechanism by which ethanol could enhance the generation of cAMP in neurons, in vitro studies in neuroblastoma cells have shown that cell exposure to ethanol results in an increased cAMP production; action that has been associated to an indirect activation of adenosine A2a receptors (Nagy, Diamond, Casso, Franklin, & Gordon, 1990). In this regard, whole-cell patch clamp studies in rat VTA dopamine neurons have shown that baclofen, an agonist of GABAB receptors that reduce the intracellular levels of cAMP, is able to reduce the hyperpolarization-induced current mediated by HCN channels (Jiang, Pessia, & North, 1993). Indeed, preclinical and clinical studies have demonstrated the effectiveness of baclofen to modulate alcohol-related behaviors, allowing its approval for the treatment of alcohol dependence in France (See Soyka & Mu¨ller, 2017). Another mechanism by which ethanol could regulate intracellular cAMP levels involves the stimulation of specific isoforms of adenylyl cyclase (Yoshimura & Tabakoff, 1995). Indeed, knock-out mice lacking the AC1 and AC8 isoforms of adenylyl cyclase showed reduced voluntary ethanol consumption in comparison to wild-type animals (Maas et al., 2005). HCN channels have been also implicated with the action of other drugs of abuse like nicotine, cocaine and cannabinoids. Studies in Sprague Dawley rats have shown that cocaine-induced locomotor sensitization is correlated with a significant increment of the Nglycosylated isoform of HCN2 channels in the VTA (Santos-Vera et al., 2013), being N-glycosylation of HCN2 channel an important factor for the generation

of functional channels on neuron membrane surface (Zha, Brewster, Richichi, Bender, & Baram, 2008). In a recent study, Gonza´lez et al. (2016) showed that a marked increase in HCN2 channel levels is observed in the mesolimbic system of mice that were subchronically administered with methamphetamine (1 mg/kg, 7 days) and subjected to 4 days of withdrawal. In addition, animal experiments have shown that HCN channels are necessary for the synaptic plasticity elicited by cannabinoids through its action on cannabinoid receptors type 1, since the pharmacological blockade of HCN channels reduces the cannabinoid-induced effects on long term potentiation and memory (Maroso et al., 2016). These results highlight the relevance of HCN channels in the neuronal functional changes associated to psychostimulant addiction.

HYPERPOLARIZATION-ACTIVATED CYCLIC NUCLEOTIDE-GATED ION CHANNELS AND CARDIAC FUNCTION In the heart, HCN channels control the spontaneous depolarization of the sinus node and, therefore, commands the heart rate. In cardiac tissue, HCN channels exhibit a heterogeneous distribution, being the sinoatrial node and the conduction system the structures that exhibit the highest expression of this type of channels. Regarding the distribution of the different subunits, the HCN4 subunit is the most highly expressed isoform in sinoatrial node and Purkinje cells, while HCN2 and HCN1 isoforms show a lower abundance in these tissues (Huang, Yang, Yang, Zhang, & Ma, 2016). Electrophysiological studies have shown that HCN4 channels are responsible for 70% 80% of the hyperpolarization-activated current that control heart

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pacemaker activity, while the contribution of HCN2 channels for this current is only 20% (Baruscotti et al., 2011). Considering the activating effects of ethanol on HCN channels, it is possible that ethanol consumption could generate alterations in cardiac function because of the abnormally enhancement of hyperpolarizationactivated currents. Indeed, patch clamp studies in human cardiomyocytes have shown that the activation of HCN channels in cardiac regions different from the sinus node can elicit the generation of ectopic excitatory focus and potentially lead to cardiac arrhythmias (Stillitano et al., 2008). Furthermore, Aasebø (2001) found that acute ethanol-intoxicated patients display alterations in electrocardiogram recordings consistent with alterations in the function of the ionic channels responsible for the generation of action potentials in the heart. The author also concludes that these electrical alterations may be involved in the increased incidence of arrhythmias and mortality in alcoholics.

HYPERPOLARIZATION-ACTIVATED CYCLIC NUCLEOTIDE-GATED ION CHANNELS AS A DRUG TARGET Despite the important physiological functions supported by HCN channels, the development of pharmacological agents aimed at modifying its functionality is limited. There is only one nonselective HCN blocker, ivabradine, approved for its clinical use as heart rate lowering agent for the treatment of angina pectoris. In vitro experiments have shown that ivabradine blocks with a similar affinity both HCN4 and HCN1 isoforms, but differences in the blockade mechanism which depend on the state of activation of the channel have been identified (Bucchi, Tognati, Milanesi, Baruscotti, & DiFrancesco, 2006). Since ivabradine does not cross the blood brain barrier, its in vivo administration does not have any effect on neuronal HCN channels. However, visual side effects have been described as a transiently enhanced brightness in the visual field, which have been correlated with the blockade of HCN1 channels present in retinal cells (Savelieva & Camm, 2006). Other nonselective blockers of HCN channels such as ZD7288, zatebradine and cilobradine display similar pharmacodynamics properties to ivabradine, however their development have been limited to experimental tools for preclinical studying HCN functions. However, site-directed mutagenesis studies have allowed the identification of amino acid differences in the binding region of HCN1, HCN2 and HCN4 isoforms, leading to the possibility of developing new blockers with selectivity for specific isoforms of HCN channels (Cheng, Kinard, Rajamani, & Sanguinetti, 2007). Indeed, Del Lungo et al. (2012)

tested two new compounds derived from the structure of zatebradine (EC18 and MEL57A) in HEK-293 cells previously transfected with HCN4, HCN2, or HCN1 genes and also in guinea pig sinoatrial cells. Using electrophysiological recordings, the investigators demonstrated that EC18 showed a higher affinity for HCN4, while MEL57A displayed a 30-fold higher selectivity over HCN1. Regarding the HCN2 isoform, Melchiorre et al. (2010) described the synthesis of (R)-5, a phenylalkylamine-derived HCN blocker agent, which shows at low concentrations (2 µM), a higher affinity for HCN2 in comparison to HCN4 and HCN1 channels when expressed in HEK-293 cells. Considering the pharmacodynamic characteristics of (R)-5 and the relevance of HCN2 channels in the rewarding effects of ethanol, future drug developments will hopefully test in vivo if selective HCN2 blockers: (1) can cross the blood brain barrier; (2) reduce or block de central effects of ethanol; and (3) exert these effects without blocking HCN channels that control cardiac function. In summary, experimental evidence suggests that HCN channels could represent an important cellular mechanism mediating the in vivo pharmacological effects of ethanol. The development of new isoformselective blockers of HCN channels able to cross the blood brain barrier together appropriate animal models would provide additional evidence on the role of HCN channels in alcohol abuse and addiction.

MINI-DICTIONARY OF TERMS Blood brain barrier Semipermeable barrier formed by brain endothelial cells that separates blood from the CNS. Only lipophilic drugs are able to cross passively this barrier. Dopamine mesolimbic system Brain circuit composed by dopamine neurons that connects the midbrain with limbic structures. Its activation is associated to drug-induced reward and pleasure. Drug self-administration Behavioral procedure in which a subject (animal or human) performs an action resulting in the delivery of a dose of drug. A cue associated to the self-administration of a reinforcing drug can become in a conditioned reinforcer. In situ hybridization Laboratory technique used to detect specific sequences of DNA or RNA in cells or tissues. Its specificity relies on the use of target-complementary nucleic acids probes usually radioactive or labeled with fluorophores. Immunohistochemistry Laboratory technique used to detect specific proteins in cells or tissue samples. Target detection is able by using specific antibodies conjugated to an enzyme that, upon exposure to a suitable substrate, generates a detectable stain in the sample. Lentiviral vector Modified lentivirus used to integrate exogenous genetic sequences into the genome of cells. Lentiviral vectors lack genes allowing its pathogenic properties, but retain those necessary for cell entry and genome integration. Microdialysis Sampling technique used for the in vivo detection and quantification of neurotransmitters or small peptides. It relies

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REFERENCES

on the use of small probes equipped with a semipermeable membrane perfused with a physiological solution. Pacemaker activity Spontaneous electrical activity displayed for some type of cells that depolarizes membrane towards the voltage threshold of action potential. This spontaneous electrical activity is supported by the inward cationic current (Ih) which is activated during the hyperpolarization phase. Sinoatrial node cells Specialized cells located in the right atrium of the heart characterized for displaying spontaneous pacemaker activity. The electrical activity of these cells is transmitted through the myocardium via the conduction system allowing the coordinated contraction of the heart. Transfection Laboratory technique that allows the incorporation of genetic materials, usually plasmids, to cells. Cell permeabilization can be achieved using physical (electric field) or chemical agents (liposomes, calcium phosphate).

KEY FACTS • Ions are unable to cross cellular membranes by themselves. • Ion channels are transmembrane proteins that form a hydrophilic pore allowing the movement of ions between extra- and intracellular sides of the cell. • The direction of ion movement depends on its electrochemical gradient, which is function of ion concentration on both sides of the membrane, and cell membrane potential. • In general, ion channels are selective for cations (Na1, K1, Ca21) or anions (Cl2). • Depending on its type of gating, ion channels are classified as voltage-gated ion channels or ligandgated ion channels. • Voltage-gated ion channels are activated by changes of membrane potential. • Ligand-gated ion channels are activated by the binding of chemical ligands such as neurotransmitters (GABA, glutamate, acetylcholine) or intracellular signaling molecules (cAMP, ATP, Ca21).

SUMMARY POINTS • In vivo studies show that ethanol activates dopaminergic neurons of the mesolimbic reward system. • Dopaminergic neurons are characterized for display an autonomous activity, which is controlled by HCN channels. • Pharmacological studies show that the stimulating effects of ethanol on dopaminergic neurons are associated to the activation of HCN channels. • Pharmacogenetic studies show that higher levels of HCN2 isoform in the mesolimbic system relate with increased rewarding and stimulant effects of ethanol.

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• The mechanism by which ethanol activate HCN channels is unknown, but the modulation of intracellular cAMP levels is involved in this action. • The development of selective blockers of HCN channels able to cross de blood brain barrier will be useful to elucidate the role of HCN channels in ethanol effects.

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19 Neuroimmune Aspects of Alcoholism and Affective Comorbidity Sudan P. Neupane1,2,3

1

Norwegian National Advisory Unit on Concurrent Substance Abuse and Mental Health Disorders, Innlandet Hospital Trust, Brumunddal, Norway 2Norwegian Centre for Addiction Research (SERAF), University of Oslo, Oslo, Norway 3Bowles Center for Alcohol Studies, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

LIST OF ABBREVIATIONS AUD CNS CRP HMGB1 IFN-γ IL sIL-2 IL-1RA LPS MCP-1 NF-κB TLR TNF-α

alcohol use disorder central nervous system C-reactive protein high-mobility group box 1 interferon gamma interleukin soluble interleukin-2 interleukin 1 receptor antagonist lipopolysaccharide monocyte chemoattractant protein-1 nuclear factor kappa-light-chain-enhancer of activated B cells toll-like receptor tumor necrosis factor alpha

INTRODUCTION Alcohol is an immune modulating agent. Medical literature has long appreciated the immune suppressing effect of chronic heavy drinking. These evidences originate from the frequent clinical observations of increased susceptibility of individuals with alcohol use disorders (AUDs) to infections and cancers as well as delayed healing (Trevejo-Nunez, Kolls, & De Wit, 2015). Mechanisms such as poor diet, malabsorption and liver damage were believed to underlie alcoholinduced immune impairment. Updates in the field during the past three decades demonstrate that alcohol insults multiple arms of the body’s immune response

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00019-2

system (Szabo & Saha, 2015). Of particular significance is alcohol’s peripheral activation of immune cells, the signals of which ultimately relay to specific brain regions and induce neuropathology. AUD independently causes over 40 diseases and conditions while contributing to over 200 diseases, injuries, and conditions—including chronic debilitating diseases such as diabetes, cardiovascular diseases, cancer, depression, and dementia (Rehm et al., 2017; World Health Organization, 2014). One could wonder how alcohol drinking could potentially cause so many diseases with systemic aberrations and devastating consequences. One feature that stands out as a common underlying pathophysiology is inflammation. Chronic heavy drinking can cause inflammatory response in the periphery and in the central nervous system (CNS) (Coleman & Crews, 2018). Indeed, many of the comorbid conditions of AUD involve immune inflammatory changes as well. Neuroimmune defects can elicit the faulty neurotransmitter, neuroendocrine and autonomic functions as well as neurodegeneration (Kettenmann, Kirchhoff, & Verkhratsky, 2013). Thus, neuroimmune dysregulation as a result of alcohol drinking can provide an important pathological basis for multiple neuropsychiatric conditions. With this perspective in mind, this chapter provides an overview of current knowledge and recent advances in the field of alcohol and its closely related affective comorbidity.

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ALCOHOL DRINKING ACTIVATES THE NEUROIMMUNE SYSTEM Ethanol readily crosses the blood brain barrier and affects the brain function by acting on multiple neurotransmitter systems such as glutamate, γ-aminobutyric acid, dopamine, serotonin, glycine, and opioid peptides (Most, Ferguson, & Harris, 2014). These functional effects manifest as neuronal loss, cognitive decline, and motor dysfunction and represent some of the clinical signs of chronic alcoholism. The exact mechanism of how ethanol and its active metabolites, that is, acetaldehyde and acetone, cause addiction is nonetheless unclear and remains an active area of research. What is clear from the research during the past couple of decades is that neuroimmune signaling induced by ethanol contributes to drinking behavior consistent with alcohol dependence (Cui, Shurtleff, & Harris, 2014). Immune cells in the periphery, that is, monocytes, macrophages, B and T lymphocytes, fibroblasts, endothelial and mast cells respond to immune challenges by secreting signaling molecules including inflammatory cytokines and chemokines. These low molecular weight proteins regulate the nature, duration and intensity of the mounted response. Peripherally produced inflammatory cytokines including interleukin (IL)-1ß, IL-6, tumor necrosis factor alpha (TNF-α), interferon gamma (IFN-γ), and chemokines, for example, monocyte chemoattractant protein-1 (MCP-1) or their signals reach the brain where neuroimmune changes ensue (Raison, Capuron, & Miller, 2006). Penetration of the blood brain barrier occurs through multiple mechanisms, which include direct leakage through porous areas of the blood brain barrier, active transport mechanism and secondary messengermediated transport within the CNS endothelium (Raison et al., 2006). Additionally, nerve endings in the GI tract are known to sense and relay the inflammatory signals through sensory vagal fibers along nucleus tractus solitarius to the brain parenchyma (Maier, Goehler, Fleshner, & Watkins, 1998). In the brain, these signals, alongside signaling molecules and the locally activated resident immune cells (i.e., microglia and astrocytes), accentuate neuroimmune response. Thus, the brain is not immune privileged and, in fact, subject to immunological reaction initiated and mediated by the peripheral immune apparatus. Ethanol seems to have a double immune effect on the gut. Firstly, heavy doses of ethanol disrupt tight junctions in the intestinal mucosa (Bala, Marcos, Gattu, Catalano, & Szabo, 2014; Keshavarzian et al., 2009). Secondly, alcohol may facilitate overgrowth of gramnegative bacterial flora (Mutlu et al., 2012). Together,

these mechanisms result in the slippage of gramnegative bacterial wall proteins such as lipopolysaccharide (LPS), and potentially also peptidoglycan (Tabata, Tani, Endo, & Hanasawa, 2002), into systemic circulation. LPS is a strong inducer of the proinflammatory cascade that results in the production of cytokines, chemokines, nitric oxide, and reactive oxygen species. In clinical populations with AUD, a number of research groups have reported elevated levels of inflammatory cytokines in plasma compared to nondrinking individuals (Achur, Freeman, & Vrana, 2010; Szabo & Saha, 2015). It is now established that ethanol can independently (in the absence of another immune challenge) upregulate the inflammatory pathways in the periphery as well as in the brain (Qin & Crews, 2012; Valles, Blanco, Pascual, & Guerri, 2004; Yen et al., 2017). In mice models of binge drinking, Qin and colleagues (Qin et al., 2008) showed that ethanol potentiates LPS-induced upregulation of inflammatory cytokines in the brain. The study demonstrated for the first time that alcoholactivated neuroimmune signaling would persist for a much longer duration. It is, thus, clear that the ensued neuroinflammation may give rise to multiple diseases.

Neuroimmune Consequence of Modest Drinking Alcohol’s effect on the neuroimmune system depends on the dose, duration, and pattern of drinking. Of interest is the potential effect of the pattern of low-dose drinking thought to have some beneficial effects in preventing cardiovascular diseases (Ronksley, Brien, Turner, Mukamal, & Ghali, 2011). Monocytic production of inflammatory cytokines TNF-α and IL-1ß upon LPS challenge were reduced along with nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) downregulation in humans 18 hours after moderate alcohol consumption, while the antiinflammatory IL-10 was augmented (Mandrekar, Catalano, White, & Szabo, 2006). This finding has been replicated (Muralidharan et al., 2014), and healthy men and women drinking 1 2 drinks per day were found to have significantly lower levels of TNF-α, IL-6, and C-reactive protein (CRP) levels compared to nondrinkers (Pai et al., 2006). Direct measurement of the chemokine MCP-1 in multiple brain areas of moderate drinkers showed significantly reduced levels compared to alcoholic brain tissues, confirming that the neuroimmune effects of moderate drinking contrasts with that of heavy drinking (He & Crews, 2008). A randomized cross-over trial among healthy men fed with 30 g alcohol (control orange juice) daily with dinner for 4 weeks found that moderate alcohol consumption was associated with reduced interleukin 1

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receptor antagonist (IL-1RA) and IL-18 and acute phase protein levels and a downregulated NF-kB gene expression (Joosten, Van Erk, Pellis, Witkamp, & Hendriks, 2012). Taken together, these studies indicate a possibility of immune protective role for moderate drinking. Carefully controlled studies with a longer follow-up are required to draw definitive conclusions concerning whether ethanol-related J-shaped relationship with some chronic cardiovascular conditions are due to such effects on the innate immunity.

Neuroimmune Response to Acute Intoxication Upon binge drinking, healthy individuals had a rapid and transient rise in serum LPS levels, and this LPS increase was associated with the release of TNFα, IL-6, and MCP-1 (Bala et al., 2014). Increase in the production of inflammatory cytokines and chemokines as a result of binge drinking has been documented as early as 20 minutes following ethanol intake and altered immunity may last for a prolonged duration (Afshar et al., 2015; Neupane, Skulberg, Skulberg, Aass, & Bramness, 2016). In the former experiment, Afshar and colleagues showed that early proinflammatory changes switched within 2 5 hours to antiinflammatory state as indicated by reduced numbers of circulating monocytes and natural killer cells as well as downregulated IL-1ß and upregulated IL-10 (Afshar et al., 2015). Furthermore, rats exposed to a single intoxicating dose of alcohol (5 g/kg; intragastric) increased within 1 hour the IL-10 brain levels (Suryanarayanan et al., 2016). It is demonstrated that even in healthy individuals a single binge can impair gut barrier function for at least 24 hours (Bala et al., 2014). In LPS-challenged mice, acute alcohol administration significantly impaired IL-1ß and IL-6 production while augmenting IL-10 for up to 24 hours (D’souza El-Guindy, De Villiers, & Doherty, 2007). Put together, studies generally have found toll-like receptor (TLR) tolerance, reduced NF-κB activity, reduced TNF-α, IL6, and IL-12 levels and an elevated IL-10 level as a result of acute intoxication (Neupane, 2016).

Chronic Heavy Drinking and Neuroimmune Function Clinical samples with various grades of liver damage are by far the human populations most extensively studied within the field of neuroimmunology of AUD. Data from human studies directly measuring neuroimmune activation are scarce for obvious reasons. Fulton Crews’ group conducted a series of in vitro and in vivo animal studies as well as postmortem human alcohol brain analyses and found that chronic ethanol exposure increased expression of TLR-2-4 and the

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TLR-4 agonist high-mobility group box 1 (HMGB1) (Crews et al., 2015; Crews, Walter, Coleman, & Vetreno, 2017; Zou & Crews, 2010). They also reported that chronic alcohol treatment causes persistent increases in neuroimmune gene induction in the brain (Qin et al., 2007; Qin et al., 2008), an effect that could be ameliorated by blockade of neuroimmune signaling (Crews, Vetreno, Broadwater, & Robinson, 2016). Thus, there is an overwhelming data supporting an increase in the levels of multiple cytokines in the periphery (Doremus-Fitzwater et al., 2014; Walter & Crews, 2017; Yen et al., 2017) as well as increased expression of inflammatory mediators, glial activation and immune signaling in the brain of alcoholics (Qin et al., 2008; Walter & Crews, 2017). Recently, young adult humans with a history of binge drinking were found to have higher plasma LPS and upregulated markers of the TLR-4/NF-κB inflammatory pathway in peripheral blood mononuclear cells (Orio et al., 2017). Women were found to be particularly vulnerable to neuroimmune effects of alcohol (Alfonso-Loeches, Pascual, & Guerri, 2013; Orio et al., 2017; Pascual et al., 2017).

NEUROIMMUNE INVOLVEMENT IN ALCOHOL ADDICTION, WITHDRAWAL, AND ABSTINENCE Although neuroimmune ramifications of alcohol drinking have been increasingly established over the years, direct contributions of the neuroimmune system in alcohol drinking behavior have only begun to unravel. It is known that TLR-4 knocked down mice develop neither LPS-induced sickness behavior (Johnson, Gheusi, Segreti, Dantzer, & Kelley, 1997) nor induce neuroinflammation upon alcohol exposure (Alfonso-Loeches, Pascual-Lucas, Blanco, Sanchez-Vera & Guerri, 2010; Kelley & Dantzer, 2011), providing a crucial role of TLR-4 on alcohol-induced neuroinflammation. Ethanol induces NF-κB target genes including the proinflammatory mediators, TNF-α, IL-1β, and IL-6, MCP-1 in human alcoholic brain (Zou & Crews, 2010). Further, gene deletion of immune signaling components decreases alcohol consumption in the rodent models (Blednov et al., 2011). TLR-4 signaling accentuates alcohol drinking while also aggravating negative affect and anxiety during the withdrawal phase of the addiction cycle (Blednov et al., 2011). Stress is an important component of alcohol addiction by which efforts for sustained abstinence fails. Stress can possibly activate neuroimmune response through the gut-brain axis; upstream through dysbiotic gut (Dinan & Cryan, 2017) and downstream through increased sympathetic outflow (Raison et al., 2006).

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Indeed, chronicity of drinking is associated with microglial density and inflammatory cytokine production within the brain (Pradier, Erxlebe, Markert, & Racz, 2018). Alcohol craving has been found to positively correlate with TNF-α, IL-6, IL-10, and CRP in patients at the onset of withdrawal (Leclercq et al., 2012). The withdrawal phase of alcohol addiction is marked by stress, anxiety, and dysphoria. The withdrawal reaction was found to be aggravated by direct intracerebroventricular injection of the proinflammatory cytokines TNF-α, IL-1ß, and MCP-1, the same effect as by LPS administration (Breese et al., 2008). It should be noted that this withdrawal phase accompanies an interaction between psychological stress, ethanol, and the neuroimmune mechanism (Coleman & Crews, 2018). These lines of evidence support the role of immune signaling in higher control of alcohol drinking behavior as well as mediation of anxiety-like symptoms during withdrawal. Two days into withdrawal from alcohol, chronic drinking rat models showed upregulation of multiple innate immune genes in the amygdala (Freeman et al., 2012). Upon abstinence though, the immune system returns to homeostasis and neuro-regeneration occurs (Brust, 2010; Crews & Nixon, 2009). Relatedly, a sustained abstinence of 4 weeks was associated with elevated blood levels of brain-derived neurotrophic factor in alcohol-dependent subjects (D’sa, Dileone, Anderson, & Sinha, 2012), evidently in parallel with a clear resolution of upregulated cytokine expression after 4 weeks of abstinence (Yen et al., 2017). These findings are in line with recovery of general wellbeing after sustained abstinence. Further, these evidences set the stage for clinical intervention studies targeting the neuroimmune system.

AFFECTIVE CONSEQUENCES OF ALCOHOL-INDUCED CENTRAL NERVOUS SYSTEM NEUROIMMUNE ACTIVITY In the short term, the proinflammatory response induced by alcohol drinking may commence adaptive phenomenon termed “sickness behavior,” and is often observed in the backdrop of physiologically stressful situations or cytokine therapy (O’connor et al., 2009). Sickness behavior manifests as physiological responses such as fever and sleep disturbance, and behavioral symptoms such as isolation, loss of appetite, and physical activity. These symptoms may persist in some patients and emanate depression (Dantzer, O’connor, Freund, Johnson, & Kelley, 2008). Activated microglia and astrocytes and their products not only regulate immune function in the brain, but their interactions with neural pathways contribute to CNS health and

disease. Although alcohol-induced neuroimmune activity can invite a number of disorders of neuronal origin, further examinations are necessary to elucidate these previously unexpected roles of the immune components in the brain. The interface at which the neuroimmune system and affective disorders interact has been widely explored. Disorders of moods are common in alcoholism. Almost all patients with AUD report mood alterations some time during their lives (Lynskey, 1998). Every third patient with AUD satisfies criteria for clinically relevant depression during the same year (Lynskey, 1998; Schuckit, 2006). Patients with depression have, on the other hand, a doubled risk of AUD (Boden & Fergusson, 2011). It is clear that many patients suffer from depression even after a sustained abstinence. Neuroimmune alterations in depression have been extensively studied, with numerous reviews on the topic (Haapakoski, Mathieu, Ebmeier, Alenius, & Kivimaki, 2015; Kohler et al., 2017; Liu, Ho, & Mak, 2012). With some heterogeneity in results, these reviews suggest that depressed patients as a group have increased levels of the cytokines IL-6, IL-1RA, IL-10, TNF-α, sIL-2 receptor, and MCP-1 compared to healthy controls. Similar findings are replicated in meta-analyses of longitudinal studies (Copeland, Shanahan, Worthman, Angold, & Costello, 2012; Valkanova, Ebmeier, & Allan, 2013; Vogelzangs et al., 2012) as well as positive effects of antiinflammatory treatment on depression, albeit as an adjuvant therapy (Kohler et al., 2018; Raison et al., 2013). Chronic alcoholism and depression seem to have shared neuroimmune origins. The difference, however, is that alcoholism carries a clearer putative explanation for inflammatory rise whereas, in case of depression compelling evidences suggest that neuroimmune alterations serve as both cause and effect of depressed mood (Raison & Miller, 2011). It is plausible that alcohol-induced neuroinflammation may underlie depressive comorbidity (Neupane, 2016). The suggested mechanisms include, oxidative and nitrosative neuronal damage, activated stress response, production of neurotoxic catabolites along the kynurenine pathway of tryptophan degradation induced by IFN-γ, neurodegeneration, as well as reduced neurogenesis (Maes et al., 2009). Thus, neuroimmune involvement in multiple and complex processes of depressive illness suggests that it does not limit to the dysphoric mood observed in the context of chronic heavy drinking and transient withdrawal. A few clinical observational studies have examined possible neuroimmune involvement in comorbid depression in alcoholism. A Belgian sample of AUD patients showed positive associations between depressive symptoms and IL-6 blood levels at the

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MINI-DICTIONARY OF TERMS

onset of withdrawal, while 3 weeks into abstinence, patients showed negative correlations between IL-10 levels and depressive, anxiety, and craving scores (Leclercq et al., 2012). We reported in diverse AUD populations that depression symptoms are positively related to inflammatory cytokines (Martinez, Lien, Zemore, Bramness, & Neupane, 2018; Neupane et al., 2014). In a Norwegian sample of AUD patients, anxiety symptoms were negatively associated with IFN-γ (Martinez et al., 2018). Comorbid depression was also related to lower neurotrophic factor levels in the plasma (Neupane et al., 2015). However, depressionrelated neuroimmune changes were more pronounced in the sample with lower severity of drinking, suggesting a complex interaction between alcohol drinking, depression, and peripheral immune allostasis. In patients with bipolar disorder, both manic and depressive phases are related to raised proinflammatory cytokines and reduced antiinflammatory cytokines (Luo, He, Zhang, Huang, & Fan, 2016; Sayana et al., 2017). In patients with mania and schizophrenia, the findings are not as obvious as in depression. Still, a caveat is that the neuroimmune changes are only found in some patients within the group, with variations across the sample. Psychiatric populations constitute generally heterogeneous groups and the contributions of other environmental and genetic vulnerabilities should also be borne in mind. In addition to the affective disorders, immune pathways are also suggested to be involved in externalizing disorders, such as adult antisocial behavior. Immunerelated genes are consistently found to be associated with adult antisocial behavior (Salvatore et al., 2015) and other personality disorders (Oglodek, Szota, Just, Mos, & Araszkiewicz, 2015). The knowledge on neuroimmune interaction in drug use disorders, mostly opioids, is also ever-increasing suggesting a largely similar pattern of proinflammatory activity. A common pattern of innate immune involvement across diagnostic classes of the disorders of stress, fear, and anxietybased disorders encourages a different approach to classifying these psychiatric conditions based on their underlying neurobiological features. Extensions of the ongoing investigations to include the multiple comorbidities of AUDs are necessary.

CONCLUSIONS AND FUTURE DIRECTIONS Alcoholism and comorbid depression are associated with activated immune response, as indicated by increased peripheral and CNS inflammatory mediators. The evidence for shared neuroimmune underpinning of these conditions is conducive to the overlapping clinical presentations of these disorders.

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Binge patterns of drinking, especially in adolescents, has been investigated widely because of its potential deleterious effects on later life. The neuroimmune changes with alcohol drinking appears to be dependent upon the pattern, dose and duration of drinking, with modest and acute drinking causing antiinflammatory and chronic heavy drinking causing proinflammatory changes. However, the cutoffs at which the switching between putatively positive and negative roles by alcohol-induced immune responses takes place remain to be established. The neuroimmune signature observed in psychiatric conditions does not necessarily show a respect for classification systems of symptom-based criteria that the field has been using. Identifying patient groups with neuroimmune changes that can be attributed to specifically dysregulated pathways is crucial. Animal, ex vivo and human studies have generated important findings in the field often based on animal models or human subjects with isolated AUD. Further investigations should include a range of comorbidities associated with alcoholism, given the large burden of comorbid conditions and a need for reclassification of psychiatric conditions based on neurobiological underpinnings. The stage is set for intervention studies based at multiple target points in the neuroimmune system. This exciting field is challenged by heterogeneity in clinical samples, the lack of a definitive biomarker cytokine or other immune mediator, and selective exclusion of patients with comorbid conditions from studies. Cross-disciplinary approaches to evaluate the neuroimmune contribution to the disease course and multiple endpoints in alcoholism and related conditions should be applied. It is possible that the immune alterations as a function of alcohol drinking can underlie pathophysiological changes observed in many comorbid conditions of alcoholism.

MINI-DICTIONARY OF TERMS Alcohol use disorder A clinical entity for alcoholism in which an individual has experienced during the same year two or more of the 11 symptoms of harmful drinking according to the DSM-5 classification system. Symptoms encompass the main domains of difficulty cutting down, preoccupation with alcohol, continuous use despite harms, tolerance, and withdrawal. Binge drinking Drinking a large quantity of alcohol in a short time leading to blood alcohol concentration of 0.08 g% typically reached by drinking 5 units (men) or 4 units (women) within 2 hours. Cytokines Cell signaling proteins that serve pleiotropic cellular functions, including regulation of the immune inflammatory process. Examples include interleukins, interferons, chemokines, and tumor necrosis factor. High-mobility group box 1 (HMGB1) A nuclear and cytoplasmic TLR-4 agonist protein that can cause innate immune activation; enhanced by ethanol exposure.

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Lipopolysaccharide (LPS) A lipid and polysaccharide component of gram-negative bacterial wall, also known an endotoxin. Microglia Resident macrophages of the CNS. Monocyte chemoattractant protein-1 (MCP-1) A key member of the CC chemokine family that regulates monocytic migration and infiltration. Nuclear factor kappa B (NF-κB) A transcription factor that is responsible for the regulation of many genes including those responsible for cytokine production in response to immune challenge. Toll-like receptor (TLR) One of the 13 specific immune receptors devised by the immune system to recognize molecules of pathogenic origin such as lipopolysaccharide and peptidoglycan. Sickness behavior An adaptive response to infection, triggered by proinflammatory cytokines and comprises fever, sleep disturbance, social isolation, loss of appetite, and reduced physical activity.

SUMMARY POINTS • Alcohol drinking induces neuroimmune changes, reflected as elevated cytokine levels in the periphery and brain regions. • Neuroimmune involvement is a part of the addiction cycle in alcoholism. • Alcohol-induced neuroimmune changes can underlie pathogenesis of affective comorbidity. • The associations between alcoholism and chronic diseases may be related to immune changes in a spectrum of comorbidities. • Lack of definitive neuroimmune biomarker and heterogeneity in patient samples are some of the challenges in this study field.

KEY FACTS References

Neuroimmune Signaling • The neuroimmune signaling system consists of a complex network of immune, endocrine, and nervous systems. • Participants of the neuroimmune signaling in the brain are microglia, astrocytes, mast cells, dendritic cells, and neurones with involvement of the blood brain barrier. • Host survival against physical and psychological stressors depends upon the organization of a coordinated sensing of danger signals and response through the immune, nervous, and the endocrine systems. • The immune system receives regulatory signals from the neuroendocrine components and relays immune signals through cytokines. The system is extended to the periphery by brain-to-peripheral immune communication and peripheral immune-tobrain communication. • The neuroimmune response is mediated by cytokines, chemokines, neurotransmitters, neuropeptides, growth factors, complement system, and hormones. • The neuroimmune interaction is essential for normal homeostasis and their dysregulation causes diseases. • Proinflammatory cytokines can directly cause the adaptive response termed sickness behavior characterized by physiological responses (fever, sleep disturbance) and behavioral symptoms of social isolation, loss of appetite, and reduced physical, sexual, and body-care activities. • Dysregulated neuroimmune system is associated with altered mood, memory, arousal, motivation, and motor activity, as well as behavioral changes along with numerous diseases of the brain and psyche.

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C H A P T E R

20 Social Drinking and Motor Inhibition: Evidences From FMRI Go/Nogo Tasks fMRI Studies on Alcohol Effect on Inhibition Elisa Schro¨der and Salvatore Campanella Laboratory of Medical Psychology and Addictology, ULB Neuroscience Institute (UNI), Universite´ Libre de Bruxelles (ULB), Brussels, Belgium

LIST OF ABBREVIATIONS RI ED AUD rIFG ACC DLPFC (pre)SMA RT

response inhibition error detection alcohol use disorder right inferior frontal gyrus anterior cingulate cortex dorsolateral prefrontal cortex (pre)supplementary motor area reaction time

INTRODUCTION Inhibition, as defined by the ability to withhold inadequate responses, is a key cognitive component of human behavior (Hofmann, Schmeichel, & Baddeley, 2012). Inhibition allows us to suppress responses that are inappropriate in a specific context (e.g., stopping from laughing at a funeral), to suppress no-longer relevant responses and to orient our actions toward a new goal (e.g., stopping yourself from turning the lights on when you enter a room where the lights are already turned on), or to protect ourselves from immediate threat (e.g., stopping from crossing the road when a fast-moving car appears) (MacLeod, 2007). With regard to alcohol use, the role of response inhibition (RI) is particularly crucial as it will, for instance, allow users to resist the temptation to consume heavy amounts of alcohol at parties or in

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00020-9

social contexts where everyone else is drinking (Ewing, Sakhardande, & Blakemore, 2014). When considering substance dependence, subjects display an inability to abstain from searching for and consuming the substance(s) of abuse (Luijten et al., 2014). Thereby, unsurprisingly, alcohol use disorder (AUD) have been linked to RI deficits, as alcoholic patients tend to display poorer RI performances than matched controls (Noe¨l et al., 2013; Petit et al., 2014; see Smith, Mattick, Jamadar, & Iredale, 2014 for a meta-analysis), and deficient inhibition is believed to be linked to the relapse rate in AUD, along with attentional bias towards alcohol-related cues (Wiers et al., 2007). Several studies have highlighted the neural correlates of RI in addictive behaviors (see Luijten et al., 2014 for a review), but surprisingly few have tried to underline the effect of alcohol use on neural correlates of RI in drinkers (but not addicts). This chapter will review fMRI studies having investigated RI in young drinkers thanks to a well-known paradigm, the Go/No-Go task.

THE GO/NO-GO TASK The Go/No-Go task is one of the most commonly used tasks to measure RI, along with the Stop Signal Task (Luijten et al., 2014). Participants are asked to

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respond as quickly as possible to a frequent Go stimulus, and to withhold their response to an infrequent No-Go stimulus (see Fig. 20.1). In this way, the task installs a dominant, automatic response towards the stimuli that the participants have to overcome when an infrequent No-Go stimulus appears (Kiefer, Marzinzik, Weisbrod, Scherg, & Spitzer, 1998). Behavioral performances at Go/No-Go tasks can be measured by the reaction times (RTs) (how quickly the subject will respond to Go stimuli), No-Go false-alarms (the subjects respond to a No-Go stimulus when they shouldn’t have done so) also referred to as the error rate, and Go-correct hits (the subject adequately responds to Go stimuli). The Go/No-Go task allows the study of the neural activity related to RI, thanks to the No-Go trials, and the neural activity related to error detection (ED), as the task typically generates relatively high errors rates thanks to the time pressure (Campanella et al., 2017). The neural correlates of RI in the Go/No-Go task are mainly located within the inferior frontal gyrus (IFG), the anterior cingulate cortex (ACC), the (pre) supplementary motor area (preSMA) and the dorsolateral prefrontal cortex (DLPFC), along with parietal and subcortical areas (such as the thalamus and basal ganglia) (Chambers, Garavan, & Bellgrove, 2009; Simmonds, Pekar, & Mostofsky, 2008; Steele et al., 2013). ED activates the ACC, preSMA, insula,

FIGURE 20.1 The Go/No-Go task. Subjects have to push on a button for every Go stimulus (here: the letter “M”), which is frequent and usually appears for 70% of trials, and to withhold for every NoGo trials (here: the letter “W”). Thanks to this design, subjects learn a dominant response (i.e., pushing as fast as possible whenever something appears on the screen as it is more probable to have a Go stimulus), and have to inhibit this response in front of a No-Go stimulus.

thalamus, and DLPFC (Hester, Fassbender, & Garavan, 2004; Menon, Adleman, White, Glover, & Reiss, 2001).

DIFFERENTIAL ACTIVATIONS RELATED TO ALCOHOL CONSUMPTION PATTERNS IN COLLEGE STUDENTS Ahmadi and colleagues (2013) compared fMRI and behavioral responses of heavy (n 5 56) versus light (n 5 36) drinkers (constituted of college students, ranging in age from 18 to 20) during a Go/No-Go task. At the behavioral level, they found that heavy drinkers were significantly slower for Go-correct hits and for No-Go false-alarms (erroneous motor response for a No-Go stimulus) RT’s. Heavy and light drinkers performed similarly in regards to error rates. Functional imaging results about No-Go correct rejections showed that heavy drinkers showed a decreased activity compared to light drinkers in the left SMA, bilateral ACC, bilateral parietal lobules, thalamus, putamen, hippocampus and right parahippocampal gyrus, bilateral middle frontal gyrus, and left superior temporal gyrus. Moreover, the Blood-oxygen-level dependent (BOLD) signal changes in some of these regions (the ACC, left postcentral, thalamus, middle frontal gyrus, and right putamen) correlated negatively with alcoholconsumption related scores (such as the number of blackouts). Overall, heavy drinkers were, therefore, slower and presented a decreased pattern of activity in the regions of interest for RI and attention. The authors suggested that their results were the consequence of a general decrease of the efficiency of inhibitory function in young heavy drinkers, mirroring the deficiencies observed in AUD. Ames and colleagues (2014) also compared heavy (n 5 21) and light (n 5 20) drinkers (college students, ranging in age from 18 to 22), with an adaptation of the Go/No-Go task in order to add alcohol-related images (bottle of beer) as No-Go stimuli, expecting an increase rate of false-alarms in heavy drinkers when confronted to alcohol-related cues. As in the study of Ahmadi and colleagues, overall, light drinkers performed better than heavy drinkers, specifically with an increase rate of Go-correct hits, but heavy drinkers did not display the expected increase in false-alarms on No-Go trials. However, with regards to the imaging results, heavy drinkers showed an increased activity in the right DLPFC and in the anterior and mid cingulate cortex. The alcohol-related stimuli were specifically related to an increased neural activity in heavy drinkers in the right anterior insula when compared to light drinkers. The increased activity observed in heavy drinkers was interpreted by the authors as a consequence of the presentation of the alcohol-related

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DIFFERENTIAL ACTIVATIONS RELATED TO ALCOHOL CONSUMPTION PATTERNS IN COLLEGE STUDENTS

stimuli, as the increased incentive value of the alcoholrelated cues may have biased the cognitive processing and saturated their working memory (as reflected by the activation of the DLPFC) and, therefore, resulted in a greater difficulty to withhold their response. More specifically, the authors suggested that the attentional bias generated by the alcohol-related stimuli might result from an increased exposure to alcohol. One main limitation to the interpretation of the study of Ames and colleagues relied on the fact that the design did not allowed the authors to differentiate the activity linked to the attentional bias towards alcohol-related cues from the activity linked to RI per se. Campanella and colleagues (2017) designed a “contextual Go/No-Go task” in which the alcohol-related cues were not substituted to the No-Go stimuli, but were presented as a long-lasting background upon which the Go or No-Go stimuli were presented (see Fig. 20.2). Doing so, the authors specifically tested behavioral and BOLD responses to the Go/No-Go task from heavy (n 5 19) versus light (n 5 17) drinkers,

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comparing the impact of the context (Alcohol Context, Nonalcohol Context and No Context) on RI and ED. First, the behavioral results both from heavy and light drinkers did not show any effect of context on RI. Second, heavy, and light drinkers did not differ in their behavioral performances. fMRI results regarding the correct No-Go trials (succeeded RI) did not reveal any difference between light and heavy drinkers. However, fMRI BOLD signals consequents to falsealarm on No-Go trials (failed RI) showed that heavy drinkers presented an increased activity in the left superior occipital, the left caudate, left amygdale, and right cerebellum areas when contrasted with light drinkers, while light drinkers showed an increased activity in the right inferior frontal, right middle cingulate, and left superior temporal regions when contrasted with heavy drinkers (see Fig. 20.3). The authors suggested that the lack of differences in BOLD signal in RI might index a still-efficient inhibitory control and play a “protective role” against dependence. Results on ED were interpreted by the authors as the

FIGURE 20.2

The contextual Go/No-Go Task. The design is similar to a classical Go/No-Go task, the subjects have to press a button for each Go stimulus (“M”) and prevent themselves from pushing for No-Go trials (“W”), but here the stimuli are displayed on a contextual background. Three kinds of context exist in this study: No Context (NC, black background), Nonalcohol related Context (NAC, neutral image) and Alcohol related Context (AC, image of alcohol). Source: From Campanella, S., Absil, J., Carbia Sinde, C., Schroder, E., Peigneux, P., Bourguignon, M., . . . De Tie`ge, X. (2017). Neural correlates of correct and failed response inhibition in heavy versus light social drinkers: an fMRI study during a go/nogo task by healthy participants. Brain Imaging and Behavior, 11(6), 1796 1811. doi:10.1007/s11682-016-9654-y. Note: Presented with the permission of Salvatore Campanella.

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FIGURE 20.3 Brain areas activated by false-alarm. The parcel on the left (“Failed Inhibitions”) represents the average of all participants (heavy and lights drinkers) in situations of a false-alarm. Parcels on the right illustrate the group differences in error-linked activity. Light drinkers (on top) exhibit stronger activation in “executive-based” areas, while heavy drinkers show a stronger “visually-driven” emotional reactivity. Source: From Campanella, S., Absil, J., Carbia Sinde, C., Schroder, E., Peigneux, P., Bourguignon, M., . . . De Tie`ge, X. (2017). Neural correlates of correct and failed response inhibition in heavy versus light social drinkers: an fMRI study during a go/no-go task by healthy participants. Brain Imaging and Behavior, 11(6), 1796 1811. doi:10.1007/s11682-016-9654-y. Note: Presented with the permission of Salvatore Campanella.

manifestation of a different type of strategy engaged by light versus heavy drinkers when facing an error: light drinkers recruited areas linked to RI, response selection and prediction of actions while heavy drinkers recruited areas associated with movement control, proactive slowing, and visual computing. The authors concluded that light drinkers disclosed an “executive-based response” to errors, and heavy drinkers a “visuallydriven emotional response” to errors. Interestingly, most of the subjects recruited in the aforementioned studies were qualified either as light or heavy drinkers, the last presenting a hazardous consumption pattern in the heavy drinker group, as defined by the Alcohol Use Disorders Identification Test (AUDIT) (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993). In a recent study, Hatchard and colleagues (2017) pointed toward the effects of a low-level consumption pattern on neural functional activity. The authors compared the performances and BOLD signals of alcohol users (n 5 17) versus controls (n 5 11) recruited among young adults (age ranging from 19 to 21). The two groups did not differ in regards to their behavioral performances on the Go/No-Go task. fMRI results showed that alcohol users showed an increased activation in the left superior frontal gyrus and the left precentral gyrus, right superior parietal lobule and cerebellum, and in the left hippocampus and parahippocampal gyrus. The increased activity in the left superior frontal and precentral gyrus (regions thought to be involved in response competition and response

correction) for the alcohol users was interpreted as an indication of compensatory mechanisms, along the activation of the superior parietal lobe (associated with selfmonitoring of responses) and the cerebellum (associated with motor functioning). Moreover, the unexpected activation of the hippocampus might be associated, according to the authors, to a compensatory recruitment of additional areas displayed by alcohol users when they are “struggling” with the Go/No-Go task. Therefore, the results suggest that even restricted alcohol consumption might already impact the neural functioning of the brain in a situation requiring inhibition. Moreover, this increased activity displayed by drinkers might be predictive of a further escalation of the maximum number of drinks consumed in one occasion. Indeed, Worhunsky and colleagues (2016) studied the activity of the frontoparietal network in 36 young adults (of 18 years old) during a Go/No-Go task and observed that the increased engagement of this network successfully predicted the augmentation of the number of drinks 1 year later. Altogether, studies about social drinking and inhibitory control suggest a precocious impact of alcohol consumption, even at a low-level of consumption, on the functioning of brain areas related to RI and ED. Behavioral impairments linked to alcohol consumption remain unclear, as the results are inconsistent. However, the question about the causal relationship between alcohol consumption and neural dysfunction still needs to be addressed.

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DISRUPTED NEURAL SIGNATURE OF RI AS A PRECURSOR OR A CONSEQUENCE OF ALCOHOL USE?

DISRUPTED NEURAL SIGNATURE OF RI AS A PRECURSOR OR A CONSEQUENCE OF ALCOHOL USE? The longitudinal study of Norman and colleagues (2011) offers insights about the predictive factors of further alcohol abuse. Adolescents aged from 12 to 14 years old underwent an fMRI Go/No-Go task, and were then followed annually. Based on their evolution, subjects were then classified as future heavy users (n 5 21) or future controls (n 5 17). Future heavy users and future controls did not differ in regards to their behavioral performances. However, future heavy users displayed a decreased inhibition BOLD response to NoGo trials in the left DLPFC, left SMA, right inferior frontal and medial frontal, bilateral motor and left cingulate, left putamen and middle temporal, and inferior parietal regions bilaterally. A close pattern of decreased activation in the ventromedial prefrontal cortex as a predictor of further drug dependence symptoms (over an 18 month follow-up) has also been found by Mahmood and colleagues (2013) in older adolescents, between 16 and 19 years old. These results suggest an altered neural activation during RI in future heavy users, supporting the hypothesis that adolescents presenting a decreased neural activation linked to inhibition could be at risk of problem behaviors, such as alcohol use. However, the preservation of the behavioral performances suggests a relative efficiency of prefrontal mediated control. The authors pinpointed an alternative explanation about the decreased neural activation linked to RI: as

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the subjects are still in a period of brain development, the observed reduced activation might indicate a delayed maturation which could, in turn, be predictive of future heavy consumption of alcohol. About this aspect, the study of Wetherill and colleagues (2013) brought new perspectives in comparing behavioral and fMRI responses of adolescents to a Go/ No-Go task before any onset of heavy drinking, and 3 years later. A group of adolescents who transitioned into heavy drinking (n 5 20) and a group of matched nondrinking adolescents (n 5 20) were constituted. Results showed that, while behavioral performances at the task improved with age, no differences in behavioral performances were observed between the two groups. Nonetheless, fMRI results showed differential patterns of activation depending on the group: at baseline, before any onset of alcohol use, future heavy drinkers showed less activation for No-Go trials in the bilateral middle frontal gyri, the right inferior parietal lobule, the left putamen, and the left cerebellar tonsil. But at the follow-up, heavy drinkers showed greater activation in these regions (except for the left putamen) (see Fig. 20.4). The authors are connecting these results with the typical neural maturation observed in adolescents: activations tend to diminished with time as neural networks become more specialized, efficient and refined. Therefore, it is expected to observe a decrease in neural activation as adolescents grow older. However, it appeared that adolescents who have evolved towards heavy drinking showed an opposite pattern, with an increase of activation, suggesting alcohol may affect the typical neural development. FIGURE 20.4 Interaction between group (future heavy drinkers vs controls) and time (baseline vs follow-up 3 years later). At baseline, future heavy drinkers showed a general hypoactivation compared to controls in left Medial Frontal Gyrus (L MFG), left Putamen, left Cerebellar Tonsil, right Middle Frontal Gyrus, and right Inferior Parietal Lobule, suggesting a preexisting vulnerability. At the time of the follow-up, controls showed a decrease of their activation while heavy drinkers showed an increase of their activation in the same areas (except for the putamen), suggesting a stronger involvement in the task in order to be able to succeed it. Source: From Wetherill, R. R., Squeglia, L. M., Yang, T. T., & Tapert, S. F. (2013). A longitudinal examination of adolescent response inhibition: Neural differences before and after the initiation of heavy drinking. Psychopharmacology, 230(4), 663 671. doi:10.1007/s00213-013-3198-2. Note: Presented with the permission of Susan Tapert.

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Beyond the examination of future heavy or hazardous drinkers, such a pattern of decreased frontal activity during a Go/No-Go task has also been observed in youths with a family history of alcoholism. More specifically, youths with a positive familial history of alcoholism showed a decreased activation in the left middle frontal gyrus. The authors, therefore, suggested that this altered activity may underlie disinhibition and potentially lead to future AUD (Schweinsburg et al., 2004). It is interesting to note that an overall blunted activation pattern in the prefrontal cortical regions (e.g., the left middle frontal gyrus) following a failed inhibition in the Go/No-Go task during childhood appears to be predictive of a transition to a problematic substance use that is not specific to alcohol, as it may also concern illicit substance use (Heitzeg et al., 2014).

particular context, or to stop an already initiated response that is no longer relevant. Error detection Error detection and processing refers to the cognitive mechanisms implicated in the detection of an error, the emotional response to the error and the further adjustments made in order to avoid any further errors of this type. Alcohol use disorder AUD are referring to the patterns of alcohol drinking that are susceptible to have a harmful impact on physical or mental health, such as alcohol dependence and alcohol abuse. Reaction time The time a subject takes to produce a motor response to a stimulus. False-alarms errors (or commission errors) A false-alarm (or commission) error corresponds to a response given to a stimulus that had to be inhibited.

CONCLUSIONS

What do those categories mean? The answer may vary depending on who is responding to the question.

Altogether, these studies suggest that the mutual influences of RI and alcohol consumption are extremely narrow. On the one hand, subjects that will further develop a pattern of alcohol abuse seem to present specific vulnerabilities indexed by a decrease activity in, for instance, the frontal gyrus, parietal areas, and putamen (Ahmadi et al., 2013; Norman et al., 2011; Wetherill et al., 2013). On the other hand, subject who indeed transitioned into alcohol use (even with a restricted consumption) display increased activities in these regions, suggesting that a particular effort has to be invested in order to perform normally at the Go/No-Go task (Ames et al., 2014; Campanella et al., 2017; Hatchard et al., 2017; Wetherill et al., 2013). Thus, preexisting vulnerabilities may increase the probability of alcohol consumption and abuse (Thomsen, Osterland, Hesse, & Ewing, 2018), which in return might superimpose neural dysfunctions related the RI. The lack of consistent results on behavioral performances enhances the importance of neuroimaging techniques, as compensatory mechanisms might be at play and mask any reorganization of the functional activity consequent to specifics vulnerabilities. The results emphasize the crucial necessity to develop efficient prevention strategies regarding alcohol use and adolescent, as alcohol can significantly affect the developing brain even at very early stages of alcohol consumption.

• The National Institute on Alcohol Abuse and Alcoholism (NIAAA) defines binge drinking as a pattern of consumption that will bring blood alcohol concentration levels above 0.08 g/dL. The Substance Abuse and Mental Health Services Administration (SAMHSA, USA) speaks about binge drinking when a subject drinks 5 1 (for men) or 4 1 (for women) drinks on the same occasion. • Hazardous alcohol consumption is defined by a score superior or equal to 8 at the Alcohol Use Disorders Identification Test (AUDIT, Saunders et al., 1993). • Heavy alcohol use is defined by the SAMHSA as 5 or more episodes of binge drinking per month.

MINI-DICTIONARY OF TERMS Response inhibition Response inhibition is thought as the mechanism that allows us to stop or abort inappropriate responses in a

KEY FACTS Heavy/Hazardous/Binge Drinking

Overall, definitions may vary tremendously, making it difficult to compare different studies when the targeted population is not well defined.

SUMMARY POINTS • Response inhibition is critical in addictive and substance abuse behaviors as it allows the subject to refrain from seeking and consuming the substance. • The results about behavioral performance of response inhibition in heavy drinkers, studied thanks to Go/No-Go tasks, are inconsistent as in most studies heavy and light drinkers perform similarly. • Neural correlates of response inhibition—indexed by an hypoactivation of the areas involved in response inhibition—in heavy drinkers show that the deterioration of response inhibition can be seen

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REFERENCES

prior the onset of alcohol use and might, therefore, be considered as a vulnerability factor. • A general hyperactivation of the areas involved in response inhibition in heavy drinkers is generally reported and appears as a manifestation of compensation mechanisms. Such activation patterns can be observed even when the alcohol consumption is low. • Results suggest that the impact of alcohol on response inhibition is extremely precocious.

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inhibition: Evidence from event-related potentials in a go/no go task. Neuroreport, 9(4), 765 770. Luijten, M., Machielsen, M. W. J., Veltman, D. J., Hester, R., de Haan, L., & Franken, I. H. A. (2014). Systematic review of ERP and fMRI studies investigating inhibitory control and error processing in people with substance dependence and behavioural addictions. Journal of Psychiatry & Neuroscience: JPN, 39(3), 149 169. MacLeod, C. M. (2007). The concept of inhibition in cognition. In D. S. Gorfein, & C. M. MacLeod (Eds.), Inhibition in cognition (pp. 3 23). Washington, DC: American Psychological Association. Available from http://dx.doi.org/10.1037/11587-001. Mahmood, O. M., Goldenberg, D., Thayer, R., Migliorini, R., Simmons, A. N., & Tapert, S. F. (2013). Adolescents’ fMRI activation to a response inhibition task predicts future substance use. Addictive Behaviors, 38(1), 1435 1441. Available from https://doi. org/10.1016/j.addbeh.2012.07.012. Menon, V., Adleman, N. E., White, C. D., Glover, G. H., & Reiss, A. L. (2001). Error-related brain activation during a Go/NoGo response inhibition task. Human Brain Mapping, 12(3), 131 143. Noe¨l, X., Van der Linden, M., Brevers, D., Campanella, S., Verbanck, P., Hanak, C., . . . Verbruggen, F. (2013). Separating intentional inhibition of prepotent responses and resistance to proactive interference in alcohol-dependent individuals. Drug and Alcohol Dependence, 128(3), 200 205. Available from https://doi.org/ 10.1016/j.drugalcdep.2012.08.021. Norman, A. L., Pulido, C., Squeglia, L. M., Spadoni, A. D., Paulus, M. P., & Tapert, S. F. (2011). Neural activation during inhibition predicts initiation of substance use in adolescence. Drug and Alcohol Dependence, 119(3), 216 223. Available from https://doi. org/10.1016/j.drugalcdep.2011.06.019. Petit, G., Cimochowska, A., Kornreich, C., Hanak, C., Verbanck, P., & Campanella, S. (2014). Neurophysiological correlates of response inhibition predict relapse in detoxified alcoholic patients: Some preliminary evidence from event-related potentials. Neuropsychiatric Disease and Treatment, 10, 1025 1037. Available from https://doi.org/10.2147/NDT.S61475. Saunders, J. B., Aasland, O. G., Babor, T. F., de la Fuente, J. R., & Grant, M. (1993). Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption--II. Addiction (Abingdon, England), 88(6), 791 804. Schweinsburg, A. D., Paulus, M. P., Barlett, V. C., Killeen, L. A., Caldwell, L. C., Pulido, C., . . . Tapert, S. F. (2004). An FMRI study of response inhibition in youths with a family history of alcoholism. Annals of the New York Academy of Sciences, 1021(1), 391 394. Available from https://doi.org/10.1196/annals.1308.050. Simmonds, D. J., Pekar, J. J., & Mostofsky, S. H. (2008). Meta-analysis of Go/No-go tasks demonstrating that fMRI activation associated with response inhibition is task-dependent. Neuropsychologia, 46 (1), 224 232. Available from https://doi.org/10.1016/j. neuropsychologia.2007.07.015. Smith, J. L., Mattick, R. P., Jamadar, S. D., & Iredale, J. M. (2014). Deficits in behavioural inhibition in substance abuse and addiction: A meta-analysis. Drug & Alcohol Dependence, 145, 1 33. Available from https://doi.org/10.1016/j.drugalcdep.2014.08.009. Steele, V. R., Aharoni, E., Munro, G. E., Calhoun, V. D., Nyalakanti, P., Stevens, M. C., . . . Kiehl, K. A. (2013). A large scale (N 5 102) functional neuroimaging study of response inhibition in a Go/ NoGo task. Behavioural Brain Research, 256, 529 536. Available from https://doi.org/10.1016/j.bbr.2013.06.001. Thomsen, K. R., Osterland, T. B., Hesse, M., & Ewing, S. W. F. (2018). The intersection between response inhibition and substance use among adolescents. Addictive Behaviors, 78, 228 230. Available from https://doi.org/10.1016/j.addbeh.2017.11.043.

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Wetherill, R. R., Squeglia, L. M., Yang, T. T., & Tapert, S. F. (2013). A longitudinal examination of adolescent response inhibition: Neural differences before and after the initiation of heavy drinking. Psychopharmacology, 230(4), 663 671. Available from https:// doi.org/10.1007/s00213-013-3198-2. Wiers, R. W., Bartholow, B. D., van den Wildenberg, E., Thush, C., Engels, R. C. M. E., Sher, K. J., . . . Stacy, A. W. (2007). Automatic and controlled processes and the development of addictive behaviors in adolescents: A review and a model. Pharmacology,

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C H A P T E R

21 Myelopathy and Neuropathy Associated With Alcoholism Haruki Koike Department of Neurology, Nagoya University Graduate School of Medicine, Nagoya, Japan

LIST OF ABBREVIATION ALDH

aldehyde dehydrogenase

INTRODUCTION Neurological disorders related to excessive alcohol consumption are diverse, affecting the central nervous system, peripheral nervous system, and skeletal muscles (de la Monte & Kril, 2014; Koike et al., 2003; Preedy et al., 2001; Sage, Van Uitert, & Lepore, 1984). Ethanol or its metabolites may be directly related to the pathogenesis of neurological disorders associated with alcoholism, while nutritional deficiencies associated with ethanol consumption also cause a variety of neurological disorders (Charness, 1993; Koike et al., 2001, 2017). Because the neurological manifestations of alcoholics may be a consequence of the combination of direct toxicity and nutritional deficiency, neurological manifestations in alcoholics are diverse (de la Monte & Kril, 2014; Koike & Sobue, 2006). Hence, the diagnosis of alcohol-related neurological disorders is sometimes difficult unless physicians consider the spectrum of alcohol-related neurological disorders. Chronic consumption of ethanol affects the brain, resulting in addiction and cognitive decline that lead to a significant socio-economic impact. Therefore, many investigators have published studies regarding the brain damage resulting from alcoholism. By contrast, less attention has been paid to other parts of the nervous system in the context of alcoholism. Particularly, there is less recognition of the influence of alcoholism on the

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00021-0

spinal cord and peripheral nervous system. However, abnormalities in the spinal cord (i.e., myelopathy) and peripheral nervous system (i.e., neuropathy) can significantly disturb patients’ functional status and quality of life. In this chapter, myelopathy and neuropathy resulting from alcoholism are described, with a focus on their pathogeneses, clinical features, and management.

MYELOPATHY Pathogenesis Clinically significant myelopathy in patients with alcoholism has been anecdotally reported (Koike et al., 2017; Mendoza, Marti-Fa`bregas, Kulisevsky, & Escartı´n, 1994; Sage et al., 1984). Thus far, myelopathy in alcoholics has been linked to liver cirrhosis resulting from alcoholism (Mendoza et al., 1994; Nardone et al., 2014). Since spastic paraparesis occurs in patients with liver cirrhosis regardless of the presence or absence of alcoholism (Troisi, Debruyne, & de Hemptinne, 1999), it has been designated hepatic myelopathy. Myelopathy may occur even in the absence of liver failure if the patient has portosystemic blood shunting (Demirci, Tan, Elibol, ˘ Gedikoglu, & Sariba¸s, 1992). For example, progressive spastic paraparesis occurred in a patient with portosystemic shunting caused by congenital hepatic fibrosis (Demirci et al., 1992). In this patient, liver functions were normal, except for an elevated blood ammonia level, suggesting that blood shunting allows toxic substances to bypass the liver and damage the spinal cord,

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leading to hepatic myelopathy. Hepatic myelopathy may be accompanied by encephalopathy due to portosystemic blood shunting (Lewis & Howdle, 2003). Interestingly, this hepatic encephalopathy responds well to treatment aimed at reducing blood ammonia levels, whereas the response to such therapies is usually poor in hepatic myelopathy (Lewis & Howdle, 2003; Weissenborn et al., 2003). Additionally, Sage et al. reported on five patients with so-called alcoholic myelopathy without substantial liver disease in 1984 (Sage et al., 1984). Laboratory findings in these alcoholic patients with myelopathy indicated normal liver function, except for minimal elevation of aspartate transaminase and alanine transaminase levels in one patient. Moreover, their nutritional status, including folate and cobalamin status, was good. Hence, the direct toxicity of ethanol or its metabolites caused myelopathy in these patients. Since then, the possible contribution of nutritional deficiency has not been extensively examined in alcoholics with myelopathy (de la Monte & Kril, 2014). However, myelopathy due to vitamin deficiency also occurs in alcoholics (Koike et al., 2017). Cobalamin, folate, vitamin E, and copper deficiencies are well-known causes of myelopathy (Kumar, 2012; Schwendimann, 2013). Particularly, folate deficiency may occur due to alcoholism because ethanol intake decreases folate by inhibiting the absorption of folate from the intestines, reducing its hepatic stores, and increasing its urinary excretion (Halsted, Villanueva, Devlin, & Chandler, 2002). An unbalanced diet associated with alcoholism may also contribute to reduced nutritional intake. Taking these anecdotal reports into consideration, the main causes of myelopathy in patients with alcoholism are portosystemic blood shunting resulting from liver cirrhosis, the direct toxicity of ethanol or its metabolites, and nutritional deficiency accompanied by alcoholism.

Clinical Features In general, clinical manifestations of myelopathy include gait disturbance, lower limb weakness, and sensory manifestations in a stocking-glove distribution. Hyperreflexia, spasticity in the limbs, and extensor plantar responses are representative signs suggestive of myelopathy. Bladder and rectal disturbances are also important findings indicative of spinal cord lesions. Romberg’s sign indicates involvement of the posterior column. Furthermore, patients with subacute combined degeneration of the spinal cord due to nutritional deficiency may exhibit signal changes on T2-

weighted images of the cervical spinal cord (Kumar, 2014). As neuropathy may concomitantly occur in patients with alcoholism (i.e., myeloneuropathy) as described later, abnormalities in nerve conduction indices do not exclude the possibility of myelopathy. Moreover, Achilles tendon reflexes tend to be reduced or absent in such patients. In most previous reports, myelopathy in alcoholics was considered hepatic myelopathy due to portosystemic blood shunting resulting from liver cirrhosis (de la Monte & Kril, 2014). The features of hepatic myelopathy include progressive spasticity in the lower limbs, called spastic paraparesis, and scarce sensory deficits (Ben Amor, Saied, Harzallah, & Benammou, 2014; Mendoza et al., 1994). By contrast, Sage et al. reported that five patients with myelopathy and alcoholism had no substantial liver disease (Sage et al., 1984). These patients were well nourished, and their serum folate and cobalamin levels were reportedly normal. Hence, the cause of myelopathy in these patients was attributed to the direct toxicity of ethanol (Sage et al., 1984). The patients comprised four men and one woman, with ages ranging from 53 to 63 years. Four patients consumed beer, while another drank whisky for a duration ranging from 8 to 20 years. These patients experienced progressive paresthesia in the feet, followed by spasticity and ataxia during a 1 4 year period. Symptoms in the upper limbs and dysuria were not reported in any of the patients. Neurological examination revealed spastic paraparesis similar to that of hepatic myelopathy. Hyperreflexia in the lower limbs and extensor planter responses were observed. Vibration and joint position sensations were decreased in the toes, while pin and touch sensations were normal. Mental status and cerebellar signs were unremarkable. The representative clinical features of myelopathy caused by nutritional deficiency include subacute combined degeneration of the spinal cord associated with cobalamin and folate deficiency (Reynolds, 2006). Unlike spastic paraparesis caused by portosystemic blood shunting, subacute combined degeneration is usually accompanied by loss of deep sensations, including vibratory and joint sensations, predominantly in the lower limbs, resulting in sensory ataxia (Okada, Koike, Nakamura, Watanabe, & Sobue, 2014; Reynolds, 2006). However, previous studies of patients with alcoholism and myelopathy with folate deficiency have highlighted the incidence of pyramidal tract damage (Koike et al., 2017). Since both the direct toxicity of ethanol or its metabolites and nutritional deficiency, particularly B vitamins, may lead to transient or persistent damage in the brain, concomitant disturbance of consciousness or cognitive decline is frequently seen in patients with myelopathy (Koike et al., 2017). Concomitant peripheral neuropathy, as described later, may also be frequent.

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Diagnosis Appropriate history taking, neurological examination, electrophysiological tests, and radiological assessment are needed for the diagnosis of myelopathy in alcoholics. The presence of portosystemic blood shunting accompanied by liver failure is required for the diagnosis of hepatic myelopathy in alcoholics. For the diagnosis of subacute combined degeneration of the spinal cord, the presence of causative nutritional deficiency, such as cobalamin and folate deficiency, is needed for confirmation. Although folate deficiency is more frequently associated with alcoholism (Halsted et al., 2002; Koike et al., 2012), concomitant deficiency of other vitamins may also occur (Koike et al., 2017). Importantly, serum levels of cobalamin and folate, which are usually measured in daily clinical practice, do not accurately reflect actual nutritional status. Elevated plasma homocysteine can help to determine whether a patient has clinically significant cobalamin and folate deficiency (Reynolds, 2006). Elevated plasma methylmalonic acid also suggests cobalamin deficiency (Kumar, 2014). Anemia and macrocytosis are not frequently seen in patients with neurological impairments resulting from cobalamin and folate (Koike et al., 2015; Lindenbaum et al., 1988). By contrast, the diagnosis of alcoholic myelopathy caused by the direct toxicity of ethanol or its metabolites is often difficult because it is essentially based on the exclusion of other causes of spastic paraparesis. Electrophysiological findings, such as somatosensory evoked potentials and central motor conduction time, may support the clinical diagnosis of myelopathy (Koike et al., 2017; Okada et al., 2014). However, magnetic resonance imaging may be normal even in patients with significant myelopathic features (Koike et al., 2017; Okada et al., 2014). Abnormalities in nerve conduction indices do not exclude the possibility of myelopathy because neuropathy may concomitantly occur in patients with alcoholism. Achilles tendon reflexes tend to be reduced or absent in such patients. Additionally, cerebrospinal fluid examinations are usually normal and can be useful to discriminate between alcoholism-associated myelopathies and immune-mediated or infectious myelopathies.

Treatment and Prognosis In general terms, damage to the nervous systems, including the spinal cord, tend to remain even after treatment (Koike et al., 2017). For example, abstinence from alcohol intake prevents only further deterioration in patients with myelopathy caused by the direct toxicity of ethanol or its metabolites (Sage et al., 1984). Hence, early diagnosis of underlying causes of

myelopathy and prompt initiation of treatment are needed to avoid significant residual deficits. In addition to disease-specific treatments based on the pathogenesis of myelopathy, rehabilitation, including physical and occupational therapies, is recommended. Administration of muscle relaxants may ameliorate spasticity, leading to gait improvement. Hepatic myelopathy also has a poor prognosis (Nardone et al., 2014). However, precisely estimating the natural history of hepatic myelopathy may be difficult because achieving complete alcohol abstinence is difficult in alcoholic patients. Conservative treatment to control blood ammonia concentrations ameliorates spastic paraparesis in some patients, particularly when it is initiated in early phase of myelopathy (Hirozawa et al., 2014). Liver transplantation may also be effective, leading to significant improvement in some patients (Weissenborn et al., 2003). In patients with nutritional deficiency, supplementation should be initiated as early as possible to minimize residual deficits. Multivitamin supplementation is also recommended because patients may also be deficient in vitamins other than those likely to cause myelopathy (Sechi, Sechi, Fois, & Kumar, 2016). As the recovery of neurological impairments is usually slow, supplementation should be continued for months (Reynolds, 2006). Since megaloblastic anemia caused by nutritional deficiency recovers more rapidly than does myelopathy (Reynolds, 2006), cessation of treatment should not be determined based on hematological indices.

NEUROPATHY Pathogenesis The pathogenesis of neuropathy associated with alcoholism is diverse and has previously been considered in relation to nutritional deficiency resulting from alcoholism (Novak & Victor, 1974; Victor & Adams, 1961). As described earlier, alcohol intake can alter the intake, absorption, and utilization of various nutrients. A variety of nutritional aspects, particularly vitamins, are affected in alcoholics (Lieber, 2000). Deficiencies in riboflavin (vitamin B2), niacin (vitamin B3), pyridoxine (vitamin B6), folate (vitamin B9), cobalamin (vitamin B12), or vitamin E may cause neuropathy (Hammond, Wang, Dimachkie, & Barohn, 2013; Koike et al., 2004). Among these vitamin deficiencies, thiamine deficiency has received attention as the cause of neuropathy in alcoholics (Novak & Victor, 1974; Victor & Adams, 1961). Thiamine deficiency is closely related to alcoholism because ethanol diminishes thiamine absorption in the intestine, reduces thiamine stores in the liver, and

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reduces thiamine’s active form by affecting its phosphorylation (Hoyumpa, 1980; Singleton & Martin, 2001). In addition, folate deficiency, one of the earlier described causes of myelopathy in alcoholics, may result in neuropathy (Koike et al., 2015). Pellagra is associated with niacin deficiency and is characterized by diarrhea, dermatitis, and dementia; it may also accompany neuropathy and has been reported in patients with alcoholism (Badawy, 2014). In addition to these nutritional deficiencies, the direct toxicity of ethanol or its metabolites may be a cause of neuropathy (Koike et al., 2001, 2003; Mellion, Gilchrist, & de la Monte, 2011). A relationship between the total lifetime amount of ethanol intake and the severity of neuropathy supports this view (Ammendola et al., 2001; Monforte et al., 1995). A candidate for the direct neurotoxicity of ethanol is acetaldehyde, a highly toxic ethanol metabolite. Ethanol is oxidized to acetaldehyde, mainly by alcohol dehydrogenase. Acetaldehyde is then oxidized to less harmful acetate, mainly by aldehyde dehydrogenase (ALDH). ALDH2, one of the isozymes of ALDH, has a polymorphism (ALDH2 2, Glu487Lys) that is prevalent among Mongoloids, but absent in Caucasoids or Negroids (Agarwal & Goedde, 1992). Because ALDH2 is inactive in individuals with the ALDH2 2 allele, they fail to rapidly metabolize acetaldehyde (Yoshida, Hsu, & Yasunami, 1991). A study of Japanese patients with alcoholic neuropathy found that patients who are heterogeneous for ALDH2 2 had significantly lower amplitudes of sensory nerve action potentials in the sural and median nerves, suggesting more conspicuous axonal degeneration, than do those without the ALDH2 2 allele (Masaki et al., 2004). These studies suggest that the accumulation of acetaldehyde has toxic effects on the peripheral nervous system, resulting in alcoholic neuropathy.

Clinical Features In general, clinical manifestations of neuropathy include gait disturbance, lower limb weakness, and sensory manifestations in a glove-and-stocking distribution. Reduced or absent deep tendon reflexes indicate the presence of neuropathy. As neuropathies in alcoholics invariably manifest symmetric polyneuropathy with greater involvement of the lower rather than the upper limbs, numbness or pain initiates from the distal portion of the lower limbs (i.e., toes) and gradually progresses in a centripetal manner (Koike et al., 2003). Sensory disturbances in the upper limbs appear later (Koike et al., 2001). As the clinical features of neuropathies resulting from thiamine deficiency, folate deficiency, and the direct toxicity of ethanol or its metabolites without

nutritional deficiency are essentially different, these three types of neuropathies are described separately. Neuropathy resulting from thiamine deficiency, which is identical to beriberi neuropathy, is usually characterized by acute progression and motor-dominant symptoms, affecting both superficial and deep sensation, although exceptions are present (Koike et al., 2001, 2004). Guillain-Barre´ syndrome may initially be suspected in some patients because motor weakness progresses over days, leading to loss of ambulation (Koike et al., 2008; Murphy, Bangash, & Varma, 2009). Concomitant central nervous system involvement (i.e., Wernicke’s encephalopathy) and cardiovascular involvement (i.e., wet beriberi) may be seen in some, but not all, patients (Koike et al., 2003, 2004). By contrast, neuropathy caused by folate deficiency is relatively uniform, characterized by slowly progressive polyneuropathy with predominant involvement of the lower limbs, with a tendency to manifest as sensory rather than motor neuropathy and predominantly deep rather than superficial sensory loss (Koike et al., 2015). Gait unsteadiness may be conspicuous due to loss of deep sensations in the distal portions of the lower limbs. As myelopathy may concomitantly present with neuropathy in patients with folate deficiency, deep tendon reflexes may be preserved or increased, particularly in the upper limbs. Neuropathy caused by the direct toxicity of ethanol or its metabolites, but not nutritional deficiency, also exhibits relatively uniform features characterized by slowly progressive, sensorydominant symptoms, with predominant impairment of superficial sensation, especially nociception (Koike et al., 2001, 2003). Pain in the lower limbs is usually the primary complaint in these patients. Although the pattern of progression in the pure form of alcoholic neuropathy is usually slow, patients with a combination of alcohol abuse and malnutrition may exhibit rapidly progressive neuropathy that resembles Guillain-Barre´ syndrome (Tabaraud et al., 1990; Wo¨hrle, Spengos, Steinke, Goebel, & Hennerici, 1998). Although the clinical characteristics of neuropathy are distinct among these three types of neuropathy, a mixture of these neuropathies is also frequently present (Koike et al., 2004). Hence, the features of neuropathy associated with alcoholism show extensive variation.

Diagnosis As in patients with myelopathy, appropriate history taking, neurological examination, and electrophysiological examination are needed to diagnose a patient with neuropathy associated with alcoholism. Although the screening of nutritional deficiency that may cause neuropathy is important, susceptibility to nutritional

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deficiency may vary among individual patients (Blass & Gibson, 1977; Koike et al., 2004). Hence, careful interpretation regarding nutritional status is needed. Characteristic neuropathic features, such as rapidly progressive weakness in thiamine deficiency, gait unsteadiness due to sensory ataxia in folate deficiency, and pain in the lower limbs in alcoholic neuropathy with normal nutritional status, indicate the etiology of neuropathy (Koike et al., 2003, 2015). The cessation of progression or improvement in neurological impairment after abstinence or nutritional supplementation confirms the diagnosis. Anemia accompanied by macrocytosis is a famous clinical sequela in folate deficiency. However, anemia poorly correlates with neurological deficits (Koike et al., 2015; Reynolds, 2006). Hence, the absence of these hematological abnormalities does not necessarily exclude folate deficiency. Nerve conduction studies provide important information to demonstrate the presence of neuropathy and show features compatible with axonal neuropathy predominant in the lower rather than the upper limbs (Koike et al., 2003, 2015). Compound muscle action potentials and sensory nerve action potentials are reduced, while motor conduction velocities, sensory conduction velocities, and distal latencies are preserved (Koike et al., 2003, 2015).

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Since many diseases, such as amyloidosis and diabetes mellitus, cause axonal neuropathy similar to neuropathies associated with alcoholism, confirming the diagnosis is sometimes difficult (Brown, Martin, & Asbury, 1976; Callaghan, Cheng, Stables, Smith, & Feldman, 2012; Koike et al., 2004). A nerve biopsy may be performed to exclude the possibility of other underlying diseases. The sural nerve, which contains sensory afferent and autonomic efferent fibers, is usually obtained for histopathological examination. The presence of axonal degeneration without findings suggestive of demyelination is an essential pathological finding in patients with neuropathies associated with alcoholism (Behse & Buchthal, 1977; Koike et al., 2004). Small fiber-predominant axonal loss is the characteristic feature in alcoholic neuropathy with normal nutritional status in accordance with its characteristic superficial sensory impairment (Koike et al., 2001). On light microscopic examination, sural nerve biopsy specimens show predominant loss of small myelinated fibers compared with that of large myelinated fibers (Fig. 21.1). Loss of unmyelinated fibers is also evident on electron microscopic examination (Fig. 21.2). By contrast, large fibers are predominantly reduced in patients with nutritional deficiencies, including thiamine and folate deficiency (Koike et al., 2004, 2015).

FIGURE 21.1 Representative light microscopic images of sural nerve biopsy specimens from a patient with alcoholic neuropathy with normal nutritional status (A) and a control subject (B). Small myelinated fibers are predominantly reduced in the specimen from a patient with alcoholic neuropathy with normal nutritional status. A representative of small myelinated fibers is indicated by an arrow in A. Transverse section. Toluidine blue stain. Scale bars 5 20 µm.

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FIGURE 21.2 Representative electron microscopic images of sural nerve biopsy specimens from a patient with alcoholic neuropathy with normal nutritional status (A) and a control subject (B). Unmyelinated fibers are predominantly reduced in the specimen from a patient with alcoholic neuropathy with normal nutritional status. A representative of unmyelinated fibers is indicated by an arrow in B. Transverse section. Uranyl acetate and lead citrate stain. Scale bars 5 2 µm.

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Loss of large myelinated fibers is more conspicuous than that of small myelinated fibers on light microscopic examination of sural nerve biopsy specimens from patients with thiamine deficiency (Fig. 21.3) (Koike et al., 2004, 2008). In cases with an acutely progressive clinical course, myelin ovoids are abundant, reflecting the acute phase of axonal degeneration. Unmyelinated fibers tend to be preserved despite the extent of myelinated fiber loss (Fig. 21.4). However, pathological features may be variable in patients with thiamine deficiency because the direct toxicity of ethanol or its metabolites influences the modality of nerve fiber loss (Koike & Sobue, 2006; Koike et al., 2003). Patients with folate deficiency neuropathy also show predominant loss of large myelinated fibers (Fig. 21.5) (Koike et al., 2015), while unmyelinated fibers are relatively preserved (Fig. 21.6). As described earlier, an important differential diagnosis for neuropathy caused by thiamine deficiency is Guillain-Barre´ syndrome because both neuropathies show rapidly progressive weakness (Koike et al., 2008). The features of folate deficiency neuropathy resemble those of cobalamin and copper deficiency

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FIGURE 21.3 Representative light microscopic image of a sural nerve biopsy specimen from a patient with thiamine deficiency neuropathy. Large myelinated fibers are predominantly reduced in the specimen from a patient with thiamine deficiency neuropathy. A remaining large myelinated fiber is indicated by an arrow. Transverse section. Toluidine blue stain. Scale bar 5 20 µm.

FIGURE 21.4 Representative electron microscopic image of a sural nerve biopsy specimen from a patient with thiamine deficiency neuropathy. Unmyelinated fibers are relatively preserved despite the extent of the loss of myelinated fibers in the specimen from a patient with thiamine deficiency neuropathy. Representatives of myelinated fibers and unmyelinated fibers are indicated by a thick arrow and a thin arrow, respectively. A myelin ovoid resulted from axonal degeneration is indicated by an arrowhead. Transverse section. Uranyl acetate and lead citrate stain. Scale bar 5 2 µm. II. NEUROBIOLOGY

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FIGURE 21.5 Representative light microscopic image of a sural nerve biopsy specimen from a patient with folate deficiency neuropathy. Large myelinated fibers are predominantly reduced in the specimen from a patient with folate deficiency neuropathy. A remaining large myelinated fiber is indicated by an arrow. Transverse section. Toluidine blue stain. Scale bar 5 20 µm.

in terms of sensory ataxia due to deep sensory impairment (Kumar & Low, 2004; Reynolds, 2006; Taylor et al., 2017). These neuropathies should be differentiated from paraneoplastic syndrome and Sjo¨gren’s syndrome (Koike & Sobue, 2013; Mori et al., 2005). Similar features including painful symptoms and small fiber-predominant axonal degeneration with relative preservation of large myelinated fibers in alcoholic neuropathy have also been reported in familial amyloid polyneuropathy, Fabry disease, and a subgroup of neuropathies associated with diabetes mellitus or Sjo¨gren’s syndrome (Brown et al., 1976; Dyck & Lambert, 1969; Koike et al., 2004; Mori et al., 2005; Onishi & Dyck, 1974). However, unlike these neuropathies, alcoholic neuropathy does not exhibit conspicuous autonomic symptoms (Koike et al., 2001, 2003; Low, Walsh, Huang, & McLeod, 1975).

(Koike et al., 2001, 2015). By contrast, autonomic dysfunction is reversible with abstinence (Tan, Johnson, Lambie, & Whiteside, 1984). The clinical importance of autonomic dysfunction may be due to its relationship with higher mortality from cardiovascular events among alcoholics (Johnson & Robinson, 1988). For patients with nutritional deficiency, supplementation should be initiated as early as possible to minimize residual deficits (Koike et al., 2001). Multivitamin supplementation is recommended because patients with nutritional deficiency may be deficient in multiple vitamins (Sechi et al., 2016). For suspected thiamine deficiency patients, high-dose thiamine should be administered parenterally in the initial phase. Adequate blood thiamine concentrations can be achieved with oral supplementation even in patients with gastrectomy (Koike et al., 2001). Substantial functional recovery of weakness in the extremities has been achieved by thiamine supplementation at 3 6 months, but sensory symptoms tend to remain as residual deficits (Koike et al., 2001). Thiamine supplementation also substantially improves Wernicke’s encephalopathy and cardiovascular beriberi (Koike et al., 2008). However, Korsakoff’s syndrome persists even a long time after the initiation of treatment (Koike et al., 2001). Recovery is poorer in patients with folate deficiency than that in patients with thiamine deficiency because sensory symptoms are usually predominant in neuropathy caused by folate deficiency (Koike et al., 2015). As patients with neuropathy associated with alcoholism frequently complain about limb pain (Koike et al., 2001, 2003), pharmacological treatment for neuropathic pain contributes to improved patient quality of life. Tricyclic antidepressants, serotonin norepinephrine reuptake inhibitors, pregabalin, and gabapentin are recommended as first-line treatment options for neuropathic pain (Zeng, Alongkronrusmee, & van Rijn, 2017). Rehabilitation is also recommended.

MINI-DICTIONARY OF TERMS Treatment and Prognosis Although the number of studies regarding neuropathy associated with alcoholism seems to be larger than that of myelopathy, its prognosis has not been fully investigated which is, at least in part, attributable to the difficulty of achieving complete alcohol abstinence in alcoholics. A previous study indicated a good prognosis for mild to moderate somatic neuropathy after 3 5 years of abstinence (Hillbom & Wennberg, 1984). Sensory deficits in patients with neuropathy tend to persist even after treatment of underlying causes

Dry beriberi Disorders of the peripheral nervous system caused by thiamine deficiency. Hepatic myelopathy Myelopathy resulting from portosystemic blood shunting. Korsakoff’s syndrome A syndrome characterized by anterograde amnesia associated with thiamine deficiency. Myelopathy Neurological impairment resulting from damage in the spinal cord. Neuropathy Neurological impairment resulting from damage in the peripheral nervous system. Subacute combined degeneration of the spinal cord Degeneration of the posterior and lateral columns of the spinal cord resulting from nutritional deficiency, such as cobalamin, folate, and copper.

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FIGURE 21.6 Representative electron microscopic image of sural nerve biopsy specimen from a patient with folate deficiency neuropathy. Unmyelinated fibers are relatively preserved despite the extent of the loss of myelinated fibers in the specimen from a patient with folate deficiency neuropathy. Representatives of myelinated fibers and unmyelinated fibers are indicated by a thick arrow and a thin arrow, respectively. A band of Bu¨ngner, suggestive of the degeneration of myelinated fibers, is indicated by an arrowhead. Transverse section. Uranyl acetate and lead citrate stain. Scale bar 5 2 µm.

Wet beriberi Disorders of the cardiovascular system caused by thiamine deficiency. Wernicke’s encephalopathy Acutely developing central nervous system disorders caused by thiamine deficiency.

KEY FACTS Regarding Myelopathy and Neuropathy in Alcoholics • The direct neurotoxic effect of ethanol or its metabolites, nutritional deficiency, and liver failure are associated with a variety of neurological disorders. • Myelopathy resulting from liver failure and the toxicity of ethanol or its metabolites is characterized by spastic paraparesis. • In addition to spastic paraparesis, patients with subacute combined degeneration of the spinal cord

manifest sensory ataxia due to loss of deep sensations. • Alcoholic neuropathy without nutritional deficiency is characterized by pain in the lower limbs. • Patients with thiamine deficiency neuropathy may manifest rapidly developing weakness mimicking Guillain-Barre´ syndrome. • Patients with folate deficiency neuropathy tend to exhibit sensory rather than motor symptoms and predominantly deep rather than superficial sensory loss.

SUMMARY POINTS • This chapter focuses on myelopathy and neuropathy associated with alcoholism. • In addition to cerebral involvement, damage to the spinal cord (i.e., myelopathy) and peripheral

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•

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nervous system (i.e., neuropathy) may occur due to alcohol intake. Myelopathy and neuropathy can significantly disturb the functional status and quality of life of patients. The major causes of myelopathy associated with alcoholism are diverse, including liver failure, the direct neurotoxicity of ethanol or its metabolites, and nutritional deficiency, particularly folate. The major causes of neuropathy in alcoholics are the direct neurotoxicity of ethanol or its metabolites and nutritional deficiency, particularly thiamine and folate. For both myelopathy and neuropathy, early diagnosis and treatment are important to avoid irreversible damage.

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C H A P T E R

22 Alcohol Consumption and the Risk of Amyotrophic Lateral Sclerosis Fabrizio D’Ovidio, Umberto Manera and Adriano Chio` “Rita Levi Montalcini” Department of Neuroscience, University of Turin, Torino, Italy

LIST OF ABBREVIATIONS ALS OR SIR CI BMI NMDAr GABA WHO ISTAT

alcohol exposure on ALS; and (3) a final part including some important methodological reflections and sociocultural considerations aimed at interpreting the conflicting results on the association between alcohol and ALS onset.

amyotrophic lateral sclerosis odd ratio standardize incidence ratio confidence interval body mass index N-methyl-D-aspartate receptor gamma-aminobutyric acid World Health Organization Italian National Institute of Statistics

AMYOTROPHIC LATERAL SCLEROSIS: AN OVERVIEW

INTRODUCTION This chapter focuses on the relationship between alcohol consumption and amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disease affecting the motor system (van Es et al., 2017). In particular, the chapter emphasizes the role of alcohol in developing the disease, an area of study that has been explored only marginally and of whose findings remain inconsistent. The reasons may be the differences in alcohol intake among countries and the limitations of available data, study designs or the difficulty of collecting the history of alcohol consumption in elderly persons, like those affected by ALS. Therefore, the aim of this chapter is to explore study-designs and findings of previous studies that focused on alcohol exposure and ALS onset, with particular attention to their methodological and socio-cultural limitations. In order to better illustrate the findings on the association between alcohol and ALS, this chapter is divided into three parts: (1) an overview of ALS, its incidence, etiology, phenotypes, and risk factors; (2) a section exploring the main findings about the effects of

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00022-2

ALS is a neurodegenerative disease, characterized by muscular atrophy leading to death due to respiratory failure. The peak of onset is between 55 and 75 years of age (Chio` & Traynor, 2011). The median survival of ALS is 2 4 years from symptoms onset, while a period of 9 12 months usually occurs from first symptoms to diagnosis (Al-Chalabi & Hardiman, 2013; Chio` et al., 2009). Incidence of ALS varies across the world. A systematic review of published contributes from 1995 to 2011 reported an incidence of 2.08 (IQR 5 1.47 2.43) in Europe, of 1.80 (IQR 5 1.75 2.02) in North America and of 0.60 (IQR 5 0.40 1.43) in Asia (Chio` et al., 2013). The confirmation of ALS diagnosis is a complex process, since there is no definite diagnostic test for ALS and no biomarkers are available to distinguish its phenotypes. Its confirmation is based on clinical procedures, neurophysiological testing results, and exclusion of mimics (Al-Chalabi et al., 2016). The pathogenic mechanism underlying neurodegeneration in ALS is not yet elucidated, although a number of possible mechanisms have been proposed, including oxidative stress, neurofilament accumulations, intracellular protein aggregates, mitochondrial

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dysfunction, inflammation, decreased availability of growth factors, and excitotoxicity (Van Damme, Dewil, Robberecht, & van den Bosch, 2005). Persons with a family history of the disease are at higher risk of developing ALS (Fallis & Hardima, 2009). ALS is familial in about 10% of the cases and apparently sporadic in the remaining 90% (Renton, Chio`, & Traynor, 2014). The etiology of ALS is still unknown, despite the large number of studies focused on genetic risk (an area in rapid expansion), environmental exposures and phenotypes. In the last decades, the genes most frequently identified in ALS patients were SOD1, TARDBP, FUS/TLS, ANG, OPTN, C9ORF72, and VCP (Chio` & Traynor, 2011). Thanks to progress in genetic research, the genetic etiology of two thirds of familial cases and of about 11% of sporadic ALS cases is known (Renton et al., 2014). With regard to environmental etiology, no risk factors for sporadic ALS have been firmly established, with the only possible exception of cigarette smoking, which has consistently been shown to be associated with ALS, particularly in women (Alonso, Logroscino, & Herna´n, 2010). A variety of lifestyle factors has been thoroughly studied in association with ALS onset, including physical activities and traumas (Pupillo, Poloni, et al., 2017), nutritional intake (Pupillo, Bianchi, et al., 2017), drugs consumption (D’Ovidio et al., 2016), hormones (Rooney et al., 2017), phisical activity (Visser et al., 2018), and the performance of specific professions (Sutdeja, Fischer, et al., 2009). This latter area has been explored and has demonstrated that some occupations are significantly associated with ALS onset, like construction workers (Fang et al., 2009), veterinarians and hairdressers (Chio`, Meineri, Tribolo, & Schiffer, 1991; Park et al., 2005), soccer and American football players (Chio`, Benzi, Dossena, Mutani, & Mora, 2005; Lehman, Hein, Baron, & Gersic, 2012), power-production plant operators (Savitz, Loomis, & Tse, 1998), armed forces (Chio` et al., 1991; Haley, 2003), and occupations which imply a direct contact with the public (D’Ovidio, d’Errico, Calvo, Costa, & Chio`, 2017). A relevant emphasis in literature has also been given to the exposure to industrial and agricultural chemicals, like pesticides, solvents, and heavy metals (Ahmed & Wicklund, 2011; Kamel et al., 2012; Sutdeja, Veldink, et al., 2009). Nevertheless, the inconsistency of findings and the poor quality of methodological design—due to the difficulty of exposure assessment, insufficient statistical power, and lack of representativeness, etc.,—reduced the likelihood of identifying established risk factors for ALS (Sutdeja, Fischer, et al., 2009; Sutdeja, Veldink, et al., 2009). Since research is still far from providing a complete framework of established risk factors for ALS, the

discovery of environmental and genetic causes, or the interaction between these two levels, is the priority among scientists all over the world.

THE ASSOCIATION BETWEEN ALCOHOL AND AMYOTROPHIC LATERAL SCLEROSIS The results of studies regarding the relationship between alcohol consumption and ALS onset are not consistent (Meng et al., 2016), in particular when comparing papers from different geographic areas. No significant associations were found in the first studies performed in the United States and Japan in the 1990s, while significant contrasting associations were reported in recent European studies. Table 22.1 summarizes the main contributions on the relationship between alcohol and ALS, reporting study designs, exposure assessment, cases and controls ascertainment, main results, and limitations. The first study that focused specifically on the role of alcohol in ALS development was conducted by Kamel, Umbach, Munsat, Shefner, and Sandler (1999) from 1993 to 1996 in the United States. It was a casecontrol study which recruited 109 ALS cases and 256 controls, frequency matched by age, sex, and geographical area, in which the authors found that ever exposure to alcohol was not significantly associated with ALS (OR 5 1.1; 95% CI: 0.4 3.2). Even considering the cumulative exposure to alcohol, no significant associations and test for trend (P 5 .281) were detected. Another North American (population-based) casecontrol study was conducted by Nelson, McGuire, Longstreth, and Matkin (2000) from 1990 to 1994. A total of 161 incident ALS patients were matched with 321 controls for gender and age ( 6 5 years) by using random digit dialing. Also, in this case, alcohol consumption did not result to be associated with the risk of ALS. Even stratifying the data by type of alcoholic beverage, effect estimates were lower for the highest levels of beer consumption and wine consumption, but not statistically significant. No significant associations were detected in Japan, where Okamoto et al. (2009) explored the effect of alcohol on ALS onset conducting a case-control study, from 2000 to 2005, which enrolled 183 ALS patients and 366 controls randomly matched for age ( 6 2 years) and gender from a register of residents. More recently, two population-based case-control studies performed in The Netherlands found a significant association between alcohol consumption and ALS onset. Both studies enrolled a large cohort of ALS cases and frequency matched controls from general practitioners’ registers. The first one (de Jong et al., 2012) was

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TABLE 22.1 Design, Main Results and Limitations of Studies Focused on the Association Between Alcohol Consumption and ALS Onset Authors and location

Study design

Kamel et al. Case-control study (1993 96). (1999), 109 ALS cases and 256 controls, United frequency matched by age, sex States and telephone area code (as surrogate for region of residence).

Logistic regression analysis adjusted for age, sex, region and education was performed.

Nelson Population-based case-control et al. (2000), study (1990 94). United States

161 incident ALS patients were matched with 321 controls for gender and age within 5 years. Random digit dialing was used to locate eligible controls. Conditional logistic regression analysis was performed, adjusted for age, gender, education, and respondent type (self vs proxy).

Case (and controls) ascertainment

Exposure assessment

Results

Limitations

ALS cases were recruited: (1) through two of the major referral centers in New England; (2) if they had received their first ALS diagnosis within the 2 years prior to enrollment; (3) if they lived in New England at least 50% of the year; and (4) if they were able to complete the study.

Alcohol exposure was defined as ever exposure (having at least 10 drinks of beer, wine or liquor) and cumulative exposure (number of drinks per month).

Ever alcohol exposure was not significantly associated with ALS (OR 5 1.1, 95% CI: 0.4 3.2), as well as the high category of cumulative dose of alcohol exposure (more than 30 drinks per month) (OR 5 1.4, 95% CI: 0.7 3.0) (test for trend P 5 .281).

The direct association between smoking and ALS could be due to bias, since cases were less well educated than controls, suggesting that the two groups might represent different populations with different propensities to smoke.

Controls were eligible to participate: (1) if they lived in New England at least 50% of the year; (2) if they were able to complete the study; and (3) if they were not affected by neurological diseases.

The small and nonsignificant increase in alcohol use among cases was apparently due to confounding by smoking.

Incident ALS cases over 18 years old were identified through multiple local sources: referrals of neurologists, medical examiners, physiatrists, neurosurgeons, neuroradiologists, neuropathologists, and archives of Hospices and Associations.

Alcohol consumption was assessed by using the National Cancer Institute’s Health Habits and History Questionnaire.

Because more than 95% of the region’s households have telephones, random digit dialing was used to locate eligible controls.

Ever and cumulative exposures to beer, wine and liquor consumption were considered.

Alcohol consumption was not associated with the risk of ALS. Stratifying the analysis by type of alcohol, effect estimates were lowest for the highest levels of beer consumption and wine consumption, but not statistically significant.

The alcohol exposure regarded only one recent year of adult Life; information on lifetime drinking habits was not obtained. Nonresponse bias due to the inability to reach some Medicare controls (instead of those reached through random digit dialing).

(Continued)

TABLE 22.1 (Continued) Authors and location

Study design

Okamoto Population-based Case-control et al. (2009), study (2000 2005). Japan 183 ALS patients and 366 controls randomly matched for age ( 6 2 years) and gender from register of residents.

Multiple conditional logistic regression models adjusted for age, sex, BMI, smoking and drinking habits, behavior pattern and total energy were performed. de Jong population-based case-control et al. (2012), study (2006 2009). The Netherlands

Case (and controls) ascertainment

Exposure assessment

214 out of 274 total ALS patients (75.3%) Drinking status was classified as current were eligible cases, but only 183 of whom drinkers or nondrinkers (including exdrinkers). completed the entire questionnaire. ALS patients enrolled were identified using the El-Escorial Criteria. They were 18 81 years old, with a disease duration of maximum 3 years within the study period 2000 2005, in six medical centers in the Tokai area.

Limitations

No significant association with the risk of ALS was found for current alcohol drinkers (OR 5 1.1; 95% CI 5 0.7 1.5), in respect of nondrinkers.

Possible effect of potential bias by proxy respondents in approximately half of the cases.

Current alcohol consumption was significantly associated with a reduced risk of ALS (incident group OR 5 0.52; prevalent group OR 5 0.35; total group OR 5 0.43).

Lack of information on other lifestyle and biometric factors (i.e., physical activity, BMI).

Controls were selected by a proportional simple random sampling with stratification by sex and age groups from among the general population in the same district as our cases based on the electoral register. ALS patients were recruited through multiple sources (neurologists, rehabilitation physicians, patient support associations, and a website). 494 incident and 255 prevalent ALS patients (diagnosed before January 1, 2006, and still alive after that date), diagnosed as having possible, probable (laboratorysupported), or definite ALS, according to the revised El-Escorial Criteria were included.

Data on age at the start and cessation of alcohol consumption, and daily numbers of units of alcohol consumed were collected.

494 patients with incident ALS 1599 controls were recruited through the Alcohol consumption status were and 1599 controls, matched for general practitioners Archives. categorized as never, former, or current gender and age ( 6 5 years), were at the time of ALS onset. recruited through the general practitioners Archives. Multivariate logistic regression models were performed, adjusted for age, gender, educational level and smoking.

Results

Alcohol consumption was not associated In general, persons with survival or age at onset of disease. participating in casecontrol studies are healthier than the general population (Healthy Worker Effect Lifetime consumption of alcohol was The study did not find significant phenomenon). expressed as the total number of units of interaction between alcohol alcohol consumed. Information on the consumption and cigarette smoking. amount of red wine consumed was also recorded, because of its potential antioxidant effect.

Huisman Population-based case-control et al. (2015), study (2006 2011). The 674 incident ALS patients were Netherlands frequency matched with 2093 controls, randomly selected from the general practitioners’ registers, for sex and age.

All patients with a new diagnosis of possible, probable (laboratory supported), or definite ALS according to the revised El-Escorial Criteria were included and multiple sources were used to ensure complete case ascertainment: neurologists, rehabilitation physicians, the Dutch Binary logistic regression models Neuromuscular Patient Association, and a website. with 3 adjustment levels were performed: (1) for age, sex and education; (2) for also BMI, smoking habits, and lifetime physical activity; and (3) for also total energy intake.

D’Ovidio Population-based case-control et al. (2018), study (2011 15). Ireland, Italy, The Netherlands

1557 patients with ALS and 2922 controls, matched for sex, date of birth, and area of residency. Logistic regression models adjusted for sex, age, cohort, education, leisure time physical activity, smoking, heart problems, hypertension, stroke, cholesterol, and diabetes were performed.

Incident cases from Ireland, The Netherlands, and Italy (Lombardia, Piemonte e Valle d’Aosta, Puglia Italian regions), with definite, probable, probable laboratory-supported, and possible ALS were recruited in the study, according to the revised El Escorial Criteria.

Patients and controls were asked to complete a 199-item Food Frequency Questionnaire (FFQ), covering the previous month. If dietary changed since the onset symptom, patients were asked to recall those habits for the 1-month period prior to the ALS onset, in order to avoid a possible influence of disease on their dietary intake.

Higher intake of alcohol was Patients completed the significantly associated with a decreased questionnaires after risk of ALS (OR 5 0.91; 95% symptom onset and CI 5 0.84 0.99). diagnosis. Dietary interventions after diagnosis might affect usual dietary habits and, consequently, the validity of answers.

Alcohol consumption data were gathered using: the ever exposure to alcohol; the years of start and cessation of alcohol drinking; the number of years of abstinence; the number of glasses of alcohol per week (distinguished by general alcoholic beverages and red wine).

The overall intake of alcohol was not significantly associated with ALS (OR 5 0.93; 95% CI 5 0.75 1.15), although a significant increased risk for former drinkers was detected (OR 5 1.63; 95% CI 5 1.11 2.38).

In order to control for reverse causation, exposures to smoking, physical activity, cardiovascular risks, and alcohol were truncated 3 years before date of survey, for both cases and controls.

Stratifying the association by ALS cohort, alcohol drinkers in the Netherlands reported a lower probability to develop ALS (OR 5 0.68; 95% CI 5 0.47–0.98), while generic and red wine drinkers from Southern Italy reported a twofold increased risk in developing ALS (OR 5 2.38; 05% CI 5 1.35–4.21 and OR 5 2.53; 95% CI 5 1.43–4.46, respectively)

Lack of information about healthy BMI and about the exposure to other types of alcoholic beverages, such as white wine, spirits, and beer.

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performed from 2006 to 2009 and included 494 incident ALS patients and 1599 controls. The current alcohol consumption proved to be significantly associated with a reduced risk of ALS (incident group OR 5 0.52; prevalent group OR 5 0.35; total group OR 5 0.43). The other Dutch study was conducted by Huisman et al. (2015) from 2006 to 2011, enrolling an even larger cohort of patients (N 5 674) and controls (N 5 2093), and found that a higher intake of alcohol was significantly associated with a decreased risk of ALS (OR 5 0.91; 95% CI 5 0.84 0.99); however, this study did not separately assess current and former alcohol drinkers. Another study specifically focused on alcohol use disorders was conducted in Sweden, where Sundquist and Sundquist (2016) found a decreased risk of ALS associated with alcohol intake. The authors followed up a cohort of 7965 ALS patients diagnosed with ALS during the period 1973 2010, 136 with and 7829 without alcohol use disorders. The study revealed an overall SIR of 0.54 (95% CI 5 0.45 0.63), a finding consistent for all stratified analyses by gender, educational level, birth county, follow-up period, and smoking (derived from diagnosis of chronic obstructive pulmonary disease). Lastly, a recent European case-control study (EuroMOTOR) on the association between alcohol exposure and ALS was performed (D’Ovidio et al., 2018). This study collected clinical, environmental, and genetic data on 1557 ALS cases and 2922 controls enrolled in The Netherlands, Ireland, and four Italian regions (Piedmont, Valle d’Aosta, Lombardy, and Apulia) (D’Ovidio, Rooney, Visser, Vermeulen, et al., 2017). In general, preliminary analysis revealed no significant association between ever and cumulative exposure to alcoholic beverages and ALS onset, but showed a significantly increased risk of developing ALS in former alcohol drinkers (OR 5 1.63; 95% CI 5 1.11 2.38). Stratified analysis revealed that alcohol was a protective factor in The Netherlands (OR 5 0.68; 95% CI 5 0.47 0.98) and a risk factor in Apulia, Southern Italy (OR 5 2.38; 95% CI 5 1.35 4.21). Furthermore, since in studies based on animal models the intake of red wine in a lyophilized form was found to increase mean survival time (Amodio et al., 2006; Esposito et al., 2000; Patel & Hamadeh, 2009), presumably because of the blocking effect of antioxidants on glutamate-induced apoptosis in neurons, red wine exposure was also considered in the EuroMOTOR case-control study. ORs related to red wine consumption did not prove to be significantly associated with ALS disease, but remained directly associated with ALS onset in Southern Italy (OR 5 2.53; 95% CI 5 1.43 4.46). Presumably, beverages consumed in The Netherlands other that wine increase the protective role of alcohol against developing ALS, while red wine,

consumed by 90% of the Southern Italian cohort drinkers, is probably a risk factor for Italian people. Also in this case, as well as for general alcohol intake, analysis did not show significant associations considering cumulative exposure of red wine consumption. However, the study did not discriminate between the different types of alcoholic beverages, like white wine, beer and spirits, what represented a strong limitation for this study and, on a general level, for the possibility to have a clear and complete picture of the role of alcohol in the development of ALS.

WHY RESULTS ARE SO CONFLICTING AND HETEROGENEOUS? The findings reported in the previous section require some considerations, since inconsistencies could be due either to different study designs or to intrinsic differences between geographical areas. For both features, methodological issues might play an important role in exploring this relationship. For example, can the quality of exposure assessment affect the results? Why does literature show results that are so different between geographical areas? Is it possible to consider the intake of alcoholic beverages in the same way in different countries? In order to answer these questions, some preliminary considerations are necessary. The process of identification of environmental risks factors for ALS can be performed through two main observational designs, that is, cohort and case-control studies. Especially for the representativeness issue, the former ones may be preferred but they could have limited power in the ALS research context due to the low incidence of the disease, the difficulty of assessment of exposures and the risk of misclassification of ALS (Rothman, Greenland, & Lash, 2008). For this reason, almost all studies that focused specifically on the association between alcohol and ALS onset adopted casecontrol study design. However, since in case-control studies information is collected through questionnaires and ALS patients have a mean age of 65 years, it is likely that a complete identification of exposures is affected by recall biases. A possible approach to minimize recall bias could be the use of a very detailed questionnaire (D’Ovidio, Rooney, Visser, Vermeulen, et al., 2017), which however makes data collection more complicated and could influence response rates and external validity. A better approach to avoid recall bias is represented by the use of official registers with sufficient historical depth of data, but unfortunately these registries are not easily available. A collection of integrated clinical and environmental data of the whole population—or part of it—begun only during

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CONCLUSIONS

the past few decades mainly in Northern European countries, but some decades will be needed to have a complete frame of information at individual level. Another main problem to account for performing a well-designed case-control study is represented by the size of the samples. In both American and Japanese case-control studies on the association between alcohol and ALS (Kamel et al., 1999; Nelson et al., 2000; Okamoto et al., 2009), the number of enrolled cases and controls was quite low (ranged between 109 and 183 cases). Furthermore, other limitations of studies should be considered: in one American study (Kamel et al., 1999) cases were less educated than controls, suggesting that the two groups represent different populations; the study performed by Nelson et al. (2000) had a high nonresponse bias due to the inability to reach some controls by random digit dialing; lastly, in the Japanese study conducted by Okamoto et al. (2009), information on alcohol exposure was provided by half respondents controls (even if no age and gender differences were detected) and the questionnaire was self-administered. The European case-control studies are characterized by a greater sample size (ranged between 494 and 1557 cases), with double matched controls (even triple in the Dutch studies) and demonstrated a significant protective role of alcohol. Nevertheless, these studies have some important limitations regarding mainly the lack of lifestyle and biometric data availability (i.e., physical activity or BMI) and the global assessment of the different types of alcoholic beverages. This last limitation could be crucial when studying alcohol as a risk factor, especially in international studies conducted in different countries. Differences in alcohol consumption between countries—but also between different areas of the same country—depend on a complex range of economic, sociodemographic, cultural, and religious factors. Furthermore, alcohol consumption also varies according to the types of alcoholic beverages, mostly wine, beer, and spirits, which differ in alcoholic strength and ingredients, as well as in their production process. According to a recent WHO report (2014), the most consumed alcoholic beverage in the world were spirits (50.1%), followed by beer (34.8%), while only 8% of alcohol was consumed as wine. However, differences between geographical areas were very important, to the point that wine consumption made up one fourth of the total consumption in the WHO European countries (25.7%) and beer represented the most consumed alcoholic beverage in the Americas (55.3%). The European case-control studies on the association between alcohol and ALS showed contrasting results. That could be due to intrinsic differences in alcohol consumption in the examined countries. For example,

in the same WHO report (2014), beer was the most reported consumed beverage in The Netherlands (46.8%), followed by wine (36.4%) and spirits (16.9), with a total of pure alcohol per capita of 11.2 g/day. In Sweden, the pure alcohol intake per capita per day was 28.4 g and the most consumed beverage was wine (46.6%), like in Italy which instead represented the second European country with the highest wine consumption (65.6%) and lowest spirits intake (11.5%), after Slovenia (8.6%). According to a recent report by Istat (2017), the consumption of wine and beer in Northern Italy was higher than in the South. Therefore, it would be reasonable to expect different associations between alcohol and ALS in the three Euro-MOTOR Italian cohorts, referred to Northern and Southern Italy, due to different lifestyle habits, vineyard management techniques, and winemaking processes.

CONCLUSIONS The relationship between alcohol and ALS represents a complex area of research, in which available studies reported inconsistencies. In the American and Japanese studies, findings did not show significant evidences of the role of alcohol on developing the disease. On the contrary, in recent European studies alcohol was found to be significantly correlated to ALS, although in opposite directions: inversely associated in Sweden and in The Netherlands, and directly associated with ALS in Southern Italy. Even if the type and the quality of the research designs might have played a relevant role in determining these conflicting findings, a well-designed research could not be sufficient to approach the assessment of the relationship between alcohol and ALS. The conflicting results could also be due to several biological mechanisms. Ethanol produces various effects on the central nervous system (Roberto & Varodayan, 2017): (1) it increases the GABA action on GABA-A receptors and, consequently, increases the inhibitory neurons activity; (2) it inhibits calcium intake via voltagedependent calcium channels; and (3) it inhibits the NMDA receptor functions. These mechanisms go in the opposite direction of the excitotoxicity, which represents one of the few recognized mechanisms responsible for ALS (Van Damme et al., 2005), and could justify the neuroprotective role of alcohol found in Northern European studies. To understand the results obtained in Southern Italy, a different approach might be used. Since wine is the most consumed alcoholic beverage in Italy (WHO, 2014), it would be reasonable to consider that the typical amount of alcohol contained in wine ranges only between 9% and 16%,

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while the remaining volume is represented by a variety of other chemical compounds—which have not been studied yet in ALS—like sugar, acids, minerals, phenolic compounds, and additives (Artero, Artero, Tarı´n, & Cano, 2015). Moreover, the chemical or biological composition of wine is strictly related to the concept of terroir, the set of environmental and cultural factors including soil, climate, terrain, and traditional viticulture and winemaking practices that impart a distinctive taste and flavor to the wine of a specific region. As a consequence, wine compounds vary considerably among winemaking regions and their systemic interaction, along with the geographical and climate differences between Northern and Southern Europe, is most likely to influence the relationship between alcohol and ALS. The link between alcohol and ALS still represents an unexplored field of study, where the different alcohol intake patterns and the type of alcohol beverage(s) must be taken into account, especially on the basis of the interactions between environmental and genetic factors. Further investigation on this topic is, therefore, required.

MINI-DICTIONARY OF TERMS Cohort study The analysis unit is represented by a cohort of population identified by the exposure or event of interest, followed prospectively or retrospectively within a temporal framework until an outcome (event or disease) occurs. Causality can be assessed by the temporal intervals between exposures and outcome, providing strong scientific evidence. Case-control study Subjects enrolled in a case-control study are identified by outcome status (i.e., type of surgery, complication, certain disease diagnosis). On the basis of outcome specification, two groups of cases and controls are selected, composed respectively by subjects affected by the disease of interest and by healthy subjects, or subjects not affected by the disease of interest. This kind of observational study is well suited to investigate rare diseases, or in general when information on entire cohort of population are not available. Odds ratio (OR) It is a measure of association between an exposure and an outcome. It combines the odds that the outcome occurs given a particular exposure compared to the odds of the outcome occurring in the absence of that particular exposure. Confidence interval It is an estimate interval which is likely to include an unknown population parameter, with different thresholds of probabilities commonly defined at 95% or 99%. BMI The Body Mass Index (BMI) represents a useful tool to indicate whether a person is underweight, normal (healthy weight), overweight or obese. The formula is kg/m2, where kg represents the mass in weight and m the height in meters. Excitotoxicity A deleterious cellular response to excitatory stimulation leading ultimately to cell death. This mechanism can occur either by inappropriately high activity of the presynaptic neuron, by abnormal responsiveness of the postsynaptic neuron to excitatory stimuli or both factors combined. Glutamate is the principal neurotransmitter involved and can damage neurons

by allowing high levels of calcium ions (Ca2 1 ) to enter via ligand gated ion channel. GABA It is the main inhibitory neurotransmitter in the human central nervous system. It is synthesized from glutamate using the enzyme glutamate decarboxylase (GAD) and pyridoxal phosphate as a cofactor. It works on two general classes of GABA receptor: GABAA, an ionotropic receptor and ligand-gated ion channel and GABAB metabotropic receptors, which are G protein-coupled receptors that open or close ion channels via intermediaries. NMDAr It is one of three types of ionotropic glutamate receptors, together with AMPA and kainate receptors, that can be present in neurons. It allows positively charged ions to flow through the cell membrane, such as calcium ions. The activity of the NMDA receptor is affected by many psychoactive drugs such as alcohol (ethanol).

KEY FACTS Amyotrophic Lateral Sclerosis • ALS is the most common adult-onset motor neuron disease. • On average, ALS leads to death after 3 years from the first symptoms. • According to a systematic review (Chio` et al., 2013), the estimated worldwide annual incidence of ALS in 2010 was about 1.9 per 100,000 subjects, with a median of 30.038 incident cases and 60.495 prevalent cases in Europe, Asia (Japan and China) and the United States. • There is no cure for ALS, but pharmacological, supportive and psychological treatments can increase ALS patients’ life expectancy and quality of life. • ALS is a progressive disease which causes high economic, familial and social burden. • ALS is familial in about 10% cases and sporadic in the remaining 90%. • The etiology of ALS is still unknown, despite the high quantity of studies performed. • Recent studies encourage a different approach in studying the etiology of ALS, based on the interplay between genetic and environment factors.

SUMMARY POINTS • This chapter focuses on the role of alcohol in the development of ALS. • ALS causes a progressive loss of muscle strength of limbs, dysphagia, dysarthria, and respiratory failure. • Literature on the association between previous consumption of alcohol and ALS onset produced conflicting results.

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• According to a recent WHO report, differences of alcoholic beverages consumption across the countries were considerable, and ethanol is just one of the chemical compounds contained in these alcoholic beverages. • The reasons of such conflicting results could be due to the type and quality of the research designs, methodological limitations, the lifestyle habits, the ethnicity, and the variety of production processes or the type of alcoholic beverages in different geographical areas.

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C H A P T E R

23 Alcohol and Pain Interactions 1

Henry L. Blanton1, Susan E. Bergeson1, Daniel J. Morgan2 and Jose´e Guindon1 Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, United States 2Department of Anesthesiology, Penn State College of Medicine, Hershey, PA, United States

LIST OF ABBREVIATIONS AUD BEC CDC COX-2 CRF DID DMM GABA GIRK IV NMDA NSAIDs PAG PKC PSNL SNRI SSRI

alcohol use disorder blood ethanol concentration center for disease control cyclooxygenase 2 corticotropin-releasing factor drinking in the dark destabilization of medial meniscus gamma-aminobutyric acid G protein-regulated inward-rectifying potassium channels intravenous N-methyl-D-aspartate nonsteroidal antiinflammatory drugs periaqueductal gray protein kinase C partial sciatic nerve ligation serotonin norepinephrine reuptake inhibitor selective serotonin reuptake inhibitor

INTRODUCTION Major health issues and unmet clinical treatment needs are associated with the interaction of alcohol use disorder (AUD) and managing pain as suggested by numerous clinical reports and emerging evidence from animal models (Apkarian et al., 2013). Severe AUD (DSM-V 2017) affects B10% of the population worldwide and the AUD spectrum costs the United States $249 billion dollars annually in morbidity, mortality, and personal suffering costs (CDC, 2017). Binge drinking, defined as .0.08 g/dL blood ethanol concentration (BEC; expressed as 0.8 mg/mL in rodent research), typically appears after the consumption of four drinks for women and five drinks for men in less

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00023-4

than two hours. Binge drinking and heavy alcohol use affects 26.9% and 7% of people ages 18 or older, respectively (NSDUH, 2015). The 2012 National Health Interview Survey (NHIS) found that 55.7% (126.1 million) of United States adults experienced some form of chronic pain (Nahin, 2015). The Center for Disease Control reports that chronic pain associated costs in the United States ranges between $560 billion to $635 billion annually (Gaskin & Richard, 2012). Research to better understand the increased risk for AUD in chronic pain patients, as well as adverse ethanol-related increases in pain intensity and duration, have garnered increasing attention (Apkarian et al., 2013). Similar to the sensory components of pain, the cognitive/evaluative and emotional/affective components (Fig. 23.1) to pain perception display well-known interactions with alcohol consumption. For example, comorbidity of chronic pain and mental illness, such as anxiety disorders (Carleton et al., 2018) and depression, are prevalent (Boselie, Vancleef, & Peters, 2018). There is also evidence that chronic pain adversely affects cognitive function (Cowen et al., 2018). Furthermore, considerable overlap exists between the mechanisms and genetic factors that modulate reward and stress pathways (Yeung, Craggs, & Gizer, 2017). Interestingly, the interaction of pain and alcohol during prenatal development indicates that children born following high fetal alcohol exposure have altered pain responses.

PAIN Pain has complex and multifaceted physiological components and mechanisms (Fig. 23.1). Pain can be

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FIGURE 23.1 Dimensions of pain and influencing factors. Pain comprises sensory-discriminative, motivational-affective, and cognitive-evaluative dimensions and is influenced by different factors that influence an individual’s experience, perception, and recovery from pain as shown.

FIGURE 23.2 Different types of pain. Pain is felt, experienced, and processed differently depending on the location and individual differences.

somatic or visceral in origin, as well as superficial or deep (see Guindon & Hohmann, 2009 for review). Importantly, many forms of pain can be adaptive while other forms of chronic and/or pathological pain are maladaptive and require clinical treatment (Fig. 23.2). Processing of the site, intensity, duration, and quality of pain occurs through reflex circuits in the spinal cord as well as through supraspinal ascending and descending pathways between the brain and spinal cord (Fig. 23.3). Multiple regions of the brain

including the prefrontal and somatosensory cortex, motor cortex, periaqueductal gray (PAG), rostroventral medulla, hypothalamus, and amygdala are involved in relaying, integrating, perceiving, responding to, and modulating sensory, cognitive, and affective pain components (Fig. 23.3). The treatment of pain represents a huge medical, economic, and societal burden that is largely unmet. Despite the use of anticonvulsants, antidepressants, local anesthetics, anxiolytics, nerve blocks, neurotoxins, nonsteroidal antiinflammatory drugs (NSAIDs), and opioids approximately 50% of patients report inadequate pain relief from currently available treatments. Furthermore, the widespread use of prescription opioids in pain management have contributed to the current opioid health crisis (Madras, 2018). In the United States, 214,881,622 opioid prescriptions were dispensed in 2012, a prescription rate of 66.5 prescriptions per 100 persons. The rise in opioid prescriptions since the 1990s has coincided with an increase in opioid-related deaths that reached an unexpected proportion in 2015 with 15,281 persons dying from opioid overdose (CDC, 2017). Perhaps not surprisingly, AUD, among other substance use disorders, is the strongest predictor of opioid misuse (Turk, Swanson, & Gatchel, 2008). Although, for the past three decades, opioid compounds were often used as the “first line of defense” in pain management based on their relatively high efficacy, chronic pain specialists now have become increasingly reluctant to use these compounds due to the risk of addiction and overdose. Thus, the identification of additional pharmacological, behavioral, or cognitive methods to alleviate pain is an important and timely medical need. Clearly defining pain is a unique and evolving challenge as the various subtypes and modalities of pain make consensus difficult (Guindon & Hohmann, 2009 for review). The ancient Greeks did not view pain as a sensation, but rather as a homeostatic state like emotion or appetite. In their conceptualization, pain was the opposite of pleasure. The concept of pain as a sensation, with a specific pathway of transmission was the cornerstone of the specificity theory, developed by Decartes in 1664. The understanding of the sensory pathways of pain was expanded in greater detail by Muller, Goldschider, and von Frey (Guindon & Hohmann, 2009 for review). The interplay between the sensory, cognitive, and affective components of pain was further elucidated in the 20th century. Pavlov demonstrated that displays of evoked pain could be suppressed in food-conditioned animals, indicating that pain could be modulated by psychological factors. Currently, the predominant theory of pain is that it comprises sensory-discriminative, motivationalaffective and cognitive-evaluative dimensions, with

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PAIN SIGNALING

FIGURE 23.3 Ascending pain signaling and descending pain inhibition. Free nerve endings located on A delta and C fibers in the periphery are activated by a variety of noxious stimuli that may be chemical, mechanical, or thermal in nature. This sensory information is transmitted along a pathway called the anterolateral system/spinothalamic tract, from the periphery to the spinal cord and brain. Descending pain pathways are activated in order to quell the ascending pain signaling from the brain to inhibitory interneurons at the dorsal horn of the spinal cord and ending at the periphery.

various internal and external factors influencing these dimensions (Fig. 23.1). Although our definition and understanding of pain has evolved through time, the pharmacological treatment options for treating pain have remained narrowly focused on a relatively few number of critical targets (Guindon, Walczak, & Beaulieu, 2007). Plantbased medicines such as opium, cannabis, salicylaterich extracts, and natural preparations such as ethanol were some of the earliest agents used in pain pharmacopeia. Ethanol in particular has a well-documented history of broad application in medicine as an anesthetic, antiseptic, and analgesic agent. However, ethanol’s broad and inadequately characterized pharmacological targets, toxic metabolites, and potential for abuse represent concerns for health professionals that prevent clinical use (NSDUH, 2015). As explored in this chapter, the use of ethanol as an

analgesic can be problematic due to its ability in both animal models and human subjects to exacerbate existing pain and increase the likelihood of developing chronic pain.

PAIN SIGNALING The mechanics of pain have been well-established as a model of transduction, transmission, modulation, and perception (Guindon & Hohmann, 2009 for review). At the site of injury, noxious mechanical, thermal, or chemical stimuli are transduced into action potentials by primary afferent nociceptors in the periphery (Melzack & Wall, 1991). Those action potentials are transmitted to second-order neurons in the dorsal horn of the spinal cord through peripheral A δ and C fibers. Axons from these second-order

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FIGURE 23.4 Assessment of pain in humans. Four valid instruments to assess pain in humans: (1) McGill Pain Questionnaire, (2) VisualAnalog Scale, (3) Verbal Rating Scale, and (4) Smile-Sad Faces Scale.

dorsal horn neurons cross over to the contralateral side of the spinal cord and ascend to the brain via the spinothalamic tract where they synapse onto third order neurons in the ventroposterolateral nucleus of the thalamus (Fig. 23.3). The thalamus then relays nociceptive information to various cortical and limbic structures, such as the sensory cortex and amygdala (Melzack & Wall, 1991). Various brain regions modulate pain signals received from the periphery. Notably, pain is attenuated by activation of the PAG (Reynolds, 1969). The PAG receives input from the thalamus and various cortical areas such as the sensory and motor cortex and extends descending pain pathways to the spinal cord via the rostroventral medulla and the dorsolateral funiculus. These descending pain pathways can inhibit pain transmission through the activation of inhibitory spinal interneurons (Basbaum & Fields, 1978). Finally, perception describes the personal experience and evaluation of pain, which can be altered by various psychological and physiological factors (Guindon et al., 2007).

CLINICAL EVALUATION OF PAIN The evaluation of pain in humans involves description of pain experienced across the sensory, affective,

and cognitive dimensions (Melzack, 2005). Pain in humans can be assessed and quantified in verbal, smile-sad faces, or visual-analog scales (Fig. 23.4). These scales are limited in their scope of assessment, typically only evaluating one component of pain. Verbal scales typically evaluate pain intensity (Beecher, 1959), while visual-analog scales (VAS) and smile-sad faces (Faces Pain Scale) evaluate the unpleasantness associated with pain (Nielsen, Price, Vassend, Stubhaug, & Harris, 2005). The McGill pain questionnaire (Melzack, 2005) was developed to comprehensively evaluate all three dimensions of pain using sensory, affective, and cognitive-evaluative descriptors, and is a valuable clinical and research tool that represents the “gold standard” in the clinical assessment of pain (Fig. 23.4). In contrast, behavior-based pain assessments are used in patients where self-rated measures are not possible, such as for infants or adults without the cognitive or language capacity to do so (Ross & Ross, 1984). Animal models of pain that mimic human pain pathologies have been essential to better understand the physiological, cellular, and molecular mechanisms responsible for pain signaling and for the development of novel analgesic treatments. Acute pain can be induced in animals via noxious mechanical, thermal, or chemical stimulation (Dubner & Ren, 1999). There are also models of persistent and pathological pain

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EFFECTS OF ETHANOL ON ACUTE PAIN

conditions such as nerve injury or chemotherapyinduced peripheral neuropathy (Guindon & Hohmann, 2009 for review) where hypersensitivity to normally innocuous stimuli, a condition known as allodynia, can be measured. The behaviors and physiological responses elicited by application of these noxious stimuli correlate well to pain behaviors in humans (Dubner & Ren, 1999).

ALCOHOL AND PAIN The relationship between alcohol use and pain is a growing field of interest, and one that is highly relevant to the general population. Although there is a great deal of evidence demonstrating the negative effects of chronic and excessive ethanol consumption, there is also some evidence suggesting positive benefits associated with lower doses and reduced use of ethanol including decreased risk of heart attack, stroke, and diabetes (CDC, 2017; NSDUH, 2015). Additionally, it has been suggested that low to moderate ethanol consumption may correlate to decreased risk for chronic pain compared to either high ethanol consumption or complete abstinence (Zale, Maisto, & Ditre, 2015).

EFFECTS OF ETHANOL ON ACUTE PAIN In preclinical rodent models, acute administration of a moderate dose of ethanol (2 g/kg) produces antinociception to acute thermal stimuli in the tail-flick assay (Gatch & Lal, 1999). Exposure to a liquid diet containing ethanol produced rapid tolerance to the antinociceptive effects of ethanol in the tail-flick test (Gatch & Lal, 1999) while withdrawal after 10 days of the ethanol liquid diet produced marked hyperalgesia in the tail-flick test. Ethanol was also found to exhibit antinociceptive effects in the hotplate test, another test for acute thermal pain (Campbell, Taylor, & Tizabi, 2007). Acute or chronic ethanol exposure during early neonatal development in rats has been shown to potentiate formalin, but not postsurgical mechanical and thermal allodynia (Shumilla, Sweitzer, & Kendig, 2004). Thus, the acute antinociceptive effects of ethanol appear to be dependent on the type of pain being examined. Fewer studies investigating the acute analgesic effects of ethanol in humans have been performed. Administration of intravenous (IV) ethanol (1 g/dL) to healthy human subjects caused an increase in the subject’s ability to tolerate a painful electrical stimulus without altering the stimulus threshold required to perceive it as painful (Perrino et al., 2008). Interestingly, the effect of IV ethanol on tolerance to

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painful electrical stimuli was enhanced at low doses of ethanol in patients with high levels of neuroticism and a family history of alcoholism, emphasizing the multifaceted nature of pain (Ralevski et al., 2010). Additional studies have demonstrated the ability of oral or IV ethanol to dampen electric shock pain stimulus (Stewart, Finn, & Pihl, 1995) and mechanical pressure pain (Woodrow & Eltherington, 1988) in human subjects. The mechanism of action for the antinociceptive effects of ethanol has been proposed to involve signaling through the opioid, GABA, and glutamate systems, among other mechanisms (Fig. 23.5). The use of opioid receptor antagonists demonstrates that the antinociceptive effects of ethanol in the tail-flick test, and to a lesser extent in the hotplate test, are at least partially opioid-dependent (Campbell et al., 2007). Studies using naloxone to block ethanol-induced antinociception have generated mixed results. Some studies have demonstrated that naloxone can inhibit ethanol-induced antinociception (Boada, Feria, & Sanz, 1981) while others have failed (Jorgensen & Hole, 1981). More recent work using selective antagonists for the mu, delta, and kappa receptors demonstrate that the antinociceptive effects of ethanol in the tail-flick test, and to a lesser extent in the hotplate test, are at least partially opioid-dependent (Campbell et al., 2007). This finding raises the possibility that ethanol-induced antinociception mediated at the level of the spinal cord (tail-flick) may be more dependent on opioid mechanisms than antinociception that relies more heavily on supraspinal pathways (hotplate). Interestingly, acute ethanol has been found to reverse tolerance to the antinociceptive effects of morphine and oxycodone, further illustrating the complex interplay between ethanol and the opioid system (Jacob, Poklis, Akbarali, Henderson, & Dewey, 2017). A study in human subjects found that naloxone was not able to completely abolish ethanol-induced analgesia (Saddler, James, & Harington, 1985). However, it is also well-established that ethanol consumption stimulates the release of endogenous opioids in the orbitofrontal cortex and nucleus accumbens of human subjects (Mitchell et al., 2012). The sedative effects of ethanol are mediated through positive allosteric modulation of the GABAa receptor, like the benzodiazepine class of anxiolytics. Therefore, it is not surprising that GABAergic signaling is also involved in the antinociceptive effects of ethanol. Pretreatment with flumazenil, a benzodiazepine antagonist, completely abolished ethanol-induced antinociception in the tail-flick test (Gatch, 1999). More recent work demonstrates that acute administration of ethanol into the medial prefrontal cortex (mPFC) produces antinocieption for mechanically-induced acute pain

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FIGURE 23.5

Proposed mechanisms of alcohol analgesia. Alcohol has numerous target sites, with a net inhibitory effect on cell excitability. Alcohol’s primary effect is potentiation of the inhibitory effects of GABA at the GABAa receptor. Other mechanisms of inhibition include excitatory NMDA receptor blockade, potentiation of hyperpolarizing potassium currents, and inhibition of depolarizing calcium currents. The opioid system has demonstrated involvement in the reinforcing effects of alcohol, and this system, along with the endocannabinoid system may play a role in ethanol’s analgesic effects.

through the activation of GABAA receptors (Geng et al., 2016). Glutamatergic signaling through the NMDA receptor has been also shown to contribute to the nonopioid component of ethanol-induced antinociception. Blockade of the NMDA receptor using MK801 diminished ethanol-induced antinociception and coadministration of both MK-801 and naloxone completely abolished this analgesic effect (Mogil et al., 1993). Additional studies demonstrate the importance of other mechanisms for ethanol-induced antinociception. For example, previous work found that ethanol can open G protein-regulated inward-rectifying potassium (GIRK) channels that are involved in the modulation of neuronal excitability (Kobayashi et al., 1999). Mice lacking GIRK2, one of the neuronal isoforms of this channel, display a marked reduction in ethanolinduced antinociception (Kobayashi et al., 1999). Ethanol-induced antinociception was diminished in rats treated with the L-type calcium channel antagonist, nitrendipine, while ethanol withdrawal-induced hyperalgesia was completely abolished by this antagonist (Gatch, 1999).

EFFECTS OF CHRONIC ETHANOL ON PAIN Estimates of peripheral neuropathy in patients with AUD vary widely (12.5% 66%) depending on study inclusion criteria used (Chopra & Tiwari, 2012). The specific causes for the correlation between AUD and pain in human subjects are not well-understood. While evidence suggests that neurotoxicity from AUD might drive neuropathic pain (Zale et al., 2015) there is also evidence to suggest that chronic pain can cause patients to self-medicate with alcohol (Witkiewitz et al., 2015). The severity of the affective component to pain, lack of relaxation strategies, and being male have been shown to be the strongest predictors of AUD (Lawton & Simpson, 2009). Sex differences represent an important factor in the association between AUD and chronic pain. Males are more likely to be diagnosed with AUD and also report greater use for anxiolytic and analgesic effects than females. (Zale et al., 2015). Induction of chronic pain caused by partial sciatic nerve ligation (PSNL) induced increased alcohol drinking in mice (Gonza´lez-Sepu´lveda, Pozo, Marcos, &

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TREATMENT OPTIONS

Valverde, 2016). Glutamatergic signaling and IL-1β expression were both increased in mice subjected to PNSL surgery (Gonza´lez-Sepu´lveda et al., 2016), providing additional evidence that neuro-immune function and glutamate homeostasis play important roles in alcohol-pain interactions. Our own work has found that repeated cycles of intoxication and withdrawal in the DID (drinking in the dark) model of binge alcohol consumption potentiates inflammatory formalin pain and produces mechanical and thermal allodynia (Bergeson et al., 2016). Chronic exposure to a liquid diet containing ethanol is sufficient to cause neuropathic pain in rats (Dina et al., 2008). The mechanism for this ethanolinduced neuropathic pain is not well-understood, but has been proposed to be caused by small fiber neuropathy due to the neurotoxic effects of ethanol (Diamond & Messing, 1994), as well as through the engagement of neurocircuitry that produces a persistent state of negative affect (Egli, Koob, & Edwards, 2012). The activation of microglia, inflammatory cytokine signaling, free radical generation, and metabolism of ethanol to cytotoxic acetylaldehydes have been proposed to be involved in the etiology of alcoholic small fiber neuropathy (reviewed by Chopra & Tiwari, 2012). Although an acute episode of intoxication and withdrawal is sufficient to cause transient mechanical allodynia (reviewed by Gatch, 1999), additional work has found that multiple cycles of intermittent ethanol access and withdrawal potentiate the severity of ethanol withdrawal-induced hyperalgesia in rodent models (Dina et al., 2008). Hyperalgesia to thermal and electrical stimulation has also been observed in humans during ethanol withdrawal (Jochum, Boettger, Burkhardt, Juckel, & Bar, 2010). The mechanisms responsible for chronic ethanolinduced enhancement of pain response require further investigation, but have been shown to involve some of the same allostatic signaling mechanisms and pathways that also drive alcohol relapse. Animal studies have demonstrated that ethanol withdrawal-induced hyperalgesia can be attenuated by diazepam (Gatch, 1999), the NMDA antagonist MK-801 (Dunbar & Yaksh, 1996), calcium channel blockers (Gatch, 2006), and COX-2 inhibitors (Dhir, Naidu, & Kulkarni, 2005). Inhibition of protein kinase C (PKC) has been shown to reverse ethanol-induced neuropathic pain as well as hyperalgesia associated with ethanol withdrawal (Dina et al., 2008). It has been hypothesized that seeking relief from the negative affect and hyperalgesia during ethanol withdrawal might drive additional episodes of intoxication. Chronic exposure to ethanol vapor confers dependence in rats while also causing robust mechanical allodynia that was dose-dependently

reversed by treatment with the corticotropin-releasing factor (CRF) receptor 1 antagonist, MPZP (Edwards et al., 2012). Additional studies have found that neuropathic pain caused by ethanol-stimulated activation of hypothalamic-pituitary stress axis is glucocorticoid receptor dependent and also requires epinephrine signaling through the beta-2-adrenergic receptor (β2-AR) (Dina et al., 2008).

TREATMENT OPTIONS Treatment options for comorbid AUD and chronic pain are limited and this represents a critical unmet medical need that requires novel pharmacological interventions (Fig. 23.6). Vitamin B formulations have been investigated in the clinic and have shown efficacy in the treatment of alcohol-induced neuropathy (Peters et al., 2006). Other proposed therapeutic options represent standard treatments for neuropathic pain including alpha-lipoic acid, vitamin E, acetyl-L-carnitine, N-acetylcysteine, methylcobalamine, topical capsaicin, selective serotonin, or norepinephrine reuptake inhibitor (SSRI or SNRI) antidepressants, neurotoxins, topical analgesics, and anticonvulsants such as gabapentin (Chopra & Tiwari, 2012). Preclinical studies demonstrate the potential benefit of approaches that target affective or reward pathways for the treatment of comorbid pain and AUD. For example, animal models have demonstrated that blocking stress-associated signaling pathways through the use of CRF1R glucocorticoid receptor, and β2-ARs antagonists can mitigate alcohol-induced pain (Dina et al., 2008; Edwards et al., 2012). Other studies have demonstrated that selective kappa-opioid receptor antagonists might be able to reduce ethanol self-administration in dependent animals (Walker & Koob, 2008). Our own work demonstrates that tigecycline, a glycylcycline antibiotic, can be used to reverse mechanical and thermal allodynia associated with binge-like drinking (Bergeson et al., 2016). However, tigecycline was able to reverse ethanol-induced allodynia in male, but not female, mice demonstrating the importance of understanding sex-specific pathways involved in AUD and pain (Bergeson et al., 2016). Changes in neurochemistry produced by pharmacological interventions alone are likely not sufficient to completely eliminate either AUD or chronic pain (Fig. 23.6). Thus, additional cognitive and behavioral modification techniques might also be needed for effective treatment of AUD and AUD-associated chronic pain. For example, one study found that human subjects self-reporting pain in affective terms were more likely to abuse alcohol compared to

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FIGURE 23.6 Breaking the cycle: alcohol and pain. It is often unclear when chronic pain, substance dependence, and affective disorders are present together whether there was a single initiatory moment that cascaded. An injury may occur first, prompting seeking pain relief from prescription opioids or other available analgesics, such as ethanol. The temporary relief from pain is reinforcing, but comes at a price of increased pain sensitivity when the analgesic effects subside. In a long-term, a cycle can emerge in which baseline pain sensitivity is elevated along with a consistent negative affective state which engenders a continued seeking for analgesic relief. Alternative approaches including psychological, pharmacological, surgical, and other therapies may be beneficial for breaking this cycle.

patients that described pain using sensory terms (Lawton & Simpson, 2009). Future treatments for comorbid pain, substance use, and affective disorders will need to more effectively integrate sensory, affective, and cognitive components to sufficiently address these conditions.

MINI-DICTIONARY OF TERMS Acute Pain A form of pain that lasts longer than transient pain (which is usually devoid of tissue injury) and shorter than chronic pain (which can involve neural changes and sensitization). Examples of this type of pain include twisting an ankle or cutting one’s finger. It involves a perception of pain, a cognitive and emotional evaluation of the injury and its consequences, and a conscious decision to avoid further damage to the site. Algesia Describes the sensitivity to pain. A state of low sensitivity to pain is referred to as hypoalgesia, which high sensitivity to pain is referred to as hyperalgesia. Allodynia A state in which an organism experiences pain from ordinarily innocuous stimuli, such as a light touch or mild cold or warm stimulus. Analgesia This is a removal of sensitivity to pain; when one takes an analgesic medication, they reduce the sensation of pain. AUD Alcohol use disorder is a DSM-5 diagnosis characterized by compulsive alcohol consumption, loss of control over intake, and a negative affective state when not consuming.

Binge Drinking A pattern of alcohol use in which a sufficient amount of ethanol is consumed in a limited duration of time that produces a blood alcohol concentration of 0.08 grams of ethanol per deciliter of blood in an organism. Chronic Pain This form of pain is long-term pain that persists after tissue injury should have healed and does not serve an adaptive function to the organism. This pain isn’t a symptom of an injury or disease, but rather its own medical condition requiring unique approaches to treatment from acute pain. Neuropathy A state in which damage to peripheral nerves can create motor weakness, numbness, and painful sensations of burning, tingling, or throbbing, especially in the hands and feet. Nociceptor A sensory neuron with a cell body in the dorsal root ganglion of the spinal cord that is responsible for the transmission of painful chemical, mechanical, and thermal sensations from the periphery to the spinal cord and brain.

KEY FACTS Ethanol and Pain • AUD and pain affects millions of people worldwide. • AUD and chronic pain cost billions annually in morbidity, mortality, personal suffering, medical expenses, loss of productivity, and long-term insurance disability. • Binge drinking is the most prevalent cause of AUD.

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REFERENCES

• Severe AUD affects around 10% of the population worldwide. • Preclinical and clinical studies are investigating the role of the sensory, cognitive, and affective aspects of pain and their relationship with alcohol consumption. • New therapeutics using nonopioid translational targets show promise to reduce the negative interactions of pain and risky alcohol use.

SUMMARY POINTS • This chapter focuses on the bidirectional interactions between ethanol use and pain. • Pathological or chronic pain is a medical problem and unmet medical need with current analgesics (anticonvulsants, antidepressants, anxiolytics, local anesthetics) being effective in only 50% of patients. • Moderate doses of alcohol may produce alleviation of acute pain mediated through opioid, GABA, and glutamate systems among other mechanisms. • Alcohol consumption and withdrawal can cause increased pain sensitivity that could lead to central sensitization and potential transition to chronic pain states. • Evidence suggests that AUD promotes the development of chronic pain. • Treatment options for comorbid AUD and pain conditions are limited, proposed options range from vitamin formulations, amino acid derivatives, and over the counter (OTC) analgesic to prescription medications, including SSRI/SNRI antidepressants, anticonvulsants, and anxiolytics. • Future directions for novel treatment is to target overlapping emotion and reward pathways that play a critical role in pain and substance use disorder.

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C H A P T E R

24 Neurobiological Aspects of Ethanol-Derived Salsolinol 1

Elio Acquas1, Simona Scheggi2 and Alessandra T. Peana3 Department of Life and Environmental Sciences, Centre of Excellence on Neurobiology of Addiction, University of Cagliari, Cagliari, Italy 2Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy 3 Department of Chemistry and Pharmacy, University of Sassari, Sassari, Italy

LIST OF ABBREVIATIONS α-MpT AcbSh ACD ADH ALDH CPP DA DMDHIQ1 ERK EtOH GABA H2O2 6-OHDA MPTP NM-SALS N-MT pVTA ROS SALS TIQs

α-methyl-p-tyrosine shell of the nucleus accumbens acetaldehyde alcohol dehydrogenase aldehyde dehydrogenase conditioned place preference dopamine 1,2-dimethyl-6,7-dihydroxyisoquinolinium ion extracellular signal-regulated kinase ethanol γ amino-butyric acid hydrogen peroxide 6-hydroxydopamine 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine N-methyl-salsolinol N-methyl-transferases posterior ventral tegmental area reactive oxygen species salsolinol (1-methyl-6,7-dihydroxy-1,2,3,4tetrahydroisoquinoline) tetrahydroisoquinolines

INTRODUCTION Ethanol (EtOH) is still a puzzling psychoactive molecule since its mechanism of action, in spite of the enormous research efforts, remains elusive in many of its pharmacological and toxicological aspects. Indeed, although the complexity of EtOH actions in the central nervous system may be ascribed to its property to directly involve neurotransmitters, such as glutamate (Tabakoff & Hoffman, 2013) and γ amino-butyric acid

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00024-6

(GABA) (Tabakoff & Hoffman, 2013), a large body of literature strongly supports an indirect participation of dopamine (DA) (So¨derpalm & Ericson, 2013), opioid peptides (Font, Luja´n, & Pastor, 2013), adenosine (Lo´pez-Cruz, Salamone, & Correa, 2013), and serotonin (5-HT) (Vengeliene, Bilbao, Molander, & Spanagel, 2008) to interpret EtOH’s effects on behavior, cognition, motor coordination, and sleep. Moreover, in addition to the involvement of such neurotransmitters, EtOH’s metabolism has also been attributed a critical role on at least two main features: (1) the effects of its main metabolite, acetaldehyde (ACD), being a highly reactive electrophilic compound, and (2) the effects of tetrahydroisoquinolines (TIQs), the condensation products of ACD with nucleophilic molecules (monoamines). In the past few decades, great attention has been placed on peripheral EtOH’s biotransformation by the action of alcohol dehydrogenase (ADH), peroxisomal catalase-hydrogen peroxide (H2O2), cytochrome P450, isoform CYP2E1, and, centrally, by the action of catalase-H2O2-mediated oxidation. Further, aldehyde dehydrogenase (ALDH)-mediated conversion of ACD into acetate also represents a critical factor for the demonstration of the role of EtOH metabolism’s effects. Originating from the observation that a blockade of ACD metabolic disposal, by the use of an ALDH inhibitor (Antabuse, Disulfiram), could cause pleasurable effects in the presence of low doses of EtOH (Chevens, 1953). These investigations revealed that ACD shares with its parent compound a number of psychopharmacological effects. In vivo experiments in this regard

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24. NEUROBIOLOGICAL ASPECTS OF ETHANOL-DERIVED SALSOLINOL

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revealed that the oxidative metabolism of EtOH was prevented by the use of ADH (Peana et al., 2008), catalase-H2O2 (Aragon & Amit, 1985), and ALDH (Zimatkin, Pronko, Vasiliou, Gonzalez, & Deitrich, 2006) inhibitors. Accordingly, the role of ACD in the reinforcing and motivational effects of EtOH was studied upon manipulation of its peripheral and central metabolism and upon application of ACDsequestering agents able to reduce ACD bioavailability (Orrico et al., 2017). In particular, these properties of EtOH-derived ACD (and of ACD on its own) were assessed by place conditioning (Font, Miquel, & Aragon, 2008; Quintanilla & Tampier, 2011) and selfadministration studies (Martı´-Prats, Zornoza, Lo´pezMoreno, Granero, & Polache, 2015; Peana et al., 2011, 2012, 2015; Peana, Muggironi, & Diana, 2010; Peana, Pintus, et al., 2017; Plescia, Brancato, Marino, & Cannizzaro, 2013). Interestingly, further advances have also linked the ability of ADH inhibitors, such as 4methylpyrazole, to indirectly affect catalase-H2O2mediated central EtOH metabolism by interfering with fatty acid oxidation-mediated generation of H2O2 (Peana, Pintus, et al., 2017) (Fig. 24.1). In addition, the critical role of metabolism in the psychopharmacological effects of EtOH has been explained on molecular, cellular, and electrophysiological grounds. In particular, based on the observations that EtOH increases the firing pattern of ventral tegmental area (VTA) DA neurons (Gessa, Muntoni, Collu, Vargiu, & Mereu, 1985), preferentially increases DA transmission (Howard, Schier, Wetzel, Duvauchelle, & Gonzales, 2008) and extracellular signal-regulated kinase (ERK) phosphorylation (Ibba et al., 2009) in the accumbens shell (AcbSh), these studies disclosed the role of EtOHderived ACD in the ability of EtOH to regulate the electrophysiological properties of DA neurons in posterior VTA (pVTA) (Foddai, Dosia, Spiga, & Diana, 2004; Melis, Carboni, Caboni, & Acquas, 2015; Melis, Enrico, Peana, & Diana, 2007; Xie et al., 2012) and, in the AcbSh, DA transmission (Melis et al., 2007) and ERK phosphorylation (Vinci et al., 2010). Moreover, inspired by the demonstration that naltrexone (μ opioid receptor antagonist) prevents the intravenous selfadministration of ACD (Myers, Ng, & Singer, 1984) and by the involvement of central opioidergic system in the effects of EtOH (Font et al., 2013), opioid receptors were shown to exert a crucial influence on the effects of EtOH-derived ACD on locomotor activity (Sa´nchez-Catala´n, Hipo´lito, Zornoza, Polache, & Granero, 2009) and conditioned place preference (CPP) (Pastor & Aragon, 2008) on DA transmission (Melis et al., 2007) and ERK phosphorylation in the AcbSh and on ACD oral self-administration (Peana et al., 2011). These studies, having undergone extensive reviews (Correa et al., 2012; Peana, Sa´nchez-Catala´n,

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FIGURE 24.1 Effect of pVTA 4-methylpyrazole on ethanol self-administration. Effects of intra-pVTA 4-Methylpyrazole (mM in 0.5 μL/min) during maintenance of ethanol self-administration on (A) active responses and (B) ethanol intake (g/kg). Source: Reproduced with permission from Peana, A. T., Pintus, F. A., Bennardini, F., Rocchitta, G., Bazzu, G., Serra, P. A. . . . Acquas, E. (2017). Is catalase involved in the effects of systemic and pVTA administration of 4-methylpyrazole on ethanol self-administration? Alcohol (Fayetteville, N.Y.), Alcohol, 63, 61 73, with minor modifications.

et al., 2017; Peana, Rosas, Porru, & Acquas, 2016), strongly support the tenet that ACD is a pharmacologically active compound on its own and, as EtOH’s metabolite, thus assigning to its metabolism a fundamental role in the mechanism of its psychopharmacological effects. As to the second feature, that is, the role of TIQs and, in particular, of salsolinol (SALS, (R,S)-1-methyl6,7-dihydroxyisoquinoline) in the effects of EtOH, ACD not only directly exerts its known effects but also generates biologically active by-products. Among these molecules, SALS, the condensation product of ACD and DA (Fig. 24.2), has been involved in the neurobiological basis of alcoholism (Davis & Walsh, 1970; Yamanaka, Walsh, & Davis, 1970) and in the neurotoxic consequences of EtOH exposure (Mravec, 2006; Naoi, Maruyama, Akao, & Yi, 2002). The next sections will focus on three significant aspects of the effects of SALS and EtOH-derived SALS: (1) the origin(s) of

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THE ORIGIN OF SALS AND ITS BASAL CONCENTRATIONS IN THE BODY FLUIDS AND IN THE BRAIN

HO

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Synthetic pathways of salsolinol. Salsolinol (bio)synthesis via (A) Pictet-Spengler condensation between dopamine and acetaldehyde or (C) via the postulated salsolinol synthase. Pathway B depicts the condensation between dopamine and pyruvate to yield salsolinol-1-carboxylic acid (still undetermined whether spontaneous (to yield a racemate) or enzymatic). This intermediate undergoes (E1 ) spontaneous decarboxylation into salsolinol or (D) oxidation into 1,2-dehydroxysalsolinol which, in turn, is reduced to salsolinol.

SALS and its basal concentrations in body fluids and the brain; (2) the role of SALS in the neurobiological basis of alcoholism; and (3) the role of SALS in the emergence of neurological disorders associated, in particular, to DA neurodegeneration. Two further issues should be mentioned. The first refers to the advancement on blood and brain ACD determinations since it represents one of the main sources of EtOH-derived SALS. Notably, due to its reactivity, it is very difficult to reliably detect ACD’s concentrations (Correa et al., 2012; Peana, Pintus, et al., 2017); moreover, its spontaneous Pictet-Spengler condensation with nucleophilic amines may take place even after collecting the samples for analysis. All this notwithstanding, and although the in vivo determination of ACD concentrations has long represented a puzzling issue (see Correa et al., 2012), recent data report that ACD can be reproducibly detected in biological fluids and in the brain (Jamal et al., 2016; Schlatter, Chiadmi, Gandon, & Chariot, 2014; Yokoi et al., 2015). The other critical feature to keep in mind is that SALS has a chiral carbon and, therefore, the racemate can be resolved in R-SALS and S-SALS (Fig. 24.2), carrying key metabolic and pharmacodynamic implications.

THE ORIGIN OF SALS AND ITS BASAL CONCENTRATIONS IN THE BODY FLUIDS AND IN THE BRAIN With the above caveats in mind, a critical overview of the literature on the presence of SALS in biological fluids and the brain reveals that, since its discovery in 1970 (Davis & Walsh, 1970), SALS has been detected in very low concentrations both spontaneously and under EtOH ingestion-stimulated conditions. These data, summarized in an excellent review (Hipo´lito, Sa´nchezCatala´n, Martı´-Prats, Granero, & Polache, 2012), reveal that such low concentrations, ranging from picograms/mg (Myers et al., 1985) and picomoles/g (Matsubara, Fukushima, & Fukui, 1987) to nanograms/mg (Haber, Stender, Mangholz, Ehrenreich, & Melzig, 1999) found in rat (Matsubara et al., 1987; Starkey, Mechref, Muzikar, McBride, & Novotny, 2006) and human (DeCuypere, Lu, Miller, & LeDoux, 2008) brain tissue, may depend on a number of factors, including amount, route, and length of EtOH intake (Hipo´lito et al., 2012) as well as SALS’s possible direct ingestion through diet. In agreement with such complexity, Collins, Ung-Chhun, Cheng, and Pronger (1990) reported that in SALS- and L-DOPA- (a DA precursor) free diet fed rats, either short-term (3 weeks) or

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long-term (23 weeks) exposure to an EtOH-containing liquid diet (6.6%, vol/vol) resulted in failure to increase SALS levels in plasma and in different brain regions; however, striatal concentrations of SALS were significantly higher when EtOH intake was supplemented with dietary L-DOPA. Moreover, with respect to SALS’s concentrations in the brain following its systemic intake/administration, the confirmation that SALS crosses the blood brain barrier (BBB) and, hence, that its presence in the brain may not necessarily originate from ACD’s in situ biosynthesis (via lipid peroxidation) has been critical. This issue (Origitano, Hannigan, & Collins, 1981), justified by the observation that SALS has a polarity and a permeability coefficient that would not sustain an easy penetrability through the BBB, was unquestionably set by the demonstration that peripherally-administered SALS could, similarly to centrally-administered SALS (Hipo´lito, Martı´-Prats, Sa´nchez-Catala´n, Polache, & Granero, 2011), elicit CPP and locomotor activity (Matsuzawa, Suzuki, & Misawa, 2000; Quintanilla et al., 2014; Quintanilla et al., 2016). As shown in Fig. 24.2, both SALS’s stereoisomers may originate from the spontaneous condensation between DA and, endogenous or exogenous, ACD. However, since R-SALS is consistently found at higher concentrations than S-SALS (Hipo´lito et al., 2012), it was suggested that R-SALS could be produced enzymatically by the never unequivocally demonstrated (R)-salsolinol synthase (Naoi et al., 1996). In fact, although its isolation was claimed (Naoi et al., 1996), no sequence has been reported for this enzyme, making it impossible to know whether it is, indeed, a genuine (R)-salsolinol synthase or whether (R)-SALS is a by-product of another enzyme. Moreover, bioinformatics analysis has failed, to date, to detect a mammalian sequence homolog to well-known plant PictetSpenglerases (strictosidine and norcoclaurine synthases) able to catalyze the synthesis of distinct TIQs (Ilari et al., 2009). Interestingly, an alternative biochemical pathway of stereo-selective synthesis of SALS has also been suggested through pyruvate (Fig. 24.2) that would condensate, spontaneously or enzymatically, with DA to yield salsolinol-1-carboxylic acid that, in turn, would undergo a spontaneous nonenzymatic decarboxylation to yield SALS.

THE ROLE OF SALS IN THE NEUROBIOLOGICAL BASIS OF ALCOHOLISM Over the past few decades, the role of SALS in the neurobiological basis of alcoholism (Davis & Walsh, 1970; Yamanaka et al., 1970) has long bewildered

neuroscientists up to the more recent demonstrations that involve SALS in the acute, motor stimulant, reinforcing, and motivational effects of EtOH (Correa et al., 2012; Deehan, Brodie, & Rodd, 2013; Hipo´lito et al., 2012; Peana et al., 2016) and that it even facilitates (in alcohol-preferring rats) EtOH consumption (Quintanilla et al., 2016). Accordingly, (R,S)-SALS, at significantly lower concentrations than EtOH, sustains acquisition and maintenance of its intra-pVTA selfadministration (Rodd et al., 2008) and, when delivered in the pVTA, stimulates DA transmission in the Acb (Deehan et al., 2013), locomotor activity (Hipo´lito, Sa´nchez-Catala´n, Zornoza, Polache, & Granero, 2010), and CPP (Hipo´lito et al., 2011). Moreover, the mechanistic relationship between EtOH and its by-products, ACD and SALS, has been demonstrated in pVTA DA neurons (Melis et al., 2015). Using mesencephalic slices from mice treated with α-methyl-p-tyrosine (α-MpT) or reserpine (agents that inhibit DA synthesis and deplete vesicular stores), this elegant investigation demonstrated that SALS, in contrast to ACD and EtOH, stimulates the spontaneous firing of DA neurons even in the absence of newly synthesized DA (Fig. 24.3). However, failure of EtOH or ACD to elicit increased firing activity in DA-depleted animals could be restored by the stoichiometric addition of DA disclosing that, in order to stimulate spontaneous firing of these neurons, EtOH needs to be converted into ACD which, in turn, in the presence of exogenous or endogenous DA (Fig. 24.4), condensates with it to form SALS, the chemical responsible for the observed effects. Interestingly, although this evidence was provided using R,S-SALS, a subsequent study disclosed the role of R-SALS: using an optimal analytical procedure to obtain a chiral separation of the stereoisomers, Quintanilla et al. (2016) demonstrated that the effects of (R,S)-SALS on locomotor activity, CPP and bingelike EtOH intake were reproduced by the administration of R-SALS, but not S-SALS.

THE ROLE OF SALS IN THE EMERGENCE OF NEUROLOGICAL DISORDERS Whatever its source or origin in the brain, SALS’s fate appears linked to the sequential actions of the enzymes N-methyl-transferase (N-MT) to yield Nmethyl-SALS (NM-SALS), and of a semicarbazidesensitive (but not monoamine oxidase-sensitive, MAO) oxidase to yield 1,2-dimethyl-6,7-dihydroxyisoquinolinium ion (DMDHIQ1) (Fig. 24.5) (Maruyama, StrolinBenedetti, & Naoi, 2000; Naoi et al., 2002). DMDHIQ1 may also originate from N-MT by auto-oxidation (Naoi et al., 2002). These metabolic pathways and the large

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FIGURE 24.3 Effects of ethanol, acetaldehyde, and salsolinol on pVTA DA neuronal excitability. Effects of ethanol (100 mM): (A) acetaldehyde (10 nM); (B) salsolinol (100 nM); and (C) on firing rate of pVTA dopamine neurons of mice pretreated with either αMpT (white circles) or reserpine (gray circles). Black bars indicate time of drug application. Gray areas represent mean responses in control mice. Source: Reproduced with permission from Melis, M., Carboni, E., Caboni, P., & Acquas E. (2015). Key role of salsolinol in ethanol actions on dopamine neuronal activity of the posterior ventral tegmental area. Addiction Biology, 20, 182 193, with minor modifications.

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FIGURE 24.4 Effects of ethanol, acetaldehyde, and salsolinol on pVTA DA neuronal excitability: The role of exogenous dopamine. The effect of ethanol (100 mM) on firing rate of pVTA dopamine neurons of αMpT pretreated mice is restored in the presence of exogenous dopamine (10 nM), (A) but is abolished in the presence of DA (10 nM) when acetaldehyde formation is prevented by the catalase H2O2 inhibitor, 3-AT (1 mM) (B). Gray areas represent mean responses in control mice. Source: Reproduced with permission from Melis, M., Carboni, E., Caboni, P., & Acquas E. (2015). Key role of salsolinol in ethanol actions on dopamine neuronal activity of the posterior ventral tegmental area. Addiction Biology, 20, 182 193, with minor modifications.

molecular and mechanistic similarities of these byproducts with the most famous neurotoxins such as 1methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and 6-hydroxydopamine (6-OHDA) (Herraiz, 2016; Mravec, 2006) prompted to the suggestion that SALS might also be involved in the etiopathogenesis of Parkinsonism (Antkiewicz-Michaluk, 2002). In support

of this possibility, experimental evidence indicates that NM-SALS and DMDHIQ1, whose concentrations in the substantia nigra positively correlate with the activity of N-MT in the striatum (Naoi, Maruyama, Matsubara, & Hashizume, 1997), are responsible of dopaminergic cell death through mitochondrial dysfunction mediated by impairment of complex I

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and metabolites in L-DOPA treated patients with respect to healthy controls (Scholz, Klingemann, & Moser, 2004) and since SALS and its by-products were found elevated in the brain and cerebral spinal fluid of patients regardless of their exposure to L-DOPA (Moser et al., 1995), it was concluded that just their central concentrations might serve as a biological marker of the disease (Scholz et al., 2004). Interestingly, although these hypotheses, at least in terms of ethanol-derived SALS, have never reached momentum after their early formulation nor have been supported by epidemiological evidence linking heavy alcohol drinking to EtOH-derived SALS-mediated development of Parkinsonism, a study reporting the effects of H2O2 exposure onto differentiated Parkin knock down PC12 cells disclosed a critical role of SALS and NM-SALS in their oxidative, stress-related, increased vulnerability (Su et al., 2013).

MINI-DICTIONARY OF TERMS

FIGURE 24.5 Metabolic fate of salsolinol. Pathways of NMethyl-salsolinol and of 1,2-dimethyl-6,7-dihydroxyisoquinolinium ion biosynthesis via N-Methylation (A) and (auto-)oxidation (B).

activity, inhibition of electron transport chain, depletion of ATP, and increased production of reactive oxygen species (ROS), as assessed in cell cultures with dopaminergic neuroblastoma SH-SY5Y cells (Kim et al., 2001). Moreover, the involvement of SALS in the basis of Parkinsonism was also sustained by the clinical evidence of increased N-MT activity in Parkinsonians’ lymphocytes (Maruyama et al., 2000; Naoi et al., 2002) and by the cerebrospinal fluid and urine SALS and NM-SALS concentrations (Maruyama, Abe, Tohgi, Dostert, & Naoi, 1996; Niwa et al., 1991) that in the late 1990s brought the suggestion that these molecules could represent a biological marker for early diagnosis and indirect monitoring of the progression of this neurological disorder and of the success of therapeutic approaches (Moser, Scholz, & Nobbe, 1995). These hypotheses were, however, questioned on the grounds of failure to detect SALS and related compounds during early development of the disease in untreated patients and by the observation that therapeutically administered L-DOPA might represent a confounding in their determination. Moreover since there was no correlation between the severity of the disease progression and the concentrations of SALS

Electrophilic Able to accept an electron pair; highly reactive with electron-rich molecules. Nucleophilic Able to donate an electron pair; highly reactive with electron-poor molecules. Pro-drug/Pro-toxic agent Molecule that owes its effects to its metabolic conversion into different biologically active molecules. Racemate Mixture that has equal amounts of left- and right-handed enantiomers of a chiral molecule. Stereoisomer Molecule made of the same atoms connected in the same sequence, but with some of the atoms positioned differently in space with respect to the opposite stereoisomer. Chiral separation Process of separation of two stereoisomers from their racemate.

KEY FACTS Role of Ethanol Metabolism • Ethanol is a psychopharmacologically active compound of extreme pharmacological and toxicological interest. • The exact(s) mechanism(s) of ethanol’s actions are still to be determined. Extensive experimental evidence suggests that it acts through the involvement of multiple neurotransmitter systems and, after its metabolism, into biologically active byproducts, acetaldehyde and salsolinol (the condensation product between acetaldehyde with dopamine). • Ethanol can be considered the pro-drug of the following biologically active molecules: acetaldehyde, salsolinol, N-methyl-salsolinol, and 1,2-dimethyl-6,7-dihydroxyisoquinolinium ion.

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REFERENCES

Role of Stereo-Selectivity in the Effects of Salsolinol • Both R- and S-salsolinol are detected in body fluids and the brain of ethanol-naı¨ve rats and humans, and after ethanol ingestion. • The effects of salsolinol on locomotion, place conditioning, and ethanol intake, originally shown using the racemate, have been demonstrated to be due to R-salsolinol.

Neurotoxicity of Salsolinol By-products • Salsolinol, by the sequential actions of N-methyltransferase and of a semicarbazide-sensitive oxidase is converted into N-methyl-salsolinol and 1,2dimethyl-6,7-dihydroxyisoquinolinium ion, which are toxic to dopaminergic neurons.

SUMMARY POINTS 1. Ethanol acts through glutamate and GABA, but indirectly necessitates dopamine, opioid peptides, adenosine, and serotonin neurotransmission. 2. Ethanol acts through the involvement of ethanolderived acetaldehyde. 3. Acetaldehyde is a highly reactive, electrophilic molecule. 4. Tetrahydroisoquinolines are the acetaldehyde’s condensation products with biogenic monoamines. 5. Salsolinol, the condensation product of acetaldehyde and dopamine, has been implicated in the neurobiological basis of alcoholism and in the emergence of neurological disorders. 6. Ethanol may act both as a pro-drug and a pro-toxic agent.

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Lo´pez-Cruz, L., Salamone, J. D., & Correa, M. (2013). The impact of caffeine on the behavioral effects of ethanol related to abuse and addiction: A review of animal studies. Journal of Caffeine Research, 3(1), 9 21. Martı´-Prats, L., Zornoza, T., Lo´pez-Moreno, J. A., Granero, L., & Polache, A. (2015). Acetaldehyde sequestration by Dpenicillamine prevents ethanol relapse-like drinking in rats: Evidence from an operant self-administration paradigm. Psychopharmacology, 232(19), 3597 3606. Maruyama, W., Abe, T., Tohgi, H., Dostert, P., & Naoi, M. (1996). A dopaminergic neurotoxin, (R)-N-methylsalsolinol increases in parkinsonian cerebrospinal fluid. Annals of Neurology, 40, 119 122. Maruyama, W., Strolin-Benedetti, M., & Naoi, M. (2000). N-methyl (R)salsolinol and a neutral N-methyltransferase as pathogenic factors in Parkinson’s disease. Neurobiology, 8, 55 68. Matsubara, K., Fukushima, S., & Fukui, Y. (1987). A systematic regional study of brain salsolinol levels during and immediately following chronic ethanol ingestion in rats. Brain Research, 413, 336 343. Matsuzawa, S., Suzuki, T., & Misawa, M. (2000). Involvement of muopioid receptor in the salsolinol-associated place preference in rats exposed to conditioned fear stress. Alcoholism: Clinical & Experimental Research, 24, 366 372. Melis, M., Carboni, E., Caboni, P., & Acquas, E. (2015). Key role of salsolinol in ethanol actions on dopamine neuronal activity of the posterior ventral tegmental area. Addiction Biology, 20, 182 193. Melis, M., Enrico, P., Peana, A. T., & Diana, M. (2007). Acetaldehyde mediates alcohol activation of the mesolimbic dopamine system. European Journal of Neuroscience, 26, 2824 2833. Moser, A., Scholz, J., & Nobbe, F. (1995). Presence of N-methylnorsalsolinol in the CSF: Correlations with dopamine metabolites of patients with Parkinson’s disease. Journal of Neurological Sciences, 131, 183 189. Mravec, B. (2006). Salsolinol, a derivate of dopamine, is a possible modulator of catecholaminergic transmission: A review of recent developments. Physiological Research, 5(4), 353 364. Myers, W. D., Mackenzie, L., Ng, K. T., Singer, G., Smythe, G. A., & Duncan, M. W. (1985). Salsolinol and dopamine in rat medial basal hypothalamus after chronic ethanol exposure. Life Science, 36, 309 314. Myers, W. D., Ng, K. T., & Singer, G. (1984). Effects of naloxone and buprenorphine on intravenous acetaldehyde self-injection in rats. Physiology & Behavior, 33(3), 449 455. Naoi, M., Maruyama, W., Akao, Y., & Yi, H. (2002). Dopaminederived endogenous N-methyl-(R)-salsolinol: Its role in Parkinson’s disease. Neurotoxicology & Teratology, 24, 579 591. Naoi, M., Maruyama, W., Dostert, P., Hashizume, Y., Nakahara, D., Takahashi, T., & Ota, M. (1996). Dopamine-derived endogenous 1 (R),2(N)-dimethyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline, N-methyl-(R)-salsolinol, induced parkinsonism in rat: Biochemical, pathological and behavioral studies. Brain Research, 709(2), 285 295. Naoi, M., Maruyama, W., Matsubara, K., & Hashizume, Y. (1997). A neutral N-methyltransferase activity in the striatum determines the level of an endogenous MPP 1 -like neurotoxin, 1,2-dimethyl6,7-dihydroxyisoquinolinium ion, in the substantia nigra of human brains. Neuroscience Letters, 235, 81 84. Niwa, T., Takeda, N., Yoshizumi, H., Tatematsu, A., Yoshida, M., Dostert, P., . . . Nagatsu, T. (1991). Presence of 2-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline and 1,2-dimethyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline, novel endogenous amines, in parkinsonian and normal human brains. Biochemical and Biophysical Research Communications, 177, 603 609. Origitano, T., Hannigan, J., & Collins, M. A. (1981). Rat brain salsolinol and blood-brain barrier. Brain Research, 224, 446 451.

Orrico, A., Martı´-Prats, L., Cano-Cebria´n, M. J., Granero, L., Polache, A., & Zornoza, T. (2017). Pre-clinical studies with D-Penicillamine as a novel pharmacological strategy to treat alcoholism: Updated evidences. Frontiers in Behavioral Neuroscience, 11, 37. Pastor, R., & Aragon, C. M. (2008). Ethanol injected into the hypothalamic arcuate nucleus induces behavioral stimulation in rats: An effect prevented by catalase inhibition and naltrexone. Behavioral Pharmacology, 19(7), 698 705. Peana, A. T., Enrico, P., Assaretti, A. R., Pulighe, E., Muggironi, G., Nieddu, M., . . . Diana, M. (2008). Key role of ethanol-derived acetaldehyde in the motivational properties induced by intragastric ethanol: A conditioned place preference study in the rat. Alcoholism: Clinical & Experimental Research, 32(2), 249 258. Peana, A. T., Muggironi, G., & Diana, M. (2010). Acetaldehydereinforcing effects: A study on oral self-administration behavior. Frontiers in Psychiatry, 1, 23. Peana, A. T., Muggironi, G., Fois, G. R., Zinellu, M., Sirca, D., & Diana, M. (2012). Effect of (L)-cysteine on acetaldehyde selfadministration. Alcohol (Fayetteville, N.Y.), 46(5), 489 497. Peana, A. T., Muggironi, G., Fois, G. R., Zinellu, M., Vinci, S., & Acquas, E. (2011). Effect of opioid receptor blockade on acetaldehyde self-administration and ERK phosphorylation in the rat nucleus accumbens. Alcohol (Fayetteville, N.Y.), 5(8), 773 783. Peana, A. T., Pintus, F. A., Bennardini, F., Rocchitta, G., Bazzu, G., Serra, P. A., . . . Acquas, E. (2017). Is catalase involved in the effects of systemic and pVTA administration of 4-methylpyrazole on ethanol self-administration? Alcohol, 63, 61 73. Peana, A. T., Porcheddu, V., Bennardini, F., Carta, A., Rosas, M., & Acquas, E. (2015). Role of ethanol-derived acetaldehyde in operant oral self-administration of ethanol in rats. Psychopharmacology, 232(23), 4269 4276. Peana, A. T., Rosas, M., Porru, S., & Acquas, E. (2016). From ethanol to salsolinol: Role of ethanol metabolites in the effects of ethanol. Journal of Experimental Neuroscience, 10, 137 146. Peana, A. T., Sa´nchez-Catala´n, M. J., Hipo´lito, L., Rosas, M., Porru, S., Bennardini, F., . . . Acquas, E. (2017). Mystic acetaldehyde: The never-ending story on alcoholism. Frontiers in Behavioral Neuroscience, 11, 81. Plescia, F., Brancato, A., Marino, R. A., & Cannizzaro, C. (2013). Acetaldehyde as a drug of abuse: Insight into AM281 administration on operant-conflict paradigm in rats. Frontiers in Behavioral Neuroscience, 7, 64. Quintanilla, M. E., Rivera-Meza, M., Berrı´os-Ca´rcamo, P., Cassels, B. K., Herrera-Marschitz, M., & Israel, Y. (2016). (R)-Salsolinol, a product of ethanol metabolism, stereospecifically induces behavioral sensitization and leads to excessive alcohol intake. Addiction Biology, 21(6), 1063 1071. Quintanilla, M. E., Rivera-Meza, M., Berrios-Ca´rcamo, P. A., Bustamante, D., Buscaglia, M., Morales, P., . . . Israel, Y. (2014). Salsolinol, free of isosalsolinol, exerts ethanol-like motivational/ sensitization effects leading to increases in ethanol intake. Alcohol (Fayetteville, N.Y.), 48(6), 551 559. Quintanilla, M. E., & Tampier, L. (2011). Place conditioning with ethanol in rats bred for high (UChB) and low (UChA) voluntary alcohol drinking. Alcohol (Fayetteville, N.Y.), 45(8), 751 762. Rodd, Z. A., Oster, S. M., Ding, Z. M., Toalston, J. E., Deehan, G., Bell, R. L., . . . McBride, W. J. (2008). The reinforcing properties of salsolinol in the ventral tegmental area: Evidence for regional heterogeneity and the involvement of serotonin and dopamine. Alcoholism: Clinical & Experimental Research, 32(2), 230 239. Sa´nchez-Catala´n, M. J., Hipo´lito, L., Zornoza, T., Polache, A., & Granero, L. (2009). Motor stimulant effects of ethanol and acetaldehyde injected into the posterior ventral tegmental area of rats: Role of opioid receptors. Psychopharmacology, 204(4), 641 653.

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C H A P T E R

25 Brain Networks in Active Alcoholism and Enduring Recovery: Functional Magnetic Resonance Imaging, Electrophysiological Studies, and Implications for Targeted Treatments 1

George Fein1,2 and Valerie Cardenas2

Department of Medicine and Psychology, University of Hawaii, Honolulu, HI, United States 2 Neurobehavioral Research Inc., Kahului, HI, United States

LIST OF ABBREVIATIONS AUD DLPFC EEG ICA LTAA LTAAS MDD NAcc NSAC rs-fMRI RSS sgACC STAA STAB STAF SUD

Ogburn, & Grant, 2007), directly afflicting about 24 million individuals and impacting the lives of many millions more, with a staggering monetary cost to society for the health consequences, lost productivity, alcoholassociated violence and crime, and broken families. In this chapter, we will examine brain network function in active alcoholism and in enduring alcoholism recovery. In doing this, we will also take into consideration heterogeneity within alcoholic clinical populations. We are working under the assumption that effective neurobiological treatments for active alcoholism should be informed by an understanding of the neurobiology of enduring alcoholism recovery. We will discuss potential treatment interventions suggested by the data and highlight further research that will help refine such treatment approaches.

alcohol use disorders dorsolateral prefrontal cortex electroencephalogram independent components analysis long-term abstinent alcoholics (greater than 18 months abstinent) long-term abstinent alcoholics with comorbid stimulant dependence major depressive disorder nucleus accumbens nonsubstance abusing controls resting-state functional magnetic resonance imaging resting-state synchrony subgenual anterior cingulate cortex short-term abstinent alcoholics (6 15 weeks abstinent) short-term abstinent alcoholics studied at baseline short-term abstinent alcoholics studied at 6 12 months follow-up substance use disorder

BRAIN NETWORKS IN ACTIVE ALCOHOLISM

Alcohol spectrum disorders are among the most prevalent behavioral disorders, with major negative consequences for the individual, the family, and society. In 2001 2002, the 12-month prevalences of DSM-IV alcohol abuse and dependence in the United States were 4.7% and 3.8%, respectively (Hasin, Stinson,

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00025-8

Alcoholism is characterized by a lack of control over impulsive and compulsive behaviors toward excessive alcohol consumption despite significant negative consequences. There is evidence that these impulsive and compulsive behaviors are related to the reorganization

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FIGURE 25.1 Network imbalance in alcohol use disorders. Top-down and bottom-up processes are in balance in light or moderate drinkers, with weak top-down (decrease in inhibitory control and emotion regulation network synchrony) and strong bottom-up (increase in appetitive drive network synchrony) processes in alcohol use disorders, and the opposite observed in long-term abstinence.

of brain functional networks after repeated high level exposure to alcohol (Kalivas & O’Brien, 2008; Mameli & Luscher, 2011), resulting in an imbalance characterized by increased signal exchange in appetitive drive networks and decreased signal exchange in inhibitory control networks (Volkow, Wang, Tomasi, & Baler, 2013), as illustrated in Fig. 25.1. As we have stated in previous research (Fein, Camchong, Cardenas, & Stenger, 2017), using the analogy of a car, the alcoholic will often shoot out into dangerous intersections (begin a new episode of risky drinking and ignoring accumulating consequences of such behavior) because the motor is idling way too fast (craving is easily elicited by alcohol-related stimuli). Additionally, an alcoholic is in the habit of shooting out into these intersections despite accumulating experience that the brakes are faulty (they have minimal or nonexistent inhibitory control once they start drinking). Using functional magnetic resonance imaging (fMRI), lesser activation of prefrontal executive control regions than seen in controls has been observed in alcoholics during spatial and verbal working memory tasks (Cservenka & Nagel, 2012; Desmond et al., 2003; Pfefferbaum et al., 2001). Active drinkers show enhanced blood-oxygen-level-dependent (BOLD) activation in the ventral striatum when presented with visual alcohol cues, which also supports the notion of a stronger appetitive and reward drive in current alcohol dependence (Ihssen, Cox, Wiggett, Fadardi, & Linden, 2011; Myrick et al., 2004, 2008). Active drinkers diagnosed with of alcohol dependence show higher activity in the dorsal lateral prefrontal cortex (DLPFC) regions during delayed reward decisions (Amlung, Sweet, Acker, Brown, & Mackillop, 2012) compared to active drinkers without alcohol dependence, which may reflect

alcoholics’ increased demand of the executive control network when required to make decisions on behavior ruled by appetitive drive. These studies demonstrate that excessive alcohol use, and even the genetic vulnerability to alcoholism (observed prior to initiating alcohol use), is associated with fMRI activation patterns different than controls in brain regions that are part of the executive control and appetitive drive network. Recent work has examined resting-state fMRI (rs-fMRI) synchrony in multiple brain networks in individuals with current alcohol use disorders (AUDs) (Weiland et al., 2014). The fMRI time series measures of synchrony (i.e., average within-network correlations of BOLD signal magnitude across the network’s nodes) were computed for 14 networks in each of 422 individuals with active AUDs and 97 controls. Network strength on average for all networks (multivariate test) was lower for AUD than controls. Univariate tests showed lower synchrony in AUD versus controls for the left executive control network, sensorimotor, basal ganglia, and primary visual networks. In another fMRI study, moderate/heavy active drinkers were shown to have lower central executive network connectivity during a working memory task, although whether this was a sign of direct alcohol toxicity or an early sign of aging could not be determined (Mayhugh et al., 2016). An fMRI network study that examined smokers, drinkers, and smoking drinkers found a general pattern of hypoconnectivity in substance users (Vergara, Liu, Claus, Hutchison, & Calhoun, 2017). In contrast, another study of active drinkers found increased fMRI network connectivity in the default mode network, executive control network, salience network, and prefrontal cortex network (Zhu et al., 2015).

II. NEUROBIOLOGY

COMPENSATORY MECHANISMS OF RESTING STATE BRAIN NETWORK SYNCHRONY IN LONG-TERM ABSTINENT ALCOHOLICS

COMPENSATORY MECHANISMS OF RESTING STATE BRAIN NETWORK SYNCHRONY IN LONG-TERM ABSTINENT ALCOHOLICS With rs-fMRI, we have shown adaptive changes in brain network resting state synchrony (RSS) in longterm abstinent alcoholics (LTAA) that reverse the network synchrony differences that were associated with the development of alcoholism. To study such brain functional organization associated with long-term abstinence, we examined RSS in a sample of 23 LTAA (8 females, age: 48.46 6 7.10 years, abstinent: 94.8 6 93.6 months), and 23 nonsubstance abusing controls (NSAC; 8 females, age: 47.99 6 6.70 years) (Camchong, Stenger, & Fein, 2013c). We examined the strength of RSS within the appetitive drive and executive control networks by using a seed-based approach with nucleus accumbens (NAcc) and subgenual anterior cingulate cortex (sgACC) seeds. All subjects performed the intra/extradimensional set shift task outside of the scanner to explore the relationship between RSS and cognitive flexibility.

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Compared to NSAC, LTAA showed: (A) decreased synchrony of limbic reward regions (e.g., caudate and thalamus) with both the sgACC seed and the NAcc seed (Fig. 25.2A, voxels shaded orange); and (B) increased synchrony of bilateral NAcc seeds with left DLPFC (suggesting greater inhibitory control) and between the sgACC seed and right DLPFC (consistent with greater emotion regulation) (Fig. 25.2B). RSS within the inhibitory control network was positively correlated with cognitive flexibility task performance outside of the scanner. These results support the notion of a compensatory mechanism in LTAA evident during rest, in which enhanced RSS within the executive control networks (both inhibitory control and emotion regulation) and attenuated RSS within the appetitive drive network may facilitate the behavioral control required to maintain abstinence. Increased synchrony between the NAcc and left DLPFC is consistent with the literature showing that DLPFC input to the NAcc is involved in inhibition of behavior (Ballard et al., 2011; McClure, Laibson, Loewenstein, & Cohen, 2004), as is the correlation of

FIGURE 25.2 Resting state networks in alcoholics and controls. (A) Appetitive drive resting state networks (mean 6 SD of the restingstate synchrony measure) show graded decreases from NSAC to LTAA, with no decrease in LTAAS; (B) Inhibitory control and emotion regulation networks show graded increases from NSAC to LTAA.

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this synchrony measure with intra/extradimensional set shift task performance.

COMPENSATORY MECHANISMS OF RESTING STATE SYNCHRONY IN SHORT-TERM ABSTINENT ALCOHOLICS We next investigated whether the RSS patterns found in LTAA can be identified in STAA (Camchong, Stenger, & Fein, 2013d). We examined RSS in 27 STAA (9 females, age: 49.3 6 7.05 years, abstinent 72.6 6 18.4 days), and compared them to the LTAA and NSAC subjects in the previous section. We found ordered RSS effects from NSAC to STAA and then to LTAA within both the appetitive drive and executive control networks: with lower RSS of the appetitive drive network (NSAC . STAA . LTAA) and higher RSS of the executive control networks (NSAC , STAA , LTAA). We also found significant positive correlations between strength of RSS in the inhibitory control network and cognitive flexibility, and a negative correlation with current antisocial behavior. These findings suggest that abstinent alcoholics show adaptive changes in RSS patterns compared to controls, with the magnitude of the change increasing with the duration of abstinence. These results are shown in Fig. 25.2A, B.

DIFFERENCES IN RESTING STATE SYNCHRONY BETWEEN LONG-TERM ABSTINENT ALCOHOLICS WITH VERSUS WITHOUT COMORBID DRUG DEPENDENCE Findings reported above examined alcoholics without comorbid drug dependence. We have evidence that long-term abstinent alcoholics with comorbid stimulant dependence (LTAAS) have both similarities and differences in brain organization during rest when compared to LTAA without comorbid drug dependence (Camchong, Stenger, & Fein, 2013a). Resting-state fMRI data were compared between 35 LTAAS (20 females, age: 47.85 6 7.30 years, abstinent 68.9 6 58.3 months), and the LTAA and NSAC data above. Results showed commonalities in LTAA and LTAAS RSS (similar enhanced executive control RSS (Fig. 25.2B) as well as differences (no attenuation of appetitive drive RSS in LTAAS (Fig. 25.2A). Additionally, LTAAS had higher RSS between the NAcc seed and bilateral insula than both NSAC and LTAA. When examining RSS in insular regions of interest, LTAA as well as LTAAS had significantly increased RSS between NACC and left insula

compared to NSAC; LTAA and LTAAS did not differ (P 5 .16). Other research suggests this is associated with regulation of emotion and appetitive behavior. Increased RSS in the right insula was only present in LTAAS, and LTAAS RSS was greater than that of LTAA. Other research suggests this is related to the ability to modulate emotional and interoceptive awareness to effectively respond to the environment. These findings suggest common as well as specific targets for treatment in chronic alcoholics with versus without comorbid stimulant dependence.

DEGREE OF RESTING STATE SYNCHRONY DURING EARLY ALCOHOL ABSTINENCE PREDICTS SUBSEQUENT RELAPSE We examined and identified generalized RSS differences between STAA that relapse versus abstain over an approximate 6-month follow-up period. We examined RSS in a sample of 69 alcoholics at 6 15 weeks of abstinence (Camchong, Stenger, & Fein, 2013b), including participants with codependence on alcohol and drugs (to increase the sample size and consequently, predictive power). At follow-up, participants were grouped as abstainers (N 5 40; age: 46.70 6 6.83 years) and relapsers (N 5 29; age: 46.91 6 7.25 years) based on self-report. With the same analysis methods as in the studies above, we examined RSS within executive control and appetitive drive networks and investigated whether strength of RSS within these networks could predict relapse. Compared to abstainers, relapsers showed significantly decreased RSS within both the reward and executive control networks. Additional analyses showed that lower RSS in relapsers was generalized to other networks (e.g., the visual and insular networks). Regression analysis showed that low RSS was a good predictor of relapse. Lower generalized RSS also significantly correlated with poor performance on the affective Go/No-Go task. Results suggest that, regardless of the network examined, lower RSS during short-term abstinence predicts subsequent relapse. This finding suggests that lower generalized network synchronization during rest in early abstinence may constitute a faulty foundation for future restrained responses to external cues, which can be manifested as an inability to inhibit behavior, resulting in relapse.

LONGITUDINAL STUDY OF NETWORK RSS IN STAA We acquired follow-up rs-fMRI on a subset of STAA who maintained abstinence. We compared network RSS between 16 STAA at baseline (STAB, 12 of whom had

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RESTING STATE SYNCHRONY IN LTAA WITH VERSUS WITHOUT A CURRENT MAJOR DEPRESSIVE DISORDER

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FIGURE 25.3 Resting state networks in abstinent alcoholics followed longitudinally. (A) Inhibitory control, (B) emotion regulation, and (C) appetitive drive RSS (mean 6 SD) showing baseline (STAB) and follow-up (STAF) studies on 16 STAA. Inhibitory control RSS shows graded changes, while emotion regulation RSS shows most of its increase by 6 10 weeks abstinence, with no additional change during the follow-up period. Appetitive drive RSS shows small graded changes in synchrony over time, consistent with 12/16 STAA having comorbid stimulant dependence.

comorbid stimulant dependence), with those subjects at approximately 6 12-month follow-up (STAF), the LTAA group, and NSAC. Fig. 25.3A shows graded increases in rs-fMRI inhibitory network synchrony from NSAC, to STAB, to STAF, suggesting that our observed increased synchrony in LTAA is the result of a longitudinal change with abstinence. Fig. 25.3B suggests that increases in emotion regulation network synchrony have mostly taken place by 6 10 weeks of abstinence. Fig. 25.3C shows small decreases in appetitive drive, suggesting that network synchrony changes may be occurring that are supportive of abstinence maintenance. Note, however, that the magnitude of these reductions is smaller than the increases in inhibitory control RSS, consistent with 12 of the STAA in this follow-up sample having comorbid stimulant dependence.

LTAA WITH A CURRENT MAJOR DEPRESSIVE DISORDER In our Hawaii samples, we showed that 14.5% of middle-aged LTAA (n 5 110) had a current major depressive disorder (MDD) diagnosis, compared to a 2.4% rate in age and gender comparable NSAC (n 5 82) (Fein, 2013). These results were comparable to what we found in Northern California in 2007 [19.2% of LTAA (n 5 52) had a current MDD diagnosis versus 4.2% of NSAC (n 5 48)] (Di Sclafani, Finn, & Fein,

2007). We hypothesized that most current MDDs in LTAA reflected depression independent of—rather than secondary to—the substance use disorder (SUD) based on the argument that were the MDD secondary to the SUD, one would expect it to be in remission (rather than meeting criteria for a current MDD diagnosis) after multiple years of abstinence. We proposed that the majority of LTAA with a current MDD had a primary depression that they medicated with alcohol (often with drugs also). The combined burden of an MDD with alcohol dependence (sometimes also with drug dependence) drove such individuals to formal treatment or 12-step recovery, where they have been successful for multiple years in maintaining abstinence from alcohol and drugs. However, they have not been particularly successful in dealing with their MDD. Were their efforts to deal with their MDD successful, one would expect the disorder to be in remission.

RESTING STATE SYNCHRONY IN LTAA WITH VERSUS WITHOUT A CURRENT MAJOR DEPRESSIVE DISORDER We hypothesized that LTAA with a current MDD drank primarily to deal with the negative affect associated with their MDD, and not because of a heightened externalizing diathesis associated with the genetic vulnerability to alcoholism (Pfefferbaum, Ford, White, &

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FIGURE 25.4

Resting state networks in alcoholics with and without comorbid depression. Resting-state synchrony comparisons (mean 6 SD) between NSAC, LTAA with a current major depressive disorder (MDD-current), LTAA with no lifetime major depressive disorder (MDD-never) or with major depressive disorder in remission (MDD-remission) are shown for the: (A) inhibitory control; (B) emotion regulation; and (C) appetitive drive networks. Panel (A) shows that all LTAA subgroups show higher inhibitory control network synchrony compared to NSAC, with the LTAA MDD-current showing the greatest inhibitory control network RSS. Panel (B) shows that MDD-current do not show higher synchrony compared to controls, suggesting that LTAA with a current MDD still evidence impaired emotion regulation, even after multiyear abstinence (consistent with their having a current MDD). Panel (C) shows that MDD-current do not show reduced appetitive drive compared to controls, consistent with elevated appetitive drive not being a strong contributing force in the development of their alcohol dependence.

Mathalon, 1991). Consequently, such individuals would not exhibit the RSS adaptations characteristic of pure alcoholics during extended abstinence (Fein et al., 2017). In Hawaii, we acquired rs-fMRI on eight LTAA with a current MDD, 32 LTAA without (either MDD in remission or never having a MDD), and 69 controls. In the inhibitory executive control network, LTAA with a current MDD showed increased synchrony compared to controls (Fig. 25.4A), while in the emotion regulation executive control network they did not show increased synchrony compared to controls (Fig. 25.4B). In the appetitive drive network, LTAA without a current MDD showed the expected reduction in RSS compared to controls, while LTAA with a current MDD showed no reduction (Fig. 25.4C). These results support the notion of different pathways to alcohol

dependence in LTAA with versus without a current MDD, and differences in the neurobiology of enduring alcohol abstinence, highlighting the heterogeneity within alcoholism and the need for targeted treatment.

P3B AMPLITUDE IN LTAA WITH VERSUS WITHOUT A CURRENT MAJOR DEPRESSIVE DISORDER We hypothesized that LTAA with a current MDD would not exhibit the reduced P3b event-related potential amplitude endophenotype for alcoholism (Fein & Cardenas, 2017), consistent with the notion that they developed alcohol dependence via self-medication of the MDD. We combined P3b data from studies in

II. NEUROBIOLOGY

PARALLEL ICA IDENTIFIES EEG COHERENCE CORRELATES OF RS-FMRI SYNCHRONY

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FIGURE 25.5 P3b amplitudes in alcoholics with and without comorbid depression. P3b amplitude (mean 6 SD) comparisons between NSAC, LTAA with current major depressive disorder (MDD-current), LTAA with no lifetime major depressive disorder (MDD-never) or with major depressive disorder in remission (MDD-remission) are shown for: (A) all participants; (B) Hawaii participants only; and (C) California participants only. Because no differences were found between MDD-never and MDD-remission, these groups were collapsed for comparison to NSAC and MDD-current. LTAA with a current MDD diagnosis did not show the P3b reduction associated with the alcoholism endophenotype (suggesting they did not evidence that endophenotype), and results were consistent across study sites.

California and Hawaii (26 LTAA with current MDD, 127 LTAA without a current MDD, and 125 controls), and found that LTAA with a current MDD did not differ from controls, while LTAA without a current MDD showed lower P3b amplitudes (Fig. 25.5). We conclude that alcohol dependence in LTAA with a current MDD did not derive from the alcoholism endophenotype. This suggests that it is unlikely that this group exhibited the externalizing diathesis characterized by impulsive, disinhibitive behavior and may have developed alcohol dependence via excessive drinking in an attempt to self-medicate their MDD. These results are consistent with the rs-fMRI results from the Hawaii sample; both are suggestive of the need for developing specific targeted treatments for alcoholism that presents with a comorbid MDD.

PARALLEL ICA IDENTIFIES EEG COHERENCE CORRELATES OF RS-FMRI SYNCHRONY We explored the use of parallel ICA for multimodal data fusion between the resting state fMRI and resting state electroencephalogram (EEG) for the 20 LTAA and 21 NSAC from our original study of resting-state synchrony that had both usable fMRI and EEG (Camchong et al., 2013c). This approach is wellaccepted in the medical image processing community and has been used for joint analysis of fMRI, structural MRI, EEG, and genetic data. Parallel ICA allowed us to consider two sets of extracted features from each subject’s data (e.g., fMRI seed connectivity map, and

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FIGURE 25.6 Resting electroencephalogram gamma coherence correlates of resting-state functional magnetic resonance imaging synchrony. The contributions to the gamma1 (31 40 Hz) EEG coherence component that differentiates between LTAA and NSAC and is linked to the rs-fMRI seed correlation map encompassing the executive control and appetitive drive networks are shown within a matrix. Each element of the component vector has been converted to a z-score and only elements with |z| . 1.96 are displayed, where green shows pairs with |z| , 1.96, red shows lower coherence in LTAA vs. NSAC, and blue shows lower coherence in NSAC versus LTAA. The position within the matrix identifies the contributing electrode pair (see the corresponding row and column labels at the top and right side of map). Overall, there is lower gamma coherence in LTAA compared to NSAC, especially left ipsilaterally and fronto-centrally, which may lead to impaired perceptual experience, cognition, and recollection.

the resting state EEG coherence maps for each subject) and identify components that contributed in a similar way to each subject and are “linked.” Parallel ICA revealed a network component that reflected both higher synchrony in executive function regions and lower synchrony in appetitive drive regions (in these subjects, the inhibitory control and appetitive drive networks were reflected by a single independent component). This rs-fMRI component was highly correlated with an EEG coherence component showing mostly higher theta and alpha coherence in LTAA compared to NSAC, and lower gamma coherence in LTAA compared to NSAC. The EEG theta and alpha coherence results suggest enhanced top-down control in LTAA and the gamma coherence results suggest

impaired appetitive drive in LTAA (Fig. 25.6) (Cardenas, Price, & Fein, 2017). Though promising, definitive evidence for an EEG surrogate for rs-fMRI inhibitory control RSS requires a demonstration that the rs-fMRI and EEG surrogate measures covary together on a moment-to-moment basis, and is a direction of future research.

IMPLICATIONS FOR TREATMENT Neurofeedback approaches may have efficacy for modifying network synchrony toward what we see in successful long-term recovery. In this regard, there are a number of laboratories showing the feasibility of

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rs-fMRI neurofeedback to modify network RSS. However, rs-fMRI neurofeedback is not practical, given its cost and complexity. In this regard, we have promising preliminary findings using 64 channel resting EEG, showing that the coherency matrix contains components that vary in conjunction with our rs-fMRI network synchrony measures, as described above. We see this effort moving toward development of an EEG RSS neurofeedback treatment approach to facilitate abstinence maintenance in alcoholics, enhancing RSS of the executive control network to facilitate inhibitory control, and attenuating RSS of the appetitive drive network to decrease the compulsive search for reward. The results of our studies of the impact of comorbid stimulant dependence (Camchong et al., 2013a) or a current MDD (Fein & Cardenas, 2017; Fein et al., 2017) may help us tailor approaches such as this to the heterogeneity present in the population of recovering alcoholics. For example, the most efficacious neurofeedback approach for alcoholics self-medicating for a MDD would be to train enhanced RSS of the executive control network, and potentially in the emotion regulation network, but not train attenuation of RSS in the appetitive drive network.

CONCLUSION The studies reviewed here have clinical significance because they bring focus on previously ignored phenomena indicating significant psychiatric morbidity in LTAA. We believe there is a sizeable pool of individuals with MDD (and possibly with other mood and anxiety disorders) who are muddling along in life within the 12-step recovery community. Twelve-step recovery supports such individuals sufficiently for them to remain sober—and we are in no way disparaging the importance of this accomplishment. Yet, we believe such individuals could be much more productive, happy, and have a generally greater quality of life were their mood or anxiety disorder efficaciously treated. The results reviewed here are a first step toward developing targeted intervention and treatment approaches to accomplish this goal. The work reviewed here is also important because it exposes heterogeneity within the LTAA population. It is clear that LTAA samples (such as our Hawaii and California samples) may differ in the proportion of individuals showing the pattern of current MDD. We have also found that LTAA samples may differ in other ways, reviewed in our recent paper on rs-fMRI versus current MDD diagnoses (Fein et al., 2017). For example, LTAA in Oahu were not as healthy (much higher BMI) as those in California and were much less

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highly educated than those in California (possibly indicating less brain functional reserve capacity)—both of these factors may be related to longer P3b latencies. We believe a major import of these phenomena is that one cannot generalize from one study of LTAA to the population of LTAA. LTAA cohorts may differ in alcoholism severity and in their ability to recover from such burdens. Our experience points out the importance to the research endeavor of multiple laboratories studying the clinical and neurobiological underpinnings of long-term abstinence, and targeting treatment to individuals based on their substance or psychiatric comorbidities.

MINI-DICTIONARY OF TERMS Functional magnetic resonance imaging A brain imaging technique taking advantage of the observation that regions of neural activation induce an increase in oxygenated vs. deoxygenated hemoglobin in blood; blood with oxygenated vs. deoxygenated hemoglobin has greater magnetic susceptibility, resulting in a greater MR signal strength when observed with an imaging sequence sensitive to magnetic susceptibility, allowing measurement of a higher blood-oxygen-level dependent (BOLD) MR signal in areas of increased oxygen supply (inferring increased neural activation), observed at a high spatial resolution. Resting state The brain at rest, or when not performing a task. Spontaneous fluctuations over time in the brain’s electrical, magnetic, or BOLD signal can be observed in the resting state. The spatial pattern of fluctuations may reflect the manner in which activation in the brain is organized spatially, inferring brain networks. The strength of fluctuations in particular networks may reflect the degree of activation in such networks, perhaps indexing the “readiness” of brain networks to respond to external stimulation. Resting state synchrony The synchrony (e.g., correlation or other statistical analysis) of the resting state electrical, magnetic, or BOLD time series measured from anatomically distinct regions. The RSS between regions indexes the degree to which those areas are involved in a functional network—measuring brain organization. Brain network Anatomically distinct brain regions that work in synchrony either to perform certain functions, or to wait in readiness to perform such functions. Examples include the default mode network (active at rest), the dorsal attention network, and the salience network. Independent components analysis (ICA) A computational method for decomposing a multivariate signal into its additive statistically independent subcomponents to help understand the structure of the multivariate data. For example, when used in medical imaging analysis, if for BOLD signal fluctuations across 10,000 spatial locations in the brain, 80% of the variability could be explained by 20 subcomponents; these components may indicate 20 brain networks that underlie the majority of voxel-by-voxel variation in BOLD signals. Neurofeedback A method to teach self-regulation of brain function, using real-time visual or auditory feedback that varies as a function of some measure of brain activity. Reward is offered for increasing (or decreasing) the index of brain function.

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KEY FACTS Executive Control Networks • Faulty functioning of the executive control (inhibitory control and emotion regulation) networks may underlie the poor regulation of behavior and emotion that contributes to alcoholism and relapse. • Regions of the brain involved with executive control include: basal ganglia, bilateral middle frontal gyrus, middle cingulate gyrus, and lateral prefrontal cortex, with connections to the limbic system (encompassing the hippocampus, amygdala, and anterior thalamus).

increased synchrony in the emotion regulation network or decreased appetitive drive network synchrony, suggesting that their MDD is primary and that they developed alcohol dependence via excessive drinking in an attempt to self-medicate their MDD. • Parallel independent components analysis suggests that fMRI RSS of executive control and appetitive drive networks is present in the spontaneous EEG. • Neurofeedback approaches may have efficacy for modifying network synchrony toward what we see in successful long-term recovery, but the heterogeneity within the population of alcoholics should be considered in order to develop treatment interventions targeting specific subpopulations of alcoholics.

Appetitive Drive Networks • An overactive appetitive drive network (involved in forming and responding to appetites, drives, and desires) may underlie the compulsive urge to drink alcohol that contributes to alcoholism and relapse. • Regions of the brain involved in the appetitive drive include: amygdala, caudate, hippocampus, insula, nucleus accumbens, orbitofrontal cortex, posterior cingulate cortex, prefrontal cortex, putamen, thalamus, and the ventral tegmental area.

SUMMARY POINTS • In alcoholism, the lack of control over impulsive and compulsive behaviors is characterized by increased signal exchange (RSS) in appetitive drive networks and decreased RSS in inhibitory control networks. • Enduring abstinence is accompanied by adaptive changes in brain network RSS, more than compensating for the differences that were associated with the development of alcoholism, with graded effects from short-term to long-term abstinence. • Long-term abstinent alcoholics (LTAA) with comorbid stimulant dependence have both similarities and differences in brain network function compared to LTAA without comorbid stimulant dependence; with all alcoholics showing enhanced executive control network tone, but those with stimulant dependence showing no attenuation of appetitive drive network tone. • LTAA with a current major depressive disorder (MDD) show increased synchrony in the inhibitory executive control network, but do not show

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26 Central Role of Amygdala and Hypothalamus Neural Circuits in Alcohol Withdrawal Symptom 1

Katheryn Wininger1, Victor Karpyak2, Seungwoo Kang3 and Doo-Sup Choi3

Neurobiology of Disease Program, Mayo Clinic College of Medicine, Rochester, MN, United States Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, MN, United States 3 Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine, Rochester, MN, United States 2

LIST OF ABBREVIATIONS AUD AWS Amy CeA BNST NAc LC PAG BLA VTA PFC GABA NMDA AMPA CRF NPY HPA ACTH

alcohol use disorder alcohol withdrawal syndrome amygdala central amygdala bed nucleus of the stria terminalis nucleus accumbens locus coeruleus periaqueductal gray basolateral amygdala ventral tegmental area prefrontal cortex γ-aminobutyric acid N-methyl-D-aspartate α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid corticotrophic releasing factor neuropeptide Y hypothalamus-pituitary-adrenal adrenocorticotropic hormone

INTRODUCTION Alcohol use disorder (AUD) constitutes a spectrum of mental disorders that affect approximately 4% 5% of the population (Ezzati et al., 2002; Nam et al., 2015) and causes a substantial global socio-economic burden (Collins et al., 2011). The severity of AUD is typified by an individual’s persistent uncontrolled

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00026-X

consumption of alcohol despite serious adverse effects on health, as well as professional and personal development (Connor, Haber, & Hall, 2016; Grant et al., 2015). As many as 50% of individuals suffering from AUD experience alcohol withdrawal syndrome (AWS) (Saitz, 2005). AWS develops in alcohol-dependent individuals between 6 and 12 hours after cessation of alcohol, usually lasting 1 week, with some symptoms lasting weeks to months (McKeon, Frye, & Delanty, 2008; Mirijello et al., 2015; Victor & Adams, 1953). Patients undergoing AWS display both acute (autonomic hyperactivity, nausea, tremor, tachycardia, hallucinations, and seizures and, in severe cases, delirium tremens and even coma) and prolonged (insomnia, anxiety, depression) symptoms (Heilig, Egli, Crabbe, & Becker, 2010; McKeon et al., 2008; Mirijello et al., 2015; Ruby, O’Connor, Ayers-Ringler, & Choi, 2014) (Fig. 26.1). Understanding the molecular mechanisms of AWS is critical, given that symptoms are severely debilitating and increase the risk of relapse (Heilig et al., 2010; Mirijello et al., 2015). Chronic alcohol use disrupts the signaling within many brain regions causing long-term consequences and adaptations to the circuit which may contribute to the symptoms observed in alcohol withdrawal (Barson & Leibowitz, 2016; Koob & Volkow, 2010; Ruby et al., 2014; Smith & Aston-Jones, 2008; Tunstall, Carmack, Koob, & Vendruscolo, 2017;

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FIGURE 26.1 Alcohol withdrawal syndrome among patients can be very heterogeneous with symptoms ranging from hypertension and tachycardia to tremor and seizures and even anxiety and depression. Symptoms typically begin within 6 12 h following their last drink and last roughly a week. However, symptoms can last much longer increasing the risk of relapse.

Valenzuela, 1997). In particular, alterations in signaling within the extended amygdala, composed of the central amygdala (CeA), bed nucleus of the stria terminalis (BNST), and nucleus accumbens shell region (NAcSh) play an important role in the symptomology and negative affects observed during AWS (de Guglielmo et al., 2016; Gilpin, Herman, & Roberto, 2015; Koob & Volkow, 2010). Additionally, alterations in regions within the circuit of the extended amygdala—such as the locus coeruleus (LC), periaqueductal gray (PAG), and hypothalamus—contribute through changes in the stress response (Barson & Leibowitz, 2016; Koob, 2008; Koob & Volkow, 2010; Smith & Aston-Jones, 2008) (Fig. 26.2). Furthermore, disruption of inhibitory control in the frontal cortices is thought to contribute to the craving observed during withdrawal (Koob & Volkow, 2010). Understanding the circuit and the mechanisms behind AWS and these disabling symptoms, thus, may help patients remain abstinent from alcohol.

Alcohol Withdrawal as a Hallmark of Physiological Dependence It is well-established that patients with AUD progress gradually from impulsive alcohol consumption to compulsive alcohol seeking (Koob & Volkow, 2010). This progression encompasses three stages: binge/ intoxication, withdrawal/negative affect, and preoccupation/anticipation (Koob & Le Moal, 1997, 2005; Koob & Volkow, 2010). Early on, the positive reinforcement of alcohol motivates binge episodes. However, as AUD progresses, the motivation to seek alcohol is replaced by the negative reinforcement of withdrawal

and a compulsive need to obtain alcohol. This cycle of repeated binge episodes followed by withdrawal from alcohol elevates the severity of AWS and consequently increases the risk of relapse (Becker, 1998) (Fig. 26.3). This is possibly due to the overlap of acute pathological neuronal activity in related brain regions and the irreversible transition to pathological allostatic levels. Initial alcohol consumption enhances inhibitory neurotransmission and reduces excitatory neurotransmission (Malcolm, 2003; Mirijello et al., 2015; Valenzuela, 1997). When repeated multiple times, it results in a molecular phenomenon described as “kindling” (Becker, 1998). In particular, downregulation of γ-aminobutyric acid (GABAA) receptors (Cagetti, Liang, Spigelman, & Olsen, 2003) and upregulation of N-methyl-D-aspartate (NMDA) receptors as well as α-amino-3-hydroxy-5methylisoxazole-4 propionic acid (AMPA) receptors has been observed (Haugbol, Ebert, & Ulrichsen, 2005). As a result, abrupt cessation of alcohol produces an imbalanced reduction of GABAergic signaling in conjunction with hyperglutamatergic states, thus creating synaptic hyperexcitability (Heilig et al., 2010; Valenzuela, 1997). This hyperexcitability may increase in magnitude when repeated multiple times (“kindling” phenomenon), which may result in development of acute symptoms such as tremor, seizures, nausea, and an increased risk for delirium tremens which typically subside within a week (Mirijello et al., 2015; Victor & Adams, 1953). Of note, the repeated cycle of withdrawal relapse disrupts neuroendocrine systems, which in turn aggravates the withdrawal symptoms through maladaptive hormonal regulations such as the corticotropin-releasing factor (Becker, 2012; Mirijello et al., 2015). Indeed, most cases of relapse within the first year are not only due to the acute

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FIGURE 26.2 The neural circuit of AUD is complex with many brain regions involved in the initial motivation and movement in alcohol seeking behavior and changes in this circuit with continued exposure to alcohol as well as withdrawal from alcohol. The rewarding properties of alcohol are due to dopamine release from the VTA to the NAc. In addition to these reinforcing properties, a closed loop circuit (NAc-GPThal-mPFC-NAc) contributes to the motivation and movement to seek alcohol. Over time, this seeking becomes a habit and the open loop circuit takes over (mPFC-CPu-GP-Thal-MC-brainstem). Brain regions involved in withdrawal feed into this circuit through changes in signaling within the extended amygdala, composed of CeA, BNST, and the NAc shell region. In addition, connections between the extended amygdala, LC, PAG, and hypothalamus contribute to the changes in stress response, negative affect, heightened anxiety and depression and sleep disturbances observed during alcohol withdrawal. In addition to habitual alcohol seeking, alcohol drinking to relieve or avoid withdrawal symptoms instead of for rewarding properties is observed. Hyp, Hypothalamus; GP, Globus pallidus; Thal, Thalamus; mPFC, Medial prefrontal cortex; CPu, Caudate and putamen; MC, Motor cortex.

FIGURE 26.3 Patients with AUD progress from impulsive alcohol consumption to compulsive alcohol seeking in three main stages: binge drinking and intoxication, withdrawal symptoms and negative affect, and preoccupation and anticipation. Early on, the cycle of binge drinking is motivated by positive reinforcement. However, with repeated binge and withdrawal episodes neuroadaptations such as changes in neural circuit, inhibitory and excitatory neurotransmission, and the neuroendocrine response lead to binge drinking motivated by negative reinforcement. These adaptations will lead to an exaggerated stress response and a decrease in reward which can increase the risk of relapse in patients attempting to abstain from drinking. Source: Modified from Koob, G. F., & Volkow, N. D. (2010). Neurocircuitry of addiction. Neuropsychopharmacology, 35(1), 217 238. doi: 10.1038/npp.2009.110.

physical withdrawal symptoms, but also protracted affective symptoms playing a critical role in AWS (Becker, 2012; Heilig et al., 2010; Hunt, Barnett, & Branch, 1971). New allostatic levels during protracted abstinence involves deficits in associative processing, including absence of an expected positive response to a normally pleasurable experience and increased anxiety and negative affect to normally insignificant stressors or challenges (Heilig et al., 2010; Sinha & Li, 2007). Importantly, psychological symptoms of

withdrawal and prolonged sleep disturbances may be responsible for provoking negative emotions, irritability, and internal tension resulting in “relief craving” and is capable of triggering relapse (Brower & Perron, 2010; Heinz et al., 2003; Ruby et al., 2014). Consequently, it is important to understand how acute AWS mechanisms affect neural activity and how those extend the role in circuit adaptations, which may play a role in allostatic pathology inducing loss of capacity reverting to normal allostasis.

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Amygdala and Alcohol Withdrawal The amygdala is highly involved in the motivational and emotional symptoms observed in repeated alcohol withdrawal, as alcohol withdrawal alters amygdala physiology and connectivity (O’Daly et al., 2012; Stephens & Duka, 2008). In particular, top-down control of emotional input by cortico-amygdalar circuit is dampened, while conversely, bottom-up cortico-amygdala connectivity is heightened (O’Daly et al., 2012). These aberrant changes in circuit specific activation and connectivity may contribute to the increases in anxiety reported during acute and protracted withdrawal, which may be an underlying factor for stress-induced relapse. Increased bottom-up activation would provoke exaggerated emotional reactivity to the stressor, while the decrease in top-down control would elicit inappropriate analysis of this emotional reactivity (O’Daly et al., 2012). Additionally, the mesocorticolimbic dopamine system, integral for the reinforcing effects of alcohol, also has projections to the amygdala (Koob & Le Moal, 2005). Long-term activation of dopaminergic systems during chronic alcohol consumption have been reported to contribute to the connectivity and signaling changes observed within the amygdala and many of the affective symptoms observed during withdrawal (Gilpin et al., 2015; Koob & Volkow, 2010). In particular, the extended amygdala, through numerous afferent connections (BLA and hippocampus) and efferent connections (hypothalamus, PAG, LC) (Gilpin et al., 2015; Koob & Volkow, 2010; Tovote, Fadok, & Luthi, 2015), plays an essential role connecting the brain’s arousal and stress systems with hedonic processing systems producing the negative emotional states observed in alcohol withdrawal (Fig. 26.4). Individuals suffering from AUD display multiple neuroadaptions within this circuit in an attempt to overcome the chronic presence of alcohol and restore normal function in its presence (Valenzuela, 1997). For example, the extended amygdala is associated with many pro-stress (corticotrophic releasing factor, CRF) and anti-stress (neuropeptide Y, NPY) neuropeptides. Reductions in GABAergic signaling from the CeA to PAG and LC during withdrawal alters these neuropeptides (Gilpin et al., 2015; Gray & Magnuson, 1992; Reyes, Carvalho, Vakharia, & Van Bockstaele, 2011; Roberto et al., 2008) producing heightened anxiety. During stress and AUD, CRF and NPY in the CeA are recruited, having opposing but converging effects on anxiety-like behavior and elevated alcohol consumption. CRF increases (Roberto et al., 2010), while NPY decreases (Gilpin et al., 2011), the release of GABA in the CeA. It is well-known that acute alcohol exposure increases GABAergic signaling, and long-term chronic alcohol exposure compensates for this effect by increasing glutamatergic signaling while conversely decreasing

FIGURE 26.4 Overview of the amygdala-HPA-axis involved in alcohol withdrawal syndrome. The extended amygdala plays an essential role connecting the brain’s arousal and stress systems with hedonic processing systems producing the negative emotional states observed in alcohol withdrawal. Patients with AUD display multiple neuroadaptions within this circuit in the attempt to overcome the chronic presence of alcohol. For example, chronic alcohol disrupts the HPA axis function and increases sympathetic nervous system activity. During withdrawal higher levels of CRF, ACTH, and cortisol as well as NE are observed causing increased anxiety and stress response. Similarly, reductions in GABAergic signaling from the CeA during withdrawal can alter neuropeptides within PAG and LC producing heightened anxiety. This may be further heighted by the decreased top-down cortical control over the amygdala.

GABAergic signaling (Valenzuela, 1997). Importantly, neuropeptides in the amygdala may also attempt to compensate for these signaling changes by increasing CRF levels (Roberto et al., 2010), as it has been demonstrated that CRF1 antagonist microinjection into the extended amygdala prior to stress or alcohol withdrawal prevent anxiety-like behavior in alcohol-dependent rats (Huang et al., 2010). Thus, it is likely that anxiety during withdrawal is mediated, at least in part, by CRF elevations. Likewise, administration of NPY2 antagonist in alcoholdependent rats decreased anxiety-like behavior during withdrawal (Kallupi et al., 2014). Furthermore, a study of alcohol-dependent patients has proposed that single nucleotide polymorphisms (SNPs) within the corticotropin releasing hormone receptor 1 (CRHR1) gene are associated with binge drinking and a lifetime prevalence of alcohol intake (Treutlein et al., 2006). While it is clear that neuropeptide stress signaling plays a role in the severity of AUD and withdrawal-induced anxiety, additional studies are required to prevent or reverse these molecular adaptations following cessation of alcohol.

Hypothalamus and Alcohol Withdrawal In addition to neuropeptide signaling, AUDinduced dysregulation of the hypothalamus-pituitaryadrenal (HPA) axis stress response also contributes to

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MINI-DICTIONARY OF TERMS

the dysfunctional affect observed in AWS (Adinoff, Junghanns, Kiefer, & Krishnan-Sarin, 2005). Like stress, acute alcohol intake activates the HPA axis, with acute intoxication (BAC $ 0.08 g%) being associated with hypothalamic induced increase in blood cortisol, adrenocorticotropic hormone (ACTH), and norepinephrine (Allen, Rivier, & Lee, 2011; Blaine & Sinha, 2017; Frias, Torres, Miranda, Ruiz, & Ortega, 2002). However, chronic alcohol use disrupts normal HPA axis function (Tunstall et al., 2017). Chronic alcohol use similarly increases sympathetic nervous system activity (Blaine & Sinha, 2017). This increase in the basal level of cortisol and norepinephrine following chronic alcohol exposure can contribute to sustained excitotoxic signaling resulting in spine density changes in the PFC (Gamo & Arnsten, 2011; Karatsoreos & McEwen, 2013; Sinha, 2008) and may prime the brain to react using instinctual and habitual responses typically observed during a fight-or-flight response (Blaine & Sinha, 2017) (Fig. 26.4). It is hypothesized that these spine density changes are a contributing factor which affects decreased top-down control over compulsive alcohol seeking and affective symptomology in alcohol withdrawal (Heinz, Beck, Grusser, Grace, & Wrase, 2009; Koob & Le Moal, 2005; O’Daly et al., 2012; Stephens & Wand, 2012). During withdrawal and early abstinence, higher basal levels of CRF, ACTH, cortisol, as well as catecholamines such as norepinephrine and epinephrine (Breese, Sinha, & Heilig, 2011; Heilig et al., 2010) are again observed causing increased anxiety and stress responses. Interestingly, the severity of withdrawal symptoms is seemingly associated with the degree of increase in cortisol response (De Witte, Pinto, Ansseau, & Verbanck, 2003). Although this appears to level off after a couple weeks to months, neuroadaptations remain as future stresses elicit exaggerated stress response and subsequent increase in affective symptoms. It has also been suggested that these changes in stress response may lead to altered alcohol and stress-cue reactivity, increasing risk of relapse (Blaine, Seo, & Sinha, 2016). Thus, dysregulation of the HPA-axis stress response not only contributes to AUD by increasing affective symptoms during AWS, but may also drive compulsive alcohol seeking through decreased inhibitory control to the physiological response to stressors.

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receives afferent connections from the extended Amy (Gilpin et al., 2015), but also has norepinephrine efferent connections to many brain regions involved in AUD and AWS symptomology (Amy, hippocampus, cerebellum, hypothalamus, and VTA) as well as activating the sympathetic nervous system (Bobzean, DeNobrega, & Perrotti, 2014). Thus, the LC further contributes to lasting changes in the circuit throughout the brain through norepinephrine signaling and changes to the sympathetic nervous system activation. Many of the symptoms observed in acute withdrawal can be attributed to this signaling and may help to explain why stressors in prolonged abstinence can cause increases in affective symptoms and trigger relapse. The PAG, known for its involvement in processing pain, fear, and anxiety also has a role during alcohol withdrawal. McClintick and colleagues examined gene expression profiles in the PAG of rats following repeated binge/withdrawal episodes of alcohol and found that 14% were differentially regulated 3 hours after the last drink (McClintick et al., 2016). Many of the changes were in neurotransmitter signaling, including changes in receptor composition of NMDA, AMPA, and GABAA receptors. Lasting changes in this signaling could increase the sensitivity of the individual to stress and anxiety and increase chances of relapse to relieve these symptoms (Heinz et al., 2003). Likewise, individuals with alterations in this system due to stress disorders may be more susceptible to AUD. In summary, while there are many regions involved in AUD and the symptomology of alcohol withdrawal, the extended amygdala, hypothalamus, and their subsequent connections, play a key role in maintaining AUD through the negative reinforcement of withdrawal. When treating AUD, it is important to not only alleviate the acute withdrawal symptoms, but also to find a way to correct the long-term circuit and signaling changes observed in theses brain regions that contribute to prolonged affective symptoms and altered stress response. Understanding more about how to compensate for these long-term adaptions may not only find a way to alleviate these debilitating affective symptoms and decrease the chance of relapse, but may help explain some of the psychiatric comorbidities with AUD.

MINI-DICTIONARY OF TERMS

Other Brain Regions Implicated in Alcohol Withdrawal Although we have briefly discussed the role of the LC and PAG in AWS through afferent and efferent connections, these brain regions contribute further to the symptomology observed in AWS. The LC not only

Alcohol use disorder A chronic, progressive mental disorder characterized by loss of control over alcohol intake, continuation of alcohol consumption despite negative consequences, and preoccupation or craving of alcohol. Alcohol withdrawal syndrome A set of symptoms that may occur following cessation of alcohol following a period of excessive use.

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Symptoms can vary from autonomic hyperactivity, nausea and vomiting, and tremor to seizures, hallucinations, anxiety, depression, and insomnia. Negative affect Reduction in pleasure derived from events or stimuli that would normally be perceived and rewarding. Stress response A hyperarousal or physiological response to a perceived harmful event, or threat to survival that is initiated by the neuroendocrine system. Allostasis An adaptive mechanism in which the body adjusts to environmental changes to maintain a stable equilibrium and survive. Impulsive Acting without forethought or consideration of consequences. Compulsive An irresistible urge to do something either without forethought or against a person’s conscious wishes. Positive reinforcement Motivation due to an association with a rewarding outcome. Negative reinforcement Motivation due to avoidance of a negative outcome. Associative processing Cognitive connections between events, emotional states, and behaviors usually resulting from a cued connection. Top-down control The ability the cortex has to control the emotional input received by the amygdala in the cortico-amygdalar circuitry. Bottom-up control The emotional input sent to the cortex by the amygdala in the cortico-amygdalar circuitry in response to the individuals emotional state and environment. Hedonic processing The extent to which pleasure or pain motivates an individual toward a goal or away from a threat.

KEY FACTS • About half of alcohol use disorder patients suffer from AWS. • AWS is diverse depending on duration and symptom severity. • Acutely, it shows autonomic hyperactivity, nausea, tremor, tachycardia, hallucinations, and seizures and, in severe cases, delirium tremens and even coma symptoms. Prolonged and chronic symptoms include insomnia, anxiety, and depression. • The cycle of repeated binge episodes followed by withdrawal from alcohol elevates the withdrawal severity and consequently increases the risk of relapse. • Many brain regions are involved in AWS.

SUMMARY POINTS • This chapter focuses on two main brain regions, the amygdala and hypothalamus, which mediate several key AWS. • The amygdala is highly involved in the motivational and emotional symptoms observed in repeated alcohol withdrawal, as alcohol withdrawal alters amygdala physiology and connectivity.

• Hypothalamus-pituitary-adrenal (HPA) axis regulates withdrawal-induced stress responses. • Interaction between amygdala and hypothalamus through several key neurotransmitters and hormones regulate AWS. • Since withdrawal-associated physical and mental symptoms triggers negative reinforced alcohol seeking behaviors and increases the risk of relapse, it is essential to develop therapeutic intervention targeted for AWS.

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27 Neural Reward Processing in Human Alcoholism and Risk: A Focus on Event-Related Potentials, Oscillations, and Neuroimaging Chella Kamarajan, Ph.D. Department of Psychiatry, SUNY Downstate Medical Center, Brooklyn, NY, United States

LIST OF ABBREVIATIONS ACC AUD BOLD DLPFC EEG ERN ERO ERP FC fMRI FRN GM NAc OFC VTA WM

consistent attempt to understand neural mechanisms underlying reward processing in alcohol/drug addiction using electrophysiological (for a review, see Stewart & May, 2016) and neuroimaging methods (for reviews, see O’Doherty, 2004; Wang, Smith, & Delgado, 2016). The focus of this chapter is to summarize key findings related to reward processing in alcoholics as well as in high-risk (HR) individuals with a family history of alcoholism.

anterior cingulate cortex alcohol use disorder blood-oxygenation-level dependent contrast dorsolateral prefrontal cortex electroencephalogram error-related negativity event-related oscillations event-related potentials functional connectivity functional magnetic resonance imaging feedback-related negativity gray matter nucleus accumbens orbitofrontal cortex ventral tegmental area white matter

REWARD CIRCUITRY

INTRODUCTION Reward seeking and risk avoidance are the most basic features governing the evolutionary processes from simple organisms to higher animals and human beings (Hommer, Bjork, & Gilman, 2011). Anomalies in neural reward circuitry and associated dysfunctions in reward processing may underlie the core of addictive pathology, including alcoholism. Alcohol use disorder (AUD) has often been characterized as a reward deficit disorder (Koob, 2013), and there has been a

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00027-1

Major theories of addiction harbor the notion that alterations in the brain’s reward system underlie addiction (Hommer et al., 2011), and a brief exposition of the reward network as implied in addiction may be useful to understand the related findings and interpretations that ensue. Makris et al. (2008) espoused a simplified reward circuitry for alcohol/drug addiction involving several interconnected structures: prefrontal cortex, cingulate cortex, limbic brain stem, amygdala, ventral tegmental area (VTA), nucleus accumbens (NAc), sublenticular extended amygdala (SLEA), insular cortex, thalamus, and hypothalamus (Fig. 27.1). Clark (2013) extended the canonical reward circuitry by including circuits for vision, action, and memory based on compelling findings by Vickery, Chun, and Lee (2011) that

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FIGURE 27.1 Reward circuitry and associated brain regions. (A) Reward circuitry involved in alcohol addiction. (B) Brain anatomical structures of the reward system. (A) Reprinted by permission of Elsevier from Makris, N., Oscar-Berman, M., Jaffin, S. K., Hodge, S. M., Kennedy, D. N., Caviness, V. S., . . . Harris, G. J. (2008). Decreased volume of the brain reward system in alcoholism. Biological Psychiatry, 64(3), 192 202. Copyright 2008 by the Society of Biological Psychiatry.

neural response to rewards and punishments included additional brain regions which were not previously thought to be involved in reward processing.

ELECTROPHYSIOLOGICAL FINDINGS The majority of electrophysiological studies on reward processing in alcoholism have primarily used traditional event-related potential (ERP) methods, and only a handful of studies have used modern signal processing methods of event-related oscillations (ERO) (for detailed reviews of electrophysiological methods and findings in alcoholism, see Kamarajan, 2018; Chapter 13: Brain Electrophysiological Signatures in Human Alcoholism and Risk; Kamarajan & Porjesz, 2015; Porjesz et al., 2005; Rangaswamy & Porjesz, 2014). The key findings of ERP and ERO studies on reward processing are discussed next.

Error-Related Paradigm A major electrophysiological index of error monitoring is “error-related negativity” (ERN), a negative potential around 150 ms after the participant makes an “incorrect” response in tasks that require “correct” identification of the stimulus presented (Falkenstein, Hohnsbein, Hoormann, & Blanke, 1991). ERN is reported to be aberrent in several neuropsychiatric disorders (Olvet & Hajcak, 2008). Studies have shown that acute alcohol administration significantly reduced ERN amplitude (e.g., Easdon, Izenberg, Armilio, Yu, & Alain, 2005). Similarly, heavy drinkers also displayed a smaller ERN amplitude (Bartholow, Henry, Lust, Saults, & Wood, 2012). In contrast, ERN amplitudes were found to be higher for alcohol-dependent patients compared to healthy controls, particularly in patients with comorbid anxiety disorders (Schellekens et al., 2010). However, there are no prominent ERN findings reported in HR individuals. Outcome-Related Paradigm

ERP Findings in Alcoholism ERP studies have predominantly used error-related paradigms as well as outcome/feedback-related paradigms to examine reward processing. These studies have primarily analyzed N2 (a negative wave/trough around 200 ms) and/or P3 component (a positive wave/peak around 300 ms) as indices of reward processing.

Studies aimed at examining the outcome or feedback related ERP components have used either the Monetary gambling task (MGT) (Fig. 27.2A) or balloon analogue risk task (BART) in order to eluicidate reward processing mechanisms in alcoholism. Two components have been studied: (1) Outcome/Feedback Related Negativity (ORN/FRN/N2) which occurs around 200 ms after the feedback of either loss or gain as outcomes; and (2) Outcome/Feedback Related Positivity

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FIGURE 27.2 ERP waveforms and topography in alcoholic and HR individuals during a monetary gambling task. (A) A monetary gambling task showing a sample of two trials with choice stimulus (CS, 50b and 10b) and outcome stimulus (OS) with a feedback of either gain (green box) or loss (red box) for the selected amount of the bet (50b or 10b). (B) ERP waveforms of Pz electrode (middle panels) and topographic maps of P3 amplitudes (left and right panels) of: (i) alcoholic group compared with control subjects [Source: top row panels; Adapted from Kamarajan, C., Rangaswamy, M., Tang, Y., Chorlian, D. B., Pandey, A. K., Roopesh, B.N., . . . Porjesz, B. (2010). Dysfunctional reward processing in male alcoholics: An ERP study during a gambling task. Journal of Psychiatric Research, 44(9), 576 590]; and (ii) high-risk offspring compared with control subjects [bottom row panels; Source: Adapted from Kamarajan, C., Pandey, A. K., Chorlian, D. B., Manz, N., Stimus, A. T., Bauer, L. O., . . . Porjesz, B. (2015). Reward processing deficits and impulsivity in high-risk offspring of alcoholics: A study of event-related potentials during a monetary gambling task. International Journal of Psychophysiology, 98(2 Pt 1), 182 200 (Kamarajan, Pandey, Chorlian, Manz, Stimus, Bauer, et al., 2015)].

(ORP/FRP/P3) which is elicited around 300 ms after the onset of feedback stimuli (Fig. 27.2B). In an early study, Porjesz, Begleiter, Bihari, and Kissin (1987) reported that abstinent alcoholics showed decreased P3 amplitude in response to incentive stimuli. Using an MGT paradigm, suppressed ORN and/or ORP components were identified in alcoholics (Kamarajan et al., 2010) as well as in HR subjects (Kamarajan, Pandey, Chorlian, Manz, Stimus, Bauer, et al., 2015), especially to the loss outcome (Fig. 27.2B). Using BART, Fein and Chang (2008) reported that smaller N2 amplitudes in feedback trials were associated with a greater family history density of alcohol problems. Crowley et al. (2009) reported that HR adoscent boys were less responsive to loss versus gain outcome compared to controls. These studies are suggestive of reward processing deficits in HR individuals, although more studies are needed to confirm these findings.

for the rewarding object or alcohol/drugs (Bartholow, Henry, & Lust, 2007). Studies have reported that abstinent alcoholics have amplified P3 responses to visual alcohol cues (e.g., Heinze, Wolfling, & Grusser, 2007; Namkoong, Lee, Lee, Lee, & An, 2004). Several studies have explored P3 responses to alcohol cues in different subgroups of alcoholics (Bartholow, Lust, & Tragesser, 2010; Petit et al., 2015; Stewart & May, 2016). While such studies are rare in HR subjects, Ehlers, Phillips, Sweeny, and Slawecki (2003) reported that HR individuals with a family history of alcoholism had an augmented N1 component while regular marijuana users showed diminished N1 response to the presentation alcohol-related words. These studies indicate that alcoholics and HR subjects attach heightened motivational significance (salience) to alcohol/drug cues, which may potentially lead these individuals to craving and addiction to alcohol/drugs.

Alcohol Cue Reactivity Paradigm

ERO Findings During Reward Processing in Alcoholism

A cue reactivity paradigm elicits neural responses (e.g., P3) to alcohol-related visual cues or stimuli (words or pictures). Cue-elicited P3 responses are thought to be associated with motivational significance

There are only a few ERO findings on reward processing. These studies have used the MGT paradigm

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FIGURE 27.3 ERO theta power in alcoholic and HR individuals. Reward-processing deficits in alcoholic and high-risk individuals as shown by attenuated ERO theta power (µV2) in response to loss and gain outcomes in a monetary gambling task. Topographic maps for overall scalp (panels in rows 1 and 4) and time-frequency maps for a representative electrode (panels in rows 2 and 3) of mean total theta power (within 200 500 ms poststimulus window) in alcoholic versus control groups [panelset A; Source: Adapted from Kamarajan, C., Pandey, A. K., Chorlian, D. B., Manz, N., Stimus, A. T., Bauer, L. O., . . . Porjesz, B. (2015). Reward processing deficits and impulsivity in high-risk offspring of alcoholics: A study of event-related potentials during a monetary gambling task. International Journal of Psychophysiology, 98(2 Pt 1), 182 200] and in high-risk offspring versus control subjects [panelset B; Source: Adapted from Kamarajan, Pandey, Chorlian, Manz, Stimus, Anokhin, et al. (2015)].

to evaluate theta band (around 4 7 Hz) oscillatory activities that constitute ORN/N2 and ORP/P3 components (within 200 500 ms time window). Findings indicate that alcoholics and HR offspring displayed lower total theta power during loss and gain conditions (Kamarajan, Pandey, Chorlian, Manz, Stimus, Anokhin, et al., 2015; Kamarajan et al., 2012) (Fig. 27.3). In a study on social drinkers, Nelson, Patrick, Collins, Lang, and Bernat (2011) found that while alcohol intoxication attenuated theta ERO underlying ORN/N2 as well as delta ERO underlying ORP/P3, theta ERO attenuation was stronger for the loss than the gain outcome—“the loss loomed larger.” These findings, while confirming the reward-processing deficits reported by the ERP studies, additionally provided frequency-specific indices of oscillatory signals related to alcoholism, which may be useful to tailor EEG-based intervention programs (e.g., neurofeedback, theta burst stimulation, etc.) for addiction.

NEUROIMAGING FINDINGS A growing number of structural and functional brain imaging studies, using MRI methods, have targeted the brain reward system in individuals with AUD (Sullivan & Pfefferbaum, 2014; Zahr &

Pfefferbaum, 2017), binge or heavy drinking (Cservenka & Brumback, 2017), and a family history of alcoholism (Cservenka, 2016; Squeglia & Cservenka, 2017). These studies have identified dysfunctional reward processing in AUD and HR individuals. Some of the key findings are discussed next.

Structural Findings on Reward System in Alcoholism Specifically, several volumetric studies have reported shrinkage in brain structures in the striatallimbic reward and affect systems in alcoholics (Cardenas et al., 2011; Makris et al., 2008). Structures within the reward system compromised by chronic alcohol exposure include prefrontal regions, hippocampus, amygdala, thalamus, caudate nucleus, and putamen (Sullivan & Pfefferbaum, 2014). Volumetric studies in HR subjects (for details, see Cservenka, 2016) showed a smaller amygdala (e.g., Hill et al., 2013; Wrase et al., 2008) and a larger NAc (Cservenka, Gillespie, Michael, & Nagel, 2015). Studies examining functional recovery with sustained abstinence have shown that cortical gray matter and white matter shrink with continued drinking (Pfefferbaum, Sullivan, Rosenbloom, Mathalon, & Lim, 1998), and that cortical

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NEUROIMAGING FINDINGS

FIGURE 27.4 Brain volume differences across AUD groups. Brain volume differences reported by Cardenas et al. (2011). Voxels shaded in blue/green (top rows in each panel) represent smaller volume in: (i) abstainers relative to light drinkers (LD) (Panel A); (ii) relapsers relative to LD (Panel B); and (iii) relapsers relative to abstainers (Panel C). The numbered regions in pink (bottom rows in each panel) indicate the regions where volume differences were significant: (1) Left amygdala, head of hippocampus, entorhinal cortex, thalamus, adjacent WM; (2) Right thalamus, right colliculi, adjacent WM; (3) Left orbitofrontal; (4) Right middle temporal (including insula); (5) Right occipital; (6) Left superior corona radiata; (7) Left lateral orbitofrontal; (8) Left fronto-temporo-parietal; (9) Right lateral orbitofrontal; and (10) Left amygdala, head of hippocampus, entorhinal cortex. Reprinted by permission of Elsevier from Cardenas, V. A., Durazzo, T. C., Gazdzinski, S., Mon, A., Studholme, C., & Meyerhoff, D. J. (2011). Brain morphology at entry into treatment for alcohol dependence is related to relapse propensity. Biological Psychiatry, 70(6), 561 567. Copyright 2011 by the Society of Biological Psychiatry.

gray matter and subjacent white matter volumes get normalized with sobriety (e.g., van Eijk et al., 2013). It was further elicited that relapsers had smaller brain volumes in regions of the brain reward system compared to abstainers and controls (Cardenas et al., 2011; Durazzo et al., 2011) (Fig. 27.4). Relatedly, diffusion tensor imaging (DTI) studies in alcoholics revealed a compromised white matter (WM) integrity in the form of decreased fractional anisotropy (FA) and increased radial diffusivity (RD) in specific fiber tracts that connect reward structures (Sorg et al., 2012; Yeh, Simpson, Durazzo, Gazdzinski, & Meyerhoff, 2009). Fiber connectivity disruptions in these tracks have also been reported in alcoholics (Kuceyeski, Meyerhoff, Durazzo, & Raj, 2013). Similar abnormalities in WM microstructure in HR offspring have also been reported (e.g., Acheson et al., 2014; for a discussion on this topic, see Cservenka, 2016), implicating a genetic underpinning for WM malformation.

Reward Related Functional MRI Findings in Alcoholism Numerous fMRI studies have examined reward processing in alcoholism under various task conditions. A recent meta-analysis on this topic revealed that individuals with alcohol and other addictions manifested decreased striatal activation during reward anticipation, while showing increased activation in the ventral striatum during reward outcome (evaluation) compared to normal controls (Luijten, Schellekens, Kuhn, Machielse, & Sescousse, 2017). Another meta-analytic review on the alcohol cue reactivity paradigm concluded that alcoholics exhibited greater BOLD response to alcohol cues than controls in the regions that are part of the reward circuitry (Schacht, Anton, & Myrick, 2013). On the other hand, there are only a few fMRI studies on reward processing in HR individuals that showed significant activation in the reward

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network regions (for reviews, see Cservenka & Brumback, 2017; Squeglia & Cservenka, 2017). For example, Acheson, Robinson, Glahn, Lovallo, and Fox (2009) reported that HR subjects showed more activation in the left dorsal ACC and left caudate nucleus compared to controls. These findings support the claim that functional architecture of the reward system is compromised in alcoholic and HR individuals.

Functional Connectivity Findings on the Reward System in Alcoholism Functional connectivity (FC) represents temporal correlation or synchrony of neural signals between anatomically separated brain regions. The FC measures of the brain signals (e.g., fMRI and EEG/MEG) can be computed either from the resting state or from the event-related task performance data. A growing number of FC studies have reported altered FC across several brain regions that are part of the reward networks. Resting State Functional Connectivity The resting state functional connectivity (rsFC) represents intrinsic functional organization of the brain (Raichle, 2011). A series of rsFC studies comparing short-term and long-term abstinent alcoholics, as well as abstainers and relapsers, reported altered functional connectivity in the networks that support reward processing and executive functioning (Camchong, Stenger, & Fein, 2013a; Camchong, Stenger, & Fein, 2013b; Camchong, Stenger, & Fein, 2013). Recently, MullerOehring, Jung, Pfefferbaum, Sullivan, and Schulte (2015) reported significantly weaker connections in alcoholics in the reward network connections (NAc amygdala and NAc angular gyrus) compared to controls. Among the few rsFC studies on HR subjects (for a relevant discussion, see Cservenka, 2016; Squeglia & Cservenka, 2017), a recent study reported altered connectivity of NAc with inferior frontal gyrus and orbitofrontal gyrus in these individuals (Cservenka, Casimo, Fair, & Nagel, 2014), thus, implicating a compromised reward circuitry. Task Related Functional Connectivity Using a reward-guided decision-making task, Park et al. (2010) found that abnormal connectivity between striatum and dorsolateral prefrontal cortex (dlPFC) predicted impairment in reinforcement learning and the magnitude of alcohol craving. Courtney, Ghahremani, and Ray (2013) reported that individuals with more severe alcohol dependence exhibit less frontal connectivity with the striatum during the performance of a Stop Signal Task. Muller-Oehring et al. (2013) found a weaker midbrain connectivity to medial

and dlPFC in response to alcohol-related and negative emotional words during a Stroop task. Similarly, there is growing evidence for altered connectivity in HR individuals during various cognitive processes (Cservenka, 2016), including reward processing (Weiland et al., 2013). In summary, aberrant functional connectivity within reward networks during task performance and at rest, indicating abnormal neural communications across the reward structures, may underlie the core symptomatology of alcoholism as well as the vulnerability to develop AUD and related traits.

ISSUES AND FUTURE DIRECTIONS This article has summarized prominent findings related to reward processing in individuals with AUD and in those with a family history of alcoholism, as elicited by electrophysiological and neuroimaging (MRI-based) methods. However, relevant findings from other modalities, for example, positron emission tomography (PET), are not included as it is beyond the scope of this chapter. Further, some of the issues and limitations involving the research on reward processing needs to be mentioned. Firstly, differences in the reported findings across various modalities. For example, the PET studies of dopamine release and receptor density strongly support the rewarddeficiency hypothesis, while the more recent fMRI studies of goal-directed behavior provide both support and contradiction for each of the hypotheses (cf. Hommer et al., 2011). Secondly, although conventional approaches have assumed subcortical structures (basal ganglia and limbic system) as the primary neural substrate for reward processing, the reinforcement-related BOLD signals were ubiquitous in the gray matter of nearly every subdivision of the human brain (Vickery et al., 2011), thus adding to our understanding that reward processing may include and/or have an influence on a much broader range of cognitive and perceptual processes than previously thought. Therefore, future theoretical and empirical approaches should take these new findings into account. Thirdly, in order to maximize our understanding of reward processing mechanisms underlying addiction, multimodal studies combining different neuroscientific methods on the same subjects (Andreou et al., 2017) should be encouraged as there are only a few such studies on reward processing (e.g., Martin, Potts, Burton, & Montague, 2009). Lastly, longitudinal studies are essential to understand reward processing in the context of progression of AUD symptoms, diagnosis, risk propensity, and manifestations. It is suggested that future studies may employ improved experimental protocols and advanced technologies to address these issues and

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limitations. On the positive side, amid the existing differences, there is also a growing consensus across findings of different domains and modalities in unraveling neurobiological and neurocognitive mechanisms underlying AUD and its risk. It is hoped that further advancements in electrophysiological and neuroimaging technology will deepen our understanding of the disorders and provide new translational opportunities to treat AUD and other addictive disorders.

MINI-DICTIONARY OF TERMS Diffusivity A measure of diffusion rate of water molecules in the neuronal fibers. This can be either axial (along the main axis) or radial (orthogonal to the axis). Event-Related Oscillations (ERO) Representation of time- and frequency-specific oscillatory patterns specific to neurocognitive processing under different task conditions. Event-Related Potentials (ERP) Brain electrical activity of alternating positive and negative potentials/waves that are time locked to a stimulus occurrence or event. Feedback-Related Negativity (FRN) A negative potential observed around 200 ms in response to a feedback or outcome. It is also called outcome-related negativity. Fractional Anisotropy (FA) A measure of microstructural integrity that quantifies the movement of water molecules in the white matter fiber tracts. Functional Connectivity (FC) Temporal correlation or synchrony of neural signals between anatomically separated brain regions. Magnetic resonance imaging (MRI) A technique to create images of body organs using magnetic resonance principles. It can be either structural or functional (fMRI).

KEY FACTS • Addictions to alcohol and other drugs are associated with the dysfunction of reward circuitry. • Electrophysiological and neuroimaging methods have elucidated reward processing deficits underlying alcoholism and risk. • Decreased ERP amplitudes as well as attenuated ERO theta response to outcome stimuli have been observed in alcoholics and HR offspring/relatives. • Neuroimaging studies have revealed altered structural and functional indices of reward processing in alcoholics and HR individuals. • Further understanding of reward pathways in alcoholism may lead to therapeutic applications.

SUMMARY POINTS • Both electrophysiological and neuroimaging methods have been found to be highly useful to delineate neurocognitive mechanisms underlying reward processing.

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• Individuals with alcoholism and their HR relatives manifest reward-processing deficits, as revealed by electrophysiological and neuroimaging findings. • Decreased ERP amplitude as well as attenuated ERO theta response to outcome stimuli have been primarily reported in alcoholics and HR offspring. • Neuroimaging studies have revealed reward processing deficits in alcoholics and HR individuals in terms of differences in brain volume, cortical thickness, white matter integrity, and functional connectivity. • Further studies with sound methodology and novel techniques are warranted in order to answer myriad questions regarding the neurobiology of addictions.

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28 Occipito-Temporal Sensitivity and Emotional Faces in Alcohol Use Disorder 1

Saranya Sundaram1,2, Eva M. Mu¨ller-Oehring1,3 and Tilman Schulte1,2

Neuroscience Program, Center for Health Sciences, Bioscience Division, SRI International, Menlo Park, CA, United States 2Doctoral Program for Clinical Psychology, Palo Alto University, Palo Alto, CA, United States 3 Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States

LIST OF ABBREVIATIONS AUD Inf. OG Sup. TS Lat. FG Hippo Amyg Ins DS VTA VS ACC VLPFC IFG OFC

having lifetime AUD. Based on the number of criteria met, AUD severity is differentiated between mild (2 3 symptoms), moderate (4 5 symptoms), and severe ($6 symptoms) (American Psychiatric Association, 2013). In concordance with DSM 5 criteria, the lifetime prevalence of individuals with AUD is approximately 29.1% (Grant et al., 2015), with an increase in problematic alcohol consumption by women (Wagner & Anthony, 2007). Increasing severity of alcohol abuse is commonly accompanied by impairments in visuospatial abilities and higher cognitive functioning (OscarBerman & Marinkovi´c, 2007); however, it is less clear how the neural systems of emotional alterations are associated with long-term, heavy alcohol consumption.

alcohol use disorder inferior occipital gyrus superior temporal sulcus lateral fusiform gyrus hippocampus amygdala insula dorsal striatum ventral tegmental area ventral striatum anterior cingulate cortex ventrolateral prefrontal cortex inferior frontal gyrus orbitofrontal cortex

INTRODUCTION

AUD AND EMOTION

Alcohol use disorder (AUD) is becoming one of the most prevalent mental and public health problems with high mortality rates across the life span (Kendler et al., 2016). AUD is characterized by the loss of control over alcohol intake (e.g., Wilcox, Dekonenko, Mayer, Bogenschutz, & Turner, 2014), development of tolerance for the effects of alcohol, and a negative emotional state when alcohol is not available (Grant et al., 2004). The recently updated Diagnostic and Statistical Manual of Mental Disorders—5th edition (DSM 5) specifies eleven possible criteria for a diagnosis of AUD, with individuals having to meet at least two criteria within the previous 12 months to be diagnosed as

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00028-3

An AUD can significantly disable individuals in their daily life activities and social interaction skills, and is often associated with other psychiatric disorders and severe physical health problems (Dawson, Li, Chou, & Grant, 2009; Rehm, 2011). In particular, the high comorbidity between depression, anxiety, and alcoholism is clinically more difficult to treat than one exclusive disorder (Lynskey, 1998; Pettinati, Rukstalis, Luck, Volpicelli, & O’Brien, 2000). Despite the various etiologies of AUD, psychosocial factors and negative affective states are considered to be two of the main contributing factors in the development and maintenance of an

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AUD, which can also significantly impact an individual’s social functioning (Klingemann & Gmel, 2001; Room et al., 2010). Successful development of interpersonal relationships involves nonverbal communication skills (Montague, Chen, Xu, Chewning, & Barrett, 2013), as well as the accurate interpretation of nonverbal signals, which contributes to experiencing rewarding social interactions (Carton, Kessler, & Pape, 1999).

EMOTIONAL FACIAL EXPRESSIONS Facial expressions are salient emotional stimuli that capture attention (Parks, Kim, & Hopfinger, 2014) and increase arousal (Smith, Weinberg, Moran, & Hajcak, 2013). Marked impairments in recognition of emotional facial expressions (EFE) occur in AUD (Philippot et al., 1999). For example, Kornreich et al. (2016) found that nonverbal emotion-encoding deficits in recently detoxified AUD patients were linked to perceptual difficulties rather than deficits in semantic labeling of emotion in faces or voices. Although the perception of basic emotions is considered a general ability, further research provided evidence for knowledge guiding the transformation of facial affect perceptions into perceptions of discrete emotions, such as anger, disgust, fear, and sadness (Lindquist, Gendron, Barrett, & Dickerson, 2014).

NEURAL CORRELATES OF EFE IDENTIFICATION Difficulties in the perception and recognition of facial emotion in AUD may be linked to certain brain areas, such the occipito-temporal areas for facial perception (Charlet et al., 2014; Kanwisher, McDermott, & Chun, 1997), the amygdala for emotion processing, the hippocampus for knowledge-guided perception (Marinkovic et al., 2009), and the ventrolateral prefrontal cortex (VLPFC) for detection of unexpected, behaviorally relevant or salient stimuli (Pourtois & Vuilleumier, 2006). Neuroimaging studies have attempted to shed light on the neural pathways underlying emotion-processing deficits in AUD. One study examined the association between brain volume shrinkage that accompanies multiple detoxifications and relapses in AUD and cognitive flexibility and emotion perception (Trick, Kempton, Williams, & Duka, 2014). The findings of this study revealed that individuals with AUD were not only impaired in shifting their behavior according to the rules of a cognitive flexibility and set-shifting task, they were also less accurate in recognizing fearful facial expressions (Trick et al., 2014). In addition, poorer recognition of fear was correlated with the decreased gray matter volume in the right inferior frontal gyrus (IFG)—

an area associated with inhibitory control functions (Munakata et al., 2011). Overall, in comparison to healthy controls, individuals with AUD displayed decreased gray matter volume in several brain regions, including the medial and inferior frontal cortices, insula, and inferior parietal lobule, which are all associated with impaired emotion recognition and inhibitory control. In agreement with the structural findings, O’Daly et al. (2012) observed in a functional MRI (fMRI) study that difficulties in recognizing fearful faces in AUD were associated with decreased activation in prefrontal cortices involved in attentional and executive processes, as well as decreased prefrontal insular and amygdala pallidum functional connectivity, which was further related to AUD severity (number of detoxifications). Additionally, in a recent fMRI study, we investigated the mesocorticolimbic network responsivity in AUD to alcohol cues and social emotion cues (Alba-Ferrara, Mu¨ller-Oehring, Sullivan, Pfefferbaum, & Schulte, 2016). Primarily, we found that while viewing pictures of alcoholic versus nonalcoholic beverages and emotional faces, individuals with AUD and healthy controls displayed activation in the fusiform gyrus (FG) during emotional face processing, and the hippocampal and pallidum regions during alcohol-picture processing. However, in AUD, we found less fusiform activity to emotional faces and more pallidum activity to alcoholic pictures, which appeared to be related to increased length of sobriety. Here, the lower occipito-temporal sensitivity to emotional faces and enhanced striatal sensitivity to alcohol stimuli are characterizations of the neurofunctional abnormalities in sober, early-remission AUD patients. Taken together, altered regional activation and interaction of occipitotemporal and mesocorticolimbic network nodes for processing facial affects may underlie impaired social competencies and socioemotional stress in AUD, possibly contributing to individual vulnerability and relapse risk.

BRAIN MODEL OF CORE AND EXTENDED REGIONS OF EFE PROCESSING The mesocorticolimbic pathway (MP) appears to be involved in the emotional processing of alcoholseeking behaviors (Vollsta¨dt-Klein et al., 2012). When encountering an appetitive emotional stimulus that signals a reward, this pathway directs the dopaminergic projections from the ventral tegmental area to other neural substrates of the mesocorticolimbic system, for example, the dorsal (DS) (e.g., caudate, putamen) and ventral striatum (VS) (e.g., nucleus accumbens), and influences attention and cognitive behaviors (Schultz, Dayan, & Montague, 1997). The DS and VS likely contribute to cue-induced, alcohol-engaging behaviors

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(Bassareo, Luca, & Chiara, 2002). In individuals with AUD, the MP appears to be suppressed in response to aversive stimuli (Kienast et al., 2013). In emotional processing, the MP intersects with the corticostriatal pathway (CP), which is implicated in the reward processing of addictive behaviors (Kelley & Berridge, 2002). As such, individuals with AUD appear to have decreased occipito-temporal mesocorticolimbic sensitivity to emotional faces and increased corticostriatal sensitivity to alcohol-related stimuli. Research has found that face-specific activity, such as face detection and identification of facial features, is mediated in the FG and the inferior occipital gyrus (Haxby, Hoffman, & Gobbini, 2000; Schiltz & Rossion, 2006). Prefrontal regions play specific roles in emotional decision-making and the control of behavior in interaction with striatal reward and limbic emotion areas (Bechara, Damasio, Damasio, & Lee, 1999; Clark et al., 2008). For example, activation of the anterior cingulate cortex (ACC) is involved in error processing (Carter et al., 1998), particularly based on affective or motivational signals (Bishop, Duncan, Brett, & Lawrence, 2004; Bush, Luu, & Posner, 2000). The orbitofrontal cortex is involved in controlling and

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correcting reward-related and punishment-related behavior, such as in emotion (Guo et al., 2017; Gupta, Koscik, Bechara, & Tranel, 2011). This region has been found to respond selectively to facial expression, specifically when expressions indicate that behavior should change (Hornak et al., 2003). Fig. 28.1 depicts a modified model of facial expression perception in which the information process is aberrant in chronic alcohol abuse affecting activations within a distributed brain network, including core occipito-temporal regions and extended limbic, striatal, and prefrontal regions.

IMPLICATIONS OF EFE PROCESSING DEFICITS Difficulties in the decoding of emotional meanings of facial expressions could potentially underlie or exacerbate interpersonal issues, especially in individuals with AUD (Frigerio, Burt, Montagne, Murray, & Perrett, 2002) and promote social isolation (Duberstein, Conwell, & Caine, 1993). Social isolation, in turn, can promote alcohol use as a maladaptive coping

FIGURE 28.1 Model of the neural pathways of aberrant face processing in AUD. Source: The part on core and extended face analysis neural systems is modified from Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. (2000). The distributed human neural system for face perception. Trends in Cognitive Sciences. http://doi.org/10.1016/S1364-6613(00)01482-0. AUD, Alcohol use disorder; Sup. TS, Superior temporal sulcus; Inf. OG, Inferior occipital gyrus; Lat. FG, Lateral fusiform gyrus; Hippo, Hippocampus; Amyg, Amygdala, INS, Insula; DS, Dorsal striatum (caudate/putamen); VTA, Ventral tegmental area; VS, Ventral striatum; ACC, Anterior cingulate cortex; VLPFC, Ventrolateral prefrontal cortex; IFG, Inferior frontal gyrus; OFC, Orbitofrontal cortex.

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mechanism (Kornreich et al., 2002). Typically, emotional processing of facial expressions is quick, seldom lasting longer than one second (Ekman, 1984). Emotional faces can enhance sensory processing, particularly for faces exhibiting fear or anger (Schupp et al., 2004; Vuilleumier & Pourtois, 2007). However, individuals with AUD have been found to overestimate the intensity of emotional facial expressions (Kornreich et al., 2001). In essence, individuals with AUD appear to require greater facial expression intensities to correctly decode nonverbal emotion, especially women with AUD (Frigerio et al., 2002). A recent study (D’Hondt, de Timary, Bruneau, & Maurage, 2015) testing emotion identification thresholds using morph steps for facial stimuli (happy, angry, sad, and neutral expressions) found that categorical perception of facial emotion was preserved in AUD subjects. However, AUD individuals had increased identification thresholds, that is, they under-identified the predominant emotion in ambiguous facial stimuli. As we typically encounter a continuum of emotional expressions in the faces of others in daily life, a deficit in identifying subtle emotion may significantly impede social functioning in AUD individuals.

FUNCTIONAL CONNECTIVITY BETWEEN CORE AND EXTENDED EFE NETWORK REGIONS Processing of emotional expressions other than fear and anger may involve increased sustained attention, discrimination, and categorization (Batty & Taylor, 2003; Luo, Feng, He, Wang, & Luo, 2010). Research has found increased neural activity in core occipitotemporal and extended limbic, striatal, and prefrontal regions cortices across multiple stages of emotional processing (Pessoa, McKenna, Gutierrez, & Ungerleider, 2002; Schupp et al., 2004; Vuilleumier & Pourtois, 2007). The vast cortical network that mediates facial perception include the insula and amygdala for processing of facial expressions (Ishai, 2008), the FG for the identification of people (Grill-Spector, Knouf, & Kanwisher, 2004), the nucleus accumbens for connecting face processing and social interaction processes with the reward circuitry (Kranz & Ishai, 2006), and the superior temporal sulcus for executive control processes related to gaze direction and speech-related movements (Beauchamp, Lee, Argall, & Martin, 2004). Within that reward circuitry, research has found that the FG, associated with facial feature identification processes, exhibits a dominant influence over the other brain regions (Fairhall & Ishai, 2007). Content-specific dynamic alterations between the FG and amygdala increase the processing of emotional faces (Fairhall &

Ishai, 2007; Herrington, Taylor, Grupe, Curby, & Schultz, 2011). The amygdala is also highly receptive to fearful facial expressions (LeDoux, 2003), possibly inciting cortical functionality to aid in response to a threat ¨ hman, 2005). The insula, on the other hand, appears (O to be particularly responsive to facial expressions of disgust (Ruiz et al., 2013). Alcohol detoxification is associated with inaccurate recognition of fear (Townshend & Duka, 2003), and converging with that observation, individuals with alcohol dependency and greater detoxifications showed decreased connectivity between the insula and inferior frontal-cortical region, but increased connectivity between the amygdala and prefrontal cortical regions associated with attention and executive function processes (O’Daly et al., 2012). These results suggest that AUD, as well as its severity, affect functional neural networks, to the extent that individuals with AUD are less likely to recognize emotional cues and fearful facial expressions than controls.

ALCOHOL-RELATED CUES AND EFE RECOGNITION Categorical perception of EFE is influenced by contextual cues that impact how individuals distinguish between various emotional expressions (Freeman et al., 2015). Similarly, contextual cues can gain emotional valence with repeated alcohol consumption by associating them with the rewarding effects of alcohol. Individuals are then more likely to respond emotionally to alcohol-related cues, as well as be subject to increased alcohol cravings and alcohol seeking behaviors (Myrick et al., 2004). Alcohol-related stimuli consequently act as an incentive that arouses and governs behavior (Flagel et al., 2011). Even in the absence of a pharmacological effect, the conditioned alcohol-related cues can elicit dopaminergic striatal activity (Gru¨sser et al., 2004; Heinz, Siessmeier, Klein, Gru¨sser-Sinopoli, & Schreckenberger, 2004). Furthermore, the affective state of an individual can influence cue-reactivity (Rees & Heather, 1995). Individuals who perceive reward may respond to alcohol-related cues in an appetitive emotional state (i.e., positive affect and positive urge to drink) (Ivory, Kambouropoulos, & Staiger, 2014). As such, heavy alcohol consumption can increase attentional biases toward alcohol-related cues, affect emotional responsiveness, and impact EFE (Maurage et al., 2011). Deficits in the categorial perception of EFE in AUD can differ among categories. For example, individuals with AUD may decode sad, happy, and surprised expression similar to controls, but show enhanced fear perceptions when confronted with faces showing mixed emotions (Townshend & Duka, 2003). This may be due to shared nodes in the

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KEY FACTS

neural circuits underwriting anxiety and addiction (Agoglia & Herman, 2018). Both fear-paired cues and alcohol-related cues elicit activity in the amygdala (Dager et al., 2013; Duvarci & Pare, 2014), which plays a role in assigning emotional valence to internal and external stimuli (Beyeler et al., 2018) and is affected with heavy alcohol consumption (Crane, Gorka, Phan, & Childs, 2018). While individuals with AUD may encompass the ability to perceive categorical differences in EFE, they may, however, require higher emotion intensity thresholds to decode nonverbal expressions (Frigerio et al., 2002) and process ambiguous EFE (D’Hondt et al., 2015).

CONSIDERATIONS FOR FUTURE RESEARCH OF AUD AND EFE PROCESSING To better understand how occipito-temporal regions, specifically the FG for facial expressions, contribute to difficulties in emotional face processing in AUD, it is critical to recruit large sample sizes to investigate how key brain regions and their neural network interconnectivity are altered. For most studies on AUD, comorbidity should be considered as other substances may contribute to the neural mesocorticolimbic network response to emotion and alcohol cues. AUD not only occurs in conjunction with other abuse of substance, it also shows a high comorbidity with psychiatric disorders, often making it difficult to pinpoint the unique contribution of alcohol addiction to difficulties in emotion processing, specifically facial expressions that uniquely convey human interaction and communication skills.

MINI-DICTIONARY OF TERMS Attention The ability to focus or concentrate on certain information while often also ignoring unrelated information (selective attention), or divided attention with focus on multiple tasks at the same time. Alcohol Use Disorder As by DSM-5, AUD as a psychiatric disorder is understood as a continuum between abuse and dependency based on 11 diagnostic criteria. Cognitive Flexibility The ability to process and switch between thinking about multiple concepts of information or thinking about multiple concepts of information at the same time. Cognition The conscious mental ability of acquiring general knowledge and understanding through one’s own experiences. Comorbidity The presence of two diseases, disorders, conditions, illnesses, etc. that occur at the same time. Decode The mental ability to evaluate and interpret unintelligible information into something intelligible. Emotional Recognition The ability to detect or identify human emotions. Emotional Valence The positive or negative emotional value or feeling of something. Encoding The initial learning or taking in of information. Facial Perception The ability to recognize, process, and interpret faces. Inhibition The ability to consciously or unconsciously stop an action or response. Perceptual Reasoning The ability to analyze and reason using nonverbal language. Salient Something that is the most noticeable or significant. Sensory Processing The brain’s ability to register, evaluate, organize, and interpret information that is received through the senses: sight, touch, hearing, smell, and taste. Stimulus Something that leads an individual to respond. Visuospatial The ability to perceive information visually about objects located in space. We use this to guide or movements and orientation of the world.

KEY FACTS Emotional Facial Perception and Recognition

CONCLUSION Chronic alcohol consumption is related to difficulties perceiving emotion in faces potentially through altered dynamic interactions among nodes of core visual, mesocorticolimbic, and corticostriatal systems. Encoding salience in emotional faces is highly relevant considering how it may impact daily life and social interactions of individuals with AUD. Accordingly, treatment planning should emphasize the implementation of emotional skills and facial affect perception that aim to strengthen an individual’s interpersonal communication, which can potentially reduce relapse.

• Emotional facial recognition is a biologically and genetically inherent and adaptive skill. • There are seven universal emotions of facial expressions: anger, fear, disgust, happiness, sadness, contempt, and surprise. • Our first impressions of others are based on their facial expressions. • Difficulties with recognition of facial emotions are prevalent in various psychiatric disorders, such as AUD. • Perception and recognition of emotional facial expressions (EFE) guide social interactions, with impairments in EFE causing difficulties with behaviors and actions in social contexts.

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SUMMARY POINTS • Difficulties in processing facial emotion occur in AUD individuals. • This chapter presents a model of neural brain systems involved in emotional face processing in AUD individuals. • Difficulties may arise as early as the identification of facial features mediated by fusiform and inferior occipital cortices. • Dysfunctional pathways among occipitotemporal visual, mesocorticolimbic emotion, and corticostriatal reward systems may underlie socialemotion deficits in AUD. • Accurate perception of facial affect has relevance for experiencing rewarding social interactions, strengthening social competencies, and reducing socio-emotional stress.

Acknowledgment The authors declare no competing financial interests. Support was provided by National Institutes of Health grants AA023165 and AA018022.

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29 Alcohol and Violence in Psychopathy and Antisocial Personality Disorder: Neural Mechanisms 1

Nathan J. Kolla1,2,3,4 and Christine C. Wang5

Forensic Psychiatrist, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada 2Violence Prevention Neurobiological Research Unit, CAMH, Toronto, ON, Canada 3Department of Psychiatry and Criminology, University of Toronto, Toronto, ON, Canada 4Waypoint Centre for Mental Health Care, ON, Canada 5Medical Student, University of Toronto, Toronto, ON, Canada

LIST OF ABBREVIATIONS ASPD DSM 5-HT CNS 5-HIAA CSF DA DAT SPECT MAO-A OFC VS fMRI MAOA-H MAO-L PCL-R IPV SUDs

antisocial personality disorder Diagnostic and Statistical Manual of Mental Disorders serotonin or 5-hydroxytryptophan central nervous system 5-hydroxyindoleacetic acid cerebrospinal fluid dopamine dopamine transporter single-photon emission computed tomography monoamine oxidase-A orbitofrontal cortex ventral striatum functional magnetic resonance imaging high in vitro activity MAO-A genotype low in vitro activity MAO-A genotype Psychopathy Checklist-Revised intimate partner violence substance use disorders

INTRODUCTION Research has consistently shown that alcohol affects people in different ways. One adverse outcome of alcohol use can be violent behavior. Personality disorders have also been linked to alcohol misuse and violence. This chapter considers the interrelationship between alcohol, ASPD, psychopathy, and violence. We begin with a definition and description of terms and then

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00029-5

provide a fulsome discussion of the neural underpinnings of violent behavior when both alcohol misuse and ASPD or psychopathy is present. Many terms have been used to describe the misuse of alcohol. From a psychiatric perspective, the DSM-5 (American Psychiatric Association, 2013) defines problematic use of alcohol as the manifestation of an alcohol use disorder that may be mild, moderate, or severe in intensity. The previous edition of the DSM (American Psychiatric Association, 2000) categorized harmful use of alcohol as either alcohol abuse or alcohol dependence. Alcoholism is a colloquial expression that has garnered criticism given its vagueness, although it also connotes problematic alcohol use. For the purposes of this chapter, we use the term “alcohol misuse” to encompass all forms of harmful alcohol use. ASPD is a condition characterized by a longstanding pattern of disregard for, and infringement of, the rights of others. According to the DSM-5, the adverse behavior must have occurred by the age of 15 years and three or more of the following must be present: (1) inability to conform to social norms and lawful behaviors; (2) deceitfulness, persistent lying, and conning others; (3) impulsivity; (4) aggressiveness as indicated by repeated physical fights or assaults; (5) reckless disregard for safety; (6) irresponsibility; and (7) lack of remorse. The individual must also be at least 18 years old and conduct disorder needs to have been present

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before the age of 15 years. Most individuals with ASPD have a record of criminal offending and approximately 85% have enacted violence toward others (Robins & Regier, 1991; Samuels et al., 2004). Other research has identified ASPD as the psychiatric disorder with the highest rate of violence toward strangers, intimate partners, and children (Coid et al., 2006). There is evidence that ASPD belongs to an externalizing spectrum of behaviors that includes alcohol misuse (Krueger et al., 2002), and the odds of ASPD individuals having any alcohol use disorder was reported as 8.0 in one investigation (Compton, Conway, Stinson, Colliver, & Grant, 2005). Psychopathy is a well-researched personality disorder that shares commonalities with ASPD. In addition to early and pervasive criminal behavior, psychopathy features such maladaptive personality traits as egocentricity, callousness, empathic deficits, manipulativeness, and impulsivity (Miller & Lynam, 2012). Some evidence indicates that psychopathy is a more severe form of ASPD (Coid & Ullrich, 2010). Although alcohol misuse is not as well-studied in psychopathy as in ASPD, some research indicates that alcohol use disorders are more common among individuals with psychopathy than those without the disorder. One study found that 93% of incarcerated males with psychopathy met criteria for an alcohol use disorder compared with 65% of prisoners without psychopathy (Smith & Newman, 1990). What follows is a comprehensive account of investigations reporting on neurobiological findings in individual with ASPD or psychopathy who misuse alcohol and are violent.

NEUROBIOLOGICAL MECHANISMS Neurochemistry Serotonin Numerous studies investigating the neurochemical correlates of aggression among individuals with alcohol misuse and a history of violence have highlighted possible serotonergic dysfunction. Mounting evidence points to a central 5-HT deficit underpinning violence in offenders with problematic alcohol use. 5-HT is a monoamine neurotransmitter that plays a key role in modulating behavioral responses, such as aggression and cooperation (Kiser, Steemers, Branchi, & Homberg, 2012). In the CNS, 5-HT arises from specialized groups of cell bodies known as the raphe nuclei that are located in the brainstem reticular formation (Brown & Bowman, 2002). Postmortem autoradiography has

demonstrated that presynaptic and postsynaptic serotonin receptors in the human brain are concentrated in the diencephalon, striatum, and cingulate cortex, where the density of 5-HT reuptake is highest (Ba¨cksto¨m & Marcusson, 1987; Backstrom, Bergstrom, & Marcusson, 1989). Low levels of 5-HIAA, a metabolite of 5-HT, have also been correlated with a greater likelihood of committing violent offenses when individuals are under the influence of alcohol (Virkkunen, Nuutila, Goodwin, & Linnoila, 1987). Whether comorbid alcohol misuse is present or not, associations between deficient 5-HT metabolism and violent behavior have been consistently reported in the literature (Brown et al., 1982; Linnoila et al., 1983). Behavioral and environmental factors, in addition to the effects of 5-HT, also contribute to vulnerability for alcohol misuse and aggression. Cloninger’s influential dichotomy theory proposed two patterns of alcohol misuse, and differing neurobiological substrates of the two types have also been proposed (Cloninger, Bohman, & Sigvardsson, 1981). In Cloninger’s nomenclature, Type 1 alcoholics are characterized by endorsing stable social behavior, harm avoidance, and preserved impulse control, along with a later onset of alcohol misuse. Type 2 alcoholics, on the other hand, exhibit antisocial personality traits, highly impulsive behavior, and earlier problems with alcohol. Several independent studies have corroborated the validity of this typology (Laakso et al., 2000; Tiihonen et al., 1995). These two phenotypes are also accompanied by differences in 5-HIAA metabolism. For example, whereas Type 1 alcoholics typically have higher levels of 5-HIAA measured from the CSF, Type 2 alcoholics show lower levels of CSF 5-HIAA metabolites (Higley & Linnoila, 1997). Other investigations provide support for this finding by providing similar evidence of reduced 5-HIAA in the CSF of men with early onset alcohol misuse and impulsivity (Linnoila et al., 1983; Virkkunen et al., 1987). In a study investigating the relationship between impulsivity and 5-HT activity, the concentration of CSF 5-HIAA was compared in impulsive arsonists, violent offenders, and a group of 10 healthy controls. Arsonists, who exemplified an extreme form of impulse control disorder, were found to demonstrate significantly lower CSF 5-HIAA metabolites than the other groups. The vast majority of the arsonists also fulfilled DSM-III criteria for alcohol abuse (American Psychiatric Association, 1980). The authors hypothesized that alcohol abuse may have represented an attempt to self-medicate, as alcohol consumption could have acutely improved impulse control by releasing 5-HT, although chronic depletion of 5-HT would ultimately exacerbate impulsivity (Linnoila et al., 1983; Lovinger, 1999; Virkkunen et al., 1987).

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NEUROBIOLOGICAL MECHANISMS

Dopamine Dopaminergic activity has also been implicated in aggression and alcohol misuse. DA is a catecholamine neurotransmitter that acts on both the CNS and sympathetic branch of the peripheral nervous system (Yanowitch & Coccaro, 2011). Rodent studies initially established the importance of dopaminergic signaling in modulating aggressive behavior. For instance, in an analysis examining the behavior of mice attacking intruders, assayed by the resident-intruder paradigm, increased DA turnover was detected in the nucleus accumbens, a region of the brain associated with impulsivity, reward, and motivation (Basar et al., 2010; Haney, Noda, Kream, & Miczek, 1990). Mice with deletion mutations in the DAT gene have also shown increased extracellular concentrations of DA and a greater propensity for aggressive behavior (Giros, Jaber, Jones, Wightman, & Caron, 1996). Both animal and human studies have also reported a strong association between increased dopaminergic transmission and aggressive behavior in the context of excessive alcohol use (Kuikka et al., 1998). For example, a SPECT study conducted in a group of impulsive violent offenders and nonviolent offenders, both with alcohol misuse, measured striatal DAT density using the radionuclide [123I]β-CIT. The heterogeneity of DAT distribution was also examined. Heterogeneity of DAT density was calculated by measuring the relative dispersion of the regional count densities when the striatum was divided into a number of subregions. The authors found that striatal DAT density was significantly lower in nonviolent offenders with alcohol misuse than in healthy controls. Conversely, violent offenders with alcohol misuse displayed higher striatal DAT density and greater heterogeneity in right striatal regions. The authors attributed the increased DAT heterogeneity to a higher density of synapses that increased overall dopaminergic transmission, leaving these individuals more vulnerable to aggression and antisocial behavior (Kuikka et al., 1998). The association between violent behavior and monoamine transporter deficiency has been further investigated in a SPECT study imaging 5-HT and DA reuptake sites in the brain through their specific binding of [123I]β-CIT (Tiihonen et al., 1997). Key to the study’s methodology was investigating three distinct groups: (1) violent offenders with alcohol misuse; (2) nonviolent controls with alcohol misuse; and (3) healthy controls. Thus, the investigators were able to distinguish the effects of violent behavior versus those of alcohol misuse on 5-HT or DA. By quantifying [123I]β-CIT binding to 5-HT and DA transporters,

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Tiihonen et al. (1997) found lower 5-HT transporter density in the midbrain of violent offenders with alcohol misuse compared to nonviolent controls with alcohol misuse and healthy controls. This finding suggests that lower serotonergic functioning may not be specifically related to alcohol misuse but rather to coexisting violent behavior or habitual impulsivity.

Monoamine Oxidase-A Another neural substrate associated with pathological aggression and impulsivity is MAO-A. MAO-A is an enzyme located on outer mitochondrial membranes that metabolizes 5-HT and DA, in addition to other neurotransmitters. It exhibits the highest levels of activity in the striatum and hypothalamus (Youdim, Edmondson, & Tipton, 2006). The neuromodulatory influence of MAO-A on impulsivity was investigated in a PET study measuring MAO-A density in violent offenders with ASPD (Kolla et al., 2015). Fifty percent of the sample in this study also had comorbid alcohol dependence. The OFC and VS were chosen as primary regions of interest, as past studies of ASPD had found abnormalities in these areas related to impulsivity (Dalley, Everitt, & Robbins, 2011; Meyer et al., 2008). The study indicated that lower MAO-A total distribution volume, a measure of MAO-A density, was present in the OFC and VS of ASPD compared with controls, as seen in Fig. 29.1 (Kolla et al., 2015). Behavioral, self-report and clinically rated measures of impulsivity, such as the PCL-R, were also negatively correlated with VS MAO-A levels, as seen in Fig. 29.2 (Kolla et al., 2015). Differences between offenders with alcohol misuse and those without were not examined. These findings suggest that MAO-A may be implicated in the impulsive behavior characteristic of ASPD or ASPD with alcohol dependence. Subsequent fMRI work in this sample revealed that activation of corticostriatal pathways associated with impulsive behavior could also relate to VS MAO-A levels (Kolla et al., 2016). Certain MAO-A genetic polymorphisms have also shown a relationship with violent behavior. The MAO-A gene is located on the X chromosome, and a variable nucleotide tandem repeat polymorphism can alter its transcriptional activity, resulting in either high (MAOA-H) or low (MAOA-L) in vitro activity. One further study exploring the genetic background of extreme aggression in Finnish prisoners revealed an association between aggressive behavior and MAOA-L (Tiihonen et al., 2015). The authors discussed how a low DA metabolism rate could be associated with the

III. PSYCHOLOGY, BEHAVIOR, AND ADDICTION

FIGURE 29.1 Lower MAO-A total distribution volume in ASPD. Results of a multivariate analysis of variance (MANOVA) indicated that ASPD was associated with lower MAO-A total distribution volume in the OFC and VS compared with controls (MANOVA group effect: F2,33 5 6.8, P 5 .003). An effect of diagnosis on MAO-A total distribution volume was also present across all brain regions shown in the figure. Horizontal bars indicate mean MAO-A total distribution volume values. Source: Data are from Kolla, N. J., Matthews, B., Wilson, A. A., Houle, S., Michael Bagby, R., Links, P., . . . Meyer, J. H. (2015). Lower monoamine oxidase-A total distribution volume in impulsive and violent male offenders with antisocial personality disorder and high psychopathic traits: An [11C]-harmine positron emission tomography study. Neuropsychopharmacology, 40(11), 2596 2603, with permission from the Publishers.

FIGURE 29.2 VS MAO-A total distribution volume association with measures of impulsivity in ASPD. VS MAO-A total distribution volume is negatively associated with measures of impulsivity in ASPD. (A) VS MAO-A total distribution volume is negatively correlated with risky performance during the latter half of the Iowa Gambling Task (Pearson’s r 5 2 0.52, P 5 .034). (B) VS MAO-A total distribution volume is negatively correlated with self-reported impulsivity on the NEO Personality Inventory-Revised (Pearson’s r 5 2 0.50, P 5 .034). (C) Lower VS MAO-A total distribution volume was present in ASPD subjects who were rated the most impulsive on the PCL-R (PCL-R score 5 2) when compared to subjects rated less impulsive (PCL-R 5 1). (means (horizontal bars): 17.4 versus 21.5; t16 5 2.8, P 5 .013). Source: Data are from Kolla, N. J., Matthews, B., Wilson, A. A., Houle, S., Michael Bagby, R., Links, P., . . . Meyer, J. H. (2015). Lower monoamine oxidase-A total distribution volume in impulsive and violent male offenders with antisocial personality disorder and high psychopathic traits: An [11C]-harmine positron emission tomography study. Neuropsychopharmacology, 40(11), 2596 2603. doi:10.1038/npp.2015.106, with permission from the Publishers.

NEUROBIOLOGICAL MECHANISMS

low-activity MAO-A genotype, which might result in higher levels of aggression during alcohol intoxication. In a related study where 34% of the sample presented with ASPD, PCL-R scores predicted impulsive re-convictions in MAOA-H but not MAOA-L offenders. Results also revealed that PCL-R factor 2 scores, which assess antisocial behaviors, were a strong predictor of recidivism in both MAOA-H and MAOA-L groups after controlling for alcohol exposure and age. Conversely, the effect of PCL-R total score decreased significantly when MAO-A genotype, alcohol exposure, and age were all considered (Tikkanen et al., 2011). MAOA-H offenders were also at increased risk to commit severe recidivistic violent crimes after exposure to healthy drinking, as demonstrated in another study by the same authors (Tikkanen et al, 2010). The investigation concluded that MAOA-H carriers were more vulnerable to the negative effects of alcohol than individuals with MAOA-L (Tikkanen et al., 2010). An additional study considered the relationship between MAO-A genotype and experience of childhood sexual abuse on development of ASPD in a sample of adult females belonging to an American Indian community (Ducci et al., 2008). Among the 291 females examined, 168 had a lifetime alcohol use disorder. Some 39 individuals had a concurrent alcohol use disorder and ASPD. Control participants had no history of alcohol misuse or ASPD. Results revealed that subjects who were homozygous for the MAOA-L allele and had a history of childhood sexual abuse endorsed higher rates of alcohol misuse, ASPD, and more ASPD symptoms than individuals homozygous for MAOA-H who had been similarly abused. These results suggest that relationships between MAO-A genotype, alcohol misuse, ASPD, and violence are also relevant to females.

Neuroelectrophysiology Neuroelectrophysiological techniques, which include electroencephalogram, event-related potentials, and event-related oscillations, can identify potential effects of alcohol and maladaptive personality traits on commission of violent behavior. Informationprocessing paradigms that require participants to identify target stimuli activate a late evoked potential component known as P3. One electrophysiological study compared the P3 component of event-related potentials in Type 2 alcoholics and individuals who misused alcohol, but did not manifest other prototypical Type 2 characteristics (Branchey, BuydensBranchey, & Lieber, 1988). Antisocial and aggressive behavior were evaluated using the Buss Durkee Hostility Inventory (Buss & Durkee, 1957) and data from a questionnaire asking about disciplinary

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problems at work or in the army, assaults on people, incarceration for aggressive behavior, property damage, incarceration for other crimes, and commission of crimes not resulting in incarceration. Results indicated that P3 amplitudes were lower in patients who had had a prior incarceration or who had been incarcerated for crimes involving violence versus subjects without these histories. A significant negative correlation also emerged between Buss Durkee Hostility Inventory scores and P3 amplitudes. The authors were unable to localize the source driving their results, acknowledging that the observed P3 alterations may have been due to externalizing conditions in persons who misuse alcohol or alcohol use itself.

Structural Brain Changes A strong body of evidence links violence and alcohol misuse with structural brain changes. There has been a particular focus on the hippocampus. The hippocampus is a key structure of the limbic system that plays a central role in memory formation and spatial navigation (Nadel & Hupbach, 2008). Hippocampal fibers converge to form the fornix, which in turn contributes to other pathways involving limbic regions. One such region is the amygdala that plays a key role in emotional processing (Heimer et al., 2008). Postmortem studies have distinguished decreased hippocampal volumes among chronic alcoholics (Laakso et al., 2000). MRI studies have also identified hippocampal alterations in the context of numerous psychiatric and neurologic conditions (Bremner et al., 1995; Frisoni et al., 1999; Laakso et al., 2000; Lawrie & Abukmeil, 1998; Soares & Mann, 1997). An MRI study that specifically examined the hippocampus in Type 1 alcoholics without ASPD and Type 2 alcoholics with ASPD found group differences in hippocampal volume (Laakso et al., 2000). Both alcoholic groups had smaller right hippocampi compared with controls consisting of healthy volunteers representing a wide age range, while left hippocampal volumes showed no differences compared with controls. Among the Type 1 alcoholics, the duration of alcohol misuse was inversely correlated with hippocampal volume, suggesting an association between alcoholism and cumulative volume loss related to alcohol misuse. On the other hand, there was a significant positive correlation between age and right hippocampal volume in Type 2 alcoholics. The authors proposed that the structural changes observed in Type 2 alcoholics were due to correlates of violent behavior as opposed to alcohol misuse. They suggested that inborn, developmental, or other fundamental deficiencies related to primary psychopathology were more

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likely alternatives to explain the relationship between age and hippocampal volume as opposed to alcohol use. Alterations of the amygdala have also shown a relationship with alcohol dependence, antisocial behavior, and violence (Hill et al., 2001; Zhang et al., 2013). In an MRI study of individuals who were dependent on alcohol and perpetrated IPV, a correlation between alcohol dependence and amygdala volume was discerned. Specifically, results showed that persons who misused alcohol and had a history of IPV presented a significant volume reduction in the right amygdala compared with nonviolent alcoholic-dependent patients and healthy controls (Zhang et al., 2013). Since the amygdala has been implicated in the rewarding effects of alcohol (Koob, 1999) and exerts influence over social interactions (Adolphs, Tranel, & Damasio, 1998), the authors concluded that structural deficits in the right amygdala may have been associated with impulsivity and aggression in alcoholics with a history of criminal violence (Zhang et al., 2013). In discussing possible confounds, the authors noted that both the violent alcohol-dependent group and nonviolent alcohol-dependent group had the same lifetime consumption of alcohol, making it less likely that a neurotoxic effect of alcohol influenced amygdala volume. They did concede, however, that amygdala size could contribute to age of onset of drinking, as the group of alcohol-dependent perpetrators had an earlier drinking onset. Another MRI study parsed alterations in brain structure associated with persistent violent behavior from those related to alcohol misuse and other SUDs. Changes in gray matter volume were compared in violent offenders and lifelong substance users (Schiffer et al., 2011). Among participants with a history of violent behavior and substance use, MRI findings revealed increased gray matter volume in regions comprising the mesolimbic reward system, namely the amygdala, left nucleus accumbens, and right caudate head. Conversely, among participants with a substance abuse history who did not exhibit violent behavior, reduced gray matter volumes were noted in the prefrontal cortex, OFC, and premotor area. Differences in gray matter volume between men with and without SUDs were correlated with response inhibition scores based on a questionnaire and results of a response inhibition task measuring impulsivity. Participants with SUDs obtained higher scores on measures of response inhibition during the go/no-go task versus those without SUDs. The authors suggested that their results signaled a correlation between gray matter volume in the mesolimbic reward system and aggression. They also opined that the findings of decreased gray matter volumes in the prefrontal cortex, OFC, and

premotor area were associated with the presence of SUDs. One study limitation is that offenders used multiple substances, in addition to alcohol. Thus, it is not possible to attribute findings to the sole effect of alcohol. A final MRI study examined the relationship between MAO-A genetic variants and amygdala and OFC surface areas in a sample of males with ASPD, where approximately 50% endorsed alcohol dependence, and healthy controls (Kolla, Patel, Meyer, & Chakravarty, 2017). A group 3 genotype interaction emerged, such that the ASPD group with MAOA-L had reduced surface area in the right basolateral nucleus of the amygdala and increased surface area in the right anterior cortical amygdaloid nucleus (Kolla et al., 2017). In conclusion, there is an association between alcohol misuse and levels of serotonin and dopamine modulated by MAO-A. MRI analyses also indicate that structural changes, such as hippocampal alterations and decreased amygdala volumes, show a relation with alcohol misuse and a history of violent behavior. Highly impulsive males with ASPD also show lower MAO-A total distribution volume in the OFC and VS. A limitation common to virtually all studies is that it is impossible to discern whether alcohol misuse produced the neural anomalies or whether they were present prior to the onset of alcohol misuse and subsequently led to increased vulnerability. While results require replication in related samples, this work supports the need to address a wide variety of neurobiological correlates to better understand the association between antisocial personality disorder/psychopathy, alcohol misuse, and violence. Secondary prevention of violence must, therefore, adopt a more nuanced approach that considers the multitude of brain abnormalities predisposing vulnerable individuals who misuse alcohol to engaging in violence.

MINI-DICTIONARY OF TERMS Alcohol misuse From a psychiatric perspective, the Diagnostic and Statistical Manual of Mental Disorders (DSM) Fifth Edition defines problematic use of alcohol as manifestation of an alcohol use disorder that may be mild, moderate, or severe in intensity. The previous edition of the DSM categorized harmful use of alcohol as either alcohol abuse or alcohol dependence. For the purposes of the chapter, we use the term “alcohol misuse” to encompass all forms of harmful alcohol use. Antisocial personality disorder A condition characterized by a longstanding pattern of disregard for and infringement of the rights of others. Psychopathy A personality disorder with characteristic features including impulsivity, manipulativeness, egocentricity, and callousness, along with a history of past and pervasive criminal behavior.

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REFERENCES

Monoamine oxidase-A An enzyme located on brain outer mitochondrial membranes that metabolizes serotonin and dopamine, along with other neurotransmitters. Dopamine A catecholamine neurotransmitter associated with reward and motivation mechanisms. Dopamine acts on both the central nervous system and the sympathetic branch of the peripheral nervous system.

KEY FACTS Monoamine Oxidase-A • Monoamine oxidase-A is an enzyme that degrades neurotransmitters, such as serotonin, dopamine, and norepinephrine. • Evidence from preclinical and clinical studies support an association between monoamine oxidase-A brain levels and aggression. • Monoamine oxidase-A is a treatment target in certain mood disorders and neurodegenerative illnesses. • Monoamine oxidase-A levels have been shown to be lower in individuals with antisocial personality disorder (Kolla et al., 2015). • The morphology of the amygdala shows a relationship to the monoamine oxidase-A gene in antisocial personality disorder (Kolla et al., 2017).

SUMMARY POINTS • Robust evidence supports an association between neurochemical dysfunction and violence in individuals with an alcohol misuse history. • Type 1 alcoholics have higher levels of serotonin and decreased dopamine levels. • Type 2 alcoholics display lower levels of serotonin and increased dopamine levels. • Monoamine oxidase-A, an enzyme that modulates serotonin and dopamine activity, may underlie pathological aggression. • Monoamine oxidase-A genetic polymorphisms make individuals more vulnerable to alcohol’s negative effects, including violence. • Magnetic resonance imaging analyses show decreased hippocampal volumes in Type 1 and Type 2 alcoholics. • Alcohol misuse and violent behavior present with decreased amygdala volumes. • Secondary prevention of violence must adopt a more nuanced approach that considers the multitude of brain abnormalities predisposing alcohol misuse to violence.

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C H A P T E R

30 Language Lateralization in Fetal Alcohol Spectrum Disorders Annukka K. Lindell Department of Psychology and Counselling, School of Psychology and Public Health, La Trobe University, Bundoora, VIC, Australia

LIST OF ABBREVIATIONS DTI EEG FA FAS FASD fMRI MRI

diffusion tensor imaging electroencephalogram fractional anisotropy fetal alcohol syndrome fetal alcohol spectrum disorders functional magnetic resonance imaging magnetic resonance imaging

LANGUAGE LATERALIZATION IN FETAL ALCOHOL SPECTRUM DISORDERS For the majority of the population the left hemisphere is language dominant. Although the right hemisphere also makes important contributions to language processing (see Lindell, 2006), the left hemisphere’s superiority has been established since Broca (1865) noted a coincidence between left hemisphere damage and profound language deficits. In the typical brain a left-lateralized network of fronto-temporo-parietal regions controls language processing (please refer to Fig. 30.1), with these regions both structurally larger and functionally more active during language processing than their right hemisphere counterparts (e.g., Lindell & Hudry, 2013). Alterations to the typical pattern of left lateralization are evident in a number of developmental disorders, including dyslexia (e.g., Illingworth & Bishop, 2009), specific language impairment (Whitehouse & Bishop, 2008), and autism spectrum disorders (Lindell & Hudry, 2013; refer to Table 30.1). Not coincidentally, language deficits are key characteristics of these

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00030-1

disorders. Although language impairments are a prominent feature of Fetal Alcohol Spectrum Disorders (FASD) and are linked to atypical language lateralization (e.g., Bracewell & Marlow, 2002), surprisingly little is known about language lateralization in FASD (Domello¨f, Ro¨nnqvist, Titran, Esseily, & Fagard, 2009). This chapter examines the effects of gestational alcohol consumption on language lateralization in FASD, confirming atypical structural and functional lateralization. Such findings are in line with evidence from other developmental disorders associated with language impairments (e.g., dyslexia, specific language impairment, autism), with the data implying a direct link between atypical lateralization and language impairment in FASD.

Fetal Alcohol Spectrum Disorder Prenatal alcohol exposure is the most common preventable cause of birth defects and neurodevelopmental disorders (American Academy of Pediatrics, 2000). Because alcohol is a teratogen that readily crosses the placenta, alcohol ingested by a pregnant mother directly affects the developing fetus. The consequences vary: prenatal alcohol exposure at different gestational stages affects the morphogenesis of different brain structures and the severity of the effects (e.g., Riley & McGee, 2005). Thus, chronic alcoholism and intermittent high consumption or binge drinking in a pregnant mother can have similar consequences on the developing fetus (e.g., Clarren, Alvord, Sumi, Streissguth, & Smith, 1978), resulting in cognitive and

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FIGURE 30.1 Left hemisphere fronto-temporo-parietal network involved in typical language processing. Source: Brain illustration by Michael Lindell.

TABLE 30.1 Regions of Atypically Reduced Left Hemisphere Structural Asymmetry in Neurodevelopment Disorders Associated with Language Impairments Autism spectrum disorders

Fetal alcohol Dyslexia spectrum disorder

Inferior frontal region (including Broca’s Area)

X

X

Superior posterior temporal region (including Wernicke’s Area)

X

X

Planum temporale

X

X

White matter tracts connecting frontal and temporal lobes (arcuate fasciculus, uncinate fasciculus)

X

X

behavioral problems postnatally. Knowledge of these negative sequelae is far from new: Sullivan (1899) first researched the impact of alcohol consumption (“maternal inebriety,” p. 489) on the developing fetus, finding higher rates of still birth and infant morbidity for alcoholic mothers. Though presumably not investigated experimentally, the Old Testament warned that pregnant women should abstain from alcohol millennia ago: “Beware, and drink no wine or strong drink. . .for lo, you shall conceive and bear a son” (Judges 13:4, 5). Unfortunately, despite the well-publicized risks, a significant minority of pregnant women worldwide (9.8%) consume alcohol during gestation (Popova, Lange, Probst, Gmel, & Rehm, 2017), with much higher gestational alcohol consumption reported in some regions (e.g., in remote Australia it stands at 55%, Fitzpatrick, Latimer, Carter, Oscar, & Ferreira, 2015, and in Ireland, 60.4%, Popova et al., 2017). Jones, Smith, Ulleland, and Streissguth (1973) were the first to formally describe the characteristic abnormalities resulting from prenatal alcohol exposure. In their assessments of eight children born to alcoholic mothers they noted a consistent pattern of

Specific language impairment X

X

X X

X

X

malformations. Based on this congruent symptomatology, Jones and Smith (1973) introduced the term fetal alcohol syndrome (FAS): a permanent birth defect syndrome that results from prenatal alcohol consumption. FAS is diagnosed based on three criteria: (1) prenatal and/or postnatal growth deficiencies; (2) a unique cluster of craniofacial anomalies (refer to Fig. 30.2); and (3) central nervous system dysfunction and/or structural brain abnormalities. Recent meta-analysis of 62 studies indicates a global prevalence of FAS of 1.46 per 1000 people (Popova et al., 2017), though there is much variability between investigations (95% CI 0.94 2.33 per 1000). Some researchers have reported considerably higher prevalence estimates, for example, May, Baete, Russo, Elliot, and Blankenship (2014) found that FAS affects 6 9 individuals per 1000 live births in a middle class US sample. Other studies indicate even higher incidences of FAS in areas with lower socioeconomic status and/ or societal trends for higher alcohol consumption (e.g., Fitzpatrick et al., 2015; up to 12 per 1000; May, Brooke, Gossage, Croxford, & Adnams, 2000; up to 47 per

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FIGURE 30.2 Characteristic facial signs of FAS. Source: From Warren, K. R., Hewitt, B. G., & Thomas, J. D. (2011). Fetal alcohol spectrum disorders: Research challenges and opportunities. Alcohol Research & Health, 34(1), 4 14.

1000), highlighting the need for more effective prevention strategies (Popova et al., 2017). The brain damage resulting from prenatal alcohol exposure is highly variable and influenced by the timing and dosage of alcohol consumption. Alcohol’s teratogenic effects disrupt morphogenesis, producing a wide variety of abnormalities that affect cortical structure from the microscopic to the macroscopic level (Clarren et al., 1978; Norman, Crocker, Mattson, & Riley, 2009). In some cases exposure results in cerebral and/or cerebellar dysgenesis (e.g., Coulter, Leech, Schaefer, Scheithauer, & Brumback, 1993; O’Hare et al., 2005), and in others, complete agenesis of regions such as the cerebellar vermis or the corpus callosum (AuttiRa¨mo¨ et al., 2002; Riley et al., 1995). Research thus confirms that the consequences of prenatal alcohol exposure on brain development are wide-ranging and devastating. The resulting cognitive and behavioral sequelae consequently run the gamut from mild developmental delay to global developmental disability affecting both motor and cognitive domains. Because even low levels of prenatal alcohol exposure can negatively impact the developing fetus while not necessarily meeting the criteria for FAS, the umbrella term Fetal Alcohol Spectrum Disorders (FASD) was introduced. Initially not a medical diagnosis, FASD is increasingly used diagnostically to describe the spectrum of abnormalities resulting from maternal alcohol consumption during pregnancy (Bower & Elliott, 2016; Mukherjee, Hollins, Abou-Saleh, & Turk, 2005); FAS anchors the severe end of the FASD spectrum. An internationally accepted and consistent classification system for FASD has yet to be adopted; however, national guides have been introduced in countries like Australia and Canada to standardize diagnosis (e.g., Bower & Elliott, 2016; Cook, Green, Lilley, Anderson, & Baldwin, 2016; refer to Table 30.2 for typical FASD diagnostic criteria).

Akin to FAS, estimates of the prevalence of FASD vary, with the Centers for Disease Control and Prevention (2016) factsheet indicating that up to one in 20 US school children may have FASD. As such, FASD is the most common preventable cause of developmental disabilities. FASD is linked to a broad range of cognitive deficits, affecting language, attention, executive function, memory, and visuospatial processing (e.g., Mattson & Riley, 1998; Streissguth, Sampson, & Barr, 1989). Indeed, Sowell et al. (2007) suggest that “it is not clear that there are any cognitive domains completely unaffected by prenatal exposure to alcohol” (p. 635). Speech and language problems are an area of specific concern, with FASD causing deficits across the full range of expressive and receptive language abilities, including speech impairments (Church, Eldis, Blakley, & Bawle, 1997), grammar deficits (Carney & Chermak, 1991), impaired language comprehension and naming ability (Mattson & Riley, 1998), and impaired verbal learning (e.g., Sowell et al., 2007). These language impairments have far-reaching negative effects, resulting in more general learning difficulties, behavioral problems, and compromised interpersonal communication in people with FASD (e.g., Shaywitz, Caparulo, & Hodgson, 1981).

Structural Lateralization in Fetal Alcohol Spectrum Disorders Given that atypical lateralization is present in a number of developmental disorders and is associated with language deficits, surprisingly few studies have compared the consequences of prenatal alcohol exposure on the structure of the left and right hemispheres. Sowell and colleagues are the exception, having performed several investigations including hemispheric comparisons in FASD (Sowell et al., 2008; Sowell,

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30. LANGUAGE LATERALIZATION IN FASD

FASD Diagnostic Criteria

Diagnosing FASD FASD diagnosis is complex, and ideally performed by a multidisciplinary team (psychologist, occupational therapist, speech and language therapist, pediatrician, geneticist). Three criteria are typically key: 1. confirmation of alcohol exposure during pregnancy 2. neurodevelopmental impairments 3. sentinel facial features (short palpebral fissures, thin upper lip, smooth philtrum) In Australia, there are two sub-categories of FASD diagnosis: 1. FASD with three sentinel facial features (similar to FAS) 2. FASD with less than 3 sentinel facial features (Bower & Elliott, 2016) In Canada, a third nondiagnostic subcategory is included for individuals with confirmed prenatal alcohol exposure who do not meet the criteria for diagnosis 1 or 2: 1. FASD with sentinel facial features 2. FASD without sentinel facial features 3. At risk for neurodevelopmental disorder and FASD (Cook et al., 2016) 

In the UK and USA there are currently no diagnostic guidelines for FASD.

Thompson, Mattson, et al., 2002; Sowell, Thompson, Peterson, et al., 2002; Sowell, Delis, Stiles, & Jernigan, 2001). For example, Sowell, Thompson, Mattson, et al. (2002) examined the brains of children and adolescents with heavy prenatal alcohol exposure and typically developing controls. In addition to an overall reduction in brain size, there were regionally-specific atypicalities in people with FASD. Results indicated attenuation of the left anterior and orbital frontal cortex, consistent with reduced growth in FASD. Such findings imply that the left hemisphere is highly susceptible to the negative impact of prenatal alcohol exposure. Earlier research by the same group revealed atypical structural asymmetries in other left hemisphere regions. Sowell et al. (2001) examined the brains of children and adolescents prenatally exposed to alcohol and typically developing controls. In comparison with the control group, 3D MRI revealed increased gray matter in the left hemisphere posterior temporoparietal cortices of children with FASD. As children develop, gray matter typically thins as a result of pruning (e.g., Gogtay & Thompson, 2010); though it may appear counterintuitive, reduced gray matter volume relative to brain size is associated with better cognitive performance (e.g., Gogtay & Thompson, 2010; Sowell et al., 2001). Given that the left temporo-parietal region is crucially involved in language processing, housing both Wernicke’s area and the angular gyrus, abnormally increased left temporo-parietal volume appears completely consistent with the language impairments evident in the FASD.

Subsequent research by Sowell, Thompson, Peterson, et al. (2002) similarly indicates atypical asymmetry. Whereas typically developing controls show a left hemisphere volumetric bias in the posterior inferior temporal region, adolescents who were prenatally exposed to alcohol evidence reduced asymmetry/ greater symmetry in this area. Like the left temporoparietal region, the left perisylvian region is part of the network of left hemisphere regions that mediate language processing in typical development (e.g., Catani & Jones, 2005). Attenuated structural asymmetries may thus help account for the functional language deficits commonly observed in FASD. White matter connectivity between left hemisphere language regions is also compromised in FASD, compounding the gray matter abnormalities. Lebel et al. (2008) examined white matter tracts in children with FASD and typically developing controls using diffusion tensor imaging (DTI, used to delineate white matter tracts) and fractional anisotropy (FA, used to establish white matter integrity). Results revealed widespread white matter aberrations in children with FASD, affecting 7/10 white matter tracts examined in comparison with controls. Consistent with the notion that atypical left hemisphere structure underlies the language deficits present in FASD, the most prominent differences between the FASD and control groups were evident in white matter tracts innervating temporal regions; as white matter serves as a conduit for information transfer between different brain regions, changes in white matter structure compromise communication.

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Both Sowell et al. (2001) and Sowell et al. (2002) similarly found highly significant reductions in white matter volumes in the left parietal and temporal lobes of children and adolescents with FASD. White matter tracts connecting the frontal, temporal, and parietal lobes (e.g., arcuate fasciculus, uncinate fasciculus) show a left hemisphere asymmetry in the typically developing population (e.g., Nucifora, Verma, Melhem, Gur, & Gur, 2005). Greater connectivity in the left temporo-parietal region facilitates efficient and effective language processing; reduced white matter connectivity thus appears a probable contributor to the language deficits evident in FASD. Overall, though the number of studies that have compared left versus right hemisphere structure in people with FASD is presently small, they consistently indicate differential hemispheric effects. Sowell et al.’s (2001, 2002, 2008) findings highlight atypical structural asymmetries in gray matter, with Lebel et al.’s (2008) and Sowell et al.’s (2001, 2002) research further confirming white matter abnormalities in left temporoparietal regions. These findings suggest that maternal gestational alcohol consumption has a particularly negative effect on the left hemisphere, adversely altering hemispheric lateralization.

Functional Lateralization in Fetal Alcohol Spectrum Disorders As prenatal alcohol exposure has a greater impact on left than right hemisphere brain structure (e.g., Sowell et al., 2001, 2002), language impairments in FASD would be predicted based on the left hemisphere’s dominance in language processing. Research confirms that the majority of people with FASD present with language deficits. As one would anticipate, language impairments are increasingly severe at the upper end of the spectrum: Riikonen, Salonen, Partanen, and Verho (1999) found that 100% of their FAS sample exhibited both receptive and expressive language difficulties. Moreover, all school-aged children with FAS were diagnosed as dyslexic, and all the children with FAS had expressive impairments, ranging from delayed speech to no speech at all. Analysis of regional cerebral blood flow confirmed that all the children with FAS had mild hypoperfusion in the left hemisphere, whereas typically developing children showed significantly greater blood flow in the left than right hemisphere (up to 5% greater flow). As such, Riikonen et al.’s (1999) results indicate impaired left hemisphere function in children with FAS. Research also indicates that just as the left hemisphere is smaller in people with FASD (Sowell et al., 2002), it also generates lower levels of

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electroencephalogram (EEG) power, particularly in alpha frequencies (Kaneko, Ehlers, Philips, & Roley, 1996). Kaneko et al. found that adolescents with FAS showed significantly lower mean alpha power across the left hemisphere, measured at fronto-central (F3-C3) and parieto-occipital (P3-O1) sites. As EEG alpha rhythms are the dominant scalp frequency in adults, indexing a range of cognitive processes including memory (e.g., Klimesch, 1999), the lower alpha power evident in people with FAS is again consistent with the left hemisphere’s particular vulnerability to prenatal alcohol exposure. Given the left hemisphere abnormalities noted, it is not surprising that verbal performance is markedly poorer than nonverbal performance in children prenatally exposed to alcohol (e.g., Riikonen et al., 1999; Streissguth et al., 1994). Indeed, children with heavy prenatal exposure to alcohol have a mean performance IQ score 8.7 points higher than their mean verbal IQ score (WISC-R; Mattson, Riley, Delis, Stern, & Jones, 1996). Mattson and Riley (1998) demonstrated that children who had been prenatally exposed to alcohol showed significantly poorer comprehension (Peabody Picture Vocabulary Test-Revised) and naming (Boston Naming Test) performance than typically developing controls. Not coincidentally, both these tasks are subserved by the left tempo-parietal region that is atypically structurally lateralized in FASD (Lebel et al., 2008; Sowell et al., 2001, 2002). In keeping with the abnormal structural lateralization, functional imaging research indicates that the brains of children with FASD show atypical patterns of activation during language processing. For example, Sowell et al. (2007) used fMRI to examine activation while people who had heavy prenatal alcohol exposure completed a verbal paired associates learning task. In the alcohol-exposed group the task prompted significantly less activation in the left medial and posterior temporal regions, and significantly more activation in the left and right dorsal prefrontal cortices, than in typically developing controls (refer to Fig. 30.3). Because the researchers controlled for group differences in general memory ability, the atypical activation can be attributed to language processing, with the alcohol-exposed group relying on dorsal prefrontal cortices bilaterally, rather than the left temporal region, to perform the task. Such findings imply that in addition to altering brain structure, prenatal alcohol exposure has a negative impact on the function of the perisylvian temporal region that mediates verbal learning in the typical population. Reliance on difference areas of the brain results in impaired language performance: increased involvement of the dorsolateral prefrontal cortices does not adequately compensate for

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FIGURE 30.3 Sowell et al.’s (2007) results, indicating group differences in activation during verbal learning: green areas indicate greater activation in the alcohol-exposed group; red areas indicate greater activation in the control group. Source: Adapted from Nuˆnez, S. C., Roussotte, F., & Sowell, E. R.(2011). Structural and functional brain abnormalities in Fetal Alcohol Spectrum Disorders. Alcohol Research & Health, 34(1), 121 132.

TABLE 30.3

Summary of Left Hemisphere Atypicalities in FASD

Structure Gray matter

White matter

Left hemisphere atypicality

Population

Increased volume in the left posterior temporo-parietal cortex (Sowell et al., 2001)

FASD

Reduced asymmetry in the posterior inferior temporal region (Sowell, Thompson, Peterson, et al., 2002)

FASD

Reduced volume in the anterior and orbito-frontal cortex (Sowell, Thompson, Mattson, et al., 2002)

FASD

Reduced volumes in the temporal and parietal lobes (Sowell et al., 2001; Sowell, Thompson, Mattson, et al., 2002)

FASD

Function Metabolism Hypoperfusion (Riikonen et al., 1999)

Activation

FAS

Reduced alpha power (Kaneko et al., 1996)

FAS

Reduced activation in the medial and posterior temporal regions, and increased activation in the dorsal prefrontal region, during verbal learning (Sowell et al., 2007)

FASD

the left parieto-temporal dysfunction resulting from prenatal alcohol exposure. In another investigation, Sowell et al. (2008) offered further evidence that people with FASD rely on different brain regions for language processing than typically developing controls. Sowell et al. (2008) demonstrated that verbal recall performance was positively correlated with right hemisphere dorsolateral thickness in people with FASD, in marked contrast with controls for whom thickness in this region was not linked to verbal performance. Such data again suggest that people with FASD may rely on frontal right hemisphere regions for language processing to compensate for dysfunction in the left temporo-parietal regions that typically mediate such processes. While there is a strong body of research examining language processing in FASD, to date few investigations have coupled these behavioral measures with functional imaging. The available research indicates that such investigation is worthwhile, having the potential to highlight links between the abnormal

structural lateralization evident in FASD and resulting language impairments. The brains of people prenatally exposed to alcohol show a number of functional abnormalities, including reduced left hemisphere blood flow (Riikonen et al., 1999) and lower left hemisphere alpha activity (Kaneko et al., 1996). In addition, there is significantly less activation in the left temporo-parietal region during verbal learning in people with FASD (Sowell et al., 2007), likely reflecting the structural abnormalities observed in the same region. Instead, there is greater activation in the left and right dorsal prefrontal cortices, with negative consequences for language performance. Reliance on atypical brain regions during language processing may help account for the abnormally increased cortical thickness in the right dorsolateral cortex evident in FASD (Sowell et al., 2008): prenatal alcohol exposure results in different brain regions subserving language processing in people with FASD, compromising language ability.

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KEY FACTS

CONCLUSIONS Research confirms that the development of cerebral asymmetries is perturbed by prenatal alcohol exposure, causing abnormalities in structural and functional lateralization for language (refer to the summary in Table 30.3). People with FASD show reduced blood flow (Riikonen et al., 1999) and lower alpha power (Kaneko et al., 1996) in the left hemisphere, suggesting that the left side of the brain is particularly vulnerable to maternal gestational alcohol ingestion. Structural research is congruent, indicating atypical asymmetries in both gray (Sowell et al., 2001) and white matter in the left temporo-parietal region in FASD (Sowell et al., 2002). Given that this region subserves language processing in the typically developing population, such structural atypicalities are linked to language impairments (Mattson & Riley, 1998). Indeed, people exposed to alcohol prenatally show atypical dorsolateral frontal activation, rather than activating the typical left temporo-parietal region, during verbal learning (Sowell et al., 2007). Reliance on alternate brain regions results in language deficits in FASD: the dorsolateral prefrontal cortices cannot adequately compensate for the left parieto-temporal dysfunction resulting from prenatal alcohol exposure. Given the consistency in findings reviewed in this chapter, it appears striking that comparatively few FASD studies have specifically examined hemispheric differences. This appears a lost opportunity as the cost of such comparisons is minimal, and the potential benefits are clear: if atypical structural asymmetries are present from birth, early identification offers the opportunity for earlier diagnosis and intervention implementation in FASD. As previously argued (Lindell, 2016), systematic investigation is necessary to determine the distinguishing cortical indices of FASD from those of other neurodevelopmental disorders. Increased temporo-parietal gray matter (Sowell et al., 2001) accompanied by reduced white matter in the same region (Sowell et al., 2002) appears a likely candidate (Lindell, 2016), but whether it is sufficient to distinguish probable FASD from other disorders requires dedicated investigation. Further investigation of lateralization in FASD thus offers clear benefits: if the left temporo-parietal abnormalities identified by existing research are: (1) present at birth; and (2) distinct from the atypicalities present in other neurobehavioral disorders, they may help facilitate earlier diagnosis and intervention implementation. Researchers examining brain structure and/or function in FASD are, therefore, encouraged to include and report hemispheric comparisons.

Increasing the body of research evidence will advance understanding of the neurocognitive phenotype of FASD, offering the potential for earlier identification andthus, improved outcomes for people prenatally exposed to alcohol.

MINI-DICTIONARY OF TERMS Agenesis Failure to develop all, or part, of an organ during embryonic growth, resulting in its absence (e.g., agenesis of the corpus callosum refers to the failure to develop all, or part, of the corpus callosum). Asymmetry Differences in structure and/or function between the left and right sides of the brain. Dysgenesis Abnormal development of an organ during embryonic growth (e.g., cerebral dysgenesis refers to abnormal development of the brain). FASD Abbreviation for Fetal Alcohol Spectrum Disorders, a group of developmental disorders that result from brain damage caused by prenatal alcohol exposure. fMRI Abbreviation for functional Magnetic Resonance Imaging, a neuroimaging technique that indirectly indicates which parts of the brain are active by measuring blood oxygen level-dependent changes (hemodynamic response). Lateralization One side of the brain plays the dominant role in controlling a particular function. For example, in most people the left hemisphere controls speech production whereas face processing is controlled by the right hemisphere. Temporo-parietal region Area of the brain in which the temporal and parietal lobes meet at the end of the sylvian fissure. The left hemisphere temporo-parietal region plays a crucial role in language processing and production.

KEY FACTS Developmental Problems in Fetal Alcohol Spectrum Disorders As a result of the brain damage caused by prenatal alcohol exposure, people with FASD may show a wide range of developmental problems, including: • • • • • • • • • • • • • •

poor memory short attention span poor speech and language hyperactivity impulsivity slow cognitive processing poor organization poor eyesight hearing difficulties sleeping difficulties poor social skills difficulty understanding consequences difficulty following instructions difficulty with abstract concepts

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The National Organisation for Fetal Alcohol Spectrum Disorders Australia has a useful factsheet detailing the characteristics of FASD across the lifespan (www.nofasd.org.au/resources/fact-sheets)

SUMMARY POINTS • Atypical language lateralization is associated with language impairments. • This chapter examines the effects of Fetal Alcohol Spectrum Disorders (FASD) on language lateralization. • FASD results from the deleterious effects of prenatal alcohol exposure on the brain. • Research confirms that the left temporo-parietal region shows atypical structural and functional asymmetries in people with FASD. • As the left temporo-parietal region plays a vital role in language processing, the research suggests a direct link between atypical lateralization in FASD and language impairments.

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resonance imaging of verbal learning in children with heavy prenatal alcohol exposure. NeuroReport, 18, 635 639. Sowell, E. R., Mattson, S. N., Kan, E., Thompson, P. M., Riley, E. P., & Toga, A. W. (2008). Abnormal cortical thickness and brainbehavior correlation patterns in individuals with heavy prenatal alcohol exposure. Cerebral Cortex, 18, 136 144. Sowell, E. R., Thompson, P. M., Mattson, S. N., Tessner, K. D., Jernigan, T. L., Riley, E. P., & Toga, A. W. (2001). Voxel-based morphometric analyses of the brain in children and adolescents prenatally exposed to alcohol. NeuroReport, 12, 515 523. Sowell, E. R., Thompson, P. M., Mattson, S. N., Tessner, K. D., Jernigan, T. L., Riley, E. P., & Toga, A. W. (2002). Regional brain shape abnormalities persist into adolescence after heavy prenatal alcohol exposure. Cerebral Cortex, 12, 856 865. Sowell, E. R., Thompson, P. M., Peterson, B. S., Mattson, S. N., Welcome, S. E., Henkenius, A. L., . . . Toga, A. W. (2002). Mapping cortical gray matter asymmetry patterns in adolescents with heavy prenatal alcohol exposure. NeuroImage, 17, 1807 1819. Streissguth, A. P., Barr, H. M., Olson, H. P., Sampson, P. D., Bookstein, F. L., & Burgess, D. M. (1994). Drinking during pregnancy decreases word attack and arithmetic scores on standardized tests: Adolescent data from a population-based prospective study. Alcoholism: Clinical and Experimental Research, 18, 248 254. Streissguth, A. P., Sampson, P. D., & Barr, H. M. (1989). Neurobehavioral dose-response effects of prenatal alcohol exposure in humans from infancy to adulthood. Annals of the New York Academy of Sciences, 562(1), 145 148. Sullivan, W. C. (1899). A note on the influence of maternal inebriety on the offspring. British Journal of Psychiatry, 45(190), 489 503. Warren, K. R., Hewitt, B. G., & Thomas, J. D. (2011). Fetal alcohol spectrum disorders: Research challenges and opportunities. Alcohol Research & Health, 34(1), 4 14. Whitehouse, A., & Bishop, D. (2008). Cerebral dominance for language function in adults with specific language impairment or autism. Brain, 131, 3193 3200.

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C H A P T E R

31 Deprivation in Rewards and Alcohol Misuse Ashley A. Dennhardt1, Samuel F. Acuff1, Ali M. Yurasek2 and James G. Murphy1

1

Department of Psychology, The University of Memphis, Memphis, TN, United States 2Department of Health Education & Behavior, The University of Florida, Gainesville, FL, United States

LIST OF ABBREVIATIONS SFAS RE RPI LET’S ACT

substance-free activity session reinforcing efficacy reward probability index life enhancement treatment for substance use

DEPRIVATION IN REWARDS AND ALCOHOL MISUSE In the late 1970s, psychologist Bruce Alexander conducted the Rat Park experiments that provided a powerful experimental test of the role of environmental reward deprivation as a risk factor for drug selfadministration. The Rat Park studies showed that when compared to rats that were put in an enriched environment in which they had access to food, sex, and leisure activities such as running wheels, rats who were solitarily caged without access to these rewards consumed more morphine, suggesting that environmental reward deprivation is related to drug use (Alexander, Beyerstein, Hadaway, & Coambs, 1981). Vuchinich and Tucker (1988, 1983) extended the finding by demonstrating an inverse relation between choice for alcohol versus monetary alternative rewards among humans. These findings have been widely replicated and led to theoretical models of addiction such as the reinforcement pathology model (Bickel, Jarmolowicz, Mueller, & Gatchalian, 2011; Bickel, Johnson, Koffarnus, MacKillop, & Murphy, 2014) in which alcohol addiction is thought to result from interactions between physiologically mediated subjective response to alcohol, and environmental factors such as low availability of alternative rewards (i.e., reward

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00031-3

deprivation). The process is self-perpetuating because repeated use of alcohol and other addictive substances will often have negative effects on the availability of alternatives, which will, in turn, increase the relative degree of preference for the drug. This behavior is represented mathematically with the matching law (Herrnstein, 1974), which demonstrates that the relative reinforcing efficacy of a particular behavior is a ratio between the response rate of the behavior and the response rates of other possible reinforcing behaviors. Thus, repeated substance use will be more likely in environments that are deprived of viable drug-free alternative reinforcers.

Measurement of Reward Deprivation/SubstanceFree Reinforcement Behavioral economic theory posits that substance use is related to the under-engagement in substance-free activities that are associated with delayed reinforcement (Bickel, Marsch, & Carroll, 2000) and substance use will generally decrease if access to alternative reinforcers is increased (Higgins, Heil, & Lussier, 2004). The term reinforcing efficacy (RE), which is also known as reward value or relative reinforcing efficacy is used to describe the level of preference for a reinforcer, such as alcohol or marijuana (Hursh & Silberberg, 2008) and refers to the behavior strengthening or maintaining properties of a substance (Griffiths, Brady, & Bradford, 1979). The RE of a drug is dynamic and contextually determined by the direct reinforcing effects of the drug, individual difference factors related to decisionmaking, and the availability of alternative reinforcers (Bickel et al., 2000).

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© 2019 Elsevier Inc. All rights reserved.

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Measuring this preference for substance use is based on the relative levels of resource allocation towards substances versus alternatives and can be accomplished across different settings using a variety of assessment tools. In laboratory settings, RE is quantified by the amount of effort or resources allocated towards obtaining a reinforcer (Vuchinich & Tucker, 1983), with substances that elicit higher rates of responding or preference having greater RE than those with lower response rates (Bickel et al., 2000; Murphy & MacKillop, 2006). Different aspects of RE can also be measured by self-reported assessments (Table 31.1).

Demand Demand for a substance and sensitivity to reinforcement from that substance can be assessed via Hypothetical Purchase Tasks ( Murphy & MacKillop, 2006). Purchase tasks are simulation measures that calculate substance demand by quantifying the relationship between drug consumption and cost (see Table 31.2). Demand curve indices of RE can be created by assessing how much of a particular substance (e.g., alcohol, cigarettes, marijuana) an individual will purchase across a range of prices. The indices generated from demand curves include intensity (reported consumption at the lowest price), breakpoint (first price at which consumption is zero), Omax (maximum TABLE 31.1

expenditure on the substance), Pmax (price at maximum expenditure), and elasticity (sensitivity to increase in price).

Substance-Free Reinforcement There are several self-report approaches to assessing substance-free reinforcement. The most common approach uses reinforcement surveys to assess the frequency of participation in different activities and the amount of enjoyment or pleasure obtained from those activities within a certain timeframe (e.g., the past 30 days) (see Table 31.3). The frequency and enjoyment ratings of each activity are then multiplied to calculate the level of reinforcement obtained. Participants completing these schedules are often asked to endorse frequency and enjoyment for each activity twice: once for activities while sober, and once for activities engaged in while under the influence of substances. An index score, capturing the reinforcement from substance-related activities relative to alternative substance-free activities, can then be determined by dividing the total substance-related reinforcement score by the sum of the total (e.g., reinforcement ratio). The Pleasant Events Schedule (PES; Correia, Simons, Carey, & Borsari, 1998), initially used in research for depression (Lewinsohn & Graf, 1973), was the first measure modified to capture substance-free versus

Example of Alcohol Purchase Task

Imagine that you and your friends are at a bar from 9 p.m. to 2 a.m. to see a band. The following questions ask how many drinks you would purchase at various prices. The available drinks are standard size beer (12 oz), wine (5 oz), shots of hard liquor (1.5 oz), or mixed drinks with one shot of liquor. Assume that you did not drink alcohol before you went to the bar and will not go out after. How many drinks would you consume if they were free? How many drinks would you consume if they were $0.25 each? How many drinks would you consume if they were $0.50 each? How many drinks would you consume if they were $1.50 each? How many drinks would you consume if they were $2.00 each? How many drinks would you consume if they were $2.50 each? How many drinks would you consume if they were $3.00 each? How many drinks would you consume if they were $4.00 each? How many drinks would you consume if they were $5.00 each? How many drinks would you consume if they were $6.00 each? How many drinks would you consume if they were $7.00 each? How many drinks would you consume if they were $8.00 each? How many drinks would you consume if they were $9.00 each? How many drinks would you consume if they were $10.00 each? The table shows an example purchase task. Unpublished.

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TABLE 31.2

Example of Reinforcement Schedule

Activities

Frequency with alcohol Frequency without or drugs alcohol or drugs

Enjoyment with alcohol Enjoyment without or drugs alcohol or drugs

Frequency

Enjoyment

0 5 0 times

0 5 unpleasant or neutral

1 5 once a week or less

1 5 mildly pleasant

2 5 2 4 times per week

2 5 moderately pleasant

3 5 about once a day

3 5 very pleasant

4 5 more than once a day

4 5 extremely pleasant

1. Go places with siblings or family members 2. Talk with friends 3. Read a book 4. Go on a date

Frequency 3 Enjoyment 5 Obtained Reinforcement The table shows an example measure of reinforcement derived from alcohol or drugs and substance-free sources. Unpublished.

TABLE 31.3

Key Measures Assessing Reward Deprivation and Related Constructs Sample item

Item quantity

Substance-free and substance-related?

Key citation

Adolescent Reinforcement Survey Schedule

How often did you go out to eat with friends? How enjoyable was it?

32 54

Yes

Murphy et al. (2005)

Alcohol Purchase Task

How many drinks would you consume if they were $1.00?

14

No

Murphy & MacKillop (2006)

Modified Pleasant Events Schedule

How often have you watched TV? How pleasant was it?

42 320

Yes

Correia et al. (1998)

Reward Probability Index

A lot of activities in my life are pleasurable

20

No

Carvalho et al. (2011)

The table lists the key measures used to assess reward deprivation and related constructs. Unpublished data.

substance-related reinforcement. The PES contains 330 items, many of which were time-specific and have since become outdated. More recently, these reinforcement schedules have been modified to more accurately capture the experiences of individuals. The Adolescent Reinforcement Survey—Substance Use Version (ARSSSUV; Murphy, Correia, Colby, & Vuchinich, 2005) is an adapted version of the PES with greater degradation of response options within rating scales, less items (32 45), and a focus on items relevant to adolescent and young adult experience. Other reinforcement schedules have been developed, such as the Pleasant Activities List (PAL; Roozen et al., 2008), although their use has been limited. The Reward Probability Index (RPI; Carvalho et al., 2011) is a 20-item measure assessing reward deprivation by examining the availability of rewards in the

environment and the likelihood of obtaining reinforcement from available rewards. The RPI was also a tool originally intended for use with depressed populations. Specifically, the RPI was an attempt to measure response-contingent positive reinforcement using self-report rating scale questions. Unlike reinforcement survey approaches, it does not ask about specific activities or explicitly distinguish between substance-related and substance-free activities, but instead includes items that assess general reward functioning. Items include “I have had many unpleasant experiences,” and “There are many activities that I find satisfying.” The RPI produces a total score and two subscales that reflect an ability to experience reward (Reward Probability) and the availability of rewarding stimuli in one’s environment (Environmental Suppressors).

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ALTERNATIVE REINFORCEMENT AMONG TEENAGERS AND ADOLESCENTS Research supports the theoretical claims connecting reward deprivation and alcohol misuse at various points across the lifespan. Several studies have employed variations of the pleasant event schedule (Lewinsohn & Graf, 1973) to study this relation by asking individuals to report the frequency of engagement in and enjoyment associated with activities and whether the activity is associated with alcohol or drug use. In a cross-sectional study, Leventhal et al. (2015) tested whether greater engagement with activities associated with substance use would mediate the relation between socioeconomic status (SES) and substance use with a sample of over 2800 9th grade students. Socioeconomic status was inversely associated with lifetime alcohol consumption, and alternative reinforcement mediated this relation, such that lower SES was associated with lower alternative reinforcement, which was in turn associated with both greater total lifetime alcohol consumption. A longitudinal follow-up study found that 6-month alternative reinforcement mediated the relation between baseline SES and 12-month alcohol consumption (past 6 months; Andrabi, Khoddam, & Leventhal, 2017). For the follow-up study, all three elements of reinforcement (frequency, enjoyment, and frequency 3 enjoyment) were examined and found to be separate mediators, although the crossproduct accounted for the most variance, suggesting that frequently engaging in enjoyable drug-free activities is an important protective factor against alcohol misuse among teens. In the same sample, alternative reinforcement was examined as a mediator of the relation between another predictor of substance misuse, conduct problems (e.g., getting into fights, skipping school, etc.), and both past 6-month alcohol use (yes or no) and frequency among high school students (Khoddam & Leventhal, 2016). In addition to alternative reinforcers, participants could designate activities as complementary reinforcers, or activities that the individual associates with alcohol use, which were also examined as mediators. Interestingly, greater levels of complementary reinforcers did not mediate the relation between conduct problems and both past 6-month alcohol use (yes or no) and alcohol use frequency (alcohol use status not tested), but diminished levels of alternative reinforcers did, suggesting that diminished alternative activity, rather than simply increased substance-related activity, plays a vital role in alcohol engagement.

ALTERNATIVE REINFORCEMENT AMONG COLLEGE STUDENTS AND EMERGING ADULTS Reward deprivation is also a robust predictor of alcohol misuse among college students. Several crosssectional studies have demonstrated that greater levels of substance-related reinforcement relative to substancefree reinforcement are associated with lower alcohol use and related problems (Correia et al., 1998; MacKillop & Murphy, 2007). Consistent with these studies, Joyner et al. (2016) demonstrated that reward deprivation (measured with the RPI) was cross-sectionally associated with alcohol use disorder among college students, further evidence that reward deprivation may be an important early risk factor for developing problematic alcohol misuse. Due to a greater number of studies on the topic, the link between reward deprivation and alcohol misuse is understood with greater precision among heavy-drinking college students.

RELATION BETWEEN GENDER AND ALTERNATIVE REINFORCEMENT Several studies have examined the moderating role of gender and have found that women typically report greater substance-free reinforcement than men. In one study, women reported greater peer, family, and total substance-free reinforcement than men regardless of alcohol use level (Skidmore & Murphy, 2010). This may be because men generally report engaging in fewer substance-free activities that include peers, limiting their social interactions to drinking occasions (Murphy & MacKillop, 2006). Another study found that women reported higher overall enjoyment from substance-free activities compared to men, and that gender moderated the relation between substance-free enjoyment and past 3-month alcohol use. In other words, women who reported greater enjoyment while engaging in substance-free activities reported lower levels of past 3-month alcohol use, while there was not a significant relation between substance-free enjoyment and alcohol use among men (Murphy, Barnett, Goldstein, & Colby, 2007).

RELATION BETWEEN SOCIAL CONTEXT AND ALTERNATIVE REINFORCEMENT Heavy drinking in college most often occurs in a social context and several studies have reported that heavy-drinking college students typically report

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RELATION BETWEEN SOCIAL CONTEXT AND ALTERNATIVE REINFORCEMENT

greater social reinforcement, both substance-free and substance-related, compared to light drinkers. One study comparing reinforcement for substance-free and substance-related activities among binge (4/5 drinks in one occasion for females/males) versus light-drinking college students found that binge drinkers reported greater frequency, and enjoyment of substance-related activities, and light drinkers reported greater frequency and enjoyment for introverted, nonsocial, and passive outdoor substance-free activities (Correia, Carey, Simons, & Borsari, 2003). Light drinkers also reported greater enjoyment of several other substancefree activities, including social, solitary, and moodrelated substance-free activities. Interestingly, light drinkers primarily obtained greater reinforcement in nonsocial domains, except for obtaining greater enjoyment from substance-free social activities. Partially consistent with this finding, another study found that heavy drinking college students reported greater substance-free social and sex reinforcement (frequency and enjoyment cross-product) than light drinkers (Skidmore & Murphy, 2010). Murphy, Barnett, and Colby (2006) examined reports of enjoyment over the past 30 evenings as a function of drinking frequency, quantity, and the nature of activity participation in a sample of college student drinkers who violated a campus alcohol policy. Although overall participants rated their drinking evenings as more enjoyable than their abstinent evenings, several substance-free activities (e.g., watching movies, eating at restaurants, and hanging out with friends) were reported to be as enjoyable as substance-related activities, and the number of peers present for an activity was a more powerful predictor of enjoyment than was drinking level. Further, consistent with the gender differences described above, women reported greater overall

substance-free activity enjoyment than men. Despite substance-free peer activities being more enjoyable than solitary activities, males reported less engagement in substance-free peer activities, suggesting that college men may be especially reliant on alcohol to facilitate social interactions. Although no study has examined the natural relation between diminished alternative reinforcement and alcohol use prospectively, one study has used alternative reinforcement as a predictor of alcohol use outcomes following a brief intervention. The results of this study generally correspond to the gender and social findings addressed above. The authors randomized participants to personalized drinking feedback conditions delivered with or without motivational interviewing style counseling. Drinking outcomes did not differ by intervention condition. In this study, proportionate substance-related reinforcement predicted drinking outcomes at 6 months (Murphy et al., 2005). Further, those with moderate to large reductions in drinking (. 1 SD) at 6-month follow-up also reported significantly lower substance-free peer reinforcement, greater substance-free school reinforcement, and overall lower proportionate substance-related reinforcement (see Table 31.4). An important aspect of future interventions for this population should, thus, attempt to bolster substance-free peer reinforcement, as the deficits in social interaction that follows reductions in drinking may prevent long-term change from occurring. It is important to note that, although no study has examined the naturalistic relation between alternative reinforcement and alcohol misuse, one study has demonstrated a relation with cigarette smoking onset and duration among teens (Audrain-McGovern et al., 2012), and naturalistic studies with heavy-drinking populations may demonstrate similar results.

TABLE 31.4 Changes in Substance-Free Reinforcement and Reinforcement Ratio Scores Among Participants With Moderate to Large Drinking Reductions Baseline ARSS-SUV reinforcement scale

M

SD

Follow-up M

SD 

Peer interaction

8.42

2.87

7.24

2.91

Dating

9.08

3.13

8.38

3.29

Sexual activity

5.33

3.31

4.54

3.26



School

4.17

3.03

6.00

3.37

Substance-free (total)

6.43

1.65

5.83

1.88

Reinforcement ratio

0.33

0.11



0.28



0.12

p , .05 p , .01 The table shows means and standard deviations in reinforcement scores among participants who reduced their drinking (n 5 26). From Murphy, J. G., Correia, C. J., Colby, S. M., & Vuchinich, R. E. (2005). Using behavioral theories of choice to predict drinking outcomes following a brief intervention. Experimental and Clinical Psychopharmacology, 13(2), 93 101. https://doi.org/10.1037/1064-1297.13.2.93. Reprinted with permission from the American Psychological Association.



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ALTERNATIVE REINFORCEMENT AMONG ADULTS Relatively few studies have examined reward deprivation among heavy-drinking adults. However, the few studies available are consistent with the research with high school and college students and suggest that reward deprivation is implicated in alcohol misuse among this population as well. One study collected cross-sectional data on a sample of drinking adults (M 5 32.85, SD 5 11.15) using crowdsourcing through Amazon’s Mechanical Turk website (Morris et al., 2017). Controlling for gender, age, race, and income, proportionate alcohol-related reinforcement significantly predicted alcohol use disorder severity and accounted for 18% of the variance. In this study, proportionate alcohol-related reinforcement was also significantly correlated with alcohol demand indices. Another study (N 5 609; Magidson, Robustelli, SeitzBrown, & Whisman, 2016) separately examined the frequency and enjoyment of alternative activities among adults (M 5 54.10, SD 5 11.80) and found that activity enjoyment, but not frequency, was correlated with alcohol-related problems and heavy drinking after statistically adjusting for depression scores. Adults in this study reported low levels of drinking (M 5 0.26, SD 5 0.71); despite this, the results are consistent with previous research and suggest that enjoyment of an alternative activity may have a greater impact on alcohol use than frequency of alternative activities.

ALTERNATIVE REINFORCEMENT AS A TRANSDIAGNOSTIC RISK FACTOR FOR COMORBID PSYCHOPATHOLOGY Despite recent calls to consider reward deprivation as a transdiagnostic risk factor for psychopathology

(Vujanovic, Wardle, Smith, & Berenz, 2016), only two studies have examined the relation between reward deprivation and alcohol misuse among psychiatric patients (Correia & Carey, 1999). The study (N 5 34) found that proportionate substance-related reinforcement predicts substance use better than reinforcement from substance-related activities alone after adjusting for gender, age, and psychiatric diagnosis. Although the sample size was relatively small, these initial findings are encouraging and suggest that more research should specifically examine reward deprivation as a transdiagnostic risk factor for comorbidity.

Treatment Targeting Reward Deprivation The Substance-Free Activity Session (SFAS) (Murphy et al., 2012). The SFAS developed by Murphy and colleague utilizes behavioral economic elements in the context of motivational interviewing-based brief intervention. Specifically, the SFAS attempts to increase the individual’s commitment to important goals, engagement in substance-free activities, and general degree of future orientation; thus, directly targeting reward deprivation (see Fig. 31.1 for sample intervention content). Individuals who participate in a SFAS session can work towards these goals without an expressed desire to reduce substance use, but tend to reduce substance use as a function of achieving these goals. Theoretically, this is because increases in future orientation and engagement in substance-free activities will indirectly increase the likelihood of reductions in alcohol and drug use (e.g., Correia, Benson, & Carey, 2005) Research to date suggests that the SFAS may increase the efficacy a standard brief motivational alcohol intervention, which is a recognized efficacious intervention, particularly with college students (Murphy et al., 2012) (Fig. 31.2). The SFAS is an ideal intervention for college students because they are a high-risk group in terms of

35

FIGURE 31.1 Intervention element from

30

Substance-Free Activity Session. The figure shows an example of one element that is provided as personalized feedback in the Substance-Free Activity session (SFAS)

25

Family Studying

20 15

Exercising Drinking/Drug use Volunteer

10

Working

5 0

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MINI-DICTIONARY OF TERMS

FIGURE 31.2 Reduction in alcohol problems by students who participated in Substance-Free Activity Session (SFAS). Source: This figure shows drinking reductions in college students (N 5 82) by intervention condition from Murphy et al. (2012). Reprinted with permission from the American Psychological Association.

18 16

Alcohol problems

14 12 10 Relaxation

8

SFAS

6 4 2 0 preintervention

1-Month post intervention

6-Months post intervention

alcohol and drug use, and such use is generally incompatible with successful completion of college and career-development goals. However, the SFAS may also be a useful intervention for noncollege young adults and certain at-risk groups, such as military veterans who may be prone to experiencing reward deprivation after relinquishing substance-free rewards and relationships while deployed. Future research should investigate the SFAS as an adjunct to substance-use interventions with these other populations. Empirically supported interventions, such as community reinforcement therapy or contingency management (Higgins et al., 2004), are examples of intensive intervention approaches that target some of the same theoretical mechanisms as the SFAS (e.g., increasing substance-free reinforcement and reducing impulsive decision-making). Individuals with severe substance abuse and or cognitive impairment may require these intensive approaches, but the SFAS may be a more viable approach with individuals with mild to moderate substance-use problems. In addition to college students, we suspect that there are other potential populations of substance abusers who might benefit from the SFAS. In particular, young adults who are not college students might also benefit from an approach that helps them to address drinking/drug use in the context of developing a greater consideration of the future and identifying patterns of goaldirected substance-free activities. Similarly, military veterans are a high-risk group that might also lack viable alternatives to drinking and require an approach that attempts to specifically address this issue (McDevitt-Murphy et al., 2014). The SFAS may also be especially helpful for individuals with psychiatric comorbidity, which is often associated with diminished engagement in rewarding alternatives to substance use (Murphy et al., 2012).

Life enhancement treatment for substance use (LETS ACT) (Daughters, Magidson, Lejuez, & Chen, 2016). LETS ACT is a behavioral activation-based treatment program that was developed to be conducted in an inpatient setting in small groups with three to five group members. The authors describe their treatment as focusing on the treatment rationale and generating, scheduling, engaging in, and recording substance-free activities to increase positive reinforcement. The increase in substance-free activities also helps to reduce reward deprivation. Each session focuses on identifying areas of value for the participants and activities that are compatible with these life values. The aim is that participants will be able to reduce the tendency to respond to a negative mood with harmful behaviors (e.g., substance use) and instead increase behaviors that facilitate positive reinforcement. Research has shown that LET’S ACT is more successful in obtaining abstinence outcomes and results in experiencing fewer alcohol-related problems compared to a time and group size-matched control condition delivered in a residential treatment (Daughters et al., 2016). The SFAS and LET’S ACT are two recently developed treatments that appear to have promise in reducing alcohol use and the related consequences and appear to do so, at least in part, by targeting reward deprivation. This suggests that reward deprivation may be a key construct to consider when treating alcohol abuse and should be considered in the development and study of future treatments.

MINI-DICTIONARY OF TERMS Reward Deprivation A concept in addictions literature that refers to the lack of access to, and ability to experience reward.

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Behavioral Economics A theory that combines behavioral psychology and microeconomics to describe, understand and predict behavior, and is widely utilized in understanding substance use. Matching Law A quantitative relationship that holds between the relative rates of response and the relative rates of reinforcement in choice situations. An implication is that the rate of response for a given behavior (e.g., drug use) is a product of both the reinforcement associated with that behavior as well as the reinforcement associated with available alternative behaviors (e.g., prosocial activities). Reinforcing efficacy The behavior strengthening or maintaining properties of a substance that can be quantified by the level of preference or degree of resource allocation for a reinforcer, such as alcohol or marijuana (Hursh & Silberberg, 2008). Hypothetical Purchase Tasks Purchase tasks are simulation measures that calculate reinforcing efficacy by plotting hypothetical levels of consumption (demand) across a range of prices. Substance-Free Activity Session (SFAS) A brief one-session intervention that was designed as a supplement to a standard brief motivation intervention for substance use that utilizes behavioral economic elements to attempt to increase an individual’s commitment to important goals, engagement in substance-free activities, and general degree of future orientation. LET’S ACT A 5 8 session behavioral activation-based treatment for substance abuse that is conducted in small groups and aims to increase substance-free rewards.

• Reward deprivation fits with the behavioral economic view of substance use that considers context/environment of the use in addition to individual factors • Deprivation of alternative reinforcers is a robust predictor of alcohol misuse among high school and college students. • Research with general adult populations also suggests that various proxies for reward deprivation (poverty, unemployment, social isolation) predict increased risk for substance misuse. There has been little research on the role of reward deprivation and substance use in noncollege adults. • Reward deprivation can be measured using various methods including calculating substance-free activity participation and the ability to experience substance-free rewards. • Several recently developed treatments, the Substance-Free Activity Session (SFAS) and LET’S ACT, target reward deprivation in order to reduce substance use.

References

KEY FACTS Reward Deprivation • The Rat Park experiments of the 1970s provided a powerful experimental test of the role of environmental reward deprivation as a risk factor for drug self-administration. • In the reinforcement pathology model, alcohol or drug addiction are thought to result from interactions between physiologically mediated subjective response to drugs and environmental factors, such as low availability of alternative rewards (i.e., reward deprivation). • The matching law demonstrates that the relative reinforcing efficacy of a particular behavior is a ratio between the response rate of the behavior and the response rates of other possible reinforcing behaviors. • Reward deprivation can be measured in several ways including calculating substance-free activity participation and the ability to experience substance-free rewards. • Several promising treatments for alcohol misuse target reward deprivation by aiming to increase enjoyable and goal-directed substance-free activities.

SUMMARY POINTS • This chapter focuses on the role of reward deprivation, the inability to experience or access reward, in substance abuse.

Alexander, B. K., Beyerstein, B. L., Hadaway, P. F., & Coambs, R. B. (1981). Effect of early and later colony housing on oral ingestion of morphine in rats. Pharmacology, Biochemistry, and Behavior, 15 (4), 571 576. Available from https://doi.org/10.1016/0091-3057 (81)90211-2. Andrabi, N., Khoddam, R., & Leventhal, A. M. (2017). Socioeconomic disparities in adolescent substance use: Role of enjoyable alternative substance-free activities. Social Science & Medicine, 176, 175 182. Available from https://doi.org/ 10.1016/j.socscimed.2016.12.032. Audrain-McGovern, J., Rodriguez, D., Leventhal, A. M., Cuevas, J., Rodgers, K., & Sass, J. (2012). Where is the pleasure in that? Low hedonic capacity predicts smoking onset and escalation. Nicotine and Tobacco Research, 14(10), 1187 1196. Available from https:// doi.org/10.1093/ntr/nts017. Bickel, W. K., Jarmolowicz, D. P., Mueller, E. T., & Gatchalian, K. M. (2011). The behavioral economics and neuroeconomics of reinforcer pathologies: Implications for etiology and treatment of addiction. Current Psychiatric Reports, 13, 406 415. Available from https://doi.org/10.1007/s11920-011-0215-1. Bickel, W. K., Johnson, M. W., Koffarnus, M. N., MacKillop, J., & Murphy, J. G. (2014). The behavioral economics of substance use disorders: Reinforcement pathologies and their repair. Annual Review of Clinical Psychology, 10, 641 677. Available from https:// doi.org/10.1146/annurev-clinpsy-032813-153724. Bickel, W. K., Marsch, L. A., & Carroll, M. E. (2000). Deconstructing relative reinforcing efficacy and situating the measures of pharmacological reinforcement with behavioral economics: A theoretical proposal. Psychopharmacology. Available from https://doi.org/ 10.1007/s002130000589. Carvalho, J. P., Gawrysiak, M. J., Hellmuth, J. C., McNulty, J. K., Magidson, J. F., Lejuez, C. W., & Hopko, D. R. (2011). The reward probability index: Design and validation of a scale measuring access to environmental reward. Behavior Therapy, 42(2), 249 262. Available from https://doi.org/10.1016/j.beth.2010.05.004. Correia, C., & Carey, K. (1999). Applying behavioral theories of choice to substance use in a sample of psychiatric outpatients.

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C H A P T E R

32 Alcohol (Mis)Use in Individuals With Mild to Borderline Intellectual Disability 1

Neomi van Duijvenbode1,2,3, Joanne E.L. VanDerNagel1,3,4 and Robert Didden2,5

Tactus, Deventer, The Netherlands 2Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands 3Nijmegen Institute for Scientist-Practitioners in Addiction, Radboud University Nijmegen, Nijmegen, The Netherlands 4Aveleijn, Borne, The Netherlands 5Trajectum, Zwolle, The Netherlands

LIST OF ABBREVIATIONS AUD BIF ID MBID MID

alcohol use disorder borderline intellectual functioning intellectual disability mild to borderline intellectual disability mild intellectual disability

INTRODUCTION An intellectual disability (ID) is characterized by deficits in intellectual and adaptive functioning that origin in childhood (American Psychiatric Association, 2013). Intellectual functioning includes a wide range of mental abilities, such as reasoning, planning, problemsolving, judgment, and abstract thinking. These abilities are measured by standardized intelligence quotient (IQ) tests, on which a score of approximately two standard deviations below the population’s mean represents an ID. This typically equals an IQ of 70 or below (Fig. 32.1). In the definition of ID, a great emphasis is placed on adaptive functioning, which refers to skills that are needed to function in day-today life, and includes conceptual skills (language, reading, writing, math), social skills (interpersonal communication skills, ability to make and retain friendships, social judgement), and practical skills (money management, planning and organizational skills, self-care).

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00032-5

The majority of individuals with ID are classified as having a mild intellectual disability (MID). They have deficiencies in conceptual, social, and practical skills and can, therefore, experience difficulties living independently and succeed at school, work, and leisure if they do not receive support. These difficulties are often also present in the group of persons with borderline intellectual functioning (BIF, IQ 70 85), a group comprising about 14% of the population. Though BIF is not formally classified as a disability, individuals with BIF may just as well have needs in many aspects of their lives that are similar to those with MID. In this chapter, we group individuals with MID and BIF together and refer to them as individuals with mild to borderline intellectual disability (MBID). MBID is often accompanied by co-occurring mental disorders, including alcohol misuse and alcohol use disorder (AUD). For many years, the risk of a co-occurring AUD—or other mental health problems for that matter—was profusely underestimated. Individuals with MBID were thought to live sheltered lives, protected from the dangers in society, with little or no risk of alcohol use—let alone alcohol misuse and AUD. In the past two decades, however, there has been a growing body of research on alcohol use and misuse among individuals with MBID. In fact, they have now been identified as a risk group for more severe negative consequences of alcohol use (Slayter, 2008) and for developing AUD (Burgard, Donohue, Azrin, & Teichner, 2000; McGillicuddy, 2006). In this

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FIGURE 32.1 The normal distribution of IQ scores. When IQ scores of large numbers of people are grouped together, it is normally distributed with a mean IQ of 100 and a standard deviation of 15. Roughly 68% of the population has a score within one standard deviation of the mean (85 115) and 95% of the population would have an IQ score within two standard deviations of the mean (70 130). This means that 2.5% of the population would be expected to have an IQ below 70, which is classified as an intellectual disability.

chapter we summarize research on the prevalence, risk factors, and neuropsychological underpinnings of alcohol (mis)use and AUD in individuals with MBID and provide suggestions for policy and practice.

PREVALENCE Although the literature on alcohol (mis)use and AUD among individuals with MBID remains scarce, we know that all types of substances are used in this group (VanDerNagel et al., 2017). Alcohol is the main substance used and misused in individuals with MBID, followed by cannabis and stimulants. In comparison with the general population, a relatively large proportion of individuals with MBID are teetotalers, meaning they do not use any substances at all (Simpson, 2012; VanDerNagel, Kiewik, Van Dijk, De Jong, & Didden, 2011). However, this does not imply that alcohol (mis)use or AUD is not an issue of importance in this group. In fact, individuals with MBID who do use alcohol seem to be at an increased risk of developing AUD.

Prevalence of Alcohol (Mis)use and Alcohol Use Disorder There have been a number of (European) studies on the prevalence of alcohol (mis)use and AUD among individuals with MBID. These studies show a wide variation in prevalence rates, which may reflect: (1) differences in the definition of ID (including or excluding those with BIF or individuals with

moderate or severe ID); (2) differences between specific subgroups (such as those receiving ID service or AUD treatment, those with comorbid mental disorders, or forensic patients); (3) methodological and measurement issues (use of proxy or self-report measures); or (4) potential differences in prevalence rates over time and between countries (Van Duijvenbode et al., 2015). Regarding alcohol use, for instance, 64% of a sample of 419 individuals with MBID in Dutch disability services used alcohol in the previous month (VanDerNagel et al., 2017), while in an Irish sample of 157 individuals with mild to profound ID in family or residential group homes, only 10% were regular drinkers (McGuire, Daly, & Smyth, 2007). Similarly, a wide range of rates for AUD is found, from 1% substance use disorder (including AUD) in a British communitybased study among 1023 adults with mild to profound ID (Cooper, Smiley, Morrison, Williamson, & Allen, 2007) to 21% alcohol misusers in a community sample (n 5 122) with mild to moderate ID in the United States (McGillicuddy & Blane, 1999). In samples from psychiatric or behavioral treatment facilities for individuals with ID, generally relatively high rates of 17% 28% AUD (and other substance use disorders) are found (Chaplin, Gilvarry, & Tsakanikos, 2011; Didden, Embregts, Van der Toorn, & Laarhoven, 2009; Pezzoni & Kouimtsidis, 2015). These same trends are seen in children and adolescents with MBID. Of particular concern are recent studies which indicate that they start using alcohol at a rather young age. For instance, Kiewik, VanDerNagel, Kemna, Engels, and De Jong (2016) showed that 75% of 12- to 15-year-old Dutch adolescents with MBID had initiated drinking. Emerson, Robertson, Baines, and Hatton (2016) found similar results in the United Kingdom, and reported 11-year-old children with MID to be more likely to have used alcohol in the previous 4 weeks, to have been intoxicated, and to have more positive attitudes toward drinking compared to children without ID. In addition, they found that children with MID accounted for 9% of all children with potentially harmful levels of drinking. Despite differences in reported prevalence rates, individuals with MBID who drink alcohol seem to be at an increased risk for developing AUD. This heightened risk seems to be the result of an accumulation of risk factors in individuals with MBID (Van Duijvenbode et al., 2015), including adverse life events, social distance from the community, family and social problems, and a low socioeconomical status. In addition, risk factors associated with MBID itself (such as the desire to “fit in” and susceptibility to peer pressure) further increase this risk. Alcohol use by peers, family members, and professional caregivers seems of

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THE NEUROPSYCHOLOGICAL UNDERPINNINGS OF ALCOHOL USE DISORDER

particular interest in this regard, increasing the risk for alcohol use in both children (Emerson et al., 2016) as well as adults (VanDerNagel et al., 2017).

Screening and Assessment Lack of systematic screening for, and assessment of, alcohol use and AUD in individuals with ID results in—at best—a rather fragmented view of its rates and consequences. Professionals working with individuals with ID mostly rely on their clinical judgement to detect alcohol use and AUD, even while they indicate that they lack the skills and knowledge to do so (VanDerNagel et al., 2011). Systematic screening in the ID population, however, is hindered by the lack of suitable instruments. Widely used screening instruments for AU(D) may be less suitable for individuals with ID because of their complexity (e.g., use of difficult wording and lengthy phrases) and the tendency of individuals with ID to acquiescence (i.e., to agree with whatever statement has been given) as well as to “say nay” regarding questions relating to social taboos, such as

TABLE 32.1

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alcohol use (Van Duijvenbode et al., 2015). The Substance Use and Misuse in Intellectual Disability Questionnaire (SumID-Q; VanDerNagel et al., 2011; VanDerNagel, Kemna, & Didden, 2013) has been developed to circumvent these issues while assessing substance use, risk factors, and consequences in individuals with MBID (Table 32.1). It takes the needs of individuals with MBID into account, for example, by avoiding long and difficult sentences and words and by using pictures and other visual aids (Fig. 32.2).

THE NEUROPSYCHOLOGICAL UNDERPINNINGS OF ALCOHOL USE DISORDER Around 1990, researchers began to study the neurological and neuropsychological consequences of alcohol misuse and AUD. They soon discovered that this research not only provided a theoretical framework for understanding AUD, but could also potentially answer some of the difficulties in assessing and treating

Structure of and Sample Questions From the SumID-Q

Structure In the SumID-Q, substance use is discussed in an empathetic, nonconfrontational way. The first part of the SumID-Q interview assesses the client’s familiarity with substances (e.g., alcohol, cannabis), presenting substance-related pictures and asking what is shown. This will clarify the terminology of the client, which is then used in the remainder of the interview to prevent misunderstandings and to make the client feel at ease. In the second part of the interview, clients are asked about their knowledge of, and attitude toward, using these substances, as well as substance use by close others (i.e., friends, family, staff members). Discussing these topics without (negative) judgment facilitates the client to speak freely and truthfully when asked about their own substance use. Patterns of substance use are further explored by asking about frequencies, quantities, and circumstances in which substances are regularly used. Sample questions Alcohol-related knowledge Driving a car after consuming four glasses of alcohol is allowed Childrena are allowed to buy alcohol Drinking a lot of alcohol reduces appetite Drinking a lot of alcohol can impair your memory Alcohol-related attitudes Drinking . . . is stupid . . . is tasty/pleasantb Persons who drink . . . are weak Persons who drink . . . are clever Persons who drink . . . are “cool” Drinking . . . is unhealthy a

The interviewer is instructed to explain that “Children” refers to persons under the age of 16. In Dutch the word “lekker” is used, referring to tasty and/or pleasant bodily sensations. This table provides the structure and some sample questions of the Substance use and Misuse in Intellectual Disability Questionnaire (SumID-Q; VanDerNagel et al., 2011), a Dutch semistructured interview to assess multiple aspects of substance use (familiarity, knowledge, attitude, substance use by others, patterns of substance use, severity of substance use-related consequences) in individuals with mild to borderline intellectual disability. b

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FIGURE 32.2 Sample of pictures from the SumID-Q. The Substance use and Misuse in Intellectual Disability Questionnaire (SumID-Q; VanDerNagel et al., 2011) starts by showing a set of pictures, asking for each picture “What is this?” This identifies an individual’s familiarity with several types of substances as well as the terminology they use. To assist with answering the knowledge and attitude questions in the SumID-Q (for a sample of these questions, see Table 32.1), pictograms are used for “disagree,” “neither agree nor disagree,” “agree,” and “I don’t know.”

alcohol misuse and AUD (Stacy & Wiers, 2010; Yu¨cel & Lubman, 2007). A specific line of research in the field of AUD has, therefore, been directed at its neurological and neuropsychological underpinnings and the applicability of neuropsychological measures in the assessment and treatment of AUD.

Ability

Cognitive resources

Dual Process Models of Addiction Alcohol misuse and AUD have long been thought to be the outcome of rational decision-making. However, problematic drinkers often do not merely consciously weigh the expected or experienced benefits and costs of alcohol use (Stacy & Wiers, 2010). According to dual process models of addiction (Fig. 32.3, e.g., Bechara, Noel, & Crone, 2006; Strack & Deutsch, 2004), behavior is also influenced by fast, automatic processes that are difficult to control and sometimes occur outside of conscious awareness. Attention selection and allocation, evaluation of environmental cues, and approach/avoidance tendencies are examples of such processes. In dual process models, these processes have been called “implicit,” whereas slow and controlled processes, such as motivation and executive control, are called “explicit.” Alcohol misuse leads to long-term adaptations in both systems, resulting in disruptions in motivational, reward, and inhibitory control processes, and subsequent deficiencies in information processing (Hyman, Malenka, & Nestler, 2006; Koob, 2013). More specifically, alcohol misuse and AUD have been associated with several cognitive biases, including biases in attention, action tendencies, and memory associations (Robinson & Berridge, 2008). This means that alcohol-

Willingness

Implicit processes

Alcohol use

FIGURE 32.3

Dual process model of addiction. Schematic and simplified overview of dual process models of addiction. These models theorize that behavior is influenced by implicit and explicit processes. Implicit processes are fast and automatic. Explicit processes, on the other hand, are slow and deliberate. The influence of implicit processes on behavior is moderated by (the strength of) explicit processes, or cognitive resources. In other words: the influence of implicit processes on behavior can be suppressed if there is sufficient motivation and cognitive abilities to do so (Fazio & Olson, 2003).

related stimuli have gained “incentive salience” and, as a result, “grab the attention,” seem attractive and elicit approach behavior. Alcohol misuse and AUD have also been associated with executive dysfunctioning, reflected in a smaller working memory capacity, difficulties in delaying gratification, and less behavioral control in problematic drinkers compared to nonproblematic drinkers (Hyman et al., 2006). Together, these disruptions indicate a growing loss of control over alcohol use (Koob, 2013).

III. PSYCHOLOGY, BEHAVIOR, AND ADDICTION

CONCLUSION AND IMPLICATIONS FOR PRACTICE

Deficiencies in Information Processing in Problematic Drinkers With Mild to Borderline Intellectual Disability Although this has been studied extensively, this line of research has only recently been expanded to individuals with MBID by Van Duijvenbode, Didden, Korzilius, and Engels (2017b). Following dual process models of addiction, they hypothesized that behavior in those with weak executive control, such as individuals with MBID (Willner, Bailey, Parry, & Dymond, 2010), might be more strongly influenced by implicit processes than in those with strong executive control. This, then, might explain why individuals with MBID are at risk of developing AUD after initial alcohol use. The overall aim of their research project was to: (1) study the influence of IQ on deficiencies in information processing associated with alcohol misuse and AUD and (2) explore the practical use of indirect measures of cognitive biases and executive dysfunction for the screening, assessment, and treatment of AUD in individuals with MBID. The first part of the research project focused on biases in implicit processes (attention, approach tendencies, interpretation, or memory associations) in problematic drinkers with and without MBID. Overall, they found no evidence of an attentional bias or approach bias in problematic drinkers. Problematic drinkers did not direct their attention to pictures of alcoholic beverages more often than light drinkers, did not look at these pictures longer than light drinkers, and did not respond faster to these pictures than light drinkers (Van Duijvenbode, Didden, Korzilius, & Engels, 2016a; Van Duijvenbode, Didden, Korzilius, & Engels, 2016c). Though there were no differences between problematic drinkers with and without MBID, individuals with MBID had high intraindividual variability in reaction times, possibly as a result of fluctuations in their attention or deficiencies in executive functions (Haishi, Okuzumi, & Kokubun, 2011). Problematic drinkers with and without MBID did show a so-called interpretation or association bias. That is, they were inclined to interpret ambiguous words (such as “draft” or “pitcher”) or situations in an alcohol-related manner. This was especially true for negative situations, such as quarreling or feelings of stress (Van Duijvenbode, Didden, Korzilius, & Engels, 2016b). These results were replicated in a second study in which it was found that drinking motives could predict the strength of the interpretation bias. People who drink alcohol to reduce unpleasant emotions often gave alcohol-related answers to negative situations. People who drink alcohol to make social situations more fun or to facilitate social relationships, on the other hand, tended to associate positive situations such

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as a party or festival with alcohol use (Van Duijvenbode, Didden, VanDerNagel, Korzilius, & Engels, 2018b). The second part of the research project focused on disruptions in explicit processes, that is, executive and cognitive dysfunctioning. Unexpectedly, problematic drinkers did not have a smaller working memory capacity, less inhibitory control, or a lower verbal IQ (i.e., verbal reasoning and vocabulary) than light drinkers (Van Duijvenbode, Didden, Korzilius, & Engels, 2017a). Problematic drinkers without MBID did have a lower performance IQ than light drinkers, pointing to possible constraints in processing speed, problemsolving ability, and flexibility. In problematic drinkers with MBID, however, performance IQ was not lower than in light drinkers with MBID (Van Duijvenbode, Didden, VanDerNagel, Korzilius, & Engels, 2018a). This could mean chronic and/or excessive alcohol use does not impede cognitive functioning even further in those with MBID. However, methodological difficulties such as poor differentiability in the lower IQ range (Whitaker, 2005) and a diffuse pattern of cognitive decline after chronic and/or excessive alcohol use (Parsons, 1998) might be more likely explanations.

CONCLUSION AND IMPLICATIONS FOR PRACTICE Alcohol misuse and AUD among individuals with MBID have gained increasing attention over the past few years, with a growing number of studies on prevalence, assessment, prevention, and treatment of alcohol misuse and AUD in this population. In this chapter, we have provided an overview of the current knowledge on (the neurology of) AUD in individuals with MBID. It can be concluded that individuals with MBID are at risk for developing alcohol misuse and AUD. At least in a subgroup of problematic drinkers (both with and without MBID) this is associated with neuropsychological disruptions that, to some degree, seem to be affected by IQ. Based on the earlier findings, Van Duijvenbode et al. (2015, 2017b) have proposed several suggestions for policy and practice to further improve the care for individuals with MBID and AUD (Table 32.2). Individuals with MBID require specialized care from multidisciplinary teams in which knowledge and expertise regarding both ID and AUD are present. To achieve this, collaboration and fertilization between addiction medicine and ID service providers is vital. Fortunately, models to ensure such collaboration (see, for example, VanDerNagel, Van Dijk, Kemna, Barendregt, & Wits, 2017) as well as protocols to deliver addiction treatment adapted to the needs to

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TABLE 32.2

Suggestions for Policy and Practice

Topic

Suggestion for policy and practice

Prevention

• Be aware that MBID and AUD often go together and that individuals with MBID are at risk of developing AUD • Develop interventions to prevent or postpone alcohol use in children and adolescents with MBID

Screening and assessment

• Make alcohol use a common topic of conversation, by discussing it regularly in an open, empathetic, and nonjudgmental manner and thereby removing it from its stigma • Train staff members in intellectual disability care in recognizing, screening, and assessing alcohol use and misuse • Train staff members in addiction facilities in recognizing and screening a possible MBID • Implement formal screening and assessment of alcohol use and MBID in routine diagnostic procedures • Implement a thorough neurocognitive assessment (executive, intellectual functioning) in an early phase of the diagnostic or treatment phase.

Treatment

• Use treatment interventions that are tailored to the needs of those with MBID • Do not implement cognitive bias modification procedures (aimed at reducing cognitive biases) or neuropsychological treatment protocols (aimed at improving executive functioning) to treat alcohol misuse and AUD • Collaborate with partners in other fields of health care (addiction medicine, intellectual disability care, general health care)

This table provides a summary of suggestions for policy and practice that could further improve the care and treatment for individuals with mild to borderline intellectual disability (MBID) with alcohol use disorder (AUD) (Van Duijvenbode et al., 2015, 2017b).

individuals with ID (see, for example, Kouimtsidis et al., 2017; VanDerNagel & Kiewik, 2016) are becoming increasingly available. An example of this is an adapted cognitive behavioral therapy (CBT 1 ), in which individuals with MBID and AUD are taught several different self-regulation techniques to reduce or quit alcohol use (Fig. 32.4). Regarding the usefulness or efficacy of neuropsychological treatment options, the studies of Van Duijvenbode et al. (2017b) have pointed out some methodological challenges that need to be addressed in future research (Van Duijvenbode, 2017). The use of cognitive bias modification procedures (aimed at reducing cognitive biases) or neuropsychological treatment protocols (aimed at improving executive functioning) to treat alcohol misuse and AUD in individuals with ID is, therefore, premature and is discouraged. But there is still a long way to go. Scientific research is limited; many gaps in the literature on prevalence and risk factors remain, and valid screening and assessment tools and effective treatment interventions are scarce. Together with the recommendations we have made in this chapter, more research is needed to further improve the care and treatment of individuals with MBID and AUD.

MINI-DICTIONARY OF TERMS Adaptive functioning The conceptual, social and practical skills that are needed to function in day-to-day life. Borderline intellectual functioning Individuals whose IQ lies between normal intellectual functioning and ID (typically IQ 70 85).

FIGURE 32.4 Pictures to illustrate self-regulation techniques taught in the CBT 1 CBT 1 (VanDerNagel & Kiewik, 2016) is a cognitive behavioral treatment (CBT) intervention aimed to reduce alcohol and other substance misuse among individuals with mild to borderline intellectual disability by increasing self-regulation techniques: Distance, Different choices, Distraction, Declare (or tell), Different thinking and different acting, Doing great (thumbs up). With “Distance” as a self-regulation technique, for example, clients learn to keep physical distance to risk situations and events that trigger (the urge to) substance use. With “Distraction,” clients are trained to substitute maladaptive responses with alternative behavior that is not compatible with substance use under high-risk circumstances.

Dual process model Theoretical model that states that behavior is not only influenced by rational thoughts and conscious decisionmaking (explicit processes), but also by relatively fast and automatic processes that scan, filter, and interpret environmental cues (implicit processes).

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REFERENCES

Intellectual disability A chronic neurodevelopmental disorder that originates in childhood and is characterized by (mild to profound) deficits in intellectual functioning and adaptive functioning. Intellectual functioning A wide range of mental abilities (e.g., reasoning, planning, problem-solving, judgment, and abstract thinking) that together form someone’s IQ.

KEY FACTS Intellectual Disabilities • ID is characterized by deficits in both intellectual and adaptive functioning. • Individuals with ID form a heterogeneous group, as the nature and severity of the deficits can vary. • Based on the theoretical distribution of IQ scores, 2.5% of the population has ID and 14% borderline intellectual functioning. • ID can be caused by a number of factors, including genetic abnormalities, problems during pregnancy or the perinatal period (e.g., exposure to toxic substances, alcohol or drugs, infections, or trauma), and environmental deprivation (e.g., malnutrition). • Individuals with ID are at risk for a wide range of adverse life circumstances, mental health problems, and alcohol/substance use disorder. This is most likely due to an accumulation of general risk factors, which are more common in individuals with ID, and specific risk factors associated with having ID (such as susceptibility to peer pressure).

SUMMARY POINTS • Individuals with MBID are considered to be at risk for developing alcohol misuse and AUD. • As in individuals without ID, alcohol misuse and AUD seem be to be associated with neuropsychological disruptions in the motivational, reward, and inhibitory control processes. • Emphasis should be placed on prevention and systematic screening and assessment of co-occurring MBID and AUD. • Treatment interventions should be tailored to the needs of individuals with MBID. • The use of cognitive bias modification procedures or neuropsychological treatment protocols to treat AUD in individuals with MBID is discouraged. • To provide specialized treatment to individuals with MBID and AUD, a close collaboration and cross-fertilization between ID service providers and addiction medicine is vital.

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Van Duijvenbode, N., Didden, R., Korzilius, H. P. L. M., & Engels, R. C. M. E. (2016b). Everybody is. . .drinking! Interpretation bias in problematic drinkers with mild to borderline intellectual disability. Journal of Mental Health Research in Intellectual Disabilities, 9, 101 117. Van Duijvenbode, N., Didden, R., Korzilius, H. P. L. M., & Engels, R. C. M. E. (2016c). The addicted brain: Cognitive biases in problematic drinkers with mild to borderline intellectual disability. Journal of Intellectual Disability Research, 60, 242 253. Van Duijvenbode, N., Didden, R., Korzilius, H. P. L. M., & Engels, R. C. M. E. (2017a). The role of executive control and readiness to change in problematic drinkers with mild to borderline intellectual disability. Journal of Applied Research in Intellectual Disabilities, 30, 885 897. Van Duijvenbode, N., Didden, R., Korzilius, H. P. L. M., & Engels, R. C. M. E. (2017b). The usefulness of implicit measures for the screening, assessment and treatment of problematic alcohol use in individuals with mild to borderline intellectual disability. Advances in Neurodevelopmental Disorders, 1, 42 51. Van Duijvenbode, N., Didden, R., Korzilius, H. P. M. L., & Engels, R. C. M. E. (2016a). Attentional bias in problematic drinkers with and without mild to borderline intellectual disability. Journal of Intellectual Disability Research, 21, 255 265. Van Duijvenbode, N., Didden, R., VanDerNagel, J. E. L., Korzilius, H. P. L. M., & Engels, R. C. M. E. (2018a). Cognitive deficits in problematic drinkers with and without mild to borderline intellectual disability. Journal of Intellectual Disabilities, 22, 5 17. Van Duijvenbode, N., Didden, R., VanDerNagel, J. E. L., Korzilius, H. P. L. M., & Engels, R. C. M. E. (2018b). The relationship between drinking motives and interpretation bias in problematic drinkers with mild to borderline intellectual functioning. Journal of Intellectual and Developmental Disability, 43, 125 136. Van Duijvenbode, N., VanDerNagel, J. E. L., Didden, R., Engels, R. C. M. E., Buitelaar, J. K., Kiewik, M., & De Jong, C. A. J. (2015). Substance use disorders in individuals with mild to borderline intellectual disability: Current status and future directions. Research in Developmental Disabilities, 38, 319 328. Whitaker, S. (2005). The uses of the WISC-III and the WAIS-III with people with a learning disability: Three concerns. Clinical Psychology Forum, 50, 37 40. Willner, P., Bailey, R., Parry, R., & Dymond, S. (2010). Evaluation of executive functioning in people with intellectual disabilities. Journal of Intellectual Disability Research, 54, 366 379. Yu¨cel, M., & Lubman, D. I. (2007). Neurocognitive and neuroimaging evidence of behavioural dysregulation in human drug addiction: Implications for diagnosis, treatment and prevention. Drug and Alcohol Review, 26, 33 39.

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33 Sex, Stress, and Neuropeptides Interact to Influence Alcohol Consumption Todd B. Nentwig and Judith E. Grisel Department of Psychology, Neuroscience Program, Bucknell University, Lewisburg, PA, United States

LIST OF ABBREVIATIONS ACTH BNST CeA HPA axis CRH CORT β-E POMC DID EtOH BECs AUD NAc VTA PVN ArcN NTS

dependent manner, it is likely that neuropeptides also exert sex-specific effects on brain stress systems to influence drinking. We describe the impact of neuropeptides in rodent models of excessive ethanol (EtOH) consumption and suggest that sex and brain stress systems interact with neuropeptides to regulate drinking.

adrenocorticotropic hormone bed nucleus of the stria terminalis central nucleus of the amygdala hypothalamic pituitary adrenal axis corticotropin-releasing hormone corticosterone β-endorphin proopiomelanocortin “drinking in the dark” ethanol blood ethanol concentrations alcohol use disorders nucleus accumbens ventral tegmental area paraventricular nucleus of the hypothalamus arcuate nucleus of the hypothalamus nucleus of the solitary tract

CORTICOTROPIN-RELEASING HORMONE

INTRODUCTION Excessive alcohol consumption precedes many negative health consequences, including alcohol use disorder (AUD) (Jennison, 2004), yet the rates of excessive drinking continue to increase, especially in females (Keyes, Li, & Hasin, 2011). For decades, rates of excessive alcohol use and AUD were reportedly higher in men; however, accumulating evidence suggests that this gender gap is rapidly closing (Keyes, Martins, Blanco, & Hasin, 2010). Although many factors contribute to the etiology of AUD, neuropeptides consistently emerge as key regulators of excessive alcohol consumption due, in part, to their stress-promoting or stress-buffering effects (Koob, 2008). Because stress appears to effect alcohol consumption in a sex-

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00033-7

Fig. 33.1 shows some stress-related neuropeptides involved in alcohol consumption. This chapter focuses on the role of corticotropin-releasing hormone (CRH) and β-endorphin (β-E) in alcohol consumption; other neuropeptide systems have been reviewed elsewhere (Anderson & Becker, 2017; Koob, 2008; Lee & Weerts, 2016; Thorsell & Mathe´, 2017). CRH, a 41-amino acid peptide, was first isolated from the ovine hypothalamus in 1981 (Spiess, Rivier, Rivier, & Vale, 1981). CRH acts throughout the central nervous system (Peng et al., 2017; Swanson, Sawchenko, Rivier, & Vale, 1983) via two Gprotein-coupled receptors, CRH1 and CRH2 (Chang, Pearse, O’Connell, & Rosenfeld, 1994; Lovenberg et al., 1995). CRH has a higher affinity for the CRH1 receptor (CRH1R). CRH can also be bound by CRH-binding protein, which restricts availability for binding to its cognate receptors (Behan et al., 1995). CRH receptors can also be activated by urocortins, a related family of endogenous ligands (Ryabinin et al., 2012). CRH is characterized as a master orchestrator of the neuroendocrine stress response (Vale, Spiess, Rivier, & Rivier, 1981). Parvocellular neurons in the paraventricular nucleus of the hypothalamus (PVN) release CRH into the median eminence of the anterior pituitary

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FIGURE 33.1 Partial list of stress-related neuropeptides involved in alcohol consumption. Diagrams illustrate neuropeptide ligands (cloud) binding to their cognate G-protein-coupled receptors and activating corresponding signal transduction mechanisms (yellow circle). Lists of putative receptor targets are organized according to highest binding affinity (top to bottom). CRH and β-E are highlighted to emphasize the focus of this chapter. MOR, DOR, KOR: mu-, delta-, and kappa-opioid receptors, respectively; NPY: neuropeptide Y.

gland, inducing synthesis of the precursor protein, proopiomelanocortin (POMC). POMC is then cleaved into various functional peptide subunits, such as adrenocorticotropic hormone (ACTH) and β-E (RaffinSanson, de Keyzer, & Bertagna, 2003). Once in the peripheral circulation, ACTH acts in the adrenal glands to stimulate glucocorticoid secretion that regulates behavioral and biochemical sequelae of stress, including negative feedback inhibition of the hypothalamic pituitary adrenal axis (HPA axis) (Guillemin, Dear, Nichols, & Lipscomb, 1959). Fig. 33.2 illustrates CRH-containing cell bodies and axon fibers throughout the rodent brain and effects of CRH on the HPA axis.

ROLE OF CORTICOTROPIN-RELEASING HORMONE IN ALCOHOL CONSUMPTION AND ADAPTATIONS CRH signaling mediates neuroadaptations associated with chronic ethanol consumption dependence (Phillips, Reed, & Pastor, 2015). The extended amygdala—comprised of the CeA, bed nucleus of the stria terminalis (BNST), and NAc shell—is a principal site of CRH’s effects on alcohol drinking and behavior following chronic ethanol exposure (Koob, 2008). During withdrawal, extracellular levels of CRH increase in the CeA (Merlo Pich et al., 1995) and BNST (Olive, Koenig, Nannini, & Hodge, 2002) along with voluntary ethanol consumption and anxiety-like behavior. A CRH1R antagonist in the central nucleus of the amygdala (CeA) or BNST mitigates these increases (Funk, O’Dell, Crawford, & Koob, 2006; Huang et al., 2010). While extrahypothalamic CRH circuits are sensitized

following chronic EtOH exposure, hypothalamic CRH is suppressed. During withdrawal, POMC and CRH mRNA, and ACTH and corticosterone (CORT) plasma levels decrease in dependent rats, relative to controls (Rasmussen et al., 2000; Richardson, Lee, O’Dell, Koob, & Rivier, 2008). Extensive connectivity between extrahypothalamic CRH circuits and the HPA axis (Herman, 2012) suggest these systems may be attractive therapeutic targets for individuals with AUD (Rodriguez & Coven˜as, 2017). Unfortunately, studies cited here only used male rodents, and evidence suggests that sex differences in CRH signaling and stress sensitivity may increase vulnerability in females (Bangasser et al., 2010). Thus, intrinsic sex differences in CRH signaling suggest that ethanol-induced adaptations in CRH-mediated processes might also differ between sexes. The dearth of data testing this hypothesis may be hampering translational efforts. Evidence also suggests that CRH systems are engaged during excessive, binge-like EtOH consumption. Studies described next utilize a mouse model of binge drinking, termed “drinking in the dark” (DID), typically carried out in C57BL/6J mice (or transgenics on a C57BL/6J background) because they have a genetic propensity for EtOH acceptance. Animals are offered access to an EtOH solution for 2 hours, approximately 3 hours into the dark phase of their light dark cycle, for 3 consecutive days and access is extended to a 4-hour binge test (BT) on day 4. The DID model engenders high levels of EtOH consumption and intoxicating blood ethanol concentrations (BECs) of 80 mg/ dL or greater, a hallmark of human binge drinking (Rhodes, Best, Belknap, Finn, & Crabbe, 2005).

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FIGURE 33.2

Illustration of CRH-producing cell bodies (dots) and projections (arrows). Although CRH is widely distributed across the brain, the majority of neurons are located within interconnected regions known to control the HPA axis response to stress (PVN) as well as regulate negative affect-like behaviors and EtOH consumption (BNST and Amyg). The BNST and Amyg also contribute to regulation of the stress response via direct and indirect projections, respectively, to the PVN. Hipp: Hippocampus; LC: locus coeruleus; legend for other terms can be found in the list of abbreviations. Source: Compiled from Koob, G.F. (2008). A role for brain stress systems in addiction. Neuron, 59(1), 11 34. doi:10.1016/j.neuron.2008.06.012; Peng, J., Long, B., Yuan, J., Peng, X., Ni, H., Li, X., . . . Li, A. (2017). A quantitative analysis of the distribution of CRH neurons in whole mouse brain. Frontiers in Neuroanatomy, 11, 63. doi:10.3389/fnana.2017.00063; Swanson, L.W., Sawchenko, P.E., Rivier, J., & Vale, W.W. (1983). Organization of ovine corticotropin-releasing factor immunoreactive cells and fibers in the rat brain: An immunohistochemical study. Neuroendocrinology, 36(3), 165 186.

Blocking CRH1Rs before EtOH access on the BT decreases EtOH consumption at a dose that does not affect locomotor behavior or sucrose drinking and reduces BECs below 80 mg/dL (Sparta et al., 2008). This initial finding has been extended to show that intracerebroventricular injections of a nonselective CRH1R antagonist or a CRH2R agonist reduced binge-like ethanol consumption. Reduction in drinking following CRH1R antagonism appears to be independent of HPA axis signaling as metyrapone, a CORT synthesis inhibitor, and mifepristone, a glucocorticoid receptor antagonist, fail to selectively reduce binge-like ethanol consumption (Lowery et al., 2010) suggesting that extrahypothalamic CRH regulates binge-like EtOH consumption and that CRHR subtypes may exert opposing effects on alcohol consumption (Lowery et al., 2010). To further elucidate the circuitry involved in CRHmodulated binge drinking, Thiele and colleagues (Lowery-Gionta et al., 2012) used immunohistochemistry to demonstrate that CRH is upregulated in the CeA and ventral tegmental area (VTA) following binge drinking in the DID model, and intra-CeA, injections of CRH1R antagonists selectively reduced binge-like ethanol consumption, but not moderate levels of ethanol intake in male mice (Lowery-Gionta et al., 2012). These results suggest that the CRH system is acutely engaged

during, or following, excessive binge-like drinking in brain regions associated with alcohol dependence (Koob, 2008). Subsequent studies showed that intraVTA CRH1R antagonism and CRH2R agonism reduced binge-like consumption, and that chemogenetic inactivation of CRH projections from the BNST to the VTA, but not local inhibition of VTA CRH neurons, blunted binge-like EtOH consumption (Rinker et al., 2017). Thus, extrahypothalamic CRH signaling is recruited is stress-related and reward-related limbic regions during/ following binge-like EtOH consumption, perhaps amplifying the efficacy of CRH1R antagonists to reduce drinking. However, genetic studies have revealed nonspecific effects of CRHR antagonists on general fluid intake (Giardino & Ryabinin, 2013) and differential modulation of EtOH consumption in males and females. Relative to wild types, male and female CRH1R knock-outs (KOs) exhibit reduced alcohol consumption and BECs, an effect especially pronounced in female KOs (Kaur, Li, StenzelPoore, & Ryabinin, 2012). In contrast, there was no sex difference in CRH2R KOs. Akin to CRH1R KOs, CRH KOs showed sex-dependent reductions in BECs, with female KOs reaching higher BECs (B100 mg/dL), identical to wild-type females, and supporting the contention that sex may modulate the effect of CRH on binge-like EtOH consumption.

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β-ENDORPHIN’S ROLE IN ALCOHOL CONSUMPTION We recently found evidence of sexually dimorphic effects of β-endorphin levels on binge-like alcohol consumption and CRH gene expression in the extended amygdala (Nentwig, Wilson, Rhinehart, & Grisel, 2018). β-E, is a member of the endogenous opioid peptide family that has long been implicated in the effects of alcohol (Herz, 1997; Roth-Deri, Green-Sadan, & Yadid, 2008). β-E is derived from the large precursor protein, POMC, following posttranslational processing (Raffin-Sanson et al., 2003). β-E is an agonist with high affinity for the μ-opioid and δ-opioid receptors (Mansour, Hoversten, Taylor, Watson, & Akil, 1995) and acts on μ receptors to modulate the reinforcing effects of alcohol (Contet, Kieffer, & Befort, 2004). β-E is synthesized and released by POMC neurons in the ArcN and the nucleus of the solitary tract (NTS) (Bloom & Battenberg, 1983; Bloom, Battenberg, Rossier, Ling, & Guillemin, 1978) though sparse populations exist in the amygdala, NAc, and VTA (Leriche, CoteVe´lez, & Me´ndez, 2007), where alcohol induces β-E release, and likely contributes to the rewarding effects of alcohol (Jarjour, Bai, & Gianoulakis, 2009; Olive, Koenig, Nannini, & Hodge, 2001). Fig. 33.3 illustrates POMC/β-E-containing cell bodies and axon fibers throughout the rodent brain.

In the clinic, genetic variation in β-E is associated with increased risk for AUD. Low basal levels of β-E are inversely correlated with genetic risk and the β-E response to alcohol (Dai, Thavundayil, & Gianoulakis, 2005; Kiefer, Jahn, Otte, Nakovics, & Wiedemann, 2006). Our laboratory and others have shown that transgenic mice lacking β-E (Rubinstein et al., 1996) exhibit altered EtOH consumption (Racz et al., 2008; Williams, Holloway, Karwan, Allen, & Grisel, 2007). However, these impacts manifest differently in males and females, such that β-E 2 / 2 males tend to consume less EtOH, relative to wild types, whereas β-E 2 / 2 females exhibit similar or enhanced EtOH consumption (McGonigle, Nentwig, Wilson, Rhinehart, & Grisel, 2016; Zhou, Rubinstein, Low, & Kreek, 2017). The mechanisms underlying this sex-dependent modulation remain elusive, but interactions between β-E and CRH offer some insight.

β-E, CORTICOTROPIN-RELEASING HORMONE, AND SEX INTERACT TO REGULATE DRINKING TO COPE β-E negatively regulates HPA axis activity and CRH (Buckingham, 1986; Lam & Gianoulakis, 2011). CRH release from PVN neurons triggers neurons in the ArcN to release β-E onto CRH neurons in the PVN

FIGURE 33.3 Illustration of POMC/β-E-producing cell bodies (dots) and projections (arrows). The ArcN is the primary source of β-E in the brain, and it sends numerous projections to areas involved in stress/anxiety regulation (BNST, Amyg, PVN, LC) and alcohol reward (NAc and VTA). Sparse distributions of β-E-producing neurons exist in limbic and hindbrain structures, with a dense population involved in appetite regulation located in the NTS. Hipp: Hippocampus; LC: Locus coeruleus; legend for other terms can be found in the list of abbreviations. Source: Compiled from Bloom, F.E., & Battenberg, E.L. (1983). Immunocytochemistry of endorphins and enkephalins. Methods in Enzymology, 103, 670 687; Bloom, F., Battenberg, E., Rossier, J., Ling, N., & Guillemin, R. (1978). Neurons containing beta-endorphin in rat brain exist separately from those containing enkephalin: Immunocytochemical studies. Proceedings of the National Academy of Sciences of the United States of America, 75(3), 1591 1595; Leriche, M., Cote-Ve´lez, A., & Me´ndez, M. (2007). Presence of pro-opiomelanocortin mRNA in the rat medial prefrontal cortex, nucleus accumbens and ventral tegmental area: Studies by RT-PCR and in situ hybridization techniques. Neuropeptides, 41(6), 421 431. doi:10.1016/j. npep.2007.08.004.

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CONCLUSIONS

FIGURE 33.4 Overlap of β-E and CRH systems in the rodent brain. β-E and CRH neurons often colocalize, and project to structures critically involved in stress regulation and EtOH consumption. Notably, PVN-projecting ArcN β-E neurons are necessary for inhibition of CRH release and subsequent HPA axis activation. Perturbations in β-E-mediated inhibition of CRH can lead to dysregulation of HPA axis activity and increased stress sensitivity. β-E and CRH also interact in other regions involved in EtOH consumption and stress sensitivity (i.e., Amyg). Hipp: Hippocampus; LC: locus coeruleus; legend for other terms can be found in the list of abbreviations.

providing tonic inhibition (Logan et al., 2015; Plotsky, 1991). β-E is also necessary for intact HPA axis function as transplantation of β-E neurons into the PVN reduces basal CORT, anxiety-like behavior, and stressinduced CORT secretion (Logan et al., 2015). Low levels of β-E are associated with elevated anxiety. β-E-deficient mice exhibit increased anxiety-like behavior in the elevated plus maze, light dark box, tail suspension test, response to forced swim stress, and novelty suppressed feeding test (Barfield et al., 2010; Barfield, Moser, Hand, & Grisel, 2013; Grisel, Bartels, Allen, & Turgeon, 2008). However, following EtOH administration, β-E-deficient mice show reduced anxiety-like behavior relative to wild types, suggesting that low β-E enhances sensitivity to EtOH’s anxiolytic effects. Fig. 33.4 illustrates the overlap between β-E and CRH systems, suggesting potential interactions between these neuropeptides in key brain regions involved in regulating stress, anxiety, and EtOH consumption. Therefore, we hypothesized that CRH may play a role in sex differences in β-E regulated EtOH consumption. Using behavioral, neuroendocrine, and genetic methods we showed that β-E deficiency enhances binge-like EtOH consumption in females, but not in males (Nentwig et al., 2018). β-E-deficient mice of both sexes exhibit elevated basal CORT, which is normalized by voluntary binge-like EtOH consumption in female mice, but not male mice. Under basal conditions, β-E-deficient females exhibit increased BNST Crh expression, also abolished by EtOH consumption. In total, β-E deficiency results in sex-specific alterations in HPA axis activity and Crh mRNA expression in the extended amygdala resulting in exaggerated stress

FIGURE 33.5 Model depicting the interactive influences of sex,

stress, and β-E on the trajectory toward excessive drinking. Low β-E may confer elevated stress sensitivity and heightened susceptibility toward risky drinking in females, but tend to reduce high EtOH consumption in males. Increased EtOH consumption observed in females with low β-E may reflect enhanced sensitivity to EtOH’s stress relieving effects, whereas decreased consumption in males may be attributed to a reduction in β-E’s positive modulation of the rewarding properties of EtOH. Sexually dimorphic effects of β-E highlight the importance of understanding how sex impacts the neuropeptide regulation of EtOH consumption.

sensitivity that promotes “self-medication” with EtOH. Fig. 33.5 shows a model summarizing these findings.

CONCLUSIONS In this review, we emphasize the role of CRH and β-E in EtOH consumption and underscore the influence of sex on the effects of these neuropeptides. Striking sex differences in stress-related psychiatric disorders

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FIGURE 33.6 Pubmed survey results illustrating the proportion of reports evaluating sex-dependent effects of neuropeptide manipulations on EtOH consumption. As an example, 25 total studies have examined CRH manipulations and EtOH consumption, four of which allowed for direct comparison between sexes, and 1/4 observed sex-dependent effects.  NPY search revealed seven reports that included only females. Pubmed search terms (CRH: CRF alcohol drinking; corticotropin alcohol drinking; β-E: POMC alcohol drinking, β-endorphin alcohol drinking; DYN: dynorphin alcohol drinking, kappa alcohol drinking; nor-BNI JDTic alcohol drinking; NPY: NPY alcohol drinking, neuropeptide Y alcohol drinking; OXT: oxytocin alcohol drinking; AVP: vasopressin alcohol drinking).

(Bangasser & Valentino, 2014) affirm the need to study both sexes in order to properly understand the neurobiology underlying neuropsychiatric vulnerability. Despite compelling evidence that females are more sensitive to stress and alcohol (Logrip, Oleata, & Roberto, 2017), the neural mechanisms involved in sex-dependent regulation of alcohol use are poorly understood. Fig. 33.6 represents the results of a literature survey evaluating the number of studies assessing effects of the stress-related neuropeptides on EtOH consumption. The vast majority have assessed only males, but when females have been evaluated, evidence suggests sex-dependent effects. Overall, we highlight the previously understudied impact of sex and β-E on EtOH consumption and suggest that sex and stress peptide interactions may provide important insight into sexdependent trajectories toward problem drinking.

Corticosterone Glucocorticoid hormone secreted from the adrenal cortex in response to activation of the hypothalamic pituitary adrenal (HPA) axis; its binding to glucocorticoid receptors inhibits further HPA axis activity. Corticotropin-releasing hormone Peptide hormone that initiates the neuroendocrine response to stress and can act as a neuromodulatory transmitter. Drinking in the dark procedure Rodent model of binge ethanol drinking in which animals consume high amounts of ethanol in 2 4 hours, resulting in blood ethanol typically . 0.08 g percent. Hypothalamic pituitary adrenal axis Neuroendocrine system comprised of the hypothalamus, and pituitary and adrenal glands that interact to coordinate the response to stress. Neuropeptides Small protein molecules secreted primarily by neurons to transmit information. Paraventricular nucleus of the hypothalamus Initial site of HPA axis activation. This region projects to the pituitary gland to release CRH into the blood in response to stress.

MINI-DICTIONARY OF TERMS β-Endorphin Neuropeptide essential for regulating the stress response also involved in the rewarding effects of alcohol. Alcohol use disorder Medical diagnosis for severe problem drinking characterized by compulsive alcohol intake despite negative consequences, high rates of relapse, and withdrawal symptoms when not using. Binge drinking Defined by the National Institute on Alcohol Abuse and Alcoholism as achieving a blood ethanol level of at least 0.08 g percent, typically four drinks for women or five drinks for men in about 2 hours. Blood ethanol concentration The content of ethanol in the blood as a measure of intoxication.

KEY FACTS Sex Differences in Alcohol Consumption • Human males consume more alcohol than females, but other animals show the opposite pattern. • Men tend to have higher rates of alcohol use disorders than women, but in recent years this gender gap has continually decreased. • Women are more prone to develop stress/anxiety disorders than men, and women with such disorders are more susceptible to use alcohol as a coping mechanism, compared to men.

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• Sex differences in neurobiological substrates contribute to sex differences in the vulnerability for excessive alcohol intake. • Improved understanding of sex-specific processes involved in regulating alcohol intake will guide treatment for alcohol use disorders.

SUMMARY POINTS • This chapter discusses evidence that sex, stress, and neuropeptides interact to regulate alcohol consumption. • In animal models, males and females often demonstrate different patterns of alcohol sensitivity and response, including neurobiological adaptations from the drug. • CRH mediates alcohol consumption through negative reinforcement and is dysregulated following binge alcohol consumption. • β-E, an endogenous opioid peptide, has long been implicated in the heritable risk for high alcohol consumption. • β-E regulates the HPA axis, CRH, and sensitivity to EtOH. • Sex-specific interactions between CRH and β-E influence alcohol consumption.

IMPLICATIONS FOR TREATMENTS Research on the sex-dependent neural mechanisms of AUD is still in the early stages. Genetic and endocrine factors influence neurocircuitry and behavior differently in males and females. Gaining a better understanding of the shared and nonshared causes and trajectories for AUD in men and women will help guide more targeted strategies for prevention and intervention, though much basic research remains to be done to better understand divergent neural substrates that underlie behavioral differences between the sexes.

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34 Maternal Separation Stress in Fetal Alcohol Spectrum Disorders: A Case of Double Whammy Shiva M. Singh and Bonnie Alberry Department of Biology, University of Western Ontario, London, ON, Canada

LIST OF ABBREVIATIONS ADHD BLI CPD FASD ncRNA PAE

attention deficit hyperactivity disorder binge-like injection continuous preference drinking fetal alcohol spectrum disorder noncoding RNA prenatal alcohol exposure

Adverse experience during infancy and early childhood is a risk factor for adult psychopathology. It may result from various forms of stress, including maternal separation and neglect. Such children are often exposed to multiple challenges, confounding interpretations of cause and effect. A case in point are children born with fetal alcohol spectrum disorder (FASD), caused by maternal alcohol consumption during pregnancy (Jones, Smith, Ulleland, & Streissguth, 1973). In 2012, almost 80% of Canadian women reported consuming alcohol (Health Canada, 2014), and an estimated 51% of North American pregnancies are unintended (Sedgh, Singh, & Hussain, 2014). Such pregnancies are often unwanted, facing various tensions and traumas for mother and child. Despite education and societal awareness of risks, an estimated 9.8% of women in the world consume alcohol while pregnant (Popova, Lange, Probst, Gmel, & Rehm, 2017). Globally, FASD represents an estimated 22.7 per 1000 newborns, with Canadian prevalence at 30.52 per 1000 (Roozen et al., 2016). Often a baby with FASD faces additional stress associated with maternal separation, including foster care and adoption (Lange, Shield, Rehm, & Popova, 2013). Although FASD

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00034-9

literature is extensive, and the effect of maternal separation on child development is recognized, minimal attempts are made to assess compound effects of prenatal alcohol and adverse early life experience, including postnatal maternal separation. In this chapter, we review experimental results using a mouse model to argue that this combination represents a double whammy. Insight into FASD relies on the impact of prenatal alcohol exposure (PAE) and postnatal stress on neurodevelopment beginning in utero and lasting for decades. It may contribute to extensive variability and heterogeneous manifestation within a diagnosis of FASD.

NEURODEVELOPMENT IS A LONGLASTING CONTINUUM MODULATED BY ENVIRONMENT Neurodevelopment in mammals begins embryonically and spans decades, lasting into adulthood (Urban & Guillemot, 2014). This period entails a delicate orchestration directed by fetal genotype in close interplay with the prenatal and postnatal environment. The precise interactions of genetic and environmental factors, although recognized, have been difficult to uncover due to technical challenges. The development of molecular technologies and experimental approaches have allowed identification of specific genes and mechanisms in neurodevelopment. Novel insights in neurogenesis and synaptogenesis, including involvement of such genes in specific mental disorders, have been observed (Grego´rio et al., 2009). The same level of

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precision is not represented for the environment’s effect on neurodevelopment and maturation. Exposure to toxic substances during development cause serious health consequences and specific disorders (De Felice, Ricceri, Venerosi, Chiarotti, & Calamandrei, 2015). Also, several chemicals, including alcohol, are implicated in specific neurodevelopmental disorders (Jones et al., 1973), though mechanisms are not understood. To this end, understanding the impact of the postnatal environment during neurodevelopment and maturation remains challenging. An enriching postnatal environment may improve outcomes, while a stressful environment may worsen them (Tost, Champagne, & MeyerLindenberg, 2015). Given the long-lasting continuum of mammalian neurodevelopment, it raises the question: is modulation of deficiencies caused by prenatal exposures by postnatal manipulations possible? If yes, one may wish to assess postnatal exposures that worsen or improve outcomes in a subset of prenatal exposures. Here, we focus on children diagnosed with FASD often facing postnatal maternal separation.

FETAL ALCOHOL SPECTRUM DISORDERS FASD refers to developmental aberrations caused by PAE, characterized by neurological, physical, developmental, and behavioral deficits (Chudley et al., 2005). FASD is a common cause of learning disabilities, cognitive deficits, and intellectual disability (Abel & Sokol, 1986). In Canada, FASD occurs every 30.52 per 1000 births (Roozen et al., 2016). Children diagnosed with FASD show hyperactivity and deficits in attention, executive function, learning, and memory, as well as social skills (Sokol, Delaney-Black, & Nordstrom, 2003). Yet, no feature is unique to FASD and is present in other disorders. This overrepresentation makes definitive diagnosis of FASD difficult, subjective, and unreliable. FASD is comorbid with attention deficit hyperactivity disorder (ADHD) (Rasmussen et al., 2010), and is often misdiagnosed as such (Peadon & Elliott, 2010). An FASD diagnosis is most easily achieved with known maternal alcohol consumption. Unfortunately, this information is often unavailable or unreliable. Although neurodevelopmental ethanol exposure causes FASD, the underlying mechanism associated with it is difficult to discover in humans.

REVEALING FETAL ALCOHOL SPECTRUM DISORDER ETIOLOGY VIA AN ANIMAL MODEL Studies aimed at understanding initiation and progression of FASD are not practical in humans. These

deficits and underlying mechanisms following PAE have been modeled in animals, particularly mice (Chokroborty-Hoque, Alberry, & Singh, 2014; Kleiber et al., 2014; Patten, Fontaine, & Christie, 2014; Schneider, Moore, & Adkins, 2011). A recent review of published results concluded that altered neurogenesis and neuron differentiation follows alcohol-induced changes to chromatin structure, contributing to behavioral abnormalities (Gavin, Grayson, Varghese, & Guizzetti, 2017). To further elaborate on these processes, our research has used two different neurodevelopmental alcohol exposure paradigms in C57BL/6 (B6) mice. First, in the continuous preference drinking (CPD) model pregnant mice consume moderate amounts of 10% alcohol (Kleiber, Wright, & Singh, 2011). Consumption is monitored daily with two accessible bottles containing either water or a 10% alcohol solution for each pregnant female (Fig. 34.1). Pups with neurodevelopmental and behavioral deficits that persist into adulthood result (Table 34.1) (Kleiber et al., 2011). To gain further insight, assessment of gene expression in the adult whole brain found many significant changes (Kleiber, Laufer, Wright, Diehl, & Singh, 2012). This allowed for modeling of gene networks that may contribute to the manifestation of FASDassociated aberrations (Table 34.2). Alternatively, the binge-like injection (BLI) model uses alcohol injections during different developmental stages, matching the first, second, and third trimesters of human pregnancy (Fig. 34.2). Using this model, we demonstrated that the nature and extent of behavioral deficits observed are dependent on timing (Table 34.1) (Mantha, Kleiber, & Singh, 2013). Further, adult gene expression differences are also dependent on timing (Kleiber, Laufer, Stringer & Singh, 2014; Kleiber, Mantha, Stringer, & Singh, 2013; Mantha, Laufer, & Singh, 2014; Stringer, Laufer, Kleiber, & Singh, 2013). These results show subtle, reliable, and relevant changes in genome-wide gene expression. Genes affected in each study have been implicated in cognitive dysfunction, anxiety, hyperactivity, and mood disorders—phenotypes shared by individuals diagnosed with FASD. Predominantly, early-alcohol exposure during the human first trimester equivalent in mice affects cell proliferation genes; cell migration and differentiation by exposure in the human second trimester equivalent; and cellular communication and neurotransmission by exposure during the human third trimester equivalent (Kleiber et al., 2013). Hub genes connect networks and pathways identified for each model, providing commonality in FASD gene expression features, and establishing a lifelong gene expression footprint left by alcohol exposure (Table 34.2). The question remains: what determines this footprint?

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(B) 10% Ethanol consumed (mL)

(A)

4

3.5 3 2.5 2 1.5 1 0.5 0 0 –8

–1

–6

–4

–2 ting G2 G4 G6 G8 G10 G12 G14 G16 G18 irth a B Day M

FIGURE 34.1 Continuous preference drinking model of prenatal alcohol exposure. (A) Sample cage setup for the continuous preference drinking (CPD) model of prenatal alcohol exposure with water (blue) and 10% ethanol solution (yellow) freely available throughout gestation. Daily liquid consumption is recorded by monitoring levels in each modified serological pipette. (B) Mean daily ethanol consumption before and throughout gestation for C57BL6/J mice in the CPD model.

TABLE 34.1

Phenotypic Characterization Following Neurodevelopmental Alcohol Exposure in C57BL/6 Mice

Exposure model

Phenotype

Reference

Continuous preference drinking (CPD)

• Delayed achievement of developmental milestones • Reduced activity in a novel open field and in a home environment • Impaired learning of target in Barnes maze test for learning and memory

Kleiber et al. (2011)

Binge-like injection (trimester 1)

• Delayed achievement of developmental milestones • Increased activity in a novel open field and in a home environment • Impaired learning of target in Barnes maze test for learning and memory

Mantha et al. (2013)

Binge-like injection (trimester 2)

• • • • •

Delayed achievement of developmental milestones Increased activity in a novel open field environment Increased time spent in center of open field Increased time spent in light area of light/dark box Impaired learning and memory of target in Barnes maze test for learning and memory

Mantha et al. (2013)

Binge-like injection (trimester 3)

• • • •

Delayed achievement of developmental milestones Increased activity in a home environment Reduced time spent in center of open field (anxiety-like behavior) Impaired learning and memory of target in Barnes maze test for learning and memory

Mantha et al. (2013)

Developmental and behavioral phenotypes observed following neurodevelopmental alcohol exposure in C57Bl/6 mice via either the continuous preference drinking or binge-like injection model.

The potential for epigenetic features as the mechanism of lasting changes in gene expression has been reviewed in FASD literature (Chokroborty-Hoque et al., 2014; Kleiber et al., 2014; Laufer et al., 2013). In both models, profound changes in whole brain DNA methylation and noncoding RNA (ncRNA) expression may underlie lasting changes in gene expression and behavior (Laufer, Diehal & Singh et al., 2013). More recently, we assessed epigenetic changes in the BLI model in the adult hippocampus, the area of the brain critical for learning and memory, and found altered gene expression, DNA methylation, and histone methylation

(Chater-Diehl, Laufer, Castellani, Alberry, & Singh, 2016). These results argue that FASD is an epigenetic disorder. PAE leaves long-lasting alterations to DNA methylation as a footprint on select gene promoters, often within 50 of approximately 100 imprinted regions of the genome (Laufer et al., 2013). This effect is not random and was repeated under different treatment protocols. It affects imprinted regions harboring sequences interacting with regulatory proteins and ncRNAs. It also affects promoters of major network nodes, such as Pten signaling, that contain transcription repressor CTCF-binding sites and affect cytosine methylation.

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328 TABLE 34.2

34. MATERNAL SEPARATION STRESS IN FETAL ALCOHOL SPECTRUM DISORDERS: A CASE OF DOUBLE WHAMMY

Genetic and Epigenetic Characterization Following Neurodevelopmental Alcohol Exposure in C57BL/6 Mice

Molecular feature

Model (Tissue)

Top affected pathways

Reference

Gene expression

Continuous preference drinking (whole brain)

• Cellular development, tissue development, embryonic development • Free radical scavenging, cellular growth and proliferation • Lipid metabolism, small molecule biochemistry, vitamin, and mineral metabolism

Kleiber et al. (2012)

Binge-like injection trimester 1 (whole brain)

• • • • •

Kleiber et al. (2013)

Binge-like injection trimester 2 (whole brain)

• Fatty acid biosynthesis • Serotonin receptor signaling • Regulation of actin-based motility by Rho

Kleiber et al. (2013)

Binge-like injection trimester 3 (whole brain)

• • • • •

Kleiber et al. (2013)

Binge-like injection trimester 3 (hippocampus)

• Olfactory transduction • Colorectal cancer • Free radical scavenging, gene expression, dermatological diseases and conditions • Cellular development, developmental disorder, hereditary disorder

Chater-Diehl et al. (2016)

Continuous preference drinking (whole brain)

• Cdk5 signaling • Pten signaling • Behavior, neurological disease, and psychological disorders

Laufer et al. (2013)

Binge-like injection trimester 3 (hippocampus)

• Cellular movement, cell death and survival, cellular development • Cell cycle, cellular development, cellular growth, and proliferation • Peroxisome • Lysosome

Chater-Diehl et al. (2016)

Histone modification: H3K27me3

Binge-like injection trimester 3 (hippocampus)

• Endocrine system development and function, molecular transport, protein synthesis • Cancer, skeletal and muscular disorders, tissue morphology • Cellular function and maintenance, inflammatory response, hematological system development • MTOR signaling pathway

Chater-Diehl et al. (2016)

Histone modification: H3K4me3

Binge-like injection trimester 3 (hippocampus)

• Carbohydrate metabolism, molecular transport, small molecule biochemistry • Regulation of cellular mechanics by calpain protease • Fatty acid β-oxidation • Pathways in cancer • Fatty acid metabolism

Chater-Diehl et al. (2016)

DNA methylation

Endoplasmic reticulum stress pathway Xenobiotic metabolism signaling Glucocorticoid receptor signaling Phospholipase C signaling Antiproliferative role of somatostatin receptor 2

Glutamate receptor signaling Retinoic acid mediated apoptosis signaling Ephrin receptor signaling Circadian rhythm signaling One carbon pool by folate

Top pathways implicated by different molecular features assessed in either whole brain or hippocampus following neurodevelopmental alcohol exposure in C57BL/6 mice using either the continuous preference drinking or binge-like injection model.

We conclude that alcohol serves as a potent methylation modifier during prenatal development. This change involves specific sites, genes, and pathways connecting PAE to FASD phenotypes. Next, we assessed the relevance of methylation results on mice in children with an FASD diagnosis. In

a pilot study, we found significant, genome-wide DNA methylation changes in children diagnosed with FASD (Laufer et al., 2015), results later independently replicated (Portales-Casamar et al., 2016). This research represents a breakthrough, with the potential use of cheek-swab DNA as a biological diagnostic tool.

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329

Continuous preference drinking (CPD) model Binge-like injection (BLI) models:

Trimester 1 (gestational days 8 and 11) Trimester 2 (gestational days 14 and 16)

0 P1

P8

P6

P4

6 G1 8 Bi rth P2

2

0

4

G1

G1

G1

G1

G8

G6

G4

G2

M

ati

ng

Trimester 3 (postnatal days 4 and 7)

Day FIGURE 34.2 Visual summary of neurodevelopmental alcohol exposure models in C57Bl/6 mice. The typical gestation period for C57BL/6 mice is 18.5 days. In the continuous preference drinking (CPD) model (orange), pregnant females have the choice between water and 10% ethanol throughout gestation. In the binge-like injection (BLI) models (yellow), pregnant females are injected with ethanol or saline during human trimester 1 or 2 equivalent, or pups are injected during human trimester 3 equivalent.

Known actions of alcohol support this, that is, disrupting the methionine-homocysteine cycle, impairing folate absorption, and conversion of methionine to Sadenosyl methionine, a key methyl donor in the DNA methylation reaction (Halsted, Villanueva, Devlin, & Chandler, 2002; Hamid & Kaur, 2005, 2007; Hamid, Kaur, & Mahmood, 2007). The results discussed in this chapter suggest FASD is like the tip of an iceberg in that neurodevelopmental alcohol exposure effects are not all discernible. There is much more beneath the surface—altered gene expression, DNA methylation, histone methylation—than what is observable. Results generated from our research establish that even a single alcohol exposure can produce profound, lifelong deficits. Various methods and approaches modulate these epigenetic effects. There may be a window during postnatal development to intervene, although this would require early and reliable diagnosis. Further, there is no known safe time or dose of alcohol during pregnancy. Ethanol’s effect on neurodevelopment is dynamic, involving varied mechanisms to orchestrate gene expression changes. This begins early, and may go on for a long time after exposure. Postnatal environment may affect these outcomes, positively or negatively. Here, we focus on postnatal stress by maternal separation, common for babies born with FASD.

CHILDREN WITH FETAL ALCOHOL SPECTRUM DISORDER FACE ADDITIONAL POSTNATAL CHALLENGES An FASD diagnosis in newborns and young children is not easy. Although born to mothers that consumed alcohol during pregnancy, this information is often unavailable or unreliable. Also, while some children exposed to ethanol show characteristic facial features, most are born without diagnostic physical deformities. Any effect of alcohol often manifests over time through delayed developmental milestones. Additionally, for various sociological reasons, such children are not always raised in favorable conditions. Exposure to stress during childhood has lasting effects on adult psychopathology. Clinical studies implicate early life stress with abnormalities in neuroendocrine systems, neurochemicals, physiology, behavior, and neuroimaging (Heim & Nemeroff, 2002). Also, parental mental illness, child abuse, and neglect are among the strongest predictors of mental disorders (Kessler et al., 2010). Timing of stress can lead to different outcomes, likely a result of differential brain maturation rates of underlying stress response regulation (Chaby, Zhang, & Liberzon, 2017). As a result, for the lucky, some outcomes may be manageable, while for others daily life is a burden. Deficits in language, attention, memory,

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intelligence, and behavior are more likely in children following ethanol exposure and traumatic childhood experiences than those with one type of adverse environmental exposure (Price, Cook, Norgate, & Mukherjee, 2017). One common stress in the early years for such children is maternal separation. The mother may find it difficult to offer the best care or children are raised in the absence of the biological mother, often in unstable living conditions. Here, we address the extra impact of maternal separation common in children born with FASD. While FASD is heterogeneous in its manifestation, there is significant comorbidity between PAE and adverse postnatal environments (Coggins, Timler, & Olswang, 2007). Children in childcare systems, such as foster care or orphanages, represent a particularly high incidence group with estimates at 60 per 1000 children diagnosed with FASD (Lange et al., 2013). This is likely due to many factors, including apprehension at birth due to known alcohol use and parental history, but may also be a result of postnatal environment. As compared to children with FASD entering foster care at birth, children with FASD who had lived with their biological parents and then removed as well as having had more foster placements, displayed more severe concentration and hyperactivity deficits (Koponen, Kalland, Autti-Ra¨mo¨, Laamanen, & Suominen, 2013). Also, children prenatally exposed to alcohol and postnatal traumatic experience, such as abuse or neglect, had more severe deficits in language, memory, hyperactivity, impulsivity, and attention than children only traumatized postnatally (Henry, Sloane, & Black-Pond, 2007). By incorporating maternal separation stress into animal models of FASD, we may be able to further our understanding of its manifestation in humans.

MODELING MATERNAL SEPARATION IN RODENTS Early, postnatal maternal separation in rats has diverse and lasting behavior effects, hormone response, and corticotropin-releasing factor gene expression in various brain regions (Plotsky & Meaney, 1993; Plotsky et al., 2005). Like rats, maternal separation in mice leads to altered fear and anxietylike responses (Romeo et al., 2003). We subjected mice to maternal separation by isolating them for 3 hours per day from postnatal days 2 to 14 (Alberry & Singh, 2016). Mouse pups that had undergone maternal separation weighed less than controls, following earlier reports (Savignac, Dinan, & Cryan, 2011). Using the Barnes Maze test for learning and memory, we found significant effects of maternal separation and sex (Alberry & Singh, 2016). Sex differences in response to

stress are common in rodent literature, with underlying differences in brain development. Females have shown decreased hippocampal neurogenesis following maternal separation, while males show no decrease, or even a reported increase (Loi, Koricka, Lucassen, & Joe¨ls, 2014; Oomen et al., 2009). Next, we examined how maternal separation may exacerbate phenotypic alterations following PAE. We examined pup growth and survival, activity and anxiety-like behaviors, as well as learning and memory using the CPD model and daily maternal separation (Alberry & Singh, 2016). While we identified PAE and maternal separation effects on pup growth and survival, results were modest and no significant interaction between treatments was observed. This may be a result of mild forms of alcohol and stress exposure paradigms used. Investigations into learning and memory using the Barnes Maze Test also presented complex results. We found significant main effects of sex, alcohol exposure, and maternal separation on latency to find the target hole. Females were faster than males, mice exposed to alcohol were slower than controls, and mice that had undergone maternal separation were slower than controls. While we found interactions between sex and ethanol exposure, as well as between day of testing, sex, and maternal separation, we found no significant interaction between treatments. Learning delays are hallmarks of FASD mouse models, independent of exposure paradigm (Allan, Goggin, & Caldwell, 2014; Berman & Hannigan, 2000; Chokroborty-Hoque et al., 2014; Hamilton et al., 2014; Lilliquist, Highfield, & Amsel, 1999; Livy, Miller, Maier, & West, 2003; Murawski, Jablonski, Brown, & Stanton, 2013; Wagner, Zhou, & Goodlett, 2014). Learning takes longer in individuals diagnosed with FASD, and is affected by repetition (Engle & Kerns, 2011). In the Barnes Maze, mice use repetition to learn target hole location—PAE mice were still able to learn location, but at a slower rate than control mice. While these are subtle deficits, accumulation of subtle learning deficits over time may impact a child, particularly when faced with a poor environment. We note that although PAE and maternal separation result in learning impairments, they had no measured effect on memory (Alberry & Singh, 2016). Although such results follow previous work in separated rats (Oomen et al., 2010), they remain unexplained. While studies examining maternal separation following PAE are very few, we are not the only group to examine the combination of PAE and early life stress. Recent results combining PAE with early life stress via limited availability of nest material in rats found marked changes in immune function (Raineki et al., 2017). Suppression of these immune factors following early life stress, but not in combination with PAE, is a

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REFERENCES

novel avenue to pursue in understanding the varied behavioral phenotypes.

Neurodevelopment Brain and nervous system development, including new neuron formation, migration, and synapse establishment. Prenatal alcohol exposure Any instance of ethanol exposure during prenatal development, represented by maternal alcohol consumption in humans and mice, or ethanol injection in animal models.

IMPLICATIONS FOR TREATMENTS The effect of alcohol in this chapter deals with a model of FASD using C57BL/6 mice. Varied treatment protocols included lead to phenotypes in the resulting offspring that are comparable to FASD. These same phenotypes are worsened by postnatal maternal separation. Such results argue that the brain development continuum is subject to additional stresses and is amenable to the external environment. Consequently, the severity of manifestation in FASD phenotypes could be reduced by improved postnatal care. Additionally, a more enriched environment may have the potential to improve outcomes.

KEY FACTS Fetal Alcohol Spectrum Disorder • PAE can result in FASD, representing one of the few forms of intellectual disability with a known cause. • FASD is characterized by neurological, physical, developmental, and behavioral deficits. • FASD affects approximately 2% 3% of newborns. • Obtaining a diagnosis is challenging, with no reliable biomarkers. • No cure or specific treatment exists for this devastating disorder.

CONCLUSION Children born with FASD are not always raised in a favorable environment, and often end up in foster care systems. These children show delayed developmental milestones, including deficits in language, attention, memory, and intelligence. Often results are attributed to PAE, with no consideration for postnatal environment. This chapter addresses how adverse postnatal environment may increase manifestation of FASDrelated deficits. In experiments outlined with mouse models, minor maternal separation results in deficits of activity, anxiety-like behavior, and learning. Also, maternal separation following PAE has additional adverse effects. In no case was the effect of PAE improved following maternal separation. This effect of maternal separation compounds on prenatal experience, supporting the suggestion that mammalian brain is vulnerable to environmental factors during postnatal development. Any evidence that postnatal environment influences the effect on the child may improve the severity of the manifestation. Moreover, we recommend avoidance of any extra stresses during postnatal development, independent of PAE.

MINI-DICTIONARY OF TERMS Epigenetics Heritable changes in gene expression without changes in underlying DNA sequence. Fetal alcohol spectrum disorder Umbrella term referring to the set of abnormal conditions resulting from maternal alcohol consumption during pregnancy. Maternal separation An early, postnatal environmental stress or represented by reduced time spent with the biological mother.

SUMMARY POINTS • Children with FASD face adverse developmental environments. • Extra stress during neurodevelopment impacts behavior. • In mice, PAE and maternal separation result in learning deficits. • More research on the effects of the postnatal environment on children with, and without, FASD is necessary. • Evidence that the postnatal environment may affect FASD outcomes suggests intervention potential.

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35 Impulsivity and Binge Drinking: A Neurocognitive Perspective Pierre Maurage1, Se´verine Lannoy1, Mickael Naassila2, Benjamin Rolland3,4 and Joe¨l Billieux5 1

Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Universite´ catholique de Louvain, Louvain-la-Neuve, Belgium 2INSERM UMR1247, GRAP, CURS, University of Picardie Jules Verne, Amiens, France 3UCBL, CRNL, INSERM U1028, CNRS UMR5292, Universite of Lyon, Lyon, France 4 UP-MOPHA Department, Le Vinatier Hospital Centre, University Service of Addictology of Lyon (SUAL), Bron, France 5Addictive and Compulsive Behaviours Lab (ACB-Lab), Institute for Health and Behaviour, University of Luxembourg, Esch-sur-Alzette, Luxembourg

LIST OF ABBREVIATIONS AUD BD UPPS

alcohol-use disorders binge drinking urgency, lack of premeditation, lack of perseverance, sensation seeking

BINGE DRINKING AS A HARMFUL ALCOHOL-CONSUMPTION PATTERN The excessive consumption of alcohol constitutes a critical public health problem, as alcohol is the substance presenting the most harmful consequences (Nutt, King, Phillips, & Independent Scientific Committee on Drugs, 2010). However, studies exploring alcohol-related problems have long focused on severe alcohol-use disorders (AUD), with the implicit proposal that the main consequences of alcohol only appear after long-term excessive consumption. During the past decade, several studies have cast doubt on this proposal, by showing that even moderate consumption can lead, in the long run, to durable cognitive or brain effects (Anderson, Nokia, Govindaraju, & Shors, 2012), and by observing that, aside from severe AUD, other consumption patterns can rapidly lead to psychological or cognitive repercussions. Among those, binge drinking (BD) occupies a central position as it constitutes a widespread

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00035-0

phenomenon (Archie, Zangeneh Kazemi, & AkhtarDanesh, 2012) leading to rapid effects, even though criteria for AUD are often not met in this population (Rolland & Naassila, 2017). BD is an alcohol-consumption mode characterized by excessive, but episodic, intakes, with the absorption of large quantities in short periods to rapidly reach drunkenness (Townshend & Duka, 2002). Quantitative definitions of BD are strongly varying across countries, the most frequent threshold stating that a consumption of more than four to five 14 g alcohol doses (for women and men, respectively), in 2 hours at least once per month during 6 months, qualifies the individual as a binge drinker. This pattern, classically observed among student populations, has largely expanded toward adolescents (Jang, Patrick, Keyes, Hamilton, & Schulenberg, 2017) and now concerns around 40% of people between 15 and 24 years of age. Despite the omnipresence of BD, the exploration of its long-lasting consequences, beyond the well-known acute consumption risks, has only emerged recently. This research field has allowed the exploration of personal, cognitive, social, and cerebral abilities, leading to coherent results: BD is associated with persistent deficits, including reduced school or professional performance, increased mood disorders and altered interpersonal relations (Kuntsche, Kuntsche, Thrul, &

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Gmel, 2017). BD is also related to neurobiological impairments, including altered brain structure (particularly in hippocampal and prefrontal regions) and modified brain functioning (Hermens et al., 2013). These cerebral explorations have been reinforced by neuropsychological studies detecting important deficits in BD for visuospatial, attentional, memory, or executive abilities. Such evidence gathered through neuropsychology and neuroscience led to considering the potential role of impulsivity in BD, as impulsivity is central in substance abuse and linked to a wide range of cognitive deficits involved in the etiology of addictions, like executive functions or decision-making impairments (Dick et al., 2010). Addictive disorders can indeed be conceptualized as primarily relying on impulsive thoughts and behaviors toward the substance, related to low inhibitory abilities, and reduced consideration of long-term consequences (Jentsch et al., 2014). However, various models, definitions, and measures of impulsivity have been used in BD, and these scattered explorations have hampered obtaining a comprehensive overview of impulsivity’s involvement. In the following sections, we will capitalize on a wellestablished impulsivity model (Whiteside & Lynam, 2001) to provide a theoretically grounded overview of this process in BD, before underlining the research avenues needed to clarify several key questions in this field.

A MULTILEVEL CONCEPTUALIZATION OF IMPULSIVITY IN BINGE DRINKING Impulsivity is the tendency to express unplanned, premature, or excessive behaviors, without taking into account their riskiness or inappropriateness; these behaviors frequently lead to delayed negative

consequences (Evenden, 1999). From the first psychological conceptualizations (Eysenck, 1967), theoretical models have considered impulsivity as a multidimensional ability encompassing dissociable cognitive, affective, and motivational processes. Capitalizing on these initial works, Whiteside and Lynam (2001) have proposed an integrative model identifying four impulsivity subcomponents (Fig. 35.1), namely Urgency (positive and negative), lack of Premeditation, lack of Perseverance, and Sensation seeking (UPPS model). Large-scale studies in healthy populations have confirmed the validity of this model by demonstrating that the four subcomponents are simultaneously interrelated (and thus part of a common umbrella concept of impulsivity) and separable (justifying this multicomponent approach). Moreover, this model has been widely used to explore the specific links between each subcomponent and addictive states (e.g., Dick et al., 2010). UPPS thus constitutes an ideal framework for a theoretically grounded description of impulsivity in BD. We will offer an integrative neurocognitive perspective of impulsivity among binge drinkers, first by showing that increased self-reported impulsivity in BD has been documented for all UPPS subcomponents, but also that differences exist regarding the links between subcomponents and drinking characteristics. Then, capitalizing on studies linking UPPS subcomponents and experimental tasks (Rochat, Billieux, Gagnon, & Van der Linden, 2017; Fig. 35.1), we will extend this description to behavioral and neuroimaging studies using neuropsychological measures to evaluate the UPPS subcomponents. First, higher levels of urgency characterize binge drinkers compared to low or nondrinkers in most studies using the UPPS questionnaire (Coskunpinar, Dir, & Cyders, 2013). High urgency (and particularly negative urgency) is the strongest predictor for severe AUD in

UPPS model Urgency

Lack of premeditation

Lack of perseverance

Sensation seeking

Main characteristics

Tendency to act rashly in intense emotional contexts

Difficulty to plan behaviors and consider their consequences

Difficulty to maintain attention on a task

Propensity to look for new and exciting experiences

Cognitive mechanisms

Prepotent response inhibition

Decision-making Delay Response

Resistance to proactive and distractor interference

Reward/Punishment sensitivity

Experimental tasks

Go/No-Go Task Stop-Signal Task

Iowa Gambling Task Delay Discounting Task

Recent Negative Task Flanker Task

Balloon Analogue Risk Task Learning Reinforcement Task

Brain correlates

Inferior frontal gyrus Anterior cingulate Amygdala, Insula

Dorsolateral and ventromedial prefrontal cortex Amygdala, Insula

Lateral and anterior prefrontal cortex

Prefrontal and orbitofrontal cortex Basal gangila, Insula

FIGURE 35.1 Presentation of the four UPPS model’s subcomponents. Description of the four impulsivity subcomponents, their underlying cognitive mechanisms, the experimental tasks used to measure them, and their brain correlates. Source: Adapted from Rochat, L., Billieux, J., Gagnon, J., & Van der Linden, M. (2017). A multifactorial and integrative approach to impulsivity in neuropsychology: Insights from the UPPS model of impulsivity. Journal of Clinical and Experimental Neuropsychology, 11, 1 17.

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A MULTILEVEL CONCEPTUALIZATION OF IMPULSIVITY IN BINGE DRINKING

youth (Tomko, Prisciandaro, Falls, & Magid, 2016). Elevated urgency would, thus, be centrally involved in the transition from BD to severe AUD, and is the pivotal impulsivity subcomponent involved in alcoholrelated problems. At the experimental level, urgency appears strongly related to prepotent response inhibition (Wilbertz et al., 2014), the ability to cancel or suppress a dominant or automatic response. This executive function is usually measured with tasks like the Go/No-Go or Stop-Signal (Fig. 35.2), and results obtained in BD have confirmed the role played by urgency: binge drinkers present reduced inhibitory control, characterized by increased commission errors; this impairment being proportional to BD habits’ intensity (Lo´pez-Caneda, Rodrı´guez Holguı´n, Cadaveira, Corral, & Doallo, 2014). Recent results (Czapla et al., 2015) have also suggested that this impairment might be particularly present when inhibition has to be performed on alcohol-related stimuli. Neurobiological studies have extended these results by showing abnormalities in the electrophysiological correlates of inhibitory processes, suggesting that binge drinkers have slower brain responses and need higher brain activations to inhibit their behaviors (Lo´pezCaneda et al., 2012). Longitudinal results have moreover suggested that these deficits are present before the emergence of BD habits, and are then aggravated by alcohol neurotoxicity (Wetherill, Squeglia, Yang, & Tapert, 2013). As a whole, and despite some contradictory results (e.g., Bø, Aker, Billieux, & Landrø, 2016), a relatively coherent pattern of results emerge from selfreported, behavioral, and neuroscience data: BD is associated with higher urgency, related to a reduced cognitive and cerebral ability to inhibit dominant or automatic responses.

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Second, a meta-analysis showed that increased lack of premeditation is associated with earlier alcohol-use initiation and more intense BD habits (Stautz & Cooper, 2013). BD habits could, thus, emerge in adolescents with low premeditation due to their inability to take into account upcoming consequences of uncontrolled alcohol intakes, which might favor the emergence of AUD (Coskunpinar et al., 2013). This diminished premeditation can be evaluated using decision-making or delaying response tasks. Regarding decision-making, the most used task in BD is the Iowa Gambling Task (Fig. 35.3A), where participants have to maximize their gains by choosing a strategy avoiding short-term gratifications to promote long-term ones. Initial results (Goudriaan, Grekin, & Sher, 2011) identified reduced decision-making abilities in BD and a predictive value of this impairment for the persistence of BD habits. Neuroimaging data (Xiao et al., 2013) also showed that these deficits were subtended by over-activations in the limbic system, but more recent results (Bø, Billieux, Gjerde, Eilertsen, & Landrø, 2017) have not confirmed this decisionmaking deficit in BD; the current literature, thus, indicates mixed findings. Delayed response is explored using Delay Discounting Task (Fig. 35.3B), where participants have to choose between small, immediate rewards and delayed, larger ones, adolescent binge drinkers presenting a tendency to favor short-term rewards (indicating impulsive response), particularly when alcohol consumption started at an early age (Kollins, 2003). Furthermore, longitudinal results showed a progressive increase of this trend to devaluate delayed rewards during the expansion of BD (Jones, Steele, & Nagel, 2017). However, decisionmaking and delaying response impairments were not

FIGURE 35.2 Illustration of two tasks related to urgency and measuring prepotent response inhibition. In the Go/No-Go Task (Part A), participants have to react when a target is presented (e.g., here, press when a “X” appears) but to inhibit reaction when another target is presented (e.g., here, a “O”). In the Stop-Signal Task (Part B), participants have to perform a binary decision task on targets (e.g., here, deciding whether the name presented is an animal or an object), but have to refrain answering when a sound (the Stop-Signal) is presented right after the target.

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FIGURE 35.3 Illustration of two tasks related to the lack of premeditation and respectively measuring decision-making and delay response abilities. In the Iowa Gambling Task (Part A), participants receive an amount of money and are asked to pick up cards from four desks to earn more money. In each trial, participants choose a card from one deck, each card leading to a gain and/or a loss. Two decks (A and B, unfavorable decks) lead to high gains but also high losses, with a negative total in the long term, while the two others (C and D, favorable decks) lead to lower gains but reduced losses, with a positive total in the long term. Participants are not aware of these gain/loss ponderations between the decks, and have to progressively infer them and sharpen their decision-making to maximize gains, by privileging long-term, low gains rather than short-term, high ones. In the Delay Discounting Task (Part B), participants have to choose, for each trial, between an immediate but small reward and a delayed but higher reward, thus evaluating delay discounting (i.e., the tendency to reduce gratification delay by choosing short-term rewards).

correlated with self-reported lack of premeditation, casting doubt on the correspondence between selfreported and experimental measures and leading to the conclusion that, while the lack of premeditation is established by self-reported measures in BD, its evaluation using specific experimental tasks has to be improved. Third, the lack of perseverance appears centrally related to the switch from BD to alcohol-related problems, but does not strongly predict the intensity of current BD habits (Magid & Colder, 2007). Binge

drinkers who lack perseverance might have reduced academic and personal goals, and would, thus, be less sensitive to the negative impact of excessive alcohol consumption on these goals, resulting in unregulated drinking habits (Tomko et al., 2016). This impulsivity subcomponent is related to the resistance to proactive and distractor interference (Gay et al., 2010), where participants respectively have to inhibit previously encoded (e.g., Recent Negative Task, Fig. 35.4A) or currently available, but nonpertinent (e.g., the Eriksen Flanker Task, Fig. 35.4B) information. BD does not

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FIGURE 35.4

Illustration of two tasks related to the lack of perseverance and respectively measuring resistance to proactive and distractor interference. In the Recent Negative Task (Part A), three words successively appear. Then, a fourth word appears and participants have to say whether this word was among the three presented before. Proactive interference occurs when a word has not been presented in the current trial, but has been presented in the previous one (e.g., here, “red,” already presented in Trial 1, provokes proactive interference in Trial 2). In the Eriksen Flanker Task (Part B), participants have to make a binary decision on a central target (e.g., here, decide whether the central arrow is pointing left or right) while ignoring flankers (e.g., here, the arrows located on the left or right), which can be identical (congruent trials) or opposite (incongruent trials, leading to distractor interference) to the target.

appear associated with a deficit in resistance to proactive interference, but is conversely marked by an increased difficulty to resist distractor interference (Lannoy, D’Hondt, Dormal, Billieux, & Maurage, 2017; Lannoy et al., 2017). At the cerebral level, this deficit appears to rely on impaired electrophysiological activity related to early attentional engagement, followed by a compensatory increased attentional control (Connell, Danzo, & Dawson, 2018). Fourth, regarding sensation seeking, this subcomponent is mainly related to drinking frequency and intensity (Curcio & George, 2011), and is, thus, the central predictor of current BD habits, with the proposal that high sensation seekers will need more alcohol intakes to obtain their desired stimulation level. Sensation seeking is related to reward/punishment sensitivity, notably measured by the Balloon Analogue Risk Task (Fig. 35.5A). Mixed results have been obtained in BD; some studies showing that increased reward sensitivity (i.e., increased risktaking to obtain higher reward) predicted BD (Fernie, Cole, Goudie, & Field, 2010), while others detected no differences with controls (Lannoy et al., 2017). These discrepancies might rely on the fact that this task is not a pure reward sensitivity measure, as it also relies on more global inhibition abilities. Another reward sensitivity task is the Learning Reinforcement Task (Fig. 35.5B), which allows to dissociate reward and punishment sensitivity. While BD might be related to reduced punishment sensitivity underlid by modified frontal activations (Worbe et al., 2014), this paradigm has not been used in BD and the dissociation between reward and punishment sensitivity remains to be explored.

ONE STEP BEYOND: FRAMING FUTURE RESEARCH ON IMPULSIVITY IN BINGE DRINKING Contrasting evidence emerges from the available data on impulsivity in BD: BD is associated with higher selfreported impulsivity, showing specific relations between UPPS subcomponents and alcohol-consumption characteristics, as well as modifications in the cognitive and motivational functions related to impulsive behaviors. However, while we presented neuropsychological and neuroscience data using the UPPS framework, the literature currently presents massive limitations, centrally related to the absence of robust and specific links between self-reported impulsivity subcomponents and experimental measures: UPPS subcomponents are most often intricated in impulsivity experimental tasks (e.g., prepotent response inhibition is related to urgency, but also lack of premeditation; decision-making is linked to lack of premeditation, but also urgency and sensation seeking, Rochat et al., 2017). Globally, the links between self-reported and experimental measures remain weak; self-reported questionnaires and laboratory tasks not measuring isomorphic constructs. A central aim for future research will, thus, be to develop experimental tasks which are specific to each impulsivity subcomponent. A first step forward would be to more precisely define which cognitive, affective, and motivational processes are uniquely underlying each UPPS subcomponent, by joining personality psychology (i.e., the initial UPPS framework), cognitive psychology (identifying the core cognitive components involved), and neurosciences (specifying the brain correlates of impulsivity, Fig. 35.1). At the experimental

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FIGURE 35.5 Illustration of two tasks related to sensation seeking and measuring reward/punishment sensitivity. In the Balloon Analogue Risk Task (Part A), participants have to pump a balloon to obtain a reward. Each pump either increases balloon’s size (and the related reward; positive feedback) or bursts the balloon (leading to the loss of the cumulated points; negative feedback). The probability of balloon burst increases with each pump. After each pump, participants have to choose between collecting points or pumping again. In the Learning Reinforcement Task (Part B), participants first take part in a training phase in which Hiragana symbols are repeatedly presented in three pairs (A B; C D; E F), participants have to choose one of the two symbols for each trial, which leads to a feedback (“correct”/“incorrect”). While initially choosing randomly, participants progressively learn that each symbol is associated with a probability of positive feedback (80% 20% 70% 30% 60% 40% for A B C D E F symbols, respectively). Then a testing phase starts, based on the same symbols but reorganized pairs (e.g., A C; B D), which allows to evaluate whether participants have mostly learned using negative or positive feedbacks, by measuring the frequency of A versus B symbol selection. Indeed, participants learning through positive feedbacks will mostly choose the “A” symbol (related to most positive feedbacks in the learning phase), indicating high-reward sensitivity, while participants learning through negative feedbacks will mostly avoid choosing the “B” symbol (related to most negative feedbacks in the learning phase), indicating high-punishment sensitivity.

level, this multidisciplinary approach could help understanding the links between impulsivity and other core cognitive deficits in BD (Hermens et al., 2013). At the fundamental level, understanding the processes underlying impulsivity would allow implementing this

concept in addiction models (e.g., dual-process models, Stacy & Wiers, 2010), and particularly determining whether impulsive behaviors are centrally related to under-activated prefrontal/cognitive system, as proposed in most studies, or to over-activated limbic/

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KEY FACTS

automatic system, as recently suggested for negative urgency (Chester, Lynam, Milich, & DeWall, 2016). Beyond this need to offer a more integrated exploration of impulsivity in BD, the role of several other factors should be clarified, particularly concerning: 1. Drinking motivations: The relation between impulsivity and BD has been considered as direct but other variables could play a mediating role, among which are drinking motives. Indeed, mediational analyses (Adams, Kaiser, Lynam, Charnigo, & Milich, 2012) have shown that the links between impulsivity and BD are mediated by coping (i.e., drinking to reduce negative emotions) and enhancement (i.e., drinking to increase positive emotions) motives. More globally, impulsivity should not be seen as an isolated phenomenon in its relation with alcohol consumption, but should be considered together with key psychological variables (e.g., expectancies, interpersonal relations, contextual factors) strongly determining drinking habits. 2. Preexisting versus alcohol-induced modifications: Earlier studies based on cross-sectional data were unable to explore the causal link between BD and impulsivity. While BD has obvious harmful consequences on cognitive and brain functioning (negatively impacting impulsivity through alcohol neurotoxicity), an impulsive background (Brumback et al., 2016) might facilitate the emergence of BD. Large-scale longitudinal explorations are needed to clarify this causal relation, and to understand the transition (potentially favored by urgency and lack of perseverance) between BD and severe AUD, suggested by the continuum hypothesis (Enoch, 2006). The differential brain consequences of BD versus other intense alcohol-consumption modes (e.g., social/heavy drinking) and the variation of these deficits according to age, gender, and BD intensity/frequency should also be further explored. 3. Interindividual variability: The variation of BDimpulsivity links according to individual traits and alcohol-related characteristics has been explored, but binge drinkers have mostly been considered as a unitary population. However, cluster approaches (Lannoy, Billieux, Poncin, & Maurage, 2017) have shown that impulsivity subcomponents are not homogeneously distributed in BD; some subgroups presenting a global impulsive profile while others only display increased lack of premeditation and perseverance, or conversely elevated urgency and sensation seeking. Future work should, thus, consider this heterogeneity by complementing their groupbased comparisons with cluster or individual analyses. 4. Correlation with clinical severity and outcomes: Only few studies assessed the Diagnostic and Statistical

Manual of Mental Disorders (DSM-IV-Tr or DSM-5) criteria for AUD in BD. In one study (Beseler, Taylor, Kraemer, & Leeman, 2012), increased impulsivity was found among binge drinkers presenting higher alcohol-use severity (i.e., those meeting DSM-IV-Tr criteria for alcohol dependence). High impulsivity could, thus, constitute a significant severity feature in BD. Future studies should determine whether people with BD and elevated impulsivity (but not currently fulfilling criteria for AUD), are more at risk to subsequently develop such criteria. Finally, an important further step will be to implement research results into prevention and clinical practices. While young people do not usually consider their BD as problematic, global information programs underlining the rapid cognitive and brain consequences of this pattern are needed, together with prophylactic interventions reducing these deficits. Validated psychological interventions have been proposed, notably using motivational interviewing or implementation intention to increase emotional/ cognitive self-control and, thus, reduce BD (Norman & Wrona-Clarke, 2016), but they do not focus on specific processes and have limited efficiency. More innovative therapeutic proposals, capitalizing on the recent blooming of neuropsychological remediation in AUD should, thus, be proposed to directly target the cognitive processes related to increased impulsivity.

MINI-DICTIONARY OF TERMS Impulsivity An umbrella concept covering a wide range of behaviors which are poorly planned, excessively expressed, and unnecessary risky, often leading to negative personal or interpersonal repercussions. Lack of perseverance The difficulty to maintain one’s attentional and cognitive focus on a task or goal which might be hard, long, or boring. Lack of premeditation The difficulty to plan one’s behaviors or to think about the consequences of an action before performing it. Sensation seeking The propensity to look for thrilling and unconventional life experiences, despite their riskiness. Urgency The tendency to produce rash behavioral responses when facing intense positive or negative emotional states.

KEY FACTS Cognitive Impairments in Binge Drinking • BD is the most frequent alcohol-consumption pattern in youth. It is characterized by repeated alternations between massive alcohol intakes and withdrawal periods.

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• While short-term consequences related to acute alcohol consumption (e.g., road accidents and uncontrolled behaviors) are established, its midterm and long-term effects on physical and mental health have only been explored recently. • BD is associated with large-scale and persisting negative effects on attention, memory, and executive functions (e.g., planning, inhibition, and decisionmaking), as well as with reduced and disorganized brain activity. • Some impairments might be present before BD and favor its emergence, but most deficits result from excessive alcohol consumption. • These cognitive deficits should be addressed by prophylactic and therapeutic programs as they play a role in the extension of BD habits.

SUMMARY POINTS • This chapter reviews current data measuring the links between impulsivity and BD. • BD is usually described as being related to strong impulsivity leading to uncontrolled alcohol-use; however, impulsivity has been explored using a large range of conceptual frameworks and techniques, leading to scattered data. • We capitalized on the UPPS model, distinguishing four impulsivity subcomponents (urgency, lack of premeditation, lack of perseverance, and sensation seeking), to review psychological, cognitive, and neuroscience results regarding impulsivity in BD. • BD is related to increased self-reported impulsivity for all subcomponents, but current BD habits are mostly determined by strong lack of premeditation and high sensation seeking, while the presence of alcohol-use problems mostly rely on intense urgency and lack of perseverance. • Neuropsychological and neuroscience results have also shown impaired performance and modified brain activations during tasks related to each subcomponent in BD, but the correspondence between impulsivity subcomponents and related cognitive functions remains to be fully understood. • Future studies should also explore the interactions between impulsivity and other key factors in BD, as well as the causal links between BD and impulsivity disorders.

Acknowledgments PM is a research associate and SL is a research fellow at the Fund for Scientific Research (F.R.S.-FNRS, Belgium). This chapter has been supported by a grant from the “Fondation pour la Recherche en Alcoologie” (FRA, France).

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C H A P T E R

36 Acetaldehyde and Motivation Anna Brancato and Carla Cannizzaro Department of Sciences for Health Promotion and Mother and Child Care “G. D’Alessandro” University of Palermo, Palermo, Italy

LIST OF ABBREVIATIONS VTA NAc DA CPP AT SAL

ventral tegmental area nucleus accumbens dopamine conditioned place preference 3-amino-1,2,4-triazole salsolinol

INTRODUCTION In the past decade, a large body of evidence has shown that alcohol is not the solo player on the stage of its multiple biological actions. Rather, the products of alcohol biotransformation, primarily acetaldehyde, contribute to its mechanism of action with its own behavioral and neuropharmacological effects. As the first metabolite of alcohol, acetaldehyde is produced soon after the consumption of alcoholic beverages by the action of alcohol dehydrogenase, cytochrome P450-2E1, and catalase—enzymatic systems that have tissue-specific expression (Cohen, Sinet, & Heikkila, 1980; Edenberg, 2007; Ramchandani, Bosron, & Li, 2001). Depending on alcohol doses and modalities of administration, peripheral acetaldehyde can cross the blood brain barrier and potentially add to that which is locally produced (Heap et al., 1995; Jamal et al., 2016; Plescia et al, 2014; Plescia et al., 2015a; Quertemont, Tambour, Bernaerts, Zimatkin, & Tirelli, 2004; Tabakoff, Anderson, & Ritzmann, 1976; Ward, Colantuoni, Dahchour, Quertemont, & De Witte, 1997). However, acetaldehyde motivational properties have a multifaceted nature. Acetaldehyde naturally occurs in alcoholic beverages and confers to ciders, fortified wines, and spirits a distinctive flavor (Lachenmeier, Gill, Chick, & Rehm, 2015). This is likely Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00036-2

to contribute to chemosensory attributes of alcoholic drinks, which are reported as especially effective at eliciting craving and drug-seeking responses in alcoholexperienced individuals (Filbey et al., 2008; Kareken et al., 2004; Yamamoto, 2009). In this regard, acetaldehyde directly activates the sensory neuronal TRP channels TRPA1 that are relevant for taste and chemesthesis (Bang, Kim, Yoo, Kim, & Hwang, 2007; Roper, 2014). The chemosensory information gains immediate access to the central nervous system and influences limbic forebrain and cortical areas involved in controlling ingestive motivation and consummatory behavior. Either as a drinking component or as an alcohol bioproduct, acetaldehyde possesses stimulating effects on brain areas that control reward and motivation, that is, ventral tegmental area (VTA) or nucleus accumbens (NAc), leading to positive reinforcement and induction of dependence (Cavallaro et al., 2016; Cannizzaro, Plescia, & Cacace, 2011; Plescia et al., 2015b). This chapter will present evidence showing that acetaldehyde exerts rewarding and motivational properties that play a functional and specific role in the development of alcohol abuse and alcoholism. In more detail, studies that employed behavioral paradigms are able to highlight acetaldehyde’s motivational effects, and the specific involvement of relevant neurotransmissions will be taken into account (Fig. 36.1 and Table 36.1).

ACETALDEHYDE HAS ITS OWN MOTIVATIONAL PROPERTIES Acetaldehyde’s own reinforcing properties were first shown in conditioned place preference (CPP)

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FIGURE 36.1 Behavioural tests that highlight the motivational properties of acetaldehyde. As alcohol does, acetaldehyde (ACD) per se induces CPP for paired environment and cues, is voluntarily self-administered in a two-bottle choice-drinking paradigm and induces and maintains operant behavior in an operant conditioning paradigm.

paradigm, a widely used behavioral procedure where animals show increased preference for environmental cues paired with a rewarding experience and drugs of abuse. Laboratory rats that received intracerebroventricular acetaldehyde infusions showed increased preference for environmental cues paired with the drug administration (Smith, Amit, & Splawinsky, 1984). A strong preference for acetaldehyde-paired environment and stimuli was also observed when the administration was either intraperitoneal or oral (Peana et al., 2007; Quertemont & De Witte, 2001). Spina et al. (2010) demonstrated that acetaldehydeinduced CPP was critically controlled by dopamine (DA) transmission, since the blockade of D1 receptors

during acetaldehyde conditioning, prevented the acquisition of CPP. The reinforcing properties of acetaldehyde have been more specifically explored by the employment of self-administration paradigms in rats, where the amount of the drug consumed is suggestive of the drug’s rewarding properties. As alcohol does, acetaldehyde is voluntarily self-administered in a two-bottle choice-drinking paradigm and its consummatory behavior was dose-dependent in that acetaldehyde intake increased when a higher solution strength was provided (Brancato, Plescia, Lavanco, Cavallaro, & Cannizzaro, 2016; Cacace, Plescia, La Barbera, & Cannizzaro, 2011; Plescia et al., 2015a). The flavor and taste of the acetaldehyde solution have been proposed to take part in the reinforcing properties and may actually serve as conditioned stimuli of its postingestional effects (Brancato, Lavanco, Cavallaro, Plescia, & Cannizzaro, 2017; Cannizzaro et al., 2011). Motivational and activating effects of drugs are primarily assessed by operant conditioning, in which animals are trained to emit a specific response (lever press or nose poke) to gain the reinforcement. Operant behavior for acetaldehyde was readily acquired by rats, both through intracerebroventricular and intravenous routes of administration (Brown, Amit, & Rockman, 1979; Myers, Ng, Marzuki, Myers, & Singer, 1984). Furthermore, in the intracranial self-administration paradigm, whereby rats receive response-contingent drug infusions in a discrete brain region, rats readily self-administer acetaldehyde into the VTA (Rodd et al., 2003; Rodd et al., 2005). Specifically within the VTA, acetaldehyde activates DA neurons by significantly increasing their firing rate, similarly to alcohol (Deehan, Engleman, Ding, McBride, & Rodd, 2013; Foddai, Dosia, Spiga, & Diana, 2004). Also, DA neurons within the posterior VTA exhibit a significantly greater sensitivity to acetaldehyde than to alcohol, so that 23 µM acetaldehyde is effective at significantly increasing DA efflux within the NAc shell to levels 200% above baseline (Rodd et al., 2005). Besides, when the acetaldehyde solution is delivered in operant drinking paradigms, acetaldehyde induces and maintains operant behavior according to fixed and progressive ratios of reinforcement (Cacace, Plescia, Barberi, & Cannizzaro, 2012; Peana, Muggironi, & Diana, 2010).

ACETALDEHYDE INDUCES AN ADDICTIVE PHENOTYPE Apart from drug taking, the operant conditioning paradigm enables researchers to explore discrete features of addictive-like behavior, modeling the

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TABLE 36.1 Behavioral Correlates of Acetaldehyde’s Motivational Properties Conditioned place preference

Preference for ACD-paired environment and cues

Smith et al. (1984) Quertemont and De Witte (2001) Peana et al. (2007)

Self-administration

Consummatory behavior in two-bottle choice ACD drinking paradigm

Plescia et al. (2015a)

Operant conditioning

Emission of specific responses (lever-press or nose poke) for gaining ACD delivery

Brown et al. (1979) Myers et al. (1984) Rodd et al. (2003) Peana et al. (2010) Cacace et al. (2012)

Acetaldehyde (ACD) contributes to alcohol’s neuroactive effects through its own motivational properties unveiled in CPP test, selfadministration paradigm, and operant conditioning.

diagnostic criteria established for humans (American Psychiatric Association, 2013). Indeed, different schedules of drug reinforcement critically model distinct aspects of incentive motivation for the drug, such as drug-seeking and relapse following periods of abstinence and use despite adverse consequences, which constitute central issues of the translational research on addiction. The employment of such tailored paradigms showed that acetaldehyde acts as a positive reinforcement that elicits challenging behavior, such as cravings and relapse, as shown for alcohol. Indeed, acetaldehyde-drinking rats displayed resistance to extinction—that is, the emission of a high number of operant responses when reinforce delivery was withheld—and a powerful deprivation effect when acetaldehyde availability was resumed after repeated cycles of deprivation (Brancato et al., 2014; Cacace et al., 2012; Peana et al., 2010; Plescia, Brancato, Marino, & Cannizzaro, 2013). DA transmission was proven to affect the acetaldehyde-induced addicted phenotype. Indeed, when low doses of a D2-DA receptor agonist, which preferentially activated presynaptic D2-DA autoreceptors, were administered systemically in order to decrease acetaldehyde-induced DA release, rats reduced the number of lever presses for acetaldehyde, also during extinction and, after acetaldehyde deprivation, during relapse (Brancato et al., 2014; Rodd et al., 2005) (Fig. 36.2 and Table 36.2). The motivational properties of acetaldehyde were crucially tested by the operant conflict paradigm, where an aversive stimulus was associated with rat operant response for acetaldehyde. Indeed, when a mild foot-shock was delivered following each lever press rewarded with acetaldehyde (punished response), acetaldehyde-drinking rats were not

FIGURE 36.2 Pharmacological modulation of acetaldehyde’s effects on dopamine and endocannabinoid transmissions. The motivational properties of acetaldehyde (ACD) in the operant paradigms involve DA and eCB release. When DA and eCB signaling are blocked by the administration of the D1-DA receptor (D1-R) antagonist SCH39166 or the D2-dopamine (D2-R) autoreceptor agonist quinpirole, or the administration of the CB1-cannabinoid receptor (CB1-R) antagonist AM-281, respectively, operant behavior for ACD decreased.

discouraged from lever pressing and emitted a higher number of punished responses than control rats (Cacace et al., 2012). In the Geller-Seifter procedure, anxiolytic dugs do not affect the unpunished component of operant responses, whereas drugs with nonspecific motor effects decrease it. Actually, acetaldehyde was able to increase the unpunished responses, although to a lesser extent than the punished ones, suggesting a prevailing motivational effect, rather than anticonflict properties (Cacace et al., 2012; Cannizzaro et al., 2011).

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TABLE 36.2 Pharmacological Modulation of Acetaldehyde’s Motivational Properties D1-DA receptor antagonist

↓ ACD conditioned place preference

Spina et al. (2010)

D2-DA autoreceptor agonist

↓ ACD operant behavior

Rodd et al. (2005)

↓ ACD operant responding during extinction CB1-cannabinoid receptor antagonist

↓ ACD operant responding during relapse

Brancato et al. (2014)

↓ ACD operant behavior

Plescia et al. (2013)

↓ ACD operant responding during relapse ↓ ACD operant responding during conflict Acetaldehyde (ACD) per se induces CPP for paired environment and cues, involving DA transmission; moreover, ACD induces and maintains operant behavior that is modulated by DA and endocannabinoid transmissions.

ENDOCANNABINOIDS AND NEUROPEPTIDE Y Besides DA’s role in the expression of operant behavior, the endocannabinoid system plays an important role in value attribution processing and modulation of motivated behavior (Brancato, Lavanco, Cavallaro, Plescia, & Cannizzaro, 2016; HendersonRedmond, Guindon, & Morgan, 2016). Consistently with this background, CB1 receptor antagonist decreased acetaldehyde-seeking behavior during extinction and decreased acetaldehyde lever pressing and intake following forced abstinence. Most importantly, the CB1 antagonist decreased the punishment resistance observed in acetaldehyde-drinking rats in the operant conflict paradigm when the footshock was associated with acetaldehyde delivery (Plescia et al., 2013). These data suggest that the reinforcing properties of acetaldehyde involve endocannabinoids production which, in turn, modulate DA’s mesocorticolimbic pathway through CB1 receptors (Fig. 36.2 and Table 36.2). In addition, the interplay between acetaldehyde and endocannabinoids takes place in the recruitment of peripheral and central stress response. In particular, acetaldehyde was shown to mediate alcohol-induced activation of the hypothalamic pituitary adrenal axis (Cannizzaro, La Barbera, Plescia, Cacace, & Tringali, 2010; Escrig, Pardo, Aragon, & Correa, 2012; Kinoshita et al., 2001). This stress system contributes, in various extents, to the development of alcohol-related behaviors. Indeed, although the activation of the stress system by alcohol and acetaldehyde can facilitate behavioral reactivity in aversive conditions (Cacace et al., 2011; Plescia et al., 2015a), repeated cycles of alcohol intoxication and withdrawal deeply affect the homeostasis of brain stress and antistress systems. Indeed, both chronic alcohol and

acetaldehyde decreased the expression of the anxiolytic peptide neuropeptide Y (NPY) in limbic brain regions, such as the hippocampus and ventral striatum (Kinoshita et al., 2000; Olling et al., 2007; Plescia et al., 2014), contributing to the occurrence of the aversive psychological state characteristic of withdrawal. These modifications are consistent with the so-called involvement of the “dark side,” or stress systems, in the development of alcohol use problems (Koob, 2013). Individuals would consume alcohol in an attempt to return to homeostasis via a negative reinforcement process, that maintains and promotes drug taking. Similarly to alcohol, acetaldehyde contributes to engender an aversive (anxious, depressive) state by bidirectional effects on the two major and functionally opposite stress-related peptides, corticotropinreleasing hormone (CRH) and NPY, thus, perpetuating excessive alcohol consumption.

ACETALDEHYDE MEDIATES ALCOHOL MOTIVATIONAL PROPERTIES As a metabolic product of alcohol, many studies investigated the role of acetaldehyde in mediating the motivational effects of its parent compound; their results consistently showed that by using acetaldehyde-sequestrating agents and/or by reducing acetaldehyde production, alcohol is virtually devoid of its motivational and neuroactive properties (Cannizzaro et al., 2010). Thiol compounds, such as the amino acid cysteine, are able to covalently bind acetaldehyde formed from alcohol, producing stable, nontoxic 2-methyl-thiazolidine-4-carboxylic acid compound. Interestingly L-cysteine dose-dependently prevented both alcohol and acetaldehyde-induced CPP, but did not interfere with morphine-induced conditioning, suggesting that the

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acetaldehyde-sequestration specifically interferes with the motivational properties of alcohol (Peana, Assaretti, Muggironi, Enrico, & Diana, 2009). These results replicated what was observed by Font, Aragon, and Miquel (2006), who showed that the administration of D-penicillamine, as acetaldehyde sequestering agent, prevented the acquisition of alcohol-induced CPP. Notably, the administration of D-penicillamine also decreased the stimulatory effects of alcohol on mesolimbic DA transmission. In detail, while both alcoholincreased DA release in the NAc and the activity of antidromically identified mesoaccumbens DA neurons, in coupled in vivo microdialysis—single cell extracellular recording experiments, pretreatment with D-penicillamine prevented both alcohol—and acetaldehyde-induced effects, again without affecting morphine stimulatory actions (Enrico et al., 2009). In addition, the catalase-dependent metabolism of alcohol to acetaldehyde in the brain was shown to be crucial for the motivational properties of alcohol and

FIGURE 36.3 Pharmacological modulation of acetaldehyde concentration in the brain. Acetaldehyde (ACD) is produced from alcohol by catalase in the brain. ACD’s central concentration is decreased by the administration of the catalase inhibitor 3-amino-1,2,4-triazole (AT), and anticatalase shRNA, or ACD-sequestrating agents, such as L-cysteine and D-penicillamine. TABLE 36.3

the associated environmental stimuli. Indeed, the acquisition of alcohol-induced CPP can be blocked when animals are treated with 3-amino-1,2,4-triazole (AT), a catalase inhibitor, previous to alcohol administration (Font, Miquel, & Aragon, 2009). This effect was specific to alcohol because neither morphine-induced nor cocaine-induced CPP were affected by AT treatment. Further, specific gene-blocking techniques that allow the inhibition of catalase in the VTA and, in turn, the local production of acetaldehyde from alcohol, demonstrated that acetaldehyde mediates the alcohol-reinforcing effect in self-administration paradigms. In these studies, microinjection of lentiviral vector encoding anticatalase shRNA into the VTA strongly decreased voluntary alcohol consumption in rats and abolished the increased DA release in NAc induced by acute administration of alcohol (Karahanian et al., 2011; Quintanilla et al., 2012). Moreover, VTA anticatalase shRNA injection reduced the marked increase in alcohol intake that follows a period of deprivation; an effect that was proposed to reflect the increased reinforcing value of alcohol (Tampier et al., 2013) (Fig. 36.3 and Table 36.3). In addition, and despite its own short half-life, acetaldehyde may condensate with monoamines, to produce tetrahydroisoquinolines. When condensation occurs with DA, acetaldehyde generates 1-methyl-6,7dihydroxy-1,2,3,4-tetrahydroisoquinoline, salsolinol (SAL) (Chen et al., 2011). SAL content increases after very different alcohol drinking procedures in several brain regions (NAc, caudate putamen, midbrain, hypothalamus) (Matsubara, Fukushima, & Fukui, 1987; Myers, Ng, Singer, Smythe, & Duncan, 1985; Sjo¨quist, Liljequist, & Engel, 1982).

Acetaldehyde Involvement in Motivational Properties of Alcohol

ACD-sequestrating agents

ACD-central production inhibition

L-cysteine

Dose-dependently prevented both alcohol and ACDinduced CPP

Peana et al. (2009)

D-penicillamine

Prevented the acquisition of alcohol-induced CPP

Font et al. (2006)

Decreased the stimulatory effects of alcohol on mesolimbic DA transmission

Enrico et al. (2009)

Prevented the acquisition of alcohol-induced CPP

Font et al. (2009)

Decreased voluntary alcohol consumption

Karahanian et al. (2011)

Decreased alcohol-induced DA release in NAc

Quintanilla et al. (2012)

Reduced alcohol deprivation effect

Tampier et al. (2013)

Catalase inhibitor 3-Amino-1,2,4-triazole Anticatalase shRNA

When acetaldehyde (ACD) is trapped by sequestrating agents (L-cysteine and D-penicillamine) and/or its central production ACD is decreased (catalase inhibitor 3-amino-1,2,4-triazole, and anticatalase shRNA), alcohol is devoid of its motivational and neuroactive properties.

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However, increasing attention must be paid to alcohol and, indirectly, acetaldehyde exposure during gestation and lactation since the neuronal systems suffer from a severe vulnerability (Cannizzaro et al., 2005; Cannizzaro et al., 2002; Cannizzaro et al., 2006), and acetaldehyde has not been studied in the perinatal period yet. Also, a deeper understanding of SAL activity at the molecular level will drive exciting avenues of future research and will provide new insights into the neurobiological basis of alcoholism.

MINI-DICTIONARY OF TERMS FIGURE 36.4 Mechanism of action of acetaldehyde in the reward system. Acetaldehyde (ACD) contribution to alcohol’s neuroactive effects involves the release of dopamine (DA) and endocannabinoids (eCB), and the stimulation of DA-receptors (DA-Rs) and CB1-cannabinoid receptor (CB1-R). When ACD is trapped by sequestrating agents, such as L-cysteine and D-penicillamine, and/or its central production is decreased, by the administration of the catalase inhibitor 3-amino-1,2,4-triazole (AT) and anticatalase shRNA, alcohol is devoid of its neuroactive properties.

Moreover, significant place preference is induced by SAL (Matsuzawa, Suzuki, & Misawa, 2000) and rats readily self-administer SAL into the NAc shell and posterior VTA (Rodd et al., 2008), suggesting that SAL itself may act as a reinforcer in the mesolimbic system. Indeed, in a recent elegant study, Melis, Carboni, Caboni, and Acquas (2015) found that, similarly to alcohol and acetaldehyde, SAL significantly stimulates the firing rate of DA cells in the posterior VTA. Specifically, the onset of the effects of alcohol, acetaldehyde, and SAL is similar and alcohol derivatives reveal overlapping dose response curves. Amine-aldehyde metabolites constitute causal neurochemical factors in the onset of the rewarding properties of alcohol and in the development of alcohol addiction.

CONCLUSIONS The understanding of the interplay between acetaldehyde, DA, and endocannabinoids in the modulation of the reward system is crucial to untangle the etiology of alcohol-related behaviors, since the incomplete understanding of the neurobiological background beyond alcohol’s central effects hampers the development of successful pharmaceutical agents. Indeed, the pharmacological targeting of acetaldehyde production and neurotransmissions relevant for both acetaldehyde and alcohol actions might accelerate the development of more effective therapeutic interventions to reduce the incidence of alcohol abuse and alcoholism (Fig. 36.4).

Acetaldehyde The first metabolite of alcohol, it is enzymatically produced in the periphery by alcohol dehydrogenase ad CYP-2E1, but also in the brain by catalase, where it can reach local high concentrations. Conditioned place preference Widely used behavioral paradigm where animals show increased preference for environmental cues paired with a rewarding experience and drugs of abuse. Two-bottle choice-drinking paradigm Self-administration paradigms where animals are provided with water and alcohol (or acetaldehyde) solution in their home cage. The amount of drug consumed is suggestive of the drug rewarding properties. Operant conditioning Pivotal behavioral paradigm for studying motivational effects of drugs. In this procedure, animals are trained to emit a specific response (lever press or nose poke) for actively gaining the reinforcement. Apart from drug taking, operant conditioning allows to explore discrete features of addictivelike behavior, such as drug seeking, relapse, and drug-use despite negative consequences, which are diagnostic criteria found in human addicts. Operant conflict Operant paradigm where an aversive stimulus (mild foot-shock) is associated with operant response for reward delivery. It models drug abuse despite negative consequences and punishment resistance in the clinical setting.

KEY FACTS Acetaldehyde • Acetaldehyde, the first metabolite of alcohol, is enzymatically produced in the periphery but also in the brain, where it can reach local high concentrations. • Acetaldehyde naturally occurring in alcoholic beverages confers to ciders, wines, and spirits their distinctive flavors. • Acetaldehyde central production can be blocked by either pharmacological or RNA interference inhibitors of catalase. • Acetaldehyde central levels can be decreased by sequestrating agents. • Depending on alcohol doses and modalities of administration, peripheral acetaldehyde can cross the blood brain barrier and potentially add to the locally produced one.

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SUMMARY POINTS • Acetaldehyde contributes to alcohol’s neuroactive effects through its own motivational properties that involve DA transmission. • Acetaldehyde per se induces CPA for paired environment and cues. • As alcohol does, acetaldehyde is voluntarily selfadministered in a two-bottle choice-drinking paradigm and its consummatory behavior is dose dependent. • Acetaldehyde induces and maintains operant behavior that is modulated by DA and endocannabinoid transmissions. • When acetaldehyde is trapped by sequestrating agents and/or its central production is decreased, alcohol is devoid of its motivational and neuroactive properties. • Acetaldehyde contributes to engender an aversive state by bidirectional effects on the two major and functionally opposite stress-related peptides, CRH and NPY, thus, perpetuating excessive alcohol consumption. • SAL, a DA-acetaldehyde condensation product, constitutes a causal neurochemical factor in the onset of the rewarding properties of alcohol.

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37 Age-Related Differences in the Appetitive and Aversive Motivational Effects of Alcohol 1

Ricardo Marcos Pautassi1,2 Instituto de Investigacio´n Me´dica M. y M. Ferreyra (INIMEC—CONICET-Universidad Nacional de Co´rdoba), Co´rdoba, Argentina 2Facultad de Psicologı´a, Universidad Nacional de Co´rdoba, Co´rdoba, Argentina

LIST OF ABBREVIATIONS AUD CS CPP CPA CTA PD

alcohol use disorders conditional stimulus conditioned place preference conditioned place aversion conditioned taste aversion postnatal day

INTRODUCTION Alcohol drinking is normative among most Western countries. Data that were gathered from a sample of Argentinean college students revealed, among lifetime drinkers, a mean age of alcohol onset of 15 years. Thirty percent of that sample had begun drinking at age 13 or younger. By age 16, approximately 80% of them had initiated alcohol drinking. During the first year of college, Argentinian students drink an average of seven standard drinks in a typical drinking occasion (Pilatti, Read, & Pautassi, 2017). Another study reported that 56% of children aged 8 12 had sipped or tasted alcohol (Pilatti, Godoy, Brussino, & Pautassi, 2013). An early age of alcohol drinking onset can predict the subsequent development of alcohol use disorders (AUD). Those who begin drinking as adolescents escalate much more quickly to a diagnosis of AUD than those who begin drinking during adulthood (Clark, Kirisci, & Tarter, 1998). Binge drinking behavior is associated with several negative consequences, including a greater likelihood of AUD. Binge drinking is also much more prevalent in adolescents and young adults than in older subjects (Bell et al., 2017). Therefore, it is

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00037-4

important to analyze the factors that promote the use of alcohol during late infancy and adolescence. Although most adolescents will drink alcohol, only a small fraction will develop AUD. Vulnerability factors for AUD span across community, socio-cognitive, and biological factors. For example, evidence suggests that the number of alcohol establishments in a particular geographic area is associated with the drinking patterns of those who live nearby. These social factors interact with psychobiological factors, such as genetic makeup and sensitivity to the pharmacological effects of the drug, thus, rendering an individual either more or less susceptible to alcohol use and eventually AUD. This chapter focuses on sensitivity to the motivational effects of alcohol and the ways in which sensitivity changes during the course of the life span in animal models of alcohol’s effects. The aim is to determine whether infants and adolescents exhibit differential sensitivity to alcohol’s motivational effects that could explain their propensity to engage in, and escalate, alcohol intake.

WHAT ARE THE MOTIVATIONAL EFFECTS OF ALCOHOL, AND HOW DO WE MEASURE THEM? Alcohol ingestion causes the release of several neurotransmitters, including dopamine and endogenous opioids. The activation of receptors that are associated with these transmitters is associated with feelings of euphoria and well-being. Alcohol also exerts aversive,

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undesirable effects, such as dysphoria, social avoidance, motor depression, and gastrointestinal malaise. Alcohol’s positive appetitive and aversive effects mostly work in parallel, although this depends on the dose and postadministration time. Appetitive effects are usually associated with low doses and an early postadministration time when blood alcohol levels are rising. Aversive effects are more prominent at later postadministration times and are associated with peak blood alcohol levels. This was supported by a study by Cunningham and Prather (1992), in which a chamber (referred to as the conditional stimulus (CS)) was paired only with the early stage of alcohol intoxication or the later stages of intoxication. A longer duration of exposure to the CS was associated with less preference for the alcohol-paired CS. Specifically, different groups of mice were confined to a chamber that had a distinctive floor for 5, 15, or 30 minutes after the administration of alcohol. The animals were then allowed to explore a box that contained the floor CS that was paired with alcohol or an alternative floor. Mice in the 5 minutes group spent 83% of the total test time on the floor that signaled the effects of alcohol, but this proportion decreased to 66% in the 30 minutes group. This illustrates the biphasic nature of alcohol’s motivational effects and conditioned place preference (CPP), which assesses sensitivity to the appetitive or aversive effects of alcohol. Aversive effects are most commonly measured by the conditioned taste aversion (CTA) procedure in which animals drink a novel taste followed by the administration of alcohol. This results in avoidance of the taste in a subsequent test. Sensitivity to the motivational effects of alcohol is assumed to help identify subjects who are at risk for AUD. Based on this assumption, individuals with greater sensitivity to alcohol’s appetitive effects, or less sensitivity to alcohol’s aversive effects, would exhibit greater alcohol intake and, thus, a higher propensity to develop AUD. Still unclear, however, are whether the motivational effects of alcohol are actually related to alcohol intake and the extent of such a relationship. One approach to solve this issue is to test alcohol-induced CTA and CPP in rats that are selectively bred for low or high alcohol consumption (for review, see Bell et al., 2017). Alcohol-induced conditioned place aversion (CPA) is significantly greater in alcohol-nonpreferring rats than in alcohol-preferring rats (Stewart, Murphy, McBride, Lumeng, & Li, 1996). Adolescent alcoholpreferring and high-alcohol-drinking rats, but not adolescent alcohol-nonpreferring or low-alcohol-drinking rats, exhibit motor activation after low doses of alcohol (0.25 0.75 g/kg). Moreover, adolescent high-alcoholdrinking rats were shown to be resistant to the motorsedative effects of alcohol that were reliably exhibited by their low-alcohol-drinking counterparts (Rodd

et al., 2004). Consistent with these differences, alcoholinduced CPP was exhibited by Universidad de Chile bibulous rats but not by Universidad de Chile abstinent rats (Quintanilla & Tampier, 2011). Rats that are selectively bred for high alcohol intake also appear to be resistant to alcohol-induced CTA. We recently observed a blunted response to alcoholinduced CTA and an exacerbated response to alcoholinduced forward locomotion in adolescent rats that were derived from parents who had exhibited high alcohol intake during adolescence (Fernandez et al., 2017). Lower sensitivity to alcohol-induced CTA has also been reported in Warsaw Alcohol high-preferring rats compared with Warsaw Alcohol low-preferring rats (Dyr et al., 2016) and in high-alcohol preference mice compared with low-alcohol preference mice (Chester, Lumeng, Li, & Grahame, 2003). Selection pressure for high or low alcohol drinking likely fixates genes that are associated with sensitivity to the appetitive or aversive effects of alcohol. Evidence that supports such an association between sensitivity to alcohol’s motivational effects and alcohol intake is much less conclusive when we focus on experiments that analyze associations with these indices within individuals or between strains. Cailhol and Mormede (2002), for example, found significant differences in sensitivity to the aversive effects of alcohol between Wistar Kyoto Spontaneously Hypertensive and Wistar Kyoto Hyperactive rat strains. These differences, however, were unrelated to different levels of alcohol intake that were observed across these strains.

DO THE MOTIVATIONAL EFFECTS OF ALCOHOL CHANGE ACROSS THE LIFE SPAN? Alcohol-Induced Taste Aversion Perhaps the most notable age-related difference involves alcohol-induced aversion. This chapter focuses on adolescent versus adult differences in alcohol-induced CTA, but we first discuss oftenoverlooked, age-related changes in responding to alcohol’s aversive effects across the preweanling period. Rodents that are # 21 postnatal days (PDs) old are usually referred to as infants or preweanlings. The term adolescence is usually reserved for rats and mice that are 28 42 days old, respectively. The developmental windows immediately before (PD21 28) or after (PD42 60) adolescence are sometimes referred to as periadolescence, whereas rats and mice are considered adults by PD70. Alcohol-induced CTA is difficult to detect up to PD8 10, but it is subsequently reliably observed, even

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DO THE MOTIVATIONAL EFFECTS OF ALCOHOL CHANGE ACROSS THE LIFE SPAN?

after relatively low levels of alcohol intoxication. Arias and Chotro (2006) gave 7- to 8-day-old and 10- to 11-day-old rats a high dose of alcohol (3 g/kg) that is known to induce orosensory stimulation via nonmetabolic excretion of the drug through perspiration and other sources. Preference for, and aversion to, the odor of alcohol was observed in younger and older animals, respectively. In a subsequent study (Nizhnikov, Pautassi, Varlinskaya, Rahmani, & Spear, 2012), 12-day-old rats exhibited saccharin-induced CTA after pairings of saccharin and 2.0 g/kg alcohol, whereas 4-day-old rats did not. At lower doses (0.15 0.25 g/ kg), the younger animals exhibited conditioned preferences, whereas no effect was observed in animals that underwent conditioning on PD12. The literature on adolescent versus adult differences has indicated that adolescents are much less sensitive to alcohol-induced CTA, regardless of species and most other parameters. In one study (Vetter-O’Hagen, Varlinskaya, & Spear, 2009), adults exhibited avoidance of a saccharin solution that was paired with 1.0 or 1.5 g/kg alcohol, whereas adolescents only expressed CTA when a 2.0 g/kg dose was used (Fig. 37.1). Subsequent studies by Vetter-O’Hagen et al. found that adolescent rats required either a higher dose of alcohol or more pairings between the taste CS and alcohol’s postabsorptive effects to exhibit CTA that was similar to adult rats (Anderson, Varlinskaya, & Spear, 2010). Other studies, in turn, found reduced sensitivity to ethanol-induced CTA in adolescent compared to adult C57BL/6J mice (Holstein, Spanos, & Hodge, 2011). Adolescent rats and mice usually drink significantly more alcohol than adult rodents under various test conditions. This suggests the relevance of the CTA

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findings discussed herein because they indicate that lower sensitivity to alcohol-induced aversion may promote greater engagement in alcohol intake in young individuals. None of these studies, however, provided direct evidence to support this hypothesis. This was addressed by Schramm-Sapyta et al. (2010), who induced CTA by alcohol in adolescents and adults and then assessed alcohol intake in the same groups of animals. The study recapitulated the difference in alcohol-induced CTA across ages and also found an age-specific association between CTA and alcohol intake. Lower expression of CTA in adolescents was associated with greater alcohol intake that was measured after a period of alcohol deprivation. CTA scores and alcohol intake scores were unrelated in adult animals. These results are consistent with findings from animal strains that were selectively bred for differential alcohol intake, which mostly indicated that CTA that is induced by alcohol is closely genetically linked to the predisposition to alcohol intake. Importantly, adolescents appear to exhibit lower sensitivity to the aversive effects of a wide array of drugs, including tetrahydrocannabinol, amphetamine, cocaine, and nicotine, indicating that lower sensitivity in adolescents is not unique to alcohol (for a review, see Doremus-Fitzwater & Spear, 2016). Most of the studies that found reliable adolescent versus adult differences in alcohol-induced CTA employed CSs that were not highly palatable, and these studies conditioned and tested the animals under moderate water or social deprivation (i.e., singlehousing). Some of the age-related differences disappeared, or at least became more complex, when these conditions changed. Morales, Schatz, Anderson, Spear,

FIGURE 37.1 Saccharin intake (mL/kg) of adolescent and adult male rats on a test day, as a function of ethanol dose given during training. The rats were isolated during the intoxication period.  Indicates a significant difference between a group and its age-matched 0.0 g/kg control. Source: Adapted under the terms of a Creative Commons CC BY license, from Vetter-O’Hagen, C., Varlinskaya, E., & Spear, L. (2009). Sex differences in ethanol intake and sensitivity to aversive effects during adolescence and adulthood. Alcohol and Alcoholism, 44(6), 547 554.

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FIGURE 37.2 Boost intake (% from saline control) at test, of rats from different age groups that received Boost-ethanol pairings during training.  Denotes significant difference from age-matched saline control. Source: Reproduced, with permission, from Saalfield, J., & Spear, L. (2016). The ontogeny of ethanol aversion. Physiology & Behavior, 156, 164 170.

and Varlinskaya (2014) trained and tested nonwaterdeprived adolescent and adult animals in a social, nonisolated context and paired the effects of alcohol with a highly palatable CS (3% sucrose 1 0.13% saccharin in water). Under these conditions, as expected, adolescent males were less sensitive to alcohol-induced CTA than adults, but adolescent females were more sensitive to alcohol-induced CTA than their same-sex adult counterparts. Similarly, Saalfield and Spear (2016) found few adolescent versus adult differences in alcohol-induced CTA after using a highly palatable CS (Chocolate Boost) in nonwater-deprived animals. In a follow-up experiment, the authors switched to the more “typical” procedure of using saccharin and sucrose as the CS in animals that were subjected to a 50% water restriction schedule. Under these conditions, male adolescents did not exhibit CTA at any of the alcohol doses tested (1.0, 1.5, or 2.0 g/kg), but all of the doses effectively induced aversive learning in adult males. The results from Saalfield and Spear (2016) are depicted in Fig. 37.2. This elegant work also dissected the level of expression of alcohol-induced CTA within specific developmental periods that bridged the gap between weaning and adulthood—that is, preadolescence (PD23 25), early adolescence (PD28 30), midadolescence (PD35 37), late adolescence (PD42 44), emerging adulthood (PD52 54), and adulthood (PD72 74). The results indicated that the early stage of adolescence was associated with the greatest insensitivity to alcohol-induced CTA and suggested a graded shift from no, or less aversion, in early adolescence to the “adult” pattern of reliable alcohol-induced CTA.

FIGURE 37.3

Latency to approach and time spent on an odor conditioned stimulus (CS, s) paired with the effects of alcohol (2.25 or 2.5 g/kg, adolescent and adult rats, respectively). Source: Reproduced, with permission, from Pautassi, R. M., Godoy, J. C., & Molina, J. C. (2015). Adolescent rats are resistant to the development of ethanol-induced chronic tolerance and ethanol-induced conditioned aversion. Pharmacology Biochemistry and Behavior, 138, 58 69.

Alcohol-induced olfactory aversion appears to follow the same pattern of ontogenetic divergence for alcohol-induced taste aversions. A study paired an odor with the effects of alcohol (2.25 and 2.5 g/kg in adolescents and adults, respectively) and another odor after the administration of vehicle. When subsequently tested for odor preference (Fig. 37.3), adult animals avoided the alcohol-paired odor, whereas adolescents exhibited a trend toward preferring it (Pautassi, Godoy, & Molina, 2015). These results suggest that adolescents may exhibit a blunted response to alcohol’s aversive effects, as most of the data reviewed in this section would support, and they may be more sensitive to the appetitive effects of the drug.

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CONCLUDING COMMENTS

Alcohol-Induced Place Conditioning Most CPP studies that employed alcohol doses $ 1.0 g/kg in rats that were $ 60 days old have observed aversive conditioning (i.e., CPA), whereas lower doses were usually associated with a lack of conditioning (Roger-Sanchez, Aguilar, Rodriguez-Arias, Aragon, & Minarro, 2012). However, a different pattern emerged in studies that were conducted in younger animals. Using a second-order variation of the typical CPP procedure, Molina, Pautassi, Truxell, and Spear (2007) found that 2-week-old rats exhibited conditioned preference for a sandpaper-lined chamber that signaled either the early (5 20 minutes postadministration) effects of 0.5 or 2.0 g/kg alcohol or the late (30 45 minutes postadministration) effects of 0.5 g/kg alcohol (Fig. 37.4). Interestingly, the rat pups expressed conditioned aversion when the chamber was paired with the late (30 45 minutes postadministration) effects of 2.0 g/kg alcohol. This suggests that alcohol exerts appetitive effects during the rising limb of the blood alcohol curve early in rat development, but the motivational effects of high doses of the drug become aversive during later stages of intoxication. Alcohol-induced appetitive conditioning in preweanling rats was also found in studies that employed more standard CPP procedures (for a review, see Pautassi, Nizhnikov, & Spear, 2009). The few published studies that assessed alcoholinduced CPP in adolescent rats indicated persistence of the alcohol-induced appetitive conditioning phenotype that was observed in infants. Alcohol-induced CPP was found in adolescent rats (PD25, 0.2 g/kg) and lateadolescent rats (PD45, 0.5 and 1 g/kg), whereas a trend

FIGURE 37.4 Time spent by preweanling rats over a sandpaperlined chamber that signaled either the early or late effects of 0.5 or 2.0 g/kg (the “Unpaired” is a control group). Source: Reproduced, with permission, from Molina, Pautassi, R. M., Truxell, E., & Spear, N. (2007). Differential motivational properties of ethanol during early ontogeny as a function of dose and postadministration time. Alcohol, 41(1), 41 55.

toward conditioned aversion was found in young adults (PD60; Philpot, Badanich, & Kirstein, 2003). Similarly, CPP was reported in adolescent rats that received daily pairings (PD30 33) between alcohol’s effects (1.0 g/kg) and a rough texture (Acevedo, Nizhnikov, Spear, Molina, & Pautassi, 2013). In another study, alcohol (1.0 g/kg) induced CPP in female, but not male rats, and this effect was fairly similar in adolescents and adults (Torres, Walker, Beas, & O’Dell, 2014). Reminiscent of the findings of CTA studies, the use of a higher dose (2.0 g/ kg) yielded significant place aversion in both male and female adults, but not in their adolescent counterparts. The results suggest greater sensitivity to the appetitive-rewarding effects of alcohol in adolescent rats than in adult rats and are consistent with studies that employed exteroceptive-conditioned stimuli other than textures or chambers. Adolescent rats exhibited conditioned preference for a taste that signaled a relatively low dose of alcohol (Ferna´ndez-Vidal, Spear, & Molina, 2003). Several studies reported that adolescent, but not adult, rats exhibited behavioral stimulation after receiving moderate to high doses of alcohol (Camarini & Pautassi, 2016). Adult mice generally exhibit reliable alcoholinduced CPP, but studies in adolescent mice have yielded inconsistent results. Early work indicated that adolescent mice may require higher doses of alcohol, more conditioning trials, or exposure to stress to express CPP that is comparable to adult mice (Dickinson, Kashawny, Thiebes, & Charles, 2009; Song et al., 2007). This has led some authors to postulate that the usual age-related pattern of sensitivity to the appetitive effects of alcohol that is found in rats may be the opposite in mice. The studies by Dickinson et al. (2009) and Song et al. (2007), however, have the caveat of being conducted only in adolescent animals. Subsequent work compared alcohol-induced CPP in both adolescent and adult mice in a single study and using the same doses, apparatus, and conditioning procedures. Pautassi et al. (2017) reported CPP by alcohol (2.0 g/kg) in adult Swiss mice that were reared under standard animal care conditions, but not in their adolescent counterparts. Interestingly, an enriched housing environment promoted the expression of alcohol-induced CPP in adolescents (Fig. 37.5), but did not affect its expression in adults (Fig. 37.6). RogerSanchez et al. (2012) observed CPP by 2.5 g/kg alcohol in early-adolescent and young adult female mice and early-adolescent males, but not in young adult males.

CONCLUDING COMMENTS This chapter reviewed age-related differences in the motivational effects of alcohol. A common, albeit not

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FIGURE 37.5 Time spent (s or % preference) by adolescent mice in a chamber associated with ethanol’s effects (conditioned stimulus [CS1]), as a function of rearing condition (standard [control] conditions and environmental enrichment; SC and EE groups, respectively) and treatment during training (vehicle or 2.0 g/kg ethanol).  Denotes significant differences between the ethanol-EE group and the other groups. Source: Adapted, under the terms of Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), from Pautassi, R. M., Suarez, A., Barbosa Hoffmann, L., Rueda, A. V., Rae, M., Marianno, P. & Camarini, R. (2017). Effects of environmental enrichment upon ethanol-induced conditioned place preference and pre-frontal BDNF levels in adolescent and adult mice. Scientific Reports. https://doi:10.1038/s41598-017-08795-0.

universal, denominator is that infants and adolescents appear to perceive alcohol as more rewarding or less aversive compared with adults. Evidence for this was found particularly within the dose range of 1.0 2.0 g/ kg alcohol, although age differences above or below this range have also been reported. Another common denominator is that each model provides relevant information to understand agerelated differences in alcohol’s effects, but none of the models alone provides a full account of the relationship between sensitivity to these effects within a single individual or its relationship with alcohol intake patterns. Approaches are needed that combine exposure

FIGURE 37.6

Time spent (s or % preference) by adult mice in a chamber associated with ethanol’s effects (conditioned stimulus [CS1]), as a function of rearing condition (standard [control] conditions and environmental enrichment; SC and EE groups, respectively) and treatment during training (vehicle or 2.0 g/kg ethanol).  Denotes a significant difference between ethanol- and vehicletreated mice. Source: Adapted, under the terms of Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), from Pautassi, R. M., Suarez, A., Barbosa Hoffmann, L., Rueda, A. V., Rae, M., Marianno, P. & Camarini, R. (2017). Effects of environmental enrichment upon ethanol-induced conditioned place preference and pre-frontal BDNF levels in adolescent and adult mice. Scientific Reports. https://doi:10.1038/s41598-017-08795-0.

to tastes and exteroceptive stimuli in a single conditioning session and measure alcohol drinking patterns at the individual level. Such types of combined CPP/ CTA approaches, which have rarely been used, may help dissect the balance between the appetitive and aversive effects of alcohol and the modulation of such effects by age. Also needed is an analysis of the mechanisms that underlie these apparent age-related differences in alcohol responsivity. Several hypotheses have been suggested. Alcohol exposure during early

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REFERENCES

development (e.g., gestation, infancy, and adolescence), but not during adulthood, may alter the developmental trajectories of transmitter systems or magnify the typical novelty-seeking phenotype of adolescence and this, is turn, could facilitate the expression of alcohol-induced preference. Another possibility is that adolescents, compared with adults, are more apt to learn about positive reinforcers, more likely to be sign-trackers than goaltrackers, and less apt to learn about negative outcomes. All of these possibilities deserve future attention. As noted by Doremus-Fitzwater and Spear (2016), assessments are needed of the ways in which the apparent reward-sensitive phenotype of adolescence is modulated by environmental factors (e.g., stress and alcohol preexposure) and genetic factors, and whether agerelated differences also emerge in the modulating role of these factors.

MINI-DICTIONARY OF TERMS Conditioned place preference A procedure that assesses the appetitive and aversive effects of drugs. The test measures the preference for, or avoidance of, a place where the subject experienced a drug’s effects. Conditioned taste aversion A procedure that measures the aversive effects of drugs by pairing the ingestion of a novel taste with the pharmacological effects of the drug. Motivational effects of drugs These are pharmacological effects that cause a drug user to either increase or decrease behaviors that result in access to, and consumption of, the drug. These effects can be divided into appetitive or positively rewarding effects, aversive effects, and anxiolytic or negative reinforcing effects. Binge drinking In humans, drinking 4 5 standard drinks in # 2 hours. Vulnerability factors Factors that promote the escalation of alcohol drinking and development of AUD.

KEY FACTS Animal Models of Alcohol Use Disorders • Alcohol use disorder (AUD) is a chronic, relapsing disorder that is characterized by a compulsive pattern of alcohol use. • AUD can involve the development of tolerance and emergence of negative symptoms during abstinence. • In the United States, 15.7 million people were diagnosed with AUD in 2015. • The highest prevalence of AUD is found in late adolescence and young adulthood. • There are several animal models of excessive alcohol consumption; most of them employ rodents (rats and mice). • Some of these animal models analyze the effects of alcohol that are responsible for the development of AUD.

• The use of these animal models has allowed testing promising therapies to prevent or ameliorate AUD.

SUMMARY POINTS • Alcohol drinking behaviors emerge early in life and modulate the likelihood of exhibiting alcohol use disorder. • This chapter focuses on age-related differences in sensitivity to the motivational effects of alcohol, assessed in rodent studies. • The motivational effects of alcohol are pharmacological effects that modulate alcoholseeking and alcohol-taking behaviors. • Infant and adolescent rats are less sensitive to the aversive effects of alcohol compared with adults. • Infant and adolescent rats are more sensitive to the appetitive, rewarding effects of alcohol compared with adults. • This pattern of reactivity to alcohol may explain the higher propensity of young individuals to engage in binge drinking and heavy drinking.

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Cunningham, C. L., & Prather, L. K. (1992). Conditioning trial duration affects ethanol-induced conditioned place preference in mice. Animal Learning & Behavior, 20(2), 187 194. Dickinson, S. D., Kashawny, S. K., Thiebes, K. P., & Charles, D. Y. (2009). Decreased sensitivity to ethanol reward in adolescent mice as measured by conditioned place preference. Alcoholism: Clinical and Experimental Research, 33(7), 1246 1251. Doremus-Fitzwater, T. L., & Spear, L. P. (2016). Reward-centricity and attenuated aversions: An adolescent phenotype emerging from studies in laboratory animals. Neuroscience & Biobehavioral Reviews, 70, 121 134. Available from https://doi.org/10.1016/j. neubiorev.2016.08.015. Dyr, W., Wyszogrodzka, E., Paterak, J., Siwinska-Ziolkowska, A., Malkowska, A., & Polak, P. (2016). Ethanol-induced conditioned taste aversion in Warsaw Alcohol High-Preferring (WHP) and Warsaw Alcohol Low-Preferring (WLP) rats. Alcohol, 51, 63 69. Available from https://doi.org/10.1016/j.alcohol.2015.11.011. Fernandez, M. S., Baez, B., Bordon, A., Espinosa, L., Martinez, E., & Pautassi, R. M. (2017). Short-term selection for high and low ethanol intake yields differential sensitivity to ethanol’s motivational effects and anxiety-like responses in adolescent Wistar rats. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 79(Pt B), 220 233. Available from https://doi.org/10.1016/j.pnpbp.2017.06.027. Ferna´ndez-Vidal, J. M., Spear, N. E., & Molina, J. C. (2003). Adolescent rats discriminate a mild state of ethanol intoxication likely to act as an appetitive unconditioned stimulus. Alcohol, 30 (1), 45 60. Available from https://doi.org/10.1016/s0741-8329 (03)00093-4. Holstein, S. E., Spanos, M., & Hodge, C. W. (2011). Adolescent C57BL/6J mice show elevated alcohol intake, but reduced taste aversion, as compared to adult mice: A potential behavioral mechanism for binge drinking. Alcoholism: Clinical and Experimental Research, 35(10), 1842 1851. Available from https:// doi.org/10.1111/j.1530-0277.2011.01528.x. Molina, J. C., Pautassi, R. M., Truxell, E., & Spear, N. (2007). Differential motivational properties of ethanol during early ontogeny as a function of dose and postadministration time. Alcohol, 41(1), 41 55. Available from https://doi.org/10.1016/j. alcohol.2007.01.005. Morales, M., Schatz, K. C., Anderson, R. I., Spear, L. P., & Varlinskaya, E. I. (2014). Conditioned taste aversion to ethanol in a social context: Impact of age and sex. Behavioural Brain Research, 261, 323 327. Available from https://doi.org/10.1016/ j.bbr.2013.12.048. Nizhnikov, M. E., Pautassi, R. M., Varlinskaya, E. I., Rahmani, P., & Spear, N. E. (2012). Ontogenetic differences in ethanol’s motivational properties during infancy. Alcohol, 46(3), 225 234. Available from https://doi.org/10.1016/j.alcohol.2011.09.026. Pautassi, R. M., Godoy, J. C., & Molina, J. C. (2015). Adolescent rats are resistant to the development of ethanol-induced chronic tolerance and ethanol-induced conditioned aversion. Pharmacology Biochemistry and Behavior, 138, 58 69. Available from https://doi. org/10.1016/j.pbb.2015.09.012. Pautassi, R. M., Nizhnikov, M. E., & Spear, N. E. (2009). Assessing appetitive, aversive, and negative ethanol-mediated reinforcement through an immature rat model. Neuroscience & Biobehavioral Reviews, 33(6), 953 974. Pautassi, R. M., Suarez, A., Barbosa Hoffmann, L., Rueda, A. V., Rae, M., Marianno, P., & Camarini, R. (2017). Effects of environmental

enrichment upon ethanol-induced conditioned place preference and pre-frontal BDNF levels in adolescent and adult mice. Scientific Reports. Available from https://doi.org/10.1038/s41598017-08795-0. Philpot, R. M., Badanich, K. A., & Kirstein, C. L. (2003). Place conditioning: Age-related changes in the rewarding and aversive effects of alcohol. Alcoholism: Clinical and Experimental Research, 27 (4), 593 599. Pilatti, A., Godoy, J. C., Brussino, S., & Pautassi, R. M. (2013). Underage drinking: Prevalence and risk factors associated with drinking experiences among Argentinean children. Alcohol, 47(4), 323 331. Available from https://doi.org/10.1016/ j.alcohol.2013.02.001. Pilatti, A., Read, J., & Pautassi, R. M. (2017). ELSA 2016 cohort: Alcohol, tobacco, and marijuana use and their association with age of drug use onset, risk perception, and social norms in Argentinean college freshmen. Frontiers in Psychology. Available from https://doi.org/10.3389/fpsyg.2017.01452. Quintanilla, M. E., & Tampier, L. (2011). Place conditioning with ethanol in rats bred for high (UChB) and low (UChA) voluntary alcohol drinking. Alcohol, 45(8), 751 762. Available from https:// doi.org/10.1016/j.alcohol.2011.06.002. Rodd, Z. A., Bell, R. L., McKinzie, D. L., Webster, A. A., Murphy, J. M., Lumeng, L., . . . McBride, W. J. (2004). Low-dose stimulatory effects of ethanol during adolescence in rat lines selectively bred for high alcohol intake. Alcoholism: Clinical and Experimental Research, 28(4), 535 543. Roger-Sanchez, C., Aguilar, M. A., Rodriguez-Arias, M., Aragon, C. M., & Minarro, J. (2012). Age- and sex-related differences in the acquisition and reinstatement of ethanol CPP in mice. Neurotoxicology and Teratology, 34(1), 108 115. Available from https://doi.org/10.1016/j.ntt.2011.07.011. Saalfield, J., & Spear, L. (2016). The ontogeny of ethanol aversion. Physiology & Behavior, 156, 164 170. Available from https://doi. org/10.1016/j.physbeh.2016.01.011. Schramm-Sapyta, N. L., DiFeliceantonio, A. G., Foscue, E., Glowacz, S., Haseeb, N., Wang, N., . . . Kuhn, C. M. (2010). Aversive effects of ethanol in adolescent versus adult rats: Potential causes and implication for future drinking. Alcoholism: Clinical and Experimental Research, 34(12), 2061 2069. Available from https:// doi.org/10.1111/j.1530-0277.2010.01302.x. Song, M., Wang, X. Y., Zhao, M., Wang, X. Y., Zhai, H. F., & Lu, L. (2007). Role of stress in acquisition of alcohol-conditioned place preference in adolescent and adult mice. Alcoholism: Clinical and Experimental Research, 31(12), 2001 2005. Available from https:// doi.org/10.1111/j.1530-0277.2007.00522.x. Stewart, R. B., Murphy, J. M., McBride, W. J., Lumeng, L., & Li, T. K. (1996). Place conditioning with alcohol in alcohol-preferring and -nonpreferring rats. Pharmacology Biochemistry and Behavior, 53(3), 487 491. Torres, O. V., Walker, E. M., Beas, B. S., & O’Dell, L. E. (2014). Female rats display enhanced rewarding effects of ethanol that are hormone dependent. Alcoholism: Clinical and Experimental Research, 38(1), 108 115. Available from https://doi.org/10.1111/ acer.12213. Vetter-O’Hagen, C., Varlinskaya, E., & Spear, L. (2009). Sex differences in ethanol intake and sensitivity to aversive effects during adolescence and adulthood. Alcohol and Alcoholism, 44(6), 547 554.

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38 Alcoholism in Bipolar Disorders: An Overview of Epidemiology, Common Pathogenetic Pathways, Course of Disease, and Implications for Treatment 1

Marco Di Nicola1, Lorenzo Moccia1, Vittoria Rachele Ferri1, Isabella Panaccione2 and Luigi Janiri1

Institute of Psychiatry and Psychology, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, Universita` Cattolica del Sacro Cuore, Rome, Italy 2Department of Neurosciences, Mental Health and Sensory Organs, Sant’Andrea Hospital, Sapienza University of Rome, Rome, Italy

LIST OF ABBREVIATIONS GBD DALYs AUD BD SUD PRS CRH BDNF NMDA NMDARs HPA ACC PFC DLPFC IGT

patients (30%) (Hunt, Malhi, Cleary, Lai, & Sitharthan, 2016). Individuals with AUD-BD comorbidity show early age of onset, a more severe course of illness, serious neurocognitive deficits, increased risk of suicide, and higher healthcare costs (Rakofsky & Dunlop, 2013; Balanza´-Martı´nez, Crespo-Facorro, Gonza´lez-Pinto, & Vieta, 2015). In chronic AUD patients, BD may remain undiagnosed because periodic alterations of mood and energy levels tend to be related to alcohol consumption and not recognized as BD symptoms. Also, the traditional separation between “psychiatric” and “addiction” treatment services often leads to comorbid patients to be left behind, and so not receiving appropriate treatment (Fig. 38.1). Finally, despite the substantial body of literature investigating the link between AUD and BD, there is still little evidence on the common pathogenetic pathways and a lack of standardized treatment guidelines.

global burden of disease disability-adjusted life years alcohol use disorder bipolar disorder substance use disorder polygenic rick score corticotropin-releasing hormone brain-derived neurotrophic factor N-methyl-D-aspartate NMDA receptors hypothalamic pituitary adrenal anterior cingulate cortex prefrontal cortex dorsolateral prefrontal cortex integrated group therapy

INTRODUCTION The latest Global Burden of Disease Study found Alcohol Use Disorder (AUD) and Bipolar Disorder (BD) to be respectively the fourth and fifth cause of disability-adjusted life years among psychiatric disorders (GBD 2013 DALYs and Hale Collaborators, 2015). In a recent meta-analysis, AUD was the substance use disorder (SUD) with the highest prevalence in bipolar

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00038-6

EPIDEMIOLOGY A recent meta-analysis set the occurrence of AUD in BD patients to an estimated 30% 35%, with a significantly higher prevalence in Northern America and

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comorbidity could arise from a reciprocal feedback loop, involving multiple simultaneous causal factors.

GENETIC FACTORS

FIGURE 38.1 Impact of alcoholism on bipolar disorder. The figure summarizes the impact of AUD on the clinical course and outcomes of BD.

Europe compared with Asian regions (Di Florio, Craddock, & van den Bree, 2014). Comorbidity rates are higher in male BD subjects, with a lifetime prevalence of AUD being almost double than females (Di Florio et al., 2014; Hunt et al., 2016). However, the relative risk of developing an AUD is greater in women than in men with BD, when compared to the general population (Farren, Hill, & Weiss, 2012). According to some studies, AUD seems to be slightly more frequent in alternation of manic and depressive episodes (BD-I) than alternation of depressive episodes and hypomanic episodes (BD-II) patients (Hasin, Stinson, Ogburn, & Grant, 2007), but this finding is not confirmed by other reports (Di Florio et al., 2014; Hunt et al., 2016).

COMMON PATHOGENETIC PATHWAYS Alcohol use may precede or follow the onset of BD. According to a first line of evidence, alcohol and/or other substance use may increase the risk of developing BD (Chitty, Lagopoulos, Hickie, & Hermens, 2015). A second line of evidence suggests that comorbidity may arise from shared genetic factors that predispose the individual to both conditions (Reginsson et al., 2017). Finally, it has been proposed that people with BD might use alcohol (or substances) as self-treatment to relieve distressing mood states (Swann, Lijffijt, Lane, Steinberg, & Moeller, 2009). Of note, early traumatic experiences, such as childhood maltreatment and sexual abuse, have been associated with several unfavorable clinical outcomes in BD, including alcohol and substance abuse (Agnew-Blais & Danese, 2016). However, given the heterogeneity of comorbid AUD-BD, it is likely that a single etiopathogenetic mechanism could not encompass and explain all different aspects. It may be suggested that AUD-BD

BD and AUD are heritable disorders. Genome-wide association studies (GWAS) found significant evidence of associations with different genes and single nucleotide polymorphisms (SNPs), suggesting that both diseases are polygenic and their development is influenced by the presence of several small-effect genetic variants (Litten et al., 2015; PGC-Bipolar-DisorderWorking-Group, 2011). Interestingly, some studies suggest that certain specific genetic variants may increase the risk for the co-occurrence of BD and AUD (Carmiol et al., 2014). Recently, the polygenic risk scores (PRSs) for BD have been applied to predict addiction to nicotine, alcohol, or substances of abuse in subjects with a diagnosis of SUD, to differentiate the effect of the diseases themselves from those of the underlying genetic risk factors. Authors found odds ratios for alcohol and substance use disorders ranging from 1.07 to 1.29 for the BD-PRS (Reginsson et al., 2017), supporting the hypothesis of a common genetic pathway for the comorbidity between SUD and BD.

NEUROPHYSIOLOGICAL CORRELATES An increased understanding of the detrimental neurobiological effects of chronic alcohol intake on nervous system highlights that AUD might adversely affect long-term mood stability in BD subjects. In fact, chronic alcohol exposure negatively influences several neurotransmitter and neuropeptide functions involved in the pathophysiology of BD, such as glutamate, GABA, dopamine, serotonin, acetylcholine, cannabinoids, endogenous opioids, corticotropin-releasing hormone (CRH), and the brain-derived neurotrophic factor (BDNF) (Rakofsky & Dunlop, 2013). Long-term mood stability may also be impaired by disruption in sleep architecture, which derives from chronic alcohol abuse. By affecting the nervous signaling system, possibly via a kindling process, excessive alcohol use may significantly worsen mood episodes in terms of frequency (i.e., rapid cycling) and severity. Alternatively, alcohol may aggravate BD neuro-progression via brain damages due to oxidative stress. Several alterations of ionotropic glutamate NMDA receptor (NMDAR) have been observed in BD, and NMDARs have been shown to mediate both acute and chronic effects of alcohol in the brain. Among BD subjects, pathophysiological impairments in NMDAR functioning may also contribute to vulnerability toward developing alcohol-related problems (Chitty et al., 2015, Fig. 38.2).

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FIGURE 38.2 A neurobiological model for AUD-BD comorbidity. Both the NMDA receptor (A) and oxidative stress (B) are implicated in the pathophysiology of BD. BD is a neuro-progressive illness and oxidative stress contributes to the gradual worsening of the disease over time (C). The consequences of neuro-progression and alcohol use in BD patients overlap (D). Alcohol induces Reactive Oxygen Species (ROS) production (E). NMDARs mediate both acute and chronic alcohol effects in the brain (F). Glutathione (GSH) is the major antioxidant in the brain, reducing ROS (G). Oxidative stress occurs when the balance of oxidant and antioxidant agents is in favor of the firsts (H). GSH can modulate the function of the NMDA receptor (I). Excessive activation of NMDA receptor by glutamate results in excitotoxicity and ROS production, that mediates cell death (J). Impaired NMDAR functioning contributes to the increased tolerance to alcohol and susceptibility to alcohol misuse (K). The impairment of NMDARs functioning in BD patients drives their increased susceptibility to alcohol use/misuse (L). Alcohol aggravates BD neuro-progression through oxidative stress pathway or via allostatic load on NMDARs (M). Solid black lines: established neurobiological pathways; solid gray lines: pathophysiological associations; gray dotted lines: associated symptoms/traits; black dotted lines: theoretical pathways; lightning bolts: potential pathways that can be pharmacologically modulated; gray boxes outlined in black dotted lines: neurobiological pathways associated with the BD-alcohol comorbidity. Source: Reproduced from Chitty, K.M., Lagopoulos, J., Hickie, I.B., & Hermens, D.F. (2015). Alcohol use in bipolar disorder: A neurobiological model to help predict susceptibility, select treatments and attenuate cortical insult. Neuroscience and Biobehavioral Reviews, 56, 193 206 with permission from the Publisher.

Structural and neurochemical alterations may also be related to chronic alcohol exposure in BD subjects. Decreased volumes in right anterior cingulate (ACC) and left prefrontal cortex (PFC), which are both involved in affect regulation and cognitive control (Moccia et al., 2017), have been observed in BD subjects with co-occurring AUD (Nery et al., 2011; Fig. 38.3). Furthermore, long-term remitting AUD-BD subjects show significantly lower glutamate levels in left dorsolateral prefrontal cortex (DLPFC) compared to BD patients without a previous history of AUD (Nery et al., 2010). Interestingly, low levels of glutamate and GABA within PFC have been negatively correlated to both craving and impulsivity in AUD-BD subjects (Prisciandaro et al., 2017). Although definitive conclusions cannot be drawn, these studies suggest that the physiological brain connectivity, which sustains mood stability, may be weaker in BD patients with co-occurring AUD compared to those without comorbidity. BD-SUD comorbidity has been conceptualized within an allostatic model of disease. Allostasis

broadly refers to the physiological mechanisms, including hypothalamic pituitary adrenal (HPA) axis functioning, circadian rhythms, immune-inflammatory systems, that are required for internal adaptation in face of perceived or anticipated demands. Although adaptive systems of allostasis can be protective for the individual, an allostatic load, which is associated with pathological conditions, ultimately results from chronic overactivity or inactivity of these physiological mechanisms that are involved in the adaptation to environmental challenges. The effects of allostatic load in the mesocorticolimbic brain system and in HPA axis may help to explain some findings, such as vulnerability to addiction, cognitive impairment, and higher rates of physical comorbidity and mortality that are frequently observed in BD. Consistently within this framework, BD has been conceptualized as a disease of cumulative allostatic loads whereby allostasis increases progressively as stressors, affective episodes, and drug abuse occur over time (Fig. 38.4). Similarly, allostatic alterations in the brain reward system could

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FIGURE 38.3 Differences in regional gray matter volumes in BD patients with, and without, comorbid AUD in a magnetic resonance imaging (MRI) study. Comorbid AUD-BD patients show decreased gray matter volumes of the left medial frontal gyrus (left panel) and the right anterior cingulate cortex (right panel) than BD patients without AUD. The cross-hair presents the coordinate with the maximum threshold. Source: Reproduced from Nery, F.G., Matsuo, K., Nicoletti, M.A., Monkul, E.S., Zunta-Soares, G.B., Hatch, J.P.. . . & Soares, J.C. (2011). Association between prior alcohol use disorders and decreased prefrontal gray matter volumes in bipolar I disorder patients. Neuroscience Letters, 503, 136 140 with permission from the Publisher. FIGURE 38.4 The allostatic load is increased by stressors, mood episodes and substances of abuse. According to the allostatic model, BD could be hypothesized as a disease of cumulative allostatic states where allostatic load progressively increases with (1) stressors, (2) clinical relapses, and (3) exposure to alcohol and substances of abuse. Increased allostatic load contributes to the development of cognitive impairments and interval dysthymia, as well as more physical and psychiatric comorbidities. Source: Reproduced from Kapczinski, F., Vieta, E., Andreazza, A.C., Frey, B.N., Gomes F.A., Tramontina, J.. . . & Post, R.M. (2008). Allostatic load in bipolar disorder: implications for pathophysiology and treatment. Neuroscience and Biobehavioral Reviews, 32 (4),675-692 with permission from the Publisher.

render BD patients more vulnerable to drug addiction, favoring a very rapid transition from occasional, recreational drug use to compulsive, pathological, and drug dependence (Fig. 38.5) (Kapczinski et al., 2008; Pettorruso et al., 2014).

PSYCHOPATHOLOGICAL CORRELATES High impulsivity characterizes both BD and AUD. On the one hand, increased impulsivity (i.e., the propensity to act rapidly without considering the

possible consequences) has been associated with the susceptibility for AUD (Fernie et al., 2013), but, on the other hand, impulsive behaviors could also originate because of excessive alcohol use (Voon et al., 2013). Impulsivity traits have been recognized as a core feature of BD, being present not only during manic episodes, but also during euthymic mood states (Swann et al., 2009). Growing evidence suggests that impulsivity may represent a link between BD and AUD/SUD (Di Nicola et al., 2010); accordingly, several studies found that patients with comorbid AUD-BD showed higher impulsivity traits compared to patients

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FIGURE 38.5 Allostatic alterations in BD and susceptibility to substance addiction. Allostatic changes in the brain reward system may render BD patients more vulnerable to drug addiction, favoring a rapid transition from occasional substances use to addiction. Mood episode recurrence and substance use have been hypothesized to contribute to stress system activation.

with BD alone (Nery et al., 2013). Affect instability, defined as “rapid oscillations of intense affect, with a difficulty in regulating these oscillations or their behavioral consequences” (Marwaha et al., 2014), is another common psychopathological feature of both BD and SUD. In BD, increased affect instability characterizes manic and mixed episodes, as well as euthymic periods. Moreover, affective dysregulation has been proposed as a susceptibility factor for problematic substance use independently from psychiatric diagnoses. Interestingly, in BD subjects, increased inter-episodic affective instability has been correlated with the presence of a lifetime AUD (Lagerberg et al., 2017). Finally, studies focusing on personality traits associated with AUD-BD comorbidity suggest that certain affective temperaments, including hyperthymic and irritable temperament, may be associated in BD with an increased vulnerability to develop problematic alcohol use (Singh et al., 2015).

CLINICAL FEATURES, COURSE AND PROGNOSIS BD and AUD seem to negatively influence the course of each other. Patients with AUD-BD comorbidity have an early age of onset and more severe mood episodes, compared to BD patients without addictive disorders (Ferrari et al., 2013; Nery, Miranda-Scippa, Nery-Fernandes, Kapczinski, & Lafer, 2014). They also show increased frequency of relapses, hospitalizations, mixed episodes, and rapid cycling (Salloum et al., 2005). Moreover, AUD-BD patients are more frequently comorbid with anxiety and other addictive disorders (Azorin et al., 2017), and show higher

impulsivity (Swann et al., 2009), violent behavior, legal problems, and suicide attempts (Rakofsky & Dunlop, 2013). Comorbid addictions in BD also worsen neurocognitive impairments (Balanza´-Martı´nez et al., 2015) and negatively affect global functioning and quality of life (Farren et al., 2012). Alcohol/substance use may also interfere with mood stabilizer therapy (Sportiche et al., 2017) and treatment adherence (Leclerc, Mansur, & Brietzke, 2013). As a result, comorbid AUD-BD patients show a significantly worse clinical outcome than patients with BD alone.

TREATMENT IMPLICATIONS Clinical programs that integrate treatments for substance use and comorbid psychiatric disorders are largely adopted. Nonetheless, little empirical work has been done to provide guidelines for prescribing pharmacotherapy for these patients (Pettinati, O’Brien, & Dundon, 2013). To date, the effectiveness of pharmacological compounds as monotherapy or adjunctive treatment in AUD-BD comorbidity has only been partially assessed (Naglich, Adinoff, & Brown, 2017). It has been observed that atypical antipsychotics represent a better choice than typical antipsychotics in treating comorbid AUD-BD patients, probably because of their weaker dopamine antagonism that results in a better management of craving symptoms. Among antipsychotic medications, quetiapine is the most extensively evaluated compound. In some open-label trials (Longoria, Brown, Perantie, Bobadilla, & Nejtek, 2004) quetiapine showed to be an effective add-on treatment in AUDBD comorbidity, improving both reduced alcohol

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intake and mood symptoms. However, these data have not been confirmed by randomized trials (Brown et al., 2014; Stedman et al., 2010; Brown, Garza, & Carmody, 2008). Partial data suggests effectiveness of aripiprazole (Brown, Jeffress, Liggin, Garza, & Beard, 2005) and olanzapine (Littlewood et al., 2015) in AUD-BD comorbidity, but randomized controlled trials are required before these compounds can be recommended in standardized treatment guidelines. Among mood stabilizing agents, divalproex is the only compound that showed some effect in improving drinking outcomes in comorbid AUD-BD patients. In a large, randomized, placebo-controlled trial, the administration of divalproex to lithium-treated comorbid patients significantly reduced alcohol intake (Salloum et al., 2005). However, early studies suggest that lithium alone is ineffective in treating drinking problems TABLE 38.1

in comorbid AUD-BD patients (Dorus et al., 1989; Fawcett et al., 1984). Other mood stabilizers, such as lamotrigine and topiramate, have been evaluated for treating AUD-BD comorbidity, with mixed results (Naglich et al., 2017; Sylvia et al., 2016). Data from clinical trials are summarized in Table 38.1. Among compounds with a specific indication for SUDs, the opioid antagonist naltrexone is the most investigated. Comorbid AUD-BD patients treated with naltrexone showed a trend towards a greater decrease in alcohol craving and drinking days than patients receiving placebo (Brown et al., 2009; Brown et al., 2006). Another opiate antagonist, nalmefene, has been demonstrated to significantly reduce alcohol consumption when taken as needed, with better tolerability than naltrexone (Di Nicola et al., 2017). Although nalmefene is likely to represent a valid therapeutic option,

Double-Blind, Placebo-Controlled Trials of Medications for AUD-BD Comorbidity

Patients Effect on drinking outcome

Recommended for AUD-BD Effect on mood outcome treatment

Medication

Dosage

Brown et al. (2008)

Quetiapine

600 mg (add-on)

115

No effect on PACSa, drinking days/week, heavy drinking/ week

Significant decrease in HAM-Db scores

No

Stedman et al. (2010)

Quetiapine

300-800 mg (add-on)

362

No effect on heavy drinking days, nondrinking days, standard drinking per day

Effect on YMRSc and CGId, but not on MADRSe or HAM-Af scores

No

Brown et al. (2014)

Quetiapine

600 mg (add-on)

90

No effect on any drinking outcome

No differences on HAMDb or YMRSc scores

No

Brown et al. (2009)

Naltrexone

50 mg (add-on)

50

Significant decrease in drinking days, alcohol craving, and liver enzyme markers

No differences on HAMDb or YMRSc scores

Yes

Tolliver et al. (2012)

Acamprosate 1998 mg (add-on)

33

No effect on time to first drinking day or time to first heavy drinking day

No differences on MADRSe or YMRSc

No

Geller et al. (1998)

Lithium

maintenance serum levels

25

Decrease in positive urine drug screens

-

No

Salloum et al. (2005)

Divalproex

maintenance serum levels

59

Significant decrease in number of heavy drinking days and drinks per heavy drinking

No differences on HAMDb or BRMSg scores

Yes

Sylvia et al. (2016)

Topiramate

300 mg (add-on)

12

Worse outcome for topiramate-treated patients

Improvements on HAMD and YMRS scores

No

a

PACS: Penn Alcohol Craving Scale. HAM-D: Hamilton Rating Scale for Depression. YMRS: Young Mania Rating Scale. d CGI: Clinical Global Impression. e MADRS: Montgomery-Asberg Depression Rating Scale. f HAM-A: Hamilton Rating Scale for Anxiety. g BRMS: Bech-Rafaelsen Mania Scale. The table shows the available double-blind, placebo-controlled trials conducted on eligible medications for the treatment of AUD-BD comorbidity. The average dosage used, number of recruited patients, and effectiveness on alcohol and mood outcomes are specified. b c

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SUMMARY POINTS

its efficacy has not yet been evaluated in comorbid AUD-BD patients (Mann, Bladstro¨m, Torup, Gual, & van den Brink, 2013). Partial evidence suggests that both acamprosate and disulfiram, which have been demonstrated to be useful in the management of AUD, may be effective in reducing alcohol intake in patients with BD and other psychiatric disorders (Tolliver, Desantis, Brown, Prisciandaro, & Brady, 2012). Psychosocial approaches (including psychotherapy) for patients with co-occurring BD and AUD have been widely adopted in several clinical programs. Among psychosocial treatments, the efficacy of Integrated Group Therapy (IGT) in BD-SUD comorbidity has been systematically investigated. Based on cognitivebehavioral therapy principles, IGT is specifically planned to integrate therapeutic interventions for both BD and AUD by focusing on the two disorders simultaneously. In order to promote the therapeutic process of acceptance, during IGT sessions particular emphasis is given to the reciprocal psychopathological interactions that occur between AUD and BD so that patients are led to think of themselves as having a single disorder. Evidence suggests that group and individual integrated interventions are, in fact, more effective in the management of AUD-BD comorbidity than psychotherapies focusing specifically on either disease. Other therapeutic approaches consist of psychoeducational programs which are often combined with self-help groups such as Alcoholics Anonymous (Farren et al., 2012).

MINI-DICTIONARY OF TERMS y-Aminobutyric acid (GABA) The main inhibitory neurotransmitter in brain. GABA is widely distributed within the neurons of the cortex, is involved in a great number of cortical functions, and in the pathogenesis of epileptic and anxious syndromes. Allostasis The ability to implement physiological or behavioral changes as a response to external or internal stimuli, in order to maintain stability (homeostasis). Allostatic load In the long run, allostatic mechanisms may fail, and allostatic load represents “the price to pay” to maintain homeostasis. Disability-adjusted life years (DALYs) A metric measure used to quantify the burden of a given disease/injury, and it is expressed as the number of healthy years lost. DALY incorporate both the mortality, quantified as the years of life lost (YLLs), and morbidity, quantified as years lived with disability (YLDs). Glutamate The main excitatory neurotransmitter in the brain. Glutamate is involved in synaptic plasticity, brain development, and cognitive functions, such as learning and memory. Moreover, glutamate plays a key role in clinical neurology because of its neurotoxicity at higher concentrations. Hyperthymic temperament A stable personality type characterized by increased energy, an exceptionally positive mood, and goaldirected attitude, as opposed to dysthymia.

Mixed affective state A mood state wherein features typical to both depression and mania occur either simultaneously or in very short succession. NMDA receptor Ionotropic glutamate receptor, consisting in an ion channel protein. The NMDA receptors play a key role in synaptic plasticity and memory function. Polygenic risk score (PRS) Corresponds to the cumulative effect of common loci with a single, small effect size, calculated by using P-values and logarithms of the odds ratio from a subset of single nucleotide polymorphism (SNPs), based on the genome-wide association studies (GWASs) of the Psychiatric Genetics Consortium. Rapid cycling A course specifier of BD, defined as having four or more mood disturbance episodes within a 1-year time span.

KEY FACTS Bipolar Disorders • Bipolar disorder (BD) is a serious mental disease, characterized by fluctuations in mood, ranging from major depression to manic states. • Despite the relatively low global prevalence, BD has a high global burden, due to its early onset, severity, and chronicity. • The bipolar spectrum includes Bipolar I disorder, Bipolar II disorder, cyclothymic disorder, and unspecified bipolar disorder. • Mood stabilizers (e.g., lithium, divalproex, and lamotrigine) are the pivot treatment of BD. • Atypical antipsychotics (e.g., olanzapine, quetiapine, aripiprazole) are extensively used as add-on therapy.

SUMMARY POINTS • Alcohol use disorder (AUD) represents a frequent comorbidity in patients with bipolar disorder (BD), with a prevalence rate of 30% 35%. • Shared genetic variants may increase the risk for both BD and AUD. • Alcohol intake might negatively affect long-term mood stability, by influencing several neurotransmitter functions and disrupting sleep architecture. • Alcohol may aggravate bipolar disorder neuroprogression via oxidative stress. • Impairments in NMDARs functioning may contribute to both BD and AUD vulnerability. • Allostatic changes in brain reward system may render BD patients more vulnerable to drug addiction. • AUD-BD patients show higher impulsivity compared to patients with BD alone; impulsivity may represent a link between the two conditions.

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• AUD-BD patients have an earlier onset, a worse course of illness, and poorer treatment response. • There is still a lack of evidence on effective treatments for patients with AUD and BD. • Divalproex is the only medication that has been found to be significantly effective in reducing alcohol intake in bipolar patients. • Psychotherapy and Integrated Group Therapy are effective in the management of AUD-BD.

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39 Socio-Emotional Deficits in Severe Alcohol Use Disorders 1

Pierre Maurage1, Benjamin Rolland2,3 and Fabien D’Hondt4,5

Laboratory for Experimental Psychopathology, Psychological Science Research Institute, Universite´ catholique de Louvain, Louvain-la-Neuve, Belgium 2UCBL, CRNL, INSERM U1028, CNRS UMR5292, Universite of Lyon, Lyon, France 3UPMOPHA Department, Le Vinatier Hospital Centre, University Service of Addictology of Lyon (SUAL), Bron, France 4University of Lille, CNRS, UMR 9193, SCALab - Sciences Cognitives et Sciences Affectives, Lille, France 5CHU Lille, Clinique de Psychiatrie, CURE, Lille, France

LIST OF ABBREVIATIONS AUD ToM

alcohol use disorders theory of mind

THE IMPORTANCE OF SOCIOEMOTIONAL FACTORS IN SEVERE ALCOHOL USE DISORDERS Severe alcohol-use disorders (AUD, following DSM5 nomenclature, Hasin et al., 2013) are a widespread pathology affecting 5% 10% of adults in Western countries, and constitute the most frequent psychiatric disorder (Rehm et al., 2010). In view of their omnipresence and large-scale negative consequences, they have emerged as a central experimental and clinical research field for a wide range of scientific disciplines during the past few decades, among which are psychology and neurosciences. Neuropsychological models of AUD have mostly conceptualized this disorder as characterized by a strongly increased attraction toward the substance, combined with a progressive loss of cognitive control over consumption. This consensual view is illustrated in the currently dominant theoretical proposals, namely the dual-process models (Stacy & Wiers, 2010), stating that AUD relies on the imbalance between an over-activated limbic-automatic system (involved in the appetitive responses towards alcohol-related stimuli) and an under-activated

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00039-8

prefrontal-cognitive system (involved in cognitive evaluation and behavioral control). This theoretical framework has received strong empirical support: on the one hand, the excessive activation of the automatic system has been documented by studies showing intense craving and attentional biases toward alcohol in AUD (Field & Cox, 2008); on the other hand, AUD is obviously characterized by impaired performance in a wide range of cognitive abilities, these impairments being particularly massive for inhibition and underpinned by large-scale frontal lobe dysfunctions (Stavro, Pelletier, & Potvin, 2013). Following this view, therapeutic programs should, thus, centrally aim at reestablishing an equilibrium between these two systems, by reducing automatic attraction, and/or increasing cognitive control. While offering a reliable conceptualization of AUD leading to fruitful experimental and clinical implications, dual-process models have neglected other key processes involved in the emergence and maintenance of AUD, among which are emotional and interpersonal disorders. Indeed, patients with AUD cannot only be defined as “dysregulated machines” presenting an automatic-control imbalance. As repeatedly reported in clinical observations, AUD is also an affective and relational disease: firstly, the comorbidity between AUD and mood disorders has long been established, most patients with AUD presenting intense negative emotionality, as well as depressive and anxious symptoms (Schuckit, 2006). Secondly, AUD is associated

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with familial, professional, and social difficulties, a majority of patients with AUD presenting reduced social networking, limited social support, or even persistent social isolation. Centrally, these socio-emotional disturbances should not be considered as secondary variables in AUD treatment as empirical studies have identified social support as a major factor for abstinence (Gordon & Zrull, 1991), and as 40% of relapses are directly attributed to persistent negative effects or reduced social networking (Zywiak, Westerberg, Connors, & Maisto, 2003). Negative emotionality and disrupted interpersonal functioning are, thus, at the heart of the addictive pathology, and a more inclusive conceptualization of AUD should include socioemotional impairments. However, evidence-based studies have long neglected these factors and their experimental exploration in AUD has only emerged during the past two decades. To underline the importance of social cognition in AUD, this chapter will propose a typology-based description of the currently available data regarding socio-emotional abilities in patients with AUD, and then identify the main fundamental and therapeutic perspectives in this field to encourage an in-depth experimental exploration of these factors, as well as their implementation in clinical evaluation and remediation settings.

A TYPOLOGICAL REVIEW OF SOCIAL COGNITION IN PATIENTS WITH AUD Social cognition is the ability to use psychological and cognitive resources to efficiently detect, understand, regulate, and react to stimulations emerging from interpersonal environments and social interactions (Green, Horan, & Lee, 2015). Although recent, the psychological and neuroscience exploration of social cognition in AUD constitutes a blooming research field. To offer the clearest possible description of this literature, this chapter’s review will use a classification of social cognition subcomponents proposed in schizophrenia research (Green et al., 2008), dividing these abilities into five subcategories (Fig. 39.1): Theory of Mind (ToM), social perception, social knowledge, attributional bias, and emotional processing. While these categories present some overlap and while several tasks simultaneously assess multiple categories, data will be described following this typology. First, ToM constitutes a complex social cognition component repeatedly shown as impaired in several psychopathological states, such as schizophrenia or depression (Bora, Bartholomeusz, & Pantelis, 2016). In AUD, several paradigms have been used to explore ToM abilities, from quite large batteries (Bosco, Capozzi, Colle, Marostica, & Tirassa, 2014) to more

specific investigations using the false-beliefs task (Fig. 39.2; Maurage, de Timary, Tecco, Lechantre, & Samson, 2015) or the faux-pas task (Thoma, Winter, Juckel, & Roser, 2013). These works led to coherent results documenting reduced ToM abilities in AUD; this deficit being present for all subcomponents of ToM (first-/third-person perspective taking, first-/ second-order inferences). Moreover, beyond this generalized deficit, other studies have explored the dissociation between cognitive and affective ToM, suggesting that the affective component (i.e., others’ emotions or feelings) is more strongly impaired (Nandrino et al., 2014). Beyond these dissociations, patients with AUD, thus, present significantly reduced ToM abilities, as clearly confirmed by meta-analyses (Bora & Zorlu, 2017; Onuoha, Quintana, Lyvers, & Guastella, 2016). Additionally, a social cognition component strongly associated with ToM is empathy. The links between ToM and empathy are still being debated (Green et al., 2015), but empathy is clearly a key component to develop and maintain efficient social interactions, and this ability is impaired in AUD: a first study observed lower empathy levels in AUD (Martinotti, Di Nicola, Tedeschi, Cundari, & Janiri, 2009), while later explorations (Maurage et al., 2011) showed a dissociation between impaired affective (i.e., detecting and feeling others’ emotional states) and preserved cognitive (i.e., understanding others’ nonemotional, mental states) empathy subcomponents. Second, social perception is evaluated by tasks presenting pictures or videos of social interactions, based on which the participant has to interpret verbal and nonverbal content to understand multifaceted interpersonal relations. This subcomponent had already been partly measured in the ToM tasks (Nandrino et al., 2014), but the measure of social perception abilities in AUD has been more directly conducted in two studies: A recent one (Maurage et al., 2016) used the “Movie for Assessment of Social Cognition task” (Fig. 39.3; Dziobek et al., 2006), requiring the participant to detect and categorize the thoughts, affects, and actions of four characters, and to infer their intentions and interpersonal relations. Patients with AUD were impaired in understanding the emotions expressed by the characters, but remained able to comprehend their nonemotional thoughts or behaviors. This result thus extends, on the basis of a more direct measure of the interpersonal relationships’ perception, the proposal of a dissociation between an impaired emotional subcomponent of social cognition and a preserved cognitive one. Another study, using neuroimaging measures, went one step beyond this by exploring the cerebral correlates of social perception in AUD, but also the self-related consequences of negative social interactions (Maurage et al., 2012). This study used the

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FIGURE 39.1 Subcomponents of social cognition. Graphical presentation of the five subcomponents related to social cognition, as defined by Green et al. (2008).

cyberball paradigm (Williams & Jarvis, 2006), a balltossing game in which a situation of social rejection is created by leading two other computer-guided players to exclude the participant from the game. When confronted with rejection, patients with AUD presented an increased social perception of this ostracism (indexed by more intense ostracism feelings and insula/cingulate cortex activities). These results, thus, suggest that, regarding social perception, AUD is associated with: (1) a reduced ability to take into account others’ emotional states during tasks in which the participant is not involved; (2) conversely, an increased sensitivity to the social perception of others thoughts and behaviors when these are directed toward the participant, threatening their social integration. Third, preliminary results suggest that AUD is associated with abnormalities in social knowledge, which might constitute a core deficit provoking a cascade of negative consequences for social interactions. Specifically, patients

with AUD have a reduced ability to correctly perform a humor detection task based on written jokes involving interpersonal contexts (Uekermann, Channon, Winkel, Schlebusch, & Daum, 2007). This indexes a difficulty to use social knowledge to identify the humoristic break of social rules provoked by an incongruity in the described interactions. It has also been shown that AUD is related to a reduced detection of irony (Amenta, Noe¨l, Verbanck, & Campanella, 2013), witnessing a reduced knowledge of the social rules and roles underlying human interactions. Another social knowledge facet measured in patients with AUD is the presence of maladaptive self-beliefs related to social standards: patients with AUD present a specific tendency to over-evaluate the standards required in social interactions (Maurage et al., 2013). In other words, AUD is related to an exaggerated estimation of the requested interpersonal performance to obtain a satisfactory social outcome. This biased social knowledge, strongly correlated with interpersonal difficulties, could, thus, contribute to the emergence of a

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FIGURE 39.2 False-beliefs task. Schematic illustration of the events’ sequence in the false-beliefs task used to explore ToM in AUD. (A) Track-Task (spontaneous tracking of the other person’s perspective): (1) The woman (right) watches in which box the green object is located (while the participant cannot see it); (2) She leaves the room and the man (left) switches boxes; (3) She returns and gives a hint by placing the pink object on one of the boxes to help finding the green object. At this point, the participant has to point to the box containing the green cube; (B) Inhibit-Task (self-perspective inhibition): (1) The woman watches in which box the green object is located. The participant can also see the object‘s location; (2) The woman leaves the room and the man changes the object‘s location; (3) The woman returns and the participant has to indicate which of the two boxes the woman will open first. Note: for description’s clarity, the green cube is visible in the illustration whereas it is hidden in the box during the experiment.

FIGURE 39.3 Movie for Assessment of Social Cognition task. Illustration of an item of the Movie for Assessment of Social Cognition task used to explore social perception in AUD. The upper part describes the critical sequences of the video. The lower part gives the four possible answers proposed to the participant.

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TOWARDS A DEEPER UNDERSTANDING OF SOCIAL COGNITION IN PATIENTS WITH AUD

vicious cycle: the exaggerated standards may lead to negative feelings during social interactions, which might, in turn, increase social isolation. Fourth, attributional bias is the only subcomponent of social cognition still to be explored in patients with AUD. Many studies have been conducted on attentional or cognitive biases among patients (Field & Cox, 2008), but this approach has not yet been applied to interpersonal biases. Several studies have identified attributional biases in other psychiatric states, and these results should encourage future works to explore these processes in patients with AUD by using attributional bias tasks (e.g., Combs, Penn, Wicher, & Waldheter, 2007). Fifth and finally, numerous studies have been conducted to explore emotional processing in patients with AUD. After a seminal study (Philippot et al., 1999) describing a reduced ability to identify the emotional states expressed by human faces, a large variety of experimental designs have been used (Donadon & Oso´rio, 2014) presenting various facial emotions by means of numerous procedures, most results confirming the presence of this deficit: patients with AUD need more emotional intensity to detect others’ affective states (Fig. 39.4; D’Hondt, de Timary, Bruneau, & Maurage, 2015). Importantly, this deficit appears specific for emotional states and more intense for negative emotions (Bora & Zorlu, 2017). However, it is generalized to all emotional stimulations, including voice prosody or body posture (Maurage et al., 2009). As the aptitude to decode emotional cues offered by others is crucial to efficiently understand their state-of-mind and affective feelings, it has been suggested that this global emotion decoding difficulty in patients with AUD plays a role in the reduction of interpersonal bonds and in the social isolation frequently observed

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in this population (D’Hondt, Campanella, Kornreich, Philippot, & Maurage, 2014). Moreover, the impaired capacity to identify others’ emotions in patients with AUD also extends towards the identification of one’s own emotions, as AUD is related to increased alexithymia, that is, an impaired ability to feel, identify, and express internal affective states (Stasiewicz et al., 2012).

TOWARDS A DEEPER UNDERSTANDING OF SOCIAL COGNITION IN PATIENTS WITH AUD Overall, the large majority of studies exploring social cognition in AUD have documented substantial impairments, particularly for ToM and emotional processing. In view of the key role played by these aptitudes in interpersonal relations, these impairments might contribute to the personal, professional, and societal difficulties reported in patients with AUD (Kornreich et al., 2002) and should, thus, be further considered in clinical settings beyond the classical focus on cognitive functions. In this respect, it is noteworthy that the correlation between AUD-related deficits in social cognition and standard clinical features of AUD severity—for example, DSM-5 AUD criteria (Hasin et al., 2013), “Alcohol Use Disorder Identification Test” score (Bohn, Babor, & Kranzler, 1995), or features of AUD outcomes like postdetoxification relapse rates—have hardly been explored, as only one study (Rupp, Derntl, Osthaus, Kemmler, & Fleischhacker, 2017) showed that reduced emotional processing abilities at the start of treatment is associated with higher relapse rates, thus, confirming the involvement of social cognition in clinical outcomes.

FIGURE 39.4 Emotional processing paradigm. Example of stimuli illustrating the various emotional valences and intensities used to explore emotion processing in AUD. (A) Example of a realistic face depicting four different prototypical emotional facial expressions (neutral, happy, angry, and sad); (B) Example of a morphing continuum (angry sad) for one identity. The percentage of each emotion contained in each of the 10-morph step is mentioned at the bottom of the figure (e.g., 95% 5% means that this stimulus contains 95% of anger and 5% of sadness).

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Furthermore, future studies should also couple the neuropsychological assessment of social cognition with more clinically-focused tools used to assess social functioning—for example, Measurement in Addictions for Triage and Evaluation, whose assessment is partly based on the WHO international classification of functioning (Schippers, Broekman, Buchholz, Koeter, & van den Brink, 2010). Another challenge regarding future studies is that this research field suffers from a lack of theoretical background and experimental coherence, as studies have not been integrated into a clear fundamental model. The present attempt to offer a typology of social cognition data in patients with AUD, based on the proposals emerging in other psychiatric states, has clearly shown that, while ToM and emotional processing have been largely studied (using scattered and often multidetermined paradigms), other components of social cognition have not been thoroughly measured. A first major research perspective would, thus, be to capitalize on the typology presented here to develop a coherent research program which would propose, for each identified social cognition subcomponent, an in-depth exploration based on controlled and component-specific tasks, as initiated in schizophrenia (Green et al., 2015), as well as on a strict control of AUD characteristics and comorbid psychopathological states. Recent papers (Kwako, Momenan, Litten, Koob, & Goldman, 2016) have initiated this ambitious program by proposing a neuroscience-grounded battery to explore key variables in AUD, among which are some measures of emotional and social processing. This constitutes an important first step towards a rational evaluation of social cognition in patients with AUD, despite a still quite imprecise specification of the processes to be evaluated. Beyond the needed clarification and deepening of the core socio-emotional processes at stake in patients with AUD, other crucial research questions should be addressed (Fig. 39.5), among which: 1. The interactions between socio-emotional and cognitive processes: Most studies have explored social cognition in AUD in an isolated fashion, but these abilities might strongly interact with other AUD deficits, and centrally cognitive functions. Preliminary results have indicated that social cognition in AUD is influenced by working (Uekermann et al., 2007) or autobiographical (Nandrino et al., 2014) memory, and that socioemotional difficulties might be partly caused by visuo-perceptive impairments (D’Hondt, Lepore, & Maurage, 2014), but these proposals should be confirmed using more controlled joint explorations of socio-emotional and cognitive abilities.

2. The interindividual variability of socio-emotional deficits: All presented studies have capitalized on a groupbased approach, considering patients with AUD as a homogeneous population. However, when going one step beyond this to analyze individual performances, it appeared that only 50% of patients with AUD present a genuine ToM deficit (Maurage et al., 2015). Moreover, this heterogeneity in socioemotional disorders has been specifically explored using a cluster analytic approach (Maurage, de Timary, & D’Hondt, 2017), which clearly showed that AUD is a constellation of individuals with a wide variety of socio-emotional profiles. Future studies should, thus, systematically complement the classical group approach by individual analyses specifying the interindividual variation of the deficits, as well as the differential role played by psychopathological and addictive comorbidities. 3. The causal relation between AUD and social cognition deficits, and their evolution: Previous studies have focused on recently detoxified patients with AUD. This focus did not allow determining whether socioemotional impairments are a consequence of the neurotoxicity provoked by repeated excessive alcohol use or, at least partly, a causal factor involved in AUD development. More globally, the evolution of social cognition deficits during the course of the disease (e.g., after long-term abstinence) and in its successive stages should be more thoroughly explored through longitudinal studies and explorations focused on other alcohol-consumption patterns related to socio-emotional impairments—for example, binge drinking (Maurage, Bestelmeyer, Rouger, Charest, & Belin, 2013). 4. The inclusion of social cognition deficits in AUD models: The dominant dual-process models have not integrated emotional and social functions, which are still considered as mere side-products of the imbalance between automatic and controlled systems. A subsequent theoretical proposal, the triadic model (Noe¨l, Brevers, & Bechara, 2013), postulates a third insula-based system involved in the detection of interoceptive signals and in their conversion in affective feelings. This model, while having received limited empirical support as yet, might constitute a foundation to integrate socioemotional deficits in AUD models. Finally, these research results should urgently be integrated into clinical practices, where social cognition deficits are totally under-evaluated and undertreated, despite repeated clinical observations underlining their importance in the detoxification process. Centrally, proposals regarding the implementation of

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MINI-DICTIONARY OF TERMS

379 FIGURE 39.5 Proposal for future research avenues. Graphical synthesis of the main research perspectives proposed to deepen the understanding of social cognition in patients with AUD.

cognitive remediation in addictive disorders have recently bloomed (Verdejo-Garcia, 2016), but these programs have been focused on cognitive variables. In line with what has been proposed in schizophrenia (Grant, Lawrence, Preti, Wykes, & Cella, 2017), a structured neuropsychological training program focusing on the evaluation and training of social cognition in patients with AUD should urgently be tested in care structures as it could improve socio-emotional abilities, but also positively impact clinical outcomes of patients by breaking the vicious cycle linking social cognition deficits, social isolation, and alcohol consumption.

MINI-DICTIONARY OF TERMS Attributional bias The propensity to consider that the personal and interpersonal events occurring in one’s life are mostly due to internal (i.e., individual responsibility) or external (i.e., others’ responsibility or contextual variables) causes.

Emotional processing The efficient perception, interpretation, and reaction to the emotional states expressed by other individuals through their facial expression, voice prosody, or body posture, as well as the correct decoding and regulation of one’s own affective states. Empathy The capacity to understand other individuals’ cognitive or affective perspectives and to propose a verbal or behavioral answer adapted to the emotions, feelings, or thoughts they expressed. Social cognition The psychological processes related to the identification and interpretation of social signals sent by other individuals in interpersonal contexts, as well as the skills needed to effectively respond to these signals. Social knowledge The awareness and understanding of the rules and conventions to be followed during social interactions, and of the role assigned to each participant in social contexts. Social perception The aptitude to interpret verbal and nonverbal stimuli to infer individuals’ role and current relationships in equivocal or intricate interpersonal contexts. Theory of mind The ability to use the interpersonal signals produced by other individuals to infer their mental states, thoughts, or emotions, and to anticipate their behaviors or actions.

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KEY FACTS Social Cognition in Alcohol Use Disorders • Severe alcohol use disorders (AUD) are the most frequent psychiatric disorder, affecting 5% 10% of adults in Western countries. • AUD are associated with cognitive deficits, as indexed by altered perceptive motor, attentional and memory capacities, but also reduced executive functions (e.g., inhibition, flexibility, problem solving). • Social cognition impairments have more recently been identified in patients with AUD, encompassing reduced performance in Theory of Mind (i.e., the inference of others’ mental states based on the interpersonal signals they send) and emotion decoding (i.e., the decoding of others’ emotional states expressed through their face, voice, or body)—two central abilities for efficient social interactions. • These social cognition deficits might favor the persistence of AUD in patients by creating a vicious cycle: impaired social cognition would lead to social isolation, itself leading to increased alcohol consumption used as a coping strategy, which would, in turn, aggravate social cognition impairments due to alcohol neurotoxicity. • Social cognition should, thus, be further investigated in AUD, and more globally in addictive states, notably to specify its role in the emergence and stabilization of excessive alcohol consumption and its evolution during the disease’s course.

SUMMARY POINTS • This chapter reviews social cognition impairments in alcohol use disorders (AUD). • Beyond the well-established cognitive deficits, AUD are also characterized by large-scale impairments to detect, interpret, and use social signals in interpersonal contexts. • Reduced abilities have been repeatedly found for Theory of Mind and emotion processing among patients with AUD. • The potential deficit for other social cognition subcomponents (social perception, social knowledge, and attributional bias) has still to be thoroughly evaluated. • Future studies should also explore the causal links between AUD and social cognition deficits, as well as their interactions with cognitive deficits and their variation across individuals with AUD.

• In view of the massive alterations observed for socio-emotional processes in patients with AUD, these factors should be taken into account in clinical settings, centrally, by proposing a specific social cognition evaluation and training.

Acknowledgments Pierre Maurage is research associate at the Fund for Scientific Research (F.R.S.-FNRS, Belgium). This chapter was supported by a grant from the “Fondation pour la Recherche en Alcoologie” (FRA, France).

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C H A P T E R

40 Relapse Risks in Patients With Alcohol Use Disorders 1

Ayako Yamashita1 and Shin-ichi Yoshioka2

Department of Nursing, Faculty of Human Health Sciences, Niimi College, Niimi, Japan 2School of Health Science, Tottori University Faculty of Medicine, Yonago, Japan

LIST OF ABBREVIATIONS AA AAH ARRS AI CA EP NE PE SV AUD CBT CET CST

alcoholics anonymous AA-related helping alcohol Relapse Risk Scale awareness of illness compulsivity for alcohol emotionality problems lack of negative expectancy for alcohol positive expectancy for alcohol stimulus-induced vulnerability alcohol use disorder cognitive behavioral therapy cue-exposure treatment coping skills training

INTRODUCTION The development of alcohol use disorders (AUD) is influenced by biological, psychological, and social factors. Although the importance of biological factors is evident, an understanding of the psychosocial factors related to AUD is lacking, and this is needed to support patients who have recovered and to prevent their relapse. As the understanding of biological factors related to addiction has expanded, it has also become clear that relapse and its management are influenced by psychosocial factors and their interactions. Despite the recent developments in the biology of addiction, a significant part of relapse and its management is still influenced by psychosocial factors and the interplay between them (Sureshkumar, Kailash, Dalal, Reddy, & Sinha, 2017).

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00040-4

AUD is a chronic disorder in which patients are unable to control their alcohol consumption, and the patient’s life can revolve around alcohol consumption. When treating AUD, the interventions are matched to disorder severity and the stage of the recovery process. Drug-seeking behavior is stimulated by a strong physical and psychological dependence. AUD patients repeatedly experience trembling extremities, sweating, irritability, and other unpleasant symptoms. If they repeatedly consume more alcohol to avoid experiencing physical complications, withdrawal symptoms, mental pressure, or alcohol craving, then they lose even more control of their alcohol consumption. When drinking occupies a large part of a patient’s life, it has a negative influence on their studies or work and decreases their quality of life. Alcohol abuse or addiction leads to an abundance of mental, physical, and social problems that lead to a cycle of dependence (Robinson & Berridge, 1993) despite an understanding of the harmful effects of drinking. The decline in quality of life caused by AUD is evidenced by a deterioration in academic performance, work performance, and social relationships caused by increasingly severe alcoholrelated problems, and alcohol consumption occupies a central role in daily activities. Recovery support requires a holistic approach to interventions that improve the quality of life. To recover from AUD, patients must acknowledge their drinking patterns and adopt strategies to cope with the factors that cause them to drink. Recovery is considered to be “the process of overcoming the severe effects of mental disorder and finding a new meaning and purpose in life” (Anthony, 1993). Recovering from AUD involves breaking out of

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40. RELAPSE RISKS IN PATIENTS WITH ALCOHOL USE DISORDERS

a lifestyle controlled by a dependence-producing drug, correcting existing patterns of thought and action, and adopting a new way of life that does not require drug intoxication. Successful recovery depends on not only stopping the use of alcohol, but also acquiring lifestyle habits and coping skills that do not require alcohol. AUD easily becomes chronic if dependency develops. Even after abstaining for a long period of time, patients can relapse if they begin to drink again. Being a survivor means confronting the impulse to drink, controlling the disorder, and breaking free from the cycle of addiction that depends on strong craving leading to drug-seeking behavior. The recovery process exists against a backdrop of recovery stories. This review outlines a typical recovery process model as applied to AUD, and discusses the psychosocial risks of relapse. Studies that focus on the concept of resilience with regard to AUD relapse and on methods of providing psychosocial support are discussed.

Relapse as It Applies to AUD What constitutes an AUD relapse? A major difficulty encountered when evaluating AUD treatment outcomes and relapse rates is the lack of consensus about the definition of a relapse (Witkiewitz & Marlatt, 2007). A patient experiences a relapse as loss of control of alcohol use and psychological dependence and/or withdrawal symptoms that result in their everyday life being negatively impacted. Relapse is an integral part of recovery (Marlatt & George, 1984), and from the perspective of an intervener, it is not a sign of a treatment failure, but an event that highlights the need for lifestyle intervention and promotion of health and welfare aimed at improving the patient’s coping skills. The resumption of drinking is an event associated with relapse, but a relapse does not necessarily indicate a resumption of drinking. As an index of recovery from AUD, relapse risk is evaluated by considering various factors, and rehabilitation steps are accordingly performed to improve quality of life. A study of abstinence in patients in Japan who were hospitalized for alcohol dependence reported an abstinence rate of 28% 32% 2 3 years after hospital treatment, 22% 23% 5 years after treatment, and 19% 30% 8 10 years after treatment. Most patients relapsed soon after discharge, but the abstinence rate stabilized at 20% 30% 5 years after treatment (Matsushita, 2012). Other studies have reported that the treatment of AUD was still successful in 29.5% patients 3 years after discharge, with AUD relapse rates 5.6% at 5 years, 9.1% at 10 years and 12% at 20 years after discharge (Tuithof, Ten Have, van den Brink, Vollebergh, & de Graaf, 2013). From the above, we can see that AUD relapses are repeating incidents of impaired control of drinking

habits. The treatment of psychological or substance use disorders can thus be called a “rocky road” (Witkiewitz & Marlatt, 2007). The definition of relapse varies among researchers and clinicians, but it generally refers to the return to a previous level of symptomatic behavior. The model for relapse prevention proposed by Marlatt and Gordon is an important element in treating alcohol dependence (Larimer, Palmer, & Marlatt, 1999). Their model (Marlatt & George, 1984) assumes the importance of the psychosocial factors that contribute to relapse, and a key consideration in the management of AUD and relapse prevention depends on discovering the connections between psychosocial factors and relapse.

Recovery From AUD AUD relapse can be caused by a combination of diverse factors. It is necessary to systematically identify these in the patient environment, and then consider their individual importance to minimize relapse risk. Recovery necessarily includes the patient as an active and responsible participant in their own rehabilitation project. As the patient’s environment influences recovery (Deegan, 1988), the AUD recovery process continues while the investigation regarding the environmental factors that lead to drinking is ongoing. Biopsychosocial Model The biopsychosocial model (Engel, 1977) is often considered when discussing factors influencing AUD (Correˆa Filho & Baltieri, 2012; Johnson et al., 1998) as it takes into consideration dimensions that are lacking in models based on biomedical science alone. In this model, relapses are caused not by a single factor, but by a combination of various biopsychosocial factors. It is designed to help to prevent relapse by assessing patients from many different perspectives to gain a deeper understanding of how they succumb to AUD and to clarify relapse risk. Stages of Behavioral Change Model In terms of recovery support for AUD patients, a stage of change approach using the transtheoretical model (Prochaska & DiClemente, 1983) has been shown to be effective in facilitating behavioral change (Peteet, Brenner, Curtiss, Ferrigno, & Kauffman, 1998). This approach is based on a study of people who voluntarily stopped smoking. The stages of behavioral change are precontemplation (not thinking about behavioral change), contemplation (considering the advantages and disadvantages of behavioral change), preparation (making the decision to change and forming an action plan), action (acting to bring about specific change), and maintenance (maintaining changes made over the long-term).

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INTRODUCTION

Those providing support to AUD patients need to understand episodes of the psychological and physical suffering that result from the cravings associated with drug-seeking behavior and are part of the cycle of dependency. This model is useful for assessing the AUD patient’s recovery stage and the need for intervention.

Risk Of Psychological Relapse Relapse is often caused by a distorted understanding of drinking-related behavior patterns and psychological dependence. The development of psychological dependence creates strong cravings that drive the search for the item that is the subject of the dependence. During recovery from AUD, relapse risk is evaluated in consideration of the potential influence of various factors; rehabilitation then proceeds with the aim of improving quality of life. Craving Depression, which is caused by mood disorders such as impulsive emotions and other psychiatric comorbidities associated with cravings that are part of drug-seeking behavior, increases the AUD relapse risk. Items related to craving include three factors: negative emotions as precipitants of drug use, positive emotions, and difficulties attributed to coping with craving (Martı´nez-Gonza´lez, Vilar Lo´pez, Lozano-Rojas, & Verdejo-Garcı´a, 2017). Coping Skills The cognitive behavioral model of AUD relapse prevention (Witkiewitz & Marlatt, 2004) includes personal factors, skills for coping with psychological pain and other types of stress, and environmental factors such as interpersonal relationships and accessibility to alcohol. In AUD, alcohol is the chosen means of dealing with stress, and training is, thus, provided to help patients gain the skills required to avoid drinking. This training uses cognitive behavioral therapy (CBT), where the patient is taught how to change their cognitive formulation and behavior towards drinking. Coping skills training (CST) is also an effective method for decreasing the frequency and severity of AUD relapse. The effectiveness of CST has been documented (Monti & Rohsenow, 1999), and together with body/mind relaxation techniques, CST is a major component of CBT (Longabaugh & Morgenstern, 1999), the aim of which is to acquire healthy skills for dealing with stress. Cue-exposure therapy (CET) exposes the patient to alcohol-related cues (e.g., the sight or smell of alcohol), thereby allowing the patient to practice responses to such cues in real-life situations (Drummond & Glautier, 1994). CET also teaches a variety of coping skills for dealing with urges caused by such cues (Witteman et al., 2015).

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Stress has both physiological and psychological aspects, and the relationships of psychological symptoms and physical condition and how to deal with the resulting stress have been widely studied. Coping skill, as mentioned earlier, refers to methods for dealing with stress, while stress management refers to actions that are taken to decrease stress response or to prevent, or recover from, stress disorders (Shapiro, Shapiro, & Schwartz, 2000). Teaching stress management to someone with AUD involves providing an accurate understanding of stress and how to recognize and deal with it, and then continuing to help until they can deal with it on their own. This self-care process requires self-monitoring of the signs of the cognitive process and self-insight. As relapse is a process that progresses in stages over a period of time, a key concept of relapse prevention is patient recognition of the first signs of relapse, which is the stage with the greatest possibility of successful treatment (Melemis, 2015). Social anxiety disorders and suicidal ideations are considered to increase relapse risk (Soundararajan, Narayanan, Agrawal, & Murthy, 2017). Mindfulness-based cognitive therapy is one way to monitor the discomfort associated with cravings and any negative influences and, thus, decreases relapse risk. Previous reports have confirmed the potential (Bowen et al., 2014) and effectiveness (Zgierska, Shapiro, Burzinski, Lerner, & Goodman-Strenski, 2017) of this method to improve coping skills that support long-term success. Self-Efficacy Monti et al. reported a correlation between a decline in self-efficacy and an impulse to drink, and the resumption of drinking. They also found a correlation between a decline in general coping skills, self-efficacy, impulse development, and the resumption of drinking (Monti et al., 2001). Spirituality People who have had a spiritual experience have a lower relapse rate, and increased feelings of spirituality are associated with an increased likelihood of successful recovery (Schoenthaler et al., 2015).

Sociological (Environmental) Relapse Risks Drug abuse leads to drug cravings and may also affect drug-seeking behavior (Conklin, Robin, Perkins, Salkeld, & McClernon, 2008; Stevenson et al., 2017). When abstainers are in an environment where they have previously experienced the pharmacological effects of alcohol, they experience tremendous pressure to relapse (Janak & Chaudhri, 2010). For patients to endure the strong alcohol-stimulated cravings and stay on the path to recovery, in spite of relapses, they need

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40. RELAPSE RISKS IN PATIENTS WITH ALCOHOL USE DISORDERS

the support and understanding of everyone around them, such as coworkers and family members. They also need a treatment environment where they can talk with people who have had similar experiences and to find role models for recovery. Interpersonal Relationships Rehabilitation is conducted through self-help groups focused on helping participants improve their quality of life. Self-help groups enable patients to form relationships with people who have had similar experiences and to aim for recovery. A study of Alcoholics Anonymous (AA) attendees with a 10-year follow-up showed that AA-related helping had a direct influence on the decreased relapse risk of attendees (Pagano, White, Kelly, Stout, & Tonigan, 2013). Family It is clear that factors such as persistent psychiatric symptoms and marital status influence relapse (Zeng, Wang, & Xie, 2016).

the depth of self-disclosure scale (Niwa & Maruno, 2010); and (3) the risk for relapse, which was assessed using the Alcohol Relapse Risk Scale (ARRS; Ogai., et al., 2009). The bidimensional resilience scale measures innate-resilience factors, which are strongly related to an individual’s inherent nature, and acquired-resilience factors, which are those acquired later in life and are affected by an individual’s environment. A higher score indicates stronger resilience. The depth of self-disclosure was gauged using a scale based on the social penetration theory, which consists of four levels: hobbies (Level 1), difficult experiences (Level 2), defects or weaknesses that are not detrimental (Level 3), and negative characteristics and abilities (Level 4). A higher score means a deeper level of self-disclosure. ARRS was used to assess relapse risk using five subscales: (1) stimulus-induced vulnerability (SV); (2) emotionality problems (EP); (3) compulsivity for alcohol; (4) lack of negative expectancy for alcohol (NE); and (5) positive expectancy for alcohol (PE). Five supplementary items provided insight into the respondent’s intensity of awareness regarding their condition. ARRS overall score was calculated from the

Resilience for Recovery Recovery Support to Increase Resilience “Resilience” has been described as a natural potential that aids AUD patients in recovery (Alim et al., 2012). Resilience is a dynamic process that encompasses positive adaptation during situations of significant adversity (Rutter, 1985). Resilience can include factors linked directly to the individual and factors acquired while the patient experiences various environments (Luthar, Cicchetti, & Becker, 2000). It is defined as “processes and factors that can promote patients’ innate potential for recovery and help to prevent psychiatric disorders.” In this section, we review results from our study on the effect of resilience on self-disclosure and relapse risk in AUD patients participating in a self-help group, and discuss methods for providing them with psychosocial support. Resilience Associated With Self-Disclosure and Relapse Risks in Patients With AUD The aim of this study was to clarify the selfdisclosure and risks of relapse associated with promoting the resilience of patients with AUD and participating in self-help groups (Yamashita & Yoshioka, 2016). The study was conducted with 48 AUD patients who filled out self-administered questionnaires between February and April 2015. The questionnaire included questions regarding basic attributes: (1) the level of resilience, which was assessed using the bidimensional resilience scale (Hirano, 2010); (2) the level of self-disclosure, which was assessed using

TABLE 40.1

The Mean Value for Scale (n 5 48)

Items

M 6 SD

BIDIMENSIONAL RESILIENCE SCALE Innate-resilience factors

38.2 6 8.1

Acquired-resilience factors

30.1 6 5.5

SELF-DISCLOSURE SCALE (A SCALE TO ASSESS DEPTH OF SELF- DISCLOSURE) Level 1 (hobbies)

31.7 6 9.5

Level 2 (difficult experiences)

18.6 6 4.9

Level 3 (foibles)

24.5 6 7.7

Level 4 (inferior personality characteristics and abilities)

28.5 6 9.1

Total

103.3 6 26.9

ALCOHOL RELAPSE RISK SCALE Stimulus-induced vulnerability

11.7 6 4.7

Emotionality problems

12.3 6 3.7

Compulsivity for alcohol

3.8 6 1.5

Lack of negative expectancy for alcohol

6.5 6 2.2

Positive expectancy for alcohol

4.3 6 2.1

Awareness of illness

10.6 6 2.8

Total

38.5 6 10.5

AUD, alcohol use disorders; M, mean; n, number of participants. Modified from Yamashita, A., & Yoshioka, S. (2016). Relapse risks in patients with alcohol use disorders. Yonago Acta Medica, 59(4), 279 287; with permission.

III. PSYCHOLOGY, BEHAVIOR, AND ADDICTION

IMPLICATIONS FOR TREATMENTS

five subscales, with higher scores indicating a greater risk for relapse. The mean value for each scale is shown in Table 40.1. Score distributions for the [bidimensional] resilience scale, self-disclosure scale and ARRS are shown in Fig. 40.1. Comparative analysis of the two groups (higher and lower innate-resilience groups) on the basis of their median acquired-resilience scores revealed that the higher acquired-resilience group had a significantly lower total score and lower scores for risk factors for relapse, such as EP and PE, whereas they had higher innateresilience factors with deeper levels of self-disclosure at all levels. There was a significant positive correlation between innate and acquired-resilience factor scores, whereas inherent resilience factor scores showed a significant negative correlation with risk factors for relapse and a positive correlation with self-disclosure scores. Acquired-resilience factor scores showed a significant negative correlation with risk factors for relapse and a positive correlation with self-disclosure scores.

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Multiple logistic regression analysis (maximum likelihood method) of resilience revealed that significant factors in the higher innate-resilience group included ARRS and acquired-resilience scores, whereas significant factors in the higher acquiredresilience group included innate-resilience scores (Table 40.2). Innate/Acquired Resilience Have a Mutually Reinforcing Relationship Patients with high resilience had lower risk of alcohol relapse and deeper self-disclosure. The results suggest that as one way of recovery support of patients with AUD, assisting them in building personal relationships with others and in deepening self-disclosure in a setting where they can relax, result in the promotion of their natural ability to recover.

IMPLICATIONS FOR TREATMENTS Psychological risk factors for AUD relapse include strong cravings for alcohol associated with behavior patterns that lead to drinking and psychological

FIGURE 40.1 Histograms of the total scores of each scale. Histograms of the total scores of each scale. (A) Innate-resilience scores. (B) Acquired-resilience scores. (C) Alcohol relapse risk scale scores. (D) Self-disclosure scale scores. Source: From Yamashita, A., & Yoshioka, S. (2016). Relapse risks in patients with alcohol use disorders. Yonago Acta Medica, 59(4), 279 287; with permission.

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40. RELAPSE RISKS IN PATIENTS WITH ALCOHOL USE DISORDERS

TABLE 40.2 Summary of Logistic Regression Analysis for Variables Contributing to High and Low Groups of Innate- and AcquiredResilience Factors β INNATE-RESILIENCE ARRS

0.085

Acquired-resilience ACQUIRED-RESILIENCE Innate resilience

SE

Wald

df

P-value

OR (95% CI)

0.042

4.154

1

0.042

0.918 (0.846 0.997)



0.182

0.084

4.654

1

0.031

1.200 (1.017 1.415)

0.254

0.083

9.266

1

0.002

1.289 (1.095 1.517)





OR and 95% CI were calculated with the use of logistic regression analysis. P , .05, P , .01. ARRS, Alcohol Relapse Risk Scale; CI, confidence interval; df, degrees of freedom; OR, odds ratio; PE, positive expectancy for alcohol; SE, standard error. From Yamashita, A., & Yoshioka, S. (2016). Relapse risks in patients with alcohol use disorders. Yonago Acta Medica, 59(4), 279 287; with permission.

dependence, distorted cognition, and a decline in the degree of self-disclosure. Sociological (environmental) risk factors for relapse include interpersonal relationships and family relationships. Resilience is essential for AUD patients to achieve recovery.

MINI-DICTIONARY OF TERMS AUD relapse A condition where (impulse) control disorder progresses to the stage where psychological or physical dependence, such as withdrawal symptoms, is exacerbated, causing problems in everyday life. Biopsychosocial model A scientific model that takes into consideration aspects lacking in models based on biomedical science alone. Recovery The process of overcoming the severe effects of a mental disorder and finding new meaning and purpose in life. Resilience The phenomenon of attempting to adapt, regardless of serious risks. Acquired resilience Resilience acquired through life experiences. Innate resilience Resilience related to an individual’s inherent nature. Transtheoretical model A model used in this study that was based on research regarding people who quit smoking voluntarily and consists of five stages: precontemplation, contemplation, preparation, action, and maintenance.

KEY FACTS Relapse Risks in Patients with AUD • AUD relapse is caused by a combination of biological, psychological, and sociological factors. • AUD relapse refers to a condition where (impulse) control disorder progresses to the stage where psychological or physical dependence, such as withdrawal symptoms, is exacerbated, causing problems in everyday life. • Relapse is often caused by a distorted understanding of drinking-related behavior patterns and psychological dependence. • As relapse is one of the phenomena along the way to recovery. It should be viewed as an opportunity

for gauging the timing of intervention, rather than as treatment failure. • To achieve recovery from AUD relapse, it is necessary to ascertain drinking patterns and learn how to handle factors that cause cravings for alcohol. • It is essential for AUD patients to have the support of family, work colleagues, and people who share similar experiences to resist the strong cravings for alcohol and recover from AUD. • Acquired resilience is the key element in recovery and can be improved through empowerment.

SUMMARY POINTS • In this chapter, we focus on the psychosocial risks for relapse in AUD patients, and consider the meaning of recovery based on a typical recovery process model for addiction. • Recovering from an AUD means breaking out of a lifestyle dependent on a dependence-producing drug, correcting old patterns of thought and action, and adopting a new way of life that does not require intoxication by drugs. • Psychological risk factors for AUD relapse include strong cravings for alcohol associated with behavior patterns that lead to drinking and psychological dependence, distorted cognition, and a decline in the degree of self-disclosure. • Sociological (environmental) risk factors for relapse include interpersonal relationships and family relationships. • Resilience is essential for AUD patients to achieve recovery.

Acknowledgment We would like to express our sincere, heartfelt gratitude to everyone who cooperated with this study. Additionally, this study was completed as part of research conducted via the Grant-in-Aid for Scientific Research (C) (Grant Number JP15K11835).

III. PSYCHOLOGY, BEHAVIOR, AND ADDICTION

REFERENCES

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individuals, a prospective general population study. Addiction, 108(12), 2091 2099. Available from https://doi.org/10.1111/ add.12309, Epub August 28, 2013. Witkiewitz, K., & Marlatt, G. A. (2004). Relapse prevention for alcohol and drug problems, that was Zen, this is Tao. The American Psychologist, 59(4), 224 235. Witkiewitz, K., & Marlatt, G. A. (2007). Modeling the complexity of post-treatment drinking, it’s a rocky road to relapse. Clinical Psychology Review, 27(6), 724 738. Witteman, J., Post, H., Tarvainen, M., de Bruijn, A., Perna Ede, S., . . . Wiers, R. W. (2015). Cue reactivity and its relation to craving and relapse in alcohol dependence, a combined laboratory and field study. Psychopharmacology, 232(20), 3685 3696. Available from https://doi.org/10.1007/s00213-015-4027-6, Epub August 11, 2015.

Yamashita, A., & Yoshioka, S. (2016). Relapse risks in patients with alcohol use disorders. Yonago Acta Medica, 59(4), 279 287. Zeng, R., Wang, L., & Xie, Y. (2016). An analysis of factors influencing drinking relapse among patients with alcohol-induced psychiatric and behavioral disorders. Shanghai Archives of Psychiatry, 28 (3), 147 153. Available from https://doi.org/10.11919/j.issn. 1002-0829.216009. Zgierska, A. E., Shapiro, J., Burzinski, C. A., Lerner, F., & GoodmanStrenski, V. (2017). Maintaining treatment fidelity of mindfulnessbased relapse prevention intervention for alcohol dependence, a randomized controlled trial experience. Evidence-Based Complementary and Alternative Medicine. 2017. Available from https://doi.org/10.1155/2017/9716586, Epub July 5, 2017.

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C H A P T E R

41 The Neurocognitive Effects of Alcohol Hangover: Patterns of Impairment/ Nonimpairment Within the Neurocognitive Domains of the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition L. Darren Kruisselbrink Centre of Lifestyle Studies, School of Kinesiology, Acadia University, Wolfville, NS, Canada

LIST OF ABBREVIATIONS AHS AHSS BAC DSM-5 HSS Mg%

This chapter’s overview of the neurocognitive effects of an alcohol hangover will outline how a hangover is conceptualized and measured, and will organize research findings on the neurocognitive effects of hangovers to show a pattern that has emerged over the past 60 years.

acute hangover scale alcohol hangover symptoms scale blood alcohol concentration diagnostic and statistical manual of mental disorders, 5th edition hangover symptoms scale milligrams of alcohol per 100 mL (deciliter) of blood

WHAT IS A HANGOVER?

INTRODUCTION The day following a night of heavy drinking can be a struggle for many as the fun that accompanied acute intoxication gives way to the aches and malaise of a hangover. However, an alcohol hangover is more than merely an inconvenient phase of physiological readjustment. Perceptual-motor, memory, and decisionmaking impairments can occur after blood alcohol concentration (BAC) has returned to zero, which have the potential for serious consequences, especially for pilots, professional drivers, medical personnel, and other occupations where poor neurocognitive functioning can harm the safety or welfare of oneself or others.

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00041-6

A consensus definition of hangover is “the combination of mental and physical symptoms, experienced the day after a single episode of heavy drinking, starting when blood alcohol concentration approaches zero” (van Schrojenstein Lantman, van de Loo, Mackus, & Verster, 2016, p. 153). Most heavy drinkers experience a hangover as fewer than 6% have been shown to be hangover immune (Kruisselbrink, Bervoets, de Klerk, van de Loo, & Verster, 2017). Although the precise pathology of an alcohol hangover is not yet fully understood, a number of physiological effects are present during hangovers; these include dehydration and electrolyte imbalance, hormonal

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© 2019 Elsevier Inc. All rights reserved.

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41. THE NEUROCOGNITIVE EFFECTS OF ALCOHOL HANGOVER

changes, gastrointestinal disturbance, low blood sugar, disruption of sleep and circadian rhythm, headache, and inflammatory responses (Penning, van Nuland, Fliervoet, Olivier, & Verster, 2010; Tipple, Benson, & Scholey, 2016). Although these effects have not been found to correlate with hangover severity (Penning et al., 2010), their presence align with many of the physical and mental symptoms of hangovers most frequently experienced. These include fatigue, thirst and dry-mouth, drowsiness and sleepiness, headache, nausea, weakness, difficulties in concentrating, and reduced alertness (Penning et al., 2010, 2013).

MEASURING HANGOVER The number and type of symptoms included in hangover measures have varied over time and across researchers, although a core group of symptoms seem to regularly appear (e.g., fatigue, thirst, headache, nausea, and dizziness). Three published scales currently exist (Penning et al., 2013; Rohsenow et al., 2007; Slutske, Piasecki, & Hunt-Carter, 2003), although a composite scale that integrates all of them has been devised recently (Hogewoning et al., 2016). The first scale to appear was the hangover symptoms scale (HSS, Slutske et al., 2003) which measures the percentage of drinking occasions followed the next morning by each of 13 symptoms derived from the eight classes of symptoms identified by Swift and Davidson (1998). Symptom frequency over the previous 12 months is rated from “never” to “every time” on a five-point scale. Because the HSS did not measure hangover severity following a single drinking episode, Rohsenow et al. (2007) developed the acute hangover scale (AHS) using symptoms supported by previous laboratory research. The severity of eight individual symptoms plus overall hangover is rated on an eight-point Likert scale ranging from 0 (none) to 7 (incapacitating). Since there was little overlap between the symptoms measured by the HSS and AHS, Penning, McKinney, and Verster (2012) conducted a factor analysis of 47 symptoms previously listed in experimental and survey studies, discovering that they loaded onto 11 factors. Using symptoms from the six factors with Cronbach’s alpha .0.7, Penning et al. (2013) developed the Alcohol Hangover Severity Scale (AHSS). The severity of 12 symptoms is rated on an 11-point Likert scale ranging from 0 (absent) to 10 (extreme). Most recently, symptoms from all three scales have been integrated to form a 23-item composite scale in which items are rated on an 11-point Likert scale ranging from 0 (absent) to 10 (extreme) (see Hogewoning et al., 2016). The symptoms listed in each of the described scales are shown in Table 41.1.

ORGANIZING RESEARCH ON NEUROCOGNITIVE PERFORMANCE DURING HANGOVER Lemon (1993) and Rohsenow, Howland, Arnedt et al. (2010) have discussed the need to conceptually separate the effects of hangover severity on performance from residual effects of alcohol on performance since the effects of hangover severity imply that performance impairments fluctuate with hangover severity after BAC reaches zero, whereas the residual effects of alcohol simply refers to any performance impairments after BAC returns to zero. It should be noted that more hangover research reports residual versus hangover effects, as many studies examining performance during hangover have not measured hangover severity, and the correlations reported by those studies that do have been small. Thus, part of the problem in establishing the effects of hangover severity on performance is that a consistently used measure of hangover has been lacking, whereas another part of the problem has been the independence of hangover severity and performance impairment. Nonetheless, a number of reviews have been written over the past 25 years with authors organizing the research findings thematically in various ways (Barker, 2004; Lemon, 1993; Ling, Stephens, & Heffernan, 2010; Prat, Adan, Pe´rez-Pa`mies, & Sa`nchez-Turet, 2008; Stephens, Grange, Jones, & Owen, 2014; Stephens, Ling, Heffernan, Heather, & Jones, 2008). Over time, the organizational schemes have become more sophisticated and refined. The most refined scheme to date was proposed in the most recent review of hangover literature by Stephens et al. (2014). The strength of this review was that they classified the research they reviewed within the domains of attention and memory, and identified clusters of tests within these domains. They subcategorized tests of attention as sustained attention, selective attention and divided attention, and tests of memory into long-term and short-term memory. Building on the strength of Stephens et al. (2014), to organize research examining neurocognitive performance during the alcohol hangover, I looked to the Diagnostic and Statistical Manual of Mental Disorders (5th edition) (DSM-5) for guidance (American Psychiatric Association, 2013). Aligning hangover research with the DSM-5 classification system will allow for the development of a database showing which neurocognitive domains and subdomains have been most—and least— studied, which neurocognitive domains and subdomains are affected by hangover, and to what extent. For the fifth edition of the DSM, the Neurocognitive Disorders Work Group indicated that “the term

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ORGANIZING RESEARCH ON NEUROCOGNITIVE PERFORMANCE DURING HANGOVER

TABLE 41.1 Hangover Symptoms Included in the Hangover Symptoms Scale (HSS), Acute Hangover Scale (AHS), Alcohol Hangover Symptoms Scale (AHSS), and Composite Hangover Scale (CHS) AHS (Rohsenow et al., AHSS (Penning et al., 2013) 2007)

CHS (Hogewoning et al., 2016)

Hangover

Hangover

Hangover

Felt more tired than usual

Tired

Fatigue (being tired)

Tiredness

Felt very nauseous

Nausea

Nausea

Nausea

Felt extremely thirsty or dehydrated

Thirsty

Thirst

Thirst

Concentration problems

Concentration problems

Dizziness

Dizziness

HSS (Slutske et al., 2003)

Had difficulty concentrating Dizziness, faintness Experienced a headache

Headache

Experienced trembling or shaking Stomach ache Sweated more than usual

Headache Shivering

Shaking, shivering

Stomach pain

Stomach pain

Sweating

Sweating

Was anxious

Anxiety

Felt depressed

Depression

More sensitive to light and sound than usual

Sensitivity to light

Had a lot of trouble sleeping

Sleep problems

Vomited

Vomiting

Felt very weak

Weakness Heart racing

Heart racing

Loss of appetite

Reduced appetite Apathy (lack of interest/concern)

Apathy

Clumsiness

Clumsiness

Confusion

Confusion

Heart pounding

Heart beating Regret Sleepiness

‘neurocognitive’ was applied to [a] cluster of disorders to emphasize that disrupted neural substrates lead to symptoms, and that, in most cases, such disruption can be reliably measured” (Sachdev et al., 2014, p. 635). The group identified six domains of cognitive impairment based on the most noticeable and defining features of a cognitive deficit. These domains include complex attention, executive function, learning and memory, language, perceptual-motor function, and social cognition. In reviewing the past 60 years of research on the neurocognitive effects of hangover, each measure of neurocognitive performance in each study was examined and categorized into the DSM-5 domain that best characterized its neurocognitive referent. Within each domain, the Neurocognitive

Disorders Work Group identified a number of subdomains (American Psychiatric Association, 2013; Sachdev et al., 2014). The domain of Complex Attention includes sustained attention, selective attention, divided attention, and processing speed as subdomains. Sustained attention refers to the ability to maintain attention over time; selective attention involves maintaining attention despite competing stimuli or distractors; divided attention is the ability to attend to two tasks within the same time period; and processing speed refers to the speed with which any task is performed. In the research that was reviewed, each measure catalogued within the domain of complex attention was further categorized into the subdomain that represented the

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most appropriate cognitive function (American Psychiatric Association, 2013). Some tasks were double classified since the performance measures involved a pair of subdomains. For example, a vigilance task may require a research participant to press a key as quickly as possible (processing speed) in response to a particular feature within an array of competing stimuli, the accuracy of which is evaluated over a substantial period of time (sustained attention). Executive Function was subdivided into subdomains of planning, decision-making, working memory, responding to feedback, inhibition/overriding habits, and cognitive flexibility. According to the DSM-5: planning involves forming a solution to a problem or interpreting pictures or objects arranged in a sequence; decision-making requires making a decision among competing alternatives; working memory requires the ability to hold information in mind for a short period of time and manipulate it in some way; responding to feedback demands the ability to use feedback to identify an underlying principle to solve a problem; inhibition/ overriding habits necessitates inhibiting a dominant response and choosing a more effortful solution (e.g., Stroop); and cognitive flexibility requires shifting between a pair of concepts or response rules in responding to a stimulus array (American Psychiatric Association, 2013). The Learning and Memory neurocognitive domain was parsed into seven subdomains, which include: (1) immediate memory, which refers to the ability to immediately recall a list, and recent memory of encoded information after a period of time, which involves; (2) free recall (recall as much as possible); (3) cued recall (recall certain information identified by a cue); and (4) recognition memory (identify whether an item appeared). Memory for facts (5; semantic memory), personal events (6; autobiographical memory), and unconscious learning (7; implicit learning) are considered subdomains of “very long term memory” (American Psychiatric Association, 2013). The domain of Perceptual-Motor function includes the subdomains of visual perception, visuoconstructional functioning, perceptual-motor, praxis, and gnosis. Visual perception includes motor-free tasks that require the ability to identify or match figures; the visuoconstructional functioning subdomain demands hand-eye coordination for tasks like drawing, copying, and assembling blocks; perceptual-motor tasks require perception to inform purposeful movement; the praxis subdomain demands the ability to imitate or demonstrate learned movement patterns; and gnosis involves perceptual awareness and recognition of things (American Psychiatric Association, 2013). Within the Language domain are the subdomains of expressive and receptive language. Expressive

language involves naming (identifying the names of pictures or objects), word finding, and fluency (e.g., recall and name an exhaustive list of items in a semantic or phonemic category within a specific time frame), which also includes fluency in the use of grammar and syntax. Receptive language refers to comprehension of speech and responding to verbal commands (American Psychiatric Association, 2013). Social cognition is the last DSM-5 neurocognitive domain, subdomains of which include the recognition of emotions (e.g., identification of emotions from images of faces) and the ability to take another’s perspective by considering what they might think, want, intend to do, or what they may have experienced (American Psychiatric Association, 2013). In addition to some tasks that can be double classified within a domain, for some of the neurocognitive tasks that have been reported in hangover research more than one neurocognitive domain can apply. For example, in a choice reaction time task where a response key is associated with each stimulus cue, the Executive Function subdomain of decision-making would be responsible for deciding which of the response options among the alternatives to execute—which could be evaluated by measuring response accuracy—whereas how quickly the information was processed from stimulus onset to response completion would be classified as processing speed.

NEUROCOGNITIVE PERFORMANCE DURING HANGOVER In reviewing the literature, the tasks and measures reported in each of the 36 reviewed studies were carefully assessed and assigned to an appropriate neurocognitive domain and subdomain by constantly comparing the description of the performance measures for each task to the examples of assessments listed in Table 1 of the Neurocognitive Disorders chapter of the DSM-5 (American Psychiatric Association, 2013). Once classified, performance effects for each measure reported in each study were categorized as either impaired (ü) or not impaired (û) during hangover. The pattern of results across the domains, and subdomains, of complex attention, executive function, learning and memory, and perceptual-motor function are shown in Table 41.2. A number of observations become immediately evident after scanning the pattern of results across neurocognitive domains and subdomains. First, some domains and subdomains have received more research attention than others. Table 41.2 shows that the domains of complex attention and executive function have received the most research attention, followed by

III. PSYCHOLOGY, BEHAVIOR, AND ADDICTION

TABLE 41.2 Summary of Research Examining Hangover Effects Within the DSM-5 Domains of Complex Attention (2A), Executive Functioning (2B), Learning and Memory (2C), and Perceptual-Motor functioning (2D). Impairment on individual subdomain tests/tasks is indicated by a checkmark (ü), lack of impairment is indicated by an X (û) (A) Source

Sample & research Amount of alcohol consumed; design time frame

Sustained Peak BAC (mg%) attention

Divided attention

Selective attention

Processing speed

Takala, Siro, and Toivainen (1958)

38H 45C (M)

1.40 g/kg; 150 min

Brandy 5 160 Beer 5 130

Ja¨rvilehto, Laakso, and Virsu (1975)

9HC (M)

1.50 g/kg; 180 min

170 260

Seppa¨la¨, Leino, Linnoila, Huttunen, and Ylikahri (1976)

10H 10C (M)

1.75 g/kg; 180 min

210 230

û

û

Collins (1980)

8HPC (4M 4F)

1.28 g/kg; 180 min

90a

û

û

Collins and Chiles (1980)

11HPC (7M 4F)

1.30 g/kg; 240 min

93

û

Myrsten, Rydberg, Idestrom, and Lamble (1980)

12HPC (M)

1.43 g/kg; 70 min

Morrow, Leirer, and Yesavage (1990)

14HP (M)

Lemon, Chesher, Fox, Greeley, and Nabke (1993)

ûû ü

û

ûû

125

ü

û

Target 5 100 mg%; 130 160 min

95 108

ü

19H 15P (M)

1.00 g/kg; 30 min

83

Morrow et al. (1993)

28HP (M)

Target 5 100 mg%; 180 210 min

98 116

Chait and Perry (1994)

14HP (10M 4F)

1.20 g/kg; 160 min

88

Taylor, Dolhert, Morrow, Friedman, and Yesavage (1994)

28HP (M)

Target 5 80 mg%; 45 min

72 87

û

Yesavage, Dolhert, and Taylor (1994)

14H 13P (M)

Target 5 100 mg%; 45 min

95 105

ü

Taylor, Dolhert, Friedman, Mumenthaler, and 23HC (11M 12F) Yesavage (1996)

Target 5 80 mg%; 45 min

M 5 87 6 10, F 5 84 6 15

û

Finnigan, Hammersley, and Cooper (1998)

40HP (M)

Target 5 100 mg%; Single dose

Not specified, est. û . 100

Anderson and Dawson (1999)

16H 10C (13M 13F)

Est. . 1 g/kg; not specified

Not specified

Dorafshar, O’Boyle, and McCloy (2002)

14HC 14PC (M)

1.05 g/kg; 15 min

85

Petros et al. (2003)

12H 12P (M)

1.20 g/kg; 45 min

112

Verster, van Duin, Volkerts, Schreuder, and Verbaten (2003)

24HC 24PC (24M 24F)

1.40 g/kg; 30 min

155

McKinney and Coyle (2004)

48HC (15M, 33F)

M 5 132 6 75 g, F 5 95 6 64 g; 240 min

Est. . 100

Finnigan et al. (2005)

25H 33C (27M 31F)

Ad libitum; not specified

Not specified

û

û

ûûû üûü

û

ûû

û

û üû

û

û üû û

û üü

ü

û

û (Continued)

TABLE 41.2

(Continued) Sample & research Amount of alcohol consumed; design time frame

Sustained Peak BAC (mg%) attention

Kruisselbrink, Martin, Megeney, Fowles, and Murphy (2006)

12HC (F)

81 g; 220 min

106; R 5 87 131

û

McKinney and Coyle (2007)

78HC (23M, 55F)

M 5 148 6 63 g, F 5 98 6 55 g; 240 min

Est. . 100

üûüû

Howland, Rohsenow, Greece et al. (2010)

193HP (107M, 86F)

Target 5 120 mg%; 60 min

. 120

üüûûûûû

û

ûûûûûûû

Rohsenow, Howland, Arnedt et al. (2010)

95HP (37M, 58F)

Target 5 100 mg%; 90 min

110; R 5 90 150

üüûûû

ü

üûûûû

McKinney, Coyle, Penning, and Verster (2012) 48HC (15M, 33F)

M 5 132 6 75 g, F 5 95 6 64 g; 240 min

Est. . 100

ûû

üûû

Verster et al. (2014)

42HC (23M, 19F)

MB111 6 48 g, FB90 6 33 g; B330 min

MB110, FB160

Hartung et al. (2015)

36HC (12M, 24F)

Not specified; 540 min

130; R 5 106 160

Grange, Stephens, Jones, and Owen (2016)

31HC (11M, 20F)

Ad libitum; not specified

Est. 180

üüüû

Stock, Hoffmann, and Beste (2017)

18HC (M)

Target 5 125 mg%; 30 min

106

ûbûbûû

Wolff, Gussek, Stock, and Beste (2018)

23HC (M)

Target 5 125 mg%; 30 min

124

û

(A) Source

û

Totals (B) Source

Sample and design

Amount of alcohol consumed; time frame

Peak BAC (mg %)

Takala et al. (1958)

38H 45C (M)

1.40 g/kg; 150 min

brandy 5 160 beer 5 130

Seppa¨la¨ et al. (1976)

10H 10C (M)

1.75 g/kg; 180 min

210 230

ü

Collins and Chiles (1980)

11HPC (7M 4F)

1.30 g/kg; 240 min

93

û

û

Myrsten et al. (1980)

12HPC (M)

1.43 g/kg; 70 min

125

ûû

ü

Yesavage and Leirer (1986)

10HC (M)

Target 5 100 mg%; 90 min

101 120

üû

üû

Morrow et al. (1990)

14HP (M)

Target 5 100 mg%; 130 160 min

95 108

ü

ü

Morrow et al. (1993)

28HP (M)

Target 5 100 mg%; 180 210 min

98 116

üûü

üûü

Chait and Perry (1994)

14HP (10M 4F)

1.20 g/kg; 160 min

88

û

ûû

Taylor et al. (1994)

28HP (M)

Target 5 80 mg%; 45 min

72 87

û

û

Yesavage et al. (1994)

14H 13P (M)

Target 5 100 mg%; 45 min

95 105

ü

ü

Selective attention

Processing speed

üü û

7ü 12û Decision making

Divided attention

Working memory

0ü 9û

Feedback utilization

8ü 11û Over-riding habits

10ü 36û

Mental Planning flexibility

üûûûûûûûûû

û

(Continued)

TABLE 41.2

(Continued)

(B) Source

Sample and design

Amount of alcohol consumed; time frame

Peak BAC (mg %)

Decision making

Working memory

Streufert et al. (1995)

21HP (M)

Target 5 90 110 mg%; 30 min

90 110

û

Taylor et al. (1996)

23HC (11M 12F)

Target 5 80 mg%; 45 min

M 5 87 6 10, F 5 84 6 15

û

Finnigan et al. (1998)

40HP (M)

Target 5 100 mg%; Single dose

Not specified, est. . 100

û

Anderson and Dawson (1999)

16H 10C (13M 13F)

Est. . 1 g/kg; not specified

Not specified

ü

Kim et al. (2003)

13HC (M)

1.50 g/kg; 30 min

75 6 28a

ü

üû

Petros et al. (2003)

12H 12P (M)

1.20 g/kg; 45 min

112

üû

üû

Finnigan et al. (2005)

25H 33C (27M 31F)

Ad libitum; not specified

Not specified

Kruisselbrink et al. (2006)

12HC (F)

81 g; 220 min

106; R 5 87 131

ü

Rohsenow, Howland, Minsky, and Arnedt (2006)

61HPC (50M 1F)

Target 5 100 mg%; 90 min

115; R 5 90 170

û

Howland, Rohsenow, Greece et al. (2010)

193HP (107M, 86F)

Target 5 120 mg%; 60 min

. 120

ûûû

Rohsenow, Howland, Arnedt et al. (2010)

95HP (37M, 58F)

Target 5 100 mg%; 90 min

110; R 5 90 150

ûû

McKinney et al. (2012)

48HC (15M, 33F)

M 5 132 6 75 g, 5 95 6 64 g; 240 min

Est. . 100

û

Grange et al. (2016)

31HC (11M, 20F)

Ad libitum; not specified

Est. 180

üû

Stock et al. (2017)

18HC (M)

Target 5 125 mg%; 30 min

106

ûbû

Wolff et al. (2018)

23HC (M)

Target 5 125 mg%; 30 min

124

Feedback utilization

Over-riding habits

û

Mental Planning flexibility û

û

ü

ü

û

û

üû

û

ü

ü

Totals

10ü 15û

13ü 26û

(C) Source

Sample and design

Amount of alcohol consumed; time frame

Peak BAC (mg%)

IM: free recall

Myrsten et al. (1980)

12HPC (M)

1.43 g/kg; 70 min

125

û

Morrow et al. (1990)

14HP (M)

Target 5 100 mg%; 130 160 min

95 108

üûü

Morrow et al. (1993)

28HP (M)

Target 5 100 mg%; 180 210 min

98 116

üûü

Chait and Perry (1994)

14HP (10M 4F)

1.20 g/kg; 160 min

88

ûû

û 0ü 3û IM: cued recall

1ü 0û LTM: semantic

1ü 2û RM: delayed recall

0ü 1û RM: recognition

(Continued)

TABLE 41.2

(Continued)

(C) Source

Sample and design

Amount of alcohol consumed; time frame

Peak BAC (mg%)

IM: free recall

Taylor et al. (1994)

28HP (M)

Target 5 80 mg%; 45 min

72 87

û

Yesavage et al. (1994)

14H 13P (M)

Target 5 100 mg%; 45 min

95 105

ü

Finnigan et al. (1998)

40HP (M)

Target 5 100 mg%; Single dose

Not specified, est. . 100

Kim et al. (2003)

13HC (M)

1.50 g/kg; 30 min

75 6 28a

üû

Petros et al. (2003)

12H 12P (M)

1.20 g/kg; 45 min

112

û

Verster et al. (2003)

24HC 24PC (24M 1.40 g/kg; 30 min 24F)

155

û

McKinney and Coyle (2004)

48HC (15M, 33F)

M 5 132 6 75 g, 5 95 6 64 g; 240 min

Not specified, est. . 100

üû

Finnigan et al. (2005)

25H 33C (27M 31F)

Ad libitum; not specified

Not specified

û

McKinney and Coyle (2007)

78HC (23M, 55F)

M 5 148 6 63 g, F 5 98 6 55 g; 240 min

Est. . 100

üû

Howland, Rohsenow, Greece et al. (2010)

193HP (107M, 86F)

Target 5 120 mg%; 60 min

. 120

û

Rohsenow, Howland, Arnedt et al. (2010)

95HP (37M, 58F)

Target 5 100 mg%; 90 min

110; R 5 90 150

Totals Sample and design

Amount of alcohol consumed; time frame Peak BAC (mg%)

Takala et al. (1958)

38H 45C (M)

1.40 g/kg; 150 min

brandy 5 160 beer 5 130

ûbû

Seppa¨la¨ et al. (1976)

10H 10C (M)

1.75 g/kg; 180 min

210 230

û

8HPC (4M 4F) 1.28 g/kg; 180 min

90

û

Collins and Chiles (1980)

11HPC (7M 4F)

1.30 g/kg; 240 min

93

ûûû

Laurell and To¨rnros (1983)

22HC (16M 6F)

Ad libitum; 360 min

147

ü

Yesavage and Leirer (1986)

10HC (M)

Target 5 100 mg%; 90 min

101 120

üû

Morrow et al. (1990)

14HP (M)

Target 5 100 mg%; 130 160 min

95 108

ü

RM: delayed recall

RM: recognition

ü

û ü

üü ûûûû

û û

Perceptual motor

Collins (1980)

a

LTM: semantic

û

8ü 13û

(D) Source

IM: cued recall

0ü 1û Visual perception

0ü 4û Gnosis (aware-ness)

1ü 0û Visuoconstruct

3ü 3û Praxis (motor planning)

(Continued)

TABLE 41.2

(Continued) Sample and design

Amount of alcohol consumed; time frame Peak BAC (mg%)

Perceptual motor

To¨rnros and Laurell (1991)

24HC (23M 1F)

Ad libitum; 300 min

176

û

Lemon et al. (1993)

19H 15P (M)

1.00 g/kg; 30 min

83

û

Morrow et al. (1993)

28HP (M)

Target 5 100 mg%; 180 210 min

98 116

üûü

Taylor et al. (1994)

28HP (M)

Target 5 80 mg%; 45 min

72 87

û

Yesavage et al. (1994)

14H 13P (M)

Target 5 100 mg%; 45 min

95 105

ü

Taylor et al. (1996)

23HC (11M 12F)

Target 5 80 mg%; 45 min

M 5 87 6 10, 5 84 6 15 û

Finnigan et al. (1998)

40HP (M)

Target 5 100 mg%; Single dose

Not specified, est. . 100

û

Dorafshar et al. (2002)

14HC 14PC (M)

1.05 g/kg; 15 min

85

û

Kim et al. (2003)

13HC (M)

1.50 g/kg; 30 min

75 6 28a

û

Petros et al. (2003)

12H 12P (M)

1.20 g/kg; 45 min

112

üû

Finnigan et al. (2005)

25H 33C (27M Ad libitum; not specified 31F)

Not specified

û

McKinney and Coyle (2007)

78HC (23M, 55F)

Est. . 100

üü

Howland, Rohsenow, Greece et al. (2010)

193HP (107M, Target 5 120 mg%; 60 min 86F)

. 120

ûû

Rohsenow, Howland, Arnedt et al. (2010)

95HP (37M, 58F)

Target 5 100 mg%; 90 min

110; R 5 90 150

ü

Verster et al. (2014)

42HC (23M, 1F)

MB111 6 48 g, B90 6 33 g; B330 min

MB110, FB160

ü

Hartung et al. (2015)

36HC (12M, 24F)

Not specified; 540 min

130; R 5 106 160

ü

(D) Source

Totals a

M 5 148 6 63 g, F 5 98 6 55 g; 240 min

12ü 20û

Visual perception

Gnosis (aware-ness)

Visuoconstruct

Praxis (motor planning)

ü

û

ü

û

0ü 1û

1ü 0û

0ü 1û

û

1ü 1û

BAC was measured soon after drinking had stopped, likely on the ascending limb of the BAC curve. Performance better during hangover than control. Research design H C or H P means a hangover group (H) and a control (C) or placebo (P) group; HC or PC means participants participated in hangover and control (HC) or placebo (HP) conditions; HPC means participants participated in hangover, placebo and control conditions; HC PC indicates that hangover and placebo groups were tested before and after consumption. The gender composition of the sample is indicated by M 5 male, F 5 female. Alcohol was administered in a variety of ways, lab studies typically provided alcohol in proportion to body weight (grams of alcohol per kilogram of body weight, or g/kg) or to a target BAC (milligrams of alcohol per deciliter of blood, or mg%) whereas naturalistic studies allowed for ad libitum consumption, the self-reports of which, if provided, have been converted to grams of alcohol where possible. The duration over which alcohol was consumed is provided by min 5 minutes. Peak BACs are typically expressed as averages; some studies provide ranges (R), others allow BACs to be reasonably estimated (est), and yet others do not specify. Memory tests (Table D) of newly presented material were conducted either immediately (IM) or after a short delay (RM); tests of material learned some time ago tapped into long term memory (LTM).

b

400

41. THE NEUROCOGNITIVE EFFECTS OF ALCOHOL HANGOVER

perceptual-motor, and learning and memory. So few studies examined performance in the domains of language and social cognition that tables were not warranted. In fact, only two studies reported tests of language (Finnigan, Schulze, Smallwood, & Helander, 2005; Kim, Yoon, Lee, Choi, & Go, 2003), both showing no impairment, and one survey study examined what could be construed as social cognition (Ames, Grube, & Moore, 1997) showing more evidence of nonimpairment than impairment. The near absence of research examining the ability to empathize, read facial expressions, or read social cues during a hangover represents a significant gap in the literature. Second, a wide range of methods has been used across studies with regard to the amount of alcohol consumed, ingestion time, and reported BAC’s. Lack of standardization in methods across studies is not surprising since it likely reflects the diversity of drinking patterns across people. However, it does make generalization to everyday life challenging. A more systematic approach to dealing with variables such as alcohol administration (amount and time) and recording of BAC would be helpful. Third, when measures of neurocognitive performance in hangover studies are expressed as impaired (ü) or not impaired (û), it is somewhat striking how few times neurocognitive performance is found to be significantly impaired during hangover; impairment emerges in approximately one-third to one-fourth of domain-specific performance measures during hangover. It appears that neurocognitive impairments due to the residual effects of alcohol are challenging to find. One explanation for this pattern of results is that perhaps the neurocognitive tests and measures are not sensitive enough to fully capture impairment. Accuracy/errors and speed have typically been used as performance measures; perhaps other aspects of performance should be examined. For instance, the examples of symptoms or observations of mild neurocognitive impairment provided in the DSM-5 suggest that increased effort and fatigue to generate the same level of performance (speed and accuracy) may constitute evidence of impairment, but these are rarely assessed. Another explanation may lie with the types of tests that have been used. For instance, a limitation of the studies reviewed here is that virtually all of the experimental tasks required individuals to solve the problems demanded by the task on their own. In workplace environments where productivity is often a function of teamwork, perhaps the ability to integrate one’s abilities with those of colleagues to solve problems collectively, rather than the ability to perform individually, is what limits performance. The interpersonal conflicts and power struggles within a group dynamic may be exacerbated during hangover by

impaired abilities to empathize, read facial expressions, or read social cues, thereby impairing collective, but not individual, problem-solving. More research within the Social Cognition domain is needed to examine this issue.

MINI-DICTIONARY OF TERMS Complex attention Ability to quickly attend to a single stimulus or multiple stimuli, either alone or among distractors, for short or long periods of time. Executive function Holding and manipulating information in mind in service of solving a problem. Hangover The combination of mental and physical symptoms experienced after blood alcohol concentration reaches zero the day following an episode of heavy drinking. Mg% A measure of blood alcohol concentration expressed as the weight of alcohol (in milligrams) per volume of blood (in deciliters). 1 dL 5 100 mL. Neurocognitive performance The neural functions underlying our ability to acquire information and understand. Perceptual-motor function Use of visual and kinesthetic information to inform object identification and purposeful movement. Social cognition Ability to recognize emotions in others and take others’ perspective.

KEY FACTS Hangover • Hangover is most commonly associated with headache and fatigue, but also includes cognitive, balance, respiratory, cardiovascular and gastrointestinal problems, and altered water balance, mood, and affect. • Fewer than 6% of heavy drinkers who have consumed enough alcohol for their blood alcohol concentration to exceed 100 mg% report never having experienced a hangover. • Hangover severity depends on numerous factors including how much alcohol is consumed, the type of alcohol consumed, genetics, mood, and one’s personality. • The intensity of hangover symptoms is thought to peak around the time blood alcohol concentration returns to zero, which could be in the afternoon following a heavy drinking episode.

Blood Alcohol Concentration • Blood alcohol concentration is generally expressed as the weight of alcohol per volume of blood. Common expressions are given in milligrams of alcohol per deciliter of blood (mg/dL or mg%) or grams of alcohol per deciliter of blood (g/dL or g%).

III. PSYCHOLOGY, BEHAVIOR, AND ADDICTION

REFERENCES

• Globally, a driver with a blood alcohol concentration over 50 mg% (or 0.05 g%) is considered to be impaired. • Blood alcohol concentration can be estimated by the concentration of alcohol in breath. • Blood alcohol concentration can be estimated using a number of different equations. Each equation considers the concentration of alcohol (by weight) within total volume body water along with a correction factor. As the density (weight) of ethanol is 0.79 times the density of water, 1 g of water 5 1 mL, whereas 1 g ethanol 5 1.26 mL.

SUMMARY POINTS • Hangover is the combination of mental and physical symptoms experienced after blood alcohol concentration reaches zero the day following an episode of heavy drinking. • The measurement of hangover has evolved over time and includes a retrospective rating of past year hangover symptoms (HSS), a pair of rating scales of acute hangover symptoms (AHS; AHSS), and, most recently, a composite scale that includes the symptoms of all three scales. • The Diagnostic and Statistical Manual of Mental Disorders (5th edition) chapter on neurocognitive disorders provides a useful framework for organizing the results of hangover research on neurocognitive effects. • It is striking how few times neurocognitive performance is found to be significantly impaired during hangover (approximately a third to a quarter of the time). • Future hangover research should examine a wider range of neurocognitive performance in the domains and subdomains that have been given little research attention, especially in the domain of Social Cognition.

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C H A P T E R

42 Neuroactive Steroids and Ethanol Exposure: Relevance to Ethanol Sensitivity and Alcohol Use Disorders Risk 1

Patrizia Porcu1, Alessandra Concas2 and A. Leslie Morrow3

Neuroscience Institute, National Research Council of Italy (CNR), Cittadella Universitaria, Cagliari, Italy Department of Life and Environment Sciences, Section of Neuroscience and Anthropology, University of Cagliari, Cagliari, Italy 3Department of Psychiatry, Department of Pharmacology, Bowles Center for Alcohol Studies, University of North Carolina School of Medicine, Chapel Hill, NC, United States 2

LIST OF ABBREVIATIONS 3α(3β)-HSD ACTH AUD BNST CIE CRH DHEA DOC HPA mPFC NAcc P450scc VTA WSP WSR

3α(3β)-hydroxysteroid dehydrogenase adrenocorticotropic hormone alcohol use disorders bed nucleus of the stria terminalis chronic intermittent ethanol vapor exposure corticotrophin releasing hormone dehydroepiandrosterone deoxycorticosterone hypothalamus-pituitary-adrenal (axis) medial prefrontal cortex nucleus accumbens P450 side chain cleavage ventral tegmental area withdrawal seizure-prone withdrawal seizure-resistant

INTRODUCTION Neuroactive steroids modulate brain function, influencing neuronal excitability, neuroplasticity, and behavior. Based on their structure, they can be classified into pregnane derivatives of progesterone and deoxycorticosterone (DOC), which are allopregnanolone and tetrahydrodeoxycorticosterone (THDOC), respectively, and into androstane steroids including DHEA, 3α,5α- and 3α,5β-androstanediol, 3α,5α-androsterone,

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00042-8

and etiocholanolone (or 3α,5β-androsterone) (Carver & Reddy, 2013) (Fig. 42.1). Neuroactive steroids regulate key neuronal functions via genomic and membrane-mediated actions, via specific interactions with ion-channel-coupled receptors for neurotransmitters, including GABAARs, N-methyl-D-aspartate, nicotinic, serotonin type 3, and sigma-1 receptors (Porcu et al., 2016). Specifically, allopregnanolone and THDOC are potent endogenous modulators of GABAAR-mediated inhibitory neurotransmission, while 3α,5α-androstanediol, 3α,5α-androsterone, and ethiocholanolone also potentiate GABAARs, albeit with less potency (Carver & Reddy, 2013). Anxiolytic, sedative, antidepressant, anticonvulsant, and anesthetic effects are the most significant psychopharmacological actions elicited by GABAergic neuroactive steroids, along with some nonbeneficial effects such as detrimental learning, irritability/aggression, and weight gain. Moreover, allopregnanolone facilitates social and sexual motivation, and exhibits analgesic, neuroprotective, neurotrophic, and antiapoptotic actions in animal models of traumatic, neuropathic, and neurodegenerative diseases (Porcu et al., 2016). Neuroactive steroids also possess rewarding properties in rodents, and can modulate ethanol or cocaine intake. Indeed, acute administration of several drugs of abuse, like, alcohol, nicotine, morphine, γ-hydroxy-butyric acid, or

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© 2019 Elsevier Inc. All rights reserved.

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42. NEUROACTIVE STEROIDS AND ETHANOL EXPOSURE

FIGURE 42.1 Biosynthetic pathway for neuroactive steroids. Neuroactive steroids with inhibitory activity on neurons are shown in green while neuroactive steroids with excitatory activity on neurons are show in blue. Precursors are shown in purple. Abbreviations not defined in the List: 5α(5β)-R, 5α(5β)-reductase; 5α(5β)-DHP, 5α(5β)-dihydroprogesterone; 5α(5β)-DHDOC, 5α(5β)-dihydrodeoxycorticosterone; 17β-HSD, 17β-hydroxysteroid dehydrogenase.

Δ9-tetrahydrocannabinol, increases brain and plasma concentrations of allopregnanolone and/or its precursors progesterone and pregnenolone in rats or mice, which might contribute to their rewarding effects (Porcu et al., 2016). Although all GABAAR subtypes are modulated by allopregnanolone, the extrasynaptic α4βδ GABAARs are the most sensitive to its action. Two distinct binding sites for allopregnanolone are present on the GABAAR, one localized on the α subunits transmembrane domain, and the other localized on the α-β subunit interface, whose activation mediates the allosteric modulation and the direct activation of the receptor, respectively (Hosie, Wilkins, da Silva, & Smart, 2006). In the nanomolar range, allopregnanolone allosterically enhances the affinity of GABA for its receptor, while at micromolar concentrations it directly gates the receptor channel. Additional targets for allopregnanolone action are the membrane-progesterone receptors (different

from the classical genomic receptors), and the nuclear pregnane xenobiotic receptor, whose activations mediate some of the neuroprotective actions of allopregnanolone (Porcu et al., 2016). Fluctuations in brain neuroactive steroid concentrations, either naturally occurring or induced by exogenous administration of steroid hormones or other drugs, have been associated with changes in GABAAR subunit expression and function (Carver & Reddy, 2013; Porcu et al., 2016). As GABAARs are implicated in a variety of neuropsychophysiologic phenomena, including anxiety, sleep, seizures, and depression, such fluctuations in neuroactive steroid concentrations may contribute to the neuropsychiatric symptomatology in conditions characterized by marked changes in the hormonal milieu. Thus, altered peripheral and cerebrospinal fluid allopregnanolone concentrations have been related to the pathophysiology of depressive, anxiety and posttraumatic stress disorders,

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ALCOHOL AFFECTS NEUROACTIVE STEROID CONCENTRATIONS

premenstrual syndrome, bipolar disorder, schizophrenia, and alcohol use disorders (AUD); moreover, administration of drugs clinically relevant for the treatment of these pathologies, influences allopregnanolone synthesis (Porcu et al., 2016).

ALCOHOL AFFECTS NEUROACTIVE STEROID CONCENTRATIONS Alcohol differentially affects neuroactive steroid concentrations depending on type of exposure (acute vs chronic), as well as on species and brain regions examined.

Acute Alcohol Effects Systemic administration of ethanol (1 2.5 g/kg) increased plasma, cerebrocortical and hippocampal levels of allopregnanolone, and THDOC in male Sprague-Dawley rats (Morrow et al., 1999; VanDoren et al., 2000) and Sardinian alcohol-preferring rats (Barbaccia et al., 1999). More recent immunohistochemistry studies found that acute ethanol administration produces divergent brain region and cell-type TABLE 42.1

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specific changes in allopregnanolone content in male Wistar rats (Cook, Dumitru, O’Buckley, & Morrow, 2014), as summarized in Table 42.1. The ethanol-induced increase in plasma neuroactive steroids is mediated by the hypothalamus-pituitary-adrenal (HPA) axis, since it is absent in hypophysectomized and adrenalectomized rats (Boyd, Kumar, O’Buckley, Porcu, & Morrow, 2010; Khisti, VanDoren, O’Buckley, & Morrow, 2003; Porcu et al., 2004). However, acute ethanol administration increases allopregnanolone in rat hippocampal slices (Sanna et al., 2004), and ethanol-induced elevations of allopregnanolone immunoreactivity are independent of adrenal activation in the CA1 pyramidal cell layer, dentate gyrus polymorphic layer, bed nucleus of the stria terminalis (BNST), and paraventricular nucleus of Wistar rats (Cook, Nelli, et al., 2014). Moreover, the ethanol-induced decreases in allopregnanolone labeling in the nucleus accumbens (NAcc) core shell border and central nucleus of the amygdala are also independent of adrenal activation, while in the medial prefrontal cortex (mPFC) ethanol increased allopregnanolone immunoreactivity after sham surgery, but not after adrenalectomy, suggesting that adrenals contribute to allopregnanolone elevations in the mPFC (Cook, Nelli, et al., 2014).

Summary of the Alcohol-Induced Changes in Neuroactive Steroids in Rats Acute alcohol

Chronic alcohol

Pregnenolone

m Levels in plasma and cerebral cortex

Not assayed

Progesterone

m Levels in plasma and cerebral cortex

Not assayed

Allopregnanolone m Levels in plasma, cerebral cortex, hippocampus m Immunoreactivity in mPFC, hippocampal CA1 pyramidal cell layer, dentate gyrus polymorph cell layer, BNST, and paraventricular nucleus of the hypothalamus k Immunoreactivity in NAcc and central nucleus of the amygdala Unchanged immunoreactivity in VTA, dorsomedial striatum, dentate gyrus granule cell layer, lateral or basolateral amygdala

k Levels in cerebral cortex and hippocampus of dependent rats Unchanged levels in cerebral cortex at withdrawal Blunted elevations in cerebral cortex following ethanol challenge

DOC

m Levels in plasma, cerebral cortex, hippocampus, hypothalamus, olfactory bulb, and cerebellum

Unchanged levels in plasma, cerebral cortex, hippocampus, hypothalamus, olfactory bulb, and cerebellum. Blunted elevations in plasma, cerebral cortex, hippocampus, hypothalamus, olfactory bulb, and cerebellum following ethanol challenge

THDOC

m Levels in plasma, cerebral cortex, hippocampus

Not assayed

3α,5αAndrosterone

Unchanged levels in plasma

Not assayed

Etiocholanolone

Unchanged levels in plasma

Not assayed

Testosterone

m Levels in plasma, frontal cortex

Not assayed

3α,5αAndrostandiol

Unchanged levels in plasma

Not assayed

m, increase; k, decrease.

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Summary of the Alcohol-Induced Changes in Neuroactive Steroids in Mice Acute alcohol

Chronic alcohol

Pregnenolone

m Levels in plasma of C57BL/6J and DBA/2J

k Levels in plasma of WSP at withdrawal Unchanged levels in plasma of WSR at withdrawal

Progesterone

m Levels in plasma of C57BL/6J and DBA/2J Unchanged levels in cerebral cortex and hippocampus of C57BL/6J and DBA/2J

Not assayed

Allopregnanolone k Levels in plasma, unchanged levels in cerebral cortex and hippocampus of C57BL/6J Unchanged levels in plasma, cerebral cortex and hippocampus of DBA/2J m Levels in whole brain of DBA/2J Unchanged levels in whole brain of C57BL/6J

k Levels in plasma of dependent WSP, and in cerebral cortex of dependent WSR Unchanged levels in plasma of dependent WSR and in cerebral cortex of dependent WSP k Levels in plasma and cerebral cortex of WSP and WSR at withdrawal m Levels in whole brain of C57BL/6J k Immunoreactivity in central nucleus of the amygdala, lateral amygdala, mPFC, NAcc core, dorsolateral striatum, VTA of C57BL/6J at withdrawal m Immunoreactivity in CA3 hippocampus of C57BL/6J at withdrawal

DOC

m Levels in plasma of C57BL/6J and DBA/2J

Not assayed

THDOC

Unchanged levels in plasma of C57BL/6J and DBA/2J

Unchanged levels in plasma of WSP and WSR at withdrawal

DHEA

Not assayed

k Levels in plasma of WSP and WSR at withdrawal

3α,5αAndrosterone

Unchanged levels in plasma of C57BL/6J and DBA/2J

k Levels in plasma of WSP and WSR at withdrawal

3α,5αAndrostandiol

Unchanged levels in plasma of C57BL/6J and DBA/2J

k Levels in plasma of WSP and WSR at withdrawal

3α,5βAndrostandiol

Unchanged levels in plasma of C57BL/6J and DBA/2J

k Levels in plasma of WSP and WSR at withdrawal

m, increase; k, decrease.

Ethanol’s effects on neuroactive steroid levels in mice differ among strains (Table 42.2). Systemic ethanol administration (2 g/kg) increased plasma levels of the precursors pregnenolone, progesterone, and DOC in male C57BL/6J and DBA/2J strains, but it decreased plasma allopregnanolone levels in C57BL/6J mice, without altering its levels in DBA/2J mice (Porcu et al., 2010). Moreover, acute ethanol administration (1 4 g/kg) did not alter cerebrocortical and hippocampal levels of allopregnanolone and progesterone in C57BL/6J and DBA/2J mice, despite activating the HPA axis, as shown by increased brain and plasma corticosterone levels in both strains (Porcu et al., 2014). However, other studies reported that ethanol administration (2 g/kg) increased whole brain allopregnanolone content in male DBA/2J, but not C57BL/6J mice, while orally consumed ethanol increased whole brain allopregnanolone levels in male, but not female, C57BL/6J mice (Finn, Beckley, Kaufman, & Ford, 2010). The effects of acute ethanol administration on neuroactive steroid concentrations in humans and nonhuman primates are limited. Ethanol (1.5 g/kg) did not alter plasma concentrations of neuroactive steroids or cortisol in cynomolgus monkeys (Porcu et al., 2010;

Porcu, Grant, Green, Rogers, & Morrow, 2006) (Table 42.3). In humans, plasma concentrations of allopregnanolone were elevated in male and female adolescents seen in the emergency room for alcohol intoxication (which likely had higher blood alcohol levels) (Torres & Ortega, 2003, 2004). However, controlled laboratory administration of low (0.2 g/kg) or moderate (0.8 g/kg) ethanol doses did not alter (Holdstock, Penland, Morrow, & de Wit, 2006; Porcu et al., 2010), or did decrease (Nyberg et al., 2005; Pierucci-Lagha et al., 2006), serum allopregnanolone levels in healthy subjects (Table 42.4). Indeed, the same dose consumed by humans in the laboratory studies failed to alter allopregnanolone levels in rats (Porcu et al., 2010), suggesting that higher doses of ethanol might affect neuroactive steroid concentrations in humans; moreover, the possibility that ethanol may increase brain neuroactive steroid levels without affecting those in the periphery cannot be excluded.

Chronic Alcohol Effects In contrast to acute ethanol administration, chronic alcohol consumption slightly decreased cerebrocortical

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TABLE 42.3

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Summary of the Alcohol-Induced Changes in Neuroactive Steroids in Cynomolgus Monkeys Acute alcohol

Chronic alcohol

Pregnenolone

Unchanged levels in plasma

Not assayed

Progesterone

Not assayed

Not assayed

Allopregnanolone

Unchanged levels in plasma

k Levels in plasma k Immunoreactivity in lateral and basolateral amygdala

Pregnanolone

Unchanged levels in plasma

Not assayed

DOC

Unchanged levels in plasma

Unchanged levels in plasma after schedule induction of alcohol self-administration Blunted response to CRH and ACTH challenges m Levels in plasma after voluntary alcohol self-administration m Response to naloxone, CRH, ACTH, and ethanol challenges after voluntary alcohol self-administration

THDOC

Unchanged levels in plasma

Not assayed

3α,5α-Androsterone

Unchanged levels in plasma

Not assayed

3α,5α-Androstandiol

Unchanged levels in plasma

Not assayed

m, increase; k, decrease.

TABLE 42.4

Summary of the Alcohol-Induced Changes in Neuroactive Steroids in Humans Acute alcohol

Chronic alcohol

Pregnenolone

m Or unchanged levels in serum of healthy volunteers

m levels in several limbic regions of alcoholics

Progesterone

m Levels in plasma of women in the luteal phase Unchanged levels in plasma of men and women in the follicular phase k Levels in plasma of healthy volunteers

k levels in serum during dependence

Allopregnanolone

m Levels in plasma of male and female adolescents under alcohol intoxication k Or unchanged levels in serum of healthy volunteers

k levels in serum during dependence and withdrawal m immunoreactivity in VTA and substantia nigra pars medialis

Pregnanolone

Unchanged levels in serum of healthy volunteers

k levels in serum during dependence

DOC

Not assayed

Unchanged levels in plasma during dependence Delayed response to CRH challenge

THDOC

Unchanged levels in serum of healthy volunteers

k levels in serum during dependence and withdrawal

DHEA

m Levels in serum of healthy volunteers

m levels in several limbic regions of alcoholics

3α,5αAndrosterone

Unchanged levels in serum of healthy volunteers

Not assayed

Etiocholanolone

Unchanged levels in serum of healthy volunteers

Not assayed

Testosterone

m Or unchanged levels in plasma of healthy men m Levels in plasma of healthy women

k levels in plasma of AUD men Unchanged levels in several limbic regions of alcoholics

3α,5αAndrostandiol

Unchanged levels in serum of healthy volunteers

Not assayed

3α,5βAndrostandiol

Unchanged levels in serum of healthy volunteers

Not assayed

m, increase; k, decrease.

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and hippocampal allopregnanolone levels in ethanoldependent male, but not female, rats, while chronic ethanol withdrawal did not affect allopregnanolone concentrations (Janis, Devaud, Mitsuyama, & Morrow, 1998; Morrow, Porcu, Boyd, & Grant, 2006). Ethanol dependence also resulted in a blunted elevation of cerebrocortical allopregnanolone, and of plasma and brain DOC levels following an acute ethanol challenge (Khisti, Boyd, Kumar, & Morrow, 2005; Morrow et al., 2006), suggesting tolerance to ethanol-induced increases in neuroactive steroid levels (Table 42.1). Chronic ethanol also blunts HPA axis activity, and it is likely that HPA axis adaptations may contribute to tolerance to ethanol’s effects and to the blunted neuroactive steroid responses. Effects of chronic ethanol exposure and its withdrawal in mice vary across strains and across procedures (Table 42.2). Ethanol dependence and withdrawal differentially affect plasma and cerebrocortical allopregnanolone levels, as well as plasma levels of other neuroactive steroids in male Withdrawal Seizure-Prone (WSP) and Withdrawal SeizureResistant (WSR) mice (Finn et al., 2010; Snelling et al., 2014). Voluntary ethanol consumption under a limited access procedure increased whole brain allopregnanolone content in male, but not female, C57BL/6J mice (Finn et al., 2010). By contrast, CIE exposure and subsequent withdrawal in male C57BL/6J mice decreased allopregnanolone immunoreactivity in the lateral amygdala and VTA (Maldonado-Devincci et al., 2014). Twelve-months voluntary alcohol self-administration decreased plasma allopregnanolone levels, and allopregnanolone immunoreactivity in the lateral and basolateral amygdala of male cynomolgus monkeys (Table 42.3). This decrease was more pronounced in heavy drinkers; in fact, allopregnanolone immunoreactivity in the lateral and basolateral amygdala was inversely related to daily ethanol intake. Moreover, cellular allopregnanolone in the lateral amygdala correlated with dexamethasone-induced changes in pregnenolone levels, assessed in the same monkeys prior to any ethanol exposure, suggesting that allopregnanolone in the amygdala may correlate to HPA axis function (Beattie et al., 2017). Chronic alcohol exposure also altered circulating levels of DOC and the DOC responses to pharmacological challenges to the HPA axis in male cynomolgus monkeys. Specifically, basal DOC levels were increased following 6-months voluntary alcohol self-administration, and the DOC responses to naloxone, CRH, and ACTH challenges were increased compared to baseline responses before any ethanol exposure (Table 42.3). Moreover, voluntary alcohol self-administration also increased the DOC responses to acute ethanol challenges (1.0 and 1.5 g/kg), compared to the baseline ones (Jimenez, Porcu, Morrow, & Grant, 2017).

In humans, serum levels of progesterone, allopregnanolone, and THDOC were decreased in alcoholics during withdrawal and returned to normal levels upon recovery (Hill et al., 2005; Romeo et al., 1996). By contrast, no changes in basal plasma DOC levels were found in alcohol-dependent subjects compared to healthy controls; however, alcohol-dependent subjects had a delayed DOC response to corticotrophin releasing hormone (CRH) challenge (Porcu, O’Buckley, Morrow, & Adinoff, 2008) (Table 42.4). Effects of chronic alcohol consumption on neuroactive steroids in the human brain are still fairly unknown. A recent study examined allopregnanolone immunoreactivity in several brain areas from alcohol-dependent subjects. Cellular allopregnanolone was increased in the ventral tegmental area (VTA) of alcoholics compared to controls; however, allopregnanolone immunoreactivity in the VTA did not correlate with lifetime alcohol consumption. By contrast, in the substantia nigra pars medialis, an increase in allopregnanolone immunoreactivity was observed in male, but not female, alcoholdependent subjects, compared to the respective controls (Hasirci, Maldonado-Devincci, Beattie, O’Buckley, & Morrow, 2017). Furthermore, pregnenolone and dehydroepiandrosterone (DHEA) levels measured by liquid chromatography-tandem mass spectrometry in postmortem brains of alcohol-dependent subjects were elevated in several limbic regions (Karkkainen et al., 2016), further suggesting that brain neuroactive steroid synthesis is dysregulated in alcoholics (Table 42.4). Whether this dysregulation is preexistent to, or is the consequence of, alcohol exposure is still unclear.

NEUROACTIVE STEROIDS MEDIATE SPECIFIC BEHAVIORAL EFFECTS OF ETHANOL Ethanol-induced elevations in allopregnanolone reach physiologically relevant concentrations that enhance GABAergic transmission. In fact, ethanolinduced allopregnanolone elevations contribute to many behavioral effects of ethanol in rodents, including ethanol’s anticonvulsant effects, sedation, impairment of spatial memory, anxiolytic-like, and antidepressant-like effects (Porcu & Morrow, 2014). Each of these behavioral responses is prevented by adrenalectomy and/or by inhibition of allopregnanolone biosynthesis with finasteride. Notably, administration of 5α-dihydroprogesterone, the immediate precursor of allopregnanolone, to adrenalectomized rats restores ethanol’s effects, suggesting that brain allopregnanolone synthesis modulates those effects (Khisti et al., 2003). Thus, elevations in neuroactive steroids influence many of the GABAergic effects of ethanol

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INDIVIDUAL VARIATION IN NEUROACTIVE STEROIDS CONTRIBUTES TO ETHANOL INTAKE IN RODENTS AND MONKEYS

in vivo and contribute to sensitivity to the behavioral effects of ethanol. Neuroactive steroids contribute to the subjective effects of alcohol in humans. In fact, finasteride pretreatment blocked subjective effects of alcohol, measured during the rising phase of the blood alcohol curve, using three different scales to measure the activating, sedating, anesthetic, and peripheral dynamic aspects of alcohol actions (Pierucci-Lagha et al., 2005). 5α-reductase inhibition with dutasteride also diminished the sedative and anesthetic effects of alcohol in moderate to heavy drinking men, and decreased subsequent alcohol consumption in heavy drinkers (Covault et al., 2014). Moreover, subjects treated with finasteride for male pattern hair loss, also reported a decrease in alcohol consumption, which was greater in those who consumed the most alcohol. These subjects also showed increased anxiety, tiredness, and dizziness after alcohol exposure, which may have contributed to alcohol aversion (Irwig, 2013). Overall, these results further support the hypothesis that neuroactive steroids mediate subjective effects of alcohol and contribute to ethanol sensitivity in humans.

NEUROACTIVE STEROIDS INFLUENCE DRINKING BEHAVIOR IN RODENTS Neuroactive steroids affect ethanol reinforcement and consumption. In male C57BL/6J mice, allopregnanolone dose-dependently modulates ethanol intake, with low doses (3.2 mg/kg) increasing, and high doses (24 mg/kg) decreasing alcohol consumption in a 2hour limited access paradigm. In the same strains, allopregnanolone also reinstates ethanol-seeking behavior, while finasteride prevents acquisition of drinking (Finn et al., 2010). Allopregnanolone has a biphasic effect on alcohol consumption in rats; in fact, it increased ethanol-reinforced operant responding in nondependent, male Long-Evans rats (Janak, Redfern, & Samson, 1998), but it also decreased ethanol consumption in dependent, alcohol-preferring rats (Morrow, VanDoren, Penland, & Matthews, 2001). In addition, administration of the neuroactive steroid precursor pregnenolone, or the endogenous (epiallopregnanolone) or synthetic (3α,5β-20-oxo-pregnane-3carboxylic acid) neuroactive steroids, also reduced ethanol self-administration in male, alcohol-preferring rats (Besheer, Lindsay, O’Buckley, Hodge, & Morrow, 2010; O’Dell et al., 2005), suggesting that neuroactive steroids may protect against excessive drinking. To further test this hypothesis, neuroactive steroid biosynthesis was promoted by over-expression of P450scc, the rate limiting enzyme in steroid synthesis (Fig. 42.1). Recombinant adeno-associated serotype-2-vector-mediated

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over-expression of P450scc in the VTA of alcoholpreferring male rats induced a long-lasting reduction in ethanol reinforcement and consumption, and a concomitant increase in allopregnanolone immunoreactivity in this area (Cook, Werner, et al., 2014). Therefore, targeted modulation of neuroactive steroid synthesis through administration of steroid precursors or through increased expression of specific neurosteroidogenic enzymes may represent a useful therapeutic approach for patients with AUD.

INDIVIDUAL VARIATION IN NEUROACTIVE STEROIDS CONTRIBUTES TO ETHANOL INTAKE IN RODENTS AND MONKEYS Individual differences in vulnerability to AUD have a genetic component (Schuckit, 2009), and studies in rodents showed a shared genetic sensitivity to ethanol, anxiety, and stress/HPA axis response (Boehm, Reed, McKinnon, & Phillips, 2002). We investigated the genetic regulation of basal DOC levels across the BXD strains, and found significant genetic variation in cerebrocortical and plasma DOC levels (Porcu et al., 2011). Moreover, variation in DOC levels was linked to ethanol-induced sedation, ethanol-induced ataxia, and ethanol-induced corticosterone levels. Thus, strains with higher DOC levels showed greater ethanol sensitivity, consistent with the hypothesis that elevated GABAergic neuroactive steroids may protect against the risk for AUD (Morrow et al., 2006; Porcu & Morrow, 2014). We recently examined the genetic regulation of ethanol-induced serum levels of pregnenolone, allopregnanolone, and THDOC in BXD strains subjected to CIE exposure. We found significant genetic variation in levels of these neuroactive steroids in both airexposed controls and CIE-exposed strains, which was linked to several behavioral phenotypes of anxiety, previously determined in these strains, consistent with the fact that neuroactive steroids modulate anxiety-like behavior. Moreover, individual variation in allopregnanolone levels was inversely related to ethanol consumption in both control and CIE-exposed strains: strains with lower allopregnanolone levels were the ones that consumed more alcohol in a two-bottle choice paradigm. This effect appeared specific to allopregnanolone, as similar correlations were not observed for THDOC or pregnenolone levels (Porcu et al., 2017). Interestingly, allopregnanolone content was related to alcohol intake also in cynomolgus monkeys: the lowest cellular allopregnanolone levels in the lateral and basolateral amygdala were observed in those

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subjects with the highest alcohol consumption (Beattie et al., 2017). It is unknown whether this condition was preexistent to, or is the consequence of, alcohol exposure. However, the observations that elevated neuroactive steroid levels are associated with increased ethanol sensitivity in monkeys (Grant, Azarov, Shively, & Purdy, 1997), and reduced drinking in rodents (Cook, Werner et al., 2014; Finn et al., 2010), suggest that low allopregnanolone levels in the amygdala may have contributed to increased drinking. The DOC response to the dexamethasone challenge in ethanol-naive cynomolgus monkeys also predicted subsequent voluntary alcohol consumption. That is, the highest alcohol consumption was observed in those monkeys that had the lowest suppression of DOC levels following HPA axis inhibition by dexamethasone (Porcu et al., 2006). Thus, dexamethasone suppression of DOC may be a putative biomarker of risk for elevated alcohol consumption in monkeys (Porcu et al., 2006).

However, no correlation was found between basal allopregnanolone levels and average alcohol use frequency, quantity, or “AUD Identification Test” scores. Another study reported that polymorphic variation in the genes for 5α-reductase and 3α-HSD, the enzymes that convert progesterone and DOC into their neuroactive metabolites allopregnanolone and THDOC, was associated with risk for AUD. The minor C-allele for SRD5A1 exon 1 SNP rs248793 (encoding for 5α-reductase), and the minor G-allele for AKR1C3 2 exon 1 SNP rs12529 (encoding for 3α-HSD) were more frequent in control subjects compared to alcoholdependent subjects, suggesting that these minor alleles may have a protective effect against AUD (Milivojevic, Kranzler, Gelernter, Burian, & Covault, 2011). Taken together, these results provide further indirect evidence that neuroactive steroids may play a role in AUD in humans.

Individual Variation in Neuroactive Steroids May Contribute to Alcohol Use Disorder in Humans

Findings reviewed in this chapter support the hypothesis that elevated allopregnanolone content in response to alcohol may protect against excessive drinking and risk for AUD (Fig. 42.2). Chronic alcohol consumption decreases neuroactive steroid levels and results in blunted elevations of neuroactive steroids in response to challenges across different species. This diminished response would result in reduced sensitivity to the anxiolytic, sedative, anticonvulsant, cognitive-impairing, and subjective effects of ethanol (Morrow et al., 2006; Porcu & Morrow, 2014). Reduced sensitivity to ethanol is associated with greater risk for the development of AUD in individuals with genetic

Genetic variation may contribute to the differences in neuroactive steroid responses to stress or alcohol in humans. Recent studies investigated the role of genetic polymorphisms in AUD with a focus on neuroactive steroids. Naltrexone administration increased serum allopregnanolone levels among alcohol-dependent subjects with the Asp40 allele of the opioid receptor mu-1 gene, but not among those carrying the Asn40 allele (Ray, Hutchison, Ashenhurst, & Morrow, 2010).

CONCLUSIONS

FIGURE 42.2 Hypothetical role of neuroactive steroids in AUD. Schematic illustration of the hypothetical role of neuroactive steroids in alcohol sensitivity and risk for AUD.

IV. PHARMACOLOGY, NEUROACTIVES, MOLECULAR, AND CELLULAR BIOLOGY

REFERENCES

vulnerability to AUD (Schuckit, 2009). Thus, neuroactive steroid responses to alcohol may play a role in vulnerability to AUD, and targeted manipulation of their levels may represent a new therapeutic approach for patients with AUD.

MINI-DICTIONARY OF TERMS GABAARs γ-Aminobutyric acid type-A receptors, hetero-pentameric channels that mediate most of the inhibitory transmission in the central nervous system. Allopregnanolone (3α,5α)-3-Hydroxypregnan-20-one, or 3α,5αTHP, endogenous neuroactive neurosteroid. THDOC (3α,5α)-3,21-Dihydroxypregnan-20-one, or tetrahydrodeoxycorticosterone, neuroactive metabolite of DOC. Deoxycorticosterone A progesterone metabolite and precursor of THDOC and corticosterone. Finasteride A 5α-reductase inhibitor that prevents the formation of the 3α,5α-reduced metabolites of progesterone, DOC, DHEA and testosterone. BXD strains C57BL/6J (B6) 3 DBA/2J (D2) recombinant inbred mouse strains, a reference population to study networks of phenotypes and their modulation by gene variants.

KEY FACTS Neuroactive Steroids • Neuroactive steroids are endogenous or exogenous steroids that induce rapid changes in neuronal excitability and elicit behavioral effects within seconds to minutes. • Endogenous steroids synthesized de novo in the central and peripheral nervous systems, independent of endocrine glands, are termed neurosteroids. • Neuroactive steroids regulate neuronal function via genomic and membrane-mediated actions through specific interactions with ion-channel-coupled neurotransmitter receptors. • Among them, allopregnanolone is the most potent endogenous modulator of GABAA receptors through which it exerts anxiolytic, sedative, antidepressant, and anticonvulsant effects. • Altered allopregnanolone concentrations have been reported in several psychiatric disorders, including alcohol use disorders.

SUMMARY POINTS • Alcohol differentially affects neuroactive steroid concentrations depending on acute versus chronic exposure, as well as on species and brain regions examined.

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• Neuroactive steroids mediate behavioral and subjective effects of alcohol across species. • Neuroactive steroids influence drinking behavior in rodents and monkeys. • Neuroactive steroids increase ethanol sensitivity and often reduce alcohol consumption, but genetic variation moderates these effects. • Animal studies provide a strong rationale to explore therapeutic actions of neuroactive steroids in alcohol use disorders, but human studies are needed.

References Barbaccia, M. L., Affricano, D., Trabucchi, M., Purdy, R. H., Colombo, G., Agabio, R., & Gessa, G. L. (1999). Ethanol markedly increases “GABAergic” neurosteroids in alcohol-preferring rats. European Journal of Pharmacology, 384(2 3), R1 R2. Beattie, M. C., Maldonado-Devincci, A. M., Porcu, P., O’Buckley, T. K., Daunais, J. B., Grant, K. A., & Morrow, A. L. (2017). Voluntary ethanol consumption reduces GABAergic neuroactive steroid (3α,5α)3-hydroxypregnan-20-one (3α,5α-THP) in the amygdala of the cynomolgus monkey. Addiction Biology, 22(2), 318 330. Besheer, J., Lindsay, T. G., O’Buckley, T. K., Hodge, C. W., & Morrow, A. L. (2010). Pregnenolone and ganaxolone reduce operant ethanol self-administration in alcohol-preferring p rats. Alcoholism, Clinical and Experimental Research, 34(12), 2044 2052. Boehm, S. L., II, Reed, C. L., McKinnon, C. S., & Phillips, T. J. (2002). Shared genes influence sensitivity to the effects of ethanol on locomotor and anxiety-like behaviors, and the stress axis. Psychopharmacology (Berl), 161(1), 54 63. Boyd, K. N., Kumar, S., O’Buckley, T. K., Porcu, P., & Morrow, A. L. (2010). Ethanol induction of steroidogenesis in rat adrenal and brain is dependent upon pituitary ACTH release and de novo adrenal StAR synthesis. Journal of Neurochemistry, 112(3), 784 796. Carver, C. M., & Reddy, D. S. (2013). Neurosteroid interactions with synaptic and extrasynaptic GABAA receptors: Regulation of subunit plasticity, phasic and tonic inhibition, and neuronal network excitability. Psychopharmacology (Berl), 230(2), 151 188. Cook, J. B., Dumitru, A. M., O’Buckley, T. K., & Morrow, A. L. (2014). Ethanol administration produces divergent changes in GABAergic neuroactive steroid immunohistochemistry in the rat brain. Alcoholism, Clinical and Experimental Research, 38(1), 90 99. Cook, J. B., Nelli, S. M., Neighbors, M. R., Morrow, D. H., O’Buckley, T. K., Maldonado-Devincci, A. M., & Morrow, A. L. (2014). Ethanol alters local cellular levels of (3α,5α)-3-hydroxypregnan20-one (3α,5α-THP) independent of the adrenals in subcortical brain regions. Neuropsychopharmacology, 39(8), 1978 1987. Cook, J. B., Werner, D. F., Maldonado-Devincci, A. M., Leonard, M. N., Fisher, K. R., O’Buckley, T. K., & Morrow, A. L. (2014). Overexpression of the steroidogenic enzyme cytochrome P450 side chain cleavage in the ventral tegmental area increases 3α,5αTHP and reduces long-term operant ethanol self-administration. The Journal of Neuroscience, 34(17), 5824 5834. Covault, J., Pond, T., Feinn, R., Arias, A. J., Oncken, C., & Kranzler, H. R. (2014). Dutasteride reduces alcohol’s sedative effects in men in a human laboratory setting and reduces drinking in the natural environment. Psychopharmacology (Berl), 231(17), 3609 3618. Finn, D. A., Beckley, E. H., Kaufman, K. R., & Ford, M. M. (2010). Manipulation of GABAergic steroids: Sex differences in the effects on alcohol drinking- and withdrawal-related behaviors. Hormones and Behavior, 57(1), 12 22.

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Grant, K. A., Azarov, A., Shively, C. A., & Purdy, R. H. (1997). Discriminative stimulus effects of ethanol and 3alpha-hydroxy5alpha-pregnan-20-one in relation to menstrual cycle phase in cynomolgus monkeys (Macaca fascicularis). Psychopharmacology (Berl), 130(1), 59 68. Hasirci, A. S., Maldonado-Devincci, A. M., Beattie, M. C., O’Buckley, T. K., & Morrow, A. L. (2017). Cellular GABAergic neuroactive steroid (3α,5α)-3-hydroxy-pregnan-20-one (3α,5α-THP) immunostaining levels are increased in the ventral tegmental area of human alcohol use disorder patients: A postmortem study. Alcoholism, Clinical and Experimental Research, 41(2), 299 311. Hill, M., Popov, P., Havlikova, H., Kancheva, L., Vrbikova, J., Kancheva, R., & Starka, L. (2005). Altered profiles of serum neuroactive steroids in premenopausal women treated for alcohol addiction. Steroids, 70(8), 515 524. Holdstock, L., Penland, S. N., Morrow, A. L., & de Wit, H. (2006). Moderate doses of ethanol fail to increase plasma levels of neurosteroid 3α-hydroxy-5α-pregnan-20-one-like immunoreactivity in healthy men and women. Psychopharmacology (Berl), 186(3), 442 450. Hosie, A. M., Wilkins, M. E., da Silva, H. M., & Smart, T. G. (2006). Endogenous neurosteroids regulate GABAA receptors through two discrete transmembrane sites. Nature, 444(7118), 486 489. Irwig, M. S. (2013). Decreased alcohol consumption among former male users of finasteride with persistent sexual side effects: A preliminary report. Alcoholism, Clinical and Experimental Research, 37(11), 1823 1826. Janak, P. H., Redfern, J. E., & Samson, H. H. (1998). The reinforcing effects of ethanol are altered by the endogenous neurosteroid, allopregnanolone. Alcoholism, Clinical and Experimental Research, 22 (5), 1106 1112. Janis, G. C., Devaud, L. L., Mitsuyama, H., & Morrow, A. L. (1998). Effects of chronic ethanol consumption and withdrawal on the neuroactive steroid 3alpha-hydroxy-5alpha-pregnan-20-one in male and female rats. Alcoholism, Clinical and Experimental Research, 22(9), 2055 2061. Jimenez, V. A., Porcu, P., Morrow, A. L., & Grant, K. A. (2017). Adaptations in basal and hypothalamic-pituitary-adrenalactivated deoxycorticosterone responses following ethanol selfadministration in cynomolgus monkeys. Front Endocrinol (Lausanne), 8, 19. Karkkainen, O., Hakkinen, M. R., Auriola, S., Kautiainen, H., Tiihonen, J., & Storvik, M. (2016). Increased steroid hormone dehydroepiandrosterone and pregnenolone levels in post-mortem brain samples of alcoholics. Alcohol (Fayetteville, N.Y.), 52, 63 70. Khisti, R. T., Boyd, K. N., Kumar, S., & Morrow, A. L. (2005). Systemic ethanol administration elevates deoxycorticosterone levels and chronic ethanol exposure attenuates this response. Brain Research, 1049(1), 104 111. Khisti, R. T., VanDoren, M. J., O’Buckley, T., & Morrow, A. L. (2003). Neuroactive steroid 3alpha-hydroxy-5alpha-pregnan-20-one modulates ethanol-induced loss of righting reflex in rats. Brain Research, 980(2), 255 265. Maldonado-Devincci, A. M., Cook, J. B., O’Buckley, T. K., Morrow, D. H., McKinley, R. E., Lopez, M. F., & Morrow, A. L. (2014). Chronic intermittent ethanol exposure and withdrawal alters (3α,5α)-3-hydroxy-pregnan-20-one immunostaining in cortical and limbic brain regions of C57BL/6J mice. Alcoholism, Clinical and Experimental Research, 38(10), 2561 2571. Milivojevic, V., Kranzler, H. R., Gelernter, J., Burian, L., & Covault, J. (2011). Variation in genes encoding the neuroactive steroid synthetic enzymes 5α-reductase type 1 and 3α-reductase type 2 is associated with alcohol dependence. Alcoholism, Clinical and Experimental Research, 35(5), 946 952.

Morrow, A. L., Janis, G. C., VanDoren, M. J., Matthews, D. B., Samson, H. H., Janak, P. H., & Grant, K. A. (1999). Neurosteroids mediate pharmacological effects of ethanol: A new mechanism of ethanol action? Alcoholism, Clinical and Experimental Research, 23 (12), 1933 1940. Morrow, A. L., Porcu, P., Boyd, K. N., & Grant, K. A. (2006). Hypothalamic-pituitary-adrenal axis modulation of GABAergic neuroactive steroids influences ethanol sensitivity and drinking behavior. Dialogues in Clinical Neuroscience, 8(4), 463 477. Morrow, A. L., VanDoren, M. J., Penland, S. N., & Matthews, D. B. (2001). The role of GABAergic neuroactive steroids in ethanol action, tolerance and dependence. Brain Research. Brain Research Reviews, 37(1-3), 98 109. Nyberg, S., Andersson, A., Zingmark, E., Wahlstrom, G., Backstrom, T., & Sundstrom-Poromaa, I. (2005). The effect of a low dose of alcohol on allopregnanolone serum concentrations across the menstrual cycle in women with severe premenstrual syndrome and controls. Psychoneuroendocrinology, 30(9), 892 901. O’Dell, L. E., Purdy, R. H., Covey, D. F., Richardson, H. N., Roberto, M., & Koob, G. F. (2005). Epipregnanolone and a novel synthetic neuroactive steroid reduce alcohol self-administration in rats. Pharmacology, Biochemistry, and Behavior, 81(3), 543 550. Pierucci-Lagha, A., Covault, J., Feinn, R., Khisti, R. T., Morrow, A. L., Marx, C. E., & Kranzler, H. R. (2006). Subjective effects and changes in steroid hormone concentrations in humans following acute consumption of alcohol. Psychopharmacology (Berl), 186(3), 451 461. Pierucci-Lagha, A., Covault, J., Feinn, R., Nellissery, M., HernandezAvila, C., Oncken, C., & Kranzler, H. R. (2005). GABRA2 alleles moderate the subjective effects of alcohol, which are attenuated by finasteride. Neuropsychopharmacology, 30(6), 1193 1203. Porcu, P., Barron, A. M., Frye, C. A., Walf, A. A., Yang, S. Y., He, X. Y., & Melcangi, R. C. (2016). Neurosteroidogenesis today: Novel targets for neuroactive steroid synthesis and action and their relevance for translational research. Journal of Neuroendocrinology, 28(2), 12351. Porcu, P., Grant, K. A., Green, H. L., Rogers, L. S., & Morrow, A. L. (2006). Hypothalamic-pituitary-adrenal axis and ethanol modulation of deoxycorticosterone levels in cynomolgus monkeys. Psychopharmacology (Berl), 186(3), 293 301. Porcu, P., Locci, A., Santoru, F., Berretti, R., Morrow, A. L., & Concas, A. (2014). Failure of acute ethanol administration to alter cerebrocortical and hippocampal allopregnanolone levels in C57BL/6J and DBA/2J mice. Alcoholism, Clinical and Experimental Research, 38(4), 948 958. Porcu, P., & Morrow, A. L. (2014). Divergent neuroactive steroid responses to stress and ethanol in rat and mouse strains: Relevance for human studies. Psychopharmacology (Berl), 231(17), 3257 3272. Porcu, P., O’Buckley, T. K., Alward, S. E., Song, S. C., Grant, K. A., de Wit, H., & Morrow, A. L. (2010). Differential effects of ethanol on serum GABAergic 3α,5α/3α,5β neuroactive steroids in mice, rats, cynomolgus monkeys, and humans. Alcoholism, Clinical and Experimental Research, 34(3), 432 442. Porcu, P., O’Buckley, T. K., Lopez, M. F., Becker, H. C., Miles, M. F., Williams, R. W., & Morrow, A. L. (2017). Initial genetic dissection of serum neuroactive steroids following chronic intermittent ethanol across BXD mouse strains. Alcohol (Fayetteville, N.Y.), 58, 107 125. Porcu, P., O’Buckley, T. K., Morrow, A. L., & Adinoff, B. (2008). Differential hypothalamic-pituitary-adrenal activation of the neuroactive steroids pregnenolone sulfate and deoxycorticosterone in healthy controls and alcohol-dependent subjects. Psychoneuroendocrinology, 33(2), 214 226.

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Porcu, P., O’Buckley, T. K., Song, S. C., Harenza, J. L., Lu, L., Wang, X., & Morrow, A. L. (2011). Genetic analysis of the neurosteroid deoxycorticosterone and its relation to alcohol phenotypes: Identification of QTLs and downstream gene regulation. PLoS One, 6(4), e18405. Porcu, P., Sogliano, C., Ibba, C., Piredda, M., Tocco, S., Marra, C., & Concas, A. (2004). Failure of gamma-hydroxybutyric acid both to increase neuroactive steroid concentrations in adrenalectomizedorchiectomized rats and to induce tolerance to its steroidogenic effect in intact animals. Brain Research, 1012(1-2), 160 168. Ray, L. A., Hutchison, K. E., Ashenhurst, J. R., & Morrow, A. L. (2010). Naltrexone selectively elevates GABAergic neuroactive steroid levels in heavy drinkers with the Asp40 allele of the OPRM1 gene: A pilot investigation. Alcoholism, Clinical and Experimental Research, 34(8), 1479 1487. Romeo, E., Brancati, A., De Lorenzo, A., Fucci, P., Furnari, C., Pompili, E., & Pasini, A. (1996). Marked decrease of plasma neuroactive steroids during alcohol withdrawal. Clinical Neuropharmacology, 19(4), 366 369. Sanna, E., Talani, G., Busonero, F., Pisu, M. G., Purdy, R. H., Serra, M., & Biggio, G. (2004). Brain steroidogenesis mediates ethanol

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C H A P T E R

43 Alcohol’s Effects on Extracellular Striatal Dopamine 1

Ashley A. Vena1 and Rueben Gonzales2

University of Chicago, Chicago, IL, United States 2The University of Texas at Austin, Austin, TX, United States

LIST OF ABBREVIATIONS ACSF BAC FSCV NAc SN VTA

artificial cerebrospinal fluid blood alcohol concentration fast-scan cyclic voltammetry nucleus accumbens substantia nigra ventral tegmental area

OVERVIEW OF STRIATAL ANATOMY AND FUNCTION The striatum is a highly integrated, heterogeneous structure that is critically involved in the regulation and expression of motivated behaviors. The striatum integrates sensory (primarily from the cortex), emotional, and cognitive information, as well as memories of past experiences to determine and guide appropriate behavioral responses. Striatal subregions derive their functional roles from distinct cortical inputs. The ventral striatum receives input from the orbitofrontal and anterior cingulate cortices in addition to the amygdala, making it highly responsive to the emotional and motivational components of reward (Haber, 2014). Specifically, the nucleus accumbens (NAc) region of the ventral striatum plays a key role in detecting and responding to the reinforcing properties of alcohol and alcohol-related stimuli (Boileau et al., 2003; Doyon et al., 2003; Gonzales, Job, & Doyon, 2004). The dorsal striatum, or the caudate-putamen in primates and humans, coordinates voluntary motor behaviors. This region can be topographically divided into two functional domains: the dorsomedial striatum

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00043-X

(caudate in primates) and dorsolateral striatum (putamen in primates). The dorsomedial striatum/ caudate, which is innervated by cortical regions associated with cognition and executive control over behavior, coordinates the selection and initiation of goal-directed actions (Grahn, Parkinson, & Owen, 2008; Haber, 2014). The dorsolateral striatum/putamen receives input from the sensorimotor cortex and coordinates automatic or habitual behavioral responses to meaningful stimuli (Grahn et al., 2008; Haber, 2014). Behavioral responses produce outcomes that become associated with environmental stimuli, which are believed to be represented in the ventral striatum and its cortical inputs (Everitt & Robbins, 2005). With repeated experiences, the dorsomedial striatum becomes involved in associating behaviors with specific outcomes. Eventually, behavioral responses may become habitual, or automated, in the presence of specific stimuli, which relies on the dorsolateral striatum (Everitt & Robbins, 2005).

DOPAMINE IN THE STRIATUM Dopamine is a key neuromodulator in the regulation of motivated behaviors. The striatum receives dense innervation from dopamine neurons originating primarily from two midbrain nuclei (Fig. 43.1). The dopaminergic projections originating in the ventral tegmental area (VTA) and terminating in the NAc make up the mesolimbic dopamine pathway, which has been identified as a common target for most drugs of abuse. The nigrostriatal dopamine pathway is

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© 2019 Elsevier Inc. All rights reserved.

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43. ALCOHOL’S EFFECTS ON EXTRACELLULAR STRIATAL DOPAMINE

FIGURE 43.1

Schematic representation of the mesolimbic and nigrostriatal dopamine circuits. The VTA sends dopaminergic projections to the NAc (core and shell subregions) and to the medial subregion of the dorsal striatum, and the SN sends dopaminergic projections to the dorsal striatum. Inhibitory GABAergic neurons in these terminal regions innervate midbrain dopamine neurons, forming striato-nigrostriatal loops. This spiraling circuitry connects the NAc with the dorsal striatum, facilitating the learning and development of stimulus-driven behaviors. Source: Adapted by permission from Lu¨scher, C., & Bellone, C. (2008). Cocaine-evoked synaptic plasticity: A key to addiction? Nature Neuroscience, 11(7), 737 738. https://doi.org/ 10.1038/nn0708-737, Macmillian Publishers Ltd: Nature Neuroscience.

central to the coordination of voluntary motor behaviors (i.e., in response to environmental stimuli), and consists of dopamine neurons originating in the substantia nigra (SN) and terminating in the dorsomedial and dorsolateral striatum. The dorsomedial striatum also receives dopaminergic input from the VTA (Joel & Weiner, 2000). Within the VTA and SN, GABAergic synapses onto dopamine neurons play an important role in regulating dopamine neuron activity. Evidence suggests that the ventral and dorsal striatal subregions are connected in series via a spiraling striatonigrostriatal circuit (Fig. 43.1), which facilitates the development and expression of learned behaviors (Haber, 2014; Ikeda, Saigusa, Kamei, Koshikawa, & Cools, 2013). Within the striatal subregions, dopamine release occurs in response to rewarding stimuli and actions that produce rewarding outcomes, facilitating the learning and expression of conditioned behaviors (Willuhn, Wanat, Clark, & Phillips, 2010; Wise, 2009). Additionally, striatal dopamine appears to convey information about an organism’s motivational state and, thus, contributes to the drive to seek and obtain rewards. For example, dopamine-deficient mice retain their motor capacities, but do not show seeking or approach behavior for a food pellet, even when in a hungry state (Palmiter, 2008). Therefore, identifying alcohol’s specific effects on extracellular striatal dopamine may be critical to understanding the motivational

properties of alcohol and how these contribute to the development of alcohol-seeking and consumption behaviors.

Reward Prediction Error The ability to assign value to behaviors as a result of their outcomes enhances survival by enabling an organism to prioritize those actions that result in favorable outcomes while avoiding those that produce unfavorable outcomes. This requires learning which outcomes are favorable and how to predict the potential for favorable outcomes based on environmental stimuli. Such learning incorporates a prediction error signal as an indication of whether an outcome is better, worse, or the same as predicted. Substantial evidence demonstrates a role for phasic (see Key facts of phasic vs. tonic dopamine signals) dopamine in the mesolimbic pathway as a reward prediction signal (Hart, Rutledge, Glimcher, & Phillips, 2014; O’Doherty et al., 2004; Schultz, 1997; Willuhn et al., 2010). Upon receipt of an unexpected or betterthan-expected reward, there is a spike in dopamine neuron firing and release. In contrast, if an outcome is perceived as worse than expected or aversive, then there is a brief depression in dopamine neuron firing (Schultz, 1997, 1998). If the magnitude of a reward is as predicted, then there is no change in dopamine neuron activity (Schultz, 1997, 1998). The dopamine

IV. PHARMACOLOGY, NEUROACTIVES, MOLECULAR AND CELLULAR BIOLOGY

TECHNIQUES FOR MEASURING EXTRACELLULAR STRIATAL DOPAMINE IN ANIMALS

TECHNIQUES FOR MEASURING EXTRACELLULAR STRIATAL DOPAMINE IN ANIMALS

signal facilitates learning which environmental cues and behavioral actions are associated with rewarding outcomes (Schultz, 1998). Once a reward has been associated with a specific stimulus, the phasic dopamine response transfers to the reward-predicting stimulus (Schultz, 1997, 1998), and dopamine neurons respond to such stimuli in a similar manner to which they respond to rewards.

The primary techniques for quantitating extracellular striatal dopamine concentrations are microdialysis and fast-scan cyclic voltammetry (FSCV). Microdialysis (Fig. 43.2) is a chemical sampling technique in which a probe is implanted into the brain region of interest (Chefer, Thompson, Zapata, & Shippenberg, 2009). The active area of the probe is in direct contact with brain tissue, and is sheathed in a semipermeable membrane. The probe is continuously perfused with artificial cerebrospinal fluid (ACSF) at a constant flow rate to optimize analyte recovery. After dopamine passively diffuses from the extracellular space across the membrane, it is pumped through the probe into collection vials (Chefer et al., 2009). Analytical chemistry methods, usually high-performance liquid chromatography (HPLC), can then be used to quantify dialysate dopamine concentrations. FSCV is an electrochemical technique in which a carbon fiber microelectrode is implanted into the brain region of interest. A rapidly cycling voltage is applied to the electrode, causing extracellular electroactive molecules that come into contact with it to be oxidized and reduced. The resulting current is directly proportional to the number of oxidized molecules (Robinson, 2003). An advantage of FSCV over microdialysis is the enhanced temporal resolution, usually about 100 ms, making it ideal for quantitating real-time phasic

Incentive Salience Striatal dopamine is also hypothesized to mediate the reward seeking and approach behavior that occurs in response to a reward-paired stimulus. The ability of conditioned sensory stimuli to attract attention and affect behavior is referred to as incentive salience, and the mesolimbic dopamine pathway has been implicated in the attribution of incentive salience to environmental stimuli (Berridge & Robinson, 1998; Berridge, 2007). Mesolimbic dopamine neurons are activated upon detection of reward-paired stimuli (Wassum, Ostlund, Loewinger, & Maidment, 2013), possibly triggering a motivational state of “wanting,” or an urge to obtain the reward associated with the stimulus. This may have particular relevance to addiction because with chronic drug or alcohol use, the hedonic impact of the substance appears to diminish, but midbrain dopamine neurons become increasingly sensitized to the incentive value of drugrelated stimuli (Berridge & Robinson, 1998; Berridge, 2007).

FIGURE 43.2 Simplified schematic of a microdialysis experiment in a rodent. The microdialysis probe consists of inlet (blue) and outlet (red) tubing that converge in the probe’s active area, which is implanted through the skull into the brain region interest. A syringe pump pushes artificial cerebrospinal fluid (ACSF) through the probe at a constant rate. The inset illustrates the probe active area, which is sheathed by a semi-permeable membrane that is selective based on molecular weight. Neurotransmitters released by surrounding neurons may passively diffuse across the membrane, getting picked up by the perfusate and pumped out into a collection tube.

Syringe pump

Collection tube

419

ACSF (perfusate) Dialysate

Probe membrane

Neuron terminals

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420 TABLE 43.1

43. ALCOHOL’S EFFECTS ON EXTRACELLULAR STRIATAL DOPAMINE

Short-Term Effects of Alcohol on Behavior by Dose

Blood alcohol content (BAC)

Potential behavioral effects in humans

B0.00% 0.05%

Mild speech, cognitive, and balance impairments Perceived positive effects, such as reduced anxiety and/or euphoria Drowsiness/sedation may begin to develop

B0.06% 0.15%

Further impairment of speech, cognition, and balance/motor coordination Increased risk of aggression and/or injury towards oneself and others, in some people

B0.16% 0.30%

Significant impairment of speech, cognition, reaction time, and motor coordination Blackouts Vomiting Loss of consciousness

B0.31% and higher

Coma Death

Behavioral effects of alcohol typically vary depending on the achieved blood alcohol content (National Institute on Alcohol Abuse and Alcoholism, 2015). Therefore, researchers often study the pharmacological effects of various doses of alcohol.

Several studies aimed at identifying the direct pharmacological effects of acute ethanol on extracellular dopamine have utilized in vivo monitoring techniques in awake, freely behaving animal models. Typically, these studies quantify the neurochemical response to an intoxicating dose of ethanol that is systemically administered via an intravenous catheter or injection into the peritoneal cavity to ethanol-naı¨ve animals. Such models permit the study of ethanol’s direct pharmacological properties without the potential confounds of behavior, expectation, and motivation. Ethanol’s pharmacological actions and thus, effects on behavior, vary significantly depending on the dose (Table 43.1). Therefore, using rodent models, ethanol’s effects on extracellular striatal dopamine have been studied under various doses of ethanol. Low to moderate doses of acute, systemic ethanol (0.25 2.5 g/kg i.p.; 0.5 2.0 g/kg i. v.) stimulate VTA dopamine neuron firing (Brodie, Pesold, & Appel, 1999), resulting in a transient, but robust increase in extracellular dopamine concentrations in the NAc (Fig. 43.3) (Howard, Schier, Wetzel, Duvauchelle, & Gonzales, 2008; Imperato & Di Chiara, 1986; Tang, George, Randall, & Gonzales, 2003; Yan, 1999; Yim & Gonzales, 2000; Yoshimoto,

Ethanol Dopamine

40

25 20

30

15

20

10

10

5

0

0

0

30

60 90 Time (min)

Tissue ethanol (mM)

ETHANOL’S ACUTE PHARMACOLOGICAL EFFECTS ON EXTRACELLULAR STRIATAL DOPAMINE

50

Dopamine (% over baseline)

dopamine activity (see Key facts of phasic vs. tonic dopamine signals). However, microdialysis is the preferred method for measuring extracellular tonic dopamine concentrations because the temporal resolution is lower.

120

FIGURE 43.3 Dopamine response in the nucleus accumbens of Long Evans rats following acute ethanol administration (1 g/kg). Microdialysis studies indicate that acute ethanol (empty boxes) administration stimulates a robust dopamine (filled boxes) response in the NAc. However, the dopamine response returns to baseline while tissue concentrations of ethanol remain elevated. Here, the intraperitoneal injection of ethanol occurred at time 5 0 min. Source: From Vena, A.A., & Gonzales, R.A. (2014). Temporal profiles dissociate regional extracellular ethanol versus dopamine concentrations. ACS Chemical Neuroscience, 6(1), 37 47. https://doi.org/10.1021/cn500278b.

McBride, Lumeng, & Li, 1992). However, high doses of ethanol (5.0 g/kg and higher) acutely decrease extracellular dopamine concentrations (Imperato & Di Chiara, 1986). Consistent with these findings, in vitro voltammetry studies conducted in rodent brain slices demonstrate that high concentrations (150 200 mM) of ethanol reduce electrically evoked dopamine release in the NAc (Budygin, Mathews, Lapa, & Jones, 2005; Budygin, Phillips, Wightman, & Jones, 2001). In vivo microdialysis studies in rats have also demonstrated a greater dopamine response in the NAc relative to the dorsal striatum following acute systemic ethanol administration (Imperato & Di Chiara, 1986;

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EFFECTS OF ALCOHOL SELF-ADMINISTRATION ON EXTRACELLULAR STRIATAL DOPAMINE

421

FIGURE 43.4 Extracellular dopamine (normalized to baseline) activity in the dorsomedial striatum (left) and the dorsolateral striatum (right) following cumulative infusions of ethanol (filled circles) or saline (empty circles). The arrows represent the four administrations of intravenous ethanol (producing cumulative doses of 0.5, 1.0, 1.75, and 2.5 g/kg, respectively) or saline to naı¨ve, freely behaving Long Evans rats. The asterisks indicate a significant change from baseline; the carets indicate significance between saline versus ethanol. Source: From Vena, A.A., & Gonzales, R.A. (2014). Temporal profiles dissociate regional extracellular ethanol versus dopamine concentrations. ACS Chemical Neuroscience, 6(1), 37 47. https://doi.org/10.1021/cn500278b.

Melendez, Rodd-Henricks, McBride, & Murphy, 2003; Vena, Mangieri, & Gonzales, 2016). Furthermore, systemic administration of acute ethanol produces differential effects on tonic dopamine activity within the dorsomedial and dorsolateral striatal subregions. For example, moderate-to-high doses of ethanol (1.75 2.5 g/kg) produce a gradual, but significant increase in dopaminergic tone in the dorsomedial striatum, but have no effects on extracellular dopamine in the dorsolateral striatum (Fig. 43.4) (Vena et al., 2016). One interpretation of the differential effects of acute ethanol on extracellular dopamine across these striatal subregions is that midbrain dopamine neurons differ in their sensitivity to ethanol-induced stimulation. Indeed, nigrostriatal dopamine neurons show a reduced sensitivity to ethanol relative to mesolimbic dopamine neurons (Mereu, Fadda, & Gessa, 1984). Even within these dopaminergic pathways, individual neurons may vary in their sensitivity to ethanol. For example, in an in vivo FSCV study, only a subset of dopamine neurons terminating in the NAc were responsive to acute intravenous ethanol (Robinson, Howard, McConnell, Gonzales, & Wightman, 2009). Consistent with this observation, another study demonstrated that among dopamine neurons originating in the VTA, only those in the medial subregion were responsive to ethanol (Mrejeru, Martı´-Prats, Avegno, Harrison, & Sulzer, 2015). Differential sensitivities to the stimulating effects of acute ethanol may be due to the anatomical, physiological, and pharmacological heterogeneity of midbrain dopamine neurons (Lammel, Lim, & Malenka, 2014; Vena & Gonzales, 2014; Westerink, Kwint, & deVries, 1996), which continues to be a focus of current research.

EFFECTS OF ALCOHOL SELFADMINISTRATION ON EXTRACELLULAR STRIATAL DOPAMINE The pharmacokinetic properties (absorption, distribution, metabolism, and excretion) of ethanol vary depending on the route of administration, and this must be considered in the interpretation of alcohol’s effects on extracellular dopamine. While acute intravenous administration in animal models enables assessment of ethanol’s direct pharmacological actions, oral ethanol administration provides greater face validity as a model of human alcohol use. Additionally, operant self-administration studies, in which access to the ethanol solution is contingent upon completion of a response, are models for investigating the motivational and reinforcing properties of ethanol. It has been consistently demonstrated that animals (and humans) will exert effort to obtain alcohol. Monitoring extracellular dopamine via microdialysis during oral ethanol self-administration permits the study of the relationship between neurochemical activity and the seeking and consumption of ethanol (Gonzales et al., 2004). Animals typically undergo a period of training and, thus, are usually ethanolexperienced prior to the microdialysis session. Under a continuous reinforcement schedule, in which a conditioned response is required for each brief access to a drinking solution, the pattern of extracellular dopamine activity in the NAc differs if the drinking solution contains ethanol or only a natural reinforcer (such as sucrose or saccharin) (Gonzales et al., 2004). During ethanol self-administration under this model, extracellular accumbal dopamine significantly increases for the duration of the operant session. In contrast, when

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the drinking solution contains only sucrose or saccharin, the dopamine response is insignificant or occurs only briefly at the start of the self-administration period (Bassareo, Cucca, Frau, & Di Chiara, 2017; Gonzales & Weiss, 1998; Weiss, Lorang, Bloom, & Koob, 1993). On the basis of these findings, ethanol intoxication and/or ethanol-seeking behaviors appear to specifically alter extracellular accumbal dopamine relative to other caloric natural reinforcers. One caveat of the continuous reinforcement schedule is the inability to isolate the neurochemical effects of reward anticipation from the oral ingestion of ethanol. Reward predicting stimuli and seeking behavior can stimulate NAc dopamine activity. Therefore, it is unclear whether the dopamine stimulation observed during ethanol self-administration under a continuous reinforcement schedule is attributable to ethanol’s specific pharmacological properties because both seeking and consumption behaviors occurred during microdialysis sampling (Gonzales et al., 2004). The development of an appetitive-consummatory model, in which a wait period precedes a period of free access to the drinking solution, facilitated the discovery that extracellular dopamine concentrations are only transiently stimulated at the beginning of the consumption period, when brain concentrations of ethanol are very low (Carrillo & Gonzales, 2011; Doyon et al., 2003; Gonzales et al., 2004). Moreover, this effect was specific to the ethanol-experienced animals as those that received water or sucrose in the operant chambers did not display a significant dopamine response (Carrillo & Gonzales, 2011; Doyon et al., 2003). Interestingly, the dopamine response to the oral consumption of ethanol declines to baseline as brain ethanol concentrations increase. This dissociation in the temporal profiles of dialysate ethanol and dopamine indicates that the dopamine response may not be a direct pharmacological action of ethanol, but instead may be a response to the sensory cues associated with ethanol (Gonzales et al., 2004). While this hypothesis continues to be investigated, it is consistent with the proposed role of accumbal dopamine as a reward prediction signal. The abundance of microdialysis data strongly implicates tonic dopamine signaling, particularly within the NAc, in ethanol self-administration. The potential role of striatal phasic dopamine activity during ethanol self-administration has received considerably less attention. A study using an optogenetic approach demonstrated that selective tonic activation, but not phasic activation, of VTA dopamine neurons reduced ethanol consumption in animals that received prior operant ethanol self-administration training (Bass et al., 2013). Extracellular phasic dopamine signals in the NAc may occur in response to conditioned stimuli indicating reward availability (Shnitko & Robinson, 2015) to

facilitate the initiation of approach or seeking behavior. In contrast, tonic dopamine activity in the NAc may be involved in conveying the motivational properties of ethanol. Further research is necessary to delineate the functional roles of tonic and phasic dopamine signaling in striatal subregions, particularly within the dorsal striatum, during oral ethanol self-administration.

CLINICAL STUDIES OF ALCOHOL’S EFFECTS ON EXTRACELLULAR STRIATAL DOPAMINE Positron emission tomography (PET) imaging studies in humans (Fig. 43.5) have generally supported the findings from the microdialysis and FSCV studies. While studies using oral alcohol administration in healthy human social drinkers have reported inconsistent

FIGURE 43.5 Imaging the striatal dopamine response to oral alcohol consumption in humans using PET. The binding potential (scale at the bottom of the figure) of a radioactive tracer indicates the availability of dopamine receptors. When extracellular concentrations of dopamine are low, the binding potential of the radioactive tracer is high (indicated by orange/red on the scans), and vice versa. Following the consumption of alcohol (right panel images), there is significantly less binding of the radioactive tracer in the nucleus accumbens relative to consumption of juice alone (placebo; left panel images), indicating dopamine release. Reprinted by permission of Elsevier from Urban, N.B.L., Kegeles, L.S., Slifstein, M., Xu, X., Martinez, D., Sakr, E., . . . Abi-Dargham, A. (2010). Sex differences in striatal dopamine release in young adults after oral alcohol challenge: A positron emission tomography imaging study with [11C]raclopride. Biological Psychiatry, 68 (8), 689 696. Copyright 2010 by the Society of Biological Psychiatry.

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SUMMARY POINTS

effects (Boileau et al., 2003; Salonen et al., 1997; Urban et al., 2010), this may due to small sample sizes, expectancy effects, and individual variability in ethanol metabolism and pharmacokinetics. To circumvent this issue, further studies have used intravenous ethanol administration to study the effects of acute alcohol on extracellular striatal dopamine. The use of intravenous administration enables greater control over blood alcohol concentrations (BAC) (Hendler, Ramchandani, Gilman, & Hommer, 2011). Similar to the microdialysis findings from rodent models, human social drinkers show a significant dopamine response in the NAc, but minimal (or no) response in the caudate or putamen, following acute intravenous alcohol administration (Aalto et al., 2015; Oberlin et al., 2015; Yoder et al., 2009). Human alcoholics also show a significant increase in extracellular accumbal dopamine, which may be larger in magnitude relative to social drinkers, following an intravenous alcohol challenge (Yoder et al., 2016). Gustatory alcohol cues have also been shown to stimulate extracellular accumbal dopamine, though this effect appears to be lateralized to right NAc. For example, in a PET imaging study conducted in male heavy drinkers (consuming . 14 drinks/week), when controlling for acute alcohol exposure, the taste of beer induced a significant dopamine response in the right NAc. In contrast, when controlling for gustatory and olfactory stimuli, acute intravenous alcohol produced a significant increase in extracellular dopamine in the left NAc (Oberlin et al., 2013, 2015). However, there were no significant effects of acute gustatory stimuli on extracellular dopamine in the caudate or putamen (Oberlin et al., 2013). While the implication of lateralized effects is not clear, these PET imaging studies support the role of NAc, but not dorsal striatal, dopamine in mediating the acute reinforcing effects of alcohol and alcohol-related sensory stimuli. In summary, alcohol’s direct pharmacological effects on extracellular striatal dopamine vary depending on the dose, route of administration, striatal subregion, and possibly previous alcohol experience. Oral self-administration studies in animals implicate accumbal dopamine in mediating the reinforcing properties of alcohol and in predicting the availability of alcohol. However, significantly more work is necessary to determine whether dorsal striatal dopamine is implicated in alcohol-seeking and consummatory behaviors. As researchers continue to study alcohol’s effects on extracellular striatal dopamine, an objective for future research is to determine the mechanisms by which alcohol alters dopaminergic signaling.

MINI-DICTIONARY OF TERMS Anterior cingulate cortex A region of the frontal cortex involved in motivation, emotional learning, social behavior, and regulating autonomic functions.

GABAergic Associated with gamma-aminobutyric acid (GABA) signaling. GABA is the primary inhibitory signaling molecule in the central nervous system. Incentive salience A cognitive process in which a stimulus induces a motivational drive to seek and obtain a reward. Optogenetics A neuroscience technique that combines genetics and optics to precisely manipulate neurons in living tissue. Orbitofrontal cortex A region of the prefrontal cortex that receives and responds to olfactory, gustatory, and visual information. Additionally, this region is involved in decision-making, impulse control, and emotion. Positron emission tomography (PET) A type of imaging technology that uses a radioactive tracer to produce images of metabolic activity within the body. In neuroscience, PET can also be used to monitor specific neurochemical activity and receptor expression by analyzing the receptor binding potential of a specific radioactive tracer.

KEY FACTS Phasic Versus Tonic Dopamine Signals • Two modes of dopamine signaling exist: phasic and tonic. • Phasic dopamine release occurs when dopamine neurons are activated by salient sensory stimuli, such as those predicting reward availability (i.e., the smell of alcohol in a bar). • The synaptic phasic dopamine signal is robust, but transient, occurring on a subsecond time scale, and sufficient to facilitate behavioral activation and reward-related learning (Grace, 1995; Grace, 2000; Willuhn et al., 2010). • Tonic dopamine release occurs under basal conditions as a result of the spontaneous pacemaker activity of midbrain dopamine neurons. • Tonic dopamine activity conveys the baseline responsivity of midbrain dopamine systems (Grace, 2000; Willuhn et al., 2010). • Extracellular dopaminergic “tone” has been shown to be altered by various drugs of abuse and motivational states, though changes in tonic dopamine concentrations occur on a slower time course and the behavioral implications of changes in tonic dopamine are unclear.

SUMMARY POINTS • Striatal dopamine plays a critical role in the expression of goal-directed behaviors and in mediating the reinforcing effects of various drugs of abuse, including alcohol. • Techniques such as microdialysis and fast-scan voltammetry, which enable monitoring molecules in the extracellular space of freely behaving animals, have permitted the study of ethanol’s effects on dopamine activity in striatal subregions.

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• Animal models have demonstrated that alcohol produces differential effects on extracellular dopamine in the striatum, depending on the route of administration, dose, and subregion. • The alcohol-induced dopamine response appears greatest within the nucleus accumbens, relative to the dorsolateral and dorsomedial subregions. • Clinical studies using positron emission tomography have generally supported the findings from animal models.

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C H A P T E R

44 Nicotinic Cholinergic Mechanisms in Alcohol Abuse and Dependence 1

Shafiqur Rahman1 and Richard L. Bell2 Department of Pharmaceutical Sciences, College of Pharmacy, South Dakota State University, Brookings, SD, United States 2Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States

LIST OF ABBREVIATIONS AUD nAChRs ACH DA VTA GABA

alcohol use disorders nicotinic acetylcholine receptors acetylcholine dopamine ventral tegmental area gamma aminobutyric acid

INTRODUCTION Alcohol dependence is a chronic, relapsing, neuropsychiatric disorder affecting tens of millions of people worldwide and represents a serious, global, public health problem (Dwyer-Lindgren et al., 2015; Harris & Koob, 2017; Koob & Volkow, 2016). According to the World Health Organization (2011), alcohol consumption is attributed to 3.3 million deaths, or 6% of all global deaths each year (World Health Organization (WHO), 2014). Also, alcohol misuse is considered the fifth leading risk factor for premature death and disability among people between the ages of 15 and 49 (World Health Organization (WHO), 2015). However, due to limited current treatment and prevention strategies to treat alcohol use disorders (AUD), often with high relapse rates, there is a need for novel approaches and a greater understanding of targets and biological mechanisms mediating these disorders (Rahman, Engleman, & Bell, 2016; Tarren & Bartlett, 2017; Volkow et al., 2017). The neurobiological role of nicotinic acetylcholine receptors (nAChRs) in addictive disorders, including alcohol dependence, has been

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00044-1

characterized using a number of preclinical or clinical models (Crunelle, Miller, Booji, & Van den Brink, 2010; Litten, Falk, Ryan, & Fertig, 2016; Rahman & Prendergast, 2012; Rahman et al., 2016). The current chapter focuses on published animal and human studies involving cholinergic nicotinic mechanisms and associated nAChRs implicated in AUD. Furthermore, this chapter highlights potential targets, mechanisms, and future directions for future treatment strategies targeting AUD. As part of the central cholinergic system, nAChRs belong to the superfamily of ligand-gated, membranebound, ion-channel-associated receptors and are composed of pentameric assemblies of five subunits forming a hydrophilic channel (pore) at the center of the receptor complex (Albuquerque, Pereira, Alkondon, & Rogers, 2009; Gotti et al., 2009; Le Novere, Corringer, & Changeux, 2002). More than 12 subunits of neuronal nAChRs have been identified and classified as α subunits (α2 α10) and β subunits. The particular subunit arrangements results in various combinations to form a multitude of pentameric nAChR subtypes which, in turn, have diverse functional and pharmacological properties (Gotti et al., 2009). Based on subunit compositions, brain nAChRs are classified into functional heteromeric pentamers such as α4β2 ( indicates the inclusion of other α or β subunits, such as α3, α5, or α6, and β3 or β4) and α-bungarotoxin-sensitive homomeric pentamers composed of five identical α7 or α10 subunits (Fasoli & Gotti, 2015; Gotti et al., 2009). With diverse subunit combinations, the nAChR subtypes are extensively distributed differentially across brain

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regions (Gotti et al., 2009). Therefore, nAChR subunit composition is crucial for the diverse biological and pharmacological properties observed with different agonists/partial agonists and antagonists (Fasoli & Gotti, 2015). High-affinity α4β2 and low-affinity α7 subtypes are the most abundant nAChRs in the brain (Gotti et al., 2009). Cellular and molecular studies and knock-out models reveal that the α4β2 subtypes form high-affinity binding sites centrally (Zoli, Pistillo, & Gotti, 2015). The nAChRs are predominantly located at presynaptic terminals to facilitate neurotransmitter release into the synaptic cleft by increasing the intracellular influx of Ca12 ions and subsequent depolarization. This influx of Ca11 ions through nAChR channels triggers a cascade of intracellular signaling events that eventually lead to a myriad of cell-specific changes underlying various neuronal processes (Dani, 2015; Zoli et al., 2015). Somato-dendritic or postsynaptic nAChRs modulate neuronal cell excitability and activity-dependent, long-term potentiation in association with other receptor ion channels leading to the induction of synaptic plasticity (Dani, 2015). Furthermore, various nAChR subtypes are extensively distributed on dopamine (DA) cell bodies in the ventral tegmental area (VTA) which regulate dopaminergic neuronal firing (Zoli et al., 2015). The nAChR subtypes located on the presynaptic terminals of projections neurons as well as DA cell bodies are critically involved in the neurotransmitter release and subsequent regulation of dopaminergic neuronal activation within the mesocorticolimbic reward neurocircuitry (Gotti et al., 2010; Livingstone & Wonnacott, 2010). Additional studies have demonstrated the presence of α7 nAChR subtypes in the axonal terminals projecting to the DA cell bodies of the VTA (Gotti et al., 2010). The presynaptic α7 nAChRs facilitates the release of glutamate in the vicinity of the DA cell bodies, thus, potentiating the activation of these dopaminergic neurons (Gotti et al., 2010; Livingstone & Wonnacott, 2010). The presynaptic nAChRs, mainly α4β2 subtypes, located on the gamma aminobutyric acid (GABA)ergic afferents provide inhibitory control over this dopaminergic neurocircuit, through the release of GABA (Livingstone & Wonnacott, 2010). The α6containing nAChRs comprise 25% 30% of the presynaptic nAChRs in rodents, and as much as 70% in nonhuman primates (Berry, Engle, McIntosh, & Drenan, 2015). In addition, α7-containing nAChRs are abundantly expressed in the brain and account for the majority of high-affinity binding (Zoli et al., 2015). Presynaptic α7 nAChRs regulate glutamate release in the hippocampus and the VTA (de Kloet, Mansvelder, & De Vries, 2015) as well as prefrontal cortex efferents to the nucleus accumbens. Thus, different physiological outcomes and neurobehavioral changes may be

associated with the broad distribution of nAChRs in the central nervous system (Corrigall, Coen, & Adamson, 1994; Rahman, Lopez-Hernandez, Corrigall, & Papke, 2008; Rahman, Zhang, & Corrigall, 2003; Rahman, Zhang, & Corrigall, 2004). In general, nAChR subtypes are diversely localized across brain regions and play important roles in regulating various neurobiological and behavioral effects.

Cholinergic Nicotinic Mechanisms in Alcohol Dependence Extensive research during the past decade suggests that the rewarding effects of alcohol are mediated, at least in part, by brain cholinergic nicotinic mechanisms. The role of diverse nAChR subtypes in the rewarding effects in alcohol dependence has been well studied in a variety of animal models (Bell, Eiler, Cook, & Rahman, 2009; Bito-Onon, Simms, Chatterjee, Holgate, & Bartlett, 2011; Blomqvist, Hernandez-Avila, Van Kirk, Rose, & Kranzler, 2002; Ericson, Blomqvist, Engel, & So¨derpalm, 1998; Leˆ, Corrigall, Harding, Juzytsch, & Li, 2000; Soderpalm, Ericson, Olausson, Blomqvist, & Engel, 2000; Sotomayor-Zarate et al., 2013) and in humans (Chi & de Wit, 2003; Reus et al., 2007; Young, Mahler, Chi, & de Wit, 2005) for a better understanding of their biological effects and the development of new treatment strategies. Specifically, systemic or local administration of mecamylamine, a noncompetitive nAChR antagonist reduces alcohol drinking in a number of animal models (Ericson et al., 1998; Leˆ et al., 2000; Soderpalm et al., 2000). Furthermore, nAChRs in the VTA regulate alcohol drinking and their associated neurochemical effects have been studied in a number of animal models (Ericson et al., 1998). Clinically, mecamylamine reduces or fails to reduce alcohol drinking in humans (Chi & de Wit, 2003; Young et al., 2005), suggesting a mixed efficacy for mecamylamine to treat AUD. However, the complex pharmacological mechanisms of this noncompetitive antagonist, mecamylamine, still remain unknown. Unexpectedly, the selective α4β2 antagonist, dihydro-β-erythroidine, failed to suppress alcohol consumption suggesting a role for α6β2 or other subtypes, but not the α4β2 subtypes, in alcohol reinforcement (Larsson & Engel, 2004). The effects of methyllycaconitine, an α7 nAChR antagonist, were also to be found ineffective in reducing alcohol intake of rodents (Kamens, Anderson, & Picciotto, 2010). The nAChR ligand varenicline, a partial agonist at α4β2 nAChR (approved medication for smoking cessation), was found to reduce ethanol drinking in animal models and humans (McKee et al., 2009; Steensland, Simms, Holgate, Richards, & Bartlett, 2007).

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CONCLUSIONS

The nAChR ligand varenicline was developed as a potent high-affinity partial agonist at α4β2 nAChRs (Reus et al., 2007); however, the ligand also targets other nAChR subtypes. Other nAChR-based compounds such as cytisine, a partial agonist at α4β2 , and lobeline, a nonselective antagonist, were found to reduce alcohol consumption and nicotine-induced alcohol drinking in a number of studies (Chatterjee, Steensland, Rollema, & Bartlett, 2011; Hendrickson, Zhao-Shea, & Tapper, 2009; Sajja & Rahman, 2011, 2012, 2013) as well as alcohol-induced increases in tissue DA levels (Sajja, Dwivedi, & Rahman, 2010) in mice. Furthermore, these ligands, cytisine and lobeline, at nAChRs were found to decrease alcohol selfadministration in high-alcohol-drinking rats (Bell et al., 2009), a genetic animal model of alcoholism (Bell et al., 2012, 2016, 2017), suggesting that lobeline and cytisine may serve as effective therapeutic candidates to treat individuals with a genetic predisposition to develop AUD. A relatively new nicotinic ligand, sazetidine-A which selectively desensitizes α4β2 nAChRs through partial agonistic activity was developed (Xiao et al., 2006) and was shown to reduce alcohol drinking in alcohol-preferring rats (Rezvani et al., 2010), another animal model of alcoholism (Bell et al., 2012, 2016, 2017). Thus, the desensitizing effects of sazetidine on α4β2 nAChR subtypes may have the potential to treat AUD by targeting a novel nAChR-mediated mechanism. From these animal studies one can conclude that the rewarding effects of alcohol are dependent on the activation of nAChRs which, in turn, activates the mesolimbic DA reward neurocircuit (Chatterjee et al., 2011; Rahman & Prendergast, 2012). These findings support the hypothesis that cholinergic activity and nAChRs, in particular, are critical targets mediating the reinforcing effects of alcohol (Rahman et al., 2016). Similarly, other nAChR ligands such as CP-601932 and PF-4575180, partial agonists at α3β4 nAChRs, were found to reduce alcohol consumption and preference in rats indicating the role of other nAChR subtypes in alcohol reward/reinforcement (Chatterjee et al., 2011). In view of this evidence, it is clear that nAChR partial agonism or antagonism (Table 44.1) modulates alcohol-drinking and self-administration, suggesting important roles for central nAChRs and cholinergic pathways in AUD; and that these are crucial targets for future therapeutic strategies to treat AUD.

that individuals who abuse nicotine/tobacco are more likely to abuse alcohol than the general population (Apollonio, Philipps, & Bero, 2016; Nocente et al., 2013). Preclinical work with the alcohol-preferring rat animal model of alcoholism has shown this association between nicotine and alcohol intake, such that nicotine exposure enhanced alcohol intake (Hauser et al., 2012a) as well as alcohol-seeking behavior (Hauser et al., 2012b, 2014), with mecamylamine attenuating the effect of nicotine in the latter study (Hauser et al., 2014). An earlier study also reported nicotinepotentiated alcohol-seeking behavior in outbred rats (Leˆ et al., 2003). Using outbred rats, another study reported that neramexane, a glutamate-NMDAR and nAChR antagonist, reduced alcohol relapse-like drinking (Vengeliene, Bachteler, Danysz, & Spanagel, 2005). Finally, a single nucleotide polymorphism in the nicotinic acetylcholine (ACH) gene-cluster CHRNA5 CHRNA3 CHRNB4 appears to confer a predisposition for polysubstance abuse, including alcohol and nicotine (Buhler et al., 2015). Like comorbid alcohol and nicotine addiction, emerging evidence suggests nicotinic mechanisms are involved in AUD with comorbid psychiatric disorders such as anxiety and depression (Rahman, 2015; Roni & Rahman, 2014, 2017). For example, the nAChR ligand lobeline reduces alcohol-withdrawal or abstinence-induced depression-like behavior in an animal model likely by targeting brain β2-containing nAChRs (Roni & Rahman, 2017). Similarly, this nAChR ligand reduces nicotine-withdrawal-induced depression-like behavior indicating common neural circuitry and mechanisms are involved in these comorbid disorders. Previous studies in animal models indicate that prolonged exposure and abstinence from alcohol causes long-lasting neuroadaptations that may underlie the development of depression-like behavior (Stevenson et al., 2009). For example, chronic alcohol consumption reduced the expression of brain-derived neurotrophic factor in the rat hippocampus, an effect associated with depression-like behavior (Hauser, Getachew, Taylor, & Tizabi, 2011). Thus, β2 -nAChR modulation and its associated mechanisms appear to be critical in reducing depression-like behavior in alcohol-dependent rodent models. However, the role of specific nAChR subtypes in comorbid AUD and psychiatric conditions requires further investigation.

Nicotinic Acetylcholine Mechanisms in Alcohol Dependence With Comorbid Addictive and/or Psychiatric Disorders

CONCLUSIONS

First and foremost, individuals with AUD are more likely to abuse nicotine/tobacco and vice versa, such

Animal and human studies have contributed a wealth of information elucidating the role of nAChRs and nicotinic ACH mechanisms in AUD. As outlined in Table 44.1, promising nicotinic receptor-based

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TABLE 44.1 Cholinergic Nicotinic nAChR-Based Medicinal Compounds and Their Mechanism of Action in Alcohol Dependence or Alcohol Use Disorders Medicinal agent

Pharmacologic type and associated brain target/mechanisms Partial agonist

Varenicline

α4β2anAChR Antagonist

Mecamylamine Cytisine

Nonselective nAChR Partial agonist α4β2anAChR

Lobeline

Antagonist/partial agonist Nonselective nAChR

Sazetidine-A

Partial agonist/desensitizer α4β2anAChR

CP-601932

Partial agonist α3β4anAChR

PF-4575180

Partial agonist α3β4anAChR

Indicates the inclusion of other α or β subunits, such as α3, α5, or α6, and β3 or β4.

a

treatments are either partial agonist or antagonists at α4β2 /α3β4 nAChRs. Thus, brain cholinergic nicotinic mechanisms and nAChRs represent unique therapeutic targets for the treatment of alcohol dependence. Despite this modest success, there are several issues that need further investigation. For example, additional research is needed to identify specific compounds and associated neurobiological mechanisms targeting subtype-specific nAChRs other than α4β2 / α3β4 nAChRs. Such research will provide better therapeutic design and/or drug development strategies for treating AUD. Further exploration of genetic variants associated with AUD, especially in the context of comorbid conditions, is another strategy to identify nAChR-based pharmacogenetic treatments. Finally, the co-abuse of alcohol and nicotine with regard to withdrawal and relapse, along with comorbid psychiatric conditions such as depression, need considerably more research at both the clinical (imaging) and preclinical (animal models) levels. Taken together, answers to these open questions will provide critical information to develop new nicotine ACH-based therapeutics to treat AUD.

MINI-DICTIONARY OF TERMS Alcohol dependence A chronic and often progressive disease that includes a strong need to drink despite repeated problems.

Alcohol use disorders Chronic relapsing conditions characterized by compulsive alcohol use, loss of control over alcohol intake, and a negative emotional state when not using. Relapse Return to alcohol consumption after a period of abstinence. Comorbidity The simultaneous presence of two chronic diseases or conditions in a patient, that is, alcohol dependence with nicotine addiction. Brain nicotinic acetylcholine receptors Receptor proteins found in the brain, including brain reward systems. They respond to the brain neurotransmitter acetylcholine, receptor agonists, and drugs, including alcohol or nicotine. Nicotinic cholinergic mechanisms Biological mechanisms in the brain involving nicotinic acetylcholine receptors.

KEY FACTS • Alcohol dependence is a chronic brain disorder. • The brain nicotinic acetylcholine receptors (nAChRs) are proteins which respond to alcohol or nicotine. The cholinergic nicotinic mechanisms involving nAChRs play important regulatory roles in alcohol dependence. • Preclinical research has established that medicinal compounds decrease alcohol dependence by targeting brain nAChRs. • Clinical studies have shown that several medicinal agents involving brain nAChRs associated with nicotinic cholinergic mechanisms produce therapeutic benefits for the treatment of alcohol dependence.

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• Additional drug candidates that target brain nAChRs and cholinergic mechanisms in reducing alcohol dependence are highlighted.

SUMMARY POINTS • Alcohol dependence is a chronic, relapsing disorder. The underlying neurobiological mechanisms are still not well understood. • Evidence from animal and human studies suggest that brain nAChRs and cholinergic nicotinic mechanisms play important roles in alcohol use disorders (AUD), including alcohol dependence. • This chapter highlights the findings from animal models involving nAChR ligands in regulating alcohol dependence and associated biological mechanisms. • A number of medicinal agents, in the form of partial agonists or antagonists of brain nAChRs, have shown therapeutic potential in reducing AUD. • Emerging therapeutic drug candidates that target brain nAChRs and cholinergic mechanisms for alcohol dependence are discussed.

CONFLICT OF INTEREST The authors declare no conflicts of interest related to this manuscript.

Acknowledgments The authors wish to acknowledge grant support from The American Foundation for Pharmaceutical Education and South Dakota State University Research Foundation.

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Volkow, N. D., Wiers, C. E., Shokri-Kojori, E., Tomasi, D., Wang, G. J., & Baler, R. (2017). Neurochemical and metabolic effects of acute and chronic alcohol in the human brain: Studies with positron emission tomography. Neuropharmacology, 122, 175 188. World Health Organization. Department of Mental Health and Substance Abuse, Global Status Report on Alcohol. (2011). The Global status report on alcohol and health. Geneva: World Health Organization, Department of Mental Health and Substance Abuse. World Health Organization (WHO). (2014). Global status report on alcohol and health. p. XIV. ed. Available from ,http://www. who.int/substance_abuse/publications/global_alcohol_report/ msb_gsr_2014_1.pdf?..

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World Health Organization (WHO). (2015). Alcohol. Available from ,http://www.who.int/mediacentre/factsheets/fs349/en/#.. Xiao, Y., Fan, H., Musachio, J. L., Wei, Z. L., Chellappan, S. K., Kozikowski, A. P., et al. (2006). Sazetidine-A, a novel ligand that desensitizes nicotinic acetylcholine receptors without activating them. Molecular Pharmacology, 70, 1454 1460. Young, E. M., Mahler, S., Chi, H., & de Wit, H. (2005). Mecamylamine and ethanol preference in healthy volunteers. Alcoholism, Clinical and Experimental Research, 29, 58 65. Zoli, M., Pistillo, F., & Gotti, C. (2015). Diversity of native nicotinic receptor subtypes in mammalian brain. Neuropharmacology, 96, 302 311.

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C H A P T E R

45 Opioid System and Alcohol Consumption Jorge Jua´rez and Luz M. Molina-Martı´nez Laboratory of Pharmacology and Behavior, Instituto de Neurociencias, CUCBA, Universidad de Guadalajara, Jalisco, Me´xico

LIST OF ABBREVIATIONS Amy ArN DOR EV GABA Hip MLCS MOR MSN NAc PFC VP VTA WT

such that changes in one affect the other, though genetic factors and acute versus chronic intake may be involved. One point of controversy is whether the opioid system plays a prevalent role in the appetitive or consummatory phases of the motivation to consume alcohol, though some of the experimental evidence available suggests that opioids, particularly β-endorphins, may affect both. Clinical and experimental strategies have been used to study the role of the opioid system in the acquisition and maintenance of alcohol use and abuse. Together, they provide important information that has improved our understanding of this phenomenon.

amygdala arcuate nucleus delta opioid receptor estradiol valerate gamma-aminobutyric acid hippocampus mesolimbic-cortical system Mu opioid receptor medium spiny neurons nucleus accumbens prefrontal cortex ventral pallidum ventral tegmental area wild type

The Role of Endogenous Opioids and Their Receptors in Brain Reward Processes

INTRODUCTION Alcohol has no addictive properties per se; its effects on different brain structures and neurotransmission systems may produce a broad range of sensations—from rewarding effects to aversion—depending on the peripheral and central physiological state of an organism. Alcohol acts in practically all tissue milieu; however, the rewarding effects depend on its action on specific targets in the brain. The mesolimbic-cortical system (MLCS) plays an important role in the rewarding effects of primary incentives, drugs and other stimuli, which have a positive valence for an individual. Several neurotransmission systems acting in the MLCS are known to be involved in the rewarding effects of alcohol, including the dopamine and opioid systems. There is evidence that these systems act conjointly, in some cases in cause
effect relations, and in others independently. Also, there is a reciprocal interaction between the opioid system and alcohol consumption,

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00045-3

The rewarding effects of alcohol are mediated by different neurotransmitters and brain structures associated with the MLCS, especially the ventral tegmental area (VTA), nucleus accumbens (NAc), and amygdala (Amy). It is well known that alcohol promotes dopamine secretion from dopaminergic neurons and, indirectly, through other neurotransmitters, such as gamma-aminobutyric acid (GABA), glutamate, and endogenous opioids. However, there is a widely held view that the opioid system plays a key role in the rewarding and reinforcing effects of alcohol (for a review, see Herz, 1997). Ethanol primarily induces the release of β-endorphins from the hypothalamic arcuate nucleus (ArN), which sends projections to GABAergic interneurons that tonically modulate dopaminergic neurons in the VTA. We also know that mu opioid receptors (MOR) are located on these GABA neurons; therefore, endorphins may, in turn, interact with these

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receptors to produce disinhibition of the dopaminergic neurons by inhibiting GABAergic terminals. This mechanism increases dopamine release to the NAc, Amy, and prefrontal cortex (PFC), and so contributes to the acquisition of reward and the positive, reinforcing effects of alcohol (Fig. 45.1). In addition, it has been shown that alcohol promotes enkephalin secretion in the VTA, which contributes to GABAergic inhibition through delta opioid receptor (DOR) activation (for a review, see Gianoulakis, 2009). It has been suggested that dopamine release induced by MOR activation is a delayed phase that maintains dopamine levels in the NAc since a MOR-independent mechanism is involved in the initial release of dopamine into the NAc. Apparently, this alcohol-induced dopamine release involves serotonin, nicotinic, and glycine receptors (Valenta et al., 2013). Because alcohol consumption is not blocked by lesions on dopaminergic neurons, it has also been posited that the reinforcing effects of alcohol are mediated by an independent mechanism (Rassnick, Stinus, & Koob, 1993; Shoemaker, Vavrousek-Jakuba, Arons, & Kwok, 2002). Accordingly, it is suggested that alcoholinduced endorphin release from the ArN acts directly on the NAc and participates in the acquisition and maintenance of alcohol consumption through a dopamine-independent, opioid mechanism (Marinelli, Quirion, & Gianoulakis, 2003a) (Fig. 45.1). There is also evidence of immunoreactivity by enkephalins, dynorphins, and β-endorphins in the NAc and

expression sites of MOR, DOR, and kappa opioid receptors. Principally in the shell region of this nucleus, MORs are located in the dendrites of GABAergic and medium spiny neurons (MSN), whereas DORs are found mainly in presynaptic axon terminals that project into the ventral pallidum (VP) (Svingos, Clarke, & Pickel, 1998). The NAc consists primarily of MSN (90%) that contain GABA, and peptides as dynorphins and enkephalins (Meredith, 1999), which is related to reward and drug self-administration. It has been suggested that inhibition of GABAergic MSN efferents in the NAc through presynaptic MOR activation disinhibits downstream brain regions, such as the VP. This activated VP region seems to be an additional mechanism involved in the rewarding effects of alcohol and the regulation of voluntary ethanol intake (Carlezon & Thomas, 2009; Kemppainen, Raivio, Suo-Yrjo, & Kiianmaa, 2012). Recent studies have discerned two subpopulations of dynorphinergic neurons in the NAc that simultaneously regulate opposite functions. In the ventral shell, dynorphinergic neurons are related to aversive behaviors and more closely related to negative affective states. In contrast, the dorsal shell region is related to conditioned place preference and positive reinforcement (Al-Hasani et al., 2015). Therefore, it is important to understand how opioids drive the balance of positive or negative affective states in the NAc, and how they contribute to the reward that alcohol provides.

FIGURE 45.1 Neural mechanisms of the opioid system activation induced by alcohol and its effects on behavior (unpublished).

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DEFICIENCY OF β-ENDORPHINS AND ALCOHOL CONSUMPTION

Effects of Acute and Chronic Alcohol Intake on Opioid Peptides and Receptors Acute alcohol consumption induces the release of endogenous opioids (β-endorphins, enkephalins and dynorphins) in rat brain regions related to the MLCS, including the NAc (Marinelli et al., 2003a), Amy (Lam, Marinelli, Bai, & Gianoulakis, 2008), and VTA (Jarjour, Bai, & Gianoulakis, 2009). The long-term effects of alcohol consumption are generally related to adaptive changes in the content and release of endogenous opioids; thus, they may differ from the acute effects that have been observed. Most studies have focused on differences in β-endorphin release because this peptide is considered the most important endogenous opioid that modulates the reward aspect of alcohol consumption. In both wild type (WT) and alcohol-preferring rats, endorphin release induced by acute alcohol exposure initially increases in just a few minutes, but declines over time (Lam, Nurmi, Rouvinen, Kiianmaa, & Gianoulakis, 2010). In contrast, it has been suggested that chronic alcohol intake decreases β-endorphin activity, which may regulate consumption through negative reinforcement (Gianoulakis, 2009). In addition, in WT rats, chronic consumption produces a decrease in enkephalins, accompanied by an increase in dynorphin levels in some brain reward regions (Lindholm, Ploj, Franck, & Nylander, 2000). These long-term changes in both enkephalins and dynorphins have been related to negative reinforcement and symptoms of alcohol withdrawal. Research with WT rats has shown that acute ethanol consumption decreases the binding affinity of DAMGO (a MOR selective agonist) in the first minutes in the NAc and VTA. Also, the binding affinity of DAMGO and DPDPE (a DOR agonist) increases in the PFC and NAc after 2 hours of alcohol consumption (Mendez, 2013). These findings suggest that acute alcohol intake induces MOR down-regulation that could occur due to endocytosis; while, up-regulation of these receptors occurs at 2 hours, probably due to a rapid recycling of these receptors to the cell membrane. Repeated exposure to alcohol also promotes adaptive changes in opioid receptor density. Experiments with WT rats have shown that chronic alcohol consumption increases DOR density in the hippocampus (Hip), but decreases MOR in regions such as the PFC, Hip, striatum, and NAc (Saland, Hastings, Abeyta, & Chavez, 2005). These authors suggest that these changes in receptors may be adaptations produced during desensitization, internalization, and recycling and, so, could be factors in ongoing ethanol consumption and tolerance. Most studies on receptor density have been performed in rats genetically selected on the basis of their

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preference for alcohol. Thus, observations have shown that MOR densities in regions related to the MLCS are higher in alcohol-preferring rat strains than in nonalcohol preferring animals (McBride, Chernet, McKinzie, Lumeng, & Li, 1998). These intrinsic differences in MOR may explain, in part, differences in alcohol consumption among distinct genetic lines. These findings suggest that chronic alcohol exposure produces adaptive changes that may be related to high levels of consumption and, alternatively, that genetic variability plays a role in the predisposition to high alcohol intake. Considering that MOR and DOR play significant roles in the rewarding effects of alcohol, several studies have addressed the mechanisms that affect their regulation under conditions of chronic alcohol exposure. This research has reported a decrease in the coupling of G-proteins to opioid receptors in the striatum, NAc, lateral septum, and Hip in WT rats (Saland et al., 2004), as well as in alcohol-preferring rats chronically exposed to alcohol (Chen & Lawrence, 2000). Because G-proteins are the structural requirement for the activation of opioid receptors, the uncoupling of these proteins from MOR and DOR in the presence of alcohol decreases intracellular signaling. It has been shown that G-protein coupling to opioid receptors does not depend on alcohol preference, leading to the suggestion that chronic alcohol exposure modifies some aspect of receptor phosphorylation or internalization (Saland et al., 2004). In this regard, studies have demonstrated that chronic alcohol consumption inhibits MOR internalization in the spinal cord and produces opioid antinociceptive tolerance in rats. This change in alcohol-induced MOR was associated with an uncoupling of G-proteins and increased receptor density, further accompanied by a significant decrease in the Gprotein-coupled receptor kinase that is responsible for opioid receptor phosphorylation and internalization (He & Whistler, 2011). These authors suggested that chronic alcohol consumption decreases the receptor’s internalization capacity, perhaps related to analgesic tolerance, and may have important therapeutic implications for alcoholic subjects undergoing naltrexone treatment. Such adaptive changes in receptor densities and intracellular signaling may depend on intrinsic genetic characteristics, or result from exposure to alcohol. Thus, these changes could have consequences for alcohol consumption and the treatment of alcoholism.

DEFICIENCY OF β-ENDORPHINS AND ALCOHOL CONSUMPTION Early studies identified that alcoholic patients show lower concentrations of β-endorphin in the cerebrospinal fluid than nonalcoholic controls (Genazzani et al.,

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1982). This suggests that β-endorphin deficiency is intimately related to alcohol abuse. It is well known that alcohol consumption releases β-endorphins from the ArN; therefore, the alcohol-seeking characteristic of alcoholics could be due to a compensatory strategy that attempts to increase this β-endorphin deficiency. In this regard, men with a family history of alcoholism (high-risk) also show lower plasma β-endorphin concentrations than those who have a negative history of alcoholism (low-risk) (Gianoulakis, Dai, Thavundayil, & Brown, 2005). This constitutes evidence that the genetic factor could increase vulnerability to alcohol abuse. Dai, Thavundayil, and Gianoulakis (2005) found that low-risk, nonalcoholic subjects had higher basal plasma concentrations of β-endorphin than low-risk alcoholics, high-risk nonalcoholics and high-risk alcoholics, so that alcohol dependence, per se, may also decrease β-endorphins, even in men with negative family histories of alcoholism. In addition, Gianoulakis (1996) found that alcohol intake increased β-endorphins in a dose-dependent manner only in the high-risk group whose β-endorphin levels exceeded those of lowrisk subjects when the highest dose of alcohol (0.75 g) was tested. These findings support an enhanced sensitivity of pituitary β-endorphins to alcohol in high-risk subjects (Table 45.1). Different paradigms have been used to explore the role of β-endorphinergic neurons and β-endorphin deficiency in relation to alcohol consumption in animal models. One pharmacological strategy consists in administering compounds that produce neurotoxicity in these neurons. Studies have described that a single dose of estradiol valerate (EV; 2 mg/rat) in female rats maintain the release of estradiol for 2
3 weeks. Initially, this long-term exposure to estrogen promotes TABLE 45.1

the establishment of polycystic ovaries, followed later by neurotoxicity in β-endorphin-producing neurons in the ArN (Brawer, Beaudet, Desjardins, & Schipper, 1993). Desjardins, Brawer, and Beaudet (1993) found a decrease of approximately 60% in β-endorphinergic neurons in the ArN 8 weeks after an EV injection. Moreover, β-endorphin content decreased, but two peptides from the ArN—met-encephalin and neuropeptide Y—remained unchanged. Similarly, monosodium glutamate and gold thioglucose have been used as neurotoxins. Both of these compounds cause a loss of approximately 80%
90% of neurons in the ArN, but gold thioglucose also produces neuronal loss in neighboring regions, such as the ventromedial hypothalamus (Sanchis-Segura & Aragon, 2002). Therefore, EV treatment is a useful model for studying deficits in the β-endorphinergic system in relation to alcohol consumption. A single dose of EV produces an increase in alcohol consumption several weeks after injection (Marinelli, Quirion, & Gianoulakis, 2003b). In this regard, Reid et al. (2002) studied high alcohol intake before and after EV administration. They concluded that this does not induce higher alcohol consumption directly but, rather, that the adaptive changes resulting from the EV treatment are what produce an increase in alcohol intake. These enduring changes and increases in the consumption of alcoholic beverages have been observed after 1 month and for up to 3 months (Reid, Hubbell, & Reid, 2003). Apparently, a decrease in the number of β-endorphin-producing neurons does not necessarily coincide with reduced β-endorphin concentrations. Marinelli et al. (2003b), for example, found that alcohol consumption in female Wistar rats increased 9 weeks after EV administration; however, the neuronal deficit was

β-End and MOR Density Changes in Heritable High-Risk and Low-Risk Organisms (Unpublished)

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OPIOID ANTAGONISTS AND ALCOHOL CONSUMPTION

related to an increase in β-endorphin levels, at least in the post-EV treatment period, although the possibility that some adaptive mechanisms participate in the activity of β-endorphins cannot be ruled out. In this vein, Jua´rez, Camargo, and Gomez-Pinedo (2006) observed an increase in voluntary alcohol consumption between the fourth and fifth weeks after EV administration, in a finding that coincided with the onset of neurotoxicity. This exacerbated alcohol consumption decreased over time, and remained above baseline values after 9
10 weeks. Despite the decrease in β-endorphinergic neurons, no changes in β-endorphins were observed in that study, suggesting a compensatory effect in the β-endorphin system, such as adaptive changes in opioid receptors. In this regard, it is well known that estrogens induce MOR internalization, which reduces its availability. Therefore, while alcohol induces β-endorphin release, the decrease in the availability of estrogen-induced MOR would diminish the rewarding effects of alcohol and, initially, decrease consumption. When plasma estrogen levels diminish, the opposite phenomenon occurs; that is, upregulation of MOR that promotes a greater availability to be activated by alcohol-induced β-endorphin release which, in turn, increases the rewarding effects of alcohol (Jua´rez, Va´zquez-Corte´s, & Barrios De Tomasi, 2005). Clearly, a deficit in the number of β-endorphin neurons produces an increase in alcohol consumption; however, a long-lasting effect has not been found consistently across studies. This suggests that a compensatory effect may occur in the synthesis and release of β-endorphins in the regulation of opioid receptors or in other neurotransmission mechanisms related to seeking alcohol.

OPIOID ANTAGONISTS AND ALCOHOL CONSUMPTION Given that the opioid system plays an important role in the rewarding effects of alcohol, several studies have examined the effects of opioid antagonists on alcohol consumption. In 1994, the US Food and Drug Administration (FDA) approved the use of naltrexone (an opioid antagonist) for the treatment of alcohol dependence based on results obtained in both preclinical and clinical studies. It is thought that naltrexone decreases alcohol consumption through the following mechanism: alcohol consumption increases β-endorphin concentrations; therefore, when naltrexone binds to the opioid receptor it lowers the rewarding effects of alcohol and so reduces intake and the craving for alcohol (Balldin et al., 2003; Helstrom et al., 2016; O’Malley, Krishnan-Sarin, Farren, Sinha, & Kreek, 2002). Due to

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this mechanism, it has been reported that naltrexone increases both the rate of abstinence and the risk of relapse (Guardia et al., 2002; Pekka et al., 2001). Nevertheless, some studies failed to find significant differences in alcohol consumption between subjects under naltrexone treatment and others who received a placebo (Chick et al., 2000; Lo´pez, Barr, Reid-Quin˜ones, & de Arellano, 2017). This discrepancy could be due to low adherence to naltrexone treatment and the high dropout rate associated with therapies of this kind; two common problems described in numerous studies (Chick et al., 2000; Monti, Rohsenow, & Swift, 2001; Pettinati, Volpicelli, Pierce, & O’Brien, 2000). Naltrexone’s effect on reducing alcohol consumption has also been described in animal studies (Bienkowski, Kostowski, & Koros, 1999; Gardell, Hubbell, & Reid, 1996), particularly when alcohol was measured in the short term; that is, only a few hours after administration. However, when animals were exposed (24 h/day) to a free choice between alcohol and water, naltrexone failed to decrease daily alcohol intake (Barrios De Tomasi & Jua´rez, 2014; Jua´rez & Barrios De Tomasi, 2008). This discrepancy could be related to the acute effects of the opioid antagonist, which depends on its half-life. It has been posited that naltrexone and alcohol should act simultaneously in order for animals to detect a reduction in the rewarding effects of the latter. However, Davidson and Amit (1997) found that when ethanol intake was paired with naltrexone no reduction in alcohol consumption occurred at the end of treatment with naltrexone. This result can be explained as follows: the opioid antagonist produces opioid receptor up-regulation after several days of treatment (Parkes & Sinclair, 2000) such that the greater availability of opioid receptors after naltrexone treatment can produce an increase in the rewarding effects of alcohol. In this regard, Jua´rez & Barrios De Tomasi (2007) observed an increase in voluntary alcohol consumption in rats after 7 days of naltrexone treatment. Concurring results were reported in a study with baboons, where naltrexone did not decrease alcohol consumption when treatment was initiated in an abstinence period and continued through a period with access to alcohol, though when treatment was initiated under conditions that allowed access to alcohol, naltrexone did reduce intake (Holtyn, Kaminski, & Weerts, 2017). In an effort to optimize pharmacological treatment, Bold et al. (2016) studied young adults with a pattern of heavy alcohol consumption. Their subjects were instructed to take a targeted dose of naltrexone as needed prior to drinking, together with a fixed daily dose of naltrexone. The authors found that naltrexone reduced the likelihood of intoxication compared to a

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placebo group; indicating that collaboration and commitment among patients undergoing treatment are crucial for achieving the objectives outlined. Several pharmacological strategies using other opioid antagonists and drugs have been used to treat alcoholism, but experience indicates that commitment and completing therapy programs complemented by cognitive
behavioral therapy play a vital role in successful treatment outcomes.

CONCLUSIONS There is no doubt about the important role that the opioid system plays in modulating the rewarding effects of alcohol, which occurs through two principle mechanisms: facilitating the release of dopamine from the VTA, and acting directly on the NAc through a dopamine-independent opioid mechanism. Chronic alcohol exposure produces adaptive changes in the opioid system; therefore, the acute effects of alcohol consumption can change with the passing of time. These adaptive changes, together with genetic variability in the opioid system, play an important role in the predisposition to exacerbated alcohol consumption. A family history of alcoholism is a highrisk condition associated with a central deficiency of β-endorphins; however, there is evidence that alcoholism itself can produce a deficit in β-endorphin concentrations. In addition, a broad variety of plastic changes in the opioid system have been associated with exacerbated alcohol consumption. Finally, treatment with opioid antagonists requires a specific regimen of medication, together with the individual’s firm commitment to comply with the therapeutic program. Therefore, complementing such treatments with cognitive
behavioral therapy to reduce or prevent excessive alcohol consumption is highly recommended.

MINI-DICTIONARY OF TERMS Binding Assay to quantify the joining of a ligand to its receptor, and provides information of the quantity of receptors expressed. Endocytosis Mechanism by which the cell membrane forms a vesicle to introduce a molecule or protein into cytoplasm. Internalization Process by which an activated receptor is desensitized and introduced from the membrane into the cell to be processed and sent to degradation or recycling. Down-regulation Decrease in the number of receptors expressed in the cell membrane. Up-regulation Increase in the number of receptors expressed in the cell membrane.

KEY FACTS • The opioid receptor activation by an agonist promotes the intracellular signaling through G-proteins. • As a result, it decreases the release of neurotransmitters and protein synthesis. • Once the receptor is activated, it is internalized so its density decreases in the membrane. • Antagonists such as naltrexone prevent the receptor activation. • A prolonged inactivation can also induce receptor up-regulation.

SUMMARY POINTS • The opioid system plays a key role in the rewarding effects of several incentives, such as food, sex, and drugs. • The main endogenous opioids, β-endorphins, enkephalins, and dynorphins are involved in rewarding and analgesia. • Ethanol induces the release of β-endorphins from the hypothalamic arcuate nucleus. • Central β-endorphin deficiency has been related to a predisposition to exacerbated alcohol consumption. • Opioid antagonists have been used to treat alcoholism with acceptable results.

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400.

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C H A P T E R

46 The Enkephalinergic System and Ethanol Effects 1

Milagros Me´ndez1, Karla Herna´ndez-Fonseca1 and Paula Abate2

Departamento de Neuroquı´mica, Subdireccio´n de Investigaciones Clı´nicas, Instituto Nacional de Psiquiatrı´a Ramo´n de la Fuente, Ciudad de Me´xico Me´xico 2Laboratorio de Psicologı´a Experimental, Centro de Investigaciones Psicolo´gicas (CIPsi-CONICET-UNC), Facultad de Psicologı´a, Universidad Nacional de Co´rdoba, Enfermera Gordillo esq. Enrique Barros, Ciudad Universitaria, Co´rdoba, Argentina

LIST OF ABBREVIATIONS amCP AUD DA DAergic [3H]-DAMGO [3H]-DPDPE δKO GDs ig ip Met-enk mpCP mRNA μKO NAcc PDs PET PFC Pro-enk RIA SN SNc SNr VTA

anterior-medial caudate-putamen alcohol use disorders dopamine dopaminergic [3H] [D-Ala2, MePhe4, Gly-ol5]-enkephalin [3H] (2-D-penicillamine, 5-D-penicillamine)-enkephalin delta receptor knockout gestational days intragastric intraperitoneal methionine-enkephalin medial-posterior caudate-putamen messenger ribonucleic acid Mu receptor knockout nucleus accumbens postnatal days prenatal ethanol treatment prefrontal cortex pro-enkephalin radioimmunoassay Substantia nigra Substantia nigra, pars compacta Substantia nigra, pars reticulata ventral tegmental area

INTRODUCTION Alcohol (ethanol) is a depressant substance of the central nervous system that exhibits dose-dependent biphasic effects on behavior. In animals and humans,

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00046-5

low doses produce psychomotor activation and euphoria, whereas high doses decrease locomotor activity and induce sedation (Lukas & Mendelson, 1988; Me´ndez & Herrera, 2012). The initial administration of low alcohol doses may progressively induce consumption of higher doses, leading to drug abuse and/or dependence. This cycle initiates with the activation of neural reinforcement and reward circuits, which may induce neuroadaptive changes that progressively lead to drug dependence (Nestler, Hyman, & Malenka, 2001). Alcohol exhibits positive and negative reinforcement properties that are crucial in drug-seeking behavior and dependence (Koob, Sanna, & Bloom, 1998; Wise & Bozarth, 1987). Ethanol-induced activation of DAergic transmission of the mesocorticolombic system (VTA, PFC, and NAcc) plays a key role in the mechanisms underlying ethanol reinforcement and reward (Wise & Bozarth, 1987). Ethanol increases the firing rate of DAergic neurons in the VTA and DA synthesis, release and metabolism in the NAcc and the PFC (Di Chiara & Imperato, 1985; Fadda, Mosca, Colombo, & Gessa, 1989; Gessa, Muntoni, Collu, Vargiu, & Mereu, 1985). The stimulatory effect of ethanol on DA release from the NAcc is considered a key event in the reinforcing actions of ethanol. On the other hand, brain sensitivity to ethanol has been suggested to be an indicator of the vulnerability to develop alcohol addiction since in humans a low response to ethanol has been associated to a greater

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probability to develop alcoholism (Schuckit, 1994). The DAergic activity of the nigrostriatal pathway seems to determine brain sensitivity to ethanol, which could be directly related to addictive processes (Yanai, Shaanani, & Pick, 1995).

ETHANOL AND OPIOID EFFECTS ON DOPAMINERGIC TRANSMISSION: ROLE IN REINFORCEMENT Besides DA, ethanol modifies activity of other neurotransmitter and neuromodulator systems, such as that of opioid peptides (Gianoulakis, 2009; Ulm, Volpicelli, & Volpicelli, 1995). Numerous studies indicate that the endogenous opioid system (enkephalins, endorphins, and dynorphins) regulate the DAergic activity of the mesocorticolimbic and nigrostriatal systems and modulate ethanol actions in these pathways (Herz, 1997; Ulm et al., 1995). Mu opioid receptor agonists increase the firing rate of DAergic neurons in the VTA (Gysling & Wang, 1983) and stimulate DA release and metabolism in the NAcc and PFC, whereas delta agonists do not have an effect (Spanagel, Herz, & Shippenberg, 1990; Wood & Rao, 1991). These findings indicate that activation of opioid receptors by endogenous opioids is critical in the regulation of DAergic mesocorticolimbic transmission, suggesting that the effects of opioids are similar to those exerted by ethanol. Ethanol and opioid peptides (as well as opiates) share numerous pharmacological properties and have similar effects on behavior in animals and humans. Low doses of ethanol and opioids stimulate motor activity through DAergic activation in the VTA, while high doses activate DAergic terminals in the NAcc (Joyce & Iversen, 1979; Kalivas, Widerla¨v, Stanley, Breese, & Prange, 1983). Activation of the DAergic mesocorticolimbic system by mu and delta agonists induces reinforcement, whereas kappa agonists produce dysphoria. These actions are mediated by an increase or decrease in DA release from the NAcc, respectively (Herz, 1997). Overall, these studies suggest that opiate and alcohol dependence may be mediated by a common neurobiological mechanism involving DAergic reward circuits (Wise & Bozarth, 1987). Alcohol reinforcement is partially mediated by the ethanol-induced activation of the endogenous opioid system (Froehlich, 1995; Gianoulakis, 2009; Herz, 1997; Ulm et al., 1995). This activation would increase the hedonic value and the reinforcing properties of alcohol which, in turn, may increase drug consumption. Eventually, this mechanism would be relevant in the establishment of an addictive behavior. The use of opioid receptor agonists and antagonists has contributed to understanding the role of opioid

peptides in ethanol reinforcement and high levels of alcohol-drinking behavior. The pharmacological manipulation of opioidergic transmission modifies alcohol reinforcement, preference, and consumption in animal models (Chotro & Arias, 2007; Me´ndez & Herrera, 2012; Pautassi, Nizhnikov, & Spear, 2009; Spear & Molina, 2005). Low doses of mu agonists increase alcohol consumption in rats (Wild & Reid, 1990), whereas high doses decrease intake (Volpicelli, Ulm, & Hopson, 1991). Mu and delta selective and nonselective (naloxone or naltrexone) antagonists, as well as kappa agonists, reduce alcohol consumption in different animal models (Higley & Kiefer, 2006; Hyytia¨ & Kiianmaa, 2001; Lindholm, Werme, Brene, & Franck, 2001; Stromberg, Casale, Volpicelli, Volpicelli, & O’Brien, 1998). In alcoholic patients, naltrexone reduces alcohol craving and relapse (Volpicelli, Alterman, Hayashida, & O’Brien, 1992). In addition, studies using mu (μKO) and delta (δKO) opioid receptor knockout mice show that alcohol self-administration and drug preference are reduced in μKO mice (Roberts et al., 2000), whereas δKO animals show a higher ethanol preference and consumption (Roberts et al., 2001). Overall, these studies indicate that activation of the β-endorphinergic and enkephalinergic systems via mu and delta receptors is relevant in ethanol reinforcement and in the maintenance of a high levels of alcohol-drinking behavior. Alcohol modifies opioidergic neurotransmission at different levels (Froehlich, 1995; Gianoulakis, 2009; Me´ndez & Morales-Mulia, 2008a, 2008b; Ulm et al., 1995). Ethanol increases the expression, content, and release of Met-enk and β-endorphins in brain areas of the reward circuits (Gianoulakis, 2009; Marinelli, Bai, Quirion, & Gianoulakis, 2005; Me´ndez & MoralesMulia, 2006; Me´ndez, Barbosa-Luna, Pe´rez-Luna, Cupo, & Oikawa, 2010; Olive, Koenig, Nannini, & Hodge, 2001). These changes could be associated with alcohol preference and consumption in animals (Gianoulakis, de Waele, & Thavundayil, 1996a). Moreover, a correlation has been made between the increase in β-endorphin levels and the risk of alcoholism in humans (Gianoulakis, Krishnan, & Thavundayil, 1996b). During the past few years, our group has investigated the acute and chronic effects of ethanol on neurotransmission of the enkephalinergic and β-endorphinergic systems. We have shown that ethanol selectively modifies precursor mRNA expression and peptide content, release and inactivation, as well as opioid binding to receptors (Leriche & Me´ndez, 2010; Me´ndez & Morales-Mulia, 2006; Me´ndez et al., 2010; Me´ndez, Leriche, & Calva, 2001; Me´ndez, Morales-Mulia, & Leriche, 2004).

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PRENATAL ETHANOL EFFECTS ON ENKEPHALINERGIC TRANSMISSION

ACUTE AND CHRONIC ETHANOL EFFECTS ON ENKEPHALINERGIC TRANSMISSION Ethanol differentially alters binding of selective opioid ligands to mu ([3H]-DAMGO) and delta ([3H]DPDPE) receptors in distinct brain regions of Wistar adult rats, with different kinetic patterns. Ethanol (2.5 g/kg) increases [3H]-DPDPE binding in the PFC, NAcc (core and shell), SNr, and CP (Me´ndez et al., 2004), as well as [3H]-DAMGO binding in the PFC (Me´ndez et al., 2001). The same treatment decreases [3H]-DAMGO binding in the VTA, the shell of the NAcc and the SNr. Ethanol does not affect [3H]DAMGO binding in the CP (Me´ndez et al., 2001; Me´ndez, Leriche, & Calva, 2003). These studies suggest that ethanol reinforcement may be partially mediated by up-regulation and down-regulation mechanisms of mu and delta receptors in the mesocorticolimbic and nigrostriatal pathways. Ethanol (2.5 g/kg) decreases the expression of Proenk mRNA in the VTA, the SNc, and SNr, but increases mRNA expression in the PFC of Wistar adult rats. This treatment induces a sustained augmentation of Pro-enk mRNA levels in the NAcc and CP (Me´ndez & Morales-Mulia, 2006; Me´ndez, Morales-Mulia, & Pe´rez-Luna, 2008). Additionally, high ethanol doses (2.5 g/kg) decrease Met-enk content in the NAcc and CP and a dose of 0.5 g/kg induces a reduction in the PFC. Furthermore, intermediate to high ethanol doses stimulate Met-enk release from the NAcc (Me´ndez et al., 2010). Overall, these studies indicate that the enkephalinergic system is an important ethanol target and Met-enk release is one of the essential events in these actions. Mesolimbic enkephalins may play a key role in ethanol reinforcement. Overall, these studies indicate that acute administration of ethanol induces selective alterations in the enkephalinergic system, particularly in the brain regions of reward circuits, although other areas are also affected by the drug. Likewise, chronic alcohol consumption (10%, 4 weeks) modifies enkephalinergic transmission in a specific manner. Ethanol selectively increases Met-enk content in the VTA and PFC. This treatment neither affects [3H]-DAMGO nor [3H]-DPDPE binding to mu and delta receptors in these areas (Barbosa-Luna, 2012; Leriche & Me´ndez, 2010). These studies suggest that some neuroadaptive alterations take place in mesocortical enkephalinergic neurons during long-term exposure to alcohol, which could be associated with drug reinforcement.

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PRENATAL ETHANOL EFFECTS ON ENKEPHALINERGIC TRANSMISSION The impact of ethanol exposure throughout different ontogenic stages provides information about the predisposition or facilitation to react towards the drug during development. Ethanol experiences during early ontogeny, even during prenatal periods, facilitate the posterior acceptance and consumption of the drug (Abate, Pueta, Spear, & Molina, 2008; Molina, Domı´nguez, Lo´pez, Pepino, & Faas, 1999). Ethanolseeking and intake are modulated by the appetitive and aversive properties of the drug in animal models (Pautassi et al., 2009). Preweanling rats have proven valuable models for assessing these behaviors. A pattern of high acceptance of ethanol early in ontogeny seems to be associated with the pharmacological effects of the drug, rather than with its orosensory properties (Abate et al., 2008; Pautassi et al., 2009; Spear & Molina, 2005). In addition, preweanling rats are sensitive to the locomotor activating effects of ethanol (Arias, Mlewski, Molina, & Spear, 2009), suggesting that infants are prone to process the stimulating effects of ethanol rather than its sedative consequences. Similar to adult rodents, ethanol reinforcement and acceptance in preweanling rats seem to be regulated by the opioid system. Co-administration of ethanol with nonselective opioid antagonists (naloxone) during gestation, disrupts the facilitative ethanol effect on alcohol intake during infancy (Chotro & Arias, 2007). Furthermore, opioid antagonist administration interferes with appetitive reinforcement towards the drug (Miranda-Morales, Spear, Nizhnikov, Molina, & Abate, 2012). In newborn and infant rats, mu and kappa opioid receptor systems modulate ethanolmediated appetitive reinforcement through the inhibition of positive behaviors (Nizhnikov, Varlinskaya, Petrov, & Spear, 2006). Alcohol intake and ethanol-induced motor activation can also be reduced by nonselective or selective (mu or delta) antagonists during the preweanling period (Arias, Molina, & Spear, 2010; Hallmark & Hunt, 2004). Overall, these results show that a functional opioid system is required to promote ethanol-related responses during postnatal development. Even when ethanol-induced molecular changes in opioid systems have been extensively studied in adults, knowledge about the impact of exposure to low or moderate ethanol doses during early ontogeny is scarce. Thus, we investigated the effect of ethanol exposure (2 g/kg, ig) during the last period of gestation (GDs 17 20) of Wistar rats on Met-enk expression

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in brain regions of infant (PD15) and adolescent (PD30) animals. Prenatal ethanol treatment (PET) rises ethanol consumption in PD15 offspring (intake test: 0%, 5%, or 10% ethanol) and induces a 57% increase in Met-enk content in the NAcc of pups that consume a 10% ethanol solution. In addition, PET decreases Met-enk content (45%) in the VTA, but increases peptide levels (68%) in the PFC of animals consuming water (see Fig. 46.1). PET also induces increments in Met-enk content in the mpCP of pups that consume a 5% ethanol solution (98%) or water (57%) (Fig. 46.2). Interestingly, Met-enk levels were significantly increased in the hypothalamus and hippocampus of pups in response to PET. Increments of 77%, 72%, and 80% (hypothalamus) and

85%, 73%, and 84% (hippocampus) were observed in pups that consume water, 5%- or 10% ethanol, respectively (see Fig. 46.3). PET does not affect peptide levels in the SN, the amCP, and the amygdala (see Figs. 46.2 and 46.3) (Abate, Herna´ndez-Fonseca, Reyes-Guzma´n, Barbosa-Luna, & Me´ndez, 2014). These studies indicate that PET promotes ethanol consumption in infant rats and induces changes in Met-enk content in specific regions of the mesocorticolimbic and nigrostriatal pathways, as well as the hypothalamus and hippocampus. On the other hand, ethanol (1.0 g/kg) administered to PET-animals, increases Met-enk concentrations in the PFC (25%), the amCP (91%), the hypothalamus (90%), and the hippocampus (36%) (see Figs. 46.4 46.6). No ethanol effect was observed on peptide levels in the FIGURE 46.1 Prenatal ethanol effect on Methionineenkephalin concentration in mesocorticolimbic areas of infant rats. Methionine-enkephalin (Met-enk) concentration (pg/mg protein) data are expressed as percent of controls (100%, pups from prenatal water-treated dams) and correspond to 9479 6 1512 in the ventral tegmental area (VTA) (n 5 6), 855 6 101 in the prefrontal cortex (PFC) (n 5 9) and 1932 6 232 in the nucleus accumbens (NAcc) (n 5 10). Bars represent the mean 6 standard error of the mean.  P , .020;  P , .030;  P , .050 versus controls. Adapted from Abate, P., Herna´ndez-Fonseca, K., Reyes-Guzma´n, A.C., Barbosa-Luna, I.G., & Me´ndez, M. (2014). Prenatal ethanol exposure alters met-enkephalin expression in brain regions related with reinforcement: possible mechanism for ethanol consumption in offspring. Behavioural Brain Research, 274, 194 204.

FIGURE 46.2 Prenatal ethanol effect on Methionine-enkephalin concentration in nigrostriatal regions of infant rats. Methionine-enkephalin (Metenk) concentration (pg/mg protein) data are expressed as percent of controls (100%, pups from prenatal water-treated dams) and correspond to 2516 6 199 in the substantia nigra (SN) (n 5 5), 1440 6 177 in the anterior-medial caudate-putamen (amCP) (n 5 12) and 2372 6 382 in the medial-posterior caudate-putamen (mpCP) (n 5 12). Bars represent the mean 6 standard error of the mean.  p , 0.030;  p , 0.040 versus controls. Adapted from Abate, P., Herna´ndez-Fonseca, K., Reyes-Guzma´n, A.C., Barbosa-Luna, I.G., & Me´ndez, M. (2014). Prenatal ethanol exposure alters met-enkephalin expression in brain regions related with reinforcement: possible mechanism for ethanol consumption in offspring. Behavioural Brain Research, 274, 194 204.

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IMPLICATIONS FOR TREATMENTS

447

FIGURE 46.3 Prenatal ethanol effect on Methionine-enkephalin concentration in the amygdala, hypothalamus and hippocampus of infant rats. Methionine-enkephalin (Met-enk) concentration (pg/ mg protein) data are expressed as percent of controls (100%, pups from prenatal water-treated dams) and correspond to 2230 6 271 in the amygdala (n 5 8), 2041 6 201 in the hypothalamus (n 5 12) and 2062 6 409 in the hippocampus (n 5 12). Bars represent the mean6 standard error of the mean.  p , 0.0001;  p , 0.005;  p , 0.010;  p , 0.050 versus controls. Adapted from Abate, P., Herna´ndez-Fonseca, K., ReyesGuzma´n, A.C., Barbosa-Luna, I.G., & Me´ndez, M. (2014). Prenatal ethanol exposure alters met-enkephalin expression in brain regions related with reinforcement: possible mechanism for ethanol consumption in offspring. Behavioural Brain Research, 274, 194 204.

FIGURE 46.4 Effect of ethanol administration on Methionine-enkephalin concentration in mesocorticolimbic areas of adolescent rats. Methionine-enkephalin (Met-enk) concentration (pg/mg protein) data are expressed as percent of controls (100%, offspring from prenatal water-treated dams) and correspond to 2618 6 339 in the ventral tegmental area (VTA) (n 5 8), 1827 6 145 in the prefrontal cortex (PFC) (n 5 8) and 2231 6 314 in the nucleus accumbens (NAcc) (n 5 8). Bars represent the mean 6 standard error of the mean.  p , 0.050 versus control. Adapted from Abate, P., ReyesGuzma´n, A.C., Herna´ndez-Fonseca, K., & Me´ndez, M. (2017). Prenatal ethanol exposure modifies locomotor activity and induces selective changes in Met-enk expression in adolescent rats. Neuropeptides, 62, 45 56.

VTA and NAcc (Fig. 46.4), the SN and mpCP (Fig. 46.5), and the amygdala (Fig. 46.6) (Abate, Reyes-Guzma´n, Herna´ndez-Fonseca, & Me´ndez, 2017). As in infant rats, these studies indicate that Met-enk levels are specifically changed by ethanol in the mesocorticolimbic and nigrostriatal systems, the hypothalamus, and hippocampus. Our results suggest that PET could determine sensitivity of adolescents to further ethanol exposure.

IMPLICATIONS FOR TREATMENTS Despite evidence from studies in animal models, knowledge about the impact of ethanol upon opioid systems, particularly the enkephalinergic one, provides

useful information for pharmacological approaches for treatments of alcohol abuse. In this sense, naltrexone is the most extensively characterized medication to treat AUD (Nicholson, Dilley, & Froehlich, 2017). Naltrexone decreases heavy drinking in both alcoholdependent and nondependent drinkers (Hendershot, Wardell, Samokhvalov, & Rehm, 2017), and reduces ethanol craving (Volpicelli et al., 1992). However, not all alcoholic patients respond efficiently to naltrexone administration (Ray & Hutchison, 2004). Alternative treatments have shown that acamprosate is more effective in promoting and maintaining abstinence and less effective in reducing craving or relapse (Davidson, Wirtz, Gulliver, & Longabaugh, 2007). Both medications seem to be more effective when administered to

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FIGURE 46.5 Effect of ethanol administration on Methionine-enkephalin concentration in nigrostriatal regions of adolescent rats. Methionine-enkephalin (Metenk) (pg/mg protein) data are expressed as percent of controls (100%, offspring from prenatal water-treated dams) and correspond to 1558 6 223 in the substantia nigra (SN) (n 5 8), 2317 6 257 in the anterior-medial caudate-putamen (amCP) (n 5 8) and 4810 6 517 in the medial-posterior caudate-putamen (mpCP) (n 5 8). Bars represent the mean 6 standard error of the mean.  p , 0.010 versus control. Adapted from Abate, P., ReyesGuzma´n, A.C., Herna´ndez-Fonseca, K., & Me´ndez, M. (2017). Prenatal ethanol exposure modifies locomotor activity and induces selective changes in Met-enk expression in adolescent rats. Neuropeptides, 62, 45 56.

FIGURE 46.6 Effect of ethanol administration on Methionine-enkephalin concentration in the amygdala, hypothalamus, and hippocampus of adolescent rats. Methionine-enkephalin (Met-enk) concentration (pg/mg protein) data are expressed as percent of controls (100%, offspring from prenatal water-treated dams) and correspond to 2893 6 330 in the amygdala (n 5 8), 2796 6 479 in the hypothalamus (n 5 8) and 1977 6 141 in the hippocampus (n 5 6). Bars represent the mean 6 standard error of the mean.  p , 0.001;  p , 0.010 versus controls. Adapted from Abate, P., Reyes-Guzma´n, A.C., Herna´ndez-Fonseca, K., & Me´ndez, M. (2017). Prenatal ethanol exposure modifies locomotor activity and induces selective changes in Met-enk expression in adolescent rats. Neuropeptides, 62, 45 56.

detoxified and abstinent patients at the beginning of treatment (Maisel, Blodgett, Wilbourne, Humphreys, & Finney, 2013). More research is needed to investigate how these two medications might be usefully integrated with other treatments.

adolescent rats, as well as in adults. Ethanol-induced activation of mesocorticolimbic enkephalin-neurons may be relevant in infant rats, whereas mesocortical enkephalin-neurons seem to be a main ethanol target in adolescents.

CONCLUSIONS

MINI-DICTIONARY OF TERMS

Overall, the studies reviewed in this chapter suggest a key role of the enkephalinergic system in ethanol reinforcement and the maintenance of a high level of alcohol-drinking behavior in infant, adolescent, and adult rats. Mesocorticolimbic enkephalins may be critical in ethanol reinforcement mechanisms in infant and

Endogenous opioid system A term referring to endogenous opioid neural systems that participate in drug reinforcement. Enkephalins and endorphins participate in positive drug reinforcement, whereas dynorphins are involved in negative reinforcement. Negative reinforcement A process that implies the execution of a task to prevent an unpleasant or disagreeable sensation in response to an aversive event or stimulus.

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REFERENCES

Opiates A pharmacological term used to describe a drug derived from opium. Opiates are alkaloid compounds naturally found in the opium poppy plant (Papaver somniferum). They are exogenous compounds that bind to opioid receptors with high affinity and display the function of opioid peptides. Opioid peptides Endogenous small molecules (enkephalins, endorphins, dynorphins, endomorphins, and nociceptins), also known as opioids, that bind to opioid receptors and mediate analgesia. They also participate in other functions, including drug reinforcement and reward. Opioid receptors A family of receptors that bind opioid ligands with distinct affinity. The main opioid receptor subtypes are mu, delta, and kappa. They are inhibitory G protein-coupled receptors. Opioid and opioid receptors are widely distributed in the brain, the spinal cord, and digestive tract. Positive reinforcement A process that implies the execution of a task to obtain pleasure and/or reward in response to a certain event or stimulus. Prodynorphin An endogenous opioid polypeptide hormone which, via proteolytic cleavage, can originate several dynorphin fragments: Dynorphin A (1 17), Dynorphin A (1 8), Dynorphin B (1 29), and Dynorphin B (1 13). Proteolytic cleavage of this protein can also give rise to three copies of Leucine-enkephalin. This protein was formerly known as Proenkephalin B. Proenkephalin An endogenous opioid polypeptide hormone which, via proteolytic cleavage, produces the enkephalin peptides Methionine-enkephalin, and to a lesser extent, Leucine-enkephalin. Upon cleavage, each proenkephalin peptide results in the generation of four copies of Methionine-enkephalin, two extended copies of Methionine-enkephalin, and one copy of Leucine-enkephalin. This protein was formerly known as Proenkephalin A. Pro-opiomelanocortin An endogenous opioid polypeptide hormone which, via proteolytic cleavage, generates γ-lipotropin, which is processed to β-endorphins. The Pro-opiomelanocortin precursor also gives rise to other peptides with no opioidergic activity, such as adrenocorticotropic hormones and three different forms of Melanocyte-stimulating hormones. Radioimmunoassay (RIA) A biochemical technique with high sensitivity that is used to quantitate very low concentrations of peptides in tissues and fluids.

KEY FACTS Alcoholism • Alcoholism is one of the main drug health disorders in the world that causes several social, economic, and labor problems. • Alcohol abuse and dependence are related to several diseases, including cardiovascular, hepatic and digestive alterations, and Central Nervous System disorders. • Alcohol abuse and dependence may induce neurotoxic and teratogenic effects in animals and humans. • Alcohol consumption during pregnancy may induce neural developmental alterations in offspring at birth that eventually causes life-long behavioral and cognitive problems. • Alcohol overdose may cause motor and cognitive impairment, temporal coma, and death.

SUMMARY POINTS • Alcohol reinforcement involves the ethanol-induced activation of the endogenous opioid system (enkephalins, endorphins, and dynorphins). • Beta-endorphinergic and enkephalinergic transmission play a key role in ethanol reinforcement in adult rats. • Prenatal ethanol exposure increases Methionineenkephalin content in the prefrontal cortex, nucleus accumbens, and other brain areas of preweanling rats. • Prenatal ethanol treatment rises Methionineenkephalin levels in the prefrontal cortex and other regions of 30-day-old (adolescent) rats. • Changes in mesocorticolimbic enkephalin expression could be essential in ethanol reinforcement in offspring.

References Abate, P., Herna´ndez-Fonseca, K., Reyes-Guzma´n, A. C., BarbosaLuna, I. G., & Me´ndez, M. (2014). Prenatal ethanol exposure alters met-enkephalin expression in brain regions related with reinforcement: possible mechanism for ethanol consumption in offspring. Behavioural Brain Research, 274, 194 204. Abate, P., Pueta, M., Spear, N. E., & Molina, J. C. (2008). Fetal learning about ethanol and later ethanol responsiveness: evidence against “safe” amounts of prenatal exposure. Experimental Biology and Medicine, 233, 139 154. Abate, P., Reyes-Guzma´n, A. C., Herna´ndez-Fonseca, K., & Me´ndez, M. (2017). Prenatal ethanol exposure modifies locomotor activity and induces selective changes in Met-enk expression in adolescent rats. Neuropeptides, 62, 45 56. Arias, C., Mlewski, E. C., Molina, J. C., & Spear, N. E. (2009). Ethanol induces locomotor activating effects in preweanling SpragueDawley rats. Alcohol, 43, 13 23. Arias, C., Molina, J. C., & Spear, N. E. (2010). Differential role of mu, delta and kappa opioid receptors in ethanol-mediated locomotor activation and ethanol intake in preweanling rats. Physiology & Behavior, 99, 348 354. Barbosa-Luna, I.G. (2012). Participacio´n de las encefalinas en los mecanismos de neuroadaptacio´n al alcohol en la vı´a mesocorticolı´mbica de la rata. Tesis de Maestrı´a en Ciencias Biolo´gicas (Biologı´a Experimental), Facultad de Medicina, UNAM. Chotro, M. G., & Arias, C. (2007). Ontogenetic difference in ethanol reinforcing properties: the role of the opioid system. Behavioural Pharmacology, 18, 661 667. Davidson, D., Wirtz, P. W., Gulliver, S. B., & Longabaugh, R. (2007). Naltrexone’s suppressant effects on drinking are limited to the first 3 months of treatment. Psychopharmacology (Berl), 194, 1 10. Di Chiara, G., & Imperato, A. (1985). Ethanol preferentially stimulates dopamine release in the nucleus accumbens of freely moving rats. European Journal of Pharmacology, 115, 131 132. Fadda, F., Mosca, E., Colombo, G., & Gessa, G. L. (1989). Effect of spontaneous ingestion of ethanol on brain dopamine metabolism. Life Sciences, 44, 281 287. Froehlich, J. C. (1995). Genetic factors in alcohol self-administration. The Journal of Clinical Psychiatry, 56, 15 23.

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Me´ndez, M., Leriche, M., & Calva, J. C. (2001). Acute ethanol administration differentially modulates μ opioid receptors in the rat meso-accumbens and mesocortical pathways. Brain Research. Molecular Brain Research, 94, 148 156. Me´ndez, M., Leriche, M., & Calva, J. C. (2003). Acute ethanol administration transiently decreases [3H]-DAMGO binding to mu opioid receptors in the rat substantia nigra pars reticulata but not in the caudate-putamen. Neuroscience Research, 47, 153 160. Me´ndez, M., & Morales-Mulia, M. (2006). Ethanol exposure differentially alters Pro-enkephalin mRNA expression in regions of the mesocorticolimbic system. Psychopharmacology, 189, 117 124. Me´ndez, M., & Morales-Mulia, M. (2008a). Role of mu and delta opioid receptors in alcohol drinking behaviour. Current Drug Abuse Reviews, 1, 239 252. Me´ndez, M., & Morales-Mulia, M. (2008b). Ethanol exposure and Pro-enkephalin mRNA expression in regions of the mesocorticolimbic system. In L. Sher (Ed.), Research on the neurobiology of alcohol use disorders (pp. 177 202). New York: Nova Science Publishers Inc. Me´ndez, M., Morales-Mulia, M., & Leriche, M. (2004). [3H]-DPDPE binding to d opioid receptors in the rat mesocorticolimbic and nigrostriatal pathways is transiently increased by acute ethanol administration. Brain Res., 1028, 180 190. Me´ndez, M., Morales-Mulia, M., & Pe´rez-Luna, J. M. (2008). Ethanolinduced changes in Proenkephalin mRNA expression in the rat nigrostriatal pathway. J. Mol. Neurosci., 34, 225 234. Miranda-Morales, R. S., Spear, N. E., Nizhnikov, M. E., Molina, J. C., & Abate, P. (2012). Role of mu, delta and kappa opioid receptors in ethanol-reinforced operant responding in infant rats. Behav. Brain Res., 234, 267 277. Molina, J. C., Domı´nguez, H. D., Lo´pez, M. F., Pepino, M. Y., & Faas, A. E. (1999). The role of fetal and infantile experience with alcohol in later recognition and acceptance patterns of the drug. In N. E. Spear, L. P. Spear, J. H. Hanningan, & C. R. Goodlett (Eds.), Alcohol and Alcoholism: Brain and Development (pp. 199 228). Hillsdale: Lawrence Erlbaum Associates. Nestler, E. J., Hyman, S. E., & Malenka, R. C. (2001). Reinforcement and addictive disorders. In E. J. Nestler, S. E. Hyman, & R. C. Malenka (Eds.), Molecular Neuropharmacology: A foundation for Clinical Neuroscience (pp. 355 382). New York: The McGraw-Hill Companies, Inc. Nicholson, E. R., Dilley, J. E., & Froehlich, J. C. (2017). Coadministration of low-dose naltrexone and bupropion reduces alcohol drinking in alcohol-preferring (P) rats. Alcohol.: Clin. Exp. Res. Available from https://doi.org/10.1111/acer.13577. Nizhnikov, M. E., Varlinskaya, E. I., Petrov, E. S., & Spear, N. E. (2006). Reinforcing properties of ethanol in neonatal rats: involvement of the opioid system. Behav. Neurosci., 120, 267 280. Olive, M. F., Koenig, H. N., Nannini, M. A., & Hodge, C. W. (2001). Stimulation of endorphin neurotransmission in the nucleus accumbens by ethanol, cocaine, and amphetamine. J. Neurosci., 21, 1 5. Pautassi, R. M., Nizhnikov, M. E., & Spear, N. E. (2009). Assessing appetitive, aversive, and negative ethanol-mediated reinforcement through an immature rat model. Neurosci. Biobehav. Rev., 33, 953 974. Ray, L. A., & 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. Roberts, A. J., Gold, L. H., Polis, I., McDonald, J. S., Filliol, D., Kieffer, B. L., & Koob, G. F. (2001). Increased ethanol selfadministration in delta-opioid receptor knockout mice. Alcohol.: Clin. Exp. Res., 25, 1249 1256. Roberts, A. J., McDonald, J. S., Heyser, C. J., Kieffer, B. L., Matthes, H. W. D., Koob, G. F., & Gold, L. H. (2000). μ-opioid receptor

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C H A P T E R

47 Alcohol and Central Glutamate Activity: What Goes Up Must Come Down? 1

Richard L. Bell1, Youssef Sari2 and Shafiqur Rahman3

Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States 2Department of Pharmacology and Experimental Therapeutics, University of Toledo, Frederic and Mary Wolfe Center, Toledo, OH, United States 3Department of Pharmaceutical Sciences, College of Pharmacy, South Dakota State University, Brookings, SD, United States

LIST OF ABBREVIATIONS A2A ACC Ach AGAP AKAP AMPAR AMYG Arc ASP AUD BAC BLA BNST Ca21 cAMP CaMKII CeA CNS CP D2 DRN EAAT ERK FC FHN FHP GABA GKAP GLAST GLN GLT GluA1 GluK1 GluN1

adenosine 2A receptor anterior cingulate cortex acetylcholine ADP-ribosylation factor GTPase-activating protein A-kinase anchor protein α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor amygdala Arg3.1 5 activity-regulated cytoskeleton-associated protein aspartate alcohol use disorders blood alcohol concentration basolateral AMYG bed nucleus of the stria terminalis calcium ion cyclic adenosine monophosphate calcium/calmodulin-dependent protein kinase type 2 central AMYG central nervous system caudate-putamen dopamine-2 receptor dorsal raphe nucleus excitatory amino acid transporter extracellular signal-regulated kinase frontal cortex family history negative family history positive gamma-amino-butyric acid guanylate kinase-associated protein glutamate-aspartate transporter glutamine glutamate transporter glutamate AMPAR subunit 1 glutamate KAR subunit 1 NR1 5 glutamate NMDAR subunit 1

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00047-7

GLY GP GPCR GRASP GRID Grik1 GRIP GTP H1 HAB Hipp Hyp iGluR IP3 K1 KA1 KAR LC LS LTD LTP MAPK MDTN mGluR mPFC mRNA NA1 NAcb NARP NMDAR nNOS NR1 OB OC OFC OT PAG

453

glycine globus pallidum G-protein coupled receptor neuron-specific guanine nucleotide exchange factor associated with GRIP GluD 5 glutamate receptor ionotropic delta glutamate KAR subunit 1 glutamate receptor-interacting protein guanosine triphosphate hydrogen ion habenula hippocampus hypothalamus ionotropic glutamate receptor inositol trisphosphate potassium ion KAR subunit 1 kainate receptor locus coeruleus lateral septum long-term depression long-term plasticity mitogen-activated protein kinase medial dorsal thalamic nucleus metabotropic glutamate receptor medial PFC message ribonucleic acid sodium ion nucleus accumbens neural activity dependent pentraxin N-methyl-D-aspartate receptor neuronal nitric oxide synthase NMDAR subunit 1 olfactory bulb occipital cortex orbital frontal cortex olfactory tubercle peri-aqueductal gray

© 2019 Elsevier Inc. All rights reserved.

454 PC PFC PKA PSD SAP SC SLC SN synGAP TC VDCC VGLUT VTA xCT

47. ALCOHOL AND CENTRAL GLUTAMATE ACTIVITY: WHAT GOES UP MUST COME DOWN?

Glutamate

parietal cortex prefrontal cortex protein kinase A postsynaptic density synapseassociated protein superior colliculus solute carrier substantia nigra synaptic RAS GTPase-activating protein1 temporal cortex voltage-dependent calcium channel vesicular glutamate transporter ventral tegmental area cystine glutamate exchanger

INTRODUCTION Early work on ethanol dependence highlighted the role of glutamate in withdrawal-associated seizures. Subsequent research has shown that central glutamate activity plays a large role in the development of alcohol use disorders (AUD). This chapter discusses this role in view of both preclinical and clinical studies on how ethanol affects the structure and function of the central glutamatergic system (Burnett, Chandler, & Trantham-Davidson, 2016; Cui, Grandison, & Noronha, 2013; Herman et al., 2003; Koob, Arends, & LeMoal, 2014; Noronha, Cui, Harris, & Crabbe, 2014; Tabakoff & Hoffman, 2013).

Cortex1,2,3,4,5

Glutamate (glutamic acid) is the primary excitatory neurotransmitter of the central nervous system (CNS). Glutamate also serves as the precursor for gammaaminobutyric acid (GABA), the primary inhibitory neurotransmitter of the CNS. Therefore, it is not surprising that glutamate receptors and transporters are located throughout the brain (See Fig. 47.1). However, glutamate receptor subunits are differentially distributed relative to brain region, cell-type, synaptic region, and intracellular compartment. Moreover, ratios of flip or flop isomers are modulated by activity or disease with cell-type and subunit-specific differences mediating this effect (Balazs, Bridges, & Cotman, 2006; Gereau & Swanson, 2008; Pomierny-Chamiolo et al., 2014).

Metabotropic Glutamate Receptors (mGluRs) The mGlu receptors are G-protein-coupled protein receptors (GPCRs) located at the neuronal synapse, perisynaptically, and extrasynaptically, as well as on glial cells. These receptors are divided into three groups: Group I, Group II, and Group III mGluRs (Gereau & Swanson, 2008; Ngomba, Di Giovanni, Battaglia, & Nicoletti, 2017). For CNS location of mGluRs, see Fig. 47.1. For synaptic location of mGluRs, see Fig. 47.2.

PC1,2,3,4,5

OC1,3

FC1,2,3,4,5 PFC1,2,3,4,5

OB1,2,3,5

ACC1,2,5 CP1,2,3,4,5 1,5 OFC

OT 1,2,3,5

Hipp1,2,3,4,5

SC1,2,5 Cerebellum1,2,3,4,5

HAB1,2,3,4,5 LS1,2,3,4,5 Thalamus1,2,3,4,5

PAG1,2,3,5

NAcb1,2,3,4,5 GP1,2,3,4,5 LC1,2,3,5 1,2,3,5 DRN AMYG1,2,3,4,5 Hyp1,2,3,5

SN1,2,3,5 VTA1,2,3,5

Medulla3,4,5

Pons1,5 FIGURE 47.1 CNS glutamatergic projections and receptor localization. 1, NMDAR; 2, AMPAR; 3, KAR; 4, GRID; 5, mGluRs; ACC, anterior cingulate cortex; AMYG, amygdala; CP, caudate putamen; DRN, dorsal raphe nucleus; FC, frontal cortex; GP, globus pallidum; HAB, habenula; Hipp, hippocampus; Hyp, hypothalamus; LC, locus coeruleus; LS, lateral septum; NAcb, nucleus accumbens; OB, olfactory bulb; OC, occipital cortex; OFC, orbital frontal cortex; OT, olfactory tubercle; PAG, periaqueductal gray; PC, parietal cortex; PFC, prefrontal cortex; SC, superior colliculus; SN, substantia nigra; VTA, ventral tegmental area. See text for the definition of other abbreviations. Source: Adapted from Bell, R.L., Hauser, S., Rodd, Z.A., Liang, T., Sari, Y., et al. (2016). A genetic animal model of alcoholism for screening medications to treat addiction. International Review of Neurobiology, 126, 179 261. IV. PHARMACOLOGY, NEUROACTIVES, MOLECULAR AND CELLULAR BIOLOGY

INTRODUCTION

Group I mGluRs

455

Group I metabotropic receptors, mGluR1 and mGluR5, engage in slow excitatory neurotransmission. Group I metabotropic receptors are located predominantly postsynaptically, perisynaptically, on glia, and intracellularly. Intracellular localization includes the endoplasmic reticulum, nuclear surface, and the intranuclear compartment. Activation of Group I mGluRs generally leads to an increase in intracellular Ca21 and Na1 concentrations with an efflux of K1. In addition, there is evidence that heterodimerization occurs between mGluR5 and mGluR1, adenosine 2A (A2A), or dopamine 2 (D2) receptor subunits.

Group II metabotropic receptors are located predominantly presynaptically, with some postsynaptic, perisynaptic, and glial localization. However, Group II has limited intracellular localization. Activation of Group II mGluRs generally increases intracellular Na1 and K1 concentrations. Synaptic Group II mGluRs lead to myosin6-stargazin transport of extrasynaptic, cell surface GluA1-AMPARs to the postsynaptic density (PSD), whereas activation of perisynaptic or extrasynaptic Group II mGluRs increases Ca21 CaMKII-Ras/ MAPK-SAP97/myosin6 insertion of GluA1-AMPARs in the cell membrane of the perisynapse. In addition, activation of presynaptic Group II mGluRs inhibits neurotransmitter release.

Group II mGluRs

Group III mGluRs

Group II metabotropic receptors, mGluR2 and mGluR3, engage in slow inhibitory neurotransmission.

Group III metabotropic receptors, mGluR4, mGluR6, mGluR7, and mGluR8, are mainly located in the active

FIGURE 47.2 Glutamate-associated receptors and transporters in the excitatory synapse. AGAP, ADP-ribosylation factor GTPaseactivating protein, ASP, aspartate, EAAT, excitatory amino acid transporter, GLN, glutamine, GLT, glutamate transporter, GLU, glutamate, GLY, glycine, SLC, solute carrier, VDCC, voltage-dependent calcium channel, xCT, glutamate-cystine exchanger. See text for the definition of other abbreviations. Source: Adapted from Bell, R.L., Hauser, S., Rodd, Z.A., Liang, T., Sari, Y., et al. (2016). A genetic animal model of alcoholism for screening medications to treat addiction. International Review of Neurobiology, 126, 179 261.

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47. ALCOHOL AND CENTRAL GLUTAMATE ACTIVITY: WHAT GOES UP MUST COME DOWN?

zone of the presynaptic terminal. Like Group II mGluRs, Group III mGluRs engage in slow inhibitory neurotransmission. All evidence suggests that localization of mGluR6s is restricted to the retina. Similar to Group II mGluRs, activation of Group III mGluRs generally increases intracellular Na1 and K1 concentrations. Activation of presynaptic Group III mGluRs inhibits neurotransmitter release whereas postsynaptic activation can lead to paradoxical excitation.

Effects of Ethanol on mGluRs Research indicates that the interoceptive properties of ethanol, which affect seeking and selfadministration behavior, require functional mGluR5s in the NAcb and BLA (Besheer et al., 2010; Sinclair, Cleva, Hood, Olive, & Gass, 2012). Preclinical and clinical research implicates the mGluR2, and its gene Grm2, in AUD patients (Laukkanen et al., 2015; Wood et al., 2017; Zhou et al., 2013). Similar to mGluR2, the mGluR7, and its gene Grm7, has also been implicated in AUD patients (Gyetvai et al., 2011; Vadasz et al., 2007). Therefore it is not surprising that preclinical research has identified mGluR1, mGluR2/3, mGluR4, mGluR5, mGluR7, and mGluR8 as candidate pharmacotherapy targets to treat AUD (Bell et al., 2012; Bell, Hauser, McClintick, Rahman, & Edenberg, 2016; Bell, Hauser, Rodd, Liang, & Sari, 2016; Bell et al., 2017; Goodwani, Saternos, Alasmari, & Sari, 2017; Holmes, Spanagel, & Krystal, 2013; Meyers et al., 2015; Rao, Bell, Engleman, & Sari, 2015).

Ionotropic Glutamate Receptors There are three families of ionotropic glutamate receptors (iGluRs), including N-methyl-D-aspartate (NMDAR), α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPAR), kainate (KAR), and delta (GRID) receptors (Hashimoto, 2017; Rodriguez-Moreno & Sihra, 2011; VanDongen, 2009). For CNS locations of iGluRs, see Fig. 47.1. For synaptic location of iGluRs, see Fig. 47.2.

NMDARs NMDAR subunits are differentially distributed throughout the brain. For instance, NR1 (GluN1), NR2A (GluN2A), and NR2B (GluN2B) are highly expressed in cortical layers, whereas NR2C (GluN2C), NR2D (GluN2D), and NR3 (GluN3) subunits are lowly expressed in cortical layers, but highly expressed in the Hipp and cerebellum. In the cortex, most NMDARs are located postsynaptically on dendrites

and dendritic spines. NMDARs form both diheteromeric (NR1/NR2) and triheteromeric (NR1/NR2/ NR3) receptors.

AMPARs The primary AMPAR heterodimers are GluA1/ GluA2 (GluR1/GluR2) or GluA2/GluA3 (GluR2/ GluR3) and are highly expressed in the cortices and Hipp with moderate expression elsewhere. Perisynaptic AMPARs on the presynaptic terminal also have been shown to have metabotropic-like actions which inhibit neurotransmitter release. Additionally, AMPARs on glia modulate astrocytic glutamate transporter activity, glial morphology, and regulation of gene expression. AMPARs and NMDARs are linked by synaptic surface proteins (See Fig. 47.1) in the PSD and jointly mediate long-term synaptic plasticity—long-term potentiation (LTP) or long-term depression (LTD). Synaptic Ras GTPase-activating protein (SynGAP), guanylate kinaseassociated protein (GKAP), Shank, Homer, and multiple PSD proteins are key scaffolding proteins that link different iGluRs with mGluRs (See Fig. 47.1). AMPARs are also abundantly localized intracellularly in the perisynaptic region of the postsynapse, with increased glutamatergic activity (e.g., LTP) they are inserted into the cell membrane and shuttled to the PSD. In hippocampal subregions, there are AMPA-only and kainate-only synapses, which, following LTP, can switch from kainateonly synapses to AMPA-only synapses.

KARs Kainite receptor subunits include GluK1-GluK4 (Grik1-Grik5 5 GluK1-GluK5 5 GluR5-GluR7 1 KA1KA2), with GluR5-1, GluR5-2a-2d, GluR6a-6b, and GluR7a isoforms identified thus far. KARs are widely expressed postsynaptically. In addition, a substantial portion of KARs are located perisynaptically, and/or presynaptically, where they express metabotropic-type inhibitory activity on GABA release. KAR subunits form heteromeric receptors, such as GluK2/GluK5 and mice lacking GluK2 do not appear to have functional GluK5-containing KARs. Regarding the putative dual signaling activity (ionotropic and metabotropic) of KARs, it appears that GluK1 subunits are required for this function.

GRIDs Although delta receptors (GRID1 and GRID2) are considered orphan receptors, they share B40% amino acid sequence with AMPARs and KARs as well as

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INTRODUCTION

B25% with NMDARs which has led them to be classified iGluRs. While GRID1 and GRID2 are not coexpressed in neurons, these receptors are coexpressed with other iGluRs. GRIDs have been shown to be crucial for normal posture and ambulation, appear to modulate the size of the PSD area relative to the presynaptic active zone, and may facilitate AMPAR internalization.

Effects of Ethanol on iGluRs Early research showed that ethanol exposure inhibits NMDARs, with a concomitant upregulation of NMDAR number and/or function. Alterations in NMDAR synaptic plasticity have been implicated in ethanol-induced locomotor sensitization and high ethanol consumption (Abrahao et al., 2013). In particular, the NR2B subunit is associated with both ethanol consumption and associated withdrawal (Wang et al., 2010). Thus, it is not surprising that NMDAR antagonists, such as memantine or MK-801, disrupt ethanolinduced sensitization, motor impairment, cognitive deficits, and neurotoxicity (Idrus, McGough, Riley, & Thomas, 2011; Malpass, Williams, & McMillen, 2010). Moderate ethanol intake increases neural activity dependent pentraxin (NARP), which facilitates AMPAR-associated synaptic plasticity (Ary et al., 2012; Salling et al., 2016). AMPAR agonists have been shown to decrease ethanol-induced intoxication and motor impairment, whereas AMPAR antagonists reduce ethanol-associated craving, seeking, and relapse-like behavior (Cannady, Fisher, Durant, Besheer, & Hodge, 2013; Jones, Messenger, O’Neill, Oldershaw, & Gilmour, 2008), Overall, these findings indicate that NMDARs and AMPARs are important targets for pharmacotherapies to treat AUD patients (Bell et al., 2012, Bell, Hauser, McClintick et al., 2016; Bell, Hauser, Rodd et al., 2016, 2017; Goodwani et al., 2017; Holmes et al., 2013; Hopf, 2017; Morisot & Ron, 2017; Rao et al., 2015).

Glutamate-Associated Transporters Glutamate levels are regulated by several glutamate transporters (Anderson & Swanson, 2000). There are five glutamate transporters expressed on glia, which are termed excitatory amino acid transporters (EAAT15). EAAT1 (Glutamate-Aspartate Transporter, GLAST) and EAAT2, with EAAT2 located extrasynaptically on some neurons. EAAT3 and EAAT4 are located presynaptically and postsynaptically on neurons, whereas EAAT5 localization is limited to the retina. These

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transporters are Na1 dependent transporters that influx Na1 and H1 ions and efflux K1 ions, which leads to a gradient concentration that results in glutamate uptake. Among these transporters, glutamate transporter 1 (GLT-1, human homolog EAAT2) is the primary transporter for maintaining extracellular glutamate levels in the brain (Danbolt, 2001). The cystine/glutamate exchanger (xCT) is located on glia and regulates glutamate uptake through the exchange of extracellular cystine for intracellular glutamate (Bannai et al., 1984). For synaptic location of glutamate-associated transporters, see Fig. 47.2.

Vesicular Glutamate-Associated Transporters There are also vesicular glutamate transporters (VGLUTs), which mediate the uptake and sequestration of glutamate, from intracellular stores, in vesicles in the presynapse. There are three VGLUTs (VGLUT1, VGLUT2, and VGLUT3) located in the brain. VGLUT1 is found in the cortices, thalamus, and Hipp; while VGLUT2 is also expressed in the OB, and subiculum. VGLUT3 is expressed in glia and somato-dendrocytes throughout the brain (Liguz-Lecznar & SkangielKramska, 2007).

Effects of Ethanol on Glutamate Transporters Ethanol-enhanced levels of glutamate appear to follow reduced glutamate transporter activity. This increase in extracellular glutamate (a hyperglutamatergic state) affects many aspects of neuroplasticity and impairs neurocircuits involved in AUD (Tsai & Coyle, 1998). These glutamatergic changes have been modeled extensively in animals with the finding that ethanol self-administration leads to down-regulation of GLT-1 in the NAcb, but not in the PFC (Sari, Sreemantula, Lee, & Choi, 2013); whereas xCT expression is downregulated in both the PFC and NAcb (Alhaddad, Das, & Sari, 2014). This decrease in xCT expression can decrease perisynaptic glutamate, which can result in a loss of glutamatergic tone at perisynaptic mGlu2/3 receptors with a consequent increase in synaptic glutamate release (Moran, McFarland, Melendez, Kalivas, & Seamans, 2005; Javitt et al., 2011). Clinically, chronic alcoholism reduces GLAST protein and increases GLAST mRNA in the PFC, with the authors suggesting a compensatory relationship between the GLAST protein and mRNA levels (Flatscher-Bader, Harrison, Matsumoto, & Wilce, 2010; Kryger & Wilce, 2010). Given ethanol’s effects on extracellular glutamate levels as well as glutamate transporter levels,

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47. ALCOHOL AND CENTRAL GLUTAMATE ACTIVITY: WHAT GOES UP MUST COME DOWN?

pharmacological upregulation of GLT1 expression and/or function has been extensively evaluated with very promising results (Goodwani et al., 2017; Rao et al., 2015; Scofield et al., 2016).

The Mesocorticolimbic Reward System The mesocorticolimbic dopamine (DA) reward system mediates orientation toward and acquisition of rewards including ethanol. In some people, these rewards appear to “hijack” this reward system, which, in turn, perpetuates and increases ethanol selfadministration. The core mesocorticolimbic DA system can be described as a set of neurocircuitry, including the Amyg, medial PFC (mPFC), NAcb, and ventral tegmental area (VTA) and has multiple reciprocal glutamatergic projections between its nuclei and those of the rest of the brain (Popoli, Diamond, & Sanacora, 2014; Schmidt & Reith, 2005). The mPFC receives glutamate, acetylcholine (ACh), and DA inputs and has glutamatergic projections to other mesocorticolimbic brain areas. The Amyg receives glutamatergic input from the mPFC and is well-connected with other structures in the mesocorticolimbic system, including the VTA and NAcb (See Fig. 47.3). The Amyg, in particular the BLA and central Amyg (CeA) nuclei, integrates information, for learning and memory, regarding stress and emotional states. The VTA contains DA cell bodies projecting to corticolimbic regions including the Amyg, mPFC, and NAcb. The VTA also receives glutamatergic input from the Amyg and mPFC. The NAcb receives glutamatergic inputs from the Amyg and mPFC and has GABAergic efferent projections to the Amyg and VTA (See Fig. 47.3). The NAcb mediates

conditioning-based learning and memory. Regarding glutamate receptors, the mesocorticolimbic reward circuit expresses high levels of mGluRs notably in the Amyg, bed nucleus of the stria terminalis (BNST), cortices, CP, Hipp, LS, mPFC, NAcb, and VTA as well as hypothalamic and thalamic subregions. The Hipp mediates biographical as well as spatial learning and memory, with glutamatergic projections to the NAcb and mPFC and glutamate input from the BNST. The CP mediates stimulus-response learning and memory receiving glutamate input from the BNST, Amyg, and mPFC (See Fig. 47.3). Regarding synaptic plasticity, AMPA and NMDA receptors are often colocalized with mGluRs and mediate many learning and memory processes such as LTD and LTP.

Ethanol and the Mesocorticolimbic Reward System The PFC and OFC mediate behavioral and cognitive functions involved in AUD, with ethanol disrupting many of these glutamate-associated functions across species (Kuo & Dodd, 2011; Mishra, Harrison, Gonzales, Schilstrom, & Konradsson-Geuken, 2015; Nimitvilai et al., 2017). The Hipp, and its function, is highly susceptible to ethanol-induced insults (Zorumski, Mennerick, & Izumi, 2014). The Amyg regulates emotional states with acute and chronic ethanol altering glutamatergic mediation of these processes (Kallupi et al., 2014; McCool, Christian, Diaz, & Lack, 2010). Similarly, ethanol alters NMDA-associated synaptic plasticity in the striatum, Amyg, and Hipp (Moykkynen & Korpi, 2012). Finally, research with a rat animal model of alcoholism has revealed that FIGURE 47.3

mPFC /OFC

VTA

NACB

= Core mesocorticolimbic system = Core extended amygdala system

MDTN

CTX

AMYG

CP

BNST

HIPP

CNS glutamatergic projections and the recruitment of multiple memory systems in AUDs. The amygdala (Amyg) mediates emotional, fear, and “flashbulb” learning and memory. The caudate-putamen (CP) mediates stimulus-response and habit learning and memory. The hippocampus (Hipp) mediates episodic, biographical, and spatial learning and memory. The medial dorsal thalamic nucleus (MDTN) links limbic memory structures with the prefrontal cortex (PFC). The nucleus accumbens (NAcb) mediates classical cue-conditioned learning and memory. The PFC mediates working memory. Excessive glutamate activity (the arrows indicate major glutamatergic projections) enhances learning, memory, and reactivity to cues associated with AUD. Source: Adapted from Rao, P.S., Bell, R. L., Engleman, E.A., Sari, Y. (2015). Targeting glutamate uptake to treat alcohol use disorders. Frontiers in Neuroscience, 9, 144.

= Multiple memory systems

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SUMMARY POINTS

physiologically relevant levels of ethanol are selfadministered directly into both the VTA and NAcb (Ding, Ingraham, Rodd, & McBride, 2015; Engleman et al., 2009; Toalston et al., 2014) and ethanol exposure alters glutamate levels in both of these brain regions as well (Das, Althobaiti, Alshehri, & Sari, 2016; Ding et al., 2013). Thus, it is likely that dysregulation of these glutamatergic circuits will impair an individual’s ability to evaluate the risks and rewards of engaging in AUD (Bell, Hauser, McClintick et al., 2016; Bell, Hauser, Rodd et al., 2016; Rao et al., 2015; Scofield et al., 2016; Szumlinski & Woodward, 2014) (See Fig. 47.3).

Future Directions The research findings discussed in this chapter make it clear that glutamate plays a significant role in the development of AUD, as well as addiction in general, and there are a number of candidate molecular targets for medication development and/or screening. These molecular targets span the myriad of glutamate receptors and transporters as well as associated synaptic proteins (scaffolding proteins and vesicular docking proteins). In addition, research on glutamateassociated enzymes and intracellular cascades may yield promising pharmacotherapies. Importantly, given that AUD are associated with long-term dysfunction of a number of neurobiological and neurobehavioral processes, treatment of AUD patients will need to go beyond simply blocking relapse. Regarding this, the central glutamatergic system provides an ideal target for the holistic treatment of AUD because it mediates not only positive processes, such as learning and memory, but also negative processes, such as neurotoxicity. Thus, a delicate balance will need to be struck between these processes when developing pharmacotherapies. Finally, despite substantial progress in our understanding of how the central glutamatergic system mediates AUD, there is still much to accomplish in combating this serious public health concern.

MINI-DICTIONARY OF TERMS Glutamate The primary excitatory neurotransmitter in the brain and serves as a precursor for the synthesis of the primary inhibitory neurotransmitter in the brain, gamma-aminobutyric acid (GABA). Excitotoxicity This is often induced by excessive neuronal stimulation, which, in turn, is often induced by excessive neuronal glutamate activity and its associated excessive Ca21 influx. The postsynaptic density PSD is a specialized cellular junction that places neurotransmitter receptors of the postsynapse in close proximity to the neurotransmitter’s vesicular release sites, in the active zone, of the presynapse.

The tripartite synapse This refers to the presynapse, the postsynapse, and surrounding glia as a functional unit, which underscores the active role that glia play in neuroactivity of the brain. The brain’s reward neurocircuitry A group of circuits that interact with each other to mediate alcohol and substance use disorders. The most basic components include the mesolimbic dopamine projection from the ventral tegmental area to the nucleus accumbens; the extended amygdala which includes nuclei of the amygdala, the bed nucleus of the stria terminalis, and the nucleus accumbens shell; and the umbrella mesocorticolimbic system, which incorporates both the mesolimbic and extended amygdala as well as memory and other neurocircuits. Multiple memory systems This refers to the fact that different brain nuclei play a significant role in different forms of learning and memory; such that the hippocampus mediates recall of facts and places, the prefrontal cortex mediates working memory, the amygdala mediates responses to stimuli associated with fear and anxiety, the nucleus accumbens mediates conditioned cue-induced approach behavior, and the caudate nucleus mediates procedural recall and habit formation.

KEY FACTS Key Synaptic Components of the Glutamatergic System Include • • • • • • • •

Metabotropic glutamate receptors Ionotropic glutamate receptors Glutamate transporters Cystine-glutamate exchanger Glutamine transporters Glycine transporters Scaffolding proteins of the postsynaptic density NARE complex of the presynaptic active zone

SUMMARY POINTS • Glutamate activity in the CNS reward neurocircuitry is crucial for the development and maintenance of alcohol and substance use disorders. • Both ionotropic and metabotropic glutamate receptors as well as transporters are located in tripartite synapses throughout the CNS. • Acute alcohol exposure results in functional antagonism of NMDA receptors. • Chronic alcohol exposure downregulates glutamate transporters, which leads to excessive CNS glutamate levels/activity. This excessive glutamate activity, in turn, can lead to excitotoxicity/neurotoxicity. • Chronic alcohol exposure alters NMDA/AMPA and Group I metabotropic receptor activity interfering with synaptic plasticity. Alterations in synaptic plasticity lead to changes in learning, memory, and stimulus conditioning associated with alcohol and substance use disorders.

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Acknowledgements Preparation of this manuscript was supported in part by NIAAA AA013522 (RLB).

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48 Ethanol and Hippocampal Gene Expression: Linking in Ethanol Metabolism, Neurodegeneration, and Resistance to Oxidative Stress 1

Mario Dı´az1, Vero´nica Casan˜as-Sa´nchez2, David Quinto-Alemany3 and Jose´ A. Pe´rez2

Departamento de Biologı´a Animal, Edafologı´a y Geologı´a & Unidad Asociada de Investigacio´n ULL-CSIC, “Fisiologı´a y Biofı´sica de la Membrana Celular en Patologı´as Neurodegenerativas y Tumorales”, Facultad de Ciencias, Seccio´n Biologı´a, Universidad de La Laguna, Tenerife, Spain 2Departamento de Bioquı´mica, Microbiologı´a, Biologı´a Celular y Gene´tica & Instituto Universitario de Enfermedades Tropicales y Salud Pu´blica de Canarias, Facultad de Ciencias, Seccio´n Biologı´a, Universidad de La Laguna, Tenerife, Spain 3Departamento de Biologı´a Animal, Edafologı´a y Geologı´a, Facultad de Ciencias, Seccio´n Biologı´a, Universidad de La Laguna, Tenerife, Spain

LIST OF ABBREVIATIONS AMPA CYP2E1 FAK GABA-A LTD LTP NMDA PKC ROS SOD CAT

α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid cytochrome P450 isoform 2E1 focal adhesion kinase gamma-aminobutyric acid A long-term depression long-term potentiation N-methyl-D-aspartate protein kinase C reactive oxygen species superoxide dismutase catalase

INTRODUCTION Ethanol is a very pleiotropic molecule and its effects extend to nearly all organs in an organism. Cell membranes are highly permeable to alcohol, and once alcohol enters the bloodstream it diffuses into nearly every cell in the body, including the brain. Ethanol is known to induce neurocognitive deficits and to provoke neuronal function impairments and, at high doses or long-

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00048-9

term consumption, to provoke injuries associated with neuronal degeneration (Givens, Williams, & Gill, 2000). There is general consensus on the participation of oxidative stress in the deleterious effects of ethanol and that ethanol-driven generation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) are implicated in nerve tissue injury (Das & Vasudevan, 2007). However, given the pleotropic face of ethanol, the precise mechanisms underlying ethanol-induced neurological disorders are diverse and only partially understood (Harris, Trudell, & Mihic, 2008). Ethanol targets include a plethora of molecules from neurotransmitter receptors, kinases, signaling molecules, transcription factors, proto-oncogenes, and ion channels, among others (reviewed in Harris et al., 2008; Ryabinin, 1998). Further, recent evidence have demonstrated that ethanol drives changes in gene expression and transcriptional modulation, as well as in chromatin remodeling (Casan˜as-Sa´nchez, Perez, QuintoAlemany, & Dı´az, 2016; Chandrasekar, 2013; Hsieh & Gage, 2005; Jin et al., 2014; Moykkynen & Korpi, 2012; Nagy, Kolok, Dezso, Boros, & Szombathelyi, 2003). In

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the brain, the hippocampus is particularly sensitive to ethanol. It is known that acute exposure to alcohol alters cognitive functions, such as working memory and spatial learning (Givens et al., 2000; White, Matthews, & Best, 2000). Studies addressing the effects of alcohol on human memory have shown that acute intoxication is more severe on the acquisition of new memories than for retrieval of already-formed (consolidated) memories, and that these effects of alcohol are similar to those reported after hippocampal damage (Ryabinin, 1998; White et al., 2000). Current evidence indicates that alcohol-mediated memory impairments are rather a “continuum of effects” (Collins et al., 2009) ranging from short-term memory deficits seen in lowdose acute exposures (i.e., moderate drinkers), to blackouts in chronic consumers (in some alcoholics), and permanent inability to form memories, as observed in alcoholic subjects with Wernicke Korsakoff syndrome (Sanvisens et al., 2017). In the past decade, a number of epidemiological studies have reported significantly reduced risks of cognitive decline or dementia (including Alzheimer’s disease) in light to moderate alcohol consumers in comparison to nondrinkers (and, obviously, to heavy drinkers) (Collins et al., 2009; Mukamal et al., 2003; NIAAA, 2000; Ruitenberg et al., 2002). The association of alcohol intake with dementia was boosted by the recognition that dementia shares risk factors with cardiovascular disease (Collins et al., 2009; Mukamal et al., 2006). Indeed, the relationship between alcohol intake and risk of dementia (Vascular dementia and Alzheimer disease) or cardiovascular disease (coronary heart disease or ischemic stroke) followed similar Ushaped dependences (Collins et al., 2009; Mukamal et al., 2006) with increased risks at higher alcohol intakes (Fig. 48.1). This U-shape relationship suggests that the effects of ethanol are hormetic (exhibit hormesis) and that beneficial or detrimental effects of ethanol are tightly correlated to the dose (Mattson, 2008). On the other hand, Bate and Williams (2011) demonstrated that pretreatment with low concentrations of ethanol (0.02% 0.08%) protected cortical and hippocampal neurons against Aβ-induced synapse damage. Interestingly, these authors also demonstrated that ethanol was able to protect neurons against the damage produced by presynaptic accumulation of α-synuclein (which are characteristic aggregates in Parkinson’s disease and dementia with Lewy bodies). However, the molecular mechanisms of ethanol-induced neuroprotection are largely unknown and only recently have started to be unraveled. Another intriguing aspect on the effects of low to moderate doses of ethanol is that its exposure brings about a degree of protection against other cell insults. This has been better demonstrated in experimental

FIGURE 48.1 The relationship between alcohol intake and risk of dementia in the Cardiovascular Health Study (Mukamal et al., 2006). Data gathered by Collins et al. (2009) were submitted to cuadratic polynomial fitting to show the U-shape relationship. The median of class categories was used as X-values. Former: Long-term abstainers.

ischemia-reperfusion injuries in animal models, where preadministration of low to moderate ethanol exposure prevents cardiovascular damage (Collins et al., 2009; Murry, Jennings, & Reimer, 1986). This phenomenon, namely “preconditioning,” allows tissues or cells to evolve towards a cytoprotective “phenotype” endowed with a higher tolerance against different insults (Murry et al., 1986). For instance, alcohol preconditioning effects on inflammatory neurotoxicity has been demonstrated in organotypic slices of rat hippocampusentorhinal cortex (two brain regions significantly affected in Alzheimer’s disease) in response to neuroinflammatory proteins HIV-1 gp120 neurotoxicity (Collins et al., 2009, 2010). Current hypothesis points to ethanol-induced changes in gene expression as putative mechanisms whereby it may not only exert some of its acute and chronic effects in the hippocampus, but also drive preconditioning in nerve cells. The changes in gene expression will be the focus of this chapter.

METABOLISM OF ETHANOL IN THE HIPPOCAMPUS Mounting evidence indicates that both chronic and acute alcohol consumption can cause brain oxidative damage. It is known that acetaldehyde resulting from ethanol metabolism, mediates many behavioral, neurochemical, and neurotoxic effects in the brain. However, systemic acetaldehyde derived from its peripheral metabolism (mainly from the liver) hardly penetrates into the brain due to the high aldehyde dehydrogenase

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(ALDH) activity in the endothelial cells at the bloodbrain barrier (Hipolito, Sanchez, Polache, & Granero, 2007). In the liver, ethanol is metabolized by ADH, catalase (CAT), and CYP2E1 (CYP450 isoform 2E1, a member of the superfamily). Conversely, in the brain, ADH is present at very low or negligible levels (Estonius, Svensson, & Hoog, 1996), and in vitro data indicate that CAT accounts for 60% of ethanol oxidation, whereas CYP2E1 accounts for an additional 20% (Zimatkin, Pronko, Vasiliou, Gonzalez, & Deitrich, 2006). Thus, because alcohol dehydrogenase activity is nearly negligible in the brain, the generation of acetaldehyde from ethanol occurs in situ and is mediated by catalase and CYP2E1 enzymes. In addition, catalytic activity of CYP2E1 on ethanol can produce ROS, which eventually causes damage to mitochondria, DNA modification, lipid peroxidation, and even cell death (Caro & Cederbaum, 2004). The mechanisms involved in ROS generation involve different cellular compartments and biochemical/chemical reactions which are shown in Fig. 48.2. CYP2E1 proteins are not uniformly expressed in brain regions, but rather are circumscribed to specific areas, including the hippocampus, substantia nigra, and cerebellum (Garcı´a-Sua´stegui et al., 2017; Shahabi, Andersson, & Nissbrandt, 2008). Ethanol is not only

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the substrate, but also a potent inducer, of CYP2E1 in the liver and brain, and current evidence suggests that ethanol toxicity and ethanol-related ROS generation is associated to elevated CYP2E1 levels in susceptible brain regions (Zhong et al., 2012). Indeed, earlier studies have shown that brain CYP2E1 was inducible by chronic (Roberts, Shoaf, Jeong, & Song, 1994) and acute (Yadav, Dhawan, Singh, Seth, & Parmar, 2006) ethanol treatment in rats. In the rat brain, chronic or acute ethanol treatment increases the amount of CYP2E1 proteins, mRNA levels, and activity in the hippocampus, cerebellum, and frontal cortex, but no significant changes were observed in other brain regions (Garcı´aSua´stegui et al., 2017; Zhong et al., 2012). Interestingly, in the study by Zhong et al. (2012), ethanol markedly increased the levels of CYP2E1 proteins and activity, but not the mRNA levels, in the brainstem after chronic ethanol treatment, indicating that posttranslational processing may also be involved in CYP2E1 induction. The elevated CYP2E1 levels were paralleled by ROS generation and neuronal damage in the hippocampus, cerebellum, and brainstem (Zhong et al., 2012). In summary, the hippocampus, cerebellum, and brainstem are susceptible regions to ethanol neurotoxicity. This selective sensitivity may be attributed to the cellular-specific, ethanol-induced, upregulation of

FIGURE 48.2 Ethanol oxidation by CYP2E1 in endoplasmic reticulum and CAT in peroxisomes results in an increase of ROS and oxidative stress. Ethanol is converted to acetaldehyde, which may enter the mitochondria and is oxidized to acetate by ALD or directly oxidized by CYP2E1 in the reticulum. O22radicals leave the mitochondria and endoplasmic reticulum and is converted into H2O2 by SOD isoforms in the cytoplasm and mitochondria. In the presence of iron ions (ferrous form), H2O2 gives rise to highly reactive OH radicals by virtue of the Fenton reaction. In addition, ethanol can increase the expression/activity of CYP2E1 resulting in an additional increase of ROS which starts a feedback cycle of ROS production. Increased ROS levels induce oxidative damage of lipids, proteins, DNA, and mitochondria. ALDH, aldehyde dehydrogenase; ETC, electron transport chain; OH, hydroxyl radical; ∙O22, superoxide anion radical; H2O2, hydrogen peroxide; Fe21, ferrous iron; MEOS, microsomal ethanol-oxidizing system.

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CYP2E1 or by posttranscriptional processing of CYP2E1, which in any case is paralleled by ROS generation to levels above neuronal ROS buffering capacities, eventually leading to neuronal degeneration.

CHRONIC AND LONG-TERM EFFECTS OF ETHANOL IN THE HIPPOCAMPUS Further to its effects on ROS generation, ethanol also affects several neurotransmitter systems in the brain. Compelling evidence indicates that an important site of ethanol actions is the glutamatergic neurotransmitter system, the main excitatory neurotransmitter in the brain. Ionotropic glutamate receptors form glutamate-gated ion channels and are classified into three main groups, AMPA receptors, kainate receptors, and NMDA receptors, with different locations and functions in neuronal synapse (Moykkynen & Korpi, 2012; Smart & Paoletti, 2012). The AMPA receptors normally mediate fast synaptic transmission and synaptic strength. NMDA receptors exhibit high calcium permeability and regulate intracellular signaling and synaptic plasticity. Finally, kainate receptors are present both in the presynaptic and postsynaptic membranes and have a modulatory role on neurotransmitter release. The three types are expressed in the hippocampus and are responsible for processes like LTP (long-term potentiation) and LTD (long-term depression), which are involved in synaptic plasticity, cognitive performance, and different types of memories (Nicoll & Roche, 2013). A number of studies have shown that ethanol is a potent inhibitor of ionotropic glutamate receptor function by decreasing current amplitude and by accelerating current desensitization (Carta, Ariwodola, Weiner, & Valenzuela, 2003; Moykkynen & Korpi, 2012), and LTP in vivo (Givens & McMahon, 1995), which ultimately alters neuronal plasticity. Of the different ionotropic glutamate receptors, NMDA receptors are regarded as the most sensitive to ethanol as they can be inhibited by clinically relevant concentrations of ethanol (20 mM). These inhibitory effects of ethanol occur almost immediately after ethanol enters the blood brain barrier, and appear to be mediated by interaction with specific binding sites of NMDA receptor subunits. However, chronic and prolonged ethanol exposition leads to a compensatory “upregulation” of NMDA receptors by modulation of gene expression (Jin et al., 2014; Moykkynen & Korpi, 2012). Not surprisingly, these alterations are supposed to contribute to the development of ethanol tolerance and dependence, as well as ethanol withdrawal syndrome (Nagy, 2004).

Ionotropic glutamate receptors are tetrameric proteins composed of different subunits, whose combinations determine their biophysical, physiological, and pharmacological properties. Recent papers on the effects of ethanol in in vitro and in vivo models have revealed alterations in the subunit composition of hippocampal glutamate receptors after long-term ethanol exposure. For instance, the NR2B subunit expression of the NMDA receptor has been demonstrated to be increased in cultured hippocampal and cortical neurons after 3 days of intermittent ethanol treatment (Nagy, 2004). mRNA and/or protein levels of NR2A and NR2B subunits were found elevated in rat hippocampus after in vivo chronic alcohol exposure (Follesa & Ticku, 1995; Nagy et al., 2003). In addition, in postmortem human brains from alcoholics, Jin et al. (2014) reported the significant increase in the mRNAs encoding for different subunits of AMPA receptors (GluA2 and GluA3), NMDA receptors (GluN1, GluN2A, GluN2C, GluN2D, and GluNA3), and kainate receptors (GluK2, GluK3, and GluK5) in the hippocampusdentate gyrus, but not in the prefrontal cortex. These results indicate that ethanol effectively affects the transcription levels of glutamate receptor subtypes in the brain, likely through different mechanisms (Chandrasekar, 2013), and more interestingly, that these changes are strictly circumscribed to specific brain regions. Assuming that these gene expression changes are translated into new subunits, it is expected that extensive remodeling of neurotransmission, signaling, and neuronal network excitability in the hippocampus occurs after chronic alcoholism. Further to its effect on glutamatergic systems, evidence accumulated over more than 30 years, demonstrates that ethanol effects on the central nervous system are intimately associated to its effects on GABAergic neurotransmission, the major inhibitory neurotransmitter in the brain. Substantial evidence supports the thesis that low to moderate (3 30 mmol/ L) ethanol concentrations enhance the inhibitory activity of GABA-A receptors (reviewed in Alfonso-Loeches & Guerri, 2011). GABA-A channels are pentameric ligand-gated chloride channels, in which the subunit composition determines the physiological and channel’s pharmacological properties, including its ethanol sensitivity. The majority of GABA-A receptors are composed of α-, β-, γ-, and δ-subunits (Olsen & Sieghart, 2008). A region in the transmembrane domains of the α/β subunits of the GABA-A receptor has been identified as the potential binding site for ethanol (Lobo & Harris, 2008), which might account for the acute inhibitory effects of alcohol intake. Nevertheless, the effects of ethanol strongly depend on the subunit composition of GABA-A receptors. GABA-A channels containing the α4, α5, or the δ

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subunit are of particular interest. These subunits are part of extrasynaptic GABA-A channels which give rise to tonic neuronal inhibition, resulting in decreased frequency of action potentials (Jin et al., 2011; Pavlov, Savtchenko, Kullmann, Semyanov, & Walker, 2009). Maximum sensitivity to ethanol appears to occur when the γ subunit (which is located outside of the synapse) was present (Alfonso-Loeches & Guerri, 2011). It is now widely accepted that activation of GABA-A channels containing these subunits have implications for cognitive functioning (Alfonso-Loeches & Guerri, 2011). As for glutamate receptors, chronic and long-term ethanol exposure also alters gene expression of GABA-A receptor subunits. Also, these changes occur in a brain region-specific manner in alcoholic subjects. Indeed, Jin et al. (2011) have shown a significant increase in the mRNAs encoding for α1, α4, α5, β1, and γ1 subunits in the hippocampal and dentate gyrus region of individuals suffering from alcoholism, whereas no changes in the dorsolateral prefrontal cortex were detected in postmortem human brains (Jin et al., 2011). These data further support the association of long-term changes in the GABA-A isoform expression and alcohol dependence (Lobo & Harris, 2008). Finally, studies have also demonstrated the existence of epigenetic changes after long-term alcohol consumption. Epigenetic modifications involve chromatin modifications, that is, histone acetylation, phosphorylation, and DNA methylation, which positively or negatively modulate transcriptional activity. Epigenetic modifications have been shown to play an important role in gene expression underlying the stability and plasticity of developing neuronal circuits (Hsieh & Gage, 2005). Chronic alcohol exposure in experimental animals have revealed decreased HDAC (Histone deacetylase) activity along with upregulation in histone acetylation (H3 and H4), CREBP (cAMPresponsive element binding protein), and neuropeptide Y (NPY), which are associated with the anxiolytic effects of alcohol exposure (Pandey, Ugale, Zhang, Tang, & Prakas, 2008). Interestingly, alterations in DNA methylation in the promoter regions of the α-synuclein gene have been observed in mesolimbic systems (Bonsch, Lenz, Kornhuber, & Bleich, 2005). Also, α-synuclein is involved in the regulation of dopamine biosynthesis and neurotransmission in the mesolimbic system, which plays a crucial role in reinforcing alcohol-seeking behavior (Perez et al., 2002). In agreement, an increased mRNA expression of α-synuclein in alcoholic subjects has been correlated with α-synuclein promoter DNA methylation and obsessive craving (Bonsch et al., 2004, 2005). These results suggest an association between the gene-specific DNA promoter hypermethylation and chronic alcohol consumption (Alfonso-Loeches & Guerri, 2011).

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ACUTE NONTOXIC ETHANOL INTAKE, HIPPOCAMPAL GENE EXPRESSION, AND ANTIOXIDANT POTENTIAL Epidemiological and prospective studies indicate that, at population levels, low to moderate alcohol consumption may be cardio-neuro-protective (reviewed in Collins et al., 2009). The mechanisms underlying these effects of ethanol are largely unknown. Some of these processes likely occur through changes in the ability of endogenous cytoprotective systems to cope with oxidative stress and also with the ability to modulate the transcriptional processes. Regarding brain tissues, seminal studies in cellular and animal models, showed that ethanol exposure under low exposure paradigms activated different signaling mechanisms, that is, selective activation of protein kinase C epsilon (PKCε) and focal adhesion kinase (FAK), which appear to be channeled through expression of heat-shock proteins (HSP) (Sivaswamy, Neafsey, & Collins, 2010). Furthermore, considerable research indicates that the increase of different HSPs (Heat-Shock Proteins, such HSP27, HSP70, HSP90), can be putative neuroprotective “effectors” (Reviewed in Collins et al., 2009, 2010). In this regard, a significant increase in inducible HSP70 and HSP27 proteins occurred in Hippocampal-Entorhinal cortex slices after B6 days of moderate alcohol exposure, which correlates with the onset of significant neuroprotection against gp120-induced (a proinflammatory glycoprotein from HIV-1) neurotoxicity (Collins, Wang, Achille, & Neafsey, 2005). Furthermore, in vitro studies in rat hippocampal cultures have shown that low to moderate ethanol exposure protects against neurotoxic protein aggregates, such amyloid peptides (Aβ) in Alzheimer’s disease, and improved the cognitive processes of learning and memory in 3xTgAD mice (Mun˜oz et al., 2015). Under this paradigm, it was shown that low concentrations of ethanol protect against synaptotoxicity induced by Aβ in hippocampal neurons (Belmadani, Kumar, Schipma, Collins, & Neafsey, 2004; Mun˜oz et al., 2015). Further, in mice, hippocampal cultures of ethanol protect against α-synuclein-induced toxicity, a hallmark in Parkinson
s disease (Bate & Williams, 2011). Moreover, epidemiological studies have pointed out that low to moderate alcohol consumption is associated with a lower risk of incident dementia among older adults, being these individuals less likely to develop Alzheimer’s disease (Mukamal et al., 2003) (see Fig. 48.1). Ethanol is a prominent source of oxidative radicals in the brain (Das & Vasudevan, 2007). The high levels of peroxidable lipids and iron ions, together with the relatively low amounts of glutathione, make the brain particularly susceptible to nonenzymatic oxidation of

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cell components. However, recent experimental evidence has pointed out that different brain regions are capable of inducing the activation of antioxidant systems (Fig. 48.3) in response to an ethanol challenge, specifically at low to moderate concentrations (0.02% 0.1%). Indeed, work from our laboratory has demonstrated that 0.1% ethanol exposure to hippocampal-derived HT22 cells, modulates the expression of different genes belonging to the classical, glutathione/glutaredoxin and thioredoxin/peroxiredoxin antioxidant systems (Casan˜as-Sa´nchez et al., 2016). Among the different mRNAs up-regulated by ethanol we found: Sod1 (encoding for Cu/ZnSOD, the cytosolic superoxide dismutase isoform), Sod2 (encoding for MnSOD, the mitochondrial superoxide dismutase isoform), Gpx1 (encoding for GPx1, glutathione peroxidase 1), Gclc (encoding for the catalytic subunit GCLC, and responsible for de novo glutathione synthesis), and Txnrd1 (encoding for TXRD1, the cytoplasmic thioredoxin reductase isoform, the most abundantly expressed neurons) (Table 48.1). Further, in

consonance with the upregulation of Txnrd1, ethanol down-regulated the expression of Txnip, which is an endogenous inhibitor of thioredoxin (Yoshihara et al., 2014) and those of peroxiredoxins (Prdx1-5). Paralleling these changes, enzyme activities of total SOD, total glutathione peroxidase, and total thioredoxin reductase, were all increased (Fig. 48.4) (Casan˜as-Sa´nchez et al., 2016). In addition, ethanol exposure prevented glutamateinduced excitotoxicity in the same time-course as changes in gene expression (Fig. 48.5). These results were in agreement with previous results in the hippocampus of rats receiving acute intraperitoneal injections of ethanol (1.5 1.6 g/kg) showing significant increases in SOD and CAT activities (Enache et al., 2008) or in the rat cerebral cortex, hippocampus, and corpus striatum for glutathione peroxidase activity (Somani et al., 1996). We hypothesize that the transcriptional activation of critical enzymes of neuronal antioxidant systems, as well as that of inducible forms of HSP, underlie the efficient preconditioning effects of ethanol.

FIGURE 48.3

Organization of Classical, Thioredoxin/Peroxiredoxin, and Glutathione/Glutaredoxin antioxidant systems. For clarity the three systems were represented as separated pathways, although connections exist between them. For instance, reduced TRX may transfer the electrons in the two SH groups to oxidized PRDX, rendering reduced PRDX. TXNRD, thioredoxin reductase; TXN, thioredoxin; TXNIP, thioredoxin interacting protein; PRDX, peroxiredoxin; SRXN, sulfiredoxin; GPX, glutathione peroxidase; GSR, glutathione-S-reductase; GLRX, glutaredoxin; GST, glutathione-S-transferase; GSH, glutathione (reduced form); GSSG, glutathione (oxidized form).

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TABLE 48.1 Time-Course of Ethanol-Induced Changes in Gene Expression of Enzymes Belonging to the Three Antioxidant Systems in Hippocampal HT22 Cells

Thioredoxin/Peroxiredoxin

Generic

AOX system

GENE

6 Hr

24 Hr

30 Hr

48 Hr

Sod1 Sod2 Cat Txn1 Txn2 Txnip Txnrd1 Txnrd2 Txnrd3 Prdx2 Prdx3 Prdx4

Glutathione/ Glutaredoxin

Prdx5 Gclc Gsr Glrx1 Glrx2 Gpx1 Gpx4 Up-regulation

Down-regulation

Encoding genes: Sod1-2, superoxide dismutases 1 and 2; Cat, catalase; Txn1-2, thioredoxins 1 and 2; Txnip, thioredoxin interacting protein; Txnrd1-3, thioredoxin reductases 1-3; Prdx1-5, peroxiredoxins 1-5; Gclc, catalytic subunit of glutathione synthase; Gsr, glutathione-S-reductase; Glrx1-4, glutaredoxins 1 4.

FIGURE 48.4 Time-course of ethanol-induced changes in enzyme activities of antioxidant systems in mouse-derived hippocampal HT22 cells. t-SOD, total SOD; t-TXRND, total thioredoxin reductase; t-GPX, total glutathione peroxidase. Source: Adapted from Casan˜as-Sa´nchez V., Perez, J.A., Quinto-Alemany, D., & Dı´az M. (2016). Sub-toxic ethanol exposure modulates gene expression and enzyme activity of antioxidant systems to provide neuroprotection in hippocampal HT22 cells. Frontiers in Physiology, 7, 312.

In summary, we conclude that subtoxic exposure to ethanol may well be neuroprotective against oxidative insults (and perhaps other forms of cellular stress) in the cerebral cortex and hippocampus by triggering

transcriptional activation of antioxidant defenses and expression of inducible heat-shock proteins. These processes may well underlie the preconditioning effects of ethanol in the brain.

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FIGURE 48.5 Low doses of ethanol protect against glutamate-induced neurotoxicity. A representative experiment showing real-time changes in HT22 cell proliferation exposed to ethanol (1% or 0.1%) or ethanol (0.1%) 1 glutamate (20 mM) at the times indicated. Cell index is a parameter that measures cell proliferation/survival based on impedance measurements.

MINI-DICTIONARY OF TERMS Hormesis Any process in a cell or organism that exhibits a biphasic response to exposure to increasing amounts of a substance or condition. Thus, a generally favorable or beneficial biological response is characteristic of low exposures to the substance or other stressors, whereas unfavorable or detrimental effects are characteristic of higher amounts or condition levels, usually resulting in an inverted U-shaped dose-response. LTP Long-Term Potentiation consists on a rapidly induced and long-lasting form of synaptic plasticity linked to learning. It has been best studied in the hippocampus. Preconditioning A phenomenon that allows cells exposed to subtoxic or sublethal levels to toxicants or degree of injuries, not only to overcome the stress caused by them, but also to acquire protection against other kinds of insults. Oxidative stress A disturbance in the balance between the production of ROS and cellular antioxidant defenses. When antioxidant defenses are deficient, then ROS accumulate and may lead to cellular injury and even death. Hippocampus A brain structure belonging to the limbic system. In primates, including humans, it is located in the medial temporal lobe of the cerebral cortex. The hippocampus has a functional role in the consolidation of short-term memory to long-term memory, and also in the construction of spatial memory.

KEY FACTS • The effects of ethanol in hippocampal tissues are biphasic, provoking either detrimental or beneficial effects. • Chronic, long-term ethanol exposure or binge consumption causes severe damage in hippocampal neuronal and glial cells, usually accompanied by cell death. • Many of these deleterious effects are likely due to alcohol-induced generation of reactive oxygen species.

• Compensatory mechanisms involving changes in gene expression in the hippocampus usually parallel chronic, long-term ethanol exposure. • Conversely, acute, subtoxic exposure to ethanol triggers the transcriptional activation of antioxidant enzymes and heat-shock proteins, which protect hippocampal cells against oxidant stress and other insults. • These specific transcriptional activations likely underlie the preconditioning effects of ethanol.

SUMMARY POINTS • Ethanol exposure causes changes in gene expression in the hippocampus. • Chronic, long-term ethanol consumption affects neurotransmitter receptor functions and consolidation of hippocampal working memories. • Chronic, long-term ethanol exposure modulates neurotransmitter receptor gene expression in the hippocampus. • Exposure to acute low to moderate ethanol triggers the expression of different genes encoding for antioxidant enzymes and also heat-shock proteins. • Preconditioning effects of ethanol might be related to reinforcement of cellular antioxidant systems.

References Alfonso-Loeches, S., & Guerri, C. (2011). Molecular and behavioural aspects of the actions of alcohol on the adult and developing brain. Critical Reviews in Clinical Laboratory Sciences, 48, 19 47.

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49 Stress, Alcohol, and Hippocampal Genes 1

Jessica A. Baker1, Lu Lu2 and Kristin M. Hamre1 Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, United States 2Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States

LIST OF ABBREVIATIONS FDR Fkbp5 GABA Gpr88 GR HPA axis Il1r1 NF-KB NMDA PCR PTSD RI SNP Tac1 TLR WebGestalt

false discovery rate FK506 binding protein gamma-aminobutyric acid G protein-coupled receptor 88 glucocorticoid receptor hypothalamic-pituitary-adrenal axis interleukin 1 receptor type 1 nuclear factor kappa-light-chain-enhancer of activated B cells N-methyl-D-aspartic acid polymerase chain reaction post-traumatic stress disorder recombinant inbred single nucleotide polymorphisms tachykinin precursor 1 toll-like receptors WEB-based Gene SeT AnaLysis Toolkit

INTRODUCTION Alcoholism is an addictive disease dependent on the interactions of an individual’s genetic makeup and environment. In efforts to analyze the framework of this disease, alcohol abuse has been linked to several anxiety-related disorders due to its connection with stress. Stressful events have been found to increase an individual’s vulnerability to becoming dependent on alcohol (Spanagel, Noori, & Heilig, 2014). These stressors and their relationship with an individual’s genetic predisposition have led researchers to focus their studies on brain regions specific to the body’s stress response system. Areas such as the hippocampus, hypothalamic-pituitary-adrenal (HPA) axis, and amygdala have been shown to display molecular alterations

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00049-0

after alcohol exposure (Moonat & Pandey, 2012). Examining gene expression in these regions across multiple species and strains has allowed researchers to identify potential candidate genes underlying alcoholism; understanding their role in the relationship between alcohol consumption and stress could facilitate the development of novel therapeutic treatments for alcoholism. The hippocampus is a brain structure that is critical for a healthy stress response (Table 49.1) (Li et al., 2016). The hippocampus is highly sensitive to alcohol exposure, leading to numerous alterations, such as changes in anatomy and neurochemistry (Stankiewicz et al., 2015). The hippocampus is also susceptible to alterations caused by stress. Exposure to both acute and chronic stress have been found to cause changes in hippocampal neuron morphology and stress response pathways, showing a connection between the hippocampus and stress-related disorders (Kim, Pellman, & Kim, 2015). While advances have been made in understanding the impact of both stress and alcohol on alcohol use disorders (AUD), the complex relationship between these factors is not fully understood. Because stress and alcohol exposure have both been shown to individually have considerable harmful effects on the structure and function of the hippocampus, it is an ideal focal area to analyze how their interaction mediates gene expression changes. The goal of this chapter is to: (1) discuss the relevant genes and genetic pathways that underlie responses to ethanol, with or without stress, in the hippocampus; (2) discuss a bioinformatics strategy that we have successfully used to identify novel genetic pathways; and (3) to show the success of this methodology by

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474 TABLE 49.1

49. STRESS, ALCOHOL, AND HIPPOCAMPAL GENES

Key Facts of the Hippocampus

• The hippocampus is well-known as a vital region involved in learning, memory, and other cognitive functions. • The hippocampus receives inputs and delivers outputs, mainly through the entorhinal cortex, to multiple brain regions including the hypothalamus, amygdala, and septal nuclei. • The hippocampus is also involved in the stress response. In response to stress, glucocorticoids (stress hormones) bind to glucocorticoid receptors in the hippocampus which produces negative feedback to inhibit the continued release of glucocorticoids from the hypothalamic-pituitary-adrenal axis. • The hippocampus is highly sensitive to ethanol exposure and has been shown to be altered in alcoholics. The hippocampus is found in all mammals. Therefore, these facts apply between animals and humans.

discussing a specifically identified gene and its relevant molecular network. Initially, this chapter will review changes in hippocampal gene expression that occur following stress or alcohol individually. Gene expression was analyzed on a gene-by-gene basis in many early studies using techniques such as in situ hybridization, PCR, or various means of protein analyses. Current research focuses primarily on whole genome analyses using techniques such as microarrays and the more recently developed technique of RNAsequencing. We will focus on expression changes that are most relevant to the stress ethanol interaction. Behavioral and physiological responses to stress and/ or ethanol exposure, mediated by differing gene expression, can be studied using genetic reference panels of animals such as the BXD RI strains (Lu et al., 2008). Behavioral and expression differences in BXD mice have been extensively evaluated and the combination of all the data generated can be used to study genetic networks involved in complex phenotypes, such as the interaction of stress and alcohol (Jellen et al., 2012; Mozhui et al., 2010; Mulligan et al., 2012).

HIPPOCAMPAL GENE EXPRESSION CHANGES FOLLOWING EXPOSURE TO STRESS Because of the substantial role that the hippocampus plays in stress responses, changes in gene expression in this brain structure have been examined in a number of studies. The specific genes and genetic pathways are impacted by a number of critical factors, most notably the type of stressor used, the duration of stress exposure (i.e., acute versus chronic), and the time between the last stress exposure and tissue

collection (i.e., the length of the recovery time). To give an example, changes in hippocampal gene expression in mice exposed to acute restraint stress were examined and the profile of differentially-expressed genes were observed in a time-dependent manner with salient genetic pathways identified such as those mediating neurogenesis (Sannino et al., 2016). In contrast, studies by other groups have examined changes in hippocampal gene expression following exposure to chronic stress. The results of these studies demonstrated altered expression, in a study-dependent manner, of the NF-KB pathway including Gpr88 and Tac1, and neuroinflammatory responses such as the TLR pathway (Gray, Rubin, Hunter, & McEwen, 2014; Liu, Yang, & Zuo, 2010; Ubaldi et al., 2015; Wang et al., 2017). Similar expression differences can be observed when comparing across varying types of stress and experimental parameters (Bohacek, Manuella, Roszkowski, & Mansuy, 2015; Datson et al., 2012; Iwamoto, Morinobu, Takahashi, & Yamawaki, 2007; Li et al., 2013). One of the other critical factors that influences expression changes following stress exposure is the genetic make-up of the individual. This has been elegantly examined in the study by Andrus et al. (2012) in which hippocampal gene expression is examined in several rat strains as well as populations of selectivelybred rats following restraint stress. The results demonstrated that there were strain-specific expression changes and, in fact, the majority of differentiallyexpressed genes showed little overlap among the different populations (Andrus et al., 2012). Similar results were found using a mouse model (Tsolakidou et al., 2008). While the earlier studies highlight the differences in expression observed between studies, there are also several categories of genetic pathways that have been found on a more consistent basis. The most common examples are alterations in genes associated with various neurotransmitter systems and synaptic transmissions, including GABA, prolactin, and NMDA (Gray et al., 2014; Harada, Yamaji, & Matsuoka, 2008; Liu et al., 2010; Ubaldi et al., 2015). Studies in animal models provide a starting point to examine expression changes in human populations. However, exposure to stress is typically observed in conjunction with other neuropsychiatric disorders, including depression and anxiety, and it is, therefore, difficult to separate which effects are specific to stress exposure. The only human population where stress is the predominant feature is for individuals with post-traumatic stress disorder (PTSD). However, to our knowledge, global gene expression changes have not been examined in the hippocampus in this population.

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HIPPOCAMPAL GENE EXPRESSION CHANGES FOLLOWING EXPOSURE TO ETHANOL Changes in gene expression following alcohol exposure have been examined in a number of brain structures. However, most of the expression changes have been examined in other structures, specifically those that are more strongly associated with alcohol addiction and withdrawal, and, therefore, there are only a limited number of papers that examine expression changes in the hippocampus. Similar to the scenario observed following stress exposure, the results obtained from these experiments are influenced by a number of factors including the dose of alcohol, the duration of the alcohol exposure (acute vs chronic), the type of administration paradigm, and length of time after the last exposure and collection of the tissue (i.e., whether or not withdrawal was experienced). While a number of differences have been found, there are several genes and/or genetic networks that have been consistently found using different paradigms. The majority of studies have examined changes following chronic alcohol exposure. Some of the most common pathways found were those involved in synaptic plasticity, signaling pathways, and neurotransmitter-related pathways, including GABA and dopamine (Sinirlioglu, Coskunpinar, & Akbas, 2017; Stankiewicz et al., 2015). Examination of gene expression changes across time following ethanol withdrawal also highlighted the importance of alterations in the expression of neuroinflammatory genes (Smith et al., 2016). Several additional studies have identified other genes, including those related to circadian rhythms and neurotransmitter-related genes (Arlinde et al., 2004; Enoch et al., 2012; Kimpel et al., 2007; Lee et al., 2010; Mulligan et al., 2012; Rodd et al., 2007; Saito, Smiley, Toth, & Vadasz, 2002; Witt et al., 2013). It is interesting to note that there is considerable overlap in the differentially expressed genes observed after exposure to stress and those found after alcohol exposure. While, perhaps, this overlap is unsurprising given the critical nature of these processes in brain function, it also points to possible molecular similarities in the response of the hippocampus to exposure to each factor. Examination of gene changes in the hippocampus of human alcoholics has been conducted by several groups (Bazov et al., 2013; Enoch, Zhou, Kimura, 2012; Enoch et al., 2013; Jin et al., 2011; McClintick et al., 2013; Enoch, Baghal, Yuan, & Goldman, 2013; Murano, Koshimizu, Hagihara, & Miyakawa, 2017; Zhou, Enoch, & Goldman, 2014). It is interesting to note that

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there is generally a strong concordance between the differentially expressed genes found in human and animal models. Specific genetic pathways include those found related to GABA and other neurotransmitters. Of particular interest are the genes found in the study by McClintick (2013) which identified a number of differentially expressed genes that function in stress responses including genes such as Il1r1, again providing a possible mechanism of overlap between the molecular responses to stress and alcohol exposure, although it unclear whether exposure to both alters gene expression differently than individual exposure (McClintick et al., 2013).

HIPPOCAMPAL GENE EXPRESSION CHANGES FOLLOWING EXPOSURE TO THE COMBINATION OF STRESS AND ETHANOL The complex relationship between stress and alcohol and its role in alcohol use has yet to be elucidated. Most studies examining hippocampal gene expression have looked at changes after exposure to stress alone or ethanol alone. Though many studies have examined stress responses in relation to ethanol exposure, hippocampal gene expression changes after a combination of exposure to ethanol and stress have not been thoroughly investigated. A previous microarray study by our laboratory, identified significantly differentially expressed genes in the hippocampus of BXD and their parental C57BL/6J and DBA/2J strains after exposure to acute stress, acute ethanol, or a combination of both acute stress followed by acute ethanol compared to nonstressed, saline controls (Baker et al., 2017). We found unique genes were differentially expressed after exposure to stress, ethanol, or the combination of both, showing that changes in gene expression after exposure to stress are modulated by subsequent exposure to ethanol. In this study, one of the genes identified was Fkbp5, a member of the immunophilin protein family which encodes for a GR-binding protein (Qiu et al., 2016). Fkbp5 was significantly differentially expressed after exposure to combined stress and ethanol, but not acute stress or acute ethanol (Fig. 49.1). Fkbp5 is highly expressed in the brain, especially in the hippocampus where it influences GR sensitivity (Scharf, Liebl, Binder, Schmidt, & Muller, 2011). Fkbp5 has been previously shown to be involved in the stress response, as well as in alcohol consumption in human and animal models (Green, Nottrodt, Simone, & McCormick, 2016; McClintick et al., 2013; Nylander et al., 2016; Touma et al., 2011). Moreover, the Fkbp5 genotype is critical for

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FIGURE 49.1 Differential mean expression of Fkbp5 after exposure to acute stress, acute ethanol, and the combination of both compared to control animals. The graph shows the mean difference ( 6 standard error of the mean; x-axis), compared to saline-treated nonstressed control animals, in hippocampal expression of Fkbp5 after experimental treatment (y-axis) ( 5 p # 0.01, q # 0.1). The red bar shows difference in expression of Fkbp5 after acute stress alone. The green bar shows difference in expression of Fkbp5 after exposure to acute ethanol alone. The blue bar shows difference in expression of Fkbp5 after combined acute stress and acute ethanol. Unpublished data from GeneNetwork.org.

mediating the interaction between early life stress and level of alcohol consumption (Lieberman et al., 2016). Therefore, in the present review, we aim to further examine Fkbp5 through an unbiased bioinformatic analyses using the tools publicly available at GeneNetwork.org. These results serve as an example of steps and tools available to analyze candidate genes from large microarray studies and identify gene networks involved in alcohol and stress interactions and demonstrate the utility of this approach in reverse translational studies. Hippocampal expression of Fkbp5 was measured across the parental and 28 BXD strains using the Illumina v6.1 microarray. Fkbp5 expression is variable in naı¨ve animals with a 3.1-fold difference between the highest and lowest values across the BXD lines and a 2.3-fold difference found between the highest and lowest values across the BXD lines exposed to combined acute stress and acute ethanol (Fig. 49.2). The amount and direction of differential expression after all three treatment groups is variable across BXD strains (Fig. 49.3). Fkbp5 was examined for polymorphisms using the tools on GeneNetwork.org. Polymorphisms are genetic variations that can be present in the coding regions or regulatory regions of the gene, that is, exon or intron, respectively. Analyses revealed that Fkbp5 does contain SNPs in the intron region of the gene, but not in the exon region. Although SNPs were not present in the coding region of the gene, SNPs located on the intron have the potential to effect transcription and methylation processes. Phenotype analyses were conducted on GeneNetwork.org to identify phenotypes that significantly correlated (p , 0.05) with Fkbp5 expression in the hippocampus. Multiple, anxiety-related phenotypes were significantly correlated with Fkbp5

including percent of time in close arms of an elevated plus maze and effects of chronic variable stress on freezing to a fear-conditioned tone (Carhuatanta, Shea, Herman, & Jankord, 2014; Philip et al., 2010). Fkbp5 expression was also significantly correlated with various ethanol-related phenotypes such as motor coordination on the rotarod after ethanol exposure, ethanol consumption using drinking in the dark method, and ethanol intake using a 2-bottle choice test (Philip et al., 2010). Finally, expression of Fkbp5 was correlated with anxiety-related and ethanol-related phenotypes in the same mice used for expression analyses, such as time in the open quadrants of the elevated zero maze after exposure to both restraint stress and an ethanol injection (Cook et al., 2015). Gene correlations were performed on GeneNetwork.org to identify genes that either participate in the same pathway as Fkbp5 or overlapping pathways. The following criteria were used to identify these co-varying genes: expression greater than 7.0 in the hippocampus, significant correlation with Fkbp5 expression (p , 0.05), and literature correlation greater than 0.5 according to previously published reports (Urquhart et al., 2016). Based on these criteria, approximately 1,400 genes were identified to be significantly correlated with Fkbp5. We previously reported fifteen of these genes to be significantly differentially expressed after exposure to acute stress, acute ethanol, or a combination of both (Table 49.2) (Baker et al., 2017). To further examine Fkbp5 and its significantly correlated genes in the hippocampus, WebGestalt (www.webgestalt.org/option.php) was used to preform functional enrichment analyses. Gene Ontology and Mammalian Phenotype analyses identified numerous significantly over-represented categories relating to anxiety, learning, and cell death (Table 49.3).

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FIGURE 49.2

Variable expression of Fkbp5 in the hippocampus for the parental strains and 28 BXD lines. The x-axis denotes the strain while the y-axis denotes the mean expression given in a LOG2 scale. Each bar shows the mean expression values 6 standard deviation. Fkbp5 Record ID: ILM2190048. Fkbp5 expression across two parental and 28 BXD strains in (A) naı¨ve animals (B) animals exposed to a combination of acute stress and acute ethanol. Unpublished data from GeneNetwork.org.

FIGURE 49.3 Variable and differential expression of Fkbp5 in the hippocampus in BXD strains after exposure to acute stress, acute ethanol, and the combination of both compared to control animals. The x-axis denotes the strain while the y-axis denotes the mean differential expression of Fkbp5 in the hippocampus after treatment as compared to the saline-treated nonstressed control group. For each strain the bars show difference in expression after exposure to stress (red), ethanol (green), or the combination of stress and ethanol (blue). Unpublished data from GeneNetwork.org.

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TABLE 49.2 Genes Significantly Correlated With Fkbp5 That Have Also Been Previously Shown to be Significantly Differentially Expressed After Exposure to Ethanol, Stress, or the Combination of Both in the Hippocampus of Adult Mice Symbol

Name

Previous group

Aif1

Allograft inflammatory factor 1

Ethanol alone

Cklf

Chemokine-like factor

Combination

Ear2

Eosinophil-associated, ribonuclease A family, member 2

Ethanol alone, Combination

Eif3i

Eukaryotic translation initiation factor 3, subunit 1

Ethanol alone

Errfi1

ERBB receptor feedback inhibitor 1

Combination

Foxn3

Forkhead box N3

Combination

Homer1

Homer scaffolding protein 1

Ethanol alone

Limk2

LIM motif-containing protein kinase 2

Combination

Mef2a

Myocyte enhancer factor 2 A

Ethanol alone

Ntng2

Netrin G2

Ethanol alone

Serinc3

Serine incorporator 3

Ethanol alone

Slc6a1

Solute carrier family 6, member 1

Ethanol alone

Thrsp

Thyroid hormone responsive

Ethanol alone

Ttc3

Tetratricopeptide repeat domain 3

Ethanol alone

Ttll7

Tubulin tyrosine ligase-like family, member 7

Stress alone, Ethanol alone

Previously reported genes that are differentially expressed after exposure to ethanol alone, stress alone, or the combination of both that are also significantly correlated with Fkbp5. Genes were previously reported in Baker et al. (2017). Data for the table was generated using tools available at GeneNetwork.org.

TABLE 49.3 genes

Top Over-represented Categories in Gene Ontology and Mammalian Phenotypes for Fkbp5 and its significantly correlated

Gene ontology ID

Category

# of genes

p

FDR

0022008

Neurogenesis

148

1.35E-13

2.67E-11

0030182

Neuron differentiation

125

5.21E-12

8.69E-10

0031175

Neuron projection development

90

3.16E-10

1.92E-08

0009725

Response to hormone

98

1.53E-08

2.47E-05

0033554

Cellular response to stress

160

1.36E-09

1.92E-06

0007610

Behavior

74

2.51E-11

3.91E-09

0009605

Response to external stimulus

169

6.76E-11

1.03E-08

0045786

Negative regulation of cell cycle

53

2.41E-09

2.84E-07

0043068

Positive regulation of programmed cell death

83

3.77E-15

8.94E-13

0043065

Positive regulation of apoptotic processes

83

9.30E-10

1.16E-07

0097193

Intrinsic apoptotic signaling pathway

46

1.00E-11

1.65E-09

0031399

Regulation of protein modification process

141

9.66E-11

1.40E-08

0017148

Negative regulation of translation

28

2.31E-10

3.14E-08

1932532

Negative regulation of intracellular signal transduction

58

5.24E-10

6.75E-08 (Continued)

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479

MINI-DICTIONARY OF TERMS

TABLE 49.3

(Continued)

Mammalian Phenotype ID

Category

# of genes

p

FDR

0000313

Abnormal cell death

165

3.15E-09

2.50E-05

0001648

Abnormal apoptosis

142

2.13E-07

8.46E-04

0008942

Abnormal induced cell death

196

6.26E-05

2.22E-02

0000352

Decreased cell proliferation

338

7.40E-05

2.35E-02

0002065

Abnormal fear/anxiety-related behavior

54

8.13E-06

5.86E-03

0001362

Abnormal anxiety-related response

50

9.98E-06

6.58E-03

0002572

Abnormal emotion/affect behavior

80

2.94E-06

3.34E-03

0002557

Abnormal social/conspecific interaction

284

6.72E-05

2.22E-02

0012689

Abnormal adrenal gland weight

4

4.87E-04

8.39E-02

0002063

Abnormal learning/memory/conditioning

80

4.94E-05

2.22E-02

0014114

Abnormal cognition

80

5.29E-05

2.22E-02

0001463

Abnormal spatial learning

36

2.42E-04

5.48E-02

0002800

Abnormal short-term object recognition memory

47

4.84E-04

5.48E-02

0004166

Abnormal limbic system morphology

84

4.84E-04

8.39E-02

0004768

Abnormal axonal transport

10

4.38E-06

3.78E-03

0002207

Abnormal long-term potentiation

36

4.36E-05

2.16E-02

0002206

Abnormal CNS synaptic transmission

77

6.51E-05

2.22E-02

0008415

Abnormal neurite morphology

47

2.48E-04

5.48E-02

0004811

Abnormal neuron physiology

67

5.62E-04

9.49E-02

Top significant Gene Ontology and Mammalian Phenotypes correlated with Fkbp5 and its significantly correlated genes in the hippocampus. A p-value of less than 0.05 and a false discovery rate (FDR) less than 0.1 are considered significant. Correlated genes were identified using the publically accessible GeneNetwork. org. Gene Ontology and Mammalian Phenotype data were identified using tools on the publically accessible www.WebGestalt.org. More information on the categories can be found using the ID number at www.WebGestalt.org.

CONCLUSIONS Alcohol and stress are complex, interacting phenotypes. While exposure to each alone alters expression of some of the same genes and genetic pathways, it is clear that exposure to both variables alters hippocampal gene expression in unique ways that are not simply a combination of the effects of each individual factor. Recent research has emphasized that to fully understand these complex phenotypes involves identifying critical genetic networks rather than individual genes (Wolen & Miles, 2012). Bioinformatic analyses provide an excellent means for identifying these networks particularly when using a significant gene as a starting point in building this network. The appropriateness of our bioinformatic approach is shown by the success in identifying genes that have been previously identified in human populations and demonstrates its utility in reverse translational analyses. These analyses

further provide the starting point for subsequent studies on this network to further understand how Fkbp5 plays a role in stress’s ability to influence alcohol addiction.

MINI-DICTIONARY OF TERMS Hippocampus A part of the limbic system in the temporal lobe of the central nervous system. Stress An environmental stimulus that results in the disruption of the body’s natural homeostasis and produces physiological or biological responses. Hypothalamus-Pituitary-Adrenal (HPA) Axis Consists of three main endocrine glands that respond to stress via complex feedback interactions. BXD Recombinant Inbred (RI) Mice These strains are derived by crossing C57BL/6J and DBA/2J inbred strains, followed by 20 generations of inbreeding of the resulting progeny. Glucocorticoids Glucocorticoids are a class of corticosteroids that are synthesized in the adrenal cortex and can have multiple effects such as immune, metabolic, developmental, arousal, and cognition.

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49. STRESS, ALCOHOL, AND HIPPOCAMPAL GENES

SUMMARY POINTS • Exposure to ethanol or stress individually causes gene expression changes in multiple brain regions, including the hippocampus. There are overlaps in the differentially expressed genetic pathways between these two factors. • Examination of gene expression in conjunction with bioinformatics analyses are excellent tools to identify candidate genes mediating responses to alcohol and stress. Recent studies have just begun to identify gene expression changes after exposure to the combination of ethanol and stress with the goal of understanding the molecular mechanisms underlying this interaction and the role of this interaction in alcohol addiction. • To examine the interaction of ethanol and stress and its effect on hippocampal gene expression, it is important to look at genotype as a variable. • Using bioinformatic analysis of differentially expressed genes in the BXD recombinant inbred mouse lines, our lab has found Fkbp5 to be significantly differentially expressed in the hippocampus across BXD strains after exposure to the combination of restraint stress and ethanol exposure, but not after restraint stress or ethanol exposure alone. • The Fkbp5 gene has previously been shown to be involved in alcohol exposure and the stress response in human studies demonstrating the reverse translational applicability of this methodology.

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C H A P T E R

50 Genes and Alcoholism: Taste, Addiction, and Metabolism Arturo Panduro1,2, Ingrid Rivera-In˜iguez1,2, Omar Ramos-Lopez1,2 and Sonia Roman1,2 1

Department of Molecular Biology in Medicine, Civil Hospital of Guadalajara “Fray Antonio Alcalde”, Guadalajara, Mexico 2Health Sciences Center, University of Guadalajara, Guadalajara, Jalisco, Mexico

LIST OF ABBREVIATIONS ACSS ADH ALDH ANKK1 BRS CO2 CYP2E1 DRD2 FFA MEOS NAD 1 NADH NA PROP PTC RDS SNPs TCA TRPV1 VS VTA VLDL-C

These SNPs provide protective and risk alleles which, combined with environmental factors, have been related to the susceptibility towards alcoholism. Furthermore, these genes also influence food choices in susceptible individuals, increasing the risk for obesity and nutrition-related chronic diseases in alcoholics. Sociocultural factors may also interact with genes influencing alcohol addiction.

acyl-CoA synthetase short chain family member alcohol dehydrogenase aldehyde dehydrogenase ankyrin kinase domain containing 1 brain reward system carbon dioxide cytochrome P4502E1 dopamine D2 receptor free fatty acids microsomal ethanol oxidizing system nicotinamide adenine dinucleotide oxidized nicotinamide adenine dinucleotide reduced nucleus accumbens 6-n-propylthiouracil phenylthiocarbamide reward deficiency syndrome single nucleotide polymorphisms tricarboxylic acid cycle transient receptor potential cation channel subfamily V member 1 ventral striatum ventral tegmental area very- low density cholesterol

TASTE AND ALCOHOLISM

INTRODUCTION Alcohol consumption and addiction in humans involve the interaction between several biological functions including taste, flavor perception, brain reward systems, and alcohol detoxification pathways. This chapter focuses on several genes encoding single nucleotide polymorphisms (SNPs) that show a differential distribution among populations worldwide. Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00050-7

Bitter taste is a sensory factor that influences drinking patterns (Tepper et al., 2009). Ethanol elicits bitterness, burning, and stinging sensations in the oral cavity (Nolden, McGeary, & Hayes, 2016). Hence, variations in the perception of ethanol intensity account for differences in alcohol consumption. Synthetic compounds such as 6-n-propylthiouracil (PROP) and phenylthiocarbamide (PTC) are used to phenotypically classify individuals in nontasters and tasters (Tepper et al., 2009). Tasters are classified as medium tasters and supertasters. Nontasters have a higher preference and more frequent consumption of alcoholic beverages than tasters (Duffy et al., 2004b), as well as an association with a history of alcoholism (DiCarlo & Powers, 1998). Conversely, supertasters consume less beer than nontasters when they first started drinking beer on a regular basis, suggesting that supertasters are protected against alcoholism (Intranuovo & Powers, 1998). The TAS2R proteins expressed by the taste receptor cells of the tongue and palate epithelia mediates bitter-

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50. GENES AND ALCOHOLISM: TASTE, ADDICTION, AND METABOLISM

taste perception. These bitter-taste receptors are seventransmembrane, G-protein-coupled, receptor proteins encoded by intronless genes (Feeney, O’Brien, Scannell, Markey, & Gibney, 2011). One example is the TAS2R38 gene related to the perception of glucosinolates, bitter-tasting compounds found in the Brassica sp. (Kim et al., 2003) and PTC/PROP compounds. Three functional TAS2R38 polymorphisms (A49P, V262A, and I296V) may explain up to 85% of the variance in PTC taste sensitivity (Drayna, 2005; Kim et al., 2003) which, in turn, correlate with ethanol bitterness (Allen, McGeary, & Hayes, 2014; Hayes, Feeney, & Allen, 2013). Moreover, PAV and AVI are two of the most common TAS2R38 haplotypes which have been related to the greatest (tasters) and lowest (nontasters) sensitivity to PTC/PROP bitterness, respectively (Bufe et al., 2005; Kim & Drayna, 2005). PAV homozygotes perceive greater bitterness from ethanol on circumvallate papillae than heterozygotes and AVI homozygotes (Nolden et al., 2016). PAV homozygotes consume lower amounts of alcohol compared with PAV/AVI heterozygotes and AVI homozygotes (Duffy, Peterson, & Bartoshuk, 2004a; Hayes et al., 2011; Wang et al., 2007). Additionally, two novel TAS2R38 haplotypes were recently reported in the Mexican population (PAI and AVV) (Ramos-Lopez et al., 2015) which confer a taster and nontaster phenotype, respectively, as demonstrated by functional expression analyses (Bufe et al., 2005). AVV nontaster haplotype was the most prevalent among Mexicans and was associated with alcohol intake (Ramos-Lopez et al., 2015). Other TAS2R bitter-taste genes are implicated in alcoholism (Edenberg & Foroud, 2006). A missense mutation in the TAS2R16 gene (K172N) was associated with risk for alcohol dependence and alcohol-drinking scores in African-Americans (Hinrichs et al., 2006; Wang et al., 2007). This variant is located in the ligand-binding domain altering receptor sensitivity to the bitter compounds, beta-glucopyranosides (Hinrichs et al., 2006). Moreover, the N259S polymorphism located within the TAS2R13 gene showed significant association with overall intensity for an ethanol whole-mouth solution (Allen et al.) and with measures of alcohol consumption (Dotson, Wallace, Bartoshuk, & Logan, 2012). Additionally, three SNPs within the transient potential cation channel subfamily V member 1 (TRPV1) gene, which encodes a polymodal nociceptor (also denoted as vanilloid receptor 1) were associated with higher ratings of ethanol sensations, such as burning and stinging (Allen et al., 2014) (Table 50.1, upper section).

ALCOHOL ADDICTION The brain reward system (BRS) modulates survival behaviors such as food intake and sexual activity.

Several psychoactive substances, such as alcohol (Ma & Zhu, 2014), also target the BRS. The brain reward circuitry is constituted by the ventral tegmental area (VTA), nucleus accumbens (NA), ventral striatum (VS), bed nucleus of the stria terminalis, hippocampus, and amygdala. In the BRS, dopamine is the main neurotransmitter involved in motivation and reinforcement (Tupala & Tiihonen, 2012). Alcohol intake stimulates the release of dopamine, mainly in the NA (Boileau et al., 2003). Consequently, increases in dopamine regulate the rewarding effects of alcohol and may promote drinking (Di Chiara, 1997). Alterations in dopaminergic neurotransmission associated with dysfunctional reward processing, impaired reinforcement learning, and increased sensitivity to alcoholassociated stimuli lead to addictive behaviors, such as alcohol seeking and excessive consumption (Charlet, Beck, & Heinz, 2013). Changes in striatal dopamine levels in response to alcohol intake may be neurobiological markers of vulnerability to alcohol use disorders (AUD) (Setiawan et al., 2014). Five different receptor subtypes that belong to the large G-protein-coupled, receptor superfamily mediate dopamine activity. Nevertheless, dopamine D2 receptor (DRD2) encoded by the DRD2 gene is a key regulator of dopamine actions (Mi et al., 2011). Thus, differences in the relative amount or functional capacity of DRD2 affect the subjective pleasure associated with positive rewards (Wise, 2006). One of the most widely researched polymorphisms is the DRD2/ ANKK1 Taq1A restriction fragment length polymorphism, which resides in exon 8 of a neighboring gene, ankyrin repeat, and kinase domain containing 1 (ANKK1), located 10 kb downstream from the DRD2 gene (Neville, Johnstone, & Walton, 2004). This functional variant causes a Glu713Lys substitution within the 11th ankyrin repeat of the ANKK1 gene (Table 50.1, middle section). In vivo human studies have found an altered DRD2-binding capacity and density in the striatum of TaqA1 allele carriers (Jo¨nsson et al., 1999; Ritchie & Noble, 2003). Interestingly, some studies have supported the putative association of the TaqA1 polymorphism with alcoholism (Munafo`, Johnstone, Welsh, & Walton, 2005) and risk for alcohol dependence (Wang, Simen, Arias, Lu, & Zhang, 2013). Additionally, the TaqA1A1 genotype was recently associated with heavy alcohol-drinking patterns in a Mexican-Mestizo population (Panduro et al., 2017a). Furthermore, the TaqA1 allele was associated with increased mortality over a 10-year period in alcohol-dependent individuals (Berggren et al., 2010). The frequency of the TaqA1 allele shows variations among populations which, in turn, may help to partially explain some of the differences in alcohol-drinking habits reported worldwide. The highest frequencies of

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TABLE 50.1

Genomic Data of Gene Polymorphisms Involved in Alcoholism

Gene Name

Locus

Gen size (base pair)

Polymorphism

Reference sequence (rs)

Risk variant

7q34

1143

A49P

rs713598

AVI haplotype

V262A

rs1726866

I296V

rs10246939

BITTER TASTE RECEPTOR PROTEINS Gen ID: 5726 Taste 2 receptor member 38, TAS2R38

Gen ID: 50833

7q31.32

996

K172N

rs846664

K allele

12p13.2

1637

N259S

rs1015443

S allele

17p13.2

43,996

A/G intron variant

rs224547

A allele

Taste 2 receptor member 16, TAS2R16 GEN ID: 50838 Taste 2 receptor member 13, TAS2R13 Gen ID: 7442 Transient potential cation channel subfamily V member 1, TRPV1

A/C intron variant rs4780521

C allele

C/T intron variant rs161364

C allele

Glu713Lys (TaqA1/A2)

rs1800497

TaqA1 allele

C957T

rs6277

C allele

2 141C Ins/Del

rs1799732

2 141C/Del allele

A1385G

rs6276

G allele

Arg48His ( 1/ 2)

rs1229984



1 allele

12q24.12 43,099

Glu487Lys ( 1/ 2)

rs671



1 allele

10q26.3

2 1053 C/T ( C1/ C2)

rs2031920



C2 allele

DOPAMINE RECEPTORS Gen ID: 1813

11q23.2

65,685

Dopamine receptor D2, DRD2

ALCOHOL-METABOLIZING ENZYMES Gen ID: 125

4q23

15,056

Alcohol dehydrogenase 1B (class I), beta polypeptide, ADH1B GEN ID: 217 Aldehyde dehydrogenase 2 family (mitochondrial), ALDH2 GEN ID: 1571

11,754

Cytochrome P450 family 2 subfamily E member 1 CYP2E1

Data obtained at NCBI GenBank: Accessed August 2017. Bp: base pairs; Rs: Reference sequence.

this risk allele documented to date have been found in indigenous populations from Mexico, including Mayas (70%), Nahuas, and Huicholes (65% and 67%, respectively) and Pima Indians (63%) (Panduro et al., 2017a). In contrast, Asian (Chinese, Japanese, Vietnamese) and African (Nigerian, Gambian, Kenyan) populations present a 40% frequency of this allele. In contrast, certain European populations have some of the lowest frequencies (about 20%) described across the globe including Britain and Italy (1000 Genomes Project Consortium, 2015).

Other polymorphisms within the DRD2 gene have been implicated in alcohol-related phenotypes. The Callele and C/C genotype of the synonymous C957T polymorphism showed a decreased DRD2-binding and strong association with alcohol dependence (Swagell et al., 2012). A significant association between a deletion polymorphism 141C Ins/Del in the promoter region of the DRD2 gene and early onset of alcohol dependence was found (Grzywacz et al., 2012). Another SNP located in exon 8 of the DRD2 gene (A1385G) correlated with the presence of alcohol withdrawal syndrome with

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486 TABLE 50.2

50. GENES AND ALCOHOLISM: TASTE, ADDICTION, AND METABOLISM

Genetic Susceptibility Profiles Associated With Alcoholism Phenotypic outcome

Genes

Risk profile

Protective profile

Alcohol bitterness perception

Nontaster

Taster

TAS2R38

AVI or AVV haplotype carriers do not perceive greater ethanol bitterness

PAV or PAI haplotype carriers perceive greater ethanol bitterness

Alcohol addiction

Addictive behavior

Nonaddictive behavior

DRD2/ANKK1

DRD2/ANKK1 Taq A1 have a higher consumption of alcohol and unhealthy foods

DRD2/ANKK1 Taq A2 have a moderate consumption of alcohol and unhealthy foods

Alcohol metabolism Lower acetaldehyde levels

Higher acetaldehyde levels

Alcohol dehydrogenase (ADH) ADH1B

ADH1B 1

ADH1B 2

Lower enzymatic activity

Higher enzymatic activity Unpleasant alcohol consumption related symptoms and signs

Aldehyde dehydrogenase (ALDH) ALDH2

ALDH2 1

ALDH2 2

Active form

Inactive form

Higher acetaldehyde turnover to acetate

Lower acetaldehyde turnover to acetate Unpleasant alcohol consumption related symptoms and signs

Cytochrome P450 (CYP2E1) CYP2E1

CYP2E1 C2

CYP2E1 C1

Higher acetaldehyde turnover to acetate

Lower acetaldehyde turnover to acetate

seizures (Grzywacz et al., 2012). Furthermore, DRD2 haplotypes have been associated with some alcoholrelated phenotypes in distinct populations (Kraschewski et al., 2009) (Table 50.1, middle section).

Influence of Alcoholism-Related Taste and Addiction Genes With Food Choice Taste and addiction genetic signatures that confer high risk for alcoholism also affect food choices. This scenario may predispose people with these genetic factors to obesity and chronic diseases due to the high consumption of unhealthy foods and alcohol abuse. The bitter taste related to alcohol consumption also influences the intake of cruciferous vegetables (Bartoshuk, Duffy, & Miller, 1994). Studies in children show that PROP tasters do not prefer bitter, cruciferous vegetables. In contrast, children with TAS2R38 nontaster genotypes consume more energy from sugary foods and beverages (Joseph, Reed, & Mennella, 2016). Moreover, PROP nontasters seem to have a greater body composition and higher

preference for fatty foods (Keller, 2012). Other genes such as CD36 could predispose to increased fat consumption in African populations (Keller, 2012). It is not clear whether TAS2R38 directly affects body composition (Ortega et al., 2016). Gender, age, ethnicity, and social, emotional, and cognitive factors could be interacting with genetics. Furthermore, disturbances in BRS trigger unhealthy food consumption. Lack of self-control is common in people with addiction disorders (MacKillop, 2013), who could also be at high risk for being overweight or obese. Similarly, emotional alterations influence addictive behaviors. A western type of diet provides small, short-term rewarding feelings to a greater degree than healthy eating, thus, promoting an imbalance of gut bacteria that exacerbate negative emotions (Panduro, Rivera-In˜iguez, Sepulveda-Villegas, & Roman, 2017b). Furthermore, overeating is often an attempt to reduce negative emotions (Gianini, White, & Masheb, 2013; Gibson, 2012). Consumption of high-energy, palatable foods stimulate dopamine release in the BRS and influence motivated behaviors as much as alcohol

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ALCOHOL METABOLISM GENES

and drug use (Russo & Nestler, 2013; Urban & Martinez, 2012). However, it has been shown that people with addictive behavior experience reward deficiency syndrome (RDS) (Blum et al., 1996). Hence, food could reinforce the repetitive behavior among alcoholics by affecting appetite control (Spoelder, Tsutsui, Lesscher, Vanderschuren, & Clark, 2015). DRD2/ANKK1 TaqA1/A2 polymorphism is associated with addictive behaviors, psychiatric and personalities disorders, and cognitive impairments (Gelernter et al., 2006; Noble, 2000; Richter et al., 2015). Emerging research has pointed out that eating disorders are related to DRD2 expression (Genis-Mendoza, Nicolini, Tovilla-Zarate, Lopez-Narvaez, & Gonzalez-Castro, 2016). Moreover, carriers of A1 allele consume more energy-dense foods (carbohydrates and fast food), present overconsumption episodes, and loss of food control when compared with TaqA2 carriers (Epstein et al., 2007). In contrast, in some populations the A1/A1 genotype is not frequent and binge episodes are more influenced by emotional feelings, especially in females (Davis et al., 2012). Nonetheless, these rewarding food behaviors appear to promote weight gain, and the presence of the A1 allele is related to weight gain and body fat percentage (Chen et al., 2012). Notably, the presence of A1 allele interferes with the body’s ability to lose weight. A1 carriers present lower reductions in body composition and lower adherence while dieting when compared with A2 carriers (Roth, Hinney, Schur, Elfers, & Reinehr, 2013).

ALCOHOL METABOLISM GENES Excessive alcohol consumption is associated with chronic diseases such as cancer, diabetes, cardiovascular, liver, and neuropsychiatric diseases (Rehm & Shield, 2013). Physiologically, alcohol abuse is influenced by impairments in alcohol metabolism. Less than 10% of alcohol is excreted in breath, sweat, and urine. The rest is oxidized mainly in the liver (B 90%) and in other organs, such as stomach, muscle, kidneys and brain. The first-pass metabolism occurs by action of alcohol dehydrogenase (ADHσ) in the small intestine. Alcohol enters the hepatocytes by passive diffusion, which depends on blood alcohol concentration (Cederbaum, 2012). Alcohol is oxidized in the cytosol by ADH1B forming a toxic by-product, acetaldehyde. This reaction requires NAD 1 as a cofactor that is reduced to NADH. NAD 1 availability limits this reaction. Acetaldehyde is converted to acetate by ALDH2, and again NAD 1 is reduced to NADH. Acetate can be further oxidized to carbon dioxide (CO2) in the heart, skeletal muscle, and brain, or converted to Acetyl-CoA by Acyl-CoA synthetase short chain family member (ACSS) consuming ATP. Acetyl-

487

CoA can be used for the synthesis of free fatty acids, very low-density cholesterol (VLDL-C), and ketone bodies, or enter the Krebs cycle (Cederbaum, 2012). An illustrative summary of the main metabolic pathways involved in alcohol oxidation is shown in Fig. 50.1 (Zakhari, 2006). However, alcohol metabolism differs according to enzymatic isoforms (Edenberg, 2007). Polymorphic variations among alcohol metabolizing-enzyme genes ADH, ALDH, and CYP2E1 influence alcohol rate metabolism (Table 50.1, lower section). As shown in Figs. 50.1A and B, two metabolic profiles are described which confer a risk or protective profile, respectively. Furthermore, these isoenzymes are present in distinct proportions according to ethnicity (Zuo et al., 2013). For example, the Arg48His polymorphism in the ADH1B gene generates two allelic functional variants referred as ADH1B 1 (Arg48) and ADH1B 2 (His48). ADH1B 1 is more prevalent among Caucasians (Eng, Luczak, & Wall, 2007) than in other populations. In contrast, ADH1B 2 carriers show a higher enzymatic activity (40 100-fold increase), resulting in higher conversion to acetaldehyde, which confers unpleasant symptoms such as flushing, rhinitis, and vomiting, thus reducing the desire to drink (Cook et al., 2005). Therefore, ADH1B 2 is considered a protector allele against alcohol consumption. This variant is predominant among north Asian populations (Japanese, Chinese and Koreans), followed by middle Easters, and is rare among native Mexicans (Roman, ZepedaCarrillo, Morena-Luna, & Panduro, 2013). This polymorphism has recently been associated with high risk of mortality in men (Almeida et al., 2017). Furthermore, the mitochondrial enzyme ALDH2 also presents functional polymorphisms that affect drinking behavior. Glu487Lys in exon 12 has been studied worldwide, showing two variants, ALDH2 1 and ALDH2 2 (Ehlers, Liang, & Gizer, 2012). ALDH2 2 has been referred to as a protective variant against alcoholism in Asian populations due to its low or null activity, which promotes lower acetaldehyde turnover to acetate. Therefore, manifestations of unpleasant alcohol consumption appear, and alcohol consumption ceases. In contrast, in populations with Mexican-Amerindian ancestry, the protective allele is absent (GordilloBastidas et al., 2010; Roman et al., 2013). An alternative microsomal pathway is activated at high alcohol blood concentrations by the CYP2E1 enzyme producing ROS, toxic, and carcinogenic compounds. The -1053 C/T polymorphism encoded in the CYP2E1 gene generates CYP2E1 C1 and CYP2E1 C2 allelic variants. Carriers of C2 allele show an increased enzymatic activity that rapidly converts ethanol into acetaldehyde. The highest prevalence in the world of the C2 allele has been reported in native Mexican Huicholes (Gordillo-Bastidas et al., 2010).

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50. GENES AND ALCOHOLISM: TASTE, ADDICTION, AND METABOLISM

1A: Genetic protection Portal vein

Ethanol Peroxisomes

MEOS

Catalase

CYP2E1*C1

Ethanol

Acetaldehyde

H2O2

H2O

Acetaldehyde NADP+ + 2H2O

NADPH + H+ + O2

NAD + ADH1B*2 NADH Acetaldehyde Mitochondria

Acetaldehyde NAD+ ALDH2*2 NADH Acetate

Circulation ATP

ACSS AMP Acetyl-CoA

CO2 TCA

Energy required tissues

FFA

VLDL

Ketone bodies

1B: Genetic risk

FIGURE 50.1 Genetic variants of alcohol metabolizing-enzymes. ADH1B and ALDH2 enzymes metabolize alcohol in the liver into acetaldehyde, and then to acetate. The enzyme CYP2E1 (Km 5 8 10 mM) metabolizes alcohol at high blood concentrations. The peroxisomal catalase is an alternate pathway. A, genetic protection variants include: ADH1B 2 (Km 5 1.9 mM, Vmax 5 4.8 U/mg) carriers, which have a higher enzymatic activity, resulting in higher conversion to acetaldehyde; ALDH2 2 (Km 5 0.0046 mM, Vmax 5 0.017 U/mg) carriers have lower acetaldehyde turnover to acetate, and CYP2E1 C1 carriers have lower enzymatic activity. B, genetic risk variants include: ADH1B 1 (Km 5 0.016 mM, Vmax 5 0.18 U/mg) carriers have a lower enzymatic activity; ALDH2 1 (Km 5 0.00020 mM, Vmax 5 0.60 U/mg) carriers have higher acetaldehyde turnover to acetate, and CYP2E1 C2 carriers show an increased enzymatic activity that rapidly converts ethanol into acetaldehyde. MEOS, microsomal ethanol oxidizing system, ACSS, Acyl-CoA synthetase short chain family member, CO2, carbon dioxide, FFA, Free fatty acids, very low-density cholesterol, TCA, tricarboxylic acid cycle.

Portal vein

Ethanol

MEOS

Peroxisomes CYP2E1*C2

Catalase Acetaldehyde

Acetaldehyde

Ethanol NADPH + H+ + O2

H2O2

H2O

NADP ++ 2H2O

NAD+ ADH1B*1 NADH

Acetaldehyde

Mitochondria Acetaldehyde NAD+

ALDH2*1

NADH Acetate

Circulation ATP

Energy required tissues

ACSS

AMP

CO2 TCA

Ketone bodies

Acetyl-CoA

FFA VLDL

SOCIOCULTURAL FACTORS Alcohol drinking is a human practice in which the biological and social tolerance towards ethanol are entwined. Genetic polymorphisms derived from coevolutionary processes may have enabled humans to use the additional calories of alcohol without harm. However, allele distribution and cultural differences may influence the prevalence of a risk or protective genetic profile towards alcohol addiction combined

with a modern-day lifestyle (Table 50.2). For example, in Mexico, the production of low-degree alcoholic beverages such as tejuino and pulque obtained by the fermentation of the endemic maize and agave plants, respectively, were part of a traditional Mesoamerican lifestyle (Roman et al., 2013). On the other hand, drinking was prohibited for most of the native population and was reserved only for the sick and warriors, or during certain religious festivities. Interestingly, Mexican-Amerindians have a higher prevalence of the

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REFERENCES

risk alleles than modern Mexicans (Mestizos). Nonetheless, after Spanish colonization, not only a genetic admixture of the native population was initiated, other drinks such as wine, beer, mezcal, and tequila became available, and the pattern of drinking was modified. Currently, the heterogeneticallyadmixed population is exposed to high-caloric foods and alcohol and are at higher risk for chronic diseases. More so, the high-risk score of drinking patterns in Mexico is typified by three stages of drinking (Panduro et al, 2017a; Roman et al., 2013). Regional alcoholic beverages are consumed in family festivities at early ages and those who continue to drink excessively during adulthood may provoke an early onset of liver disease, especially in Mestizo individuals with genetic susceptibility. In contrast, native populations that maintain their traditional lifestyle despite their risky genetic background are less prone to liver damage even when consuming large quantities of alcohol (Panduro et al., 2017a).

MINI-DICTIONARY OF TERMS Taster People that perceive more intensively bitter flavor. Medium tasters People that perceive PROP as a moderately bitter flavor. Supertasters People that perceive PROP as extremely bitter. Nontaster People that less intensively perceive bitter flavor. Reward deficiency syndrome A dopamine deprivation that affects emotions and cognition among people with addictions. Tejuino Alcoholic beverage obtained by fermented maize. Pulque Alcoholic beverage obtained by fermented agave sap.

KEY FACTS Genetic Marks for Alcoholism • Alcohol consumption and addiction are mediated by taste, flavor perception, brain reward systems, and alcohol detoxification pathways. • TAS2R38 polymorphisms modulate the nontaster phenotype, affecting alcohol perception and food intake. • DRD2/ANKK1 Taq1A polymorphism is associated with addictive behaviors, such as alcohol intake and unhealthy eating patterns. • Genetic variations in detoxification liver enzymes (ADH1B, ADH1C, ALDH2, and CYP2E1) mediate the metabolic rate of alcohol. • Key gene polymorphisms have a heterogeneous allele frequency among different populations that influence the pattern of drinking.

SUMMARY POINTS • This chapter describes some important key genes involved in alcohol addiction. • These genes include the bitter taste receptors, (TASR238), dopaminergic transmission pathways (DRD2), and alcohol-metabolizing enzymes (ADH, ALDH, CYP2E1). • The risk of addiction is associated with an alcohol nontaster, low D2 receptor density, and lower acetaldehyde accumulation profile. • Protection against addiction is associated with an alcohol taster, higher D2 receptor density, and higher acetaldehyde accumulation profile. • Additionally, the risk genetic profile of excessive alcohol consumption seems to predispose alcoholics to become overweight or obese by inducing the intake of unhealthy foods. • Social and cultural factors influence the availability of alcohol and patterns of drinking.

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C H A P T E R

51 Ethanol Exposure During Development, and Brain Oxidative Stress Joana Gil-Mohapel1, Claudia D. Bianco2, Patricia A. Cesconetto3, Ariane Zamoner3 and Patricia S. Brocardo2,4

1

Division of Medical Sciences, University of Victoria and Island Medical Program, Faculty of Medicine, University of British Columbia, Victoria, BC, Canada 2Neuroscience Program, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil 3Department of Biochemistry, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil 4Department of Morphological Sciences, Biological Sciences Center, Federal University of Santa Catarina, Florianopolis, Brazil

LIST OF ABBREVIATIONS 5-HT ADH ALDH ARBD ARND CAT CNS CYP1A2 CYP2E1 CYP3A4 FAS FASD GABA GD GPx GR GSH HO• LTP 1 NAD /NADH 1

NADP /NADPH NMDA NO• O22• PND ROS SOD TCA

serotonin alcohol dehydrogenase aldehyde dehydrogenase alcohol-related birth defects alcohol-related neurological disorders catalase central nervous system cytochrome P450 1A2 cytochrome P450 2E1 cytochrome P450 3A4 fetal alcohol syndrome fetal alcohol spectrum disorders gamma-aminobutyric acid gestational day glutathione peroxidase glutathione reductase glutathione hydroxyl radical long-term potentiation nicotinamide adenine dinucleotide oxidized/ reduced nicotinamide adenine dinucleotide phosphate oxidized/reduced N-methyl-D-aspartate nitric oxide superoxide postnatal day reactive oxygen species superoxide dismutase tricarboxylic acid cycle

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00051-9

INTRODUCTION Ethanol exposure during development causes a variety of developmental abnormalities that can generate long-lasting physiological and behavioral alterations (Alfonso-Loeches & Guerri, 2011; Sadrian, Wilson, & Saito, 2013). These abnormalities involve a wide range of deficits in growth, anatomy, behavior, and cognition, and are referred to as fetal alcohol spectrum disorders (FASD). The variation in symptoms arising from FASD reflects different factors, including dose, timing, and duration of exposure (Guerri, Bazinet, & Riley, 2009; Sokol, Delaney-Black, & Nordstrom, 2003). FASD includes alcohol-related birth defects (ARBD), alcohol-related neurological disorders (ARND), and fetal alcohol syndrome (FAS) (Burd & Martsolf, 1989) (Fig. 51.1), which is the most severe outcome of prenatal ethanol exposure and is wellcharacterized by a pattern of cranio-facial dysmorphologies, growth retardation, and central nervous system (CNS) impairment (Jones & Smith, 1973). While the underlying mechanisms of prenatal ethanol damage to the developing brain are likely multifaceted, a clear relationship between prenatal ethanol exposure and oxidative stress in the brain has been

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© 2019 Elsevier Inc. All rights reserved.

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51. ETHANOL EXPOSURE DURING DEVELOPMENT, AND BRAIN OXIDATIVE STRESS

Fetal alcohol spectrum disorders

Fetal alcohol syndrome (FAS) Alcohol-related birth defects (ARBD)

Partial fetal alcohol syndrome (pFAS) Alcohol-related neurological disorders (ARND)

FIGURE 51.1 Fetal alcohol spectrum disorders (FASD). FASD is an umbrella term that covers the deficits caused by maternal alcohol consumption. Source: The authors.

established (Brocardo, Gil-Mohapel, & Christie, 2011). Ethanol can increase the generation of reactive oxygen species (ROS) by acting directly on mitochondrial respiration and leading to the formation of superoxide (O22•), hydroxyl radical (HO•), and nitric oxide (NO•), while the metabolism of ethanol can also generate oxidative stress.

ETHANOL METABOLISM IN THE FETAL BRAIN Ethanol metabolism is regulated by the reactions catalyzed by alcohol dehydrogenase (ADH), the microsomal ethanol oxidizing system, and catalase (CAT), which oxidize ethanol to acetaldehyde. Aldehyde dehydrogenase (ALDH) then oxidizes acetaldehyde to acetate (Fig. 51.2). The predominant route for metabolism of ethanol is through the hepatic ADH enzyme system, which oxidizes ethanol to acetaldehyde with 1 reduction of NAD to NADH in the cytosol. ADH isozymes can be found in the brain and are distinguished by their affinity for ethanol (Wu et al., 2014). Cytochrome P450 is an enzyme complex involved in the detoxification of drugs and toxins and the form most involved in ethanol metabolism is cytochrome P450 2E1 (CYP2E1), which has been identified in the brain and can be found in neurons and glial cells in several brain regions (Warner, Stro¨mstedt, Wyss, & Gustafsson, 1993). CYP2E1 is inducible after ethanol administration, and its contribution to ethanol metabolism is, therefore, increased after chronic ethanol consumption. In addition, there are P450 isozymes other

than CYP2E1 that can also contribute to microsomal ethanol metabolism, such as cytochrome P450 1A2 (CYP1A2) and CYP3A4 (Kunitoh, Tanaka, Imaoka, Funae, & Monna, 1993). The biotransformation of ethanol by CYP2E1 produces oxidized metabolites (acetaldehyde and acetate) in the liver and brain (Hernandez, Lopez-Sanchez, & Rendon-Ramirez, 2016). This is accompanied by an 1 increase in the NADPH:NADP ratio, causing the reduction of ferric iron to ferrous iron which, in turn, further facilitates the generation of HO• radicals (Mansouri et al., 2001). In addition, the enzyme CAT, present in peroxisomes, can also play a role in the production of acetaldehyde from ethanol in the brain (Zimatkin, Pronko, Vasiliou, Gonzalez, & Deitrich, 2006). Acetaldehyde can then be further oxidized into acetate by acetaldehyde dehydrogenase (also present in the brain), generating NADH. Approximately 90% of the acetaldehyde generated is further metabolized to acetate in the liver (Fig. 51.2).

MECHANISMS UNDERLYING FETAL BRAIN ETHANOL TOXICITY While the mechanisms underlying ethanol-induced prenatal brain damage remain unclear, they may result from direct or indirect actions of ethanol on the metabolism of neurotransmitters, such as serotonin (5-HT), glutamate, and γ-aminobutyric acid (GABA), as well as on the modulation of its receptors and oxidative stress induction (Brocardo et al., 2011; Prosser, Mangrum, & Glass, 2008). In addition, direct effects of ethanol in the developing brain also involve its interaction with a wide range of cell surface receptors and ion channels, including GABAA, N-methyl-D-aspartate (NMDA), and 5-HT3 receptors, as well as the modulation of L-type voltage-dependent Ca21 channels and G protein-activated inwardly rectifying K1 channels (Crews, Morrow, Criswell, & Breese, 1996; Davies, 2003). Indirectly, ethanol exposure may affect maternal physiology leading to malnutrition, thus, compromising the availability of nutrients necessary to support fetus development (Goodlett & Horn, 2001). Ethanol ingested by pregnant females may freely cross the placental barrier and be delivered directly to the amniotic fluid and to the fetus (Brien, Loomis, Tranmer, & McGrath, 1983). Prenatal exposure to ethanol may compromise placental development and function, which is associated with impaired blood flow and nutrient transport to the fetus as well as an increased chance of low birth weight (Burd, Roberts, Olson, & Odendaal, 2007). The risk for more severe adverse neurodevelopmental outcomes of maternal ethanol consumption is

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FIGURE 51.2 Pathways of ethanol metabolism. Ethanol is metabolized mainly by alcohol dehydrogenase (ADH) to produce acetaldehyde. At high levels of ethanol consumption, cytochrome P450 2E1 (CYP2E1) becomes involved in metabolizing ethanol to acetaldehyde. Catalase (CAT) metabolizes B60% of ethanol within the brain where physiologically active ADH is lacking. Acetaldehyde is oxidized into acetate mainly by aldehyde dehydrogenase (ALDH). Acetate may then be converted into acetyl- Coenzyme A, which can be oxidized in the tricarboxylic acid cycle (TCA). The α- ketoglutarate from TCA may be used as a source of glutamate, glutamine, or GABA. Ethanol metabolism results in the formation of NADH and, thus, changes the cellular redox state. Re-oxidation of NADH via the mitochondrial electron transport chain results in the formation of reactive oxygen species (ROS). Source: The authors.

dependent on several factors, such as maternal age, parity, pattern of ethanol consumption during pregnancy, use of other drugs, and nutritional status, as well as genetic and environmental factors (May et al., 2013). Genetic studies suggest that maternal and fetal genotype can influence the risk for, or susceptibility to, ethanol teratogenesis. For example, maternal ADH2 3 alleles, coding for a more efficient ADH enzyme, decrease the risk of FAS (Gemma, Vichi, & Testai, 2007). The developmental timing of ethanol exposure is also relevant in the neurodevelopmental outcome of perinatal ethanol exposure, as well as the brain regions that will be affected by ethanol (Guerri et al., 2009). During the embryonic stage of gastrulation (which corresponds to weeks three and four of human gestation) ethanol exposure can interfere with neural tube development and cause microcephaly (Miller, 1996) and the facial dysmorphologies that characterize FAS (Sulik, 2005). During the second trimester of development— weeks 7 20 in humans; gestational days (GDs) 12 21 in rats and mice—cell proliferation and migration occur. Ethanol can disrupt these processes by altering migration, impairing the timing of cell proliferation, and reducing neuron and glial cell numbers in several

areas of the brain, including the neocortex and hippocampus (Gressens, Lammens, Picard, & Evrard, 1992; Rubert, Min˜ana, Min˜ana, & Guerri, 2006). Ethanol exposure also causes devastating effects during the third trimester—weeks 28 40 in humans; postnatal days (PNDs) 1 10 in rats and mice—when the “brain growth spurt” occurs (Dobbing & Sands, 1979). Neurons are highly susceptible to the apoptotic effects of ethanol during this period (Ikonomidou et al., 2000) and excessive cell death may lead to long-term deficits in learning and memory (Wozniak et al., 2004). Autopsies of patients affected with FASD show that damage occurs throughout the brain and that microcephaly is particularly apparent in many cases, along with errors in migration and anomalies in the cerebellum and brainstem (Jones & Smith, 1973).

EFFECTS OF ETHANOL EXPOSURE DURING DEVELOPMENT ON ROS PRODUCTION AND OXIDATIVE STRESS In the developing brain, an increase in ROS generation can lead to cell damage as free radicals can attack carbohydrates, proteins, lipids, and nucleic acids

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51. ETHANOL EXPOSURE DURING DEVELOPMENT, AND BRAIN OXIDATIVE STRESS

FIGURE 51.3

Ethanol and oxidative stress. Ethanol can produce reactive oxygen species (ROS), which cause lipid peroxidation, protein oxidation, and DNA damage. Ethanol can also increase oxidative stress by decreasing GSH levels. Decreased antioxidant protection and increased oxidative damage can lead to redox modifications, cell signaling impairments, and cell death. These effects may result in brain damage. Source: The authors.

causing an increase in stable lipid peroxidation or protein carbonyl products as well as DNA mutations (Brocardo et al., 2011) which, in turn, result in alterations in gene transcription that are often irreversible and impair cell function (Fig. 51.3). Antioxidant levels are much lower during development than in mature cells; therefore, developing neurons are considerably more susceptible to these mechanisms of oxidative stress (Henderson, Chen, & Schenker, 1999). The expression and activity of enzymes responsible for the recycling of reduced glutathione (GSH; arguably the most important endogenous non-enzymatic antioxidant) can also be altered by prenatal ethanol exposure and this may influence basal levels of this antioxidant in the brain (Brocardo et al., 2011). The effects of this increase in oxidative stress can have long-term consequences (Fig. 51.4). Various studies have shown increases in markers of oxidative damage in rodent models of FASD, with the extent of oxidative damage observed depending on the brain region analyzed, the timing and pattern of exposure, the dose of ethanol consumed, and the blood alcohol concentrations reached, as well as the age of the offspring at the time of analysis (Brocardo et al., 2011). Indeed, increases in lipid peroxidation (Bagheri, Goudarzi, Lashkarbolouki, & Elahdadi Salmani, 2015; Brocardo et al., 2012; Brocardo et al., 2017; Cesconetto et al., 2016; Henderson, Devi, Perez, & Schenker, 1995; Patten, Brocardo, & Christie, 2013; Petkov, Stoianovski, Petkov, & Vyglenova, 1992), protein oxidation (Brocardo et al., 2012; Marino, Aksenov, & Kelly,

FIGURE 51.4 Long-term effects of ethanol exposure during development. Source: The authors.

2004), and DNA damage (Chu, Tong, & de la Monte, 2007; Kumar, Singh, Lavoie, Dipette, & Singh, 2011; Miller-Pinsler, Pinto, & Wells, 2015; Shirpoor, Salami, Khadem-Ansari, Minassian, & Yegiazarian, 2009) have been found in different models of FASD. Alterations in the endogenous antioxidant system are also common following perinatal ethanol exposure. While some studies have observed an up-regulation in the activities of the antioxidant enzymes glutathione peroxidase (GPx) and superoxide dismutase (SOD), in what is thought to be an adaptive compensatory effect (Heaton, Paiva, Madorsky, Shaw, 2003; Reddy, Husain, Schlorff, Scott, & Somani, 1999), others have observed a perinatal ethanol exposure-induced reduction in antioxidant capacity, with decreased levels of GSH and a down-regulation of the activities of the enzymes glutathione reductase (GR) and SOD (Bagheri et al., 2015; Henderson et al., 1995; Reyes, Wolfe, & Marquez, 1989). This decrease may indicate an oxidative modification of the enzymatic proteins caused by enhanced generation of free radicals during ethanol and acetaldehyde metabolism. Alternatively, it may also result

IV. PHARMACOLOGY, NEUROACTIVES, MOLECULAR, AND CELLULAR BIOLOGY

USE OF ANTIOXIDANTS AS THERAPEUTIC STRATEGIES FOR FASD TREATMENT

from a decrease in the synthesis of these enzymes (as a consequence of impaired gene expression). Even acute maternal exposure to ethanol has been shown to result in decreased GSH content and increased levels of lipid peroxidation (Henderson et al., 1995), as well as mitochondrial deregulation, apoptosis, and DNA fragmentation in the fetal brain (Ramachandran et al., 2001). Similarly, the effects of ethanol exposure on brain oxidative stress can also be seen in newborn rodents. Indeed, exposure of rodents to ethanol during the first days of postnatal life (equivalent to the third gestational trimester in humans) has been shown to alter the GSH content while increasing the levels of lipid peroxides and protein carbonyls in several brain regions (Brocardo et al., 2017; Heaton, Paiva, Mayer, & Miller, 2002; Marino et al., 2004). One of the most prominent oxidative changes induced by ethanol in the developing brain is an increase in lipid peroxidation (Brocardo et al., 2012; Brocardo et al., 2017; Cesconetto et al., 2016; Henderson et al., 1995; Patten, Brocardo, & Christie, 2013; Reddy et al., 1999) and the concomitant decrease in GSH content (Brocardo et al., 2012; Patten, Brocardo, & Christie, 2013). Of note, both of these phenomena are likely to have long-lasting functional and behavioral effects in the offspring as an increase in oxidative stress and/or the lack of antioxidants such as GSH are known to reduce long-term potentiation (LTP) (Almaguer-Melian, Cruz-Aguado, & Bergado, 2000), a neurobiological correlate of learning and memory (Bruel-Jungerman, Davis, & Laroche, 2007). Within this scenario, we have shown an increase in lipid peroxidation and a reduction in GSH levels in various brain regions of both male and female offspring following perinatal ethanol exposure (Brocardo et al., 2012; Brocardo et al., 2017; Patten, Brocardo, & Christie, 2013). Importantly, this increase in oxidative stress, particularly in the hippocampus, may be one of the major contributors to the LTP deficits observed in male animals, since the reduction in this form of synaptic plasticity can be rescued with N-acetyl cysteine, a cysteine donor for the synthesis of GSH (Patten et al., 2013). These results indicate that, at least in males, perinatal ethanol exposure may cause reductions in LTP by reducing the intracellular pool of this endogenous antioxidant.

USE OF ANTIOXIDANTS AS THERAPEUTIC STRATEGIES FOR FASD TREATMENT Several studies have tested the therapeutic potential of antioxidants in rodent models of FASD. However, given the number of experimental variables associated with these studies (including the perinatal ethanol

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exposure model, the type of antioxidant used, and the time of administration, as well as the age of the animals at the time of analysis and the features evaluated), direct comparisons among the various studies are challenging. Therefore, the experimental protocols and the main findings of these studies are summarized in Tables 51.1 and 51.2. In summary, most studies have shown that antioxidant treatment decreases oxidative stress levels and/or increases brain antioxidant capacity (Kumral et al., 2005; Ramezani et al., 2011; Zheng et al., 2014) (Table 51.1). These beneficial effects of antioxidant treatment have been observed when antioxidant exposure occurred during pregnancy, concomitant with ethanol exposure. For example, mice exposed to ethanol on GD 8 and treated with epigallocatechin-3gallate, the main polyphenol constituent of green tea, on GDs 7 8 and analyzed 1 day later (GD 9), showed a decrease in brain hydrogen peroxide levels, an indicator of oxidative stress (Long, Rosenberger, & Picklo, 2010). Ethanol exposure along with administration of silymarin during GDs 1 21 caused a reduction in the activity of the gamma glutamyl transpeptidase enzyme in the brain and liver of GD 21 fetuses (Edwards et al., 2000; La Grange et al., 1999). Other studies have also found beneficial effects when antioxidants were administered to ethanolexposed offspring, a fact of potential clinical relevance. For example, administration of vitamin E on PNDs 6 and 9 caused a significant reduction in protein carbonyl levels and a decrease in hippocampal cell loss at PND 29 in rats exposed to ethanol between PNDs 7 9 (Marino et al., 2004). In a different study, administration of tocotrienol (a potent isoform of vitamin E) between PNDs 6 and 28 caused a reduction in nitrite and lipid peroxidation levels, an increase in SOD and CAT activities and GSH levels, and a decrease in apoptosis in the cerebral cortex and hippocampus of rats exposed to ethanol between PNDs 7 9 (Tiwari, Arora, & Chopra,2012). Moreover, rats exposed to ethanol during PNDs 7 9 and treated with epigallocatechin-3gallate from PNDs 6 28 presented a reduction in cholinesterase activity and in nitrite and lipid peroxidation levels, as well as increased SOD and CAT activities, and GSH levels in the cerebral cortex and hippocampus (Tiwari, Kuhad, & Chopra, 2010). Various studies have also evaluated the potential of several antioxidants in mitigating the behavioral deficits in FASD rodent models (Monk, Leslie, & Thomas, 2012; Ryan, Williams, & Thomas, 2008; Schneider & Thomas, 2016; Thomas et al., 2007) (Table 51.2). For example, choline has been shown to decrease behavioral abnormalities induced by ethanol exposure either during the prenatal or the early-postnatal period. Administration of choline during GDs 5 20 normalized behavioral development and delayed the

IV. PHARMACOLOGY, NEUROACTIVES, MOLECULAR, AND CELLULAR BIOLOGY

TABLE 51.1 Effects of Antioxidant Treatment on Oxidative Stress Parameters of In Vivo Rodent Models of FASD Period of exposure

BAC levels (mg/dL)

Antioxidant (period of treatment)

Time of analysis

Tissue analyzed

Antioxidants effects

Reference

Sprague-Dawley rats (36% EtOH)

GDs 1 21

ND

SY (GDs 1 21)

GD 21

Brain; liver

k GGTP activity

La Grange et al. (1999), Edwards, Grange, Wang, & Reyes (2000)

Sprague-Dawley rats (36% EtOH)

GDs 1 21

135

Omega-3 (Mothers: GD21PND22; Pups: PNDs 22 60)

PND 60

Cerebellum

m GSH levels in DG and CB

Patten, Brocardo, and Christie (2013)

FASD model Liquid diet

Hippocampus k Lipid peroxidation in hippocampal DG Prefrontal cortex

Gavage

GDs 1 21

Long-Evans rats (12% EtOH)

PNDs 4 5

260

Vitamin E (PNDs 4 5)

PND 15

Cerebellum

Long-Evans rats (5.25 g/kg EtOH)

PNDs 7 9

447

Vitamin E (PNDs 6 9)

PND 29

Hippocampus k Protein carbonyls; Prevented alcoholinduced cell loss

Wistar rats (12% EtOH)

PNDs 7 9

301

EGCG (PNDs 6 28)

PNDs

Cortex

Tocotrienol (PNDs 6 28)

24 28

Hippocampus m GSH levels; m SOD and CAT activities; k TNF-α, IL-1β and TGF-β1 levels; k NFκβ p56 subunit expression; k Apoptosis

Melatonin (GD 6 PND 21)

PND 21

Cerebellum

Wistar rats (40% EtOH)

i.p. injection

101

NAC (PNDs 23 60)

PNDs

Hippocampus Restored LTP in males; m GSH levels

Sprague-Dawley rats (36% EtOH)

Patten et al. (2013)

55 70

GD 6 PND 21 ND

k Loss of cerebellar Purkinje cells

k Cholinesterase activity; k Nitrite levels; k Lipid peroxide levels

k Hcy levels; k MDA levels

PNDs

m SOD, CAT and GPx activities

31 33

k Bax; m Bcl-2

Heaton et al. (2000) Marino et al. (2004) Tiwari et al. (2010, 2012)

Bagheri et al. (2015)

C57BL/6 mice (25% EtOH)

GD 8

ND

EGCG (GDs 7 8)

GD 9

Embryo brains

k H2O2; k MDA

Long et al. (2010)

Wistar rats (35% EtOH)

PND 4

336

17β-estradiol (PND 4)

PND 4

Cerebellum

k TBARS levels; m GPx and CAT activities; k Motor impairment

Ramezani et al. (2011)

PNDs 21 23

s.c. injection

C57BL/6 mice (25% EtOH)

GD 8

ND

AST (GDs 7 8)

GD 10

Embryos

k H2O2 and MDA levels; m GPx levels; k MyD88, NF-kB, TNF-α, and IL-1b levels

Zheng et al. (2014)

C57BL6 (2.5 g/kg EtOH)

PND 7

225

EPO (PND 7)

PND 8

Cerebellum

m Density and numbers of neurons

Kumral et al. (2005)

Hippocampus k Apoptosis; k TBARS levels Prefrontal cortex

m GPx activity

Wistar rats (20% EtOH)

GDs 7 21

ND

1

Vitamin E (GDs 7 21 1 PNDs 1 21)

PND 21

Cerebellum

k Hcy levels; k apoptosis

Shirpoor et al. (2009)

Hippocampus

PNDs 1 21 C57BL/6 (20% EtOH)

PND 7

ND

C3G (PNDs 6 7)

PND 7

Brain

k Caspase-3 activity; k Apoptosis; k Microglia activity; k p47phox expression

Ke et al. (2011)

Inhalation chamber

Long-Evans rats (95% EtOH)

PND 7

385

Resveratrol (PNDs 6 7)

PND 7

Cerebellum

k Caspase-3 activity; k Apoptosis; k Lipid peroxidation; k ROS formation; k Thiol levels

Kumar et al. (2011)

m SOD activity; m GSH levels m Nrf2 levels AST, Astaxanthin; Bax, proapoptotic protein; Bcl-2, antiapoptotic protein; CAT, catalase; CB, cerebellum; C3G, cyanidin-3-glucoside; DG, dentate gyrus; EGCG, ( )-epigallocatechin-3-gallate; EPO, erythropoietin; EtOH, ethanol; EUK-134, synthetic superoxide dismutase plus catalase mimetic; GD, gestational day; GGTP, Gamma glutamyl transpeptidase; GPx, glutathione peroxidase; GR, glutathione reductase; GSH, reduced glutathione; i.p., intraperitoneal; Hcy, homocysteine; H2O2, hydrogen peroxide; IL-1β, interleukin 1 beta; LTP, long-term potentiation; MDA, malondialdehyde; MyD88, myeloid differentiation primary response gene 88; NAC, N-acetyl cysteine; ND, not determined; NFκβ, nuclear factor kappa beta; Nrf2, nuclear factor erythroid 2 related factor; PND, postnatal day; s.c., subcutaneous; p47phox, essential regulatory protein of NADPH oxidase; ROS, reactive oxygen species; SOD, superoxide dismutase; SY, silymarin; TBARS, Thiobarbituric acid reactive substances; TGF-β1, Transforming growth factor beta 1; TNF-α, tumor necrosis factor alpha.

TABLE 51.2 Effects of Antioxidant Treatment in Mitigating the Behavioral Deficits in FASD Rodent Models Period of exposure

BAC levels (mg/dL)

Antioxidant (period of treatment)

Time of analysis

GDs 1 21

ND

SY (GDs 1 21)

PND 90

Fischer/344 rats (35% GDs 1 21 EtOH)

ND

SY (GDs 1 21)

PND 84

Sprague-Dawley rats (11.9% EtOH)

320

Choline

PNDs

334

PNDs 4 30

30 33; 35; 45

k Hyperactivity

PNDs 11 20

61 64; 65 73

m Spatial working memory

PNDs 21 30

87 91

k muscarinic M2/4 receptors density

PNDs 15 17

Normalized behavioral development in reflex ontogeny; Restored development of spontaneous alternation

2 20

m Working memory

FASD model Liquid diet

Gavage

Sprague-Dawley rats (35% EtOH)

PNDs 4 9

Tissue analyzed

Corpus callosun

Antioxidants effects

References

m Social recognition

Reid et al. (1999)

m Right-paw preference

Moreland et al. (2002)

k impairment in corpus callosum development

Hippocampus m Spatial memory

Ryan et al. (2008), Monk et al. (2012), Schneider and Thomas (2016)

PNDs 40 60 Sprague-Dawley rats (28,5% EtOH)

GDs 5 20

248

Choline (GDs 5 20)

Thomas, Idrus, Monk, & Dominguez (2010), Thomas et al. (2009)

(Continued)

TABLE 51.2 (Continued) Period of exposure

FASD model

BAC levels (mg/dL)

Antioxidant (period of treatment)

Time of analysis

Tissue analyzed

Antioxidants effects

References

Thomas et al. (2009, 2010)

15 17

Normalized behavioral development in reflex ontogeny; Restored development of spontaneous alternation

2 20

m Working memory

28 32 39 45 65 66 Sprague-Dawley rats (28,5% EtOH)

GDs 5 20

248

Choline (GDs 5 20)

PNDs

28 32 39 45 65 66 Wistar rats (12% EtOH)

PNDs 7 9

C57BL/6 mice (13.6% EtOH)

PND 5

Oral Dunkin-Hartley administration Guinea pigs (30% EtOH)

GDs 2 67

Artificial rearing

PNDs 4 9

Sprague-Dawley rats (6.8% EtOH)

301

m Learning and memory

Tiwari et al. (2010, 2012)

PND 30

m Balance; m Coordination

Bearer, Wellmann, Tang, He, & Mooney (2015)

Vitamin C 1 Vitamin E (GDs 2 67)

PND 45

m Task-retention performance

Nash, Ibram, Dringenberg, Reynolds, & Brien (2007)

Choline (PNDs 10 30)

PND

EGCG (PNDs 6 28)

PNDs

Cortex

Tocotrienol (PNDs 6 28)

24 28

Hippocampus

517

Choline (PNDs 1 5; PNDs 6 20)

257

333

No alterations in LTP impairments

31 34

EGCG, ( )-epigallocatechin-3-gallate; EtOH, ethanol; GD, gestational day; ND, not determined; PND, postnatal day; s SY, silymarin.

k Overactivity; m Spatial learning

Thomas, Biane, O’Bryan, O’Neill, Dominguez (2007)

501

SUMMARY POINTS

occurrence of spontaneous alternation behavior and working memory deficits in rats exposed to ethanol during the prenatal period (GDs 5 20) (Thomas, Abou, & Dominguez, 2009; Thomas et al., 2010). In a different study, choline treatment during PNDs 1 5 prevented deficits in balance and motor coordination (cerebellum-dependent tasks) seen in adolescent rats (PND 30) exposed to ethanol on PND 5 (Bearer et al., 2015). In addition, postnatal choline treatment also improved both spatial and working memories, and reduced hyperactivity in rats exposed to ethanol during PNDs 4 9 (Monk et al., 2012; Ryan et al., 2008; Schneider & Thomas, 2016; Thomas et al., 2007). Other antioxidants were also shown to have beneficial behavioral effects. For example, a combination of vitamin E and vitamin C improved task retention in the Morris water maze in guinea pigs when antioxidant treatment occurred concomitantly with prenatal ethanol exposure (GDs 2 67) (Nash et al., 2007). Also, treatment of rats exposed to ethanol during PNDs 7 9 with epigallocatechin-3-gallate from PNDs 6 28 improved learning and memory (Tiwari et al., 2010), whereas silymarin administration concomitant with ethanol exposure (GDs 1 21) improved social recognition in PND 90 rats (Reid et al., 1999). Morphological alterations caused by perinatal ethanol exposure can also be alleviated by antioxidants. For example, administration of vitamin E at PNDs 4 and 5 decreased Purkinje cell loss in PND 15 rats (Heaton, Mitchell, & Paiva, 2000). In addition, silymarin administration concomitant with ethanol exposure (GDs 1 21) reduced ethanol-induced corpus callosum deficiencies in PND 84 rats (Moreland, La Grange, & Montoya, 2002). Moreover, administration of cyanidin-3-glucoside, a natural antioxidant, protected against ethanol-induced neuroapoptosis (Ke et al., 2011).

CONCLUSIONS Oxidative stress plays a major role in the neuropathology and behavioral alterations associated with FASD and these can be mitigated, at least in part, by antioxidant treatment. However, in the studies discussed, antioxidant treatment was administered before and/or during the period of ethanol exposure. While the results obtained in these studies have increased our knowledge of the mechanisms underlying biochemical, neuroanatomical, and behavioral changes associated with FASD, there is a need to examine the effects of antioxidant therapy following ethanol exposure. Indeed, if antioxidants prove to be beneficial when given after the period of exposure, they can become valid therapeutic options for FASD-affected

children. Furthermore, while oxidative stress may mediate many of the impairments induced by this teratogen, deficits in neurogenesis and synaptic plasticity as well as increases in inflammation. Thus, it might be beneficial to determine the potential therapeutic effects of combination therapies in FASD models, as different compounds might act synergistically in mitigating some of the deficits associated with these disorders.

MINI-DICTIONARY OF TERMS Fetal alcohol spectrum disorders (FASD) A group of neurodevelopmental conditions related to permanent brain damage caused by prenatal alcohol exposure. Fetal alcohol syndrome (FAS) A group of facial malformations and cognitive impairments associated with heavy prenatal alcohol exposure. Reactive oxygen species (ROS) Unstable chemical species that can react with, and modify, cellular biomolecules. Antioxidants Substances that neutralize the damaging effects of oxidation. Microcephaly A condition where a baby’s head is smaller than expected when compared to babies of the same sex and age.

KEY FACTS FASD • • • • •

Alcohol exposure during development Physical and neurodevelopmental abnormalities Long-lasting effects Behavioral and learning problems Growth retardation

SUMMARY POINTS • Prenatal ethanol exposure can produce a variety of central nervous system abnormalities in the offspring resulting in FASD. • Ethanol induces brain damage through numerous processes, with the generation of ROS being one of the leading mechanisms of ethanol-induced toxicity. • Ethanol can act directly on the mitochondrial respiratory chain, stimulating the production of ROS. • Ethanol-induced oxidative stress during the period of brain development can have long-lasting effects by rendering the antioxidant defense system less effective throughout life. • Some of the deleterious effects of ethanol exposure during the period of brain development can be mitigated by antioxidants.

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C H A P T E R

52 Alcohol-Induced Oxidative Stress in the Brain: Suggested Mechanisms, Associated Disorders, and Therapeutic Strategies Miroslava Georgieva Varadinova1, Maria Lozanova Valcheva-Traykova2 and Nadka Ivanova Boyadjieva1 1

Department of Pharmacology and Toxicology, Medical Faculty, Medical University, Sofia, Bulgaria 2Department of Medical Physics and Biophysics, Medical Faculty, Medical University, Sofia, Bulgaria

LIST OF ABBREVIATIONS AD ADH AO BBB BDNF cAMP CAT CNS CoQ10 COX-2 CREB DD ER GDNF GPx GSH H2O2 HNE IL-1 beta MDA MS NAD(P) NF-kB NO NOS NP ONOO2 OS PD RNS

Alzheimer’s disease alcohol dehydrogenase antioxidant blood brain barrier brain-derived neurotrophic factor cyclic adenosine monophosphate catalase central nervous system coenzyme Q10 cyclooxygenase-2 cAMP-response element binding protein depressive disorder endoplasmic reticulum glial cell-derived neurotrophic factor glutathione peroxidase glutathione reductase hydrogen peroxide hydroxynonenal interleukin-1 beta malondialdehyde multiple sclerosis nicotinamide adenine dinucleotide (phosphate) nuclear factor kappa beta nitric oxide nitric oxide synthase nanoparticle peroxynitrite oxidative stress Parkinson’s disease reactive nitrogen species

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00052-0

ROS SOD TLR TNF-alpha XO

reactive oxygen species superoxide dismutase toll-like receptor tumor necrosis factor alpha xanthine oxidase

INTRODUCTION Alcohol is one of the most commonly abused substances in modern society. Excessive alcohol use is known for its numerous deleterious effects on the central nervous system (CNS), depending on the age of the individuals, as well as the dose, duration, and pattern of exposure. Chronic ethanol consumption causes direct or indirect changes to both mature and developing brains, and are associated with profound damage (Deitrich & Erwin, 1996) (Fig. 52.1). It is believed that ethanol-induced oxidative stress may be considered as the primary event related to inflammatory processes in the CNS, neurotoxicity, and neurodegeneration (Herna´ndez, Lo´pez-Sa´nchez, & Rendo´nRamı´rez, 2016). Oxidative stress (OS) refers to the imbalance between production and removal of free radicals, reactive oxygen (ROS) and reactive nitrogen (RNS) species, in the cells. The most deleterious radicals are

505

© 2019 Elsevier Inc. All rights reserved.

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52. ALCOHOL-INDUCED OXIDATIVE STRESS IN THE BRAIN

FIGURE 52.1 Overview of harmful effects of ethanol in the brain. Ethanol affects the brain on a cellular and molecular level. The effects of ethanol and its metabolic products are related to BBB dysfunction, neuroinflammation, lipid peroxidation, protein denaturation, inhibited DNA repair, and disrupted intracellular signaling pathways.

superoxide (O2•2), hydroxyl radical (OH•), hydrogen peroxide (H2O2), nitric oxide (NO), and peroxynitrite (ONOO2). While free radicals are implicated in many physiological processes, if the redox balance is disturbed, they may induce molecular and cellular dysfunctions through membrane destruction, denaturation of cellular proteins, lipid peroxidation, and structural DNA damage (Halliwell & Gutteridge, 2015) (Fig. 52.2). The antioxidant (AO) protection of the brain includes direct and indirect AOs, exogenous and endogenous AOs, enzymatic and nonenzymatic AOs, radical scavengers and chelators of metal ions, etc., (Galkina, 2013), as illustrated in Fig. 52.3. The complexity of mechanisms and location of brain AO defense corresponds to the structural and functional specificities in the various brain regions. In comparison to other organs, the AO enzymes of glutathione metabolism, superoxide dismutase (SOD), catalase (CAT), and the thioredoxin enzyme families have lower expression and activity in the brain. Nevertheless, given the regional brain specificities, they are very efficient in the elimination of hydroperoxides (including lipid peroxides) and protein disulfides. The nonenzymatic AOs include histidines, tocopherols, melatonine, glutathione, and co-enzyme Q10, and the main hydrophilic protector of neurons (especially in cortex, hippocampus, and cerebellum), ascorbate. The brain is particularly vulnerable to OS because of its vast oxygen consumption, abundance of polyunsaturated fatty acids, high iron content, and relatively low AO defense (Galkina, 2013; Sun & Sun, 2001).

FIGURE 52.2 Endogenous sources of free radicals in the brain. There are numerous physiological sources of ROS in the brain: receptor function, synaptic transmission, metabolic processes, inflammatory reactions, and mitochondrial electron transport, etc. In pathological conditions, there may be excessive production of free radicals and depletion of antioxidant defense mechanisms, leading to oxidative stress.

MECHANISMS OF ETHANOL-INDUCED OXIDATIVE STRESS Ethanol can cross the blood brain barrier (BBB) and it can be metabolized in the brain (Deitrich & Erwin, 1996) (Fig. 52.1). Metabolizing pathways engage catalase, cytochrome CYP2E1, and alcohol dehydrogenase (ADH). CYP2E1 and catalase are the principal metabolizers that convert ethanol to acetaldehyde in the brain, while ADH is of less importance (Zimatkin, Pronko, Vasiliou, Gonzalez, & Deitrich, 2006). Ethanol induces CYP2E1, which is associated with excessive production of ROS (Haorah et al., 2008) (Fig. 52.4). In addition, the products of ethanol metabolism increase ROS and RNS via induction of nicotinamide adenine dinucleotide phosphate (NADP), xanthine oxidase (XO), and nitric oxide synthase (NOS) in the brain (Haorah et al., 2008). NO is produced by the constitutive NOS in the brain and serves as a neuromodulator of synaptic plasticity. However, alcohol consumption may cause OS in the brain via changes in the cytokine signaling

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507

FIGURE 52.3 Types of antioxidant defense.

pathways, activation of inducible NOS (iNOS), and excessive production of ROS, NO, and ONOO- (Sun & Sun, 2001). Chronic ethanol intake enhances OS in the brain both by overproduction of ROS and RNS, and disrupted expression and activity of enzymatic and nonenzymatic AOs (Herna´ndez et al., 2016). While escalating, OS leads to continuous lipid peroxidation of membrane phospholipids, thus, producing reactive aldehydes like 4-hydroxynonenal (HNE) and malondialdehyde (MDA) (Pizzimenti et al., 2013). Our experimental data also demonstrate that chronic ethanol intake may cause elevation in XO activity and MDA levels in the brain (Varadinova, Valcheva-Traykova, & Boyadjieva, 2016). Ethanol-induced OS and increased HNE or MDA levels are associated with altered gene expression and mitochondrial dysfunction, subsequently activating caspases, and triggering apoptosis and neuronal loss (Ramachandran et al., 2003) (Fig. 52.4). Recently, a cross-talk between OS and endoplasmic reticulum stress (ERS) has been suggested as a possible mechanism of ethanol-induced neurotoxicity and brain damage (Yang & Luo, 2015). ERS is a result of accumulation of unfolded and misfolded proteins in the endoplasmic reticulum and has been implied in apoptosis and neurodegeneration. Interestingly, ERS in the brain may be triggered by OS (Chen et al., 2008), and vice versa; ERS can provoke OS (Xu, Bailly-Maitre, & Reed, 2005). Also, it is documented that both OS and ERS

might stimulate autophagy in the CNS (Luo, 2014). Autophagy, which has gained a lot of attention recently, is proposed as a defensive mechanism against alcohol-induced CNS damage (Chen et al., 2012). However, when the detrimental effects exceed the capacity of the protective responses, neurons transform irreversibly. Pla, Pascual, Renau-Piqueras, and Guerri (2014) have shown that excessive ethanol consumption is associated with impaired autophagy, which results in brain damage and neurodegeneration. Moreover, intensive neuroinflammation and NF-kappa β (NF-kB) pathway activation have also been involved (Yang & Luo, 2015). Accumulating evidence focuses on neuroinflammation as one of the ethanol-induced neuropathological mechanisms (Guizzetti, Zhang, Goeke, & Gavin, 2014; Saito, Chakraborty, Hui, Masiello, & Saito, 2016). Ethanol abuse has been shown to overactivate tolllike receptor (TLR) signaling in microglia, thus, triggering OS. This and the resulting elevation of NF-kB, caspase-3, and cytokine (tumor necrosis factor-alpha and interleukin-1 beta) levels participate in neuronal damage and apoptosis (Guizzetti et al., 2014). Furthermore, experimental studies report that alcohol provokes OS in astrocytes (Guizzetti et al., 2014). Blanco, Valles, Pascual, and Guerri (2004) have shown that ethanol induces ROS overproduction and upregulates cyclooxygenase-2 (COX-2) and iNOS expression via TLR4/IL-1R1 receptor 1 and NF-kB activation (Fig. 52.4).

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dysregulation of pro-inflammatory signaling pathways play important roles in ethanol-induced neurotoxicity and neurodegeneration.

BRAIN DISORDERS ASSOCIATED WITH OXIDATIVE STRESS

FIGURE 52.4 Ethanol-induced oxidative stress in the brain. Excessive ethanol consumption leads to disturbed redox balance in the brain. Oxidative stress impairs cell survival and differentiation, and induces a proapoptotic mechanism associated with neurodegeneration.

Our earlier studies have also shown that microglial activation is involved in ethanol-induced apoptosis in hypothalamic neurons (Boyadjieva & Sarkar, 2010). Exposure of developing hypothalamic neurons to ethanol has led to increased levels of ROS and RNS, and reduced activity of glutathione peroxidase (GPx), CAT, and SOD, as well as increased production of microglial-derived factors (Boyadjieva & Sarkar, 2013a,b). Furthermore, the neurotoxic effect of ethanol is associated with decreased cellular levels of the brain-derived neurotrophic factor (BDNF) and cyclic adenosine monophosphate (cAMP), leading to disturbed redox status and increased apoptotic activity in neuronal cell cultures (Boyadjieva & Sarkar, 2013a,b). In addition, we have demonstrated that cAMP or BDNF may inhibit ethanol’s, or ethanol-activated microglial conditioned media’s, capacity to escalate apoptotic processes by decreasing free radical levels and increasing the production of glutathione reductase (GSH) and CAT in developing neurons. Taken together this data suggest that ethanol activation of microglia and astrocytes, induction of OS and

Excessive alcohol consumption is associated with neuronal loss in different brain regions, such as the prefrontal cortex, hippocampus, and cerebellum. Depending on the developmental stage, these deficits are related to behavioral changes, deteriorations in memory and motor functions, cognitive dysfunctions, neuropsychiatric, and neurodevelopmental disorders, etc. (Alfonso-Loeches & Guerri, 2011). In recent years, alcohol-induced OS has been considered as a key mechanism involved in ethanol neurotoxicity (Wang et al., 2017). Concurrently, ischemic brain injury, Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), depressive disorder (DD), schizophrenia, and autism spectrum disorders have all been linked to OS and neuroinflammation (PopaWagner, Mitran, Sivanesan, Chang, & Buga, 2013). Cerebral ischemia/reperfusion are followed by increased OS, BBB disruption, and mitochondrial dysfunction, which trigger proinflammatory reactions associated with neurodegeneration (Popa-Wagner et al., 2013). Furthermore, neuronal loss is strongly related to OS-induced TLR-mediated and NF-kBmediated elevations of inflammatory mediators, such as cytokines and chemokines. Similarly, OS and consequent neuroinflammation are critically involved in PD (Hirsch & Hunot, 2009). HNE and MDA have been significantly elevated in PD brains (Kim, Kim, Rhie, & Yoon, 2015). Hirsch and Hunot (2009) suggest that both adaptive and innate immunity dysfunctions are linked to neurodegeneration in PD subjects. The neuroinflammatory mechanisms involve activation of microglia, astrogliosis, overproduction of ROS, and overexpression of COX-2, and subsequent dopaminergic neuronal loss. There is compelling evidence that amyloid beta protein-mediated OS, microglial activation, and cytokine release may contribute to neuronal loss in AD patients (Kalaria, Harshbarger-Kelly, Cohen, & Premkumar, 1996). Upregulation of TLR2 and TLR4 due to disrupted innate immune responses might account for neurodegeneration and memory loss in AD (Cribbs et al., 2012). DD are also often associated with impaired neuroplasticity and neuronal loss, due to dysregulated inflammatory reactions and OS (Popa-Wagner et al., 2013). It is reported that progression of bipolar disorder may be due to dysfunctional interaction between

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THERAPEUTIC APPROACHES IN OXIDATIVE STRESS-RELATED BRAIN DISORDERS

neurotransmitters, inflammation, OS, and BDNF (Berk et al., 2011). Our earlier studies have focused on the link between OS and the development of depressivelike symptoms in rats (Varadinova, Docheva-Drenska, & Boyadjieva, 2009; Varadinova, Docheva-Drenska, & Boyadjieva, 2013). Moreover, we documented that anthocyanins as AOs might alleviate those symptoms. Mytochondrial dysfunction, immune dysregulation, and OS are suggested to be important mechanisms in neurodevelopmental disorders like autistic spectrum disorders (Rossignol & Frye, 2012) and schizophrenia (Kulak et al., 2013). Furthermore, ethanol-induced OS and intensive inflammatory responses are proposed to play a crucial role in cognitive and behavioral impairments typical for FAS (Ikonomidou et al., 2000). TABLE 52.1

509

THERAPEUTIC APPROACHES IN OXIDATIVE STRESS-RELATED BRAIN DISORDERS Given the compelling evidence that OS is of paramount importance in ethanol-induced neurotoxicity, AO therapy is postulated as potentially promising for neuroprotection (Table 52.1). AOs protect the redox balance in neural cells by targeting both the upstream and downstream mechanisms of OS (Uttara, Singh, Zamboni, & Mahajan, 2009). AO compounds can diminish the detrimental effects of OS in the brain directly—by binding to ROS, or indirectly—by reducing the toxic effects of misfolded protein aggregation and neuroinflammatory processes.

Substances With Potential Neuroprotective Activity in Oxidative Stress-Related CNS Disorders

Substance

Mechanism

Effect

References

Polyenes Polyphenols

Antioxidant activity, antiinflammatory activity

Neuroprotection in AD

Uttara et al. (2009)

Vitamin C

ROS scavenging

Slowing of vascular dementia progression Uttara et al. (2009)

Vitamin E

Antioxidant activity

Reduced prevalence of AD

Uttara et al. (2009)

Reduced risk of PD

Kim et al. (2015)

CoQ10

Antioxidant activity

Dose-related beneficial effects on cognition in AD

Kim et al. (2015)

N-acetylcysteine

Neuroprotection (reduced secondary ROS metabolites)

Improvement of some cognitive parameters in AD

Uttara et al. (2009)

Melatonin

Reduced oxidative neurotoxicity

Beneficial in DD

Malhotra, Sawhney, and Pandhi (2004)

Lithium

Reduced oxidative stress and excitotoxicity

Neuroprotection in BP disorder and ischemic stroke

Popa-Wagner et al. (2013)

17β-estradiol

Antioxidant, antiinflammatory, neuroprotective

Reduced risk of AD

Amantea, Russo, Bagetta, and Corasaniti (2005)

Attenuate symptoms of PD

Kim et al. (2015)

Favorable effects in DD Decreased risk of ischemic stroke MAO-inhibitors

Prevent excitotoxicity

Favorable effects in AD, PD, DD

Uttara et al. (2009) Kim et al. (2015)

Fluvoxamine Fluoxetine Reboxetine

Antiinflammatory activity Neuroprotection

Clozapine Risperidone

Antiinflammatory effects

PPARγ-agonists

Antiinflammatory activity

Neuroprotection

Neuroprotection

Beneficial in depressive and schizophrenic disorder

Popa-Wagner et al. (2013)

Additional favorable effects in schizophrenic disorder

Popa-Wagner et al. (2013)

Decreased subsequent damage in ischemic stroke

Popa-Wagner et al. (2013)

This table summarizes the results of recently performed experimental and/or clinical studies on antioxidant and antiinflammatory properties of drug products and dietary supplements which have shown beneficial therapeutic effects in CNS disorders associated with ethanol-induced oxidative stress.

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AO-based therapeutic interventions have achieved encouraging results in neurodegenerative conditions associated with neurological, psychiatric or neurodevelopmental disorders (Table 52.1). Furthermore, other common drugs have shown additional beneficial effects on neuroplasticity by reducing OS and neuroinflammation in the brain (Table 52.1). However, clinical evidence for the neuroprotective effects of AOs and antiinflammatory substances is still unsatisfactory. There are many recommendations for a more precise characterization of optimal doses, timing, and duration of treatment in neurodegenerative conditions (Kim et al., 2015). Additionally, different types of AOs or combinations with other drugs should be considered to achieve better therapeutic results. One of the major challenges for neuroprotective AO compounds is to optimize their movement across the BBB. Nanotechnological approaches are gaining considerable research attention. Nanoparticles (NPs) are designed as drug carriers, or therapeutic agents, and noninvasive alternatives of conventional AO therapies. Drug transport via nanocarriers through the BBB proceeds by endocytic uptake by brain capillary endothelial cells followed either by drug release in the cell and diffusion in the brain, or by uptake through transcytosis (Kreuter, 2005). After uptake, the NP formulations interact with biomolecules from the environment forming surface protein corona, which enables their recognition (Abdal Dayem et al., 2017). The integrity of BBB and NP functionalization (Arya et al., 2016; Kreuter, 2005; Zhou, Fang, Lu, & Yi, 2016) play important roles in brain uptake and translocation of NP formulations. The composition, size, shape, and dose of NP

formulations are critical for their therapeutic efficacy in brain therapy (Arya et al., 2016; Hegazy et al., 2017; Polak & Slufi, 2015; Setyawati, Tay, & Leong, 2013; Strickland et al., 2016). The main advantages of NPs in brain treatment are their high uptake and efficacy as transporters of different medications. Recently, the use of NPs has shown promising results in the treatment of CNS disorders (Polak & Slufi, 2015; Saraiva et al., 2016; Sharma & Sharma, 2007). NP application displays great therapeutic potential and efficacy in animal models of neurodegenerative disorders and diseases (Hegazy et al., 2017; Setyawati et al., 2013; Strickland et al., 2016). Two prospective interrelated approaches with NP formulations have proved to be therapeutically effective: control over the ethanol-induced brain OS and treatment of the subsequent OS-induced neurological pathologies, neurotoxicity, and neurodegenerative disorders. NPs and NP formulations may diminish the OS level in the brain through various mechanisms (Fig. 52.5). NP use against uncontrolled OS has resulted in therapeutic efficacy in AD, PD, MS, ischemic stroke, brain inflammation, and brain autoimmunity (Eitan et al., 2015; Naz et al., 2017; Rzigalinski, Garfana, & Ehrich, 2017; Zhou et al., 2016). Several metal-containing NPs are shown to decrease ROS and RNS levels in rodent brains. Nanoceria exerts SOD-mimic and CAT-mimic activity, scavenges RNS, and decomposes ONOO2 on its surface (Abdal Dayem et al., 2017; Pirmohamed et al., 2010; Rzigalinski et al., 2017). Selenium-rich NPs 15 nm or less in size, decrease Aβ-formation in the brain by reducing ROS in a rat model of AD (Nazioglu, Muhamad, & Pecze,

FIGURE 52.5 Nanoparticle effects against oxidative stress. The figure shows possible mechanisms of antioxidant action of NP formulations against alcohol-induced oxidative stress in the brain.

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SUMMARY POINTS

2017). Small doses of ZnO-NPs activate p53 which subsequently increases the expression of several AO enzymes (Setyawati et al., 2013). Another way to decrease brain OS is to enhance the uptake of nonenzymatic AOs (Ghosh, Sarkar, Choudhury, Ghosh, & Das, 2017; Loureiro et al., 2017; Yadav, Shunkaria, Singhal, & Sandhir, 2017). Studies by Ghosh et al. (2017) show that negatively charged polymeric NPs functionalized with triphenylphosphonium cation are efficient transporters for quenserin in the brain. Likewise, when solid lipid NPs are used as vehicles for resveratrol delivery in an animal model of vascular dementia, they increase its brain uptake 4.5 times (Loureiro et al., 2017; Yadav et al., 2017). NPs functionalized with suitable antibodies diminish brain OS level, reduce mitochondrial ROS production, increase Mn-SOD activity, and ameliorate cognitive decline (Loureiro et al., 2017). Polymer nanoparticles with attached protein chelators of metal ions decrease OS in AD lesions in rat brains (Bonda et al., 2012; Liu, Men, Perry, & Smith, 2010). These polymer nanocarriers help to avoid complications related with toxicity and BBB impermeability for high molecular weight metal ion chelators. Bearing in mind the complex mechanisms of ethanolinduced OS in the brain (Figs. 52.2 and 52.4), it may be a good idea to explore the effects of elaborate NPs formulations, containing more than one type of NP in the future. For instance, it would be tempting to study combinations of nanoceria and low-dose zinc oxide. Zinc oxide NPs may boost the expression of endogenous AO enzymes. Nanoceria exhibit SOD-mimicking and CATmimicking activity and radical scavenging properties. Further future research should focus on the capabilities of polymer and lipid solid nanoparticles with attached nonenzymatic AOs and chelators. Overall, NPs provide numerous opportunities as delivery systems and therapeutic agents. However, there are still many unknown details about their pharmacokinetics and toxicity. Particular concerns about the adverse health effects of NPs include their characteristics, distribution, and interaction with biological systems, which are related to one of the most frequently reported mechanisms of NP-associated cytotoxicity—ROS production (Manke, Wang, & Rojanasakul, 2013). Further investigations with targeted and standardized experimental designs are needed to fully evaluate the beneficial over harmful effects of NPs in medical practice.

MINI-DICTIONARY OF TERMS Antioxidants Compounds capable to diminish the accumulation of free radicals.

Apoptosis Physiological process of programmed cell death which has a crucial role in development. When dysregulated, the apoptosis is involved in various pathologies, including neurodegenerative conditions. Free radicals Highly reactive and nonselective chemical species containing unpaired electrons. Nanoparticle Particle of organic or inorganic chemical nature between 1 and 100 nm in size in one of its three dimensions. Neuroinflammation Inflammation in the brain characterized by activation of glial cells, overproduction of free radicals, and associated with neuronal loss. Neuroplasticity The ability of the brain to modify itself and adjust in response to new conditions, injury, or disorder. This involves biochemical and structural changes to form new neuronal connections throughout life. Neurotoxicity Neuronal damage caused by exposure to endogenous and exogenous deleterious factors, which is associated with neuronal dysfunction or neurodegeneration.

KEY FACTS Oxidative Stress • Reactive oxygen species (ROS) are generated by oxygen metabolism, and in normal concentrations are involved in physiological functions as mediators in signaling processes. • Excessive ROS levels have deleterious effects on major biomolecules like lipids, proteins, and DNA. • Oxidative stress is a result of an imbalance between the accumulation of free radicals and their elimination by the antioxidant defense systems. • Oxidative stress plays a detrimental role in aging and in numerous pathological conditions like atherosclerosis, cancer, diabetes, inflammatory conditions, and neurodegenerative disorders. • The brain is exceptionally vulnerable to oxidative stress due to its high oxygen consumption, abundant amount of polyunsaturated fatty acids, and the relatively weak antioxidant defense.

SUMMARY POINTS • Ethanol-induced oxidative stress may be considered as the primary event associated with inflammatory processes in the brain and impaired neuroplasticity. • Ethanol-induced oxidative stress and increased levels of end-products of lipid peroxidation have been associated with altered gene expression and mitochondrial dysfunction, subsequently triggering apoptosis and neuronal death. • Neuronal loss is strongly related to oxidative stressinduced TLR-mediated and NF-kB-mediated elevations of inflammatory mediators, such as cytokines and chemokines.

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• Ischemic brain injury, neurodegenerative, psychiatric, and neurodevelopmental disorders have all been linked to oxidative stress and neuroinflammation. • Antioxidant-based therapeutic interventions have achieved encouraging outcomes in neurodegenerative conditions associated with neurological, psychiatric, or neurodevelopmental disorders. • Nanoparticles are designed as drug carriers, or therapeutic agents, and noninvasive alternatives of conventional antioxidant therapies. • Nanoparticles display great therapeutic potential in a variety of animal models of neurodegenerative conditions.

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53 Lead Exposure and Ethanol Intake: Oxidative Stress as a Converging Mechanism of Action 1

Miriam B. Virgolini1,2, Mara S. Mattalloni1, Romina Deza-Ponzio1,2, Paula A. Albrecht1,2 and Liliana M. Cancela1,2 Universidad Nacional de Co´rdoba, Facultad de Ciencias Quı´micas, Depto. de Farmacologı´a, Co´rdoba, Argentina 2 IFEC, CONICET, Haya de la Torre y Medina Allende, Ciudad Universitaria, Co´rdoba, Argentina

LIST OF ABBREVIATIONS 4-HNE ACD ADH ADP ALDH ALT AST ATP ATP synthase BBB [Ca]i CAT CNS CoQ Cu21 CuZnSOD CYP2E1 Cyto C ð-ALA ð-ALA-D DNA eNOS ETC EtOH FAD FADH2 Fe21 GPx GR GSH GSH ox GSSH H2 Hsp70 IMM

4-hydroxynonenal acetaldehyde alcohol dehydrogenase adenosine diphosphate aldehyde dehydrogenase alanine aminotransferase aspartate aminotransferase adenosine triphosphate adenosine triphosphate synthase blood brain barrier intracellular calcium catalase central nervous system coenzyme Q cupric cation copper-zinc superoxide dismutase cytochrome P-450 E1 cytochrome complex delta aminolevulinic acid delta aminolevulinic acid dehydrase deoxyribonucleic acid endothelial nitric oxide synthase electron transport chain ethanol flavin adenine dinucleotide flavin adenine dinucleotide reduced ferrous cation glutathione peroxidase glutathione reductase glutathione glutathione oxidase glutathione disulfide molecular hydrogen 70 kDa heat shock proteins inner mitochondrial membrane

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00053-2

IMS LOAEL MDA mtNOS MEOS Mg21 MMP MnSOD NAD1 NADH NADHd NADPH NO ONOO• NOAEL NOx O2•2 OH2 OMM Pi Pb Prx RNA ROS SDH Se21 shRNA SOD TBARs UChB VDAC VTA Zn21

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intermembrane space lowest-observed-adverse-effect level malondialdehyde mitochondrial nitric oxide synthase microsomal ethanol oxidase system magnesium cation mitochondrial membrane permeabilization manganese superoxide dismutase oxidized nicotinamide adenine dinucleotide reduced nicotinamide adenine dinucleotide nicotinamide adenine dinucleotide dehydrogenase reduced nicotinamide adenine dinucleotide phosphate nitric oxide peroxynitrite no-observed-adverse-effect level nicotinamide adenine dinucleotide phosphate oxidase superoxide hydroxide anion outer mitochondrial membrane inorganic phosphate lead peroxiredoxin ribonucleic acid reactive oxygen species succinate dehydrogenase selenium cation short hairpin ribonucleic acid superoxide dismutase thiobarbituric acid reactive substances drinker rat line voltage-dependent anion channel ventral tegmental area zinc cation

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INTRODUCTION Industrial and environmental lead (Pb) exposure coexists with ethanol (EtOH) consumption, particularly in western societies, affecting the occupational and general population, and display adverse effects in developing organisms. Alcohol use and abuse have increased dramatically, while Pb exposure, although reduced as a result of regulatory policies, still persists and constitutes a global public health problem. Given that Pb and EtOH are ubiquitous and the vast evidence of potentiated toxicity, particularly in the central nervous system (CNS), this coexistence deserves further study. A distinction must be made between developmental and adult Pb exposure, given the opposite effects of the metal on different stages of the life span. This chapter summarizes key clinical and experimental findings, focusing particularly on the neurotoxic effects of imbalance in the redox status of the individual, with special emphasis on the role of brain EtOH in metabolizing enzymes, proposing the resultant oxidative stress as a common mechanism of action for the potentiation of the detrimental effects of Pb/EtOH interaction.

OXIDATIVE STRESS The health versus disease status of an organism is dependent on several factors including the prooxidant/antioxidant balance. Mitochondria are the major source of reactive oxygen species (ROS) that, at physiological levels, are messengers in intracellular signaling, while, at high concentrations, they can modify macromolecules, affecting the cellular functionality or promoting cell death. Interestingly, Complex I seems to be the primary source of ROS in the brain under normal conditions and in several pathologies (Turrens, 2003). Additionally, imbalance in the oxidized nicotinamide adenine dinucleotide:nicotinamide adenine dinucleotide (NAD1:NADH) ratio is responsible for ROS generation through impairments in several processes such as glycolysis, lipoxidative damage, and sirtuin-mediated deacetylation of proteins. Thus, “both complex I and a-ketoglutarate dehydrogenase produce more ROS when the ratio of NAD1 to NADH is low; in turn, increased ROS would compromise the capacity of complex I to oxidize NADH, starting a vicious circle” (Stefanatos & Sanz, 2011). On the other hand, polyunsaturated fatty acids are the molecules that are most sensitive to oxidation, with lipid peroxidation playing a major role in the redox status of the cell. The main ROS include hydroxyl radical (OH•), superoxide (O2•2), and hydrogen peroxide (H2O2).

Although the latter is not considered a free radical, it is a major intermediate in the generation of the highly toxic OH• via the Fenton or Heber-Weiss reactions, which require ferrous cation (Fe21) or cupric cation (Cu21), respectively. O2•2, rapidly formed from O2 in the neighborhood of the internal mitochondrial membrane, is mostly released into the matrix at complex I and III and to the intermembrane space (IMS) at complex III, but it is also generated from flavoenzymes, NADPH oxidase (NOx) or lipoxygenases and cyclooxygenases. Once formed, two molecules of O2•2 can be dismutated to H2O2 and O2 by the enzyme superoxide dismutase (SOD). Subsequently, catalase (CAT) and glutathione peroxidase (GPx) convert H2O2 into H2O and O2, which, with SOD, GRx and peroxiredoxins (Prxs), are the main components of the enzymatic antioxidant system aimed at counteracting the deleterious effects of ROS. Given that both CAT and GPx are implicated in H2O2 removal, it is suggested that CAT may be a defense mechanism against excessive H2O2 levels, while GPx would predominantly act in the presence of low H2O2 concentrations (Fig. 53.1). In addition, the peptide glutathione (GSH) is the main nonenzymatic antioxidant, particularly in the mitochondria, where it protects this organelle from excessive ROS generation. The majority of GSH is used by GPx and Prx6 to catalyze H2O2 reduction. Other natural antioxidants are ascorbic acid, tocopherol, metallothionein, cysteine, zinc cation (Zn21), Selenium cation (Se21), etc. (Halliwell, 1992). Importantly, these compounds are employed as complements to traditional chelation therapy for intoxication with various metals, including Pb (Flora, Gupta, & Tiwari, 2012).

LEAD Indiscriminate use of Pb over centuries in numerous industrial applications (mainly in gasoline, paints, water pipes, and batteries) is responsible for its ubiquitous presence in the environment, with the resultant effects on human health, not only in occupationally exposed adults (producing saturnism), but also in the general population, and particularly in developing organisms, that is, fetuses and young children (Fig. 53.2). Interestingly, it is proposed that any exposure during early development may influence the individual response to challenging events later in life (Osmond & Barker, 2000). From a toxicokinetic perspective, once inside the body, Pb reaches the circulation and is concentrated in the red blood cells for about a month after which it is redistributed to the soft tissues, particularly the brain, liver, and kidney. It subsequently accumulates in the hard tissue (bone, teeth, nails, and hair), which

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FIGURE 53.1 Overview of mitochondrial ROS production and removal.

becomes a long-term storage site for the metal. Importantly, Pb crosses the blood brain barrier (BBB) and the placenta and is excreted through maternal milk, constituting a potential exposure source for developing offspring. Although the detrimental effects of Pb are multisystemic, Pb interference with heme formation enables the hematologic parameters to be considered as a tool for the diagnosis of Pb intoxication and/or exposure (Flora, Gautam, & Kushwaha, 2012). The nervous system is considered a preferential target for the most severe effects of the metal. High exposures cause peripheral neuropathy in adults and encephalopathy in developing organisms, while lowlevel Pb exposure induces neurobehavioral alterations in children, manifested as learning disabilities, hyperactivity, and impulsivity. For this reason, the US Centers for Disease Control (CDC) (ACCLP, 2012) has progressively reduced the lowest-observed-adverseeffect level (LOAEL) for Pb over the years, even considering that a no-observed-adverse-effect level (NOAEL) does not exist for early-life exposure to this metal. Importantly, the deleterious effects are potentiated by nutritional deficits, by physiological (e.g., pregnancy) or pathological mobilization of the metal from the storage sites, or by the concomitant presence of

other toxicants (Patrick, 2006a). Thus, from a mechanistic point of view, and depending on the time of exposure, Pb can be viewed either as a developmental neurotoxicant or as an interfering toxicant in adults when exposure occurs concurrently with other xenobiotics. Although several mechanisms such as thiol inhibition and competition with essential bivalent cations may account for the adverse effects of Pb, oxidative stress is a major factor in the etiology of Pb toxicity (reviewed in Patrick, 2006b). While it is not a redoxactive metal, its pro-oxidant actions can be mediated by delta aminolevulinic acid dehydrase (δ-ALA-D) inhibition and, thus, delta aminolevulinic acid (δ-ALA) accumulation, a compound that undergoes enolization and autoxidation with resultant ROS generation. Alternatively, by GSH decrease as a result of thiol inhibition, antioxidant enzyme depletion or via Fe21 stimulation, Pb may alter cell membrane integrity, permeability, and functionality, which may favor lipid peroxidation. Perinatal Pb exposure has been associated with increased Pb levels and lipid oxidation production in several brain regions (Villeda-Hernandez et al., 2001). Interestingly, the components of the enzymatic antioxidant system are metalloproteins involved

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FIGURE 53.2 Sources of Pb exposure stressing their potentially higher impact in the different periods of the life span.

in O2•2 and H2O2 detoxification, and are, thus, susceptible to Pb competition for the metal site or to inhibition of the thiol group. However, although Pb may inhibit these enzymes at high levels or after long-term exposure, Pb-induced activation has also been reported, probably as a compensatory response to enhanced oxidative stress resulting from exaggerated lipid peroxidation. This is particularly true for CAT activity, in which a positive correlation with Pb levels was reported in adults (Gurer-Orhan, Sabir, & ¨ zgu¨ne¸s, 2004), children (Ahamed, Verma, Kumar, & O Siddiqui, 2005), and in the brain of Pb-exposed laboratory animals (Bokara et al., 2008; Correa, Miquel, & Aragon, 2000). It should be noted that, besides CAT’s ability to metabolize H2O2 via a catalytic reaction, this enzyme can also promote the reaction of H2O2 with H2 donors, such as low molecular-weight alcohols, through a peroxidatic reaction, constituting a major metabolic step in brain EtOH oxidation (Vetrano et al., 2005).

ETHANOL Although there are some trading restrictions, EtOH is a socially accepted drug that, when it is abused,

causes adverse consequences in several aspects of the individual’s life. Once EtOH is ingested, oxidative metabolism occurs mainly in the liver and brain (Fig. 53.3), while nonoxidative metabolism involves the transformation of EtOH to ethyl ether from fatty acids in organs, such as the pancreas, liver, heart, and adipose tissue. Peripheral EtOH oxidation to ACD is catalyzed primarily by cytosolic ADH with NAD1 as a cofactor. However, chronic consumption favors metabolism through the MEOS by CYP2E1 induction, an enzyme that uses NADPH, cytochrome P-450 and O2 as cofactors. The CAT/H2O2 system present in the peroxisomes also catalyzes peripheral EtOH oxidation, but only under nonphysiological conditions. ACD is further metabolized to acetate by mitochondrial ALDH2, which also requires NAD1 as a cofactor. Thus, alterations in either of these enzymatic activities, or cofactor availability, can modify ACD levels, the systemic accumulation of which leads to symptoms such as flushing, nausea, headaches, and tachycardia, all deterrents for EtOH consumption (Quertemont, 2004). Since only large amounts of ACD are able to cross the BBB due to the presence of the enzyme ALDH in brain microvessels, it is acknowledged that central ACD is generated in situ by CAT

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LEAD AND ETHANOL

FIGURE 53.3 Concurrent events involved in EtOH-induced oxidative stress during liver and brain ethanol metabolism.

(approximately 70%) and CYP2E1 (approximately 20%), given the very low ADH activity in the brain. In contrast to its systemic action, centrally-formed ACD accumulation results in increased EtOH consumption, leading to the use of the term “acetaldehydism” instead of “alcoholism” due to the positive motivational properties of the metabolite (Peana et al., 2017) (Israel, Quintanilla, Karahanian, Rivera-Meza, & Herrera-Marschitz, 2015). Although no single event can be ascribed to EtOH toxicity, unbalanced redox status is often pointed out as a converging mechanism (reviewed in Cederbaum, Lu, & Wu, 2009). Many concurrent events could lead to EtOH-induced oxidative stress: (1) changes in the NAD1/NADH ratio, a critical step in EtOH metabolism; (2) the production of ACD, a toxic metabolite susceptible to form adducts; (3) mitochondrial damage with resultant decreased ATP production; (4) effects on cellular membranes due to its amphipathic characteristics; (5) the induction of brain and liver CYP2E1, a major source of ROS; (6) the reduction of GSH levels in the mitochondria; and (7) the increase in Fe21 concentrations, an ion that, along with H2O2, promotes OH formation through the nonenzymatic Fenton reaction (Fig. 53.3). All these factors could contribute to the

generation of reactive aldehydes, such as 4-HNE (a compound that is detoxified by ALDH2 and ALDH1A1) and MDA, a substrate of the ALDH family, including ALDH2 (Zhao & Wang, 2015).

LEAD AND ETHANOL Substantial evidence points out a close relationship between Pb and EtOH. Clinical studies demonstrate that EtOH intake favors Pb absorption and modifies its distribution and mobilization promoting high Pb levels, thereby increasing its toxicity. In addition, and from a neurobehavioral perspective, experimental studies in adult animals indicate that chronic Pb exposure modifies several responses to EtOH (Table 53.1). Regarding the causes of these potentiated effects between both neurotoxicants, the earliest reports pointed to “nutritional factors rather than mutual enhancement of the closely related cellular effects of these two toxins” (Mahaffey, Goyer, & Wilson, 1974). It is known that the amphipathic nature of EtOH affects the membrane permeability of all cells and, thereby, facilitates Pb gastrointestinal absorption, which increases blood and brain Pb levels in rats

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53. LEAD EXPOSURE AND ETHANOL INTAKE: OXIDATIVE STRESS AS A CONVERGING MECHANISM OF ACTION

Main Evidence for the Existence of an Association Between Ethanol and Lead Toxicity

(Flora, Gautam, & Dwivedi, 2012) that, in turn, influences the toxicokinetics of essential cations, many of them constituents of metalloenzymes implicated in the defense of the organism against oxidative stress (Gupta & Gill, 2000).

LEAD, ETHANOL, AND OXIDATIVE STRESS Thus, on the basis of the evidence presented, four different but nonexcluding mechanisms may account for the Pb EtOH interaction: (1) the already reported EtOH effects on Pb toxicokinetics; (2) essential metal deficiency; (3) the increased ROS production of each individual toxicant or through a common mechanism; and (4) GSH depletion, either via direct thiol binding or through ROS formation. For the most part, the toxic effects of Pb would be potentiated by EtOH, by accentuating the oxidative stress induced by this metal (Jindal & Gill, 1999) and the production of free radicals and lipid peroxidation in the liver, kidney, and brain; effects that may be mitigated by the presence of an antioxidant (Gautam & Flora, 2010) (Fig. 53.4). Moreover, Verma, Dua, and Gill (2005) reported that adult rats chronically administered with Pb and EtOH showed impaired brain mitochondrial respiration and energy supply, with three key mitochondrial enzymes

(cytochrome oxidase, SDH, and NADH dehydrogenase) depleted in these animals. The authors ascribed these effects to “either direct action of Pb and EtOH on the ETC components and associated lipids or a secondary effect due to excessive generation of ROS and thereby altering the mitochondrial membrane potential.” Sajitha et al. (2010) reported the protective effects of vitamin E and garlic oil, probably acting as ROS scavengers in liver lipid peroxidation, and the inactivating effect of adult Pb and EtOH in blood CAT and hepatic enzymes, the latter was also reported by Flora and Tandon (1987). Furthermore, after acute Pb and EtOH coexposure, blood δ-ALA-D and GSH levels were reduced, while brain and hepatic lipid peroxidation and GSH levels were increased, accompanied by elevated Pb levels in all tissues, which were reduced by S-adenosyl-L-methionine administration (Flora & Seth, 1999). Further data reported by Flora et al. (2012) showed dose-dependent increases in blood, liver and kidney ROS, lipid peroxidation index, oxidized GSH, and [Ca21]i, along with a decrease in GSH, GPx, adenosine triphosphatase, ADH, and CAT in adult Pb and EtOH coexposed animals. These effects induced neuronal impairments, mitochondrial dysfunction, and oxidative stress, events that may lead to apoptosis. Kumar et al. (2015), in PC12 cells exposed to Pb and EtOH, described the increased production of [Ca21]i, heat shock protein (HSP70) induction, and associated

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FIGURE 53.4 Effect of the lead ethanol interaction on oxidative stress parameters.

oxidative stress, evidenced as reduced GSH, increased lipid peroxidation, and reduced mitochondrial membrane potential with resultant apoptosis and CYP2E1 upregulation, all promoting ROS generation. In addition, Pb and EtOH cotreatment potentiated the depletion of the hepatic enzymes, ALT and ALS, as well as ADH and ALDH. Interestingly, both ADH and ALDH participate in EtOH metabolism in the presence of NAD1 as a cofactor, which requires to be reoxidated in the mitochondrial ETC NADH:ubiquinone oxidoreductase complex I (Flora & Tandon, 1987), the main site of ROS reduction in this organelle, which is affected by both Pb and EtOH (Goyer & Mahaffey, 1972). Moreover, prenatal coexposure to Pb and EtOH caused an elevation in MDA levels and a reduction in SOD, CAT, and GPx brain activity, which seems related to deficits in memory as a consequence of oxidative stress either produced by the neurotoxics alone or potentiated by their combination (Soleimani, Goudarzi, Abrari, & Lashkarbolouki, 2016). These effects may not be caused only by EtOH, and it is possible that ACD also play a role in the depletion of GSH content due to the formation of adducts. Alternatively, the peroxidative damage of hepatic mitochondria may also be mediated through ACD, a mechanism that was

proposed for EtOH-induced fatty liver (Comporti et al., 2010).

LEAD, ETHANOL, OXIDATIVE STRESS, AND DRUG CONSUMPTION Among all the pharmacological effects of EtOH, a possible mechanism explaining the Pb EtOH interaction at the motivational level may lie in the drug’s metabolism (Virgolini, Mattalloni, Albrecht, DezaPonzio, & Cancela, 2017) with CAT and ALDH with the positive reinforcement properties of central ACD accumulation playing a key role (Correa et al., 2012; Israel et al., 2013; Peana et al., 2017). It was Correa, Miquel, Sanchis-Segura, and Aragon (1999a) who first demonstrated that the reduction in the locomotor stimulant effect of EtOH induced by chronic Pb administration was associated with CAT blockade (Correa, Miquel, Sanchis-Segura, & Aragon, 1999b). In contrast, acute Pb administration induced a potentiation in both CAT activity and EtOH locomotor responses (Correa et al., 1999a). This was also observed as a result of developmental Pb exposure (Somashekaraiah, Padmaja, & Prasad, 1992; Valenzuela, Lefauconnier, &

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FIGURE 53.5 Proposed relationship among relevant lead and ethanol-induced oxidative stress parameters and brain ethanol metabolism.

Chaudiere, 1989), demonstrating the metal’s consequences activating CAT activity when administered either acutely or to immature organisms. More recently, Mattalloni, De Giovanni, Molina, Cancela, and Virgolini (2013) provided pharmacological evidence that enhanced, voluntary EtOH intake observed in perinatally Pb-exposed rats is dependent on CAT activity, which coincides with data obtained in acatalasemic mice (Aragon & Amit, 1993). Moreover, using a genetic approach, that is, intra-VTA administration of a lentiviral coding for the antiCAT shRNAm, Karahanian et al. (2011) reported a substantial reduction in voluntary EtOH intake in UChB rats. In subsequent experiments, Rivera-Meza, Quintanilla, and Tampier (2012) demonstrated that the combination of an adenoviral vector that encodes for ADH1B 2 and an antisense against ALDH2 reduced voluntary EtOH intake in UChB rats, along with a 4-fold increase in blood ACD levels similar to that obtained in rats treated with disulfiram and in humans carrying the inactive ALDH2 2 (Chen, Peng, Wang, Tsao, & Yin, 2009). Like disulfiram, cyanamide is a drug considered to be a deterrent for alcoholics as a result of ALDH inhibition (Koppaka et al., 2012), although CAT and H2O2

are necessary for its activation (DeMaster, Shirota, & Nagasawa, 1985), both being factors potentiated by Pb-exposure (Fig. 53.5). In effect, when cyanamide was systemically administered to perinatally Pb-exposed animals, their high EtOH intake was reduced compared to controls. In contrast, brain cyanamide administration increased EtOH consumption in both control and Pb-exposed rats, although brain ALDH activity was not inhibited in the Pb-exposed group, a finding that could be related to the enzyme’s low basal brain activity evidenced in these animals (Mattalloni, DezaPonzio, Albrecht, Cancela, & Virgolini, 2017). At this point, putative Pb modification of the NAD1:NADH ratio should be explored, considering that EtOH metabolism decreases the NAD1:NADH ratio within the cytosol and mitochondria and could contribute to the reduction in the enzymatic activity of other NAD1 dependent enzymes, that is, sirtuins, particularly sirtuin 3 which deacetylates ALDH, generating an inactive form of the enzyme (Xue et al., 2012; Harris, Gomez, Backos, & Fritz, 2017). The key participation of the mitochondria and NAD1 in ROS generation, as well as the ALDH localization in this organelle, supports this possibility.

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REFERENCES

CONCLUSION The data reviewed in this chapter allows to conclude that Pb EtOH interaction might be the result of multifactorial effects rather than of a sole mechanism, being oxidative stress as a good candidate in their confluence at the biochemical and neurobehavioral levels. Given that liver and brain EtOH metabolism is a major source of ROS, as a tissue with high O2 demand, the CNS is particularly vulnerable to redox imbalance. Neurons have low antioxidant defenses and high inherent ROS production associated to low ATP production and mitochondrial dysfunction. Thus, the presence of redox-modifying toxicants will have a great impact on essential CNS functions and responses. ROS-related CAT/ALDH2 brain EtOH metabolism, thus, ought to be considered as a main determinant for the potentiated effects of both. In addition, some developmental stages are more sensitive to neurotoxicants. Thus, on the one hand, it seems possible that developmental Pb exposure produces a signature that determines altered responses to challenging events later in life, such as excessive behavioral and biochemical responses to EtOH. Alternatively, from the studies performed in adult animals, the possibility must also be considered that these effects may be the result of an in situ interaction between Pb and EtOH. These considerations are more important in today’s scenario in which living organisms are exposed to a combination of potentially dangerous substances and to adverse events that would act in synergy, increasing the toxicity of each toxicant in particular.

MINI-DICTIONARY OF TERMS Xenobiotic A chemical compound that is foreign to living organisms. Saturnism Also called plumbism, this is a serious, acute, or chronic condition that is caused by exposure and absorption of high levels of Pb. Fenton reaction Involves the iron-dependent decomposition of H2O2, generating the highly reactive OH•. Haber-Weiss reaction Involves the reaction of superoxide (O2•2) with hydrogen peroxide to produce molecular oxygen (O2), hydroxide radical (OH•), and OH2; often iron-catalyzed; a source of oxidative stress in blood cells and various tissues. ALDH family A group of NAD1-dependent enzymes that catalyze the oxidation of aldehydes. Acetaldehydism A term based on a theory that proposes EtOH as a prodrug whose effects are fully mediated by its first metabolite, acetaldehyde. Positive reinforcement The action of strengthening or encouraging a behavior. Apoptosis A normal physiological process of cell self-destruction that is marked by the fragmentation of nuclear DNA.

Sirtuins A family of NAD1-dependent deacetylases that are involved in regulating cellular processes including the cells’ resistance to stress.

KEY FACTS Neurobehavioral Toxicology and Teratology • Neurobehavioral Toxicology studies the adverse effects of an agent on behavior and functioning in adult animals. • Neurobehavioral Teratology is the study of postnatal behavior that is the consequence of prenatal or early postnatal exposure to an agent during development. • Lead and ethanol are both considered neurotoxicant and teratogens. • Behavioral syndromes following exposure to neurotoxicants must be differentiated from other neurological disorders in which there are no reported exposure to a xenobiotic. • Both disciplines apply to human and experimental animal studies.

SUMMARY POINTS • Pb is an environmental neurotoxicant. • EtOH is a socially accepted drug of abuse. • The combination of Pb and EtOH potentiates their individual effects. • Developmental Pb exposure increases the motivational effects of EtOH. • Oxidative stress is a proposed mechanism of action for the Pb/EtOH interaction. • CAT and ALDH are involved in brain EtOH metabolism to ACD and oxidative stress. • Blood and brain (hippocampus and cerebellum) CAT activity is increased after early Pb exposure. • Whole brain ALDH2 is reduced after early Pb exposure. • Brain ACD is proposed as a common site of action.

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Flora, S. J. S., Gautam, P., & Kushwaha, P. (2012). Lead and ethanol co-exposure lead to blood oxidative stress and subsequent neuronal apoptosis in rats. Alcohol and Alcoholism, 47(2), 92 101. Available from https://doi.org/10.1093/alcalc/agr152. Gautam, P., & Flora, S. J. S. (2010). Oral supplementation of gossypin during lead exposure protects alteration in heme synthesis pathway and brain oxidative stress in rats. Nutrition, 26(5), 563 570. Available from https://doi.org/10.1016/j.nut.2009.06.008. Goyer, R. A., & Mahaffey, K. R. (1972). Susceptibility to lead toxicity. Environmental Health Perspectives, 2, 73 80. Gupta, V., & Gill, K. D. (2000). Lead and ethanol coexposure: Implications on the dopaminergic system and associated behavioral functions. Pharmacology, Biochemistry, and Behavior, 66(3), 465 474. Available from https://doi.org/10.1016/S0091-3057(00) 00266-5. ¨ zgu¨ne¸s, H. (2004). Correlation Gurer-Orhan, H., Sabir, H. U., & O between clinical indicators of lead poisoning and oxidative stress parameters in controls and lead-exposed workers. Toxicology, 195(2 3), 147 154. Available from https://doi.org/ 10.1016/j.tox.2003.09.009. Halliwell, B. (1992). Reactive oxygen species and the central nervous system. Journal of Neurochemistry, 59(5), 1609 1623. Retrieved from http://link.springer.com/chapter/10.1007/978-3-642-776090_2. Harris, P. S., Gomez, J. D., Backos, D. S., & Fritz, K. S. (2017). Characterizing sirtuin 3 deacetylase affinity for aldehyde dehydrogenase 2. Chemical Research in Toxicology, 30(3), 785 793. Available from https://doi.org/10.1021/acs.chemrestox.6b00315. Israel, Y., Quintanilla, M. E., Karahanian, E., Rivera-Meza, M., & Herrera-Marschitz, M. (2015). The “first hit” toward alcohol reinforcement: Role of ethanol metabolites. Alcoholism: Clinical and Experimental Research, 39(5), 776 786. Available from https://doi. org/10.1111/acer.12709. Israel, Y., Rivera-Meza, M., Karahanian, E., Quintanilla, M. E., Tampier, L., Morales, P., & Herrera-Marschitz, M. (2013). Gene specific modifications unravel ethanol and acetaldehyde actions. Frontiers in Behavioral Neuroscience, 7, 80. Available from https:// doi.org/10.3389/fnbeh.2013.00080. Jindal, V., & Gill, K. D. (1999). Ethanol potentiates lead-induced inhibition of rat brain antioxidant defense systems. Pharmacology & Toxicology, 85(1), 16 21. Karahanian, E., Quintanilla, M. E., Tampier, L., Rivera-Meza, M., Bustamante, D., Gonzalez-Lira, V., . . . Israel, Y. (2011). Ethanol as a prodrug: Brain metabolism of ethanol mediates its reinforcing effects. Alcoholism: Clinical and Experimental Research, 35(4), 606 612. Available from https://doi.org/10.1111/j.15300277.2011.01439.x. Koppaka, V., Thompson, D. C., Chen, Y., Ellermann, M., Nicolaou, K. C., Juvonen, R. O., . . . Vasiliou, V. (2012). Aldehyde dehydrogenase inhibitors: A comprehensive review of the pharmacology, mechanism of action, substrate specificity, and clinical application. Pharmacological Reviews, 64(3), 520 539. Available from https://doi.org/10.1124/pr.111.005538. Kumar, V., Tripathi, V. K., Jahan, S., Agrawal, M., Pandey, A., Khanna, V. K., & Pant, A. B. (2015). Lead intoxication synergies of the ethanol-induced toxic responses in neuronal cells—PC12. Molecular Neurobiology, 52(3), 1504 1520. Available from https:// doi.org/10.1007/s12035-014-8928-x. Mahaffey, K. R., Goyer, R. A., & Wilson, M. H. (1974). Influence of ethanol ingestion on lead toxicity in rats fed isocaloric diets. Archives of Environmental Health: An International Journal, 28(4), 217 222. Available from https://doi.org/10.1080/ 00039896.1974.10666471. Mattalloni, M. S., Deza-Ponzio, R., Albrecht, P. A., Cancela, L. M., & Virgolini, M. B. (2017). Developmental lead exposure induces

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54 Alcohol and Gambling Addiction 1

Marko Martinac1, Dalibor Karlovi´c2 and Dragan Babi´c3

Center for Mental Health, Mostar, Bosnia and Herzegovina 2Department of Psychiatry, Catholic University of Croatia, University Hospital Centre Sestre Milosrdnice, Zagreb, Croatia 3Department of Psychiatry, University Hospital Mostar, Mostar, Bosnia and Herzegovina

LIST OF ABBREVIATIONS ADHD CBT DSM-IV-TR DSM-V GABA

attention-deficit/hyperactivity disorder cognitive behavior therapy diagnostic and statistical manual of mental disorders, fourth edition, text revision diagnostic and statistical manual of mental disorders, fifth edition gamma-aminobutyric acid

INTRODUCTION Alcohol abuse worsens gambling problems, entices risky behaviors in gamblers, and contributes to the development and maintenance of a gambling disorder (Stewart & Kushner, 2005). Gambling disorder is a behavioral addiction that overlaps with alcohol and drug addiction, such as losing control, tolerance, and abstinence (Goudriaan, Oosterlaan, de Beurs, & van den Brink, 2006; Lawrence, Luty, Bogdan, Sahakian, & Clark, 2009). The term pathologic gambling from DSM-IV-TR was renamed into gambling disorder in DSM-V and is situated in the section SubstanceRelated and Addictive Disorders (American Psychiatric Association, 2013). Often, a gambling disorder is in comorbidity with alcohol addiction, anxiety, and depressive disorders. Alcohol abuse, on many occasions, precedes gambling development; under the influence of alcohol, gamblers engage more in gambling and spend more money, and it is more probable they will develop a gambling disorder (Jauregui, Estevez, & Urbiola, 2016; Lyvers, Mathieson, & Edwards, 2015). Gamblers who play for larger stakes drink more alcohol than those who play for smaller stakes, which leads to greater alcohol abuse and the

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00054-4

risk of alcohol addiction (Harvanko, Schreiber, & Grant, 2013). In other words, alcohol addiction can predispose the development of a gambling disorder and vice versa (Messerlian, Gillespie, & Derevensky, 2007). It is likely that there are variables pathogenically related to both disorders, such as mutual genetic vulnerability, disturbed dopamine reward brain regulation, premorbid childhood disorder, prenatal alcohol exposure and mother’s alcohol abuse during later childhood, impulsiveness, and compulsive behavior patterns (Choi et al., 2014; Florez et al., 2016; Kully-Martens, Treit, Pei, & Rasmussen, 2013; Stewart & Kushner, 2005; Temcheff, Dery, St-Pierre, Laventure, & Lemelin, 2016; Tran, Clavarino, Williams, & Najman, 2016). Due to dysfunction of ventromedial prefrontal cortex there is an indication of disordered decision-making in gamblers and alcoholics (Goudriaan, Oosterlaan, de Beurs, & van den Brink, 2005). Behavioral and social consequences of alcohol abuse and gambling are very similar; comorbidity in gambling disorder and alcoholism is related to poor treatment response. (Jimenez-Murcia et al., 2016; Josephson, Carlbring, Forsberg, & Rosendahl, 2016; Messerlian et al., 2007; Toneatto, Brands, & Selby, 2009).

ALCOHOLISM AND GAMBLING COMORBIDITY, EPIDEMIOLOGICAL DATA A lifetime prevalence of gambling affects around 86% of adults, while the frequency of a gambling disorder is between 0.5% and 2% of the general population (Dabrowska, Moskalewicz, & Wieczorek, 2017;

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Harries, Redden, Leppink, Chamberlain, & Grant, 2017). Often, alcohol addiction is in comorbidity with a gambling disorder, where the comorbidity is more prevalent in men. Alcohol addiction rates in gamblers are around 73%, and alcoholics are 5 6 times at greater risk to developing a gambling disorder when compared to the general population (Jauregui et al., 2016; Skaal, Sinclair, Stein, & Myers, 2016; Tran et al., 2016). The severity of a gambling disorder is connected with the amount of alcohol consumed and the age when drinking began. Furthermore, the rate of alcoholism is more frequent in pathological gamblers (Florez et al., 2016; Jimenez-Murcia et al., 2016; Miguez Varela Mdel & Becona, 2015; Stewart & Kushner, 2005; Tran et al., 2016; Yip et al., 2013). Apart from alcohol addiction, even acute alcohol abuse increases odds for gambling, encourages persistence in gambling even while experiencing losses, prolongs gambling periods, and encourages gamblers to play for higher stakes (Barrett, Collins, & Stewart, 2015; Kyngdon & Dickerson, 1999). The theory which explains how alcohol incites gambling is called the model of divided attention, according to which alcohol decreases the ability to process available information and limits attention to the most challenging stimuli, or in other words, it leads to cognitive constriction which, in this case, is called alcohol myopia (Cronce & Corbin, 2010).

DEVELOPMENT FACTORS RELATED TO COMORBIDITY BETWEEN ALCOHOLISM AND GAMBLING Alcohol damages brain development in many ways. It interferes with neural proliferation, decreases myelination, and provokes cell death. The consequences of prenatal alcohol exposure are learning and memory disabilities, lower IQ, language disabilities, poor academic performance, disturbed visual-spatial abilities, motor function disturbances, and poor adaptive behavior, attention, and executive functioning. Damage in the frontal cortex and basal ganglia caused by alcohol has a negative effect on the decision-making process, executive function, and learning-experience ability which contributes to impulsive behavior, such as gambling or alcohol abuse (Kully-Martens et al., 2013). Apart from prenatal alcohol exposure, the mother’s drinking patterns have an independent effect on the risk of gambling and alcohol abuse in their children, where male children are more sensitive than females. The mother’s alcohol abuse during their children’s early childhood is related to the risk of gambling and alcoholism when their male children are adults (Tran et al., 2016). Childhood behavior disorders are a very significant, nonspecific, risk factor and are significantly connected

to an increased risk for regular alcohol consumption in early adolescence. A number of symptoms of behavior disorders are related to greater risk of developing heavy alcoholism, earlier start of drinking, and frequent drinking. Apart from alcohol abuse, behavior disorders are closely connected to gambling in adolescents and young adults. (Temcheff et al., 2016).

BIOLOGICAL FACTORS RELATED TO ALCOHOLISM AND GAMBLING COMORBIDITY Alcohol effect is primarily anxiolytic via GABA receptors inhibition in amygdala. Besides, alcohol, on one hand, by affecting the dopamine reward system, strengthens the feeling of reward in the prefrontal cortex while, on the other hand, it inhibits the activity of the prefrontal cortex more than other brain regions. In other words, alcohol has an impact on the increased reward reactivity and on the decreased punishment reactivity (Lyvers et al., 2015). In healthy people, the mesolimbic reward system is activated by standard positive reinforcement. Ventral striatum is activated in reward anticipation and during the reward itself, while the medial prefrontal cortex is only activated during the reward. Unlike healthy people who have mesolimbic reward system active in situations when they win money, in gamblers, the activity in the ventral striatum and ventromedial prefrontal cortex is decreased, which indicates diminished reward sensitivity. In addition, there are indications of functional changes in the area of the mesolimbic reward system, particularly in the ventral striatum, in alcohol addicts where alcohol, instead of positive reinforcing, plays the role of an activator in the ventral striatum area (Lyvers et al., 2015; Romanczuk-Seiferth, Koehler, Dreesen, Wustenberg, & Heinz, 2015). In alcoholic gamblers there is reduced activity in the ventral striatum in the period of reward anticipation and increased activity, or without change, after receiving a reward (Romanczuk-Seiferth et al., 2015). The average amount of invested money during gambling is negatively related to the activation of the striatum in the period while anticipating huge rewards, which can indicate weaker activation in the reward system in those who play with bigger stakes. Heavy drinking in these gamblers serves the purpose to strengthen activation of the reward system (Harvanko et al., 2013). A few theories exist which could explain changes in the limbic reward system and the way these changes contribute to individuals developing addictive behavior. One of the theories puts the process of long-term synaptic potentiation in a central position, which represents experience-related strengthening of synaptic

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BIOLOGICAL FACTORS RELATED TO ALCOHOLISM AND GAMBLING COMORBIDITY

transmission and is considered crucial for learning and memory. This is inevitable in the processes of synaptic plasticity, which is the basis for neural adjustment in the development of tolerance and addiction. It is believed that the mechanism occurs in the dopamine mesolimbic reward system through which alcohol and gambling have gratifying effects on the potentiation of an addiction development (Slutske, Ellingson, Richmond-Rakerd, Zhu, & Martin, 2013). The second theory is concerns sensitization, according to which repeated alcohol abuse or gambling leads to long-term and progressive changes in the brain reward system, acting in a way that alcohol- or gambling-connected stimuli become very attractive and more capable to control emotions than conventional rewards (Romanczuk-Seiferth et al., 2015). The third possibility is that repeated action of facing the loss and avoiding it could result in adjustments in the brain reward system in a way that avoiding money loss becomes dominant in gamblers in relation to natural reward situations (Romanczuk-Seiferth et al., 2015). To sum up, alcohol abuse and gambling can lead to progressive and long-term changes in the dopamine brain reward system and it is possible that these changes in the mesolimbic system represent a biological basis for the development of addiction-related substances as well as substance-free addictions. Structural and functional disorders of the prefrontal cortex and executive function disorders were found in alcoholics and persons with a gambling disorder. Executive functions incorporate the prefrontal cortex’s regular functioning with the accompanying neural circuits in subcortical structures. Executive functions which originate in these brain structures are attention, estimating time, working memory, flexible thinking, planning, using strategies, and inhibition. In alcoholics and gamblers, executive function disorders are manifested through the disorder of objective-oriented behavior, planning, and inhibition. An executive function disorder, on the one hand, can be a direct consequence of alcohol abuse, although, on the other hand, it can be a risk factor for the development of alcohol and gambling addiction (Goudriaan et al., 2006; KullyMartens et al., 2013). Neuroimaging studies show that executive functioning activates different areas within the prefrontal cortex along with areas related to the prefrontal cortex, such as in the nc caudatus, putamen, thalamus, cingulum, and parietal cortex. In gamblers, abnormalities in the ventromedial prefrontal cortex with accompanying neural projections from the thalamus and basal ganglia were found. In alcoholics, disorders and microstructural abnormalities in frontostriatal circuits and the anterior corpus callosum were found (Goudriaan et al., 2006; Yip et al., 2013). Different imaging studies show that structural and functional

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damage in the lateral prefrontal cortex in alcoholics, along with detected acute alcohol effects on executive functions, related to this region (Lawrence et al., 2009). Further damage was noticed in the dorsolateral prefrontal function, presumably caused by structural damage from alcohol intake (Yip et al., 2013). Studies additionally indicate a connection between white matter integrity and impulsiveness. Damage seen in myelination between frontal areas in gamblers were more prevalent in the presence of comorbidity with alcoholism. On the other hand, a correlation was noticed between damaged white matter and alcoholism in alcoholics which also indicates a high prevalence of gambling disorder (Yip et al., 2013). Taking all these observations into account, it is justifiable to assume that damage in the ventral prefrontal cortex with accompanying neural circuits represents a common pathophysiologic basis for the development of alcohol addiction and gambling disorder. Decision-making ability, which is an executive function, is distorted in alcoholics. Decision-making can be divided into decisions based on ambiguity and risk. In ambiguous conditions the decision must be made among different options without explicitly knowing the possible results and the possibility for reward and punishment. In risky situations, decisions are made between options which are consequently rewarded or punished. The dorsal striatum and posterior parietal cortex play a role in the assessment of possible risky outcomes, while the amygdala, striatum, and orbitofrontal cortex are involved in the coding of insecurity levels. Alcohol addiction has harmful effects on executive functions by disturbing activities in frontal regions, such as the dorsolateral prefrontal cortex and frontal cingulate cortex. Alcoholics who develop early alcohol addiction show abnormal tendency for an immediate reward in situations of decision-making (Kim, Sohn, & Jeong, 2011). In this way, alcohol influences decision-making in risky situations and significantly increases the tendency toward risky behavior in the gambling environment. A similar tendency toward taking risks is found in people with damage in the prefrontal cortex regions, and similar deficit is seen in normal persons under the influence of alcohol. According to these findings, alcohol consumption leads to acute dysfunction of the ventromedial prefrontal cortex. Consequently, many casinos serve free drinks during gambling (Lyvers et al., 2015; Slutske et al., 2013). Some research found a genetic relation between gambling disorder and alcohol addiction. The concordance ratio was between 50% and 75%. Results from these studies indicate that gambling and alcoholism have a common genetic background equally present in both males and females (Slutske et al., 2013).

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PERSONALITY TRAITS AND COMORBIDITY OF ALCOHOLISM AND GAMBLING DISORDER Impulsive and Compulsive Behavior Impulsiveness is characterized by a tendency to sudden and unplanned behavior regardless of the possible negative effects. It is believed to be a consequence of the inhibitory control damage which is a basic component of executive function. Inhibitory control is a function of neural circuits in the cortical and subcortical structures, in which the lateral prefrontal cortex is an important part (Choi et al., 2014; Lawrence et al., 2009; Spoelder et al., 2015). Impulsiveness is an important factor in the development and durability of different addiction types, and the relation between impulse control and gambling has been shown in many studies (Barnes, Welte, Hoffman, & Dintcheff, 2002; Florez et al., 2016). Impulsiveness is a strong personality trait in gamblers, (Yip et al., 2013) and a crucial risk factor for developing gambling addiction and severe gambling problems are connected to stronger impulsiveness (Harries et al., 2017). In gamblers, impulsiveness is correlated to cognitive disorders, and impulsive decision-making can increase the possibility for accepting wrong beliefs (Florez et al., 2016). Gamblers with earlier onset of gambling disorder are more impulsive and usually suffer from severe disorder types (Harvanko et al., 2013). In addition, impulsiveness is a risk factor for developing alcohol addiction, prolonging alcoholism, and causing relapse. Alcoholics display reduced impulse control and distorted decisionmaking skills. In other words, impulsive behavior accompanied with distorted decision-making can present a vulnerability factor for alcoholism; it usually precedes alcoholism, although it can be caused by longterm alcoholism (Lawrence et al., 2009; Spoelder et al., 2015) due to the fact that regular alcohol consumption diminishes the individual’s experience-based learning ability (Spoelder et al., 2015). Alcoholics with earlier onset in alcoholism are more impulsive, manifest a greater desire for sensations, show aggressive behavior, and seek immediate rewards (Harvanko et al., 2013). However, alcohol abuse is a risk factor, regardless of impulsiveness, for the progression of a gambling disorder and the tendency towards serious gambling types in men, while alcohol abuse in females is a risk factor for progression of gambling disorder only in the case of an equally present high impulsiveness rate (Barnes et al., 2002; Messerlian et al., 2007). Impulsiveness is a significant risk factor for developing a gambling disorder in both sexes, regardless of alcohol intake, as well as being a risk factor for developing alcoholism. Higher impulsiveness rates are evident in gamblers addicted to alcohol

and also in gamblers with comorbidity alcoholism than in persons who are either alcoholics or gamblers, which corroborates with impulsiveness being a mutual risk factor for developing a gambling disorder and alcohol addiction (Barnes et al., 2002; Florez et al., 2016; Stewart & Kushner, 2005). In alcoholics and gamblers, impulsiveness is at the root of the tendency toward short-term rewards. If regular alcohol use or gambling reoccur during a longer time period, learning mechanisms based on rewards develop into compulsive behavior (Choi et al., 2014), and it is possible that addictive pathology includes progression from impulsiveness to obsessive compulsiveness (Choi et al., 2014). In gamblers with very high impulsiveness rate, alcohol fosters riskier gambling, influences the amount of average stakes, and leads to quicker money loss (Cronce & Corbin, 2010).

Emotion Regulation Apart from impulsiveness, emotion regulation can also be one of the factors which contributes to the development of alcohol addiction and a gambling disorder (Jauregui et al., 2016). Executive function can be divided into cognitive and affective component. The cognitive aspect of executive function is dominant in situations which demand abstract information manipulation and, consequently, carries no reward or punishment. Affective executive function is prevalent in situations which demand the regulation of emotions and motivations, and actions are based on reward and punishment. Daily decision-making involves cognitive aspects, such as impulse control and flexible and responsive responses to cognitive strategies. Nevertheless, in rare occasions, decisions are made without affective or motivational influence, which can interfere with the implementation of the cognitive aspects. (Kully-Martens et al., 2013). Gamblers have difficulties with emotion regulation, and emotion regulation is in direct relation to alcohol abuse. Gambling is connected to the expectation of a positive effect or with diminishing a negative effect, while drinking alcohol soothes negative emotions, reduces stress, increases positive impact, and diminishes desire. Negative emotional states along with bad self-control can lead to impulsive behavior, such as gambling and drinking alcohol, which helps negative emotion regulation (Jauregui et al., 2016).

TREATMENT PROBLEMS In the treatment of patients who are alcoholics with a gambling disorder comorbidity, the complexity of the psychopathology—which is manifested in multiple psychiatric disorders, which besides alcohol addiction

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KEY FACTS

and gambling disorders, are personality disorders, depressive, and anxiety disorders—needs to be taken into consideration (Cowlishaw & Hakes, 2015). Previous experience shows that a small number of patients are being treated and that around 75% have never asked for treatment. The biggest obstacles when entering treatment are the belief that they can resolve their problems on their own, experiencing shame, fear of stigmatization, poor adaptation to program rules, lack of social support, low personal motivation, poor insight into the severity of problem, and a negative opinion of the treatment efficacy. Stigma and shame are barriers which are usually identified in alcoholics and gamblers (Dabrowska et al., 2017). In gamblers there is a negative relation between alcohol abuse and treatment response (Jimenez-Murcia et al., 2016). The treatment of these patients which has proven to be effective includes integrated strategies for resolving gambling problems in comorbidity with alcohol, accompanied with intensive psychotherapy. A therapeutic approach aimed at gambling issues mostly includes modified treatment modalities which are already being used in alcohol addiction such as motivational interviewing, CBT, and relapse prevention. Patients with a gambling disorder in comorbidity with alcoholism will greatly benefit from motivational interviewing (Josephson et al., 2016). Brief interventions aimed at reducing gambling can also be helpful (Jimenez-Murcia et al., 2016). Using a pharmacological approach, there have been attempts of introducing naltrexone in the treatment of comorbidity of alcohol addiction and gambling disorder. However, treatment with naltrexone has not proven to be more efficient than a placebo in reducing drinking alcohol or with a reduction of gambling in alcoholics with a gambling disorder (Toneatto et al., 2009). It has been noted that methylphenidate in patients with ADHD improves decision-making processes and decreases the tendency towards risky behavior, and, given its beneficial effect on the executive function disorders in ADHD patients, it would be justified to consider this kind of treatment for gambling and alcohol addicts (DeVito et al., 2008; Goudriaan et al., 2006). An additional problem is comorbidity with other psychiatric disorders, such as personality, depressive, and anxiety disorders. In such cases, pharmacological treatment of comorbidity states according to existing guidelines for the treatment of psychiatric disorders is used (Babi´c, 2016).

CONCLUSION Alcohol drinking and gambling are mutually connected activities and the comorbidity of alcoholism

and a gambling disorder is more of a rule than an exception. Apart from the fact that one disorder can precede the other, and vice versa, alcoholism and gambling disorders share mutual genetic vulnerability, they are influenced by similar neurodevelopmental factors and personality traits, and entail similar brain changes. Comorbidity of alcoholism and a gambling disorder is by far a more serious clinical and social problem than the individual disorders. Comorbidity is stigmatized, and often is concomitant with a lack in treatment cooperation with resulting unsatisfactory outcomes in many cases. It is indicative to perform further research for the purpose of finding appropriate treatments for these patients.

MINI-DICTIONARY OF TERMS Behavioral addiction Addiction to a behavior like gambling rather than to a drug. Comorbidity The simultaneous presence of two chronic conditions in a patient. Reward system The reward system is a group of neural structures responsible for positive emotions. Impulsiveness Tendency to act without consideration of consequences. Compulsive behaviors Actions that people feel driven to do that they cannot resist or control. Cognitive behavior therapy This psychotherapy method combines the techniques of cognitive psychotherapy and behavior therapy. Relapse Recurrence of alcohol abuse in an individual who has previously achieved and maintained abstinence for a significant period of time beyond withdrawal. Lifetime prevalence The proportion of individuals in a population that at some point in their lives have experienced a disease or a negative/destructive behavior. Positive reinforcement The presentation of a stimulus that increases the future likelihood that a behavior will occur.

KEY FACTS Alcohol and Gambling Disorder • The comorbidity of alcoholism and gambling disorder is more a rule than an exception. • One disorder can precede the other, and vice versa. • Alcoholism and gambling disorders share mutual, genetic vulnerability. • The mesolimbic reward system is deficient in both disorders. • Structural and functional disorders of the prefrontal cortex and deficient executive functioning are found in both disorders. • Impulsivity is a significant personality trait in both disorders.

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SUMMARY POINTS • Alcohol abuse usually precedes the development of a gambling disorder. • Comorbidity of alcohol addiction with a gambling disorder is more prevalent in men. • The severity of a gambling disorder is related to the amount of alcohol consumed and the age when the drinking began. • Possible variables which may contribute to pathogenesis of these disorders are: • genetic vulnerability • prenatal alcohol exposure • mother’s alcohol abuse during childhood • conduct problems in childhood • impulsive and compulsive behaviors • deficit emotion regulation • dysregulation of the dopamine reward system • defects in the prefrontal cortex • deficient executive functioning • Comorbidity between gambling disorder and alcoholism is related to poor response to treatment.

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55 Neuroscience of Alcohol and Crack Cocaine Use: Metabolism, Effects and Symptomatology Antonio Gomes de Castro-Neto1, Rossana Carla Rameh-de-Albuquerque2, Pollyanna Fausta Pimentel de Medeiros2 and Roberta Uchoˆa3 1

Study Group on Alcohol and other Drugs, Research Group on Biomedical Nanotechnology, Department of Pharmaceutical Sciences, Federal University of Pernambuco, Recife, Brazil 2Study Group on Alcohol and other Drugs, Federal University of Pernambuco, Recife, Brazil 3Study Group on Alcohol and other Drugs, Department of Social Work, Federal University of Pernambuco, Recife, Brazil

LIST OF ABBREVIATIONS ACTH CBT CE CRH DIS hCE-1 LE NMDA NTX SD

adrenocorticotropic hormone cognitive-behavioral therapy cocaethylene corticotropin-releasing hormone disulfiram human carboxylesterase-1 Lond-Evans rats N-methyl-D-aspartic acid naltrexone Sprague-Dawley rats

INTRODUCTION Many authors state that alcohol is an “open door” to other drugs (Barbosa et al., 2015; Jorge, Quindere, Yasui, & Albuquerque, 2013). Some qualitative studies on crack cocaine users show that alcohol use was commomplace among their relatives and, in some cases, family members were alcohol dependent (Scheffer, Pasa, & Almeida, 2010; Seleghim & Oliveira, 2013). In addition, other studies indicated that because alcohol is a licit drug, easily available, and relatively cheap, it became a socialization tool to young people (Barbosa et al., 2015; Silva & Padilha, 2011). Studies related to drug relapse show that alcohol plays an important role in most drug treatment process (Marlatt & Gordon, 1985). It is considered a “trigger” to the use of other drugs (Carroll, 1998),

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00055-6

especially crack cocaine. The relationship between alcohol and crack cocaine consumption becomes clear among those users who seek treatment. In Brazil, the magnitude of this association can be seen through the prescription drug, disulfiram (DIS), one of the most commom substances used during treatment as a means to reduce alcohol drinking and, thus, crack cocaine use (Castro & Batieri, 2004). Pain and physical discomfort are frequent reactions to simultaneous use of DIS and alcohol, which leads to reduction of alcohol intake (Carroll et al., 2004). Despite DIS prescription, alcohol appears as an obstacle to crack cocaine treatment. Users state that simultaneous use of alcohol and crack cocaine increases the effects of both drugs, and since alcohol is easily available at home and elsewhere, it is harder to carry on with treatment (Acioli Neto, 2014). Therefore, it is important to understand the users’ perspective on why they use crack cocaine and alcohol simultaneously in the attempt to find better treatment strategies and achieve better results. Many users state that when they use alcohol during crack cocaine use, they feel an increased thrill as well as they have a longer lasting “trip.” Users’ stories, as well as the observation of drug use scenes, show how alcohol plays a decisive role among crack cocaine users.

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When she finishes smoking, Katicilene puts a bit of alcohol in her pipe and burns it. According to her, this thecnic helps

© 2019 Elsevier Inc. All rights reserved.

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to reach crack remains in the pipe quicker. After the pipe is burned, with the help of a metal wire, she rubs its black rest, “crack residue.” This residue is set again in the pipe and burned by Katicilene: so she can have a more concentrated crack cocaine dose. Malheiro (2012, p. 91).

And yet: She puts alcohol in her pipe, burn it all together and then again with the help of a metal wire, she rubs a viscous substance, that is reused with ashes and burned in the pipe. Malheiro (2012, p. 92).

This strategy to obtain better crack cocaine combustion may explain why alcohol is commonly present at most crack cocaine scenes as it facilitates simultaneous use of these drugs. Many users state that alcohol, besides being a trigger to crack cocaine use, aggravates mental confusion more than when crack cocaine is used alone. After alcohol use, the loss of control is higher and the bigger the craving becomes to use crack cocaine repeatedly. As stated before, the mixture of alcohol and crack cocaine worsen consumption conditions, aggravates crack cocaine dependence, and may facilitate multiple and crossed dependences, as well as possibly making treatment and social reintegration more difficult (Acioli Neto, 2014; Barbosa et al., 2015). Crack cocaine users submitted to treatment are likely to withdraw from the treatment because of law conflicts, few social abilities, family mental disorder histories, and alcohol dependence (Duailibi, Ribeiro, & Laranjeira, 2008).

CONSUMPTION United States surveys on multiple-drug use show that concurrent cocaine/crack cocaine and alcohol consumption is higher than simultaneous use for all combinations of alcohol with other drugs. Prevalence figures for simultaneous (0.9%) and concurrent (0.8%) cocaine/crack cocaine and alcohol use from a survey carried out in 2000 (Midanik, Tam, & Weisner, 2007) are considerably lower than prevalence figures for simultaneous (4.7%) and concurrent (6.1%) use of these drugs from a survey in 1990 (Grant & Harford, 1990). These discrepancies might be due to different methodological procedures (e.g., sample size and questionnaire protocol) and should be the object of further research. A crack cocaine survey carried out in Brazil showed that 77% of its users are also alcohol drinkers. These figures are even higher (81%) in cities that are not state capitals (Bastos & Bertoni, 2014). Another survey undertaken in Recife, Northeast Brazil, showed that

42% of crack cocaine users, under drug treatment in specialized public health services between 2010 and 2011, also used alcohol (GEAD - Grupo de Estudos ´ lcool e outras Drogas, 2010). Figures in Recife, sobre A a state capital, are lower than the national average, yet the Brazilian average is much higher than that in the United States, probably due to the socioeconomic differences between the two countries (UNODC - United Nations Office on Drug & Crime, 2017).

ALCOHOL AND CRACK COCAINE MIXTURE METABOLISM Combined alcohol and crack cocaine use increases cocaine and norcocaine plasma levels, reduces benzoylecgonine concentration, and induces cocaethylene synthesis in the liver. Alcohol (ethanol) inhibits the methylesterase hydrolisis of cocaine to benzoylecgonine. Cocaethylene is the only cocaine metabolite that is shaped during alcohol presence. This substance, also called benzoyl ecgonine ethyl ester or benzoylethylecgonine, as a result of ethyl transesterification, in which the cocaine carboxymethyl group is transesterificated into carboxyethyl during alcohol presence mediated by hCE-1 (Fig. 55.1). This reaction only occurs when there is silmultaneous alcohol and cocaine use. One of the most important aspects of cocathylene formation is that this substance has a pharmacological action comparable to cocaine (Song, Parker, & Laizure, 1999) (Fig. 55.1). Due to strucutural similarities between cocaine and cocaethylene, the later follows the same kinetics patterns as its precursor (Fig. 55.2). As cocaine, cocaethylene presents α-1-acid glicoprotein with a higher affinity and crosses the placentary barrier at a similar speed as cocaine, resulting in benzoylecgonine, ecgonine ethyl ester, norcocaethylene, and other bioactive products during its oxidation (Chasin & Midio, 1997) (Fig. 55.2). As cocaethylene has a strucutural homology very similar to cocaine, it is hypothetized that it could have similar neurochemichal and behavioral properties. It was found that cocaethylene has the same potency as cocaine to inhibit specific ligant biding to the dopamine reuptake complex and to inhibit dopamine increase in synaptosomes, as well as and the capability to increase dompamine extracellular concentration after administration in rats (Fig. 55.3). It is believed that the mechanism of cocaine’s positive reinforcement properties involves dopamine reuptake inhibition with the consequent synaptic dopamine increased levels related to reward mechanism. It was also observed locomotory activity stimulation and lifts movement in rats after systemic administration of cocaethylene,

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FIGURE 55.1 Cocaine hepatic transesterification in cocaethylene. Transesterification reaction of cocaine and ethanol is mediated by hCE-1 resulting in cocaethylene synthesis in liver.

FIGURE 55.2 Cocaine and cocaethylene metabolites. Metabolic paths of cocaine and cocaethylene. 1 5 carboxylesterase; 2 5 plasma cholinesterase (EC 3.1.1.8); 3 5 cytochrome P450; Δ 5 heat.

suggesting that this metabolite could share cocaine psychostimulant properties. (Jatlow et al., 1991) (Fig. 55.3). The time of alcohol and crack cocaine administration seems to be vital to determine whether alcohol does, or does not, inhibit cocaine metabolism. Studies with rats showed that blood cocaine concentration is directly related to ethanol concentration. Cocaine blood concentration significantly reduced to 5400 ng/mL in 20 minutes to 3200 ng/mL in 60 minutes and 2000 ng/mL in

100 minutes after the coadministration of 40 mg/kg of cocaine and 3.3 g/kg of alcohol. However, it was noted that alcohol blood concentration were comparable to the group of rats treated with 3.3 g/kg of ethanol at 60 μg/ dL in 20 minutes (240 mg/dL) postinjection; in turn, cocaine metabolism was only inhibited among the group treated with ethanol at 5.0 g/kg (Chen & West, 1998). The order of alcohol and crack cocaine intake is also an important factor which influences the effect of their interaction. When alcohol is used before crack cocaine

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FIGURE 55.3 Cocaethylene’s main mechanism of action. Cocaethylene binds to dopamine reuptake complex resulting in dopamine increase at the synaptice cleft.

administration, there is a significant increase in plasma cocaine concentration, its subjective effects, and in cardiac frequency. On the other hand, when crack cocaine intake is before alcohol, there are no changes in plasma cocaine concentration, its subjective effects, and in cardiac frequency due to slower cocaethylene formation (Perez-Reyes, 1994). Cocaethylene presents a higher brain-to-plasma distribution ratio (1.44 6 0.17) than cocaine (1.18 6 0.26) and other cocaine metabolites, like norcocaine (0.97 6 0.14) and benzoylecgonine (0.147 6 0.032). Body total clearence estimates for cocaine and cocaethylene are 140 6 19 and 111 6 16 mL/minutes/kg, respectively. This substance has more potent and prolonged effects in neurochimical and cardiac responses and QRS interval, having the same potential as cocaine to increase mean arterial pressure (Pan & Hedaya, 1999). Cocaethylene half-life time is around 2.5 hours, almost four times higher than cocaine’s half-life time (40 minutes). Cocaethylene may be stored in body tissues and its slower clearence makes it more likely to become a drug of abuse (Harris, Everhart, Mendelson, & Jones, 2003). Cocaethylene binds to dopamine transporters with similar affinity, but is not identical to cocaine. It also has higher noradrenaline transporter affinity at the cortical neurons than cocaine. Besides these properties, cocaethylene is 40 times less potent

than cocaine when it interacts with serotonine receptors (Rose, 1994). These results show changes in cocaine’s metabolic profile and cocaethylene’s active pharmacological metabolic formation are, at least partially, responsible for its longer and more intense euphoric effects reported by users after a long period of simultaneous alcohol and crack cocaine use. In summary, the simultaneous use of alcohol and crack cocaine produces a significant increase in cocaine’s euphoric effects, psycomotor performance, cardiac frequency, and arterial pressure, compared with the isolated use of either drug, as well as reducing drunkenness feelings. Due to cocaethylene binds with high affinity to dopamine transporters, this leads to an increase in dopamine extracellular concentration in brain regions related to craving.

COCAETHYLENE AND ITS NEURAL SYSTEM ACTIONS Cocaethylene induces ACTH and corticosterone/ cortisol secretions in rats, nonhuman primates, and humans. These two hormones, along with CRH, constitute hypothalamus-hypophysis-adrenal axis, which is the most important homeostasis regulating region in these mammals’ bodies. Consequently, the synthesis

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FIGURE 55.4 Cocaethylene action at hypothalamus-hypophysis-adrenal axis. Cocaethylene acts on the hypophysis stimulating secretion of ACTH.

and secretion of these hormones are needed for stressing stimulus to promote adequate and adapted behavioral answers (Fig. 55.4). Evidence suggests that the activation of this axis can be an important factor to determine induced vulnerability by drug abuse stress (Torres, Horowitz, Lee, & Rivier, 1996) (Fig. 55.4). Cocaethylene formation in vivo produces its own euphoric and pleasure rewarding effects through the interaction with neural systems that usually are affected by the particular effects of alcohol and cocaine. Therefore, cocaethylene can reinforce drug use brain circuit adaptations, that could be related to drug dependence mechanisms (Torres et al., 1996). Cocaethylene induces a FOS-like protein neuronal expression inside striatal neurons susceptible to the drug. The FOS-like protein is a transcription protein that can regulate subsequent wave patterns of gene expression, mediating long-term consequences of trans-synaptic stimulation. FOS-like proteins induced by cocaethylene occur within 1 hour after administration and has a duration of around 6 hour. The increase of protein levels is quick and relatively short-lived (Horowitz, DiPirro, Kristal, & Torres, 1997). Yet, cocaethylene induces c-fos gene transcription in neural substracts related to drug use. Preliminary intracellular mechanisms that mediate this nuclear induction have been determined as being regulated, at least in part, by D1 and NMDA subtype receptors. Although opiate ligands, such as dinorfine, are capable to influence dopaminergic neurons’ activity in striatal neurons in rats, known selective kappa opiate agonist receptors could not overcome FOS-like protein induction observed after cocaethylene administration. The mechanisms for this effect are not known, although it could be due to the pharmacological differences between cocaine and cocaethylene (Horowitz et al., 1997). Cocaethylene is the most potent phosphoinosite metabolite and binder inhibitor. The effect from cocaine was more prominent in muscarinic receptors, although a small histamin metabolic inhibiton and

phosphoinosites-stimulated serotonin was also observed (Tan & Costa, 1994). Cocaine and cocaethylene interaction with phosphoinosites metabolism stimulated by muscarinic receptors can be relevant to certain aspects of neurotoxicity in body development. In addition, opposite to ethanol’s effects, where the interaction with this system may be limited to specific periods of time during growth peak, cocaine effects are mediated by the interaction with muscarinic bind sites and could be involved in phosphoinosites system interruption, even in adults. In this respect, this demonstrates the changes in cocaine-dependent, brain-phospholipid metabolites (Tan & Costa, 1994). Myoinositol’s low concentration in the dorsolateral prefrontal cortex of alcohol and cocaine users were found in comparison with alcohol-dependent users and low drinkers through 1H magnetic ressonance spectroscopy. However, myoinositol’s precise function is still being debated, but it has been suggested that it is an astroglial matter marker. Increase in astroglial matter is interpreted as hypertrophy and/or astroglial proliferation that affects brain function negatively. Once the dorsolateral prefrontal cortex has volumes of interest of white substance, myoinositol reduction can indicate glial matter loss and/or damage (e.g., astrocytes) related to multiple drug consumption. Myoinosotol reduction can also happen through its synthesis or absorption inhibition (Abe et al., 2013). Using the sucrose gap recording technique, cocaethylene shows a prolonged pattern of axonal impulse inhibition compared to cocaine. A patch clamp study of full cells indicated that, like cocaine, the mechanism of action was sodium channel block (Fig. 55.5). As action potential block duration was longer with cocaethylene, it can cause cocaethylene euphoric effects in humans. However, the same study, showed equivalent effects over in vitro and in vivo extracellular dopamine (Tokuno et al., 2004) (Fig. 55.5).

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FIGURE 55.6

Main disulfiram effects. Disulfiram mechanisms are related to decreased use of alcohol and cocaine.

FIGURE 55.5 Cocaethylene mechanism of action at sodium channel. Cocaethylene blocks sodium channels resulting in a localized anesthetic effect.

Yet, cocaethylne can indulce tonic-clonic convultions and epiletic states in animals similarly to cocaine, and can cause cross sensibilization when cocaine is used after cocaethylene (Meehan & Schechter, 1996). Alcohol and cocaine combined produce a taste aversion among rats in relation to isolated drugs, and also produces higher avertions to what would be expected if individual drug effects were added. These results indicate a synergic interaction between alcohol and cocaine. Despite this, cocaethylene effects alone are relatively weak, comparatively. Unlike that alcohol, cocaine and cocaethylene added aversive effects when separately administrated and represent a group of increased aversive effects than when alcohol and cocaine are simultaneously used. Although alcohol and cocaine combined shows toxicological synergism in taste avertion learning, the mechanism for this synergism seems to be unknown (Etkind, Fantegrossi, & Riley, 1998). LE rats show less behavioral sensibily to cocaethylene than SD rats. Dopamin and serotonin basal synthesis rates in different brain regions do not differ between LE and SD rats. Cocaethylene caused significant inhibition dopamine synthesis in the caudate and accumbens nucleus in both rat types. While cocaethylene also tends to a reduction of serotonin synthesis in LE and SE rat brains, this effect is relatively weak. This data suggest that differences in dopamin and serotonin transmission cannot represent cocaethylene’s differential behavioral effects in LE and SD rats. However, it the possibility should not be rejected that fundamental differences in

monoamine functions (e.g., transmission liberation mechanism or postsynaptic sensibility of receptors) exist in these types of rats, but were not detected by the methods applied in these studies. Other studies are needed to determine the neurobiological substracts to mediate cocaethylene behavioral insensibility observed in LE rats (Baumann, Horowitz, Kristal, & Torres, 1998). A randomized controlled study with 12 individuals showed that CBT was the best approach to take for the treatment of alcohol and cocaine codependence. In this study, three of four subjects designated to the CBT group finished the 12-week treatment period and reduced consumption, but did not quit drugs. Although all subjects in the DIS/CBT or NTX/CBT groups reduced intake during treatment, only one one individual in the DIS/CBT group was still under treatment at the same period of time. During the first 4 weeks, DIS/CBT significantly reduced positive urine analyses percentages for both, cocaine and cocaethylene, suggesting that DIS was effective to prevent alcohol and cocaine intake (Grassi, Cioce, Giudici, Antonilli, & Nencini, 2007). This finding is consistent with results from another study and can be the result of convergent mechanisms induced by DIS in different enzimatic sythems (Carroll et al., 2004). Aldehyde dehydrogenase enzyme inhibition by DIS is one of the mechanisms that reduce alcohol intake due to the increase of acetaldehyde levels which leads to symptoms such as facial flushes, weakness, headache, nausea, vomiting, sweating, vertigo, hypotension, and other unpleasant symptoms. Inhibition of dopamine hydroxylase due to DIS use increases dopamine levels, and since cocaine is a potent dopamine reuptake inhibitor, DIS reduces craving for cocaine, changing the pleasure sensation promoted by drug use. (Gaval-Cruz & Weinshenker, 2009; Manvich, DePoy, & Weinshenker, 2013) (Fig. 55.6). Although some literature suggests that cocaethylene is an alcohol marker consumption, a recent study suggests that ethylecgonine, the cocaethylene metabolite, can be a better marker for combined alcohol and cocaine consumption (Kapur, 2014).

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REFERENCES

FINAL CONSIDERATIONS Despite simultaneous alcohol and crack cocaine use being well-described since 1990, there are few recent studies on its pharmacological mechanisms. Many studies refer to cocaethylene administration, the cocaine-active metabolite when used simultaneously with alcohol, in animals, but not in humans. However, in practice, cocaethylene is not administrated in humans as it is a result of liver enzymatic mechanisms. Surveys of multiple-drug use have great variations in their results, probably due to there being no criteria to evaluate simultaneous and concurrent drug use. Frequently, drug users are not only single drug users, therefore, there is an urgent need to establish better data collection and analysis techinques to improve multiple-drug use identification. As a result of cocaethylene’s more intense and longer effects than cocaine alone, its toxicity becomes greater, causing several health problems, especially in the brain. Neurotransmitters and hormone synthesis and secretion changes have systemic and behavioral consequences among drug users, in turn, making treatment of drug dependence more complicated. Alcohol can act as a trigger for crack cocaine use. Despite the simultaneous consumption of alcohol and crack cocaine, the effects of alcohol are reduced while the effects fo cocaine become more intense and longer due to the formation of cocaethylene. Because of this, crack cocaine use can be an aggravation in an alcohol user’s treatment. By using both drugs simultaneously, the user can minimize the effects of alcohol, but this makes cocaine addiction more difficult to treat. A better understanding of alcohol and crack cocaine use patterns and their pharmacological mechanisms needs to be carried out to establish better and more efficient prevention and treatment strategies.

MINI-DICTIONARY OF TERMS Relapse When a person tries to modify or quit a problematic behavior, for example, problematic drug use, but fails. Trigger Motivation that leads to relapse. It can be caused by an internal (emotional or psychological) or an external (friends influence) drive. Concurrent use Use of alcohol and other drugs during the same time period. Simultaneous use Use of alcohol and other drugs at the same time. Transesterification Chemical reaction when the alcohol of ester reagent is substituted by another alcohol. FOS-like protein Protein used as a neuronal active marker after a given stimulus. c-fos gene Human homologous of retroviral v-fos proto-oncogene, involved with cancer transformation and progression.

Phosphoinositides Phosphorylited phospholipids are derived from phosphatidylinositol use as intermediaries of cell receptors signaling pathways. Myoinositol Substance that acts in animal and microorganism growing factors which has an important role as a structural base to eukaryotic cell secondary messengers, such as inositol phosphate. Behavioral-cognitive therapy Psychotherapy based on empirical psychology which includes specific and nonspecific methods (related to mental disorders).

KEY FACTS Cocaethylene • Crack cocaine users are frequently alcohol users. • Simultaneous crack cocaine and alcohol use produces more intense and longer effects. • Simultaneous crack cocaine and alcohol use produces an active metabolic called cocaethylene. • Cocaethylene’s half-life time is four times longer than cocaine, and has similar effects. • Cocaethylene makes drug-dependence treatment more difficult due to its more intense and longer effects.

SUMMARY POINTS • This chapter is concerned with simultaneous and concurrent crack cocaine and alcohol use. • Simultaneous and concomitant crack cocaine and alcohol use are commom among crack cocaine users. • After simultaneous and concurrent crack cocaine and alcohol use, a transesterification reaction occurs in the liver which produces cocaethylene. • Cocaethylene is a cocaine active metabolic with similar, but more intense and longer, effects. • Cocaethylene may cause several neurological problems as well as making drug-dependence treatment more difficult.

References Abe, C., Mon, A., Durazzo, T. C., Pennington, D. L., Schmidt, T. P., & Meyerhoff, D. J. (2013). Polysubstance and alcohol dependence: Unique abnormalities of magnetic resonance-derived brain metabolite levels. Drug and Alcohol Dependence, 130, 30 37. Acioli Neto, M. (2014). Os contextos de uso do crack: representac¸o˜es e pra´ticas sociais entre usua´rios. Recife: Novas Edic¸o˜es Acadeˆmicas. Barbosa, K. K. S., Rocha, W. S., Vieira, K. F. L., Alves, E. R. P., Leite, G. O., & Dias, M. D. (2015). Concepc¸o˜es de usua´rios de crack acerca da droga. Revista de Enfermagem da UFSM, 5, 286 294. Bastos, F.I., & Bertoni, N. (2014). Pesquisa Nacional sobre o uso de crack: Quem sa˜o os usua´rios de crack e/ou similares do Brasil? Quantos sa˜o nas capitais brasileiras? Rio de Janeiro: Editora ICICT/FIOCRUZ. Baumann, M. H., Horowitz, J. M., Kristal, M. B., & Torres, G. (1998). Effects of cocaethylene on dopamine and serotonin synthesis in

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Long-Evans and Sprague-Dawley brains. Brain Research, 804, 316 319. Carroll, K. M. (1998). A cognitive-behavioral approach: Treating cocaine addiction. Rockville: National Institute on Drug Abuse. Carroll, K. M., Fenton, L. R., Ball, S. A., Nich, C., Frankforter, T. L., Shi, J., & Rounsaville, B. J. (2004). Efficacy of disulfiram and cognitive behavior therapy in cocaine-dependent outpatients. Archives of General Psychiatry, 61, 264 272. Castro, L. A., & Batieri, D. A. (2004). The phamacologic treatment of the alcohol dependence. Revista Brasileira de Psiquiatria, 26, 43 46. Chasin, A. A. M., & Midio, A. F. (1997). Exposic¸a˜o humana a` cocaı´na e ao cocaetileno: disposic¸a˜o e paraˆmetros toxicocine´ticos. Revista de farma´cia e bioquı´mica da Universidade de Sa˜o Paulo, 33, 1 12. Chen, W. J. A., & West, J. R. (1998). Alcohol-induced inhibition of cocaine metabolism and the formation of cocaethylene in neonatal rats. Neurotoxicology and Teratology, 20, 565 570. Duailibi, L. B., Ribeiro, M., & Laranjeira, R. (2008). Profile of cocaine and crack users in Brazil. Cadernos de Sau´de Pu´blica, 24, s545 s557. Etkind, S. A., Fantegrossi, W. E., & Riley, A. L. (1998). Cocaine and alcohol synergism in taste aversion learning. Pharmacology Biochemistry and Behavior, 59, 649 655. Gaval-Cruz, M., & Weinshenker, D. (2009). Mechanisms of disulfiram-induced cocaine abstinence: Antabuse and cocaine relapse. Molecular Interventions, 9, 175 187. ´ lcool e outras Drogas. (2010). GEAD - Grupo de Estudos sobre A Entre pedras e tiros: perfil dos usua´rios, estrate´gias de consumo e impacto social do uso do crack [DVD-ROM]. Recife: FACEPE. Grant, B. F., & Harford, T. C. (1990). Concurrent and simultaneous use of alcohol with cocaine: Results of national survey. Drug and Alcohol Dependence, 25, 97 104. Grassi, M. C., Cioce, A. M., Giudici, F. D., Antonilli, L., & Nencini, P. (2007). Short-term efficacy of disulfiram or naltrexone in reducing positive urinalysis for both cocaine and cocaethylene in cocaine abusers: A pilot study. Pharmacological Research, 55, 117 121. Harris, D. S., Everhart, E. T., Mendelson, J., & Jones, R. T. (2003). The pharmacology of cocaethylene in humans following cocaine and ethanol administration. Drug and Alcohol Dependence, 72, 169 182. Horowitz, J. M., DiPirro, J. M., Kristal, M. B., & Torres, G. (1997). Dopaminergic and glutamatergic mechanisms mediate the induction of FOS-like protein by cocaethylene. Brain Research Bulletin, 42, 393 398. Jatlow, P., Elsworth, J. D., Bradberry, C. W., Winger, G., Taylor, J. R., Russel, R., & Roth, R. H. (1991). Cocaethylene: A neuropharmacologically active metabolite associated with concurrent cocaineethanol ingestion. Life Sciences, 48, 1787 1794. Jorge, M. S. B., Quindere, P. H. D., Yasui, S., & Albuquerque, R. A. (2013). Ritual de consumo do crack: aspectos socioantropolo´gicos e repercusso˜es para a sau´de dos usua´rios. Cieˆncia & Sau´de Coletiva, 18, 2909 2918. Kapur, B. (2014). Is cocaethylene a marker of ethanol use in cocaine users? Clinical Biochemistry., 47, 1151.

Malheiro, L. (2012). Tornando-se um usua´rio de crack. In A. NeryFilho, E. MacRae, L. A. Tavares, M. Reˆgo, & M. E. Nun˜ez (Eds.), As drogas na contemporaneidade perspectivas clı´nicas e culturais. Colec¸a˜o drogas: clı´nica e cultura. Salvador: EDUFBA/CETAD. Manvich, D. F., DePoy, L. M., & Weinshenker, D. (2013). Dopamine β-hydroxylase inhibitors enhance the discriminative stimulus effects of cocaine in rats. Journal of Pharmacology and Experimental Therapeutics, 347, 564 573. Marlatt, G. A., & Gordon, W. H. (1985). Relapse prevention Introduction na overview of the model. British Journal of Addiction., 79, 261 273. Meehan, S. M., & Schechter, M. D. (1996). Cocaethylene-induced kindling of seizure effects: Cross-specificity with cocaine. Pharmacology Biochemistry and Behavior, 54, 491 494. Midanik, L. T., Tam, T. W., & Weisner, C. (2007). Concurrent and simultaneous drug and alcohol use: Results of the 2000 National Alcohol Survey. Drug and Alcohol Dependence, 90, 72 80. Pan, W. J., & Hedaya, M. A. (1999). Cocaine and alcohol interactions in the rat: Contribution of cocaine metabolites to the pharmacological effects. Journal of Pharmaceutical Sciences, 88, 468 476. Perez-Reyes, M. (1994). The order of drug administration: Its effects on the interaction between cocaine and ethanol. Life Sciences, 55, 541 550. Rose, J. S. (1994). Cocaethylene: A current understanding of the active metabolite of cocaine and ethanol. American Journal of Emergency Medicine, 12, 489 490. Scheffer, M., Pasa, G. G., & Almeida, R. M. Mde (2010). Dependeˆncia de a´lcool, cocaı´na e crack e transtornos psiquia´tricos. Psicologia: Teoria e Pesquisa, 26, 533 541. Seleghim, M. R., & Oliveira, M. L. Fde (2013). Influeˆncia do ambiente familiar no consumo de crack em usua´rios. Acta Paulista de Enfermagem, 26, 263 268. Silva, S. E´. D., & Padilha, M. I. (2011). Atitudes e comportamentos de adolescentes em relac¸a˜o a` ingesta˜o de bebidas alcoo´licas. Revista da Escola de Enfermagem da USP, 45, 1063 1069. Song, N., Parker, R. B., & Laizure, S. C. (1999). Cocaethylene formation in rat, dog, and human hepatic microsomes. Life Sciences, 64, 2101 2105. Tan, X. X., & Costa, L. G. (1994). Inhibition of muscarinic receptorstimulated phosphoinositide metabolism by cocaine, norcocaine and cocaethylene in rat brain. Developmental Brain Research, 79, 132 135. Tokuno, H. A., Bradberry, C. W., Everill, B., Agulian, S. K., Wilkes, S., Baldwin, R. M., . . . Kocsis, J. D. (2004). Local anesthetic effects of cocaethylene and isopropylcocaine on rat peripheral nerves. Brain Research, 996, 159 167. Torres, G., Horowitz, J. M., Lee, S., & Rivier, C. (1996). Cocaethylene stimulates the secretion of ACTH and corticosterone and the transcriptional activation of hypothalamic NGFI-B. Molecular Brain Research, 43, 225 232. UNODC - United Nations Office on Drug and Crime. (2017). World Drug Report 2017. Vienna: United Nations Publication.

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56 The Impact of Ethanol Plus Caffeine Exposure on Cognitive, Emotional, and Motivational Effects Related to Social Functioning 1

Merce` Correa1,2, Laura Lo´pez-Cruz1,3, Simona Porru1,4 and John D. Salamone2

Department of Psychobiology, University Jaume I, Castello, Spain 2Department of Psychology, University of Connecticut, Storrs, CT, United States 3Department of Psychology, University of Cambridge, Cambridge, United Kingdom 4Department of Life and Environmental Sciences, University of Cagliari, Cagliari, Italy

LIST OF ABBREVIATIONS ACg ACo BLA CeA Core DA DARPP-32 DMS ENT IL IP KO MeA MSN Nacb OT PrL Shell WT

anterior cingulated cortex anterior cortical nucleus of the amygdala basolateral nucleus of amygdala central nucleus of amygdala nucleus accumbens core dopamine dopamine-regulated and cAMP-regulated phosphoprotein Mr 32 kDa dorsomedial striatum equilibrative nucleoside transporter infralimbic cortex intraperitoneal knockout medial nucleus of amygdala median spiny neuron nucleus accumbens olfactory tubercle prelimbic cortex nucleus accumbens shell wild type

CAFFEINE AS A MODULATOR OF ETHANOL ABUSE LIABILITY Methylxantines such as caffeine or theophylline—in traditional forms as coffee, tea, or mate—are some of the most common psychoactive substances consumed

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00056-8

in the world. Interest in caffeine has grown ever since the introduction of energy drinks into the market, which contain variable and unregulated concentrations of caffeine and related substances, usually in quite high concentrations. Energy drinks are used by consumers to improve cognitive and athletic performance, increasing concentration and memory, and reducing fatigue (Lalanne, Lutz, & Paille, 2017). These highly caffeinated beverages are often consumed in combination with alcohol because of the popular belief that caffeine can counteract some of the disruptive effects of ethanol on cognitive function and motor impairments, especially during episodes of binge drinking. However, the ability of energy drinks to counteract these effects depends on the degree of alcohol intoxication and the volume of energy drinks consumed (Peacock, Cash, & Bruno, 2015). Combined consumption often leads to a reduction in perceived ethanol intoxication, that among young people, can increase impulsivity, and risk-taking behaviors, such as unprotected sex, fighting, or drunk driving (Snipes, Jeffers, Green, & Benotsch, 2015). Adolescent risk-taking typically occurs when they are with peers. The presence of peers is a very salient stimulus that can increase motivation (Salamone & Correa, 2012), inducing a behavioral activation that, when pathological, can lead to aggression and foraging

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for drugs, as well as overwhelming adolescents’ immature capacity for inhibitory control. The presence of “peers” increases alcohol consumption among adolescent mice, but not among adults (Logue, Chein, Gould, Holliday, & Steinberg, 2014). Thus, social environments are very relevant for drug consumption, and drugs can help to redefine social roles. Drugs can also modulate internal states that, in turn, can potentiate or impair social activities. Interestingly, while the intake of energy drinks alone has been associated with the use of cocaine and nicotine, the consumption of ethanol mixed with energy drinks is more common among cannabis and heroin consumers, who also self-administer tranquillizers and sedatives (Arria et al., 2010). Thus, there are distinctive preferences for the effects associated to different categories of drugs; psychostimulant drugs such as nicotine, cocaine, and caffeine itself, have energizing properties and can potentiate activities such as going out and actively interacting with novel and challenging environments. In contrast, the use of sedatives, opioids, and cannabinoids is preferred by people with a more socially withdrawn profile, and they have been shown to be used in more familiar and habitual environments (Badiani, 2013). It is possible that the consumption of ethanol mixed with energy drinks is more likely associated with a profile of consumer that looks for an intermediate effect, thus, consuming a tranquilizer that reduces anxiety, but also a mild energetic drug that favors active social encounters. However, in spite of potential benefits of low doses of both substances, concentrations of caffeine in energy drinks are so high than consuming several during a single episode can lead to a high dose of caffeine that may, in fact, induce anxiety (Correa & Font, 2008). Social anxiety can be related to alcohol drinking, not only for anxiety reduction, but also in high-risk

situations, such as conflict with others, social pressure, and testing personal control (Buckner, Eggleston, & Schmidt, 2006). In predisposed individuals, there is also a tendency toward increased anxiety when using both drugs in combination (Snipes et al., 2015). Altogether, a pattern for maladaptive social behaviors emerges when evaluating the impact of the consumption of highly caffeinated beverages mixed with alcohol.

THE NEUROMODULATOR ADENOSINE: COMMON TARGET FOR ETHANOL AND CAFFEINE Caffeine and ethanol have various actions on several neurotransmitters and neuromodulators; however, the adenosinergic and the dopaminergic systems are the ones more clearly affected by these two drugs. Adenosine is a central neuromodulator by regulating neuronal excitability and neurotransmitter release (Svenningsson, Le Moine, Fisone, & Fredholm, 1999). It operates mainly through volume transmission regulated by ongoing production and transport. Adenosine acts on four subtypes of G-protein-coupled receptors; A1, A2A, A2B, and A3, with A1 and A2A being the most abundant (Fuxe et al., 2003). A1 receptors are broadly distributed in the brain, with a relatively high concentration in the hippocampus, but adenosine A2A receptors are expressed at high levels, and almost exclusively, in the striatum and olfactory bulbs and tubercle (Svenningsson et al., 1999) regions that are involved in the regulation of voluntary motor processes, activational aspects of motivation, and social behaviors (Fig. 56.1) (Cabib, D’Amato, Puglisi-Allegra, & Maestripieri, 2000; Salamone & Correa, 2012).

FIGURE 56.1 Localization of A1 and A2A adenosine receptors in the rodent brain. Schematic representation of regional distribution of the two most abundant adenosine receptor subtypes (A1 and A2A) in the brain.

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THE NEUROMODULATOR ADENOSINE: COMMON TARGET FOR ETHANOL AND CAFFEINE

Caffeine acts as a nonselective adenosine A1/A2A antagonist. This mechanism of action mediates its stimulant (Ferre´, 2008), anxiogenic (Correa & Font, 2008), and motivational effects (Lo´pez-Cruz et al., 2018; Salamone et al., 2009). While increases in adenosine levels induce sleep and produce sedation and fatigue, caffeine is generally consumed to reduce these effects, and to increase alertness (Johnson, Spinweber, & Gomez, 1990). Moreover, A1 and A2A receptor antagonists have been proposed as therapeutic targets for the treatment of motivational impairments, such as anergia and fatigue (Salamone et al., 2009). Adenosine A1 and A2A receptors are colocalized with DA D1 and D2 receptors in striatal areas, including the Nacb shell and core, but they are found in different populations of neurons (Nunes et al., 2013). DA D2 and adenosine A2A receptors are colocalized on enkephalin-containing MSN, while D1 and A1 receptors are colocalized on substance P-containing MSN (Fuxe et al., 2003). These pairs of receptors can converge onto the same signal transduction mechanisms, having opposite effects on intracellular signaling cascades (Ferre´, 2008; Fuxe et al., 2003). Caffeine and adenosine antagonists acting on A1 or A2A receptors generally produce opposite effects to DA antagonists on markers, such as DARPP-32 (see Fig. 56.2) (Nunes et al., 2013). Mesolimbic DA is involved in the regulation of the invigorating component of motivated behaviors

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(Salamone & Correa, 2012). DA depletion or antagonism impairs this activational aspect of motivation, shifting preferences from high effort-demanding reinforcers to more sedentary ones. Selective adenosine antagonists, and several methylxantines, can reverse the anergia-like effect induced by DA impairments (Lo´pezCruz et al., 2018; Pardo et al., 2012; Salamone & Correa, 2009). Although ethanol does not act directly on adenosine receptors, it can increase adenosine by increasing release, decreasing ENT-dependent adenosine uptake, or as a by-product of ethanol metabolism, because acetate generated by ethanol metabolism promotes adenosine synthesis (Correa et al., 2012; Israel, Orrego, & Carmichael, 1994; Lo´pez-Cruz, Salamone, & Correa, 2013). Thus, it seems that caffeine and ethanol have opposite effects on the adenosine system and should, therefore, have opposite effects on adenosine-regulated behaviors. In this chapter, focus will be placed on animal models that assess social behaviors. We will summarize the impact of caffeine ethanol actions on social interaction, social cognition, and mood. Since adenosine is a common target for both substances, studies focusing on the effects of selective adenosine receptor antagonists, as well as genetic adenosine receptor deletion and their interaction with ethanol will be also presented in an attempt to shed light on potential neural mechanisms.

FIGURE 56.2

Effects of ethanol and caffeine on the adenosine system. Schematic representation of the mechanism of adenosine production after ethanol administration and of postsynaptic effects of caffeine as A2A/A1 receptor antagonist and the metabotropic effects.

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SOCIAL INTERACTION AND ITS MODULATION BY ANXIETY: IMPACT OF CAFFEINE ETHANOL INTERACTION Rodents are highly social animals and, through aggression and defense behaviors, they establish hierarchies. Furthermore, they show robust playful behavior, especially during adolescence. Seeking social contact shows reinforcing properties in classical paradigms, such as socially conditioned place preference, or operant tasks that use sex-matched conspecifics as reinforcers (Martin & Iceberg, 2015; Panksepp, 2010). Time spent approaching and exploring a conspecific, as opposed to exploration of a nonsocial stimulus, can offer information about the preference for social contact, and is a measure of appetitive social motivation. In addition, social paradigms also can provide information about social memory by showing the ability to differentiate between familiar versus novel conspecifics (Moy et al., 2004). Important emotional components involved in social interactions, such as anxiety, have been inferred from these studies, as well as patterns of aggressive or playful behavior. Studies of ethanol on sociability in animal models have addressed several of these different components. For instance, low to intermediate doses of ethanol increase active aggression, while high doses increased defensive escape among aggressive mice (Krsiak, 1976). Later studies have found that in general populations of rodents, acute low doses of ethanol facilitate social contact, but high doses reduce social interactions (Hilakivi, Durcan, & Lister, 1989; Lo´pez-Cruz et al., 2016). Interestingly, adult rats show more hangoverrelated social suppression than adolescents, with males being more affected than females. Moreover, adolescents increase play fighting during recovery, pointing to a hangover-related social facilitation that is not evident in adults (Varlinskaya & Spear, 2006) This facilitation of interaction with peers by ethanol has been attributed to its alleviation of anxiety (Kirchner, Sayette, Cohn, Moreland, & Levine, 2006; Varlinskaya & Spear, 2006). In addition to the intrinsic motivational properties of interaction with conspecifics, anxiety is one of the factors that can induce avoidance of social interaction. Social behaviors are sensitive to anxiolytic or anxiogenic effects of drugs, and the social interaction task, in which both conspecifics are in direct contact, has been widely used as an animal model of anxiety (File & Seth, 2003). Adenosine modulates processes involved in social interaction, such as exploration, anxiety, and memory (Correa & Font, 2008; Hauber & Bareiss, 2001). At high doses, caffeine decreases social interaction in mice and rats (Baldwin & File, 1989; Hilakivi et al., 1989; Lo´pez-

Cruz et al., 2016), which has been interpreted as an anxiogenic effect (Baldwin & File, 1989; Hilakivi et al., 1989), but lower doses seem to increase social contact (Nadal, Pallares, & Ferre´, 1993). Using classical procedures where animals are in direct contact, a high dose of caffeine, that did not modify the time spent engaged in social interaction by itself, was able to reverse the impairment induced by a high dose of ethanol (Hilakivi et al., 1989). Acutely administered caffeine and ethanol have been shown to have opposite effects on anxiety (Correa, Manrique, Font, Escrig, & Aragon, 2008; Prediger, Batista, & Takahashi, 2004). Caffeine and its metabolite theophylline induce anxiogenic effects at moderate and high doses (Lo´pez-Cruz, Pardo, Salamone, & Correa, 2014). In contrast, the anxiolytic effects of ethanol have been widely demonstrated in mice and rats (Correa et al., 2008; Prediger et al., 2004). Each of these drugs has been shown to affect social interaction in a manner consistent with their anxiogenic or anxiolytic profile. However, a direct positive relationship between anxiety and social interaction is not always clear, and contradictory results have been found depending on the animal model and the parameters used (Baldwin & File, 1989; Nadal et al., 1993). To minimize anxiety, new paradigms of social interaction for rodents have been developed. Sociability can be measured in a three-chamber social box (Moy et al., 2004). This procedure eliminates the possibility of physical aggression since the target mouse is enclosed in a wire cage (Moy et al., 2004). The use of this paradigm (see Fig. 56.3), which allows free exploration with no body contact, gives a measure of preference that is less affected by anxiety and aggression. Aggressive behavior can still be evaluated by registering tail rattle frequency, which reflects threat behavior towards the conspecific (Krsiak, 1976). Time spent sniffing each target (conspecific vs. object) and time spent in each compartment are measures of social preference (Moy et al., 2004). In addition, vertical and horizontal locomotion in all compartments can be also registered as indices of environmental exploration and motor behavior. Moreover, social memory can also be assessed 24 hours after the social preference test in a “social novelty test.” During this test, a novel caged mouse replaces the object. The index of social recognition is based upon comparing the time spent investigating the novel mouse versus the more familiar one (Moy et al., 2004). The effects of caffeine, adenosine receptor antagonists, alcohol, and their combination have been evaluated using this procedure (Lo´pez-Cruz et al., 2016, 2017). As shown with other rodent paradigms and in human studies (Karlsson & Roman, 2016), ethanol

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FIGURE 56.3 Schematic illustration of social preference and social memory tests. Representation of the animal paradigm for social approach and recognition with no body contact.

showed a biphasic effect; low doses improved social preference but high doses reduced social preference, although no dose produced social avoidance for the conspecific, since animals still spent more time in the compartment with the conspecific than alone or with the object (Lo´pez-Cruz et al., 2016). Intermediate doses of caffeine decreased social preference, but animals were still oriented towards the conspecific. However, high doses of caffeine totally blocked the preference for the conspecific, and animals showed withdrawal from direct exploration of both stimuli (Lo´pez-Cruz et al., 2016). This avoidance of direct exploration (not only social exploration) can be produced by an increase in anxiety, since intermediate to high doses of caffeine are anxiogenic in this strain of mice, as seen in the elevated plus maze (Lo´pez-Cruz et al., 2013). It is also possible that caffeine at these doses impaired sustained attention (i.e., animals were less focused toward specific stimuli). Low doses of ethanol counteracted the suppressive effects of intermediate and high doses of caffeine on social approach (Lo´pez-Cruz et al., 2016). These effects on social behavior do not seem to be mediated by changes in environment exploration since there was no effect on locomotion measured as crosses between the three chambers (Lo´pez-Cruz et al., 2016). Results from selective A1 and A2A receptor antagonists, indicate that reductions in social interaction induced by high doses of caffeine were not mediated by actions on these receptors, since neither one reduced social interaction (Lo´pez-Cruz et al., 2016) at doses that had effects on other motivated behaviors (Pardo et al., 2012). On the other hand, the A2A

receptor antagonist MSX-3 on its own increased rather than decreased preference for the social target. However, there was no significant interaction between MSX-3 and ethanol (Lo´pez-Cruz et al., 2016). Consistently, high levels of social interaction have been observed in A2AKO mice (Lo´pez-Cruz et al., 2017). Interestingly, A2AKO mice showed an anxiogenic profile, which again argues against a simple relationship between anxiety and social interaction (Lo´pez-Cruz et al., 2017). A2AKO mice did not have odor detection impairments since they were not different to WT in social versus nonsocial odor preference (Lo´pez-Cruz et al., 2017). Recently, using the three-chamber test, we assessed the impact of a dose of ethanol (1 g/kg, administered IP, 10 minutes before the social interaction test) that impaired social interaction in outbred mice in a previous experiment (Lo´pez-Cruz et al., 2016) to see whether this substrain of A2AKO mice were more resistant to the impairing effects of ethanol on sociability when compared with WT counterparts. Results show that both strains spent similar amounts of time seeking social contact, and show the same social preference (data shown in Figs. 56.4A and 56.4B), a pattern of results consistent with the pharmacological antagonism of A2A receptors. Student’s t-test for dependent samples indicate that both strains spent significantly more time sniffing a conspecific than an object; WT (t 5 6.84, P , .01) and KO (t 5 4.01, P , .01). In addition, WT mice remained in the compartment with the conspecific longer than they did in the object compartment (t 5 3.51, P , .01). Student’s t-test for independent samples showed that horizontal

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FIGURE 56.4 Effects of ethanol on WT and A2AKO mice evaluated in the three-chamber social preference test. WT and A2AKO mice performance in the social preference test after receiving 1 g/kg of ethanol IP (N 5 8 per group). (A) Mean ( 6 SEM) of time sniffing the conspecific or the; (B) time spent in the compartments were the conspecific or the object are located; and (C) total horizontal and vertical locomotion. ##P , .01, #P , .05 indicates significant differences between conspecific versus object.

FIGURE 56.5 Brain areas for c-Fos immunoreactivity counting. Diagram of coronal sections with bregma coordinates: (A) 1.94 mm; (B)

1.18 mm; and (C) 21.34 mm, showing the location of the brain areas for c-Fos counting. Source: Taken from Franklin, K.B.J., & Paxinos, G. (2007). The mouse brain in stereotaxic coordinates (3th ed.). San Diego, CA: Elsevier Academic Press (Franklin & Paxinos, 2007) atlas.

locomotion after receiving ethanol was significantly lower in KO than in WT mice (t 5 2.60, P , .05) (data are presented in Fig. 56.4C). Finally, expression of the immediate early-gene product c-Fos as a measure of neuronal activation was evaluated in different A2A receptor-containing regions, as well as areas that are important for the regulation of active motivated behaviors and emotion (Fig. 56.5). Immunoreactivity for c-Fos in A2AKO mice was significantly different from WT in ACg (t 5 2.95, P , .01), Nacb core (t 5 4.7, P , 0.01), and shell (t 5 2.96, P , .01), important structures in the circuitry that regulate the activational component of motivation that leads to seeking behaviors (Salamone & Correa, 2012), and MeA (t 5 1.96, P , .01) (data shown in Fig. 56.6).

Amygdala is a region rich in adenosine receptors (Svenningsson et al., 1999) and this region, especially the medial nucleus, has been implicated in processing social information in humans (Critchley et al., 2000) and subordinate and defensive behaviors in rodents which can lead to anxiety. Previous studies using A2AKO mice have shown that they have increased sensitivity to the anxiolytic effects of low doses of ethanol (Houchi et al., 2008). Thus, our studies with A2AKO mice do not support the idea of a simple and direct relationship between anxiety and social interaction in mice, since an anxiolytic dose of ethanol (Correa et al., 2008) reduced social exploration in A2AKO mice compared with the high baseline of social exploration of these animals (Lo´pez-Cruz et al., 2017).

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CONCLUSIONS AND FUTURE DIRECTIONS

FIGURE 56.6 Effects of ethanol on c-Fos immunoreactivity of WT and A2AKO mice. c-Fos immunoreactivity in brain areas of WT and KO mice (N 5 5 6 per group) after ethanol administration (1 mg/kg, IP). Mean ( 6 SEM) number of c-Fos positive cells per mm2.  P , .01 significant differences between strains for every structure.

SOCIAL RECOGNITION: EFFECT OF CAFFEINE AND ALCOHOL ON COGNITION AND MEMORY The amnesic effect of ethanol is well-known. Bingedrinking episodes have been linked to memory impairments in humans including disruptions of encoding, storage, consolidation, or retrieval. In animals, high doses of ethanol can also cause learning impairments and amnesia, effects that can persist long after the drug wears off (Lo´pez-Cruz et al., 2016). However, it has also been reported that moderate doses of ethanol, caffeine, and other methylxantines, delivered after learning, can facilitate memory acquisition and retention in animals (Manrique, Miquel, & Aragon, 2005; Hauber & Bareiss, 2001). The focus here is on how these drugs can affect different forms of memories about conspecifics. Ethanol, at low doses, acts as a short-term social memory enhancer in rodents exploring a juvenile conspecific (Manrique et al., 2005). The development and consolidation of memory seems to be modulated by A1 and A2A adenosine receptor-dependent mechanisms in the hippocampus (Hauber & Bareiss, 2001). Selective adenosine receptor agonists disrupt, while antagonists improve, short-term juvenile recognition. The selective agonistsinduced impairment of short-term social memory was reversed by caffeine, as well as by selective A1 and A2A antagonists (Prediger & Takahashi, 2005). No study so far has assessed the impact of caffeine on the short-term memory effects of ethanol, however, there are some studies on long-term social memory. In a social odor recognition test in rats, a low dose of caffeine blocked memory impairments induced by a high dose of ethanol (Spinetta et al., 2008). In the three-chamber paradigm, both ethanol and caffeine, or their combination,

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produced predominantly amnesic effects (Lo´pez-Cruz et al., 2016). Ethanol, even at low doses that do not impair social interaction, did impair social recognition 24 hours later, and caffeine coadministration was not able to block the amnesic effects of ethanol (Lo´pez-Cruz et al., 2016). Caffeine at high doses that reduce preference for social interaction, impaired recognition of the familiar conspecific (Lo´pez-Cruz et al., 2016). As for the role of selective adenosine receptor antagonists, it appears that A1 antagonists do not reverse ethanol-induced impairments in recognition memory (Lo´pez-Cruz et al., 2016). In contrast, A2A antagonism seems to be more implicated in social memory. On the one hand, constitutional A2AKO mice showed poor recognition of a familiar mouse, allocating equal amounts of time exploring both conspecifics (Lo´pez-Cruz et al., 2017). This lack of social recognition could not be explained by deficits in spatial memory since A2AKO mice have better results in spatial memory tasks in comparison with WT mice (Wang et al., 2006). It is possible that since these mice seem more sociable, as seen in test of social preference (Lo´pezCruz et al., 2017), they do not show distinctive preferences when the two stimuli are conspecifics. The other piece of data about the involvement of A2A receptors comes from the use of the selective A2A receptor antagonists, which increased preference for the conspecific (Lo´pez-Cruz et al., 2016). However, a low dose of antagonist that potentiated social exploration was able to block the amnesic effect of a low dose of ethanol, but not a higher dose (Lo´pez-Cruz et al., 2016). It is possible that higher doses of A2A antagonists would have produced similar effects to the A2A mutation, affecting social recollection.

CONCLUSIONS AND FUTURE DIRECTIONS After reviewing the literature on caffeine ethanol interactions, one can see that more work needs to be performed. Thus, in this chapter, we offer a tentative profile of the pharmacological interaction between alcohol and caffeine and its impact on social behaviors. In particular, we addressed basic animal studies that have utilized avoidance and approach behaviors as measures of willingness to interact socially. Moreover, social learning using recognition of a familiar conspecific has been studied as a way of describing whether these drugs can facilitate long-term social memory. Results indicate that low doses of ethanol facilitate social contact, but high doses reduce social interactions. The same biphasic pattern of facilitation and suppression of direct exploration can be observed in relation to caffeine. However, high doses of caffeine can induce withdrawal from direct exploration

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in general, possibly via an axiogenic action or a loss of focused attention. Although anxiety plays a modulatory role in social interaction, it does not explain the entire phenomenon. The very few studies addressing the interactions between these two drugs on social exploration seem consistent. Thus, high doses of caffeine that do not have an effect on their own can reverse social impairment induced by a high dose of ethanol, and low doses of ethanol can counteract the suppressing effects of doses of caffeine that have an effect on their own. In summary, it seems that there is only a very narrow range of doses that can be combined to improve social interaction. It also seems clear that there is a relative independence between social preference and social memory. Although low doses of ethanol seem to improve social short-term memory, they also seem to impair long-term social memory, and caffeine coadministration can only block that impairment in memory at very low doses, but not at high ones. In addition, results suggest that A1 receptors do not seem to regulate social motivation and social recognition. Blockade of A2A receptors, however, seems more important for enhancement of social behavior. Moreover, because selective A1 and A2A antagonists do not mimic the effects of caffeine, it is possible that blockade of both receptors is necessary for producing a caffeine-like action. Alternatively, at high doses, caffeine may not be acting solely as an adenosine antagonist. Thus, although an increase in adenosine levels could be mediating ethanol effects, the usefulness of highly caffeinated drinks in counteracting ethanol-induced impairments on social processes is questionable. Basic studies of the impact of ethanol caffeine interactions should look for a more detailed characterization of the nature of social approach. Thus, measures of play behaviors and aggressive play behaviors, such as wrestling and biting (Marquardt & Brigman, 2016), will give a broader perspective on the role of the caffeine alcohol effect on social contact. It is worth noting that most of the studies cited above focus on males, but there is clear evidence showing how female rodents have a different behavioral profile in social interactions to males (Marquardt & Brigman, 2016). In conclusion, despite the fact that this area of inquiry has grown increasingly, animal research has only scratched the surface of this complex and multifaceted field.

MINI-DICTIONARY OF TERMS Adenosine Endogenous purine nucleoside that acts via G-proteincoupled receptors. Anergia Symptom of depression and other psychiatric and neurological disorders, which reflects psychopathologies related to behavioral activation.

Binge drinking Heavy episode of alcohol use in a short period of time. Medium spiny neurons GABAergic neurons that express both D1 and D2 receptors and represent more than 90% of cells in the striatum. Methylxanthines Alkaloids derived from purine nucleotides present in plants including coffee, tea, and cacao.

KEY FACTS Caffeine Consumption • Caffeine was isolated from coffee and tea in the early 1820s and is considered to be the mostconsumed stimulant in the world. • More than 85% of adults in United States consume caffeine regularly and, generally, the intake starts in childhood. • Caffeine affects several tissues simultaneously through actions on adenosine receptors, which are ubiquitous in the brain and in the vascular endothelium, heart, liver, adipose, and muscle tissues. • Energy drinks contain exceptionally high levels of caffeine and are increasingly being consumed combined with alcohol, specially, among young people. • It is believed that caffeine can counteract the impairing effects of alcohol on behavior, but this improvement depends on the amount of each drug consumed. • Among young people, caffeine can produce a false sense of reduced impairment during alcohol bingedrinking episodes, that can lead to further risktaking situations. • Social interactions among peers and social anxiety are not clearly benefited by the combined consumption of alcohol and energy drinks.

SUMMARY POINTS • Ethanol and caffeine have opposite effects on the adenosine function. • This chapter focuses on how both substances can modulate social behaviors in animal models. • Caffeine as a nonselective adenosine antagonist, and selective A1 adenosine receptor antagonists do not improve social behaviors. • A2AKO mice and A2A receptor antagonists potentiate social exploration. • Ethanol impairments on social behavior are counteracted only at low and intermediate doses of caffeine, but not at high doses.

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REFERENCES

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Pardo, M., Lopez-Cruz, L., Valverde, O., Ledent, C., Baqi, Y., Mu¨ller, C. E., . . . Correa, M. (2012). Adenosine A2A receptor antagonism and genetic deletion attenuate the effects of dopamine D2 antagonism on effort-based decision making in mice. Neuropharmacology, 62(5-6), 2068 2077. Peacock, A., Cash, C., & Bruno, R. (2015). Cognitive impairment following consumption of alcohol with and without energy drinks. Alcoholism, Clinical and Experimental Research, 39(4), 733 742. Prediger, R. D. S., & Takahashi, R. N. (2005). Modulation of shortterm social memory in rats by adenosine A1 and A(2A) receptors. Neuroscience Letters, 376(3), 160 165. Prediger, R. D. S., Batista, L. C., & Takahashi, R. N. (2004). Adenosine A1 receptors modulate the anxiolytic-like effect of ethanol in the elevated plus-maze in mice. European Journal of Pharmacology, 499(1-2), 147 154. Salamone, J. D., & Correa, M. (2009). Dopamine/adenosine interactions involved in effort-related aspects of food motivation. Appetite, 53(3), 422 425. Salamone, J. D., & Correa, M. (2012). The mysterious motivational functions of mesolimbic dopamine. Neuron, 76(3), 470 485. Salamone, J. D., Farrar, A. M., Font, L., Patel, V., Schlar, D. E., Nunes, E. J., . . . Sager, T. N. (2009). Differential actions of

adenosine A1 and A2A antagonists on the effort-related effects of dopamine D2 antagonism. Behavioural Brain Research, 201(1), 216 222. Snipes, D. J., Jeffers, A. J., Green, B. A., & Benotsch, E. G. (2015). Alcohol mixed with energy drinks are robustly associated with patterns of problematic alcohol consumption among young adult college students. Addictive Behaviors, 41, 136 141. Spinetta, M. J., Woodlee, M. T., Feinberg, L. M., Stroud, C., Schallert, K., Cormack, L. K., & Schallert, T. (2008). Alcohol-induced retrograde memory impairment in rats: Prevention by caffeine. Psychopharmacology, 201(3), 361 371. Svenningsson, P., Le Moine, C., Fisone, G., & Fredholm, B. B. (1999). Distribution, biochemistry and function of striatal adenosine A2A receptors. Progress in Neurobiology, 59(4), 355 396. Varlinskaya, E. I., & Spear, L. P. (2006). Differences in the social consequences of ethanol emerge during the course of adolescence in rats: Social facilitation, social inhibition, and anxiolysis. Developmental Psychobiology, 48(2), 146 161. Wang, Y., Mackes, J., Chan, S., Haughey, N. J., Guo, Z., Ouyang, X., . . . Mattson, M. P. (2006). Impaired long-term depression in P2X3 deficient mice is not associated with a spatial learning deficit. Journal of Neurochemistry, 99(5), 1425 1434.

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C H A P T E R

57 Biomarkers of Alcohol Misuse Aurelie De Vos, Rani De Troyer and Christophe Stove Laboratory of Toxicology, Ghent University, Ghent, Belgium

LIST OF ABBREVIATIONS ALT AST C-DBS CDT% DBS EtG EtS FAEEs fL GGT MCV MW PEths Tf VAMS

Fig. 57.1 depicts the nonoxidative metabolization scheme of ethanol, which leads to these ethanol metabolites—also referred to as “direct biomarkers of ethanol.”

alanine aminotransferase aspartate aminotransferase capillary dried blood spots carbohydrate deficient transferrin dried blood spots ethyl glucuronide ethyl sulfate Fatty acid ethyl esters femtoliter gamma glutamyltransferase mean corpuscular volume molecular weight phosphatidylethanol species transferrin volumetric absorptive microsampling

ETHANOL

INTRODUCTION Alcohol is a widely used, legal, psychoactive substance that is consumed all over the world. Chronic alcohol misuse can cause diseases, while acute intoxications may lead to coma and even death (World Health Organization, 2014). Ethanol is a small size (molecular weight (MW) 5 46 g/mol), weak acid (pKa 15.9 at 25
C) which is absorbed into the bloodstream from the stomach and small intestine. For the removal of ethanol from the body, we can distinguish three different excretion pathways. First, a small amount of the ingested ethanol (2%5%) is removed unchanged in urine, sweat, and breath. The main part of ethanol (95%) is excreted by oxidative metabolism (phase I) and 0.1% is removed by nonoxidative metabolism (phase II). The latter pathway results in the formation of the direct ethanol biomarkers: phosphatidylethanol molecules (PEths), ethyl glucuronide (EtG), ethyl sulfate (EtS), and fatty acid ethyl esters (FAEEs) (Kummer et al., 2016a).

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00057-X

Ethanol can be determined in blood, urine, and exhaled breath. Within 2 h after the start of drinking, peak alcohol concentrations are reached in blood. The detection window in blood depends on the amount of alcohol consumed and on the elimination rate of ethanol, which is estimated to be 0.12 g/L/h for social drinkers. The rate of disappearance can be up to 1.5 times higher in heavy drinkers. Ethanol levels exceeding 1.5 g/L without any signs of intoxication or ethanol levels exceeding 3.0 g/L at any time suggest abnormal ethanol tolerance and alcohol misuse (Jones, 1993). In urine, mean peak alcohol concentrations are reached within 1.5 h. The urineblood alcohol concentration ratio is estimated to be 1.3:1 at steady state concentrations. In general, ethanol is somewhat longer detectable in urine, compared to blood, which is beneficial (Jones & Holmgren, 2003). A good correlation between the concentration of ethanol in breath and blood has been established. The bloodbreath concentration ratio (conversion factor) differs from one country to another (2300:1 for Belgium and The Netherlands, 2000:1 for most other European countries, and 2100:1 for the United States). The mean elimination rate of ethanol was estimated at 0.082 mg/L/h, which corresponds to 0.16 g/L/h when expressed as BAC (Jones, 1993). In general, detection of ethanol in these matrices is of limited use to detect abstinence from alcohol, given

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FIGURE 57.1 Nonoxidative phase II metabolism of ethanol. Nonoxidative phase II metabolism of ethanol into EtG, EtS, PEths (PEth 16:0/18:1, PEth 18:1/18:1, and PEth 16:0/16:0), and FAEEs (ethyl myristate [E14:0], ethyl palmitate [E16:0], ethyl stearate [E18:0], and ethyl oleate [E18:1]), with an indication of the molecular weight (MW). PAPS: 30 -phosphoadenosine-50 -phosphosulfate, UDPGA: uridine 50 -diphospho-β-glucuronic acid. Source: Reproduced with permission from Kummer, N., et al. (2016b). Quantification of phosphatidylethanol 16:0/18:1, 18:1/18:1, and 16:0/16:0 in venous blood and venous and capillary dried blood spots from patients in alcohol withdrawal and control volunteers. Analytical and Bioanalytical Chemistry, 408, 825838.

the relatively short detection window, which depends on the amount of ethanol consumed.

INDIRECT BIOMARKERS Indirect biomarkers of alcohol consumption reflect the indirect effects of ethanol on the body, via its interference with glycosylation present in the body (increased CDT%), with liver function (increased gamma glutamyltransferase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST)), or via its effect on the size of the red blood cells (MCV). These markers are altered upon chronic and excessive alcohol consumption due to interference of ethanol with biochemical processes and/or a liver pathology, induced by alcohol misuse. These markers are being widely applied to assess alcohol consumption.

However, they suffer from limitations such as aspecificity and low sensitivity, because they do not directly reflect (excessive) alcohol consumption. For their analysis, the conventional matrices blood or serum are used (Kummer et al., 2016b).

Carbohydrate Deficient Transferrin Carbohydrate deficient transferrin (CDT%) results are usually expressed as a percentage of the total transferrin. Transferrin (Tf) is a group of glycoproteins that all consist of two binding sites and two carbohydrate chains, branched with sialic acid residues (Maenhout et al., 2014). Liver damage, for example caused by excessive alcohol consumption, induces an increase of isoforms with less carbohydrate chains, named carbohydrate deficient transferrin. Asialo-Tf (usually not detected in the serum of healthy persons) and disialo-Tf (normally

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DIRECT MARKERS

present in only small amounts) were found to be the main alcohol-related glycoforms, present at increasing concentrations after a daily consumption of 5080 g ethanol during 12 weeks. Hence, short periods of high alcohol consumption are not detected (Arndt, 2001). In alcoholic patients, CDT% results normalize within 2 weeks after cessation of drinking. This may pose a problem when alcoholics can choose to some extent when they provide a blood sample for follow-up, as they may reduce their drinking behavior in the weeks prior to sampling. CDT% is considered the most reliable among the indirect markers to detect chronic and excessive alcohol consumption (Appenzeller et al., 2005). Nevertheless, several conditions (among which serious liver diseases such as liver carcinomas and chronic hepatitis) can lead to false positive results. The specificity varies from approximately 60% to 95% and the sensitivity from 10% to 90% (Bortolotti et al., 2006).

serum (Tavakoli, Hull, & Michael Okasinski, 2011). Their half-life is estimated to be between 13 and 16 days. Normal values are reached within 23 weeks after the cessation of alcohol consumption (Niemela¨, 2007). Sensitivity values between 23% and 50% were reported, specificity values are between 87% and 98% to detect alcohol abuse (Conigrave et al., 2003). Muscle disorders and use of many drugs increase AST levels as well. An AST/ALT ratio over 2 has been proposed to suggest alcohol-induced liver damage in 90%95% of the cases (specificity), but this ratio is not elevated for all alcoholdependent individuals (sensitivity ,40%) (Tavakoli et al., 2011). Upper reference limits for AST at 31 and 37 U/L and for ALT at 31 and 40 U/L for females and males, respectively, have been suggested (Schumann et al., 2002).

Gamma Glutamyltransferase

The mean corpuscular volume (expressed in femtoliter, fL) is the average volume of the erythrocytes and is calculated by dividing the hematocrit (volume (%) of erythrocytes in total volume blood) by the number of erythrocytes (Niemela¨, 2007). The normal range is 8698 fL. The cut-off value to detect alcohol dependence is 9396 fL. A period of chronic and excessive alcohol use is known to increase the size of the red blood cells (macrocytosis). Values up to 109 fL have been measured in patients in alcohol withdrawal. Since red blood cells have a life span of 120 days, MCV levels only normalize after 34 months after cessation of drinking (Maenhout, De Buyzere, & Delanghe, 2013). MCV is also influenced by vitamin B12 or folic acid deficiency, hematological diseases, etc. MCV has shown a specificity of 75%95% to detect alcohol abuse, sensitivity values are below 50% (Tavakoli et al., 2011).

Gamma-glutamyltransferase (GGT) is an enzyme present in the cell surface membrane of many tissues. Only the isoform of GGT present in the liver is detected in serum. It catalyzes the transfer of the gammaglutamyl group of glutathione to peptides, amino acids, or water to form glutamate. By regulating glutathione levels, this reaction is possibly involved in protection against oxidative stress (e.g., induced by the metabolism of ethanol) (Jousilahti, Rastenyte, & Tuomilehto, 2000). A daily consumption of between 80 and 200 g of ethanol, for a period of several weeks, is required for an increase in GGT activity (measured in serum). The halflife of GGT is between 14 and 26 days. Normal GGT values are reported within 25 weeks after cessation of alcohol consumption (Rose, 2008). Elevated GGT can be caused by excessive alcohol consumption, but is also seen in cases of liver damage due to cholestasis, and pancreas or kidney damage, and obesity, etc. Upper reference limits of 36 and 61 U/L for females and males, respectively, have been published, with sensitivity and specificity values of 30%60% and 65%95%, respectively (Conigrave et al., 2003).

Aspartate Aminotransferase and Alanine Aminotransferase AST and ALT are two transaminase enzymes, which catalyze the reversible transfer of an α-amino group from aspartate (AST) or alanine (ALT) to α-ketoglutarate to create oxaloacetate (AST) or pyruvate (ALT) and glutamate. ALT and AST are predominantly present in the liver, but AST is also found in heart, muscle, and kidneys, etc. The activity of these enzymes is measured in

Mean Corpuscular Volume

DIRECT MARKERS The direct biomarkers of ethanol use include a set of minor ethanol metabolites, depicted in Fig. 57.1. These metabolites are formed by biochemical reactions that involve coupling of the ethanol moiety to an endogenous compound. Hence, their presence can be directly related to the consumption of ethanol, which is advantageous in the monitoring of alcohol use (Cabarcos et al., 2013). Moreover, they can also be monitored via so-called “alternative sampling strategies.” These comprise both the sampling of conventional matrices (blood, plasma, serum, or urine) in an alternative way, as well as the collection of “alternative” samples in all kind of ways. A typical example of the former is the

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collection of dried blood spots (DBS), while examples of the latter include sampling of, for example, hair (Kummer et al., 2016a). Before elaborating on the direct biomarkers of ethanol use, the possibilities and challenges of the best established and most promising matrices of interest in the context of follow-up of alcohol (mis)use will be discussed.

Alternative Sampling Strategies of Interest in the Context of Follow-Up of Alcohol (Mis)use A capillary dried blood spot (C-DBS) is obtained by depositing a blood drop, typically obtained after a finger prick, onto a filter paper, followed by drying (Fig. 57.2). These samples improve the stability of many compounds and facilitate storage and transportation. The sampling can be performed either in a volumetric (e.g., by using a precision microcapillary) or in a nonvolumetric way (direct application from the finger). Compared to venipuncture, this technique is minimally invasive and can be performed by minimally trained, nonmedical staff (De Kesel et al., 2015). Besides filter paper, volumetric absorptive microsampling (VAMS) devices may also be applied (Van Uytfanghe et al., unpublished). The latter is a relatively new microsampling approach, in which a fixed volume of liquid is absorbed by a polymeric tip, fixed to a plastic handle (Denniff & Spooner, 2014). Quantification of direct biomarkers in urine allows an extended detection window. However, when aiming at guaranteeing authenticity of the urine, privacy issues accompany the sampling. To facilitate transfer, storage, management, and to improve stability of urine samples, quantification of direct ethanol biomarkers can be performed in dried urine samples, as demonstrated by Herna´ndez Redondo and colleagues (2012). Dried urine samples can also be generated using VAMS, but hitherto, no methods using VAMS for the determination of alcohol markers have been described. (Kummer et al., 2013; Kummer et al., 2016b). Hair is a nonconventional matrix that is currently being used in many countries for follow-up of problematic alcohol users (Alt et al., 2000). Quantification of

direct alcohol markers in hair provides several advantages: hair sampling is noninvasive, does not pose privacy issues, and makes it possible to detect ethanol use over an extended time period. Moreover, the level of certain ethanol metabolites can be correlated to the amount of alcohol used, offering the potential to distinguish heavy drinking, social drinking, and abstinence. On the other hand, hair sampling can be considered somewhat intrusive and collection requires some skill (Appenzeller et al., 2007a; Cabarcos et al., 2013). Guidelines and a consensus on alcohol markers in hair are available from the Society of Hair Testing (SoHT; www.soht.org/), an international scientific society that promotes research in hair testing technologies and develops proficiency tests for these markers (Kintz, 2015).

Direct Alcohol Metabolites Ethyl Glucuronide and Ethyl Sulfate EtG and EtS are two small, polar, acidic metabolites of ethanol whose presence is correlated to the amount of alcohol used. Glucuronidation of ethanol is a phase II conjugation reaction with UDPGA (uridine 50 diphospho-β-glucuronic acid), catalyzed by UDPglucoronosyltransferase in the endoplasmic reticulum. Sulphatation of ethanol is a phase II conjugation reaction with PAPS (30 -phosphoadenosine-50 -phosphosulfate), catalyzed by cytosolic sulfotransferase. Both can be measured in blood and urine, while EtG can also be monitored in hair (Beyer et al., 2011; Halter et al., 2008). After the consumption of 0.50.78 g ethanol/kg body weight, peak concentrations of EtG in serum of 0.31.1 mg/L were reached between 2.3 and 5 h after the start of drinking. For EtS, peak concentrations of 0.10.8 mg/L were observed between 2.1 and 3.9 h. EtG and EtS in blood have an extended detection window compared to blood ethanol (Thierauf et al., 2010). Analysis of EtG and EtS in urine allows the detection of drinking small amounts of alcohol during the past few days, which makes it possible to monitor alcohol consumption during withdrawal treatment, for

FIGURE 57.2 Dried blood spot card with the structure of a phosphatidylethanol species. By depositing a blood drop on a filter paper, a dried blood spot is obtained. Determination of phosphatidylethanol in dried blood is favorable because of the stability of the components in a dried matrix.

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DIRECT MARKERS

workplace testing and to monitor abstinence in the context of driving license regranting. EtG and EtS can be detected in urine for 1320 h after a single alcohol consumption (0.1 g/kg), and up to 5 days after drinking large amounts of alcohol (Helander et al., 2009). Commercially available EtG colorimetric test strips permit on-site analysis of urine samples. Caution is advised when using these rapid screening tests, since false positive and false negative results cannot completely be ruled out. Urinary concentrations of EtG and EtS are highly influenced by urine dilution, which may be controlled or corrected for by monitoring urinary creatinine concentrations (Arndt, 2009) (Fig. 57.3). Several recent studies support the use of EtG testing in hair as a marker of alcohol abuse (Alt et al., 2000). Hair grows approximately 1 cm per month, which allows assessment of ethanol intake during the past few months (depending on the hair length) (Oppolzer, Barroso, & Gallardo, 2016). Since incorporation of EtG is independent of the melanin content, it isn’t impacted by pigmentation degree or natural hair color. Furthermore, there is no evidence in the literature that belonging to specific ethnic groups may determine another source of bias (Appenzeller et al., 2007b). Two cut-off values have been proposed, at 7 pg/mg and at 30 pg/mg, respectively, to disprove a strict abstinence period and to strongly suggest excessive and chronic alcohol consumption (defined as consumption of $ 60 g ethanol/day over several months) (Kintz, 2015) (Fig. 57.4). Phosphatidylethanol (PEth) PEths are a group of aberrant phospholipids that are formed in the cell membrane, only in the presence of ethanol. PEths are formed by a reaction between ethanol and phosphatidylcholine, which is catalyzed by phospholipase D (Gnann, Weinmann, & Thierauf, 2012). PEths are discussed more into detail in the

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chapter by Javors et al., elsewhere in this book. They are alcohol biomarkers present in blood, mainly located in erythrocytes and in different organs (Gnann et al., 2009). Up to forty-eight different PEths have been detected in blood collected in autopsy cases of heavy drinkers. All PEths have a common phosphoethanol head onto which two fatty acid chains of variable length and degree of saturation are attached. Blood analysis of heavy drinkers shows that, although there is inter-individual variation, PEth 16:0/18:1 and PEth 16:0/18:2 (the numbers 16 and 18 are referring to the length of the carbon chain; the numbers 0, 1 or 2 are referring to the number of unsaturated CC bonds) are the most abundant PEth species, accounting for 30%46% and 16%28%, respectively. Other PEths detected in blood are PEth 18:0/18:0, 18:0/18:2 (together accounting for 11%12%) and 16:0/16:0 (accounting for about 5%). The half-life of PEths in whole blood was calculated to be 4.0 6 0.7 days (Gnann et al., 2010). In case of chronic/excessive alcohol consumption, PEths are detectable in blood up to 28 days after sobriety. Moreover, a significant correlation between PEth concentrations in blood and the amount of consumed ethanol has been demonstrated. In comparison to indirect ethanol biomarkers, PEth has been shown to have increased specificity and sensitivity for the detection of latent ethanol use (Kummer et al., 2016a). While no formal internationally accepted cut-offs have been established, yet, PEth 16:0/18:1 levels above 20 ng/mL indicate “social drinking,” while concentrations above 150 or 221 ng/mL (depending on the source) may be suggestive for chronic and excessive alcohol consumption (Kummer et al., 2016b; Schro¨ck et al., 2017). C-DBS sampling has been suggested to be particularly useful for PEth analysis in the context of driving license regranting programs (Kummer et al., 2016a). Recently, a pharmacokinetic model was proposed that should allow to

FIGURE 57.3 Urine sample used for the detection of ethyl glucuronide (left structure) and ethyl sulfate (right structure). Ethyl glucuronide (left structure) and ethyl sulfate (right structure) are two direct metabolites of ethanol that are used for the determination of alcohol consumption. Both can be determined in urine samples.

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FIGURE 57.4 A hair sample in which ethyl glucuronide can be analyzed. Ethyl glucuronide is incorporated in hair. A hair segment of 36 cm can serve as a matrix for the determination of ethyl glucuronide.

make prospective or retrospective statements on the concentration of PEth 16:0/18:1 in blood, based on several parameters such as blood alcohol concentration and the maximum rate of increase in PEth concentration, etc. (Simon, 2018). Results obtained by the model were in good accordance with those published by Gnann et al (2012) and Schro¨ck et al. (2017). Although promising, this is still a preliminary model and more knowledge about the formation of PEths is necessary to generate a biologically-based model (Simon, 2018). Fatty Acid Ethyl Esters FAEEs are a group of more than 20 substances, formed by enzymatic esterification of ethanol and free fatty acids. Ethyl myristate (E14:0), ethyl palmitate (E16:0), ethyl stearate (E18:0) and ethyl oleate (E18:1) are the most common FAEEs. Different enzymes (i.e., FAEE synthetase, acyl-coA-ethanol O-acyltransferase [AEAT], . . .) catalyze the esterification of ethanol to free fatty acids (Pragst et al., 2010). FAEEs are present in blood of alcohol users and abstainers. In abstainers, serum FAEEs concentrations of 2487 nmol/L have been suggested as reference values. During the first 18 h after alcohol consumption, 95% of the FAEEs detected in serum are eliminated. Hence, a slightly longer detection window in blood is present relative to ethanol itself. Therefore, detection of serum FAEEs for abstinence monitoring is of limited, if any, value (Politi et al., 2007). More value may lie in the detection of FAEEs in hair. FAEEs are incorporated into the head hair mainly through sebum. FAEE concentrations increase from the proximal region to the distal and decrease after 510 cm in length (Pragst & Yegles, 2008). This phenomenon has been explained by the contact of hair with sebum from the sebaceous gland or by a more intense hair wash near the scalp. Hair melanin content does not influence the concentration of FAEEs (Auwa¨rter et al., 2001). Bleaching and perming hair may influence the concentration of FAEEs in hair, while dyeing has been shown

to decrease the FAEE concentration. The SoHT has also put forward recommendations on the use of FAEE results in hair analysis (Kintz, 2015). (www.soht.org/ images/pdf/Revision%202016_Alcoholmarkers.pdf): • While the analysis of FAEEs alone is not recommended to determine abstinence from ethanol, it can be used in cases of suspected false negative EtG results, by applying ethyl palmitate cut-off concentrations of 0.12 and 0.15 ng/mg for respectively a 3 and 6 cm proximal scalp hair segment. It should be noted that a positive FAEE result combined with an EtG below 7 pg/mg result does not clearly disprove abstinence, but indicates the need for further monitoring. • Cut-off concentrations of 0.35 and 0.45 ng/mg for ethyl palmitate in scalp hair are considered strongly suggestive for chronic excessive alcohol consumption, depending on the length of the used proximal hair segment (3 and 6 cm, respectively).

IMPLICATIONS FOR PATIENT TREATMENT AND FOLLOW-UP Alcohol markers can be used for the follow-up of (absence of) alcohol consumption in patients on the liver transplant list, or posttransplant patients. Detecting problematic drinking behavior is important for the treatment of liver patients, since this allows intervening therapy (e.g., referral for addiction care) (Stewart et al., 2014). The follow-up of alcohol consumption can be used to assess the patient’s willingness and ability to stay abstinent on a long-term basis, which is required in this setting, since severe graft injury can occur in case the patient continues to consume alcohol in an excessive manner, resulting in poor patient survival and prognosis. Because indirect biomarkers (e.g., serum liver enzymes and MCV) are not accurate in liver disease patients, detection of direct alcohol markers is considered as a tool for the determination of alcohol consumption within the liver transplant setting

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SUMMARY POINTS

(Staufer et al., 2011). The same actually holds true in the context of driving license regranting, where those individuals that continue to use alcohol can be guided towards more intensive therapy.

CONCLUSION Alcohol consumption is monitored in various contexts, such as workplace testing, driving license regranting, alcohol withdrawal treatment, and suspected and at-risk pregnancies, etc. Currently, the detection of ethanol itself in blood, urine, and breath is widely used to indicate alcohol consumption. Although these methods have the advantage of being highly specific for alcohol consumption, their detection window is limited, which only makes them useful for detection within a short period of time after consumption. Indirect biomarkers of alcohol use such as CDT%, GGT, ALT/AST, and MCV are monitored in blood, and are also frequently applied to monitor excessive alcohol consumption. These biomarkers suffer from a lack of sensitivity and aspecificity, which poses a problem when aiming at detecting chronic and excessive alcohol consumption, or abstinence monitoring. Direct biomarkers of alcohol consumption comprise a set of minor ethanol metabolites whose presence is directly related to alcohol consumption, which is advantageous when monitoring alcohol use. Moreover, these direct biomarkers cannot only be monitored by using “conventional sampling strategies” (i.e., blood, plasma, serum, and urine), but also via “alternative sampling strategies” (e.g., dried blood samples and hair, etc.). These alternative sampling strategies offer distinct advantages over conventional sampling strategies as they are minimally invasive or noninvasive, and sampling can be done by minimally trained personnel. Moreover, they can facilitate storage and transportation issues and provide increased stability for many compounds. Yet, much research is still required in this field to confirm promising results, establish widely accepted cut-offs, and organize proficiency tests using alternative samples, etc. When successful, this may lead to some alternative sampling strategies for the assessment of alcohol intake of living persons to become “established” rather than “alternative” sampling strategies.

MINI-DICTIONARY OF TERMS Indirect biomarkers Endogenous markers that are altered as a result of chronic and excessive alcohol consumption, because of interference of ethanol with biochemical processes and/or the induction of a liver pathology.

Direct biomarkers Ethanol metabolites, formed by a biochemical reaction that involves coupling of the ethanol moiety to an endogenous compound. Abstinence monitoring Follow-up to see if persons are abstinent, that is, refraining from drinking alcoholic beverages. Chronic and excessive alcohol consumption Term for a drinking pattern that is considered to exceed acceptable standards (social drinking) (WHO, 1994). Alternative sampling strategies Sampling strategies comprising both the sampling of conventional matrices (blood, plasma, serum, or urine) in an alternative way, as well as the collection of “alternative” matrices in all kinds of ways. Conventional sampling strategies Sampling of conventional matrices in a conventional way, being venipuncture or the collection of urine.

KEY FACTS Indirect Ethanol Biomarkers • These are altered upon chronic and excessive use of ethanol. The most currently used are CDT%, ALT/ AST, GGT, and MCV. • CDT% is considered the most reliable among the indirect markers to detect chronic and excessive alcohol consumption, with a sensitivity of 10%90% and a specificity of 60%95%. • For GGT, sensitivity values between 30% and 60% and specificity values between 65% and 95% have been reported. • Sensitivity values between 23% and 50% and specificity values between 87% and 98% for detecting alcohol abuse have been reported for ALT and AST. • For MCV, sensitivity values are below 50% to detect alcohol abuse; specificity is 75%95%.

Direct Ethanol Biomarkers • Direct biomarkers of ethanol use constitute a set of minor ethanol metabolites including EtG, EtS, PEths, and FAEE. • Their presence is directly related to the use of ethanol and they show higher sensitivity and specificity than indirect biomarkers.

SUMMARY POINTS • Indirect biomarkers of ethanol use are markers that are altered upon chronic and excessive use of ethanol. They have limited, if any, value in demonstrating abstinence from ethanol. • Direct biomarkers, constituting minor ethanol metabolites, show higher sensitivity and specificity than indirect biomarkers of alcohol consumption. • Direct biomarkers can be monitored via so called “alternative sampling strategies,” of

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which dried blood samples and hair are the most relevant in the context of abstinence monitoring. • Quantification of EtG and EtS in urine allows to detect alcohol consumption during the past few days. • Phosphatidylethanol in blood (whole blood or dried blood samples) reflects the alcohol consumption during the past month. • EtG in hair can provide information about alcohol consumption during the past few months, depending on the length of the hair strand.

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Gnann, H., Weinmann, W., & Thierauf, A. (2012). Formation of phosphatidylethanol and its subsequent elimination during an extensive drinking experiment over 5 days. Alcoholism: Clinical and Experimental Research, 36, 15071511. Halter, C. C., et al. (2008). Kinetics in serum and urinary excretion of ethyl sulfate and ethyl glucuronide after medium dose ethanol intake. International Journal of Legal Medicine, 122, 123128. Helander, A., et al. (2009). Detection times for urinary ethyl glucuronide and ethyl sulfate in heavy drinkers during alcohol detoxification. Alcohol and Alcoholism, 44, 5561. Herna´ndez Redondo, A., et al. (2012). Inhibition of bacterial degradation of EtG by collection as dried urine spots (DUS). Analytical and Bioanalytical Chemistry, 402, 24172424. Jones, A. W. (1993). Pharmacokinetics of ethanol in saliva: Comparison with blood and breath alcohol profiles, subjective feelings of intoxication, and diminished performance. Clinical Chemistry, 39, 18371844. Jones, A. W., & Holmgren, P. (2003). Urine/blood ratios of ethanol in deaths attributed to acute alcohol poisoning and chronic alcoholism. Forensic Science International, 135, 206212. Jousilahti, P., Rastenyte, D., & Tuomilehto, J. (2000). Serum gammaglutamyl transferase, self-reported alcohol drinking, and the risk of stroke. Stroke, 31, 18511855. Kintz, P. (2015). 2014 consensus for the use of alcohol markers in hair for assessment of both abstinence and chronic excessive alcohol consumption. Forensic Science International, 249, A1A2. Kummer, N., et al. (2013). A fully validated method for the quantification of ethyl glucuronide and ethyl sulphate in urine by UPLCESI-MS/MS applied in a prospective alcohol self-monitoring study. Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, 929, 149154. Kummer, N., et al. (2016a). Alternative sampling strategies for the assessment of alcohol intake of living persons. Clinical Biochemistry, 49, 10781091. Kummer, N., et al. (2016b). Quantification of phosphatidylethanol 16:0/18:1, 18:1/18:1, and 16:0/16:0 in venous blood and venous and capillary dried blood spots from patients in alcohol withdrawal and control volunteers. Analytical and Bioanalytical Chemistry, 408, 825838. Maenhout, T. M., et al. (2014). Usefulness of indirect alcohol biomarkers for predicting recidivism of drunk-driving among previously convicted drunk-driving offenders: Results from the Recidivism Of Alcohol-impaired Driving (ROAD) study. Addiction, 109, 7178. Maenhout, T. M., De Buyzere, M. L., & Delanghe, J. R. (2013). Nonoxidative ethanol metabolites as a measure of alcohol intake. Clinica Chimica Acta, 415, 322329. Niemela¨, O. (2007). Biomarkers in alcoholism. Clinica Chimica Acta, 377, 3949. Oppolzer, D., Barroso, M., & Gallardo, E. (2016). Determination of ethyl glucuronide in hair to assess excessive alcohol consumption in a student population. Analytical and Bioanalytical Chemistry, 408, 20272034. Politi, L., et al. (2007). Bioanalytical procedures for determination of conjugates or fatty acid esters of ethanol as markers of ethanol consumption: A review. Analytical Biochemistry, 368, 116. Pragst, F., et al. (2010). Combined use of fatty acid ethyl esters and ethyl glucuronide in hair for diagnosis of alcohol abuse: Interpretation and advantages. Forensic Science International, 196, 101110. Pragst, F., & Yegles, M. (2008). Determination of fatty acid ethyl esters (FAEE) and ethyl glucuronide (EtG) in hair: A promising way for retrospective detection of alcohol abuse during pregnancy? Therapeutic Drug Monitoring, 30, 255263. Rose, G. (2008). Rose’s strategy of preventive medicine. Oxford: Oxford University Press.

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Schro¨ck, A., et al. (2017). Phosphatidylethanol (PEth) detected in blood for 3 to 12 days after single consumption of alcohol-a drinking study with 16 volunteers. International Journal of Legal Medicine, 131, 153160. Schumann, G., et al. (2002). IFCC primary reference procedures for the measurement of catalytic activity concentrations of enzymes at 37
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C H A P T E R

58 Phosphatidylethanol Homologs in Blood as Biomarkers for the Time Frame and Amount of Recent Alcohol Consumption 1

Nathalie Hill-Kapturczak1, Donald M. Dougherty1,2, John D. Roache1,2, Tara E. Karns-Wright1, Marisa Lopez-Cruzan1 and Martin A. Javors1,2

Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, United States 2Department of Pharmacology, University of Texas Health Science Center, San Antonio, TX, United States

LIST OF ABBREVIATIONS BAC BrAC HPLC/MS/MS PEth

alcohol use biomarker (PEth) and the potential for using different PEth homologs to identify the amount and time frame of recent drinking.

blood alcohol concentration breath alcohol concentration high-pressure liquid chromatography combined with tandem mass spectroscopic detection phosphatidylethanol

The Discovery of Phosphatidylethanol

INTRODUCTION The discovery and use of ethanol consumption biomarkers have significantly evolved over the past 30 years. Currently available biomarkers fall into two broad categories: indirect and direct biomarkers. These are described in more detail in Chapter 57, Biomarkers of Alcohol Misuse. One of the direct biomarkers is phosphatidylethanol (PEth). PEth is an ideal candidate as an alcohol-use biomarker because it has a high sensitivity and specificity (Aradottir, Asanovska, Gjerss, Hansson, & Alling, 2006; Hartmann et al., 2007; Helander, Peter, & Zheng, 2012; Wurst et al., 2010) and a long window of detection (e.g., Gnann, Weinmann, & Thierauf, 2012; Helander et al., 2012; HillKapturczak, Dougherty, Roache, Karns-Wright, & Javors, 2018; Javors, Hill-Kapturczak, Roache, KarnsWright, & Dougherty, 2016). In addition, there have been no reports thus far of false positives for PEth (SAMSA, 2012). The purpose of this chapter is to describe the history and development of this specific

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00058-1

In 1983, it was observed that rats chronically treated with ethanol had an abnormal phospholipid found in high concentrations in the brain, kidney, liver, and other organs (Alling, Gustavsson, & Anggard, 1983). This abnormal phospholipid was identified in 1984 (Alling, Gustavsson, Mansson, Benthin, & Anggard, 1984). A series of studies determined that PEth was quickly synthesized after a single injection of ethanol and could be observed in several brain regions for up to 14 24 hours (Lundqvist, Aradottir, Alling, BoyanoAdanez, & Gustavsson, 1994). PEth is synthesized in most organs after acutely or chronically administered ethanol, but variations in distribution, synthesis, and elimination of this compound are organ specific (Aradottir, Lundqvist, & Alling, 2002; Aradottir, Moller, & Alling, 2004). In subsequent years, in vitro studies determined that PEth was synthesized by phospholipase D in the presence of ethanol in most animal organs [except the red blood cells (RBCs) of mice, rat, ferret, or pig] and cell lines (Aradottir et al., 2002; Aradottir et al., 2004; Bocckino, Wilson, & Exton, 1987; Gustavsson & Alling, 1987; Gustavsson, Moehren, & Hoek, 1991; Holbrook, Pannell, Murata, &

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58. PHOSPHATIDYLETHANOL HOMOLOGS IN BLOOD AS BIOMARKERS FOR THE TIME FRAME

Daly, 1992; Kobayashi & Kanfer, 1987; Liscovitch, 1989; Metz & Dunlop, 1990; Tettenborn & Mueller, 1988). In humans, there are two different PLD isoforms: PLD1 and PLD2 (reviewed in Peng & Frohman, 2012; Shukla et al., 2001; Viel et al., 2012). PLD1 has a low basal activity and, under steady-state conditions, is primarily located within the cell (e.g., Golgi complex, endosomes, lysosomes, etc). PLD2 has a high basal activity and is primarily located in the plasma membrane. Both PLD1 and PLD2 can catalyze the formation of PEth (reviewed in Shukla et al., 2001; Viel et al., 2012). A total of 48 homologs of PEth has been identified in whole blood samples, specifically in RBCs by highpressure liquid chromatography combined with tandem mass spectroscopic detection (HPLC/MS/MS) (Gnann et al., 2010). The phospholipid precursor of PEth species and the source of diversity of fatty acids at the sn-1 and sn-2 positions on the 3-carbon glycerol portion of the phospholipid structure is phosphatidylcholine (Helander & Zheng, 2009). For this review, we will focus on PEth 16:0/18:1, 16:0/18:2, and 16:0/20:4, which appear to be the predominant species in human whole blood, representing about 37%, 26%, and 13%, respectively, for a total of 76% of total PEth (Helander & Zheng, 2009). PEth 16:0/18:1 is the homolog that is almost exclusively used for clinical and forensic purposes at the time of this review. A clever procedure for storing whole blood samples as dried blood spots on clinical spot cards has provided a convenient way to collect, store, and ship these samples. However, there is significant research interest to combine the measurement of the predominant species because of their diverse pharmacokinetic characteristics, which appear to provide enriched information about the amount and time frame of recent alcohol consumption and will be discussed next. The chemical structures of the PEth precursor phosphatidylcholine 16:0/18:2 and PEth 16:0/ 18:1, 16:0/18:2, and 16:0/20:4 are shown in Fig. 58.1.

Development of Phosphatidylethanol as an Alcohol Marker Interest in PEth as a potential biomarker for alcohol use began after Rubin (1988) found that PEth was synthesized in human platelets after being exposed to ethanol in vitro. Shortly after this report, there were numerous studies examining the presence of PEth in blood among different samples of alcohol users. For example, Lundqvist, Alling, Aradottir, and Gustavsson (1994) showed that PEth was measurable in white blood cells taken from alcoholics for up to 23 hours after ethanol consumption. It was not until 1997 that the idea of using PEth as a possible biomarker for alcohol use was advanced (Hansson, Caron, Johnson, Gustavsson, & Alling, 1997), after it was discovered that higher levels

FIGURE 58.1 Chemical structures of the PEth precursor phosphatidylcholine 16:0/18:2, PEth 16:0/18:1, PEth 16:0/18:2, and PEth 16:0/20:4.

of PEth could be measured in whole blood samples (using thin layer chromatography) and that detectable levels could be observed for up to 14 days among alcoholics admitted to a detoxification program. The PEth half-lives in platelets and white blood cells were discovered to be less than 24 hours. Subsequent studies indicated a 4 7-day PEth half-life in whole blood samples, which was found to be due to a unique elimination system only present in RBCs; which was the absence of one of three degradative enzymes (Viel et al., 2012). Numerous other subsequent studies examined the detection and elimination of PEth in human subjects admitted into various types of treatment programs (Aradottir et al., 2006; Gunnarsson et al., 1998; Hartmann et al., 2007; Helander et al., 2012; Varga, Hansson, Johnson, & Alling, 2000; Wurst et al., 2010). In 2009, a more sensitive and specific method to quantify PEth levels was developed (HPLC/MS/MS; Gnann et al., 2009; Helander & Zheng, 2009; Zheng, Beck, & Helander, 2011). The ability of the more sensitive and specific method allows for the identification of individual homologs of PEth. It is now known that 48 PEth homologs exist and that corresponding phosphatidylcholine precursors and ethanol are the substrates

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INTRODUCTION

from which PLD synthesis produces PEth homologs (Gnann et al., 2010; Helander & Zheng, 2009; Nalesso et al., 2011; Gnann, Thierauf, Hagenbuch, Rohr, & Weinmann, 2014). PEth 16:0/18:1 and 16:0/18:2 appear to be the predominant species, accounting for 37% 46% and 26% 28%, respectively, of total PEth in blood from heavy drinkers (Helander & Zheng, 2009; Nalesso et al., 2011). More recently, Gnann et al. (2014) have demonstrated that PEth 16:0/18:1 is usually the most frequent homolog as observed in both hospitalized alcoholic-dependent subjects and social drinkers selfreporting patterns of moderate drinking. Using HPLC/ MS/MS, PEth has been detected in whole blood from inpatients for longer periods of time, even up to 28 days, during abstinence (Wurst et al., 2012). In addition to studies that were conducted on inpatient alcoholics to determine how long PEth can be detected after abstinence, there have been several studies that have evaluated the ability of PEth levels to detect alcohol consumption outside of a controlled setting (e.g., Aradottir et al., 2006; Asiimwe et al., 2015; Comasco et al., 2009; Hahn et al., 2012; Helander et al., 2012; Nalesso et al., 2011; Stewart, Reuben, Brzezinski, Koch, Basile, Randall, & Miller, 2009; Stewart, Law, Randall, & Newman, 2010, Stewart, Koch, Willner, Anton, & Reuben, 2014; Jain, Evans, Briceno, Page, & Hahn, 2014; Skipper, Thon, Dupont, Baxter, & Wurst, 2013). For example, Stewart et al. (2009, 2014) evaluated the ability of PEth to detect alcohol use in patients with liver disease in two studies. It was discovered that PEth levels can differentiate “any drinking” from abstinence. Furthermore, PEth has been used in other populations with success in identifying drinking among impaired health professionals’ programs and individuals undergoing an outpatient treatment program for alcohol dependence (Helander et al., 2012; Skipper et al., 2013). It should be pointed out, however, that these PEth studies (e.g., Aradottir et al., 2006; Asiimwe et al., 2015; Comasco et al., 2009; Hahn et al., 2012; Helander et al., 2012; Jain et al., 2014; Nalesso et al., 2011; Skipper et al., 2013; Stewart et al., 2009; Stewart et al., 2010; Stewart et al., 2014; Wurst et al., 2010) either relied on selfreported alcohol use or relied on patients who confirmed alcohol consumption after being confronted by positive test results. The oft-noted inaccuracy of verbal reports of alcohol consumption underlies the need for biomarkers such as PEth.

Studies on the Synthesis and Elimination of Phosphatidylethanol After Controlled Alcohol Consumption Previous studies have examined PEth synthesis and elimination after controlled conditions of ethanol

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consumption using HPLC/MS/MS (Gnann et al., 2012; Hill-Kapturczak, et al., 2018; Javors et al., 2016; Kechagias et al., 2015; Schrock, Thierauf-Emberger, Schurch, & Weinmann, 2017). Gnann et al. (2012) observed that after 11 healthy volunteers consumed enough alcohol in the lab to achieve a blood alcohol concentration (BAC) of 1 g/kg (w/w) that PEth 16:0/ 18:1 was detectable in whole blood samples within 1 hour. They observed an interindividual variability in the rate and capacity of PEth synthesis that has been identified in other studies (Javors et al., 2016; Hahn, Anton, & Javors, 2016). The mean half-life was reported to be from 4 to 7 days in the Gnann study. In a second study, Kechagias et al. (2015) randomized participants to either alcohol abstinence (n 5 23) or consumption of a specific amount of moderate alcohol daily for 3 months outside the lab (n 5 21). PEth 16:0/ 18:1 was detected after moderate alcohol intake conditions. It was concluded that PEth 16:0/18:1 probably could be used to distinguish between abstinence and moderate consumption. In a third study (Schrock et al., 2017), the pharmacokinetics of synthesis and elimination of PEth 16:0/18:1 and 16:0/18:2 were analyzed (n 5 7 women and n 5 9 men) after consumption of enough alcohol to achieve a BAC of 1 g/kg (w/w). Blood samples were collected over the next 12 days. Less PEth 16:0/18:2 was synthesized, but was eliminated faster compared to PEth 16:0/18:1 in most participants. All of these studies used self-reported abstinence when alcohol consumption was not directly observed. In two additional studies (Hill-Kapturczak et al., 2018; Javors et al., 2016), transdermal alcohol concentration (TAC) was monitored to promote abstinence 7 days before and 14 days after controlled alcohol consumption. In a preliminary study (Javors et al., 2016), participants received 0.25 (n 5 16) or 0.50 g/kg (n 5 11) oral doses of alcohol. In the larger study (HillKapturczak et al., 2018), participants received 0.4 (n 5 28) or 0.8 g/kg (n 5 26) oral doses of alcohol. PEth 16:0/18:1 and 16:0/18:2 levels were quantified by HPLC/MS/MS. The time course for PEth 16:0/18:1 and 16:0/18:2 synthesis during the first 6 hours after alcohol consumption are shown in Fig. 58.2A and B, respectively. The elimination of both homologs during the 14 days after controlled alcohol consumption is shown in Fig. 58.3A and B. Positive baseline levels were observed even for participants with 1 week of abstinence objectively confirmed by TAC monitoring. Baseline PEth levels correlated with self-reported percent heavy drinking days during the 28 days prior to the 7 day abstinence period [22.1% 6 14.5% (SD) for men and 12.8% 6 8.35% (SD) for women]. Given the half-lives of PEth 16:0/18:1 [ 7.8 6 3.3 (SD) days] and PEth 16:0/18:2 [6.4 6 5.0 (SD) days] that we observed

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FIGURE 58.2 Synthesis of PEth 16:0/18:1 after consumption of 0.4 or 0.8 g/kg of ethanol. Mean PEth concentrations of (A) 16:0/18:1 and (B) 16:0/18:2 at each time point up to 360 minutes after 0.4 (gray squares) and 0.8 (gray circles) g/kg doses of ethanol consumption. The doses of alcohol were consumed during the first 15 minutes of the pharmacokinetic data on the graph. Each symbol represents the mean and 95% confidence intervals for 29 research subjects. Source: Reprinted with permission from Hill-Kapturczak, N., Dougherty, D. M., Roache, J. D., Karns-Wright, T. E. & Javors, M. A. (2018). Differences in the synthesis and elimination of phosphatidyethanol homologues after acute doses of alcohol. Alcoholism: Clinical and Experimental Research, 42(5), 851 860.

(Fig. 58.4), this is not surprising (Hill-Kapturczak et al., 2018). The half-lives reported in our studies are similar to those previously reported: 3 7 days for PEth 16:0/ 18:1 (e.g., Gnann et al., 2012; Schrock et al., 2017; Zheng et al., 2011) and 4.4 6 2.2 days (SD) for PEth 16:0/18:2 (Schrock et al., 2017). Monitored alcohol use outside the lab using TAC monitoring served as an objective confirmation of actual consumption showed

some low-level drinking before and after alcohol administration in some participants. Abstinence was confirmed in most participants. A few abstinence violations had little effect on the measurement of the synthesis and half-lives of these two homologs. Nonetheless, the detection of a few low-level drinking events highlights the value of using another marker for alcohol consumption (e.g., transdermal alcohol monitoring) in studies where abstinence is requested and expected. PEth has the sensitivity to detect acute consumption of moderate and heavy doses of alcohol. After consumption of 0.25, 0.4, 0.5, and 0.8 g/kg ethanol, there was an immediate increase in both PEth homolog levels in all but one participant. (Hill-Kapturczak et al., 2018; Javors et al., 2016). The initial rate of synthesis of both PEth homologs (Fig. 58.5) was not statistically different at the 0.4 and 0.8 g/kg alcohol doses (HillKapturczak et al., 2018), suggesting that PLD (the enzyme responsible for PEth synthesis) might have been saturated in vivo at the relatively low ethanol concentrations in the blood. On the other hand, our unpublished data indicate that the in vitro mean initial rates of synthesis of PEth 16:0/18:1 and 16:0/18:2 by PLD were significantly different at 100 mM ethanol. It is likely that other unknown factors affect the in vivo PLD enzyme activity. The mean peak PEth levels and the mean 360 minutes area under the curves (AUC 360) were higher at the 0.8 g/kg ethanol dose (HillKapturczak et al., 2018; Javors et al., 2016). The initial rate of synthesis and the AUC 360 for PEth 16:0/18:2 was greater than those for PEth 16:0/18:1 at 0.4 and 0.8 g/kg doses (Figs. 58.5 and 58.6). Several studies have shown a substantial betweensubject variability in PEth levels and AUC 360s among research participants who either received the same g/ kg dose of alcohol or were given enough alcohol to achieve the same blood alcohol levels in all participants (Gnann et al., 2012; Hill-Kapturczak et al., 2018; Javors et al., 2016; Schrock et al., 2017). For studies where subjects received the same ethanol dose by weight, twofold and threefold variability was observed in the absorption of ethanol (Hill-Kapturczak et al., 2018; Javors et al., 2016). In one study, after participants (n 5 11) drank alcohol to reach a BAC of about 1 g/L, PEth 16:0/18:1 blood levels varied as much as threefold between participants (Gnann et al., 2012). In a similar study by Schrock et al. (2017), mean peak levels of PEth 16:0/18:1 ranged from 37.2 to 208 ng/ mL and peak levels of PEth 16:0/18:2 ranged from 21.0 to 130 ng/mL after participants consumed enough alcohol in the lab to achieve a BAC of 1 g/kg. In our most recent study (Hill-Kapturczak et al., 2018), we observed that PEth 16:0/18:1 AUC 360 ranged from 535 to 26,507 ng-min/mL and from 4469 to

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INTRODUCTION

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activities, variability among phosphatidylcholine homologs (PEth precursors), and PEth elimination rates may be factors that account for the wide interindividual variabilities (Hahn et al., 2016). Our most recent study was designed to compare the pharmacokinetics of PEth 16:0/18:1 and 16:0/18:2 between men and women. We did not observe sex differences in initial rates of synthesis, AUC 360 values, or half-lives of PEth 16:0/18:1 or 16:0/18:2 with equal numbers (n 5 27 each) of men and women. A previous study reported similar findings using overall PEth levels (i.e., all PEth homologs combined) measured over time in alcohol-dependent patients entering inpatient treatment—9 women and 48 men; and no sex differences were found for PEth levels at any time point (Wurst et al., 2010). These findings are important because despite known sex differences in BAC when men and women consume the same amount of alcohol (Baraona et al., 2001; Breslin, Kapur, Sobell, & Cappell, 1997; Dettling et al., 2007; Fiorentino & Moskowitz, 2013), the extent to which those alcohol levels drive PEth formation seems to be unaffected by sex.

The Potential to use Different Phosphatidylethanol Homologs to Indicate Recentness of Alcohol Consumption

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Time (days) FIGURE 58.3 Elimination of PEth 16:0/18:1 during 2 weeks of abstinence. Mean PEth (A) 16:0/18:1 and (B) 16:0/18:2 concentrations during the 14 days after 0.4 (gray squares) and 0.8 (gray circles) g/kg oral doses of ethanol. The subjects remained abstinent during this period based on transdermal ethanol measurements by a monitor worn on the ankle. Each symbol represents the mean and 95% confidence intervals for 29 research subjects. Half-lives of PEth homolog elimination in whole blood samples was determined using Prism 7.03 software. Source: Reprinted with permission from HillKapturczak, N., Dougherty, D. M., Roache, J. D., Karns-Wright, T. E. & Javors, M. A. (2018). Differences in the synthesis and elimination of phosphatidyethanol homologues after acute doses of alcohol. Alcoholism: Clinical and Experimental Research, 42(5), 851 860.

38,303 ng-min/mL at the 0.4 and 0.8 g/kg doses, respectively. We also observed that PEth 16:0/18:2 AUC 360 ranged from 4218 to 64,842 ng-min/mL and from 6364 to 62,753 ng-min/mL at the 0.4 and 0.8 g/kg doses, respectively. The reported half-lives of PEth 16:0/18:1 and 16:0/18:2 also vary widely (e.g., Gnann et al., 2012; Hill-Kapturczak et al., 2018; Javors et al., 2016; Schrock et al., 2017). Differing PLD levels/

It is now well-established that PEth 16:0/18:1 and 16:0/18:2 have different rates of synthesis and elimination. We observed that the increase in PEth 16:0/18:2 was greater than those of 16:0/18:1, unlike Schrock et al., 2017; and was eliminated faster (shorter halflives) in most participants, similar to Schrock et al. (2017). Blood collections for our study were taken at 0, 15, 30, 45, 60, 90, 120, and 360 minutes. In contrast, Schrock et al. (2017) collected blood at 0, 1, 3, 6, and 8 hours after alcohol consumption. Our results are supported by earlier studies (Gnann et al., 2014; Helander & Zheng, 2009) that also suggest that PEth 16:0/18:1 is formed and eliminated at lower rates compared to PEth 16:0/18:2. For example, Helander and Zheng (2009) suggested that PEth 16:0/18:2 levels were the most important additional species to measure during relapse. Also, PEth 16:0/18:2 levels decreased in a group of inpatients (n 5 12) over 20 days, while PEth16:0/18:1, PEth 18:0/18:2, and PEth 18:0/18:1 blood levels remained relatively constant (Gnann et al., 2014). In that study, PEth 16:0/18:2 levels in blood collected from social drinkers (n 5 78) decreased over a 20-day period, while PEth 16:0/18:1 levels remained unchanged. Taken together, most studies indicate that PEth 16:0/18:2 is synthesized at higher rates compared to PEth 16:0/18:1, but it is also eliminated at higher rates. With less-rapidly changing levels of PEth

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PEth homolog FIGURE 58.4 Comparison of the half-lives of PEth 16:0/18:1 and 16:0/18:2. Mean half-lives of PEth 16:0/18:1 (black circles, n 5 54) and PEth 16:0/18:2 (gray squares, n 5 54). Error bars represent 95% confidence intervals. Source: Reprinted with permission from HillKapturczak, N., Dougherty, D. M., Roache, J. D., Karns-Wright, T. E. & Javors, M. A. (2018). Differences in the synthesis and elimination of phosphatidyethanol homologues after acute doses of alcohol. Alcoholism: Clinical and Experimental Research, 42(5), 851 860.

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PEth homolog FIGURE 58.5 Comparison of initial in vivo rates of synthesis of PEth 16:0/18:1 and PEth 16:0/18:2 after 0.4 and 0.8 g/kg doses of ethanol. Mean initial rates of PEth 16:0/18:1 and PEth 16:0/18:2 synthesis after 0.4 (gray squares) and 0.8 (gray circles) g/kg doses of ethanol. N 5 28 and 26 subjects at the 0.4 and 0.8 g/kg doses, respectively. The initial rate of PEth homolog synthesis was determined during the first 45 minutes after alcohol consumption. Error bars represent 95% confidence intervals. Source: Reprinted with permission from Hill-Kapturczak, N., Dougherty, D. M., Roache, J. D., Karns-Wright, T. E. & Javors, M. A. (2018). Differences in the synthesis and elimination of phosphatidyethanol homologues after acute doses of alcohol. Alcoholism: Clinical and Experimental Research, 42(5), 851 860.

FIGURE 58.6 Comparison of the AUC 360 of the increase of PEth 16:0/18:1 and PEth 16:0/18:2 after 0.4 and 0.8 g/kg doses of ethanol. Mean areas under the PEth 16:0/18:1 (black circles) and PEth 16:0/18:2 (gray squares) curves (AUC 360) from 0 to 360 minutes. The sample sizes for PEth 16:0/18:1 and PEth 16:0/18:2 were 28 and 26 for the 0.4 and 0.8 g/kg doses, respectively. Error bars represent 95% confidence intervals. Source: Reprinted with permission from HillKapturczak, N., Dougherty, D. M., Roache, J. D., Karns-Wright, T. E. & Javors, M. A. (2018). Differences in the synthesis and elimination of phosphatidyethanol homologues after acute doses of alcohol. Alcoholism: Clinical and Experimental Research, 42(5), 851 860.

16:0/18:1, it is possible these data support the hypothesis that PEth 16:0/18:2 levels maybe a good indicator of more recent drinking. In other words, the longer a person is abstinent after drinking, the greater the ratio of PEth 16:0/18:1 to PEth 16:0/18:2 will be. Recently, we became interested in examining the synthesis and elimination of the third most abundant homolog, PEth 16:0/20:4, which has been reported to represent about 8% 13% of total PEth (Gnann et al., 2010; Helander & Zheng, 2009; Nalesso et al., 2011). Using blood samples obtained after the consumption of 0.4 and 0.8 g/kg alcohol (Hill-Kapturczak et al., 2018) the levels of PEth 16:0/20:4 were quantified during alcohol consumption and the 2-week follow-up period (Lopez-Cruzan et al., In press). We observed that PEth 16:0/20:4 was synthesized in all participants after alcohol consumption. The increase in PEth 16:0/ 20:4 above the baseline was less than that of either PEth 16:0/18:1 and PEth 16:0/18:2 at both doses of alcohol. Also, importantly, the mean half-life of PEth 16:0/20:4 was significantly lower than either of the other two homologs (unpublished data). The differential synthesis and elimination of these three PEth homologs may prove to be useful characteristics to estimate the time since the last drink or at least whether a person has been abstinent recently. For

VI. BIOMARKERS OF ALCOHOL MISUSE

MINI-DICTIONARY OF TERMS

example, if there are high levels of PEth 16:0/18:2 compared to 16:0/18:1, and this is accompanied by levels of 16:0/20:4, drinking may have occurred during the preceding day or two. In contrast, if PEth 16:0/20:4 was not detectable and PEth 16:0/18:2 levels were very low relative to PEth 16:0/18:1 or not detectable, the interpretation would be that no alcohol had been consumed for the previous several days, but had been before that.

SUMMARY AND CONCLUSIONS The discovery and detection of two primary metabolites of ethanol was coincidental with the development of HPLC/MS/MS. Because less than 1% of consumed ethanol is converted to ethyl glucuronide (EtG) and PEth homologs, the sensitivity and specificity of this more accurate and sensitive technique was necessary. The term direct biomarker for alcohol consumption highlights the fact that ethanol is part of the chemical structure. PEth and ethyl glucuronide are metabolites of ethanol. The indirect biomarkers are physiological/biochemical results of excessive use of ethanol, which produces an indirect, possibly toxic, effect. The indirect biomarkers of alcohol consumption are less sensitive to lower levels of alcohol consumption. For example, the elevation of serum carbohydrate deficient transferrin above the normal range results only from an average of several drinks per day for a 10 14 day period. The elevation of serum gammaglutamyl transferase is the result of the toxic effect of alcohol abuse for longer periods of time. Of all the biomarkers to quantify and estimate the amount and time frame of alcohol consumption, PEth has emerged as the single most important biomarker based on the sensitivity of the HPLC/MS/MS assay, which allows detection of low levels of consumption, but also the longer, intermediate window of detection compared to breath or blood ethanol. Multiple studies indicate that even a single standard alcohol drink (14 g ethanol) will produce a detectable PEth level in whole blood samples and PEth levels, which have a half-life of 4 7 days, have been detectable for as long as 28 days in some individuals. PEth is being used currently as a standalone biomarker to identify alcohol consumption for a variety of purposes: (1) medical practice to identify individuals consuming unhealthy amounts of alcohol and/or the cause of observed medical conditions; (2) treatment for alcoholism to assess level of compliance with a treatment program’s requirements; and (3) forensic settings to confirm legally imposed mandates related to alcohol consumption. PEth 16:0/18:1 is 1 of 48 known homologs of PEth observed in human whole blood samples and has been

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shown to represent about 37% of total PEth. As an alternate to storing whole blood samples at 280 C, blood samples can be placed on clinical lab spot cards that dry within about 2 hours. PEth is stable and the cards can be stored in desiccated, plastic bags with zipper locks away from light, heat, and moisture (Bakhireva et al., 2016). This noninvasive sample collection procedure is convenient and widely used. A couple of laboratories, including ours, have added the measurement of two additional PEth homologs, PEth 16:0/18:2 and 16:0/20:4. The total of these three homologs comprises about 75% of total PEth. Ours and others’ studies have shown that each of these PEth homologs has markedly different characteristics for rate of formation, amount of PEth formed, and elimination rate. These subtle differences can be used to more accurately estimate not only the amount, but also the time frame of recent alcohol consumption. Finally, while PEth levels in whole blood samples function nicely as a standalone direct biomarker for alcohol consumption, it should be noted that the combination of biomarkers, direct and indirect, can provide additional information about the amount and time frame of alcohol intake and should be used in settings where they are available. Future studies are warranted for the further characterization of these biomarkers as important diagnostic tools for the identification and treatment of alcohol abuse and alcoholism.

MINI-DICTIONARY OF TERMS Direct biomarker A metabolite of ethanol such as phosphatidylethanol, ethyl glucuronide, and fatty acid ethyl esters. Half-life The length of time for the concentration of a biological analyte or drug to decrease by half. Homolog Individual isoforms of phosphatidylethanol. High performance liquid chromatography with tandem mass spectroscopy detection Lab equipment that is used to separate chemicals which are then injected into a detector to measure the concentration of the chemicals in biological matrices. Indirect alcohol biomarker A biological analyte whose concentration changes with the consumption of ethanol and is considered a toxic effect of ethanol. Examples are increased levels of liver enzymes in serum such as gamma-glutamyltransferase and serum carbohydrate deficient transferrin. Pharmacokinetics The characterization of the changes in concentration of biological analytes or drugs over time. Phosphatidylethanol 16:0/18:1 1-Palmitoyl-2-oleoyl-sn-glycero-3phosphoethanol Phosphatidylethanol 16:0/18:2 1-Palmitoyl-2-linoleoyl-sn-glycero-3phosphoethanol Phosphatidylethanol 16:0/20:4 1-Palmitoyl-2-arachidonoyl-sn-glycero-3-phosphoethanol Phosphatidylcholine The phospholipid precursor of phosphatidylethanol Phosphatidylethanol A minor metabolite of ethanol that is used as a direct biomarker for the detection of recent alcohol consumption. Phospholipase D The enzyme that catalyzes the synthesis of phosphatidylethanol from phosphatidylcholine and ethanol.

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KEY FACTS Phosphatidylethanol as a Direct Biomarker of Alcohol Consumption • Phosphatidylethanol homologs are minor metabolites of ethanol, phospholipids that are synthesized, stored in membranes of RBCs, and measured in whole blood samples. • A unique feature of its pharmacokinetics in RBCs is the lack of a critical catabolic enzyme, which is unlike all other cell types studied. • Using high performance liquid chromatography with tandem mass spectroscopic detection, PEth levels can be detected in whole blood samples even after a single standard alcohol drink (14 g ethanol). • There are 48 known homologs of PEth in RBCs. • PEth 16:0/18:1 is the predominant homolog, representing about 37% of total PEth. • The elimination half-life of PEth 16:0/18:1 is 4 7 days which provides a window of detection up to 28 days during abstinence. • PEth 16:0/18:2 and 16:0/20:4 are additional homologs with different pharmacokinetics (rates of synthesis and elimination) than PEth 16:0/18:1. These differences can be used to estimate the recent time frame of alcohol consumption. • Relative PEth homolog levels provide more information to estimate the time frame and levels of recent alcohol consumption than any other single biomarker. • The combination of direct and indirect biomarkers for alcohol consumption provide additional accuracy to estimate the time frame and levels of recent alcohol consumption

SUMMARY POINTS • The concentration of PEth in human RBCs is the current, most accurate, standalone biomarker for the estimation of recent alcohol consumption. • PEth homologs are quantified in liquid whole blood samples and dried blood samples on spot cards. • The current standard for collecting, storing, and shipping PEth samples is dried blood on spot cards. • Multiple studies indicate that even a single standard alcohol drink (14 g ethanol) will produce a detectable PEth level in whole blood samples. • PEth levels have been detectable during abstinence for as long as 28 days in some individuals. • PEth 16:0/18:1 is currently the only homolog measured to identify and estimate recent alcohol consumption.

• PEth 16:0/18:1, 16:0/18:2, 16:0/20:4 in RBCs have different mean half-lives: 7.8 6 3.3 (SD) days, 6.4 6 5.0 (SD) days, 2.1 6 3 (SD) days, respectively. • The measurement of PEth 16:0/18:1, 16:0/18:2, and 16:0/20:4 comprises about 75% of total PEth. These three PEth homologs have markedly different characteristics for rate of formation, amount of PEth formed, and elimination rate that can be used to more accurately estimate not only the amount, but also the time frame, of recent alcohol consumption.

SOURCES OF SUPPORT This publication was supported by the National Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health [R01AA022361and R01AA14988] and by the National Center for Advancing Translational Sciences [UL1TR001120-S1], a re-entry research supplement for Marisa LopezCruzan. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Dougherty also gratefully acknowledges support from a research endowment, the William and Marguerite Wurzbach Distinguished Professorship. Dr. Javors gratefully acknowledges support from the Nancy U. Karren Professorship Endowment. None of the authors have conflicts of interests concerning this manuscript.

References Alling, C., Gustavsson, L., & Anggard, E. (1983). An abnormal phospholipid in rat organs after ethanol treatment. FEBS Letters, 152 (1), 24 28. Alling, C., Gustavsson, L., Mansson, J. E., Benthin, G., & Anggard, E. (1984). Phosphatidylethanol formation in rat organs after ethanol treatment. Biochimica et Biophysica Acta, 793(1), 119 122. Aradottir, S., Asanovska, G., Gjerss, S., Hansson, P., & Alling, C. (2006). Phosphatidylethanol (PEth) concentrations in blood are correlated to reported alcohol intake in alcohol-dependent patients. Alcohol and Alcoholism, 41(4), 431 437. Aradottir, S., Lundqvist, C., & Alling, C. (2002). Phosphatidylethanol in rat organs after ethanol exposure. Alcoholism: Clinical and Experimental Research, 26(4), 514 518. Aradottir, S., Moller, K., & Alling, C. (2004). Phosphatidylethanol formation and degradation in human and rat blood. Alcohol and Alcoholism, 39(1), 8 13. Asiimwe, S. B., Fatch, R., Emenyonu, N. I., Muyindike, W. R., Kekibiina, A., Santos, G. M., & Hahn, J. A. (2015). Comparison of traditional and novel self-report measures to an alcohol biomarker for quantifying alcohol consumption among HIV-infected adults in sub-Saharan Africa. Alcoholism: Clinical and Experimental Research, 39(8), 1518 1527. Bakhireva, L. N., Shrestha, S., Gutierrez, H. L., Berry, M., Schmitt, C., & Sarangarm, D. (2016). Stability of phosphatidylethanol in dry blood spot cards. Alcoholism: Clinical and Experimental Research, 51 (3), 275 280.

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Peng, X., & Frohman, M. A. (2012). Mammalian phospholipase D physiological and pathological roles. Acta Physiologica (Oxford), 204(2), 219 226. Rubin, R. (1988). Phosphatidylethanol formation in human platelets: evidence for thrombin-induced activation of phospholipase D. Biochemical and Biophysical Research Communications, 156(3), 1090 1096. SAMSA, Substance Abuse and Mental Health Services Administration. (2012). The role of biomarkers in the treatment of alcohol use disorders (Vol. 11, Issue 2, pp. 1 8). Rockville, MD: Human Health Services. Schrock, A., Thierauf-Emberger, A., Schurch, S., & Weinmann, W. (2017). Phosphatidylethanol (PEth) detected in blood for 3 to 12 days after single consumption of alcohol-a drinking study with 16 volunteers. International Journal of Legal Medicine, 131(1), 153 160. Shukla, S. D., Sun, G. Y., Gibson Wood, W., Savolainen, M. J., Alling, C., & Hoek, J. B. (2001). Ethanol and lipid metabolic signaling. Alcoholism: Clinical and Experimental Research, 25(5 Suppl ISBRA), 33s 39s. Skipper, G. E., Thon, N., Dupont, R. L., Baxter, L., & Wurst, F. M. (2013). Phosphatidylethanol: The potential role in further evaluating low positive urinary ethyl glucuronide and ethyl sulfate results. Alcoholism: Clinical and Experimental Research, 37(9), 1582 1586. Stewart, S. H., Koch, D. G., Willner, I. R., Anton, R. F., & Reuben, A. (2014). Validation of blood phosphatidylethanol as an alcohol consumption biomarker in patients with chronic liver disease. Alcoholism: Clinical and Experimental Research, 38(6), 1706 1711. Stewart, S. H., Law, T. L., Randall, P. K., & Newman, R. (2010). Phosphatidylethanol and alcohol consumption in reproductive age women. Alcoholism: Clinical and Experimental Research, 34(3), 488 492.

Stewart, S. H., Reuben, A., Brzezinski, W. A., Koch, D. G., Basile, J., Randall, P. K., & Miller, P. M. (2009). Preliminary evaluation of phosphatidylethanol and alcohol consumption in patients with liver disease and hypertension. Alcohol and Alcoholism, 44(5), 464 467. Tettenborn, C. S., & Mueller, G. C. (1988). 12-O-tetradecanoylphorbol-13-acetate activates phosphatidylethanol and phosphatidylglycerol synthesis by phospholipase D in cell lysates. Biochemical and Biophysical Research Communications, 155(1), 249 255. Varga, A., Hansson, P., Johnson, G., & Alling, C. (2000). Normalization rate and cellular localization of phosphatidylethanol in whole blood from chronic alcoholics. Clinica Chimica Acta, 299(1 2), 141 150. Viel, G., Boscolo-Berto, R., Cecchetto, G., Fais, P., Nalesso, A., & Ferrara, S. D. (2012). Phosphatidylethanol in blood as a marker of chronic alcohol use: a systematic review and metaanalysis. International Journal of Molecular Sciences, 13(11), 14788 14812. Wurst, F. M., Thon, N., Aradottir, S., Hartmann, S., Wiesbeck, G. A., Lesch, O., & Alling, C. (2010). Phosphatidylethanol: normalization during detoxification, gender aspects and correlation with other biomarkers and self-reports. Addiction Biology, 15(1), 88 95. Wurst, F. M., Thon, N., Weinmann, W., Tippetts, S., Marques, P., Hahn, J. A., & Lakshman, R. (2012). Characterization of sialic acid index of plasma apolipoprotein J and phosphatidylethanol during alcohol detoxification—a pilot study. Alcoholism: Clinical and Experimental Research, 36(2), 251 257. Zheng, Y., Beck, O., & Helander, A. (2011). Method development for routine liquid chromatography-mass spectrometry measurement of the alcohol biomarker phosphatidylethanol (PEth) in blood. Clinica Chimica Acta, 412(15-16), 1428 1435.

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C H A P T E R

59 Metabolomics to Differentiate Alcohol Use Disorders From Social Drinkers and AlcoholNaive Subjects Baharudin Ibrahim and Keshamalini Gopalsamy School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia

LIST OF ABBREVIATIONS AD AUD AUDIT CAGE COPD DSM IV GC-TOF MS 1

H-NMR WHO OPLS-DA PCA

alcohol dependence alcohol use disorder alcohol use disorders identification test cut down, annoyed, guilty and eye opener chronic obstructive pulmonary disease diagnostic and statistical manual of mental disorders gas chromatography - time of flight mass spectrometry proton nuclear magnetic resonance World Health Organization orthogonal partial least square - discriminant analysis principal component analysis

INTRODUCTION Alcohol drinking is a growing public health concern worldwide. The harmful consumption of alcohol and the trends in hazardous drinking, particularly among young people, is alarming. The World Health Organization (WHO) approximated 3.3 million deaths per year due to the hazardous consumption of alcohol (WHO, 2014).

Alcohol Drinking and Its Detrimental Effects Alcohol intoxication is a result of increasing amounts of alcohol in the bloodstream. Data from several studies suggest that the hazardous effects of alcohol intoxication include, but are not limited to, mental and behavioral disorders such as alcohol use disorders (AUDs), major noncommunicable diseases such as liver cirrhosis, cancers, and cardiovascular diseases, as Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00059-3

well as injuries resulting from car collisions while driving under the influence of alcohol. In addition, the harmful use of alcohol brings significant social and economic losses to individuals and society at large (Hawkins et al., 1997; Perkins, 2002; WHO, 2015).

Alcohol Dependence and Alcohol Use Disorder The Diagnostic and Statistical Manual of Mental Disorders (DSM IV) described two distinct disorders, alcohol abuse and alcohol dependence (AD), with specific criteria for each. Nevertheless, the latest version which is DSM V integrates the two DSM IV disorders, alcohol abuse and AD, into a single disorder called AUD with mild, moderate, and severe subclassifications. AUD can be described as an abnormal pattern of drinking in which the drinker consumes excessive amounts of alcohol and has a continuous urge to drink alcohol. The drinker experiences symptoms such as a reduction in social activities, drinking-search behavior, and continuous drinking regardless of the psychological, social, and physical problems it produces (National Institute on Alcohol Abuse & Alcoholism, 2016).

CURRENT DIAGNOSTIC METHODS OF ALCOHOL USE DISORDER In the context of alcohol abuse, diagnosis can be defined as the process of identifying and determining whether an individual is addicted or dependent on

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alcohol (Babor, 1992). Currently, AUD questionnaires and some biomarkers are the principal methods of diagnosis in clinical practice.

AUD Questionnaires A number of questionnaires have been developed as screening tests to detect potential AUD and is the principal method used to diagnose AUD in clinical practice. Some examples of these questionnaires are the cut down, annoyed, guilty and eye opener (CAGE) questionnaire (Ewing, 1984), AUD identification test (AUDIT) and Michigan alcoholism screening test (MAST) (Best Practice Advocacy Centre of New Zealand, 2010). These questionnaires consist of a series of questions that can discern between normal and harmful alcohol consumption and predict the leading risk factors of some diseases associated with alcohol consumption. One of the main obstacles of AUD questionnaires is that it lacks reliability. This can be attributed to the fact that most AUD subjects are reluctant to confess/disclose their alcohol use behavior.

Biomarkers Biomarkers are quantifiable substances that indicate normal or abnormal activities taking place in our bodies and may indicate an underlying condition or disease (Strimbu & Tavel, 2010). For example, an elevated C-reactive protein level is a nonspecific indicator of arthritic or autoimmune disorders. Similarly, this concept can be applied in the diagnosis of AUD whereby the presence of certain biomarkers in biofluids can determine whether an individual has AUD. Various studies have explored the relationship between alcohol-induced organ damage and certain biomarkers (produced as a result of organ damage) to diagnose AUD (Adias, Egerton, & Erhabor, 2013; Freeman & Vrana, 2010; Litten, Bradley, & Moss, 2010). Here are brief examples found in the literature that illustrate the relationship between alcohol-induced organ damage and biomarkers. 1. Elevated levels of liver enzymes such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma glutamyltransferase (GGT) in AUD individuals are significant indicators of alcohol-induced liver injury. The differences in the levels of AST and GGT in AUD individuals compared to their abstainers have been found to be significant in several studies (Adias et al., 2013; Quaye, Nyame, Dodoo, Gyan, & Adjei, 1991). 2. Altered level of inflammatory mediators such as cytokines due to alcohol consumption had been correlated with the harmful effects of alcohol on

bone, lung, liver, and other tissues (BirkedalHansen, 1993; Fini et al., 2012; Freeman & Vrana, 2010). 3. As coagulating factors are synthesized in the liver, one study concluded that prothrombin time and activated partial thromboplastin time are significantly elevated in AUD individuals (Adias et al., 2013). These findings have paved the way to use blood and urine biomarkers of organ damage to diagnose AUD. A myriad of biomarkers have been investigated to diagnose AUD such as GGT, mean corpuscular volume (MCV), carbohydrate-deficient transferrin (CDT) and many more. Table 59.1 summarizes the types of biomarkers and their use from in the literature.

METABOLOMICS IN ALCOHOL USE DISORDERS DIAGNOSIS In recent years, there has been an increasing interest in the rapidly emerging field of metabolomics. The concept that individuals might have a metabolic profile that could be reflected in the composition of their biological fluids was pioneered by Roger Williams in the late-1940s (Gates & Sweeley, 1978; Gowda & Djukovic, 2014). Nevertheless, it was only with the advancement of analytical technologies that it became viable to quantitate the metabolites. Horning et al. introduced the term “metabolic profile (metabolome)” in 1971 after they established that gas chromatography mass spectrometry (GC-MS) could be used to quantify compounds present in human urine and tissue extracts (Horning & Horning, 1971). Metabolomics can be defined as the field of science that involves the identification and quantification of metabolites within cells, tissues, or biofluids. This is done using sophisticated analytical techniques such as 1H-NMR spectroscopy, and the data obtained is analyzed through statistical and multivariate modeling (Roessner & Bowne, 2009). Metabolomics have emerged as powerful platforms for biomarker discoveries and gene and function analyses (Harrigan & Goodacre, 2012). There is a growing body of literature that recognizes the use of metabolomics as a novel diagnostic approach for disease by studying the predominant metabolite that is present in an individual’s biofluids (Madsen, Lundstedt, & Trygg, 2010; Zhang, Sun, & Wang, 2012; Bogdanov et al., 2008). Since metabolomics capture metabolites which directly relate to processes in biological systems, metabolomics has been used to identify novel biomarkers of diseases such as bipolar disorder, diabetes mellitus, and asthma, among others. These studies have

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METABOLOMICS IN ALCOHOL USE DISORDERS DIAGNOSIS

TABLE 59.1

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Biomarkers of Alcohol Misuse

Biomarkers

Origin of biomarkers

Purported uses

GGT (Litten et al., 2010; Tavakoli, Hull, & Okasinski, 2011)

GGT is present in cell membranes and tissues of some organs such as liver, kidney, spleen, pancreas, and heart. Chronic alcohol consumption results in inflammation and necrosis of these cells, causing leakage of GGT from the destroyed cells and elevated serum GGT levels.

GGT remains elevated for 2 3 weeks after alcohol cessation. Isolated elevation or disproportionate elevation compared to other liver enzymes (such as alkaline phosphatase) can indicate alcohol abuse or alcoholic liver disease, and can indicate excess alcohol consumption up to 3 or 4 weeks prior to the test.

MCV (Conigrave, Davies, Haber, & The MCV is a measure of the average volume of a Whitfield, 2003; Tavakoli et al., 2011) red blood corpuscle. The measure is attained by multiplying a volume of blood by the proportion of blood that is cellular (the hematocrit), and dividing that product by the number of erythrocytes (red blood cells) in that volume.

Chronic ingestion of alcohol increases the size of red blood cells compared to the acute intake. MCV is an indicator of chronic use of alcohol rather than the acute intake.

CDT (BPAC, 2010; Stibler, 1991)

Transferrin is synthesized and released by the liver and transports iron throughout the body.

Regular high alcohol intake leads to a decrease in the number of carbohydrate residues attached to transferrin, increasing carbohydrate-deficient sites. Thus, serum CDT is elevated in individuals who consume large amounts of alcohol, and returns to normal level after 2 3 weeks of cessation.

Phosphatidylethanol (PEth) (Aradottir, Asanovska, Gjerss, Hansson, & Alling, 2006; Stewart et al., 2009)

PEth is a phospholipid formed by phospholipase D enzyme in the presence of ethanol. Levels of PEth in the blood are used as markers of previous alcohol consumption. For this purpose, PEth is more sensitive than CDT.

PEth remains elevated in the blood 1 2 weeks after cessation of moderate to heavy alcohol intake. Intake of less than 48 g ethanol/day for three weeks gives a whole blood a PEth concentration of ,0.7 µmol/L. Repeated ethanol intake of 48 102 g per day for 3 weeks gives a blood PEth of 1.0 2.1 µmol/L.

identified metabotypes which are able to discriminate patients from their controls (Ibrahim et al., 2011; Motsinger-Reif et al., 2013; Schicho et al., 2012). Ibrahim and colleagues used gas chromatography mass spectrometry (GM-MS) and breath as a specimen to develop a discriminatory model which distinguished COPD patients from their healthy controls with 85% sensitivity and 50% specificity. This chapter describes the application of metabolomics to distinguish between AUD, social drinkers, and alcohol-naive subjects. Throughout this chapter, the term “metabolite” is used to refer to small, low molecular-weight organic compound typically involved in a biological process as a substrate or product of metabolism. 1

Using H-NMR Spectroscopy in Metabolomics Any molecule containing one or more atoms with a non-zero magnetic moment is potentially detectable by nuclear magnetic resonance (NMR), and most biologically important molecules have at least one NMR signal (Krishnan, Kruger, & Ratcliffe, 2004). Typically, a metabolite detectable by 1H-NMR contains odd numbers of protons or neutrons and each of the protons produces one or more peaks. The number of

peaks generated by a metabolite, as well as their location and ratio of heights, are reproducible and uniquely determined by the chemical structure of the molecule. The 1H-NMR signal is generated by the motion of magnetic moments of protons or other nuclei in a magnetic field after their excitement with a high-frequency pulse (Silverstein, Webster, Kiemle, & Bryce, 2014). This, with the help of chemometrics software, will help to speculate the chemical structure of the unknown metabolites in the biological samples.

Metabolomics to Investigate Alcohol Consumption in Humans There are a few metabolomics studies that have been conducted to study the effects of alcohol consumption on human metabolome. In a study that compared the serum metabolome of two groups, light drinkers (LD) and moderate to heavy drinkers (MHD), the results showed that 40 identified metabolites in males and 18 in females differed significantly in concentration between these two groups (Jaremek et al., 2013). Out of these metabolites, 10 in males and 5 in females were specific metabolites to discriminate LD from MHD. Taken together, these results suggest

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that alcohol consumption mostly affects metabolic profile classes of diacylphosphatidylcholines, lysophosphatidylcholines, ether lipids, and sphingolipids. Nonetheless, the study did not investigate the metabolic variation associated with AUD. Another recent study looked at the use of metabolomics to discover metabolic fingerprint (metabotype) in urine and plasma that can discriminate AUD individuals from non-AUD drinkers and controls. This study is described in the next section.

Urinary and Plasma Metabolomic Profiling to Discriminate Between Alcohol Use Disorders, Social Drinkers, and Alcohol-Naive Subjects Volunteers with an age range of 18 60-years-old were recruited and divided into three groups; AUD drinkers, social drinkers, and alcohol-naive controls (Table 59.2). Some subjects were newly diagnosed AUD patients who had not started on any AUD treatment. The diagnosis was based on an AUD questionnaire and/or the National Institutes of Health (NIH) criteria of AUD (Zieve & David, 2011). Urine and blood samples were collected from the subjects and analyzed using NMR spectroscopy. The spectra were processed with topsin and AMIX and the resultant excel file was imported to Soft Independent Modeling

of Class Analogies (SIMCA 13.0.3, Umetrics) for statistical analysis to find the discriminating metabolites of AUD. Principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLSDA) were performed on the data. The metabolites were identified using online metabolomics databases. The urine metabolites study revealed: 1. As shown in Fig. 59.1, the cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol, and 2hydroxyisovaleric acid were identified as biomarkers of AUD in urine with high specificity and accuracy. 2. All the biomarkers of AUD except 2hydroxyisovaleric acid usually appear naturally in urine, but at much lower concentrations. After chronic consumption of alcohol, the concentrations of these biomarkers were greatly increased. 3. Metabolism of ethanol produces lactic acid which may cause conversion of pyruvate to lactate instead of glucose (Luft, 2001) due to the increased NADH/ NAD 1 ratio arising from ethanol metabolism. This may lead to lactic acidosis in AUD patients. 4. It has also been reported that 2-hydroxyisovaleric acid is raised in the urine of patients with lactic acidosis, but it is absent in the urine of control subjects (Landaas & Jakobs, 1977). This finding was replicated in our study. FIGURE 59.1 Example of one full 1HNMR spectrum each of the three groups. The numbers in the box on the top of the selected peaks indicate the biomarkers in urine that are different between the three groups based on the peak height/intensity. AUD (green): Compounds (2), (3), (4), (5), and (6) are higher in this group compared to other groups. Social drinkers (red) and control (blue): Compound (1) is higher compared to AUD. Source: Adapted with permission from Mostafa, H., Amin, A. M., Teh, C. H., Murugaiyah, V., Arif, N. H., & Ibrahim, B. (2016). Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects. Drug and Alcohol Dependence, 169, 80 84.

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MINI-DICTIONARY OF TERMS

FIGURE 59.2

1

H-NMR spectra of the three groups showing propionic acid (triplet) in an individual with AUD. AUD (blue): Propionate formation increases with chronic alcohol drinking. This peak is absent in social drinkers (red) and the control group (green). The 1H-NMR spectra of a male social drinker were checked to ensure that propionic acid is a true biomarker for AUD and not because of recent consumption of alcohol. Source: Adapted with permission from Mostafa, H., Amin, A. M., Teh, C. H., Arif, N. H., & Ibrahim, B. (2017). Plasma metabolic biomarkers for discriminating individuals with alcohol use disorders from social drinkers and alcohol-naive subjects. Journal of Substance Abuse Treatment, 77, 1 5.

5. Besides, in cases of lactic acidosis, it was reported that there is an increment of the intermediates of citric acid (Krebs) cycle such as citric acid and cis-aconitic acid (Bhagavan, 2002; Bowling & Morgan, 2005). Again, we identified these metabolites as biomarkers for AUD. The plasma metabolites study revealed: 1. The identified metabotype has a high discriminatory power, being associated neither with social drinking nor with absolute abstinence. Also, the discriminatory power of one metabolite—acetic acid—is not compromised by recent nonchronic drinking. 2. The findings of this study indicated that the propionic acid and the acetic acid could be used as plasma biomarkers of AUD with high specificity and accuracy. 3. Ethanol metabolism by alcohol dehydrogenase causes an increase in the NADH/NAD 1 ratio (Calabrese, Calvani, & Butterfield, 2004). This increases lactate formation from pyruvate which will cause accumulation of propionate (Calabrese et al., 2004). Since propionic acid was absent in social drinkers and control group, it is imperative to ensure that propionic acid is actually a true biomarker for AUD which is able to discriminate the AUD group from social drinkers and controls groups and not due to recent alcohol intake. Hence,

we checked the 1H-NMR spectra of a male social drinker. The spectra showed that the metabolic fingerprint was absent from the social drinker volunteer which meant that propionic acid is likely to be a true biomarker of AUD and not because of recent consumption of alcohol (Fig. 59.2). Overall, both studies strengthen the idea that 1HNMR is a powerful tool in metabolomics to obtain identifiable discriminating biomarkers in urine and plasma with excellent reproducibility for AUD. The identification of specific biomarkers of the discriminating metabotype and the further correlation between them and some metabolic pathways indicates that there is a strong association between the discovered urine and plasma biomarkers with AUD. The specificity and accuracy of the urine model were found to be excellent that it can possibly be used to diagnose AUD if a NMR instrument is available in the clinical facility.

MINI-DICTIONARY OF TERMS Alcohol use disorder Drinking behavior that becomes severe which results in addiction to alcohol. Biomarkers A biological characteristic that is objectively measured and evaluated as an indicator of normal biological or pathological processes, or a response to a therapeutic intervention.

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59. METABOLOMICS TO DIFFERENTIATE ALCOHOL USE DISORDERS FROM SOCIAL DRINKERS AND ALCOHOL-NAIVE SUBJECTS

TABLE 59.2

Frequencies and Percentages of Demographics/Clinical Data AUD, n (%)

Social drinkers, n (%)

Controls, n (%)

30 (100)

41 (75.9)

28 (46.7)

0

13 (24.1)

32 (53.3)

Malay

7 (23.3)

10 (18.5)

39 (65)

Chinese

0

17 (31.5)

2 (3.3)

Indian

23 (76.7)

26 (48.1)

19 (31.7)

0

1 (1.9)

0

45.7 (47.5)

39.46 (39)

37.13 (34.5)

Smokers

27 (90)

31 (57.4)

10 (16.7)

Ex-Smokers

0

5(9.3)

2 (3.3)

Nonsmokers

3 (10)

18 (33.3)

48 (80)

Demographics/clinical data (1),(2)

1. Gender Male Female

(1),(2)

2. Race

Other (3)

3. Mean age (Median age) (1),(2)

4. Smoking

p-value , 0.05. Chi-square test. Kruskal-Wallis test. Published with permission from Mostafa, H., Amin, A. M., Teh, C. H., Murugaiyah, V., Arif, N. H., & Ibrahim, B. (2016). Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects. Drug and Alcohol Dependence, 169, 80 84. (1) (2) (3)

Drinking-search behavior Searching for events or places that include alcohol drinking. Metabolomics The scientific study of the set of metabolites present within an organism, cell or tissue. Metabolites Intermediate products of metabolic reactions catalyzed by various enzymes that naturally occur within cells. Metabotype Metabolic profile of an individual. Principal component analysis A multivariate statistical analysis that uses orthogonal transformation to generate principal components. Proton nuclear magnetic resonance spectroscopy The application of NMR on the hydrogen-1 nuclei within the molecules of a substance to determine the structure. Social drinkers People who drink alcohol mainly on social occasions and only in moderate quantities.

KEY FACTS

• Different medical conditions can have distinct metabolic fingerprints. • Identifying a metabolic fingerprint associated with a disease is a noninvasive tool for disease diagnosis.

Principal Component Analysis • PCA is used to interpret data by reducing the dimensionality of the dataset to interpretable linear combinations of the data. • PCA demonstrates primary evaluation and visualization of between-class similarity based on the contributing variables’ variation direction in a multivariate space. • It is often used in exploratory data analysis and for making predictive models, such as in metabolomics.

Metabolomics • Metabolomics is a newly emerging field of “omics” research. • Metabolomics analysis can be conducted on various biofluids, such as blood, urine, cerebrospinal fluids, breath, and seminal fluids. • The metabolic profile of a living organism is largely affected by the internal or external environment. • Factors such as disease phenotype, specific diet exposure, and drug response may cause variations in metabolome.

SUMMARY POINTS • AUD is a ravaging public health and social problem. • Questionnaires and some biomarkers used to diagnose AUD lack specificity and sensitivity, which may delay treatment. • Metabolomics using NMR spectroscopy can provide novel techniques for the identification of novel biomarkers of AUD.

VI. BIOMARKERS AND SCREENING

REFERENCES

• This chapter describes the use of NMR spectroscopy to identify novel biomarkers to discriminate between AUD, non-AUD drinkers, and controls. • 1H-NMR-based metabolomics was used to obtain the metabolic profiles of urine samples and plasma samples. • Metabolic analysis of urine identified novel biomarkers which can discriminate AUD drinkers from social drinkers and controls with high accuracy.

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and healthy individuals. Journal of Proteome Research, 11(6), 3344 3357. Silverstein, R. M., Webster, F. X., Kiemle, D. J., & Bryce, D. L. (2014). Spectrometric Identification of Organic Compounds, 8th edition. John wiley & sons. Stewart, S. H., Reuben, A., Brzezinski, W. A., Koch, D. G., Basile, J., Randall, P. K., & Miller, P. M. (2009). Preliminary evaluation of phosphatidylethanol and alcohol consumption in patients with liver disease and hypertension. Alcohol & Alcoholism, 44(5), 464 467. Stibler, H. (1991). Carbohydrate-deficient transferrin in serum: a new marker of potentially harmful alcohol consumption reviewed. Clinical Chemistry, 37(12), 2029 2037. Strimbu, K., & Tavel, J. A. (2010). What are biomarkers? Current Opinion in HIV and AIDS, 5(6), 463.

Tavakoli, H. R., Hull, M., & Okasinski, L. M. (2011). Review of current clinical biomarkers for the detection of alcohol dependence. Innovations in Clinical Neuroscience, 8(3), 26. World Health Organization. (2014). Management of substance abuse unit. Global status report on alcohol and health, 2014. World Health Organization. World Health Organization. Media Centre. (2015). Alcohol fact sheet. National Insititute on Alcohol Abuse and Alcoholism. Available from ,https://pubs.niaaa.nih.gov/publications/dsmfactsheet/ dsmfact.htm. Accessed 08.07.17. Zhang, A., Sun, H., & Wang, X. (2012). Serum metabolomics as a novel diagnostic approach for disease: A systematic review. Analytical and Bioanalytical Chemistry, 404(4), 1239 1245. Zieve, D., & David, C. (2011). Alcoholism and alcohol abuse. Bethesda: NIH.

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C H A P T E R

60 Meconium Biomarkers of Prenatal Alcohol Exposure 1

Esther Papaseit1, Robert Muga2, Paola Zuluaga2, Arantza Sanvisens2 and Magı´ Farre´1 Department of Clinical Pharmacology, Hospital Universitari Germans Trias i Pujol, Institut Germans Trias i Pujol IGTP, Universitat Auto`noma de Barcelona, Badalona, Spain 2Department of Internal Medicine, Hospital Universitari Germans Trias i Pujol, Institut Germans Trias i Pujol IGTP, Universitat Auto`noma de Barcelona, Badalona, Spain

LIST OF ABBREVIATIONS ADH ARND ARBD BAC EtG EtS FAEE FAS ND-PAE PAE

alcohol dehydrogenase alcohol-related neurodevelopmental disorder alcohol-related birth defects blood alcohol concentration ethyl glucuronide ethyl sulfate fatty acid ethyl ester fetal alcohol syndrome neurodevelopmental disorder associated with prenatal alcohol exposure prenatal alcohol exposure

INTRODUCTION Alcohol Use in Women During Pregnancy Alcohol is the most widely used drug worldwide. Alcohol consumption is one of the world’s leading risk factors for morbidity, disability, and mortality. In recent years, alcohol use has become a widespread and common social behavior among populations who are vulnerable based on their gender, age, familiar factors, and socioeconomic status (European School Survey Project on Alcohol & Other Drugs, 2015; World Health Organization, 2014a). There are well-established gender differences for the potential harmful effects of alcohol. Women possess a wide range of physiological factors (lower body weight and total body water,

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00060-X

higher proportion of body fat, and lower activity of alcohol metabolizing enzymes and hormones), which together contribute to higher blood alcohol concentrations (BACs) than men. The major public health concerns are women’s vulnerability to alcohol-related harm and recent patterns of alcohol consumption among women of reproductive age, especially during pregnancy. Strategies to reduce health, economic, and social problems related to alcohol use are focused on protecting young people, children, and the fetus and include the specific aim to reduce exposure to alcohol during pregnancy (European Commission, 2016). At this time, there are no known health benefits of alcohol use during pregnancy or an established safe level of alcohol use during pregnancy; the best approach remains total abstinence. In fact, clinical recommendations and public health campaigns warn about the associated risks for pregnant women and women who might become pregnant and urge abstaining from any alcohol use (Table 60.1). As many women continue to use alcohol and/or have binge-drinking episodes during early pregnancy (unknown and/or unplanned) and overall pregnancy (Substance Abuse & Mental Health Services Administration, 2013), alcohol use remains a substantial public health problem. Epidemiologic studies report that alcohol use is lower during the second and third trimesters than during the first, but there are surprisingly high rates of alcohol use in pregnancy—estimated

585

© 2019 Elsevier Inc. All rights reserved.

586 TABLE 60.1

60. MECONIUM BIOMARKERS OF PRENATAL ALCOHOL EXPOSURE

Definitions of Alcohol Use in Women

Drinking level definition

Number of alcoholic drinks

Moderate alcohol use

Up to 1 alcoholic drink per day

Binge drinking

Four or more alcoholic drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) on at least 1 day in the past month

Heavy alcohol use

Binge drinking on 5 or more days in the past month

Drinking at low risk for developing alcohol use disorder

No more than 3 drinks on any single day and no more than 7 drinks per week

Pregnant women and/or women contemplating pregnancy Drinking level classification

Number of drinks

No alcohol use

No alcoholic drink during pregnancy

This table shows the drinking levels defined by National Institute on Alcohol Abuse and Alcoholism (NIAAA). Available from https://www.niaaa.nih.gov/ alcohol-health/overview-alcohol-consumption/moderate-binge-drinking.

TABLE 60.2

Maternal Factors Related With PAE

Pregnancy-related maternal factors

Nonpregnancy-related maternal factors

Smoking

Extreme maternal age

Alcohol use

Urban environment

Binge drinking

Unplanned pregnancy

Use of other drugs

Socioeconomic class Marital status Culture Exposure to violence/trauma

This table shows the main conditions that have been postulated as predictors of alcohol use during pregnancy.

prevalence of 9.8% (Ethen et al., 2009; Popova, Lange, Probst, Gmel, & Rehm, 2017)—despite clinical recommendations and public health campaigns. Some factors have been postulated as predictors of alcohol use during pregnancy and are key target prevention efforts ˚ restedt, (Skagerstro¨m, Alehagen, Ha¨ggstro¨m-Nordin, A & Nilsen, 2013; Skagerstro´m, Chang, & Nilsen, 2011; Roberts, Wilsnack, Foster, & Delucchi, 2014) (Table 60.2). Alcohol is a well-established teratogen to the human embryo when consumed during pregnancy. Epidemiologic and human clinical studies, as well as studies carried out in animal models, have demonstrated its potential teratogenicity (Ornoy & Ergaz, 2010). Alcohol transfers across the placenta to reach

the embryo/fetus and may have detrimental effects on the central nervous system and other organs of the developing embryo and fetus. Potential harmful effects of alcohol depend on the exposure (dose, frequency, and timing of alcohol use), developmental stage of the embryo and fetus, as well as other factors including maternal nutrition and metabolism, genetics, and possibly epigenetic factors, and further unknown fetal vulnerabilities (Ungerer, Knezovich, & Ramsay, 2013). Prenatal alcohol exposure (PAE) is the leading preventable cause of low-birth weight, microcephaly, craniofacial abnormalities, skeletal and organ defects, and cognitive, behavioral, and emotional difficulties (Burd, 2016; Burd, Blair, & Dropps, 2012; Kingdon, Cardoso, & McGrath, 2016). This range of neurodevelopmental disorders that are associated with PAE (NDPAE) are known as Fetal Alcohol Spectrum Disorders, and have an estimated prevalence of 15 per 10,000 people in the general population (Popova et al., 2017).

Metabolism of Alcohol: Pregnancy, Embryo/ Fetus, Neonate Alcohol is metabolized through both oxidative and nonoxidative pathways. The main oxidative metabolism is hepatic through three different mechanisms, alcohol dehydrogenase (ADH) that metabolizes alcohol to acetaldehyde (85 90%), cytochrome P450 through the CYP2E1 isoenzyme (5 10%) and catalase (5%). Acetaldehyde is then converted to acetate (acetic acid) by aldehyde dehydrogenase (ALDH). In addition to oxidation, several nonoxidative routes result in the enzymatic conjugation of ethanol to endogenous metabolites, such as glucuronic acid, sulfates, phospholipids, and fatty acids, resulting in minor metabolites such as ethyl glucuronide (EtG), ethyl sulfate (EtS), phosphatidylethanol, and fatty acid ethyl esters (FAEEs), respectively (Fig. 60.1). Furthermore, alcohol can be eliminated unchanged through cutaneous (0.1%), pulmonary (0.7% 3%), and renal excretions (0.3% 10%) (DinisOliveira, 2016; Heier, Xie, & Zimmermann, 2016). Pregnancy is a complex state where changes in maternal physiology have evolved to favor the development and growth of the placenta and the embryo/fetus (Feghali, Venkataramanan, & Caritis, 2015). Adaptations include an increase in gastric pH, reduction in intestinal motility, increased cardiac output, increased renal blood flow and glomerular filtration rate, increased portal vein blood flow, and reduced plasma albumin concentrations (Isoherranen & Thummel, 2013). Some of these physiological changes can influence drug absorption, distribution, metabolism, and excretion. Alcohol use during pregnancy results in a lower BAC than in nonpregnant women due to changes in body composition and total

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INTRODUCTION

Alcohol Oxidative metabolism ADH CYP2E1 Catalase

Non-oxidative metabolism

Acetaldehyde

Meconium SULT

ALDH

Acetate

FAAES AEAT TGL LPL ChE CE

UGT

EtS

FAEE EtG EtS

EtG FAEE

FIGURE 60.1

Alcohol metabolism and related meconium biomarkers. ADH, Alcohol dehydrogenase; AEAT, Acyl-CoA:ethanol O-acyltransferase; ALDH, Aldehyde dehydrogenase; CE, Carboxylesterase; ChE, Cholesterol esterase or carboxylester lipase; CoA, Coenzyme A; EtG, Ethyl glucuronide; EtS, Ethyl sulfate; FAEE, Fatty acid ethyl esters; FAEES, Fatty acid ethyl ester synthase; LPL, Lipoprotein lipase; SULT, Sulfotransferase; UGT, UDP-glucuronosyltransferase; TGL, Triglyceride lipase.

body water resulting in an increase in the volume of distribution. Alcohol metabolism pathways during pregnancy involve the placenta, fetus, embryo, and neonate; although, the rates of activity and concentrations depend on the gestational age. Alcohol readily crosses the placenta and rapidly distributes into the fetal compartment, resulting in similar BACs in maternal and fetal circulations where amniotic fluid acts as an alcohol reservoir (Farst, Valentine, & Hall, 2011). In the last two trimesters of pregnancy, recurrent cycles of fetal swallowing of the amniotic fluid, low fetal metabolism, and elimination of urine back into the amniotic fluid prolong ´ lvarez, Tabernero, & the BAC of the fetus (Cabarcos, A Bermejo, 2015). The fetal metabolism is constantly changing during development. Over the course of the pregnancy, ADH activity, ADH isoforms, CYP2E1 expression, and catalase activity increase in parallel with gestational age. The low expression of CYP2E1 in the fetus gradually increases after birth, reaching 30% 40% of adult hepatic levels by one year of age (Burd et al., 2012; Heller & Burd, 2014; Zelner & Koren, 2013) (Fig. 60.1). At birth, the rate of alcohol elimination from neonatal blood is about half of the elimination rate from maternal blood. In the first trimester, the fetus has low

hepatic ADH activity and low expression of some ADH isozymes; therefore, there is a limited capacity for oxidative alcohol metabolism.

Alcohol Consumption in Pregnancy and Biological Matrices Despite the use of self-reported strategies and screening questionnaires to identify alcohol consumption during pregnancy (e.g., AUDIT-C, T-ACE, TWEAK) (World Health Organization, 2014b), it is a major challenge to obtain reliable maternal information about alcohol-drinking patterns. In practice, maternal alcohol use during pregnancy continues to be under diagnosed as there is no established routine laboratory testing. During the past decade, efforts have been made to identify and quantify alcohol-related analytes of alcohol to be used as diagnostic (biomarkers of acute/ chronic damage) and prediction tools (biomarkers of exposure/use). Nowadays, the vast majority of biomarkers of alcohol exposure are detected in conventional biological matrices (blood and urine); although, in recent years nonconventional biological matrices have emerged as alternative noninvasive methods (hair,

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60. MECONIUM BIOMARKERS OF PRENATAL ALCOHOL EXPOSURE

sweat, nails) (Howlett, Abernethy, Brown, Rankin, & Gray, 2017). Particularly in pregnancy, specific biomarkers to detect PAE can be tested in different maternal and neonatal matrices (urine and blood), which are also used for nonpregnancy conditions. There is particular interest in testing specimens that provide direct maternofetal information (e.g., placenta tissues, umbilical cord blood) and in noninvasive tests that can inform about the consumption during the second and/or third trimester of pregnancy, such as maternal and neonatal hair and neonatal meconium. Recently, maternal hair testing has emerged as a reliable tool to predict PAE, in addition to meconium (Joya et al., 2016).

Alcohol-Related Analytes in Meconium Meconium, the first fecal matter of a neonate, is detected in the gastrointestinal tract of the fetus as early as 10 16 weeks of gestation. It is a sterile, blackish-green, odorless complex comprised of water (72% 80%), mucopolysaccharides, bile salts, bile acids, epithelial cells, lanugo hair, components of the vernix caseosa, proinflammatory substances, and residues of swallowed amniotic fluid. The total weight of meconium increases exponentially from about 1 g at 23 26 gestational weeks to 5 g at 27 32 gestational weeks and, finally, to 20 80 g at birth. Therefore, at least 75% of it originates from the last 8 weeks of pregnancy and is normally retained in the fetus’ bowel until after birth (Joya et al., 2012). Meconium is considered an indirect reflection of maternal drug use during the last 20 weeks of gestation, offering a wider window of exposure than other neonatal matrices (Bearer, 2003). Meconium is expelled during 1 5 days after birth. Small amounts are enough to detect and quantify alcohol biomarkers. The only precautions to consider are the correct collection and preservation to avoid external contamination. It is necessary to point out that it is not possible to clearly distinguish when in the last several weeks/months alcohol use occurred, and that first-time alcohol use just before delivery may result in a false negative meconium result because it has not been deposited yet; in addition, specimen collection can be difficult in newborns who have passed meconium in utero prior to delivery and in those who are very small or critically ill (Farst et al., 2011). The alcohol-related analytes in the meconium from nonoxidative metabolism, FAEEs, EtG, and/or EtS, have been investigated to detect PAE and/or its clinical consequences. It is notable that limited studies have simultaneously analyzed FAEEs, EtG, and EtS in meconium. Two studies have simultaneously analyzed EtG and EtS (Himes et al., 2015; Sanvisens et al., 2016); while, one cross-sectional study determined FAEEs in

combination with EtG (Goecke et al., 2014). Previously, two cohort studies quantified FAEEs in addition to EtG and EtS (Morini, Groppi et al., 2010; Pichini, Morini et al., 2009) and one of these studies compared subgroups according to the FAEE cutoff (2 nmol/g). The rest of the studies, including randomized screening, cross-sectional, cohort, and case control studies, quantified only one of the mentioned alcohol-related analytes. Globally, these analytes are valuable biomarkers of PAE with relatively good sensitivity and specificity (Bager, Christensen, Husby, & Bjerregaard, 2017; Cabarcos et al., 2014; McQuire et al., 2016; Min, Singer, Minnes, Wu, & Bearer, 2015; Peterson et al., 2008). In fact, meconium results have been legally used by child protective services and other law enforcement agencies to determine the eligibility of parents to keep their neonate.

Fatty Acid Ethyl Esters The FAEEs are nonoxidative metabolites of alcohol (endogenous alcohol production from gut microflora and from exogenous food and/or alcohol use) formed by an enzymatic esterification of ethyl alcohol with free fatty acids and other lipids by the enzyme FAEE synthase and acetyl-coenzyme A (acetyl-CoA)/ethanol O-acyltransferase mainly in the liver and pancreas (Joya et al., 2012). Compared with alcohol and its oxidative metabolites, FAEEs have a prolonged half-life and can be detected in blood at least 24 hours after alcohol use. The FAEEs can be detected in blood and organs damaged by alcohol abuse as they persist in adipose tissue after alcohol has been eliminated from the body. In total more than 20 different FAEEs have been identified in different biological matrices and are traditionally used as postmortem biomarkers for alcohol use. The FAEEs that originate from the mother do not cross the human placenta to reach fetal circulation. Hence, neonatal FAEEs in meconium represent alcohol that was metabolized in fetal tissues and is considered the first direct biomarker of PAE (Pichini, Garcia-Algar, Klein, & Koren, 2009). In the early-1990s, FAEEs were first proposed as useful biomarkers of PAE in meconium (Klein, Karaskov, & Koren, 1999). A few years later, a notinsignificant number of validated and sensitive new analytical methods of FAEEs detection were developed (Bearer, 2003; Hutson, Magri, Gareri, & Koren, 2010; Hutson, Rao, Fulga, Aleksa, & Koren, 2011; Kwak et al., 2010; Pichini et al., 2008; Roehsig, de Paula, Moura, Diniz, & Yonamine, 2010; Vaiano et al., 2016). Consequently, different FAEEs (4 10 FAEEs) and their combinations (sum of 4 9 FAEEs) emerged as potential biomarkers of PAE (Table 60.3).

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INTRODUCTION

TABLE 60.3

589

FAEEs Commonly Measured in Meconium

FAEEs

Shorthand chemical nomenclature

Ethyl laurate

E12:0

Bearer et al. (1999), Garcia-Algar et al. (2008), Himes et al. (2015), Himes, Concheiro, Scheidweiler, & Huestis (2014), Kwak et al. (2010), Moore et al. (2003), Ostrea et al. (2006), Pichini et al. (2008), Roehsig et al. (2010)

Ethyl myristate

E14:0

Bakdash et al. (2010), Bearer et al. (1999), Bearer et al. (2005), Cabarcos et al. (2012), Cabarcos et al. (2014), Garcia-Algar et al. (2008), Himes et al. (2014), Himes et al. (2015), Kwak et al. (2010), Min et al. (2015), Moore et al. (2003), Ostrea et al. (2006), Peterson et al. (2008), Pichini et al. (2008), Roehsig et al. (2010), Vaiano et al. (2016)

Ethyl palmitate

E16:0

Bakdash et al. (2010), Bearer et al. (1999), Bearer et al. (2005), Bearer (2003), Cabarcos et al. (2012), Cabarcos et al. (2014), Gareri et al. (2008), Garcia-Algar et al. (2008), Goh et al. (2010), Gross et al. (2017), Himes et al. (2014), Himes et al. (2015), Hutson, Aleksa, Pragst, & Koren, (2009), Hutson et al. (2011), Kwak et al. (2010), Min et al. (2015), Moore et al. (2003), Ostrea et al. (2006), Peterson et al. (2008), Pichini et al. (2008), Pichini et al. (2012), Roehsig et al. (2010), Vaiano et al. (2016)

Ethyl palmitoleate

E16:1

Bearer et al. (2005), Garcia-Algar et al. (2008), Gareri et al. (2008), Himes et al. (2014), Himes et al. (2015), Kwak et al. (2010), Moore et al. (2003), Pichini et al. (2008), Pichini et al. (2012), Roehsig et al. (2010)

Ethyl stearate

E18:0

Bakdash et al. (2010), Bearer et al. (1999), Cabarcos et al. (2012), Cabarcos et al. (2014), Garcia-Algar et al. (2008), Gareri et al. (2008), Goh et al. (2010), Gross et al. (2017), Himes et al. (2014), Himes et al. (2015), Hutson et al. (2009), Hutson et al. (2011), Kwak et al. (2010), Moore et al. (2003), Ostrea et al. (2006), Pichini et al. (2008), Pichini et al. (2012), Roehsig et al. (2010), Vaiano et al. (2016)

Ethyl oleate

E18:1

Bakdash et al. (2010), Bearer et al. (1999), Bearer et al. (2005), Bearer (2003), GarciaAlgar et al. (2008), Gareri et al. (2008), Goh et al. (2010), Gross et al. (2017), Himes et al. (2014), Himes et al. (2015), Hutson et al. (2009), Hutson et al. (2011), Kwak et al. (2010), Min et al. (2015), Moore et al. (2003), Ostrea et al. (2006), Peterson et al. (2008), Pichini et al. (2008), Pichini et al. (2012); Roehsig et al. (2010), Vaiano et al. (2016)

Ethyl linoleate

E18:2

Bakdash et al. (2010), Bearer et al. (1999), Bearer et al. (2005), Bearer (2003), GarciaAlgar et al. (2008), Gareri et al. (2008), Goh et al. (2010), Gross et al. (2017), Himes et al. (2014), Himes et al. (2015), Hutson et al. (2009), Hutson et al. (2011), Kwak et al. (2010), Min et al. (2015), Moore et al. (2003), Ostrea et al. (2006), Peterson et al. (2008), Pichini et al. (2008), Pichini et al. (2012), Roehsig et al. (2010)

Ethyl linolenate

E18:3

Bearer et al. (1999), Bearer et al. (2005), Garcia-Algar et al. (2008), Gareri et al. (2008), Gross et al. (2017), Himes et al. (2014), Himes et al. (2015), Kwak et al. (2010), Min et al. (2015), Moore et al. (2003), Ostrea et al. (2006), Peterson et al. (2008), Pichini et al. (2008), Pichini et al. (2012)

Ethyl arachidonate

E20:4

Bearer et al. (1999), Bearer et al. (2005), Garcia-Algar et al. (2008), Gareri et al. (2008), Gross et al. (2017), Himes et al. (2014), Himes et al. (2015), Kwak et al. (2010), Min et al. (2015), Moore et al. (2003), Ostrea et al. (2006), Peterson et al. (2008), Pichini et al. (2008), Pichini et al. (2012), Roehsig et al. (2010)

Ethyl E22:6 docosahexanoate

References

Ostrea et al. (2006)

COMBINATION OF FAEES Sum of four FAEEs

E14:0, E16:0, E18:0, E18:1

Himes et al. (2014)

Sum of four FAEEs

E16:0, E18:0, E18:1, E18:2

Goh et al. (2010), Zelner, Huston et al. (2012), Zelner, Shor et al. (2012)

Sum of five FAEEs

E14:0, E16:0, E18:0, E18:1, E18:2

Bakdash et al. (2010)

Sum of six FAEEs

E16:0, E18:0, E18:1, E18:2, E18:3, E20:4

Gross et al. (2017)

(Continued)

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590 TABLE 60.3

60. MECONIUM BIOMARKERS OF PRENATAL ALCOHOL EXPOSURE

(Continued)

FAEEs

Shorthand chemical nomenclature

Sum of seven FAEEs

E16:0, E16:1, E18:0, E18:1, E18:2, E18:3, E20:4

Garcia-Algar et al. (2008), Himes et al. (2014), Himes et al. (2015), Hutson et al. (2010), Morini, Groppi et al. (2010), Pichini et al. (2008), Pichini et al. (2009), Pichini et al. (2012)

Sum of eight FAEEs

E12:0, E14:0, E16:1, E16:0, E18:0, E18:1, E18:2, E20:4

Roehsig et al. (2010)

Sum of nine FAEEs

E12:0, E14:0, E16:0, E16:1, E18:0, E18:1, E18:2, E18:3, E20:4

Himes et al. (2014), Kwak et al. (2014), Pichini et al. (2008)

References

This table summarizes different FAEEs and FAEE combinations that have been described as potential biomarkers of PAE. It includes a list of references related to each FAEE in particular or combination of FAEEs.

There are currently great differences documented with regard to the FAEEs detected and which ones are predominant. Thus, certain FAEEs have been proposed as biomarkers to distinguish alcohol use (e.g., ethyl oleate, ethyl linoleate, ethyl laurate) from no alcohol use (e.g., ethyl myristate) during pregnancy with contradictory results (Bearer et al., 1999; Bearer et al., 2005; Chan, Klein, Karaskov, & Koren, 2004; GarciaAlgar et al., 2008; Moore, Jones, Lewis, & Buchi, 2003; Ostrea et al., 2006). Nowadays, total FAEEs concentration (cumulative concentration of several FAEEs) is considered the gold standard for alcohol detection in meconium samples (Bakdash et al., 2010; Garcia-Algar et al., 2008; Goh et al., 2010; Gross, Harris, Brown, & Gauthier, 2017; Himes et al., 2015; Kwak et al., 2014; Morini, Groppi et al., 2010; Morini, Marchei et al., 2010; Pichini et al., 2008; Pichini, Morini et al., 2009; Pichini et al., 2012; Roehsig et al., 2010; Zelner, Hutson, Kapur, Feig, & Koren, 2012; Zelner, Shor et al., 2012). Globally, FAEEs concentrations in meconium are nine times more sensitive than self-reported maternal alcohol use (McQuire et al., 2016); although, they depend on the amount of alcohol used, BAC, length of exposure, and gestational age. The high interindividual variability of the total FAEE concentrations among meconium samples, including those from neonates not exposed to alcohol during pregnancy, led to the establishment of a cut-off value. Results from FAEE concentrations suggested that the best cut-off value for the screening of PAE was 600 ng/g of meconium (2 nmol/g) when detecting six FAEEs, with cutoff values ranging from 500 to 600 ng/g (1.6 2 nmol/ g) when testing for four FAEEs. Meconium FAEE concentrations .600 ng/g (2 nmol/g) have been related to regular alcohol use ( . 2 alcohol drinks per day) or binge drinking during pregnancy. Consecutive studies have proposed cut-offs ranging from 2 to 0.5 nmol/g (Bakdash et al., 2010; English et al., 2016; Hutson et al., 2010; Morini, Groppi et al., 2010; Morini, Marchei et al., 2010; Pichini et al., 2012; Pichini et al., 2014).

False positive results have been attributed to endogenous formation, metabolic processes, external contamination with postnatal stool, incorrect sample collection and/or conservation, diet (e.g., olive oil use), and drugs (e.g., prenatal vitamin use) (Chan et al., 2004; Derauf, Katz, & Easa, 2003; Gareri, Lynn, Handley, Rao, & Koren, 2008; Zelner, Huston et al., 2012).

Ethyl Glucuronide and Ethyl Sulfate Both EtG and EtS are minor, stable, nonvolatile, water-soluble, and direct phase II metabolites of alcohol formed after conjugation with glucuronic acid via uridine 5’-diphospho-glucuronosyltransferase (UDPglucuronosyltransferase, UGT) and sulfate conjugation through the action of cytosolic sulfotransferase, respectively (Wurst et al., 2006). In blood, EtG and EtS are detectable up to 4 8 hours after alcohol use; while, in urine, EtG is detectable from 1 hour to up to five days, and EtS up to 30 hours after alcohol use. Thus, EtG and EtS are considered urinary alcohol biomarkers that can be detected for longer periods than alcohol (Joya et al., 2012); in addition, EtG and EtS have been proposed as maternal biomarkers of alcohol intake when detected in blood and maternal hair. In 2010, EtG was first investigated in meconium as a biomarker to detect PAE. There is limited information on EtS, which is generally detected in combination with EtG. Unlike FAEEs, the fetal capacities for glucuronidation and sulfatation are limited. The transfer of EtG and EtS across the human placenta suggests that their presence in meconium does originate from the mother. In addition, EtG can be also detected in placental tissue (Matlow, Lubetsky, Aleksa, Berger, & Koren, 2013; Morini et al., 2011). The EtG concentrations in meconium samples have been analyzed in different populations and range from 15.6 to 64 ng/g in Italy and up to 101.5 ng/g in Spain (Morini, Groppi et al., 2010; Pichini et al., 2009;

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591

KEY FACTS

Sanvisens et al., 2016). The proposed cut-offs for EtG range from 30 to 50 ng/mg (Abernethy et al., 2017; Morini, Groppi et al., 2010; Pichini et al., 2014). Global results showed that EtG concentrations up to 30 ng/g have relatively high sensitivity and specificity, superior to FAEE cut-offs, for maternal self-reported alcohol use after 19 weeks of gestation. The EtG in meconium has been associated with alcohol use in the last period of pregnancy. In addition, some of the advantages of EtG, compared with FAEEs, are better stability in meconium and insensitivity to maternal diet variation (Himes et al., 2015). Research on EtS is very limited compared with the other PAE biomarkers. Data from studies examining both EtG and EtS in a large number of meconium samples found that EtS was undetected in most samples (50% 80%) (Sanvisens et al., 2016) or detected at a very low concentration (,15 ng/g) (Himes et al., 2015; Morini, Groppi et al., 2010); rarely has a case had a concentration .50 ng/g (Pichini et al., 2009). In fact, EtS has always been detected in combination with EtG until 2015 when it was first detected by itself in five samples that were EtG-negative (Himes et al., 2015). In these particular cases, the positives were attributed to the low EtS limit of quantification compared with other alcohol biomarkers and/or reduced maternal EtG formation. There is not an established cut-off value for EtS and, in contrast to EtG, the evidence suggests EtS is not a good candidate for an alcohol biomarker to detect PAE. Thus, the data derived from the analysis of human meconium suggests FAEEs are the most promising biomarkers of PAE. Although, it is unclear what combinations of FAEEs should be used and if only one can accurately detect PAE. It is also uncertain at this time whether EtG and EtS could be more useful than FAEEs for the detection of PAE in the last period of pregnancy. Until now, the measurement of FAEEs and/or EtS and EtG in meconium in combination with maternal self-reports have been used as feasible tools for determining the pattern and prevalence of alcohol use during pregnancy and to compare different populations and/or subgroups in the same population (Lange, Shield, Koren, Rehm, & Popova, 2014).

CONCLUSION During pregnancy, alcohol consumption can be monitored by testing meconium. Nonoxidative metabolism of alcohol results in the formation of FAEEs, EtG, and EtS. These minor metabolites of alcohol can be objectively detected and quantified in meconium. Despite that they are widely considered as useful biomarkers to detect PAE, future research should focus

on the development of more sensitive and specific biomarkers of alcohol use to differentiate between drinking patterns. Nowadays, it is crucial that alcohol biomarkers are used in clinical practice. The detection of biomarkers of PAE can play a pivotal role in the early diagnosis of ND-PAE.

MINI-DICTIONARY OF TERMS Meconium First stool of an infant, odorless, with a dark color, and composed of mucopolysaccharides, water, bile, salts, bile acids, epithelial cells, and other lipids. Biomarker A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Cut-off value The value used in diagnostic or screening tests to divide continuous results into categories, typically positive and negative. Ethyl glucuronide (EtG) Minor nonoxidative metabolite resulting from enzymatic conjugation of alcohol with glucuronide. Ethyl sulfate (EtS) Minor nonoxidative metabolite resulting from enzymatic conjugation of alcohol with sulfate. Fatty acid ethyl esters (FAEEs) Minor nonoxidative metabolites resulting from esterification with free fatty acids, triglycerides, lipoproteins, and phospholipids, mainly under the enzymatic action of FAEE synthase. Fetal alcohol spectrum disorders A term used to characterize the scope of damage arising from prenatal exposure to alcohol. It includes commonly accepted diagnoses such as fetal alcohol syndrome (FAS), partial FAS, alcohol-related neurodevelopmental disorder (ARND), and alcohol-related birth defects (ARBD). Neurodevelopmental disorder associated with prenatal alcohol exposure (ND-PAE) A condition that is characterized by a range of developmental disabilities of the newborn following exposure to alcohol in utero. Predictive biomarker A biomarker used to identify individuals who are more likely than similar individuals without the biomarker to experience a favorable or unfavorable effect from exposure to a medical product or an environmental agent. It is associated with increased or decreased likelihood of experiencing a particular outcome of interest when an individual is subjected to the exposure. It can be used to assess the degree of vulnerability to an exposure and can be viewed as an effect modifier.

KEY FACTS About Prenatal Alcohol Use and Meconium • Alcohol is a well-known teratogen. • PAE is strongly associated with a range of neurodevelopmental and behavioral disorders. • There is no safe amount and no safe time to consume alcohol during pregnancy. • Early detection of PAE is essential to identify neonates with increased risk of alcohol-related neurodevelopmental disorder. • The most usual clinical tool to determine PAE is maternal self-reporting and questionnaires;

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60. MECONIUM BIOMARKERS OF PRENATAL ALCOHOL EXPOSURE

although, the detection of alcohol-related analytes in biological matrices is a more objective and reliable method. • Meconium, the earliest stool of a newborn, is a neonatal biological matrix, easily obtainable in clinical practice with minimal discomfort. It provides information about PAE during the second and third trimesters of pregnancy. • Determination of the alcohol-related analytes FAEEs, EtG, and EtS in meconium can potentially provide accurate data on PAE during the last 8 weeks of pregnancy.

SUMMARY POINTS • This chapter focuses on alcohol-related analytes in meconium with a description of maternal/fetal alcohol metabolism. • Alcohol is a well-known teratogen and its use during pregnancy is associated with a range of neurodevelopmental and behavioral disorders in children. • Alcohol is metabolized by oxidative and nonoxidative pathways. Nonoxidative routes result in the enzymatic conjugation of alcohol to endogenous metabolites, producing FAEEs, EtG, and EtS. • Nonoxidative alcohol metabolites persist in tissues and body fluids for a much longer time than alcohol itself and are useful biomarkers of alcohol exposure. • FAEEs, EtG, and EtS in meconium can be useful biomarkers of alcohol use in the second and third trimesters of pregnancy. • Determination of biomarkers of alcohol use in meconium provides an objective and valuable measure for detecting prenatal alcohol use. This method has the potential to provide more accurate data on alcohol use during pregnancy than maternal self-reporting or questionnaires. • Future research should focus on validating alcoholrelated analytes as biomarkers and the translation to clinical practice. • There is a crucial need to continue developing more sensitive and specific biomarkers of PAE.

Acknowledgments Funding sources: Ministry of Economy and Competitiveness, Carlos III Health Institute—FEDER (Spanish Network on Addictive Disorders—RETICS RD16/0017/0003, Juan Rode´s JR16/00020 and Rio Hortega CM17/022 programs and PI17/01962 grant); Ministry of Education [PRX18/00245]; Ministry of Health, Social Services and Equality (grants PNSD 2014I042, 2015I054 and 2016I024), Spain. Partially funded by the Amics de Can Ruti Program, Institut de Recerca Germans Trias i Pujol-IGTP, Badalona, Spain.

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Ornoy, A., & Ergaz, Z. (2010). Alcohol abuse in pregnant women: Effects on the fetus and newborn, mode of action and maternal treatment. International Journal of Environmental Research and Public Health, 7, 364 379. Ostrea, E. M., Hernandez, J. D., Bielawski, D. M., Kan, J. M., Leonardo, G. M., Abela, M. B., . . . Sokol, R. J. (2006). Fatty acid ethyl esters in meconium: Are they biomarkers of fetal alcohol exposure and effect? Alcoholism, Clinical and Experimental Research, 30, 1152 1159. Peterson, J., Kirchner, H. L., Xue, W., Minnes, S., Singer, L. T., & Bearer, C. F. (2008). Fatty acid ethyl esters in meconium are associated with poorer neurodevelopmental outcomes to two years of age. The Journal of Pediatrics, 152, 788 792. Pichini, S., Garcia-Algar, O., Klein, J., & Koren, G. (2009). FAEEs in meconium as biomarkers of maternal drinking habit during pregnancy. Birth Defects Research. Part A, Clinical and Molecular Teratology, 85, 230. Pichini, S., Marchei, E., Vagnarelli, F., Tarani, L., Raimondi, F., Maffucci, R., . . . Morini, L. (2012). Assessment of prenatal exposure to ethanol by meconium analysis: Results of an Italian multicenter study. Alcoholism, Clinical and Experimental Research, 36, 417 424. Pichini, S., Morini, L., Marchei, E., Palmi, I., Rotolo, M. C., Vagnarelli, F., . . . Zuccaro, P. (2009). Ethylglucuronide and ethylsulfate in meconium to assess gestational ethanol exposure: Preliminary results in two Mediterranean cohorts. The Canadian Journal of Clinical Pharmacology, 16, e370 e375. Pichini, S., Morini, L., Pacifici, R., Tuyay, J., Rodrigues, W., Solimini, R., . . . Moore, C. (2014). Development of a new immunoassay for the detection of ethyl glucuronide (EtG) in meconium: Validation with authentic specimens analyzed using LC-MS/MS. Preliminary results. Clinical Chemistry and Laboratory Medicine, 52, 1179 1185. Pichini, S., Pellegrini, M., Gareri, J., Koren, G., Garcia-Algar, O., Vall, O., . . . Marchei, E. (2008). Liquid chromatography-tandem mass spectrometry for fatty acid ethyl esters in meconium: Assessment of prenatal exposure to alcohol in two European cohorts. Journal of Pharmaceutical and Biomedical Analysis, 48, 927 933. Popova, S., Lange, S., Probst, C., Gmel, G., & Rehm, J. (2017). Estimation of national, regional, and global prevalence of alcohol use during pregnancy and fetal alcohol syndrome: A systematic review and meta-analysis. Lancet Global Health, 5, e290 e299. Roberts, S. C., Wilsnack, S. C., Foster, D. G., & Delucchi, K. L. (2014). Alcohol use before and during unwanted pregnancy. Alcoholism, Clinical and Experimental Research, 38, 2844 2852. Roehsig, M., de Paula, D. M., Moura, S., Diniz, E. M., & Yonamine, M. (2010). Determination of eight fatty acid ethyl esters in meconium samples by headspace solid-phase microextraction and gas

chromatography-mass spectrometry. Journal of Separation Science, 33, 2115 2122. Sanvisens, A., Robert, N., Herna´ndez, J. M., Zuluaga, P., Farre´, M., Coroleu, W., . . . Muga, R. (2016). Alcohol consumption during pregnancy: Analysis of two direct metabolites of ethanol in meconium. International Journal of Molecular Sciences, 17, 417. ˚ restedt, K., & Skagerstro¨m, J., Alehagen, S., Ha¨ggstro¨m-Nordin, E., A Nilsen, P. (2013). Prevalence of alcohol use before and during pregnancy and predictors of drinking during pregnancy: A cross sectional study in Sweden. BMC Public Health, 13, 780. Skagerstro´m, J., Chang, G., & Nilsen, P. (2011). Predictors of drinking during pregnancy: A systematic review. Journal of Womens Health (Larchmt), 20, 901 913. SubstanceAbuseandMentalHealthServicesAdministration(SAMHSA). (2013).TheNSDUHReport.Availablefromhttps://www.samhsa.gov/ data/sites/default/files/spot123-pregnancy-alcohol-2013/spot123pregnancy-alcohol-2013.pdf. Ungerer, M., Knezovich, J., & Ramsay, M. (2013). In utero alcohol exposure, epigenetic changes, and their consequences. Alcohol Research: Current Reviews, 35, 37 46. Vaiano, F., Favrett, D., Palumbo, D., Cooper, G., Mactier, H., Busardo`, F. P., . . . Bertol, E. (2016). A novel, simultaneous extraction of FAEE and EtG from meconium and analysis by LC-MS/ MS. Analytical and Bioanalytical Chemistry, 408, 2587 2594. World Health Organization (WHO). (2014a). Global status report on alcohol and health 2014. Available from http://apps.who.int/ iris/bitstream/10665/112736/1/9789240692763_eng.pdf. World Health Organization (WHO). (2014b). Guidelines for the identification and management of substance use and substance use disorders in pregnancy. Available from http://apps.who.int/ iris/bitstream/10665/107130/1/9789241548731_eng.pdf. Wurst, F. M., Dresen, S., Allen, J. P., Wiesbeck, G., Graf, M., & Weinmann, W. (2006). Ethyl sulphate: A direct ethanol metabolite reflecting recent alcohol consumption. Addiction, 101, 204 211. Zelner, I., Hutson, J. R., Kapur, B. M., Feig, D. S., & Koren, G. (2012). False-positive meconium test results for fatty acid ethyl esters secondary to delayed sample collection. Alcoholism, Clinical and Experimental Research, 36, 1497 1506. Zelner, I., & Koren, G. (2013). Pharmacokinetics of ethanol in the maternal-fetal unit. Journal of Population Therapeutics and Clinical Pharmacology, 20, e259 e265. Zelner, I., Shor, S., Lynn, H., Roukema, H., Lum, L., Eisinga, K., & Koren, G. (2012). Neonatal screening for prenatal alcohol exposure: Assessment of voluntary maternal participation in an open meconium screening program. Alcohol (Fayetteville, N.Y.), 46, 269 276.

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C H A P T E R

61 Applications of the Alcohol Use Disorders Identification Test (AUDIT) in Distinct Health Areas Marı´a-Teresa Corte´s-Toma´s and Jose´-Antonio Gime´nez-Costa Department of Basic Psychology, University of Valencia, Valencia, Spain

INTRODUCTION The distinct forms of excessive alcohol consumption (e.g., daily or intermittent high consumption, repeated intoxication episodes, etc.) are considered to be at-risk behavior with potentially adverse health effects. The ability to ensure an adjusted detection of this consumption is a clear need of healthcare professionals. Therefore, precise screening instruments that are rapid and easy to administer, score and interpret are necessary. One of the most frequently used tools for the identification of at-risk alcohol consumption is the Alcohol Use Disorders Identification Test (AUDIT) (Babor, Higgins-Biddle, Saunders, & Monteiro, 2001). The English version of that instrument, and their scoring is shown in Fig. 61.1. Despite the fact that many translations of the AUDIT lack an analysis of validity, reliability, or factorial structure to support them, in general, this questionnaire tends to reveal a high degree of internal consistency over a broad range of settings. In a review of 18 studies published since 2002, Reinert and Allen (2007) found comparable results with a median reliability coefficient of 0.83, ranging between 0.75 and 0.97. More recently, Li, Babor, Hao, and Chen (2011) conducted a systematic review (including 12 studies) of the Chinese translations of the AUDIT, concluding that their reliability ranged from 0.63 to 0.99. Despite the fact that the AUDIT is a relatively brief and rapid measurement instrument, its high internal consistency has permitted the development of abridged versions of the same (deMeneses-Gaya,

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00061-1

Waldo, Regina, & Crippa, 2009): AUDIT-3 (item 3); AUDIT QF (items 1 and 2); AUDIT-C (items 1, 2, and 3); AUDIT 4, (items 1, 2, 3, and 10); FAST, (items 3, 5, 8, and 10); and AUDIT-PC (items 1, 2, 4, 5, and 10). Of all of these, the AUDIT-C stands out; therefore, in this chapter we mainly consider this abridged version as well as the complete questionnaire. Specifically, the main conclusions derived from studies assessing the psychometric properties of both instruments and those derived from distinct systematic reviews (deMeneses-Gaya et al., 2009; Li et al., 2011; Reinert & Allen, 2007) are presented. Thus, we attempt to respond to the relevant issues guiding each of the sections.

IN WHAT CONTEXT ARE THESE INSTRUMENTS WORKED WITH? ARE THERE COUNTRY-RELATED DIFFERENCES? The interest in the proper functioning of this instrument extends both to the healthcare areas, reaching beyond the area of Primary Care for which it was originally designed, as well as other areas of a more social nature (see Table 61.1). Among the first is the hospital context, including specific services such as the traumatology, infectious diseases, urgent care, mental health departments, and addiction resources. Of the nonhealth-care areas, the most frequently seen are studies of the general population and students, mainly university students. There have

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61. APPLICATIONS OF THE ALCOHOL USE DISORDERS IDENTIFICATION TEST (AUDIT) IN DISTINCT HEALTH AREAS

FIGURE 61.1 English version of the AUDIT (Babor et al, 2001) with scoring keys.

been less studies carried out on the working population (e.g., Wade, Varker, O’Donnell, & Forbes, 2012).

It may be concluded that Europe currently continues to focus mainly on the analysis of the AUDIT in primary care, urgent care, and mental health care

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IS THE PROPOSED STRUCTURE OF THE AUDIT VALID?

TABLE 61.1 Most Representative Cut-Off Points of the AUDIT and AUDIT-C Differentiated by the Contexts in Which They Are Assessed and by Level of Alcohol Consumption Primary care Example studies

AUDIT

Hazardous

Men

Hospital context

Urgent care

Mental health

Addiction resources

General University population students

Alvarado, Garmendia, Acun˜a, Santis, and Arteaga (2009), Dewost, Michaud, Arfaoui, Gache, and Lancrenon (2006), Foxcroft, Smith, Thomas, and Howcutt (2015), Gache et al. (2005), Johnson, Lee, Vinson, and Seale (2013), Larsson and Nehlin (2016), Yip et al. (2015)

Bryce et al. (2015), Pradhan et al. (2012), Tsai, Tsai, Chen, and Liu (2005), Vitesnikova, Dinh, Leonard, Boufous, and Conigrave (2014)

Geneste et al. (2012), Neumann et al. (2009), Rodrı´guezMartos and Santamarin˜a (2007)

Boschloo et al. (2010), Cassidy et al. (2008), Dawson, Grant, and Stinson (2005), Nesvag et al. (2010), Levola and Aalto (2015)

Khadjesari et al. (2017), Moussas et al. (2009), Pal et al. (2004)

Aalto et al. (2006), Lundin et al. (2015), Osaki et al. (2014)

Adewuya (2005), Corte´s et al. (2017), Demartini and Carey (2012), Kokotailo et al. (2004), Tuliao et al. (2016)

7/8

8

8

9/10

16

7

5/6

8 Women 6 Dependence Men

13/12

8

5

5/8

16

4 8

5/6

11

11

9

8

6

9

6

9

24 Women 13/12

11

14

9

8 24

AUDIT- Hazardous C

Men

5

4/5

5

5/6

5

5

7

Women 4

4/5

4

4

4

3/4

5

situations, followed by their assessment in social environments. This is in contrast to what we observe in American states, which are characterized by their extension beyond the healthcare setting. Finally, Asian countries place similar value on the different population sectors.

IS THE PROPOSED STRUCTURE OF THE AUDIT VALID? The three conceptual domains of the AUDIT suggest a three-factor structure (Tuliao, Landoy, & McChargue, 2016), although in some cases, despite the fact that the two- and three-factor solutions offer the greatest adjustment to the data, the high correlation between these solutions may justify the selection of the most parsimonious one (Wade et al., 2012). When using the AUDIT as a screening tool in clinical environments in which there is a high prevalence

of dependence on alcohol, the existence of a single factor tends to be supported (Barry, Chaney, Stellefson, & Dodd, 2015; Nayak, Bond, & Greenfield, 2015), whereas in samples having a lower prevalence of consumption-based issues, two factors tend to appear: one on consumption (items 1 3) and another on the problems/consequences derived from the same (items 4 10) (Yee, Adlan, Rashid, Habil, & Kamali, 2015). It appears that the assessed sample directly influences the final results, as stated by Lima et al. (2005). Furthermore, upon comparing structures with one, two, or three factors, the two-factor structures are found to be the best solution (Doyle, Donovan, & Kivlahan, 2007; Lima et al., 2005). Recently, Peng, Wilsnack, Kristjanson, Benson, and Wilsnack (2012) upon analyzing the factorial structures obtained in 15 countries, concluded that in 12 of these, the twofactor model was the most suitable, having an acceptable internal reliability and concurrent validity.

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If the two-factor structure is confirmed it would be useful to establish new cut-off points for each of these, such that a specific score is obtained for at-risk consumption and for the consequences associated with this. But the two factors have not always corresponded to the distribution of the initially marked items. Mathew et al. (2010) excluded item 10 from the second factor and Hildebrand and Noteborn (2015) differentiated between a first factor having items 1, 2, 3, 9, and 10 and a second factor with items 4 8. Furthermore, upon calculating the loads of each item to each factor, Peng et al. (2012) and Nayak et al (2015) questioned the usefulness of items 1, 6, and 9 on revealing insignificant (or even negative) factorial loads, perhaps due to cultural issues. This highlights the need to adjust the items to cultural aspects defining the community being assessed.

WHAT ARE THE MOST FREQUENTLY USED CUT-OFF POINTS? Risk differs based on age, gender, consumption context-pattern, and socio-cultural factors (Babor et al., 2001); therefore, it is considered useful to assess the potential differences in the cut-off points, taking these aspects into consideration. Table 61.1 summarizes the cut-off points of the greatest frequency in psychometric studies conducted in the main contexts, as previously identified. In Primary Care, the most frequently supported cutoff point for hazardous female consumers is 6 while in males it is mainly concentrated at 7/8, with their sensitivities being approximately 80% and their specificities ranging between 80% and 94%. Furthermore, few studies have differentiated between hazardous and more serious consumption levels. Considering the diversity found in the US studies, the homogeneity of the French studies, which recommend dependence scores of 13/12, is noteworthy. This cut-off point is quite different from that which was initially recommended by AUDIT developers to identify alcohol dependence, given that they recommended scores above 19. However, they are very close to those scores (10/13) found by Daeppen, Yersin, Landry, Pe´coud, and Decrey (2000), and Contel, Gual, and Colom (1999). A similar evolution may be seen in the studies focused on determining the best cut-off points for the AUDIT-C. In the first decade of the 21st century, it was usual to establish common cut-off points of 3/4 for the detection of consumption-based risk; however, recent studies coincide in distinguishing between males and females when it comes to setting their best score: 5 for males and 4 for females.

When using the AUDIT in hospital environments, differentiation tends not to be made between genders, with a score of 8 being considered suitable, having appropriate sensitivity and specificity levels. However, when differentiating between genders, the cut-off points differ, with a score of 5 established for men and 4 for women (Pradhan et al., 2012). Furthermore, in specific populations, such as that assessed by Bryce, Spitz, and Ponsford (2015) on cerebral lesions, higher cut-off scores are obtained (11). On the other hand, the best diagnostic cut-off score for dependence was $ 11 in both males and females, much lower than in the original parameter. As in the primary care setting, it may be useful to further explore potential differences based on the gender and subtype of the assessed population. In urgent care units, the AUDIT was preferably used to assess at-risk consumption, commonly using the cut-off points of 8 for men and 5 for women, in those limited cases in which differentiation was made based on gender. Few studies have been carried out to define the cut-off point for dependence, noting similar levels as those used in other contexts. It is unusual that a resource that rewards speed has so few studies considering the usefulness and suitability of the AUDIT-C. In these cases, as in the primary care settings, the following points have been established: 5 points for men and 4 for women. When assessing the suitability of the AUDIT in populations with psychiatric comorbidity, a slight increase in cut-off points may be observed, situated between 9/10 in men and between 5, 8 and sometimes even 10 in women (Cassidy, Schmitz, & Malla, 2008). Boschloo et al. (2010) warned of screening problems in populations suffering from anxiety and depression, establishing the best cut-off point at 9 for dependence, but they were unable to identify a suitable level for alcohol abuse cases. When assessing the suitability of the AUDIT in addiction treatment services, considerable variability was found. Pal, Jena, and Yadav (2004), in the north of India, found very high cut-off scores: 16 for hazardous and 24 for dependence. On the other hand, Moussas et al. (2009), upon assessing the validity of the Greek version in adults who suffered from dependence (according to the DSM-IV) observed that a score of 8 detected 97% of all cases, with high sensitivity and specificity. By contrast, when using the AUDIT-C for screening adults seeking online help for their consumption behavior, Khadjesari et al. (2017) obtained the previously established cut-off points: 5 for men and 4 for women. In the general population, the best assessment of hazardous behavior was found when using values of

VI. BIOMARKERS AND SCREENING

DOES THE AUDIT SURPASS OTHER METHODS OF ALCOHOL CONSUMPTION SCREENING?

7/8 in men and 4 8 in women. Similarly, in the AUDIT-C, greater homogeneity was also found in the cut-off points for men (5) as compared to that of (3/4) for women. Only Aalto, Tuunanen, Sillanaukee, and Seppa (2006), in a study conducted on women, established a higher cut-off point (5). As for dependence, the most common cut-off points are 6 in the AUDIT and 6 for men and 4 for women in the AUDIT-C. But it should be noted that, as Lundin, Hallgren, Balliu, and Forsell (2015) pointed out, even though overall performance as measured with Receiver Operation Characteristic (ROC) curves was similar between these studies, the optimal cut points should be determined empirically within different cultures. Using the traditional cut-off points with university students, Kokotailo et al. (2004) revealed lower values of sensitivity and specificity; therefore, the use of a lower cut-off point (6) is recommended as an indicator of alcohol consumption problems. Adewuya (2005) was more restrictive, proposing that the cut-off point be lowered to 5 for at-risk consumption, 7 or more for harmful use, and 9 for dependence. Recently, some studies have attempted to establish the optimal cut-off points to establish a specific consumption pattern: binge drinking (BD). Corte´s, Gime´nez, Motos, and Sancerni (2017), using a highly precise definition focused on the quantity of alcohol consumed based on gender, blood alcohol level and the frequency of repetition of this behavior over the past 6 months, concluded that both the AUDIT and the AUDIT-C suitably identified BD, but did not permit differentiation between consumer subtypes within this consumption pattern. The best cut-off points for male minors was 4 in the AUDIT-C and for females, 3 in the AUDIT. This section may be concluded by noting the need to carry out, in the near future, an improved identification of the optimal cut-off points to characterize female consumption. On the other hand, studies focusing on defining the best score to identify at-risk behavior are highlighted, but a wide variety of criteria is considered to define this consumption (e.g., high average consumption, high frequent alcohol intake, etc.). This distribution allows us to understand why distinct cut-off points may be identified in similar populations while simultaneously warning of the need to consider the definition of risk that is used so as to identify the most suitable cut-off points in each case.

IS IT POSSIBLE TO IMPROVE THE AUDIT BY CHANGING ANY ELEMENT? In the search for an improved predictive capacity of the AUDIT, as well as the adjustment of the cut-off

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points, changes have been made both in the instrument response/correction scales and in the wording and content of the items. Bischof et al. (2007), in a primary care environment and Nayak et al. (2015), in the general population, opted to use a dichotomous response scale that would reduce the test’s application time. Both concluded that this would not alter the instrument’s reliability or validity. Other studies have adjusted the wording of item 2 to the value of the Standard Drinking Unit (SDU) for their particular countries, wording this item as the number of SDUs consumed (Corte´s et al., 2017), or equivalent grams of alcohol (Kim et al., 2014), or listing examples of drinks that correspond to this quantity (Kolsek, Susic, & Kersnik, 2013). These latter researchers also modified the item response scale, including the option of 0 1 drinks in the first category and 2 drinks in the second category. Finally, Blank, Connor, Gray, and Tustin (2015) proposed a more notable change in the response scale, recording the number of SDUs consumed in 1 day. Adjustments have also been made to the definition of intensive alcohol consumption, corresponding to item 3. Of the proposed changes, the number of drinks consumed has been differentiated based on gender and/or age. For example, in university students, the average for intensive consumption by males is 7 whereas for females it is 5/6 (Blank et al, 2015; Corte´s et al., 2017). In general, all of these modifications have served to improve the instrument’s identification capacity, obtaining fewer false positives for women with lower consumption and fewer false negatives for those with greater consumption (Kolsek et al., 2013). However, Broyles, Gordon, Sereika, Ryan, and Erlen (2011) warn of the need to verify that these changes do not affect the final congruency of the results given that, in their case, they obtained contradictory responses in 14% of their studied sample.

DOES THE AUDIT SURPASS OTHER METHODS OF ALCOHOL CONSUMPTION SCREENING? Of the tests that have been compared with the AUDIT, certain traditional biomarkers have been found, such as glutamyl transferase, alanine aminotransferase, aspartate aminotransferase, mean corpuscular volume, and triglycerides, etc., revealing a high correlation between some of these markers and the scores obtained with both the AUDIT and the AUDITC (Sung, Lee, & Song, 2011). However, Neumann et al. (2009) declared that biomarkers have a lower

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61. APPLICATIONS OF THE ALCOHOL USE DISORDERS IDENTIFICATION TEST (AUDIT) IN DISTINCT HEALTH AREAS

sensitivity than the AUDIT and the AUDIT-C at detecting dangerous or abusive consumption. At times, the collective use of both methods (AUDIT 1 biomarkers) has been proposed in order to improve the positive predictive values and the screening, particularly in cases such as the detection of risk for abstinence symptoms (Dolman & Hawkes, 2005). When comparing the AUDIT with other screening tests, unequal results have been observed. For example, when contrasting it with the Michigan Alcoholism Screening Test (MAST), a moderate correlation has been observed between the two (Fonte & Mota-Cardoso, 2013), although Gache et al. (2005) noted that the MAST is less effective in detecting alcohol abuse and dependence. Furthermore, the AUDIT has the advantage of being more reduced and permitting scores on a variety of other dimensions (quantity/frequency, dependence, problems/adverse effects), offering a more detailed consumer description. The AUDIT has also been compared to the RAPS (Cherpitel, Ye, Moskalewicz, & Swiatkiewicz, 2005), obtaining similar sensitivity rates for both instruments (with poorer specificity for the AUDIT in males). Geneste et al. (2012) highlighted a greater reliability and performance of the AUDIT in detecting both abuse and alcohol dependence. It has been most frequently compared to the CAGE instrument. Here, despite the fact that some studies (Yee et al., 2015) suggest significant positive correlations between both tests (not the case with the AUDIT-C, perhaps because they measure distinct aspects of alcohol consumption: consequences vs high consumption), most of the studies reveal that the CAGE has a lower sensitivity (Cherpitel et al., 2005), lower reliability (Cremonte, Ledesma, Cherpitel, & Borges, 2010) and poorer performance in the detection of abuse and/or dependence (Geneste et al., 2012). Despite these results, the CAGE continues to be widely used due to its brevity and dichotomous response format.

MINI-DICTIONARY OF TERMS Dependence The most serious form of drinking problems. Describes a strong, often uncontrollable, desire to drink, and the presence of high tolerance and alcohol withdrawal syndrome. Reliability The degree to which an assessment tool produces stable and consistent results. Validity the extent to which the conclusions drawn from a statistical test are accurate and reliable. Binge drinking The consumption of an excessive amount of alcohol in a short period of time.

Standard Drinking Unit (SDU) A unit of measurement of alcohol consumption that contains the same amount of alcohol regardless of container size or alcohol type.

KEY FACTS Audit • The AUDIT includes 10 items grouped together in 3 domains: quantity/frequency of alcohol consumption (items 1 3), questions related to dependence (items 4 6), and potential problems resulting from consumption (items 7 10). • The AUDIT has been translated and adapted to various languages: for example, Chinese, German, Spanish, French, Russian, Norwegian, Polish, Portuguese, Japanese, Finnish, etc. • The AUDIT assumes an SDU value of 10 grams of alcohol and at-risk consumption of over 20 grams of alcohol per day, 5 days per week. • Several studies have proposed suitable cut-off points for hazardous drinking, often $ 8 for AUDIT and $ 3 or $ 4 for AUDIT-C, although they tend to propose different points based on gender, the context in which they are applied, and behavior patterns. • On a severity continuum, the AUDIT differentiates between four risk levels, linking them to distinct intervention types: lower risk drinking (0 7 points), hazardous use (8 15 points), harmful use (16 19 points), and possible dependence (20 40 points).

SUMMARY POINTS • This chapter focuses on the current use of the AUDIT and AUDIT-C in a variety of settings. • Countries have distinct interests in adapting the AUDIT to specific contexts. • The most frequently repeated factorial structure recognizes two factors; one related to consumption and the other related to problems/consequences. • It is recommended that the setting as well as the user’s gender and level of consumption be considered when selecting the most precise cut-off point. • Modification of the wording of the items and even their exclusion, considering specific consumption patterns, cultural and biological characteristics, may permit improved reliability and validity of the AUDIT. • The AUDIT is found to be superior to other screening instruments, including the traditional biomarkers.

VI. BIOMARKERS AND SCREENING

REFERENCES

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Larsson, K., & Nehlin, C. (2016). Screening accuracy of brief alcohol screening instruments in a general hospital setting. Scandinavian Journal of Public Health, 44, 599 603. Levola, J., & Aalto, M. (2015). Screening for at-risk drinking in a population reporting symptoms of depression: A validation of the AUDIT, AUDIT-C, and AUDIT-3. Alcoholism-Clinical and Experimental Research, 39, 1186 1192. Li, Q., Babor, T. F., Hao, W., & Chen, X. G. (2011). The Chinese translations of Alcohol Use Disorders Identification Test (AUDIT) in China: A systematic review. Alcohol and Alcoholism, 46, 416 423. Lima, C. T., Freire, A. C., Silva, A. P., Teixeira, R. M., Farrel, M., & Farrel, M. (2005). Concurrent and construct validity of the Audit in urban Brazilian sample. Alcohol and Alcoholism, 40, 584 589. Lundin, A., Hallgren, M., Balliu, N., & Forsell, Y. (2015). The use of Alcohol Use Disorders IdentificationTest (AUDIT) in detecting alcohol use disorder and risk drinking in the general population: Validation of AUDIT using schedules for clinical assessment in neuropsychiatry. Alcoholism: Clinical and Experimental Research, 39, 158 165. Mathew, T., Shields, A., Yanov, S., Golubchikova, V., Strelis, A., Yanova, G., . . . Greenfield, S. F. (2010). Performance of the alcohol use disorders identification test among tuberculosis patients in Russia. Substance Use & Misuse, 45, 598 612. Moussas, G., Dadouti, G., Douzenis, A., Poulis, E., Tzelembis, A., Bratis, D., . . . Lykouras, L. (2009). The alcohol use disorders identification test (AUDIT): Reliability and validity of the Greek version. Annals of General Psychiatry, 8, 1 5. Nayak, M. B., Bond, J. C., & Greenfield, T. K. (2015). Evaluating shortened versions of the AUDIT as screeners for alcohol use problems in a general population study. Substance Use & Misuse, 50, 1579 1589. Nesvag, R., Lange, E. H., Faerden, A., Barrett, E. A., Emilsson, B., Ringen, P. A., . . . Agartz, I. (2010). The use of screening instruments for detecting alcohol and other drug use disorders in firstepisode psychosis. Psychiatry Research, 177, 228 234. Neumann, T., Gentilello, L. M., Neuner, B., Weiß-Gerlach, E., Schu¨rmann, H., Schro¨der, T., . . . Spies, C. D. (2009). Screening trauma patients with the Alcohol Use Disorders Identification Test and biomarkers of alcohol use. Alcoholism: Clinical and Experimental Research, 33, 970 976. Osaki, Y., Ino, A., Matsushita, S., Higuchi, S., Kondo, Y., & Kinjo, A. (2014). Reliability and validity of the alcohol use disorders identification test—consumption in screening for adults with alcohol use disorders and risky drinking in Japan. Asian Pacific Journal of Cancer Prevention, 15, 6571 6574. Pal, H. R., Jena, R., & Yadav, D. (2004). Validation of the Alcohol Use Disorders Identification Test (AUDIT) in urban community outreach and de-addiction center samples in north India. Journal of Studies on Alcohol, 65, 794 800.

Peng, C. Z., Wilsnack, R. W., Kristjanson, A. F., Benson, P., & Wilsnack, S. C. (2012). Gender differences in the factor structure of the Alcohol Use Disorders Identification Test in multinational general population surveys. Drug and Alcohol Dependence, 124, 50 56. Pradhan, B., Chappuis, F., Baral, D., Karki, P., Rijal, S., Hadengue, A., & Gache, P. (2012). The alcohol use disorders identification test (AUDIT): Validation of a Nepali version for the detection of alcohol use disorders and hazardous drinking in medical settings. Substance Abuse Treatment Prevention and Policy, 7, 42. Reinert, D. F., & Allen, J. P. (2007). The Alcohol Use Disorders Identification Test: An update of research findings. Alcoholism: Clinical and Experimental Research, 31, 185 199. Rodrı´guez-Martos, A., & Santamarin˜a, E. (2007). Does the short form of the Alcohol Use Disorders Identification Test (AUDIT-C) work at a trauma emergency department? Substance Use & Misuse, 42, 923 932. Sung, J., Lee, K., & Song, Y. M. (2011). Heritabilities of Alcohol Use Disorders Identification Test (AUDIT) scores and alcohol biomarkers in Koreans: The KoGES (Korean Genome Epi Study) and Healthy Twin Study. Drug and Alcohol Dependence, 113, 104 109. Tsai, M. C., Tsai, Y. F., Chen, C. Y., & Liu, C. Y. (2005). Alcohol Use Disorders IdentificationTest (AUDIT): Establishment of cut-off scores in a hospitalized Chinese population. Alcoholism: Clinical and Experimental Research, 29, 53 57. Tuliao, A. P., Landoy, B. V. N., & McChargue, D. E. (2016). Factor structure and invariance test of the alcohol use disorder identification test (AUDIT): Comparison and further validation in a U.S. and Philippines college student sample. Journal of Ethnicity in Substance Abuse, 15, 127 143. Vitesnikova, J., Dinh, M., Leonard, E., Boufous, S., & Conigrave, K. (2014). Use of AUDIT-C as a tool to identify hazardous alcohol consumption in admitted trauma patients. Injury-International Journal of the Care of the Injured, 45, 1440 1444. Wade, D., Varker, T., O’Donnell, M., & Forbes, D. (2012). Examination of the latent factor structure of the Alcohol Use Disorders Identification Test in two independent trauma patient groups using confirmatory factor analysis. Journal of Substance Abuse Treatment, 43, 123 128. Yee, A., Adlan, A. S. A., Rashid, R. R., Habil, H., & Kamali, K. (2015). Validation of the alcohol use disorders identification test (AUDIT)—Bahasa Malaysia version among a group of alcohol users. Journal of Substance Use, 20, 229 233. Yip, B. H. K., Chung, R. Y., Chung, V. C. H., Kim, J., Chan, I. W. T., Wong, M. C. S., . . . Griffiths, S. M. (2015). Is Alcohol Use Disorder Identification Test (AUDIT) or its shorter versions more useful to identify risky drinkers in a Chinese population? A diagnostic study. PLoS One, 10, e0117721.

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62 Craving Measurement and Application of the Alcohol Craving Experience Questionnaire 1

Jason M. Coates1,2, Gerald F.X. Feeney1,3, Matthew J. Gullo1,3, David J. Kavanagh4, Ross McD. Young3,5, Jon May6, Jackie Andrade6 and Jason P. Connor1,3,7

Centre for Youth Substance Abuse Research, The University of Queensland, Brisbane, Australia 2School of Psychology, The University of Queensland, Brisbane, Australia 3Alcohol and Drug Assessment Unit, Department of Medicine, Princess Alexandra Hospital, Brisbane, Australia 4Centre for Children’s Health Research, Institute of Health & Biomedical Innovation and School of Psychology & Counselling, Queensland University of Technology, Brisbane, Australia 5Faculty of Health, Queensland University of Technology, Brisbane, Australia 6School of Psychology, Cognition Institute, Plymouth University, Plymouth, United Kingdom 7School of Medicine, The University of Queensland, Brisbane, Australia

LIST OF ABBREVIATIONS ACE ACE-S ACE-F APA AUD CBT CEQ DSM-5 EI Theory EMA ICD-10 MACE

Gasbarrini, 2005; Connor, Haber, & Hall, 2016; HaassKoffler, Leggio, & Kenna, 2014). While a number of definitions for substance craving exist, the American Psychiatric Association (APA) defines alcohol craving as “a strong desire to drink that makes it difficult to think of anything else” (American Psychiatric Association, 2013). A craving instrument consistent with this definition can inform AUD diagnosis, prognosis, treatment, and outcome evaluation (Tiffany & Wray, 2012).

Alcohol Craving Experience questionnaire ACE Strength Scale ACE-Frequency Scale American Psychiatric Association alcohol use disorder cognitive behavioral therapy Craving Experience Questionnaire Diagnostic and Statistical Manual of Mental Disorders—Fifth Edition Elaborated Intrusion theory Ecological Momentary Assessment International Statistical Classification of Diseases and Related Health Problems—10th Edition Mini Alcohol Craving Experience questionnaire

CRAVING MEASUREMENT

DEFINITION OF CRAVING Craving, or the strong desire or urge to use a substance, is a diagnostic marker of alcohol use disorder (AUD) in the DSM-5 (American Psychiatric Association, 2013) and ICD-10 (World Health Organization, 1992). Craving has long been a target of cognitive-behavioral interventions for substance use and, more recently, pharmacotherapy (Addolorato, Leggio, Abenavoli, &

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00062-3

Despite being a prominent topic in addiction research and treatment over the past 50 years, craving measurement remains controversial. A lack of consensus on the definition of craving has contributed to the development of a broad range of craving instruments. This chapter restricts discussion to self-report craving instruments, as nonverbal techniques are generally only used in research environments. Key considerations underlying measure selection include the measure’s definition and theoretical foundation,

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© 2019 Elsevier Inc. All rights reserved.

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temporal reference, psychometric integrity, administration demand, and clinical utility. Here, we outline the key theoretical and psychometric properties of the Alcohol Craving Experience (ACE) questionnaire (Statham et al., 2011). The ACE comprises two 11-item scales assessing the strength (ACE-S) and frequency (ACE-F) of past week craving-related cognitions (Statham et al., 2011). Response options for all items lie on an 11-point visual analogue scale (anchored 0 5 Not at all; 10 5 Extremely/Constantly). The items of each scale are semantically consistent, and load onto three factors consistent with EI Theory (Kavanagh, Andrade, & May, 2005). Items 1 3 of each scale assess the respondent’s experience of feeling an urge or need to use a substance. Items 4 8 assess the presence of craving related imagery across four sensory modalities (visual, olfactory, gustatory, and oral tactile) and a general sense of how their body would feel if they had a drink (Table 62.1). The final three items 9 11 assess the intrusiveness of craving thoughts and the degree to which they interfere with other cognitive activity.

Definition and Theoretical Foundation Accurate interpretation of a craving measure is reliant upon understanding the developers’ theoretical approach to craving. Craving measures often include constructs that are correlated, yet theoretically distinct from common definitions (Kavanagh, et al., 2013). Expectations of alcohol effects (outcome expectancies;

Anton, Moak, & Latham, 1995; Raabe, Gru¨sser, Wessa, Podschus, & Flor, 2005), drinking refusal self-efficacy (Flannery, Volpicelli, & Pettinati, 1999), intention to use (Anton et al., 1995; Raabe et al., 2005), and perceived control of drinking are commonly included within popular craving scales. These are examples of correlated constructs, many of which have independently validated measures. Such multidimensional “craving” measures require careful interpretation to parse variance attributable to craving from alternative constructs. This is most important in clinical settings where these constructs have unique implications for diagnosis and intervention. The ACE was developed from EI Theory (Kavanagh et al. 2005) with the explicit goal of measuring only the cognitive aspects of alcohol craving. EI Theory is a general theory of desire experiences, defining them as “affectively laden cognitive events, where an object or activity and associated pleasure or relief are in focal attention” (May, Kavanagh, & Andrade, 2015). EI Theory may be used as an extension of neurobiological models, where addictive substances are proposed to sensitize physiological mechanisms responsible for appetitive behaviors (Robinson & Berridge, 1993). In the context of desires for substances, EI Theory proposes that physiological, environmental, and emotional cues can provoke drug-related representations in memory through unconscious associative processes. Seemingly spontaneous thoughts about the pleasure or relief associated with substance use are then more likely to intrude into conscious awareness. This is initially pleasurable, but also elicits an awareness of

TABLE 62.1

Composition of the Alcohol Craving Experience Questionnaire (ACE)

Factor

Strength scale (ACE-S)

Frequency scale (ACE-F)

Intensity

At that time. . .

Over the last week how often. . .

1

. . .how much did you want it?

. . ./did you want it?

2

. . .how much did you need it?

. . .did you need it?

3

. . .how strong was the urge to have it?

. . .did you have a strong urge for it?

Imagery

At that time, how vividly to/did you. . .

Over the last week how often did you. . .

4

. . .picture it?

. . .picture it?

5

. . .imagine its taste?

. . .imagine its taste?

6

. . .imagine its smell?

. . .imagine its smell?

7

. . .imagine what it would feel like in your mouth and throat?

. . .imagine what it would feel like in your mouth and throat?

8

. . .imagine how your body would feel?

. . .imagine how your body would feel?

Intrusiveness

At that time. . .

Over the last week how often. . .

9

. . .how hard were you trying not to think about it?

. . .were you trying not to think about it?

10

. . .how intrusive were the thoughts?

. . .were the thoughts intrusive?

11

. . .how hard was it to think about anything else?

. . .was it hard to think about anything else?

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FIGURE 62.1 The Elaborated Intrusion theory of desire (Kavanagh et al., 2005).

physiological deficit. These affective responses prompt controlled processing, involving elaboration in working memory, which further intensifies the affective reactions. Importantly, intense craving involves multisensory substance-related imagery, which is closely linked to emotion (Kavanagh, May, & Andrade, 2009). Anticipated delays in obtaining the desired substance make the associated sensory imagery highly aversive, as physiological deficits progressively become more salient. Craving subsequently intensifies unless the target substance is acquired or attention is redirected. Fig. 62.1 illustrates these theoretical processes. The ACE reflects EI Theory by assessing the subjective experience of desire for alcohol, the presence and nature of alcohol-related imagery, and the perceived intrusiveness of alcoholrelated cognitions.

Temporal Reference Given the temporal variability in craving, the time frame respondents are asked to recall is an important

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consideration in measurement selection. A common limitation among craving scales is retrospective consideration of craving experiences. Scales often require respondents to create averages or typical summaries of past craving. This introduces memory bias complicated by fluctuations in pattern, intensity, and frequency of craving. Alternatively, “real-time” assessments of craving ask respondents to report on their experience in the present moment. Such methods are popular in laboratory studies because of their high temporal control. However, real-time measures may not be suitable within clinical settings, where the time and context are not representative of their typical experience. Real-time measures may also be subject to “reactivity,” whereby asking the respondent to reflect on an experience alters the experience in question (Perlmuter, Noblin, & Hakami, 1983). For example, asking respondents to rate their current level of craving for alcohol, may draw attention to, and increase their current levels of craving. As an alternative to retrospective averaging, the ACE-S focuses on recalling when craving was most intense during the past week. This represents a discrete, salient experience. This is proposed to reduce errors attributable to difficulties averaging dynamic craving experiences, and help identify periods of high lapse risk (Statham et al., 2011). The ACE-F asks patients to rate the perceived frequency of desirerelated cognitions over the past week. Assessment of peak strength and frequency of craving provides a detailed profile of the respondent’s craving experiences. Further research is required to examine whether this method reduces the impact of memory bias as intended.

Psychometric Integrity The integrity of addiction research and treatment is reliant on the validity and reliability of assessment measures. Psychometric properties of the ACE have been assessed within several studies (Coates et al., 2017; May et al., 2014; Statham et al., 2011). As noted, craving measures are required to be interpreted through their proposed definitions and theoretical models to maintain construct validity. The theoretical foundation of the ACE provides a framework by which construct validity may be assessed. The proposed three-factor structure has been supported by exploratory and confirmatory factor analysis in alcohol dependent samples (Coates et al., 2017; May et al., 2014; Statham et al., 2011). A substance nonspecific version of the ACE—the Craving Experience Questionnaire (CEQ)—has also been tested and structurally validated for cigarette, food, and chocolate

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62. CRAVING MEASUREMENT AND APPLICATION OF THE ALCOHOL CRAVING EXPERIENCE QUESTIONNAIRE

craving (May et al., 2014). This provides strong evidence that the ACE measures the three intended factors drawn from EI Theory. Validity may be further assessed by demonstrating relationships with an alternative measure of the same construct (concurrent validity), or between predicted correlates (convergent and discriminant validity). The obsessions subscale of the Obsessive Compulsive Drinking Scale is currently one of the most theoretically valid and commonly used measures of alcohol craving (Kavanagh et al., 2013). The ACE Frequency (ACE-F) and Strength (ACE-S) forms correlate 0.46 0.60 with the OCDS-O (Coates et al., 2017; Statham et al., 2011) indicating that they share sufficient variance as to reflect similar underlying constructs. Importantly, they diverge sufficiently to suggest the ACE examines unique variance in craving. Perhaps the most heavily weighted psychometric property considered in craving assessment is the capacity to predict substance use and treatment outcome (predictive validity). A one standard deviation increase in the ACE-F and ACE-S increased the odds of lapse or discontinuation of CBT for AUD by 69% and 59%, respectively, compared to 10% for the OCDSO (Coates et al., 2017). These findings indicate that the ACE has prognostic utility, and the unique variance captured relative to the OCDS-O is important for the assessment of alcohol lapse risk. The ability of a measure to produce consistent results over repeated assessments (test retest reliability) is among the most important metrics to consider in scale evaluation. As craving is a highly dynamic construct and variant over time and context, demonstration of test retest reliability is less applicable, except where all the relevant conditions can be held constant (Shiffman,

Paty, Gnys, Kassel, & Hickcox, 1996). Test retest reliability of all ACE scales is acceptable, with correlation coefficients greater than 0.73 following a 7-day interval between assessments (Coates et al., 2017). As the respondents were seeking treatment for AUD and attempting abstinence during this period, the true stability of the ACE scales is likely underestimated. The most commonly reported index of reliability is the degree to which the items of a measure correlate (internal consistency), and is typically measured by Cronbach’s alpha (Cronbach, 1951). The ACE-F and ACE-S have consistently demonstrated good internal reliability, with Cronbach’s alpha exceeding the recommended 0.90 in all studies (Coates et al., 2017; May et al., 2014; Statham et al., 2011).

Administration Demand Administration burden of assessment instruments is a key consideration with research and clinical practice. A national survey of 152 substance abuse treatment agencies in the United States found 96% of services report craving is a useful marker of dependence, 99% think it is useful to assess craving in treatment planning, and 97% report it as a useful predictor of lapse (Fig. 62.2; Pavlick, Hoffmann, & Rosenberg, 2009). However, only 5% assess craving with standardized self-report craving measures, opting instead for singleitem or nonstandard open-ended questions (Pavlick et al., 2009). The reluctance of addiction services to apply standardized measures may reflect the perceived administration burden in busy clinical settings. The full OCDS, for example, has 14 questions, each with five alternative response sentences that the

FIGURE 62.2 While most practitioners recognize the value of assessing craving, there is little consistency in measurement approach and very few use a published scale. Source: Data from Pavlick, M., Hoffmann, E., & Rosenberg, H. (2009). A nationwide survey of American alcohol and drug craving assessment and treatment practices. Addiction Research & Theory, 17, 591 600.

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CRAVING MEASUREMENT

respondent must read and select from, and runs to three A4 pages in most formats. Although the two 11-item ACE scales only require selection of a continuous value, administration of all 22 items can be considered too time-consuming for routine clinical use. For such purposes, a brief, five-item Mini Alcohol Craving Experience Questionnaire (MACE, Coates et al., 2017) has been developed from the ACE-F with at least one item retained from each factor. Frequency of craving was selected as the focus, as repeated temptations were expected to offer a particular challenge to sustained behavioral control. Psychometric integrity was preserved within the MACE, with key strengths relative to other brief craving measures including excellent construct validity, predictive validity, and acceptable test retest reliability.

Clinical Utility Effective craving measures may inform diagnosis when the theory and content of the measure are consistent with DSM-5 or ICD-10 definitions of craving. Prognosis and lapse risk may be informed by the predictive validity of a measure. When the underlying theory of the measure is consistent with an intervention, craving measures can also assist selection of treatment strategies. Additionally, craving measures may be implemented to monitor craving as a marker of treatment response (Tiffany, Friedman, Greenfield, Hasin, & Jackson, 2011). The DSM-5 definition of craving, “a strong desire to drink that makes it difficult to think of anything else and that often results in the onset of drinking,” (American Psychiatric Association, 2013) is highly consistent with the items and underlying theory of the ACE, supporting its suitability as a diagnostic aid. All scales of the ACE have further demonstrated predictive validity, providing addiction professionals with prognostic information regarding risk of treatment lapse or dropout. By carefully interpreting each of its scales, the ACE can guide treatment planning. For example, it may be that patients with low-craving frequency, but high-peak strength, benefit more from a close analysis of triggers for that specific, particularly risky situation. Alternatively, patients with high frequency, but low-peak strength may respond well to mindfulness and acceptance strategies, since the primary challenge that they face is the need to maintain resistance to low-level temptations. Insight may be further enriched by consideration of the subfactors reflecting core elements of elaborated intrusion processes. This information may enrich mindfulness and acceptance-based therapies, which promote awareness of key cognitive and sensory experiences. Such

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approaches are consistent with EI Theory, as the promotion of cognitive and emotional ‘defusion’ from craving-related cognitions is proposed to impede previously automated elaboration (May et al., 2015). In addition to being consistent with current craving treatment approaches, the theoretical foundation of the ACE facilitates identification of novel treatment targets. For example, as craving-related cognitions occupy limited working memory capacity, craving may be reduced by cognitive tasks competing for the same working memory processes. As cognitive load is highest within the substance’s most prominent sensory modality, imagery-based tasks targeting this modality reduce craving strength (Kavanagh et al., 2009). For example, imagery of visual or olfactory stimuli has been demonstrated to reduce craving for cigarettes, coffee, and food more than verbal or auditory tasks (Kemps & Tiggemann, 2007; May, Andrade, Panabokke, & Kavanagh, 2010; Versland & Rosenberg, 2007). Recent research has directly employed EI Theory in the development of new craving management techniques (Kemps & Tiggemann, 2013; Kna¨uper, Pillay, Lacaille, McCollam, & Kelso, 2011; Rodrı´guez-Martı´n, Go´mez-Quintana, Dı´az-Martı´nez, & Molerio-Pe´rez, 2013; Skorka-Brown, Andrade, & May, 2014). While concurrent tasks may provide brief respite from especially intense craving, imagery about proximal benefits of control may have the advantage of not only competing for working memory resources with craving, but may also enhance motivation for control (Kavanagh, Andrade, May, & Connor, 2014). Application of this contention in other behavioral domains provides support for its utility (Andrade, Khalil, Dickson, May, & Kavanagh, 2016). The availability of information on the patient’s strongest recent experience of craving, as well as the perceived frequency of past week craving, affords useful clinical information to addiction practitioners. Clinical value of the ACE-S is derived from the identification of patients’ strongest bouts of craving. Exploring these salient episodes can facilitate clear identification of triggers, evaluation of coping strategies, and planning for future scenarios. Furthermore, assessing the perceived frequency of craving symptoms provides a useful indicator of prevalence. The availability of the brief MACE maximizes the practicability of undertaking this assessment on repeated occasions in clinical practice. The National Institute on Drug Abuse recommends craving as an outcome measure for substance-use disorders clinical trials (Tiffany et al., 2011). Given the ACE’s consistency with diagnostic definitions of craving and its multidimensional assessment across both frequency and peak strength of craving, it is a comprehensive measure suitable for both clinical and research environments.

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Limitations and Practical Considerations There are several limitations to be considered prior to administration. First, the ACE does not measure the duration of craving experiences, although it is not currently clear whether doing so would yield useful prognostic information. Another potential limitation is the retrospective time period. The ACE asks patients to reflect on the past week, which would be problematic in settings requiring more frequent craving assessment. However, the generalization of the ACE-F, the CEQ-F has been applied across a wide range of time periods, down to a few minutes (May et al., 2014). A final consideration in the selection of any craving measure, is that scores are carefully interpreted within a clear definition and theoretical framework. Interpretation of the ACE through the lens of EI Theory is likely to improve understanding of research outcomes and individual experiences.

KEY FACTS Craving • There is no consensus on a definition of craving. • Common definitions of craving reflect a cognitiveaffective experience of a strong desire that imposes high attentional demand. • Craving is widely perceived as a dynamic state characterized by intensity, frequency, and duration. • Craving is a core feature of substance addiction, arising from altered neurophysiological processes. • Craving is a robust marker of lapse and relapse risk among patients with AUD. • Craving is included within the ICD-10 and DSM-5 as a diagnostic marker of Substance Use Disorders. • Craving is a common treatment target for both psychological and pharmacological interventions for Substance Use Disorders.

Alcohol Craving Experience questionnaire

CONCLUSIONS Craving has long been a focal point of addiction research and treatment. Craving assessment remains a contentious and continually evolving field. Numerous self-report measures have been developed, though there is inconsistency in the definitions and theory used. Measures also differ in psychometric integrity, administration demand, temporal focus, and clinical utility. There is currently no measure suitable across purposes and context, so selection of an appropriate craving measure requires careful consideration. The ACE’s consistency with diagnostic definitions of craving, strong theoretical foundation, and assessment of peak strength and frequency of craving, deem this measure suitable for repeated use in clinical and research environments.

MINI-DICTIONARY OF TERMS ACE The ACE is a 22-item self-report craving measure assessing the strength and frequency of craving-related cognitions. MACE A brief, five-item version of the ACE, assessing the past week frequency of craving related cognitions. Craving The cognitive-affective experience of strong desire for a substance characterized by high attentional demand. Validity The accuracy in which a measure represents the intended theoretical construct. Reliability The ability of a measure to produce consistent results. Ecological Momentary Assessment A protocol involving spontaneous assessment of the respondent’s current state in naturalistic settings. Elaborated Intrusion (EI) theory A cognitive theory of desire outlining the determinants of desire-related cognitions, which distinguishes automatic and controlled processes and emphasizes the role of embodied cognitions, including imagery.

• The ACE is a self-report measure comprised of two 11-item scales measuring the peak strength of a single instance of craving (ACE-S), and the perceived frequency of past week craving experiences (ACE-F). • It assesses the strength and frequency of urges, imagery, and intrusive cognitions related to craving. • The ACE reflects key aspects of the Elaborated Intrusion (EI) theory of desire. • Response options are on an 11-point visual analogue scale anchored 0 (Not at all) to 10 (Extremely/Constantly). • It is validated within treatment-seeking, alcoholdependent populations. • A five-item Mini ACE (MACE) has been validated, and is suitable for use in time limited settings. It has similar psychometric properties to the full scale. • A generalization of the ACE—the Craving Experience Questionnaire (CEQ)—is applicable to a range of desired targets.

SUMMARY POINTS • This chapter explores important considerations in craving assessment, with a focus on the ACE questionnaire. • Key considerations in craving measure selection include: definition and theoretical foundation of craving, psychometric integrity, administration demands, temporal reference, and clinical utility. • The theoretical structure of the ACE reflects elements of the Elaborated Intrusion theory of desire.

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REFERENCES

• The ACE has demonstrated strong validity and reliability. • A brief, five-item, version of the ACE has been validated for time-limited settings. • Self-report craving measures differ greatly in the reference period respondents are required to recall. Consideration should be given to the reference period to ensure it is consistent with treatment goals. • The ACE has application in clinical settings, informing prognosis, case-formulation, treatment, and outcome evaluation.

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C H A P T E R

63 Negative Emotions and Alcohol Use Disorder Treatment Matt G. Kushner and Justin J. Anker Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States

LIST OF ABBREVIATIONS AUD CBT CRF DSM DTC HPA NESARC NIAAA NK1 PMRT RCT RDoC RPT TRH

in mind, we overview each model and conclude with summary points that highlight cross-disciplinary hypotheses and conclusions.

alcohol use disorder cognitive-behavioral therapy corticotropin-releasing factor Diagnostic and Statistical Manual of Mental Disorders drinking to cope hypothalamic pituitary adrenal National Epidemiologic Survey on Alcohol and Related Conditions National Institute on Alcohol Abuse and Alcoholism neurokinin 1 Progressive Muscle Relaxation Training randomized controlled trial research domain criteria relapse prevention therapy tension reduction hypothesis

The Psychological Tension Reduction Hypothesis Model

INTRODUCTION The disproportionate experience of strong negative emotions by those who abuse alcohol had been observed long before the modern scientific era (Babor, 1996), as had alcohol’s putative anxiolytic effect (cf., Kushner, Sher, & Beitman, 1990). Unlike many prescientific observations, the importance of negative emotions in addiction remains central to modern scientific and clinical models: Psychology—the “Tension Reduction Hypothesis” (TRH); Psychiatry—“Comorbidity”; and Neuroscience—“Opponent Process.” Unfortunately, the minimal interactions among researchers committed to these various models have limited potentially beneficial translational opportunities and potentiated unnecessary redundancies in our collective scientific effort. With this

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00063-5

The modern TRH was inspired by Freud’s view of chronic drinking as an externalized defense mechanism in response to intrapsychic conflicts (neuroses). In the hands of experimental psychologists, the TRH model specified two propositions linked through operant negative reinforcement: (1) alcohol reduces “tension” (operationalized as physical and behavioral responses to noxious stimuli and conflict situations) and (2) drinking is promoted by the reduction in tension it provides. Reviews of copious laboratory tests of alcohol’s tensionreducing properties (primarily with rodents) showed negative, equivocal, or contradictory findings (Cappell & Herman, 1972). Reviews of the animal and human experimental tests of increased alcohol intake in response to tension states have similarly concluded that the evidence is highly inconsistent (Becker, Lopez, & Doremus-Fitzwater, 2011; Pohorecky, 1990). A likely reason the TRH was not simply abandoned in the face of decades of equivocal experimental evidence is that its central idea conforms broadly to individuals’ personal experience. For example, Dvorak et al. (2014) found that individuals report increased drinking in response to negative emotions and field studies show temporal contiguity between stressful life events and increased alcohol use (Rafnsson, Jonsson, & Windle, 2006).

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Based on the finding that elevated negative affect was the single most common proximal cause (or “trigger”) given by individuals who relapse (Marlatt, 1978), Donovan and Marlatt (1980) reformulated the operant TRH within a social learning framework. According to this view, drinking to relieve negative emotions is expected to occur when a person: (1) believes alcohol will be effective for this purpose and (2) has low confidence (self-efficacy) that the negative affect can be managed in the absence of alcohol use. Marlatt and Gordon (1985) translated this reformulated TRH to develop Relapse Prevention Therapy (RPT) (cf., Larimer & Palmer, 1999). Just as a fire drill is meant to prepare individuals to engage in effective action in a fire emergency, RPT is meant to prepare patients to engage in effective action in high relapse-risk situations; commonly negative emotional states. Wellcontrolled trials of RPT have been reviewed (Carroll, 1996; Irvin, Bowers, Dunn, & Wang, 1999) showing that RPT reduces relapse rates, especially for patients with the most severe alcohol use disorder (AUD) impairment and for those with co-occurring psychopathology (comorbidity).

The Psychiatric Comorbidity Model Adoption of a Neo-Kraepelinian medical model of psychiatry in the DSM III (1980) paved the way for the concept of comorbidity to become the dominant psychiatric formulation of the negative emotions experienced by many individuals with AUD. Although comorbidity refers to the presence of any two psychiatric diagnoses in the same individual, the co-occurrence of various anxiety and depression (internalizing) disorders (e.g., panic disorder, depression, social anxiety disorder) with AUD has been the object of intense study since the introduction of DSM III (Kushner et al., 1990; Kushner, Abrams, & Borchardt, 2000). Various large-scale rigorous epidemiological and clinical studies show that all internalizing disorders are about 2 3 times more common among those with versus without an AUD (Kushner et al., 2009). Although it is commonly (but not universally) assumed that it is the negative affect shared by all internalizing disorders that accounts for their collective association with AUD, Kushner et al. (2012) directly investigated this in data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N 5 approximately 44,000). Using a latent variable structural equation modeling approach, they demonstrated that it is the shared components (i.e., those that covary), but not the unique components (i.e., those that do not covary), among seven common internalizing disorders that correlate with AUD risk. Put differently, AUD risk increased as the amount

(or “load”) of internalizing psychopathology increased, regardless of the specific “type” of internalizing disorder. This finding indicates that the common practice of focusing the study and treatment of comorbidity specific to only one internalizing disorder [e.g., social anxiety or posttraumatic stress disorder (PTSD)] in relationship to AUD is inefficient at best. Moreover, the quantitative (vs qualitative) impact of internalizing disorders on AUD risk implies that negative affect not rising to a diagnostic threshold should also be positively related to AUD risk, albeit to a lesser extent. Largely consistent with the TRH, retrospective studies are fairly consistent in showing that the onset of anxiety and depressive disorders predate the onset of a comorbid AUD in about three-quarters of comorbid cases (Kushner et al., 1990; Kushner et al., 2009); however, prospective studies paint a different picture. Kushner, Abrams, Thuras, and Hanson (2000) found that not only were college freshman who had an anxiety disorder at a two- to threefold greater risk for developing a new AUD 4 and 7 years later, but those who had an AUD as freshman were at a three- to fivefold greater risk for developing a new anxiety disorder 4 and 7 years later. Thus, while internalizing disorders may routinely onset earlier than AUD, the prospective increase in risk that either condition confers on the other is similar in magnitude. Additionally, Kushner, Maurer, Menary, and Thuras (2011) and Kushner et al. (2012) found that individuals with an internalizing disorder, whether starting before or after a co-occurring addiction, transitioned significantly more quickly (on the order of several years) from early-use milestones (e.g., first regular use) to physical dependence/addiction. Taken together, these findings make it clear that a unidirectional causal model is inadequate to fully account for comorbidity and suggest that there is a shared vulnerability to both internalizing disorders and addiction. In addition to marking an increased risk for developing AUD, internalizing disorders also mark an increased risk for relapse in the months following treatment (Kushner et al., 2005). Results of studies testing the value of adding standard psychiatric treatment to standard AUD treatment in comorbid patients have been mixed: some finding benefits for the outcomes of both comorbid disorders (Brown, Evans, Miller, Burgess, & Mueller, 1997); some finding benefits for the internalizing disorder outcome, but not the AUD outcome (Schade et al., 2005); and others finding no benefits for the outcomes of either condition (Randall, Thomas, & Thevos, 2001). Given the difficulty of interpreting these mixed findings, Hobbs, Kushner, Lee, Reardon, and Maurer (2011) conducted a metaanalysis of RCTs that compared a first-line psychiatric treatment [either cognitive-behavioral therapy (CBT)

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INTRODUCTION

or antidepressant pharmacotherapy] for a comorbid internalizing disorder to a placebo/control intervention in patients undergoing AUD treatment (N 5 15 studies). They found that psychiatric treatment was reasonably effective in treating the internalizing disorder compared to control (d 5 . 45), however, this effect did not translate into substantially improved AUD outcomes compared to controls (d 5 . 24). Given such findings, it is not surprising NIAAA concluded as recently as 2010 that: “There have been no major breakthroughs in the treatment of comorbid alcohol use disorder and anxiety/depression.” (PAS 10 251). Since then, accumulating data have suggested that drinking motivated by the goal of obtaining relief from negative emotions (drinking to cope; DTC) is a critical component of comorbidity. As shown in Fig. 63.1, Menary, Kushner, Maurer, and Thuras (2011) found that among drinkers with an anxiety disorder and no AUD, only the subset acknowledging DTC (about 20%) were consuming more alcohol than those with no anxiety disorder. Notably, those with an anxiety disorder who denied DTC drank somewhat less on a daily basis than those with no anxiety disorder. Further, they found that among those with an anxiety disorder, the risk for developing a new AUD between Waves I and II of the NESARC (approximately 3 years apart) was elevated beyond those with no anxiety disorder only among those who endorsed DTC. Similarly, Crum et al. (2013) employed a propensity score method in the NESARC dataset to show that the fraction of AUD persistence across the two time points

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attributable to DTC for an internalizing disorder was 30.6% and 11.9%, respectively. Anker et al. (2017) graphically represented the relationships between various anxiety and depression syndrome symptom levels, alcohol use and DTC in a comorbid sample using a network analytic approach. This showed that DTC served as the “bridge” connecting anxiety/depression symptoms to alcohol use and was the most central (i.e., connected) variable in the network (Fig. 63.2). Furthermore, model simulations demonstrated that in the absence of DTC, the connection between alcohol use and internalizing symptoms was eliminated (Fig. 63.3). These data suggest that improvement in AUD treatment outcomes may result from directly targeting DTC. Building on Marlatt’s RPT approach, (Kushner et al., 2006) developed a CBT intervention designed to mitigate DTC in negative emotion situations (DTCCBT) for AUD treatment patients with a comorbid anxiety disorder. Kushner et al. (2013) randomized over 300 comorbid inpatients to receive either this DTC-CBT or a standard behavioral anxiety management intervention of equivalent intensity [Progressive Muscle Relaxation Training (PMRT)]. A third cohort of comorbid patients undergoing AUD treatment as usual without PMRT or DTC-CBT was also assessed. Results indicated that both the DTC-CBT and anxiety control treatment were equally effective at reducing anxiety symptoms relative to AUD treatment alone. However, the DTC-CBT group obtained superior AUD outcomes at the 4-month posttreatment follow-up compared to the other groups. Anker, Kushner, Thuras, Menk, and Unruh (2016) showed further that the benefits of DTCCBT were strongest for the subgroup who reported the highest level of DTC in negative emotion situations prior to treatment (Fig. 63.4).

The Neuroscientific Opponent Process Model

FIGURE 63.1 The mean ounces (ozs.) of alcohol consumed per day for the year preceding Wave 1 of the NESARC. Study groups consisted of drinkers with no AUD who: (1) had an anxiety disorder and DTC (Anxiety Self Med); (2) had an anxiety disorder, but did not DTC (Anxiety No Self Med); and (3) had no anxiety disorder (No Anxiety). Source: The slightly modified figure is shown with permission, from Menary, K.R., Kushner, M.G., Maurer, E., & Thuras, P. (2011). The prevalence and clinical implications of self-medication among individuals with anxiety disorders. Journal of Anxiety Disorders, 25(3), 335 339.

There can be little doubt that academic psychiatry is moving away from the clinically-based binary diagnostic entities of the DSM and toward a neuroscientific understanding of human behavior on a continuum from adaptive function to psychiatric dysfunction. (See description of the Research Domain Criteria project by Morris and Cuthbert, 2012.) Reviews of clinical neuroscience research on stress and AUD can be found in a special edition of Alcohol Research: Current Reviews (2012, vol. 34 34). For example, Brady and Back (2012) review data showing that extreme or chronic early life stressors may permanently dysregulate brain stressresponse systems implicated in the pathophysiology of depression, anxiety and addiction. Suggesting that dysregulated stress responding is fundamental to

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FIGURE 63.2 Network structure (A) and strength centrality plot (B) of variables that represent measures of internalizing disorder symptoms, perceived stress, alcohol craving, drinking behavior/total number of drinks consumed, DTC and coping self-efficacy (SEL). Lines/edges represent partial correlations between network elements (controlling for all other elements). Source: The slightly modified figure is shown with permission, from Anker, J.J., Forbes, M.K., Almquist, Z.W., Menk, J.S., Thuras, P., ... Kushner, M.G. (2017). A network approach to modeling comorbid internalizing and alcohol use disorders. Journal of Abnormal Psychology, 126(3), 325 339.

FIGURE 63.3

An association network (A) and networks after controlling for DTC (B) and all internalizing symptoms (C) variables. Line width corresponds to the following correlation values: thinnest width 5 0.16 to 0.25, medium width 5 0.26 to 0.35, thickest width 5 0.36. Source: The slightly modified figure is shown with permission, from Anker, J.J., Forbes, M.K., Almquist, Z.W., Menk, J.S., Thuras, P., ... Kushner, M.G. (2017). A network approach to modeling comorbid internalizing and alcohol use disorders. Journal of Abnormal Psychology, 126(3), 325 339.

AUD risk, Thomas, Bacon, Sinha, Uhart, and Adinoff (2012) (also see Clarke, Nymberg, & Schumann, 2012) cite data indicating that individuals who abuse alcohol or have a genetic/familial risk for AUD, show distinctive dysregulated responses to laboratory stress. Reviews by Sinha (2012), Herman (2012), and Becker (2012) present data showing that chronic alcohol use can dysregulate stress responsivity, which, in turn, can contribute to further alcohol craving and relapse in response to stress. George Koob and his colleagues have drawn on these and related neuroscientific data to formulate a neurobiological opponent-process model of addiction (Kwako & Koob, 2017). In the first stage of addiction (binge/intoxication), ongoing and increasing substance use is motivated by the resulting hedonically positive

(pleasurable) activation of reward circuits (e.g., release of dopamine and opioid peptides in the ventral striatum). However, with chronic substance exposure, there are: (1) within system neuro-adaptations in which reward circuits become increasingly blunted with corresponding flattened affect and (2) between system neuro-adaptations in which brain stress-circuits in the extended amygdala produce drug-opposite (i.e., hedonically negative) effects with corresponding increases in stress, anxiety, and depression. Over time, these neuro-compensatory responses result in more stable changes in the set point baseline of these systems (allostasis) leading to the withdrawal/negative affect stage of addiction. At this stage, drinking is motivated by relief of the increasingly chronic and severe negative affect associated

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INTRODUCTION

Average drinking days (± SEM)

(A)

Drinking days

DTC-CBT

PMRT

20 15 10 5 0 Low DTC

Binge days

Average binge days (± SEM)

(B) 20 15 10 5

0 Low DTC

(C) Average total drinks (± SEM)

High DTC

High DTC

Total drinks 350 300

250 200 150 100 50 0 Low DTC

High DTC

FIGURE 63.4 The estimated means ( 6 SEM) for drinking days (A), binge days (B), and total drinks (C), at a 4-month posttreatment follow-up as a function of treatment [DTC-CBT vs Progressive Muscle Relaxation Training (PMRT)] and DTC in negative emotion situations (median split, low vs high groups) in the 30 days prior to treatment. Source: The slightly modified figure is shown with permission, from Anker, J.J., Kushner, M.G., Thuras, P., Menk, J., & Unruh, A.S. (2016). Drinking to cope with negative emotions moderates alcohol use disorder treatment response in patients with co-occurring anxiety disorder. Drug and Alcohol Dependence, 159, 93 100.

with allostatic changes. Finally, preoccupation/anticipation drinking motives track these neuro-adaptations with use in early addiction being motivated by pleasure during the binge-intoxication phase and use in later addiction being motivated by relief in the withdrawal-negative affect stage. As chronic substance use compromises executive control via the prefrontal

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cortex (Koob & Volkow, 2010), resistance to craving becomes more difficult. In late addiction (the “dark side”) a self-perpetuating “vicious cycle” is established in which worsening stress/mood resulting from chronic alcohol use drives increasing alcohol use aimed at relief (Fig. 63.5). The neurobiological opponent-process model implies specific addiction treatment targets to mitigate the brain-circuit deviations thought to drive substanceinduced allostasis and underlying dysregulated stress and mood systems. One such target is corticotropinreleasing factor (CRF), a 41-amino acid neuropeptide that is active in many key brain processes, including those related to stress responses mediated by the extended amygdala circuit. Preclinical studies in animals show that CRF antagonists inhibit alcohol withdrawal-induced anxiety (Baldwin, Rassnick, Rivier, Koob, & Britton, 1991), alcohol intake during withdrawal and abstinence (Funk & Koob, 2007), and stress-induced reinstatement of alcohol-seeking (Liu & Weiss, 2002). However, Kwako et al. (2015) found that that pexacerfont, an oral CRH1 antagonist, had no effect on alcohol craving, emotional responses or anxiety in a small open-label trial with alcoholics. Schwandt et al. (2016) studied the CRF1 antagonist, verucerfont, in 39 alcoholic women finding the drug potentially blocked hypothalamic-pituitary-adrenal (HPA) axis response to a pharmacologic challenge, but, surprisingly, left alcohol craving unaffected. While brain imaging showed that right amygdala responses to negative emotion stimuli were attenuated by the medication, responses to alcohol-related stimuli were actually increased in other brain areas. Importantly, discontinuation rates were significantly higher in the verucerfont group. Another treatment target stemming from the opponent-process model is the alpha-1 noradrenergic system. It has been hypothesized that prazosin, an alpha-1 noradrenergic receptor antagonist, could improve alcohol outcomes by reducing stress responding, arguably by reducing forebrain CRF release. Prazosin has been shown to be effective in reducing alcohol consumption in alcohol-dependent rats and those bred for alcohol preference (Froehlich, Hausauer, Federoff, Fischer, & Rasmussen, 2013; Rasmussen, Alexander, Raskind, & Froehlich, 2009; Walker & Koob, 2008). Fox et al. (2012) examined 17 early abstinent alcohol-dependent individuals who were randomly assigned to 16 mg daily prazosin or placebo for 4 weeks. They found that stress and cue-induced craving were reduced among those given prazosin. Simpson et al. (2009) examined 17 male alcoholics who received either prazosin (titrated to 8 mg over 2 weeks) or placebo in a 6-week double-blind RCT. They found the prazosin group reported fewer drinking days and

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FIGURE 63.5 The transition from early alcohol use that is positively reinforced and motivated by pleasurable alcohol effects, to alcohol use in dependence/addiction that is negatively reinforced and motivated relief from negative emotional states. Source: The slightly modified figure is shown with permission, from Trends in Neurosciences, Heilig and Koob (2007).

total number of drinks. However, a larger doubleblind RCT in veterans with PTSD and comorbid AUD did not show benefit from prazosin relative to placebo in terms of stress or alcohol outcomes (Petrakis et al., 2016). Other drug antagonists targeting specific neuroprocesses stemming from the opponent-process model with promising preclinical data include: neuropeptide Y, a 36-amino acid peptide implicated in stress responding; dynorphins, opioid peptides with wide distribution in the CNS that have been implicated in the neurobiology of negative emotional states (Pfeiffer, Brantl, Herz, & Emrich, 1986); and, substance P [including neurokinin 1 (NK1) receptor], which has been shown to modulate emotional states associated with HPA activation (Ebner & Singewald, 2006).

CONCLUDING REMARKS We can no longer afford (if we ever could) to conduct research in disciplinary silos. Nor should we succumb to the temptation, all too common in psychology and psychiatry (Lykken, 1991), to jettison all that is old in favor of all that is new. While neuroscience offers the cutting edge of our attempt to describe and relieve mental/behavioral dysfunctions, explicitly seeking translational language, concepts, and knowledge across the related disciplines of psychology, psychiatry, and neuroscience is needed to achieve this goal.

MINI-DICTIONARY OF TERMS Allostasis In contrast to “homeostasis” (in which biological systems act to return to baseline following an acute insult/dysregulation), “allostasis” refers to a persistent change in a biological system’s baseline set-point in response to a chronic insult/dysregulation. Comorbidity Introduced by Feinstein (1970) as in reference to the effects of nonindexed illness(es) on the diagnosis, treatment and prognosis of the index illness, the concept of comorbidity as the co-occurrence of two or more psychiatric disorders was first promulgated in DSM III (1980). Neo-Kraepelinian Medical Model of Psychiatry Named for Emil Kraepelin, a German psychiatrist who argued in the late-19th and early-20th century that mental disorders were primarily of biological origin and, in that sense, were medical illnesses. In adopting this view in the DSM III (1980), academic psychiatry rejected the Freudian and behavioral theories of mental disorder. Research Domain Criteria (RDoC) A recently introduced research framework that ignores the psychiatric diagnostic approach in favor of three central postulates: (1) psychiatric problems (including addiction) result from deviated brain circuit function; (2) the tools of neuroscience can identify and characterize the function of these brain circuits; and (3) there is a unique and quantifiable bio-signature for each fundamental type of psychiatric dysfunction (Cuthbert, 2014; Morris & Cuthbert, 2012).

KEY FACTS Negative Emotions and Alcohol Use • Hippocrates prescribed wine as an anxiolytic over 2000 years ago.

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REFERENCES

• Premodern scientific descriptions of “alcoholism” consistently identified two subtypes: one characterized by DTC with a strong negative affect and one characterized by drinking as a part of pleasure-seeking (cf., Babor, 1996). • Sigmund Freud was the first to formally propose a “self-medication” model of addiction in which he considered chronic drinking to be a defense mechanism against intrapsychic “neurotic” conflicts. • Negative emotions correlate with alcohol use and AUD only when accompanied by a pattern of DTC. • The opponent process view—that pleasant drug effects proximal to use dominate in early addiction (a-process) while unpleasant drug effects distal to use dominate in later addiction (b-process)—was originally described by Solomon and Corbit (1973). However, it was not until George Koob and Le Moal (1997) linked the exaggerated and persistent bprocess in late addiction to neuro-adaptations (allostasis) stemming from chronic drug/alcohol use that this view became the preeminent neurobiological model of the role of negative emotions in addiction.

•

•

SUMMARY POINTS • For all the models reviewed, DTC is a final common pathway linking negative emotions to alcohol use and AUD. In the absence of DTC, negative emotions are not associated with increased alcohol use or risk for AUD. Data show that DTC serves as a conduit between negative emotions and drinking and can dissociate them when removed from the system. Treatment studies show that targeting DTC produces superior AUD treatment outcomes for comorbid patients than anxiety treatment alone. • The various negative emotions referenced in the models reviewed (i.e., stress, tension, negative affect/emotions/mood, anxiety, and depression) function similarly (and likely overlap neurobiologically) in relation to drinking and AUD. Intensity (internalizing load) rather than the type of negative emotions correlates positively with alcohol involvement and AUD. This suggests that the presence or absence of comorbidity is a quantitative rather than qualitative distinction regarding the role of negative emotions in AUD. • Chronic alcohol use serves as a neurobiological insult that, through allostatic adaptations, dysregulates stress-mood systems creating favorable conditions for the development of a vicious cycle of escalating negative emotions and DTC (i.e., the negative affect/withdrawal stage of addiction). This implies that negative emotions are not just a risk for

•

•

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or a consequence of addiction, but are a core feature of addiction itself. Exogenous neurobiological insults preceding addiction (e.g., from chronic/traumatic stress) and neurobiological characteristics not caused by alcohol (e.g., those associated with vulnerability to anxiety or depression syndromes) also set favorable neurobiological conditions for developing a vicious cycle of escalating negative emotions and DTC (again, the affect/withdrawal stage of addiction). This implies that those with internalizing disorders are more vulnerable to develop addiction than others even when lifetime alcohol exposure is held constant. Re-regulation of neurobiological stress-mood systems should promote and otherwise be a neurobiological sign of recovery from AUD; however, it is unclear on what timeline abstinence alone allows these systems to re-regulate. Having shown that those with comorbid psychiatric disorders develop the affect/withdrawal stage of addiction more quickly than others with AUD, and that they relapse following treatment at higher rates than others with AUD, we speculate that the reregulation of neurobiological stress-mood systems in abstinence is substantially retarded or absent altogether for comorbid individuals. Pharmacological interventions narrowly targeting neurobiological stress-mood systems, and cognitive behavioral interventions narrowly targeting DTC in high-risk negative emotion situations, are shown to minimize relapse following AUD treatment. Standard psychiatric treatment (cognitive-behavioral or pharmacological) for comorbid anxiety and depressive disorders that persist during abstinence is clinically indicated to relieve the patient’s suffering and may modestly improve AUD treatment outcomes.

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Baldwin, H. A., Rassnick, S., Rivier, J., Koob, G. F., & Britton, K. T. (1991). CRF antagonist reverses the “anxiogenic” response to ethanol withdrawal in the rat. Psychopharmacology, 103(2), 227 232. Becker, H. C. (2012). Effects of alcohol dependence and withdrawal on stress responsiveness and alcohol consumption. Alcohol Research: Current Reviews, 34, 448 458. Becker, H. C., Lopez, M. F., & Doremus-Fitzwater, T. L. (2011). Effects of stress on alcohol drinking: a review of animal studies. Psychopharmacology, 218(1), 131 156. Brady, K. T., & Back, S. E. (2012). Childhood trauma, posttraumatic stress disorder, and alcohol dependence. Alcohol Research: Current Reviews, 34, 408 413. Brown, R. A., Evans, D. M., Miller, I. W., Burgess, E. S., & Mueller, T. I. (1997). Cognitive behavioral treatment for depression in alcoholism. Journal of Consulting and Clinical Psychology, 65(5), 715 726. Cappell, H., & Herman, C. P. (1972). Alcohol and tension reduction: A review. Quarterly Journal of Studies on Alcohol, 33(1), 33 64. Carroll, K. M. (1996). Relapse prevention as a psychosocial treatment: A review of controlled clinical trials. Experimental and Clinical Psychopharmacology, 4(1), 46 54. Clarke, T. K., Nymberg, C., & Schumann, G. (2012). Genetic and environmental determinants of stress responding. Alcohol Research: Current Reviews, 34, 484 494. Crum, R. M., Mojtabai, R., Lazareck, S., Bolton, J. M., Robinson, J., Sareen, J., . . . Storr, C. L. (2013). A prospective assessment of reports of drinking to self-medicate mood symptoms with the incidence and persistence of alcohol dependence. JAMA Psychiatry, 70(7), 718 726. Available from https://doi.org/ 10.1001/jamapsychiatry.2013.1098. Cuthbert, B. N. (2014). The RDoC framework: Facilitating transition from ICD/DSM to dimensional approaches that integrate neuroscience and psychopathology. World Psychiatry, 13(1), 28 35. Donovan, D. M., & Marlatt, G. A. (1980). Assessment of expectancies and behaviors associated with alcohol consumption. A cognitive— behavioral approach. Journal of Studies on Alcohol, 41(11), 1153 1185. Dvorak, R. D., Pearson, M. R., & Day, A. M. (2014). Ecological momentary assessment of acute alcohol use disorder symptoms: Associations with mood, motives, and use on planned drinking days. Experimental and Clinical Psychopharmacology, 22(4), 285. Ebner, K., & Singewald, N. (2006). The role of substance P in stress and anxiety responses. Amino Acids, 31(3), 251 272. Feinstein, A. R. (1970). The pre-therapeutic classification of comorbidity in chronic disease. Journal of Chronic Diseases, 23(7), 455 468. Fox, H. C., Anderson, G. M., Tuit, K., Hansen, J., Kimmerling, A., Siedlarz, K. M., . . . Sinha, R. (2012). Prazosin effects on stress-and cue-induced craving and stress response in alcohol-dependent individuals: Preliminary findings. Alcoholism: Clinical and Experimental Research, 36(2), 351 360. Froehlich, J. C., Hausauer, B. J., Federoff, D. L., Fischer, S. M., & Rasmussen, D. D. (2013). Prazosin reduces alcohol drinking throughout prolonged treatment and blocks the initiation of drinking in rats selectively bred for high alcohol intake. Alcoholism: Clinical and Experimental Research, 37(9), 1552 1560. Funk, C. K., & Koob, G. F. (2007). A CRF 2 agonist administered into the central nucleus of the amygdala decreases ethanol self-administration in ethanol-dependent rats. Brain Research, 1155, 172 178. Heilig, M., & Koob, G. F. (2007). A key role for corticotropin-releasing factor in alcohol dependence. Trends in neurosciences, 30(8), 399 406. Herman, J. P. (2012). Neural pathways of stress integration: Relevance to alcohol abuse. Alcohol Research: Current Reviews, 34, 441 447.

Hobbs, J. D., Kushner, M. G., Lee, S. S., Reardon, S. M., & Maurer, E. W. (2011). Meta-analysis of supplemental treatment for depressive and anxiety disorders in patients being treated for alcohol dependence. American Journal on Addictions, 20(4), 319 329. Available from https://doi.org/10.1111/j.1521-0391.2011.00140.x. Irvin, J. E., Bowers, C. A., Dunn, M. E., & Wang, M. C. (1999). Efficacy of relapse prevention: A meta-analytic review. Journal of Consulting and Clinical Psychology, 67(4), 563 570. Koob, G. F., & Le Moal, M. (1997). Drug abuse: hedonic homeostatic dysregulation. Science, 278(5335), 52 58. Koob, G. F., & Volkow, N. D. (2010). Neurocircuitry of addiction. Neuropsychopharmacology, 35(1), 217 238. Kushner, M. G., Abrams, K., & Borchardt, C. (2000). The relationship between anxiety disorders and alcohol use disorders: A review of major perspectives and findings. Clinical Psychology Review, 20(2), 149 171. Kushner, M. G., Abrams, K., Thuras, P., & Hanson, K. L. (2000). Individual differences predictive of drinking to manage anxiety among non-problem drinkers with panic disorder. Alcoholism Clinical and Experimental Research, 24(4), 448 458. Kushner, M. G., Abrams, K., Thuras, P., Hanson, K. L., Brekke, M., & Sletten, S. (2005). Follow-up study of anxiety disorder and alcohol dependence in comorbid alcoholism treatment patients. Alcoholism Clinical and Experimental Research, 29(8), 1432 1443. Kushner, M. G., Donahue, C., Sletten, S., Thuras, P., Abrams, K., Peterson, J., & Frye, B. (2006). Cognitive behavioral treatment of comorbid anxiety disorder in alcoholism treatment patients: Presentation of a prototype program and future directions. Journal of Mental Health, 15(6), 697 707. Kushner, M. G., Maurer, E., Menary, K., & Thuras, P. (2011). Vulnerability to the rapid (“telescoped”) development of alcohol dependence in individuals with anxiety disorder. Journal of Studies on Alcohol and Drugs, 72(6), 1019 1027. Kushner, M. G., Maurer, E. W., Thuras, P., Donahue, C., Frye, B., Menary, K. R., . . . Van Demark, J. (2013). Hybrid cognitive behavioral therapy versus relaxation training for co-occurring anxiety and alcohol disorder: A randomized clinical trial. The Journal of Consulting and Clinical Psychology, 81(3), 429 442. Available from https://doi.org/10.1037/a0031301. Kushner, M. G., Sher, K. J., & Beitman, B. D. (1990). The relation between alcohol problems and the anxiety disorders (Special Article). American Journal of Psychiatry, 147, 685 695. Kushner, M. G., Sletten, S., Donahue, C., Thuras, P., Maurer, E., Schneider, A., . . . Van Demark, J. (2009). Cognitive-behavioral therapy for panic disorder in patients being treated for alcohol dependence: Moderating effects of alcohol outcome expectancies. Addictive Behaviors, 34(6), 554 560. Kushner, M. G., Wall, M. M., Krueger, R. F., Sher, K. J., Maurer, E., Thuras, P., & Lee, S. (2012). Alcohol dependence is related to overall internalizing psychopathology load rather than to particular internalizing disorders: Evidence from a national sample. Alcoholism: Clinical and Experimental Research, 36(2), 325 331. Available from https://doi.org/10.1111/j.1530-0277.2011.01604.x. Kwako, L. E., George, D. T., Schwandt, M. L., Spagnolo, P. A., Momenan, R., Hommer, D. W., . . . Heilig, M. (2015). The neurokinin-1 receptor antagonist aprepitant in co-morbid alcohol dependence and posttraumatic stress disorder: A human experimental study. Psychopharmacology, 232(1), 295 304. Kwako, L. E., & Koob, G. F. (2017). Neuroclinical framework for the role of stress in addiction. Chronic Stress, 1, 1 14. Larimer, M. E., & Palmer, R. S. (1999). Relapse prevention: An overview of Marlatt’s cognitive-behavioral model. Alcohol Research and Health, 23(2), 151 160. Liu, X., & Weiss, F. (2002). Additive effect of stress and drug cues on reinstatement of ethanol seeking: Exacerbation by history of

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64 Use of Baclofen in Alcohol Use Disorder: A Clinical Approach Bruce Imbert Global Medicines Development, Indivior Inc., Richmond, VA, United States

LIST OF ABBREVIATIONS AUD AE ANSM GABA RCT RTU

increased gradually until optimum effect is achieved (usually between 40 and 80 mg/day). The determination of optimal oral dosage requires individual titration. Baclofen withdrawal syndromes have been described after abrupt treatment discontinuation and may include a rebound increase in spasticity, fever, altered mental status, seizures, and malignant hyperthermia. In this chapter, we review the literature regarding the clinical efficacy of baclofen in the treatment of alcohol use disorder (AUD).

alcohol use disorder adverse effect French National Security Agency of Medicines and Health Products gamma-aminobutyric acid randomized controlled trials temporary recommendation for use

INTRODUCTION Historically, baclofen was designed as a potential drug to treat epilepsy. This lipophilic analog of the gamma-aminobutyric acid (GABA), was first synthesized in 1962 as a p-chlorophenyl derivative of GABA and played a crucial role in the discovery of the GABAB receptor (Faigle & Keberle, 1972). Disappointing results in this therapeutic indication led to the development and commercialization of baclofen as an antispastic agent. In 1975, two enantiomers of baclofen were identified, (R)-baclofen and (S)-baclofen (Fig. 64.1). Although the marketed version of baclofen is a racemic mixture, studies have shown that the pharmacological activity of baclofen was mostly related to the (R) enantiomer (Witczuk, Khaunina, & Kupryszewski, 1980). Since the 1970s, baclofen has been used in spasticity associated with neurologic conditions, such as multiple sclerosis and spinal cord lesions. For these indications, baclofen can be administered either in oral form or via the intrathecal route. An 80 mg/day dose is a commonly accepted maximum, however dosing up to 120 mg/day can be done in a hospital setting. Treatment should be started at a low dosage (5 10 mg two or three times per day) and

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00064-7

ROLE OF GABAB RECEPTORS IN ALCOHOL USE DISORDER GABA is an inhibitory neurotransmitter discovered in 1949 by Eugene Roberts, but it was not until the 1960s that its neurotransmitter function was identified. GABA is synthesized from glutamate, is released at the termination of GABAergic neurons and can bind to several receptors. There are two main classes of GABA receptors: ionotropic receptors and metabotropic receptors. The ionotropic receptors (classified as GABAA) are chloride ion channels to which the neurotransmitter binds directly to modulate channel opening. The metabotropic receptors (classified as GABAB) are G proteincoupled receptors which bind the neurotransmitter facilitating indirect modulation of ion channel activity. The first record of a preclinical in vivo study of baclofen occurred during the late-1980s. A French study investigating the effects of GABAA and GABAB agonists in ethanol-preferring rats, concluded that GABAA and benzodiazepines receptors did not modulate ethanol

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© 2019 Elsevier Inc. All rights reserved.

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64. USE OF BACLOFEN IN ALCOHOL USE DISORDER: A CLINICAL APPROACH

TABLE 64.1

Baclofen Pharmacologic Properties in AUD Patients

Main mechanism of action GABAB agonist

FIGURE 64.1 Chemical structure of baclofen enantiomers.

intake, unlike baclofen (a GABAB receptor agonist) that was able to significantly decrease the voluntary ethanol consumption (Daoust et al., 1987). Several subsequent experimental findings in animals have demonstrated the implication of GABAB receptor and baclofen in modulating different alcohol-related behaviors. In animal models, baclofen inhibits several addictive behaviors such as: acquisition of alcohol-drinking behavior (Colombo et al., 2002), increase in alcohol intake after abstinence, alcohol reinforcement and motivation to consume under self-administration conditions, alcohol-related motivation (Colombo et al., 2003), and cue-induced reinstatement of alcohol-seeking behavior (Agabio & Colombo, 2014). Baclofen was also shown to reduce the intensity of the emotional (anxious and aggressive behaviors) and physical responses (tremors and seizures) associated with ethanol withdrawal (Colombo, Serra, Vacca, Carai, & Gessa, 2006). In humans, through activation of GABAB receptors, baclofen may exert direct and indirect inhibitory actions on the dopamine neurons in the ventral striatum (Cruz et al., 2004). This pathway may explain the suppressive effect of baclofen on alcohol-stimulated dopamine release and, in turn, the reduction of the many dopaminecontrolled, alcohol-reinforced behaviors (Addolorato & Leggio, 2010; Agabio & Colombo, 2014). GABA neurotransmission is also involved in the control of anxiety suggesting a significant role in the regulation of emotional behavior and the control of anxiety which is a common symptom in AUD patients (Morley et al., 2014).

CLINICAL PHARMACOLOGY OF BACLOFEN The pharmacologic properties of baclofen have led to the investigation of its benefits in the treatment of AUD. Following oral administration, baclofen is rapidly and completely absorbed from the gastrointestinal tract, with

Bioavailability

70% 85%

Administration

Oral (usually three to four times a day)

Distribution

Volume of distribution 68 80 L. Crosses blood brain barrier

Plasma protein binding

30% 35%

Metabolism

15% liver and 70% 80% kidney

Elimination

Urine and feces mostly as an unchanged drug

Clearance

120 180 mL/min

Half-Life

4 7h

Peak plasma concentration

,3 h

Therapeutic approval

No approval for AUD. Approved in Europe and the United States as a muscle relaxant and antispastic agent

Drug interactions

CNS depressant effect, additive to those of alcohol and other CNS depressants

Pregnancy

Teratogenic effects with increased risk of malformations

This table provides a synthesis of baclofen main pharmacological properties. CNS, central nervous system.

a bioavailability of 70% 85% reflecting the absence of significant hepatic first-pass metabolism. Baclofen has linear pharmacokinetics with a dose proportional exposure relationship for dosages of 30 240 mg/day (dosages corresponding to those currently used in AUD patients), and this means that doubling the dose represents a doubling of blood levels and therefore a doubling of patient exposure to the drug. A wide interindividual variability was described implying that a similar dose did not lead to similar exposure in all patients. Once in the general circulation, baclofen diffuses into the body with a relatively large volume of distribution 68 80 L (Imbert, Alvarez, & Simon, 2015; Marsot et al., 2014). The concentrations found in the cerebrospinal fluid are nearly nine times lower than those observed simultaneously in plasma suggesting the presence, at the blood brain barrier level, of organic anion transporters acting by eliminating the molecule from the CNS (Ohtsuki et al., 2002). In AUD patients, the peak plasma concentrations (Cmax) after oral administration is no longer than 3 hours (Tmax), with a plasma half-life (T1/2) of 4 7 hours (Imbert et al., 2015; Marsot et al., 2014). This means that frequent administrations, three (TID) to four (QID) times per day, are required to maintain drug plasma concentrations at therapeutic levels. Such frequent dosing is inconvenient and can lead to treatment nonadherence and safety issues (missed or extra doses) (Table 64.1).

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CLINICAL EFFICACY OF BACLOFEN IN THE TREATMENT OF ALCOHOL USE DISORDER

Food intake does not alter the absorption of the drug, but taking the drug during a meal minimizes the risk of digestive disturbances. Baclofen is predominantly excreted unchanged by the kidneys (70% 80%) making it safe to use in patients who already have severe liver dysfunction from chronic excess consumption of alcohol or other causes. The remainder is excreted as unchanged drug in the feces or as metabolites in the urine and feces. To our knowledge, only one study has described both baclofen pharmacokinetics/ pharmacodynamics relationship in AUD patients. This study defined the relationship between exposure to baclofen and the reduction of craving during a 3-month cohort follow-up. Baclofen reduced craving in all patients, but two subpopulations of patients responding differently to treatment have been identified. In fact, 38% of patients had an early response (reduction in craving in the first month) while their cumulative exposure was low, while the other patients appeared to require higher exposure (Imbert et al., 2015). Witczuk et al. (1980) suggested that the mediator of baclofen pharmacological activity was the R-enantiomer, (R)-baclofen. Recent preclinical studies confirmed these findings and suggested that treatment with the two baclofen enantiomers resulted in opposite effects on alcohol drinking. Equal doses of (R)-baclofen suppressed TABLE 64.2

CLINICAL EFFICACY OF BACLOFEN IN THE TREATMENT OF ALCOHOL USE DISORDER In 1993, the first documented report of the use of baclofen in alcoholic patients (Krupitsky et al., 1993) concluded that baclofen (37.5 mg/day) was superior to placebo in reducing anxiety and depression; however, drinking outcomes were not reported, and the study was not blinded. In the following years, several case reports suggested that baclofen could reduce craving for alcohol and alcohol intake, prolong the time to first drink, and increase the number of days of abstinence (Agabio, Marras, Addolorato, Carpiniello, & Gessa, 2007; Ameisen, 2004; Bucknam 2006). Open-label pilot studies and observational studies (Table 64.2) with daily doses of baclofen ranging from 30 to 400 mg confirmed these findings and provided

Open-Label and Observational Studies Number of subjects enrolled

Daily dose in mg

Addolorato et al. (2000)

10

30 mg/day (10 mg t.i.d)

Flannery et al. (2004)

12

Ameisen and De Beaurepaire (2010)

60

de Beaurepaire (2012)

100

Publication

alcohol intake whereas the less active enantiomer, (S)baclofen stimulated alcohol intake (Kasten, Blasingame, & Boehm, 2015) or was ineffective on alcohol selfadministration (Lorrai, Maccioni, Gessa, & Colombo, 2016).

Study outcome negative/positive

Duration

• Craving reduction (P , .01) • Significant decrease (P , .01) in AST, ALT, GGT, MCV • Reduction in alcohol intake • Obsessional thinking about alcohol disappeared

Positive

4 weeks

30 mg/day (10 mg t.i.d)

• Significant reductions in: • number of drinks per drinking day (decrease of 61.8%; P , .01) • number of HDDs • anxiety (P , .04) and craving (P , .01) • Increase in the number of abstinent days (but no subjects maintained complete abstinence)

Positive

12 weeks

15 300 mg/day;

• 88% subjects completely ceased or significantly decreased alcohol consumption • Most of the subjects reported a total indifference to alcohol

Positive

12 weeks

• 92% experienced craving reducing effect of baclofen • All subjects were “high risk” at baseline. Sum of low and moderate risk was: 84% at 3 months and 70% at 6 months; and 63% at 1 year and 62% at 2 years

Positive

Up to 2 years

Mean 145 mg/day

20 330 mg/day

Detailed outcome

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64. USE OF BACLOFEN IN ALCOHOL USE DISORDER: A CLINICAL APPROACH

new evidence that baclofen could prolong the time to first drink, reduce craving for alcohol, reduce overall drinking days, and facilitate maintenance of abstinence. Other studies in AUD patients with liver disease, treated with baclofen 30 mg/day (Addolorato et al., 2007; Yamini, Lee, Avanesyan, Walter, & Runyon, 2014) or with baclofen doses between 30 and 210 mg/day with a 40 mg/day mean dose (Barrault et al., 2017) suggested that baclofen was well-tolerated and safe for the maintenance of abstinence in this particular population of patients (Table 64.3). In alcohol-dependent patients, several randomized controlled trials (RCT) using baclofen have been published to date (Table 64.4). These studies reported a high tolerability of baclofen in patients, but yielded conflicting results regarding efficacy. The different designs and methodologies (AUD severity, baclofen dose, duration of treatment, length of detoxification if any, intensity of psychosocial support, sample size, TABLE 64.3

Clinical Studies in AUD Subjects and Alcoholic Liver Disease Number of subjects enrolled

Methodology

Daily dose in mg

Addolorato et al. (2007)

84

RCT

30 mg/day

Yamini et al. (2014)

40

Open, not controlled

Barrault et al. (2017)

100

Retrospective chart review

Publication

and endpoints) may explain the inconsistent results across the RCTs. In summary, available data and analysis suggest mixed and often contradictory results regarding the benefits of low dose or high dose baclofen in AUD patients. The only positive RCTs with low-dose baclofen (#60 mg/day) are the two studies by (Addolorato et al. 2002, 2011), other studies failed to detect any difference between baclofen and placebo. Further studies are also required to demonstrate the benefit of highdose baclofen. Of the four RCTs, two had negative outcomes (Beraha et al., 2016; Reynaud et al., 2017) and two positive outcomes (Mu¨ller et al., 2015; Jaury et al., 2016). The efficacy of baclofen (low or high doses) on the maintenance of abstinence in alcohol-dependent patients with normal liver function is, for now, not demonstrated, and further studies are required to confirm its potential craving-suppressing effect. In contrast, baclofen

Study outcome negative/positive

Duration

• Significantly more patients abstinent from alcohol in baclofen group (71%) than in placebo group (29%). Odds ratio 6.3 [95% CI 2.4 16.1]; P 5 .0001 • Number of drop-outs did not differ between baclofen group (14%) and placebo group (31%); P 5 .12 • Cumulative abstinence duration was twofold higher in baclofen group [mean 62.8 (SE 5.4) days] versus placebo mean [30.8(5.5) days]; P 5 .001 • Baclofen significantly reduced craving

Positive

12 weeks

30 mg/day

• Of the 35 patients who were started on baclofen, 97% (n 5 34) remained abstinent. • Significant decrease in mean liver test scores (ALT, AST, INR, PT, Tbili) and MELD scores

Positive

1 12 months

30

• Median daily alcohol consumption reduced from 80 to 0 g/day (P , .001) • Significant decrease in median GGT, mean AST, and mean MCV (P , .001) • In cirrhotic patients, Tbili decreased significantly (P 5 0.026), PT and ALB increased (P , 0.001)

Positive

52 weeks

Alcohol-dependent subjects with current alcohol dependence and liver cirrhosis

Alcohol-dependent subjects or subjects with alcohol abuse and alcoholic hepatitis with or without cirrhosis

35 Noncirrhotic 65 Cirrhotic

210 mg/day

Mean 40 mg/day

Detailed outcome

VII. TREATMENTS, STRATEGIES AND RESOURCES

627

CLINICAL EFFICACY OF BACLOFEN IN THE TREATMENT OF ALCOHOL USE DISORDER

TABLE 64.4

Summary of Randomized Controlled Trials in AUD Subjects Number of subjects enrolled

Daily dose in mg

39

30 mg/day

Positive • Higher percentage of subjects totally abstinent from alcohol in baclofen group (70%) than in placebo group (21.1%); P , .005 • Cumulative abstinence duration threefold higher in baclofen group (19.6 6 2.6) than in placebo (6.3 6 2.4); P , .005 • Greater decrease in craving found in baclofen group • Total alcohol intake reduced in baclofen group

4 weeks

Garbutt, Kampov- 80 Polevoy, Gallop, Kalka-Juhl, 40 Baclofen and Flannery (2010) 40 Placebo

30 mg/day

Negative • No significant effect on HDD in baclofen group (25.9% 6 23.2%) compared to placebo 25.5% ( 6 23.6%); P 5 .73 • No significant effect on percent of abstinence days in baclofen group 49.9% ( 6 27.9%) compared to placebo 50.6% ( 6 25.9%); P 5 .61 • No significant differences between placebo and baclofen for craving, depression or trait anxiety • Significant effect of baclofen on state anxiety; P 5 .02

12 weeks

Addolorato et al. (2011)

30 or 60 mg/day • Significant reduction (P , .0001) in the number of drinks per day in baclofen group compared to placebo. • Baclofen 10 mg t.i.d (53% reduction) • Baclofen 20 mg t.i.d. (68% reduction) • Dose-effect relationship—Effect of baclofen 20 mg t.i.d greater than baclofen 10 mg t.i.d in reducing daily alcohol intake (P 5 .0214) • No difference in number of Heavy Drinking Days, abstinence days, relapse and craving

Positive

12 weeks

30 or 60 mg/day • No significant difference between treatment group for: • number of days to relapse (P 5 .08) • number of days to first lapse (P 5 .18) • number of HDD per week (P 5 .26) • number of drinks/drinking day (P 5 .20) • Craving

Negative

12 weeks

Publication Addolorato et al. (2002)

20 baclofen 19 placebo

42 14 Baclofen 30 mg/day 14 Baclofen 20 mg/day 14 Placebo

Morley et al. (2014) 42 14 Baclofen 30 mg/day 14 Baclofen 60 mg/day 14 Placebo

Ponizovsky, Rosca, Aronovich, Weizman, and Grinshpoon (2015)

64 32 Baclofen

Mu¨ller et al. (2015)

56

Study outcome negative/positive Duration

Posthoc analysis shows beneficial effect of baclofen 30 and 60 mg/day on time to relapse (P , .05) and baclofen 30 mg/day on time to lapse in patients with comorbid anxiety disorder 50 mg/day

• No significant baclofen effects were found for Negative number of HDDs after 12 weeks (P 5 .79) or 52 weeks (P 5 .51) of treatment • No significant baclofen effects were found for percent of abstinent days after 12 weeks (P 5 .39) or 52 weeks (.09) of treatment • No differences between groups for craving, distress, and depression

12- and 52-week follow-up

Up to 270 mg/day

• Total abstinence during high-dose phase Positive significantly higher in baclofen group (15/22,

12 weeks

32 Placebo

28 Baclofen

Detailed outcome

(Continued)

VII. TREATMENTS, STRATEGIES AND RESOURCES

628

64. USE OF BACLOFEN IN ALCOHOL USE DISORDER: A CLINICAL APPROACH

TABLE 64.4

(Continued)

Publication

Number of subjects enrolled

Daily dose in mg

Detailed outcome

28 Placebo •

• • • Beraha et al. (2016)

151 58 High-dose baclofen

Study outcome negative/positive Duration

68.2%) compared to placebo (5/21, 23.8%), P 5 .014 Cumulative abstinence duration significantly higher in baclofen group [mean 67.8 days (SD 30)] compared to placebo group [51.8 days (SD 29.6)], P 5 .047 No serious adverse events observed during the trial No difference in the number of drop-outs No effect of treatment on alcohol craving scores or anxiety and depression levels

30 or up to 150 mg/day

• No positive effect of high-dose or low-dose baclofen • Indications for a dose response effect • Only effective for heavy drinking alcohol dependent patients with limited psychotherapy

Negative

16 weeks

Up to 180 mg/ day

• No positive effect of high-dose baclofen on Negative the maintenance of abstinence • Percentage of abstinent patients during the study was low and not significantly different between groups

20 weeks

31 Low-dose baclofen 62 Placebo Reynaud et al. (2017)

320 158 Baclofen 162 Placebo

Jaury et al. (2016)

320 162 Baclofen 158 Placebo Abstinence was not an inclusion criterion

Up to 300 mg/ day

Preliminary results:

Positive

1 year

• Results were positive for baclofen, with a proportion of abstinent patients and patients with low-risk consumption much significantly higher in the baclofen arm of the study (56.8% vs 36.5%, P 5 .004).

Abbreviations: HDD, heavy drinking days; Tbili, total bilirubin; ALB, albumin; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, gammaglutamyl transferase; MCV, mean corpuscular volume; INR, international normalized ratio; PT, prothrombin time; INR, international normalized ratio; MELD, model for end-stage liver disease; SD, standard deviation.

shows promise in patients with alcohol-induced liver disease (AILD) or liver damage where most studies had positive outcomes.

SAFETY PROFILE OF BACLOFEN Numerous studies have shown that baclofen was safe and well tolerated in patients with AUD within a dose range that exceeds the dose range associated with non-AUD therapeutic indications, 180 mg/day (Reynaud et al., 2017), 270 mg/day (Dore, Lo, Juckes, Bezyan, & Latt, 2011), 275 mg/day (Mu¨ller et al., 2015), and 300 mg/day (Jaury et al., 2016). It was also stated that even at very high doses, from 350 to 400 mg/day (de Beaurepaire, 2014), baclofen demonstrates an acceptable safety profile. Indeed, the preferential renal

excretion of baclofen in an unchanged (unmetabolized) form reduces the risk of drug interactions involving induction or inhibition of P450 cytochromes, but due to this route of elimination, renal impairment can lead to accumulation of the drug. Baclofen should not be prescribed for subjects with severe renal impairment (Creatinine Clearance ,30 mL/min) and for moderate renal impairment (between 30 and 50 mL/min) initiation and dosage adjustments must be made slowly and with caution. Commonly reported adverse effects (AEs) in AUD patients are summarized in Table 64.5. Symptoms usually disappear with dose reduction. Due to these AEs resulting in a decrease in alertness, patients should always be cautioned that driving, operating heavy machinery, and other activities could be hazardous. Severe sedation has been reported for very high doses

VII. TREATMENTS, STRATEGIES AND RESOURCES

CONTROVERSIES IN THE TREATMENT OF ALCOHOL USE DISORDER WITH HIGH DOSES OF BACLOFEN

TABLE 64.5 List of Adverse Reactions Reported With the Use of Baclofen in AUD Patients (by Frequency) SERIOUS ADVERSE REACTIONS • • • • • • • • •

Confusion Convulsions/seizures Severe sedation Agitation Hallucinations Falls Disinhibition Disorientation Coma

629

abnormalities and supraventricular tachyarrhythmia (Leung et al., 2006). No antidotes have yet been studied however in case of acute intoxication, hemodialysis was reported as an effective means of treatment (Brvar et al., 2007; d’Aranda, Lacroix, Cotte, Cungi, & Meaudre, 2013). Teratogenic effects have been described in baclofenexposed pregnant women (Bernard et al., 2012) with an increased risk of malformation (central nervous system and gastrointestinal). In female AUD patients, given the risk of fetal alcohol syndrome, treatment should only be considered during pregnancy if the benefits clearly outweigh the potential risks to the fetus.

“NONSERIOUS” ADVERSE REACTIONS • • • • • • • • • • • • • • • •

Somnolence Sleep disorder Asthenia Dizziness Headache Anxiety Paresthesia Nausea Diarrhea Tinnitus Muskuloskeletal pain Muscle spasms Hyperhydrosis Arthralgia Dry mouth Decreased appetite

CONTROVERSIES IN THE TREATMENT OF ALCOHOL USE DISORDER WITH HIGH DOSES OF BACLOFEN

of baclofen and when there was a concomitant use of alcohol (Leung, Whyte, & Isbister, 2006) other sedative drugs (Lanoux, Lebrun, Andreu, Just, & Mateu, 2014) or renal impairment (Reichmuth, Blanc, & Tagan, 2015). Delirium and seizures have been reported in case of abrupt discontinuation of the treatment; therefore, if discontinuation is needed, the dose should be reduced slowly to minimize the risk of developing withdrawal syndrome (Agabio, Preti, & Gessa, 2013). Deaths have been reported in the context of massive overdoses (doses higher than 1000 mg/day) (Fraser, MacNeil, & Isner, 1991). Cases of baclofen-induced mania were reported in psychiatric patients and symptoms usually clear spontaneously after baclofen discontinuation (Geoffroy et al., 2014) (Table 64.5). Although some unusual cases of baclofen abuse have been reported, baclofen abuse potential is very low, and no subject in any of the clinical studies has reported craving for baclofen. Apart from subjects with depressive disorders and stable antidepressant therapy, subjects treated for other psychiatric comorbidities or a history of seizure have always been systematically excluded from clinical trials. Signs and symptoms of baclofen overdose as reported in clinical case studies may include vomiting, muscular hypotonia, drowsiness, accommodation disorders, coma, respiratory depression, and seizures, cardiac conduction

Off-label prescribing practices of high-dose baclofen emerged and developed primarily in France after the publication in 2008 of Olivier Ameisen’s book The End of my Addiction (Ameisen, 2008). Ameisen was an alcohol-dependent physician who in this book related his own experience with baclofen up to 270 mg/day to treat his dependence. Its exceptional media coverage contributed significantly to the rapid increase in the off-label use of high-dose baclofen in France among general practitioners and addiction specialists. Following this publication, patient’s groups, as well as physician’s organizations, have emerged to support and defend the off-label prescription of high-dose baclofen. Many websites and online forums of drinkers and former drinkers have praised the “miraculous” effect of baclofen and its alleged safety. As a consequence, between 2008 and 2012, baclofen’s sales in France increased by more than 52%. Since then, patients have been treated with off-label baclofen essentially with an objective of progressive drinking reduction. In 2012 the French regulatory agency authorized a “case by case” prescription, formalized in March 2014, with a temporary recommendation for use (RTU) of baclofen for the treatment of AUD after all other treatments had failed. This regulatory framework was granted pending the results of two ongoing clinical trials that were aiming to secure access to baclofen for the treatment of AUD in France (Jaury et al., 2016; Reynaud et al., 2017). Under this initial RTU, baclofen was the subject of a monitoring protocol to collect efficacy and safety data via an electronic portal where data had to be reported by doctors who prescribed baclofen under the RTU protocol. A maximum dose of 300 mg/day was permitted, in the indication of maintenance of abstinence or reduction of alcohol consumption. Baclofen had to be proposed as a second-line treatment after the failure of other

VII. TREATMENTS, STRATEGIES AND RESOURCES

630

64. USE OF BACLOFEN IN ALCOHOL USE DISORDER: A CLINICAL APPROACH

approved treatments for maintenance of abstinence (acamprosate and naltrexone) or the reduction in alcohol consumption (nalmefene). Patients with other addictions or psychiatric disorders, such as bipolar disorder, psychosis, and depression, were excluded from the RTU. A second medical opinion for doses higher than 120 mg/day and a peer evaluation for doses higher than 180 mg/day were required. In December 2014, more than 120,000 patients were treated with baclofen in France for AUD. In March 2017, the French regulatory agency renewed the baclofen RTU for 1 year and at that time more than 100,000 patients were still being treated. In June 2017, a pharmacoepidemiological study (ANSM Report, 2017) using databases from the French health insurance reported a doubling of the death rate with high doses of baclofen leading to the revision of the RTU with a dose limitation to 80 mg/ day (ANSM RTU, 2017). This decision was motivated by the fact that 80% of the 213,000 French patients treated with baclofen between 2009 and 2015 had received dosages lower than 80 mg/day and this was associated with the observation of a dramatic increase in the risk of hospitalization (15%) and death (50%) for doses ranging from 75 to 180 mg/day and 46% and over 120% for dosages higher than 180 mg/day. Braillon and Naudet (2017) even suggested that based on the nonreproducibility of the results across all of the RCTs and because of the serious AEs described in the ANSM report, there was, in fact, no reason to maintain the baclofen RTU.

CONCLUSIONS AND OUTLOOK Baclofen, in the past 10 years, has attracted considerable interest, especially in Europe, probably in response to the expectations of both patients and physicians. Baclofen was also the first medication, long before nalmefene, to target harm-reduction as its primary goal through a reduction in alcohol consumption. Preclinical data provide a strong basis for baclofen as a pharmacotherapy to suppress alcohol drinking, alcohol reinforcing, and motivational properties; however, contradictory findings as well as serious AEs and poor tolerance especially with high doses (ANSM Report, 2017) do not support the use of baclofen as a first-line agent for the treatment of AUD. Overall, the available evidence in the literature supports that baclofen doses lower than 80 mg/day are safe and well-tolerated. Since the occurrence of serious AEs are more frequent with the use of high doses of baclofen, it is highly recommended that high doses of baclofen should only be prescribed after an assessment of the benefit/risk balance and then closely monitored by an

experienced physician, with the aim of individually adjusting the effective minimum dose for which the expected effect is reached. The use of high-dose baclofen remains a controversial point due to the risk of serious drug reactions, overdoses, and risks associated with baclofen withdrawal syndrome. When used with the goal of reducing alcohol consumption, additive sedative effects of baclofen and alcohol may also pose significant safety risks. Further studies are required to improve the understanding of the differences in the speed of response to baclofen therapy and could lead to a tailored dosage regimen, avoiding the use of high-dose baclofen (and the risks of AEs related to these high doses) in patients who do not need these high doses. Given the lack of other effective pharmaceutical treatments on the long-term and the minimal hepatic metabolism of baclofen, the use of low-dose baclofen (,80 mg/day) may be an interesting choice for the treatment of specific subtypes of patients, especially those with severe comorbidities, such as liver damage or alcoholic liver disease, since most of the available medications are contraindicated due to their hepatic metabolism.

MINI-DICTIONARY OF TERMS Alcohol use disorder A chronic relapsing brain disease characterized by the compulsive use of alcohol, loss of control over alcohol consumption, and a negative emotional state when not using. Adverse effect An unexpected medical problem that happens during treatment with a drug or other therapy. Craving An intense desire or urge to consume a substance, in this case, alcohol. Temporary recommendation for use A regulatory framework created by the ANSM allowing off-label use for specific indications under mandatory patient registration in a national database.

KEY FACTS Alcohol-Induced Liver Disease (AILD) • AILD is caused by excessive consumption of alcohol. • There are three main stages of AILD: fatty liver disease, alcoholic hepatitis, and cirrhosis of the liver. • Cirrhosis of the liver is the most serious form of AILD and a cause of many deaths and serious illnesses. • The most effective way to prevent AILD is to stop drinking alcohol or stick to the recommended limits. • Liver transplantation may be required in severe cases where the liver has stopped functioning, and when no improvement is observed when the patient quits drinking alcohol.

VII. TREATMENTS, STRATEGIES AND RESOURCES

REFERENCES

SUMMARY POINTS • Baclofen is not an approved medication for the treatment of AUD. • Due to its short half-life, baclofen should be administered three to four times per day. Such frequent dosing is invonvenient and increases the risk of medication nonadherence. • Dosage should be individualized with a 15 mg/day starting dose and, if needed, should be increased in 15 mg increments until the desired effect is achieved. • Effect is dose-dependent with considerable interindividual variability. • The most common reported AEs are sedation or somnolence, weakness, and dizziness. These AEs are reversible with dose reduction and exacerbated by concurrent alcohol use. • Rare, but serious, AEs have been described with high doses; their occurrence increases with the dose. • In case of severe intoxication, there is no specific antidote. • Available data suggest that low-dose baclofen is safe and well-tolerated at doses up to 80 mg/day and may help maintain abstinence and prevent relapse in patients with alcoholic liver disease for whom other drugs are not safe or practical. • Safety of doses higher than 80 mg/day in AUD patients is not yet clearly demonstrated. • Clinical trials results with high-dose baclofen are contradictory and do not support routine use. • Prior to prescription, a close evaluation of the benefit/risk balance and careful medical supervision by an experienced physician must be undertaken.

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Krupitsky, E. M., Burakov, A. M., Ivanov, V. B., Krandashova, G. F., Lapin, I. P., Grinenko, A. J., & Borodkin, Y. S. (1993). Baclofen administration for the treatment of affective disorders in alcoholic patients. Drug and Alcohol Dependence, 33(2), 157 163. Lanoux, T., Lebrun, D., Andreu, P., Just, B., & Mateu, P. (2014). Baclofen poisoning. Toxicologie Analytique et Clinique, 26(4), 206 207. Leung, N. Y., Whyte, I. M., & Isbister, G. K. (2006). Baclofen overdose: defining the spectrum of toxicity. Emergency Medicine Australasia, 18(1), 77 82. Lorrai, I., Maccioni, P., Gessa, G. L., & Colombo, G. (2016). r (1)-Baclofen, but not s (2)-Baclofen, alters alcohol selfadministration in alcohol-Preferring rats. Frontiers in psychiatry, 7, 68. Marsot, A., Imbert, B., Alvarez, J. C., Grassin-Delyle, S., Jaquet, I., Lanc¸on, C., & Simon, N. (2014). High variability in the exposure of baclofen in alcohol-dependent patients. Alcoholism: Clinical and Experimental Research, 38(2), 316 321. Morley, K. C., Baillie, A., Leung, S., Addolorato, G., Leggio, L., & Haber, P. S. (2014). Baclofen for the treatment of alcohol dependence and possible role of comorbid anxiety. Alcohol and Alcoholism, 49(6), 654 660. Mu¨ller, C. A., Geisel, O., Pelz, P., Higl, V., Kru¨ger, J., Stickel, A., . . . Heinz, A. (2015). High-dose baclofen for the treatment of alcohol dependence (BACLAD study): A randomized, placebo-controlled trial. European Neuropsychopharmacology, 25(8), 1167 1177. Ohtsuki, S., Asaba, H., Takanaga, H., Deguchi, T., Hosoya, K. I., Otagiri, M., & Terasaki, T. (2002). Role of blood brain barrier organic anion transporter 3 (OAT3) in the efflux of indoxyl sulfate, a uremic toxin: Its involvement in neurotransmitter metabolite clearance from the brain. Journal of Neurochemistry, 83(1), 57 66. Ponizovsky, A. M., Rosca, P., Aronovich, E., Weizman, A., & Grinshpoon, A. (2015). Baclofen as add-on to standard psychosocial treatment for alcohol dependence: a randomized, doubleblind, placebo-controlled trial with 1 year follow-up. Journal of Substance Abuse Treatment, 52, 24 30. Reichmuth, P., Blanc, A. L., & Tagan, D. (2015). Unintentional baclofen intoxication in the management of alcohol use disorder. BMJ Case Reports, 2015. Available from https://doi.org/10.1136/bcr2015-212187. Reynaud, M., Aubin, H. J., Trinquet, F., Zakine, B., Dano, C., Dematteis, M., . . . Detilleux, M. (2017). A randomized, placebo-controlled study of high-dose baclofen in alcohol-dependent patients—The ALPADIR study. Alcohol and Alcoholism, 52(4), 439 446. Witczuk, B., Khaunina, R. A., & Kupryszewski, G. (1980). 3(p-Chlorophenyl)-4-aminobutanoic acid--resolution into enantiomers and pharmacological activity. Polish Journal of Pharmacology and Pharmacy, 32(2), 187 196. Yamini, D., Lee, S. H., Avanesyan, A., Walter, M., & Runyon, B. (2014). Utilization of baclofen in maintenance of alcohol abstinence in patients with alcohol dependence and alcoholic hepatitis with or without cirrhosis. Alcohol and Alcoholism, 49(4), 453 456.

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C H A P T E R

65 Baclofen-Induced Neurotoxicity 1

Magali Chartier1, Lucie Chevillard1 and Bruno Me´garbane2

INSERM UMRS-1144, Paris-Descartes University, Paris, France 2Department of Medical and Toxicological Critical Care, Lariboisie`re Hospital, INSERM UMR-S1144, Paris-Diderot University, Paris, France

LIST OF ABBREVIATIONS ANSM

BBB CNS GABA LNAA NMDA NTS SLC t1/2 TE TI

alterations. The present review aims to: (1) question baclofen effectiveness at high dose to treat ethanol dependence; (2) characterize baclofen-attributed neurotoxicity at therapeutic doses and in overdose; and (3) describe management of neurological features in baclofen poisoning.

(Agence Nationale de Se´curite´ du Me´dicament et des Produits de Sante´) The French National Agency for Medicines and Health Products Safety blood brain barrier central nervous system γ-aminobutyric acid large neutral amino acid N-methyl-D-aspartate nucleus of the solitary tract solute carrier half-life expiratory time inspiratory time

BACLOFEN PRESCRIPTION FOR ETHANOL ABSTINENCE

INTRODUCTION Baclofen, 4-amino-3-(p-chlorophenyl)-butanoic acid, a structural analog of γ-aminobutyric acid (GABA) is a selective agonist of the metabotropic GABAB-receptor. Baclofen activates the GABAB-receptors on the presynaptic neurons, decreasing neurotransmitter release by inhibiting the Ca21 channels (Kumar, Sharma, Kumar, & Deshmukh, 2013). Approved since the 1970s worldwide for the treatment of spasticity in various neurological conditions, baclofen has been increasingly used at high doses (up to 300 mg/day) to manage ethanol dependence, especially in France starting as off-label prescriptions (Boels et al., 2017; Franchitto, Pelissier, Lauque, Simon, & Lanc¸on, 2014; Kumar et al., 2013). Consequently, the number of poisonings has markedly increased, in relation to accidental or suicidal ingestions (Pelissier et al., 2017; Weiβhaar et al., 2012). Baclofen overdose is responsible for life-threatening neurotoxicity including consciousness impairment, respiratory depression and electroencephalogram (EEG)

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00065-9

Ethanol chronically used at elevated doses, that is, .20 g/day for women and .40 g/day for men (World Health Organization [WHO], 2000), is responsible for major health problems worldwide. Despite the absence of solid evidence to support its efficiency, baclofen has been increasingly used at high doses to facilitate abstinence in chronic alcoholics (Liu & Wang, 2017; Reynaud et al., 2017). GABAB-receptors are widely distributed in the brain including the ventral tegmental area of the mesolimbic reward system. GABAB-receptor activation suppresses the dopaminergic transmission to the nucleus accumbens, a key brain area involved in the development and maintenance of alcohol dependence (Addolorato, Leggio, Agabio, Colombo, & Gasbarrini, 2006). Recent open-label as well as double-blinded studies suggested the potential of high-dose baclofen to reduce ethanol daily intake down to abstinence and to prevent ethanol withdrawal manifestations and relapse (Addolorato et al., 2002; Mu¨ller et al., 2015). However, no convincing, definitive evidence exists and the lastpublished randomized, placebo-controlled study did not demonstrate the superiority of baclofen in the maintenance of abstinence in alcohol-dependent patients, but showed only a tendency towards a reduction in alcohol

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© 2019 Elsevier Inc. All rights reserved.

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consumption and significantly decreased craving for alcohol in favor of baclofen (Reynaud et al., 2017). In France, following the publication in 2008 of Le Dernier Verre (The Last Glass), a book by Amsein (2008) reporting the successful self-management of his alcohol dependence with extremely high-dose baclofen (up to 270 mg/day), off-labeled prescriptions exponentially increased with an estimated 213,000 treated patients between 2009 and 2015 (ANSM, 2017a). Consequently, in March 2014, the French National Agency for Medicines and Health Products Safety decided on a 3-year temporary authorization of use for baclofen treatment of ethanol dependence up to a maximal dose of 300 mg/day, reduced in 2017 to 180 mg/day. Authorized doses were far higher than doses to treat muscle spasticity (30 80 mg/day) (Food & Drug Administration, 2017). No other country has approved high-dose baclofen to treat ethanol dependence. Consistently, elevated doses of baclofen may be responsible for adverse effects and pharmacokinetic alterations that are still under consideration.

BACLOFEN PHARMACOKINETICS Pharmacokinetic parameters after oral administration of single low doses of baclofen to healthy volunteers are presented in Table 65.1. Baclofen metabolism is shown in Fig. 65.1. Baclofen pharmacokinetics has been also characterized in alcohol-dependent patients receiving high-doses (30 240 mg/day), based on a population modeling approach using one-compartment linear model and first-order absorption (Marsot et al., 2014). At a high dose, the volume of distribution (1.2 L/kg) and half-life (t1/2, 5,6 hours) are increased while the TABLE 65.1

total clearance remains similar to the values obtained with lower doses. The observed large interindividual variability in clearance and volume of distribution suggests that the same dose may not lead to the same exposure. However, neither the demographics (age, body weight, height, and gender) nor the usual biological covariates (creatinine, urea, transaminases, albumin, and liver enzymes) or the tobacco consumption seem to explain such variability. The intestinal absorption of baclofen is mediated by the Large Neutral Amino Acid (LNAA, SLC 7A5) and by the β-amino acid (SLC 6A6) transporters (Moll-Navarro, Merino, Casabo, Nacher, & Polache, 1996). At the blood brain barrier (BBB), the passive diffusion of baclofen is negligible due to its physicochemical properties (Deguchi et al., 1995). Baclofen distribution was suggested to be regulated by influx systems, mainly involving the LNAA transporter (Van Bree, Audus, & Borchardt, 1988). Baclofen distribution is also strongly restricted by efflux systems, most likely probenecid-sensitive organic anion transporters. These transport mechanisms possibly explain baclofen’s slow distribution to its targets and its delayed onset of effects. Moreover, baclofen may be secreted at the renal barrier as well by a probenecid-sensitive organic anion transporter system (Wuis, Dirks, Termond, Vree, & Van der Kleijn, 1989). Some of these transporters exhibit Michaelis-Menten properties and are potentially saturable at high doses. Additionally, these transporters may be inducible following the administration of repeated doses. Observations suggest that chronic baclofen administration results in marked modifications in its metabolism and transport mechanisms.

Plasma Pharmacokinetic Parameters After Oral Administration of Low-Dose Baclofen Pharmacokinetic parameters

Absorption

Cmax 5 180, 340, and 650 ng/mL after oral administration of 10, 20, Fast and complete absorption in the gastrointestinal tract and 30 mg Tmax 5 60 90 min

Distribution VD 5 0.7 L/kg Binding rate to plasma protein 5 30%

Cerebrospinal fluid concentrations 8.5 times lower than in blood

Metabolism Restricted metabolism by deamination in β-(p-chlorophenyl)-4-hydroxybutiric acid, the major and pharmacologically inactive metabolite This metabolite can be further glucuronoconjugated. Excretion

t1/2 5 3 4 h Cl 5 140 mL/min/kg

Mostly unchanged eliminated by renal filtration and tubular secretion

Cmax, peak plasma concentration; Tmax, time of peak concentration; VD, volume of distribution; t1/2, elimination half-life; Cl, total clearance.

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BACLOFEN-RELATED ADVERSE EFFECTS AT THERAPEUTIC DOSES

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FIGURE 65.1 Baclofen metabolism. Baclofen, 4-amino-3-(p-chlorophenyl)butanoic acid, is metabolized in 4-hydroxy3-(p-chlorophenyl)-butanoic acid which is the major metabolite, by deamination. This metabolite can be further glucuronoconjugated in 4-glucurono-3-(p-chlorophenyl)butanoic acid.

TABLE 65.2

Baclofen-Related Neuropsychiatric Adverse Effects Adverse effects

Nervous system manifestations

Psychiatric manifestations

.10%: Sedation, somnolence, sleep disorders, insomnia, asthenia, dizziness, headaches, paresthesia ,10%: Alertness disorders, withdrawal syndrome, seizures, tinnitus, vertigo, muscle pain, tremor, dysarthria, diplopia, rigidity, nystagmus, dystonia .10%: Anxiety, confusion, increased libido, memory lapses ,10%: Euphoria, excitation depression, fall, suicidal ideation, reduced libido, hypomania, hallucinations

BACLOFEN-RELATED ADVERSE EFFECTS AT THERAPEUTIC DOSES Several clinical studies and pharmacovigilance networks have assessed baclofen safety including at high doses in alcohol-dependent patients (Mu¨ller et al., 2015; Rigal et al., 2015; Rolland et al., 2017). Side effects were reported to be mild and usually easily manageable (Table 65.2). Toxicity usually occurs at the beginning of the treatment or during the titration period, mostly if doses are excessively high and if gradual titration to the targeted dose is too rapid. Although symptoms are generally transient and disappear spontaneously while continuing therapy, they can be lowered or repressed through a dosage reduction and a slow-down upward titration. They last over the treatment period, but usually do not need the end of the treatment. The majority of patients treated with high doses of baclofen experience at least one adverse effect. The most common toxicity involves the nervous system and psychiatric functions and occurs at dosages ranging from 30 to 300 mg/day. It includes sedation, sleep disorders, asthenia and dizziness, reported by at least 60% of the patients (Mu¨ller et al., 2015; Reynaud et al., 2017; Rigal et al., 2015). Severe adverse effects may require hospitalization due to falls, suicidal ideation, depression, or overdose. As baclofen is mainly eliminated by kidneys, patients with impaired renal function are

particularly at risk of side effects owing to accumulation. Patients with psychiatric comorbidities require close surveillance. Baclophone, a current French pharmacovigilance study, should provide more information on adverse effects incidence and severity in order to characterize baclofen security profile when treating alcohol dependence (Rolland et al., 2017). Side effects are dose-dependent and usually appear at doses of .80 mg/day. Because of the early occurrence of tolerance, they persist extremely rarely during the treatment except from sweating, alertness disorders, and anxiety (Reynaud et al., 2017; Rigal et al., 2015). Interestingly, preclinical investigations confirmed the development of tolerance to baclofen-induced side effects when repeatedly administered. Consistently, tolerance to baclofen-induced sedative effects was observed following chronic treatment in rats (Bains & Ebenezer, 2013). Moreover, rats treated with high-dose baclofen three times per day exhibited tolerance to the usual baclofen-related locomotor and functional effects (Beveridge, Smith, & Porrino, 2013). Development of tolerance is explained by the desensitization of GABABreceptors in different brain areas as demonstrated with the suppression of GABAB-stimulated GTPγS binding following chronic baclofen treatment (5 mg/kg, t.i.d. for 5 days) in rats (Keegan et al., 2015). Desensitization was not accompanied with modification of GABAB subunits mRNA levels (Sands, Mc Carson, & Enna, 2003). Further experiments failed to show alterations in the

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number or affinity of GABAB-receptor binding sites and protein levels following baclofen injections during 14 days in rats (Lehmann, Mattson, Edlund, Johansson, & Ekstrand, 2003). Baclofen seems, therefore, able to induce tolerance through mechanisms other than GABAB-receptor downregulation. Nonetheless, 21 days of systemic baclofen administration in rats was demonstrated to reduce GABAB-receptor density and number of binding sites suggesting more likely receptor downregulation, posttranscriptional degradation or internalization (Beveridge et al., 2013; Malcangio, Da Silva, & Bowery, 1993). Abrupt cessation of high-dose baclofen treatment results in withdrawal syndrome (Table 65.3) (Peng et al., 2008; Richter, Baldovini, Blasco, Leone, & Albanese, 2016). Clinical manifestations include hallucinations, agitation, disorientation, delirium, paranoid ideation, confusion, psychosis, seizures, bradycardia, and hypotension. Patients may even develop hypertonia, dyskinesia, and high fever mimicking neuroleptic malignant syndrome. Symptoms completely reverse after baclofen reintroduction. These observations are consistent with preclinical studies demonstrating hind limb hyperreflexia and increased magnitudes in hind limb electromyogram following the sudden cessation of chronic baclofen treatment (Priano et al., 2011; TABLE 65.3 Syndrome

Wang, Bose, Parmier, & Thompson, 2002). Recently, baclofen discontinuation in repeatedly baclofen-treated rats was shown to result in hyperlocomotion and nonanxiogenic withdrawal symptoms (Chartier et al., 2018). The mechanism of baclofen withdrawal is not fully understood. Imbalance between the GABA and dopamine systems in the mesolimbic and nigrostriatal regions has been suggested, explaining the occurrence of neuropsychiatric manifestations (Peng et al., 2008). Onset of baclofen-induced anxiety during withdrawal remains controversial (Mu¨ller et al., 2015). Baclofen may display anxiolytic effects reflecting GABAB-receptor activation within the amygdala, involved in anxiety, memorization of pleasure feelings and therefore paramount for alcohol relapse (Kumar et al., 2013). To prevent withdrawal syndrome in humans, prescribers should decrease the dosage of baclofen incrementally over a period of at least two weeks.

BACLOFEN-RELATED NEUROTOXICITY IN OVERDOSE Although clinical studies showed that high-dose baclofen can be used with manageable side effects (Kiel, Hoegberg, Jansen, Petersen, & Dalhoff, 2015;

Features of Baclofen-Related Toxicity in Overdose and Withdrawal

Baclofen intoxication baclofen

Baclofen withdrawal

Somnolence, stupor or drowsiness (B25%)

Somnolence, stupor or coma

Coma (Glasgow score ,8) (B18%) Agitation (B20%)

Agitation

Epileptic seizures

Epileptic seizures

Flaccid tetraparesis

Rebound increase in spasticity

Areflexia

Hyperreflexia Malignant neuroleptic syndrome Delirium

Mydriasis (B12%) or myosis (B10%) EEG impairment Brain death-like presentation Respiratory failure

Respiratory failure

Arterial hypotension (B10%)

Arterial hypo- or hypertension

Tachycardia (B5%) Fever

Fever

Nausea, dizziness Aspiration pneumonia (B8%)

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BACLOFEN-RELATED NEUROTOXICITY IN OVERDOSE

Mu¨ller et al., 2015; Reynaud et al., 2017; Rigal et al., 2015), the French health authorities reported dosedependent risk of hospitalization (15% and 46% increase at 75 180 and .180 mg daily doses, respectively) and death (1.5-fold and 2.27-fold increase for the same dose intervals) as compared to other approved medications used to treat ethanol dependence (ANSM, 2017b). Clinical presentation of baclofen overdose mainly includes impaired consciousness resulting in deep coma occurring rapidly after ingestion (Table 65.3). Generalized hypotonia and pupilar and limb areflexia are usually present (Franchitto et al., 2014; Pelissier et al., 2017; Peng et al., 2008). These manifestations are consistent with preclinical studies showing dosedependent sedative effects and decrease in functional brain activity following high-dose baclofen administration in rats (Bains & Ebenezer, 2013; Beveridge et al., 2013; Chartier et al., 2018). GABAB-receptor activation results in central nervous system (CNS) depression secondary to the inhibition of excitatory neurotransmitter release (Boutte, Vercueil, Durand, Vincent, & Alvarez, 2006). Moreover, high doses of baclofen were shown to reduce locomotor activity in rats, thus indicating inhibition of the dopaminergic neurons in the substantia nigra by presynaptic GABAB-receptors (Beveridge et al., 2013). Rat investigations revealed the suppression of hind limb stretch reflex activity and velocity-dependent decrease in ankle torque, in correlation with reduction in electromyogram magnitude (Oshiro et al., 2010; Wang et al., 2002). These findings clearly support baclofen use as muscle relaxant inhibiting alpha-motoneurons that stimulate peripheral muscles within the spinal cord. Baclofen-poisoned patients present severe EEG abnormalities that may even lead to mistaken diagnosis of brain death (Sullivan, Hodgman, Kao, & Tormoehlen, 2012). Toxicity is responsible for rapidonset encephalopathy characterized by slowing down in the background activity together with paroxysmal activity, periodic spike waves and biphasic and triphasic complexes (Boutte et al., 2006). Characteristic patterns include periodic spike waves organized in repeated discharges or generalized rhythmic slow poly-spike wave complexes, occasioning nonconvulsive status epilepticus patterns (Kumar, Sahaya, Goyal, Sivaraman, & Sahota, 2010; Weiβhaar et al., 2012). Baclofen displays proconvulsive effects supporting an imbalance between the GABAergic and glutamatergic systems. However, the exact mechanisms by which baclofen promote epileptogenesis remains unclear. It has been assumed that it may exert complex regulatory action on these two previous systems, mediated by the presynaptic and

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postsynaptic GABAB-receptors (Boutte et al., 2006). In more severe cases, burst-suppression patterns usually nonreactive to nociceptive stimuli, and isoelectric patterns mimicking brain death accompanied by the disappearance of stem reflexes may be observed (Kumar et al., 2010; Sullivan et al., 2012). Fortunately, patients improve rapidly and regain consciousness. EEG patterns spontaneously normalize within a few days with a progressive enrichment in the background activity. Baclofen intoxication is responsible for respiratory depression characterized by bradypnea resulting in hypercapnic acidosis and hypoxemia (Franchitto et al., 2014; Pelissier et al., 2017; Weiβhaar et al., 2012). Respiratory manifestations support the involvement of baclofen-sensitive GABAB-receptors in the control of central respiration, in particular in the bulbar and pontine structures of the brain stem. Within the pneumotaxic centers, presynaptic GABAB-receptor activation decreases glutamate release preventing the glutamate N-methyl-D-aspartate (NMDA) and non-NMDA receptors stimulation on inspiratory neurons. Experimental data evidenced that the timing of respiratory phases exclusively depends on NMDA receptors whereas the amplitude of the phrenic discharges mainly depends on non-NMDA receptors. Furthermore, GABAB-receptors may be directly involved in the control of respiratory neuronal discharge (Pierrefiche, Foutz, & DenavitSaubie´, 1993). High-doses of baclofen administered intravenously were demonstrated to reduce the amplitude of phrenic nerve discharge leading to apnea and to alter the inspiratory off-switching mechanism in cats. However, chemosensitivity is preserved resulting in increase in phrenic discharge in response to increased level of CO2 (Pierrefiche et al., 1993). Baclofen induces a large selective lengthening in inspiratory time (TI) without significant simultaneous change in expiratory time (TE) in rats and cats (Pierrefiche et al., 1993; Seifert & Trippenbach, 1998). Baclofen injection in the nucleus of the solitary tract (NTS) situated in the bulbar pneumotaxic center, modulates the Hering-Breuer inflation and deflation reflexes in rats. NTS, where vagal afferences fibers converge from the lungs, is involved in the automatic control of respiratory volume affecting thus inspiratory and expiratory phases. Although baclofen suppresses the Hering-Breuer expiratory-promoting (TE-promoting) reflex, the Hering-Breuer inspiratoryinhibitory (TI-inhibitory) and deflation reflexes are attenuated but not abolished. These observations are consistent with the distinct medullary pathways controlling the reflexes and the respiratory time phases. TI-promoting reflex is mediated exclusively by highthreshold receptors activation with all-or nothing response whereas TE-promoting reflex depends on either

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high-threshold and low-threshold receptors activation (Seifert & Trippenbach, 1998). The GABAB-receptorsmediated central control of TI and TE may be similar to that of opioid receptors-mediated control. Much higher concentrations are required to prolong TE than those necessary for TI (Chevillard et al., 2010). The difference in effects on TI and TE and on the Hering-Breuer reflexes also suggests disparities in GABAB-receptors distribution in the respiratory neuronal network. Moreover, the lack of difference between two consecutive breaths indicates absence of vagal, rapidly adapting pathways contributing to the transient effects of lung deflation. GABAB-receptors may also be involved in the medullary pathway of vagal fibers mediating instantaneous reflex of lung deflation (Seifert & Trippenbach, 1998). Baclofen-related muscle relaxing effects may additionally target inspiratory muscles resulting in changes in respiratory time phases. Recently, tolerance to baclofen-induced respiratory effects was demonstrated after prior repeated administration in rats; tolerant rats did not exhibit respiratory depression following baclofen overdose due to limitations on baclofeninduced increase in TI and TE, resulting in only slight hypoxemia without respiratory acidosis (Chartier et al., 2018). In addition to neuropsychiatric manifestations in baclofen poisonings, patients develop autonomic CNS disturbances like bradycardia or tachycardia, hypotension or hypertension, and miosis or mydriasis (Boutte et al., 2006; Pelissier et al., 2017). Hypothermia is sometimes observed, due to GABAB-receptor activation in the temperature-controlling centers of the hypothalamus (Arbouw, Hoge, Meulenbelt, & Jansman, 2014; Lehmann et al., 2003).

ALTERATIONS IN BACLOFEN PHARMACOKINETICS IN OVERDOSE As compared to therapeutic doses, baclofen pharmacokinetics in overdose is modified including delayed absorption together with rebound in plasma concentrations, increased volume of distribution (2.4 L/kg), enhanced total clearance (360 mL/min), and mildly prolonged half-lives (6 10 hours) despite normal renal function (Anderson & Nohe´r Swahn, 2008; Cleophax et al., 2015). Therapeutic serum baclofen concentrations are usually included in the range of 80 400 ng/mL concentrations .1100 ng/mL are considered toxic while concentrations .8000 ng/mL were frequently associated with fatalities (Cleophax et al., 2015; Weiβhaar et al., 2012). Studies reported that plasma concentrations in baclofen-poisoned patients decrease more rapidly than the toxic neurorespiratory features such as electroencephalographic abnormalities, coma, and respiratory

depression (Rochart, Berger, Brochet-Paille, Poiron, & Chillet, 2012). Prolonged CNS depression may, thus, persist even when plasma baclofen concentrations fall down within or under the therapeutic range. Baclofen was suggested to be eliminated more slowly from the CNS than from blood leading, therefore, to prolonged effects. Long-lasting baclofen concentrations in the brain are consistent with the involvement of transportermediated mechanism at the BBB (Franchitto et al., 2014; Weiβhaar et al., 2012). Baclofen plasma levels are consequently not correlated to the extent of CNS toxic effects. Since the exact timing of baclofen ingestion is usually unknown, prolonged medical supervision is clinically relevant (Rochart et al., 2012).

MANAGEMENT OF THE BACLOFENPOISONED PATIENT Baclofen poisoning usually requires rapid admission to the intensive care unit. Symptoms progress very fast and toxicity is observed even with doses as low as 150 mg (Franchitto et al., 2014; Kiel et al., 2015; Le´ger, Brunet, Le Roux, Lerolle, & Boels, 2017). Management is mainly supportive since no antidote is available. Gastrointestinal decontamination based on activated charcoal administration may be considered if performed early after ingestion (,2 hours). Due to the rapid onset of baclofen-induced CNS depression, patients require tracheal intubation for airway protection and respiratory support by invasive mechanical ventilation. Length of ventilation is correlated with the ingested dose (Spearman coefficient: 0.48; P , .001) (Pommier et al., 2014). Although controversial in the literature, intermittent hemodialysis, continuous hemodialysis, or hemofiltration may be considered to enhance baclofen elimination, but only in renal failure patients (Me´garbane, Labat, & Decle`ves, 2016). Extracorporeal enhancement of baclofen elimination seems unnecessary if renal function is preserved in the poisoned patient. Hopefully, despite severe features, baclofen poisoning outcome generally remains good, with complete recovery, although fatalities have been described, even after hospital admission (Addolorato et al., 2006; Weiβhaar et al., 2012). However, in comparison to nonbaclofen poisonings, baclofen poisoning was associated with more frequent aspiration pneumonitis (29% vs 2%; P 5 .005), more frequent mechanical ventilation—adjusted relative risk of 7.9 (1.4 43.5; P 5 .02—and higher frequency of death (2.6% vs 0.1%, P 5 .02) (Pommier et al., 2014).

CONCLUSIONS Baclofen may be responsible for mild neurological adverse effects at therapeutic doses, but life-threatening

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REFERENCES

toxicity in overdose. High doses of baclofen, as prescribed for ethanol abstinence, are associated with dose-dependent, increased risk of hospitalization, severe neurological complications requiring mechanical ventilation, and death, compared to the currently approved medications in the treatment of alcohol dependence and, more broadly, to other psychotropic drugs. Thus, physicians should be aware of the potential risks of baclofen when deciding to prescribe it to chronic alcoholics to facilitate ethanol abstinence.

• GABAB-receptors are widely distributed within the brain including the ventral tegmental area of the mesolimbic reward system. • GABAB-receptor activation suppresses the activity of mesolimbic dopaminergic neurons and dopaminergic transmission to the nucleus accumbens, a key brain area involved in the development and maintenance of alcohol dependence.

SUMMARY POINTS MINI-DICTIONARY OF TERMS Pharmacokinetics The study of the time-course of a drug in the body, including processes of absorption, distribution, biotransformation (metabolism), excretion, and transport. Pharmacovigilance Defined as the activity aiming to register, to assess and prevent adverse effects of drugs in order to secure their prescription and use. Tolerance When patients experience a reduced effect of a drug following prolonged treatment. It requires an increase of the drug dose to obtain the same therapeutic effect. Respiratory depression Characterized by reduced respiratory rate (,12/min), called bradypnea and/or a reduced tidal volume resulting in insufficient ventilation to maintain adequate gas exchange and, thus, leading to hypoxemia, hypercapnia, and respiratory acidosis. Hering-Breuer reflexes Includes inflation reflex preventing overdistension of the lungs, and deflation reflex triggered to shorten exhalation. Withdrawal syndrome Unpleasant physical and psychological effects resulting from an abrupt discontinuation of a drug able to induce dependence.

• Baclofen is a selective GABAB-receptor agonist. • Baclofen is extensively prescribed at high doses to maintain ethanol abstinence in chronic alcoholics. • Neurological adverse effects are frequent but mild and disappear with tolerance development. • Withdrawal syndrome after baclofen cessation includes hallucinations and encephalopathy. • Neurotoxicity in overdose may be life-threatening including consciousness impairment, respiratory depression, and characteristic electroencephalography patterns. • Baclofen overdose is responsible for increased dosedependent risk of hospitalization and fatality when compared to other psychotropic drugs. • Poisoning management is supportive including tracheal intubation and mechanical ventilation. • No antidote is available.

References KEY FACTS GABAB Receptors • GABAB-receptors are metabotropic transmembrane receptors binding the GABA which is the main inhibitory neurotransmitter of the CNS. • GABAB-receptors are heterodimeric receptors constituted of two subunits, GABAB1 and GABAB2. • GABAB-receptors are coupled to Gi protein which can interact with voltage-sensitive calcium channels or inwardly rectifying potassium channels. • At the presynaptic level, GABAB-receptor activation blocks calcium channels inhibiting the release of neurotransmitters (GABA, glutamate, dopamine, etc.). • At the postsynaptic level, GABAB-receptor activation is responsible for the opening of potassium channels increasing the output of potassium and resulting in the hyperpolarization of the neuron.

Addolorato, G., Caputo, F., Capristo, E., Janiri, L., Bernardi, M., Agabio, R., . . . Gasbarrini, G. (2002). Rapid suppression of alcohol withdrawal syndrome by baclofen. American Journal of Medicine, 112, 226 229. Addolorato, G., Leggio, L., Agabio, R., Colombo, G., & Gasbarrini, G. (2006). Baclofen: A new drug for the treatment of alcohol dependence. International Journal of Clinical Practice, 60, 1003 1008. Amsein, O. (2008). Le Dernier Verre [The Last Glass]. Paris: Denoe¨l Edition. Anderson, P., & Nohe´r Swahn, C. G. (2008). Pharmacokinetics in baclofen overdose. Journal of Toxicology, 22, 11 20. Arbouw, M. E. L., Hoge, H. L., Meulenbelt, J., & Jansman, F. G. A. (2014). Increase of baclofen intoxications: Risks involved and management. The Netherland Journal of Medicine, 72, 497 499. Bains, R. S., & Ebenezer, I. S. (2013). Effects of the GABAB receptor agonist baclofen administered orally on normal food intake and intraperitoneally on fat intake in non-deprived rats. European Journal of Pharmacology, 698, 267 271. Beveridge, R., Smith, H. R., & Porrino, L. J. (2013). Differential development of tolerance to the functional and the behavioral effects repeated baclofen treatment in rats. Pharmacology, Biochemistry and Behaviour, 106, 27 32. Boels, D., Victorri-Vigneau, C., Grall-Bronnec, M., Toure´, A., Garnier, A., Turcant, A., & Le Roux, G. (2017). Baclofen and alcoholdependent patients: A real risk of severe self-poisoning. Basic and Clinical Pharmacology and Toxicology., 121, 353 359.

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Boutte, C., Vercueil, L., Durand, M., Vincent, F., & Alvarez, J. C. (2006). EEG contribution to the diagnosis of baclofen overdose. Clinical Neurophysiology, 36, 85 89. Chartier, M., Tannous, S., Benturquia, N., Labat, L., Reis, R., Rise`de, P., . . . Me´garbane, B. (2018). Baclofen-induced neuro-respiratory toxicity in the rat: Contribution of tolerance and characterization of withdrawal syndrome. Toxicological Sciences, 164, 153 165. Chevillard, L., Me´garbane, B., Baud, F. J., Rise`de, P., Decle`ves, X., Mager, D., . . . Ricordel, I. (2010). Mechanisms of respiratory insufficiency induced by methadone overdose in rats. Addiction Biology, 15, 62 80. Cleophax, C., Goncalves, A., Chasport, C., De Beaugrenier, V., Labat, L., Decle`ves, X., & Me´garbane, B. (2015). Usefulness of plasma drug monitoring in severe baclofen poisoning. Clinical Toxicology, 53, 923 924. Deguchi, Y., Inabe, K., Tomiyasu, K., Nozawa, K., Yamada, S., & Kimura, R. (1995). Study on brain interstitial fluid distribution and blood-brain barrier transport of baclofen in rats by microdialysis. Pharmaceutical Research, 12, 1838 1844. Food & Drug Administration. Kemstros NDA 21-589 and Summary Basis of Approval (Schwarz Pharma), USA. (2017). ,https://www.accessdata. fda.gov/drugsatfda_docs/nda/2003/021589s000_KemstroTOC.cfm. Accessed 01.04.18. Franchitto, N., Pelissier, F., Lauque, D., Simon, N., & Lanc¸on, C. (2014). Self-intoxication with baclofen in alcohol-dependent patients with co-existing psychiatric illness: An emergency department case series. Alcohol and Alcoholism, 49, 79 83. French National Agency for Medicines and Health Products Safety (ANSM). Temporary Recommendation for Use of baclofen in the treatment of alcohol dependent patients (3rd version), France. (2017a). ,http:// ansm.sante.fr/S-informer/Points-d-information-Points-d-information/La-RTU-du-baclofene-dans-l-alcoolo-dependance-renouveleepour-une-duree-de-1-an-Point-d-information. Accessed 01.04.08. French National Agency for Medicines and Health Products Safety (ANSM). Baclofen in real life in France between 2009 and 2015. Use, persistence and safety, and comparison with medications to treat alcohol problems which have a marketing authorization application, France. (2017b). ,http://ansm.sante.fr/S-informer/Communiques-CommuniquesPoints-presse/Resultats-de-l-etude-sur-les-usages-et-la-securite-dubaclofene-en-France-entre-2009-et-2015-Communique. Accessed 01.04.18. Keegan, B., Beveridge, T., Pezor, J. J., Xiao, R., Sexton, T., Childers, S., & Howlett, A. C. (2015). Chronic baclofen desensitizes GABABmediated G-protein activation and stimulates phosphorylation of kinases in mesocorticolimbic rat brain. Neuropharmacology, 95, 492 502. Kiel, L. B., Hoegberg, L. C., Jansen, T., Petersen, J. A., & Dalhoff, K. P. (2015). A nationwide register-based survey of baclofen toxicity. Basic Clinical Pharmacology & Toxicology, 116, 452 456. Kumar, G., Sahaya, K., Goyal, M. K., Sivaraman, M., & Sahota, P. K. (2010). Electroencephalographic abnormalities in baclofen-induced encephalopathy. Journal of Clinical Neurosciences, 17, 1594 1596. Kumar, K., Sharma, S., Kumar, P., & Deshmukh, R. (2013). Therapeutic potential of GABAB receptor ligands in drug addiction, anxiety, depression and other CNS disorders. Evidence Based Complementary and Alternative Medicine, 110, 174 184. Le´ger, M., Brunet, M., Le Roux, G., Lerolle, N., & Boels, D. (2017). Baclofen self-poisoning in the era of changing indication: multicentric reports to a French Poison Control Centre. Alcohol Alcoholism, 52, 665 670. Lehmann, A., Mattson, J. P., Edlund, A., Johansson, T., & Ekstrand, A. J. (2003). Effects of repeated administration of baclofen to rats on GABAB receptors binding sites and subunit expression in the brain. Neurochemical Research, 28(2), 387 393.

Liu, J., & Wang, L. N. (2017). Baclofen for alcohol withdrawal. Cochrane Database System Review, 8, CD008502. Malcangio, M., Da Silva, H., & Bowery, N. G. (1993). Plasticity of GABAB receptor in rat spinal cord detected by autoradiography. European Journal of Pharmacology, 250, 153 156. Marsot, A., Imbert, B., Alvarez, J. C., Grassin-Delyle, S., Jaquet, I., Lanc¸on, C., & Simon, N. (2014). High variability in the exposure of baclofen in alcohol-dependent patients. Alcoholism: Clinical and Experimental Research, 38, 316 321. Me´garbane, B., Labat, L., & Decle`ves, X. (2016). Is extracorporeal treatment useful for managing severe baclofen poisoning? the debate is still open. Anesthesia Critical Care & Pain Medicine, 35, 171 172. Moll-Navarro, M. J., Merino, M., Casabo, V. G., Nacher, A., & Polache, A. (1996). Interaction of taurine on baclofen intestinal absorption: a nonlinear mathematical treatment using differential equations to describe kinetics inhibition models. Journal of Pharmaceuticals Sciences, 85, 1248 1254. Mu¨ller, C., Geisel, O., Pelz, P., Higl, V., Kru¨ger, J., Stickel, A., . . . Heinz, A. (2015). High-dose baclofen for the treatment of alcohol dependence (BACLAD study): A randomized, placebo-controlled trial. European Neuropsychopharmacology, 25, 1167 1177. Oshiro, M., Hefferan, M. P., Kakinohana, O., Lukacova, N., Sugahara, K., & Marsal, M. (2010). Suppression of stretch reflex activity after spinal or systemic treatment with AMPA receptor antagonist NGX424 in rats with developed baclofen tolerance. British Journal of Pharmacology, 161, 976 985. Pelissier, F., de Haro, L., Cardona, F., Picot, C., Puskarczyk, E., Sapori, J. M., . . . Franchitto, N. (2017). Self-poisoning with baclofen in alcohol-dependent patients: National reports to French Poison Control Centers, 2008 2013. Clinical Toxicology, 55, 275 284. Peng, C. T., Ger, J., Yang, C. C., Tsai, W. J., Deng, J. F., & Bullard, M. (2008). Prolonged severe withdrawal symptoms after acuteon-chronic baclofen overdose. Journal of Toxicology, 36, 359 363. Pierrefiche, O., Foutz, A. S., & Denavit-Saubie´, M. (1993). Effects of GABAB receptor agonists and antagonists on the bulbar respiratory network in cat. Brain Research, 605, 77 84. Pommier, P., Debaty, G., Bartoli, M., Viglino, D., Carpentier, F., Danel, V., & Maxime, M. (2014). Severity of deliberate acute baclofen poisoning: A nonconcurrent cohort study. Basic Clinical Pharmacology & Toxicology, 114, 360 364. Priano, L., Zara, G. P., El-Assawy, N., Cattaldo, S., Muntoni, E., Milano, E., . . . Mauro, A. (2011). Baclofen-loaded solid lipid nanoparticles: electrophysiological assessment of efficacy, pharmacokinetics and tissue distribution in rats after intraperitoneal administration. European Journal of Pharmaceutics and Biopharmaceutics, 79, 135 141. Reynaud, M., Aubin, H. J., Trinquet, F., Zakine, B., Dano, C., Dematteis, M., . . . Detilleux, M. (2017). A randomized, placebocontrolled study of high-dose baclofen in alcohol-dependent patients The ALPADIR study. Alcohol and Alcoholism, 52, 439 446. Richter, E., Baldovini, A., Blasco, V., Leone, M., & Albanese, J. (2016). About Baclofen withdrawal syndrome. La Presse Me´dicale, 45, 547 548. Rigal, L., Legay, L., Alexandre-Dubroeucq, C., Pinot, J., Le Jeune, C., & Jaury, P. (2015). Tolerability of high-dose baclofen in the treatment of patients with alcohol disorders: A retrospective study. Alcohol and Alcoholism, 50, 551 557. Rochart, N., Berger, P., Brochet-Paille, A., Poiron, L., & Chillet, P. (2012). Acute Baclofen poisoning: Which places for EEG and plasma baclofen levels? Journal Europe´en des Urgences et de Re´animation, 24, 54 59.

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Rolland, B., Auffret, M., Labreuche, J., Lapeyre-Mestre, M., Dib, M., Kemkem, A., . . . Gautier, S. (2017). Phone-based safety monitoring of the first year of baclofen treatment for alcohol use disorder: The BACLOPHONE cohort study protocol. Drug Safety, 16, 125 132. Sands, S. A., Mc Carson, K. E., & Enna, S. J. (2003). Differential regulation of GABAB receptor subunit expression and function. The Journal of Pharmacology and Experimental Therapeutics, 305, 19 196. Seifert, E., & Trippenbach, T. (1998). Effects of Baclofen on the Hering-Breuer inspiratory-inhibitory and deflation reflexes in rats. The American Physiological Society, 274, 462 468. Sullivan, R., Hodgman, M. J., Kao, L., & Tormoehlen, L. M. (2012). Baclofen overdose mimicking brain death. Clinical Toxicology, 50, 141 144. Van Bree, J., Audus, K., & Borchardt, R. (1988). Carrier-mediated transport of baclofen across monolayers of bovine brain endothelial cells in primary culture. Pharmaceutical Research, 5, 369 371.

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Wang, D. C., Bose, P., Parmier, R., & Thompson, F. J. (2002). Chronic intrathecal baclofen treatment and withdrawal: I. Changes in ankle torque and hind limb posture in normal rats. Journal of Neurotrauma, 19, 875 886. Weiβhaar, G., Hoemberg, M., Bender, K., Bangen, U., Herkenrath, P., Eifinger, F., . . . Oberthuer, A. (2012). Baclofen intoxication: A “fun drug” causing deep coma and nonconvulsive status epilepticus A case report and review of the literature. European Journal of Pediatrics, 171, 1541 1547. World Health Organisation (WHO). International Guide for monitoring alcohol consumption and related harm. (2000). ,http://www.suchtmonitoring.ch/docs/library/world_health_organization_sczq7q3btxd.pdf. Accessed 01.04.18. Wuis, E. W., Dirks, M. J. M., Termond, E. F. S., Vree, T. B., & Van der Kleijn, E. (1989). Plasma and urinary excretion kinetics of oral baclofen in healthy subjects. European Journal of Clinical Pharmacology, 37, 181 184.

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C H A P T E R

66 Treatment With Nalmefene in Alcoholism Philippe Larame´e Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, ON, Canada

LIST OF ABBREVIATIONS NICE EMA DRL WHO RCT SAG HDD TAC

TREATMENT GOALS IN ALCOHOL DEPENDENCE

National Institute for Health and Care Excellence European Medicines Agency drinking-risk level World Health Organization randomized controlled trial scientific advisory group heavy-drinking day total alcohol consumption

INTRODUCTION Alcohol dependence places a large burden on an individual’s health and on society, and this burden increases as the individual’s alcohol consumption increases (Rehm et al., 2003; Rehm, Zatonksi, Taylor, & Anderson, 2011; World Health Organization, 2004). In 2004 in the European Union, alcohol dependence accounted for more than 70% of the overall alcohol-attributable mortality in individuals aged 65 years or younger (Rehm & Shield, 2012). In addition, alcohol dependence is associated with many serious social issues, including crime, family problems, parenting problems, and lost productivity in the workplace (Rehm & Shield, 2012). In England, the prevalence of alcohol dependence is estimated to be between 4% and 6% (Drummond et al., 2005; Fuller, Jotangia, & Farrell, 2009; McManus, Meltzer, Brugha, Bebbington, & Jenkins, 2009) approximately 1.6 million individuals suffer from the disease. It was reported that only 6% of alcohol-dependent individuals in England access treatment every year (Alcohol Concern, 2014; Fuller et al., 2009; McManus et al., 2009).

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00066-0

Traditionally, management of alcohol dependence has focused primarily on promoting abstinence through interventions such as cognitive-behavioral therapy and pharmacotherapy (European Medicines Agency, 2010; National Institute for Health & Care Excellence, 2011). However, in recent years, there has been an emphasis on an alternative harm-reduction approach attempting to help alcohol-dependent individuals to achieve a reduction in alcohol consumption without the need to completely abstain (Heather, Adamson, Raistrick, & Slegg, 2010). The Clinical Guideline 115 for the treatment of alcohol dependence published by the National Institute for Health and Care Excellence (NICE) in England recognizes both abstinence from alcohol consumption and reduction of alcohol consumption as legitimate treatment goals (National Institute for Health & Care Excellence, 2011). Reduction in alcohol consumption can reduce alcoholattributable harms, and individuals who are heavier drinkers have greater reductions in alcohol-attributable harms once their alcohol use is reduced (Rehm & Roerecke, 2013). These two different treatment goals have prompted the European Medicines Agency (EMA) to propose two types of clinical study designs with which to assess the effect of treatments for alcohol dependence (European Medicines Agency, 2010): relapse-prevention studies and harm-reduction studies. Relapse-prevention studies are based on an abstinence-oriented approach in which the treatment goals are to maintain stable abstinence after detoxification or withdrawal from alcohol, and to prevent relapse. Continued abstinence at the end of the

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active treatment period and continued abstinence until the end of the study are the primary outcomes assessed by such studies. Harm-reduction studies, on the other hand, are based on a reduction-oriented approach, with the aim of reducing alcohol consumption in patients and assessing the reduction in risk of harmful consequences associated with alcohol use. In these studies, patients do not withdraw from alcohol before commencing treatment, as they do in relapse-prevention studies. A clinically significant reduced alcohol intake, with subsequent harm reduction, is the ultimate treatment goal of harm-reduction studies.

NALMEFENE FOR REDUCTION OF ALCOHOL CONSUMPTION Until 2013, no pharmacological treatment was approved in the European Union that specifically could be prescribed, alongside psychosocial support, for the indication of reduction of alcohol consumption in actively drinking, alcohol-dependent patients; patients who do not withdraw from alcohol before commencing treatment. The other available drugs used in Europe to treat alcohol dependence, that is, naltrexone, acamprosate, and disulfiram, are indicated for maintenance of abstinence after detoxification or alcohol withdrawal (European Medicines Agency, 2010). In February 2013, nalmefene was licensed in the European Union for reduction of alcohol consumption in adults with alcohol dependence who have a high drinking-risk level [DRL; refer to Table 66.1, which presents DRLs in relation to alcohol-attributable harms, as defined by the World Health Organization (WHO)], who do not have physical withdrawal

symptoms and who do not require immediate detoxification before treatment initiation. Nalmefene should be prescribed only in conjunction with continuous psychosocial support focused on treatment adherence and reducing alcohol consumption. Nalmefene should be initiated only in patients who continue to have a high DRL 2 weeks after initial assessment (Nalmefene (Selincro) [summary of product characteristics], 2013). Importantly, nalmefene’s usage is different from that of other drug treatments approved in Europe for alcohol dependence. Rather than taken as a daily regimen, nalmefene is taken as needed, that is, on each day the patient perceives there is a risk of drinking alcohol, one tablet should be taken, preferably 1 2 hours prior to alcohol consumption. If the patient has started drinking alcohol without taking nalmefene, one tablet should be taken as soon as possible. The maximum dose of nalmefene is one tablet per day (Nalmefene (Selincro) [summary of product characteristics], 2013). The specific group of patients for whom nalmefene is approved is equivalent to the NICE Clinical Guideline 115 definition of “mild” alcohol dependence (National Institute for Health & Care Excellence, 2011).

NALMEFENE-LICENSED POPULATION The clinical efficacy and safety of nalmefene in patients with alcohol dependence has been demonstrated in three phase III randomized controlled trials (RCTs): ESENSE1 (NCT00811720) (Gual, He, Torup, van den Brink, & Mann, 2013), ESENSE2 (NCT00812461) (Mann, Bladstro¨m, Torup, Gual, & van den Brink, 2013), and SENSE (NCT00811941) (van den Brink, Sorensen, Torup, Mann, & Gual, 2014), showing

TABLE 66.1 Categorical Levels for Average Volume (in grams) of Pure Alcohol Per Day for Women and Men Category

Women

Men

WHO criteria for risk of consumption on a single drinking day in relation to acute problems Low risk Medium risk

0 20 21 40

0 40 41 60

High risk

41 60

61 100

Very high risk

.61

.101

WHO criteria for risk of consumption on a single drinking day in relation to chronic harm I (low risk)

0 20

0 40

II (medium risk)

21 40

41 60

III (high risk)

$ 41

$ 61

Categorization proposed by the WHO for women and men of daily average of pure alcohol consumed in relation with the risk for the development of alcohol-attributable chronic and acute harms. WHO, World Health Organization. Source: Evidence from WHO (World Health Organization. (2004). Global status report on alcohol 2004. Retrieved August 21, 2017, from World Health Organization http://www.who.int/substance_abuse/publications/globalstatusreportalcoholchapters/en/.).

VII. TREATMENTS, STRATEGIES AND RESOURCES

NALMEFENE-LICENSED POPULATION

that as-needed nalmefene, prescribed in conjunction with psychosocial support, was more effective at reducing alcohol consumption than a placebo plus psychosocial support. The EMA guideline on the development of medicinal products for the treatment of alcohol dependence places an emphasis on the identification of alcohol-dependent patients for whom pharmacological treatments would have the greatest benefit based on the disease severity and the level of alcohol consumption (European Medicines Agency, 2010). In alcohol treatment studies, reductions in alcohol consumption during the assessment period prior to randomization have been observed and can have an impact on study outcomes (Epstein, Drapking, Yusko, Cook, & McCrady, 2005; Litten, Fertig, Falk, Ryan, & Mattson, 2012). This phenomenon was observed in the three RCTs leading the indication for nalmefene. When the data for the period between screening (baseline) and randomization (1 2-week interval) were analyzed, it became evident that a sizeable proportion of the patients had considerably reduced their alcohol consumption during that period (i.e., before they received any medicinal/placebo intervention at randomization). At screening, approximately 78% of the patients in ESENSE1 and ESENSE2 had a high/very high DRL, and of these, 74% of the patients in ESENSE1 and 57% of the patients in ESENSE2 maintained their high/very high DRL throughout the screening period until randomization (Fig. 66.1) (Lundbeck, 2012a, 2012b). In SENSE, approximately 52% of the patients had a high/ very high DRL at baseline, of which 52% continued

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to have a high/very high DRL at randomization (Fig. 66.1) (Lundbek, 2012c). Patients who considerably reduced their alcohol consumption in the period between screening and randomization consumed such a small amount of alcohol at randomization that there was little room for further improvement in alcohol consumption reduction (floor effect). Although these patients stayed in the study and maintained their low level of alcohol consumption throughout the treatment period, it may be argued that these patients were not in need of immediate pharmacologic treatment for the management of alcohol dependence. The baseline characteristics of these patients were similar to those of the total population at screening, with no apparent features that would predict their behavior in the period between screening and randomization. This nonspecific effect leading to considerable reduction of alcohol consumption between screening and randomization was considered to be due to motivational elements of participating in a RCT and to the screening intervention. Therefore, post hoc subgroup analyses were performed to substantiate the clinical efficacy and the clinical relevance of nalmefene effect, most particularly in order to define a population for whom the benefit of nalmefene would be the greatest. The licensed population for nalmefene was defined post hoc as patients with a high or very high DRL at screening and randomization (Nalmefene (Selincro) [summary of product characteristics], 2013). In this post hoc population, the treatment effect was larger than in the total clinical trial population (which

FIGURE 66.1

Schematic overview of the patient populations in ESENSE1, ESENSE2, and SENSE. Proportion of patients for the three clinical trials assessing nalmefene in its licensed indication with a high DRL at baseline (screening) and 1 2 weeks later at randomization. Nalmefene is indicated for patients who maintain a high DRL 2 weeks after initial assessment (baseline). DRL, Drinking-risk level; FAS, full analysis set. Source: Evidence from Lundbeck. (2012a). Clinical study report 12014A; Lundbeck. (2012b). Clinical study report 12023A; Lundbek. (2012c). Clinical study report 12013A.

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66. TREATMENT WITH NALMEFENE IN ALCOHOLISM

included patients with medium DRLs for ESENSE1 and ESENSE2, medium and low DRLs for SENSE, and patients who reduced their alcohol consumption after initial assessment prior to the randomization visit). During the regulatory process, the Scientific Advisory Group (SAG) to the EMA recognized the validity of the post hoc analysis defining the nalmefene-licensed population (European Medicines Agency, 2012). While it was acknowledged that post hoc analyses are not ideal, it was noted that these are commonly used in clinical trials for psychiatric drugs, given the high dropout rates encountered in these populations. The SAG confirmed that the study population is representative of the population for whom nalmefene is proposed to be prescribed and who could benefit most from nalmefene treatment (European Medicines Agency, 2012).

NALMEFENE EFFICACY AND SAFETY Clinical Trials Design The RCTs assessing nalmefene (Gual et al., 2013; Mann et al., 2013; van den Brink et al., 2014) compared its as-needed usage (18.06 mg) plus psychosocial support to placebo plus psychosocial support. In these three trials, a total of 824 patients, who continued to have a high or very high DRL during the 2-week period after baseline were randomized; these patients matching the licensed population for the drug. ESENSE1 and ESENSE2 were 6-month efficacy studies designed to evaluate the effect of as-needed use of nalmefene on alcohol consumption in patients with alcohol dependence. SENSE was a 52-week study to evaluate the long-term safety and tolerability of asneeded nalmefene with a protocol amendment after study initiation to include efficacy analyses after 6 months. All three studies assessed as-needed use of nalmefene in actively drinking patients with alcohol dependence diagnosed according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (Spitzer, 2002). The three studies were conducted in Europe and randomized 1997 patients (824 matching the approved indication). Psychosocial support, in the form of BRENDA, was provided to all treatment groups (nalmefene and placebo) in the three studies. The BRENDA approach has six components: (1) a biopsychosocial evaluation; (2) a report of findings from the evaluation given to the patient; (3) empathy; (4) addressing patient needs; (5) providing direct advice; and (6) assessing patient reaction to advice and adjusting the treatment plan as needed. BRENDA was developed for use in combination with addiction

pharmacotherapy to enhance medication adherence (Starosta, Leeman, & Volpicelli, 2006). BRENDA emphasizes the importance of adherence to treatment by providing positive feedback and help in solving difficulties with adherence; it formalizes the interaction with the patient and outlines a strategy of therapeutic care that is comprehensive, but also focuses on the individual patient’s medical and psychological needs. In the three nalmefene studies, BRENDA was administered in limiting the sessions to approximately 15 30 minutes (except for the first session administered at randomization, which was approximately 30 40 minutes) (Lundbeck, 2012a, 2012b, 2012c). Additional eligibility criteria of the studies not previously mentioned included that patients should have had $ six heavy-drinking days (HDDs; defined as a day with a consumption of alcohol $ 60 g for men and $ 40 g for women) and # 14 abstinent days in the 4 weeks preceding the screening visit. Exclusion criteria included the presence of withdrawal symptoms requiring medication, and a history of delirium tremens or alcohol withdrawal seizures. Patients’ baseline characteristics for the three studies illustrated a mean age of B50 years old, with a proportion of males of B65%, B100% Caucasian, with a majority of patients in a relationship, and with a secondary or university education level (van den Brink et al., 2014; van den Brink et al., 2013).

Clinical Trials Results The efficacy of nalmefene was measured using two co-primary endpoints: change in the monthly number of HDDs and change in monthly TAC. The co-primary endpoints of HDD and TAC were in accordance with the recommendations in the EMA guideline on the development of medicinal products for the treatment of alcohol dependence (European Medicines Agency, 2010). The EMA considers both HDD and TAC as primary variables and emphasizes that a clinically relevant difference compared with placebo should be demonstrated. TAC was defined as mean daily alcohol consumption in grams per day over a month (28 days) (van den Brink et al., 2014; van den Brink et al., 2013). In the licensed population, patients with nalmefene reduced the number of HDDs and TAC statistically significantly more than placebo from baseline to month 6 in both ESENSE1 [HDD, 23.7 days/months (P 5 .001); TAC, 218.3 g/day (P , .001)] and ESENSE2 [HDD, 22.7 days/months (P 5 .025); TAC, 210.3 g/ day (P 5 .040)] (van den Brink et al., 2013) (Fig. 66.2). In both studies, the effect in favor of nalmefene was observed by the first month and maintained

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NALMEFENE EFFICACY AND SAFETY

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FIGURE 66.2 Change from baseline in the number of HDDs and in TAC among patients with a high/very high DRL at baseline and randomization (licensed population) in ESENSE1 and ESENSE2. Results from two (ESENSE1 and ESENSE2) of the three clinical trials assessing nalmefene in its licensed indication for the co-primary endpoints: change in the monthly number of HDDs and change in monthly TAC. The difference between nalmefene and a placebo was demonstrated statistically significant throughout the length of the studies. These differences were recognized as being clinically relevant. DRL, Drinking-risk level; HDD, heavy-drinking day; MMRM, mixed model repeated measures; TAC, total alcohol consumption. Adapted from (Lundbeck, 2012a; Lundbeck, 2012b) Original from Van den Brink, W., Aubin, H. J., Bladstro¨m, A., Torup, L., Gual, A., Mann, K. (2013). Efficacy of as-needed nalmefene in alcoholdependent patients with at least a high drinking risk level: results from a subgroup analysis of two randomized controlled 6-month studies. Alcohol Alcohol, 48(5), 570 578. http://dx.doi.org/10.1093/alcalc/agt061.

throughout the study period. In the SENSE study, nalmefene significantly reduced the number of HDDs and TAC consistently more than placebo throughout the 1year treatment period. At 1 year, the mean difference to placebo in the number of HDDs was 23.6 days/ month (P 5 .016) and the mean difference to placebo in TAC was 17.3 g/day (P 5 .013) in favor of nalmefene. The difference in treatment effect between nalmefene and a placebo was persisted throughout the treatment period and even increased with time, indicating that

tolerance to the effectiveness of nalmefene did not develop within at least 12 months of treatment (van den Brink et al., 2014). In terms of safety, nalmefene was generally welltolerated and the majority of the adverse events observed were associated with treatment initiation and were mild in severity and appeared for a short duration. The most common were nausea, dizziness, insomnia, and headache (van den Brink et al., 2013; van den Brink et al., 2014).

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DISCUSSION Reduction of alcohol consumption as a clinically significant treatment goal is widely accepted in current literature (van Amsterdam & van den Brink, 2013; European Medicines Agency, 2010). Reduction of alcohol consumption, is an alternative option for patients who do not want to consider abstinence as an initial treatment goal and who do not require immediate detoxification. Approximately half of the patients seeking help at a range of services across the United Kingdom were found to choose reduction of alcohol consumption rather than abstinence as their preferred treatment goal when asked (Heather et al., 2010). There is also evidence that achieving a successful outcome of abstinence or reduction is related to initial goal preference (Adamson, Heather, Morton, & Raistrick, 2010; Orford & Keddie, 1986). Although most patients with an alcohol use disorder (AUD) identified by general practitioners in England are believed to need specialist treatment, many are not referred because of difficulties in access and patient preference not to engage in specialist treatment (Drummond et al., 2005). There is an unmet need in the management of alcohol dependence, especially for options that are more easily accessible, that encourage and motivate adherence, and that result in better treatment outcomes (Drummond, Deluca, Oyefeso, Rome, & Scrafton, 2009; European Medicines Agency, 2010). Although nalmefene is the only pharmacological treatment that is approved in Europe for the indication of reduction of alcohol consumption and that specifically can be prescribed to patients with alcohol dependence without prior detoxification, NICE, in its Clinical Guideline 115, also gave an unlicensed recommendation for naltrexone and acamprosate for the reduction of alcohol consumption for patients for whom psychological intervention alone has failed (National Institute for Health & Care Excellence, 2011). However, in clinical practice, these are usually prescribed to patients with moderate/severe alcohol dependence who have reached abstinence following a detoxification process (National Institute for Health & Care Excellence, 2011). When NICE appraised the use of nalmefene, acamprosate and naltrexone were considered as potential comparators (National Institute for Health & Care Excellence, 2013). The NICE Assessment Group determined that acamprosate was not a relevant comparator because its marketing authorization states that “treatment should only be initiated after weaning therapy, once the patient is abstinent from alcohol” (Acamprosate [summary of product characteristics],

2014). However, the Assessment Group believed that having naltrexone as a comparator was valid because the naltrexone indication includes reduction of alcohol cravings (Adepend [summary of product characteristics], 2013). The NICE Assessment Group recognized that while naltrexone is not explicitly licensed for reduction of alcohol consumption and, thus, not an established treatment, it could be used off-label within specialist services to reduce alcohol consumption for certain patients. Therefore, NICE considered naltrexone to be a relevant comparator of nalmefene (Acamprosate [summary of product characteristics], 2014). During the NICE single technology assessment process for nalmefene, the Assessment Group recognized that there are no head-to-head trial comparing nalmefene to naltrexone (Stevenson et al., 2015). In the absence of such trials, a literature review was presented in the submission dossier of nalmefene that identified trials assessing naltrexone for reduction of alcohol consumption in actively drinking adults with mild alcohol dependence. The systematic review identified three RCTs (Heinala et al., 2001; Hernandez-Avila et al., 2006; Kranzler et al., 2003); however, these studies had limitations in reporting on key variables, making them ineligible for inclusion in an indirect comparison (Heinala et al., 2001). Ultimately, the Assessment Group recommended the use of nalmefene considering a cost-effectiveness analysis of nalmefene in conjunction with psychosocial support versus psychosocial support alone (Heinala et al., 2001), cost-effectiveness analysis including a scenario assessing the integration of nalmefene within the English healthcare system treatment pathway for alcohol dependence, which assessed the use of nalmefene and naltrexone in sequence, concluding that the addition of nalmefene to psychological support is cost-saving from the National Health Services (Larame´e, Bell, Irving, & Brodtkorb, 2016; Larame´e et al., 2014) and societal perspectives (Brodtkorb, Bell, Irving, & Larame´e, 2016). In addition, future modeling analyses demonstrated the clinical relevance of reduction of alcohol consumption with nalmefene in terms of the avoidance of alcohol-attributable diseases, injuries, and death (Larame´e et al., 2016; Roerecke, Sørensen, Larame´e, Rahhali, & Rehm, 2015). Further, during the regulatory process, the SAG to the EMA confirmed that the effect size of nalmefene was clinically meaningful for the post hoc population (European Medicines Agency, 2010). In October 2014, NICE recommended nalmefene for the treatment of alcohol dependence in England, within its market authorization (Heinala et al., 2001).

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SUMMARY POINTS

CONCLUSIONS The use of nalmefene in accordance with its licensed indication is a clinically effective and cost-effective allocation of healthcare resources. Nalmefene expands treatment options and addresses an unmet medical need for patients who do not require immediate detoxification and who would prefer an initial treatment goal of alcohol reduction. Moreover, these patients can be managed in a primary care setting, thereby increasing the proportion of dependent drinkers in the local population who enter, and complete, treatment in a setting appropriate to their needs.

MINI-DICTIONARY OF TERMS Harm-reduction approach Approach in the treatment of alcohol dependence which consists in reducing the level of alcohol consumption, resulting in reducing the risk of alcohol-attributable diseases, injuries, and death. Mild alcohol dependence Severity of the alcohol dependence disease proposed by the National Institute for Health and Care Excellence in England, which represents patients with a high level of alcohol consumption who do not experience physical symptoms when withdrawing from alcohol. Drinking-risk level Level of alcohol consumption associated with a probability of risk for alcohol-attributable diseases, injuries, and deaths. Post hoc analysis Analysis of the data collected during a clinical trial which was not predefined; the trial design was not developed in anticipation of such analyses. Statistically significant Likelihood that the relationship between variables is caused by something other than random chance. Statistical hypothesis testing is used to define whether results are statistically significant, providing a P-value which represents the probability that random chance could explain the result. Generally, a P-value of 5% or lower is considered to be statistically significant. Clinically relevant Outcome from a clinical trial which demonstrates an identifiable clinical benefit for the patient’s health status. Cost-effective An intervention which provides sufficient value for the amount paid versus the standard of care. In England, the National Institute for Health and Care Excellence usually recognizes a cost-effective use of healthcare resources when an intervention cost versus the standard of care is no more than d20,000 per quality-adjusted life year (a measure combining patient quality of life and survival).

KEY FACTS Unmet Medical Needs Supported by the Availability of Nalmefene • Individuals with alcohol dependence are at risk of suffering from health problems such as liver, pancreatic and cardiovascular diseases, injuries, and serious social issues.

• In England, the access for the management of alcohol dependence is limited and is used primarily in specialist settings. • The management of alcohol dependence has traditionally focused on promoting immediate abstinence. • Certain patients suffering of mild alcohol dependence can benefit from safe medical management aimed at reducing their alcohol consumption instead of aiming for immediate abstinence. • Reducing alcohol consumption can significantly reduce the risk of alcohol-attributable diseases, injuries, and mortality. • Nalmefene has been available in Europe since 2013 and has been reimbursed by the English healthcare system since 2014. • Nalmefene is indicated for the reduction of alcohol consumption for patients with mild alcohol dependence. • Nalmefene is to be taken on an as-needed basis when the patient craves alcohol. • Nalmefene can be prescribed in primary care where patients’ management include continuous psychosocial support.

SUMMARY POINTS • As-needed usage of nalmefene was licensed in Europe for the reduction of alcohol consumption in adults with alcohol dependence who have a high drinking-risk level, who do not have physical withdrawal symptoms, and who do not require immediate detoxification before treatment initiation. • Other pharmacological treatments available in Europe to treat alcohol dependence—naltrexone, acamprosate, and disulfiram—are indicated for maintenance of abstinence after detoxification or alcohol withdrawal. • The three studies assessing nalmefene in its licensed population demonstrated that patients treated with nalmefene reduced the number of HDDs and total alcohol consumption statistically significantly more than a placebo from baseline to the end of the studies, and this was observed from the first month of treatment. • The effect of nalmefene in reducing alcohol consumption was recognized by the European Medicines Agency to be clinically relevant in terms of a reduction of the risk of alcohol-attributable diseases, injuries, and deaths.

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C H A P T E R

67 Dual Therapy for Alcohol Use Disorders: Combining Naltrexone With Other Medications Janice Froehlich, Emily Nicholson and Julian Dilley Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States

LIST OF ABBREVIATIONS NTX P VAR FLU BUP AUD FDA DA g/kg BW mg/kg BW P rats

naltrexone prazosin varenicline fluoxetine bupropion alcohol use disorders Food and Drug Administration dopamine grams per kilogram Body Weight milligrams per kilogram Body Weight alcohol-preferring rats

INTRODUCTION Alcohol use disorders (AUD) are among the most widespread of all the addictions in the world and alcoholism is one of the leading causes of preventable death worldwide. As the problems associated with hazardous alcohol use escalate, the development of effective treatments has become a global priority. Pharmacological treatment of AUD patients has been resisted by providers in both inpatient and outpatient settings. In the United States, less than a third of patients in public and private AUD treatment programs are prescribed medications to treat AUD (Ducharme, Chandler, & Harris, 2016; Harris et al., 2013) Traditionally, AUD treatment has not been medically-oriented. The realization, in the 1970s, that AUD are, in part, genetically determined dramatically changed the world view of AUD. Evidence for the

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00067-2

genetics of alcoholism is clear. Alcoholism tends to run in families, and individuals with a strong family history of alcoholism are at elevated risk for developing alcoholism. For instance, sons of alcoholics are approximately 3 5 times more likely to become alcoholics than are sons of nonalcoholics (Cotton, 1979; Goodwin, Schulsinger, & Moller, 1974) and adoption studies indicate that a significant proportion of this elevated risk is genetic rather than environmental in origin (Cadoret, Cain, & Grove, 1980; Cloninger, Bohman, & Sigvardsson, 1981). Sons of alcoholics, adopted by nonalcoholic families in early life, are still three times more likely to become alcoholic than are similarly adopted sons of nonalcoholics (Cloninger et al., 1981; Goodwin et al., 1974). The prevalence of DSM-IV alcohol dependence in relatives of persons with alcohol dependence themselves was examined in the Collaborative Study on the Genetics of Alcoholism (Nurnberger et al., 2005). It was estimated that 75% of alcohol-dependent subjects have at least one close relative with alcohol dependence (J. Nurnberger, personal communication, January 5, 2015).

NALTREXONE The recognition that excessive alcohol drinking is, in part, genetically determined led scientists to question what is inherited when one inherits a predisposition toward high alcohol drinking. Subsequent studies revealed that endogenous opioid peptides are released

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© 2019 Elsevier Inc. All rights reserved.

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during alcohol drinking and they mediate alcoholinduced euphoria or the “high” that is experienced from alcohol which is one of alcohol’s most valued effects (Gilman, Ramchandani, Davis, Bjork, & Hommer, 2008). This led to the realization that blocking the action of endogenous opioid peptides may reduce alcohol-induced euphoria and alcohol drinking. Naltrexone (NTX) is the prototypical nonselective opioid receptor antagonist that blocks the action of endogenous opioid peptides. NTX was found to reduce alcohol drinking in many preclinical and clinical studies by reducing alcohol-induced euphoria (O’Malley, Jaffe, Rode, & Rounsaville, 1996; Volpicelli, Watson, King, Sherman, & O’Brien, 1995; for review see Froehlich, O’Malley, Hyytia, Davidson, & Farren, 2003; O’Malley & Froehlich, 2003). NTX is the best characterized and most extensively used medication for treating AUDs in the United States (for review, see Froehlich & Li, 1993; Froehlich et al., 2003; O’Malley & Froehlich, 2003). However, despite the clear benefits of NTX for many alcoholics, it is underutilized because the efficacy is modest, it is not without side effects, it is not effective for all alcoholics and, when it is effective, a significant number of alcoholics fail to maintain initial treatment gains and subsequently relapse to heavy drinking (Garbutt et al., 2005; Kranzler, Modesto-Lowe, & Van Kirk, 2000; O’Malley & Froehlich, 2003). Clearly, there is a critical need to increase the number of medications available for treating AUD. Only three medications have been approved by the United States Food and Drug Administration (FDA) for the treatment of alcohol dependence: Disulfiram (Antabuse) which was approved in 1949, NTX (Trexan) which was approved in 1994, and Acamprosate (Campral) which was approved in 2004. Other options are needed to treat subpopulations of alcoholics and heavy drinkers who do not respond to these medications.

COMBINATORIAL PHARMACOTHERAPEUTICS Combinatorial pharmacotherapeutics is a good approach to treating AUD patients (Anton et al., 2006; Froehlich et al., 2016, 2017a; Heyser, Moc, & Koob, 2003; Johnson, Ait-Daoud, & Prihoda, 2000) because people drink alcohol for different reasons. Some drink to produce feelings of euphoria and well-being, others drink to reduce anxiety, stress, or depression, and still others drink to induce sedation and blunt aversive thoughts or memories. A medication that targets only one action of alcohol, as with NTX targeting euphoria, may not be as effective in reducing alcohol drinking as is a combined medication regime that targets more

than one action of alcohol. Using a rodent model of alcoholism, we have combined NTX, the “gold standard” for AUD treatment, with other drugs that have been approved for the treatment of other disorders such as posttraumatic stress disorder (prazosin, P) (Froehlich, Hausauer, & Rasmussen, 2013b; Rasmussen, Alexander, Raskind, & Froehlich, 2009), depression (fluoxetine, FLU) (Zink, Rohrbach, & Froehlich, 1997), and smoking cessation anxiety [varenicline (VAR) or Chantixr] (Froehlich et al., 2016, 2017a). We have found that these drugs, when combined with NTX, can effectively reduce alcohol intake when used in low doses that are not associated with aversive side effects. Two unique features of the studies from our laboratory are the use of rats selectively bred for alcohol preference and high-alcohol drinking, termed the “alcohol-preferring” (P line) rats and the use of an oral drug delivery approach for long-term drug treatment. P rats are selected for breeding based on their average alcohol intake during four weeks of a free-choice between alcohol 10% (v/v) and water. Those selected for breeding consume in excess of 5 g alcohol/kg body weight/day and demonstrate a greater than 2:1 preference ratio for alcohol over water. Rats of the P line have been used worldwide to evaluate the efficacy of drugs that have the potential to reduce voluntary alcohol intake and to prevent alcohol relapse (for review, see Bell et al., 2017; Froehlich, 1995; Froehlich & Li, 1991). In the following studies, P rats were used to assess the efficacy of different drug combinations for reducing alcohol drinking. All drugs in the following studies were delivered orally to allow for prolonged drug treatment which is difficult to achieve in rodents because standard routes for drug administration, which include intraperitoneal, intramuscular, and subcutaneous, cannot be used repeatedly without inducing stress and introducing significant health risks. To circumvent this problem, we developed an oral drug, self-administration approach that minimizes stress (Brown, Dinger, & Levine, 2000; Rosen, Brodin, Eneroth, & Brodin, 1992). The drug is incorporated into a small piece of flavored gelatin that is fed to the rat (Froehlich, Hausauer, Federoff, Fischer, & Rasmussen, 2013a). This delivery method eliminates the need for handling the animal, minimizes potential harm, parallels the route most often used in humans, is optimal for prolonged drug treatment, and is appropriate for delivery of any water-soluble drug. Our laboratory has used this approach in many studies involving prolonged administration of NTX alone, and in combination with P, VAR, FLU, or bupropion (BUP) (Froehlich et al., 2013a, 2013b, 2016, 2017a, 2017b; Nicholson, Dilley, & Froehlich, 2018; Rasmussen, Kincaid, & Froehlich, 2015).

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NALTREXONE 1 VARENICLINE

NALTREXONE 1 PRAZOSIN P, an α1-adrenergic receptor antagonist, was originally FDA-approved for the treatment of high blood pressure under the trade name Minipressr. The noradrenergic system plays a role in reinforcement and arousal (Aston-Jones & Cohen, 2005; Ventura, Alcaro, & Puglisi-Allegra, 2005), which are associated with alcohol drinking. P blocks the brain α1-adrenergic receptors that mediate central noadrenergic signaling (Menkes, Baraban, & Aghajanian, 1981; Rogawski & Aghajanian, 1982). P decreases alcohol drinking and alcohol self-administration in both preclinical (Froehlich et al., 2013a; Froehlich, Hausauer, Fischer, Wise, & Rasmussen, 2015; Rasmussen et al., 2009; Verplaetse, Rasmussen, Froehlich, & Czachowski, 2012) and clinical studies (Simpson et al., 2009, 2015) studies. We explored the ability of a combination of low-dose NTX with low-dose P to reduce alcohol intake in adult male P rats (Froehlich et al., 2013b). Rats were given scheduled access to a 15% (v/v) alcohol solution for two hours daily with food and water freely available. Rats were fed either NTX alone (10.0 or 20.0 mg/kg BW), P alone (2.0 mg/kg), or one of two drug combinations (10.0 mg/kg NTX 1 2.0 mg/kg P or 20.0 mg/kg NTX 1 2.0 mg/kg P). Drugs were delivered orally at 45 minutes prior to onset of the daily 2-hour alcohol-access period for a week and the effect on alcohol and water intake was assessed. Neither a low dose of NTX alone nor a low dose of P alone was effective in reducing alcohol intake, but combining the

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two drugs into a single medication significantly reduced alcohol intake (Fig. 67.1). In fact, the combination of low-dose NTX with low-dose P was as effective as was a much higher dose of NTX alone. The ability of the combination to reduce alcohol intake was prolonged, with reduced intake seen throughout 3 of the 4 weeks of treatment. In a later study, we found that combining low doses of NTX with P was also more effective than was either drug alone in reducing alcohol intake in rats with a history of alcohol drinking, alcohol dependence, and multiple alcohol withdrawals (Rasmussen et al., 2015) (Fig. 67.2). The superiority of the combination, when compared with each drug alone, is also seen when alcohol is operantly self-administered (Verplaetse et al., 2012).

NALTREXONE 1 VARENICLINE VAR, an orally active α4β2 nicotinic acetylcholinergic receptor (nAChR) partial agonist, is currently FDAapproved for smoking cessation under the trade name Chantix in the United States and as Champix in Europe and elsewhere. VAR decreases alcohol drinking and alcohol self-administration in both preclinical (Froehlich et al., 2017b; Steensland, Simms, Holgate, Richards, & Bartlett, 2007) and clinical studies (Fucito et al., 2011; Litten et al., 2013; Mitchell, Teague, Kayser, Bartlett, & Fields, 2012). However, a decrease in alcohol intake is not seen in all studies (Schacht et al., 2014).

FIGURE 67.1 Effect of NTX or P alone, and in combination, on daily alcohol preferring (P) rats. Effect of NTX alone (N 5 10) or P alone (N 5 10) or NTX 1 P (N 5 7 10), or vehicle (N 5 11) on alcohol intake in P rats. Drugs were administered orally 1 hour prior to onset of the daily 2-hour alcohol-access period for 4 weeks. Alcohol intake was averaged for each rat across each week. Each bar represents the mean 6 SE.  P , .05, and  P , .01 versus vehicle. Source: With permission from Froehlich, J.C., Hausauer, B.J., & Rasmussen, D.D. (2013b). Combining naltrexone and prazosin in a single oral medication decreases alcohol drinking more effectively than does either drug alone. Alcoholism: Clinical and Experimental Research, 37, 1763 1770, Fig. 67.2, p. 1766.

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We postulated that combining NTX with VAR may result in a medication that is more effective, in low doses, than either drug alone (Froehlich et al., 2016).

3

VEH (N = 12)

10.0 mg/kg BW NTX (N = 12)

2.0 mg/kg BWP (N = 12)

2.0 mg/kg BWP + 10.0 mg/kg BW NTX (N = 13)

Alcohol intake (g/kg BW/2 h)

*** 2

1

0

1

5

8 Days

FIGURE 67.2 Effect of NTX or P alone, and in combination, on daily alcohol preferring (P) rats with a history of alcohol drinking, dependence, and multiple withdrawals. Effects of daily treatment with NTX or P alone, or in combination, on alcohol intake in P rats during intermittent alcohol access on days 1, 5, and 8. Each bar represents the mean 6 SE.  P , .001, P 1 NTX vs vehicle (VEH). Source: Adapted with permission from Rasmussen, D.D., Kincaid, C.L. & Froehlich, J.C. (2015). Prazosin 1 naltrexone decreases alcohol drinking more effectively than does either drug alone in P rats with a protracted history of extensive voluntary alcohol drinking, dependence, and multiple withdrawals. Alcoholism: Clinical and Experimental Research, 39, 1832 1841, Fig. 67.3, p. 1836.

To test this, P rats were given access to a 15% (v/v) alcohol solution for 2 hours daily and were fed either vehicle, NTX alone, VAR alone, or one of four combinations of NTX and VAR. Drugs were delivered orally at 45 minutes prior to onset of the daily 2-hour alcohol-access period for 10 consecutive days and the effects of drug treatment on alcohol and water intake were assessed. Low doses of VAR (0.5 and 1.0 mg/kg BW) and low doses of NTX (10.0 and 15.0 mg/kg BW), when given alone were not effective in decreasing alcohol drinking (data not shown). However, when ineffective doses of the two drugs were combined, alcohol intake was significantly reduced when compared to VEH (Fig. 67.3). In a subsequent study (Froehlich et al., 2017a), we examined whether NTX combined with VAR could block the acquisition of alcohol drinking in rats that were selectively bred for high voluntary alcohol drinking (rats of the P line) if they were treated with the drugs prior to exposure to alcohol. That is, could these drugs block the expression of a genetic predisposition toward alcohol drinking? To answer this question, alcohol-naı¨ve P rats were fed NTX (15.0 mg/kg BW) or VAR (1.0 mg/kg) alone, or a combination, daily for 2 weeks prior to the introduction of alcohol (2 h/day) after which drug treatment and alcohol access continued for 19 days. While neither NTX alone nor VAR alone altered the pattern of acquisition of alcohol drinking in P rats, the FIGURE 67.3 Effect of NTX or VAR alone, and in combination, on daily alcohol-preferring (P) rats. Effect of NTX 1 VAR or vehicle (VEH) on alcohol intake in P rats. Drugs were administered orally at 1 hour prior to onset of a daily 2-hour alcohol-access period for 15 days. Each bar represents the mean 6 SE.  P , .05,  P , .01,  P , .001 versus VEH. Source: Adapted with permission from Froehlich, J.C., Fischer, S.M., Dilley, J.E., Nicholson, E.R., Smith, T. N., Filosa, N.J., & Rademacher, L.C. (2016). Combining varenicline (Chantix) with naltrexone decreases alcohol drinking more effectively than does either drug alone in a rodent model of alcoholism. Alcoholism: Clinical and Experimental Research, 40, 1961 1970, Fig. 67.5, p. 1967.

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NALTREXONE 1 FLUOXETINE

FIGURE 67.4 Effect of NTX or VAR alone, and in combination, on the initiation of alcohol intake in P rats. Effect of NTX or VAR alone, or in combination, on the acquisition of alcohol drinking in alcohol-naı¨ve P rats. Rats were pretreated for 2 weeks prior to the onset of, and throughout, 3 weeks of daily 2-hour alcohol-access. Each point represents the mean 6 SE. Source: Adapted with permission from Froehlich, J.C., Fischer, S.M., Nicholson, E.R., Dilley, J.E., Filosa, N.J., Smith, T.N., & Rademacher, L.C. (2017a). A combination of naltrexone 1 varenicline retards the expression of a genetic predisposition toward high alcohol drinking. Alcoholism: Clinical and Experimental Research, 41, 644 652, Fig. 67.2, p. 647.

combination of NTX 1 VAR virtually eliminated the acquisition of alcohol drinking (Fig. 67.4). The ability of NTX 1 VAR to block the expression of a genetic predisposition toward high alcohol intake in P rats suggests that this medication may be important for individuals at genetic risk for developing AUD and may be particularly useful if introduced prior to onset of heavy alcohol drinking. These results, along with those from clinical studies (Ray et al., 2014), suggest that NTX 1 VAR is a potentially effective medication for reducing ongoing alcohol drinking and for blocking the initiation of alcohol drinking in individuals with a family history of alcoholism.

NALTREXONE 1 FLUOXETINE FLU, a selective serotonin reuptake inhibitor, is currently FDA-approved for treating depression under the trade name Prozacr. In several off-label studies, FLU, when given alone, has been reported to decrease alcohol drinking and alcohol self-administration in both preclinical (Grupp, Perlanski, & Stewart, 1988; Le et al., 1999; Murphy et al., 1988) and clinical studies (Naranjo, Kadlec, Sanhueza, Woodley-Remus, & Sellers, 1990; Naranjo, Poulos, Bremner, & Lanctot, 1994). We postulated that combining NTX with FLU would result in a medication that was more effective in reducing alcohol intake than either drug alone. P rats, given access to alcohol for two hours daily were treated with NTX alone (10.0 or 20.0 mg/kg BW), FLU alone (10.0 or 20.0 mg/kg BW), or NTX and FLU in combination

FIGURE 67.5 Effect of NTX or FLU alone, and in combination, on daily alcohol-preferring (P) rats. Effect of NTX or FLU alone, and in combination, on alcohol intake in P rats. Drugs were given, by IG infusion, at 30 minutes prior to the onset of a 2-hour alcohol-access period. Bars represent mean 6 SE.  P , .001 drug combination vs either dose of NTX or FLU alone. Unpublished data.

(10.0 mg/kg BW NTX 1 10.0 mg/kg BW FLU) at 30 minutes prior to onset of the daily 2-hour alcoholaccess period and the effects of treatment on alcohol and water intake effects were assessed. NTX and FLU, when administered alone, reduced alcohol intake in a dose-dependent manner (Fig. 67.5). Combining low doses of NTX (10.0 mg/kg BW) and FLU (10.0 mg/kg BW) reduced alcohol intake and the reduction was greater than that seen at the highest dose of either drug alone and was greater than would be expected

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67. DUAL THERAPY FOR ALCOHOL USE DISORDERS: COMBINING NALTREXONE WITH OTHER MEDICATIONS

SUMMARY A major goal in the field of alcohol research is to find ways to improve treatment outcomes for individuals with AUD. Combining specific medications to address the particular need of subpopulations of alcoholics and heavy drinkers, using a personalized medicine approach, is one way to achieve this goal. Given that people differ in their motivation to drink alcohol, the drug combination that works for one person may be ineffective for another. Tailoring medications to address individual needs may be the best choice for individuals who want to reduce their alcohol intake, but who have found a single medication to be ineffective.

FIGURE 67.6 Effect of NTX and BUP alone, and in combination, on daily alcohol intake in P rats. Effect of NTX and BUP alone, and in combination, administered 30 minutes prior to onset of a daily 2-hour alcohol-access period. Bars represent mean alcohol intake during 5 days of drug treatment. Each point represented the mean 6 SE.  P , .01, versus VEH.

based on drug additivity. The results suggest that NTX is more effective in decreasing alcohol intake when combined with FLU than when given alone.

NALTREXONE 1 BUPROPION BUP, a norepinephrine-dopamine reuptake inhibitor (NDRI), is FDA-approved under the trade name Zybanr for treating nicotine craving, and under the trade name Wellbutrinr for treating major depression. BUP combined with NTX is FDA-approved under the trade name Contrave to induce weight loss. To our knowledge no prior studies have directly examined the effect of BUP on alcohol drinking. We examined whether NTX combined with BUP was more effective than NTX alone in reducing alcohol intake (Nicholson et al., 2018). P rats were given access to alcohol for two hours daily and were fed either NTX alone (10.0 mg/ kg), BUP alone (10.0 or 20.0 mg/kg), or NTX and BUP (10.0 mg/kg NTX 1 10.0 mg/kg BUP) at 45 minutes prior to onset of the daily 2-hour alcohol-access period for five consecutive days and the effect of drug treatment on alcohol and water intake was assessed. Neither low-dose NTX (10.0 mg/kg BW) alone nor low-dose BUP (10.0 mg/kg BW) alone significantly reduced alcohol intake, but a combination of the two drugs at low doses significantly reduced alcohol intake (Fig. 67.6). A combination of NTX 1 BUP may prove to be an additional treatment option for individuals with AUD.

MINI-DICTIONARY OF TERMS Combinatorial pharmacotherapeutics The use of more than one drug to treat a disease or condition. Naltrexone A nonspecific opioid receptor antagonist that has received approval from the Food and Drug Administration for treating AUD. Prasozin An α1-adrenergic receptor antagonist that has received approval from the Food and Drug Administration for treating high blood pressure. Varenicline An orally active α4β2 nicotinic acetylcholinergic receptor partial agonist that has received approval from the Food and Drug Administration for assisting in smoking cessation. Fluoxetine A selective serotonin reuptake inhibitor that has received approval from the Food and Drug Administration for treating depression and other mood disorders. Bupropion A norepinephrine-dopamine reuptake inhibitor (NDRI), that has received approval from the Food and Drug Administration for treating depression and assisting in smoking cessation and weight loss. P Rats Alcohol-preferring rats that are selectively bred for high voluntary alcohol intake

KEY FACTS AUD Treatment • AUD are among a small number of modifiable factors that contribute to early illness and death. • Medications are rarely used to treat AUD in academic institutions, chemical dependence treatment facilities, or in general community hospitals. • There are a limited number of drugs currently available for AUD treatment. • Developing new medications to treat AUD continues to be a worldwide priority. • Combinatorial pharmacotherapeutics is a promising approach for the treatment of AUD.

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REFERENCES

SUMMARY POINTS • AUD are among the most prevalent of all addictions. • Increasing the number of medications available for treating AUD is a worldwide priority. • Combining NTX with drugs that were developed to treat other disorders (e.g., anxiety, depression) is a promising approach for treating AUD. • Combining low doses of more than one medication may reduce potential negative side effects associated with each drug, while maintaining efficacy. • Combining low doses of drugs, that work through different physiological processes and pathways, may result in tailored medications that are uniquely suited to reduce alcohol intake in subpopulations of individuals with AUD who find a single drug to be ineffective.

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self-administration and reinstatement of alcohol seeking induced by priming injections of alcohol and exposure to stress. Neuropsychopharmacology, 21, 435 444. Litten, R. Z., Ryan, M. L., Fertig, J. B., Falk, D. E., Johnson, B., Dunn, K. E., & Kampman, K. (2013). A double-blind, placebo-controlled trial assessing the efficacy of varenicline tartrate for alcohol dependence. Journal of Addiction Medicine, 7, 277 286. Menkes, D. B., Baraban, J. M., & Aghajanian, G. K. (1981). Prazosin selectively antagonizes neuronal responses mediated by α 1-adrenoceptors in brain. Naunyn-Schmiedeberg’s Archives of Pharmacology, 317, 273 275. Mitchell, J. M., Teague, C. H., Kayser, A. S., Bartlett, S. E., & Fields, H. L. (2012). Varenicline decreases alcohol consumption in heavydrinking smokers. Psychopharmacology, 223, 299 306. Murphy, J. M., Waller, M. B., Gatto, G. J., McBride, W. J., Lumeng, L., & Li, T. K. (1988). Effects of fluoxetine on the intragastric selfadministration of ethanol in the alcohol preferring P line of rats. Alcohol, 5, 283 286. Naranjo, C. A., Kadlec, K. E., Sanhueza, P., Woodley-Remus, D., & Sellers, E. M. (1990). Fluoxetine differentially alters alcohol intake and other consummatory behaviors in problem drinkers. Clinical Pharmacology & Therapeutics, 47, 490 498. Naranjo, C. A., Poulos, C. X., Bremner, K. E., & Lanctot, K. L. (1994). Fluoxetine attenuates alcohol intake and desire to drink. International Clinical Psychopharmacology, 9, 163 172. Nicholson, E. R., Dilley, J. E., & Froehlich, J. C. (2018). Naltrexone, given in combination with bupropion, decreases alcohol intake more effectively than does either drug alone. Alcoholism-Clinical and Experimental Research, 42, 571 577. Nurnberger, J. I., Wiegand, R., Bucholz, K., O’Connor, S., Meyer, E. T., Reich, T., . . . Porjesz, B. (2005). A family study of alcohol dependence: Coaggregation of multiple disorders in relatives of alcoholdependent probands. Archives of General Psychiatry, 61, 1246 1256. O’Malley, S. S., & Froehlich, J. C. (2003). Advances in the use of naltrexone: An integration of preclinical and clinical findings. In M. Galanter (Ed.), Recent developments in alcoholism XVI: Research on alcoholism treatment (pp. 217 245). New York, NY: Kluwer Academic/Plenum Publishers. O’Malley, S. S., Jaffe, A. J., Rode, S., & Rounsaville, B. J. (1996). Experience of a “slip” among alcoholics treated with naltrexone or placebo. American Journal of Psychiatry, 153, 281 283. Rasmussen, D. D., Alexander, L. L., Raskind, M. A., & Froehlich, J. C. (2009). The α1 adrenergic receptor antagonist, prazosin, reduces alcohol drinking in alcohol-preferring (P) rats. AlcoholismClinical and Experimental Research, 33, 264 272. Rasmussen, D. D., Kincaid, C. L., & Froehlich, J. C. (2015). Prazosin 1 naltrexone decreases alcohol drinking more effectively than does either drug alone in P rats with a protracted history of

extensive voluntary alcohol drinking, dependence, and multiple withdrawals. Alcoholism-Clinical and Experimental Research, 39, 1832 1841. Ray, L. A., Courtney, K. E., Ghahremani, D. G., Miotto, K., Brody, A., & London, E. D. (2014). Varenicline, low dose naltrexone, and their combination for heavy-drinking smokers: Human laboratory findings. Psychopharmacology, 231, 3843 3853. Rogawski, M. A., & Aghajanian, G. K. (1982). Activation of lateral geniculate neurons by locus coeruleus or dorsal noradrenergic bundle stimulation: Selective blockade by the alpha1adrenoceptor antagonist prazosin. Brain Research, 250, 31 39. Rosen, A., Brodin, K., Eneroth, P., & Brodin, E. (1992). Short-term restraint stress and sc saline injection alter the tissue levels of substance P and cholecystokinin in the peri-aqueductal grey and limbic regions of rat brain. Acta Physiologica, 146, 341 348. Schacht, J. P., Anton, R. F., Randall, P. K., Li, X., Henderson, S., & Myrick, H. (2014). Varenicline effects on drinking, craving and neural reward processing among non-treatment-seeking alcoholdependent individuals. Psychopharmacology, 231, 3799 3807. Simpson, T. L., Malte, C. A., Dietel, B., Tell, D., Pocock, I., Lyons, R., . . . Saxon, A. J. (2015). A pilot trial of prazosin, an alpha-1 adrenergic antagonist, for comorbid alcohol dependence and posttraumatic stress disorder. Alcoholism-Clinical and Experimental Research, 39, 808 817. Simpson, T. L., Saxon, A. J., Meredith, C. W., Malte, C. A., McBride, B., Ferguson, L. C., . . . Raskind, M. (2009). A pilot trial of the alpha-1 adrenergic antagonist, prazosin, for alcohol dependence. Alcoholism-Clinical and Experimental Research, 33, 255 263. Steensland, P., Simms, J. A., Holgate, J., Richards, J. K., & Bartlett, S. E. (2007). Varenicline, an α4β2 nicotinic acetylcholine receptor partial agonist, selectively decreases ethanol consumption and seeking. Proceedings of the National Academy of Sciences of the United States of America, 104, 12518 12523. Ventura, R., Alcaro, A., & Puglisi-Allegra, S. (2005). Prefrontal cortical norepinephrine release is critical for morphine-induced reward, reinstatement and dopamine release in the nucleus accumbens. Cerebral Cortex, 15, 1877 1886. Verplaetse, T. L., Rasmussen, D. D., Froehlich, J. C., & Czachowski, C. L. (2012). Effects of prazosin, an α1-adrenergic receptor antagonist, on the seeking and intake of alcohol and sucrose in alcoholpreferring (P) rats. Alcoholism-Clinical and Experimental Research, 36, 881 886. Volpicelli, J. R., Watson, N. T., King, A. C., Sherman, C. E., & O’Brien, C. P. (1995). Effect of naltrexone on alcohol “high” in alcoholics. American Journal of Psychiatry, 152, 613 615. Zink, R. W., Rohrbach, K., & Froehlich, J. C. (1997). Naltrexone and fluoxetine act synergistically to decrease alcohol intake. Alcoholism-Clinical and Experimental Research, 21, 104A.

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C H A P T E R

68 The Avermectin Family as Potential Therapeutic Compounds for Alcohol Use Disorder: Implications for Using P2X4 Receptor as a Drug-Screening Platform
1

Nhat Huynh1, Sheraz Khoja1, Liana Asatryan1, Michael W. Jakowec2 and Daryl L. Davies1

Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, United States 2Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States

LIST OF ABBREVIATIONS 10E 20E ABC Transporters ATP AUD CNS GABAARs HAD1 versus LAD1, HAD2 versus LAD2 HEK 293 iP versus iNP LGICs NAc NMDARs P versus NP P2XRs P2X4Rs P2X4R KO P-gp




10% v/v ethanol solution 20% v/v ethanol solution ATP-binding cassette transporters adenonsine-50 -triphosphate alcohol use disorders central nervous system gamma-aminobutyric acid receptors type A replicate lines of high-alcohol versus low-alcohol drinking rats cell line derived from human embryonic kidney inbred alcohol-preferring versus inbred nonpreferring rats ligand-gated ion channels nucleus accumbens N-methyl-D-aspartate receptors alcohol-preferring versus nonpreferring rats purinergic P2X receptors purinergic P2X4 receptors purinergic P2X4 receptor knockout P-glycoprotein

shRNA TM VTA WT

short hairpin RNA transmembrane ventral tegmental area wild type

INTRODUCTION Alcohol use disorder (AUD) continues to have a staggering impact on individuals and societies. It is currently the third leading preventable cause of death in the United States. Significant research efforts over the past two decades have only resulted in three FDA approved medications (disulfiram, naltrexone, and acamprosate) for the treatment of AUD. They work by blocking alcohol metabolism (leading to accumulation of a toxic metabolite) or by modulating the neural circuitries involved in craving/dependence. These pharmacotherapies have only produced limited results even when combined with psychosocial intervention, as evident by the fact that over 90% of patients relapse at least once after undergoing treatment.

Nhat Huynh and Sheraz Khoja are equally contributed as co-first authors.

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00068-4

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© 2019 Elsevier Inc. All rights reserved.

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68. THE AVERMECTIN FAMILY AS POTENTIAL THERAPEUTIC COMPOUNDS FOR ALCOHOL USE DISORDER

Alcohol has been shown to act on a wide range of central nervous system (CNS) targets, while many still remain to be elucidated. This lack of information on important molecular targets has contributed to a bottleneck in AUD drug development. The need to rapidly identify more novel targets that will allow for successful translation of preclinical studies represent an important public health goal. In this chapter, we will present a largely unexplored target, purinergic P2X4 receptors (P2X4Rs) that belong to the purinergic superfamily of ligand-gated ion channels (LGICs). We will also provide evidence from our preclinical investigations on the repurposing potential of certain avermectins into novel AUD medications based on their pharmacological activity at this receptor.

OVERVIEW OF PURINERGIC P2X4 RECEPTORS LGICs have been widely implicated to be important for ethanol induced behavioral effects. In particular, the family of purinergic P2X receptors (P2XRs) is emerging as a focal point of investigation in ethanol studies (Harris, 1999). P2XRs are fasting-acting, cationpermeable ion channels that are gated by extracellular adenosine-50 -triphosphate (ATP). Seven subunits (P2X1P2X7) have been identified that can assemble into a functional receptor in homotrimeric or heterotrimeric form. Of these subtypes, P2X4Rs are the most abundantly expressed in the CNS at both the presynaptic and postsynaptic terminal on most neurons and microglia (Khakh, 2001). P2X4Rs have been associated with several important CNS functions—such as the regulation of neuropathic pain, neuroendocrine functions, and hippocampal plasticity—possibly by modulating the activity of important ionotropic receptors such as GABAA receptors (GABAARs) and N-methylD-aspartate receptors (NMDARs). For example, postsynaptic P2X4Rs can regulate NMDAR-mediated currents in the CA1/CA3 pyramidal regions of the hippocampus and GABAAR-mediated currents within various hypothalamus nuclei (Baxter, Choi, Sim, & North, 2011). Presynaptic P2X4Rs can also modulate neurotransmitter release (e.g., GABA, glutamate) in the spinal cord and various CNS regions (Li, Peoples, & Weight, 1998). Our biochemical characterizations also reported that P2X4R knockout (KO) mice exhibited altered expressions of important proteins that are involved in glutamatergic/dopaminergic neurotransmission, which further implicates an interaction between P2X4Rs and these neurotransmitter receptor systems (Khoja et al., 2016; Wyatt et al., 2013). Speculation about the link between P2X4Rs and addiction behavior was recently raised when P2X4Rs

were found to localize within important regions of the reward circuitries [e.g., ventral tegmental area (VTA) and the nucleus accumbens (NAc)]. Subsequent functional studies have shown that administration of ATP can modulate release of glutamate/dopamine in the NAc and VTA (Krugel, Spies, Regenthal, Illes, & Kittner, 2004). This ability of P2X4Rs to interact with neurotransmitter receptor systems, that are known to play important roles in ethanol behaviors, suggests that P2X4Rs can influence reward pathways’ synaptic signaling. This chapter discusses converging evidence that continue to strengthen the relationship between P2X4Rs and ethanol behavior and how we are using P2X4Rs as a drug-development platform in our preclinical investigation of avermectins as novel AUD medications.

RELATIONSHIP BETWEEN P2X4RS AND ETHANOL In Vitro Evidence Among all subtypes, P2X4R is the most ethanolsensitive. The ATP-induced current in P2X4Rs is inhibited by ethanol in a dose-dependent manner, with similar findings observed across multiple expression systems (e.g., Xenopus oocytes, HEK 293 cells, and lentiviral-transduced mouse hippocampal neurons) (Ostrovskaya et al., 2011). It was found that 5 mM of ethanol was the lowest concentration that exhibits this inhibitory effect on P2X4Rs (Li et al., 1998). This is well below the legally intoxicated bloodethanol concentration in the United States (17 mM, or 0.08%). Earlier electrophysiological studies have suggested that ethanol acts by inducing an allosteric decrease of ATP-binding affinity (Xiong, Hu, Stewart, Weight, & Li, 2005). However, our investigations indicated that ethanol inhibition can act independently of ATP concentration (1100 μM). Further, ethanol exposure did not accelerate channel deactivation or stabilize the desensitized (open) state (Ostrovskaya et al., 2011). Thus, contrary to previous findings, our results suggest that ethanol likely acts as an open-channel blocker with rapid association and dissociation low-affinity binding. Despite the contrast, all the studies agree that ethanol can interact directly with P2X4Rs. With regards to the ethanol-binding site on P2X4Rs, our previous mutagenesis studies in P2X2 and P2X3 receptors have identified the transmembrane (TM) segments as important regions (Asatryan et al., 2010). We extended this investigation to P2X4Rs, where we found that Asp 331 and Met 336 in the TM regions, when mutated to alanine, reduced ethanol inhibition in a differential manner. Asp 331 mutation was sensitive at

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PRECLINICAL INVESTIGATIONS OF AVERMECTINS

higher ethanol concentrations ( . 50 mM) while Met 336 mutation was sensitive at lower concentrations (10 mM) (Popova et al., 2010). The involvement of these two critical residues in ethanol action was later confirmed with the molecular model of rat P2X4R, which further identified Trp 46 and Trp 50 as other important residues that contribute to the ethanolbinding pocket (Popova et al., 2013). These studies continue to support the notion that ethanol have multiple binding sites with different sensitivity.

In Vivo Evidence Investigations using rodent models of alcoholism also support the link between P2X4Rs and drinking. Reduced expression of the p2rx4 gene was found in five brain regions of inbred alcohol-preferring (iP) versus nonpreferring (iNP) rats (Kimpel et al., 2007). Reduced p2rx4 was also found in the VTA of male alcohol-preferring (P) versus nonpreferring (NP) and high-alcohol drinking (HAD1) versus low-alcohol drinking (LAD1) rats (McBride et al., 2012). Similarly, we have also reported that male P2X4R KO and knockdown [via lentiviral-short hairpin RNA (shRNA) microinjected into the NAc] mice consumed significantly greater amounts of ethanol when compared to wild type (WT) controls (Khoja, Huynh, Asatryan, Jakowec, & Davies, 2018; Wyatt et al., 2014). Interestingly, it was also reported that p2rx4 was increased in a replicate HAD2 rat line versus its LAD2 counterparts (McBride et al., 2012), and the lentiviralshRNA mediated knockdown of P2X4Rs in the VTA also significantly reduced drinking in female HAD2 rats (Franklin, Hauser, Lasek, Bell, & McBride, 2015). The overall theme reinforces the relationship between P2X4Rs and ethanol behavior, and that this regulation may be sex, species, and brain region dependent.

PRECLINICAL INVESTIGATIONS OF AVERMECTINS The class of avermectins is a group of semisynthetic macrocyclic lactones derived from a soil organism, Streptomyces avermectinius. They are widely popular for exhibiting broad-spectrum anti-parasitic activity and being well-tolerated (Crump & Omura, 2011). Avermectins exert their effect by acting on nonmammalian glutamate-gated chloride ion channels leading to cellular hyper-polarization, paralysis, and eventually death of the Onchocerca volvulus. Avermectins have also been reported to be positive modulator of various mammalian LGICs such as GABAARs, glycine

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receptors, nicotinic acetylcholine receptors, and P2X4Rs (Wolstenholme & Rodgers, 2005). The introduction of ivermectin in the 1980s has revolutionized parasite control in veterinary and human medicine. Up till 2003, ivermectin has safely and effectively treated over 40 million people and contributed significantly to the fight against onchocerciasis in many areas where tropic diseases are endemic (Crump & Omura, 2011). With increasing anthelmintic resistance, other avermectins are currently being developed. Moxidectin is currently in clinical development as an alternate to ivermectin with excellent safety signals reported to date (Korth-Bradley et al., 2012).

Preclinical Ivermectin Study Earlier studies have suggested that ivermectin binds at overlapping sites with ethanol. Our investigation demonstrated that ivermectin can competitively antagonize ethanol inhibition on P2X4Rs in a concentrationdependent manner (Asatryan et al., 2010). Notably, a low dose (0.5 μM) of ivermectin was able to eliminate the inhibition on P2X4Rs by 25 and 50 mM of ethanol. Note that 25 mM ethanol is 1.5 times the legally intoxicated limit of 17 mM. This result implicates that ivermectin can potentially negate the ethanol-induced behavioral effects in intoxicating humans. We also performed mutational studies which demonstrated that Met 336 and Trp 46 on the TM domain of P2X4R, previously identified as important for ethanol action, are also critical for ivermectin action. Consistent with these results, our molecular modeling study also suggests that ethanol and ivermectin share common targets and that the interaction between these residues (Asp 331, Met 336, Trp 46, Trp 50) form the binding pocket for both drugs (Asatryan et al., 2010; Popova et al., 2013). These in vitro findings led us to hypothesize that ivermectin may have an effect on ethanol drinking behavior. In support of this, we demonstrated that acute administration of ivermectin was able to significantly reduce drinking in both male and female mice, using different paradigms that mimic social drinking (two-bottle choice), binge drinking (Drinking-in-theDark), and alcohol-seeking behavior (operant chamber) (Yardley et al., 2012). The ability of ivermectin to reduce drinking in voluntary consumption and selfadministration models indicates that it may negate the positive reinforcing effects of ethanol. The dosedependent anti-alcohol effect of ivermectin also correlates with detectable ivermectin concentration in the brain, which confirms that ivermectin acts centrally in relation to ethanol intake. Notably, ivermectin did not induce significant changes in water intake, body weight, or food intake, which indicates that it does not

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FIGURE 68.1 P2X4R drug-screening platform. (A) Ivermectin (IVM) and abamectin (ABM) eliminated the ethanol inhibitions on P2X4Rs while selamectin (SLM) had no effect on P2X4R function, values 5 mean 6 SEM for 517 oocytes per data point,
P , .05 versus ethanol application, unpaired t-test. Rat p2rx4 cRNA was used in the Xenopus oocyte/two-electrode voltage clamp system. (B) 5 mg/ kg IVM and ABM (administered intraperitoneally) reduced 10% v/v ethanol solution (10E) intake in male C57BL/6J mice using a twobottle choice, values 5 mean 6 SEM for 78 mice per group,
P , .05,

P , .01 versus Pre-Drug (day prior to drug administration), unpaired t-test. Source: Reprinted from Asatryan, L., Yardley, M. M., Khoja, S., Trudell, J. R., Huynh, N., Louie, S. G., . . . & Davies, D. L. (2014). Avermectins differentially affect ethanol intake and receptor function: Implications for developing new therapeutics for alcohol use disorders. The International Journal of Neuropsychopharmacology/ Official Scientific Journal of the Collegium Internationale Neuropsychopharmacologicum (CINP), 17, 907916 with publisher’s permission.

have any deleterious effect on the overall health of animals. We extended our investigations to other avermectins that include abamectin and selamectin. The results allowed us to establish that the ability of these avermectins to reduce drinking in mice also strongly correlates with their ability to antagonize ethanol inhibition on P2X4Rs in vitro (Fig. 68.1A and B) (Asatryan et al., 2014). Although selamectin had the highest brain accumulation, it did not cause any reduction in drinking, which correlates with its inability (even at very high concentration of 10 μM) to eliminate ethanol

inhibition on P2X4Rs. Animal studies by other researchers using male and female HAD1 and HAD2 rats also support our results that acute ivermectin administration results in decreased drinking (Franklin et al., 2015). As AUD is a chronic disease that will likely require long-term pharmacotherapy, we further tested the efficacy and tolerability of chronic (30 days) ivermectin administration in the presence of ethanol. As expected, ivermectin significantly reduced drinking across the entire testing period. There were no signs of overt toxicity, tolerance, or dependence. Notably, we also did not identify any altered morphology or signs of histopathological development when analyzing the major organs (Yardley, Huynh, Rodgers, Alkana, & Davies, 2015). We also tested other potential adverse effects of ivermectin using a broad set of behavioral paradigms that assess the emotional, perceptual, and cognitive functions in mice. We found that ivermectin exhibited anxiolytic properties in the elevated plus maze and marble burying paradigms, which could be from the modulation of GABAARs. This feature may enhance its therapeutic effect since many alcoholics also suffer from comorbid anxiety. Although suggested to have some GABAAR activity, a high dose (10 mg/kg) of ivermectin did not exhibit addictive properties in the conditioned place preference test (Bortolato et al., 2013). This dose is twice the minimum effective antialcohol dose (5 mg/kg) of ivermectin (Yardley et al., 2012). This result suggests that the anti-alcohol effect of ivermectin is dissociated from potential addictive properties that can impact therapy compliance.

Preclinical Moxidectin Study Recently, we have directed our focus to the preclinical development of moxidectin. Part of this effort is based on emerging literature suggesting that moxidectin has a superior CNS safety profile compared to ivermectin (Janko & Geyer, 2013). Firstly, moxidectin is a weaker substrate for P-glycoprotein [P-gp, which belongs to the ATP-binding cassette (ABC) transporter family] than ivermectin and is less dependent on P-gp for removal from the brain. Secondly, in agreement with published studies, our investigation also showed that moxidectin has lower potency on GABAARs compared to ivermectin (Fig. 68.2) (Huynh et al., 2017). These results suggest that the use of MOX as a longterm AUD treatment will less likely lead to complications arising from: (1) toxic brain accumulation due to a deficiency in P-gp function and/or drugdrug interaction with other concurrent medications (e.g. P-gp substrates) and (2) excessive stimulation of GABAARs that can result in CNS depression and potentially

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coma. These advantageous features have been attributed to the structural differences between moxidectin and ivermectin. Both compounds share a common macrocyclic lactone ring with different substituents at position C13, C23, and C25 (Fig. 68.3A and B). The combination of these differing substituents is thought to govern the differential P-gp binding affinity and GABAARs potentiation (Huynh et al., 2017; Lanusse et al., 1997). Moxidectin is already in clinical development as an alternate anti-parasitic agent to ivermectin with no significant clinical abnormalities reported to date (KorthBradley et al., 2012). Positive results from our preclinical investigations can rapidly translate moxidectin into clinic settings to combat alcoholism. In support of this,

FIGURE 68.2 Moxidectin (MOX) has minimal potentiation on GABAARs at high concentration when compared to ivermectin (IVM). Values 5 mean 6 SEM for 412 oocytes per data point,

P , .01,


P , .001 versus respective control, unpaired t-test. Rat GABAAR cDNA (α1:β2:γ2-1:1:10) was used in the Xenopus oocyte/ two-electrode voltage clamp system. Source: Reprinted from Huynh, N., Arabian, N., Naito, A., Louie, S., Jakowec, M. W., Asatryan, L., & Davies, D. L. (2017). Preclinical development of moxidectin as a novel therapeutic for alcohol use disorder. Neuropharmacology, 113, 6070 with publisher’s permission.

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our electrophysiological and behavioral evidence indicated that moxidectin is an effective anti-alcohol agent and has comparable efficacy to ivermectin. Similar to ivermectin, a very low dose (0.5 μM) of moxidectin eliminated the inhibitory effects of 25 mM ethanol on P2X4Rs (Huynh et al., 2017). This was the first piece of evidence regarding the anti-alcohol effect of moxidectin (based on the P2X4R platform) that has allowed us to move moxidectin forward into animal testing. In agreement with our in vitro findings, acute moxidectin administration also reduced ethanol intake in both male and female mice across several different alcohol drinking paradigms (Fig. 68.4A and B). We also identified that moxidectin elicited a significant reduction in drinking at 4 hours post administration, which is much faster than the 9 hours for ivermectin (Huynh et al., 2017). The faster brain penetration again has been attributed to the differing substituents on these compounds with moxidectin having higher lipophilicity (Lanusse et al., 1997). This also partially explains why a lower dose (2.5 mg/kg) of moxidectin has faster onset time and exhibits similar efficacy to a higher dose (5 mg/kg) of ivermectin (Huynh et al., 2017; Yardley et al., 2012). We further tested the efficacy and tolerability of moxidectin in a long-term (30 days) drinking study using a Drinking-in-the-Dark model. This paradigm has been well-characterized to model binge drinking behavior in humans. We found that moxidectin consistently reduced drinking across the entire testing period without signs of overt toxicity, tolerance, or dependence (Fig. 68.4C). It is wellaccepted that repeated binge drinking is the transition period between recreational use to substance abuse, thus, our results indicate that moxidectin can potentially be applied to this population of alcoholics. Ongoing works are also testing moxidectin using

FIGURE 68.3 Structures of (A) ivermectin and (B) moxidectin. C13: ivermectin contains disaccharide; moxidectin is protonated. C23: moxidectin contains methoxime. C25: ivermectin is a mixture of C25-ethyl and C25-methyl, moxidectin has a dimethyl-butyl group. Source: Reprinted from Huynh, N., Arabian, N., Naito, A., Louie, S., Jakowec, M. W., Asatryan, L., & Davies, D. L. (2017). Preclinical development of moxidectin as a novel therapeutic for alcohol use disorder. Neuropharmacology, 113, 6070 with publisher’s permission.

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FIGURE 68.4 Moxidectin (MOX) reduced ethanol intake in C57BL/6J mice using different drinking paradigms. Acute intraperitoneal administration of MOX reduced 10E intake in (A) male and (B) female mice in a dose-dependent manner, using a two-bottle choice paradigm, values 5 mean 6 SEM for 12 mice per group,
P , .05,

P , .01, #P , .0001 versus pre-MOX (day prior to MOX injection), two-way ANOVA. (C) MOX (5 mg/kg) was administered intraperitoneally for 30 days and consistently reduced 20% v/v ethanol solution (20E) intake in female mice across the entire testing period using a Drinking-in-the-Dark paradigm, values 5 mean 6 SEM for 1014 mice per group,
P , .05 versus saline-injected control, two-way ANOVA. Source: (A,B) Reprinted from Huynh, N., Arabian, N., Naito, A., Louie, S., Jakowec, M. W., Asatryan, L., & Davies, D. L. (2017). Preclinical development of moxidectin as a novel therapeutic for alcohol use disorder. Neuropharmacology, 113, 6070 with publisher’s permission.

various rodent models of alcoholism that replicate more severe stages of AUD (e.g., ethanol dependence and ethanol-induced withdrawal) with positive results so far (Fig. 68.5A and B). Taken together, the robust efficacy and advantageous CNS safety profile continue to support the development of moxidectin into a novel AUD medication.

Anti-alcohol Mechanism(s) of Avermectins Although avermectins are proposed to have multiple CNS targets, we have shown that the majority of their anti-alcohol effects comes from their activity on P2X4Rs. As shown in Fig. 68.6A and B, the reduction in drinking for moxidectin treatment was significantly less in P2X4R KO mice versus WT. This agrees with our previous IVM/P2X4R KO study (Wyatt et al., 2014). These results are critical as they continue to support the use of P2X4R as an in vitro drug-development

platform. However, the exact mechanism(s) of avermectin-mediated reduction in drinking remain to be elucidated. One plausible explanation may be the ability of presynaptic P2X4Rs to regulate the release of GABA and/or glutamate onto dopamine neurons in the VTA and NAc (Krugel et al., 2004; Xiao, Zhou, Li, Davies, & Ye, 2008). These neurotransmitters can then inhibit or enhance (depending on factors such as brain regions, concentration of neurotransmitters, and timing of release) the firing rate of dopamine neurons, and subsequently modulate dopamine release. The inhibition of P2X4Rs by ethanol can lead to dysregulation that will result in abnormal dopaminergic activity and, consequently, the trend toward the development of addictive behavior. In support of this hypothesis, we have previously reported that P2X4Rs play a role in other dopamine-dependent behaviors including sensorimotor gating (prepulse inhibition test) and the 6-hydroxydopamine mouse model of dopamine

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IMPLICATIONS FOR TREATMENTS

FIGURE 68.5 Moxidectin (MOX) attenuated ethanol-induced withdrawal symptoms in C57BL/ 6J mice. Acute ethanol withdrawal symptoms were induced by a single intraperitoneal injection of 4 g/kg ethanol and the severity of withdrawal was measured using the handling-induced convulsion (HIC) scoring method (Finn & Crabbe, 1999). When simultaneously administered (intraperitoneally) with ethanol, MOX attenuated withdrawal symptoms in (A) male and (B) female mice when compared to control (saline/ethanol administration), values 5 mean 6 SEM for 1215 mice per time point for each group. The insets show that MOX/ethanol-treated mice have overall lower HIC score as indicated by the lower area under the curve (AUC) calculated from the respective HIC graphs, values 5 mean 6 SEM for 1215 mice per group,
P , .05 versus saline/ethanol-injected control, unpaired t-test.

needed to identify this signaling mechanism(s), this does not detract from the fact that both moxidectic and ivermectin still have high repurposing potential to be developed into novel AUD therapeutics. Both of these compounds have already been shown to be safe and well-tolerated in humans, and have exhibited positive results in all of our preclinical drinking studies.

IMPLICATIONS FOR TREATMENTS

FIGURE 68.6 Moxidectin (MOX) produced a twofold greater reduction in ethanol intake in male C57BL/6J WT versus P2X4R KO mice. (A) Baseline 10E intake level for WT and KO mice (averaged over 3 days), using a two-bottle choice, values 5 mean 6 SEM for 89 per group,
P , .05 versus WT mice, unpaired t-test. (B) Following acute intraperitoneal injection of 2.5 mg/kg MOX, reduction in 10E intake was significantly greater in WT (56%) versus KO (27%), values 5 mean 6 SEM for 89 per group,


P , .001 versus MOX-treated P2X4R KO mice, unpaired t-test.

depletion for motor activity, which further corroborates a link between P2X4Rs and dopaminergic signaling (Khoja et al., 2016). Thus, by counteracting the ethanol inhibition on P2X4Rs, avermectins can restore this balance. Although further investigations are

Our preclinical findings demonstrate the potential of certain avermectins for treatment of AUD patients. Both moxidectin and ivermectin showed robust efficacy across multiple rodent-drinking models. In particular, moxidectin significantly reduced ethanol intake using a chronic mouse model of binge drinking and also significantly attenuated acute ethanol-induced withdrawal symptoms in mice. Notably, there were no signs of overt toxicity, tolerance, or dependence in any of our studies. In agreement with previous findings, our results also indicate that moxidectin has an excellent CNS safety profile when compared to ivermectin. Overall, these findings suggest that moxidectin is highly suitable to be developed into a long-term therapy that can be applied to a broad population of alcoholics ranging from the transitional to more severe stages. Although ivermectin may not have the most

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advantageous CNS safety features and may not be appropriate for long-term therapy, we believe that it can still be developed into a beneficial AUD medication. We have already shown in a small-scale (10 patients) safety clinical trial that acute ivermectin administration is very well-tolerated in the presence of an intoxicated blood ethanol dose (e.g., .0.08%) (Roche et al., 2016). In Europe, nalmefene is approved for use on an as-needed basis. That is, a person can take nalmafene when they feel uncontrolled drinking is imminent. The use of this medication has broadened the treatment approach in Europe and allowed for an alternate objective of reduction in drinking rather than complete abstinence. This can be more readily accepted when complete abstinence is too difficult to achieve immediately. As such, we feel that ivermectin can serve the same purpose in the United States. Moving forward, we believe that both compounds have high repurposing value to be developed into novel AUD pharmacotherapies that will increase the number of treatment options available to clinicians and patients. A final point to consider is that the chronic use of anti-parasitic agents can potentially contribute to anthelmintic resistance. However, as we have investigated and gathered ample data from multiple avermectin analogs, a chemistry evaluation can easily make appropriate changes to our lead compounds and eliminate the anti-parasitic activity while enhancing the anti-alcohol effect.

MINI-DICTIONARY OF TERMS Electrophysiological studies The electrophysiological results described in this chapter were achieved mainly via two techniques: Xenopus oocyte expression system coupled with twoelectrode voltage clamp, and a patch clamp method on brain slices or cell cultures. Ligand-gated ion channels (LGICs) Three large superfamilies of ionotropic receptors. Cys-loop receptors: nicotinic acetylcholine receptors, 5-hydroxytryptamine type 3 receptors (5-HT3s), gamma-aminobutyric acid receptors type A (GABAARs), and glycine receptors. Glutamate receptors: NMDARs, α-amino-3hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPARs), and kainite receptors. Purinergic P2X receptors: P2X1 to P2X7 receptors. Mice overt toxicity Abnormal overt behavior in mice (due to toxicity following drug treatment) can include indications such as being unresponsive to experimenter intervention or handling, piloerection of fur, minimal movement with hunched posture, constantly huddling in the cage corner, significant decreased food intake and/or weight. P-glycoprotein (P-gp) substrates A large variety of drugs that can act as substrates, inhibitors, and inducers of P-gp, consequently resulting in drugdrug interaction and potentially reduced efficacy of treatment(s) and/or toxic side effects in patients. We redirected our focus to the preclinical development of moxidectin after identifying that ivermectin is strongly dependent on P-gp for brain export.

Ventral tegmental area (VTA) and the nucleus accumbens (NAc) The mesolimbic dopaminergic pathway is comprised of the VTA in the midbrain connecting to the NAc in the ventral striatum. The release of dopamine in these regions has been widely implicated in regulating addictive behavior. The mesocortical dopaminergic pathway consisting of the VTA connecting to the prefrontal cortex in the frontal lobe is closely associated with the mesolimbic circuitry and also plays a role in reward/ addiction.

KEY FACTS The Burden of Alcohol Use Disorders • In 2012, AUD accounts for 5.9% (B3.3 million) of global deaths. • A component cause for over 200 diseases (e.g., liver cirrhosis, certain cancers, and numerous cardiovascular/gastrointestinal diseases). • In the United States, over 16 million people have been diagnosed with AUD and contributed to over 100,000 deaths and an economic cost of $220 1 billion annually. • Prevalence of binge drinking (a potential transition stage from recreational use to addiction) in 2015 in the United States: over 26% of people ages over 18, 13% of ages 1220, and 37% of college students ages 1822 reported binge drinking in the past month. • In 2012, only about 8% of adults in the United States with AUD are treated with pharmacotherapies. • There are two main reasons for this: (1) patients perceive the ineffectiveness of medications; and (2) resistance from physicians to treating substance abuse with another substance.

SUMMARY POINTS • P2X4 receptors are present in multiple brain regions (e.g., VTA and the nucleus accumbens) that have been implicated in addiction behavior. • P2X4 receptors can modulate neurotransmitter receptor systems activity postsynaptically (e.g., NMDA receptor-mediated current) and presynaptically (e.g., dopamine/glutamate release) throughout the CNS. • A low ethanol concentration of 5 mM significantly inhibits the ATP-induced current in P2X4 receptors. • Genomic studies identified an inverse relationship between the expression of p2rx4 gene and the level of ethanol intake in different strains of mice and rats. • Lentiviral-shRNA mediated knockdown of P2X4 receptor expression in the nucleus accumbens of

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REFERENCES

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•

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mice and in the VTA of rats significantly altered drinking. Avermectins (e.g., ivermectin, moxidectin) significantly antagonize the ethanol inhibition on P2X4R function. In vitro activity of avermectins strongly correlates with their ability to significantly reduce ethanol intake in mice across multiple, rodent-drinking paradigms. Reduction in drinking was twofold greater in wild type compared to P2X4 receptor knockout mice, which confirms that the majority of the anti-alcohol effect of avermectins are based on their activity on P2X4 receptors. Both ivermectin and moxidectin have been safely tested in humans for different indications. Both compounds possess high repurposing values to be developed into novel anti-alcohol medications based on positive preclinical results.

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Janko, C., & Geyer, J. (2013). Moxidectin has a lower neurotoxic potential but comparable brain penetration in P-glycoproteindeficient CF-1 mice compared to ivermectin. Journal of Veterinary Pharmacology and Therapeutics, 36, 275284. Khakh, B. S. (2001). Molecular physiology of P2X receptors and ATP signalling at synapses. Nature Reviews Neuroscience, 2, 165174. Khoja, S., Huynh, N., Asatryan, L., Jakowec, M. W., & Davies, D. L. (2018). Reduced expression of purinergic P2X4 receptors increases voluntary ethanol intake in C57BL/6J mice. Alcohol (Fayetteville, N.Y.), 68, 6370. Khoja, S., Shah, V., Garcia, D., Asatryan, L., Jakowec, M. W., & Davies, D. L. (2016). Role of purinergic P2X4 receptors in regulating striatal dopamine homeostasis and dependent behaviors. Journal of Neurochemistry, 139, 134148. Kimpel, M. W., Strother, W. N., McClintick, J. N., Carr, L. G., Liang, T., Edenberg, H. J., & McBride, W. J. (2007). Functional gene expression differences between inbred alcohol-preferring and -non-preferring rats in five brain regions. Alcohol (Fayetteville, N.Y.), 41, 95132. Korth-Bradley, J. M., Parks, V., Patat, A., Matschke, K., Mayer, P., & Fleckenstein, L. (2012). Relative bioavailability of liquid and tablet formulations of the antiparasitic moxidectin. Clinical Pharmacology in Drug Development, 1, 3237. Krugel, U., Spies, O., Regenthal, R., Illes, P., & Kittner, H. (2004). P2 receptors are involved in the mediation of motivation-related behavior. Purinergic Signalling, 1, 2129. Lanusse, C., Lifschitz, A., Virkel, G., Alvarez, L., Sa´nchez, S., Sutra, J. F., . . . Alvinerie, M. (1997). Comparative plasma disposition kinetics of ivermectin, moxidectin and doramectin in cattle. Journal of Veterinary Pharmacology and Therapeutics, 20, 9199. Li, C., Peoples, R. W., & Weight, F. F. (1998). Ethanol-induced inhibition of a neuronal P2X purinoceptor by an allosteric mechanism. British Journal of Pharmacology, 123, 13. McBride, W. J., Kimpel, M. W., McClintick, J. J., Ding, Z. M., Hyytia, P., Colombo, G., . . . Bell, R. L. (2012). Gene expression in the ventral tegmental area of 5 pairs of rat lines selectively bred for high or low ethanol consumption. Pharmacology, Biochemistry, and Behavior, 102, 275285. Ostrovskaya, O., Asatryan, L., Wyatt, L., Popova, M., Li, K., Peoples, R. W., . . . Davies, D. L. (2011). Ethanol is a fast channel inhibitor of P2X4 receptors. The Journal of Pharmacology and Experimental Therapeutics, 337, 171179. Popova, M., Asatryan, L., Ostrovskaya, O., Wyatt, L. R., Li, K., Alkana, R. L., & Davies, D. L. (2010). A point mutation in the ectodomain-transmembrane 2 interface eliminates the inhibitory effects of ethanol in P2X4 receptors. Journal of Neurochemistry, 112, 307317. Popova, M., Trudell, J., Li, K., Alkana, R., Davies, D., & Asatryan, L. (2013). Tryptophan 46 is a site for ethanol and ivermectin action in P2X4 receptors. Purinergic Signalling, 9, 621632. Roche, D. J., Yardley, M. M., Lunny, K. F., Louie, S. G., Davies, D. L., Miotto, K., & Ray, L. A. (2016). A pilot study of the safety and initial efficacy of ivermectin for the treatment of alcohol use disorder. Alcoholism, Clinical and Experimental Research, 40, 13121320. Wolstenholme, A. J., & Rodgers, A. T. (2005). Glutamate-gated chloride channels and the mode of action of the avermectin/milbemycin anthelmintics. Parasitology, 131, 8595. Wyatt, L. R., Finn, D. A., Khoja, S., Yardley, M. M., Asatryan, L., Alkana, R. L., & Davies, D. L. (2014). Contribution of P2X4 receptors to ethanol intake in male C57BL/6 mice. Neurochemical Research, 39, 11271139. Wyatt, L. R., Godar, S. C., Khoja, S., Jakowec, M. W., Alkana, R. L., Bortolato, M., & Davies, D. L. (2013). Sociocommunicative and sensorimotor impairments in male P2X4-deficient mice. Neuropsychopharmacology, 38, 19932002.

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Xiao, C., Zhou, C., Li, K., Davies, D. L., & Ye, J. H. (2008). Purinergic type 2 receptors at GABAergic synapses on ventral tegmental area dopamine neurons are targets for ethanol action. The Journal of Pharmacology and Experimental Therapeutics, 327, 196205. Xiong, K., Hu, X. Q., Stewart, R. R., Weight, F. F., & Li, C. (2005). The mechanism by which ethanol inhibits rat P2X4 receptors is altered by mutation of histidine 241. British Journal of Pharmacology, 145, 576586.

Yardley, M. M., Huynh, N., Rodgers, K. E., Alkana, R. L., & Davies, D. L. (2015). Oral delivery of ivermectin using a fast dissolving oral film: Implications for repurposing ivermectin as a pharmacotherapy for alcohol use disorder. Alcohol (Fayetteville, N.Y.), 49, 553559. Yardley, M. M., Wyatt, L., Khoja, S., Asatryan, L., Ramaker, M. J., Finn, D. A., . . . Davies, D. L. (2012). Ivermectin reduces alcohol intake and preference in mice. Neuropharmacology, 63, 190201.

VII. TREATMENTS, STRATEGIES AND RESOURCES

C H A P T E R

69 Alcohol Withdrawal Syndrome: Clinical Picture and Therapeutic Options Sarah Jesse and Albert Ludolph Department of Neurology, University of Ulm, Ulm, Germany

LIST OF ABBREVIATIONS AST ALT AUDIT AWS AWSc BZD CAGE CDT CIWA-Ar CNS DSM-5 DT EEG FAST GABA HIAA HTOL MCV MRI NMDA PAWSS RAAS TWEAK

receive the same diagnosis? Yes, both patients could, but due to delayed diagnosis and treatment, the second patient is at risk for complications and a worse outcome.

aspartate aminotransferase alanine aminotransferase Alcohol Use Disorder Identification Test alcohol withdrawal syndrome Alcohol Withdrawal Scale benzodiazepine Cut down, Annoyed, Guilty, Eye-opener carbohydrate deficient transferrin Clinical Institute Withdrawal Assessment in its revised version central nervous system Statistical Manual of Mental Disorders delirium tremens electroencephalogram Fast Alcohol Screening Test gamma aminobutyric acid 5-hydroxyindole-3-acetic acid 5-hydroxytryptophol mean corpuscular volume magnetic resonance imaging N-methyl-D-aspartate prediction of alcohol withdrawal severity scale Richmond Agitation and Sedation Score Tolerance, Worried, Eye-opener, Amnesia, K cut down

ALCOHOL WITHDRAWAL: A WIDE RANGE OF SYMPTOMS

INTRODUCTION If a patient with foetor alcoholicus, generalized tonic clonic seizures, tremor, dysautonomia, elevated liver enzymes, and a history of chronic alcohol intake attends the emergency unit, the diagnosis would be evident. Another patient with insomnia, disorientation, persecutory delusions, hypokalemia, and thrombocytopenia attends the outpatient clinic; would this patient

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00069-6

Mortality of delirium tremens (DT) and/or frequent epileptic seizures during alcohol withdrawal syndrome (AWS) is comparable to that of patients having severe malignant diseases. The earlier therapeutic interventions in AWS are started, the better the outcome, with mortality rates of 1% or less (Mainerova et al., 2015). The clinical picture represents a continuum of symptoms from autonomic, motor, awareness and psychiatric presentations that are listed in detail in Table 69.1. According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), the diagnosis of AWS requires cessation or reduction of alcohol use and exclusion of other medical, mental, or behavioral diseases that present with similar symptoms (APA, 2013). To facilitate diagnosis, prediction, and outcome, it is reasonable to grade symptoms according to time and severity that allow a classification of AWS into the categories of mild, moderate, and severe; with clinical presentation starting at about 6 hours after the last drink. Fig. 69.1 illustrates an appropriate classification of AWS. The typical patient with minor AWS in an early stage is conscious with intact orientation and symptoms that are restricted to autonomic presentation, tremor, hyperreflexia, and insomnia. Generally,

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© 2019 Elsevier Inc. All rights reserved.

672 TABLE 69.1

69. ALCOHOL WITHDRAWAL SYNDROME: CLINICAL PICTURE AND THERAPEUTIC OPTIONS

Summary of Clinical Symptoms in AWS

Autonomic symptoms

Motor symptoms

Awareness symptoms

Psychiatric symptoms

Dilated pupils

Hand tremor

Insomnia

Delusions

Diaphoresis

Body tremor

Disorientation

Illusions

Diarrhea

Gait disturbances

Hypoactive delirium

Paranoid ideas

Nausea

Ataxia

Hyperactive delirium

Hallucinations

Vomiting

Dysarthria

Irritability

Anxiety

Tachykardia

Hyperreflexia

Agitation

Affective instability

Tachypnea

Seizures

Disinhibition

Blood pressure m

Combativeness

Temperature m This table summarizes clinical symptoms that cover autonomic, motor, awareness, and psychiatric manifestations. For diagnosis of AWS, it is not necessary that a patient presents with symptoms out of all these categories. With permission from Jesse, S., Brathen, G., Ferrara, M., Keindl, M., Ben-Menachem, E., Tanasescu, R., & Ludolph, A. C. (2017). Alcohol withdrawal syndrome: Mechanisms, manifestations, and management. Acta Neurologica Scandinavica, 135(1), 4 16.

FIGURE 69.1 Classification of AWS. This figure illustrates the classification of AWS into mild, moderate, and severe, depending on the time (x-axis) and the severity of symptoms (y-axis). Source: With permission from Jesse, S., Brathen, G., Ferrara, M., Keindl, M., Ben-Menachem, E., Tanasescu, R., & Ludolph, A. C. (2017). Alcohol withdrawal syndrome: Mechanisms, manifestations, and management. Acta Neurologica Scandinavica, 135(1), 4 16.

these motor and autonomic symptoms last up to 4 48 hours. Additional occurrence of psychiatric symptoms as illusions and hallucinations—visual, tactile, or auditory—in a conscious patient characterizes moderate AWS that can persist up to 6 days. The occurrence of withdrawal seizures with generalized tonic clonic manifestations is quite probable and may represent the first, or even the only sign of AWS with the risk of passing into a convulsive or nonconvulsive status epilepticus (Rathlev, Ulrich, Delanty, & D’Onofrio, 2006). Furthermore, clinical presentation of

seizures is associated with an increase in up to fourfold mortality and often represents a strong risk factor for smooth transition into a severe withdrawal syndrome with development of DT in 30% of the cases (Victor & Brausch, 1967). DT is a dreaded clinical manifestation of AWS and typically emerges after 2 14 days. Most cases present themselves as hyperactive delirium with psychomotor restlessness, somatic dysregulation of vegetative or central nervous system manifestation, and impaired perception—frequently associated with hallucinations (Sarkar, Choudhury,

VII. TREATMENTS, STRATEGIES AND RESOURCES

LABORATORY PARAMETERS AS DIAGNOSTIC TOOLS

TABLE 69.2

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Most Relevant Differential Diagnoses of AWS

Differential diagnosis

Clinical and additional findings

Electrolyte disturbances

Laboratory findings, medical history, peculiar behavior

Encephalopathy (uremic, hepatic, drug induced)

Qualitative and quantitative impairment of consciousness Typical signs of uremia, hepatic failure or positive medical history by proxy

Meningitis/encephalitis

Fever, headache, meningism, possible focal neurological deficit, seizures

Sepsis

Fever, focus, impairment of blood pressure, laboratory infectious parameters

Head trauma

History of being found, head laceration, possible focal neurological deficit

Intoxication

Medication anamnesis, blister packages, possible indications of suicide, altered sensorium

Psychosis

Illusions, hallucinations, possible psychiatric anamnesis, no clouding of consciousness

Thyrotoxicosis

History of thyroid illness, fever, lab diagnostics for thyroid hormones

The table summarizes relevant differential diagnoses of AWS that include encephalopathy, encephalitis, electrolyte disturbances, trauma, and hormone- or druginduced imbalances. The typical clinical presentation and additional findings are mentioned. With permission from Jesse, S., Brathen, G., Ferrara, M., Keindl, M., Ben-Menachem, E., Tanasescu, R., & Ludolph, A. C. (2017). Alcohol withdrawal syndrome: Mechanisms, manifestations, and management. Acta Neurologica Scandinavica, 135(1), 4 16.

Ezhumalai, & Konthoujam, 2017). Exceedingly difficult to diagnose are those patients whose manifestation of DT is accompanied by a hypoactive state with decreased arousal and psychomotor activity so that, in particular, other medical illnesses must be ruled out and diagnosis of AWS is made by exclusion. The most important differential diagnoses for severe AWS are listed in Table 69.2 and include encephalopathy, encephalitis, and intoxication, as well as hormone and electrolyte disturbances. Independent of the severity state of AWS, clinical comanifestation of Wernicke’s encephalopathy should be taken into account, whose appearance is often divergent from the classical triade of ataxia, amnesia, and ophthalmoplegia which are restricted to a few of the cases.

LABORATORY PARAMETERS AS DIAGNOSTIC TOOLS At the time when medical history by proxy and physical examination strongly suggest existence of AWS, additional diagnostic tools should be used to substantiate tentative diagnoses. Vital signs like heart rate, blood pressure, and body temperature are easily obtained and frequently altered, but are not specific and have a low predictive value. To confirm the suspected clinical diagnosis, laboratory routine markers accessible in less than 6 hours play the most important diagnostic role. Foremost, detection of ethanol itself in various specimens like breath, blood, and urine is a common tool for confirmation of alcohol use with high sensitivity and specificity. Indeed, analysis is hampered by individual characteristics of alcohol metabolism due to

pharmacokinetic and pharmacodynamic responses that are influenced by environmental and genetic factors (Nanau & Neuman, 2015). Other markers useful in the emergency setting are hypokalemia and thrombocytopenia that are also of low specificity, but often associated with, and predictive for, segue into severe AWS (Harshe et al., 2017) and, for this reason, are indispensable in the diagnostic progress rather than the erythrocyte mean corpuscular volume, ɣ-glutamyltransferase, and the ratio AST/ALT . 2 that are subjected to many influencing factors like age, gender, comorbidities, and medication (Topic & Djukic, 2013). Alcohol-induced glucoconjugate metabolites like the well-known carbohydrate deficient transferrin (CDT) or sialic acid and ethylglucoronide—as well as other direct products of ethanol degradation like phosphatidylethanol, ethylsulfate, and fatty acid ethyl-esters—represent markers with partial high sensitivity and specificity that are not feasible in the emergency setting due to delayed or unavailable access. This also applies to the ratio 5-hydroxyindole3-acetic acid (HIAA)/5-hydroxytryptophol (HTOL) that increases fast in urine after ethanol consumption with a short window of detection of 24 hours (Hoiseth et al., 2008). Out of these long-term markers, homocysteine exclusively seems to be useful in the clinical routine setting especially in combination with CDT (Hillemacher et al., 2012) whereupon nutritional status and polymorphisms in the 5,10-methylenetetrahydrofolate reductase as the enzyme relevant for homocysteine metabolism have to be considered (Lutz et al., 2006). Table 69.3 illustrates an overview of the most relevant markers in the emergency setting that are available within 6 hours and, for the sake of

VII. TREATMENTS, STRATEGIES AND RESOURCES

TABLE 69.3 Summary of Laboratory Findings in AWS Biomarker

Sensitivity (%)/ Specificity (%)

Specimen

Detectable until . . .

Reference

Ethanol

95/90

Breath Blood Urine

5 24 hours decrease of 0.15% /h

Nanau et al.

Potassium k

90/50

Blood

Days to weeks

Goodson, Clark, and Douglas (2014)

Platelets k

75/70

Blood

7 12 days

Kim et al.

Erythrocyte MCV m

60/80

Blood

4 months

Topic et al.

γ-Glutamyltransferase

65/80

Blood

2 8 weeks

Topic et al.

Ratio AST/ALT . 2

80/50

Blood

AST 18 h/ALT 36 h

Topic et al.

Biomarker

Sensitivity (%)/ Specificity (%)

Specimen

Detectable until . . .

Reference

CDT

70/98

Blood

2 4 weeks

Hillemacher et al.

Ethylglucuronid

89/99

Blood Urine Hair

8h 20 80 h 3 months

Hoiseth et al.

Ethylsulfate

89/99

Blood Urine

8h 36 78 h

Hoiseth et al.

Phosphatidylethanol

89/99

Blood

4 weeks

Hoiseth et al.

Fatty acid ethyl esters

77/97

Blood Hair

24 h 3 months

Hoiseth et al.

Ratio 5-HTOL/5-HIAA

77/99

Urine

24 h

Hoiseth et al.

Sialic acid

81/95

Blood

Several weeks

Hoiseth et al.

Homocysteine

72/61

Blood

Several weeks

Lutz et al.

The first part of the table shows laboratory markers that are easy to access within 6 hours and helpful to confirm the suspected diagnosis. Of these, hypokalemia and thrombocytopenia are the most relevant as they indicate risk factors for severe alcohol withdrawal. The second part of the table shows markers that indicate long-term alcohol abuse and may be relevant for forensic questions. With permission from Jesse, S., Brathen, G., Ferrara, M., Keindl, M., Ben-Menachem, E., Tanasescu, R., & Ludolph, A. C. (2017). Alcohol withdrawal syndrome: Mechanisms, manifestations, and management. Acta Neurologica Scandinavica, 135(1), 4 16.

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HOW TO TREAT

completeness, parameters that indicate long-term alcohol abuse and may be relevant for forensic questions are included.

QUESTIONNAIRES: TOOLS TO GRADE SEVERITY OF SYMPTOMS In order to achieve a more objective assessment of withdrawal symptoms, some questionnaires may be helpful to detect alcohol use, prediction of AWS, or estimation of withdrawal severity. The tests to detect alcohol use disorders are dependent on the cooperation, honesty, self-reflexion, and comprehension of the patient, and are represented by the Alcohol Use Disorder Identification Test (Lundin, Hallgren, Balliu, & Forsell, 2015), the Fast Alcohol Screening Test (Jones, 2011), the Cut down, Annoyed by criticism, Guilty about drinking and need for an Eye-opener in the morning (Williams, 2014), and the Tolerance, Worried, Eye-opener, Amnesia, K cut down (Jones, 2011). Currently, there is only one test that identifies patients at risk for severe withdrawal that allows clinicians to treat the patient predictively: the Prediction of Alcohol Withdrawal Severity Scale (Maldonado et al., 2015). Questionnaires that rate severity of AWS allow adjustment of pharmacological intervention and guide therapeutic strategies. Of those tests, the Clinical Institute Withdrawal Assessment in its revised version (Sullivan, Sykora, Schneiderman, Naranjo, & Sellers, 1989) and the AWSc [Alcohol Withdrawal Scale (Wetterling et al., 1997)] are the most important ones. Again, their practicability and objectiveness depend on the qualitative and quantitative awareness of the patient. Especially in cases of impaired consciousness or lack of cooperation, common tools used in the intensive care unit setting, like the Richmond Agitation and Sedation Score, can be used. Table 69.4 highlights typical features as well as pros and cons of these questionnaires.

ASPECTS TO BEAR IN MIND BEFORE THERAPEUTIC INTERVENTION We now have reached a point where diagnosis of AWS can be positive according to the history by proxy, physical investigation, laboratory markers, and reasonable questionnaires. Before initiation of a pharmacological therapy, a few diagnostic approaches should be borne in mind concerning those patients who presented with an epileptic event, especially in cases with the first onset of seizures or status epilepticus. Patients with preexisting epilepsy, structural brain lesions, or multiple-drug dependency are at risk for seizures

during AWS (Brathen, Brodtkorb, Helde, Sand, & Bovim, 1999). Electroencephalogram (EEG) is recommended for every patient showing new onset seizures, novel semiology, or persistent altered sensorium when relevant subtle seizures in terms of nonconvulsive status epilepticus are suspected. Moreover, exclusion of other neurological conditions by magnetic resonance imaging (MRI) or computed tomography is advisable in patients with reduced consciousness and previous seizure or unexplained falls, and, in every case with ambiguous conditions. In cases of status epilepticus, MRI signal alterations may present with hyperperfusion and hyperintensities as correlates for edema in anatomical areas, like medial or dorsal hypothalamus, cerebral cortex, hippocampus, and amygdala that exceed vascular territories. These abnormalities show good, or at least partial, remission after elimination of the cause (Xiang, Li, Liang, & Zhou, 2014). Fig. 69.2 illustrates some typical MRI features from our hospital from patients with status epilepticus due to different origins.

HOW TO TREAT Therapeutic approaches in AWS rely on pathophysiological considerations. As a central nervous system (CNS) depressant, prolonged ethanol consumption results in downregulation of GABA receptors and compensatory increased expression of NMDA receptors to maintain transmitter homeostasis. In cases of withdrawal, manifestation of glutamatergic CNS excitotoxicity as well as dopamine plethora explain the clinical presentation (Rogawski, 2005). With this background, benzodiazepines (BZD) represent the drug of choice as they have a similar inhibitory effect to that of ethanol. Their bioavailability is high and penetration of the blood brain barrier is excellent, whereas distribution into various tissues is depending on their lipophilicity. Degradation of all BZD takes place in the liver with some drugs metabolizing into active metabolites so that they can be categorized as short (,12 hours, such as lorazepam, midazolam), intermediate (1 24 hours, such as clonazepam) or long acting ( . 24 hours, such as for clobazam or diazepam) which is helpful for the different therapeutic strategies and also with regard to the fact that they can induce seizures themselves when tapered (Riss, Cloyd, Gates, & Collins, 2008). Further inappropriate properties of BZD include confusion and paradoxical agitation which is difficult to distinguish from DT, respiratory depression, or excessive sedation. There are many dosing strategies for BZD,

VII. TREATMENTS, STRATEGIES AND RESOURCES

TABLE 69.4 Summary of Helpful Questionnaires in AWS Sensitivity (%)/ Specificity (%)

Reference

92/94

Lundin et al.

93/88

Jones et al.

91/77

Williams et al.

Designed as a tool based on patients’ selfreport

84/76

Jones et al.

Designed as a tool based on patients’ selfreport

93/95

Maldonado et al.

Allows for adjustment of pharmacological intervention Quick to administer

Has to be done frequently

Not available

Sullivan et al.

Quick to administer Require less reliance on patients’ response May be predictive of the course of withdrawal

A clustering of withdrawal symptoms in five categories is necessary

Not available

Wetterling et al.

Questionnaire

Abbreviation

Items investigated

Cut-off

Pros

AUDIT-10

Alcohol Use Disorder Identification Test

10 Questions covering quantity and frequency of alcohol use, drinking behavior, adverse psychological symptoms, and alcohol-related problems

$8

Excellent screening test

FAST

Fast Alcohol Screening Test

4-Item questionnaire quantity and frequency of alcohol use, drinking behavior, adverse psychological symptoms

$3

CAGE

Cut down, Annoyed by criticism, Guilty about drinking and need for an Eye-opener in the morning

4-Item questionnaire quantity and frequency of alcohol use, drinking behavior, adverse psychological symptoms

$2

Quick to administer

TWEAK

Tolerance, Worried, Eye-opener, Amnesia, K cut down

Modification of CAGE plus two additional questions—one about the person’s tolerance to alcohol and another about blackouts

$3

Superior in screening pregnant women

PAWSS

Prediction of Alcohol Withdrawal Severity Scale

Combination of threshold criteria, questions based on patient overview and items based on clinical evidence

$4

High predictive value

CIWA-Ar

Clinical Institute Withdrawal Assessment in its revised version

10 item assessment tool examining agitation, anxiety, auditory disturbances, clouding of sensorium, headache, paroxysmal sweats, tactile disturbances, tremor, and visual impairment

,10 Mild 10 18 moderate . severe

AWSc

Alcohol Withdrawal Scale

Consists of six vegetative items (pulse rate, diastolic blood pressure, body temperature, breathing rate, sweating and tremor) and five mental or psychopathological symptom items (agitation, anxiety, tactile disturbances, disorientation, and hallucinations)

,5 mild 6 9 moderate $ severe

Quick to administer Patients with alcohol use disorder are identified in .50% by using the first question

Cons Positive predictive value is restricted Overestimates the risk of withdrawal Time-consuming Designed as tool based on patients’ self-report

Relates to the hole life Not covering the current situation

The most relevant questionnaires with their items investigated, their clinically relevant cut-offs, the pros and cons as well as their sensitivities and specificities when available, are listed.

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BEYOND BENZODIAZEPINES

FIGURE 69.2 Typical MRI features of status epilepticus. This figure summarizes MRI features that can be associated with status epilepticus. (A) Axial diffusion weighted imaging. Cortical hyperintensities exceed vascular territories. (B) Axial diffusion weighted imaging. Signal hyperintensities affect mesio-temporal structures. (C) Axial diffusion weighted imaging. (D) Axial apparent diffusion coefficient. Cortical and thalamic hyperintensities show hypointense correlate in the apparent diffusion coefficient. (E) Axial T2 weighted imaging shows cortical edema that exceeds vascular territories. Source: With permission from Prof. Michael Schocke, Department of Radiology and Neuroradiology, Rehabilitation and University Hospital Ulm.

of which three are presented here with their assets and drawbacks.

BENZODIAZEPINES: DIFFERENT WAYS OF APPLICATION The aim of a loading-dose regimen is the application of high initial dosages of a long-acting BZD to quickly achieve sedation. In practice, 10 20 mg diazepam or 100 mg chlordiazepoxide are administered repetitively until withdrawal symptoms are treated in a satisfying fashion. This strategy reduces the cumulative dose of BZD, the duration of withdrawal, and forgoes intense monitoring as the application of drugs is limited to the initial period of AWS. However, over-sedation and respiratory depression constitute relevant side effects (Muzyk, Leung, Nelson, Embury, & Jones, 2013). Diazepam and chlordiazepoxide are also agents of choice for a fixed-dose treatment technique with a daily dose of 60 or 125 mg, respectively, and slow tapering after 2 3 days over a period of 10 days. This strategy is advantageous for those patients who require medication regardless of symptoms, as for nonconvulsive status epilepticus where withdrawal symptoms are hard to assess. The fixed-dose regimen should not be used in patients who are still ethanolintoxicated as potentiation of both drugs can result in unpredictable interactions (Skinner, 2014). The most complex way of BZD administration is the symptom-triggered treatment where symptomatic patients must be evaluated in regular intervals on the basis of questionnaires like CIWA-Ar where precise cutoffs lead to a certain dosage adapted to the current clinical presentation of the patient. Using relatively small amounts of diazepam (5 mg) or chlordiazepoxide (25 mg) needs reassessment after 1 hour and additional

application until a certain score in the questionnaire is reached. Intense monitoring is laborious, but there are many advantages, such as lower cumulative doses, shorter duration of detoxification, less sedation, and lower risk for respiratory depression, which makes this regimen beneficial (Sachdeva, Chandra, & Deshpande, 2014).

BEYOND BENZODIAZEPINES There are numerous non-BZD agents like antipsychotics, anticonvulsants, anesthetics, alpha2 agonists, and others that subsume clomethiazole, gammahydroxybutyric acid, sodium oxybate, and baclofen. Antipsychotic agents like butyrophenones and phenothiazines should be used cautiously in AWS due to the lowering of the seizure threshold and increasing mortality by prolongation of the QT-interval with the risk of cardiac arrhythmias. For this, their application requires continuous monitoring of vital signs and should be restricted to those cases where BZD alone could not control severe agitation, hallucinosis, and delirium (Wong, Benedict, & Kane-Gill, 2015). Anticonvulsants such as valproate, carbamazepine, or levetiracetam are widely used in the treatment of AWS. Nonetheless, no evidence of advantages in their application has been found in a Cochrane review, so their use is restricted to patients with manifest seizures (Minozzi, Amato, Vecchi, & Davoli, 2010). Alpha2 agonists lack GABAergic activity, classifying them as adjunctive agents to reduce autonomic dysregulation when BZD effects alone seem to be ineffective and to spare BZD requirement (Bielka, Kuchyn, & Glumcher, 2015). Anesthetics with GABA-enhancing properties, such as propofol and barbiturates, work synergistically with BZD and are very effective in the treatment of AWS. Unfortunately, their application is often combined

VII. TREATMENTS, STRATEGIES AND RESOURCES

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69. ALCOHOL WITHDRAWAL SYNDROME: CLINICAL PICTURE AND THERAPEUTIC OPTIONS

FIGURE 69.3 Summary of therapeutic options in mild, moderate and severe alcohol withdrawal. The figure illustrates how to treat patients during AWS depending on severity of clinical presentation. Cases of mild withdrawal should be monitored and symptoms be scored by questionnaires. Therapy with diazepam loading dose can be administered in cases presenting relevant symptoms. It is recommended to treat moderate AWS according to the symptomtriggered regimen in combination with alpha-2agonists when necessary. In cases of severe AWS, treatment starts with a loading dose of diazepam until the patient is calm but awake, with continuation of the fixed- or symptom-triggered therapy in combination with alpha-2 agonists when necessary. For refractory AWS, antipsychotic and anesthetic agents can additionally be administered. In all cases, thiamine should be supplied. Source: With permission from Jesse, S., Brathen, G., Ferrara, M., Keindl, M., Ben-Menachem, E., Tanasescu, R., & Ludolph, A. C. (2017). Alcohol withdrawal syndrome: Mechanisms, manifestations, and management. Acta Neurologica Scandinavica, 135(1), 4 16.

with depression of the respiratory center, coma, and the need for intubation and mechanical ventilation in an intensive care setting. Beyond that, rebound phenomena of withdrawal symptoms are reported after cessation of these drugs (Kattimani & Bharadwaj, 2013). Clomethiazole is a well-established drug for alcohol withdrawal, but its use has some limitations as the agent undergoes a relevant firstpass effect in the liver which is blocked by ethanol so that a combination of both agents should be avoided due to its life-threatening effects. Its addictive and hypersecretory potential restrict this medication to inhospital use with application of 200 mg capsules every 2 3 hours until sufficient sedation is reached (Bonnet, Lensing, Specka, & Scherbaum, 2011). Other GABA-mimicking agents that find use during admission are gamma-hydroxybutyric acid and sodium oxybate with anxiolytic and depressant properties in higher doses. Their clinical practice is confined to a short period as they induce addiction and abuse as a consequence of their euphoric effects. Furthermore, superiority to BZD has not been proven (Leone, Vigna-Taglianti, Avanzi, Brambilla, & Faggiano, 2010). For baclofen, a drug often prescribed for therapy of AWS, some open label reports demonstrated relevant impact in decreasing symptoms of severe withdrawal and also of craving by comparable mechanisms, such as sodium oxybate in GABA potentiation. Due to the scarcity of data, its use cannot be recommended (Liu & Wang, 2017). Fig. 69.3 illustrates

a flow chart that provides practical advice for therapeutic procedures according to Jesse et al. (2017). Adjunctive therapeutic agents, such as magnesium and thiamine, should not go unmentioned. As an inhibitor of neurotransmitter release and a cofactor for many enzymes, laboratory values of magnesium ought to be investigated and deficits be supplied, especially when patients reveal cardiac arrhythmias. At present, there is no evidence for prophylactic application (Sarai, Tejani, Chan, Kuo, & Li, 2013). Symptoms of Wernicke’s encephalopathy can mimic those of AWS, so that differentiation is often difficult or even impossible. Because of the high morbidity and mortality of Wernicke’s disease, the frequent need of parenteral nutrition in patients with AWS, the under-nourishment of alcoholics, and because it is an uncomplicated treatment, thiamine supplementation is recommended for all patients experiencing AWS (Galvin et al., 2010).

MINI-DICTIONARY OF TERMS Alcohol withdrawal syndrome Clinical symptoms that appear after reduction or cessation of alcohol intake. Seizures A syndrome with different clinical manifestations with or without loss of consciousness, as well as with or without motor signs. Delirium tremens A severe form of alcohol withdrawal with lifethreatening symptoms. Questionnaires Clinical instruments to value and score symptoms. They aid to classify the severity of a disease and to regulate therapy. Most questionnaires are validated and reliable.

VII. TREATMENTS, STRATEGIES AND RESOURCES

REFERENCES

Electroencephalogram An examination that is easy to perform. It reflects brain activity and represents an important tool to exclude nonconvulsive status epilepticus in patients with reduced consciousness. Magnetic resonance imaging An imaging technique to illustrate, for instance, brain structures. Benzodiazepines Drugs with gamma aminobutyric acid-like properties. They induce sedation and amnesia, are anxiolytic, analgetic, anticonvulsive, and a muscle relaxant. Wernicke’s encephalopathy A syndrome of malnutrition with lack of thiamine. Only 16% of patients show the classic triade of ataxia, ophthalmoplegia, and amnesia.

KEY FACTS Alcohol Withdrawal Syndrome • A common syndrome after reduction or cessation of alcohol intake in chronic alcohol abuse. • Exclusion of other mental, medical, or behavioral diseases is mandatory. • Symptoms are of an autonomic, motor, awareness, and psychiatric manner. • Laboratory findings can substantiate the diagnosis. • During withdrawal, patients should be monitored in hospital.

SUMMARY POINTS • Diagnosis of AWS is often delayed due to unspecific symptoms. • It is recommended to classify symptoms as mild, moderate, and severe. • Severe alcohol withdrawal manifests as DT and frequent epileptic seizures. • Mortality of patients with severe AWS is comparable to that of severe malignant diseases. • Laboratory markers, such as potassium, thrombocytopenia, and ratio AST/ALT . 2, support the suspected diagnosis and are available within a short time. • Questionnaires facilitate diagnosis and represent devices to adapt drug therapy to the clinical presentation. • EEG and MRI should be performed in all patients with impaired consciousness and new or untypical seizures. • The main therapeutic agents for AWS represent BZD. • Depending on the individual clinical presentation, BZD can be administered as loading-dose, fixeddose, and symptom-triggered regimens.

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Mainerova, B., Prasko, J., Latalova, K., Axmann, K., Cerna, M., Horacek, R., & Bradacova, R. (2015). Alcohol withdrawal delirium—Diagnosis, course and treatment. Biomedical Papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia, 159(1), 44 52. Maldonado, J. R., Sher, Y., Das, S., Hills-Evans, K., Frenklach, A., Lolak, S., & Neri, E. (2015). Prospective Validation Study of the Prediction of Alcohol Withdrawal Severity Scale (PAWSS) in medically ill inpatients: A new scale for the prediction of complicated alcohol withdrawal syndrome. Alcohol and Alcoholism, 50(5), 509 518. Minozzi, S., Amato, L., Vecchi, S., & Davoli, M. (2010). Anticonvulsants for alcohol withdrawal. Cochrane Database of Systematic Reviews, 3. Muzyk, A. J., Leung, J. G., Nelson, S., Embury, E. R., & Jones, S. R. (2013). The role of diazepam loading for the treatment of alcohol withdrawal syndrome in hospitalized patients. American Journal of Addictions, 22(2), 113 118. Nanau, R. M., & Neuman, M. G. (2015). Biomolecules and biomarkers used in diagnosis of alcohol drinking and in monitoring therapeutic interventions. Biomolecules, 5(3), 1339 1385. Rathlev, N. K., Ulrich, A. S., Delanty, N., & D’Onofrio, G. (2006). Alcohol-related seizures. Journal of Emergency Medicine, 31(2), 157 163. Riss, J., Cloyd, J., Gates, J., & Collins, S. (2008). Benzodiazepines in epilepsy: Pharmacology and pharmacokinetics. Acta Neurologica Scandinavica, 118(2), 69 86. Rogawski, M. A. (2005). Update on the neurobiology of alcohol withdrawal seizures. Epilepsy Currents, 5(6), 225 230. Sachdeva, A., Chandra, M., & Deshpande, S. N. (2014). A comparative study of fixed tapering dose regimen versus symptomtriggered regimen of lorazepam for alcohol detoxification. Alcohol and Alcoholism, 49(3), 287 291.

Sarai, M., Tejani, A. M., Chan, A. H., Kuo, I. F., & Li, J. (2013). Magnesium for alcohol withdrawal. Cochrane Database of Systematic Reviews, 6. Sarkar, S., Choudhury, S., Ezhumalai, G., & Konthoujam, J. (2017). Risk factors for the development of delirium in alcohol dependence syndrome: Clinical and neurobiological implications. Indian Journal of Psychiatry, 59(3), 300 305. Skinner, R. T. (2014). Symptom-triggered vs. fixed-dosing management of alcohol withdrawal syndrome. Medsurg Nursing, 23(5), 307 315, 329. Sullivan, J. T., Sykora, K., Schneiderman, J., Naranjo, C. A., & Sellers, E. M. (1989). Assessment of alcohol withdrawal: The revised clinical institute withdrawal assessment for alcohol scale (CIWA-Ar). British Journal of Addiction, 84(11), 1353 1357. Topic, A., & Djukic, M. (2013). Diagnostic characteristics and application of alcohol biomarkers. Clinical Laboratory, 59(3 4), 233 245. Victor, M., & Brausch, C. (1967). The role of abstinence in the genesis of alcoholic epilepsy. Epilepsia, 8(1), 1 20. Wetterling, T., Kanitz, R. D., Besters, B., Fischer, D., Zerfass, B., John, U., & Driessen, M. (1997). A new rating scale for the assessment of the alcohol-withdrawal syndrome (AWS scale). Alcohol and Alcoholism, 32(6), 753 760. Williams, N. (2014). The CAGE questionnaire. Occupational Medicine (London), 64(6), 473 474. Wong, A., Benedict, N. J., & Kane-Gill, S. L. (2015). Multicenter evaluation of pharmacologic management and outcomes associated with severe resistant alcohol withdrawal. Journal of Critical Care, 30(2), 405 409. Xiang, T., Li, G., Liang, Y., & Zhou, J. (2014). A wide spectrum of variably periictal MRI abnormalities induced by a single or a cluster of seizures. Journal of Neurological Science, 343(1 2), 167 172.

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C H A P T E R

70 Resources for the Neuroscience of Alcohol 1

Rajkumar Rajendram1,2 and Victor R. Preedy3

Department of Medicine, King Abdulaziz Medical City - Riyadh, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia 2Diabetes and Nutritional Sciences Research Division, Faculty of Life Science and Medicine, King’s College London, London, United Kingdom 3Faculty of Life Science and Medicine, King’s College London, London, United Kingdom

LIST OF ABBREVIATIONS DALYS

disability-adjusted life years

INTRODUCTION After caffeine, ethanol is the most commonly used recreational drug worldwide. Alcohol is synonymous with ethanol, and “drinking” often describes the consumption of beverages containing ethanol. There are a variety of alcoholic beverages (e.g., beer, wine, fortified wines, and distilled products). Most people enjoy alcohol without harming themselves or others. However, in excess, alcohol can induce any of at least 60 different alcohol-related pathologies and as many as 200 have been reported (Preedy & Watson, 2004; WHO, 2014). On a global basis, alcohol misuse causes the deaths of 3 million people each year (WHO, 2014). This is about 1 in 17 deaths (WHO, 2014). The nervous system is particularly vulnerable to alcohol and this has been known for a long time (Horsley & Sturge, 1907). In terms of the global burden of disease, neuropsychiatric disorders alone contribute to about 25% of all alcohol-attributable disability-adjusted life years (DALYS). This is greater when the proportion of alcohol-attributable DALYS due to unintentional injuries, cardiovascular diseases and diabetes, gastrointestinal diseases, intentional injuries, cancers, and infectious diseases (WHO, 2014) are taken into account. Autopsies have shown that chronic alcohol misusers have smaller, lighter brains than those who are not alcoholic (Zahr, Kaufman, &

Neuroscience of Alcohol. DOI: https://doi.org/10.1016/B978-0-12-813125-1.00070-2

Harper, 2011). Studies using computed tomography and magnetic resonance imaging have confirmed these observations and have unmasked regionspecific changes (e.g., effects on the cuneus; Wang et al., 2018). Neuroimaging plays an increasingly vital role in detecting the sequelae of alcohol misuse in routine clinical practice. Currently, advances in MR spectroscopy and positron emission tomography can reveal disruptions in the brains of alcoholics at the biochemical and molecular level (Volkow et al., 2006, 2015; Charlet, Rosenthal, Lohoff, Heinz, & Beck, 2018). Advances in other physical (e.g., electrophysiology), analytical (e.g., high throughput arrays), and statistical (e.g., bioinformatics) platforms have contributed to our understanding of the neuroscience of alcohol. There are also advances in the science of treating addictions and alcohol use disorders. It is now difficult, even for experienced scientists, to remain up-to-date. For those new to the field, it is difficult to know which of the myriad of available resources are reliable. To assist colleagues who are interested in understanding more about the neuroscience of alcohol and the treatment of alcohol misuse we have, therefore, produced tables containing resources on the neuroscience of alcohol. These were compiled by the expert authors and co-authors of this book. The experts who assisted with the compilation of these tables of resources are acknowledged below. Over 20 individuals have contributed to an array of resources which includes over 100 websites and 90 books. Tables 70.1 70.4 list the most up-to-date information on the regulatory bodies and professional

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© 2019 Elsevier Inc. All rights reserved.

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70. RESOURCES FOR THE NEUROSCIENCE OF ALCOHOL

TABLE 70.1 Regulatory Bodies, Professional Societies, and Organizations Alcohol and Substance Abuse Programs www.drugabuse.com

TABLE 70.1

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Fetal Alcohol Disorder Society www.faslink.org Federation of Drug and Alcohol Practitioners www.fdap.org.uk

Alcohol Awareness Council www.alcohol.org

Fetal Alcohol Spectrum Disorders Research Group www.fasdsg.org

Alcohol Concern www.alcoholconcern.org.uk

French government www.drogues.gouv.fr

Alcoholics Anonymous www.aa.org

Interagency Coordinating Committee on Fetal Alcohol Spectrum Disorders www.niaaa.nih.gov/about-niaaa/our-work/interagency-coordinatingcommittee-fetal-alcohol-spectrum-disorders

Alcohol Rehab Guide www.alcoholrehabguide.org Alcohol Research Group www.arg.org

International Drug Abuse Research Society www.idars.org

American Academy of Addiction Psychiatry www.aaap.org

International Society for Biomedical Research on Alcoholism www.isbra.com

American Academy of Family Physicians www.aafp.org

Japanese Medical Society of Alcohol and Addiction Studies www.f.kpu-m.ac.jp/k/jmsas

American Psychiatric Association www.psychiatry.org

Japanese Society of Alcohol-Related Problems www.j-arukanren.com

American Psychological Association www.apa.org

Japanese Society of Psychiatry and Neurology www.jspn.or.jp

American Society of Addiction Medicine www.asam.org

Joint Commission www.jointcommission.org

Asia Pacific Society of alcohol and Addiction Research www.apsaar.org

Junta Nacional de Drogas www.infodrogas.gub.uy

Asociacion Argentina de Ciencias del Comportamiento www.aacconline.org.ar

Latin American Society for Biomedical Research on Alcoholism www.lasbra.net

Association Nationale de Pre´vention en Alcoologie et www.anpaa.asso.fr

Mental Health America www.mentalhealthamerica.net

Australian Government Department of Health www.alcohol.gov.au

Mental Health Commission, Western Australia alcoholthinkagain.com.au

Australasian Professional Society on Alcohol and other Drugs www.apsad.org.au

Ministry of Health, Labour and Welfare www.mhlw.go.jp/english/

Canadian Government www.canada.ca

National Association for Alcoholism and Drug Abuse Counselors www.naadac.org

Center on Addition www.CASAColumbia.org

National Association of Addiction Treatment Providers www.naatp.org

Centers for Disease Control and Prevention www.cdc.gov

National Association of State Alcohol and Drug Abuse Directors www.nasadad.org

Children’s Information Station kidsinfost.net/disorder/illust-study/alcoholism/

National Consortium on Alcohol & Neurodevelopment in adolescence www.ncanda.org

Commission on Accreditation of Rehabilitation Facilities www.carf.org/home

National Council on Alcoholism and Drug Dependence www.ncadd.org

European Centre for Monitoring Alcohol Marketing [email protected]

National Drug Research Institute, Australia www.ndri.curtin.edu.au/home

European Society for Biomedical Research on Alcoholism www.esbra.com

National Health Service www.nhs.uk

FASworld Canada www.fasworld.com

National Hospital Organization Kurihama Medical and Addiction Center www.kurihama-med.jp/index.html

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INTRODUCTION

TABLE 70.1

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TABLE 70.2

National Institute of Health www.nih.gov

Journals Relevant to the Neuroscience of Alcohol

Alcoholism Clinical and Experimental Research PLoS One

National Institute of Mental Health www.nimh.nih.gov

Addiction Biology

National Institute on Alcohol Abuse and Alcoholism www.niaaa.nih.gov National Organization on Fetal Alcohol Syndrome www.nofas.org Neurobiology of Adolescent Drinking in Adulthood Consortium www.med.unc.edu/alcohol/nadiaconsortium Panamerican Health Organization www.paho.org

Alcohol Neuropsychopharmacology Neuropharmacology Psychopharmacology Behavioural Brain Research Journal of Neuroscience Drug and Alcohol Dependence

Plan nacional Sobre Drogas http://www.pnsd.msssi.gob.es/

Neuroscience

Research Society on Alcoholism www.rsoa.org

Journal of Stroke and Cerebrovascular Diseases

Secretarı´a de Programacio´n para la Prevencio´n de la Drogadiccio´n y la Lucha contra el Narcotra´fico (Argentina) www.argentina.gob.ar/sedronar Sociedad Cientı´fica Espan˜ola de Estudios Sobre Alcohol, Alcoholismo y Otras Toxicomanı´as www.socidrogalcohol.org

Alcohol and Alcoholism Biological Psychiatry Stroke Brain Research Pharmacology Biochemistry and Behavior

Sociedad Espan˜ola de Medicina Interna (SEMI). Grupo de Alcohol y Alcoholismo www.fesemi.org

Psychiatry Research Neuroimaging

Society for Neuroscience www.sfn.org

BMJ Case Reports

Society for the Study of Addiction www.addiction-ssa.org Substance Abuse and Mental Health Service Administration www.samhsa.gov Teen Alcohol Information www.thecoolspot.gov

Neuroscience and Biobehavioral Reviews

Journals publishing original research and review articles related to the neuroscience of alcohol. Included in this list are the top 20 journals which have published the greatest number of articles over the past 5 years. We also recommend Nature Medicine and The New England Journal of Medicine.

TABLE 70.3

Relevant Books on Alcohol

Addiction Medicine: Science and Practice (2nd edition). Johnson BA (Editor). Springer, 2011.

Teen Challenge www.teenchallenge.ca

Addictive States. O’Brien CP, Jaffe JH. Raven Press, 1992.

The Surgeon General www.surgeongeneral.gov

Addictive Substances and Neurological Disease. Watson RR, Zibadi S (Editors). Academic Press, 2017.

Unidad de Atencio´n a als Drogodepencias (Servicio Canario de Salud, Santa Cruz de Tenerife, Canary Islands) www.sanmigueladicciones.org

Adolescent Psychopathology and the Developing Brain. Romer D, Walker EF. Oxford University Press, 2007.

United Kingdom Government www.gov.uk

Adolescents, Alcohol, and Substance Abuse: Reaching Teens through Brief Interventions. Monti PM, Colby SM, O’Leary TA. Guilford Press, 2001.

World Health Organization www.who.int This table lists the regulatory bodies, professional societies, and organizations involved with the neuroscience of alcohol misuse, drug addictions, and treatments. Some sites are in languages other than English (such as Japanese). Some organizations may change names or be known by different names. For example, the Commission on Accreditation of Rehabilitation Facilities is better known as CARF International. Another example is the European Society for Biomedical Research on Alcoholism which is also known as ESBRA. To ensure consistency, we have provided the full names of the organizations and bodies. For some general site (such as those belonging to the Joint Commission or United Kingdom Government, etc.), more in-depth searches of the sites are necessary (i.e., searching sites for terms such as “alcohol,” “alcoholism,” or “services,” etc.). Table 70.4 also contains some websites which provide information on alcohol misuse, drug addictions, and treatments.

Alcohol and Alcoholism, Vol 1, The Genetics of Alcoholism. Begleiter H, Kissin B. Oxford University Press, 1995. Alcohol and Alcoholism, Vol 2, The Pharmacology of Alcohol and Alcohol Dependence. Begleiter H, Kissin B. Oxford University Press, 1996. Alcohol and Alcoholism: Effects on Brain and Development. Hannigan JH, Spear LP, Spear NE, Goodlett CR. Lawrence Erlbaum Associates, 1999. Alcohol and Aldehyde Metabolizing Systems, Vol 3. Thurman RG, Williamson JR, Drott H, Chance B. Academic Press, 1977.

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684 TABLE 70.3

70. RESOURCES FOR THE NEUROSCIENCE OF ALCOHOL

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TABLE 70.3

Alcohol and Nervous System. Sullivan E, Pfefferbaum A. Elsevier, 2014. Alcohol and Seizures: Basic Mechanisms and Clinical Concepts. Porter RJ, Mattson RH, Cramer JA, Diamond I (Editors). Davis, 1990 Alcohol and the Brain: Chronic Effects. Tarter RE. Springer, 1985.

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Development of the Central Nervous System: Effects of Alcohol and Opiates. Miller MW. Wiley, 1991. Drug Abuse in Adolescence Neurobiological, Cognitive, and Psychological Issues. de Micheli D, Andrade ALM, da Silva, EA, de Souza Formigoni MLO. (Editors). Springer-Verlag, 2016.

Alcohol Consumption of Australian Parents: Continuity and Change in the New Millennium. Laslett AL, Jiang H, Room R. Foundation for Alcohol Research and Education, 2017.

Drug and Alcohol Abuse: A Clinical Guide to Diagnosis and Treatment. Schuckit MA. Springer-Verlag, 2010.

Alcohol Effects on Adolescents. Spear LP. US Government Printing Office, 2002.

Drug Use Among American High School Seniors, College Students and Young Adults, 1975 1990 Vol 1: High School Seniors. Johnston LD, O’Malley PM, Bachman JG. US Government Printing Office, 1991.

Alcohol Harm Reduction Strategy for England. Prime Minister’s Strategy Unit. United Kingdom Department of Health, 2004. Alcohol Problems in Adolescents and Young Adults. Galanter M. Springer, 2006. Alcohol Research and Health Fetal Alcohol Spectrum Disorder. NIAAA Publications Distribution Center. National Institute on Alcohol Abuse and Alcoholism, 2009. Alcohol: A Social and Cultural History. Holt MP. Bloomsbury Publishing, 2006.

Drug Use Among American High School Seniors, College Students and Young Adults, 1975 1990 Vol 1: Secondary Students. Johnston LD, O’Malley PM, Bachman JG. US Government Printing Office, 1993. Drugs and the Neuroscience of Behavior: An Introduction to Psychopharmacology. Prus A. SAGE Publications, 2017. Drugs, Addiction and the Brain. Koob GF, Arends MA, LeMoal M. Elsevier, 2014.

Alcoholic Thinking: Language, Culture, and Belief in Alcoholics Anonymous. Wilcox DM. ABC-CLIO, 1998.

Economic Costs of Alcohol and Drug Abuse in the United States 1992 (Updated for 1998). Harwood H, Fountain D, Livermore G. Report prepared for the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism, 2000.

Alcohol-Related Violence: Prevention and Treatment. McMurran M. Wiley-Blackwell, 2013.

Epidemiology of Women’s Health. Senie RT. Jones and Bartlett Publishers, 2013.

Animal Models for Medications Screening to Treat Addiction. Bell RL, Rahman S. Academic Press, USA, 2016.

Essential Handbook of Treatment and Prevention of Alcohol Problems. Heather N, Stockwell TR (Editors). John Wiley and Sons, 2004.

Animal Models of Drug Addiction. Olmstead MC. Humana Press, 2011.

Excitatory Amino Acid Transmission in Health and Disease. Balazs R, Bridges RJ, Cotman CW. Oxford University Press, UK, 2006.

Behavioral Animal Models. Cruz-Morales SE, Arriaga-Ramı´rez JCP (Editors). Research Signpost, 2012. Behavioral Neurobiology of Alcohol Addiction. Sommer WH, Spanagel R. Springer, 2012.

Fetal Alcohol Syndrome Does Alcohol Withdrawal Play a Role? Thomas JD, Riley EP. National Institute on Alcohol Abuse and Alcoholism (NIAAA) Publications Distribution Center, 1998.

Behavioral Neuroscience of Adolescence. Spear LP. WW Norton, 2010.

Genetics of Alcoholism. Begleiter H, Kissin B. Oxford University Press, UK, 1995.

Behavioral Neuroscience of Drug Addiction. Self DW, Stanley JK. Springer-Verlag, 2010.

Genomics and Health in the Developing World. Kumar D. Oxford University Press, 2012.

Binge Britain: Alcohol and the National Response. Plant M, Plant M. Oxford University Press, 2006.

Global Perspectives on Health Promotion Effectiveness. McQueen D, Jones C (Editors). Springer, 2007.

Binge Drinking in Adolescents and College Students. Marczinski CA, Grant EC, Grant VJ. Nova Science Publishers, 2009.

Glutamate and Addiction. Herman BH, Frankenheim J, Litten RZ, Sheridan PH, Weight FF, Zukin SR. Humana Press, USA, 2003.

Binge Eating and Binge Drinking: Psychological, Social and Medical Implications. Harris SB. Nova Science Publishers, 2013.

Habits: Remaking Addiction. Fraser S, Moore D, Keane H. Palgrave Macmillan, 2014.

Biochemistry and Pharmacology of Ethanol. Majchrowicz E, Noble EP. Plenum Press, 1979.

Handbook of Alcohol-Related Pathology. Preedy, V.R., Watson, RR volumes 1 3. Academic Press, London, 2004.

Comprehensive Handbook of Alcohol Related Pathology. Preedy VR, Watson RR. Elsevier, 2005.

Handbook of Clinical Neurology, Vol 125 (3rd Series) Alcohol and the Nervous System. Sullivan EV, Pfefferbaum A (Editors). Elsevier, 2014.

Dark Remedy: The Impact of Thalidomide and Its Revival as a Vital Medicine. Brynner R, Stephens T. Basic Books, 2001.

Handleiding CGT 1 , Cognitief gedragstherapeutische behandeling van verslaving bij mensen met een lichte verstandelijke beperking [Manual of Cognitive Behavioral Therapy for Substance Use Disorder in Individuals With Mild Intellectual Disability]. VanDerNagel JEL, Kiewik M. Perspectief, 2016.

Development of Alcohol Problems: Exploring the Biopsychosocial Matrix of Risk NIAAA Research Monograph 26. Zucker RA, Boyd GM, Howard J. US Dept of Health and Human Services, 1995. (Continued)

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TABLE 70.3

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TABLE 70.3

Indigenous Australian Alcohol and Other Drug Issues: Research From the National Drug Research Institute. Gray D, Saggers S. National Drug Research Institute, Curtin University of Technology 2002. Is It Just the Tip of the Iceberg? Substance Use and Misuse in Intellectual Disability (SumID). VanDer Nagel JEL. Nijmegen, 2016. It’s All Between My Ears! Deficiencies in Information Processing in Problematic Drinkers With Mild to Borderline Intellectual Disability. van Duijvenbode N. Nijmegen, 2016. Manual of Substance Use and Misuse in Intellectual Disability Questionnaire (SumID-Q) (Dutch). Van Der Nagel J, Kiewik M, Van Dijk M, De Jong C, Didden R. Tactus, 2011. Methods in Alcohol-Related Neuroscience Research. Liu Y, Lovinger DM. CRC Press, 2002. Mindfulness-Based Relapse Prevention for Addictive Behaviors: A Clinician’s Guide. Bowen S, Chawla N, Marlatt GA. Guilford Press, 2011. Molecular Aspects of Alcohol and Nutrition. Patel VB (Editor). Academic Press, 2016. Molecular Basis of Drug Addiction. Rahman S. Elsevier, USA, 2016. Molecular Neurobiology of Addiction Recovery: The 12 Steps Program and Fellowship. Blum K, Femino J, Teitelbaum S, Giordano J, OscarBerman M, Gold M. Springer, 2013. National Survey Results on Drug Use From the Monitoring the Future Study, 1975 1997. Johnston LD, O’Malley PM, Bachman JG. National Institute on Drug Abuse, USA, 1999. National Survey Results on Drug Use From the Monitoring the Future Study, 1975 2007 Vol I: Secondary School Students. Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. National Institute on Drug Abuse, USA, 2008.

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Oxidation of Alcohols to Aldehydes and Ketones. Tojo G, Fernandez M. Springer, 2006. Pharmacological Effects of Ethanol on the Nervous System. Deitrich RA, Erwin VG. CRC Press, 1996. Pharmacology of Alcohol and Alcohol Dependence. Begleiter H, Kissin B. Oxford University Press, 1996. Political Economy of Narcotics: Production, Consumption and Global Markets. Buxton J. Zed Books, 2006. Preventing Relapse in the Addictions: A Biopsychosocial Approach. Chiauzzi EJ. Pergamon Press, 1991. Psychology of Addictive Behaviour. Moss AC, Dyer KR. Palgrave, 2010. Research on the Neurobiology of Alcohol Use Disorders. Sher L (Editor). Nova Science Publishers, 2008. Russia Goes Dry: Alcohol, State and Society. White S. Cambridge University Press, 1996. Stress, Gender, and Alcohol-Seeking Behavior, Research Monograph No 29. Hunt WA, Zakhari S. National Institute on Alcohol Abuse and Alcoholism, 1995. Swimming With Crocodiles: The Culture of Extreme Drinking. Martinic M, Measham F. Taylor & Francis Group, 2008. Teenage Kicks? Young People and Alcohol: A Review of the Literature. Newburn T, Shiner M. Joseph Rowntree Foundation, 2001. Un Libro sobre drogas. Arrieta E (Editor). El Gato y la Caja, 2017. Understanding Addiction as Self Medication: Finding Hope Behind the Pain. Khantzian EJ, Albanese MJ. Rowman & Littlefield, 2008. Women Under the Influence. The National Center on Addiction and Substance Abuse (CASA). Johns Hopkins University Press, 2005.

Neural Mechanisms of Action of Drugs of Abuse and Natural Reinforcers. Me´ndez M, Mondrago´n R (Editors). Research Signpost, 2008.

Working With Substance Misusers: A Guide to Theory and Practice. Petersen T, McBride A (Editors). Taylor & Francis, 2002.

Neural-Immune Interactions in Brain Function and Alcohol Related Disorders. Cui C, Grandison L, Noronha A. Springer, Germany, 2013.

Working With the Problem Drinker: A Solution-Focused Approach. Berg IK, Miller SD. W W Norton & Co, 1992.

Neurobiology of Addiction. Koob GF, Le Moal M. Academic Press, USA, 2006.

This table lists books on the neuroscience of alcohol.

Neurobiology of Addictions: Implications for Clinical Practice. Straussner SLA, Spence RT, Dinitto DM. Routledge, 2002. Neurobiology of Alcohol Dependence. Noronha ABC, Cui C, Harris RA, Crabbe JC. Elsevier, USA, 2014. Neuropathology of Drug Addiction and Substance Misuse. Vol 1 3. Preedy VR (Editor). Academic Press, 2016. Neuroscience: Pathways to Alcohol Dependence: Part I: Overview of the Neurobiology of Dependence. Sullivan EV. DIANE Publishing Company, 2009.

TABLE 70.4

Relevant Online Resources and Information

Addaction UK www.addaction.org.uk/about-us Addiction Center www.addictioncenter.com/alcohol Addiction Technology Transfer Center attcnetwork.org Alcohol Abuse Symptoms, Signs and Addiction Treatment drugabuse.com/library/alcohol-abuse

Neuroscience: Pathways to Alcohol Dependence: Part II: Neuroadaptation, Risk, and Recovery. Sullivan EV. DIANE Publishing Company, 2009.

Alcohol, American Academy of Family Physicians www.aafp.org/patient-care/public-health/alcohol.html

New Trends in Brain Research. Chen FJ (Editor). Nova Science Publishers, 2006.

Alcohol Help Center www.alcoholhelpcenter.net

Nutrition and Alcohol. Watson RR, Preedy VR (Editors). CRC Press, 2004.

Alcohol Misuse, National Health Service www.nhs.uk/conditions/alcohol-misuse

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686 TABLE 70.4

70. RESOURCES FOR THE NEUROSCIENCE OF ALCOHOL

(Continued)

TABLE 70.4

Alcohol Research Current Reviews, National Institute on Alcohol Abuse and Alcoholism www.arcr.niaaa.nih.gov/alert.htm Alcohol Treatment Navigator, National Institute on Alcohol Abuse and Alcoholism alcoholtreatment.niaaa.nih.gov

(Continued)

Guideline o Treatment of Alcohol Use Disorder, American Psychiatric Association www.psychiatry.org/newsroom/news-releases/apa-releases-newpractice-guideline-on-treatment-of-alcohol-use-disorder Health Direct www.healthdirect.gov.au/how-alcohol-affects-your-health

Alcohol Epidemiologic Data Directory pubs.niaaa.nih.gov/OrderForm/EncForm/Data_Directory

Know the Score knowthescore.info

ASK www.ask.or.jp/english

Mothers Against Drunk Driving www.madd.org

Biological Effects of Alcohol Misuse/Alcohol Pharmacotherapy, Larasig, Health Professional Student Training www.larasig.com/node/2867

National Alcohol Beverage Control Association www.nabca.org

Bowles Center for Alcohol Studies, University of North Carolina at Chapel Hill www.med.unc.edu/alcohol Center of Alcohol Studies. Rutgers University. alcoholstudies.rutgers.edu

National Asian Pacific American Families Against Substance Abuse napafasa.org National Association for Children of Alcoholics nacoa.org Partnership for Drug-free kids www.alcoholscreening.org/Home.aspx

Centre of Knowledge & Expertise on Substance Use Disorder and Intellectual Disability www.lvbenverslaving.nl

Pearson Center for Alcohol and Addiction Research www.tsriaddiction.com

Centro de Ayuda al Alcoho´lico y sus Familiares (CAAF), INPRF, Ciudad de Me´xico, Me´xico inprf.gob.mx/clinicos/caaft.html

Plataforma de Neurociencias Cognitivas y Ciencias de la Conducta de Argentina (PENCO) www.penco.conicet.gob.ar

College Drinking, National Institute on Alcohol Abuse and Alcoholism www.collegedrinkingprevention.gov/NIAAACollegeMaterials Down Your Drink, Camden And Islington - NHS Foundation Trust www.downyourdrink.org.uk/ DrinkWise Australia drinkwise.org.au/drinking-and-you/support-services/# Drug Abuse Warning Network (DAWN): Emergency Department Data www.samhsa.gov/data/emergency-department-data-dawn Drug Pubs Research Dissemination Center, NIDA drugpubs.drugabuse.gov

ReachOut Australia au.reachout.com/articles/alcohol-addiction Recognizing Alcohol-related Neurodevelopmental Disorder (ARND) in Primary Health Care of Children www.niaaa.nih.gov/sites/default/files/ ARNDConferenceConsensusStatementBooklet_Complete.pdf Research Initiatives, National Institute on Alcohol Abuse and Alcoholism www.niaaa.nih.gov/research/major-initiatives Rethinking Drinking (Alcohol and your health), NIAAA www.rethinkingdrinking.niaaa.nih.gov/ Secular Organizations for Sobriety www.sossobriety.org

Education Development Center www.edc.org

Sensible and Natural Alcoholism Prevention Program for You, Computer Advice Technique www.udb.jp/snappy_test/

Edvotek. Clostridium elegans www.edvotek.com/851 Environmental Approaches to Prevention Alcohol Research Center www.prev.org Epidemiology of Alcohol Problems Research Center www.arg.org

SMART Recovery www.smartrecovery.org Southern California Research Center for ALPD and Cirrhosis keck.usc.edu/alpd-and-cirrhosis-research-center Substance Abuse, World Health Organization www.who.int/substance_abuse/en/

Families Anonymous www.familiesanonymous.org Fetal Alcohol Spectrum disorder, Canadian Government www.canada.ca/en/public-health/services/diseases/fetal-alcoholspectrum-disorder.html FRANK www.talktofrank.com

Technology Assisted Care sudtech.org Translational Studies on Early-Life Stress and Vulnerability to Alcohol Addiction Research Center www.wakehealth.edu/PhysPharm/TCNSA.htm Turning Point turningpoint.org.au

Global Status Report on Alcohol and Health (WHO) www.who.int/substance_abuse/publications/ global_alcohol_report/msbgsruprofiles.pdf

University of Wisconsin-Madison chess.wisc.edu/ifrecovery/System/System.aspx (Continued)

VII. TREATMENTS, STRATEGIES AND RESOURCES

(Continued)

REFERENCES

TABLE 70.4

687

Acknowledgments

(Continued)

Washington Alcohol & Drug Abuse Institute adai.washington.edu/ebp Zen’nihon danshu renmei www.dansyu-renmei.or.jp This table lists some internet resources and sites for research platforms relevant to the neuroscience of alcohol. Some of the subsites or pages listed in Table 70.1 also provide directions to tools, advice centers, and other resources.

societies (Table 70.1), journals on the neuroscience of alcohol (Table 70.2), books (Table 70.3), and online resources (Table 70.4) that are relevant to an evidence-based approach to the neuroscience of alcohol.

SUMMARY POINTS • Ethanol, or alcohol, is one of the most commonly used recreational drugs. • On a global basis, alcohol misuse causes the death of 3 million people each year, approximately 1 in 17 deaths. • Neuropsychiatric disorders contribute to about one quarter of all alcohol-attributable DALYS. This is greater than the proportion of alcohol-attributable DALYS due to either unintentional injuries, cardiovascular diseases and diabetes, gastrointestinal diseases, intentional injuries, cancers, and infectious diseases. • This chapter lists the most up-to-date resources on the regulatory bodies, professional bodies, journals, books, and websites that are relevant to an evidence-based approach to the neuroscience of alcohol and alcohol treatments.

We would like to thank the following authors for contributing to the development of this resource: R.L. Bell, P. Brocardo, M.G. Chotro, R. Didden, E. Gonza´lez-Reimers, R. Guedes, N. Huynh, B. Ibrahim, M. Jamal, C. Kamarajan, H. Koike, M. Me´ndez Ubach, A.L. Morrow, R. Pautassi, O. Pierrefiche, L. Richter, D. Rohac, N. Siraj, C. Tanner, J.E.L. Van Der Nagel, N. Van Duijvenbode, S. Vasconcelos, M. Vaswani, M. Virgolini, A. Yamashita, and S. Yoshioka. Some links or subpages were not viable so we have either deleted these or replaced them with other pages.

References Charlet, K., Rosenthal, A., Lohoff, F. W., Heinz, A., & Beck, A. (2018). Imaging resilience and recovery in alcohol dependence. Addiction. Available from https://doi.org/10.1111/add.14259, [Epub ahead of print]. Horsley, V., & Sturge, M. D. (1907). Alcohol and the human body. New York: Macmillan and Co. Preedy, V. R., & Watson, R. R. (2004). Handbook of alcohol-related pathology: volumes 1 3. London: Academic Press. Volkow, N. D., Wang, G. J., Franceschi, D., Fowler, J. S., Thanos, P. P., Maynard, L., . . . Kai Li, T. (2006). Low doses of alcohol substantially decrease glucose metabolism in the human brain. Neuroimage, 29, 295 301. Volkow, N. D., Wang, G. J., Shokri Kojori, E., Fowler, J. S., Benveniste, H., & Tomasi, D. (2015). Alcohol decreases baseline brain glucose metabolism more in heavy drinkers than controls but has no effect on stimulation-induced metabolic increases. Journal of Neuroscience, 35, 3248 3255. Wang, J., Fan, Y., Dong, Y., Ma, M., Dong, Y., Niu, Y., . . . Cui, C. (2018). Combining gray matter volume in the cuneus and the cuneusprefrontal connectivity may predict early relapse in abstinent alcohol-dependent patients. PLoS One, 13(5), e0196860. Available from https://doi.org/10.1371/journal.pone.0196860, May 7. World Health Organisation (WHO). (2014). Global status report on alcohol and health 2014 ed. World Health Organisation. Zahr, N. M., Kaufman, K. L., & Harper, C. G. (2011). Clinical and pathological features of alcohol-related brain damage. Nature Reviews Neurology, 7, 284 294.

VII. TREATMENTS, STRATEGIES AND RESOURCES

Index

Note: Page numbers followed by “f ” and “t” refer to figures and tables, respectively.

A A2A. See Adenosine 2A (A2A) A2AKO mice, 549 AA. See Alcoholics Anonymous (AA) ABC transporter. See ATP-binding cassette transporter (ABC transporter) Abstinence, 181
182 abstinence-oriented approach, 643
644 monitoring, 562
563 AcbC. See Core region of nucleus accumbens (AcbC) AcbSh. See Shell region of nucleus accumbens (AcbSh) ACC. See Anterior cingulated cortex (ACC) Accumbens (Acb), 165f Accuracy/errors, 400 ACD. See Acetaldehyde (ACH) ACE frequency (ACE-F), 606 ACE questionnaire. See Alcohol Craving Experience questionnaire (ACE questionnaire) ACE strength (ACE-S), 606 ACE-F. See ACE frequency (ACE-F) ACE-S. See ACE strength (ACE-S) Acetaldehyde (ACH), 29
30, 39, 44, 81, 147
148, 180, 198, 227, 345, 350, 487, 494, 520
521. See also Aldehyde dehydrogenase (ALDH) acetaldehyde induces addictive phenotype, 346
347 acetaldehyde-drinking rats, 347 adducts in brain, 42
43 binds to DNA and proteins to form adducts, 43f brain ACH in ethanol neurotoxicity, 42 challenges in acetaldehyde research, 40
41 conversion of ethanol to acetaldehyde, 39
40 endocannabinoids and neuropeptide Y, 348 in fetal brain, 83 in fetal environment, 82
83 mechanism of action in reward system, 349f mediates alcohol motivational properties, 347t, 348
350 behavioral correlates, 348t pharmacological modulation, 349t and motivational properties, 345
346 oxidative pathways of ethanol metabolism, 40f

perinatal learning with, 85
86 role in alcohol effects on fetal brain development, 83
84 toxicity, 33 Acetaldehyde dehydrogenase, 82
83 Acetaldehydism, 518
519 Acetone, 180 Acetylcholine (ACh), 364, 429, 458 ACH. See Acetaldehyde (ACH) ACh. See Acetylcholine (ACh) ACSF. See Artificial cerebrospinal fluid (ACSF) ACSS chain family member. See Acyl-CoA synthetase short chain family member (ACSS chain family member) ACTH. See Adrenocorticotropic hormone (ACTH) Active drinkers, 238 Acute alcohol abuse, 132
136 intake effects on opioid peptides and receptors, 437 Acute chemosensory challenges of breathing, 90
92 Acute ethanol, 221 effects on enkephalinergic transmission, 445 Acute hangover scale (AHS), 392 Acute intoxication, neuroimmune response to, 181 Acute nonsynaptic effects of ethanol, 135
136, 136f Acute nontoxic ethanol intake, 467
469 Acute pain, 220
221 ethanol effects on, 221
222 Acute withdrawal, 252 Acyl-CoA synthetase short chain family member (ACSS chain family member), 487 Acyl-coA-ethanol O-acyltransferase, 562 AD. See Alcohol dependence (AD); Alzheimer’s disease (AD) Ad libitum, 60
61 Adaptive functioning, 307 Addiction, 21, 616, 624, 629
630 alcohol, 22, 153
155, 167, 181
182, 297, 383, 483
487, 531 dual process models of, 310, 310f Addictive pathology, 532 Adenonsine-50 -triphosphate (ATP), 662 Adenosine, 546
548 Adenosine 2A (A2A), 455

689

Adenosine A1 receptors, 546
547 Adenosine A2A receptors, 546
547 ADH. See Alcohol dehydrogenase (ADH) ADH1B polymorphism, 31 ADH1B 1 allele, 31 ADH1B 2 allele, 31, 33 ADH1B 3 allele, 33 ADHD. See Attention deficit hyperactivity disorder (ADHD) Adjunctive therapeutic agents, 678 Administration demand, 606
607 Adolescent Reinforcement Survey— Substance Use Version (ARSS-SUV), 298
299 Adolescents/adolescence, 49, 99, 300 alcohol and synaptic plasticity during, 105 risk-taking, 545
546 Adrenocorticotropic hormone (ACTH), 252
253, 315
316 Adult(s) alternative reinforcement among, 302 antisocial behavior, 183 emerging, 300 life, 99 Adverse effects (AEs), 628
629, 635 AEs. See Adverse effects (AEs) Afterhyperpolarization (AHP), 135 Ageing age-related consequences of PAE, 51
52 age-related differences in alcohol consumption effects change across life span, 356
359 motivational effects of alcohol, 355
356 Agenesis, 289 Aggressive behavior, 548 AHP. See Afterhyperpolarization (AHP) AHS. See Acute hangover scale (AHS) AHSS. See Alcohol Hangover Severity Scale (AHSS) AILD. See Alcohol-induced liver disease (AILD) Air-exposed controls, 411 Alanine aminotransferase (ALT), 558
559, 578 Alcohol, 29, 81
82, 99, 110, 131, 179, 224f, 435, 443, 445, 505, 537, 557, 661
662, 683t abuse, 36, 383, 529 mother’s alcohol abuse during later childhood, 529 addiction, 22, 153
155, 167, 181
182, 297, 383, 483
487, 531 affecting women from men, 23

690 Alcohol (Continued) alcohol-dependent patients, 634 alcohol-drinking behavior, 624 alcohol-induced oxidative stress in brain brain disorders associated with OS, 508
509 harmful effects of ethanol in brain, 506f mechanisms of ethanol-induced oxidative stress, 506
508 therapeutic approaches in OS-related brain disorders, 509
511 alcohol-induced CNS neuroimmune activity, 182
183 CTA, 356
357 excitation, 156 modification, 341 taste aversion, 356
358 alcohol-metabolizing enzymes, 29
30 alcohol-naive subjects, 580
581 alcohol-preferring rat animal model of alcoholism, 429 alcohol-related analytes in meconium, 588 cues in EFE recognition, 272
273 association between ALS and, 208
212 aversive effects of, 157
159 and brain neurodevelopment, 47
51, 48f and central glutamate activity AMPARs, 456 ethanol and mesocorticolimbic reward system, 458
459 ethanol effects on glutamate transporters, 457
458 ethanol effects on iGluRs, 457 ethanol on mGluRs effects, 456 future directions, 459 glutamate, 454 glutamate-associated transporters, 457 GRIDs, 456
457 ionotropic glutamate receptors, 456 KARs, 456 mesocorticolimbic reward system, 458 mGluRs, 454 NMDARs, 456 synaptic components of glutamatergic system, 459 VGLUTs, 457 change across life span alcohol-induced place conditioning, 359 alcohol-induced taste aversion, 356
358 clinical studies in alcohol liver disease, 626t connecting behavioral effects of alcohol and acetaldehyde in fetus, 83
84 consumers, 109 and crack cocaine mixture metabolism, 538
540 cocaethylene’s mechanism of action, 540f cocaine and cocaethylene metabolites, 539f cocaine hepatic transesterification in, 539f craving, 603 cue reactivity paradigm, 261 cues, 261

INDEX

depolarization, 135 detoxification pathways, 483 drinking, 58, 355, 488
489, 577, 654 activates neuroimmune system, 180
181 and detrimental effects, 577 effect on cognition and memory, 551 effects on corpus callosum activation of TLRs, 147 brain and corpus callosum structure and function, 149 cerebral ethanol metabolism and ROS generation, 145
147 effects of ethanol on corpus callosum, 149
150 ethanol and oxidative damage, 145 free iron accumulation, 148 gut
brain axis, 147
148 microRNA-associated oxidative stress, 148
149 pathology, 144 pathogenesis, 144
149 toxic lipids, 149 effects on nonsynaptic mechanisms, 134
139 effects on synaptic mechanisms of epileptiform activity, 132
134 employing CSD model, 110
112 on epilepsy, 139
140 explaining sex differences in neurocognitive effects of, 24 exposure, 467 during brain development, 106 fetal alcohol and acetaldehyde disposition, 82f in fetus, 86 hangover, 391 inhalation of alcohol vapors, 60 intake, 197
198 intoxication, 577 metabolism, 29, 673
675 genes, 487, 488f oxidative pathways, 82f metabolism, 586
587, 587f misuse, 21, 277
279, 282, 427 modulates glutamatergic, 156
157 motivational effects of, 355
356 motivational properties, acetaldehyde mediates, 348
350 myopia, 529
530 oxidative pathways of alcohol metabolism, 82f and pain, 221 perinatal learning with, 85
86 reinforcement, 444 reinforcing effects of alcohol and acetaldehyde in fetus, 84
85 relapse, 654 spectrum disorders, 237 and synaptic plasticity during adolescence, 105 during early development, 100
105 use, 618
619 precursor or consequence, 191
192 in women during pregnancy, 585
586, 586t

Alcohol (mis)use and AUD, 308
309 Alcohol consumption, 49, 165
166, 437
440, 506
507, 585, 600, 648 β-endorphin’s role in, 318 and adaptations, 316
317 and addiction, 483 AUDIT surpass methods of screening, 599
600 becoming “successful” drinker, 7
8 developing skills to reducing harm and maximizing pleasure as drinking, 8 differential activations relating to alcohol consumption patterns, 188
190 drinking, 9 in humans, 579
580 investigating drinking with university students, 5 nalmefene for reduction of, 644 pattern, 335
336 during pregnancy, 69 in pregnancy and biological matrices, 587
588 securing future through completing degree, 10 sex differences in, 320
321 sociology, 10
11 space shapes students’ drinking practices, 5
7 “successful” drinking and university lifestyle, 8
9 tertiary education and alcohol, 4
5 university as space
time of becoming, 4 as time and place to consume alcohol, 5, 6t university-based drinking, 7 Alcohol Craving Experience questionnaire (ACE questionnaire), 603
604, 608 composition, 604t craving, 603 measurement, 603
608 Alcohol dehydrogenase (ADH), 29, 39, 81, 227, 345, 487, 494, 586 polymorphism, 31
33 causes and percentage of alleles, 35t frequencies of alleles encoding of enzymes, 34t human ADH isoenzymes, 32t Alcohol dependence (AD), 29, 31, 36, 238, 427, 577, 643, 648, 653
654 cholinergic nicotinic mechanisms in, 428
429, 430t nicotinic acetylcholine mechanisms in, 429 treatment in, 643
644 Alcohol Hangover Severity Scale (AHSS), 392 Alcohol Relapse Risk Scale (ARRS), 386
387 Alcohol use disorders (AUD), 13
15, 15f, 17f, 21, 24, 31, 119, 153, 159, 179, 187, 217, 238, 249
250, 259, 269, 307
309, 315, 335, 355, 363, 373, 383, 406
407, 427, 454, 473, 484, 577, 580
581, 580f, 603, 614, 618f, 623, 648, 653, 661, 664 animal models of, 361 baclofen

INDEX

pharmacologic properties, 624t in treatment, 625
628 burden, 668 clinical studies, 626t combinatorial pharmacotherapeutics, 654 controversies in AUD treatment, 629
630 diagnostic methods, 577
578 biomarkers, 578 questionnaires, 578 EFE, 270 alcohol-related cues in EFE recognition, 272
273 brain model of core and extended regions, 270
271 considerations for future research and EFE processing, 273 functional connectivity between core and extended EFE network regions, 272 implications of EFE processing deficits, 271
272 neural correlates of identification, 270 and emotion, 269
270 GABAB receptors role in, 623
624 implications for treatments, 667
668 metabolomics in diagnosis, 578
581 model of neural pathways of aberrant face processing in, 271f morbidity, comorbidity, and mortality related to, 22
23 naltrexone, 653
654 naltrexone 1 bupropion, 658 naltrexone 1 fluoxetine, 657
658 naltrexone 1 prazosin, 655 naltrexone 1 varenicline, 655
657 network imbalance in, 237
238, 238f neuropsychological underpinnings, 309
311 pathways to alcohol use disorders with women, 21
22 preclinical investigations of avermectins, 663
667 purinergic P2X4 receptors, 662 RCT in, 627t recovery from, 384
385 biopsychosocial model, 384 stages of behavioral change model, 384
385 relationship between P2X4RS and ethanol, 662
663 review of social cognition in patients, 374
377 false-beliefs task, 376f movie for assessment of social cognition task, 376f treatment, 658 Alcohol Use Disorders Identification Test (AUDIT), 192, 578, 595, 596f, 600, 675 frequent cut-off points, 598
599 improvement by changing element, 599 instruments context, 595
597 representative, 597t scores, 412 structure, 597
598 surpass methods of alcohol consumption screening, 599
600 Alcohol Withdrawal Scale (AWS), 675

Alcohol Withdrawal Severity Scale, 675 Alcohol withdrawal syndrome (AWS), 131, 133
134, 135f, 249
250, 250f, 671
673, 672f, 676t, 679 amygdala and, 252 benzodiazepines, 677
678 clinical symptoms in, 672t differential diagnoses, 673t as hallmark of physiological dependence, 250
251 hypothalamus and, 252
253 laboratory findings in, 674t laboratory parameters as diagnostic tools, 673
675 other brain regions implicating in, 253 therapeutic intervention, 675 tools to grade severity of symptoms, 675 treatment, 675
677 Alcohol-induced liver disease (AILD), 626
628, 630 Alcohol-related birth defects (ARBD), 493 Alcohol-related neurodevelopmental disorder (ARND), 69
70, 493 Alcoholic(s), 144 myelopathy, 196 myelopathy and neuropathy in, 203 Alcoholics Anonymous (AA), 386 Alcoholism, 29, 31, 36, 109
110, 131, 195
201, 237
238, 277, 449, 473, 483
484, 485t, 486t, 518
519, 619 alcohol-preferring rat animal model of, 429 alcoholism-related taste and addiction genes with food choice, 486
487 electrophysiological measures in treatment, 124
125 endophenotypes for, 125 ERO findings during reward processing, 261
262 ERP findings in, 260
261 FC findings on reward system in, 264 and gambling comorbidity, 529
530 biological factors related to, 530
531 development factors related to comorbidity between, 530 personality traits and comorbidity of, 532 genetic marks for, 489 impact on BD, 364f implication for treatment, 36 nalmefene efficacy and safety, 646
647 nalmefene-licensed population, 644
646 for reduction of alcohol consumption, 644 UNmet medical needs supporting by, 649 reward related functional MRI findings in, 263
264 structural findings on reward system in, 262
263 treatment in alcohol dependence, 643
644 Aldehyde dehydrogenase (ALDH), 29, 39
40, 198, 494. See also Alcohol dehydrogenase (ADH) activity, 464
465 ALDH1A1 variants, 34 ALDH2, 198

691 ALDH2 2 allele, 198 polymorphism, 31 enzyme inhibition, 542 polymorphism, 31, 33
35 causes and percentage of alleles, 35t frequencies of alleles encoding of enzymes, 34t ALDH. See Aldehyde dehydrogenase (ALDH) Aldh2-knockout mice (Aldh2-KO mice), 40
41 Aldh2-KO mice. See Aldh2-knockout mice (Aldh2-KO mice) Allodynia, 220
221 Allopregnanolone, 405
406, 410
411 Allostasis, 250
251, 365
366, 616
617 allostatic loads, 365
366, 366f Alpha band ERO activity, 125 α-amino-3-hydroxy-5-methyl-4isoxazolepropionic acid receptor (AMPAR), 156
157, 456, 466 α-amino-3-hydroxy-5-methylisoxazole-4 propionic acid (AMPA), 250
251 α-tocopherol, 99 alcohol and brain electrical activity, 110 alcoholism and brain injury, 109
110 brain effects of alcohol employing CSD model, 110
112 electrophysiology, 115 interaction with ethanol on, 112
114 neural effects of drugs, 114 α3β4 nAChRs, 428
429 α7-containing nAChRs, 427
428 ALS. See Amyotrophic lateral sclerosis (ALS) ALT. See Alanine aminotransferase (ALT) Alternative reinforcement among adults, 302 among college students and emerging adults, 300 among teenagers and adolescents, 300 gender and, 300 social context and, 300
301 as transdiagnostic risk factor, 302
303 Alternative sampling strategies, 559
560 Alzheimer’s disease (AD), 464, 508 American Psychiatric Association (APA), 307, 603 Amine-aldehyde metabolites, 350 3-Amino-1,2,4-triazole (AT), 349 AMPA. See α-amino-3-hydroxy-5methylisoxazole-4 propionic acid (AMPA) AMPAR. See α-amino-3-hydroxy-5-methyl-4isoxazolepropionic acid receptor (AMPAR) Amphetamines, 171 Amygdala (Amy), 171, 252, 281
282, 435
436, 550 amygdala-pallidum functional connectivity, 270 Amyloidosis, 199
201 Amyotrophic lateral sclerosis (ALS), 207
208, 214 association between alcohol and, 208
212

692 Amyotrophic lateral sclerosis (ALS) (Continued) design, main results and limitations of studies, 209t results, 212
213 Analgesia, 221 Analytical chemistry methods, 419 Anemia, 197, 199 Anergia, 547 ANG gene, 208 Animal models, 165 of alcohol exposure during gestation/brain development, 90 use disorders, 361 of BD, 64 BD diagnostic in humans, 57
58 clinical criteria for developing, 58
59 current preclinical models, 59 validity, 63f voluntary alcohol consumption, 61
62 forced administration of high doses of alcohol, 59
61 forced drinking, 60
61 gavage, 59
60 inhalation of alcohol vapors, 60 intraperitoneal injections, 60 of pain, 220
221 revealing FASD etiology via, 326
329 Animal research role in FASD, 71
73 Ankyrin repeat, and kinase domain containing 1 (ANKK1), 484 Anoxia-induced apnea, 91 Anterior cingulated cortex (ACC), 188, 270
271, 365, 417 Antialcohol. See also Alcohol effect, 664 mechanisms of avermectins, 666
667 Anticonvulsants, 677
678 Antidepressant pharmacotherapy, 614
615 Antioxidant (AO), 109
110, 505
506 defense types, 507f molecule, 112
113 potential, 467
469 as therapeutic strategies for FASD treatment, 497
501, 498t, 499t Antisocial personality disorder (ASPD), 277 neurobiological mechanisms, 278
282 Anxiety, 158, 614 social, 546 social interaction and modulation by, 548
550 AO-based therapeutic interventions, 510 APA. See American Psychiatric Association (APA) Apoptosis, 507 Appetitive drive networks, 246 Appetitive-consummatory model, 422 AQP4. See Aquaporins (AQP4) Aquaporins (AQP4), 138
139 ARBD. See Alcohol-related birth defects (ARBD) Arcuate nucleus (ArN), 435
436 Aripiprazole, 367
369

INDEX

ARND. See Alcohol-related neurodevelopmental disorder (ARND) ARRS. See Alcohol Relapse Risk Scale (ARRS) ARSS-SUV. See Adolescent Reinforcement Survey—Substance Use Version (ARSS-SUV) Artificial cerebrospinal fluid (ACSF), 419 Ascorbic acid, 516 Asialo-Tf, 558
559 Asp40 allele of opioid receptor mu-1 gene, 412 Aspartate aminotransferase (AST), 558
559, 578 ASPD. See Antisocial personality disorder (ASPD) Assessment Group, 648 Associative processing, 250
251 AST. See Aspartate aminotransferase (AST) Astaxanthin, 110
112 Astrocytes, 145
146 Astrocytic regulation, 158
159 Asymmetry, 290 AT. See 3-Amino-1,2,4-triazole (AT) ATP. See Adenonsine-50 -triphosphate (ATP) ATP-binding cassette transporter (ABC transporter), 664
665 Attention, 270
272 divided, 393
394 selective, 123, 393
394 Attention deficit hyperactivity disorder (ADHD), 326 Attentional orientation, 123 Attributional bias, 374, 377 AUD. See Alcohol use disorders (AUD) AUDIT. See Alcohol Use Disorders Identification Test (AUDIT) Autism, 53, 508 Autobiographical memory, 394 Autonomic dysfunction, 202 Autophagy, 507 Avermectins class, 663 preclinical investigations, 663
667 antialcohol mechanisms, 666
667 preclinical ivermectin study, 663
664 preclinical moxidectin study, 664
666 Aversive effects of alcohol, 153, 157
159 AWS. See Alcohol Withdrawal Scale (AWS); Alcohol withdrawal syndrome (AWS)

B BAC. See Blood alcohol concentration (BAC) Baclofen, 623
625, 633, 639, 677
678 adverse reactions reporting with, 629t AILD, 630 chemical structure of baclofen enantiomers, 624f clinical efficacy of baclofen in AUD treatment, 625
628 clinical pharmacology, 624
625 controversies in AUD treatment with high doses, 629
630

distribution, 634 GABAB receptors role in AUD, 623
624 intoxication, 637
638 metabolism, 635f open-label and observational studies, 625t pharmacologic properties in AUD patients, 624t safety profile, 628
629 Baclofen-induced neurotoxicity alterations in baclofen pharmacokinetics in overdose, 638 baclofen pharmacokinetics, 634 baclofen prescription for ethanol abstinence, 633
634 baclofen-induced respiratory effects, 637
638 baclofen-induced sedative effects, 635
636 baclofen-related adverse effects at therapeutic doses, 635
636 baclofen-related neuropsychiatric adverse effects, 635t baclofen-related neurotoxicity in overdose, 636
638 baclofen-related toxicity in overdose and withdrawal syndrome, 636t GABAB receptors, 639 management of baclofen-poisoned patient, 638 Balloon analogue risk task (BART), 260
261 Basolateral amygdala (BLA), 164 BBB. See Blood
brain barrier (BBB) BD. See Binge drinking (BD); Bipolar disorders (BD) BD-SUD comorbidity, 365
366 BDNF. See Brain-derived neurotrophic factor (BDNF) BEC. See Blood ethanol concentration (BEC) Bed nucleus of stria terminalis (BNST), 249
250, 316, 407, 458 Behavior-based pain assessments, 220 Behavioral change model, stages of, 384
385 Behavioral economic theory, 297 Benzodiazepines (BZD), 675
678 administration, 677 anticonvulsants, 133
134 Benzoyl ecgonine ethyl ester, 538 Benzoylethylecgonine, 538 Beriberi neuropathy, 198 Beta band ERO activity, 125 β-amino acid, 634 β-endorphin (β-E), 315, 318
319, 319f activity, 437 deficiency, 437
439 role in alcohol consumption, 318 β2 -nAChR modulation, 429 BIF. See Borderline intellectual functioning (BIF) Binge drinking (BD), 57, 89
90, 99, 138
139, 180, 217, 335
336, 545, 599, 665
666. See also Hangover adequacy of different procedures with pathophysiology, 59t behavior, 355 cognitive impairments in, 341
342 diagnostic in humans, 57
58

693

INDEX

framing future research on impulsivity in, 339
341 multilevel conceptualization of impulsivity in, 336
339 operant, 61
62 hepatic gross morphology after BD, 63f preclinical models of, 59 Binge test (BT), 316 Binge-like injection model (BLI model), 326 Binge/intoxication, 153
155, 250
251 Binges, 105 Bioinformatic analysis, 480 Biological matrices, alcohol consumption in, 587
588 Biomarkers, 578
579, 579t, 599
600 of alcohol misuse direct markers, 559
562 ethanol, 557
558 implications for patient treatment and follow-up, 562
563 indirect biomarkers, 558
559 Biopsychosocial model, 384 Bipolar disorders (BD), 363, 369, 629
630 alcoholism impact, 364f allostatic alterations, 367f clinical features, course and prognosis, 367 epidemiology, 363
364 genetic factors, 364 neurophysiological correlates, 364
366 pathogenetic pathways, 364 psychopathological correlates, 366
367 treatment implications, 367
369 double-blind, placebo-controlled trials of medications, 368t Birth cohorts, 15
17 Bitter taste, 483 BLA. See Basolateral amygdala (BLA) Bladder disturbunce, 196 BLI model. See Binge-like injection model (BLI model) Blood alcohol concentration (BAC), 391, 400
401, 422
423, 569, 585 Blood ethanol concentration (BEC), 58, 99, 217, 316 Blood-breath concentration ratio, 557 Blood-oxygen-level-dependent activation (BOLD activation), 238 Blood
brain barrier (BBB), 39
40, 176, 506
507, 634 BNST. See Bed nucleus of stria terminalis (BNST) BOLD activation. See Blood-oxygen-leveldependent activation (BOLD activation) Borderline intellectual functioning (BIF), 307 Bottom-up control, 252 Brain ACH adducts, 42
43 in ethanol neurotoxicity, 42 alcohol and brain neurodevelopment behavioral outcomes and mechanisms with PAE, 50
51 neurodevelopmental alterations, 49
50

neurodevelopmental events, 47
49 alcohol exposure during brain development, 106 catalase, 40
41 circuits, 163 and corpus callosum structure and function, 149 disorders associated with oxidative stress, 508
509 effects of alcohol employing CSD model, 110
112 electrical activity, 110, 119 effects of ethanol consumption on brain function, 111t electrophysiology, 115 endogenous opioids and receptors in brain reward processes, 435
436 EtOH, 516 function, 405
406 injury, 109
110 nAChRs, 427
428 networks in active alcoholism, 237
238 Brain electrophysiological signatures. See also Corpus callosum attentional orientation and conflict monitoring, 123 cognitive evaluation and processing (P3/P300), 123 EEG, 119
120 electrophysiological findings in alcoholics, 121t electrophysiological measures, 128 as endophenotypes for alcoholism, 125 in treatment of alcoholism, 124
125 ERN, 123 EROs findings, 124
127 ERP findings, 120
124 language processing, 123
124 methods, 120f MMN, 123 selective attention, 123 sensory and perceptual potentials, 122
123 Brain reward system (BRS), 484 Brain-derived neurotrophic factor (BDNF), 364, 508 Brain
computer interfaces, 119 Brainstem evoked potentials, 120
122 Breathing, 92
94 animal models of alcohol exposure, 90 methodology to investigate breathing physiology, 90 pharmacology of respiratory network, 94
95 prenatal ethanol exposure and breathing function, 95 rhythmogenesis, 92
94 short-and long-term respiratory plasticity, 90
92 BRENDA approach, 646 BRS. See Brain reward system (BRS) BT. See Binge test (BT) Bupropion (BUP), 654, 658, 658f Buss Durkee Hostility Inventory, 281

BXD recombinant inbred mouse lines, 480 strains, 411 BZD. See Benzodiazepines (BZD)

C C-DBS. See Capillary dried blood spot (CDBS) c-fos gene transcription, 541, 549
550 C-reactive protein (CRP), 180, 578 C9ORF72 gene, 208 Caffeine, 546 impact of caffeine
ethanol interaction, 548
550 consumption, 552 effect on cognition and memory, 551 as modulator of ethanol abuse liability, 545
546 target for, 546
547 CAGE. See Cut down, annoyed, guilty and eye opener (CAGE) Calbindin-d28k, 163
164 Calcium (Ca), 213
214 Calcium/calmodulin-dependent kinase II (CaMKII), 156
157 Calretinin, 163
164 CaMKII. See Calcium/calmodulin-dependent kinase II (CaMKII) cAMP. See Cyclic adenosine monophosphate (cAMP) cAMP-responsive element binding protein (CREBP), 467 Candidate genes genotype x birth cohort interactions with, 14
15 studies, 18 Cannabinoids, 364, 546 Cannabis, 308 Capillary dried blood spot (C-DBS), 560 Carbohydrate deficient transferrin (CDT), 558
559, 578, 673
675 Cardiac function, 175
176 CAT/H2O2 system, 518
519 Catalase (CAT), 29, 39, 81, 464
465, 494, 505
507, 516 Catalase—enzymatic systems, 345 Cation-chloride cotransporters, 137 CBT. See Cognitive-behavioral therapy (CBT) CCEE. See Countries of Central and Eastern Europe (CCEE) CDC. See Centers for Disease Control and Prevention (CDC) CDT. See Carbohydrate deficient transferrin (CDT) CeA. See Central amygdala (CeA) Cellular allopregnanolone, 410 enzymatic pathways, 145 mechanisms, 100 Centers for Disease Control and Prevention (CDC), 22
23, 70, 516
517 Central amygdala (CeA), 249
250, 316. See also Amygdala (Amy) Central hypoxic ventilatory response, 91

694 Central motor conduction time, 197 Central nervous system (CNS), 14, 47, 99, 133, 149, 172
173, 179, 278, 454, 466
467, 493, 505, 516, 637, 661
662, 675
677 functions, 662 glutamatergic projections and receptor localization, 454f and recruitment of multiple memory systems, 458f Central respiratory network, 89
90, 92
94 CEQ. See Craving Experience Questionnaire (CEQ) Ceramide, 149 Cerebral ethanol metabolism, 145
147 Cerebral excitability, 133 Cerebral ischemia/reperfusion, 508 Cerebrospinal fluid (CSF), 278 5-HIAA metabolites, 278 CET. See Cue-exposure therapy (CET) Chantix, 654 Chemokines, 181 Childhood behavior disorders, 530 Chiral separation, 230 Chlordiazepoxide, 677 Cholinergic nicotinic mechanisms in alcohol dependence, 428
429 Chronic alcohol/alcoholism, 182 abuse, 133, 136
138 consumption, 445, 562
563. See also Alcohol consumption effects, 408
410 exposure, 153, 475 intake effects on opioid peptides and receptors, 437 misuse, 557 Chronic debilitating diseases, 179 Chronic disease, 664 Chronic ethanol. See also Ethanol (EtOH) consumption, 505 effects on enkephalinergic transmission, 445 of in hippocampus, 466
467 ingestion, 133 intake, 507 treatment, 113
114 Chronic heavy drinking and neuroimmune function, 181 Chronic ingestion of ethanol, 133 Chronic intoxication, 133 Chronic nonsynaptic effects of alcohol exposure, 139f Chronic pain, 217, 221
222 Chronic prenatal ethanol exposure, 89 Chronic X synaptic effects of alcohol, 134f CIE-exposed strains, 411 Cilobradine, 176 Circuit adaptations, 250
251 Clobazam, 675
677 Clomethiazole, 677
678 Cloninger’s influential dichotomy theory, 278 CNBD. See Cyclic nucleotide
binding domain (CNBD) CNS. See Central nervous system (CNS)

INDEX

Cobalamin, 196 serum levels of, 197 Cocaethylene, 538
539, 543 cocaine and cocaethylene metabolites, 539f cocaine hepatic transesterification in, 539f mechanism of action, 540f and neural system actions, 540
542, 541f cocaethylene mechanism of action at sodium channel, 542f main disulfiram effects, 542f Cocaine, 166, 171, 546 hepatic transesterification in cocaethylene, 539f Cognitive-behavioral therapy (CBT), 311
312, 385, 614
615, 643 Cognitive/cognition. See also Neurocognition caffeine and alcohol effect on, 551 cognitive behavioral model of AUD, 385 cognitive/emotional processes, 120 evaluation and processing (P3/P300), 123 flexibility, 270, 394 functions, 463
464 impairments in BD, 341
342 Coherence, 120, 127 Combinatorial pharmacotherapeutics, 654, 658 Comorbid psychopathology, 302
303 treatment targeting reward deprivation, 302
303 Comorbidity, 182, 269
270, 614 of alcoholism and gambling disorder, 532 Complementary reinforcers, 300 Complex Attention domain, 393
394 Compound muscle action potentials, 199 Compulsive alcohol seeking, 250
253 Compulsive behavior, 529, 532 Computed tomography, 675, 681 Conditional stimulus (CS), 356 Conditioned place aversion (CPA), 157
158, 356 Conditioned place preference (CPP), 156f, 173, 227
228, 345
346, 356 Conditioned taste aversion (CTA), 157, 356 Conflict monitoring (N2), 123 Consumption, 599 Continuous preference drinking (CPD), 326, 327f Continuous reinforcement schedule, 422 Conventional sampling strategies, 562
563 Coping skills, 385 Coping skills training (CST), 385 Copper deficiencies, 196 Core region of nucleus accumbens (AcbC), 164 Cornu Ammonis field, 100 Corpus callosum, 143, 143f. See also Brain electrophysiological signatures ethanol effects on, 149
150 pathogenesis, 144
149 activation of TLRs, 147 cerebral ethanol metabolism and ROS generation, 145
147 ethanol and oxidative damage, 145 free iron accumulation, 148 gut
brain axis, 147
148

microRNA-associated oxidative stress, 148
149 toxic lipids, 149 pathology, 144 structure and function, 149 CORT. See Corticosterone (CORT) Cortical patterning, 73
74 Cortical spreading depression (CSD), 109
110, 112t, 113f, 114, 114t Cortical
striatal
pallidal connectivity, 166 Corticosterone (CORT), 316 Corticostriatal pathway (CP), 270
271 Corticotropin releasing hormone receptor 1 (CRHR1), 252 Corticotropin-releasing factor (CRF), 223, 252, 330, 617 Corticotropin-releasing hormone (CRH), 315
316, 317f, 318
319, 364, 410 in alcohol consumption and adaptations, 316
317 Countries of Central and Eastern Europe (CCEE), 13
14 COX-2. See Cyclooxygenase-2 (COX-2) CP. See Corticostriatal pathway (CP) CP-601932, 428
429, 430t CPA. See Conditioned place aversion (CPA) CPD. See Continuous preference drinking (CPD) CPP. See Conditioned place preference (CPP) Crack cocaine, 537 alcohol and crack cocaine mixture metabolism, 538
540 Craniofacial dysmorphology, 49 Craving, 385, 603, 606, 608 assessment, 606 measurement, 603
608 administration demand, 606
607 clinical utility, 607 limitations and practical considerations, 608 psychometric integrity, 605
606 temporal reference, 605 theoretical foundation, 604
605 relief, 250
251 Craving Experience Questionnaire (CEQ), 605
606 CREBP. See cAMP-responsive element binding protein (CREBP) CRF. See Corticotropin-releasing factor (CRF) CRH. See Corticotropin-releasing hormone (CRH) CRH1 receptor (CRH1R), 315 CRHR1. See Corticotropin releasing hormone receptor 1 (CRHR1) CRP. See C-reactive protein (CRP) CS. See Conditional stimulus (CS) CSD. See Cortical spreading depression (CSD); Current source density (CSD) CSF. See Cerebrospinal fluid (CSF) CST. See Coping skills training (CST) CTA. See Conditioned taste aversion (CTA) Cue-elicited P3 responses, 261 Cue-exposure therapy (CET), 385 Cued recall, 394 Current source density (CSD), 123

INDEX

Cut down, annoyed, guilty and eye opener (CAGE), 578 Cyanamide, 40
41, 522 Cyanidin-3-glucoside, 501 Cyclic adenosine monophosphate (cAMP), 172
173, 508 Cyclic nucleotide
binding domain (CNBD), 172
173 Cyclooxygenase-2 (COX-2), 507 Cyclooxygenases, 516 Cynomolgus monkeys, 410 alcohol-induced changes in neuroactive steroids in, 409t CYP1A2. See Cytochrome P450 1A2 (CYP1A2) CYP2E1. See Cytochrome P450 2E1 (CYP2E1) CYP3A4, 494 Cysteine, 516 Cystine glutamate exchanger (xCT), 455f, 457
458 Cytisine, 428
429, 430t Cytochrome P450 1A2 (CYP1A2), 494 Cytochrome P450 2E1 (CYP2E1), 29, 39, 81, 345, 465
466, 487, 494, 506
507 Cytochrome P450, 494 Cytokines, 148, 182, 507 Cytosolic ALDH1, 33

D DA. See Dopamine (DA) DA transporter gene (DAT gene), 279 DALYS. See Disability-adjusted life years (DALYS) DAMGO, binding affinity of, 437 DAT gene. See DA transporter gene (DAT gene) DBS. See Deep brain stimulation (DBS); Dried blood spots (DBS) DC. See Direct current (DC) DD. See Depressive disorder (DD) Decision-making, 394 ability, 531 impairments, 391 Decode nonverbal emotion, 271
272 Deep brain stimulation (DBS), 167 Dehydroepiandrosterone (DHEA), 410 Delirium tremens (DT), 671
673 Delta aminolevulinic acid (δ-ALA), 517
518 Delta aminolevulinic acid dehydrase (δ-ALA-D), 517
518 Delta band ERO activity, 124
125 Delta opioid receptor (DOR), 436 Delta receptors, 221 Demand, 298 administration, 606
607 example of reinforcement schedule, 299t Dementia, 464 Demographic markers, 5 Demyelination, 199
201 Dentate gyrus (DG), 100 Deoxycorticosterone (DOC), 405
406 Deoxyribonucleic acid (DNA), 51, 73
74 adducts, 42
43 methylation, 327
328, 467 Depression, 52
53, 158, 182, 241, 385, 614, 629
630

Depressive disorder (DD), 508
509 Deprivation in rewards and alcohol misuse, 297
299 alternative reinforcement among adults, 302 among college students and emerging adults, 300 among teenagers and adolescents, 300 social context and, 300
301 as transdiagnostic risk factor, 302
303 demand, 298 gender and alternative reinforcement, 300 reward deprivation, 297
298, 304 substance-free reinforcement, 297
299 Desoxyribonucleic acid (DNA), 146 Dexamethasone suppression of DOC, 412 DG. See Dentate gyrus (DG) DHEA. See Dehydroepiandrosterone (DHEA) Diabetes mellitus, 199
201 Diagnostic and Statistical Manual of Mental Disorders (DSM
IV), 577 Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5), 269, 392, 607, 671 Diazepam, 675
677 DID model. See Drinking in dark model (DID model) Diffusion tensor imaging (DTI), 70
71, 262
263, 290 Dihydro-β-erythroidine, 428
429 1,2-Dimethyl-6,7-dihydroxyisoquinolinium ion (DMDHIQ1), 230
232 Dinorfine, 541 Direct alcohol metabolites, 560
562 EtG and EtS, 560
561 FAEEs, 562 PEth, 561
562 Direct biomarker, 567 Direct current (DC), 110, 112f Direct ethanol biomarkers, 559
563 direct alcohol metabolites, 560
562 sampling strategies in follow-up of alcohol (mis)use, 560 DIS. See Disulfiram (DIS) Disability-adjusted life years (DALYS), 681 Disialo-Tf, 558
559 Disrupted neural signature of RI, 191
192 Disturbed dopamine reward brain regulation, 529 Disulfiram (DIS), 40
41, 522, 537 Divalproex, 368
369 Divided attention, 393
394 DLPFC. See Dorsolateral prefrontal cortex (DLPFC) DMDHIQ1. See 1,2-Dimethyl-6,7dihydroxyisoquinolinium ion (DMDHIQ1) DNA. See Deoxyribonucleic acid (DNA); Desoxyribonucleic acid (DNA) DOC. See Deoxycorticosterone (DOC) Dopamine (DA), 42, 227, 279, 346, 364, 427
428, 458. See also Extracellular striatal dopamine dopamine-dependent behaviors, 666
667 levels, 153

695 mesolimbic system, 171 neurons, 172
173 pharmacological modulation of acetaldehyde’s effects, 350f in striatum, 417
419 system, 22 Dopamine 1 (D1), 164 Dopamine 2 (D2), 164 Dopamine D2 receptor (DRD2), 455, 484 Dopaminergic activity, 279 Dopaminergic neurotransmission, 662 Dopaminergic transmission, ethanol and opioid effects on, 444 DOR. See Delta opioid receptor (DOR) Dorsal striatum (DS), 270
271, 531 Dorsolateral prefrontal cortex (DLPFC), 188, 238, 264, 365 Dorsolateral striatum, 417 Dorsomedial striatum, 417 Dose-dependency of prenatal EtOH effects, 103
104 Down-regulation, 437 DRD2. See Dopamine D2 receptor (DRD2) Dried blood spots (DBS), 559
560 Dried urine samples, 560 Drinking, 7, 9. See also Binge drinking (BD) alcoholic beverages, 109 behavior, 180 consequence of modest, 180
181 drinking-search behavior, 577 forced, 60
61 heavy/hazardous/binge, 192 motivations, 341 neuroimmune response to acute intoxication, 181 resumption of, 384 social, 561
562 university-based, 7 Drinking in dark model (DID model), 61, 316 Drinking to cope (DTC), 615, 619 Drinking-risk level (DRL), 644 DRL. See Drinking-risk level (DRL) Drug(s), 546 abuse, 385
386. See also Alcohol—abuse addiction, 529 cycle, 154f administration, 654 consumption, 298. See also Alcohol consumption drug-induced inhibition, 165 drug-seeking behavior, 383 neural effects of, 114 reinforcement critically model, 347 target, 176 DS. See Dorsal striatum (DS) DSM-5. See Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) DT. See Delirium tremens (DT) DTC. See Drinking to cope (DTC) DTI. See Diffusion tensor imaging (DTI) Dual-process models, 373
374 of addiction, 310 Dynorphin calbindin, 163
164 Dynorphinergic neurons, 436 Dynorphins, 436 Dysgenesis, 289

696 Dysregulate stress responsivity, 615
616 Dysregulated neuroimmune system, 184

E EA. See Epileptiform activities (EA) EAAT. See Excitatory amino acid transporters (EAAT) EAN. See European Academy of Neurology (EAN) Early childhood, 325 Early life stress, 329
330 Early-alcohol exposure, 326 ECoG. See Electrocorticogram (ECoG) ECPBHS. See Estonian Children Personality Behaviour and Health Study (ECPBHS) ED. See Error detection (ED) EEG. See Electroencephalogram (EEG) EFE. See Emotional facial expressions (EFE) EI theory. See Elaborated Intrusion theory (EI theory) Elaborated Intrusion theory (EI theory), 604
605, 605f Electrocorticogram (ECoG), 115 Electroencephalogram (EEG), 110, 119, 131
132, 243
244, 291, 633, 675 coherence, 120 power spectral analysis, 119
120 Electrophilic compound, 227 Electrophysiological measures, 128 as endophenotypes for alcoholism, 125 in treatment of alcoholism, 124
125 Electrophysiological recording techniques, 110 Electrophysiological studies, 662 EMA. See European Medicines Agency (EMA) Embryo/fetus, 586
587 Emotion(al), 269
270 faces, 271
272 regulation, 239
240, 532 Emotional facial expressions (EFE), 270. See also Negative emotions alcohol-related cues in EFE recognition, 272
273 brain model of core and extended regions of EFE processing, 270
271 functional connectivity between core and extended EFE network regions, 272 implications of EFE processing deficits, 271
272 neural correlates of EFE identification, 270 Emotional facial perception and recognition, 273 Emotional processing, 374, 377, 377f of facial expressions, 271
272 Emotionality problems (EP), 386
387 Empathy, 374 Encephalitis, 671
673 Encephalopathy, 671
673 Endocannabinoids, 348 Endocytosis, 437 Endogenous antioxidant system, 496
497 Endogenous opioids, 364

INDEX

and receptors in brain reward processes, 435
436 system, 444 Endophenotypes, 127 for alcoholism, 125 Endoplasmic reticulum stress (ERS), 507 Endorphins, 435
436 Endotoxemia, 147
148 Energy drinks, 545
546 Enkephalin, 163
164 Enkephalinergic system, 445 alcoholism, 449 enkephalinergic transmission acute and chronic ethanol effects, 445 prenatal ethanol effects, 445
447 ethanol and opioid effects on dopaminergic transmission, 444 implications for treatments, 447
448 Enkephalins, 436 Entopeduncular nucleus (EPN), 155
156 Environment(al) factors, 483 long-lasting continuum modulation by, 325
326 relapse risks in AUD, 385
386 reward deprivation, 297 stimuli, 417 Enzymatic AOs, 505
506 Enzyme alcohol dehydrogenase, 23 EP. See Emotionality problems (EP) Epigenetics, 77 Epilepsy, 110 alcohol abuse on, 139
140 Epileptiform activities (EA), 132 nonsynaptic mechanisms, 134
139 synaptic mechanisms, 132
134 Epithalamic structure, 153 EPN. See Entopeduncular nucleus (EPN) EPSPs. See Excitatory postsynaptic potentials (EPSPs) ErbB4 receptor, 14
15 ERD/ERS. See Event-related desynchronization/synchronization (ERD/ERS) ERK. See Extracellular signal-regulated kinase (ERK) ERN. See Error-related negativity (ERN) EROs. See Event-related oscillations (EROs) ERPs. See Event-related potentials (ERPs) Error detection (ED), 188 Error-related negativity (ERN), 123, 260 Error-related paradigm, 260 ERS. See Endoplasmic reticulum stress (ERS) Estonia, 17 Estonian Children Personality Behaviour and Health Study (ECPBHS), 14 Estradiol valerate (EV), 438 EtG. See Ethyl glucuronide (EtG) Ethanol (EtOH), 30f, 42
43, 99, 143, 145, 147f, 180, 198, 219, 224
225, 227, 315, 320f, 443
445, 458
459, 463
464, 466
468, 475
478, 516, 518
519, 557
558, 561
562, 681 actions, 173
175

lentiviral-mediated overexpression, 174f overexpression of HCN2 ion channel, 174f, 175f actions, 466 acute nontoxic ethanol intake, hippocampal gene expression, and antioxidant potential, 467
469 acute pharmacological effects on extracellular striatal dopamine, 420
421 administration on methionine-enkephalin concentration, 448f α-tocopherol protective interaction on brain, 112
114 baclofen prescription for ethanol abstinence, 633
634 behaviors, 662
664 blocks NMDA receptors, 132 brain ACH in ethanol neurotoxicity, 42 chronic and long-term effects of ethanol in hippocampus, 466
467 conversion to acetaldehyde, 39
40 decouples gap junctions, 135
136 doses, 470f effects on acute pain, 221
222 on corpus callosum, 149
150 on dopaminergic transmission, 444 on glutamate transporters, 457
458 on iGluRs, 457 on mGluRs, 456 on respiratory rhythmic activity, 93f ethanol-derived salsolinol, 232 and basal concentrations in body fluids and brain, 229
230 emergence of neurological disorders, 230
232 neurobiological basis of alcoholism, 230 ethanol-exposed animals, 90
91 ethanol-induced antinociception, 222 augmentation, 110
112 changes in gene expression, 469f, 469t oxidative stress, 506
509, 508f ethanol-related phenotypes, 476 ROS generation, 465
466 EtOH-induced oxidative stress, 519f lead, oxidative stress and, 520
521, 521f and drug consumption, 521
522 lead and, 519
520, 520t metabolism, 232 in hippocampus, 464
466 metabolites, 557 neuroactive steroids mediating specific behavioral effects, 410
411 nonoxidative phase II metabolism, 558f oxidation by CYP2E1 in endoplasmic reticulum, 465f oxidizing system, 494 relationship between P2X4RS and in vitro evidence, 662
663 in vivo evidence, 663 target for, 546
547

INDEX

toxicity, 465
466 withdrawal-induced hyperalgesia, 223 Ethanol exposure, 493 antioxidants as therapeutic strategies for FASD treatment, 497
501, 498t, 499t consequences on neurodevelopment, 47 age-related consequences of PAE, 51
52 alcohol and brain neurodevelopment, 47
51 effects during development on ROS production and oxidative stress, 495
497 ethanol metabolism in fetal brain, 494 mechanisms underlying fetal brain ethanol toxicity, 494
495 ethanol metabolism pathways, 495f Ethyl glucuronide (EtG), 30, 557, 560
561, 586, 590
591 Ethyl sulfate (EtS), 30, 557, 560
561, 586, 590
591 Ethylglucoronide, 673
675 EtOH. See Ethanol (EtOH) EtS. See Ethyl sulfate (EtS) Euro-MOTOR case-control study, 212 Italian cohorts, 213 European Academy of Neurology (EAN), 212 European case-control study, 212
213 European Medicines Agency (EMA), 643
644 guideline, 644
645 European Monitoring Centre for Drugs and Drug Addiction, 89 European Union, alcohol dependence in, 643 EV. See Estradiol valerate (EV) Event-related desynchronization/ synchronization (ERD/ERS), 125 Event-related oscillations (EROs), 119, 126f, 260 findings, 124
127 alpha and beta band ERO activity, 125 delta and theta band ERO activity, 124
125 ERO connectivity, 125
127 gamma band ERO activity, 125 during reward processing in alcoholism, 261
262 Event-related potentials (ERPs), 119, 124f, 125f, 260 findings, 120
124 findings in alcoholism, 260
261 sensory pathway (evoked) potentials, 120
122 Excessive alcohol consumption, 315, 508, 562
563. See also Binge drinking (BD) BD as harmful, 335 Excitatory amino acid transporters (EAAT), 457 Excitatory postsynaptic potentials (EPSPs), 105 Excitotoxicity, 207
208, 213
214 Executive control networks, 246 Executive function, 394 disorder, 531

Executive-based response, 189
190 Expressive language, 394 External GP segment (GPe segment), 167 Extracellular accumbal dopamine, 421
423 Extracellular signal-regulated kinase (ERK), 227
228 Extracellular striatal dopamine. See also Dopamine (DA) clinical studies of alcohol’s effects, 422
423 effects of alcohol self-administration, 421
422 ethanol’s acute pharmacological effects, 420
421 reward prediction error, 418
419 short-term effects of alcohol on behavior by dose, 420t striatal anatomy and function, 417 techniques for measuring extracellular striatal dopamine in animals, 419
420 Extrasynaptic α4βδ GABAARs, 406

F FA. See Fractional anisotropy (FA) Facial perception, 270, 272 FAEEs. See Fatty acid ethyl esters (FAEEs) FAK. See Focal adhesion kinase (FAK) Family history of alcoholism, 261
262, 264
265 FAS. See Fetal alcohol syndrome (FAS) FASD. See Fetal alcohol spectrum disorder (FASD) Fast Alcohol Screening Test, 675 Fast-scan cyclic voltammetry (FSCV), 419 Fatty acid ethyl esters (FAEEs), 30, 557, 562, 586, 588
590 in meconium, 589t serum FAEEs concentrations, 562 synthetase, 562 FC. See Functional connectivity (FC) FDA. See United States Food and Drug Administration (FDA) Fenton reactions, 516 Fetal alcohol exposure, 81 Fetal alcohol spectrum disorder (FASD), 49, 69, 77, 89, 99, 287
289, 325
326, 331, 493, 494f, 501, 586 antioxidants as therapeutic strategies for treatment, 497
501 children with FASD facing postnatal challenges, 329
330 developmental problems in, 293 diagnostic criteria, 290t functional lateralization in, 291
292 left hemisphere atypicalities in, 292t phenotypes, 70t revealing FASD etiology via animal model, 326
329 structural lateralization in, 289
291 studies in humans with, 70
77 animal research role in understanding of, 71
73 DTI, 71 functional brain imaging, 71

697 neocortical circuitry development and PrEE, 73
76 potential mechanisms of PrEE
induced neocortical changes, 76
77 PrEE and neuroanatomical development, 73 PrEE impacts thickness of neocortex, 73 structural brain imaging, 71 Fetal alcohol syndrome (FAS), 32, 49, 69
70, 89, 99, 288, 493 characteristic facial signs, 289f Fetal brain acetaldehyde, 83 in fetal environment, 82
83 role in alcohol effects on development, 83
84 ethanol metabolism in, 494 mechanisms underlying fetal brain ethanol toxicity, 494
495 Fetal ethanol exposure, 49 Fetal hepatic ADH activity, 81
82 FG. See Fusiform gyrus (FG) Fibrillar processes, 136 Fibrosis, 144 Finasteride, 410
411 Fkbp5 gene, 475
476, 476f, 477f, 478t Fluency, 394 Flumazenil, 221
222 Fluoxetine (FLU), 654, 657
658 Flush reaction, 33 fMRI. See Functional magnetic resonance imaging (fMRI) Focal adhesion kinase (FAK), 467 Foetor alcoholicus, 671 Folate, 196 deficiency, 197
198 serum levels of, 197 Food choice, alcoholism-related taste and addiction genes with, 486
487 Forced drinking, 60
61 Fornix, 281 Fractional anisotropy (FA), 71, 143
144, 262
263, 290 Free iron accumulation, 148, 148f Free recall, 394 French studies, homogeneity of, 598 FSCV. See Fast-scan cyclic voltammetry (FSCV) Functional brain imaging, 71 Functional connectivity (FC), 125
127, 264 findings on reward system in alcoholism, 264 Functional lateralization in FASD, 291
292 Functional magnetic resonance imaging (fMRI), 70
71, 238, 270, 279, 291 Go/No-Go tasks fMRI studies, 187
188, 188f differential activations relating to alcohol consumption patterns, 188
190 disrupted neural signature of RI, 191
192 heavy/hazardous/binge drinking, 192 FUS/TLS gene, 208 Fusiform gyrus (FG), 270

698 G G protein-regulated inward-rectifying potassium channels (GIRK channels), 222 GIRK2, 222 G-protein-coupled protein receptors (GPCRs), 454 G-protein-coupled receptors, 546 superfamily mediate dopamine activity, 484 GABA. See Gamma amino-butyric acid (GABA) GABA subtype B receptors (GABABRs), 156, 633, 639 role in AUD, 623
624 GABAA receptors (GABAARs), 89, 221
222, 662 GABAergic activity, 133 neurotransmissions, 156
157, 466
467 receptors, 132
133 signaling, 221
222 synapses, 417
418 Gambling addiction, alcohol and, 533 development factors related to comorbidity between alcoholism and, 530 gambling comorbidity alcoholism and, 529
530 biological factors related to alcoholism and, 530
531 personality traits and comorbidity of alcoholism, 532 treatment problems, 532
533 Gambling disorder, 529, 532 Gamma amino-butyric acid (GABA), 94
95, 131
132, 213
214, 227, 364, 427
428, 435
436, 454, 494, 623, 633 GABA-enhancing properties, 677
678 neurotransmission, 624 receptors, 530, 623 Gamma band ERO activity, 125, 126f Gamma glutamyltransferase (GGT), 558
559, 578 Gas chromatography
mass spectrometry (GC-MS), 578
579 Gavage, 59
60 GBD. See Global Burden of Disease Study (GBD) GC-MS. See Gas chromatography
mass spectrometry (GC-MS) GD7. See Gestational day seven (GD7) GDs. See Gestational days (GDs) ´ lcool e GEAD. See Grupo de Estudossobre A outras Drogas (GEAD) Geller-Seifter procedure, 347 Gender and alternative reinforcement, 300 Gene encoding alcohol-metabolizing enzymes, 31 expression, 73
76, 466
467, 474 genome-wide, 326 gene-blocking techniques, 349 Genetic(s), 40
41 marks for alcoholism, 489 polymorphisms, 31 variation, 412

INDEX

Genome-wide association studies (GWAS), 364 Genome-wide gene expression, 326 Genotype x birth cohort interaction, 14 with candidate genes, 14
15 mechanisms in, 17
18 Gestation, 99
101 development, 90 Gestational day seven (GD7), 101
103 Gestational days (GDs), 495 GGT. See Gamma glutamyltransferase (GGT) GIRK channels. See G protein-regulated inward-rectifying potassium channels (GIRK channels) Girls early diagnosis and treatment tailored to women and, 25 improving alcohol usage prevention for, 24
25 GKAP. See Guanylate kinase-associated protein (GKAP) GLAST. See Glutamate-Aspartate Transporter (GLAST) Glia, 457 Glial cells, 109 Glial glutamate transporter (GLT-1), 158
159 Global Burden of Disease Study (GBD), 363 Globus pallidus (GPi), 167 GLT-1. See Glial glutamate transporter (GLT1) Glucuronidation of ethanol, 560 Glutamate, 364, 454, 494 glutamate-associated functions, 458
459 glutamate-associated transporters, 455f, 457 receptors, 455f, 467 abnormalities, 100 Glutamate transporters (GLTs) ethanol effects on, 457
458 GLT-1, 457 Glutamate-Aspartate Transporter (GLAST), 457 Glutamatergic activity, 133 neurotransmission, 662 signaling, 222
223 systems, 466
467 synaptic components, 459 Glutamic acid, 454 Glutathione (GSH), 495
496, 516 Glutathione peroxidase (GPx), 496
497, 508, 516 Glutathione reductase (GR), 496
497, 508 Glycine, 89 Go/No-Go task, 187
188, 188f, 189f, 336
337 Gold thioglucose, 438 GPCRs. See G-protein-coupled protein receptors (GPCRs) GPe segment. See External GP segment (GPe segment) GPi. See Globus pallidus (GPi); Internal GP (GPi) GPx. See Glutathione peroxidase (GPx) GR. See Glutathione reductase (GR) GRIDs, 456
457 Grm7 gene, 456

´ lcool e outras Grupo de Estudossobre A Drogas (GEAD), 538 GSH. See Glutathione (GSH) Guanylate kinase-associated protein (GKAP), 456 Guillain-Barre´ syndrome, 198, 201
202 Gustatory alcohol cues, 423 Gut
brain axis, 147
148 GWAS. See Genome-wide association studies (GWAS)

H 1

H-NMR spectroscopy, 578, 581, 581f in metabolomics, 579 Habenulomesencephalic circuit, 156
157, 156f HAD1. See High-alcohol drinking1 (HAD1) Half-life, 568 Hangover, 391
392, 398t, 400. See also Binge drinking (BD) measurement, 392 neurocognitive performance during, 394
400 organizing research on neurocognitive performance, 392
394 symptoms, 393t Hangover symptoms scale (HSS), 392 Hazardous consumption of alcohol, 577 HDAC activity. See Histone deacetylase activity (HDAC activity) HDDs. See Heavy-drinking days (HDDs) Heat-shock proteins (HSP), 467, 470 HSP70, 520
521 Heavy-drinking days (HDDs), 646, 647f Heavy/hazardous/binge drinking, 192 Heber-Weiss reactions, 516 Hedonic processing, 252 Hepatic myelopathy, 195
197 Hepcidin, 148 Hering-Breuer reflexes, 637
638 Heterogeneity of DAT density, 279 Heterogeneous distribution, 175
176 Heteromeric receptors, 456 HF. See Hippocampal formation (HF) 5-HIAA. See 5-Hydroxyindoleacetic acid (5HIAA) 5-HT. See 5-Hydroxytryptophan (5-HT); Serotonin (5-HT) High-affinity α4β2 , 427
428 High-alcohol drinking1 (HAD1), 663 High-mobility group box 1 (HMGB1), 181 High-performance liquid chromatography (HPLC), 419 High-pressure liquid chromatography combined with tandem mass spectroscopic detection (HPLC/MS/ MS), 568 High-risk (HR), 119 individuals, 259 offspring, 128 Hippocampal fibers, 281 Hippocampal formation (HF), 131 Hippocampal gene changes following exposure to combination of stress and ethanol, 475
478

699

INDEX

to ethanol, 475 to stress, 474 Hippocampal gene expression, 467
469 Hippocampus (Hip), 99
100, 100f, 135
136, 281, 437, 473, 474t chronic and long-term effects of ethanol in, 466
467 ethanol metabolism in, 464
466 synaptic plasticity in, 100
106 Histone deacetylase activity (HDAC activity), 467 HMGB1. See High-mobility group box 1 (HMGB1) 4-HNE. See 4-Hydroxynonenal (4-HNE) Hormesis, 464 Hormonal fluctuations, 22 HPA axis. See Hypothalamic
pituitary
adrenal axis (HPA axis) HPLC. See High-performance liquid chromatography (HPLC) HPLC/MS/MS. See High-pressure liquid chromatography combined with tandem mass spectroscopic detection (HPLC/MS/MS) HR. See High-risk (HR) HSP. See Heat-shock proteins (HSP) HSS. See Hangover symptoms scale (HSS) HTOL. See 5-Hydroxytryptophol (HTOL) 5-HTTLPR genotype, 14 Human alcohol consumption in, 579
580 alcoholics, 422
423 behavior, 187 brain networks, 120 EEG, 119 Hyalinization, 144 Hydrogen peroxide (H2O2), 227, 505
506 6-Hydroxydopamine (6-OHDA), 230
232 5-Hydroxyindoleacetic acid (5-HIAA), 278, 673
675 Hydroxyl radical (HO•), 42
43, 493
494, 505
506 4-Hydroxynonenal (4-HNE), 42
43, 507, 519 5-Hydroxytryptophan (5-HT), 278 5-HT1A receptors, 50 5-HT2A receptors, 94
95 5-HT3 receptors, 494 5-Hydroxytryptophol (HTOL), 673
675 Hyperalgesia, 158, 223 Hyperexcitability, 133 Hyperpolarization, 135 Hyperpolarization-activated cyclic nucleotide-gated ion channels (HCN ion channels), 172
173, 172f and cardiac function, 175
176 as drug target, 176 and ethanol actions, 173
175 ion channels, 176 Hypothalamic-pituitary-axis, 153
155 Hypothalamic
pituitary
adrenal axis (HPA axis), 252
253, 315
316, 365
366, 407, 473, 617 Hypothalamus, 249
250 and alcohol withdrawal, 252
253 Hypothetical Purchase Tasks, 298

I ICA. See Independent component analysis (ICA) ID. See Intellectual disability (ID) IFG. See Inferior frontal gyrus (IFG) IFN-γ. See Interferon gamma (IFN-γ) iGluRs. See Ionotropic glutamate receptors (iGluRs) IGT. See Integrated Group Therapy (IGT) IL. See Interleukin (IL) IL-1RA. See Interleukin 1 receptor antagonist (IL-1RA) IL-1β expression, 222
223 Il1r1 gene, 475 Immediate memory, 394 Immune cells, 180 Immune dysregulation, 509 Immunoreactivity for c-Fos in A2AKO mice, 550 Implicit learning, 394 Impulsive alcohol consumption, 250
251 Impulsive behavior, 532 Impulsiveness, 529, 532 Impulsivity, 336, 533 in BD, 335
339 framing future research, 339
341 multilevel conceptualization, 336
339 traits, 366
367 IMS. See Intermembrane space (IMS) In situ hybridization, 172
173 In vitro evidence, 662
663 In vivo evidence, 663 In vivo imaging techniques, 70
71 In vivo microdialysis studies, 171, 420
421 Inbred alcohol-preferring rats (iP rats), 663 Inbred nonpreferring rats (iNP rats), 663 Incentive salience, 419 INCs. See Intraneocortical connections (INCs) Independent component analysis (ICA), 243
244 Indirect ethanol biomarkers, 558
559, 563 AST and ALT, 559 CDT, 558
559 GGT, 559 MCV, 559 Inducible NOS (iNOS), 506
507 Infancy/infants, 325, 356 Inferior frontal cortices, 270 Inferior frontal gyrus (IFG), 188, 270 Inferior parietal lobule, 270 Inflammatory cytokines, 181 mediators, 508 neurotoxicity, 464 process, 144
145 Information-processing paradigms, 281 Ingested alcohol, 33 Inhibition, 187 of alcohol vapors, 60 inhibition/overriding habits, 394 Inhibitory control, 237
240 Innate/acquired resilience, 387 iNOS. See Inducible NOS (iNOS) iNP rats. See Inbred nonpreferring rats (iNP rats)

Inspiratory inflow index, 90
91 Insula, 270 Integrated Group Therapy (IGT), 368
369 Intellectual disability (ID), 52, 307, 313 implications for practice, 311
312, 312t neuropsychological underpinnings of AUD, 309
311 prevalence, 308
309 prevalence of alcohol (mis)use and AUD, 308
309 screening and assessment, 309 Intellectual functioning, 307 Intelligence quotient (IQ), 307, 308f Intensive inflammatory responses, 509 Interferon gamma (IFN-γ), 180 Interindividual variability, 341 Interleukin (IL), 180 Interleukin 1 receptor antagonist (IL-1RA), 180
181 Intermembrane space (IMS), 516 Internal GP (GPi), 167 Intertrial phase synchrony, 125
127 Intimate partner violence (IPV), 282 Intoxication, 671
673 Intracellular localization, 455 Intraneocortical connections (INCs), 73
76 Intraperitoneal injections, 60 Intravenous ethanol (IV ethanol), 221 Ion channels, 176 Ionic homeostasis, 134 Ionotropic glutamate receptors (iGluRs), 456, 466 ethanol effects, 457 function, 466 Ionotropic receptors, 623, 662 iP rats. See Inbred alcohol-preferring rats (iP rats) IPV. See Intimate partner violence (IPV) IQ. See Intelligence quotient (IQ) Ischemic brain injury, 508 IV ethanol. See Intravenous ethanol (IV ethanol) Ivermectin, 663, 667
668 preclinical ivermectin study, 663
664

K Kainate receptor (KAR), 456 Kainite receptor (KARs), 456 Kappa receptors, 221 KAR. See Kainate receptor (KAR) KARs. See Kainite receptor (KARs) “Kindling” phenomenon, 250
251 Knockout mice (KO mice), 662 Korsakoff’s syndrome, 202

L LAD1. See Low-alcohol drinking1 (LAD1) Lamotrigine, 368
369 Language deficits, 287 impairments, 287 lateralization, 287
292 FASD, 287
289 functional lateralization in FASD, 291
292

700 Language (Continued) structural lateralization in FASD, 289
291 processing, 123
124 Large neutral amino acid (LNAA), 634 Lateral habenula (LHb), 153, 155f, 157f, 158t alcohol modulates glutamatergic and GABAergic neurotransmissions, 156
157 circuits, 155
156 in alcohol use disorder, 159 hyperactivity and aversive effects of alcohol, 157
159 neurobiology of alcohol addiction, 153
155 Lateral habenula (LHb), 163
164 LC. See Locus coeruleus (LC) LD. See Light drinkers (LD); Linkage disequilibrium (LD) Lead (Pb), 516
518 and ethanol, 519
520, 520t ethanol, oxidative stress and, 520
521, 521f and drug consumption, 521
522 exposure stress, 518f Learning and memory neurocognitive domain, 394 Left hemisphere, 287, 289
291 Lentiviral vectors, 173 LETS ACT. See Life enhancement treatment for substance use (LETS ACT) LGICs. See Ligand-gated ion channels (LGICs) LHb. See Lateral habenula (LHb) Life enhancement treatment for substance use (LETS ACT), 303 Ligand-gated ion channels (LGICs), 661
663 Light drinkers (LD), 579
580 Linkage disequilibrium (LD), 32
33 Lipid bilayer, 134
135 Lipopolysaccharide (LPS), 180 Lipoxygenases, 516 Lithium, 369 Lithobates catesbeiana, 90 Liver functions, 195
196 Liver
brain axis, 149 LNAA. See Large neutral amino acid (LNAA) Loading-dose regimen, 677 LOAEL. See Lowest observed adverse effect level (LOAEL) Lobeline, 428
429, 430t Locus coeruleus (LC), 249
250 Long-term abstinent alcoholics (LTAA), 239
240 compensatory mechanisms of RSS in, 239
240 with current MDD, 241 Long-term abstinent alcoholics with comorbid stimulant dependence (LTAAS), 240 Long-term depression (LTD), 100, 456, 466 Long-term facilitation (LTF), 91
92 of breathing, 90
92 Long-term mood stability, 364

INDEX

Long-term potentiation (LTP), 100, 101f, 456, 466, 497 Long-term respiratory plasticity, 90
92 Longitudinal study of network RSS in STAA, 240
241 LORETA. See Low-resolution brain electromagnetic tomography (LORETA) Low-affinity α7 subtypes, 427
428 Low-alcohol drinking1 (LAD1), 663 Low-resolution brain electromagnetic tomography (LORETA), 123 Lowest observed adverse effect level (LOAEL), 516
517 LPS. See Lipopolysaccharide (LPS) LTAA. See Long-term abstinent alcoholics (LTAA) LTAAS. See Long-term abstinent alcoholics with comorbid stimulant dependence (LTAAS) LTD. See Long-term depression (LTD) LTF. See Long-term facilitation (LTF) LTP. See Long-term potentiation (LTP)

M MACE. See Mini Alcohol Craving Experience Questionnaire (MACE) Macrocytosis, 197, 199 Magnesium, 678 Magnetic resonance imaging (MRI), 70
71, 675, 677f, 681 Magnetoencephalogram (MEG), 110 Major depressive disorder (MDD), 241 LTAA with, 241 P3B amplitude in LTAA with vs. without, 242
243 RSS in LTAA with vs. without, 241
242 Malondialdehyde (MDA), 42
43, 507 MAO. See Monoamine oxidase-sensitive (MAO) MAO-A. See Monoamine oxidase-A (MAOA) MAST. See Michigan alcoholism screening test (MAST) Matching law, 297 Maternal inebriety, 287
288 Maternal separation stress in FASD children with FASD face additional postnatal challenges, 329
330 implications for treatments, 331 modeling maternal separation in rodents, 330
331 neurodevelopment, 325
326 revealing FASD etiology via animal model, 326
329 MBID. See Mild to borderline intellectual disability (MBID) McGill pain questionnaire, 220 MCP-1. See Monocyte chemoattractant protein 1 (MCP-1) MCV. See Mean corpuscular volume (MCV) MD. See Mean diffusivity (MD) MDA. See Malondialdehyde (MDA) MDD. See Major depressive disorder (MDD) Mean corpuscular volume (MCV), 559, 578

Mean diffusivity (MD), 71 Mecamylamine, 428
429, 430t Meconium biomarkers of PAE, 591
592 alcohol consumption in pregnancy and biological matrices, 587
588 alcohol use in women during pregnancy, 585
586, 586t alcohol-related analytes in meconium, 588 EtG and EtS, 590
591 fatty acid ethyl esters, 588
590 maternal factors related with PAE, 586t metabolism of alcohol, 586
587 Medial frontal cortices, 270 Medial prefrontal cortex (mPFC), 155
156, 221
222, 407, 458 Medium spiny neurons (MSNs), 164, 436 Medium tasters, 483 MEG. See Magnetoencephalogram (MEG) Membrane hyperpolarization phase, 172 Memory, 99 caffeine and alcohol effect, 551 impairments, 391 MEOS. See Microsomal ethanol oxidizing system (MEOS) Mesocorticolimbic dopamine system, 252 Mesocorticolimbic pathway (MP), 270
271 Mesocorticolimbic reward system, 458
459 Mesolimbic DA, 547 transmission, 42 dopamine pathway, 417
418, 418f reward system, 530 system, 467 activation, 171 Mesolimbic-cortical system (MLCS), 435 Metabolic pathway, 138
139 Metabolism of alcohol, 586
587 of ethanol in hippocampus, 464
466 Metabolites, 578 amine-aldehyde, 350 cocaine and cocaethylene, 539f direct alcohol, 560
562 5-HIAA, 278 Metabolomics, 582 in AUDs diagnosis, 578
581 1 H-NMR spectroscopy, 579 to investigate alcohol consumption in humans, 579
580 urinary and plasma metabolomic profiling to discriminate, 580
581 Metabotropic glutamate receptors (mGluRs), 100, 454 ethanol effects, 456 Group I, 455 Group II, 455 Group III, 455
456 Metabotropic receptors, 623 Metabotypes, 578
579 Metal-containing NPs, 510
511 Metallothionein, 516 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), 230
232 Methyllycaconitine, 428
429 4-Methylpyrazole, 227
228

INDEX

Methylxantines, 545 mGluRs. See Metabotropic glutamate receptors (mGluRs) MGT. See Monetary gambling task (MGT) MHD. See Moderate to heavy drinkers (MHD) Michigan alcoholism screening test (MAST), 578, 600 Microarrays, 474 Microcephaly, 69
70 Microdialysis, 171, 419, 419f Microencephaly, 70 Microglia activation, 145
146 MicroRNA-associated oxidative stress, 148
149 Microsomal ethanol oxidizing system (MEOS), 29
30, 145
146 Microvasculature, 39
40 MID. See Mild intellectual disability (MID) Migraines, 110 Mild alcohol dependence, 644 Mild intellectual disability (MID), 307 Mild to borderline intellectual disability (MBID), 307, 311 Mindfulness-based cognitive therapy, 385 Mini Alcohol Craving Experience Questionnaire (MACE), 607 Mismatch negativity (MMN), 123 Mitochondrial ALDH2, 33, 40 enzymes, 520
521 ROS production and removal, 517f MLCS. See Mesolimbic-cortical system (MLCS) MMN. See Mismatch negativity (MMN) Moderate to heavy drinkers (MHD), 579
580 Moderate/heavy active drinkers, 238 Molecular genetics alcohol issues, 13
14 birth cohorts, 15
17 candidate gene studies, 18 genotype x birth cohort interaction, 14 with candidate genes, 14
15 mechanisms in genotype x birth cohort interactions, 17
18 oxytocin, 19 Molecular weight (MW), 557 Monetary gambling task (MGT), 260
261 Monoamine oxidase-A (MAO-A), 279
281, 283 MAOA-H or MAOA-L, 279
281 Monoamine oxidase-sensitive (MAO), 230
232 Monocyte chemoattractant protein 1 (MCP1), 147, 180 Monosodium glutamate, 438 Mood disorders, 385 stabilizers, 369 stabilizing agents, 368 MOR. See Mu opioid receptors (MOR) Motivational alcohol intervention, 302
303 Motivational effects of alcohol, 355
356 change across life span, 356
359 Motivational properties, acetaldehyde and, 345
346

Motor impairment, 58 Motor inhibition, 187 Mouse model, 474 Moxidectin, 664
665, 665f, 666f, 667
668, 667f preclinical moxidectin study, 664
666 MP. See Mesocorticolimbic pathway (MP) mPFC. See Medial prefrontal cortex (mPFC) MPTP. See 1-Methyl-4-phenyl-1,2,3,6tetrahydropyridine (MPTP) MRI. See Magnetic resonance imaging (MRI) mRNA expression, 445 MS. See Multiple sclerosis (MS) MSA. See Multiple scheduled access (MSA) MSNs. See Medium spiny neurons (MSNs) MSX-3, 549 Mu opioid receptors (MOR), 435
436 antagonists, 167 internalization, 438
439 Mu receptors, 221 Multiple logistic regression analysis, 387 Multiple scheduled access (MSA), 61 Multiple sclerosis (MS), 508. See also Baclofen Multiple-drug usage, 538, 543 Multisensory substance-related imagery, 604
605 Mutual genetic vulnerability, 529 MW. See Molecular weight (MW) Myelin, 145, 150 Myelination, 49 Myelopathy, 195
197 in alcoholics, 203 clinical features, 196 diagnosis, 197 pathogenesis, 195
196 treatment and prognosis, 197 Mytochondrial dysfunction, 509

N N-Methyl-D-aspartate (NMDA), 250
251, 494, 637
638 glutamate receptors, 42, 132 N-Methyl-D-aspartate receptors (NMDAR), 364, 456, 466, 662, 675
677 antagonists, 457 subunits, 131
132 N-Methyl-SALS (NM-SALS), 230
232 N-Methyl-transferase (N-MT), 230
232 NAc. See Nucleus accumbens (NAc) nAChRs. See Nicotinic acetylcholine receptors (nAChRs) NAcSh. See Nucleus accumbens shell region (NAcSh) NAD. See Nicotinamide adenine dinucleotide (NAD) NADP. See Nicotinamide adenine dinucleotide phosphate (NADP) NADPH. See Nicotine adenine dinucleotide phosphate (NADPH) NADPH oxidase (NOX), 145
146, 516 Nalmefene, 368
369, 644, 648, 667
668 efficacy and safety clinical trials design, 646 clinical trials results, 646
647 nalmefene-licensed population, 644
646 for reduction of alcohol consumption, 644 UNmet medical needs supporting by, 649

701 Naloxone, 221, 444
445 Naltrexone, 167, 227
228, 444, 447
448, 533 Naltrexone (NTX), 653
654, 655f, 656f, 658f administration, 412 effect on reducing alcohol consumption, 439 Naltrexone 1 bupropion, 658 Naltrexone 1 fluoxetine, 657
658, 657f Naltrexone 1 prazosin, 655 Naltrexone 1 varenicline, 655
657, 656f, 657f Naming, 394 Nanoparticles (NPs), 510
511 effects against oxidative stress, 510f NARP. See Neural activity dependent pentraxin (NARP) National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), 614 National Health Interview Survey (NHIS), 217 National Institute for Health and Care Excellence (NICE), 643 Assessment Group, 648 National Institute on Alcoholism and Alcohol Abuse (NIAAA), 57, 192 National Institute on Drug Abuse, 607 National Institutes of Health (NIH), 580 National Organisation for Fetal Alcohol Spectrum Disorders Australia, 293 Natural antioxidants, 516 ncRNA. See Noncoding RNA (ncRNA) NDPAE. See Neurodevelopmental disorders associated with PAE (NDPAE) NDRI. See Norepinephrine-dopamine reuptake inhibitor (NDRI) NE. See Negative expectancy for alcohol (NE) Negative affect, 249
251, 614 Negative emotions, 615, 618
619. See also Emotional facial expressions (EFE) neuroscientific opponent process model, 615
618 psychiatric comorbidity model, 614
615 psychological TRH model, 613
614 Negative expectancy for alcohol (NE), 386
387 Negative reinforcement, 250
251, 253 Neocortex, 71 PrEE impacts thickness of, 73 PrEE-induced alterations in, 73 Neocortical circuitry development and PrEE, 73
76 Neonate, 586
587 Neramexane, 429 Nerve biopsy, 199
201 Nerve conduction studies, 199 Nervous system (NS), 132, 681 NESARC. See National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Network imbalance in alcohol use disorders, 237
238, 238f Neural activity dependent pentraxin (NARP), 457 Neural correlates of EFE identification, 270 Neural reinforcement, 443

702 Neural reward processing electrophysiological findings, 260
262 issues and future directions, 264
265 neuroimaging findings, 262
264 functional connectivity findings on reward system, 264 reward related functional MRI findings, 263
264 structural findings on reward system, 262
263 reward circuitry, 259
260, 260f Neural system actions, cocaethylene and, 540
542, 541f Neuregulin-1 genotype, 14
15 Neuregulins, 14
15 Neuro-adaptations, 616 Neuroactive steroids, 405
406, 413 alcohol affecting neuroactive steroid concentrations, 407
410 alcohol-induced changes in neuroactive steroids in cynomolgus monkeys, 409t in humans, 409t in mice, 408t in rats, 407t biosynthetic pathway, 406f individual variation in, 411
412 influencing drinking behavior in rodents, 411 mediating specific behavioral effects of ethanol, 410
411 Neuroanatomical development, PrEE and, 73 Neurobehavioral toxicology and teratology, 523 Neurobiological opponent-process model, 617 Neurobiology of alcohol addiction, 153
155 Neurochemical systems, 18 Neurochemistry, 278
281 Neurocognition, 392
393. See also Cognitive/cognition BD as harmful alcohol-consumption pattern, 335
336 cognitive impairments in BD, 341
342 framing future research on impulsivity in BD, 339
341 functions, 119 multilevel conceptualization of impulsivity in BD, 336
339 performance during hangover, 394
400 Neurodegeneration, 179, 505, 507
508 Neurodegenerative process, 136 Neurodevelopment(al), 325
326 alcohol exposure in C57BL/6 mice, 327t, 328t, 329f alterations induced by alcohol, 49
50 disorders, 509 events, 47
49 brain areas affected by exposure to alcohol, 48f Neurodevelopmental disorders associated with PAE (NDPAE), 586 Neuroelectrophysiology, 281 Neuroendocrine systems, 250
251 Neurofeedback approaches, 244
245

INDEX

Neurogenesis, 100, 131
132 Neuroimaging, 681 Neuroimmune aspects of alcoholism alcohol drinking activates neuroimmune system, 180
181 alcohol-induced CNS neuroimmune activity, 182
183 chronic heavy drinking and neuroimmune function, 181 consequence of modest drinking, 180
181 involvement in alcohol addiction, withdrawal, and abstinence, 181
182 neuroimmune response to acute intoxication, 181 neuroimmune signaling, 184 Neuroinflammation, 508 Neuroinflammatory responses, 474 Neurokinin 1 receptor (NK1 receptor), 617
618 Neurological disorders, 195 Neuromodulator adenosine, 546
547 systems, 444 Neuronal cells, 115 Neuronal hyperexcitability, 133
134 Neuropathy, 196
202 in alcoholics, 203 clinical features, 198 diagnosis, 198
202 pathogenesis, 197
198 treatment and prognosis, 202 Neuropeptide Y (NPY), 163
164, 252, 348, 467 Neuropeptides, 315 modulation, 163
164 stress signaling, 252 Neurophysiological correlates of AUD-BD, 364
366, 365f Neuroplasticity, 52 Neuropsychiatric disorders, 133
134, 687 Neuropsychological/neuropsychology, 335
336 models of AUD, 373 underpinnings of AUD, 309
311 deficiencies in information processing in problematic drinkers, 311 dual process models of addiction, 310 Neurosciences, 339
341 of alcohol, 683t alcohol, 683t online resources and information, 685t regulatory bodies, professional societies, and organizations, 682t of alcohol and crack cocaine uses alcohol and crack cocaine mixture metabolism, 538
540 cocaethylene and neural system actions, 540
542 consumption, 538 neuroscientific opponent process model, 615
618 Neurotensin immunoreactivity, 163
164 Neurotoxicity baclofen-related neurotoxicity in overdose, 636
638 of salsolinol by-products, 233

Neurotransmitters, 40
41, 144
145, 227, 444, 474, 494 Neurulation, 48 NFκB. See Nuclear factor κB (NFκB) NHIS. See National Health Interview Survey (NHIS) NIAAA. See National Institute on Alcoholism and Alcohol Abuse (NIAAA) NICE. See National Institute for Health and Care Excellence (NICE) Nicotinamide adenine dinucleotide (NAD), 29
30, 39 Nicotinamide adenine dinucleotide phosphate (NADP), 506
507 Nicotine, 171, 546 Nicotine adenine dinucleotide phosphate (NADPH), 144
145 Nicotinic acetylcholine mechanisms in alcohol dependence, 429 Nicotinic acetylcholine receptors (nAChRs), 427, 429, 655 Nigrostriatal dopamine pathway, 417
418, 418f NIH. See National Institutes of Health (NIH) Nitrendipine, 222 Nitric oxide (NO•), 493
494, 505
506 Nitric oxide synthase (NOS), 506
507 NK1 receptor. See Neurokinin 1 receptor (NK1 receptor) NLRs. See NOD like receptors (NLRs) NM-SALS. See N-Methyl-SALS (NM-SALS) NMDA. See N-Methyl-D-aspartate (NMDA) NMDAR. See N-Methyl-D-aspartate receptors (NMDAR) NMR. See Nuclear magnetic resonance (NMR) No observed adverse effect level (NOAEL), 516
517 Nociceptor, 219
220 NOD like receptors (NLRs), 147 Noncarotenoid vitamin α-tocopherol, 109
110 Noncoding RNA (ncRNA), 327
328 Nonenzymatic AOs, 505
506 Nonoxidative metabolization scheme of ethanol, 557 Nonoxidative pathways, 30
31 Nonsteroidal antiinflammatory drugs (NSAIDs), 218 Nonsubstance abusing controls (NSAC), 239
240 Nonsynaptic effects of alcohol abuse on epilepsy, 140 Nonsynaptic mechanisms of epileptiform activity, 134
139 acute alcohol abuse, 134
136 BD, 138
139 chronic alcohol abuse, 136
138 Nontaster phenotype, 483
484 Noradrenergic system, 655 Norepinephrine-dopamine reuptake inhibitor (NDRI), 658 NOS. See Nitric oxide synthase (NOS) NOX. See NADPH oxidase (NOX) NPs. See Nanoparticles (NPs)

INDEX

NPY. See Neuropeptide Y (NPY) NRG1 gene, 14
15 NS. See Nervous system (NS) NSAC. See Nonsubstance abusing controls (NSAC) NSAIDs. See Nonsteroidal antiinflammatory drugs (NSAIDs) NTS. See Nucleus of solitary tract (NTS) Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) Nuclear factor κB (NFκB), 145
146, 180, 507 Nuclear magnetic resonance (NMR), 579 Nucleophilic molecules, 227 Nucleus accumbens (NAc), 171, 239
240, 259
260, 345, 407, 417, 435
436, 484, 662 shell, 316 Nucleus accumbens shell region (NAcSh), 249
250 Nucleus of solitary tract (NTS), 318, 637
638

O Obsessive Compulsive Drinking Scale (OCDS), 606 OCDS. See Obsessive Compulsive Drinking Scale (OCDS) OFC. See Orbitofrontal cortex (OFC) 6-OHDA. See 6-Hydroxydopamine (6OHDA) Olanzapine, 369 Oligodendrocyte-derived myelin-related proteins, 145 Oligodendrocytes, 144
145 Operant BD, 61
62 Operant conditioning, 346
347 Operant negative reinforcement, 613 Opiate ligands, 541 Opiates, 444 Opioid(s), 546 antagonist naltrexone, 368
369 antagonists, 439
440 effects on dopaminergic transmission, 444 peptides, 444 receptor activation, 440 antagonists, 221 system, 435 effects of acute and chronic alcohol intake on, 437 endogenous opioids and receptors in brain reward processes, 435
436 OPLS-DA. See Partial least squarediscriminate analysis (OPLS-DA) Opponent-process model, 617
618 Opponent-process theory application to drug addiction, 154f OPTN gene, 208 Optogenetic approach, 422 Orbitofrontal cortex (OFC), 270
271, 279, 417 ORN/FRN/N2. See Outcome/Feedback Related Negativity (ORN/FRN/N2) ORP/FRP/P3. See Outcome/Feedback Related Positivity (ORP/FRP/P3) OS. See Oxidative stress (OS) Outcome-related paradigm, 260
261

Outcome/Feedback Related Negativity (ORN/FRN/N2), 260
261 Outcome/Feedback Related Positivity (ORP/ FRP/P3), 260
261 Overdose alterations in baclofen pharmacokinetics in, 638 baclofen-related neurotoxicity in, 636
638 Oxidative damage, 144
145, 146f Oxidative pathway, 29
31 of alcohol metabolism, 30f Oxidative pathways of alcohol metabolism, 82f Oxidative stress (OS), 52, 505
506, 511, 516
518 brain disorders associated with, 508
509 ethanol exposure effects during development, 495
497, 496f lead, ethanol, and, 520
521, 521f drug consumption and, 521
522 therapeutic approaches in OS-related brain disorders, 509
511 Oxidized nicotinamide adenine dinucleotide: nicotinamide adenine dinucleotide ratio (NAD 1 :NADH ratio), 516 OXTR. See Oxytocin receptor gene (OXTR) Oxygen, 89
90 radicals, 81 Oxytocin, 15, 19 Oxytocin receptor gene (OXTR), 15

P P-glycoprotein (P-gp), 664
665 p2rx4 gene, 663 P2X4Rs. See Purinergic P2X4 receptors (P2X4Rs) P3 component, 281 P3B amplitude in LTAA with vs. without current MDD, 242
243 P450scc, 411 Pacemaker activity, 172 PAE. See Prenatal alcohol exposure (PAE) PAG. See Periaqueductal gray (PAG) Pain, 217
219, 218f, 224
225, 224f alcohol and, 221 ascending pain signaling and descending pain inhibition, 219f assessment in humans, 220f clinical evaluation, 220
221 dimensions and influencing factors, 218f effects of chronic ethanol on, 222
223 signaling, 219
220 treatment options, 223
224 PAL. See Pleasant activities list (PAL) PAMPs. See Pathogen associated molecular patterns (PAMPs) PAPS. See 3ʹ-Phosphoadenosine-5ʹphosphosulfate (PAPS) Paraventricular nucleus (PVN), 315
316 Paraventricular thalamus (PVT), 164 Parkinson’s disease (PD), 508 Parkinsonism, 230
232 Partial FAS (pFAS), 69
70 Partial least square-discriminate analysis (OPLS-DA), 580

703 Partial sciatic nerve ligation (PSNL), 222
223 Parvalbumin (PV), 163
164 Patch clamp, 541 Pathogen associated molecular patterns (PAMPs), 147 Pathologic gambling, 529 PCA. See Principal component analysis (PCA) PCL-R. See Psychopathy Checklist-Revised (PCL-R) PD. See Parkinson’s disease (PD) PDH. See Pyruvate dehydrogenase (PDH) PE. See Positive expectancy for alcohol (PE) Peers, 545
546 Pellagra, 197
198 Perception, 220 Perceptual potentials (p1), 122
123 Perceptual-motor function domain, 394 impairments, 391 tasks, 394 Periadolescence, 356 Periaqueductal gray (PAG), 217
218, 249
250, 253 Perinatal learning with alcohol and acetaldehyde, 85
86 Perinatal Pb exposure, 517
518 Peripheral ACH, 42 Perisynaptic glutamate, 457
458 Perivascular gliosis, 144 Peroxiredoxins (Prxs), 516 Peroxynitrite (ONOO
), 505
506 Personality disorders, 277 traits of alcoholism and gambling disorder, 532 PES. See Pleasant events schedule (PES) PET. See Positron emission tomography (PET); Prenatal ethanol treatment (PET) PEth. See Phosphatidylethanol (PEth) PF-4575180, 428
429, 430t pFAS. See Partial FAS (pFAS) PFC. See Prefrontal cortex (PFC) Pharmacokinetic(s), 569, 571 alterations in baclofen pharmacokinetics in overdose, 638 baclofen, 634 model, 561
562 parameters, 634 Pharmacology of respiratory network, 94
95 Pharmacotherapy, 643 Phase synchrony methods, 125
127 Phase-locking, 125
127 Phasic dopamine signals, 423 Phenotype, 53 acetaldehyde induces addictive, 346
347 analyses, 476 ethanol-related, 476 FASD, 70t nontaster, 483
484 taster, 483
484 Phenylthiocarbamide (PTC), 483 Phosphatidyl ethanol, 30 Phosphatidylcholine, 561
562, 568
569

704 Phosphatidylethanol (PEth), 557, 561
562, 567 as alcohol marker, 568
569 as direct biomarker of alcohol consumption, 574 discovery, 567
568 homologs to indicating recentness of alcohol consumption, 571
573 studies on synthesis and elimination, 569
571 3ʹ-Phosphoadenosine-5ʹ-phosphosulfate (PAPS), 560 Pilocarpine induction model, 131 PKC. See Protein kinase C (PKC) PKCε. See Protein kinase C epsilon (PKCε) Planning, 394 Plant-based medicines, 219 Plasma metabolomic profiling to discriminate, 580
581 Plasma pharmacokinetic parameters, 634t Plasticity, functional, 100 Plasticity genes, 18 PLD isoforms, 567
568 PLD1 and PLD2, 567
568 Pleasant activities list (PAL), 298
299 Pleasant events schedule (PES), 298
299 Plethysmography, 92
94 PMRT. See Progressive Muscle Relaxation Training (PMRT) PND7. See Postnatal day 7 (PND7) PNDs. See Postnatal days (PNDs) Polygenic disorder, 31 Polygenic risk scores (PRSs), 364 Polymodal nociceptor, 484 Polymorphisms, functional, 31 POMC. See Proopiomelanocortin (POMC) Positive expectancy for alcohol (PE), 386
387 Positive reinforcement, 250
251 of ACD, 521
522 Positron emission tomography (PET), 264
265, 279, 422
423 Posterior parietal cortex, 531 Posterior VTA (pVTA), 173, 227
228 Postmortem autoradiography, 278 studies, 281 Postnatal day 7 (PND7), 101
103 Postnatal days (PNDs), 495 Postnatal environment, 325
326 Postsynaptic 5-HT 1A receptors, 53 Postsynaptic density (PSD), 455 Posttranslational processing, 465
466 Posttraumatic stress disorder (PTSD), 474, 614 Power spectral analysis, 119
120 Praxis subdomain, 394 Prazosin (P), 654
655, 655f, 656f Pre supplementary motor area (preSMA), 188 Pre-Bo¨tzinger complex, 92
94 Preconditioning phenomenon, 464 Precursor or consequence of alcohol use, 191
192

INDEX

PrEE. See Prenatal ethanol exposure (PrEE) Prefrontal cortex (PFC), 71, 171, 365, 435
436 Prefrontal regions, 270
271 Prefrontal-insular functional connectivity, 270 Pregnancy, 99, 586
587 alcohol consumption, 89, 587
588 alcohol use in women during, 585
586 Pregnenolone, 410 Premorbid childhood disorder, 529 Prenatal alcohol exposure (PAE), 49, 287
288, 325, 529, 586 acetaldehyde in fetal brain, 83 in fetal environment, 82
83 role in alcohol effects on fetal brain development, 83
84 age-related consequences of, 51
52 alcohol, 81
82 behavioral outcomes and mechanisms with, 50
51 connecting behavioral effects of alcohol and acetaldehyde in fetus, 83
84 FASD phenotypes, 70t maternal factors related with, 586t perinatal learning with alcohol and acetaldehyde, 85
86 reinforcing effects of alcohol and acetaldehyde in fetus, 84
85 studies in humans with fetal alcohol spectrum disorder, 70
77 Prenatal alcohol use, 591
592 Prenatal ethanol, 493
494 effects on enkephalinergic transmission, 445
447 ethanol administration on methionineenkephalin concentration, 447f on methionine-enkephalin concentration, 446f, 447f Prenatal ethanol exposure (PrEE), 50
51, 69 and breathing function, 95 impacts thickness of neocortex, 73 neuroanatomical development alterations in neocortex, 73 alterations in subcortical structures, 73 potential mechanisms of PrEE
induced neocortical changes, 76
77 teratogenic effects, 76f Prenatal ethanol treatment (PET), 446 Preoccupation/anticipation, 250
251 preSMA. See Pre supplementary motor area (preSMA) Preweanlings, 356 Primary Care, 598 Principal component analysis (PCA), 580, 582 Pro-drug/pro-toxic agent, 232 Pro-inflammatory signaling pathways dysregulation, 508 Processing speed, 393
394 Progressive Muscle Relaxation Training (PMRT), 615 Proinflammatory effect, 147
148 Proinflammatory factors, 148

Proopiomelanocortin (POMC), 315
316 PROP. See 6-n-Propylthiouracil (PROP) 6-n-Propylthiouracil (PROP), 483 Protein kinase C (PKC), 223 Protein kinase C epsilon (PKCε), 467 Protracted withdrawal, 252 PRSs. See Polygenic risk scores (PRSs) Prxs. See Peroxiredoxins (Prxs) PSD. See Postsynaptic density (PSD) PSNL. See Partial sciatic nerve ligation (PSNL) Psychiatric comorbidity model, 614
615 association network, 616f estimating means for drinking days, 617f network structure, 616f Psychiatric disorders, 533, 629
630 Psychological relapse risk in AUD, 385 coping skills, 385 craving, 385 self-efficacy, 385 spirituality, 385 Psychological TRH model, 613
614 Psychometric integrity, 605
606 Psychopathology, 532
533 correlates of AUD-BD, 366
367 Psychopathy, 278 neurobiological mechanisms, 278
282 Psychopathy Checklist-Revised (PCL-R), 279, 281 Psychosis, 629
630 Psychostimulant drugs, 546 PTC. See Phenylthiocarbamide (PTC) PTSD. See Posttraumatic stress disorder (PTSD) Pulque, 488
489 Purinergic P2X4 receptors (P2X4Rs), 661
662 P2X4R drug-screening platform, 664f relationship with ethanol and, 662
663 PV. See Parvalbumin (PV) PVN. See Paraventricular nucleus (PVN) PVT. See Paraventricular thalamus (PVT) pVTA. See Posterior VTA (pVTA) Pyruvate dehydrogenase (PDH), 144
145

Q Qualitative interviews, 3 Quantitative polymerase chain reaction methods, 73
74 Quetiapine, 367
369

R (R)-salsolinol synthase (R-SALS), 230 Racemate, 229 Radial diffusivity (RD), 262
263 Randomized controlled trials (RCT), 626, 627t, 644
646 Raphe nuclei, 278 Rat Park studies, 297 Rats, two-bottle choice DID for, 61 RBCs. See Red blood cells (RBCs) RCT. See Randomized controlled trials (RCT) RD. See Radial diffusivity (RD) RDS. See Reward deficiency syndrome (RDS)

INDEX

RE. See Reinforcing efficacy (RE) Reaction times (RTs), 188 Reactive nitrogen species (RNS), 463
464, 505
506 Reactive oxygen species (ROS), 42, 52, 109, 144
145, 146f, 149, 230
232, 463
465, 493
494, 505
506, 511, 516 ethanol exposure effects during development, 495
497 generation, 145
147, 466 Receptive language, 394 Recognition of emotions, 394 memory, 394 Recovery process, 383
384 from AUD, 384
385 resilience for, 386
387 Rectal disturbances, 196 Red blood cells (RBCs), 567
568 Red wine, 212 Regression analysis, 240 Rehabilitation, 386 Reinforcing efficacy (RE), 297 Reinstatement, 166 Relapse, 166
167, 427 risks in AUD patients, 384, 388 implications for treatments, 387
388 recovery from AUD, 384
385 resilience for recovery, 386
387 risk of psychological relapse, 385 sociological relapse risks, 385
386 Relapse Prevention Therapy (RPT), 614 Relief craving, 250
251 Resilience acquired, 388 for recovery, 387
388 innate/acquired resilience, 387 recovery support to increase resilience, 386 with self-disclosure and relapse risks in AUD patients, 386
387 Respiratory/respiration. See also Breathing chemosensitivity, 91 cycle, 93f depression, 637
638, 677 network pharmacology after ethanol exposure, 94
95 neuronal network, 90
91 neurophysiology, 92
94 rhythmic neurons, 89
90 short-and long-term respiratory plasticity, 90
92 ethanol effects on respiratory rhythmic activity, 93f respiratory cycle, 93f Response inhibition (RI), 187 disrupted neural signature of, 191
192 Resting state functional connectivity (rsFC), 264 Resting state synchrony (RSS), 239
240 compensatory mechanisms, 239
240 degree of, 240 differences in, 240 implications for treatment, 244
245 longitudinal study of network RSS in STAA, 240
241

in LTAA with vs. without current MDD, 241
242 in STAA, 240 Resting-state fMRI (rs-fMRI), 238 Resumption of drinking, 384 Reward circuitry, 259
260, 260f, 443 deprivation, 304 deprivation/substance-free reinforcement, 297
298 example of alcohol purchase task, 298t prediction error, 418
419 seeking, 259 system, 458 Reward deficiency syndrome (RDS), 486
487 Reward probability index (RPI), 299 Rhythmogenesis, 92
94 RI. See Response inhibition (RI) Richmond Agitation and Sedation Score, 675 Risk avoidance, 259 RMTg nucleus. See Rostromedial mesopontine tegmental nucleus (RMTg nucleus) RNS. See Reactive nitrogen species (RNS) Rodents, 58, 548 forced drinking, 60
61 metabolize alcohol, 58 modeling maternal separation in, 330
331 neuroactive steroids influencing drinking behavior in, 411 studies, 279 ROS. See Reactive oxygen species (ROS) Rostromedial mesopontine tegmental nucleus (RMTg nucleus), 155
156 RPI. See Reward probability index (RPI) RPT. See Relapse Prevention Therapy (RPT) rs-fMRI. See Resting-state fMRI (rs-fMRI) RS-FMRI synchrony, 243
244 rs1229984 gene, 32 rsFC. See Resting state functional connectivity (rsFC) RSS. See Resting state synchrony (RSS) RTs. See Reaction times (RTs) RTU. See Temporary recommendation for use (RTU)

S SAG. See Scientific Advisory Group (SAG) Salient emotional stimuli, 270 Salsolinol (SALS), 84, 228
229, 229f, 232f, 349 SAMHSA. See Substance Abuse and Mental Health Services Administration (SAMHSA) Sazetidine-A, 428
429, 430t Scarce sensory deficits, 196 Schizophrenia, 508 Scientific Advisory Group (SAG), 646 SDU. See Standard Drinking Unit (SDU) Sedatives, 546 effects of ethanol, 221
222 Seizures, 133, 671
673 Selective attention (N1), 123, 393
394 Selective serotonin reuptake inhibitor, 657
658

705 Selenium (Se21), 516 Self-administration, 163, 346 intracranial, 346 Self-care process, 385 Self-efficacy, 385 Self-medication, 319 Self-reported strategies, 587
588 Semantic memory, 394 Sensation seeking, 339, 340f Sensitization, 530
531 Sensorimotor integration, 71, 76
77 Sensory, 122
123 nerve action potentials, 199 pathway (evoked) potentials, 120
122 processing, 271
272 Serotonin (5-HT), 227, 278, 364, 494 transporter, 14 Serotonin type 1A receptors, 50, 53 SES. See Socioeconomic status (SES) Sex differences in alcohol consumption, 320
321 in neurocognitive effects of alcohol, 24 Sex interact to regulate drinking to cope, 318
319 Sexual dimorphic effect, 104
105 SFAS. See Substance-Free Activity Session (SFAS) sgACC. See Subgenual anterior cingulate cortex (sgACC) Shell region of nucleus accumbens (AcbSh), 164 Short detection window, 557
558 Short hairpin RNA (shRNA), 663 Short-lasting anoxia, 91 Short-term abstinent alcoholics (STAA), 240 compensatory mechanisms of RSS in, 240 longitudinal study of network RSS in, 240
241 Short-term respiratory plasticity, 90
92 shRNA. See Short hairpin RNA (shRNA) Sialic acid, 673
675 Sickness behavior, 182 SIDS. See Sudden infant death syndrome (SIDS) Signal-processing methods, 120 SIMCA. See Soft Independent Modeling of Class Analogies (SIMCA) Single nucleotide polymorphisms (SNPs), 14, 252, 364, 483 Single-photon emission computed tomography (SPECT), 279 Sinoatrial node cells, 172 SLEA. See Sublenticular extended amygdala (SLEA) SM. See Stria medullaris (SM) Small fiber-predominant axonal loss, 199
201 Smile-sad faces, 220 SN. See Substantia nigra (SN) SNPs. See Single nucleotide polymorphisms (SNPs) Sociability, 548 Social anxiety, 546 behavior, 14, 548 CNS responsible for, 18

706 Social (Continued) genotype x birth cohort interactions with candidate genes, 14
15 cognition, 394. See also Cognitive/ cognition in AUD patients, 377
379, 379f typological review, 374
377, 375f context, 300
301, 302f drinkers, 580
581 drinking, 561
562 interaction and modulation by anxiety, 548
550 isolation, 271
272 knowledge, 374
377 memory, 548, 549f novelty test, 548 penetration theory, 386
387 perception, 374
375 preference test, 548, 549f recognition, 551 Social drinking, 187 Society of Hair Testing (SoHT), 560 Socio-emotional deficits in severe AUD social cognition in AUD patients, 377
379, 379f socioemotional factors in alcoholdependence, 373
374 typological review of social cognition in AUD patients, 374
377 Sociocultural factors, 488
489 Socioeconomic status (SES), 300 Sociological relapse risks in AUD, 385
386 Sociology, 10
11 SOD. See Superoxide dismutase (SOD) SOD1 gene, 208 Soft Independent Modeling of Class Analogies (SIMCA), 580 SoHT. See Society of Hair Testing (SoHT) Somato-dendritic or postsynaptic nAChRs, 427
428 Somatosensory evoked potentials, 197 Somatostatin, 163
164 Spastic paraparesis, 196 Spasticity, 196
197. See also Baclofen Spatial working memory (SWM), 71 SPECT. See Single-photon emission computed tomography (SPECT) Spine density changes, 252
253 Spirituality, 385 Splenium, 143 Sprague-Dawley rats, 90 STAA. See Short-term abstinent alcoholics (STAA) Standard Drinking Unit (SDU), 599 Status epilepticus, 138
139 Steatohepatitis, 149 Stereo-selectivity in effects of salsolinol, 233 Stereoisomer, 230 Stimulants, 308 Stimulus, 270
271 Stimulus-induced vulnerability (SV), 386
387 STN. See Subthalamic nucleus (STN) Stop-Signal, 336
337 Stress, 181
182, 385

INDEX

hippocampal gene changes following exposure to, 474
478 response, 249
250, 252
253 stress-related neuropeptides, 315, 316f Stria medullaris (SM), 157 Striatal anatomy and function, 417 Striatal DAT density, 279 Striatal dopamine, 419 Striatum, 167, 417 dopamine in, 417
419 Stroke, 109
110 Structural brain changes, 281
282 Structural brain imaging, 71 Structural lateralization in FASD, 289
291 Student’s t-test, 549
550 Subacute combined degeneration of spinal cord, 196
197 Subgenual anterior cingulate cortex (sgACC), 239
240 Sublenticular extended amygdala (SLEA), 259
260 Subliminal stimuli, 133
134 Substance Abuse and Mental Health Services Administration (SAMHSA), 192 Substance Use and Misuse in Intellectual Disability Questionnaire (SumID-Q), 309, 309t, 310f Substance use disorders (SUD), 241, 282, 363, 384 Substance-Free Activity Session (SFAS), 302
303, 303f Substance-free reinforcement, 298
299, 299t, 301t Substantia nigra (SN), 417
418 Substantia nigra pars medialis, 410 Subthalamic nucleus (STN), 164 Sucrose, 165
166 gap recording technique, 541 SUD. See Substance use disorders (SUD) Sudden infant death syndrome (SIDS), 89
90 Sulphatation of ethanol, 560 SumID-Q. See Substance Use and Misuse in Intellectual Disability Questionnaire (SumID-Q) Superoxide (O2
•), 42
43, 493
494, 505
506 Superoxide dismutase (SOD), 496
497, 505
506, 516 Supertasters, 483 Sural nerve, 199
201 Sustained attention, 393
394 SV. See Stimulus-induced vulnerability (SV) SWM. See Spatial working memory (SWM) Synaptic components of glutamatergic system, 459 Synaptic effects of alcohol abuse on epilepsy, 140 Synaptic mechanisms of epileptiform activity, 132
134 acute alcohol abuse, 132
133 AWS, 133
134 chronic alcohol abuse, 133 Synaptic plasticity, 530
531 in hippocampus, 100
106

and alcohol during early development, 100
105 and synaptic plasticity during adolescence, 105 Synaptic pruning process, 49 Synaptic Ras GTPase-activating protein (SynGAP), 456 Synaptic transmissions, 474 Synaptogenesis, 48
49 SynGAP. See Synaptic Ras GTPase-activating protein (SynGAP)

T TAC. See Transdermal alcohol concentration (TAC) Tail-flick test, 221 TARDBP gene, 208 TAS2R proteins, 483 TAS2R16 gene, 484 Task related functional connectivity, 264 Taste, 483
484 Taster phenotype, 483
484 Teenage BD, 58 Teenagers, 300 Tejuino, 488
489 Telescoping effect, 25 Temporal reference, 605 Temporary recommendation for use (RTU), 629
630 Tension Reduction Hypothesis (TRH), 613 Teratogenic effects, 629 Tertiary education and alcohol, 4
5 Tetrahydrodeoxycorticosterone (THDOC), 405
406, 410 Tetrahydroisoquinolines (TIQs), 42, 227 Tetrahydropapaverine, 42 Tf. See Transferrin (Tf) Thalamocortical connection, 74
76 Thalamus, 219
220 THDOC. See Tetrahydrodeoxycorticosterone (THDOC) Theophylline, 545 Theory of Mind (ToM), 374 Therapeutic approach, 532
533 in OS-related brain disorders, 509
511 substances with potential neuroprotective activity, 509t Theta band ERO activity, 124
125 Thiamine, 678 deficiency, 144
145, 145f, 197
198 depletion, 144
145 Thiol compounds, 348
349 Thioredoxin enzyme, 505
506 Three-chamber test, 549 Tigecycline, 223 TIQs. See Tetrahydroisoquinolines (TIQs) TLR. See Toll-like receptor (TLR) TLR4/IL-1R1 receptor 1, 507 TM segments. See Transmembrane segments (TM segments) TNF-α. See Tumor necrosis factor α (TNF-α) Tocopherol, 516 Toll-like receptor (TLR), 147, 181, 507 activation, 147

707

INDEX

ToM. See Theory of Mind (ToM) Tonic dopamine signals, 423 Top-down control, 252
253 Topiramate, 368 Toxic lipids, 149 Toxic neurorespiratory features, 638 Transdermal alcohol concentration (TAC), 569
570, 646 Transdiagnostic risk factor, 302
303 Transferrin (Tf), 558
559 Transient potential cation channel subfamily V member 1 gene (TRPV1 gene), 484 Transmembrane segments (TM segments), 662
663 Treatment targeting reward deprivation, 302
303 TRH. See Tension Reduction Hypothesis (TRH) TRPV1 gene. See Transient potential cation channel subfamily V member 1 gene (TRPV1 gene) Tubulin, 42
43 Tumor necrosis factor α (TNF-α), 146
147, 180 Two-bottle choice drink-in-the-dark model, 61 for rats, 61 intermittent access model, 61 Txnip expression, 467
468 Type 1 alcoholics, 278, 281
282 Type 2 alcoholics, 278, 281
282

U UDPGA. See Uridine 5ʹ-diphosphoβ-glucuronic acid (UDPGA) United Nations Office on Drug & Crime (UNODC), 538 United States, services report craving, 606
607 United States Food and Drug Administration (FDA), 439, 653
654 Univariate tests, 238 University as a space
time of becoming, 4 lifestyle, 3
4 time and place to consume alcohol, 5 university-based drinking, 7 UNmet, 649 Unmyelinated fibers, 199
201 UNODC. See United Nations Office on Drug & Crime (UNODC) Up-regulation, 437 Urgency lack of Premeditation, lack of Perseverance, and Sensation seeking model (UPPS model), 336, 336f Uridine 5ʹ-diphospho-β-glucuronic acid (UDPGA), 560 Urinary and plasma metabolomic profiling to discriminate, 580
581 Urine dilution, 560
561 Urine
blood alcohol concentration ratio, 557

V

W

VAMS. See Volumetric absorptive microsampling (VAMS) Vanilloid receptor 1, 484 Varenicline, 430t Varenicline (VAR), 654
655 VAS. See Visual-analog scales (VAS) VCP gene, 208 Ventral pallidum (VP), 163, 164f, 168, 436 and alcohol consumption, 165
166 anatomy, pharmacology, and physiology, 163
165 and relapse, 166
167 and targeted treatments for alcohol addiction, 167 Ventral pallidum dorsolateral (VPdl), 166 Ventral pallidum ventromedial (VPvm), 166 Ventral striatum (VS), 270
271, 279, 484, 530 Ventral tegmental area (VTA), 153, 163
164, 171, 227
228, 259
260, 317, 345, 410, 417
418, 427
428, 435
436, 458, 484, 662 Ventrolateral prefrontal cortex (VLPFC), 270 Verbal recall performance, 291
292 Very low-density cholesterol (VLDL-C), 487 Vesicular glutamate-associated transporters (VGLUTs), 457 VGluT2, 157 Vesicular monoamine transporters (VMATs), 14 VGLUTs. See Vesicular glutamate-associated transporters (VGLUTs) Vigilance task, 393
394 Visual alcohol cues, 238 Visual perception, 394 Visual-analog scales (VAS), 220 Visually-driven emotional response, 189
190 Visuoconstructional functioning, 394 Visuospatial abilities, 269 Vitamin E, 196 VLDL-C. See Very low-density cholesterol (VLDL-C) VLPFC. See Ventrolateral prefrontal cortex (VLPFC) VMATs. See Vesicular monoamine transporters (VMATs) Volumetric absorptive microsampling (VAMS), 560 Voluntary alcohol consumption, 61
62 alcohol intake in two-bottle choice intermittent access model, 61 operant BD, 61
62 two-bottle choice DID model, 61 for rats, 61 VP. See Ventral pallidum (VP) VPdl. See Ventral pallidum dorsolateral (VPdl) VPvm. See Ventral pallidum ventromedial (VPvm) VS. See Ventral striatum (VS) VTA. See Ventral tegmental area (VTA)

Warsaw Alcohol high-preferring rats, 356 Weighted psychometric property, 606 Wernicke’s encephalopathy, 202, 671
673, 678 Wet beriberi, 198 WHBP. See Working Heart-Brainstem Preparation (WHBP) White matter (WM), 262
263 WHO. See World Health Organization (WHO) Wild type (WT), 437, 663 Withdrawal Seizure-Prone (WSP), 410 Withdrawal Seizure-Resistant mice (WSR mice), 410 Withdrawal/negative affect, 250
251 WM. See White matter (WM) Women, alcohol and alcohol affect women differently from men, 23, 26 barriers to treatment, 25 cultural, environmental, and societal changes, 25
26 early diagnosis and treatment tailored to girls and, 25 explaining sex differences in neurocognitive effects, 24 implications for treatment, 26 improving prevention for girls and, 24
25 morbidity, comorbidity, and mortality related to alcohol use disorders, 22
23 pathways to alcohol use disorders with women, 21
22 alcohol’s differential effects on females vs. males, 23t research limitations, 24 Word finding, 394 Working Heart-Brainstem Preparation (WHBP), 90 Working memory, 394 World Health Organization (WHO), 427, 577, 633, 644 WSP. See Withdrawal Seizure-Prone (WSP) WSR mice. See Withdrawal Seizure-Resistant mice (WSR mice) WT. See Wild type (WT)

X Xanthine oxidase (XO), 506
507 xCT. See Cystine glutamate exchanger (xCT)

Y Youth, 99

Z Zatebradine, 176 ZD7288, 176 Zinc (Zn21), 516