Glaucoma: A Neurodegenerative Disease of the Retina and Beyond: Part A 0128211067, 9780128211069

Table of contents :
Contributors
Contents
Preface
1 Functional and morphological alterations in a glaucoma model of acute ocular hypertension • Alejandro Gallego-Ortega, María Norte-Muñoz, Juan Antonio Miralles de Imperial-Ollero, Jos
e Manuel Bernal-Garro, Francisco Javier Valiente-Soriano, Pedro de la Villa Polo, Marcelino Avil
es-Trigueros, María Paz Villegas-P
erez, and Manuel Vidal-Sanz
2 Genetics of primary open-angle glaucoma and its endophenotypes • Yoichi Sakurada, Fumihiko Mabuchi, and Kenji Kashiwagi
3 A broad perspective on the molecular regulation of retinal ganglion cell degeneration in glaucoma • Gülgün Tezel
4 The role of commensal microflora-induced T cell responses in glaucoma neurodegeneration • Jing Tang, Yizhen Tang, Irvin Yi, and Dong Feng Chen
5 The role of neuroinflammation in the pathogenesis of glaucoma neurodegeneration • Maria D. Pinazo-Durán, Francisco J. Muñoz-Negrete, Silvia M. Sanz-González, Javier Benítez-del-Castillo, Rafael Gim
enez-Gómez, Mar Valero-Velló, Vicente Zanón-Moreno, and Jos
e J. García-Medina
6 Microglial changes in the early aging stage in a healthy retina and an experimental glaucoma model • Ana I. Ramírez, Jos
e A. Fernández-Albarral, Rosa de Hoz, In
es López-Cuenca, Elena Salobrar-García, Pilar Rojas, Francisco Javier Valiente-Soriano, Marcelino Avil
es-Trigueros, María Paz Villegas-P
erez, Manuel Vidal-Sanz, Alberto Triviño, Juan J. Salazar, and Jos
e M. Ramírez
7 Molecular changes in glaucomatous trabecular meshwork. Correlations with retinal ganglion cell death and novel strategies for neuroprotection • Sergio C. Saccà, Stefania Vernazza, Eugenio Luigi Iorio, Sara Tirendi, Anna Maria Bassi, Stefano Gandolfi, and Alberto Izzotti
8 Effects of caloric restriction on retinal aging and neurodegeneration • Annagrazia Adornetto, Luigi Antonio Morrone, Andrea Satriano, Maria Luisa Laganà, Ester Licastro, Carlo Nucci, Maria Tiziana Corasaniti, Paolo Tonin, Giacinto Bagetta, and Rossella Russo
9 Is stagnant cerebrospinal fluid involved in the pathophysiology of normal tension glaucoma • Hanspeter Esriel Killer

Citation preview

Progress in Brain Research Volume 256

Glaucoma: A Neurodegenerative Disease of the Retina and Beyond - Part A

Serial Editor

Vincent Walsh Institute of Cognitive Neuroscience University College London 17 Queen Square London WC1N 3AR UK

Editorial Board Mark Bear, Cambridge, USA. Medicine & Translational Neuroscience Hamed Ekhtiari, Tehran, Iran. Addiction Hajime Hirase, Wako, Japan. Neuronal Microcircuitry Freda Miller, Toronto, Canada. Developmental Neurobiology Shane O’Mara, Dublin, Ireland. Systems Neuroscience Susan Rossell, Swinburne, Australia. Clinical Psychology & Neuropsychiatry Nathalie Rouach, Paris, France. Neuroglia Barbara Sahakian, Cambridge, UK. Cognition & Neuroethics Bettina Studer, Dusseldorf, Germany. Neurorehabilitation Xiao-Jing Wang, New York, USA. Computational Neuroscience

Progress in Brain Research Volume 256

Glaucoma: A Neurodegenerative Disease of the Retina and Beyond - Part A Edited by

Giacinto Bagetta Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy

Carlo Nucci Ophthalmology Unit, Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford, OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States First edition 2020 Copyright © 2020 Elsevier B.V. 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. ISBN: 978-0-12-821106-9 ISSN: 0079-6123 For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Zoe Kruze Acquisitions Editor: Sam Mahfoudh Editorial Project Manager: Chris Hockaday Production Project Manager: Abdulla Sait Cover Designer: Alan Studholme Typeset by SPi Global, India

Contributors Annagrazia Adornetto Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy Marcelino Avil
es-Trigueros Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Giacinto Bagetta Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy Anna Maria Bassi Department of Experimental Medicine (DIMES), University of Genoa, Genoa; Inter-University Center for the Promotion of the 3Rs Principles in Teaching & Research (Centro 3R), Pisa, Italy Javier Benı´tez-del-Castillo Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022, Madrid; Department of Ophthalmology at the Hospital of Jerez, Jerez de la Frontera, Ca´diz, Spain Jos
e Manuel Bernal-Garro Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Dong Feng Chen Schepens Eye Research Institute of Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, United States Maria Tiziana Corasaniti School of Hospital Pharmacy, University "Magna Graecia" of Catanzaro and Department of Health Sciences, University “Magna Graecia” of Catanzaro, Catanzaro, Italy Rosa de Hoz Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo; Facultad de O´ptica y Optometrı´a, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Madrid, Spain Juan Antonio Miralles de Imperial-Ollero Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Pedro de la Villa Polo Department of Systems Biology, University of Alcala´; Instituto Ramo´n y Cajal de Investigacio´n Sanitaria, Madrid, Spain

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Contributors

Jos
e A. Ferna´ndez-Albarral Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo, Universidad Complutense de Madrid, Madrid, Spain Alejandro Gallego-Ortega Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Stefano Gandolfi Ophthalmology Unit, Department of Biological, Biotechnological and Translational Sciences, University of Parma, Parma, Italy Jos
e J. Garcı´a-Medina Ophthalmic Research Unit “Santiago Grisolı´a”/FISABIO and Cellular and Molecular Ophthalmo-biology Group of the University of Valencia, Valencia; Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022, Madrid; Department of Ophthalmology at the University Hospital “Morales Meseguer” and Department of Ophthalmology at the Faculty of Medicine, University of Murcia, Murcia, Spain Rafael Gim
enez-Go´mez Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022, Madrid; Department of Ophthalmology at the University Hospital “Reina Sofia”, Co´rdoba, Spain Eugenio Luigi Iorio International Observatory of Oxidative Stress, Salerno, Italy Alberto Izzotti Department of Experimental Medicine (DIMES), University of Genoa; Mutagenesis Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy Kenji Kashiwagi Department of Ophthalmology, Faculty of Medicine, University of Yamanashi, Kofu, Japan Hanspeter Esriel Killer Department of Ophthalmology, Kantonsspital Aarau, Aarau; Center for Biomedicine University of Basel, Basel, Switzerland Maria Luisa Lagana` Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy Ester Licastro Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy In
es Lo´pez-Cuenca Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo, Universidad Complutense de Madrid, Madrid, Spain

Contributors

Fumihiko Mabuchi Department of Ophthalmology, Faculty of Medicine, University of Yamanashi, Kofu, Japan Luigi Antonio Morrone Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy Francisco J. Mun˜oz-Negrete Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022; Ophthalmology Department at the University Hospital “Ramo´n y Cajal” (IRYCIS) and Surgery Department at the Faculty of Medicine, University Alcala de Henares, Madrid, Spain Marı´a Norte-Mun˜oz Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Carlo Nucci Ophthalmology Unit, Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy Maria D. Pinazo-Dura´n Ophthalmic Research Unit “Santiago Grisolı´a”/FISABIO and Cellular and Molecular Ophthalmo-biology Group of the University of Valencia, Valencia; Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022, Madrid, Spain Ana I. Ramı´rez Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo; Facultad de O´ptica y Optometrı´a, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Madrid, Spain Jos
e M. Ramı´rez Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo, Universidad Complutense de Madrid, Madrid; Facultad de Medicina, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Spain Pilar Rojas Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo, Universidad Complutense de Madrid; Hospital General Universitario Gregorio Maran˜o´n, Instituto Ofta´lmico de Madrid, Madrid, Spain Rossella Russo Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy Sergio C. Sacca` Policlinico San Martino University Hospital, Department of Neuroscience and sense organs, Ophthalmology Unit, Genoa, Italy

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Contributors

Yoichi Sakurada Department of Ophthalmology, Faculty of Medicine, University of Yamanashi, Kofu, Japan Juan J. Salazar Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo; Facultad de O´ptica y Optometrı´a, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Madrid, Spain Elena Salobrar-Garcı´a Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo; Facultad de O´ptica y Optometrı´a, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Madrid, Spain Silvia M. Sanz-Gonza´lez Ophthalmic Research Unit “Santiago Grisolı´a”/FISABIO and Cellular and Molecular Ophthalmo-biology Group of the University of Valencia, Valencia; Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022, Madrid, Spain Andrea Satriano Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy Jing Tang Department of Ophthalmology, West China Hospital, Sichuan University, Sichuan, China; Schepens Eye Research Institute of Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, United States Yizhen Tang Department of Ophthalmology and Vision Science, Eye & ENT Hospital, Shanghai Medical College, Fudan University, Shanghai, China; Schepens Eye Research Institute of Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, United States G€ulg€ un Tezel Department of Ophthalmology, Vagelos College of Physicians and Surgeons, Columbia University, Edward S. Harkness Eye Institute, New York, NY, United States Sara Tirendi Department of Experimental Medicine (DIMES), University of Genoa, Genoa; Inter-University Center for the Promotion of the 3Rs Principles in Teaching & Research (Centro 3R), Pisa, Italy Paolo Tonin Regional Center for Serious Brain Injuries, S. Anna Institute, Crotone, Italy

Contributors

Alberto Trivin˜o Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo, Universidad Complutense de Madrid, Madrid; Facultad de Medicina, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Spain Mar Valero-Vello´ Ophthalmic Research Unit “Santiago Grisolı´a”/FISABIO and Cellular and Molecular Ophthalmo-biology Group of the University of Valencia, Valencia, Spain Francisco Javier Valiente-Soriano Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Stefania Vernazza IRCCS, Fondazione G.B. Bietti, Rome, Italy Manuel Vidal-Sanz Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Marı´a Paz Villegas-P
erez Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain Irvin Yi Schepens Eye Research Institute of Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, United States Vicente Zano´n-Moreno Ophthalmic Research Unit “Santiago Grisolı´a”/FISABIO and Cellular and Molecular Ophthalmo-biology Group of the University of Valencia, Valencia; Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022, Madrid; International University of Valencia, Valencia, Spain

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Contents Contributors .............................................................................................................. v Preface .................................................................................................................. xvii

CHAPTER 1 Functional and morphological alterations in a glaucoma model of acute ocular hypertension.............1

1. 2.

3.

4.

Alejandro Gallego-Ortega, Marı´a Norte-Mun˜oz, Juan Antonio Miralles de Imperial-Ollero, Jos
e Manuel Bernal-Garro, Francisco Javier Valiente-Soriano, Pedro de la Villa Polo, Marcelino Avil
es-Trigueros, Marı´a Paz Villegas-P
erez, and Manuel Vidal-Sanz Introduction ....................................................................................... 2 Methods ............................................................................................ 4 2.1 Animal handling ...................................................................... 4 2.2 Experimental design................................................................ 4 2.3 Acute ocular hypertension induction ....................................... 5 2.4 Spectral domain optical coherence tomography (SD-OCT)................................................................................ 5 2.5 Electroretinography (ERG) ...................................................... 5 2.6 Tissue processing..................................................................... 7 2.7 Immunohistofluorescence ........................................................ 7 2.8 Image acquisition ..................................................................... 7 2.9 Quantification and spatial distribution .................................... 8 2.10 Statistical analysis .................................................................... 8 Results ............................................................................................... 8 3.1 Early thinning of the inner retina and a delayed thinning of the external retina .................................................................. 8 3.2 Dramatic and permanent alterations of all retinal waves recorded ..................................................................................... 9 3.3 Death of CBCs but not RBCs ................................................... 9 3.4 Loss of RGCs and cones but not HZs ..................................... 13 Discussion ....................................................................................... 19 4.1 AOHT reduces the thickness of the inner retina and over time the outer retina ................................................................ 19 4.2 AOHT results in early permanent retinal disfunction ............. 20 4.3 AOHT causes the loss of ganglion cells and cones but not HZs ........................................................................................... 21

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4.4 AOHT results in the death of cone bipolar cells but not rod bipolar cells ....................................................................... 21 Financial support .................................................................................. 22 References ............................................................................................ 22

CHAPTER 2 Genetics of primary open-angle glaucoma and its endophenotypes............................................................31 Yoichi Sakurada, Fumihiko Mabuchi, and Kenji Kashiwagi 1. Introduction..................................................................................... 31 2. Genome-wide association studies on POAG endophenotypes ...... 32 3. Disc area and vertical cup-to-disc ratio (VCDR) .......................... 32 4. Intraocular pressure (IOP) .............................................................. 38 5. Summary ......................................................................................... 43 Reference .............................................................................................. 43

CHAPTER 3 A broad perspective on the molecular regulation of retinal ganglion cell degeneration in glaucoma.........49 G€ ulg€ un Tezel 1. Complexity of RGC degeneration in glaucoma............................. 49 2. Injury of RGC axons at the optic nerve head ................................ 53 3. Molecularly distinct compartmentalized processes for RGC degeneration .................................................................................... 55 4. Mitochondrial dysfunction, a key pathogenic event in RGC degeneration at different compartments......................................... 57 5. Glia-driven neuroinflammation, a widespread outcome promoting RGC degeneration ......................................................... 58 6. Molecular signaling for degeneration of RGC axons .................... 60 7. Molecular signaling for RGC soma death ..................................... 62 8. Loss of RGC synapses at dendrites and axon terminals ................ 67 9. Conclusions..................................................................................... 69 Acknowledgments ................................................................................ 69 References ............................................................................................ 70

CHAPTER 4 The role of commensal microflora-induced T cell responses in glaucoma neurodegeneration................79 Jing Tang, Yizhen Tang, Irvin Yi, and Dong Feng Chen 1. Introduction..................................................................................... 80 2. Microbiota in neuroinflammation .................................................. 80 2.1 Commensal microbiota and immune regulation ..................... 80 2.2 Microbiota and the autoimmune diseases in the CNS ............ 81 2.3 Microbiota and the blood-retina barrier .................................. 82

Contents

2.4 Microbiota and microglia development, maturation and function.................................................................................... 82 2.5 Microglia and neurodegeneration in glaucoma ....................... 84 3. Heat shock proteins in glaucomatous neurodegeneration.............. 85 3.1 HSPs and their upregulation in glaucomatous neurodegeneration.................................................................... 85 3.2 The role of HSPs in autoimmune conditions and neurodegenerative diseases, including glaucoma .................... 87 4. Interactions between T cells and microglia ................................... 88 4.1 CNS T cell infiltration and activated microglia...................... 88 4.2 CNS/retina: An immune privileged site .................................. 90 5. Conclusion ...................................................................................... 90 Acknowledgment ................................................................................. 90 References ............................................................................................ 91

CHAPTER 5 The role of neuroinflammation in the pathogenesis of glaucoma neurodegeneration..................................99 Maria D. Pinazo-Dura´n, Francisco J. Mun˜oz-Negrete, Silvia M. Sanz-Gonza´lez, Javier Benı´tez-del-Castillo, Rafael Gim
enez-Go´mez, Mar Valero-Vello´, Vicente Zano´n-Moreno, and Jos
e J. Garcı´a-Medina 1. Introduction ................................................................................... 100 2. The link between neuroinflammation and oxidative stress in glaucoma neurodegeneration........................................................ 100 2.1 Neuroinflammation................................................................ 100 2.2 Oxidative stress in glaucoma neurodegeneration.................. 103 3. Genetics and omics in glaucoma neuroinflammation .................. 104 3.1 Polymorphisms of cytokine genes in glaucoma neuroinflammation ................................................................. 104 3.2 Omics in glaucoma neuroinflammation ................................ 106 4. Update on uveitic glaucoma......................................................... 107 4.1 Uveitic glaucoma pathophysiology....................................... 107 4.2 Uveitic glaucoma treatment ................................................... 109 5. Imaging methods for ocular inflammation and glaucoma ........... 111 5.1 Anterior segment optical coherence tomography ................. 112 5.2 Innovation in imaging techniques ......................................... 113 6. Clues in glaucoma neuroprotection .............................................. 115 6.1 Potential glaucoma neuroprotectants..................................... 115 7. Closing remarks ............................................................................ 116 Acknowledgments .............................................................................. 117 References .......................................................................................... 117

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CHAPTER 6 Microglial changes in the early aging stage in a healthy retina and an experimental glaucoma model..........................................................................125

Ana I. Ramı´rez, Jos
e A. Ferna´ndez-Albarral, Rosa de Hoz, In
es Lo´pez-Cuenca, Elena Salobrar-Garcı´a, Pilar Rojas, Francisco Javier Valiente-Soriano, Marcelino Avil
es-Trigueros, Marı´a Paz Villegas-P
erez, Manuel Vidal-Sanz, Alberto Trivin˜o, Juan J. Salazar, and Jos
e M. Ramı´rez 1. Introduction................................................................................... 126 2. Material and methods ................................................................... 127 2.1 Ethics statement ..................................................................... 127 2.2 Animals and anesthetics ........................................................ 128 2.3 Experimental groups .............................................................. 128 2.4 Laser treatment and IOP measurement ................................. 128 2.5 Immunohistochemistry .......................................................... 129 2.6 Quantitative retina analysis................................................... 130 2.7 Statistical analysis .................................................................. 132 3. Results ........................................................................................... 132 3.1 Laser-induced ocular hypertension ........................................ 132 3.2 General morphological characteristics of Iba-1+ retinal cells ........................................................................................ 132 3.3 Morphometric characteristics of the Iba-1+ cells ................. 133 3.4 MHCII expression ................................................................. 137 3.5 CD68 expression.................................................................... 137 3.6 P2RY12 expression ............................................................... 137 4. Discussion..................................................................................... 141 Acknowledgments .............................................................................. 145 References .......................................................................................... 145

CHAPTER 7 Molecular changes in glaucomatous trabecular meshwork. Correlations with retinal ganglion cell death and novel strategies for neuroprotection........151

1. 2. 3. 4.

Sergio C. Sacca`, Stefania Vernazza, Eugenio Luigi Iorio, Sara Tirendi, Anna Maria Bassi, Stefano Gandolfi, and Alberto Izzotti Introduction................................................................................... 152 Oxidative stress ............................................................................. 154 The Nrf2 and NF-κB systems...................................................... 159 Aging ............................................................................................ 161 4.1 Aging and TM ....................................................................... 164

Contents

5. The aqueous humor proteome: Its importance in glaucoma ....... 165 6. Neuroprotective strategies ............................................................ 169 6.1 Polyphenols ............................................................................ 170 6.2 Omega-3 ................................................................................. 171 7. Conclusions................................................................................... 173 Acknowledgments .............................................................................. 174 References .......................................................................................... 174

CHAPTER 8 Effects of caloric restriction on retinal aging and neurodegeneration......................................................189 Annagrazia Adornetto, Luigi Antonio Morrone, Andrea Satriano, Maria Luisa Lagana`, Ester Licastro, Carlo Nucci, Maria Tiziana Corasaniti, Paolo Tonin, Giacinto Bagetta, and Rossella Russo 1. Introduction ................................................................................... 189 2. Glaucoma: An ocular neurodegenerative disease ........................ 190 3. Caloric restriction and fasting in brief ......................................... 192 4. The effect of caloric restriction in retinal aging and neurodegeneration ......................................................................... 192 5. Autophagy: Mechanism and function .......................................... 195 6. Autophagy and glaucoma............................................................. 196 7. The effect of caloric restriction on autophagy ............................. 197 8. Conclusion .................................................................................... 199 References .......................................................................................... 199

CHAPTER 9 Is stagnant cerebrospinal fluid involved in the pathophysiology of normal tension glaucoma...........209 Hanspeter Esriel Killer 1. Summary ....................................................................................... 216 References .......................................................................................... 217

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Preface Glaucoma is a neurodegenerative disease of the visual system characterized by the progressive death of retinal ganglion cells (RGCs) and the loss of their axons that form the optic nerve. Increased intraocular pressure (IOP) has been demonstrated to be the main risk factor associated with the onset and progression of the disease. Despite medical and surgical approaches to reduce IOP are available, actually, this disease is one of the major cause of blindness in the world. Over the last decade, dissection under normal and pathological conditions of molecular mechanisms implicated in the control of cell survival and demise and interplay among retinal cells of diverse embryologic origin have widened the perspective for developing neuroprotective therapeutic approaches other than IOP control in glaucoma. Accordingly, a considerable interest has been recently directed toward the identification of novel therapeutic strategies based upon neuroprotection. In this issue of Progress in Brain Research dedicated to glaucoma, leaders in this scientific field have discussed their original and innovative data as well as data originated from the clinic. In view of the large collection yielded, this latter effort has been reported in two separated volumes. The first volume (256) is dedicated to the wealth of mechanisms underlying the neuronal damage in glaucoma. In particular, the reader is introduced to the potential contribution of altered fundamental cellular mechanisms (see autophagy) as well as microbial dysbiosis through the modulation of adaptive immunity. The more extensively dissected role of innate immunity via microglia activation and soluble neuroinflammatory mediators release in retinal ganglion cells as well as the contribution of oxidative stress are deeply explored. These latter may contribute to the observed alterations of the cerebrospinal fluid dynamic and/or composition that may play a role in the pathogenesis of glaucoma. Particularly interesting are the data reported in the second volume (257) starting with a chapter devoted to the use of artificial intelligence in the diagnosis and therapy of glaucoma. There are many variables that affect the early diagnosis of the disease and the monitoring of its progression; the introduction of artificial intelligence in clinical practice could greatly support the work of ophthalmologists. Data supporting the hypothesis that glaucoma may be influenced by or may share common pathogenic mechanisms with diseases of the central nervous system (CNS) have been accumulated. In agreement with the latter, evidence exists suggesting that the central nervous pathways damaged in glaucoma may play a role in sustaining functional and daily living disability caused by the disease. This second volume incorporates a meta-analysis on the clinical evidence of the neuroprotective properties of brimonidine and current scrutiny of naturally occurring potential neuroprotectans. An outlook to future strategies for glaucoma neuroprotection is also proposed. In fact, a chapter overviews the current progress on the regeneration of pluripotent stem cell-derived RGCs and outlooks the perspective in this field.

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We would like to acknowledge the outstanding contribution of all the authors to the success of these volumes of Progress in Brain Research dedicated to glaucoma and the excellent collaboration of the highly professional staff of Elsevier. In particular, we would like to acknowledge the constant and skillful support of Mr. Hilal Johnson along the whole editorial process. Finally, we would also thank the Referees who have contributed a great deal to improve our editorial work. The Editors Giacinto Bagetta Carlo Nucci

CHAPTER

Functional and morphological alterations in a glaucoma model of acute ocular hypertension

1

Alejandro Gallego-Ortegaa, Marı´a Norte-Mun˜oza, Juan Antonio Miralles de Imperial-Olleroa, Jos
e Manuel Bernal-Garroa, Francisco Javier Valiente-Sorianoa, Pedro de la Villa Polob,c, Marcelino Avil
es-Triguerosa, Marı´a Paz Villegas-P
ereza, and Manuel Vidal-Sanza,* a

Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain b Department of Systems Biology, University of Alcala´, Madrid, Spain c Instituto Ramo´n y Cajal de Investigacio´n Sanitaria, Madrid, Spain *Corresponding author: Tel.: +34 868 884330, e-mail address: [email protected]

Abstract To study short and long-term effects of acute ocular hypertension (AOHT) on inner and outer retinal layers, in adult Sprague-Dawley rats AOHT (87 mmHg) was induced for 90 min and the retinas were examined longitudinally in vivo with electroretinogram (ERG) recordings and optical coherent tomography (OCT) from 1 to 90 days (d). Ex vivo, the retinas were analyzed for rod (RBC) and cone (CBC) bipolar cells, with antibodies against protein kinase Cα and recoverin, respectively in cross sections, and for cones, horizontal (HZ) and ganglion (RGC) cells with antibodies against arrestin, calbindin and Brn3a, respectively in wholemounts. The inner retina thinned progressively up to 7 d with no further changes, while the external retina had a normal thickness until 30 d, with a 20% thinning between 30 and 90 d. Functionally, the a-wave showed an initial reduction by 24 h and a further reduction from 30 to 90 d. All other main ERG waves were significantly reduced by 1 d without significant recovery by 90 d. Radial sections showed a normal population of RBCs but their terminals were reduced. The CBCs showed a progressive decrease with a loss of 56% by 30 d. In wholemount retinas, RGCs diminished to 40% by 3 d and to 16% by 30 d without further loss. Cones diminished to 58% and 35% by 3 and 7 d, respectively and further decreased between 30 and 90 d. HZs showed normal values throughout the study. In conclusion, AOHT affects both the inner and outer retina, with a more pronounced degeneration of the cone than the rod pathway.

Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.07.003 © 2020 Elsevier B.V. All rights reserved.

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CHAPTER 1 AOHT preferentially damages the cone pathway

Keywords Acute ocular hypertension, Glaucoma, Rat retina, Bipolar cells, Horizontal cells, Cones, Retinal ganglion cells, Transient retinal ischemia

1 Introduction Glaucoma is an optic neuropathy characterized by progressive retinal ganglion cell (RGC) loss with concomitant visual field deficits that may progress silently until advanced stages of the disease (Leite et al., 2011) and constitutes the main cause of irreversible blindness (Quigley, 2006). Additional hallmark characteristics of glaucoma include structural abnormalities of the nerve fiber layer and optic disc (Chauhan et al., 2014; Weinreb et al., 2014). Independent research from a number of laboratories has shown that glaucoma is not only a disease of the inner retina, but also of the main retinofugal pathway. It has become clear in human glaucoma studies and experimental models of ocular hypertension that this disease also affects the main thalamic and midbrain relay nuclei (Dekeyster et al., 2015; ValienteSoriano et al., 2015a; Y€ ucel, 2003; Y€ucel and Gupta, 2008), as well as the primary (Nucci et al., 2013) and associated (Frezzotti et al., 2014) areas of the visual cortex. Moreover, increasing evidence indicates that the pre-ganglion cell circuit of the visual pathway is also affected both functionally and structurally (Mittag et al., 2000; Nork et al., 2000; Ortı´n-Martı´nez et al., 2015). Thus, glaucoma may be considered nowadays a disease of the whole primary visual pathway that starts somewhere near the optic nerve head, from where it progresses towards the cortical areas and backwards in a more protracted fashion towards the photoreceptors (VidalSanz et al., 2012, 2015a, 2017). Although the pathology of glaucoma is not fully understood, it is generally accepted that is a multifactorial neurodegenerative disease where axonal compression, vascular dysfunction, oxidative stress, immune-related neuroinflammation and ischemia (Burgoyne, 2015; Flammer et al., 2002; Tezel et al., 2010) may play a role. Accordingly, a number of studies have investigated the effects of axotomy, excitotoxicity, oxidative stress, immune-related inflammation and ischemia in an effort to understand the pathophysiology of glaucoma. Intraorbital optic nerve injury is a classic model that allows to study plasticity, that is, axonal regeneration (Aguayo et al., 1987; Bray et al., 1987), target reinnervation (Avil
es-Trigueros et al., 2000; Vidal-Sanz et al., 1987, 2002) synapse formation (Keirstead et al., 1989; Vidal-Sanz et al., 1987, 1991; Whiteley et al., 1998) as well as neuroprotection (Lindqvist et al., 2004; L€onngren et al., 2006; Vidal-Sanz et al., 2007) of the adult mammalian visual system. Moreover, optic nerve (ON) injury has allowed detail characterization of the effects of axotomy in adult rats and mice following complete crush or transection (Nadal-Nicola´s et al., 2015, 2017; Sa´nchezMigallo´n et al., 2018; Villegas-P
erez et al., 1993) of the intraorbital ON. These studies have shown that following axotomy there is a rapid loss of RGCs followed by a

1 Introduction

more protracted RGC death that occurs over the following months with a very small proportion of RGC surviving long after injury. The effects of retinal excitotoxicity have also been studied by means of intraocular administration of NMDA in an attempt to learn about the effects of this injury (Blanco et al., 2017; Calvo et al., 2020; Vidal-Villegas et al., 2019). Excitotoxicity resulted in rapid and massive loss of the general population of Brn3a+ RGCs, while the entire melanopsin+ RGC population was preserved. Interestingly, these retinas showed with time an important thinning of the overall retinal width indicating a protracted delayed outer retinal degeneration. Transient ischemia of the retina is another common model to investigate the short and long term effects of this injury on the survival and function of the retina (Sell
es-Navarro et al., 1996). This may be achieved using a method that involves selective ligature of the ophthalmic vessels without direct damage to the ON (Vidal-Sanz et al., 2007). These studies indicated that RGC loss is progressive and depends not only on the ischemic interval but also on the survival period, and that following a transient period of retinal ischemia, there was a delayed protracted degeneration of the outer retina as well as of the primary visual pathway (Mayor-Torroglosa et al., 2005). More recently, the early involvement of immune-related neuroinflammation following acute ocular hypertension has been studied in adult rodents (de Hoz et al., 2013, 2018; Ramı´rez et al., 2010, 2020). Because elevated intraocular pressure remains the main risk factor and its control constitutes the main target to slow down the progression of the disease, a number of experimental animal models have investigated the physiopathology and deterioration of the retina following chronic ocular hypertension (AOHT) (for review, see (Morrison et al., 2005; Vidal-Sanz et al., 2012, 2015a, 2017). These include spontaneous genetic mice models such as the DBA/2J mice (P
erez de Lara et al., 2014, 2019). In addition, a number of animal models have been developed to induce AOHT including, episcleral vein cauterization (Garcia-Valenzuela et al., 1995; Vecino et al., 2018), injection into episcleral veins of hypertonic saline (Morrison et al., 1997) or sclerosant agents (Blanco et al., 2019), injection of microbeads or viscoelastics into the anterior chamber (Ito et al., 2016) or laser photocoagulation of the episcleral and perilimbal veins (Salinas-Navarro et al., 2010). The later has been quite a popular model used to characterize the effects of AOHT in adult albino (Ou et al., 2016; Salinas-Navarro et al., 2010; Valiente-Soriano et al., 2015a) rats as well as in albino (Salinas-Navarro et al., 2009) and pigmented mice (ValienteSoriano et al., 2015b). Another model to study ocular hypertension consists of the induction of an acute elevation of the intraocular pressure (AOHT) above basal levels. This model mimics somehow the effects of an acute angle-closure glaucoma, and has been widely employed (Quigley and Anderson, 1976). Recent studies from our Laboratory in adult albino rats indicate that AOHT results in progressive RGC loss, that may be prevented with intravitreal administration of brain derived neurotrophic factor (BDNF) (Rovere et al., 2016). Furthermore, the general population of Brn3a+ RGCs or the population melanopsin+ RGCs respond differently no only to the insult but also

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CHAPTER 1 AOHT preferentially damages the cone pathway

to neuroprotection. AOHT also resulted in significant increase of the microglial cells within the RGC layer, with important changes in the expression of miRNAs associated with neuroinflammation (Wang et al., 2017). In addition, several studies have investigated the effects of AOHT in the inner and outer retina, but these were analyzed at shorter survival intervals of 3–8 weeks (Palmhof et al., 2019; Schmid et al., 2014). The present studies were designed to further investigate in adult albino rats the short- and long-term effects of AOHT on the retina. Using functional and morphological techniques we studied longitudinally in vivo up to 90 days the effects of AOHT on the architecture, and function of the main ERG wave-generating retinal neurons. Moreover, using immunohistochemistry we assessed neuronal survival from the innermost (RGCs), inner (rod and cone bipolars, and horizontal cells) and outer (cone photoreceptors) nuclear layers of the retina.

2 Methods 2.1 Animal handling Sprague-Dawley (SD) rats (
180–210 g) (Charles River Laboratories; L’Arbresle, France) were housed in animal facilities of Murcia University in temperature and light controlled rooms (12 h light/dark cycle) with food and water “ad libitum.” Experimental protocols were approved by the Ethical and Animal Studies Committee of Murcia University, and we followed Spanish and European Union regulations for Animal Care, as well as the statement for the Use of Animals in Ophthalmic and Vision Research approved by the Association for Research in Vision and Ophthalmology. Surgical manipulations were performed under general anesthesia; intraperitoneal (i.p.) injection of a mixture of ketamine (70 mg/kg, Ketolar®, Parke-Davies, S.L., Barcelona, Spain) and xylazine (10 mg/kg, Rompu´n®, Bayer, S.A., Barcelona, Spain). To minimize any discomfort analgesia was provided postoperatively with subcutaneous buprenorphine (0.1 mg/kg; Buprex, Buprenorphine 0.3 mg/mL; Schering-Plow, Madrid, Spain). Animals were sacrificed with an i.p. overdose of pentobarbital (Dolethal Vetoquinol®, Especialidades Veterinarias, S.A., Alcobendas, Madrid, Spain).

2.2 Experimental design To investigate the short- and long-time effects of AOHT we used two groups. One group was employed for the longitudinal in vivo morphological Spectral Domain Optical Coherence Tomography (SD-OCT) and functional recorded electroretinogram (ERG) responses as well as for the ex vivo whole-mount retinal studies at 1, 3, 7, 15, 30 or 90 d (n ¼ 5–7 rats per time point). A second group was analyzed in cross sections at 3, 7, 15, 30 or 90 d after AOHT (30 experimental; n ¼ 6 per time point, and 4 naı¨ve rats).

2 Methods

2.3 Acute ocular hypertension induction AOHT was induced as described (Rovere et al., 2016; Wang et al., 2017). Briefly, anesthetized rats were placed over a heating pad to maintain normal body temperature. A 30-gauge infusion needle placed in the anterior chamber of the left eye was connected to a 500-ml container of 0.9%NaCl 1.5 m above the eye. Intra-ocular pressure (IOP) raised from baseline (10  2 mmHg) to 87  4 mmHg, as monitored with Tono-Pen (Tono-Pen; Medtronic Co., Dublin, Ireland) (Ortı´n-Martı´nez et al., 2015; Valiente-Soriano et al., 2015a, 2015b). Following 90 min of AOHT, the needle was removed, IOP returned to basal values and the corneas were covered with an ointment (Tobrex; Alcon S. A., Barcelona, Spain) to prevent corneal desiccation. Retinal blood flow was examined by direct funduscopy with operating microscope (Spot OPMI 11, Carl Zeiss, Oberkochen, Germany) previously, during and after acute OHT. While AOHT resulted in lack of retinal perfusion, there was complete blood flow reperfusion after needle removal.

2.4 Spectral domain optical coherence tomography (SD-OCT) The effects of AOHT were characterized longitudinally in vivo in the same retinas at 1, 3, 7, 15, 30 (n ¼ 12) and 90 (n ¼ 7) days, using SD-OCT (Spectralis; Heidelberg Engineering, Heidelberg, Germany) as described (Ortı´n-Martı´nez et al., 2014b; Rovere et al., 2015; Valiente-Soriano et al., 2019). As shown in Fig. 1, total retinal (from nerve fiber layer to the retinal pigment epithelium), inner retinal (from the fiber layer to the outer end of the inner nuclear layer) and outer retinal (from the inner end of the outer plexiform layer to the retinal pigment epithelium) thickness were measured using the average of three measurements of calipers provided directly by the software of the device from 3 different sections per eye (one section containing the ON, one 1500 μm above and one 1500 μm below).

2.5 Electroretinography (ERG) ERG recordings were obtained longitudinally from both eyes of the same 7 rats at 1, 3, 7, 15, 30 and 90 d after AOHT as described (Alarco´n-Martı´nez et al., 2009, 2010; Valiente-Soriano et al., 2019). In brief, initially scotopic ERG waves were recorded binocularly from anesthetized rats under dark adaptation, in response to 4.4 (Scotopic Threshold Response), 2.5 (Rod Response and Scotopic Flicker Response) and 0.5 (Mixed Response) log cds/m2 provided by a Ganzfeld dome. Animals were then light adapted (30 cd/m2) for 5 min and Cone Response and Photopic Flicker Responses (0.5 log cds/m2) were further recorded. Retinal responses were recorded by Burian-Allen bipolar electrodes placed on both corneas of the animal; a drop of methyl cellulose (Methocel 2%®; Novartis Laboratories CIBA Vision, Annonay, France) was placed between the cornea and the electrode to increase electrical conductivity; one reference electrode was placed in the mouth and a needle placed subcutaneously at the base of the tail was connected to the ground electrode. The electrical signals were digitized at 20 KHz using a Power Lab data acquisition board (AD Instruments, Chalgrove, UK). Standard ERG waves were analyzed according to the International Society for Clinical Electrophysiology of Vision (ISCEV).

5

90 Days

30 Days

7 Days

15 Days

1 Day

3 Days

Control

CHAPTER 1 AOHT preferentially damages the cone pathway

H

200

*

*

#

150

125 Thickness (µm)

Inner retina Outer retina

250

Φ

75 50 25 0

100

*

50 0

0

1

15 3 7 Time (days)

30

90

I

Inner retina

100

130 Thickness (µm)

Thickness (µm)

6

01 3

7

120

15 Time (days)

30

90

J

Outer retina

110 100

*

90 80 70

01 3

7

15 Time (days)

30

90

[n=12 per group, except for group of 90 days n=7]

FIG. 1 SD-OCT images from a representative retina analyzed before and at 1, 3, 7, 15, 30 and 90 d after AOHT. SD-OCT representative images of a retina analyzed before (A) and at 1 (B), 3 (C), 7 (D), 15 (E), 30 (F) and 90 (G) days after the induction of AOHT. Image A shows the delineated retina; the blue lines depict the fibber layer; the green line outlines the IPL and ONL limit and the green line outlines the RPE. (H) Graph showing quantitative study of total retinal thickness (entire column), inner retinal thickness (light gray column) and outer retinal thickness (dark gray column) across all time intervals studied. Graphs show progress of inner retina (I) and outer retina (J) thickness. *Statistically significant difference with respect to the control; #Statistically significant difference with the 3-day group; ΦStatistically significant difference with the previous group.

2 Methods

2.6 Tissue processing Rats were deeply anesthetized, perfused transcardially with 0.9% saline followed by 4% paraformaldehyde (PF) in 0.1 M phosphate buffer and eyes were enucleated and post fixed for 1 h in 4% PF. For cross section analysis, the eye cups were immersed in increasing sucrose concentrations (15–30%), oriented and frozen in tissue tack and 16 μm thick cross sections containing the ON head were obtained in the cryostat as described (Ortı´n-Martı´nez et al., 2014a; Valiente-Soriano et al., 2014). For wholemount analysis, retinas were prepared as flattened retinas maintaining retinal orientation by making four radial cuts in the retina (the deepest one signals the superior pole of the eye) as described (Vidal-Sanz et al., 2015b, 2017).

2.7 Immunohistofluorescence Immunodetection was carried out following previous described protocols for cross sections (Ortı´n-Martı´nez et al., 2014b) or whole-mounted retinas (Vidal-Sanz et al., 2017). Primary and secondary antibodies and dilutions used in this study are detailed in Table 1. All cross-sections were counterstained with DAPI.

2.8 Image acquisition Cross sections and whole-mounts were examined and photographed using epifluorescence microscopes (Axioscop, Zeiss ETC and Leica DM6-B, Leica Microsytems, Wetzlar, Germany) controlled by image analysis software as described (Di Pierdomenico et al., 2020; Ortı´n-Martı´nez et al., 2014a; Valiente-Soriano et al., 2020). For the analysis of the retinal sections, three non-consecutive sagital retinal Table 1 Antibodies used in this work. Primary antibody Cross sections

Retinal Wholemounts

Mouse α-PKCαb Rabbit αRecoverinc Mouse α- Brn3ad Guinea αcalbindine Rabbit α-arrestinf

Dilution

Commercial reference

1:200

ABCAM, ab11723, UK

1:1000

AB5585, Millipore, Germany

1:500

MAB1585, Millipore, Germany

1:500

214–004, Synaptic Systems, Germany

1:1000

AB15282; Chemicon-Millipore Iberica, Madrid, Spain

Secondary antibodya Igg 1 Goat α-mouse 488 Donkey α-rabbit 594 Igg 1 Goat α-mouse 488 Goat α-guinea pig 647 Donkey α-rabbit 555

a All secondary antibodies were purchased from Molecular Probes, ThermoFisher, Madrid, Spain. All were used in a 1:500 dilution. b Detects rod bipolar cells (Cuenca et al., 2010). c Detects cone bipolar cells (Cuenca et al., 2010). d Detects retinal ganglion cells (Nadal-Nicola´s et al., 2014). e Detects Horizontal cells (Pasteels et al., 1990). f Detects cone outer-segments (Palmhof et al., 2019).

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CHAPTER 1 AOHT preferentially damages the cone pathway

sections including the optic nerve were photographed, images were taken of four representative areas (upper periphery, upper central, lower central and lower periphery). Retinal whole-mounts were reconstructed with 64 individual frames captured side-by-side with no gap or overlap between them with a 10 objective. When examining and photographing RGCs, wholemounts were examined vitreal side up, and to investigate and photograph calbindin+ and arrestin+ cone outer segments, wholemounts were examined vitreal side down. When required, images were further processed using a graphics editing program (Adobe Photoshop CS 8.0.1; Adobe Systems, Inc., San Jose, CA).

2.9 Quantification and spatial distribution Cross section analysis and quantification of PKC-α+ RBCs and recoverin+ CBCs was performed in naı¨ve (n ¼ 4) and AOHT rats at 3, 7, 15, 30 or 90 d (n ¼ 6 per time point). A total of 30 AOHT retinas, 30 contralateral fellow and 8 naı¨ve retinas were analyzed. All frames were manually dotted using a graphics editing program (Adobe Photoshop CS 8.0.1; Adobe Systems, Inc., San Jose, CA). Because there were no significant differences in cell counts obtained between the different areas, values were averaged and presented as mean number of cells counted per retinal frame. In addition, the same cross sections were measured for total and inner retinal thickness using the same OCT landmarks with Image Pro Plus software, as described (Valiente-Soriano et al., 2019). Wholemount analysis examined Brn3a+ RGCs, calbindin+ HZs and arrestin+ cones, these cells were counted automatically and their topography studied as described (Nadal-Nicola´s et al., 2015, 2018). The distribution of RGCs and cone outer-segments was assessed by isodensity maps and the distribution of HZs was visualized using the near neighbor algorithm as described (GalindoRomero et al., 2013). All maps were plotted using software SigmaPlot (SigmaPlot 9.0 for Windows; Systat Software, Inc., Richmond, CA, USA) and a color code to represent density of cells/mm2 or the number of neighbors around a cell.

2.10 Statistical analysis Data were analyzed and plotted with GraphPad Prism v.8 (GraphPad, San Diego, CA, USA). All averaged data are presented as means with standard deviations (SD). Statistical analysis was done using GraphPad Prism v.8. Brown-Forsythe One-way ANOVA and Ordinary One-way ANOVA was used when comparing more than two groups and Welch’s t-test when comparing two groups only. Differences were considered significant when P < 0.05.

3 Results 3.1 Early thinning of the inner retina and a delayed thinning of the external retina Control and experimental rats were analyzed in vivo with SD-OCT (representative SD-OCT images are shown in Fig. 1). There were no significant differences among the fellow right eyes, thus the results were pooled and considered as controls.

3 Results

Inner retinal thickness of the left AOHT retinas showed at 24 h a transient increase (Fig. 1A–I) with a significant decrease at 3 d that further progressed up to 7 d and was maintained without further thinning thereafter, up to 90 d (Fig. 1A–I). External retinal thickness showed normal values with a protracted delayed thinning between 30 and 90 d (Fig. 1J). Concordant results were obtained from the ex vivo measurement of cross sections (see below).

3.2 Dramatic and permanent alterations of all retinal waves recorded Longitudinal analysis of ERG recordings showed in the AOHT left eyes a significant acute reduction of all studied wave amplitudes (Fig. 2). The positive scotopic threshold response (pSTR) wave diminished to
10% at 1 d after AOTH and did not recover (Fig. 2A–A00 ). The Rod response, showed the b-wave reduced to
25% at 1 d without further recovery (Fig. 2B-B00 ). The scotopic flicker response at 3 and 10 Hz showed diminished amplitudes (Fig. 2C–C00 ). The a-wave of the mixed response diminished to
60% at 1 d with further significant reduction to
40% between 30 and 90 d (Fig. 2D–D00 ). The b-wave of the mixed response showed an initial decay to
30% without further decrease (Fig. 2D000 –D0000 ). The b-wave of the cone response showed an initial decay to
5% without further recovery (Fig. 2E–E00 ). The photopic flicker response showed no flat recordings 10 and 20 Hz (Fig. 2F–F00 ). Both scotopic and photopic flicker responses were diminished from day 1 after AOHT without further recovery. Overall, our results indicate that AOHT results in dramatic permanent alterations of retinal function that comprises all major cell populations of the retinal centripetal pathway (photoreceptors, cone and rod bipolars as well as RGCs) that generate the main waves of the ERG.

3.3 Death of CBCs but not RBCs Cross retinal sections were immunostained against recoverin to identify CBCs (Fig. 3A–F), PKC-α to identify RBCs (Fig. 3A0 –F0 ) and counterstained with DAPI (Fig. 3A00 –F00 ). Measurements obtained from cross sections for inner and outer retinal thickness showed comparable results to those observed in vivo with OCT (Fig. 4A). Overall retinal thickness in cross sections was smaller than that measured in vivo with OCT (Fig. 1H), and this may be related to tissue processing (Fig. 4A). Radial sections of naı¨ve and fellow control retinas (Fig. 3A–A00 ) showed the typical distribution of the recoverin+ CBCs; their soma was located in the INL and terminal arborizations were present within the outer and inner IPL, corresponding to the OFF and ON subdivision of the IPL, respectively (Fig. 3A). Recoverin immunolabeling was also observed within the ONL outlining photoreceptors somata as well as their outer segments (Figs. 3A–F), as observed with DAPI counterstaining (Figs. 3A00 –E00 ). In the experimental retinas, in congruence with the in vivo SD-OCT results, retinal thickness was affected over time (Figs. 3A00 –F00 , 4A). By 3 d fewer CBCs were detected and the terminal arborizations appeared thinner in the ON sublayer closest to the GCL (Figs. 3B, 4B). Further cell diminutions were

9

FIG. 2 Electroretinogram average records analyzed before and at 1, 3, 7, 15, 30 and 90 days after AOHT. (A–F) Electroretinogram traces recorded before and at 1, 3, 7, 15, 30 and 90 days after AOHT under scotopic and photopic conditions. Histogram representation for the wave amplitudes (mV) and percentage of the maximum amplitude are also shown for pSTR (A–A00 ) (4.3 log cds/m2), rod response (B–B00 ) (2.5 log cds/m2), scotopic flicker response at 3 and 10 Hz (C–C00 ) (2.5 log cds/m2), mixed response (D–D0000 ) (0.5 log cds/m2), cone response (E–E00 ) (0.5 log cds/m2) and photopic flicker response at 10 and 20 Hz (F–F00 ). *Statistically significant differences with the control group; $ Significant differences with the 30-day group.

3 Results

FIG. 3 CBC and RBC populations in control and at 3, 7, 15, 30 or 90 days after AOH. Representative retinal sections immunostained for recoverin to label CBCs (left column; A-F), PKC-α to label RBCs (middle column; A0 –F0 ) and merged with DAPI counterstain (right column; A00 –F00 ) in control retinas (A–A00 ) and AOHT-retinas analyzed at 3 (B–B00 ), 7 (C–C00 ), 15 (D–D00 ), 30 (E–E00 ) or 90 (F–F00 ) days. The images show a decrease in retinal thickness throughout the study. The morphological study shows an asymmetric evolution between CBCs and RBCs; CBCs are progressively affected over the study while RBCs remain. Scale bar ¼ 100 μm.

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CHAPTER 1 AOHT preferentially damages the cone pathway

FIG. 4 Quantitative analysis of retinal thickness and CBCs and RBCs. Graphs illustrating the retinal thickness after AOHT (A) and mean numbers of CBCs (B) and RBCs (C) manually counted per frame at all analyzed time intervals. **Statistically significant differences compared to the control group (P < 0.01); ****Statistically significant differences compared to control group (P < 0.001); ΦΦStatistically significant differences compared to the previous group (P < 0.01).

observed between 3 and 7 days after injury, and again between 15 and 30 days without further loss thereafter (Figs. 3C–D, 4B). There were few CBCs at 30 and 90 d and the INL had thinned considerably (Figs. 3E, F, 4B). In naı¨ve and fellow control eyes, PKC-α immunolabeling delineated the cell bodies distributed mainly in the outermost part of the INL, their axonal terminals were observed in the innermost part of the IPL and there was an intense labeling within the OPL reflecting their dendritic arbors (Fig. 3A0 ). In the experimental AOHT retinas (Fig. 3B0 –F0 ) despite the reduction in INL thickness, the RBC population did not appear to change significantly at any of the time intervals examined (Figs. 3A0 –F0 , 4B). Nevertheless, there was a reduction in the signal intensity of dendritic and axonal arbors in PKC-α-positive cells that was observed at later times (Fig. 3B0 –F0 ).

3 Results

3.4 Loss of RGCs and cones but not HZs Control retinas showed the typical pattern of Brn3a+ RGCs distribution within the retina (Figs. 5A, 6A) and their mean total numbers (Table 2) were in range with previously published data (Nadal-Nicola´s et al., 2014, 2015). Following AOTH, RGC loss was apparent as early as 3 d (Figs. 5A0 , 6B, 7A) (Table 2), further progressed up

FIG. 5 Representative central retinal areas showing RGC and HZs in control and at 3 and 90 days after AOHT. Flat-mount magnifications in the central retinal areas immunostained against Brn3a to label RGCs (A–A00 ) and against calbindin to label HZs (B–B00 ). Scale bar ¼ 100 μm.

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CHAPTER 1 AOHT preferentially damages the cone pathway

FIG. 6 Spatial distribution of Brn3a+ RGCs in control and at 3, 7, 15, 30 or 90 days after AOH. Representative isodensity maps showing the topographical distribution of Brn3a+ RGCs in control (A) and experimental retinas analyzed at 3(B), 7(C), 15(D), 30(E) or 90(F) days after AOHT. Color scale for isodensity maps goes from 0 (purple) to 3200 (red) RGCs/mm2 for control retina and to 2000 (red) RGCs/mm2 in experimental ones. S: superior, I: inferior, T: temporal, N: nasal. Total number of Brn3a+ RGCs is indicated for each map. Scale bar ¼ 100 μm.

3 Results

Table 2 Total number of RGCs, HZs and cone outer segments in control and AOHT retinas. Cell types and groups

Time after AOHT induction, days

Brn3a+ cells Mean

RE n ¼ 25 80,723

3, n ¼7 35,399a

7, n ¼4 37,248a

15, n ¼6 26,358b

30, n ¼5 14,736c,

90, n ¼6 13,250c,d

d

SD Calbindin+ cells Mean SD Arrestin+ cells Mean

7718 RE n ¼ 32 46,106 8681 RE n ¼ 30 173,180

9529 3, n¼ 7 45,678 2723 3, n¼ 7 98,100c

5340 7, n¼ 7 39,974 6474 7, n¼ 7 58,531c,

13,816 15, n¼ 6 38,583 5422 15, n¼ 6 59,060c,

2563 30, n¼ 6 42,026 4700 30, n¼ 6 66,384c,

d

d

d

SD

24,002

20,207

20,037

18,983

14,037

2575 90, n ¼6 43,180 5127 90, n¼ 6 39,074c–e 12,414

Mean  standard deviation of the total number of RGC, HZs and cone outer segment populations in control and experimental retinas analyzed at 3, 7, 15, 30 or 90 days after AOHT. n, number of retinas per group. Unpaired t-test with Welch’s correction. a Statistically significant when compared with intact retinas (P < 0.05). b Statistically significant when compared with intact retinas (P < 0.01). c Statistically significant when compared with intact retinas (P < 0.001). d Significant when compared with 3 days (P < 0.01). e Statistically significant when compared with 30 days (P < 0.01).

to 30 d without further loss thereafter (Figs. 5A00 , 6B–F, 7A) (Table 2). The spatial distribution of RGC loss showed an irregular patchy pattern illustrated in representative isodensity maps (Fig. 6B–F), similar to that found in previous studies (Rovere et al., 2016; Wang et al., 2017). Control retinas labeled for arrestin showed a very dense staining of cone outer segments within the entire retina forming a very thick grass field-like (Fig. 8A), and their total numbers were 173,180  24,002 (n ¼ 30) (Table 2). In the AOHT retinas, the arrestin+ cone outer-segments showed a diminution somehow reminiscent of the progressive RGC loss. Arrestin+ cone outer-segments loss was apparent as early as 3 d (98,100  20,207; n ¼ 7) (Figs. 7B, 8B, Table 2), further progressed by 7 d (58,531  20,037; n ¼ 7) (Figs. 7B, 8C, Table 2) and remained stable until a further decrease between 30 and 90 d (Figs. 7B, 8E–F, Table 2). The topographic distribution (Fig. 8) showed that most of the early cone outer-segment loss appeared in the central retina, with the vast majority of the surviving cone outer-segments remaining in peripheral areas of the retina, so that by 90 d (39,074  12,414; n ¼ 6) a small population of cone outer-segments was still present and mainly located in retinal edges. Calbindin+ HZs (Chun et al., 1999) were analyzed focusing in the outer portion of the INL. In the adult rat, only one type of HZ is identified with the calbindin

15

FIG. 7 Quantitative study RGCs, HZs and cone outer segments. Graphs illustrating in percentage the mean total population of RGCs (A), cones (B) and HZs (C) automatically counted per retina at each time interval. *Significant when compared with their fellow right control retinas (P < 0.05); **Statistically significant differences compared to the control group (P < 0.01); ****Statistically significant differences compared to the control group (P < 0.001); σσ Statistically significant when compared with 3 days (P < 0.01).

3 Results

FIG. 8 Photomontages showing arrestin+ cone outer-segments in control and experimental retinas at 3, 7, 15, 30 or 90 days after AOHT. Representative photomontages of flat-mounted retinas immunostained with arrestin to label cone outer-segments in a control (A) and experimental retinas analyzed at 3 (B), 7 (C), 15 (D), 30 (E) or 90 (F) days after AOHT. Total number of arrestin+ cone outer segments is indicated for each map. Color scale for isodensity maps goes from 0 (purple) to 3200 (red) RGCs/mm2 for control retina and to 2000 (red) RGCs/mm2 in experimental ones. Scale bar ¼ 100 μm.

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CHAPTER 1 AOHT preferentially damages the cone pathway

(Gonza´lez-Soriano, 1994), type B, similar to the HZ type HI of primates, which contact mainly cones with their dendrites and rods with their axon terminals (Cuenca et al., 2010). In control retinas, calbindin immunoreactivity clearly delineates round cell somata as well as some of their proximal processes (Fig. 5B). Total numbers of calbindin+ HZs were 46,106  8681 (n ¼ 32) (Fig. 7C) (Table 2), which expressed as cells/ mm2 corresponds to a mean density of 663  107 (n ¼ 32). These cells appeared regularly spaced and were distributed throughout the retina with higher densities in the central dorsal (682) and ventral (728) areas of the retina, with decreasing densities in the periphery being more marked in the superior (468) than in the inferior (565) (Fig. 9). These findings are in agreement with previous reports in rats using calbindin immunoreactivity showing similar densities in the central 814–850 (Chun et al., 1999; Gonza´lez-Soriano, 1994) or peripheral 460 (Gonza´lez-Soriano, 1994) retina. The slight differences between our results and those reported previously may be related to the fact rather than sampling areas of the retina, we counted the entire population of calbindin+ cells. In the AOHT retinas examined at different time intervals ranging from 1 to 90 days, HZs did not show significant variations neither in their total numbers nor in their topography (Figs. 5B0 –B0 , 7C) (Table 2).

FIG. 9 Spatial distribution of calbindin+ HZs. Neighbor maps showing the topographic distribution of calbindin+ HZs in a control retina. Color scale for the neighbor map goes from 0 to 16 (purple) to 129 (red) neighbors in a radius of 0.22 mm. Total number of calbindin+ HZs is indicated on the bottom left corner. S: superior, I: inferior, T: temporal, N: nasal. Scale bar ¼ 1 mm.

4 Discussion

4 Discussion AOHT that has been shown to oversee retinal tolerance (Bui et al., 2013, 2005) and to result in a complex insult to the eye globe resulting in direct ischemic insult to the retina, pressure-induced retinal damage because AOHT exceeds by several fold the basal IOP levels, and deformation of the eye that may cause retinal axonal damage at their exit from the eye (Rovere et al., 2016; Wang et al., 2017). This complex insult, may mimic acute angle-closure glaucoma and thus may be used to further understand the pathophysiology of glaucoma (Chrysostomou and Crowston, 2013; Fortune et al., 2011; He et al., 2006; Quigley and Anderson, 1976). In the present studies we have further investigated the short- and long-term effects of an acute elevation of the IOP to 87 mmHg for 90 min and examined the retinas between 1 and 90 d later. We used longitudinal in vivo full field ERG recordings to assess function of innermost, inner and outer retinal neurons as well as SD-OCT to assess morphological changes within the inner and outer retina in the same groups of rats. In addition, we analyzed ex vivo groups of rats at different survival intervals and used modern tools to identify and map several populations of retinal neurons, as well as to measure retinal thickness. Antibodies against Brn3a identifies most RGCs (
97%) except for one half of the ipsilaterally projecting RGCS and the Melanopsin+ RGCs (Nadal-Nicola´s et al., 2014). Antibodies against calbindin, identify within the outer INL a total of 46,106 HZs. Antibodies against PKC-α or Recoverin identify in the INL the populations of RBCs or CBCs, respectively, and antibodies against arrestin identify in the ONL a total of 173,180 cone outer segments. Our results indicate that AOHT results in: (i) Early thinning of the inner retina and a delayed thinning of the external retina; (ii) a profound and permanent alteration of all main retinal waves recorded; (iii) the loss of RGCs and cones but not HZs, and; (iv) the loss of CBCs but not RBCs. Overall, our results suggest that AOHT damages preferentially the cone pathway.

4.1 AOHT reduces the thickness of the inner retina and over time the outer retina An early transient thickening within the first 24 h has been previously reported following retinal injury (Abbott et al., 2014; Palmhof et al., 2019; Rovere et al., 2015) and may relate to an inflammatory process (de Hoz et al., 2013, 2018; Ramı´rez et al., 2010, 2020) that involves glial proliferation within the nerve fiber layer (Nadal-Nicola´s et al., 2018; Salvador-Silva et al., 2000). The early inner retinal thinning observed in the present studies parallels the greatest loss of Brn3a+ RGCs and Recoverin+ CBCs, whose dendritic and axonal processes, respectively, contribute to the width of the inner retinal layers. Indeed, bipolar cells in mice account for approximately 40% of INL cells, their somata and axonal processes make up for a large volume of the INL and IPL, and one half of the bipolar cells correspond to cone bipolar cells (Ghosh et al., 2004). Thus, assuming a comparable proportion in the rat retina, this would indicate that the loss of these cells and their axon terminals should

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result in significant thinning of the inner retina, as was the case in our present study. Similar thinning has been reported in previous studies after transient ischemia of the retina (Mayor-Torroglosa et al., 2005), acute (Rovere et al., 2016; Wang et al., 2017) or chronic (Cuenca et al., 2010; Salinas-Navarro et al., 2009) ocular hypertension that involve INL cell death (Abbott et al., 2014; Bui et al., 2013; Fortune et al., 2011; Schmid et al., 2014). The delayed thinning of the outer retina between 30 and 90 d after AOHT parallels a delayed decrease in arrestin+ cones and a further loss of the a-wave, generated by the photoreceptors. In the present studies we have not quantified, nor identified rods, but the diminished a-wave and thinning of the outer retina indicate a great loss not only of cones but also of rods which constitute the vast majority of photoreceptors (Valiente-Soriano et al., 2019).

4.2 AOHT results in early permanent retinal disfunction Longitudinal ERG recordings allow functional testing of several neuronal populations within the retina. The positive component of the STR wave is related to RGCs (Alarco´n-Martı´nez et al., 2009, 2010; Saszik et al., 2002), and this wave showed a dramatic decrease by 24 h after AOHT without recovery, suggesting that these cells ceased function immediately after the insult. The rod response and the scotopic flicker response, which are associated with activity and depolarization of RBCs (Brown and Wiesel, 1961), showed a reduction of
80% throughout the study. These results contrast with our PKC-α+ RBCs appearing unchanged at all times. It is possible that RBCs maintain the expression of protein kinase c, but with a lack of function. Indeed, previous studies indicate that following AOHT there are subtle abnormalities within their dendritic arbors that could be responsible for such a diminished ERG response (Cuenca et al., 2010). The mixed response shows a positive wave (a-wave) generated by photoreceptor activity (Brown, 1968; Brown and Wiesel, 1961) and a negative wave (b-wave) generated by the depolarization of bipolar cells (rod and cone bipolar cells) (Brown and Wiesel, 1961; Heynen and Van Norren, 1985). The a-wave showed an early decrease to
60% that further diminished to
40% between 30 and 90 d after AOHT, and these results are in agreement with total counts of arrestin+ cones in wholemounts showing an early decrease at 7 d and a further protracted reduction between 30 and 90 d, as well as with our outer retinal thickness measurements showing a delayed significant thinning between 30 and 90 d. The rodent retina is a rod dominated retina while cones comprise
3% of photoreceptors (Ghosh et al., 2004). Thus, the somewhat preservation of the a-wave and outer retinal thickness at early time intervals would imply survival of a large proportion of the photoreceptor population that is mainly comprised by rods, while the delayed a-wave loss and outer retinal thinning would imply a protracted loss not only of cones, but also of rods. The b-wave of the mixed response showed an early decrease to
25% that did not recover, and this concord with our CBCs counts showing an early loss by 3 d that progressed further to 30 d, as well as with our inner retinal thickness measurements showing early significant thinning by 7 d without further loss. The early findings of a photopic b-wave diminished to
5% together with

4 Discussion

the lack of flicker responses, further indicate an almost immediate dramatic loss of CBCs function. Thus, overall our longitudinal functional analysis indicates that AOHT results in an early and dramatic alteration of retinal function that persist over the period of study, up to 90 days. These results are in agreement with previous studies from this (Mayor-Torroglosa et al., 2005) and other laboratories (Bui et al., 2005, 2013; Fortune et al., 2011; Palmhof et al., 2019; Schmid et al., 2014) showing alterations of different components of the ERG following transient ischemia of the retina and without recovery of any of the waves at pressures above 80 mmHg, as our experimental model (Bui et al., 2013).

4.3 AOHT causes the loss of ganglion cells and cones but not HZs Wholemount analysis showed a rapid and progressive massive loss of RGCs, in agreement with an almost lack of pSTR and negative photopic wave, both of which are functional parameters of RGC wellbeing (Agostinone et al., 2018; Alarco´nMartı´nez et al., 2009, 2010). This loss of RGCs has been described in previous studies involving acute (Abbott et al., 2014; Palmhof et al., 2019; Rovere et al., 2016; Schmid et al., 2014; Wang et al., 2017; Zhou et al., 2019), or chronic (Cuenca et al., 2010; Salinas-Navarro et al., 2009, 2010; Vidal-Sanz et al., 2012) OHT. AOHT also resulted in a rapid wave of cone outer-segments loss that affected approximately 70% of the population by 7 d and an additional protracted wave of 10% cone loss between 30 and 90 d. Such an early photoreceptor loss has been shown following AOHT in previous short-term studies for cones (Palmhof et al., 2019) and rods (Joachim et al., 2017). Topographic analysis indicates that cone loss appears within the central retina and by 90 d there was a small rim of cones on the retinal edges, a region that is reach in S-Cones (Ortı´n-Martı´nez et al., 2010). However, in the present studies we did not differentiate S- from M/L cones, and thus we ignore whether one type of cone survives better than the other. In control retinas calbindin+ HZs were observed within the outer INL and displayed the typical evenly spaced distribution (Kim et al., 2010). Total numbers of HZs as well as their distribution remained comparable throughout the study, an observation in agreement with previous short-term studies analyzed at 8 weeks following AOHT (Chun et al., 1999; Kim et al., 2010; Palmhof et al., 2019) with a suggestion that calbindin may act as a neuroprotective agent in these neurons against injury (Kim et al., 2010; Kwon et al., 2005).

4.4 AOHT results in the death of cone bipolar cells but not rod bipolar cells Quantification of cone and rod bipolar cells showed an asymmetric response to AOHT. PKCα+ RBCs remained unchanged throughout the study, but showed decreased immunofluorescence of their axonal terminal arbors and within their dendrites which may also indicate some remodeling at the level of the synaptic connections between rods, rod-bipolars and corresponding axon-like processes of

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horizontal cells (Cuenca et al., 2010). In contrast to the RBC population, Recoverin+ CBCs were affected as early as 3 d and progressed until 30 d, without further loss. Accordingly, our functional results showed a drastic reduction in the cone-specific electroretinogram responses including the flicker responses, generated by the CBCs, and these reductions were even more significant than the rod response, an observation that is in agreement with previous reports (Cuenca et al., 2010; Palmhof et al., 2019). We do not have a clear explanation for the different bipolar cell survival, but it has been suggested that CBCs may die as a consequence of a lack of target neurons (Calkins, 2012; Zhou et al., 2019) and indeed, RGCs died massively after AOHT. Following the same argument RBCs would survive because their main target neurons, amacrine AII and A17 cells, may not be as affected. However, we did not study rod amacrine cell survival and this remains a question for future studies. Nevertheless, it is tempting to suggest that the rod pathway is more resistant because it does not establish synapses with RGCs, which are most sensitive to AOHT. Overall, our functional and morphometric analysis indicates that the residual b-wave recorded is generated mostly by surviving RBCs since they remain intact to the insult. Moreover, the residual a-wave might also be generated by the large proportion of surviving photoreceptors, which are mainly rods. In contrast, cones and CBCs were drastically and rapidly lost. Thus, it is tempting to suggest, that in the present studies, following AOTH the rod-pathway has a better outcome than the cone-pathway.

Financial support This study was supported by the Spanish Ministry of Economy and Competitiveness, Instituto de Salud Carlos III, Fondo Europeo de Desarrollo Regional “Una manera de hacer Europa” (PI16/00380, SAF2015–67643-P, RD16/0008/0026 and RD16/0008/0020) and by the Fundacio´n S
eneca, Agencia de Ciencia y Tecnologı´a Regio´n de Murcia (19,881/GERM/15).

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es-Navarro, I., Villegas-Perez, M.P., Salvador-Silva, M., Ruiz-Go´mez, J.M., Vidal-Sanz, M., 1996. Retinal ganglion cell death after different transient periods of pressure-induced ischemia and survival intervals: a quantitative in vivo study. Investig. Ophthalmol. Vis. Sci. 37, 2002–2014. Tezel, G., Yang, X., Luo, C., Kain, A.D., Powell, D.W., Kuehn, M.H., Kaplan, H.J., 2010. Oxidative stress and the regulation of complement activation in human glaucoma. Investig. Ophthalmol. Vis. Sci. 51, 5071–5082. Valiente-Soriano, F.J., Garcı´a-Ayuso, D., Ortı´n-Martı´nez, A., Jim
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CHAPTER 1 AOHT preferentially damages the cone pathway

Valiente-Soriano, F.J., Ortı´n-Martı´nez, A., Di Pierdomenico, J., Garcı´a-Ayuso, D., GallegoOrtega, A., Miralles de Imperial-Ollero, J.A., Jim
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erez, M.P., Agudo-Barriuso, M., 2020. Tracing the retina to analyze the integrity and phagocytic capacity of the retinal pigment epithelium. Sci. Rep. 10, 7273. Vecino, E., Urcola, H., Bayon, A., Sharma, S.C., 2018. Ocular hypertension/glaucoma in minipigs: episcleral veins cauterization and microbead occlusion methods. Methods Mol. Biol. 1695, 41–48. Vidal-Sanz, M., Bray, G.M., Villegas-P
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es-Trigueros, M., Whiteley, S.J.O., Sauv
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es-Trigueros, M., Mayor-Torroglosa, S., Salinas-Navarro, M., Alarco´n-Martı´nez, L., Villegas-P
erez, M.P., 2007. Neuroprotection of retinal ganglion cell function and their central nervous system targets. Eye 21, S42–S45. Vidal-Sanz, M., Salinas-Navarro, M., Nadal-Nicola´s, F.M., Alarco´n-Martı´nez, L., ValienteSoriano, F.J., Miralles de Imperial, J., Avil
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CHAPTER

Genetics of primary open-angle glaucoma and its endophenotypes

2

Yoichi Sakurada*, Fumihiko Mabuchi, and Kenji Kashiwagi Department of Ophthalmology, Faculty of Medicine, University of Yamanashi, Kofu, Japan *Corresponding author: Tel.: +81-273-9657; Fax: +81-273-6757, [email protected]

Abstract Glaucoma is a neurodegenerative disorder characterized by the loss of retinal ganglion cells and optic nerve fibers, resulting in the loss of visual field. Primary open-angle glaucoma (POAG) is the most prevalent subtype of glaucoma. Recent genome-wide association studies (GWASs) identified more than 100 variants associated with POAG and multiple loci associated with endophenotypes including the disc area, vertical cup-to-disc ratio (VCDR), and intraocular pressure (IOP). Especially, several GWASs reported the association between VCDR and variants near CDKN2B/CDKN2B-AS1, ATOH7, and CHEK2, and between IOP and variants near TMCO1, CAV1/CAV2, GAS7, and ARHGEF12. However, the effect of each variant on endophenotypes is modest; therefore, it is useful to construct a genetic risk score (GRS) based on the effect on endophenotypes by combining susceptible genetic variants. Several studies demonstrated that higher GRS was closely associated with endophenotypes including the VCDR, IOP, and age of diagnosis. Henceforth, by quantifying GRS, identification of high risk group before the disease onset, prediction of visual prognosis and early intervention may be possible.

Keywords Primary open-angle glaucoma, Genome-wide association studies, Endophenotypes, Genetic risk score, Vertical cup-to-disc ratio, Intraocular pressure

1 Introduction As the population of aging society increased, the number of people affected by common diseases increased substantially. Glaucoma is the leading cause of irreversible blindness worldwide. Globally, the population which got blinded in 2015 and 2020 by glaucoma is estimated to be 2.9 and 3.2 million, respectively (Flaxman et al., 2017). A recent survey reported that the number of people affected by glaucoma will increase to 112 million, globally in 2040 (Tham et al., 2014). Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.06.001 © 2020 Elsevier B.V. All rights reserved.

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CHAPTER 2 Genetics of primary open-angle glaucoma

Glaucoma is an optic neuropathy characterized by progressive loss of retinal ganglion cells and optic nerve fibers resulting in progressive visual field loss. Depending on the degree of iridocorneal angle closure, glaucoma can be classified into two subtypes: primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG). Moreover, POAG can be subdivided into normal tension glaucoma (NTG) and high-tension glaucoma (HTG) depending on intraocular pressure (IOP). Although POAG is the most common subtype in glaucoma, the pathogenesis of POAG has not been fully understood. The most important risk factor is IOP. Besides IOP, several risk factors, including ethnicity, age, refractive error, and family history have also been reported clinically. To date, a few gene mutations have been identified to be causative for POAG (Awadalla et al., 2015; Rezaie et al., 2002; Stone et al., 1997). However, cases of POAG caused by these gene mutations account for less than 5% of all POAG cases; in most cases, POAG is presumed to be a complex disease attributed to multiple predisposing genetic variants. Since the first publication regarding a genome-wide association study (GWAS) on POAG in 2009 (Nakano et al., 2009), subsequent large-scale reports have identified over 100 novel variants susceptible to POAG. Several genetic variants were found to be associated with endophenotypes including optic disc parameter and IOP. Moreover, recent studies identified pathologic genes involved glaucoma and upstream regulators using microarray (Feng and Xu, 2019; Moazzeni et al., 2019). In this review, we summarize the results of the recent GWASs on POAG and endophenotypes associated with glaucoma.

2 Genome-wide association studies on POAG endophenotypes Although approximately 30 genetic variants susceptible to POAG were identified by 2017 (Sakurada and Mabuchi, 2018), the scale in recent GWASs were much larger compared with the previous GWASs. In the last few years, over 100 novel variants were reported to reach the genome-wide significance (P < 5.0  10 8). However, it is difficult to make the best use of these variants in the clinical setting for preventive purpose. For this reason, recent GWASs focus on the investigation of variants associated with endophenotypes in POAG rather than the investigation of variants associated with POAG.

3 Disc area and vertical cup-to-disc ratio (VCDR) The first GWAS result of optic disc parameter including optic disc area and vertical cup-to-disc ratio (VCDR) was reported using Rotterdam cohorts (Ramdas et al., 2010). The results identified three loci associated with optic disc area: CDC7/ TGFBR3 region, ATOH7, and SALL1; and six loci associated with VCDR: CDKN2B,

3 Disc area and vertical cup-to-disc ratio (VCDR)

SIX1/SIX6, SCYL1, CHEK2, ATOH7, and DCLK1. Subsequent GWASs were performed and multiple loci were found to be associated with disc morphology. Tables 1 and 2 show previously identified genetic variants associated with the disc area and VCDR, respectively (Bonnemaijer et al., 2019; MacGregor et al., 2018; Ramdas et al., 2010; Springelkamp et al., 2014, 2017). Among these, variants near ATOH7 and CDC/TGFBR3 were strongly associated with disc area in a few GWASs. Table 1 Disc area associated genetic variants identified by genome-wide association studies. Near Gene

Chromosome

rs #

References

PRDM16 U6 CDC7/TGFBR3

1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 4 5 5 6 6 6 6 8 8 9 10 10 10

1:3046430 rs787541 rs1192415 rs4658101 1:169530520 rs11811982 rs12136690 rs56412756 rs1367187 rs9967780 rs4832012 rs1365902 rs3914468 rs2443724 rs11129176 rs1997404 rs9843102 rs77877421 rs115481915 rs72759609 rs5853139 rs2092524 rs12661045 rs2152876 rs9401928 8:88744441 rs6999835 rs10512176 rs12220165 rs1900004 rs7916410

Springelkamp et al. (2017) Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2017) Springelkamp et al. (2017) Springelkamp et al. (2017) Han et al. (2019) Han et al. (2019) Springelkamp et al. (2017) Han et al. (2019) Han et al. (2019) Han et al. (2019) Han et al. (2019) Springelkamp et al. (2017) Springelkamp et al. (2017) Springelkamp et al. (2017) Springelkamp et al. (2017) Han et al. (2019) Springelkamp et al. (2017) Han et al. (2019) Han et al. (2019) Han et al. (2019) Han et al. (2019) Han et al. (2019) Han et al. (2019) Springelkamp et al. (2017) Han et al. (2019) Han et al. (2019) Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2017)

FS/SELP CDC42BPA VANGL1 NAV1 DIRC3 MIR216B ATOH8 TEX41 LRP2 VGLL4 RARB COL8A1 ABI38P FOXP1 UGT8 PDZD2 LINC00461 KIF6 HSF2 CENPW RSPO3 DCAF4L2 PKIA ZCCHC6 CTNNA3 ATOH7

Continued

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CHAPTER 2 Genetics of primary open-angle glaucoma

Table 1 Disc area associated genetic variants identified by genome-wide association studies.—cont’d Near Gene

Chromosome

rs #

References

ARHGAP21

10 10 10 11 12 12 13 14 14 15 16 16 20 22 22

rs10764494 rs4748969 rs10882283 rs61101201 rs442376 rs76567987 rs9534439 rs34935520 rs61985972 rs60779155 rs1362756 rs1345467 rs6119893 rs5762752 rs56385951

Han et al. (2019) Bonnemaijer et al. (2019) Bonnemaijer et al. (2019) Springelkamp et al. (2017) Springelkamp et al. (2017) Han et al. (2019) Han et al. (2019) Springelkamp et al. (2017) Han et al. (2019) Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2017) Bonnemaijer et al. (2019) Springelkamp et al. (2017) Springelkamp et al. (2017)

RBP4 IMMP1L TMTC2 TSPAN11 LRCH1 SIX1/SIX6 DAAM ASB7 SALL1 C20orf112 CHECK2 CARD10

Table 2 Vertical cup-to-disc ratio associated genetic variants identified by genome-wide association studies. Near Gene

Chromosome

rs #

References

RERE RPE65 CDC7/TGFBR3

1 1 1 1 1 3 3 3 5 5 5 5 5 6 6 6 7

rs301801 rs1925953 rs4658101 rs1192414 rs10753787 rs2623325 rs6804624 rs10753787 rs72759609 rs17658229 rs11450336 rs7717697 rs115456027 rs868153 rs17756712 rs4960225 rs10274998

Ramdas et al. (2010) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2017) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2017) Bonnemaijer et al. (2019) Springelkamp et al. (2014) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2017)

F5 COL8A1 FLNB PDZD2 DUSP1 VCAN LINC00461 HSF2 EXOC2 RREB1 DGKB

3 Disc area and vertical cup-to-disc ratio (VCDR)

Table 2 Vertical cup-to-disc ratio associated genetic variants identified by genome-wide association studies.—cont’d Near Gene

Chromosome

rs #

References

PSCA CDKN2B/CDKN2BAS1

8 9 9 9 9 10 10

rs2920293 rs1063192 rs7865618 rs2157719 rs944801 rs1900004 rs1900005

SSSCA1

10 10 10

rs7072574 10:96008348 rs1346

ENO4 SCYL1 ADAMTS8

10 11 11

rs1681739 rs17146964 rs4936099

RPAP3 TMTC2

12 12 12 12 13 13 14 14 14 14 14 15 16 16 20 20 22

rs11168187 rs10862688 rs324780 rs7311936 rs7323428 13:36629905 rs10483727 rs4901977 rs80151512 rs2093210 14:23388793 rs4299136 rs1345467 16:51461915 rs6054374 rs6107845 rs1547014

22 22 22 22 7

rs5752773 rs5756813 rs2092172 rs2412973 rs59072263

Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2014) Springelkamp et al. (2017) MacGregor et al. (2018) Ramdas et al. (2010) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2014) Springelkamp et al. (2017) MacGregor et al. (2018) Springelkamp et al. (2017) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Ramdas et al. (2010) Springelkamp et al. (2014) Springelkamp et al. (2017) Springelkamp et al. (2014) Springelkamp et al. (2017) Bonnemaijer et al. (2019) Blue Mountains Eye and Wellcome Trust Case Control (2013)

ATOH7

PLCE1

FAM101A12 DCLK1 SIX1/SIX6

RBM23 ASB7 SALL1 BMP2 CHEK2

CARD10 HORMAD2 GLCCI1/ICA1

Continued

35

36

CHAPTER 2 Genetics of primary open-angle glaucoma

Table 2 Vertical cup-to-disc ratio associated genetic variants identified by genome-wide association studies.—cont’d Near Gene

Chromosome

rs #

References

ANGPT1

8 8 8 8 9 9

rs10505100 rs10105844 rs13270051 rs62520913 rs2487048 rs2472493

ABO

9

LMX1B/ FAM125B

9 9 9 9 9 9 9 10 10 10 10 11 11 11 11

rs8176741 rs8176743 rs945686 rs10760442 rs2286885 rs12377624 rs2224492 rs1570204 rs1831902 rs11014632 rs5785510 rs12778514 rs1222926 rs7944735 rs7940065 11:120357425 rs58073046

ADAMTS8 ETS1

11 11 11 11 11 11

rs199800298 rs2305013 rs12419342 rs79390637 rs55796939 rs7924522

LOC171391 RPLP2/PNPLA2 NR1H3 MADD MYBPC3 SPI1

11 11 11 11 11 11

rs4963156 rs10902223 rs10838681 rs326214 rs1052373 rs3740689

MacGregor et al. (2018) Choquet et al. (2018) Gao et al. (2018) Khawaja et al. (2018) Springelkamp et al. (2017) Springelkamp et al. (2015) MacGregor et al. (2018) Choquet et al. (2018) Springelkamp et al. (2017) Hysi et al. (2014) MacGregor et al. (2018) Gao et al. (2018) Nag et al. (2014) Khawaja et al. (2018) Choquet et al. (2018) Gao et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018) Gao et al. (2018) Springelkamp et al. (2017) Gao et al. (2018) Springelkamp et al. (2017) MacGregor et al. (2018) Springelkamp et al. (2015) Choquet et al. (2018) Gao et al. (2018) Hysi et al. (2014) Choquet et al. (2018) Springelkamp et al. (2017) MacGregor et al. (2018) Khawaja et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018)

FBXO32 ABCA1

GLIS3 FLJ41200/LIC00583 GPR158 ARID5B

Many genes PDDC1 ARHGEF12

RAPSN

3 Disc area and vertical cup-to-disc ratio (VCDR)

Table 2 Vertical cup-to-disc ratio associated genetic variants identified by genome-wide association studies.—cont’d Near Gene

Chromosome

rs #

References

SPI1/MIR4487 PSMC3/RAPSN CELF1 NDUFS3 PTPRJ

11 11 11 11 11 11 11 11 11 12

rs11824864 rs111228939 rs4752843 rs4147730 rs4752805 rs1681630 rs7946766 rs747782 rs2433414 rs7977237

Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Hysi et al. (2014) Hysi et al. (2014) Hysi et al. (2014) Khawaja et al. (2018) Choquet et al. (2018)

12 13 13 15 15

rs74481774 rs9552680 rs11616662 rs12926024 rs72755233

15 16 16 16 16

rs4775427 rs75828804 rs76953588 rs12926024 rs9938149

Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018) Choquet et al. (2018) Khawaja et al. (2018) Choquet et al. (2018) Gao et al. (2018) Choquet et al. (2018) Gao et al. (2018)

16 16 17 17

rs1874458 rs3743860 rs11656696 rs9913911

17 17 17 17 17 18 18 20 21

rs12150284 rs11078446 rs4790881 rs34629349 rs9038 rs150202082 rs11659764 rs3918508 rs2839082

ME3 LOC105369739/ ADAMTS20 TMEM119 LIC00424/BASP1P1 FOXO1 SMAD3 ADAMTS17 VPS13C ADAMTS18/NUDT7 BANP/ZNF469 LOC101928880/ ZNF469 CDH1 FANCA GAS

CRK SMG6 INCA1 SEPT9 TCF4 TCF4/LINC01415 LINC01734/LINC01370 COL6A1/COL6A2

Khawaja et al. (2018) Khawaja et al. (2018) van Koolwijk et al. (2012) Springelkamp et al. (2015) Springelkamp et al. (2017) MacGregor et al. (2018) Choquet et al. (2018) Gao et al. (2018) Huang et al. (2019) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018) Bonnemaijer et al. (2019) Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018)

37

38

CHAPTER 2 Genetics of primary open-angle glaucoma

Among variants associated with VCDR, genetic variants near ATOH7, CHEK2, and variants on chromosome 9 including CDKN2B and CDKN2B-AS1 were strongly associated. A recent GWAS reported more than 100 VCDR-associated variants (Craig et al., 2020).

4 Intraocular pressure (IOP) Elevated intraocular pressure (IOP) is a major and the only modifiable risk factor for development and progression of glaucoma. IOP is determined by the amount of fluid in the eyeball, which is maintained by the balance between aqueous humor production by the ciliary body and drainage through trabecular meshwork and uveoscleral outflow route. To date, several GWASs identified more than 80 genetic loci that were associated with IOP. Table 3 shows the list of genetic variants associated with IOP identified by GWASs (Blue Mountains Eye and Wellcome Trust Case Control, 2013; Bonnemaijer et al., 2019; Choquet et al., 2018; Gao et al., 2018; Huang et al., 2019; Hysi et al., 2014; Khawaja et al., 2018; MacGregor et al., 2018; Nag et al., 2014; Ozel et al., 2014; Springelkamp et al., 2014, 2015, 2017; van Koolwijk et al., 2012). Of these genetic variants, variants near TMCO1, CAV1/CAV2, GAS7, ARHGEF12 were reported to be associated with IOP in several GWASs. To date, several GWASs identified multiple genetic loci associated with optic disc parameter and IOP. Since there is a small effect of individual variants on endophenotypes, several investigators calculated genetic risk scores (GRS) /polygenic risk score (PRS) based on the multiple variants previously associated with POAG and/or endophenotypes (Mabuchi et al., 2017; Nannini et al., 2018). After investigation of 68 variants, previously associated with the VCDR, using Latino cohorts, it was reported that a higher GRS was associated with a higher VCDR even after compensating for traditional glaucoma risk factors. (Nannini et al., 2018) Recently, based on the investigation of variants influencing IOP, patients with POAG were divided into three groups depending on PRS, and a dose- dependent association between PRS and maximum IOP was reported. Moreover, it was reported that the mean age of diagnosis was lower in the high PRS group than in the low PRS group and high PRS group had more family members affected by glaucoma compared with the other groups.(Qassim et al., 2020). A recent report demonstrated that GRS related to optic nerve vulnerability rather than IOP elevation was associated with onset of POAG and GRS related to IOP rather than optic nerve vulnerability was associated with progression of POAG (Mabuchi et al., 2020).

4 Intraocular pressure (IOP)

Table 3 Intraocular pressure associated genetic variants identified by genomewide association studies. Gene (Nearest Gene) TMCO1

LOC100147773/ TMCO1 LOC440700/ TMCO1 PTCH2 LRIF1/DRAM2 HIVEP3 MIR548F3 RSPO1 COLEC11 SPTBN1 LTBP1 EFEMP1 ANTXR1 FMNL2 TNS1 COL4A3/ LOC654841 COL6A3 FNDC3B

RP11-78H24.1 DGKC/ LOC107986164/ TBCCD1 LINC01214/ TSC22D2 LPP KBTBD8/LRIG1

Chromosome

rs ID

References

1 1 1

rs10918274 rs4656461 rs7555523

1 1

rs7518099 rs7518099

Springelkamp et al. (2017) Hysi et al. (2014) van Koolwijk et al. (2012), Springelkamp et al. (2015), Gao et al. (2018) Ozel et al. (2014) MacGregor et al. (2018)

1

rs6668108

Choquet et al. (2018)

1 1 1 1 1 1 1 2 2 2 2 2 2 2 2

rs4656461 rs7525308 rs1282146 rs1866758 rs596169 rs1700874 rs4074961 rs201143466 rs4514918 rs115179432 rs7426380 rs6732795 rs55692468 rs1035673 rs143937055

Gao et al. (2018) Huang et al. (2019) Huang et al. (2019) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018) Khawaja et al. (2018) Huang et al. (2019) Huang et al. (2019) Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Choquet et al. (2018)

2 3

rs7599762 rs7635832

3 3 3 3

rs4380432 rs6445055 rs9853115 rs9853115

Choquet et al. (2018) Springelkamp et al. (2017), Choquet et al. (2018) Gao et al. (2018) Hysi et al. (2014) Bonnemaijer et al. (2019) MacGregor et al. (2018), Choquet et al. (2018)

3

rs11710845

Choquet et al. (2018)

3 3

rs13076750 rs6781336

Choquet et al. (2018) Khawaja et al. (2018) Continued

39

40

CHAPTER 2 Genetics of primary open-angle glaucoma

Table 3 Intraocular pressure associated genetic variants identified by genomewide association studies.—cont’d Gene (Nearest Gene)

Chromosome

rs ID

References

DGKG AFAP1

3 4

rs9853115 rs28795989

4 4 5 5 5 5 5

rs6816389 rs17527016 rs61394862 rs368503 rs48675762 rs73220188 rs1363919

Khawaja et al. (2018) MacGregor et al. (2018), Choquet et al. (2018) Gao et al. (2018) Choquet et al. (2018) MacGregor et al. (2018) Khawaja et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018)

6

rs2745572

MacGregor et al. (2018), Choquet et al. (2018)

6

rs2935057

MacGregor et al. (2018)

6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7

rs2073006 rs7739648 rs113985657 rs1396046 rs17752199 rs82616083 rs141917145 rs9494457 rs10258482 rs10262524 rs10281637 rs2024211 rs4236601 rs8940 rs1013278 rs10230941 rs1509922 rs6968419 rs6946058 rs59072263

8 8 8

rs10505100 rs10105844 rs13270051

MacGregor et al. (2018) Gao et al. (2018) Khawaja et al. (2018) Choquet et al. (2018) Khawaja et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Khawaja et al. (2018) Hysi et al. (2014) Hysi et al. (2014) Springelkamp et al. (2017) MacGregor et al. (2018) Gao et al. (2018) Gao et al. (2018) MacGregor et al. (2018) Khawaja et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018) Blue Mountains Eye and Wellcome Trust Case Control (2013) MacGregor et al. (2018) Choquet et al. (2018) Gao et al.(2018)

PITX2/C4orf32 ANKH MOCS2/FST FBXL17/FER LOC257396/ FST LOC102723944/ GMDS/ FOXF2/ FOXCUT LOC101929614/ LOC105378153 EXOC2

PKHD1 FAM46A/IBTK RFLP48 PDE7B CAV1 CAV1/CAV2

CAV2 CTTNBP2/CFTR SEMA3C/HGF TFEC/TES GLCCI1/ICA1

ANGPT1

4 Intraocular pressure (IOP)

Table 3 Intraocular pressure associated genetic variants identified by genomewide association studies.—cont’d Gene (Nearest Gene)

Chromosome

rs ID

References

FBXO32 ABCA1

8 9 9

rs62520913 rs2487048 rs2472493

ABO

9

LMX1B

9 9 9 9 9 9

rs8176741 rs8176743 rs945686 rs10760442 rs2224492 rs1570204 rs2286885 rs1831902

Khawaja et al. (2018) Springelkamp et al. (2017) Springelkamp et al. (2015), MacGregor et al. (2018), Choquet et al. (2018) Springelkamp et al. (2017) Hysi et al. (2014) MacGregor et al. (2018) Gao et al. (2018) Choquet et al. (2018) Gao et al. (2018) Nag et al. (2014) Choquet et al. (2018)

9 10 10 10 10 10 11 11 11 11

rs12377624 rs11014632 rs5785510 rs12778514 rs66479974 rs1222926 rs7944735 rs7940065 11:120357425 rs58073046

RAPSN PSMC3/RAPSN ADAMTS8 ETS1

11 11 11 11 11 11

rs199800298 rs2305013 rs12419342 rs79390637 rs55796939 rs7924522

LOC171391 RPLP2/PNPLA2 NR1H3 MADD MYBPC3 SPI1 SPI1/MIR4487 PSMC3/RAPSN CELF1

11 11 11 11 11 11 11 11 11

rs4963156 rs10902223 rs10838681 rs326214 rs1052373 rs3740689 rs11824864 rs111228939 rs4752843

GLIS3 FAM125B FLJ41200/ LIC00583 LMX1B GPR158 ARID5B CYP26A1/MYOF Many genes PDDC1 ARHGEF12

Khawaja et al. (2018) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018) Choquet et al. (2018) Gao et al. (2018) Springelkamp et al. (2017) Gao et al. (2018) Springelkamp et al. 2017) MacGregor et al. (2018), Springelkamp et al. (2015) Choquet et al. (2018) Gao et al. (2018) Hysi et al. (2014) Choquet et al. (2018) Springelkamp et al. (2017) MacGregor et al. (2018), Khawaja et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Gao et al. (2018) Continued

41

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CHAPTER 2 Genetics of primary open-angle glaucoma

Table 3 Intraocular pressure associated genetic variants identified by genomewide association studies.—cont’d Gene (Nearest Gene) NDUFS3 PTPRJ

NUP160/PTPRJ ME3 LOC105369739/ ADAMTS20 TMEM119 LIC00424/ BASP1P1 FOXO1 SMAD3 ADAMTS17 VPS13C ADAMTS18/ NUDT7 BANP/ZNF469 LOC101928880/ ZNF469 CDH1 FANCA GAS

CRK SMG6 INCA1 SEPT9 TCF4 TCF4/ LINC01415 LINC01734/ LINC01370 COL6A1/ COL6A2

Chromosome

rs ID

References

11 11 11 11 11 11 12

rs4147730 rs4752805 rs1681630 rs7946766 rs747782 rs2433414 rs7977237

Gao et al. (2018) Gao et al. (2018) Hysi et al. (2014) Hysi et al. (2014) Hysi et al. (2014) Khawaja et al. (2018) Choquet et al. (2018)

12 13

rs74481774 rs9552680

Choquet et al. (2018) Choquet et al. (2018)

13 15 15

rs11616662 rs12926024 rs72755233

15 16

rs4775427 rs75828804

Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018), Choquet et al. (2018) Khawaja et al. (2018) Choquet et al. (2018)

16 16 16

rs76953588 rs12926024 rs9938149

Gao et al. (2018) Choquet et al. (2018) Gao et al. (2018)

16 16 17 17

rs1874458 rs3743860 rs11656696 rs9913911

17 17 17 17 17 18 18

rs12150284 rs11078446 rs4790881 rs34629349 rs9038 rs150202082 rs11659764

Khawaja et al. (2018) Khawaja et al. (2018) van Koolwijk et al. (2012) Springelkamp et al. (2015), Springelkamp et al. (2017), MacGregor et al. (2018), Choquet et al. (2018) Gao et al. (2018) Huang et al. (2019) Choquet et al. (2018) Choquet et al. (2018) Gao et al. (2018) Bonnemaijer et al. (2019) Choquet et al. (2018)

20

rs3918508

Choquet et al. (2018)

21

rs2839082

Choquet et al. (2018)

Reference

5 Summary Although POAG is a multifactorial eye disease, accurately quantifying an individual’s GRS might enable the prediction of development and progression of POAG and visual prognosis. However, the effects of susceptible variants on POAG and its endophenotypes varies ethnically and the allele frequency is different depending on ethnicities. Therefore, it is important to construct a GRS specific to each ethnicity and collect detailed and precise endophenotype information along with GRS.

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Rezaie, T., Child, A., Hitchings, R., Brice, G., Miller, L., Coca-Prados, M., Heon, E., Krupin, T., Ritch, R., Kreutzer, D., Crick, R.P., Sarfarazi, M., 2002. Adult-onset primary open-angle glaucoma caused by mutations in optineurin. Science 295, 1077–1079. Sakurada, Y., Mabuchi, F., 2018. Genetic risk factors for glaucoma and exfoliation syndrome identified by genome-wide association studies. Curr. Neuropharmacol. 16, 933–941. Springelkamp, H., Hohn, R., Mishra, A., Hysi, P.G., Khor, C.C., Loomis, S.J., Bailey, J.N., Gibson, J., Thorleifsson, G., Janssen, S.F., Luo, X., Ramdas, W.D., Vithana, E., Nongpiur, M.E., Montgomery, G.W., Xu, L., Mountain, J.E., Gharahkhani, P., Lu, Y., Amin, N., Karssen, L.C., Sim, K.S., Van Leeuwen, E.M., Iglesias, A.I., Verhoeven, V.J., Hauser, M.A., Loon, S.C., Despriet, D.D., Nag, A., Venturini, C., Sanfilippo, P.G., Schillert, A., Kang, J.H., Landers, J., Jonasson, F., Cree, A.J., Van Koolwijk, L.M., Rivadeneira, F., Souzeau, E., Jonsson, V., Menon, G., Blue Mountains Eye Study—GWAS Group, Weinreb, R.N., De Jong, P.T., Oostra, B.A., Uitterlinden, A.G., Hofman, A., Ennis, S., Thorsteinsdottir, U., Burdon, K.P., NEIGHBORHOOD Consortium, Wellcome Trust Case Control Consortium, Spector, T.D., Mirshahi, A., Saw, S.M., Vingerling, J.R., Teo, Y.Y., Haines, J.L., Wolfs, R.C., Lemij, H.G., Tai, E.S., Jansonius, N.M., Jonas, J.B., Cheng, C.Y., Aung, T., Viswanathan, A.C., Klaver, C.C., Craig, J.E., MacGregor, S., Mackey, D.A., Lotery, A.J., Stefansson, K., Bergen, A.A., Young, T.L., Wiggs, J.L., Pfeiffer, N., Wong, T.Y., Pasquale, L.R., Hewitt, A.W., Van Duijn, C.M., Hammond, C.J., 2014. Meta-analysis of genome-wide association studies identifies novel loci that influence cupping and the glaucomatous process. Nat. Commun. 5, 4883. Springelkamp, H., Iglesias, A.I., Cuellar-Partida, G., Amin, N., Burdon, K.P., Van Leeuwen, E.M., Gharahkhani, P., Mishra, A., Van Der Lee, S.J., Hewitt, A.W., Rivadeneira, F., Viswanathan, A.C., Wolfs, R.C., Martin, N.G., Ramdas, W.D., Van Koolwijk, L.M., Pennell, C.E., Vingerling, J.R., Mountain, J.E., Uitterlinden, A.G., Hofman, A., Mitchell, P., Lemij, H.G., Wang, J.J., Klaver, C.C., Mackey, D.A., Craig, J.E., Van Duijn, C.M., MacGregor, S., 2015. ARHGEF12 influences the risk of glaucoma by increasing intraocular pressure. Hum. Mol. Genet. 24, 2689–2699. Springelkamp, H., Iglesias, A.I., Mishra, A., Hohn, R., Wojciechowski, R., Khawaja, A.P., Nag, A., Wang, Y.X., Wang, J.J., Cuellar-Partida, G., Gibson, J., Bailey, J.N., Vithana, E.N., Gharahkhani, P., Boutin, T., Ramdas, W.D., Zeller, T., Luben, R.N., Yonova-Doing, E., Viswanathan, A.C., Yazar, S., Cree, A.J., Haines, J.L., Koh, J.Y., Souzeau, E., Wilson, J.F., Amin, N., Muller, C., Venturini, C., Kearns, L.S., Kang, J.H., NEIGHBORHOOD Consortium, Tham, Y.C., Zhou, T., Van Leeuwen, E.M., Nickels, S., Sanfilippo, P., Liao, J., Van Der Linde, H., Zhao, W., Van Koolwijk, L.M., Zheng, L., Rivadeneira, F., Baskaran, M., Van Der Lee, S.J., Perera, S., De Jong, P.T., Oostra, B.A., Uitterlinden, A.G., Fan, Q., Hofman, A., Tai, E.S., Vingerling, J.R., Sim, X., Wolfs, R.C., Teo, Y.Y., Lemij, H.G., Khor, C.C., Willemsen, R., Lackner, K.J., Aung, T., Jansonius, N.M., Montgomery, G., Wild, P.S., Young, T.L., Burdon, K.P., Hysi, P.G., Pasquale, L.R., Wong, T.Y., Klaver, C.C., Hewitt, A.W., Jonas, J.B., Mitchell, P., Lotery, A.J., Foster, P.J., Vitart, V., Pfeiffer, N., Craig, J.E., Mackey, D.A., Hammond, C.J., Wiggs, J.L., Cheng, C.Y., Van Duijn, C.M., MacGregor, S., 2017. New insights into the genetics of primary open-angle glaucoma based on meta-analyses of intraocular pressure and optic disc characteristics. Hum. Mol. Genet. 26, 438–453. Stone, E.M., Fingert, J.H., Alward, W.L., Nguyen, T.D., Polansky, J.R., Sunden, S.L., Nishimura, D., Clark, A.F., Nystuen, A., Nichols, B.E., Mackey, D.A., Ritch, R.,

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Kalenak, J.W., Craven, E.R., Sheffield, V.C., 1997. Identification of a gene that causes primary open angle glaucoma. Science 275, 668–670. Tham, Y.C., Li, X., Wong, T.Y., Quigley, H.A., Aung, T., Cheng, C.Y., 2014. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology 121, 2081–2090. Van Koolwijk, L.M., Ramdas, W.D., Ikram, M.K., Jansonius, N.M., Pasutto, F., Hysi, P.G., MacGregor, S., Janssen, S.F., Hewitt, A.W., Viswanathan, A.C., Ten Brink, J.B., Hosseini, S.M., Amin, N., Despriet, D.D., Willemse-Assink, J.J., Kramer, R., Rivadeneira, F., Struchalin, M., Aulchenko, Y.S., Weisschuh, N., Zenkel, M., Mardin, C.Y., Gramer, E., Welge-Lussen, U., Montgomery, G.W., Carbonaro, F., Young, T.L., DCCT/EDIC Research Group, Bellenguez, C., McGuffin, P., Foster, P.J., Topouzis, F., Mitchell, P., Wang, J.J., Wong, T.Y., Czudowska, M.A., Hofman, A., Uitterlinden, A.G., Wolfs, R.C., De Jong, P.T., Oostra, B.A., Paterson, A.D., Wellcome Trust Case Control Consortium, Mackey, D.A., Bergen, A.A., Reis, A., Hammond, C.J., Vingerling, J.R., Lemij, H.G., Klaver, C.C., Van Duijn, C.M., 2012. Common genetic determinants of intraocular pressure and primary open-angle glaucoma. PLoS Genet. 8, e1002611.

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A broad perspective on the molecular regulation of retinal ganglion cell degeneration in glaucoma

3 G€ulg€un Tezel*

Department of Ophthalmology, Vagelos College of Physicians and Surgeons, Columbia University, Edward S. Harkness Eye Institute, New York, NY, United States *Corresponding author: Tel.: +1-212-342-3841, e-mail address: [email protected]

Abstract Glaucoma is a complex neurodegenerative disease involving RGC axons, somas, and synapses at dendrites and axon terminals. Recent research advancements in the field have revealed a bigger picture of glaucomatous neurodegeneration that encompasses multiple stressors, multiple injury sites, multiple cell types, and multiple signaling pathways for asynchronous degeneration of RGCs during a chronic disease period. Optic nerve head is commonly viewed as the critical site of injury in glaucoma, where early injurious insults initiate distal and proximal signaling for axonal and somatic degeneration. Despite compartmentalized processes for degeneration of RGC axons and somas, there are intricate interactions between the two compartments and mechanistic overlaps between the molecular pathways that mediate degeneration in axonal and somatic compartments. This review summarizes the recent progress in the molecular understanding of RGC degeneration in glaucoma and highlights various etiological paths with biomechanical, metabolic, oxidative, and inflammatory components. Through this growing body of knowledge, the glaucoma community moves closer toward causative treatment of this blinding disease.

Keywords Glaucoma, Molecular signaling, Neurodegeneration, Neuroinflammation, Optic nerve axons, Retinal ganglion cells

1 Complexity of RGC degeneration in glaucoma Glaucoma is a chronic neurodegenerative disease characterized by progressive loss of retinal ganglion cell (RGC) somas, axons, and synapses. Despite continued basic and clinical research to better understand and treat glaucoma, many aspects of Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.05.027 © 2020 Elsevier B.V. All rights reserved.

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neurodegeneration are poorly understood, and glaucoma remains a leading cause of blindness, affecting approximately 80 million people, worldwide. Evidently, the etiological framework of glaucomatous neurodegeneration involves a complex interplay of various triggers. Elevated intraocular pressure (IOP) and aging are the most prevalent stressors for RGCs in glaucoma. Since the IOP-related tissue stress, at any magnitude, increases the susceptibility for disease progression and vision loss, glaucoma treatment has long aimed to lower IOP. Yet, despite effective lowering of IOP, neurodegeneration may continue to progress. Although many of the patients with primary open-angle glaucoma typically have elevated IOP, some patients do not, or some patients with ocular hypertension never develop glaucoma. After years of extensive research, it has become clear that besides elevated IOP, multiple additional factors (either extrinsic or intrinsic to RGCs) also influence the susceptibility of these crucial neurons to injury. Evidently, complex processes of glaucomatous neurodegeneration exhibit biomechanical, metabolic, oxidative, and inflammatory components. By considering its etiological complexity, currently available treatments for glaucoma are only palliative, but not an effective cure for this blinding disease, and once the critical point of pathogenic processes are reached, irreversible vision loss is inevitable. This age-related disease is more common in some families that present genetic susceptibility to adult-onset glaucoma. However, the association of identified gene mutations to the glaucoma phenotype is generally low. It is therefore viewed that there are polygenic effects and complex interactions between genetic, epigenetic, and environmental factors (Libby et al., 2005a; Wiggs and Pasquale, 2017). Indeed, epigenetic mechanisms have been increasingly associated with transcriptional activation or repression in animal models. For example, the early gene silencing detected prior to RGC loss in DBA/2J mice with hereditary glaucoma was linked to histone deacetylase activity (Pelzel et al., 2012). Epigenetic modifications were also implicated in pro-fibrotic processes in the glaucomatous optic nerve head (McDonnell et al., 2014; Park et al., 2017). In addition, increased DNA methylation and transcriptional repression were suggested to affect the molecular balance between cell survival and death signals in human glaucoma (Yang et al., 2011). Different experimental platforms have extensively been used to analyze glaucoma-related alterations in gene/protein expression, to investigate molecular pathways of neurodegeneration, and to pinpoint potential treatment targets and biomarkers. Accumulating datasets from transcriptome (Park et al., 2019), proteome (Tezel, 2014), or metabolome (Chauhan et al., 2019) analyses of animal models or human donor tissues have provided hypothesis-generating frameworks of molecular networks. These datasets are being translated into a better molecular understanding of glaucomatous neurodegeneration, and various outcome molecules are being tested as new treatment targets. This review summarizes the recently collected molecular information. While progressing toward improved molecular understanding and causative treatment of glaucomatous neurodegeneration, ongoing research in the field also provides a more realistic perspective on many challenging research aspects. Although glaucomatous neurodegeneration occurs throughout the visual pathway from the

1 Complexity of RGC degeneration in glaucoma

retina to the brain, the optic nerve head is recognized as the critical early site of injury. However, early retinal alterations, including early pruning of RGC dendrites, soma shrinkage, and synapse loss, may accompany, or even precede, axon degeneration. It is for this reason that ongoing research still questions as to whether glaucomatous neurodegeneration independently arises from both RGC axons and somas. Neurodegeneration in glaucoma is processed through distinct molecular programs in different subcellular regions, which include multiple signaling pathways running parallel, or working together. Optic nerve axons appear to be vulnerable to glaucoma-related stressors at the optic nerve head, and a distal axonopathy is processed by Wallerian degeneration, and perhaps also by dying back. However, degeneration of RGC somas and proximal axons (a segment from the RGC soma to the optic nerve head) are processed differently from degeneration of distal axons. Early dynamic processes for dendritic and synaptic pruning are also distinct from degenerative processes in axons and somas. Despite compartmentalized processes for RGC degeneration, accumulating data also indicate time-dependent mechanistic overlaps and intricate interplays between the molecular pathways that mediate neurodegeneration in different subcellular compartments of RGCs (Fig. 1), which is yet to be elucidated. Another challenge of glaucoma research is the asynchrony of neurodegeneration that does not involve all RGCs at once. Multiple extrinsic neurotoxic stimuli and intrinsic adaptive/protective responses affect the cellular homeostasis, and a stressor threshold determines the individual susceptibility of RGCs to injury. Depending on multiple factors (subtype of RGCs, spatial differences, severity of insults to an individual RGC, contribution of other cell types or specific molecular pathways, and more), the timing and magnitude of the outcome may vary. Consequently, at a given time point in the course of glaucomatous neurodegeneration, different RGCs present different states of stress or injury. The asynchrony of RGC degeneration makes the precise dissection of earliest molecular events highly challenging. An even more challenging research aspect is related to the involvement of multiple cell types in glaucomatous neurodegeneration. While RGCs are specific victims of neurodegeneration in glaucoma, temporal and spatial responses of other cell types, mainly including glia, are also decisive for glaucomatous neurodegeneration. Two major classes of glial cells that comprise of astroglia (including astrocytes and M€ uller glia in the retina, and astrocytes, lamina cribrosa cells, and oligodendrocytes in the optic nerve) and microglia profoundly respond to glaucoma-related stressors through a variety of signaling cascades. Many contrasting facets of neuron-glia interactions, neurosupportive or neurodestructive, are commonly viewed as critical determinants of RGC susceptibility to injury. Owing to rapidly produced and dynamic responses of many different cell types, molecular characterization of precise pathogenic processes requires cell type-specific analysis. To overcome this challenge, experimental studies employ transcriptomic or proteomic analysis of the isolated samples of specific cell types (Chintalapudi et al., 2016; Park et al., 2019; Tezel et al., 2010, 2012). Single cell-based advanced technologies that become increasingly available for molecular analysis of single cells, cell type-targeting viral vectors for delivery of specific gene-based treatments, and cell type-targeting

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FIG. 1 Neurodegeneration in glaucoma involves RGC axons, somas, and synapses at dendrites and axon terminals. The etiological framework of glaucomatous neurodegeneration encompasses multiple stressors (including elevated IOP, aging, genetic, epigenetic, systemic factors), multiple injury sites (optic nerve head, retina, brain), multiple cell types (including glial cells, vascular cells), and multiple signaling pathways for asynchronous degeneration of RGCs during a chronic disease period. A stressor threshold determines the individual susceptibility of RGCs to injury. Optic nerve head is the critical site of injury, and early injury of axons at the optic nerve head can initiate distal and proximal signaling for axonal and somatic degeneration of RGCs. A distal axonopathy is processed by Wallerian degeneration and dying back; however, degeneration of the proximal axon segment appears to be secondary to the apoptosis of RGC soma (that is processed through intrinsic/mitochondrial and extrinsic/dead receptor-mediated pathways). Despite compartmentalized molecular programs for degeneration of RGC axons and somas, there are mechanistic overlaps between the degeneration of RGC axons and somas, which include biomechanical, metabolic, oxidative, and inflammatory components.

2 Injury of RGC axons at the optic nerve head

conditional transgenic models also offer excellent tools to gain cell type-specific mechanistic information. Given the complexity of cell types involved in glaucomatous neurodegeneration, more work is necessary to precisely define the molecular components and the sequence of cell type-specific events and their interactions in the process of RGC degeneration. Since axon injury is a key insult that drives RGC degeneration, many of the recent studies of molecular signaling have utilized the acute models of optic nerve axon injury. However, glaucomatous neurodegeneration is different from those models in the magnitude and time course of insults to RGCs, and additional studies of experimental glaucoma models are needed to characterize glaucoma-specific molecular pathways. Regardless, susceptibility of RGCs to structural and functional degeneration differs across different species, strains, or different models of experimental glaucoma, as being supportive of individual differences in disease generation. In fact, current animal models of glaucoma are also imperfect simulators of human disease, thereby requiring careful validation of experimental data with clinical imaging-based data and data from postmortem human samples, when possible. When seeing the big picture of glaucoma in light of recent research achievements, it is apparent that glaucomatous neurodegeneration involves multiple stressors, multiple injury sites, multiple cell types, and multiple dynamic processes during the chronic disease period. This review outlines the current knowledge of molecular processes that regulate RGC degeneration in glaucoma, with emphasis on selected recent publications.

2 Injury of RGC axons at the optic nerve head Degeneration of RGC axons at the optic nerve and apoptosis of RGC somas are pivotal features of glaucoma. An early critical site of injury is thought to be at the optic nerve head where elevated IOP may generate biomechanical and vascular stress on RGC axons when they exit the eye by passing through the openings of lamina cribrosa. This unique structure consisting of a parallel series of connective tissue plates provides mechanical support to axon bundles and also constitutes a scaffold for different cell types, including astrocytes. Elevated IOP-related structural reconfiguration of the lamina cribrosa is evident by the backward bowing and enlargement of optic disk cupping in glaucomatous eyes. Clinical presentation of glaucoma is also characterized by early arcuate defects in retinal nerve fibers and arcuate scotomas of the corresponding visual fields, all of which support a regional insult of axon bundles at the optic nerve head. Experimental studies of animal models similarly localize the initial injury site to optic nerve head, where the first morphologically detectable damage occurs, and axons degenerate earlier than the apoptosis of RGC somas in ocular hypertensive animals (Buckingham et al., 2008; Howell et al., 2007; Soto et al., 2011). According to a long-standing view of glaucoma, elevated IOP-generated local mechanical stress (force/area) and increased stretch/strain (force-induced deformation) within and across the lamina and the peripapillary sclera result in an increase in the translaminar pressure gradient and create a damaging force on RGC axons and

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capillaries at the optic nerve head. This biomechanical hypothesis links the cytoarchitecture and biochemistry of the optic nerve head to transduction of IOP-related stress to axons and initiation of a series of neurodegenerative processes (Burgoyne et al., 2005). By changing the translaminar and peripapillary sclera-derived stress, compliance or stiffness of the sclera may influence the individual susceptibility to IOPrelated biomechanical injury (Murienne et al., 2015). Biomechanical properties of the sclera also link the racial differences in extracellular matrix components to the racial differences in glaucoma susceptibility, as a greater elastic component of the sclera may likely prone tissues to deformation even under normal IOP (Park et al., 2017). Apparently, scleral biomechanics are critical not only for generating the stress experienced by optic nerve axons but also for mediating the stress responses of glial cells and vascular cells, as discussed later below. Although, many components of the optic nerve head structure determine the topography of RGC degeneration in human glaucoma, collagenous plates of the lamina cribrosa are not well-developed in rodents as in human or non-human primates, and the mechanical support to axon bundles is maintained by a network of astroglial processes, called glia lamina (Howell et al., 2007). Yet, the topography of RGC damage in rodents, which presents as pie-shaped wedges radiating from the optic nerve head to the periphery, matches well with the localized injury of axon bundles at the glial lamina. A similar pattern of ocular hypertension-induced RGC injury, regardless of the structural differences of optic nerve head, suggests that the lamina cribrosa plates are not required to induce glaucomatous damage; however, cellular (mainly astrocyte-driven) and pro-fibrotic processes create the damaging forces at the optic nerve head. It is widely recognized that besides IOP-related mechanical compression, glial and vascular components also have significant impacts on axonal vulnerability to injury (Son et al., 2010). As evident from their profound responses, glial cells, as well as RGCs, are disturbed by glaucomatous tissue stress. Early activation responses of astrocytes in glaucoma, which may be detectable prior to axon loss (Qu and Jakobs, 2013), is characterized by a series of morphological, molecular, and functional alterations (Lye-Barthel et al., 2013; Tezel et al., 2012). This state, termed reactive astrogliosis, is prominently detectable in the retina and optic nerve head of human donor eyes and animal models with glaucoma (Son et al., 2010; Tezel and Wax, 2002). Reactive astrogliosis may initially be protective by insulating uninjured axons, providing trophic and metabolic support, and promoting tissue repair after injury; however, prolonged glial responses ultimately convert to damaging forces. Astrocyte responses appear to be crucial for amplification and transduction of the IOP-generated stress to axons. By sensing the IOP-induced deformation, astrocytes produce increased amounts of extracellular matrix molecules as an early response to ocular hypertension. Besides increased accumulation of extracellular matrix, an imbalance between the generation of matrix metalloproteinases and their inhibitors may also contribute to pro-fibrotic processes. As evident from biomechanical studies of the glaucomatous optic nerve head, the astroglial responses mediating the extracellular matrix remodeling increase the biomechanical stress and strain on optic nerve axons (Roberts et al., 2010). While the vascular hypothesis proposes

3 Molecularly distinct compartmentalized processes for RGC

IOP-related direct mechanical stress on blood vessels at the optic nerve head, astrocyte responses also distress microcapillaries. Since the extracellular matrix molecules produced by astrocytes form the astrocyte-derived basal lamina that surrounds RGC axons and microcapillaries at the optic nerve head, besides tissue stiffening, astrogliosis-related chronic alterations may also impact the signaling between astrocytes and axons or astrocytes and vascular endothelial cells (Burgoyne et al., 2005). In addition, the inflammatory and cytotoxic responses of reactive glia, or excess phagocytic activities, can boost neurodegenerative insults, as summarized later below. Furthermore, reactive astrocytes with increased activities, such as adhesion, migration, proliferation, and inflammatory signaling, execute a self-survival program that may result in inadequate structural, trophic, and metabolic support to RGC axons (Dai et al., 2012). Another cell type at the optic nerve head is named lamina cribrosa cells that can also sense pressure-related deformation via stretchactivated ion channels and promote pro-fibrotic processes in glaucoma (Irnaten et al., 2018). Moreover, the age-related increase in aggregation of misfolded/stressed proteins, increased accumulation of advanced glycation end-products, and extensive cross-linking processes (Tezel et al., 2007a) may further amplify tissue stiffening and augment the IOP-generated stress. It is also important to note that the agingassociated cellular deterioration diminishes the intrinsic capacity of axons to tolerate injurious environments. While initial injury signals are thought to originate from the optic nerve head, compartmentalized pathogenic processes govern glaucomatous degeneration of RGC axons and somas, as summarized in the next section.

3 Molecularly distinct compartmentalized processes for RGC degeneration Despite the fact that soma and axon health are eventually dependent on each other, unique molecular programs can independently control degeneration of RGC axons or apoptosis of RGC somas. Experimental data support that while RGC death occurs through Bax-dependent apoptosis, expression of slow Wallerian degeneration gene (WldS) by gain of function mutation delays axon degeneration, but not the RGC soma death after axon injury (Beirowski et al., 2008). Conversely, prevention of the RGC soma death in transgenic mice that are mutant for the pro-apoptotic gene, Bax, is not sufficient to prevent axon degeneration (Howell et al., 2007; Libby et al., 2005b). These experimental observations support self-autonomous destruction pathways for different RGC compartments. Molecularly distinct compartmentalized processes for degeneration of RGC axons and somas point to the necessity of combination treatments, or ideally multi-targeting single treatments, to protect both RGC axons and somas against glaucomatous neurodegeneration. After an insult to RGC axons at the optic nerve head, distal axon segments separated from the cell body rapidly degenerate. The WldS mutation slows the axon loss in experimentally induced rat glaucoma (Beirowski et al., 2008) or DBA/2J mice with hereditary glaucoma (Howell et al., 2007). The molecular signals responsible

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for the protection conferred by WldS remain unclear; however, this observation suggests a Wallerian-type mechanism for degeneration of distal axons. This axonal self-destruction program is characterized by cytoskeletal disassembly and granular degeneration of the axon distal to the injury site, which is followed by the infiltration of reactive glia for removal of axonal and myelin debris. DBA/2J mice with the WldS allele presented significantly protected axons with lessened loss of RGC dendrites and preserved electrophysiological activity (Howell et al., 2007). The protection of both axonal and somatic compartments of RGCs by WldS in DBA/2J glaucoma may support the concept that axon degeneration is an early key driver of glaucomatous neurodegeneration. Since neurodegenerative injury starts in the axon, saving the axon may prevent degeneration of the RGC soma in glaucoma. However, findings of another experimental study question this view. Transgenic expression of WldS in rats with experimentally induced ocular hypertension delayed RGC axon degeneration, but the soma loss continued (Beirowski et al., 2008). Experimental data from a different study of DBA/2J glaucoma proposed two separate stages of RGC degeneration in the same eye, involving the RGC atrophy and decreased gene expression, and the axon insult and distal axon degeneration (Soto et al., 2008). Differences in experimental paradigms, such as chronic or more acute injury to axons with or without IOP increase, addition of an ischemic component, or genetic differences, might affect the outcome of these experimental studies. Nevertheless, it remains unclear whether RGC soma death merely results from initial axon degeneration, or whether both the RGC axons and the somas are direct injury sites where degeneration arises independently. Experimental studies also hypothesized that a dying back process progressing in a distal-to-proximal pattern may contribute to axon degeneration in mouse glaucoma. This is because a vast majority of mildly affected axons with intact axon segments proximal and distal to the lesion site show early disconnection in the brain. The dying back refers to the gradual and progressive degeneration of these axons from the synaptic region toward the cell body after the disconnection of synaptic terminals (Crish et al., 2010; Howell et al., 2007). It is most likely that these different processes for distal axonopathy are not separable and take place in the same optic nerve. Despite prominent compartmentalization between axonal and somatic degeneration, there are also interactions between the two compartments. Axon degeneration precedes RGC soma death, and axonal injury signals lead to the degeneration of both axonal and somatic compartments; however, anterograde signals from the RGC soma may also promote axon degeneration in glaucoma. In Bax-deficient DBA/2J mice, axon segments distal to the laminar region degenerated, whereas the proximal axons attached to rescued RGC somas remained intact (Howell et al., 2007; Libby et al., 2005b). Thus, after axon injury, a molecular cascade drives axon degeneration in the distal portion; however, degeneration of the proximal axon segment appears to be secondary to the apoptosis of RGC soma. These observations stimulate additional studies to further assess the time course of anterograde and retrograde degeneration gradients and the intricate interactions of degenerative signals at different compartments of RGCs in experimental glaucoma. As reviewed in the following sections,

4 Mitochondrial dysfunction, a key pathogenic event in RGC degeneration

multiple pathogenic processes of glaucomatous neurodegeneration involve cytoskeletal disruption of axons, loss of neurotrophic factors, mitochondrial dysfunction, calcium dyshomeostasis, energy failure, oxidative stress, vascular dysregulation, and neuroinflammation (Fig. 1).

4 Mitochondrial dysfunction, a key pathogenic event in RGC degeneration at different compartments Elevated IOP-related disconnection from the RGC soma results in the early interruption of axoplasmic flow, including both anterograde and retrograde components, which is essential for the trafficking of neuronal survival factors. There is a general agreement that the disruption of axonal transport, which leads to neurotropin deprivation is a critical early event that can provoke RGC apoptosis in glaucoma. In support of the asynchrony of RGC degeneration in glaucoma, axonal transport defects do not affect all RGCs simultaneously. Besides the IOP-related mechanical compression of optic nerve axons, another key pathogenic event underlying the compromised transport is disturbed mitochondrial function in energy generation (Baltan et al., 2010). Owing to the high energy demand of RGCs for structural and functional maintenance, and the high dependence on mitochondrial energy generation, a metabolic failure resulting from mitochondrial dysfunction may indeed be critical for neurodegeneration at different subcellular compartments of RGCs. In addition to generating biomechanical injury that may directly impact mitochondrial health as summarized below, elevated IOP-related stress may also compromise capillaries at the optic nerve head, thereby leading to deficiency in the vascular nutrient supply. Therefore, besides mitochondrial shortages in ATP generation, the decreased availability of energy substrates from circulation may also contribute to axonal energy failure (Dai et al., 2012). The age-related decrease in energy reserves, along with the increased metabolic demand of stressed RGCs in glaucomatous tissues, may further enhance neuronal energy deficits. In addition to mitochondrial dysfunction and capillary impairment, neuronal energy insufficiency may be secondary to the withdrawal of astroglial metabolic support. Astrocytes and oligodendrocytes normally provide axons with energy substrates in order to address increased energy need, or to overcome potential shortages in glucose transport or diffusion from blood vessels. These glial cells can also mobilize their glycogen stores to supply glucose or lactate to axons via glucose or monocarboxylate transporters (Saab et al., 2016). Lactate, and also pyruvate, are particularly essential for neurons, since mitochondrial ATP generation relies on these glycolysis-derived metabolic intermediates. However, a deficiency in astroglial metabolic support, as evident by the down-regulation of monocarboxylate transporters (Harun-Or-Rashid et al., 2018), is likely to further deteriorate energy metabolism in glaucomatous RGCs. It is also notable that a functional mitochondria is required to utilize lactate as an energy substrate. On the basis of experimental findings in animal models of glaucoma, ocular hypertension may directly impact mitochondrial structure and function.

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Mitochondrial dynamics, such as mitochondrial morphology (determined by the balance between fission and fusion), biogenesis, degradation, and transport, profoundly affect RGC viability. While mitochondrial biogenesis builds up mitochondria, mitophagy endows cells with a quality control tool to eliminate damaged mitochondria. These physiological processes continuously remodel the mitochondrial network. Mitochondria in RGC soma and axons become smaller and more fragmented in DBA/2J glaucoma, suggesting abnormally high fission, defective fusion (Kim et al., 2015), and/or mitophagy deficits (Coughlin et al., 2015). The fragmented mitochondria in glaucoma are predicted to have a decreased capacity to produce energy, which may also be counted as an early sign of apoptosis because of its correspondence to Bax translocation to the mitochondrial outer membrane. Dynamin-1-like protein (DRP1), a member of the dynamin superfamily, regulates mitochondrial fission. In optic nerves of DBA/2J mice, ocular hypertension induced a marked increase of DRP1 and decrease of OPA1 (a dynamin-related GTPase that regulates mitochondrial dynamics), and inhibition of DRP1 or overexpression of OPA1 promoted survival of RGC somas and axons (Ju et al., 2010; Kim et al., 2015). Regarding mitochondrial biosynthesis, optic nerves in DBA/2J glaucoma displayed a significantly diminished density of mitochondria, thereby depleting the energy supply to stressed axons. The energy-depleted axons exhibited chronic metabolic stress and dysfunction (Baltan et al., 2010). Improved energy availability, and also antioxidant response, provided for the structural and functional rescue of metabolically-stressed RGCs and axons during glaucomatous neurodegeneration in these mice (Harun-Or-Rashid et al., 2018). Anterograde and retrograde transport of mitochondria are mediated by the kinesin-1 family of motor proteins, or dynein proteins, respectively. The mitochondria biosynthesized in the RGC soma is transported to RGC dendrites and axons, and axonal transport defects severely affect the mitochondrial motility, leading to accumulation of stressed mitochondria. After laser-induced ocular hypertension in mice, transport of mitochondria in both anterograde and retrograde directions were significantly reduced (Takihara et al., 2015). Besides energy generation, mitochondria are essential for the regulation of intracellular calcium homeostasis, oxidative stress, and apoptosis signaling, all of which contribute to RGC degeneration in glaucoma as reviewed in the sections below. However, to provide a brief insight into the secondary degenerative processes that also influence both RGC susceptibility to injury and the molecular components of degeneration signaling, the next section will summarize glia-driven neuroinflammation.

5 Glia-driven neuroinflammation, a widespread outcome promoting RGC degeneration Both astroglia and microglia (Lye-Barthel et al., 2013; Seitz et al., 2013) present profound activation responses in glaucoma. Despite subtype-specific, topographic, and temporal variations in glial responses, their morphological, molecular, and

5 Glia-driven neuroinflammation

functional alterations persist during the chronic disease period. Although glia normally support stressed neurons and promote tissue repair after degenerative insults, increasing evidence also implicate important contribution of astrogliosis and microgliosis to glaucoma pathophysiology. Evidently, prolonged activation responses of glial cells result in the withdrawal of glial neurosupport functions with deficiencies in structural, trophic, bioenergetic, and immune regulatory/phagocytic support. In response to glaucomatous tissue stress and injury, glial cells also create an inflammatory and toxic environment for RGCs, and multiple consequences of glia-driven neuroinflammation may contribute to glaucomatous degeneration of RGC somas, axons, and synapses (Baris and Tezel, 2019). Early alterations of immune response pathways, which may even be detectable at pre-degenerative stages of glaucoma, appear to be independent from RGC injury. For example, although WldS expression protected DBA/2J mice from axon degeneration, glial immune responses persisted (Harder et al., 2017). This observation may support the independency of glial inflammatory responses from axon injury; however, pre-existing inflammation in DBA/2J mice may question this claim. Regardless, a possible supportive explanation for early glial responses rests on the fact that glial cells can sense IOP-related mechanical strain via mechanosensitive ion channels (such as purinergic receptors, transient receptor potential vanilloid, and pannexin channels) (Albalawi et al., 2017, Krizaj et al., 2014) and initiate inflammatory signaling. However, glial cells can also recognize damage-associated molecular patterns, or the ATP released from stressed or injured neurons (Reigada et al., 2008). This may explain the attenuated glial response that was detected in the retina after optic nerve injury in Bax / mice (Mac Nair et al., 2016). As such, glial responses in glaucoma may be stimulated by both the IOP-related stress and the signals arising from RGCs. Multiple studies of molecular profiling in human glaucoma or animal models identified early up-regulation of numerous molecules that include sensors/inducers, transducers, and effectors of neuroinflammation signaling with neurotoxic outcomes (Baris and Tezel, 2019). Reactive glia, and also blood-born monocytes (Howell et al., 2012), generate an inflammatory environment in the retina and optic nerve (head) by an increased secretion of pro-inflammatory mediators through the NF-κB-mediated transcriptional program that is activated during TNFR signaling, TLR signaling, and inflammasome assembly (Baris and Tezel, 2019). The pro-inflammatory cytokines secreted by reactive glia, such as TNFα (Tezel and Wax, 2000a), or FasL (Krishnan et al., 2019), can induce RGC apoptosis and axon degeneration. Microglia may also contribute to loss of RGC dendrites and synapses through complement-mediated processes (Williams et al., 2016). Based on MRI brain scanning, retinal imaging, and functional testing in glaucoma patients, and experimental observations in a mouse optic nerve injury model, glial responses may also be detectable in posterior visual projections and mediate trans-synaptic damage (You et al., 2019). Evidently, besides the innate immunity mediated by glia, these resident immunocompetent cells with increased antigen-presenting functions also become inducers of adaptive immunity in glaucoma. Systemic immune activity is evident in glaucomatous patients by abnormal distribution and activity of T cell subsets

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(Yang et al., 2019) and increased production of autoantibodies to ocular antigens (Lorenz et al., 2016; Tezel and Wax, 2000b). As recently reviewed (Baris and Tezel, 2019), increasing data from in vitro and ex vivo experiments, and in vivo antigen immunization or adoptive transfer studies, also support the likelihood of T cell-mediated and autoantibody-mediated toxicity to RGCs. Thus, glial inflammatory responses are manifest throughout the visual pathway, and glia-driven processes (including both the innate cytotoxicity, and the cytotoxicity of autoreactive T cells, autoantibodies, and complement) constitute potent stimuli for injury to RGC somas, axons, and synapses in glaucoma. Although neuroinflammation is widespread, however, it may vary between different compartments of RGCs depending on the individual contribution and inter-relationship of different glial subtypes that present distinct temporal, morphological, molecular, and functional characteristics. Additional studies are expected to further enlighten the poorly understood aspects of neuroinflammation signaling to thereby progress toward immunomodulatory treatments for neuroprotection in glaucoma.

6 Molecular signaling for degeneration of RGC axons An early insult at the optic nerve head initiates signaling cascades both distally and proximally to trigger axonal and somatic degeneration in glaucoma. Although axon injury is a major driver of RGC degeneration in glaucoma, degeneration pathways for axonal or somatic compartments are molecularly distinct. As supported by a survival factor model for axon degeneration, axons can sense the impaired supply of axonal survival factors and initiate a self-destruction program (Wang et al., 2012). Axon degeneration after mechanical injury may be activated by opening of the mitochondrial permeability transition pore that causes mitochondrial calcium overload, mitochondrial swelling, oxidative stress, and ATP depletion (Barrientos et al., 2011). A metabolic failure caused by decreased mitochondrial ATP synthesis subsequently affects axonal transport as summarized in the previous section. The ATP depletion-related axon degeneration can be prevented by WldS (Shen et al., 2013). Besides energy failure, dysregulation of calcium homeostasis is an important promoter for axon degeneration. Nicotinamide mononucleotide adenylyltransferase (NMNAT) that catalyzes the ATP-dependent conversion of nicotinamide mononucleotide to nicotinamide adenine dinucleotide (NAD+) is decreased after axon injury, causing to decreased levels of NAD+. The lack of NAD+-dependent calcium regulation results in increased intra-axonal calcium due to calcium channel-mediated influx from external stores or release from intracellular stores. Calcium dysregulation may also be related to reverse activity of the Na+/Ca++ exchanger, because decreased ATP also affects the activity of Na+/K+ ATPase. Calcium-dependent increase in activities of the ubiquitin-proteasome system can lead to proteasemediated cytoskeletal breakdown, thereby destroying the structural and functional integrity of axons (Wang et al., 2012). Calcium-dependent activation of calpains

6 Molecular signaling for degeneration of RGC axons

(cysteine proteases) may also participate in proteolysis of axonal neurofilaments and disintegration of axonal cytoskeleton during Wallerian degeneration (Ma et al., 2013). In WldS mice, increased NAD+ production led to overall decrease in intraaxonal calcium by lowering the intracellular release from axoplasmic reticulum and increasing the calcium buffering by mitochondria. Together with WldS, nicotinamide (an NAD+ precursor) significantly delayed axon degeneration in DBA/2J glaucoma (Williams et al., 2017a). Another downstream consequence of calcium overload is the activation of cellular degradation by autophagy. Although autophagy is a physiological process for cytoskeletal and organelle recycling, and adaptation to nutrient shortage and cellular stress, this cellular machinery was also implicated in disruption of axonal cytoskeleton and successful completion of Wallerian degeneration (Wakatsuki et al., 2017). In spite of this, whether modulation of the autophagic flux may confer protection to injured axons in glaucoma warrants further investigation of experimental glaucoma models. Mitophagy, a type of autophagy that selectively degrates irreparably damaged and dysfunctional mitochondria may also have important implications in glaucoma. Observations of the glaucomatous optic nerve axons in DBA/2J mice suggest that the damaged mitochondria may not be efficiently recycled by mitophagy (Coughlin et al., 2015), even though optic nerve axons exhibit an increased autophagic activity (Kleesattel et al., 2015). An alternative process for mitochondrial degradation is named transcellular mitophagy that enables the mitochondria within RGC axons to be shed and taken up by nearby astrocytes for degradation within astrocytic lysosomes (Davis et al., 2014). It will be of interest to further explore the potential implications of mitophagy, and transcellular mitophagy, in glaucomatous neurodegeneration. A number of signaling pathways contribute to axon degeneration in glaucoma. The Jun N-terminal kinase (JNK) signaling is activated immediately after axon injury at the optic nerve head, and the protective effects of WldS on distal axon degeneration may act upstream of JNK activation (Fernandes et al., 2013). There is some disagreement in the role of dual leucine zipper kinase (DLK), an upstream kinase of JNK signaling, in axon degeneration. However, TIR motif containing 1 (SARM1), an adaptor protein acting upstream of DLK/JNK signaling, appears to be important for disturbance of axonal energy homeostasis and degeneration of RGC axons that can be rescued by genetic deletion of SARM1 (Yang et al., 2015a). The SARM1 deficiency was found as protective as WldS in preventing the axon degeneration after optic nerve crush; however, DLK/JNK-mediated RGC soma degeneration was SARM1-independent (Fernandes et al., 2018). The DLK/ JNK signaling is further discussed in the next section below. Death receptor-6 (DR6) signaling is another molecular cascade linked to degeneration of RGC axons (Fernandes et al., 2018). Activation of DR6 by the surface ligands released after axon injury may induce axon degeneration through caspase-6 activation. The beta-amyloid precursor protein that is accumulated in glaucomatous tissues (Ito et al., 2012), is a DR6 ligand and can activate a caspase-dependent self-destruction program in axons. This caspase-dependent

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mechanism for axon degeneration is independent from the apoptosis pathway that requires caspase 3 as in RGC somas. However, Bax that is critical for RGC apoptosis may also be involved in intrinsic axon degeneration (Nikolaev et al., 2009). This is in agreement with previous observations that Bax deficiency slowed axon degeneration in DBA/2J glaucoma, even though Bax is not required for axon degeneration (Libby et al., 2005b). Another pathogenic mechanism for axon degeneration is linked to vascular endothelial dysfunction. Optic nerve vasculature is normally autoregulated so that small alterations in IOP or systemic blood pressure do not change vascular perfusion. However, vascular autoregulation may be impaired in glaucoma due to vascular endothelial dysfunction, astroglial dysfunction, and autonomic dysfunction resulting in a failure of the neurovascular unit. As a result of prominent circadian variations in IOP and systemic blood pressure (low mean arterial pressure increasing the risk) in glaucoma patients, there may be intermittent episodes of perfusion defects when ocular perfusion pressure falls below the lower limit of autoregulation. Key components of the vascular endothelial dysfunction in glaucoma include endothelin (ET) signaling that exhibits early up-regulation in optic nerve head astrocytes. In response to IOP elevation, optic nerve head astrocytes produce increased amounts of ET-1 (Prasanna et al., 2011) and ET-2 (Howell et al., 2011). The ET-1 acts in an autocrine fashion via ET-B receptor and produces pathogenic effects, such as proliferation, increased production of extracellular matrix molecules, matrix metalloproteinases, and their inhibitors (Prasanna et al., 2011). These potent vasoconstrictive agents may also cause vascular dysfunction by acting through ET-A receptor. Accordingly, inhibition of the endothelin system by endothelin receptor antagonists resulted in the reduction of the glaucoma-related decrease in retinal vascular lumen and provided neuroprotection in DBA/2J glaucoma (Howell et al., 2011). Despite growing knowledge about the molecular basis of glaucomatous neurodegeneration, more work is needed to further investigate specific cellular and molecular signals critical for axon degeneration in glaucoma models. The following section will focus on RGC soma death and discuss how the locally initiated signals by injured axons can trigger different effectors of degenerative processes in RGC somas, dendrites, and axon terminals.

7 Molecular signaling for RGC soma death Studies of postmortem human tissues and animal models indicated that the RGC somas die through apoptosis in glaucoma, and following studies of molecular profiling revealed numerous molecules that are involved in RGC apoptosis signaling. Evidently, molecular signaling for apoptosis of the RGC soma is independent from signaling for distal axon degeneration in glaucoma. However, current view recognizes that mitochondrial dysfunction, calcium dysregulation, energy insufficiency, increased free radical generation, and neuroinflammation are major components shared by axonal and somatic degeneration programs in RGCs. As summarized

7 Molecular signaling for RGC soma death

earlier for axon degeneration, mitochondrial dynamics, including biogenesis, fusion/ fission, transport, and degradation, are similarly critical for RGC viability and visual function, while dysregulation of these processes presents profound impacts on RGC health. Owing to their active metabolism and high energy demand, RGCs are particularly vulnerable to metabolic failure resulting from mitochondrial dysfunction. Besides declined ATP production, another paramount consequence of mitochondrial dysfunction is increased generation of reactive oxygen species. Along with the age-related decrease in intrinsic antioxidant capacity, amplified generation of free radicals leads to oxidative stress that can deeply impact RGC survival (Chrysostomou et al., 2013; Tezel, 2006). Oxidative stress can promote RGC death through the modulation of protein function by redox modifications (Tezel and Yang, 2004; Tezel et al., 2005) and through the boost of neurodegenerative inflammation (Tezel, 2011; Tezel et al., 2007b). Consequently, antioxidant treatment of experimental glaucoma protected RGC somas and axons, as well as providing immunomodulation (Yang et al., 2016b). Although ATP is primarily generated through mitochondrial oxidative phosphorylation in RGCs, proteomic profiling of the ocular hypertensive human retinas displayed increased expression of some glycolytic enzymes in parallel to down-regulation of oxidative phosphorylation (Yang et al., 2015b). Perhaps, glycolysis may become enhanced in order to compensate for the deficiency of mitochondrial ATP yield in ocular hypertensive retinas. However, whether glaucomatous RGCs may keep the capacity of switching between these two ATP-producing pathways, or whether forcing a metabolic shift toward glycolysis (Shibeeb et al., 2016) may limit the oxidative phosphorylation-associated free radical generation need further work. While the maintenance of cellular ATP level by mitochondria is important to prevent apoptosis, dysfunction of mitochondria initiates the RGC apoptosis program. Multiple apoptosis pathways in RGCs converge to a central point of Bax activation, and RGC apoptosis is dependent on this key pro-apoptotic protein. Bax is the major effector protein in the pro-apoptotic group of the Bcl2 family that tightly regulates apoptosis. Other two groups of proteins within this family include anti-apoptotic proteins and BH3-only proteins. The BH3-only proteins possess varied levels of pro-apoptotic function by activating the effectors and neutralizing the anti-apoptotic proteins. Even in the lack of detectable change in their expression in animal models of glaucoma, BH3-only proteins potentiate Bax-mediated apoptosis by neutralizing the anti-apoptotic proteins, like Bcl-X that is the most highly expressed anti-apoptotic protein in the retina. A critical balance between the three groups of Bcl2 family proteins is controlled by several upstream pathways, and their crosstalk plays a central role in determining the fate of RGCs in response to damaging stimuli. In RGCs, Bax mediates the committed step of RGC apoptosis, in which Bax activation and mitochondrial translocation leads to mitochondrial outer membrane permeabilization, and the subsequent release of cytochrome c into cytosol initiates the proteolytic caspase cascade for execution of apoptosis. Recruitment of mitochondria is the point of no return in apoptosis, and Bax deficiency provides complete protection to RGC somas (and proximal axons) with no long-term protection for distal

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axons in DBA/2J glaucoma (Howell et al., 2007; Libby et al., 2005b). In addition to complete deficiency, lowered quantity of Bax may also be protective against RGC apoptosis (Semaan et al., 2010). Thus, Bax is essential for RGC soma death, even though it is not required for axon degeneration. An alternatively spliced gene, Bak, is also present in retinal neurons of mice and non-human primates; however, its function in RGC apoptosis remain unclear (Maes et al., 2017). In addition to mitochondrial pathway, apoptotic caspase cascade can be triggered in RGCs by binding of the TNF family death receptors with their specific ligands, such as TNFα (Tezel and Wax, 2000a), and the blockage of TNFα signaling protects RGCs in ocular hypertensive animals (Nakazawa et al., 2006). The RGC death mediated by TNFα involves both caspase-dependent (via extrinsic activation of the caspase cascade) and caspase-independent mechanisms (via mitochondrial dysfunction and oxidative stress) (Tezel and Yang, 2004). Besides direct stimulation of RGC apoptosis after TNFR1 binding (Tezel and Wax, 2000a), the astroglia-secreted TNFα stimulates an increase in calcium-sensitive AMPA receptors on RGCs, and the increased calcium influx may also elicit RGC apoptosis (Cueva Vargas et al., 2015). As supported by proteomic profiling of the glaucomatous human donor retinas, diverse functional interactions of TNFα signaling with various other death-promoting pathways may also impact RGC survival in glaucoma (Yang et al., 2011). Interestingly, glial activation responses leading to neuroinflammation were dramatically muted in Bax-deficient retinas after optic nerve injury (Mac Nair et al., 2016). In addition to mitochondria-mediated apoptosis, this observation also links the RGC-protective outcomes of Bax / to the glia-driven secondary neurodegenerative processes that include TNFα-mediated RGC apoptosis (Baris and Tezel, 2019). In support of this suggestion, deletion of TNFR1 protected against the second wave of RGC death after axon injury (Tezel et al., 2004). Involvement of mitochondria was suggested as a principal distinguishing feature between the intrinsic pathway of apoptosis and the extrinsic pathway activated by engagement of dead receptors. However, caspase 8, a proximal caspase activated after TNFR1 binding, can recruit the intrinsic/mitochondrial pathway of apoptosis by cleaving the BH3-only protein, Bid. The Bid recruitment that was detected in experimental glaucoma (Huang et al., 2005) may function as an amplification step for RGC death. On the other hand, the 14-3-3 family of proteins that are involved in checkpoint regulation of cellular protein trafficking in a phosphorylation-dependent manner control the subcellular localization and function of BH3-only proteins, including Bad that is also present in RGCs. A targeted proteomics study of experimental rat glaucoma demonstrated that the 14-3-3 scaffold keeps the phosphorylated Bad sequestered in the cytoplasm and prevents its activation and mitochondrial translocation for interaction with anti-apoptotic proteins (Yang et al., 2008). These observations exemplify the importance of molecular interactions and post-translational modifications for cellular demise. Nuclear shrinkage and atrophy are among the early events detected in RGC somas in optic nerve injury models, which also appear to be post-translationally regulated by histone deacetylation (Schmitt et al., 2016). The class I histone deacetylases were shown to play a central role in early transcriptional dysregulation and

7 Molecular signaling for RGC soma death

gene silencing before the completion of RGC apoptosis. Early down-regulation of RGC-specific gene expression was also detected in DBA/2J glaucoma, prior to Bax involvement (Pelzel et al., 2012). As discussed for axon degeneration earlier, a failure in calcium buffering leads to calcium increase in RGCs as evident in a rat model of ocular hypertension (Niittykoski et al., 2010). Dysregulation of calcium homeostasis may result in increased activity of the ubiquitin-proteasome system in RGCs. Similar to axons, supplementing the NAD+ levels with nicotinamide treatment provides protection to RGCs against glaucomatous injury (Williams et al., 2017b). In addition, calcium-dependent protease calpain likely contributes to RGC death in human glaucoma (Yang et al., 2011) and animal models (Huang et al., 2010). Since axon injury at the optic nerve head is viewed as an inciting event, and the injury progresses from RGC axons to somas, signaling for RGC apoptosis in glaucoma is thought to originate from axons (Buckingham et al., 2008; Howell et al., 2007). Following an insult at the optic nerve head, an early compromise of axonal transport leads to deprivation of trophic support to RGC somas, and the subsequent neurotrophin deficiency can induce Bax-dependent death of RGCs. Increased generation of superoxide in axons and then RGC somas after optic nerve injury may also function as an upstream signal for RGC apoptosis by acting as a second messenger (Kanamori et al., 2010) or inducing the redox modification of downstream effectors (Tezel et al., 2005). More recent studies of functional genomic screening of RGCs in animal models (Welsbie et al., 2017) or high-throughput proteomic analysis of human donor tissues (Tezel, 2014; Yang et al., 2015b) have improved the molecular understanding of RGC death signaling. A major pathway that was found to trigger RGC apoptosis after axon injury included JNK, a member of the mitogen-activated protein kinase (MAPK) family that plays an integral role in signal transduction after cellular stress. As discussed earlier, JNK signaling appears to be involved in both distal axon degeneration and RGC soma death. Experimental data support that different JNK isoforms mediate physiological processes or stress signaling in glaucoma. While JNK2 and JNK3 are major regulators of axonal injury-induced RGC death, the JNK1-Jun axis integrates the upstream signals triggered by axon injury with a downstream transcriptional activity that controls RGC apoptosis (Syc-Mazurek et al., 2017a). The insults evident in the glaucomatous optic nerve head, such as distortion of axonal cytoskeleton, neurotrophin deprivation, energy failure, or neuroinflammation, can activate JNKs. Indeed, RGCs presented JNK activation in human glaucoma and experimental animals with ocular hypertension (Kwong and Caprioli, 2006; Tezel et al., 2003). Distinct upstream kinases regulate JNK activation in RGCs. MAP2Ks (MKK4 and MKK7) play redundant roles in activation of downstream JNK signaling after axon injury (Syc-Mazurek et al., 2018). In upstream of JNKs and MAP2Ks, there are MAP3Ks, such as DLK and leucine zipper-bearing kinase (LZK) (Fernandes et al., 2014). While DLK is important for pathological activation of JNK in RGCs, LZK cooperates with DLK to induce downstream signaling through MAP2Ks and JNKs (Welsbie et al., 2017). After an axonal insult, phosphorylated DLK is

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transported to RGC soma and initiates a transcriptional program for apoptosis by interacting with the Bcl2 family of genes (Watkins et al., 2013). Although DLK/ JNK signaling is important for the regulation of axonal signaling and subsequent somatic response, their roles in apoptosis of RGC somas and Wallerian degeneration of axons may be independent. This is because DLK deficiency abolished the activation of JNK in RGC somas and delayed the axonal injury-induced RGC soma loss, but it did not prevent JNK activation in axons and did not alter axon degeneration (Fernandes et al., 2014). In addition to signaling between RGC axons and somas, RGCs can sense the IOP-related stress by transient receptor potential vanilloid-1 subunit channels (Sappington et al., 2015). RGCs also respond to elevated IOP and mechanosensitive autocrine release of ATP by signaling through purinergic receptors (Xia et al., 2012) and pannexin channels (Panx1, Panx2). Up-regulation of purinergic signaling in RGCs, which is essential for visual function in the inner retina, makes them highly sensitive to glaucoma-related stressors (Dvoriantchikova et al., 2018). The apoptosis signaling in RGCs has also been linked to endoplasmic reticulum (ER) stress that is characterized by unfolded protein response (UPR) (required for protein repair/removal), up-regulation of stress-regulated chaperones (that catalyze protein folding and function as sensors detecting the UPR), and increased ubiquitination (required for targeted degradation of proteins that are not properly folded within the ER). The ER stress initially represents intrinsic adaptive efforts to preserve cell function and survival; however, persistence of impaired ER homeostasis may also initiate apoptotic cascades. Besides UPR, disturbances in calcium regulation and redox balance link the ER stress to mitochondrial dysfunction and mitochondria-generated oxidative stress. Similar to axon degeneration, ER stress and overloading of the ubiquitin-proteasome pathway were associated with RGC soma death in glaucoma models (Doh et al., 2010; Yang et al., 2016a; Zode et al., 2012). Findings in postmortem donor eyes were also supportive of the ER stress in human glaucoma (Yang et al., 2011, 2015b). Recently, ER stress signaling was linked to JNK signaling for RGC death after axon injury. Combined deficiency of Jun and Ddit3 (also known as CHOP, a key mediator of the ER stress response) reduced RGC apoptosis, thereby suggesting that these transcription factors co-regulate downstream effectors in Bax-dependent RGC apoptosis (Syc-Mazurek et al., 2017b). However, Ddit3 deletion alone conferred only mild protection to RGC somas in DBA/2J glaucoma (Marola et al., 2019). Experimental evidence also link the RGC death in ocular hypertensive monkeys (Deng et al., 2013) and DBA/2J mice (Hirt et al., 2018) to autophagy activation. Starvation, by changing the AMP/ATP ratio, induces AMP-activated protein kinase signaling that functions as a sensor of energy deprivation, down-regulates the activity of mechanistic target of rapamycin (mTOR, a negative regulator of autophagy), and initiates autophagy to restore cellular energy. Although this homeostasis pathway allows cells to survive nutrient depletion or the absence of growth factors, it may also promote cell death under specific conditions. Studies of rats with episcleral vein cautery-induced ocular hypertension detected autophagy activation, and inhibition of autophagy by 3-methyladenine suppressed RGC death in ocular

8 Loss of RGC synapses at dendrites and axon terminals

hypertensive eyes (Park et al., 2018). In contrast, enhancement of autophagy by rapamycin treatment in the same rat model resulted in neuroprotection that was attributed to inhibition of microglia-derived neurotoxic mediators and direct suppression of RGC apoptosis (Su et al., 2014). These controversies warrant further research to clarify the importance of autophagy in glaucoma. Sirtuins are NAD+-dependent deacetylases that target histones and other proteins and exert beneficial effects against aging and age-related diseases. Different members of the sirtuin family play important roles in protein homeostasis, metabolism, mitochondrial function, neuronal survival/function, and neuroinflammation. Resveratrol, a sirtuin activator, delayed Wallerian degeneration in axon injury models and improved the survival of RGC somas in glaucoma models (Cao et al., 2020). However, varying functions of sirtuin family members and conflicting responses to their therapeutic manipulation should be further explored in glaucoma models. Additional molecular signals that are known to be common inducers of neuronal apoptosis have also been implicated in glaucomatous RGC death. For example, inducible nitric oxide synthase 2 (NOS2) was found to be produced by reactive glia in human glaucoma (Liu and Neufeld, 2000), and pharmacological inhibition of NOS2 provided protection to RGCs in a rat model of glaucoma (Neufeld et al., 1999). However, subsequent studies of NOS2 inhibition in ocular hypertensive rats (Pang et al., 2005) or studies of DBA/2J mice lacking a functional NOS2 gene (Libby et al., 2007) failed to demonstrate a mediator role of NOS2 in RGC degeneration. Neurotoxic amyloid-β (Ito et al., 2012) and phospho-tau that are detectable in glaucomatous retinas (Gupta et al., 2008) were also proposed to impact RGC viability by disruption of microtubules as in the Alzheimer’s disease (Gasparini et al., 2011). N-methyl-D-aspartate receptor-mediated excitotoxicity kills RGCs in experimental models; however, following studies could not support excitotoxicity as a primary mechanism for RGC death in glaucoma. Moreover, Bax deficiency was unable to protect RGCs from excitotoxicity (Libby et al., 2005b). Thus, different death pathways are co-activated in RGC somas after glaucomatous injury, and their crosstalk may reinforce each other in government of RGC apoptosis. It remains unknown whether RGC death in glaucoma also involves other mitochondria-linked cell death programs (such as parthanatos, mitoptosis), or necrosis/necroptosis. However, a recent experimental study pointed to the pro-pyroptotic pathway via inflammasome activation in RGCs after acute elevation of IOP. Both the release of pro-inflammatory cytokines and the loss of RGCs were significantly decreased by transgenic inhibition of neuronal NLRP1/NLRP3 inflammasomes in this retinal ischemia model (Pronin et al., 2019).

8 Loss of RGC synapses at dendrites and axon terminals Evidently, other compartments of RGCs, such as dendritic and synaptic regions, also undergo separate injury processes in glaucoma. Early retinal alterations that occur after axon injury include early pruning of RGC dendritic arbors, shrinkage of

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RGC somas, and the loss of RGC synapses with amacrine and bipolar neurons in the inner plexiform layer of the retina (Pang et al., 2015; Williams et al., 2013). While the number of intraretinal RGC synapses decreases as neurodegeneration progresses in animal models of glaucoma, early intrinsic recovery responses and synaptic rearrangements are also evident prior to dendrite atrophy and function loss (Berry et al., 2015; El-Danaf and Huberman, 2015). Dendritic remodeling is accompanied by mitochondrial redistribution (Tribble et al., 2019) and glial responses. Initial responses of resident astroglia in synaptic regions, or migrating microglia, provide early trophic/metabolic/extracellular buffering support to stressed neurons and promote tissue healing by eliminating the injured dendritic structures through scavenger and phagocytosing functions. However, initially neurosupportive responses of reactive glia may later be damaging by increased release of cytotoxic molecules, or uncontrolled activation of complement components (Williams et al., 2016). The axonal-somatic axis of neurodegeneration signaling likely contributes to early dendritic and synaptic changes in glaucoma. For example, presence of the WldS allele prevents ocular hypertension-induced dendrite changes and synapse loss (Harder et al., 2017). However, since WldS also prevents axon degeneration, it may be difficult to interpret this observation as to whether early dendritic changes are prevented by the preservation of axon integrity. Even though some of the dendritic and synaptic changes may be related to initial axon injury, some changes may be independent. Early injury signals in RGCs also reach to brain synapses in lateral geniculate nucleus and visual cortex (Yucel, 2013). Degenerative changes of the lateral geniculate nucleus detected in primate models include reduced dendrite complexity and dendrite length (Ly et al., 2011). In addition, a volume loss was detected by magnetic resonance imaging (Lee et al., 2014) and postmortem histopathologic analysis (Gupta et al., 2006) in glaucoma patients. Structural alterations detectable throughout the retino-geniculo-cortical pathway are accompanied by altered functional connectivity of neural circuits. With respect to high energy demand of RGCs, insufficient energy generation may initiate early function deficits. Early alterations of RGC dendrites and synapses in the inner retina lead to RGC function loss that may be detected prior to axonal or somatic damage (Della Santina et al., 2013; Pang et al., 2015). Dendritic and synaptic alterations of RGCs may also be a potential driver of axon degeneration by reducing nerve activity. However, despite substantial dendritic pruning, experimental data supports an early and transient axogenic response that boosts RGC excitability to maintain visual signaling (Risner et al., 2018). In addition, depending on the mitochondrial volume, RGC axons may retain their synaptic contacts with brain targets for a time after the onset of early defects in anterograde axonal transport, when retrograde axonal transport is still intact (Smith et al., 2016). An early deficiency in transmitting the visual information to brain in DBA/2J glaucoma was recently linked to a Ranvier node pathology in intact axons, and

Acknowledgments

alterations, such as increased node length and redistribution of the voltage-gated sodium channels, were associated with pre-existing inflammation detected in these mice (Smith et al., 2018). Apart from cellular and molecular mechanisms participating in synapse loss, it is particularly important to highlight that RGCs have the intrinsic capacity to regenerate dendrites and synapses after injury. Owing to this synaptic plasticity and rewiring capacity, early alterations of RGC dendrites may offer a treatment window for degenerative processes in other RGC compartments. This exciting possibility stimulates further studies of glaucoma models.

9 Conclusions As reviewed herein, glaucoma is a complex neurodegenerative disease of RGC axons, somas, and synapses. Seen from a broad perspective, glaucomatous neurodegeneration involves multiple stressors, multiple injury sites, multiple cell types, and multiple signaling pathways over a chronic disease period (Fig. 1). Molecular regulation of various etiological paths, such as biomechanical, metabolic, oxidative, and inflammatory components, will continuously be explored to provide a greater insight into pathogenic processes and improved treatments. A collective understanding of the individual and interactive contributions of different cell types on neuronal, glial, and vascular mechanisms that promote glaucomatous neurodegeneration will be critical for progressing toward increased molecular knowledge and causative treatment of glaucoma. Enhanced information about intrinsic responses of RGCs will also allow strategies to promote pro-survival and self-repair activities. With respect to multifactorial aspects of glaucoma (with components differing between glaucoma patients) and compartmentalized processes of neurodegeneration, new treatments are expected to include (personalized) multi-target strategies that may be in the form of pharmacological drugs, or gene-based, and/or stem cell-based treatments to inhibit pro-death signals, stimulate pro-survival signals, and modulate neuroinflammation. Pro-regenerative therapeutics also promise for reprogramming of RGCs to regenerate axons, dendrites, and synapses for recovery of visual function. Collaborations between basic and clinical research speed the translation from bench-to-bedside and back for ultimate success in preventing blindness from glaucoma.

Acknowledgments Dr. Tezel’s work was supported in part by a research grant from National Eye Institute, Bethesda, MD (R01 EY028153), the Homer McK. Rees Scholarship in Glaucoma Research, and the AR and JR Peacock Trusts Research Grant. In addition, Research to Prevent Blindness Inc. (New York, NY) provides an unrestricted grant to Department of Ophthalmology. The author declares no conflict of interest.

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The role of commensal microflora-induced T cell responses in glaucoma neurodegeneration

4

Jing Tanga,c,†, Yizhen Tangb,c,†, Irvin Yic, and Dong Feng Chenc,* a

Department of Ophthalmology, West China Hospital, Sichuan University, Sichuan, China Department of Ophthalmology and Vision Science, Eye & ENT Hospital, Shanghai Medical College, Fudan University, Shanghai, China c Schepens Eye Research Institute of Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, United States ∗ Corresponding author: Tel.: +1-617-912-7490, e-mail address: [email protected] b

Abstract Over the last decade, new evidence has become increasingly more compelling that commensal microflora profoundly influences the maturation and function of resident immune cells in host physiology. The concept of gut-retina axis is actively being explored. Studies have revealed a critical role of commensal microbes linked with neuronal stress, immune responses, and neurodegeneration in the retina. Microbial dysbiosis changes the blood-retina barrier permeability and modulates T cell-mediated autoimmunity to contribute to the pathogenesis of retinal diseases, such as glaucoma. Heat shock proteins (HSPs), which are evolutionarily conserved, are thought to function both as neuroprotectant and pathogenic antigens of T cells contributing to cell protection and tissue damage, respectively. Activated microglia recruit and interact with T cells during this process. Glaucoma, characterized by the progressive loss of retinal ganglion cells, is the leading cause of irreversible blindness. With nearly 70 million people suffering glaucoma worldwide, which doubles the number of patients with Alzheimer’s disease, it represents the most frequent neurodegenerative disease of the central nervous system (CNS). Thus, understanding the mechanism of neurodegeneration in glaucoma and its association with the function of commensal microflora may help unveil the secrets of many neurodegenerative disorders in the CNS and develop novel therapeutic interventions.

†

These authors contributed equally.

Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.06.002 © 2020 Elsevier B.V. All rights reserved.

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Keywords Microbiota, Gut-retina axis, Glaucoma, Neurodegeneration, Retina, Heat shock proteins, T cells

1 Introduction Glaucoma is an age-related multifactorial neurodegenerative disease, characterized by progressive loss of retinal ganglion cells (RGCs) and irreversible visual deficiency. It is predicted that more than 100 million people worldwide will be affected by glaucoma by 2040 (Tham et al., 2014). Elevated intraocular pressure (IOP) is deemed to be the most important risk factor in glaucoma pathology. High IOP triggers microglia activation, immune responses, neurotrophic deprivation, oxidative damage, and mitochondrial dysfunction that eventually lead to RGC degeneration (Gallego et al., 2012; Vu et al., 2012). A currently unresolved issue in glaucoma clinics is that RGC and optic nerve degeneration continues to progress even after the IOP is effectively controlled (Mckinnon et al., 2008). Recent studies in experimental models of glaucoma revealed that RGCs undergo a prolonged phase of degeneration in glaucoma after IOP returns to a normal level as a result of T cell infiltration and activation; whereas, mice raised in the absence of microflora (germ-free) do not develop neural damage under persistent high IOP (Chen et al., 2018). Heat shock proteins (HSPs) were identified as potential immunestimulating signals in patients and animal models of glaucoma (Luo et al., 2010). Studies of HSPs, which are highly conserved from bacteria to humans, in systematic autoimmune diseases have demonstrated their ability to serve as pathogenic autoantigens (Barbera´ et al., 2013; Shoda et al., 2016; Van Eden et al., 2019). In this chapter, we comprehensively summarize the evidence reporting the links between commensal microflora and immune responses in glaucomatous neurodegeneration and further explore the possibility of preventing neuron loss through manipulating the gut-retina axis.

2 Microbiota in neuroinflammation 2.1 Commensal microbiota and immune regulation There are approximately trillions of microbes in the human gut. Evidence has emerged that commensal microbiota plays a fundamental role in the induction, training and function of the host immune system (Dopkins et al., 2018; Fung et al., 2017). The immune system, vice versa, also contributes to shape and maintain the ecology of the gut microbiota as the microbiota promotes and serves all aspects of the immune system (Arrieta et al., 2014; Belkaid and Harrison, 2017). These commensals benefit the host by taking in excessive and indigestible polysaccharides and fibers and producing short-chain fatty acid and vitamins (Rowland et al., 2018).

2 Microbiota in neuroinflammation

Changes in the composition of microbiota are proved to be associated with various autoimmunity and metabolic diseases, including bowel cardiovascular diseases and many others (Clemente et al., 2012). To determine the effect of microbiota on distant organs, strategies like germ-free mice and rats have been developed as tools for research. Increasing evidence suggests that not only intestinal diseases, but also diseases in tissues distant from the gut, can be impacted by gut commensals (Horai and Caspi, 2019). Alterations in brain physiology and leakage of the blood-brain barrier (BBB) were detected in germ-free mice (Braniste et al., 2014; Erny et al., 2015). It was reported that increased bacterial products including the endotoxin lipopolysaccharides (LPS) and pathogen-associated molecular pattern molecules (PAMP) are produced due to the increased intestinal permeability. Chronic inflammation is thus induced in several tissues through the activation of pattern recognition receptors (PRRs). Although anatomical separation exists, it was shown that the above biological crosstalk occurs in the brain and retina (Ma et al., 2019).

2.2 Microbiota and the autoimmune diseases in the CNS Gut microbiota has been shown to modulate the development, maintenance and homeostasis of the central nervous system (CNS), including the retina (Tremlett et al., 2017). Germ-free mice and broad spectrum-antibiotic-treated mice exhibited a range of cognitive and neural developmental deficits in the absence of gut microbiota (Mayer et al., 2015). It is so far acknowledged that neurodegenerative diseases, like Alzheimer’s disease (AD), Parkinson’s disease (PD) and Huntington’s disease (HD), are closely associated with alterations in the gut microbiome through the gutbrain axis (Dinan and Cryan, 2017; Ghaisas et al., 2016). Tryptophan metabolites such as serotonin and kynurenine have important functions in both the brain and the gut, which indirectly supports a role of gut microbiota in the brain (O’mahony et al., 2015). A recent paper reported significant deficits in fear extinction learning in antibiotic-treated or germ-free adult mice, revealing significant alterations in gene expression in excitatory neurons and glial cells (Chu et al., 2019). Single-cell RNA sequencing of the brain indicated that the compositions of microbiota not only affect many physiological processes, including development, metabolism and immune cell functions, but also modulate behaviors, such as social activity, stress and anxietyrelated responses that are linked to diverse neuropsychiatric disorders (Chu et al., 2019). These results suggest that the disturbance of brain-gut-microbiota axis could result in the pathogenesis and the pathology of neurodegenerative disorders. Pathological mechanisms like impaired blood-brain barrier function, increased inflammation, and vascular dysfunction, such as that found in AD patients, are commonly shared in retinal neurodegenerative diseases, including age-related macular degeneration (AMD), diabetic retinopathy and glaucoma (Gupta, 2015; Kaarniranta et al., 2011). Gut microbiota metabolites and products may modulate retina-specific immune process and the related cells. Morita et al. reported that intake of a lactic acid bacteria mitigated age-related immune defects by reducing interferon-gamma (IFN-γ)

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producing inflammatory CD4-positive T cells in the small intestine and decreasing serum levels of pro-inflammatory cytokines. Interestingly, it also suppressed retinal inflammation by reducing macrophage infiltration thus attenuating RGC loss (Morita et al., 2018). Recently, an obesity-associated gut-microbiota has been shown to drive pathological angiogenesis toward abnormal choroidal neovascularization (CNV) in the retina (Rinninella et al., 2018). Gut commensals were reported to signal directly through the retina-specific T cell receptor to induce autoreactive T cells and trigger uveitis. In contrast, depletion of gut microbiota in animal models of uveitis tempered disease progression (Horai and Caspi, 2019). In patients with primary open angle glaucoma (POAG), increased titers of antibodies against Helicobacter pylori was detected, supporting an association of Helicobacter pylori to the pathogenesis of glaucoma (Chen et al., 2015; Izzotti et al., 2009). Distinct differences in the compositions of gut microbiota and serum metabolic phenotype between POAG patients and healthy individuals have also been reported, suggesting the potential correlation between gut microbiota and glaucoma (Gong et al., 2020). Together, the evidence supports the existence of a “gut-retina axis” which plays a role in the development and/or progression of chronic ocular neurodegenerative disorders, such as glaucoma (Fig. 1).

2.3 Microbiota and the blood-retina barrier The CNS is normally shielded behind the blood-brain barrier (BBB) from direct interaction with circulating immune cells, just as the eye is protected by blood-ocular barrier. The blood-ocular barrier is composed of two main barriers: the blood-aqueous barrier and the blood-retinal barrier (BRB), and it is of great importance for the maintenance of visual function (Cunha-Vaz, 1979). The BRB contains the inner and outer compartments; the inner compartment is formed by the tight junctions between retinal capillary endothelial cells, and the outer compartment by the tight junctions between retinal pigment epithelial cells (Cunha-Vaz and Maurice, 1967). The BRB is particularly critical in keeping the eye as an immune privileged site of the body and essential for the homeostatic microenvironment of the retina. Microbial imbalance can result in disruptions of BRB that subsequently can enable the translocation of microflora pathogens and promote the development and progression of ocular disease (Fig. 1). Breakdown of the BRB no longer protects the retina from peripheral leukocytes and induces microglia activation, which release free radicals and inflammatory cytokines. T helper cells, such as Th1 and Th17, may thus be recruited and produce the pro-inflammatory cytokines IFN-γ, TNF-α and IL-17, to participate in chronic neuroinflammation, which may further damage the BRB (Dopkins et al., 2018; Gerber and Nau, 2010). Alterations of the BRB are critically involved in the pathological progression of retinopathy and retinal neurodegeneration.

2.4 Microbiota and microglia development, maturation and function An important role of microbiota was shown to mediate microglia development and maturation (Tse, 2017). Microglia are originated from the yolk sac and migrate to the brain and retina before the formation of BBB or BRB, and their maturation is

FIG. 1 Schematic illustration of the hypothetic gut-retina axis. The gut microbiota is composed of a large number of bacteria that form a complex ecosystem. The continuous crossing-talk between gut microbiota plays a pivotal role in driving the metabolic pathways. Changes of the species and complexity of gut microbiota were reported in patients with glaucoma and may result in chronic low-grade inflammation that is linked to the increased intestinal permeability, the expression of inflammatory cytokines, and the weakened BRB. Consequently, this may lead to microglial activation and recruitment of mononuclear macrophages and T cells into the retina to contribute to RGC damage in glaucoma. A better understanding of the mechanisms that underlie the “gut-retina axis” may prompt new personalized therapy for glaucoma and other neurodegenerative diseases.

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regulated by a precise genetic program and environmental factors (Alliot et al., 1999). Developing microglia are usually associated with cellular development and proliferation, while the adult microglia are often associated with immune responses (Matcovitch-Natan et al., 2016). Mature microglia constantly sense the environment, promote neuronal operation, defend against injury and provide neuroprotection (Hickman et al., 2018). Germ-free (GF) mice are animals never exposed to bacteria and viruses. Mice were found to develop functional deficiency in innate immunity (Erny et al., 2015). They upregulated microglia transcription and survival factor Sfpi1, c-fms, and colony stimulating factor 1 receptor (CSF-1R)—a key element mediating microglial proliferation, maturation and function (Erny et al., 2017). Microglia from mice tri-colonized by three specific altered Schaedler flora (ASF) bacterial strains also showed different morphology, function and maturation compared to those of normal mice (Erny et al., 2015). Temporal eradication of host microbiota was shown to restore microglia features (Erny et al., 2015). In the mature brain and retina, invaded pathogens may release PAMPs that trigger microglia secretion of pro-inflammatory cytokines (Fung et al., 2017), thereby changing the inflammatory state in the CNS. Studies show that oral bacterial counts are higher in POAG patients, and chronic peripheral inflammation has also been suggested to contribute to the neurodegeneration in glaucoma by activating microglia (Astafurov et al., 2014). A study demonstrated that high-fat diets accelerate CNV by altering gut microbiota, leading to increased intestinal permeability, chronic inflammation and elevated production of IL-6, IL-1β, TNF-α, and VEGF-A (Andriessen et al., 2016). Short-chain fatty acids and microbiota-derived bacterial fermentation products, in contrast, restores microglia homeostasis (Fung et al., 2017). These observations suggest that not only the quantity, but also the complexity of microbiota, critically affect microglia prosperity. The host bacteria vitally regulated microglia maturation and function, and functional impairment microglia may be rectified, to an extent, by complex microbiota (Erny et al., 2015).

2.5 Microglia and neurodegeneration in glaucoma Microglia are residential macrophage-like cells in the CNS (Kierdorf and Prinz, 2017; Wei et al., 2019), being responsible for immune regulation. Upon stimulation, microglia undergo phenotypic alteration and contribute to pathological processes in the eye and brain. Microglial activation leads to a robust inflammatory response that includes increased expression of major histocompatibility complex class II (MHCII) on residential microglia and infiltration of monocytes and/or CD4 + T cells in the draining cervical lymph nodes (Williams et al., 2020). Microglia express many pattern recognition receptors. For instance, activated microglia depend on triggering receptors expressed on myeloid cells-2 (TREM2) pathway to initiate phagocytosis activity and cytoskeleton reorganization by binding to various ligands (Wolfe et al., 2019). TREM2 is necessary for microglia to phagocyte amyloid plaque, which is a key point for AD development (Liu et al., 2013). Moreover, microglia are able to

3 Heat shock proteins in glaucomatous neurodegeneration

secrete inflammatory cytokines including TNF-α, IL-6, IL-10, IL-12, IL-1β (Lee et al., 2002). A unique subtype of disease-associated microglia (DAM) was found to mediate the pathogenesis of AD. Inhibiting RIPK1, which is highly expressed by microglia, suppressed the transcription of DAM, in turn preventing the accumulation of amyloid plaques in AD (Keren-Shaul et al., 2017). Microglia thus play an extremely important role in the pathogenesis of CNS neurodegeneration. Similar to what is observed in the brain, homeostatic microglia perceive the environmental signals in the retina (Fig. 1). Active microglia are detected earliest around the optic nerve head (ONH) in DBA/2J mice, before RGC loss (Bosco et al., 2011). Activation of signal-regulating kinase-1 (ASK1), p38 mitogenactivated protein kinase (MAPK) and NF-κB drive microglia in a proinflammatory manner, leading to increased production of inflammatory cytokines, such as IL-1β, TNF-α, TGF-β or IFN-γ (Chi et al., 2014; Sappington and Calkins, 2008; Yuan and Neufeld, 2000). They induce the cell apoptotic pathways to cause RGC death and degeneration of the optic nerve (Beynon and Walker, 2012). Suppression of microglia activation has been shown to significantly improve RGC axonal transport and prevent subsequent neurodegeneration (Bosco et al., 2008; Wei et al., 2019).

3 Heat shock proteins in glaucomatous neurodegeneration 3.1 HSPs and their upregulation in glaucomatous neurodegeneration The molecular signals that link the function of microbiota to microglial activities remain as a central question in neurodegeneration. Heat shock proteins (HSPs) are some of the most abundant proteins in the cell and a series of stress response proteins existing in prokaryotes, including bacteria, or eukaryotes like human cells (Khong and Spencer, 2011). They belong to a superfamily of stress proteins, which is an important part of a complex defense mechanism that can improve cell survival under adverse environmental conditions; however, they have been also associated with multiple autoimmune diseases. For example, HSP60 is involved in the morbidity of rheumatoid arthritis (RA) (Barbera´ et al., 2013), Crohn’s disease (Baca-Estrada et al., 1994), Hashimoto’s thyroiditis (Tonello et al., 2015) and Juvenile rheumatoid arthritis (De Graeff-Meeder et al., 1991; Elst et al., 2008; Lorenzo et al., 2015); HSP27 was associated with psoriasis (Besgen et al., 2010); HSP90 contributed to the pathogenesis of systemic lupus erythematosus (Erkeller-Y€uksel et al., 1992), whereas HSP70 was related to the incidence of multiple sclerosis (Mansilla et al., 2014) and RA (Shoda et al., 2016). HSPs keep a conservative evolution by the stable species structure and are expressed in all microbes. Some HSPs are induced intracellularly for their housekeeping function, while others are induced by external stimulation for immunoregulation (Liu et al., 2014). HSPs are typically named according to the molecular size, covering from 10 to 100 kDa. For example, the 60-kD protein is described as HSP60. The classification of

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HSP family includes HSP100, HSP90, HSP70, HSP60 and small HSPs. They are located in various sites within cells, with HSP10, HSP60 and HSP75 presented in mitochondria, and others located in the cytoplasmic membrane, cytosol, endoplasmic reticulum or nucleus in physiological conditions (Xu, 2002). The cellular protective effect of HSPs is related to its chaperone function as well as the effect of anti-apoptosis and anti-necrosis; however, their involvement in the activation of inflammatory cells in autoimmunity was also demonstrated (Kregel, 2002; Piri et al., 2016). Different HSP families are found to have their respective roles in neurodegeneration under stressful stimulation. In a rat model of glaucoma, HSP27 was described to relate to RGC apoptosis and cell damage (Tezel and Wax, 2000); HSP60 participated in the immune responses by elevating the secretion of IL-1β (Swaroop et al., 2016, 2018); HSP70 was the target response protein, protecting cells from apoptosis and necrosis via the suppression of caspase-3 and caspase-9 pathways (Dong et al., 2016; Li et al., 2000; Vasaikar et al., 2015); HSP90 was reported to promote mistranslation in cell stress resulting from the degradation of mutants (Stothert et al., 2017). HSP upregulation is reported in rats and humans with glaucoma (Park et al., 2001; Tezel et al., 2000) as well as in many stressed or injury conditions of the CNS. It is reported to affect the learning and memory formation in AD patients through abnormal calcineurin elevation (Kim et al., 2015). HSP27 and HSP60 were increased in RGCs of microbead induced glaucoma models, and rats inoculated with human HSP27 and HSP60 exhibited glaucomatous optic neuropathy (Chen et al., 2018; Wax et al., 2008). The data suggested that HSPs were involved in the pathogenesis of glaucoma and CNS neurodegeneration. Microglia, being residential macrophages in the CNS, are thought to be mediated by HSP signaling (Kakimura et al., 2002). HSP-release into the extracellular environment is usually an indication of loss of cell integrity and serves as a “danger signal.” HSP-release elicits microglia and innate immune responses through toll like receptor 2 (TLR2) and TLR4 to secrete pro-inflammatory cytokines, such as IL-1β, IL-6 and TNF-α (Jin et al., 2014; Rosenberger et al., 2015; Swaroop et al., 2016). Interestingly, microglia in GF mice is shown to lack TLR2 and TLR4 (Erny et al., 2015) providing an explanation for the lack of microglial activation in these mice. HSP-stimulated microglial activation plays an important role in neuroinflammation via inducing nuclear factor κB (NF-κB) and p38 mitogen-activated protein kinase pathways. HSP60 upregulation enhanced IL-1β secretion and microglial activation (Swaroop et al., 2018). Also, elevated levels of anti-HSP60 antibody in human serum and aqueous humor correlated with microglia activation in glaucoma patients (Bell et al., 2018), supporting the induction of HSP-specific autoimmunity. HSP27 immunization in rats was linked to increased inflammatory cytokine FasL release and microglia activation (Wax et al., 2008). As these studies suggest an association between HSP upregulation and microglial activation, more direct evidence is needed to uncover their complex interactions.

3 Heat shock proteins in glaucomatous neurodegeneration

3.2 The role of HSPs in autoimmune conditions and neurodegenerative diseases, including glaucoma HSPs, especially those presented in the extracellular space, are found to be highly immunogenic and can be processed and presented by antigen presenting cells to stimulate T cell responses. Recent evidence revealed a critical role for adaptive immunity, particularly HSP-specific T cell responses, in mediating glaucomatous neurodegeneration (Chen et al., 2018; Wax et al., 2008). HSPs have been shown to act as pathogenic autoantigens in many autoimmune diseases (Binder, 2014). This was also observed in mouse models of glaucoma (Grotegut et al., 2020). It is reported in mouse models of glaucoma that RGC loss proceeds in two phases: an initial phase that starts soon after IOP elevation and a second prolonged phase that begins at 2 weeks post IOP elevation but continues after IOP returns to the normal range (Chen et al., 2011, 2018). Elevated IOP induced HSP-responsive IFN-γ-secreting CD4 + T (TH1) cell infiltration into the retina as well as T cell immunity specific to HSPs, leading to the prolonged phase of neurodegeneration. Using T cell deficient mice and adoptive T cell transfer, it was established that T cell-mediate responses are both essential and sufficient for the second phase of glaucomatous neuron loss. In contrast, the initial phase of glaucomatous neurodegeneration was not blocked by T cell deficiency. CD4 + IFN-γ + and CD4 + IL-4 + T cells were detected in the retinas of POAG patients (Guo et al., 2018). Similarly, a marked increase in the frequency of HSP-specific T cells was detected in POAG patients compared to age-matched healthy controls, supporting the human relevance (Chen et al., 2018). Involvement of HSPs in glaucomatous neurodegeneration is multifaceted. On one hand, HSPs contribute to neuroprotective compensation partly through stimulating cytokine production or enhancing phagocytosis (Kakimura et al., 2002). Upregulation of HSP70 was recognized to protect RGCs from apoptosis and necrosis by reducing caspase-9 and caspase-3 expression (Dong et al., 2016). On the other hand, HSPs act as autoantigens in T cell-mediated glaucoma neurodegeneration (Chen et al., 2018). Bacterial and host HSPs are likely the natural antigens that originally induce HSP-specific memory T cells. In glaucoma, HSP27 and HSP60 are upregulated and stimulate both the innate and adaptive immune response in vivo to cause RGC death (Kalesnykas et al., 2007). Moreover, HSPs also initiate the adaptive immune responses through presenting pathogenic antigens to activate the T cell system. When HSPs bind with antigen peptides, the HSP-antigen complex is generated. After the complex reaches the endoplasmic reticulum, MHC loads and transfers it to the cell membrane, where the antigen is presented to the T cells. This mechanism of antigen presentation changes the prime-T cell to an effective-T cell (Tsai et al., 2019). Besides T cell responses, increased serum levels of HSP-specific antibodies were detected in human patients and animal models of glaucoma (Tukaj and Kaminski, 2019). Exogenous administration of HSP27 antibodies induced neuronal apoptosis and RGC loss, partly by attenuating the stabilizing effect of native HSP27 on actin

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cytoskeleton (Tezel and Wax, 2000). Higher levels of anti-HSP60 antibodies were mainly found in patients with normal tension glaucoma (Guo et al., 2018), which caused RGC loss in animal models due to IgG deposition and microglia activation (Bell et al., 2018). In line with the critical immune regulation by HSPs, mice raised in the absence of commensal microflora (germ-free mice), where immune cells have not been preexposed to bacterial HSPs, do not develop glaucomatous neurodegeneration at all after IOP elevation (Chen et al., 2018). Concomitantly, elevated IOP was unable to initiate HSP-specific T cell responses in germ-free mice (Chen et al., 2018). The results strongly suggest that elevated IOP in glaucoma presents merely a physical stress to RGCs and axons; the subsequent stress-induced events involving retinal inflammation and adaptive immune responses are keys to the pathogenesis of glaucoma. It is thus hypothesized that induction of immune tolerance to HSPs may have a therapeutic potential for preventing neurodegeneration and treating glaucoma. A critical mechanism in the development of self-tolerance involves an immuneregulatory process mediated through specialized regulatory cells, especially regulatory T cells (Van Eden, 2018). These regulatory T cells are active regulators that down-modulate autoreactive immune cells and propagate an active form of dominant tolerance; restoration of tolerance under the diseased conditions usually depend on improving regulatory T cell presence and function. Studies in experimental autoimmune encephalomyelitis model have demonstrated successful induction of tolerance to HSP60 by intranasal administration of HSP60 epitope (Billetta et al., 2012; Zhong et al., 2016). HSP60 peptide treatment in mice led to the induction of HSP60-specific regulatory T cells and attenuated brain and spinal cord neural damage with significant improvement of clinical symptoms. Being microbiota-associated antigens, it is not surprising that HSPs were suggested to be dominant in tolerance induction (Russler-Germain et al., 2017). Possible mechanistic explanations may include their conservative sequences, frequent MHC ligand source and stress-induced upregulation, that act in synergy for the outcome. To date, the initiation and pathways of tolerance induction remain to be further elucidated.

4 Interactions between T cells and microglia 4.1 CNS T cell infiltration and activated microglia T lymphocytes, which are an important player of the immune system, are categorized into T helper cells, regulatory T cells, and cytotoxic T cells. Once activated, T cells divide rapidly, secrete cytokines and further differentiate into subtypes to assist immune responses (e.g., Th1 secrete IFN-γ, Th2 secrete IL-4, Th17 secrete IL-17, Treg secrete TGF-b, etc.). The roles of pathogenic T cells in CNS neurodegeneration and autoimmunity are attracting increasing investigations. T cell infiltration was detected in the brain of PD patients, specifically reacting to antigenic MHCII derived from α-synuclein (Schetters et al., 2017). In patients with AD, increased T cells were also

4 Interactions between T cells and microglia

found in the brain and located closely to microglia (Rogers et al., 1988). As recent studies showed that retinal ischemia or transient elevation of IOP both induced T cell infiltration into the retina (Chen et al., 2018; Korn and Kallies, 2017; Thi Hong Khanh Vu et al., 2020), the data point toward critical involvement and infiltration of T cells in CNS neurodegenerative diseases. The key question is what has attracted T cells into the CNS, an immune privileged site that is supposed to be shielded from peripheral immune cells. Virtually in all injury or disease conditions in the CNS, including AD, PD and glaucoma, microglia become activated and migrate to the site of inflammation. This can occur within hours following injury or neuronal insult (Kawabori and Yenari, 2015). Activated microglia undergo phenotypic and functional changes by producing inflammatory cytokines, chemokines, complement and trophic factors. The innate immune responses initiated by microglial activation usually set a foundation for subsequent adaptive immune cells (Nayak et al., 2014). Antigens released from the degenerating neurons within the CNS may recruit antigenspecific T cells into the brain or retina in patients with AD, PD or glaucoma (Chen et al., 2018; Korn and Kallies, 2017). It is acknowledged that the accumulation of reactive microglia and T cells is commonly observed during neurodegeneration (Ellwardt et al., 2016; Korn and Kallies, 2017; Perry et al., 2010; Schetters et al., 2017). In the brain of PD patients, CD8+ cells were found in close proximity of activated microglia (Schetters et al., 2017). Electron micrograph from gray matter of an AD patient illustrated T cells in apposition to microglia with less dendrites (Togo et al., 2002). Evidence has also been shown that activated microglia and T cells were found to colocalize at the sites of demyelination and oxidative damage in multiple sclerosis (Grebing et al., 2016; Haider et al., 2011; Lucchinetti et al., 2011) and EAE (Greter et al., 2005; Murphy et al., 2010). As parts of the immune response, functional microglia and T cells show some spatial and temporal overlaps, but the interaction of these two cell types at the sites of neurodegeneration remains obscure. Activation of microglia occurs within a day after CNS ischemia/injury (Ahmed et al., 2017; Kawabori and Yenari, 2015), long preceding the detection of infiltrated T cells. In the early stage of EAE, transient disruptions of focal vessels precede microglia activation that is detectable at day 3–6, followed by infiltration of circulating dendritic cells and T cells at day 6–12; these events occur before the clinical onset of disease (Barkauskas et al., 2015). During EAE, the kinetics of myelin uptake by CNS-resident cells suggests that CX3CR1+ CD11b+ microglia are the first cell type to contain myelin antigen, likely modulating T cell responses inside the brain before peripheral APCs arrive (Sosa et al., 2013). In glaucoma and ischemic optic neuropathy, microglial activation as a primary event before RGC death is followed by T cell infiltration into the retina that results in prolonged RGC death (Bosco et al., 2015; Ramirez et al., 2017; Rojas et al., 2014; Thi Hong Khanh Vu et al., 2020; Williams et al., 2017). These observations suggest that activated microglia recruit T cells into the retina and brain under pathological conditions.

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4.2 CNS/retina: An immune privileged site The CNS is an immune privileged site, normally without peripheral immune cells and limited expression of MHC molecules. However, increasing studies reveal that peripheral immune cells, like T cells, could gain access to the CNS and interact with residential microglia and neurons (Korn and Kallies, 2017). Currently, the mechanisms of how T cell infiltrate into the CNS is still unclear. Effective T cell responses are accompanied by antigen presentation, either with MHCI or MHCII for CD8+ and CD4+ T cells, respectively. While the expression of MHCII in CNS is relatively low in stable condition, it is quickly upregulated in activated microglia (Wyss-Coray and Mucke, 2002). Activated microglia is the primary cell type expressing MHCII in the brain and retina. They were found in close proximity and temporal interaction with T cells, where neurodegeneration and cell death take place. Currently, there is no evidence suggesting that microglia could migrate to the draining lymph nodes of the eye or brain, where antigens are presented to naı¨ve T cells in the periphery (Engelhardt et al., 2017). Theoretically, there should be another mediator in between, bridging the antigen presenting process. Microglia also express PRRs, which bind and internalize foreign or misfolded proteins and are upregulated during neural damage or inflammation (Perry et al., 2010). The same PRRs are used in dendritic cells for antigen uptake and functioning as an APC of T cells. Thus, microglia have the potential for antigen uptake and presentation while they also modulate T cell responses once they enter the brain or the eye (Schetters et al., 2017). These findings provide important insight into the functions of T cells and their involvement in the pathological process of glaucoma and CNS neurodegeneration.

5 Conclusion Inflammatory response is a pathogenic component underlying neurodegeneration in glaucoma. Microbiota play a fundamental role in the development, maturation, and function of the immune system and in the regulation of BRB and BBB permeability. Microglia are the first-line defending system in the CNS that supervise and participate in the immune response and repairing process, in which development and maturation are mediated by microbiota. HSPs are critical signaling molecules that trigger inflammatory responses and activation of T cells, which also need to be presensitized by commensal microflora in order to propagate progressive neurodegeneration in glaucoma. Research on gut-retina and gut-brain axis has emerged in the past decade to link neurological conditions from glaucoma to AD. These studies may one day lead to the identification of microbiota biomarkers to stratify individuals for personalized therapy.

Acknowledgment This work was supported by NIH/NEI grants EY025913, EY025259, and P30EY003790 and Massachusetts Lions Foundation grant.

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The role of neuroinflammation in the pathogenesis of glaucoma neurodegeneration

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Maria D. Pinazo-Dura´na,b,∗,†, Francisco J. Mun˜oz-Negreteb,c,†, Silvia M. Sanz-Gonza´leza,b, Javier Benı´tez-del-Castillob,d, Rafael Gim
enez-Go´mezb,e, Mar Valero-Vello´a, Vicente Zano´n-Morenoa,b,f,‡, and Jos
e J. Garcı´a-Medinaa,b,g,‡ a

Ophthalmic Research Unit “Santiago Grisolı´a”/FISABIO and Cellular and Molecular Ophthalmo-biology Group of the University of Valencia, Valencia, Spain b Researchers of the Spanish Net of Ophthalmic Research “OFTARED” of the Institute of Health Carlos III, Net RD16/0008/0022, Madrid, Spain c Ophthalmology Department at the University Hospital “Ramo´n y Cajal” (IRYCIS) and Surgery Department at the Faculty of Medicine, University Alcala de Henares, Madrid, Spain d Department of Ophthalmology at the Hospital of Jerez, Jerez de la Frontera, Ca´diz, Spain e Department of Ophthalmology at the University Hospital “Reina Sofia”, Co´rdoba, Spain f International University of Valencia, Valencia, Spain g Department of Ophthalmology at the University Hospital “Morales Meseguer” and Department of Ophthalmology at the Faculty of Medicine, University of Murcia, Murcia, Spain ∗ Corresponding author: e-mail address: [email protected]

Abstract The chapter is a review enclosed in the volume “Glaucoma: A pancitopatia of the retina and beyond.” No cure exists for glaucoma. Knowledge on the molecular and cellular alterations underlying glaucoma neurodegeneration (GL-ND) includes innovative and path-breaking research on neuroinflammation and neuroprotection. A series of events involving immune response (IR), oxidative stress and gene expression are occurring during the glaucoma course. Uveitic glaucoma (UG) is a prevalent acute/chronic complication, in the setting of chronic anterior chamber inflammation. Managing the disease requires a team approach to guarantee better results for eyes and vision. Advances in biomedicine/biotechnology are driving a tremendous revolution in ophthalmology and ophthalmic research. New diagnostic and imaging

†

Authors sharing the first place M.D.P.-D. and F.J.M.-N. Group leaders equally contributing to the last place V.Z-M and J.J.G-M.

‡

Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.07.004 © 2020 Elsevier B.V. All rights reserved.

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modalities, constantly refined, enable outstanding criteria for delimiting glaucomatous neurodegeneration. Moreover, biotherapies that may modulate or inhibit the IR must be considered among the first-line for glaucoma neuroprotection. This review offers the readers useful and practical information on the latest updates in this regard.

Keywords Glaucoma, Neurodegeneration, Neuroinflammation, Uveitic glaucoma, Imaging, Artificial intelligence, Neuroprotection

1 Introduction Glaucoma is a chronic irreversible sight-threatening disorder (elevated intraocular pressure (IOP) is the major risk factor), leading to retinal ganglion cell (RGC) damage and death by apoptosis and, subsequently, to optic nerve (ON) fibers loss. No cure exists for glaucoma neurodegeneration. The unique glaucoma therapy are medical and surgical proceedings directed to increase outflow facilities and lowering IOP (Stamer, 2012). Currently, the molecular and cellular alterations underlying the disease are still diffuse; perhaps the biggest reason for the delay in identifying an effective neuroprotectant and to fight efficiently against glaucomatous blindness (Morrone et al., 2015; Nucci et al., 2018; Sacca` et al., 2019; Stamer, 2012). Biomedical and biotechnological advances and the irruption of the artificial intelligence (AI) in managing glaucoma are speedily leading to a new era for a better eye and vision care (Kim et al., 2017; Liesenborghs et al., 2020). In this context, oxidative stress (OS), mitochondrial failure, neuroinflammation (NI), neuroprotection (NP), and multimodal imaging-, gene-, tissue engineering-based diagnostic and therapeutic approaches, have to be now seriously acknowledged. This review offers useful and practical information on the latest updates on glaucoma neurodegeneration: “The link between NI and OS,” “Genetics-Omics in NI,” “Update on uveitic glaucoma,” “Imaging for NI” and “Clues in NP.”

2 The link between neuroinflammation and oxidative stress in glaucoma neurodegeneration 2.1 Neuroinflammation Neuropathological landmarks of glaucoma are the progressive lesion and death of RGC and the ON fibers loss (Osborne, 2008). Clinical and experimental studies point toward neurodegeneration, including impaired blood flow supply, mitochondrial dysfunction, OS, altered axonal transport, neurotrophic factors deprivation, etc. (Chitranshi et al., 2018; Pinazo-Dura´n et al., 2015). Immune response (IR) is involved in health and disease (Cronkite and Strutt, 2018; Murakami et al., 2020) (Table 1), but when involves the central nervous system

2 The link between NI and OS in GL-ND

Table 1 Mechanisms of innate and adaptative immunity. Immune response

Defense line

Innate (nonspecific)

First

Adaptive (specific)

Second

Cell phenotypes

Antigen dependency

Immediate (0–96 h)

Natural killers Macrophages Neutrophils Basophils Eosinophils Mastocytes Dendritics

Independent

Long term (>96 h)

T and B lymphocytes

Dependent

Timeline

Example Conjunctiva and other mucous membranes, hair, skin, phagocytes, granulocytes, inflammasomes Swelling, redness, pus, T and B lymphocytes

(CNS), is referred as NI (DiSabato et al., 2016; Lynch, 2020). Major actors playing pivotal roles in this matter are the resident CNS cells (macroglia, microglia, endothelial cells, perivascular macrophages) (Mendonca et al., 2020; Ramı´rez et al., 2017; Williams et al., 2017), a wide spectrum of cytokines, reactive oxygen species (ROS) and secondary messengers (Ashhurst et al., 2014; de Arau´jo Boleti et al., 2020; Zanon-Moreno et al., 2009) (Fig. 1). However, NI is also a process mediated by the inflammasomes, that when activated via the caspase 1 [plus activation of major pro-inflammatory precursors: interleukins (IL) -1β and -18] act as intracellular sensors (signaling platforms), to defend the CNS against pathogens (Chi et al., 2014; Zanon-Moreno et al., 2018). The IR is involved in glaucoma (Adornetto et al., 2019; Gauthier and Liu, 2016; Ramı´rez et al., 2017; Tezel et al., 2007; Wei et al., 2019; Williams et al., 2017), but some of its neurophysiological underpinnings remain speculative and need further investigation. Structural and functional probes are essential for determining NI involvement in glaucoma. Some clinical markers have been precisely reported to pinpoint the pathologic manifestations and to reflect disease progression (Colligris et al., 2012; Yap et al., 2018). Convincing evidence strongly supports the outstanding role of multimodal imaging (MMI) and AI systems (Fig. 2) to provide information on the glaucoma changes (Devalla et al., 2019; Zheng et al., 2019), that will be addressed in advance. Nevertheless, clinical approaches are unable to specifically reflect the bioactive changes occurring in the glaucomatous eye, important for establishing the NI stage and the prognosis of disease. Circulating molecular-genetic biomarkers for NI include: pro-inflammatory cytokines and chemokines (Bauer et al., 2018; Pinazo-Dura´n et al., 2013; Sun et al., 2018; Von Thun Und Hohenstein-Blaul et al., 2017), pro-apoptotic molecules (Pinazo-Dura´n et al., 2013; Wang et al., 2015), OS by-products (Pinazo-Dura´n et al., 2018; Sacca` et al., 2016; Zano´n-Moreno and Pinazo-Dura´n, 2008), C-reactive protein (de Voogd et al., 2006), proteomic and metabolomic profiles (Barbosa-Breda et al., 2018; Sato et al., 2018), long non-coding RNAs, micro RNAs (O’Connell et al., 2012), auto-antibody profiles (Moroi et al., 2019), etc.

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FIG. 1 Inflammation plays a pivotal role as part of a complex biologic answer of the immunity directed to a wide spectrum of damaging agents, by means of the innate and adaptative immunity. When occurring in the central nervous system it is called neuroinflammation, as shown in this drawing. Astrocytes are neuroglial cells with specific morphological and functional characteristics according to the area of the brain and neurosensory organs. Microglial cells are the CNS macrophages that in normal conditions are constantly taking care of the nervous tissue. When a damaging agent attacks the CNS, the microglia starts activation in order to recruiting other immune cells to fight against the pathogen.

DEEP LEARNING

MACHINE LEARNING ARTIFICIAL INTELLIGENCE

FIG. 2 Onion-peel model of applied artificial intelligence (AI) systems. The AI is the ability of a machine to mimic human intelligence. As subfields of the AI, the deep learning synthesizes images in ways that will make easier the diagnosis of a disease. It is based on the pattern extraction from data. Machine learning utilizes algorithms for parsing data, learning from them and finally launching a suggestion (or prediction) for the diagnosis or treatment of a disease.

2 The link between NI and OS in GL-ND

2.2 Oxidative stress in glaucoma neurodegeneration Imbalance between excessive ROS production and its insufficient neutralization by antioxidant (AOX) defense molecules is known as OS. This mechanism has been directly implicated in glaucoma pathophysiology involving the trabecular meshwork (TM), retina and OP, leading to a hallmark event in the disease: the RGC death and ON degeneration (Osborne, 2008). The OS is capable to induce NI through several pathways (Fig. 3): (1) Secretion of pro-inflammatory cytokines from neuroglial cells in response to increased oxidative dysbalance. Higher levels of IL-6, transforming growth factor-beta (TGF-β), and tumor necrosis factor alpha (TNFα) were reported in response to oxidative attack in glaucomatous retinas (Tezel et al., 2007). (2) Expression of the nuclear factor kappa B (NF-κB), inducing several pro-inflammatory responses in relation to OS (Yang et al., 2016). (3) Augmented retinal IR, through increasing antigen-presenting molecules on the glial cells surface (Ebneter et al., 2010). (4) Increased levels of glial toll-like receptors (important elements of innate immunity in astrocytes and microglia), in response to OS, as seen in the glaucomatous retinas (Luo et al., 2010). (5) Dysregulation by ROS excess of several proteins of the complement system, as the complement factor H (Tezel et al., 2010). (6) Deposition of advanced glycation end products (AGEs) in the extracellular matrix and subsequent activation of specific cell signaling pathways, in relation to OS. Moreover, AGEs may induce ROS generation feeding back the process (Kandarakis et al., 2014). Thus, AGEs may constitute long-term pro-inflammatory inductors of neurodegeneration (Yang et al., 2016). (7) Inflammasome activation by OS, as intracellular sensors to defend the cells and tissues from damaging agents (Chi et al., 2014; Guo et al., 2015; Yerramothu et al., 2018; Zanon-Moreno et al., 2018). (8) Increased phagocytosis, as a consequence of pro-inflammatory cytokines releasing facts within the

Induction of pro-inflammatory cytokines Increase of antigen-presenting molecules Dysregulation of complement system AGEs deposition in extracellular matrix Augmented RAGEs

Oxidative Stress

Activation of NF-κB Increase levels of glial toll-like receptors

Neuroinflammation

Activation of inflammasomes

Phagocytosis Effects of pro-inflammatory cytokines

FIG. 3 Oxidative stress and neuroinflammation mechanisms. These processes may mutually feed-back each other by different processes in glaucoma disease. Some of them are reflected in the drawback.

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inflammatory background, inducing ROS generation (Ahmad and Ahsan, 2020). To summarize, the OS overload stimulates the IR and the RGC susceptibility to ocular hypertension (OHT), leading to glaucoma neurodegeneration, as previously shown in Fig. 3.

3 Genetics and omics in glaucoma neuroinflammation Inflammatory processes play important roles in glaucoma ethiopathogenesis (Adornetto et al., 2019; Wei et al., 2019; Williams et al., 2017). Fig. 1 (in Section 2.1) illustrates the cascade of events in NI. This response is neuroprotective in nature, but when prolonged in time it is prone to induce a wide spectrum of pathologies. Nevertheless, the exact mechanisms by which the inflammatory response can stimulate the onset/progression of glaucoma remain to be elucidated.

3.1 Polymorphisms of cytokine genes in glaucoma neuroinflammation The balance between pro- and anti-inflammatory cytokines determines the onset of inflammation, and the TM and retinal damage (Holan et al., 2019). Main proinflammatory cytokines (signaling molecules secreted by immune cells for encouraging inflammation) include: IL-1β, IL-2, IL-6, IL-8 and TNFα. Anti-inflammatory cytokines (immunoregulatory molecules for controlling the pro-inflammatory response) comprise: IL-4, IL-6, IL-10, IL-11, IL-13 and TGF-β. We will address point by point the cytokine-related molecular and genetic facts involved in glaucoma NI and NP (Table 2). – IL-1 (secreted by macrophages in response to TNFα) exerts functions as proinflammatory/vasodilator/pro-apoptotic, contributing to neurodegeneration (Wooff et al., 2019). Significant association between the haplotype formed by 2 polymorphisms of the IL1β gene (
31C/T: rs1143627: T > C,
511C/T: rs16944C > T) and primary open-angle glaucoma (POAG) were reported, demonstrating strong relationship of this haplotype with the glaucoma risk (Oliveira et al., 2018). – IL-2 stimulates the secretion of IL-1 and TNF (α, β). Lumi et al. (2019) did not find significant data on polymorphisms in genes of different cytokines, including IL-2, in relation to retinal degeneration. Tong et al. (2017) found significantly higher vitreous IL-2 levels in acute angle-closure glaucoma (AACG) vs cataracts, suggesting that IL-2 could be used as severity biomarker for AACG. No other reports on the glaucoma role of IL-2 have been found in the literature. – IL-6 (cytokine with pro-/anti-inflammatory activities) participates in metabolic and neural processes (Scheller et al., 2011). Our group reported significantly higher IL-6 plasmatic concentration in smoking glaucomatous elder women vs controls (Zanon-Moreno et al., 2009). Using IL-6 knockout mice, Echevarria et al.

Table 2 Cytokine genes studied and their relation to glaucoma. Cytokine

Type

Gene

Polymorphism

Study sample

Result

IL-1

Pro-inflammatory

IL-1B

rs1143627 (
31 T > C) rs16944 (
511C > T)

Human (POAG patients vs healthy controls)

C/T haplotype (
31/
511) is a risk factor for POAG

Oliveira et al. (2018)

IL-2

Pro-inflammatory

Human (acute angleclosure glaucoma vs cataracts)

Tong et al. (2017)

IL-6

Pro-inflammatory

No genetic studies. Higher vitreous IL-2 levels in AACG. IL-2 may be a useful biomarker for AACG severity IL-6 is associated with increased expression of TNFα, SOCS3 and Bax genes C allele is associated with smaller C/D ratio, larger NR and thicker RNFL. Also, there were higher serum IL6 levels in advanded NTG. GC genotype could be a marker for NTG severity CC genotype of rs1800871 and AA genotype of rs1800896 are associated with susceptibility to glaucoma TGF-β could play an important role to the manifestation of POAG

IL-6

Anti-inflammatory

IL-10

Anti-inflammatory

IL-10

TGF-β

Anti-inflammatory

TGFB1 TGFB2

Mouse

rs1800795 (
174G > C)

Human (NTG patients: early-moderate vs advanced stage)

rs1800871 (
819C > T) rs1800896 (
1082A > G)

Human (PEX, PEXG, POAG vs healthy controls)

Human (article review)

Echevarria et al. (2016)

Wang et al. (2017)

Fakhraie et al. (2020)

Danford et al. (2017)

POAG: primary open-angle glaucoma; AACG: acute angle-closure glaucoma; NTG: normal tension glaucoma; PEX: pseudoexfoliation syndrome; PEXG: pseudoexfoliation glaucoma; C/D: cup-to-disk; NR: neuroretinal area; RNFL: retinal nerve fiber layer.

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(2016) found significantly lower retinal levels of glycoprotein as well as TNFα, Socs3 and Bax genes expression that in the wildtype mice, suggesting that IL-6 plays a role in NI regulatory signaling, related to the retinal response to glaucoma stressors. An interesting study conducted by Wang et al. (2017) in normal tension glaucoma (NTG) analyzed the association between the IL-6 (-174) polymorphism and clinical parameters. Smaller cup-to-disk ratio, larger neuroretinal area, and thicker retinal nerve fiber layer (RNFL) were reported in NTG patients with the GG genotype. Significantly higher serum IL-6 levels were identified in patients with advanced-stage NTG compared to early-moderate NTG, concluding that both the GC genotype of the IL-6 gene polymorphism and serum IL-6 levels could serve as NTG severity markers. – IL-10 inhibits other cytokine synthesis. Several polymorphisms of the IL-10 gene have been associated with glaucoma risk. Recently, the TT genotype of
819C/T and AA genotype of
1082A/G single nucleotide polymorphisms (SNP) of the IL-10 gene were significantly associated with susceptibility to pseudoexfoliation (PXF) syndrome, PXF glaucoma and POAG (Fakhraie et al., 2020). – IL-18 (belonging to IL-1 family) is involved in a variety of NI disorders. The nucleotide-binding oligomerization domain-like receptors (NLRs) generates after injury large signaling platforms known as inflammasomes (Chi et al., 2014; Guo et al., 2015; Zanon-Moreno et al., 2018), leading to activation of IL-1β and IL-18. Zhou et al. (2005) reported the involvement of the pro-inflammatory IL-18 in a mouse glaucoma model. Continuing with this section, an outstanding study by Danford et al. (2017) performed bioinformatic analysis of the POAGome, reporting 542 genes associated with POAG and related phenotypes. Also concluded that TGF-β signaling pathway may be important contributor to the POAG onset in the anterior and posterior eye segments.

3.2 Omics in glaucoma neuroinflammation Current knowledge on NI responses in glaucoma is based on the original concepts of response to disease (Soto and Howell, 2014). However, different areas of intensive research include the static and/or dynamic determinations of candidate molecules and genes regarding NI, by means of a variety of omics platforms: metabolomics, proteomics, lipidomics, transcriptomics, secretomics, genomics, epigenomics, and integrative multi-omics. Moreover, modern neuroimaging tools for the main NI elements, such as molecular imaging combining positron emission tomography, single photon computed emission tomography and the classic functional/structural imaging techniques (Zinnhardt et al., 2018), have to be considered to set up the basis to the MMI and multitracer tools for assessing NI in glaucoma.

4 Update on uveitic glaucoma

Using big data approaches and computational models in the context of interdisciplinary teams are essential to obtain precise NI signatures related to neurodegeneration (Dendrou et al., 2016) before to be translated to the glaucoma practice. Altogether the above data showed that NI plays important roles in glaucoma. Therefore, anti-inflammatory treatments have to be considered when managing the glaucomatous progression. Whether the NI processes are directly related to the glaucoma ethiopathogenic mechanisms, or perhaps may represent the consequence of the disease, is currently a major subject of intensive research.

4 Update on uveitic glaucoma Uveitic glaucoma (UG) includes a variety of disorders combining elevated IOP and uveitis. Different mechanisms may combine in the same patient. It is essential to investigate each case, to provide the most appropriate treatment. Essential concepts of UG mechanisms and management are:

4.1 Uveitic glaucoma pathophysiology Mechanisms of IOP elevation in UG are multiple. A combination of open and closed angle (OA/CA) increase of TM resistance and steroid response may be present in different extent (Fig. 4) (Kesav et al., 2020; Mun˜oz-Negrete et al., 2015). Otherwise, ciliary body inflammation could result in postoperative hypotony, thus complicating the surgical decision (Mun˜oz-Negrete et al., 2015) (Fig. 5). The OA/CA pathogenic UG-related processes will be exposed separately.

4.1.1 Open angle mechanism Although aqueous proteins levels are often increased in UG (Kalogeropoulos and Sung, 2018), IOP elevation is related to reduced tonographic outflow facility (Alaghband et al., 2019). Trabeculitis could contribute in some etiologies, like herpetic uveitis (Kalogeropoulos and Sung, 2018). IL-6, IL-8, monocyte chemotactic protein (MCP)-1, TNFα and vascular endothelial growth factor (VEGF) levels are elevated in aqueous humor (AH) of UG (Ohira et al., 2016). Higher AH levels of angiotensin-converting enzyme in uveitis secondary to sarcoidosis, and elevated Rho-kinase expression in patients with Behcet’s disease (Kalogeropoulos and Sung, 2018) have been reported. Around one-third of UG patients treated with corticosteroids may respond with additional IOP elevation, being difficult to distinguish the impact of the IOP corticosteroid-induced of the underlying inflammation (Mun˜oz-Negrete et al., 2015).

107

Uveitic Glaucoma

Open Angle

Seclussion Pupillae

Iris

Sectorial Atrophy

Herpes

Heterochromy

Fuchs Heterochromic cyclitis

Closed Angle

Peripheral Atrophy. Pigment dispersion

UGH syndrome

IOL malposition

Ciliary body rotation/Choroidal Effusion

Peripheral anterior synechia

Normal

Adult Recurrent episodes

Posner Schlossman Syndrome

VKH syndrome

Child

JIA

UGH: uveítis, glaucoma Hyphema; IOL: intraocular lens; JIA: juvenile idiopathic arthritis; VKH: Vogt-Koyanagi Harada FIG. 4 Etiologic diagnosis of uveitic glaucoma.

4 Update on uveitic glaucoma

FIG. 5 Biomicroscopy of the anterior eye segment of a patient with uveitic glaucoma.

4.1.2 Closed angle mechanisms Secondary CA can result from seclusion pupillae, peripheral anterior synechia or neovascularization of the anterior chamber (AC) angle. Less commonly, a ciliary body forward rotation could contribute, as in Vogt-Koyanagi-Harada syndrome (Kalogeropoulos and Sung, 2018; Kesav et al., 2020; Mun˜oz-Negrete et al., 2015). These complex interactions determine high IOP fluctuations and great variability in therapeutic response.

4.2 Uveitic glaucoma treatment Management of UG requires a multidisciplinary approach with simultaneous control of IOP, inflammation, and etiologic treatment in cases. Here we show different diagnostic/therapeutic approaches.

4.2.1 Medical uveitic glaucoma therapy Current protocols used for treating UG are: – Anti-inflammatory Treatment—First step in UG management relays in controlling inflammation. Depending on the case, topical-periocularsystemic-intravitreous corticosteroids could be used, that may contribute IOP control. However, around 30% of patients can suffer additional IOP increase. Rimexolone and loteprednol induce less IOP elevation, but the anti-inflammatory effect is insufficient for UG. Non-steroidal anti-inflammatory drugs are not

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– –

– –

useful in UG, and partially could block the IOP reduction achieved by prostaglandin analogs (PGAs). Immunomodulators—Could be helpful in corticosteroid responders. Azathioprine, tacrolimus and methotrexate are the most commonly used. Adalimumab and infliximab (monoclonal antibodies) are recently used. Hypotensive eye drops—Effectiveness of antiglaucomatous medical treatment by hypotensive eye drops markedly vary in UG, ranging from no response to profound reductions. Traditionally, topical beta-blockers and carbonic anhydrase inhibitors (CAIs) have been considered the UG first-line agents. CAIs could be also useful in managing coexistent cystoid macular edema (CME). Brimonidine (second-line UG treatment) has the potential advantage of a mild mydriasis. Granulomatous anterior uveitis has been described after long-term use of alpha 2 agonists (Kesav et al., 2020; Mun˜oz-Negrete et al., 2015). Topical ripasudil (Rho-associated kinase inhibitor) appears to be safe, substantially reducing IOP in UG patients, data consistent with the comments on elevated expression of this enzyme in UG (Kusuhara et al., 2018). Topical PGAs use is controversial and must be avoided in patients with CME, previous complicated surgery or herpetic keratitis/keratouveitis, but could be really effective in controlled uveitis (Kesav et al., 2020; Mun˜oz-Negrete et al., 2015). Cholinergic agents produce a breakdown of the blood-aqueous barrier being contraindicated in UG. Antiviral treatment—Acyclovir or Valacyclovir are indicated in UG associated to herpetic uveitis. Topical ganciclovir could be helpful in cases with positive cytomegalovirus, Posner-Schlossman syndrome or Fuchs heterochromic cyclitis (Xi et al., 2018).

4.2.2 Laser glaucoma therapy – Laser peripheral iridotomy (LPI) is mandatory for preventing/treating AACG after posterior synechia. It is convenient to perform several, or larger LPIs due to the described increased rate of closure (Kesav et al., 2020; Mun˜oz-Negrete et al., 2015). – Argon laser trabeculoplasty (ALT) could damage the TM. No recommended for UG. – Selective laser trabeculoplasty (SLT). No clinical evidence for UG.

4.2.3 Glaucoma surgery Up to 30% of UG eyes need glaucoma surgery. Preoperative inflammation suppression contributes to improve outcomes. Caution is recommended on irreversible procedures and the use of antimetabolites, to prevent prolonged hypotony and phthisis bulbi. – Trabeculectomy with mitomycin C is less effective in UG. Most common complications are recurrent inflammation, hypotony and cataract progression.

5 Imaging methods for ocular inflammation and glaucoma

– The Ex-PRESS® mini-glaucoma shunt (Alcon Laboratories, Fort Worth, Texas, USA) (less invasive than traditional trabeculectomy) does not require a sclerectomy or peripheral iridectomy, with the advantage of less potential inflammation and hyphema. Success and complication rates are similar in UG and POAG, being bleb leak the most common complication in both cases (Dhanireddy et al., 2017). – Nonperforating deep sclerectomy (NPDS) avoids AC entry, iris manipulation, and sudden hypotony, reducing the risk of postoperative inflammation and hyphema. In the largest prospective study of NPDS in UG, the complete success rate was 72.7% of total eyes. 36% eyes required neodymium (Nd): YAG laser goniopuncture. Postoperative complications included cataract progression, transient hypotony and shallow choroidal effusions (Al Obeidan et al., 2015; Mercieca et al., 2017). – Canaloplasty (a promising technique for UG) expands the intertrabecular spaces, targeting an important source of outflow resistance (Kalin-Hajdu et al., 2014). – Glaucoma drainage devices (GDD; first choice for UG surgery) (Chow et al., 2018; Ramdas et al., 2019). In extensive peripheral anterior synechiae, the tube should be placed in the sulcus rather in the AC. Risk of macular edema and hypotony was slightly higher in UG patients. It was recently shown that Baerveldt shunt surgery, trabeculectomy and Ahmed shunt provided similar IOP reduction. Trabeculectomy group had a higher rate of early hypotony. Baerveldt group had a higher rate of late hypotony and significantly lower long-term failure rates (Chow et al., 2018; Ramdas et al., 2019; Valenzuela et al., 2018). – The XEN-45® implant (Imex, Valencia, Spain) has been shown effective for UG. Complications included bleb-related ocular infection and persistent hypotony (Sng et al., 2018). There is not clinical evidence about the use of other minimally invasive glaucoma surgery (MIGS) procedures in UG. Trabectome, Kahook and goniotomy has been described with different success or complication rates in UG. Most common postoperative complication was transient hyphema (Kesav et al., 2020; Mun˜oz-Negrete et al., 2015). – Cycloablative procedures can exacerbate inflammation, leading to postoperative hypotony and phthisis bulbi, and may be the last choice in poor vision eyes (when conventional drainages surgery failed) or eyeballs with special anatomic facts (Kesav et al., 2020; Mun˜oz-Negrete et al., 2015).

5 Imaging methods for ocular inflammation and glaucoma There is scientific evidence enough to consider the clinical NI diagnosis in the glaucoma practice. NI can be occurring in different eye sites (retina, ON, optic tract, and lateral geniculate nucleus) and the process can be taken place in blood, and other tissues and organs. Thus, new MMI techniques are needed to better identify the pathologic glaucoma mechanisms in lifetime.

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5.1 Anterior segment optical coherence tomography Called AS-OCT is a noncontact rapid imaging device that uses low-coherence interferometry to obtain cross-sectional images of the anterior chamber (AC) (Radhakrishnan et al., 2001). Critical diagnostic step in glaucoma is the analysis of the angle (Asrani et al., 2008). The AC measurements display good reproducibility, are semiautomated and not operator-dependent, being an objective/quantitative method (Li et al., 2007). The AS-OCT devices can be time-domain (TD), sweptsource (SS), and spectral-domain (SD) based configurations, with different properties-speed-resolution (Li et al., 2014). The SS- and SD-based imaging (different types of Fourier-domain OCT) offer higher imaging speed (up to 20–40 kHz linescan rate), because of its inherent signal-to-noise ratio advantage, vs TD-OCT configuration. The light source wavelength is the parameter that conditions the scan resolution. Higher resolution images are obtained with shorter wavelengths, but those decrease the depth penetration of images (Maslin et al., 2015). Different biometric measurements of the AES and the AC angle have been used and published elsewhere. Classically, these quantitative measurements were based in the scleral spur identification (Ferna´ndez-Vigo et al., 2016), but it could not be detected in around 30% of AS-OCT examinations (Sakata et al., 2008). High-resolution OCT devices even allow us to identify and measure the TM (Tun et al., 2013; Wong et al., 2009) and the Schlemm’s canal (Ferna´ndez-Vigo et al., 2019). Novel AC angle parameters based on Schwalbe’s line as a landmark, highly correlated with gonioscopy findings, and may be useful to quantify the AC angle (Qin et al., 2013). Our group have detected its high capacity for identifying occludable angles in real time within the clinical practice (Fig. 6A). Higher definition SD-OCT and SS-OCT devices could objectively measure pivotal inflammatory parameters of the AES, as the existence of cells and flare in the AH (Invernizzi et al., 2017). It has been reported that quantification of the AC cells, imaged by SS-OCT tools, displayed strong correlation with categorical clinical severity assessment in uveitis (R ¼ 0.88; P < 0.001) (Baghdasaryan et al., 2019). In the glaucoma context, AS-OCT imaging methods are interesting to evaluate the conjunctival scarring process of filtering surgery, by analyzing filtration blebs characteristics. Morphological parameters, quantitative (height, extension, volume, wall thickness) and qualitative (wall reflectivity, posterior episcleral fluid) can be measured in the conjunctival bleb (Mastropasqua et al., 2014) (Fig. 6B) and these findings have been related to biomicroscopic clinical milestones in the operated glaucoma eyes (Fakhraie et al., 2011; Wen et al., 2017), as well as to a greater or lesser extent, with functional hypotensive results of glaucoma surgery (Kojima et al., 2015; Oh et al., 2017; Wen et al., 2017). Different AS-OCT techniques have been used. En-face OCT blebs imaging are able to detect in the conjunctival stroma the presence of hyperreflective areas corresponding to conjunctival fibrosis, and the vascularity rate (Meziani et al., 2016). Polarization-sensitive OCT (PS-OCT) improves the image contrast and evaluates the birefringence, by imaging phase retardation of biological ultrastructural changes in fibrous tissues (Fukuda et al., 2014, 2018).

5 Imaging methods for ocular inflammation and glaucoma

FIG. 6 Anterior eye segment optical coherence tomography facts. (A) Anterior angle chamber parameters. (B) Morphological parameters can be measured in filtering blebs for managing glaucoma surgery outcomes.

Main AS-OCT limitation is that light energy cannot go deeper, being unable to penetrate tissues behind the iris pigment epithelium. Therefore, AS-OCT cannot provide images of structures posterior to the iris (i.e., the ciliary body).

5.2 Innovation in imaging techniques Imaging innovation is mainly based on OCT and its modifications, allowing greater resolution and acquisition of better skills, as in the following:

5.2.1 Optical coherence tomography angiography It was introduced in the 2000s, on the basis of the reflectance variation of the blood cells movement, applicable to better managing the inflammatory ocular diseases. Inflammatory injuries and vascular pathologies are difficult to distinguish with

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conventional techniques, but OCT angiography (OCTA) is capable to detect the injury in 3-D extension, and to inform about the choroidal vascularization, being an ideal method to quantify the vessels and ischemic areas, facilitating the early detection or recurrences of inflammatory eye processes (Tranos et al., 2019). OCTA provided more accurate imaging of the vessels in the filtering blebs and surrounding conjunctiva (within the Tenon’s capsule), and the deeper vascular plexus that cannot be achieved by other methods. Inflammation is reflected in the vascularity degree of blebs, constituting one of the most important predictors of the likelihood of glaucoma filtration surgery failure, and poor IOP control. The latter device may constitute a powerful research tool to better understand and predict outcomes of glaucoma surgery (Scott et al., 2015).

5.2.2 Hydra optical coherence tomography This is a dual wavelenght OCT in which the conventional device is extended by one more OCT (1060 nm wavelength), acquiring better and deeper images (Traber et al., 2020).

5.2.3 Optical coherence tomography elastography The acoustic radiation force elastography (ARF-OCE) was used to quantify the elasticity of retinal layering, being adaptable to in-vivo applications. ARF-OCE is able to detect structural changes due to mechanical stress and has been used in corneal pathologies (Du et al., 2019; Yap et al., 2019). ARF-OCE allows measurements of the stress effects on the ON head and anterior laminar surface (Qu et al., 2018). ARF-OCE provides information about glaucoma early damage and stratification risk.

5.2.4 Oximetry Retinal vessel oxygen changes are involved in glaucoma. Conventional oximetry has a limited resolution (up to 100 μm). Damodaran et al. (2019) has developed a scanning laser ophthalmoscope-based oximeter, which can measure retinal oxygenation in 50 μm diameter vessels.

5.2.5 Fluorescence lifetime imaging ophthalmoscope The FLIO quantifies the lifetime of retinal endogenous autofluorescence by changing the continuous wave blue laser of a scanning laser ophthalmoscope for a pulsed picosecond 473 nm and two spectral channels (498–560 nm), allowing distinguish between various fluorophores. It provides an image with the autofluorescence intensity and color code (red ¼ short lifetime; blue ¼ long lifetime) and a curve response corresponding to calculated biexponential decay curves over time, for individual pixel locations. FLIO have been used in Stargardt disease and other retinal pathologies (Dysli et al., 2016).

6 Clues in glaucoma neuroprotection

5.2.6 Hyperspectral image The HSI obtains a contiguous spectrum of wavelenght for every pixel. Images are combined to acquire a hypercube with 3-D data, formed by two spatial dimensions and one spectral dimension. These HSI have higher resolution than multispectral imaging which captures only red, green and blue wavelength (Reshet et al., 2020). HSI is used to asses and quantify arterial oxygen saturation in glaucoma eyes (Mordant et al., 2014). This spectral information can help to better understand the molecular processes related to ocular diseases, including inflammation (Mordant et al., 2014).

5.2.7 Detection of apoptotic retinal cells Cordeiro et al. (2004) set up the DARC technique that holds the potential to observe the NI and apoptosis in real time. Utilizes intravenous fluorescent annexin-A5 binding to phosphatidylserine on the cell membrane (early apoptosis marker). The detection is possible using a modified confocal scanning light microscopy. DARC was previously used to address different strategies to reduce apoptosis in experimental glaucoma, such as apoptotic decrease with agents blocking amyloid-β aggregation (Guo et al., 2007; Yap et al., 2020), and reduced OHT-induced RGC apoptosis in vivo by systemic administration of α2A agonists (Nizari et al., 2016). Other NP strategies studied with DARC were the topical coenzyme Q10 (CoQ10) (Davis et al., 2017), intravitreal adenosine-3 receptor (Galvao et al., 2015), and rosiglitazone formulations (Normando et al., 2016). DARC phase I trial, confirmed its safety and tolerability, also detecting differences between glaucomatous and healthy eyes. DARC phase II clinical trial was designed to characterize differences between the counts and distribution of spots comparing five groups: healthy volunteers, progressing glaucoma, age-related macular degeneration, optic neuritis, and Down’s syndrome (with similar amyloid-β deposition to that in Alzheimer’s disease). Therefore DARC offers a biomarker or a surrogate marker in NI research and NP strategies.

6 Clues in glaucoma neuroprotection A set of potential NP molecules are revisited below.

6.1 Potential glaucoma neuroprotectants Endpoint of glaucoma NP is to defend neurons. Being the OS and NI closely related processes in GL-ND, theoretically, the intake of nutritional AOXs may have a beneficial impact in these patients. In fact, dietary supplementation with resveratrol (nonflavonoid polyphenol with AOX properties), showed a decrease in inflammatory markers in a glaucoma model of TM in pigs (Luo et al., 2018), in rat retinas (Avotri et al., 2019; Means et al., 2020) and in human glaucomatous TM-cells

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(Wang and Zheng, 2019). There were also interesting results on NP against NI. In a murine model of OHT, tempol (superoxide dismutase mimetic and peroxynitritederived free radical scavenger) demonstrated more than twofold decrease levels in pro-inflammatory cytokines, with a significant reduction of NF-κB activation, in the retina and ON. Other substances with both AOX and anti-inflammatory properties such as saffron (Ferna´ndez-Albarral et al., 2020), baicalin (Gong and Zhu, 2018), curcumin (Radomska-Le
sniewska et al., 2019) or azithromycin have also been showed to present promising properties in non-human glaucomatous models (Varano et al., 2017). Other animal models have confirmed the OS-related mechanisms of NI and the usefulness of AOX interventions as immunomodulation strategy for NP GL-ND (Yang et al., 2016). However, a lack of knowledge exists in clinical trials on the influence of these antioxidants with anti-inflammatory effects. Results of the few studies performed in human glaucoma with AOX supplementation showed controversial results. Our group performed a controlled-randomized clinical trial by testing various combinations of AOX and minerals with no significant differences with placebo at the beginning/end of a 2-year follow-up (Garcia-Medina et al., 2015). Citicoline, CoQ10, (endo)cannabinoids, and palmitoylethanolamide have been reviewed by Nucci et al. (2018) in the context of glaucoma NP. Sacca` et al. (2019) also reviewed a series of substances that can highly contribute to NP, such as the polyphenols, gingko biloba and polyunsaturated fatty acids. In the context of NI in GL-ND, experimental modulation or blockage of specific pro-Inflammatory pathways, seems to be itself a promising NP mechanism (Gauthier and Liu, 2016; Pinazo-Dura´n et al., 2013, 2015, 2018; Sun et al., 2018). Yadav et al. (2020) have described newer bio-tactics for RGCs NP in GL-ND. Experimental studies have been testing a high amount of neuroprotectant candidates for neurodegenerative disorders, but these cannot predict clinically successful neuroprotective actions. In spite of the promising signs, there is no proven drug, food or nutraceutic that showed significant efficiency, efficacy and/or safety to avoid GL-ND.

7 Closing remarks In this review we focus on new clues for identifying by biomedical and biotechnological issues pathogenic mechanisms of GL-ND such as NI, and outstanding NP in glaucoma. Studies point toward a clear NI activity in GL-ND. Also a series of clinical and molecular-genetic biomarkers for NI in glaucoma have yet been identified. Undoubtedly, the NP effects of a variety of molecules have been evaluated in GL-ND but further research is needed to help novel therapies to appear. Overall these data also require to challenging our knowledge to achieve the translation to the clinical practice.

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Acknowledgments This work has been financed in part by the Spanish Net of Ophthalmic Pathology OFTARED of the Institute of Health Carlos III (Madrid, Spain), through the collaborative groups of Valencia (RD16/0007/0022) and Madrid (RD16/0008/0007).

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CHAPTER

Microglial changes in the early aging stage in a healthy retina and an experimental glaucoma model

6

 A. Ferna´ndez-Albarrala,†, Rosa de Hoza,b, Ana I. Ramı´reza,b,†, Jose In es Lo´pez-Cuencaa, Elena Salobrar-Garcı´aa,b, Pilar Rojasa,c, Francisco Javier Valiente-Sorianod, Marcelino Aviles-Triguerosd, Marı´a Paz Villegas-P erezd, Manuel Vidal-Sanzd, Alberto Trivin˜oa,e, Juan J. Salazara,b,*, and Jose M. Ramı´reza,e,* a

Instituto de Investigaciones Oftalmolo´gicas Ramo´n Castroviejo, Universidad Complutense de Madrid, Madrid, Spain b Facultad de O´ptica y Optometrı´a, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Madrid, Spain c Hospital General Universitario Gregorio Maran˜o´n, Instituto Ofta´lmico de Madrid, Madrid, Spain d Department of Ophthalmology, University of Murcia and Instituto Murciano de Investigacio´n Biosanitaria-Virgen de la Arrixaca (IMIB-Arrixaca), Murcia, Spain e Facultad de Medicina, Departamento de Inmunologı´a, Oftalmologı´a y ORL, Universidad Complutense de Madrid, Spain ∗ Corresponding authors: Tel.: +34-913941669, e-mail address: [email protected]; [email protected]

Abstract Glaucoma is an age-related neurodegenerative disease that begins at the onset of aging. In this disease, there is an involvement of the immune system and therefore of the microglia. The purpose of this study is to evaluate the microglial activation using a mouse model of ocular hypertension (OHT) at the onset of aging. For this purpose, we used both naive and ocular hypertensives of 15-month-old mice (early stage of aging). In the latter, we analyzed the OHT eyes and the eyes contralateral to them to compare them with their aged controls. In the eyes of aged naive, aged OHT and aged contralateral eyes, microglial changes were observed compared to the young mice, including: (i) aged naive vs young naive: An increased soma size and vertical processes; (ii) aged OHT eyes vs young OHT eyes: A decrease in the area of the retina occupied by Iba-1 cells and in vertical processes; and (iii) aged contralateral

†

These authors should be considered as joint first authors.

Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.05.024 © 2020 Elsevier B.V. All rights reserved.

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vs young contralateral: A decrease in the soma size and arbor area and an increase in the number of microglia in the outer segment layer. Aged OHT eyes and the eyes contralateral to them showed an up-regulation of the CD68 expression in the branched microglia and a downregulation in the MHCII and P2RY12 expression with respect to the eyes of young OHT mice. Conclusion: in the early phase of aging, morphological microglial changes along with changes in the expression of MHCII, CD68 and P2RY12, in both naive and OHT mice. These changes appear in aged OHT eyes and the eyes contralateral to them eyes.

Keywords Microglia, Aging, Glaucoma, Ocular hypertension, Retina, Inflammation, MHCII, CD68, P2RY12, Iba-1, Mouse

1 Introduction Glaucoma is an age-related neurodegenerative disease, characterized by the death of retinal ganglion cells (RGCs), which leads to blindness. It affects more than 60 million people worldwide, making it the leading cause of irreversible blindness (Quigley and Broman, 2006). Clinical studies have shown that one of the risk factors for glaucoma is high intraocular pressure (IOP) (Casson et al., 2012; Chen et al., 2013). The only therapeutic strategy currently used in this pathology is the reduction of IOP, which does not always reverse neurodegeneration and stop the progression of the disease (Casson et al., 2012). However, there is another more important risk factor for glaucoma than IOP, which is aging (Casson et al., 2012; Chrysostomou et al., 2010). The Advanced Glaucoma Intervention Study (AGIS) showed that the risk of glaucoma progression increased by 30% for each 5-year increment in age (Nouri-Mahdavi et al., 2004). It has been observed that aging can increase the vulnerability of the central nervous system to damage (Kong et al., 2012; Mattson and Magnus, 2006). Changes that occur with aging can make RGCs more vulnerable to damage in the glaucomatous neurodegeneration process (Chrysostomou et al., 2010). Alterations in the retina due to aging are mainly caused by the effects of oxidative stress and chronic exposure to light and inflammation (Bonnel et al., 2003; Gao and Hollyfield, 1992; Hughes et al., 2006; Jackson et al., 2002; Kam et al., 2010). In glaucomatous neurodegeneration, as in most neurodegenerative diseases, the immune system is involved (Tezel et al., 2009). Glial cells are immune cells of the retina and optic nerve. When damage occurs, these cells respond quickly, becoming activated, to help restore tissue homeostasis and ensure the immune privilege of nerve tissue (Tezel et al., 2007). In glaucomatous neurodegeneration, initially, a controlled immune response could restore tissue functionality and thus prevent the disease progression. However, in the course of this disease, sustained tissue stress is associated with chronic glial cell activation, a clear indicator that neuroinflammatory processes are taking place (Tezel et al., 2009). In addition, with aging, a state of chronic parainflammation occurs, leading to the activation of the microglia and release of

2 Material and methods

cytotoxic factors, such as TNF-α, nitric oxide and other molecules (Sivakumar et al., 2011), that which could significantly exacerbate glaucomatous neurodegeneration. Experimental animal models have been used to study the pathogenic mechanisms of glaucoma, using an increase in IOP to induce RGCs degeneration. One of the main models for raising IOP is the unilateral model of laser-induced ocular hypertension (OHT) (Ramı´rez et al., 2015b). In this OHT animal model, mainly young animals were used. Considering that glaucoma is an age-related pathology, and that age is the main risk factor, most of the studies should have been performed on aged animals, which is not the case due to animal maintenance difficulties (Tan et al., 2015). An acute elevation of IOP in a rat model has shown a greater activation of macroglial and microglial cells in aged mice than in young adult mice (Tan et al., 2015). In addition to an acute IOP elevation (50 mmHg for 30 min) in aged mice, a significantly reduction was observed in the function of the inner retina (Kong et al., 2012). Studies have analyzed RGC death (Salinas-Navarro et al., 2009a,b; Vidal-Sanz et al., 2015) and the neuroinflammatory process (focusing on microglial cell changes) in a unilateral laser-induced OHT model in young adult mice (de Hoz et al., 2013, 2018; Ferna´ndez-Albarral et al., 2019b; Gallego and de Gracia, 2016; Gallego et al., 2012; Rojas et al., 2014). However, to the best of our knowledge, there have been no studies using this model in aged mice. In addition, it has been shown that OHT induction in one eye causes changes in the macroglial and microglial cells in the contralateral eye, supporting the involvement of the immune system in the context of neurodegeneration related to OHT (de Hoz et al., 2013, 2018; Ferna´ndezAlbarral et al., 2019b; Gallego et al., 2012; Rojas et al., 2014). These data have been obtained from young adult animals, so it would be interesting to analyze whether glial activation in the contralateral eye is exacerbated in the aging process. Taking into account the above, the objective of the present study was to analyze the changes produced in the microglial cells of the retina of mice at an early stage of aging (15 months), compared to that of young adults. This period could coincide with the appearance of simple chronic glaucoma in humans (Quigley, 1996). In addition, we also analyzed the microglial changes in 15-month-old eyes with a unilateral laserinduced OHT, compared to those in the eyes of young adults. For this purpose, in retinal whole mounts, we studied the distinctive signs of microglial activation in the different layers of the retina of both OHT and contralateral eyes, including the number of cells, soma size, retraction process, number of vertical processes and expression of PRY12, MHCII and CD68.

2 Material and methods 2.1 Ethics statement The animals in this study were handled in accordance with the Spanish legislation and guidelines for the Endpoints of animals used in biomedical research. The Ethical Committee for Animal Research of the University of Murcia (Murcia, Spain) and the Animal Health Service of the Regional Ministry of Agriculture and Water of Murcia

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(approval ID number: A1310110807) have approved the study. All the procedures used in the study have followed the institutional guidelines, established by the European Union for the use of research animals, and by the Association for Research in Vision and Ophthalmology (ARVO) statement for the use of animals in ophthalmic and vision research.

2.2 Animals and anesthetics Albino Swiss mice of 12 weeks and 15 months of age, supplied by the breeding colony of the University of Murcia, were used in this study. The animals were housed in rooms, in which the temperature and light (12 h light/dark cycle) were controlled, and had ad libitum access to water and food. Both the OHT induction and the measurement of IOP were performed under general anesthesia, which consisted of an intraperitoneal injection of xylazine (10 mg/kg; Rompu´n®, Bayer, Barcelona, Spain) and ketamine (75 mg/kg; Ketolar®, Parke-Davies, Barcelona, Spain). A tobramycin ointment (Tobrex®; Alcon, Barcelona, Spain) was administered to the cornea to prevent drying out and infection, when the animals recovered from the anesthesia. The animals were killed using an intraperitoneal injection of an overdose of pentobarbital (Dolethal Vetoquinol®, Veterinary Specialties, Alcobendas, Madrid, Spain).

2.3 Experimental groups Four groups were considered for the study: (i) a control group of young adult mice (Naı¨ve, n ¼ 6); (ii) a control group of aged mice (Aged Naı¨ve, n ¼ 6); (iii) a group of young laser mice with ocular hypertensive (OHT, n ¼ 6) and normotensive contralateral eyes (Contralateral, n ¼ 6); and (iv) a group of aged laser mice, in which both eyes were analyzed (Aged OHT, n ¼ 6 and Aged Contralateral, n ¼ 6). The laser groups were processed 15 days after the laser treatment of the left eye.

2.4 Laser treatment and IOP measurement Previously described methods were used to induce OHT (Cuenca et al., 2010; Salinas-Navarro et al., 2009a). Briefly, the episcleral veins and limbal veins of the left eyes were photocoagulated by a single diode laser session (Viridis Ophthalmic Photocoagulator-532 nm, Quantel Medical, Clermont-Ferrand, France), firing the laser beam directly into the eye, without any lenses. Between 55 and 76 burns were made, using the following parameters: spot size, 50–100 μm; duration, 0.5 s; and power, 0.3 W. In both eyes, the OHT and contralateral the IOP, was measured by means of a rebound tonometer (Tono-Lab, Tiolat, OY, Helsinki, Finland), before the laser treatment and at 1 day, 7 days and 15 days after the laser treatment in the laser groups, as well as before being sacrificed in the naı¨ve groups. The IOP was recorded using the anesthetized animal and, at the same time of the day, to avoid elevations of the IOP due to the circadian rhythm. Six consecutive measurements were made in each eye, noting the average of them.

2 Material and methods

2.5 Immunohistochemistry The animals were anesthetized, and the ocular tissues were fixed by transcardiac perfusion with 4% paraformaldehyde in a 0.1 M phosphate buffer (PB, pH 7.4). To maintain the orientation of the eye, a stitch was placed in the upper eyelid, and the caruncle and insertion of the extraocular rectus muscles were used as additional marks (Rojas et al., 2014). The eyes were postfixed in the same fixative as that used in the perfusion for 2 h. The retina was then removed and processed as a retinal whole mount (Ramı´rez et al., 1994; Trivin˜o et al., 1992). To study the retinal microglia, retinal whole mounts were immunolabeled, as previously described (Gallego et al., 2012). The rabbit anti-Iba-1 (Wako, Osaka, Japan) primary antibody was used to label the microglia (1:600 dilution). Its secondary antibody was a donkey anti-rabbit antibody conjugated to Alexa Fluor 594 (1:800 dilution). In order to differentiate the resident microglia from macrophages or infiltrated monocytes, we used anti-P2RY12. Prior to labeling, the retinas were pre-treated with antigen-unmasking solution (Vector, Burlingame, USA) and then labeled with rat anti-P2RY12 (1:100; Biolegend, San Diego, USA). Its secondary antibody was goat anti-rat α-IgG conjugated to Alexa Fluor 488 (1:150; Invitrogen, Paisley UK). To study the expression of MHC class II molecules, a rat anti-mouse MHC class II primary antibody (I-A/I-E) (eBioscience; San Diego, California, United States) was used in a 1:100 dilution. Its secondary antibody was goat anti-rat Alexa Fluor 488 (Invitrogen, Paisley, United Kingdom) in a 1:150 dilution. To study the expression of CD68 that recognizes cells with phagocytic activity, we use the primary antibody, CD68 rat anti-mouse (AbD Serotec, Oxford, United Kingdom), at a dilution of 1:40. Its secondary antibody was donkey anti-rat Alexa Fluor 488 (Invitrogen, Paisley, United Kingdom) in a 1:300 dilution. To dilute the primary antibodies, a solution containing 1% of the serum of the animal, where the secondary antibody developed, triton-x 100 and phosphate buffered saline (PBS) were used. The secondary antibodies were diluted in PBS. Negative controls were performed to demonstrate that the secondary antibody reacts only with its primary. To do this, the primary antibody was removed, and the samples were incubated in the secondary antibody and in the diluent of the primary antibody. In addition, to see the endogenous fluorescence, tissue samples were incubated in the buffers, and diluents were used, but without adding antibodies. As described previously (de Hoz et al., 2018), the retinal whole mounts were analyzed and photographed using the Apotome-2 module (Carl, Zeiss, Oberkochen, Germany) and a digital highresolution camera, Axio Cam 503 Mono (Carl Zeiss), connected to a fluorescence microscope (Zeiss Axio Imager M.2, Carl Zeiss). In addition, the microscope was equipped with fluorescence filters suitable for different emission spectra, Zeiss 10 filter set for Alexa Fluor 488 and a Zeiss 64 filter set for Alexa Fluor 594. The apotome allows conventional microscopy to generate optical sections of the sample using the “structured illumination” method, thereby improving the contrast and resolution along the optical axis. The z-stacks obtained were analyzed using the ZEN2 software (Carl Zeiss, Oberkochen, Germany). The mounting of the

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figures was done conducted using the Adobe Photoshop CS3 Extended 10.0 (Adobe Systems, Inc., San Jose, CA, USA).

2.6 Quantitative retina analysis To assess the effects of aging and OHT on microglial cells, the following signs of microglial activation were counted: (i) the number of iba-1 + cells in the OS (outer segment layer), OPL (outer plexiform layer) and IPL (inner plexiform layer); (ii) Iba1-RA (area of the retina occupied by Iba-1+ cells) in the NFL-GCL (nerve fiber layer, ganglion cell layer); (iii) The arbor area of Iba-1+ cells in the OPL and IPL; (iv) the number of microglial vertical processes connecting the OPL and OS; and (v) the cell body area of Iba-1 + cells in the OPL, IPL and NFL-GCL (de Hoz et al., 2018). The morphology of the microglial cells in the different retinal layers allows us to differentiate the retinal layer that we are analyzing. In addition, the weak fluorescence emitted by the somas in the nuclear layers of the retinal whole mounts, recorded with the Zeiss filter set 10 for Alexa Fluor 488, also facilitates the location of the retinal layer. The quantification was carried out according to the methodology previously established (Gallego and de Gracia, 2016; Rojas et al., 2014) in each of the retinal whole mounts of the Naı¨ve (n ¼ 6), Aged Naı¨ve (n ¼ 6), OHT (n ¼ 6), contralateral (n ¼ 6), Aged OHT (n ¼ 6) and Aged Contralateral (n ¼ 6). In summary, using the motorized stage of the microscope, equivalent and contiguous areas in each retinal whole mount were photographed at 20  on the vertical and horizontal meridians (crossing the optic nerve), which included the superior, inferior, nasal and temporal sectors, along the x-y axis. This provided 550 evaluated fields per retina. Each field provided an area of 0.1502 mm2. The method of quantification used depended on the number of microglial cells and how they were distributed in each retinal layer. In the plexiform layers (OPL and IPL), the microglial cells are arranged to form a regular mosaic plexus, which facilitates their individual identification and thus their automatic counting. In the NFL-GCL, the microglia often overlap, making it difficult to differentiate one cell from another and therefore difficult to count them automatically. Therefore, in this layer, we quantify the Iba1-RA. In the OS, as the cells do not form a regular plexus and cannot be counted automatically, we count them manually.

2.6.1 Iba-1+ cell number in the OS To manually count the microglial cells in the OS, we use the interactive tool for manual counting in the ZEN2 software (Carl Zeiss), which is associated with a fluorescence microscope (Zeiss Axio Imager M.2, Carl Zeiss) (Rojas et al., 2014).

2.6.2 Iba-1+ cell number in the OPL, IPL and NFL-GCL For the automatic counting of the microglial cells in OPL and IPL, we use an algorithm created by our group in MATLAB (de Gracia et al., 2015; Gallego and de Gracia, 2016), which is based on the segmentation and control of distances. Briefly,

2 Material and methods

the first step is to perform a z-stack projection on all selected images. Then, the image is normalized to the pixels that had a maximum value in the image, so that the image values had a range between 0 and 1. The threshold was then set so that all values < 0.2 were set to 0, while the remaining values were considered in our analysis. We then segmented the image and calculated the center of mass of each segment to identify the presence or absence of cells. Furthermore, in order not to count the same cell twice, we introduce the condition of what is the minimum distance between two cells. The points separated at a shorter distance are considered as the same cell, while the points separated at a longer distance are considered as different cells. After that, the algorithm provides the result of the automatic count. As mentioned above, in the NFL-GCL, the number of cells cannot be counted automatically, so in this layer, the Iba1-RA was counted in each selected image. The threshold defines a range of values within a grayscale in the pixels of objects that interest us, differentiating them from other parts of the image, based on a grayscale of the image. The threshold in MATLAB tool allows us to change the threshold values in the NFL-GCL to quantify the area of the retina immunolabeled with Iba-1. Then, when the threshold levels have been set, the “count NFL” button in the program interface gives us the percentage of the immunolabeled image in the selected image.

2.6.3 Arbor area of Iba-1+ cells in the OPL and IPL For this purpose, we selected four equivalent areas, located at different distances from the optic disk in the different retinal quadrants. These areas were chosen from those used for counting Iba-1+ cells in retinal whole mounts. Therefore, the following areas were selected: in the superior retina, the area closest to the optic disk (OD); in the inferior retina, the area located at two levels of eccentricity from the OD; in the nasal retina, the area at three levels of eccentricity from the OD; and in the temporal retina, the area at four levels of eccentricity from the OD. In the selected photographs (images) that had been taken at 20, a polygon was drawn manually by joining the most distant process points of the Iba-1+ cells using the “Interactive Measurement” tool in the ZEN2 software (Carl Zeiss). A computer-assisted morphometric algorithm quantifies the area of the polygon and therefore the “arbor area” of the Iba-1+ cells in the plexiform layers (de Hoz et al., 2018; Ferna´ndez-Albarral et al., 2019b).

2.6.4 Number of vertical processes of Iba-1+ cells connecting the OPL and OS In the areas selected to quantify the “arbor area”, micrographs were taken on the plane between the OPL and the OS. The points that correspond to vertical processes connecting the OPL and the OS were photographed at 20. These points were counted using the manual counting of the ZEN2 software (Carl Zeiss) (de Hoz et al., 2018; Ferna´ndez-Albarral et al., 2019b).

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2.6.5 Cell body area of Iba-1+ cells in the OPL, IPL and NFL-GCL In the same areas selected for the “arbor area” and “vertical processes,” micrographs were made at 20, in which the contour of the somas of the Iba-1+ cells was drawn manually. A computer-assisted morphometric algorithm, using the “Interactive Measurement” tool in the ZEN2 software (Carl Zeiss), quantified the area of the soma in the OPL, IPL and NFL-GCL layers (de Hoz et al., 2018; Ferna´ndezAlbarral et al., 2019b).

2.7 Statistical analysis The statistical study was conducted using the SPSS 25 software (IBM, Chicago, IL, USA). The data were provided as the mean  standard deviation (SD). The Wilcoxon W test (for paired data) and the Mann Whitney U test (for unpaired data) were used, with the following parameters: (i) IOP; (ii) Iba-1 + cell number (OS, OPL and IPL); (iii) Iba1-RA (NFL-GCL); (iv) arbor area of Iba-1+ cells (OPL and IPL); (v) number of Iba-1 + vertical processes; and (vi) cell body area of Iba-1 + cells (OPL, IPL and NFL-GCL). Differences were considered significant when P < 0.05.

3 Results 3.1 Laser-induced ocular hypertension The OHT eyes of young mice showed an average IOP value of 35.06  5.67 (P < 0.01 vs Naı¨ve and Contralateral eyes) 24 h after IOP induction, which decreased progressively (17.04  3.82) at 7 days, until reaching normal values at 15 days (15.29  1.35). The OHT eyes of the 15-month-old mice showed an average IOP value of 35.31  3.09 (P < 0.01 vs aged naı¨ve and aged contralateral eyes), which decreased to a similar extent as the young OHT eyes (15.38  5.11) at 7 days, showing normal values at 15 days (15.45  0.53). The IOP values of the contralateral eyes, in both young and aged mice, remained normal after IOP induction, until the time of the study. No differences were found in the young groups compared to the aged groups (naı¨ve vs aged naı¨ve; contralateral vs aged contralateral; OHT vs aged OHT) (Table 1).

3.2 General morphological characteristics of Iba-1 + retinal cells In the young adult naı¨ve eyes, the iba-1 + cells were distributed homogeneously, forming regular plexuses in the plexiform layers (OPL, IPL) and in the NFLGCL. These cells had a small soma, with long primary processes, from which secondary and tertiary processes emerged (Fig. 1B–D). However, in OS, these cells were not distributed in a homogeneous way, and the cells showed a more compact appearance (Fig. 1A). In the aged naı¨ve eyes, the distribution of Iba-1+ cells was similar to that of young adult naı¨ve eyes. However, the cells generally showed a more robust aspect (Fig. 1E–H).

3 Results

Table 1 Intraocular pressure (IOP) values shown in different groups after laser OHT induction. The data are shown as the mean ( standard deviation, SD). Basal Naı¨ve Aged Naı¨ve Contralateral Aged Contralateral OHT Aged OHT

15.02  0.79 14.99  0.48 15.26  0.70 15.29  1.11 15.02  0.79 15.22  1.25

1 day

15.20  0.72 15.54  0.63 35.06  5.67** 35.31  3.09**

7 day

15 day

15.19  0.59 15.25  0.59 17.04  3.82 15.38  5.11

15.26  0.70 15.17  0.76 15.31  1.29 15.58  0.51 15.29  1.35 15.45  0.53

Mean  SD;**P < 0.01 OHT vs Contralateral, OHT vs Naı¨ve. **P < 0.01 Aged OHT vs Aged Contralateral; Aged OHT vs Aged Naı¨ve.

In the OHT eyes (Fig. 1Q–X) and the eyes contralateral to them (Fig. 1I–P) (both young and aged), although the distribution of Iba-1+ cells was similar to that of the naı¨ve (Fig. 1A–H), in general, more cells were observed, which were thicker and showed more retracted processes. These changes were more intense in the OHT eyes than in the contralateral ones. When comparing the aged OHT eyes (Fig. 1U–X) and the eyes contralateral to them (Fig. 1M–P) with the young adult OHT eyes (Fig. 1Q–T) and the eyes contralateral to them (Fig. 1I–L), we found that, overall, in aged eyes, the cells showed a more robust aspect, with a greater thickness of the primary processes and disappearance of many of the secondary and tertiary ones.

3.3 Morphometric characteristics of the Iba-1 + cells 3.3.1 Iba-1+ cells in the retina of 15-month-old mice (aged naı¨ve) vs young adult mice (naı¨ve) In the aged naı¨ve, as compared to the young naı¨ve, retina, we observed a nonsignificant increase in the number of Iba-1 cells in the OS (Fig. 2A) and a nonsignificant decrease in the arbor area of the Iba-1+ cells in OPL (Fig. 2C). However, the significant changes were restricted to an increase in the cell body area of the Iba-1 + cells in OPL, IPL and NFL-GCL (Fig. 2B) and in the number of vertical processes between OS-OPL (Fig. 2E) (P < 0.01 in all cases).

3.3.2 Iba-1+ cells in the retina of OHT young adult mice (OHT) vs young adult mice (naive) Both the OHT eyes and contralateral eyes of young OHT mice showed signs of microglial activation, compared to naive eyes, and this was more pronounced in OHT eyes (Figs. 1 and 2). The significant changes in young OHT, as compared to young naı¨ve, eyes were: (i) an increase of the Iba-1 + cell number in the OS, OPL and IPL (Fig. 2A); (ii) an increase of the Iba1-RA in NFL-GCL (Fig. 2D); (iii) an increase of the cell body area of the Iba-1+ cells in OPL, IPL and NFLGCL (Fig. 2B); and (iv) a decrease in the arbor area of the Iba-1+ cells in OPL

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FIG. 1 Iba-1 + cells in the photoreceptor outer segment layer (OS), outer plexiform layer (OPL), inner plexiform layer (IPL) and nerve fiber-ganglion cell layer (NFL-GCL) in age-matched control groups and in laser groups at 15 days after laser-induced ocular hypertension (OHT). Iba-1 immunolabeled retinal whole mount (A–X). Morphological features of Iba-1+ cells in young adult mice (Naı¨ve) (A–D) and aged mice (Aged Naı¨ve) (E–H). Microglial cell characteristics 15 days after laser OHT induction in young adult OHT eyes (OHT) (Q–T), young adult contralateral eyes (Contralateral) (I–L), aged OHT eyes (Aged OHT) (U–X) and aged contralateral eyes (Aged Contralateral) (M–P).

3 Results

FIG. 2 Morphometric analysis of activation signs of Iba-1+ cells in age-matched control groups and in laser groups at 15 days after laser-induced ocular hypertension (OHT). (A–E) Comparisons between young adult naı¨ve, aged naı¨ve, young adult OHT, young adult contralateral, aged OHT and aged contralateral eyes. (A) Number of Iba-1+ cells per area of 0.1502 mm2 in the OS, OPL and IPL. (B) Quantitative analysis of the cell body area of the Iba-1 + cells in OPL, IPL and NFL-GCL. (C) Quantitative analysis of the arbor area of the Iba-1 + cells in OPL and IPL. (D) Quantitative analysis of the area of the retina occupied by the Iba-1 + cells (Iba-1 RA) in NFL-GCL. (E) Quantitative analysis of the number of Iba-1 + vertical processes connecting OS and OPL. The histograms show the mean number ( standard deviation, SD). *P < 0.05, **P < 0.01. Photoreceptor outer segment layer (OS), outer plexiform layer (OPL) and inner plexiform layer (IPL), nerve fiber-ganglion cell layer (NFL-GCL).

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and IPL (Fig. 2C) and an increase in the number of vertical processes between OS-OPL (Fig. 2E) (P < 0.01 in all cases). The significant changes in young contralateral eyes, as compared to young naı¨ve eyes, were: (i) an increase in the Iba1-RA in NFL-GCL (P < 0.05) (Fig. 2D); (ii) an increase in the cell body area of the Iba-1+ cells in the OPL, IPL (P < 0.01 in both) and in NFL-GCL (P < 0.05) (Fig. 2B); (iii) a decrease in the arbor area of the Iba-1+ cells in IPL (P < 0.05) (Fig. 2C); and (iv) an increase in the number of Iba-1+ vertical processes between OS-OPL (P < 0.01) (Fig. 2E). When we compared the young OHT eyes with the eyes contralateral to them, we found: (i) an increase in the number of Iba-1+ cells in OS, OPL and IPL (P < 0.05) (Fig. 2A); (ii) an increment in the Iba1-RA in NFL-GCL (P < 0.05) (Fig. 2D); (iii) an increase in the cell body area in the NFL-GCL (P < 0.05) (Fig. 2B); (iv) a decrease in the arbor area of the Iba-1 + cells in OPL and IPL (P < 0.01 in both cases) (Fig. 2C); and (v) an increase in the vertical processes between OS-OPL (P < 0.05) (Fig. 2E).

3.3.3 Iba-1+ cells in the retina of 15-month-old OHT mice (aged OHT and aged contralateral) vs 15-month-old mice (aged naı¨ve) Both aged OHT eyes and aged contralateral eyes showed signs of microglial activation in comparison with aged naı¨ve, and overall, this was more pronounced in OHT eyes (Figs. 1 and 2). The significant changes in aged OHT eyes vs naive aged eyes were: (i) an increase in the number of Iba-1+ cells in the OS (P < 0.05) and in the OPL and IPL (P < 0.01 in both cases) (Fig. 2A); (ii) an increment in the Iba1-RA in NFL-GCL (P < 0.01) (Fig. 2D); (iii) an increase in the cell body area of the Iba-1 + cells in OPL, IPL and NFL-GCL (P < 0.01 in all cases) (Fig. 2B); and (iv) a decrease in the arbor area of the Iba-1 + cells in IPL and OPL (P < 0.01 in both cases) (Fig. 2C). The significant changes in aged contralateral eyes vs aged naive eyes were: (i) an increase in the number of Iba-1 + cells in IPL (Fig. 2A) (P < 0.05); (ii) an increment in the cell body area of the Iba-1 + cells in OPL and NFL-GCL (Fig. 2B) (P < 0.05 in both cases); (iii) a decrease in the arbor area of the Iba-1 + cells in OPL (P < 0.05) and IPL (P < 0.01) (Fig. 2C). When we compare aged OHT eyes with aged contralateral eyes, we observe: (i) an increase in the number of Iba-1+ cells in OS, OPL and IPL (P < 0.05) (Fig. 2A); (ii) an increment in the Iba1-RA (P < 0.05) (Fig. 2D); (iii) an increase in the cell body area of Iba-1 + cells in OPL, IPL and NFL-GCL (P < 0.01 in all cases) (Fig. 2B); (iv) a decrease in the arbor area of the Iba-1 + cells in IPL (P < 0.05) (Fig. 2C).

3.3.4 Iba-1+ cells in the retina of 15-month-old OHT mice (aged OHT and aged contralateral) vs young adult OHT mice (OHT and contralateral) In the aged OHT, as compared to young OHT, eyes, some changes were found in both eyes (OHT and contralateral) (Figs. 1 and 2). In aged OHT eyes, as compared to young OHT, eyes, we observed a significant decrease in the Iba-1RA in the NFLGCL (P < 0.05) (Fig. 2D) and in the number of vertical processes between the OS-OPL (P < 0.01) (Fig. 2E). Additionally, we found a non-significant decrease

3 Results

in the cell body area of the Iba-1 + cells in OPL, IPL and NFL-GCL (Fig. 2B) and in the IPL arbor area (Fig. 2C). In aged contralateral eyes, we found significant differences in comparison to young contralateral eyes: (i) an increase in the number of Iba-1 + cells in OS (P < 0.01) (Fig. 2A); (ii) a decrease in the cell body area of the Iba-1 + cells in the plexiform layers (P < 0.01) (Fig. 2B); and (iii) a decrease in the arbor area of the Iba-1+ cells in IPL (P < 0.05) (Fig. 2C).

3.4 MHCII expression In both naı¨ve groups (young and aged), no expression of MHCII was observed (Fig. 3A–F). The MHCII expression was recorded in virtually all microglial cells of the retina in both the OHT (Fig. 3M–O) and the contralateral eyes (Fig. 3G–I) of young adult individuals. However, in 15-month-old individuals, the MHCII expression was limited to some Iba-1 + cells in the OS, OPL, IPL, and NFL-GCL, although there were more labeled cells in the aged OHT eyes (Fig. 3P–R) than in the eyes contralateral to them (Fig. 3J–L).

3.5 CD68 expression In the young naive eyes, the expression of CD68 + was practically absent (Fig. 4A–C). However, numerous CD68+ cells, with an amoeboid appearance, were found in the aged naı¨ve eyes (Fig. 4D–F). These amoeboid cells were more weakly stained with anti-Iba-1 than branched Iba-1+ cells. More CD68+ cells (amoeboidlike) were observed in OHT eyes than in naı¨ve eyes in both young adult (Fig. 4M–O) and aged animals (Fig. 4P–R). Furthermore, in the aged OHT eyes (Fig. 4P–R), there were more CD68+ cells with a ramified appearance than in the young adult OHT eyes (Fig. 4M–O). In the young adult contralateral eyes, there were almost no CD68+ cells (Fig. 4G–I). However, in the aged contralateral eyes, many ramified Iba-1+ cells were CD68+ (Fig. 4J–L).

3.6 P2RY12 expression In the young adult eyes, both naı¨ve (Fig. 5A–C) and OHT (Fig. 5M–O), and in the eyes contralateral to them (Fig. 5G–I), all Iba-1 + cells forming part of the microglial plexuses were P2RY12 +, with the exception of the perivascular dendritic cells (Fig. 5N and O) and the dendritic cells of the peripheral retinal margin. However, in both the aged naı¨ve (Fig. 5D–F) and aged contralateral eyes (Fig. 5J–L), there were some cells of the microglial plexuses that were Iba-1+/P2RY12 . In the aged OHT eyes, most of the Iba-1 + cells were P2RY12  (Fig. 5P–R).

137

FIG. 3 MHCII expression in age-matched control groups and in laser groups at 15 days after laserinduced ocular hypertension (OHT). Double immunolabeled retinal whole mount (Iba-1/ MHCII). The images are of the inner plexiform layer. Iba-1 (A, D, G, J, M, P), MHCII (B, E, H, K, N, Q) and merge (C, F, I, L, O, R). Iba-1+ cells in young Naı¨ve an Aged Naı¨ve eyes do not express MHCII (A–F, arrow). In young OHT eyes (M–O) and young Contralateral eyes (G–I), all Iba-1 + cells are MHCII + (arrowhead). The expression of MHCII in aged Contralateral eyes is restricted to some Iba-1 + cells (J–L, arrowhead). In aged OHT eyes, more Iba-1+ cells are MHCII + than in aged Contralateral eyes (P–R, arrowhead). The arrows point to the cells, Iba-1+/MHCII .

FIG. 4 CD68 expression in age-matched control groups and in laser groups at 15 days after laserinduced ocular hypertension (OHT). Double immunolabeled retinal whole mount (Iba-1/ CD68). The images are of the complex inner plexiform layer/nerve fiber layer. Iba-1 (A, D, G, J, M, P), CD68 (B, E, H, K, N, Q) and merge (C, F, I, L, O, R). In the aged naive group, numerous CD68 + amoeboid cells are observed (D–F, arrowhead). These cells are practically absent in the young naı¨ve group (A–C, arrowhead). Young Contralateral eyes expressed almost no CD68 (G–I, arrowhead) and in young OHT eyes, the CD68 expression is only observed in amoeboid-like cells (M–O, arrowhead). In Aged Contralateral eyes, many ramified Iba-1 + cells are CD68 + (J–L, arrow). In Aged OHT eyes, both ramified (arrow) and amoeboidlike cells (arrowhead) are CD68 + (P–R).

FIG. 5 P2RY12 in age-matched control groups and in laser groups at 15 days after laser-induced ocular hypertension (OHT). Double immunolabeled retinal whole mount (Iba-1/P2RY12). The images are of the complex inner plexiform layer/nerve fiber layer. Iba-1 (A, D, G, J, M, P), P2RY12 (B, E, H, K, N, Q) and merge (C, F, I, L, O, R). All Iba-1+ cells in the young Naı¨ve (A–C), young Contralateral (G–I) and young OHT (M–O) eyes are P2RY12+ (arrowhead), except for the perivascular dendritic cells (M–O, asterisk). In both Aged Naı¨ve eyes (D–F) and Aged Contralateral eyes (J–L), some Iba-1+ cells are P2RY12 (arrow). In Aged OHT eyes, very few Iba-1+ cells are P2RY12+ (P–R, arrowhead). The arrows point to the cells, Iba-1+/P2RY12.

4 Discussion

4 Discussion This is the first study to analyze microglial behavior in response to an increase in IOP in 15-month-old mice in a unilateral laser-induced OHT mouse model of both OHT and contralateral eyes. We have used 15-month-old mice, which is the beginning point of the aging process of the mice (Dutta and Sengupta, 2016), which is well established from 18 months. Since in humans, simple chronic glaucoma begins in adulthood, near senescence (Leske et al., 1981; Quigley, 1996), we believe that the age of 15 months is an ideal time to analyze the microglial changes associated with the onset of aging and OHT in mice. In this study, we found morphological signs of microglial activation and changes in the expression of MHCII, CD68 and P2RY12 in the naı¨ve eyes of 15-month-old mice (early stage of aging), compared to young naı¨ve adults. We also found microglial morphologic alterations and changes in the expression of MHCII, CD68 and P2RY12 in the eyes of 15-month-old OHT mice and in the eyes contralateral to them, compared to the eyes of young adult OHT mice and the eyes contralateral to them. In neurodegenerative diseases associated with aging, such as glaucoma, it has been shown that the neuroinflammatory mechanisms induced by microglial cells have an important implication in the development of disease (Ramı´rez et al., 2015a, 2017). The microglia undergo significant changes in their morphology in response to alterations in the central nervous system’s homeostasis (Ramı´rez et al., 2015a, 2017). With aging and Alzheimer’s disease, the microglia of the brain undergo morphological activation changes, thickening their somas, shortening their processes and adopting a more amoeboid morphology than that observed in young healthy individuals (Ferna´ndez-Albarral et al., 2019a; Ramı´rez et al., 2017; Udeochu et al., 2016). In retinal tissue, an increase in microglial density has been found in the fovea of aged primates, when compared to young individuals (Singaravelu et al., 2017). In the retina of CX3CR1+/GFP transgenic mice, Damani et al. (2011) found that in 18–24-month-old animals, the resting microglia had significantly smaller and less branched dendritic arbors, and also a slower process motility. This fact could compromise the ability of the microglia to monitor and interact with the environment. The authors (Damani et al., 2011) also observed that the microglia of the retina in aged mice showed ramified morphologies and were distributed in a “mosaic” manner in the IPL and OPL of the retina. This distribution was similar to that of young individuals. However, there was a small but significant increase in the microglia cell density in both IPL and OPL in aged individuals, compared to young ones (Damani et al., 2011). In our study of 15-month-old Swiss mice, we also found that the microglia maintain their mosaic distribution in both IPL and OPL. However, we did not find significant differences in the number of microglial cells in any of the retinal layers analyzed, although we found a non-significant increase in the number of cells in OS and a non-significant decrease in the arbor area in the plexiform layers. In addition, we observed a significant increase in other signs of microglial activation, such as an increase in the soma size (OPL, IPL, and NFL-GCL) and in the number of

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vertical processes (OS-OPL). The differences between these results and those found in Damani’s study (Damani et al., 2011) could be due to the fact that they studied mice older than ours (18–24 months), since our 15-month-old mice are in the early stages of aging, and the changes we observed in this study could be the first changes that microglial cells undergo in the aging process. In a rat model, Tan et al. (2015) also found no significant differences in the number and the area percentage of microglia, when comparing young and old adults (18-month-old rats) (Tan et al., 2015), which is consistent with our results. The controversies found in the number of cells during the aging process are also shown in studies on retinal ganglion cells (RGCs). Several works have shown RCGS or axonal loss during aging (Calkins, 2013; Cepurna et al., 2005; Neufeld and Gachie, 2003), while others found no changes in both rodents and other species (Cepurna et al., 2005; Garcı`a-Ayuso et al., 2015; Nadal-Nicola´s et al., 2018). Discrepancies between the different studies could be due to differences in the age of the animals, the species used and the techniques used to obtain the results. In addition, it is important to note that the fact that the number of various retinal populations does not change with age does not necessarily imply that these cells are healthy or functional (Nadal-Nicola´s et al., 2018). With aging, the microglia of mice undergo changes in the genes that control the inflammatory process, such as the NF-κβ factor (Angelova and Brown, 2019). Furthermore, in a study on the sensome genes associated with microglial aging, it was shown that the microglia changed to a neuroprotective phenotype with age (Hickman et al., 2013). However, other studies have reported an increased expression of cytokine genes and a decreased ability to migrate into damage in aging microglia, thus stimulating inflammation and thus acquiring a more neurodegenerative role (Orre et al., 2014). Therefore, although no major morphological changes are observed in microglia with aging, molecular changes may occur. In the aged naı¨ve retinas of our study, we found changes in the expression of CD68 and P2RY12. We observed numerous amoeboid-like CD68 + cells, which were weakly stained by Iba-1 and were not found in the young adult naı¨ve eyes. These cells could be macrophages that could have entered the retina through an age-altered blood retinal barrier (Chan-Ling et al., 2007). In young adult naive eyes, all Iba-1 + cells express P2RY12, with the exception of dendritic cells. However, in aged naive eyes, there was a down-regulation of the P2RY12 expression in some Iba-1 + cells. The down-regulation of the P2RY12 expression is one of the most sensitive markers of the change from a resting microglia to an activated microglia (Haynes et al., 2006; Zrzavy et al., 2018), so in our study, this indicates that some microglia are in a state of higher activation in aged mice. The activation of microglial cells can also be produced by other types of damage, such as IOP increases (Ramı´rez et al., 2015a). In human glaucoma (Yuan and Neufeld, 2001) and animal models of OHT (de Hoz et al., 2013, 2018; Gallego et al., 2012; Inman and Horner, 2007; Johnson et al., 2007; Naskar et al., 2002; Rojas et al., 2014; Wang et al., 2000), microglial activation has been observed in the retina and the optic nerve and is evident before retinal ganglion cell death occurs (Bosco et al., 2011; Ebneter et al., 2010), aiding in the progression of glaucomatous disease (Madeira et al., 2015). It has been observed, in a DBA/2J mouse model of

4 Discussion

glaucoma, that treatment with minocycline (an inhibitor of microglial activation) (Bosco et al., 2008), as well as a high dose of electromagnetic irradiation (Bosco et al., 2012), produces a decrease in RGC death. Previous works have shown, in a unilateral laser-induced OHT mouse model, that microglia present numerous morphological signs of activation, such as an increase in the soma size, a retraction of processes, an increment in the number of vertical processes, cellular migrations, an increase in the number of cells and an appearance of amoeboid forms and rod-like microglia (de Hoz et al., 2013, 2018; Gallego et al., 2012; Ramı´rez et al., 2020; Rojas et al., 2014). However, studies focusing on the changes in microglia in OHT animals during aging are very scarce. Unfortunately, the use of aged animals for experimentation can be excessively expensive and timeconsuming, thus making it impractical (Angelova and Brown, 2019). In retinal whole mounts, we found a significant increase in the signs of microglial activation (the number of cells, soma size, arbor area, and vertical processes) in all retinal layers where the microglia is located, both in the eyes of young adult OHT mice and in those of 15-month-old OHT mice, as compared to their respective naı¨ve age controls. When we compared 15-month-old OHT eyes (early stage of aging) with those of young adult OHTs, we observed a significant decrease in Iba1-Ra and in the number of vertical processes between OS-OPL in the aged group, as compared to the young group. A lower Iba1-RA may indicate a lower number of microglial cells in the NFLGCL layer in 15-month-old OHT eyes than in young adult OHT eyes. Considering that the number of microglial cells in IPL is higher in aged OHT eyes than in young OHT eyes, it could indicate that a movement of microglial cells from IPL to NFLGCL may occur in young eyes but not in aged OHT eyes. In addition, in the Iba-1 + cells of the OHT aged eyes, we observed fewer secondary and tertiary processes. All of this could be in line with the observation that, with age, the surveillance phenotype of microglia is altered, with less dendritic ramifications and less motility. Furthermore, when an injury occurs, these cells have a lower migration rate and a more sustained inflammatory response to damage (Damani et al., 2011). We also found, in aged OHT eyes, a non-significant decrease in the IPL arbor area and in the soma size in the OPL, IPL, and NFL-GCL in comparison to young OHT eyes. The fact that some of the morphological signs of activation of the microglial cells of the 15-month-old OHT eyes are reduced in comparison to young OHT eyes may indicate that these cells have a reduced ability to respond and migrate to sites of damage and may suggest a less important neuroprotective role (Orre et al., 2014). These nonsignificant changes could be due to the fact that we observed the early stages of mouse aging, and in more advanced stages, they could be significant. In a previous study (Tan et al., 2015) on an acute IOP elevation model at 45, 60 and 90 mmHg, the authors found significant differences in the area percentages of microglia and microglia number in the inner part of the retina in comparison to young adult rats and 18-month-old rats. The differences between these results and those found in the Tan study (Tan et al., 2015) could be because: (i) the IOP values in our study are lower (35 mmHg vs 45, 60, 90 mmHg; (ii) we analyzed the retinas at 15 days after OHT induction, while the Tan study (Tan et al., 2015) conducted their analysis

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after 3 days, and it has been shown that at 3 days after OHT induction, there is a greater inflammatory reaction than later on (Ramı´rez et al., 2020); (iii) the species used in the study are different (rats and mice) and could have a different behavior; and (iv) our mice were 15 months old, while their rats were 18 months old. In previous works, we demonstrated, in experimental models of unilateral OHT, that the eyes contralateral to OHT eyes suffer macroglial and microglial changes, without the death of RGCs (de Hoz et al., 2013, 2018; Pinazo-Dura´n et al., 2013; Ramı´rez et al., 2010, 2015b; Rojas et al., 2014). However, there are no data on the changes that contralateral eyes undergo when OHT is induced in the aging eyes. In the contralateral eyes of 15-month-old OHT eyes in comparison to their aged na¨ıve controls, there was a significant increase in the number of microglial cells in the IPL, a decrease in the arbor area in the OPL and IPL, and an increase in the soma size in the OPL and NFL-GCL. In addition, in the contralateral eyes of the 15-month-old OHT mice, in comparison to the contralateral eyes of the OHT young adults, we found a significant increase in the number of microglial cells in the OPL and IPL, a significant decrease in the arbor area of the IPL and, finally, a significant decrease in the soma size in the OPL and IPL. As we can see, there are more significant changes in the contralateral eyes than in the OHTs in 15-month-old individuals, which may indicate that microglial cells respond more actively in contralateral eyes than in OHT eyes. In OHT eyes, we found changes in the expression of MHCII, CD68 and P2RY12 among the groups of young adult mice and aged mice. In the young adult OHT eyes and the eyes contralateral to them, all Iba-1+ cells expressed MHCII. However, in the aged OHT eyes, only some cells expressed it, although to a lesser extent in the contralateral eyes than in the OHT eyes. It has been suggested that the expression of modest levels of MHCII may inhibit T-cell activation, while an over-expression may promote T-cell activation by increasing the inflammatory cascade (Gallego et al., 2012; Shao et al., 2007). In the OHT eyes of young and aged mice, Iba-1 +/CD68 + amoeboid cells were abundant, but in the aged eyes, many branching cells also expressed CD68. In the aged contralateral eyes, many CD68 + branched Iba-1 + cells were also observed, while the expression of this antibody in the young contralateral eyes was virtually absent. Microglia with the highest capacity of movement are the amoeboid (Ramı´rez et al., 2017). The expression of CD68 in the branched microglia of aged mice could be due to the lower motility rate of the microglia in the elderly (Damani et al., 2011), and therefore, the branched microglia have to enhance their capacity for phagocytosis in order to remove cell debris without moving. All microglial cells in the OHT eyes and the eyes contralateral to them of young adult animals showed an expression of P2RY12. However, in the older eyes, this expression was down-regulated in the contralateral eyes and almost absent in the OHT eyes. As mentioned above, the down-regulation of the P2RY12 expression is a very sensitive marker of the change from resting to activated microglia (Haynes et al., 2006; Zrzavy et al., 2018). Therefore, in the contralateral eyes and especially in the OHTs of the aged mice, the microglia would be more activated than in the young adult OHT mice. Furthermore, in previous work on a laser-induced OHT model

References

(Ramı´rez et al., 2020), we found that in the period of time after OHT induction, in which the greatest inflammatory response occurs, there is a down-regulation of the P2RY12 expression. We can conclude that in the retina of 15-month-old mice (early stage of aging), morphological signs of microglial activation occur, as well as in the expression of MHCII, CD68 and P2RY12, in both naive and OHT mice. These changes appear not only in aged OHT eyes, but also in the normotensive eyes contralateral to them.

Acknowledgments The authors would like to thank Desiree Contreras for technical assistance. This work was supported by the Ophthalmological Network OFTARED (RD16/0008/0005, RD16/0008/0026) of the Institute of Health of Carlos III of the Spanish Ministry of Economy, by the PN I + D + i 2008–2011, by the ISCIII-Subdireccio´n General de Redes y Centros de Investigacio´n Cooperativa; by the European program FEDER (SAF-2014-53779-R; SAF2015-67643-P, PI16/00380) from the Spanish Ministry of Economy and Competitiveness; and Fundacio´n Seneca, Agencia de Ciencia y Tecnologı´a Regio´n de Murcia (19881/GERM/ 15). ESG was supported by a Predoctoral Fellowship from the Universidad Complutense de Madrid. J.A.F.-A. is currently supported by a Predoctoral Fellowship (FPU17/01023) from the Spanish Ministry of Education, Culture and Sport.

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Molecular changes in glaucomatous trabecular meshwork. Correlations with retinal ganglion cell death and novel strategies for neuroprotection

7

Sergio C. Sacca`a,*, Stefania Vernazzab, Eugenio Luigi Iorioc, Sara Tirendid,e, Anna Maria Bassid,e, Stefano Gandolfif,†, and Alberto Izzottid,g,† a

Policlinico San Martino University Hospital, Department of Neuroscience and sense organs, Ophthalmology Unit, Genoa, Italy b IRCCS, Fondazione G.B. Bietti, Rome, Italy c International Observatory of Oxidative Stress, Salerno, Italy d Department of Experimental Medicine (DIMES), University of Genoa, Genoa, Italy e Inter-University Center for the Promotion of the 3Rs Principles in Teaching & Research (Centro 3R), Pisa, Italy f Ophthalmology Unit, Department of Biological, Biotechnological and Translational Sciences, University of Parma, Parma, Italy g Mutagenesis Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy *Corresponding author: Tel.: +39-010-555-2443; Fax: +39-010-555-6585, e-mail address: [email protected]

Abstract Glaucoma is a chronic neurodegenerative disease characterized by retinal ganglion cell loss. Although significant advances in ophthalmologic knowledge and practice have been made, some glaucoma mechanisms are not yet understood, therefore, up to now there is no effective treatment able to ensure healing. Indeed, either pharmacological or surgical approaches to this disease aim in lowering intraocular pressure, which is considered the only modifiable risk factor. However, it is well known that several factors and metabolites are equally (if not more) involved in glaucoma. Oxidative stress, for instance, plays a pivotal role in both glaucoma

†

These authors contributed equally to this study.

Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.06.003 © 2020 Elsevier B.V. All rights reserved.

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging onset and progression because it is responsible for the trabecular meshwork cell damage and, consequently, for intraocular pressure increase as well as for glaucomatous damage cascade. This review at first shows accurately the molecular-derived dysfunctions in antioxidant system and in mitochondria homeostasis which due to both oxidative stress and aging, lead to a chronic inflammation state, the trabecular meshwork damage as well as the glaucoma neurodegeneration. Therefore, the main molecular events triggered by oxidative stress up to the proapoptotic signals that promote the ganglion cell death have been highlighted. The second part of this review, instead, describes some of neuroprotective agents such as polyphenols or polyunsaturated fatty acids as possible therapeutic source against the propagation of glaucomatous damage.

Keywords Glaucoma pathogenesis, Trabecular meshwork, Schlemm’s canal, Endothelial dysfunction, Extracellular matrix, Aqueous humor proteome, Polyphenols, Omega-3, Neuroprotection

1 Introduction The loss of redox-homeostasis is a common hallmark of several diseases including glaucoma which (excluding hereditary juvenile forms) is considered as an agedependent neurodegenerative disorder. As known, the aging process is characterized by an increase in oxidative stress rate which contribute to age-related deterioration. Therefore, glaucoma neurodegeneration is promoted by the oxidative damage accumulation which results in the axonal transport defects, neuroinflammation, glutamate excitotoxicity and destruction of neurons (Gauthier and Liu, 2016). However, in general, the neuronal damage, regardless of its etiology, affects damaged neurons as well as both perilesional and the healthy ones who have suffered metabolic damage capable of modifying their homeostasis (Gladstone et al., 2002; Tolias and Bullock, 2004). In this regard, in order to slow-down glaucoma progression, three different therapeutic approaches named neuroprotection, neuroregeneration, and neuroenhancement have been suggested (Chang and Goldberg, 2012). However, in this review we mainly focused upon neuroprotection. The therapeutic paradigm of neuroprotection aims to slow or prevent the neuron death by preserving their physiologic functions. In particular, neuroprotection in glaucoma is to be intended as a pharmacologic approach unrelated to intraocular pressure (IOP) reduction, capable to interfere with secondary degenerations in order to prevent by the loss both the axons and retinal ganglion cells (RGCs) and to restore neurons (Sigireddi and Frankfort, 2018) (Fig. 1). However, such goal rarely is reached because, due to the translational failure between results carried out with animal models of neuroprotection and neuroprotection clinical trials, it is not always possible to demonstrate the real effectiveness of a neuroprotective treatment. Indeed, although several studies on animal glaucoma

FIG. 1 Retinal ganglion cells death. The only reduction of eye pressure is not always sufficient to slow down the evolution of glaucoma. The axons of retinal ganglion cells have a lot of mitochondria necessary to produce energy for nerve conduction. In glaucoma, the reduction in mitochondria energy production and the increase in free radical amounts could be possible targets for neuroprotection for retinal ganglion cells (see text).

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging models (i.e., rodents, nonhuman primates and so on) have demonstrated the effectiveness of various neuroprotective treatments, the mismatch between these promising findings and the clinical results severely hamper the progress in drug discovery field (Almasieh and Levin, 2017). The Memantine study besides represents one of the most well-known translational failure is also the most expensive clinical study in the history of ophthalmological trials. Indeed, although evidence on animals have shown the effectiveness of Memantine in preserving visual function through its bond with NMDA receptors (Celiker et al., 2016; Sa´nchez-Lo´pez et al., 2018), the clinical study conducted on over 2000 patients with chronic open-angle glaucoma, has not provided the same promising results (Weinreb et al., 2018). Another example of clinical trial failure is represented by the Brimonidine in which its neuroprotective role, documented by multiple animal studies, has not been proven in glaucoma patients (Cordeiro and Levin, 2011). Different reasons are undoubtedly behind the failure of these clinical trials, however, one above all could be the different degree of similarity between human disease and the animal model used. Dogs, for example, have the intrascleral plexus instead of Schlemm’s Canal while mice lack of a real lamina cribrosa. Recently, three-dimensional in vitro model of cells involved in glaucoma have been developed in order to study further molecular mechanisms in a more physiological way then the standard two-dimensional models (Aires et al., 2017). Moreover, in our previous study we have proposed an advanced in vitro model based on three-dimensional cultures of human trabecular meshwork and the bioreactor system (Sacca` et al., 2020). Such advanced model could be used also for an accurate prediction of human neuroprotective compounds. Therefore, since the mechanism of the development and progression of glaucoma is still largely unknown, this present review aims to describe in detail some of the risk factors and some molecular mechanisms underlying this disease. Moreover, in order to improve the m
enage of this condition, compounds from natural and synthetic origin has been proposed as neuroprotective treatment.

2 Oxidative stress Oxidative stress (OS) is one of the most recognized processes that leads to different pathological mechanisms including cancer, diabetes mellitus, eye diseases, neurodegenerative diseases and so on. In general, an imbalance between the reactive oxygen species (ROS) production and their removal, damages macromolecules such as DNA, proteins and lipids. However, the detrimental or beneficial effects of ROS are attributable to their amounts, indeed, low levels of ROS contribute to different molecular signaling, including cell survival mechanisms (Chrysostomou et al., 2013). As known, ROS production can derive from endogenous sources (mitochondria, endoplasmic reticulum, peroxisomes, and inflammatory cell activation) and from

2 Oxidative stress

exogenous sources, such as environmental agents (i.e., ultraviolet/ionizing radiation, pollutants, bacteria, lifestyles and so on), pharmaceuticals, and industrial chemicals (Klaunig et al., 2010). Moreover, ROS from endogenous and exogenous sources can be produced with or without catalysts (Egea et al., 2017). Therefore, non-catalytic ROS generation occurs when the power of exogenous energy source is enough to break the covalent bond in target molecule (i.e., photolysis induced by UV rays) (Halliwell and Gutteridge, 1989; Iorio, 2016). On the other side, catalytic ROS generation takes place in the presence of either metals such as iron (Fe2+/Fe3+) and copper (Cu+/ Cu2+) or specific enzymes located in plasma membrane (e.g., NADPH oxidase) as well as in mitochondria (e.g., elements of the respiratory chain responsible for oxidative phosphorylation), in endoplasmic reticulum/microsomes (e.g., cytochrome P450), in peroxisomes (e.g., flavine monooxygenase) and in cytosol (e.g., xanthine oxidase) (Mittal et al., 2014; Rahal et al., 2014; Valko et al., 2007). Among ROS, several highly reactive molecules such as hydrogen peroxide (H2O2), hydroxyl radical (OH%), peroxide hydroxyl radicals, alkoxy radicals, superoxide and the anion radical (O2
) are included (Zhao et al., 2016). Moreover, in addition to oxygen radicals also elements, such as nitrogen, carbon, sulfur and halogens are able to behave like reactive species (Albrich et al., 1981; Delattre, 2006). Reactive nitrogen species (RNS) can contribute to both cell damage and death. The reaction between nitric oxide (NO) and anion radical generates peroxynitrite and other highly reactive molecules which are part of so-called RNS (Pinazo-Duran et al., 2018). Both ROS and RNS are involved in the pathologic processes underlying eye diseases. The increase of ROS in the retina may occur after direct exposure to sunlight leading to photoreceptor cell death (Grimm et al., 2001). This probably happens due to either photobleaching of rhodopsin or lipid peroxidation and protein oxidation (Grimm et al., 2000). However, a previous in vitro study on photoreceptor cell line (661 W) have shown that a transient increase in ROS concentration promoted cell survival rather than cell death (Mackey et al., 2008). Therefore, these findings have demonstrated that the cell damage promoted by free radicals depends on both their amounts and their time of residence in the cells. Most of biological processes in living cells are based on the oxidation-reduction (redox) reactions (Halliwell and Gutteridge, 1989), which are opposite but reciprocal ubiquitous reactions. The redox reactions aim to preserve the homeostasis of the whole organism counteracting endogenous and exogenous ROS sources (Iorio and Marin, 2008; Jones, 2015; Rahal et al., 2014; Ray et al., 2012). Therefore, the proper functioning of such system, named “oxidative eustress,” is fundamental for redox regulation processes. Indeed, in physiological conditions, an efficient antioxidant system inactive ROS activity after they have act as messenger molecules. However, an inadequate stress response, named “oxidative di-stress,” capable of the improper oxidation of target molecules may occur if there are defects such as wrong oneelectron transfer reactions and either congenital or acquired system alterations (Iorio, 2016).

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging From a molecular point of view, two redox reactions are distinguished for their significant importance: the bi-electronic transfer reactions, which transfer electrons in pairs, and the mono-electronic transfer reactions which transfer single electrons (Iorio, 2016). The bi-electronic transfer reactions are mainly related to cellular energy metabolism and are all catalyzed by oxide-reductase enzymes that use the activated riboflavin as coenzyme (Halliwell and Gutteridge, 1989) (Iorio, 2016). The mono-electronic transfer reactions, on the other hand, are related with the metabolism of biological systems, of which, ROS are the best known. In these reactions the “oxidizing” element is represented by reactive species and the “reducing” ones by antioxidant (Halliwell and Gutteridge, 1989) (Iorio, 2016). Depending on the circumstances, a redox couple can act as an “oxidant” or a “reducing” toward another redox couple with a lower or a higher redox potential, respectively (Lide, 2006). Thus, in “oxidative di-stress” condition, ROS generated are not adequately controlled by the antioxidant system and this involves the triggering of all that chain reactions (e.g., lipid peroxidation) which lead to alterations to protein structure and function, cellular dysfunction and widespread tissue damage (Ramana et al., 2017; Scholpp et al., 2004). Antioxidants are a heterogeneous class of substances whose function is to inhibit or delay the oxidation of biologically relevant molecules through directlyscavenging of free radicals or chelation of redox metals (Valko et al., 2006). Antioxidants result both from endogenous or exogenous sources. The antioxidants from endogenous sources which have direct action in ROS-scavenging include: amino acids; small peptides; proteins (enzymatic or non-enzymatic); fat derivatives and metabolism end-products. Amino acids with antioxidant activity: Amino acids are essential for protein synthesis, including antioxidant enzymes. Into this sub-category, some amino acids such as arginine, cysteine, citrulline, glycine, taurine, and histidine, have an antioxidant activity. In particular, arginine is an allosteric activator of N-acetylglutamate synthase (mitochondrial enzyme) which converts glutamate and acetyl-CoA into N-acetylglutamate (Wu and Morris, 1998). Moreover, arginine and phenylalanine increase both the expression and activity of GTP cyclohydrolase-I, which indirectly allows to NO synthesis. NO, in turn, is essential for cellular signaling at both vascular endothelial (Forstermann and Sessa, 2012) and trabecular meshwork (Sacca` and Izzotti, 2014) level. Similarly to arginine, also Cysteine plays signaling roles in nutrient metabolism because it constitutes both the precursor and the limiting factor in glutathione (GSH) synthesis. Small Peptides with antioxidant activity: Among the small peptides, glutathione (GSH) and carnosine, GSH is the most important because modulates cellular redox metabolism. GSH is a powerful scavenger against various ROS, such as hydroxyl radical and superoxide anion. Furthermore, it allows the degradation of hydrolipoperoxides to organic alcohols and hydrogen peroxide to water since it is the reducing substrate of GPx.

2 Oxidative stress

GSH maintains the thiol groups of numerous proteins in a reduced state, participating indirectly in mechanisms of signal transduction mediated by hydrogen peroxide. In addition, in acidic environment, it reacts with nitrites to form S-nitrosoglutathione that besides releases NO, forms glutathione conjugates (e.g., oxidized GSH). GSH acts also as cofactor of a series of enzymes and allows the recycling of vitamin E. In glaucomatous patients the GSH serum levels decline compared to the healthy ones. This finding highlights the connection between glaucoma and a reduced antioxidant response (Gherghel et al., 2005). Protein with antioxidant activity: enzymatic antioxidant proteins mainly include the superoxide dismutase (SOD) and the peroxidases (e.g., catalase). The enzyme SOD belongs to oxidoreductases whose catalytic activity consists of the dismutation of two molecules of superoxide anion in hydrogen peroxide and molecular oxygen, preventing the formation of highly aggressive compounds such as peroxynitrite and hydroxyl radical (Iorio, 2016). The hydrogen peroxide, in turn, is then eliminated by glutathione peroxidase or catalase. Both superoxide anion and hydrogen peroxide act as signal modulators in several fundamental biological functions, therefore, depending on cellular needs, superoxide anion dismutes to hydrogen peroxide through SOD activity or not, before their amounts become harmful (Broxton and Culotta, 2016; Egea et al., 2017; Fukai and Ushio-Fukai, 2011; Iorio, 2009; Miller, 2012). As known, factors such as pro-inflammatory cytokines and prostaglandins as well as ROS and nitric oxide (NO) alter the activity of the antioxidant enzymes and therefore, very low concentration and activity of SOD is associated to oxidative stress condition. Indeed, the resulting excess of the superoxide anion is responsible for harmful events including the formation of peroxynitrite, which is an oxidant and nitrating agent, from reaction with the nitric oxide and the generation of hydroperoxyl radical, which is a powerful cytolesive oxidant. In addition, a reduced SOD activity is responsible for a lower production of hydrogen peroxide that therefore cannot act neither as signal molecule nor as oxidant (Egea et al., 2017; Fukai and Ushio-Fukai, 2011; Iorio and Balestrieri, 2009). The three known types of SOD are classified by their metal cofactor: SOD1, also known as Cu/Zn-SOD or cytosolic SOD, plays a pivotal role in cell survival and growth, in fact, its mutations or its inhibition is linked to neurological defects and early senility (Muchova´ et al., 2014). SOD2, also named Mn-SOD or mitochondrial SOD, is important because protects by ROS generated by hyperoxia and its deficiency results in increased levels of mitochondrial superoxide anion which inhibit the respiratory chain complexes I and II (Afonso et al., 2007). SOD3, also known as extracellular or secretory Cu-Zn-SOD, plays a protective role toward cells and the ECM against the harmful effects of superoxide anion from activated neutrophils. Its mutation is associated with increased cardiovascular risk (Afonso et al., 2007). Since in Glaucoma the levels of SOD are reduced, it is assumed that superoxide radicals could directly influence the endothelial cells of the Trabecular Meshwork

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging (TM). The increase in TM cell damage, in turn, probably affects the structure of the extracellular matrix and intraocular pressure (IOP) (Bagnis et al., 2012). Peroxidases are a large family of enzymes which catalyze the transfer of either one or two electrons via a single electron transfer from an organic substrate, using hydrogen peroxide as electron acceptor. Among peroxidases, glutathione peroxidase is considered the major protective system against endogenously and exogenously induced lipid peroxidation (Wendel, 1981). Catalases are enzymes whose main function is to catalyze decomposition of hydrogen peroxide in two-step process (H2O2) to water and molecular oxygen. Hydrogen peroxide in vivo is generated by several sources such as mitochondria and other cell compartments, e.g., peroxisomes and endoplasmic reticulum or by, as mentioned above, downstream antioxidant reactions. Therefore, catalase, several isoforms of glutathione peroxidases and peroxiredoxins regulate its concentration. However, although with low activity, catalases are also catalytically active in the absence of H2O2 (Gebicka and Krych-Madej, 2019). Furthermore, there are also other molecules that contribute to the redox balance such as lipophilic antioxidants (i.e., lipoic acid), fat-soluble vitamins (i.e., vitamin D, C, E and K), carotenoids (i.e., astaxanthin) and inorganic antioxidants (i.e., selenium) (Iorio, 2018). Among these, astaxanthin, for instance, could be considered as an activator of Nrf2 pathway and the FOXO3 gene, which are associated with longevity (Morris et al., 2015). Enzymatic antioxidants are mainly located at the intracellular level even though they are also at the extracellular one. Fat-soluble vitamins, e.g., tocopherols mainly protect cell membranes from ROS attack, while water-soluble vitamins, e.g., ascorbate play their antioxidant role at intracellular level (Iorio, 2018). Therefore, it is quite clear that these redox systems are complex also because their proper regulation depends on both endogenous and esogenous factors as well as epigenetic factors. However, exogenous and/or endogenous stimuli may trigger the ROS production which, in turn, can activate/inhibit specific metabolic pathways (Ahmadinejad et al., 2017; Nishida et al., 2016; Ray et al., 2012; Valko et al., 2007). For example, hydrogen peroxide, can induce reversible oxidative changes in protein containing thiol groups sufficient to modulate the key processes involved in both cell homeostasis and survival (Nishida et al., 2016; Ray et al., 2012; Weidinger and Kozlov, 2015). OS-induced lipid peroxidation leads to alterations in biological properties of the membrane (Uchida, 2003) and to increase in malondialdehyde (MDA) levels. Therefore, the MDA found in the aqueous humor of glaucomatous patients (Nucci et al., 2013) supports its pathogenetic importance at the level of the trabecular network. It has not yet been clarified why glaucomatous subjects have low levels of antioxidant defenses and high levels of oxidative di-stress but certainly free radicals play a pivotal role in cell signaling, in fact, their uncontrolled regulation activate different cellular pathways with detrimental effects (Buttke and Sandstrom, 1994).

3 The Nrf2 and NF-κB systems

3 The Nrf2 and NF-κB systems OS can be understood as a necessary mechanism for homeostasis maintenance, in which “oxidative eustress” is considered as an adaptive mechanism that allows to living organism to respond and adapt to either exogenous or endogenous stressors (Iorio, 2016). However, the loss of this fine and necessary regulation, due to an unbalance between reactive and antioxidant species, promotes the establishment of “oxidative di-stress” which, as described in a previous section, is noxious because is capable of altering all signaling involved in the correct molecular regulations (D’Aiuto et al., 2010; Iorio, 2016). Many transcription factors acting as redox-sensitive proteins are essential for responding to intracellular/environmental signals because activate the gene expression related to their pathways. Among redox-sensitive transcription factors two, the NF-E2-related factor 2 (Nrf2) and Nuclear factor (NF)-κB, are recognized as the most important because activate and coordinate distinct biological responses (Bellezza et al., 2010) (Fig. 2). Both pathways regulate cellular redox status one through the antioxidant cascade activation and the other, through the trigger of inflammatory pathway. However, the mechanisms underlying their balance have not been clarified yet (Wardyn et al., 2015) because they are related to both cell and tissue types. Nrf2 is a nuclear transcription factor that controls the expression of cytoprotective genes encoding detoxifying enzymes (e.g., glutathione transferase) and antioxidant proteins (e.g., heme oxygenase 1) as well as drug transporters (Dhakshinamoorthy et al., 2000; Ma, 2013). Under normal cellular conditions Nrf2 is retained in the cytoplasm by its cytosolic inhibitor Keap1 (Velichkova and Hasson, 2005) and every 20–30 min, Keap1 promotes Nrf2 degradation by the ubiquitin proteasome pathway (Katoh et al., 2005). However, when the cells are exposed to oxidative stress, two theories to explain the Nrf2 nucleus translocation have been proposed. One is that oxidative stress dissociates Nrf2 from Keap1 (McMahon et al., 2003), the other one is that Nrf2 in response to oxidative stress escapes Keap1 degradation (Kaspar et al., 2009). Anyway, in either way the Nrf2 nucleus translocation leads to activation of ARE-mediated gene expression driving the expression of Nrf2 target genes such as NAD(P)H quinone oxidoreductase 1 (NQO1), heme oxygenase 1 (HMOX1), glutamate-cysteine ligase (GCL) and glutathione S transferases (GSTs) (Kansanen et al., 2013). Therefore, Nrf2 is considered a main regulator of the response to OS (Bellezza et al., 2018; Minelli et al., 2009). Moreover, also several protein kinases (i.e., PKC, ERK, MAPK, p38, and PERK) are able to modify Nrf2 and activate release from Keap1 (Cullinan and Diehl, 2006; Simon et al., 2017). However, exist also a Keap1-indipendent regulation of Nrf2 transcriptional activity. Several miRNAs, for instance, can interfere with the activation of its pathway

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FIG. 2 Schematic representation about Nrf2 and NF-κB activation. Under normal condition both Nrf2 NF-κB are retained in the cytoplasm by their respective inhibitor. Upon OS stimulation, transcription factors translocate into the nucleus in order to activate their target genes by binding with high affinity to ARE region and κB element, respectively.

(Shah et al., 2013) while endogenous stimuli such as endoplasmic reticulum stress (Cullinan and Diehl, 2006) and the impairment of autophagy (Simon et al., 2017) provide the so-called chronic oxidative stress signaling through a feed-forward loop. NF-κB is one of the best-characterized transcription factors. It is ubiquitously expressed and regulates the expression of many genes, most of which encode proteins that play an important role in immunity and inflammation processes, apoptosis and cell survival. Its activation antagonizes the Nrf2 pathway (Bellezza et al., 2010). Therefore, Nrf2 and NF-κB pathways are two side of the same coin because, despite the fact that they have opposite functions, one control the response intensity of the other. The inhibition of Nrf2 pathway, for instance, causes a more aggressive inflammation response via NF-κB, compared to a condition in which Nrf2 is also activated (Chen et al., 2013). NF-κB is mainly activated through the so-called canonical pathway, by multiple proinflammatory receptors, such as the humoral necrosis factor receptor (TNF), the toll-like receptor ligands (TLR) and the B and T cell receptors (Iwai, 2012). Once activated, it translocates into nucleus, determining the transcription of target genes involved in the cellular responses of which the inflammatory response is part (Ghosh and Hayden, 2008).

4 Aging

However, NF-κB can also be activated through the non-canonical pathway or by a subgroup of TNF superfamily receptors, supporting lymphocytes B survival, and osteoclastogenesis (Sun, 2017). It can be assumed that simultaneous accumulation of both NF-κB and Nrf2 into the nucleus can occur. Such contingency may cause either the suppression of Nrf2 or NF-κB pathway (Li et al., 2008). OS via NF-κB pathway, promotes the up-regulation of pro-inflammatory cytokines which further increase the cellular stress rate (Ahmed et al., 2017). Nrf2/ ARE system, in turn, inhibits the pro-inflammatory cytokine (e.g., IL6 and IL-1β) and chemokines inductions as well as counteracts the activation of NF-ĸB attempting to attenuate the inflammatory response (Ahmed et al., 2017; Kobayashi et al., 2016). Unfortunately, when the pro-inflammatory response sustained by NF-κB prevails over the antioxidant response, the di-stress condition begins. In aqueous humor of glaucomatous eyes, in fact, high levels of pro-inflammatory cytokines (i.e., IL-1 and TNF) (Ahmed et al., 2017) promote the increase of the cell adhesion molecules (i.e., ICAM-1, VCAM-1) (Zhang et al., 2017). The latter, are expressed on endothelial cells and their increase correlate with endothelial dysfunction borne by TM (Sacca` et al., 2012). Conversely, Nrf2 up-regulation inhibits TNF-α-induced VCAM-1 gene expression in endothelial cells (Chen et al., 2003). Moreover, metalloproteinases can directly or indirectly control Nrf2 pathway, also through the NF-κB (Ahmed et al., 2017). As known, in high tension glaucoma, the elevated IOP changes the expression and activity of different metalloproteinases both in the aqueous humor and in the trabecular meshwork (De Groef et al., 2013). Defense systems against ROS become less efficient with aging so many antioxidant genes can be upregulated or under-regulated and innate and adaptive immune defense systems tend to deteriorate and this may justify the onset of degeneration (M€ uller et al., 2013). Inflammation plays an important role in aging and endothelial diseases (Csiszar et al., 2008) and in neurodegenerative diseases (Chung et al., 2009).

4 Aging Aging is a natural biological process characterized by progressive accumulation of changes that lead to the loss of physiological integrity increasing thus susceptibility to disease and death. However there is an inter- and intra-individual variability among individuals of the same age, suggesting that the biological age alone is not sufficient to measure the health status of the individual (Mather et al., 2010). Indeed, the aging and its rate process are conditioned by genetic, epigenetic factors (i.e., immunological and neuroendocrine alterations, cellular senescence) (Petersen and Smith, 2016) as well environmental damage (i.e., oxidative stress) (Martin and Sheaff, 2007). Therefore, it is necessary to have aging-biomarkers able to reflect not only biological aging but also the risk of aging-related conditions, disease, and mortality. In this regard, telomere length has been proposed as a candidate biomarker of aging. Telomeres shortening are involved strictly in cellular aging and they can predict

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging the individual lifespan (Simm et al., 2008). In addition, their shortening induces a replicative senescence where cells exhibit a gradual loss of replicative potential (Lo´pez-Otı´n et al., 2013; Sharpless and Sherr, 2015). Thus, senescent cell accumulation in tissue (Hernandez-Segura et al., 2018) contributes to tissue function loss (Fossel, 2002). Senescent cells have distinctive features including a remarkable enzymatic lysosomal β-galactosidase (SA-β-GAL) activity (Dimri et al., 1995), a lack of response to mitogenic signal (Hampel et al., 2005), a reduced expression of some heat shock proteins (i.e., HSP 70, HSP 90 and HSP 28), an increased expression of pro-inflammatory cytokines (Kuilman et al., 2008). The number increase of cells with such phenotype (Acosta et al., 2013) is promoted by growth factors (i.e., TGFβ1) (Debacq-Chainiaux, 2005; Kim et al., 2007; Muck et al., 2008) pro-inflammatory molecules, metalloproteases (Copp
e et al., 2010) and ROS (Passos et al., 2010) (Fig. 3). Moreover, also redox alterations (Genova and Lenaz, 2015) and mitochondrial dysfunctions (Lo´pez-Lluch et al., 2015) are considered part of aging-related issues. The mitochondrial DNA (mtDNA) is not protected by histones or DNA-binding proteins and it is constantly exposed to ROS and free radicals. Therefore, mtDNA

FIG. 3 The senescent phenotype. Cell senescence is an essentially irreversible process of the cell cycle arrest induced by a variety of stimuli, including oxidative stress. A diet rich in saturated fat induces premature endothelial senescence, while omega-3 fatty acids help to suppress the formation of H2O2 via NfκB pathway.

4 Aging

mutations during all course of life are accumulated but their numbers markedly increase with advancing age leading to mitochondria defects due to lipid peroxidation and oxidative protein modifications (D’Aquila et al., 2015; Wei et al., 1998). In addition, ROS-dependent modifications act on nuclear DNA altering its methylation and demethylation pattern (Zampieri et al., 2015). All these molecular modifications are considered a risk factor for several diseases but, in particular, for the neurodegenerative ones such as Alzheimer’s and Parkinson’s disease (Hindle, 2010; Niccoli and Partridge, 2012) as well as glaucoma (Sacca` et al., 2016a). Thus, ROS, senescence and genomic instability contribute to pathological state of individuals. As known, the proteome integrity maintenance is fundamental for the cell homeostasis. Aging, due to the senescent, compromise both proteasomal and autophagic activities giving rise to protein aggregates and damaged proteins (Kwon et al., 2019; Labbadia and Morimoto, 2015). Furthermore among the senescent cells, senescence-associated secretory phenotype (SASP) affects the tissue environment, enough to promote chronic inflammation (Ohtani and Hara, 2013). Indeed, even presence of small share of SASP at the tissue level (about 20%) is able to exert systemic effects. In aged brain, for example, an up-regulation of IL6 was observed (Kiecolt-Glaser et al., 2003; Starr et al., 2015) while in neurodegenerative diseases such as Parkinson’s and Alzheimer a correlation between inflammation (Calabrese et al., 2018) and SASPs (Kritsilis et al., 2018) was found. Cellular senescence is a defense mechanism against the cancer development. However, given the multifactoriality of such disease, we know that chronic inflammation condition, promoting several SASP-dependent tissue alteration and growth signals (Regulski, 2017), is involved in cancer onset and its progression. In this regard, the SASP-dependent autocrine release of interleukin ILα results in a constant activation of NF-κB pathway (Nelson et al., 2012; Salminen et al., 2012). Moreover, in senescent cells several alterations both in mitochondrial morphology and in mitochondrial oxidative I-phosphorylation (OXPHOS) have been found. Mitochondria impairment results also in retrograde signaling (from mitochondria to nucleus) defects (Ballinger, 2013) modifying cell functions and consequently, their fate (Kwon et al., 2019). The up-regulation of genes involved in Ca2+ transport and storage, in fact, determines both biochemical and phenotypic changes such as the expression of nuclear marker gene, increased cytosolic Ca2+ concentration, the loss of mitochondrial membrane potential and the alteration of cell morphology (Finley and Haigis, 2009). During the aging process, also the healthy individuals undergo to both cell and tissue dysfunctions probably because their immune system is unable to proper recall the resident immune cells. Therefore in general, the senescent cells act negatively on tissue performance because making them less efficient and more susceptible of further deteriorations which lead to disease (Childs et al., 2015). The relationship between ROS and senescence at the molecular level materializes in damage to mitochondrial DNA and the inhibition of autophagy. In addition to these, also the induction of miR-210 and miR-494 lead to a kind of a vicious circle that aggravates the oxidative di-stress condition (Lauri et al., 2014).

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4.1 Aging and TM In TM the age-related ROS promote the cell autophagy and, consequently, the cell senescence (Pulliero et al., 2014). The phenotype of senescent cells involves both morphological and molecular alterations. In particular, it is characterized by chronic activation of the DNA-damage response (DDR), increased anti-apoptotic gene expression, increased activity of the β-galactosidase associated with senescence (SA-β-Gal), lipofuscin accumulations in lysosomes, lysosomes accumulations, increased number of defective mitochondria and the activation of unfolded protein response (UPR) in endoplasmic reticulum (ER). Therefore, the senescence of the endothelial TM cells as well as of the endothelial cells during atherosclerosis (Sacca` et al., 2012), decreases their cellularity because makes them more prone to apoptosis (Zhang et al., 2002). Altered nitric oxide expression results in increased Caveolin-1 (Cav-1) levels that negative regulate the eNOS levels. The latter, in normal conditions regulates the activity of miRNAs which interfere with both inflammation and apoptosis processes (Rippe et al., 2012). Interestingly, Cav-1 is expressed in both normal and glaucoma TM cells (Surgucheva and Surguchov, 2011) and polymorphisms of Caveolin 1 gene predispose to POAG (Thorleifsson et al., 2010). Cav-1 behaves as an endogenous modulator of IOP and aqueous humor outflow through the regulation of eNOS activity (Stamer et al., 2011). Moreover, TM senescent cells are also characterized by both a reduced ATP release in response to mechanical stress and a severe dysregulation of calcium homeostasis which can contribute to TM age-related and POAG alterations (Chow et al., 2007). During the aging process, TM becomes more pigmented probably because the iris undergoes alterations on its back sheet (Khalil et al., 1996), the scleral spur becomes more evident, the trabeculae become flatter and gradually merge into each other. In addition, the denudation of trabecular areas occur, i.e., part of the endothelial cells that line them (Sacca` et al., 2016a) are lost while those that survive become larger in order to cover such trabecular areas (Alvarado et al., 1984). Furthermore, the sheaths of the elastic-like fibers in the cribriform layer of TM develop sheath derived (SD)-plaques (SD plaques) that increase their thickness (L€ utjen-Drecoll et al., 1986) (Fig. 4). These molecular alterations are similar to those found both in neurodegenerative diseases (Sacca` et al., 2016a), including glaucoma (Caprioli, 2013), and in aging (Klohs, 2019). Indeed, the decline of repair mechanisms together with ROS overproduction result in oxidative damage, oxidized proteins and amyloid depositions (Squier, 2001) which, in turn, lead to a further increase in OS rate and in mitochondrial dysfunction (Crouch et al., 2007). Thus, oxidative damage can be considered the cause for both mitochondrial dysfunction and their number decrease (Wei et al., 1998). Therefore, the conventional outflow pathway functional defects are promoted by age-related alterations, oxidative DNA-damage and the activation of autophagy (Pulliero et al., 2014).

5 The aqueous humor proteome: Its importance in glaucoma

FIG. 4 Morphological changes observable in old age and glaucoma. Normal (A) and glaucomatous (B) human trabecular meshwork. The molecular alterations such as a marked cell loss with denuding and flattening, reflect the other morphological ones in which an early senility has shown.

5 The aqueous humor proteome: Its importance in glaucoma The trabecular meshwork consists of endothelial cells immersed in their fundamental substance. These cells have different characteristics but the most important is that they can change their shape thanks to their cytoskeleton (Tamm, 2009). From a functional point of view, the conventional aqueous outflow pathway consists of endothelial cells endowed with two barriers. The first one is formed by the trabecular meshwork cells; the second one instead is formed by endothelial cells lining lumen of the Schlemm’s canal. The trabecular meshwork barrier controls the permeability of the endothelium of Schlemm’s canal by releasing of vasoactive cytokines and other factors. The endothelial barrier of Schlemm’s canal acts as a “control” site (Alvarado, 2005; Alvarado et al., 2005; Alvarado and Shifera, 2010). Between these two barriers, TM cells are responsible for responding to mechanical stretching increasing matrix turnover and changing gene expression (Sacca` et al., 2016b). Aqueous humor (AH) flows through the intercellular spaces of TM and crosses the inner wall of Schlemm’s canal via, at least, two different mechanisms: an intercellular

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging route and a transcellular route. The AH can pass through either cell junctions or cells; changing their shape and creating real channels through the TM. In glaucoma, TM cells undergo a series of molecular and morphological alterations which lead to their progressive numerical reduction and IOP elevation. The increase of IOP, in turn, is responsible for other alterations that further compromise cellular homeostasis giving rise to a real vicious circle. The characteristic changes in AH proteome of glaucoma patients, reflect these TM dysfunctions. Therefore, AH is characterized by seven different classes of proteins (Izzotti et al., 2010) including those directly related to oxidative damage. In addition, the reduced expression of antioxidant enzymes such as SOD and GST exacerbate the imbalance between ROS and NOS (Bagnis et al., 2012). In this regard, primary open-angle glaucoma (POAG) can be considered a real “mitochondriopathy” because, in AH of patients suffering from this disease, mitochondrial-derived proteins from TM cell death and damaged mitochondria are also found (Izzotti et al., 2011). The mitochondrial damage causes the intracellular calcium release with a consequent apoptosis activation via intrinsic pathway. However, not only mitochondrial damage activates apoptosis but also a variety of mechanisms including chronic/acute inflammation, vascular dysregulation, and hypoxia (Sacca` et al., 2015). Therefore, in glaucomatous AH, due to the loss of TM cellular integrity, there are TM-derived proteins with proapoptotic activity and those involved in TM function restoration. Hence, other proteins very expressed in AH from glaucomatous patients are the actin-related proteins (Arps), Arp2 and Arp3, which form a complex (Arp2/3 complex) and control the cell actin polymerization (Welch et al., 1997). In central nervous system, for instance, such complex is crucial for synaptic plasticity during both spine and synapse formation (Wegner et al., 2008). However, the presence of the Arp2/3 complex in glaucomatous AH is probably due to the alterations OS-induced in TM endothelial barrier (Sacca et al., 2009; Sacca` et al., 2012). Indeed, the Arp 2/3 complex and other proteins such as Protein kinase C, which is also increase in POAG AH (Izzotti et al., 2015), in POAG TM cells could represent an attempt to improve the TM motility (Khurana et al., 2003) changing their shape as occurs in other endothelial cells. Therefore, actin cytoskeleton rearrangements are the basis of many fundamental processes such as motility, adhesion, mitosis, endocytosis, and morphogenesis that taking place in endothelial cell (Moreau et al., 2003). Moreover, the presence of intercellular adhesion, such as connexin, junction proteins and cadherins, in AH indicates the loss of trabecular barrier function (Fig. 5). The communication between adjacent cells is supported by gap junctions, allowing passage of either ions or molecules with low molecular weight in response to certain chemical signals (i.e., changes in pH or in Ca2+ concentration). Thus, gap junctions connect the cytoplasm of adjacent cells with the extracellular environment through the interaction between two hemichannels (Vinken et al., 2006). However, inflammatory mediators produced under pathological conditions can compromise this mechanism of barrier function. Free radicals, for instance, promote both

5 The aqueous humor proteome: Its importance in glaucoma

FIG. 5 The cascade of pathogenic events in glaucoma. During the open-angle glaucoma, chronic damage to trabecular meshwork occurs. This damage is reflected in protein expressions of trabecular meshwork cells which flow in the aqueous humor. Such proteins describe the event cascade that at first leads to trabecular meshwork malfunction and then to IOP increase, becoming therefore, also biological signals able to reach the optic nerve head in the posterior segment through the conventional pathway. Nestin, for instance, probably activates the glial cells while AKAP2, which in the anterior chamber reflects the damage to the trabecular meshwork motility, in the posterior segment may be a signal for the activation of the ganglion cell apoptosis.

pro-inflammatory cytokine productions (i.e., TNF-α, IL-6 and IL-1 β) and lipid peroxidation of unsaturated lipids of cell membranes inducing structural and functional changes in cell junctions (Wang et al., 2019). Interestingly cadherins, due to their peri-synaptically location in mature synapses, are important components of these and modulate live calcium channels through the kinases RhoA and Rho (Fannon and Colman, 1996; Marrs et al., 2009). Another group of important proteins found in AH of glaucomatous patients is represented by protein kinases (PKs) which allow ensuring the proper functioning of trabecular meshwork motility. Among these, PKC belong to a family of enzymes that, through specific phosphorylations, determine a change in function of their protein target. In addition, PKA which is one of the first PKs discovered, it also known as cAMP-dependent protein kinase because its activation as well as the activation of

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging other protein kinases, protein phosphatases and ion channels, depends on cAMP. Such enzyme in response to hormonal stimuli modulates several cell processes including cellular metabolism, gene transcription, ion channel conductivity, cell growth and cell division as well as actin cytoskeleton rearrangements (Francis and Corbin, 1994; Scott, 1991). Furthermore, another important PKA-related protein activity is represented by A-kinase anchoring-2 protein (AKAP 2) because it directs subcellular localization of PKA by binding to its regulatory subunit. AKAP2 is mainly localized to the mitochondria (Wang et al., 2001) and is involved in regulation of trabecular meshwork motility through signal transductions to the actin cytoskeleton (Bishop and Hall, 2000). Actin cytoskeleton, in turn, is important for a variety of biological processes including both cell shape and polarity, motility as well as cell division (Diviani and Scott, 2001). AKAP2 is probably produced by endothelial cells which, once they die, lose their constituents in AH allowing AKAP2 to act as a survival signal at that site for cells or other tissues. In addition to above-mentioned function, AKAP 2 regulates also ion channels including Na+ channel, which involves PCK (Bengrine et al., 2007), and the K+ ones (Zhang and Shapiro, 2012). The Na-K-Cl cotransporter in TM cells aids to modulate their intracellular volume and the volume of the paracellular pathways through which AH may pass (Brandt and O’Donnell, 1999). Therefore, the role of AKAP 2 could be also related to endothelial barrier function maintenance within the anterior chamber and that would partly explain the motive for which in glaucoma, the endothelial dysfunction, impairs its activity (Sacca` and Izzotti, 2014). However, the activities of PKs and AKAP 2 are involved also at brain level in which, for instance, control the mechanism of synaptic plasticity. The transmission on synaptic pathways or not, induces changes which enhance or reduce the intensity of response between neurons. This process is known as synaptic plasticity and plays important roles in postnatal development, learning and memory as well as in neurodegenerative disease as Alzheimer. Both synaptic plasticity and the long term potentiation of excitatory synaptic transmission occur through postsynaptic AMPA-type glutamate receptors. The increase or the reduction of synaptic plasticity as well as the synaptic transmission occur through postsynaptic AMPA-type glutamate receptors. In particular, the synaptic plasticity in term of its increase or reduction is regulated by the activation of the NMDA-type glutamate receptors. However, such regulation changes its outcome depending on the concentration and the duration of Ca2+ influx through the NMDA receptor and on the subsequent downstream signaling of the protein kinases including PKA and PKC (Ullian et al., 2004). In addition, AKAP controls both NMDA and AMPA receptor functions through its interaction with two calcium binding proteins like caldendrin calmodulin (Woolfrey et al., 2018). Furthermore, also neuronal proteins such as Optineurin and Nestin are found in glaucomatous AH and their expressions mainly depend on IOP increase.

6 Neuroprotective strategies

Optineurin expression besides IOP, is also regulated by several cytokines, (Vittitow and Borra´s, 2002) and NF-κB (Sudhakar et al., 2009). In particular, NF-κB pathway activation in neurons is essential for their homeostasis (Vaughan and Jat, 2011). Indeed, this pathway could represent the proper connection between OS and inflammation because, despite the fact that its activation is an attempt to mitigate the OS in TM, it induces transcription of genes involved in different cellular processes, such as immunity, inflammation, proliferation and apoptosis. Nestin is a cytoskeleton intermediate filament which, originally, it was believed to be expressed in healthy brain only by neural progenitor cells before being replaced by specific neurons or glia proteins in differentiated cells (Bernal and Arranz, 2018). Actually, now we know that Nestin is expressed in different tissues and organs such as retina (Kohno et al., 2006) and glaucomatous TM cells. In particular, Nestin in glaucomatous TM is over expressed because it acts as stem cell activator (Bernal and Arranz, 2018). However, the loss of TM cell integrity causes an increase in TM-derived Nestin in AH which led us to hypothesize that this protein could act as biological signal for glia activation in the posterior chamber (Lloyd et al., 2019), according to the pathway described by Smith et al. (1986). As known neurodegenerative disorders are closely linked with chronic inflammation. Indeed, the activation of innate immunity in addition to an up-regulation of pro-inflammatory cytokines and chemokines as well as the neurotransmitters, the ROS-derived from macrophages and the activation of glial cells (microglia and astrocytes) (Bingham et al., 2005; Liu et al., 2009) result in vicious circle which also entails a further Nestin activation (Krishnasamy et al., 2017). These molecular events which underlying the neuroinflammation process, however, can be enhanced or reduced by other TM-derived proteins. It has been reported, for example, that the increases in cAMP levels can enhance the neuroprotection of RGCs because potentiate the trophic signaling. Conversely, such neuroprotective effect is lost following PKA inhibition, opening the possibility to the AKAP scaffolding involvement (Goldberg et al., 2002). Indeed, the AKAP proteins expressed in RGCs are necessary for the transduction of cAMP-induced pro-survival neurotrophic signaling (Wang et al., 2005). However, the signaling activation of AKAP-PKA complex could play both neuroprotective and apoptosis roles; that depends on its localization within cells (Sacca` et al., 2016a; Wild and Dell’Acqua, 2018). Therefore, if this complex is in nuclear domain, non-apoptotic cellular death or cellular differentiation is activated. Instead if it is mainly located in the plasma membrane apoptosis is promoted.

6 Neuroprotective strategies Glaucoma is a multifactorial disease in which both the increase in OS amount and the chronic activation of inflammatory response trigger a series of events from mitochondrial damage to TM endothelial dysfunction, leading to IOP increase.

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging IOP elevation is not always a glaucoma feature, in fact in Normal Tension Glaucoma (NTG) the intraocular pressure is in a normal range. Therefore, the difference between High Tension Glaucoma (HTG) and NGT lies in the involvement or not of TM defects (Sacca` et al., 2016a). In both cases the proapoptotic signals derived either from trabecular meshwork or from retinal ischemia determine RGC axonal damage, with consequent loss of RGCs, and morphological alterations to the optic nerve head. In this regard, neuroprotective strategies concerning retinal ganglion cells can be antioxidant to anti-inflammatory therapy, improvement of mitochondrial performances, the protection of trabecular cells, the improvement of vascular flow and the protection of RGC. There are many substances that can be used for this purpose, however proving their real usefulness is difficult for many reasons. Indeed, glaucoma is a long-lasting disease so the use of neuroprotective drugs could probably be more effective in the early stages of the disease before the inflammation could become chronic. Anyway, the main concern about the experimentation of neuroprotective substances in addition to new molecules is the non-optimal bioavailability of such additional elements which could have a potential useful action (polyphenols) or are involved partially in the treatment of glaucoma, for example bile acids UDCA (Ursodeoxycholic acid) and TUDCA tauroursodeoxycholic acid (Daruich et al., 2019). For clarity sake we will indicate only the substances that could find a use in glaucomatous neuroprotection, leaving aside molecules on whose use there are now few doubts such as Citicoline (Gandolfi et al., 2020) which induces antiapoptotic effects, increases the dopamine retinal level, and counteracts retinal nerve fibers layer thinning (Parisi et al., 2018); the Ginko Biloba that it has neuroprotective effect on RGCs against hypoxic injury (Cho et al., 2019) or Progesterone, steroid hormone whose neuroprotective effects such as the prevention of neuronal death or the reduction of microglia activity is well documented (Pardue and Allen, 2018).

6.1 Polyphenols The polyphenols (so-called because they have multiple phenolic groups associated in their structure) are natural antioxidants present in plants that include phenols, tannins and flavonoids. The first group includes phenolic acids, coumarins and benzoic acids. Their condensation can give rise to polymers such as lignin. They are widely distributed in foods and drinks such as coffee (caffeic acid). Tannins include proanthocyanidins, while flavonoids make up the largest group of natural phenols, made up of around 4000 compounds which are divided into several families including anthocyanins, flavonols, isoflavones, and others. These substances can produce beneficial effects for health by acting in the regulation of metabolism, on antioxidant defenses, in DNA repair and therefore in protein homeostasis (Leri et al., 2020). In particular, they have cardioprotective properties (Chong et al., 2010) by inhibiting endothelial dysfunction by intervening in redox regulation and nitric oxide production (Yamagata, 2019). Therefore, polyphenols improve mitochondrial functions, inducing the expression of genes for oxidative phosphorylation and mitochondrial

6 Neuroprotective strategies

biogenesis, causing the increase of Nrf2 levels enhancing its transcription and inhibiting its ubiquitination and degradation (Gibellini et al., 2015). They also modulate the redox state (Vauzour et al., 2008) and inhibit the apoptosis system (de Oliveira et al., 2016). Flavonoids are known antioxidants and can reduce the risk of neurodegenerative OS-related diseases (Solanki et al., 2015). Indeed, Flavonoids inhibit the ROS production, the cyclooxygenase-2 expression, the proinflammatory mediator production (e.g., NO, TNF-α, IL-1β, NADPH oxidase activation, and iNOS expression), which play a key role in neuroinflammation. In addition, they also regulate cell signaling pathways (Spencer, 2007) through, for instance, the inhibition of cell signaling cascades related to both iNOS and TNF-α expression in activated glial cells (Bhat et al., 1998). Unfortunately their use is conditioned by their low bioavailability and rapid metabolism (Brglez Mojzer et al., 2016). Recently, our research group has developed a platform based on threedimensional model of human trabecular meshwork cells for studying the early stage of glaucoma and evaluating the reliability of such model from a physiopathological point of view (Vernazza et al., 2019). In fact, we have shown that these cultures develop responses that are absolutely compatible with the pathophysiological relativity of glaucoma since they are developed in a dynamic environment and therefore more coherent with what happens in nature (Sacca` et al., 2020). A mixture of polyphenols that is in use as eye drops with the name of Drain® has been proven effective in counteracting the effects of OS and capable of reducing the levels of inflammatory (NF-κ B, IL1α, IL6 and TNFα) and pro-fibrotic cytokines (TGFβ) markers and as well as the matrix metalloproteinases. Furthermore, it had a very evident anti-apoptotic effect thus proving to be able to exert an effective role in the protection of TM cells during experimental glaucoma (Sacca` et al., 2020)

6.2 Omega-3 From a molecular point of view, Omega-3 are particularly interesting molecules due to their ability to tackle neuroinflammation. This is nothing more than a defense mechanism that aims to prevent damage to the central nervous system and, in the case of glaucoma damage to ganglion cells. Microglia, consisting of resident macrophages of the central nervous system, mediate neuroinflammation, the activation of which is characteristic of neurodegenerative (Pekny et al., 2016). Microglia support the homeostasis of neurons in case of meteoric lesions, this is transformed by activating and secreting proinflammatory and neurotoxic mediators, such as ROS, nitric oxide, IL-1 β, TNF-α (Hamby et al., 2008; Johnson et al., 2015) which are able to regulate the neuronal and synaptic transmission. (Donzis and Tronson, 2014; Pascual et al., 2012). TNF-α produced by activated glial cells can directly induce RGC apoptosis, or indirectly through nitric oxide and endothelin-1 (Santello and Volterra, 2012). It is to remember how anti-TNF therapy has proven effective in protecting RGC from TNF-α-induced apoptosis (Hong et al., 2009).

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging The neuroinflammatory reaction can eventually result in neuronal death (Lo´pez-Vicario et al., 2016). It is known that brain aging is accompanied by low-grade chronic inflammation (Di Benedetto et al., 2017) and a decreased expression of the anti-inflammatory interleukins
10 (IL-10);
4 (IL-4) and brain derived neurotrophic factor (BDNF) (von Bernhardi et al., 2010). With age, the microglial changes lead to increasing of immune responses, decreasing of synaptic plasticity and increasing of neurodegeneration (Norden et al., 2015). Furthermore, mitochondria alterations are accompanied by a decrease in the potential of mitochondrial membrane in neurons (Xiong et al., 2004); this leads to reduced ATP synthesis, alteration of redox homeostasis, and alteration of the calcium gradient of the mitochondrial membrane and consequent impairment of calcium reserves (Nicholls, 2004). In conclusion, neuroinflammation is associated with alteration of the blood brain barrier and neurodegeneration, that can be explained by the fact that aging is probably related to an increase in the NF-κB pathway (Zhang et al., 2013). The cytokines produced can therefore cross the BBB and trigger neuroinflammation (Freitas et al., 2017). Interesting molecules are the polyunsaturated fatty acids n-3 (PUFA) because they have anti-inflammatory properties (Calder et al., 2017) and they also influence the properties of the cell membrane and in the brain they influence synaptic plasticity, neurogenesis, synaptogenesis and neurite growth. Furthermore, being present in the membranes of retinal cells, it also affects vision (Sacca` et al., 2019). However, the main n-3 LC-PUFA is docosahexaenoic acid (DHA), which represents 12–14% of total fatty acids in the brain (McNamara and Carlson, 2006) and has key-regulator functions in inflammation, indeed, if the consumption of omega-3 is low or if a defect in their metabolism is perceived, an increase in neuroinflammation occurs, enhancing the risk of neurological disorders (Dantzer et al., 2008). One mechanism has been proposed to explain the resolution of inflammation is the synthesis of SPM (resolvins, protectins, maresins) (Barden et al., 2016). SPMs, in fact, promote a return to homeostasis through their both anti-inflammatory and pro-resolutive effects (Serhan, 2014; Serhan et al., 2002). Therefore, they down-regulate pro-inflammatory cytokines and up-regulate anti-inflammatory cytokines as well as promote the phagocytosis both cellular debris and dead cells (Joffre et al., 2020). SPMs are synthesized from DHA and EPA, which are transformed by membrane fatty acids in bioactive lipid mediators from phospholipase A2, or from cyclooxygenase or other enzymes (Massey and Nicolaou, 2013). There are numerous reasons why omega-3s have a rationale in the course of glaucoma. Neuro-inflammation is only one reason, however what appears to be very important is endothelial dysfunction. Endothelial dysfunction occurs in glaucoma and affects the conventional outflow pathway (Sacca` and Izzotti, 2014), indeed, from the functional point of view the TM endothelium behaves like that of a small vessel (Sacca` et al., 2012). The ability to defend against oxidative insult decreases in the elderly probably in connection with a decrease in the activity of SOD, a key enzyme for the neutralization of H2O2 (De La Paz and Epstein, 1996).

7 Conclusions

Trabecular meshwork of glaucomatous subjects, following oxidative stress, undergoes mitochondrial deletions (Izzotti et al., 2011), which leads to the functional decay of the endothelial cells of the trabecular meshwork and to an alteration of their extracellular matrix, to the malfunction of the trabecular tissue, to a subclinical inflammation and to changes in the extracellular matrix and cytoskeleton and finally to the alteration of its motility (Sacca` and Izzotti, 2014). From here the biological signals to the head of the optic nerve start, which activate the glia first and then the apoptosis of the retinal ganglion cells (Sacca` et al., 2016a). Tourtas et al. (2012) found that omega-3 and -6 fatty acids contribute to the abolition of the formation of H2O2 mediated by the nuclear NF-κB pathway or a metabolic pathway useful to protect cells from OS (Wang et al., 2001). Furthermore, polyunsaturated fatty acids and in particular omega-3 PUFAs also have an effect on the trabecular matrix, preventing its accumulation (Tourtas et al., 2012). Also on rats this diet produces a decreased glial cell activation induced by the increase of intraocular pressure (Schnebelen et al., 2009). When the oxygen level drops with age the photoreceptors are more sensitive to oxidative damage (Jarrett and Boulton, 2012) polyunsaturated fatty acids maintain the integrity of the membranes and in particular of the discs of the external segment of the rods (Gibson and Brown, 1993), demonstrating that they contrast the lesion and/or the pro-inflammatory response to restore the homeostasis of retinal cells (Bazan, 2006). In other words, this supplementation appears to have at least a prophylactic effect on glaucomatous disease.

7 Conclusions The mechanisms underlying the loss of RGC include oxidative stress, ischemia, neurotoxicity and, as above reported, many other molecular mechanisms. Neuroprotection is given by a therapeutic target in which ganglion cells and their axons are protected from damage. Modern pharmacology is trying to develop new molecules or enhance already known molecules in order to improve glaucoma therapy or to implement antihypertensive therapy with a neuroprotective or even neuroregenerative action. We leave out to mention stem cells and their experimental use in the treatment of glaucoma, because it is out of the focus of this review, but their use in support of RGC and in axonal regeneration appears very promising. Other methods also appear to be viable, such as the use of neurotrophic factors such as BDNF which increases the survival of RGCs (Weibel et al., 1995) or the extracellular vesicle therapy which involves a real multifactorial treatment. In fact these vesicles act as mediators of cell signaling and are able to supply miRNAs to the receiving cells thus modulating their gene expression (Mead and Tomarev, 2020). The search for bioactive compounds with a neuroprotective effect is of particular interest, and in particular those capable of influencing pro-inflammatory and pro-oxidant mediators and therefore capable of contrasting chronic diseases such as glaucoma. In this regard, substances capable of modulating the Nrf2 pathway and inhibiting NF-κB, such as

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CHAPTER 7 Molecular event from trabecular meshwork to retinal gaglion cells in aging Berberine (Deng et al., 2020) or salvianoic acid (Fu et al., 2018) or Helenalin (Widen et al., 2018) have a therapeutic interest. In conclusion, we can state that the availability of new experimental platforms capable of highlighting new biomarkers or early molecular mechanisms in glaucomatous damage will give the research new input to extend their focus also to antihypertensive therapies going beyond the neuroprotective ones.

Acknowledgments Dr. Stefania Vernazza was supported by the Italian Ministry of Health and by Fondazione Roma, Rome, Italy.

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CHAPTER

Effects of caloric restriction on retinal aging and neurodegeneration

8

Annagrazia Adornettoa, Luigi Antonio Morronea, Andrea Satrianoa, Maria Luisa Lagana`a, Ester Licastroa, Carlo Nuccib, Maria Tiziana Corasanitic, Paolo Tonind, Giacinto Bagettaa, and Rossella Russoa,* a

Preclinical and Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy b Ophthalmology Unit, Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy c School of Hospital Pharmacy, University "Magna Graecia" of Catanzaro and Department of Health Sciences, University “Magna Graecia” of Catanzaro, Catanzaro, Italy d Regional Center for Serious Brain Injuries, S. Anna Institute, Crotone, Italy *Corresponding author: Tel.: +39-0984-493026, e-mail address: [email protected]

Abstract Glaucoma is the most common neurodegenerative cause of irreversible blindness worldwide. Restricted caloric regimens are an attractive approach for delaying the progression of neurodegenerative diseases. Here we review the current literature on the effects of caloric restriction on retinal neurons, under physiological and pathological conditions. We focused on autophagy as one of the mechanisms modulated by restricted caloric regimens and involved in the death of retinal ganglion cells (RGCs) over the course of glaucoma.

Keywords Caloric restriction, Autophagy, Glaucoma, Retina, Neurodegeneration, Aging, SIRT1, AMPK

1 Introduction Caloric restriction and fasting are considered the most effective interventions to prevent age-related decline, promote longevity and increase resistance to stress in a wide variety of species, from yeast to primates (Fontana and Partridge, 2015). Accumulating evidence suggests that caloric restriction offers protection in many pathological conditions including diabetes, cancer, heart disease and, in particular, Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.07.005 © 2020 Elsevier B.V. All rights reserved.

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CHAPTER 8 Caloric restriction and retina

may prevent age-related neuronal loss and neurodegenerative diseases (Loos et al., 2017; Ntsapi and Loos, 2016). Restricted caloric regimens attenuate the neurodegeneration in mouse and primate models of Parkinson’s disease (Bayliss et al., 2016; Maswood et al., 2004), delay the onset of symptoms and reduce accumulation of amyloid and tau hyperphosphorylation in the brain of animal models of Alzheimer’s disease (Halagappa et al., 2007; Mouton et al., 2009). Short-term pre-operative fasting reduces infarct volume after severe focal stroke (Varendi et al., 2014) and intermittent fasting preserves neuronal integrity and improves functional recovery in a rat model of cervical spinal cord injury (Plunet et al., 2008). Despite neurodegenerative disorders differ in etiology, affected areas, pathological evolution and relative pattern of symptoms, most of them are age-dependent and associated with signs of cell senescence (Baker and Petersen, 2018); this is also true for ocular neurodegenerative diseases, like diabetic retinopathy, age-related macular degeneration (AMD), retinitis pigmentosa and glaucoma, for which age is considered one of the main risk factors (Quigley, 2011). Notwithstanding the amount of data supporting the beneficial effects of caloric restricted regimens in Central Nervous System (CNS) disorders (Loos et al., 2017; Ntsapi and Loos, 2016), evidence regarding the effects of caloric restriction in preventing or slowing the progression of retinal neurodegenerative diseases, and in particular glaucoma, are still limited. The cellular pathways involved in the beneficial effects exerted by restricted caloric regimens (i.e. energy production and utilization, autophagy, reactive oxygen species (ROS) production, insulin response, inflammatory response) (Ungvari et al., 2008) are all involved in the cascade of events leading to the death of retinal neurons in ocular degenerative disorders (Almasieh et al., 2012; Pietrucha-Dutczak et al., 2018). This suggests that, for preventing or slowing glaucomatous neurodegeneration and other age-related ophthalmic disorders, caloric restriction and fasting could be a possible strategy to be associated with current pharmacological therapies. Here we review evidence on the effects of restricted caloric regimens in retina aging and neurodegeneration. The focus of the review is centered on autophagy, a mechanism modulated by caloric restriction and involved in the death of retinal ganglion cells (RGCs), the subtype of neurons that selectively degenerates and dies in glaucoma.

2 Glaucoma: An ocular neurodegenerative disease The term glaucoma stands for a spectrum of optic neuropathies characterized by a slow and progressive degeneration of RGCs (Casson et al., 2012). The loss of RGC axons leads to the thinning of the retinal nerve fiber layer and the typical excavation of the optic nerve head with consequent functional defects (Quigley, 2011). This neurodegenerative process may extend into the lateral geniculate nuclei and the visual cortex, suggesting the involvement of central areas in the development and progression of the optic neuropathy (Nucci et al., 2016).

2 Glaucoma: An ocular neurodegenerative disease

In its various subtypes (primary open angle glaucoma, POAG; primary angle closure glaucoma, PACG; normal tension glaucoma, NTG; etc.), glaucoma is a worldwide leading cause of irreversible blindness. It has been estimated that more than 60 million people were affected by glaucoma in 2010 with 8.4 million being bilaterally blind (Quigley, 2011). A more recent analysis provided an up-to-date estimation on the global burden of glaucoma calculating that, by 2040, the number of people (aged 40–80 years) affected by glaucoma is expected to reach 111.8 million (Tham et al., 2014). The prevalence of the disease varies, depending on the ethnicity (with higher prevalence in people residing in Asia and Africa), and the clinical manifestation and progression rate significantly differ among patients. Among the multiple risk factors for glaucoma, high intraocular pressure (IOP) is recognized as one of the main and the only pharmacologically modifiable. However, this concept has been refined considering that IOP changes may be more relevant than the absolute IOP value. Furthermore, a subset of glaucoma, termed normal tension glaucoma (NTG), develops in patients with IOP values in the physiological range suggesting that the link between retinal neurodegeneration and high IOP is not straightforward and/or the pathogenesis of each subtypes of the optic neuropathy might be different. This last observation is also supported by the complex genetic basis of glaucomas. Indeed, different gene mutations have been linked to glaucoma phenotypes, although these account for a small portion of cases and there are not gene-based therapies available. Genome-wide association studies (GWAS) identified 74 genomic loci associated with the risk to develop POAG and 8 for PACG (Choquet et al., 2020; Wiggs and Pasquale, 2017). Rare mutations involving the OPTN (optineurin) and TBK1 (tank-binding protein1) genes are linked to early-onset familial NTG and account for 2–3% of NTG (Aung et al., 2005; Fingert et al., 2016). MYOC (myocilin) mutation accounts for 8–36% of juvenile open angle glaucoma (JOAG) and 2–4% of adult-onset POAG (Souzeau et al., 2013; Wiggs et al., 1998). Beside high IOP, aging is considered the main risk factor for developing the disease. Indeed, glaucoma prevalence for either open-angle and angle-closure glaucoma increases with age. The worldwide age-standardized prevalence in the population aged 40 years and older is about 3.5% (Jonas et al., 2017) and a meta-analysis of population-based studies reported an odds ratio for primary open glaucoma of 1.73 (95% CI 1.63–1.82) for each decade increase in age beyond 40 years (Tham et al., 2014). However, it may also be taken into account that, since the disease is painless and patients often remain asymptomatic even in the advanced state of the disease, the incidence of POAG in younger people may be underdiagnosed and, therefore, underestimated. The molecular links between the known risk factors and the degeneration of RGCs are still unclear; mechanical stress, axonal injury (Howell et al., 2013), alteration of neurotrophic factors’ transport and signaling (Chitranshi et al., 2018), excitotoxicity (Russo et al., 2009), oxidative stress (Tang et al., 2019), mitochondrial dysfunction (Kamel et al., 2017), autoimmunity (Wax, 2011), inflammation (Russo et al., 2016), reduced or altered blood supply (Cherecheanu et al., 2013)

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and malfunctioning of endogenous RGC survival pathways (Pietrucha-Dutczak et al., 2018) have all been considered as participants to the cascade of events leading to RGC loss. Each of these pathways has been identified as a potential target for RGC neuroprotection or neuroenhancement (Baltmr et al., 2010). Despite the plethora of in vitro and in vivo promising results, none of these has led to new therapies, yet other than lowering IOP (Cohen and Pasquale, 2014). However, hypotensive drugs (i.e. beta-blockers, prostaglandin analogues, alfa-agonist, carbonic anhydrase inhibitors and cholinergic drugs) and/or surgical outflow procedure are not able to stop or reverse the optic neuropathy but delay the progression of the disease. Therefore, there is need and space for IOP-independent strategies that might include specific eating patterns that have shown to be able to slow down neurodegenerative processes through the re-setting of key neuroprotective pathways.

3 Caloric restriction and fasting in brief Caloric restriction and fasting are two different eating patterns. Caloric restriction is defined as a reduction of average daily caloric intake, between 10% and 40%, without malnutrition and without affecting the intake of essential nutrients like vitamins and minerals (Bales and Kraus, 2013). Fasting refers to the deprivation of food and may or may not include a caloric restriction during the non-fasting periods (Longo and Mattson, 2014). For both caloric restriction and fasting there are several applicable regimens in terms of time, length and type of restrictions and fasting can be part of a caloric-restricted diet. The reduction of energy intake results in, but is not limited to, modulation of ATP/ADP and NADPH/NADP+ ratio, depletion of acetyl-CoA, downregulation of the insulin-like growth factor-1 (IGF-1)/insulin pathway and reversal of dysglycemia (Lee et al., 1999; Spindler, 2001; Walford et al., 1999). These molecular changes translate in the induction of autophagy, improvement of mitochondrial function, activation of sirtuins, reduced oxidative stress and inflammation (Bagherniya et al., 2018; Gredilla and Barja, 2005; Haigis and Guarente, 2006; Lopez-Lluch et al., 2006; Ye and Keller, 2010). Therefore, the beneficial effects of dietary restriction on aging (Das et al., 2017) and neurodegeneration (Maalouf et al., 2009) can be attributed to multiple mechanisms.

4 The effect of caloric restriction in retinal aging and neurodegeneration Age-dependent loss of retinal cells has been observed in several species (Dorey et al., 1989; Katz and Robison, 1986; Obin et al., 2000; Weisse, 1995). In particular, in mammals, aging is associated with a decline in retinal cell densities and thickness of retinal layers (Obin et al., 2000) and an age-dependent inherited loss of RGCs has also been reported (Kawai et al., 2001). The loss of RGCs in albino mice and

4 The effect of caloric restriction in retinal aging and neurodegeneration

rats has been estimated in 35–40% over the lifetime, with a loss of 2.3% per month in adult mice and approximately 1.5% per month in rats (Neufeld and Gachie, 2003). An inherited age-dependent loss of RGCs has been also reported in monkeys (Jonas and Hayreh, 2000; Morrison et al., 1990; Sanchez et al., 1986) and humans (Harman et al., 2000; Kerrigan-Baumrind et al., 2000) with a total loss, over the lifetime, which is similar to the one reported for the other species and is approximately 35–40%. This progressive loss of RGCs is likely a contributing factor of the age-related visual deficits associated with retinal dystrophies and ocular neurodegenerative conditions, like glaucoma. Evidence has been accumulated suggesting that restricted dietary regimens can delay retina aging and support retinal neurons viability (Table 1). Data sustaining the hypothesis that this decline can be counteracted by caloric restriction have first been reported by Obin et al. (2000). Age-related retinal loss was studied in 12, 24 and 30 months old rats that received, starting at 16 weeks of age, 40% fewer calories than age-matched animals; caloric-restriction enhanced retinal cell densities and thickness modulating aging in the sensory neurons (Obin et al., 2000). Similarly an age-related decline in all three nuclear layers of the neural retina (outer nuclear layer, inner nuclear layer and ganglion cell layer) was reported in Brown Norway rats by Li et al. (2003) and this effect was attenuated by a restricted dietary regimen that was initiated at 14 weeks of age with a 10% restriction, changed to 25% restriction at 15 weeks and, starting at 16 weeks, maintained at 40% restriction throughout the life of the animals; the study used 2 months old rats as a control (Li et al., 2003). In this study, the reduced cell density in the aging retina was associated with decreased water-soluble proteins, declined level of glutathione, ascorbic acid and of the amino acid taurine; these changes were attenuated by caloric restriction showing that, in the aged retina, reduced oxidative stress and sustained pool of protective factors were involved in the beneficial effect of a restricted dietary regimen (Li et al., 2003). Age not only affects the number of retinal neurons, but it also changes the ability to withstand external stresses. Kawai et al. (2001) reported increased susceptibility of RGCs to ischemic insult in old rats. In this study, caloric restriction, achieved by providing animals with food 3 days per week for 3 months, was neuroprotective against ischemia injury for peripheral RGCs in both young (2-months-old) and old (24-month-old) animals (Kawai et al., 2001). Similarly, Kong et al. (2012) reported that old rat retinas have increased susceptibility to ischemia/reperfusion injury and show an extended loss of RGCs, as compared to young mice; older mice also suffered greater decline in retinal function and higher oxidative stress following high IOP challenge (Kong et al., 2012). When subjected to dietary restriction, old mice (female C57/BL6J, 18 months old) showed a limited decline and a greater recovery of inner retinal function following IOP increase as compared to mice with ad libitum access to food (Kong et al., 2012). Caloric restriction might not only make neurons more resistant to the insult but also contain or suppress retinal glial cells activity that, in turn, affects neuronal survival. Retinas from old mice show increase glial fibrillary acid protein (GFAP) level,

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Table 1 Effect of restricted caloric regimens on retinal neurodegeneration. Animal Species Brown Norway rats (male, young vs old) Albino Fischer rats (male, young vs old) Brown Norway rats (male, young vs old)

Insult None Episcleral vessels cauterization None

Albino Fischer rats (male, young vs old)

Acute IOP elevation

C57/BL6J mice (female, old)

Acute IOP elevation

EAAC1/ C57/BL6J mice

Transgenic model of NTG

C57/BL6J mice (male)

Acute IOP elevation

Dietary regimen

Observations

References

40% fewer calories

" Retinal cell densities and thickness # Senescence # Peripheral RGCs death

Obin et al. (2000)

" Retinal cell densities and thickness # Oxidative stress

Li et al. (2003)

# Central and peripheral RGCs death # GFAP

Kim et al. (2004)

# Oxidative stress " Mitochondrial oxidative Phosphorylation enzyme activity # Oxidative stress " β-hydroxybutyrate levels and histone acetylation # RGCs loss

Kong et al. (2012)

Access to food 3 days per week for 3 months 10% calorie restriction at 14 weeks 25% calorie restriction at 15 weeks 40% calorie restriction from 16 weeks maintained throughout the life of the animal 10% calorie restriction at 14 weeks 25% calorie restriction at 15 weeks 40% calorie restriction from 16 weeks maintained throughout the life of the animal Every other day fasting for 6 months

Every other day fasting

48 h fasting

Kawai et al. (2001)

Guo et al. (2016)

Russo et al. (2018)

5 Autophagy: Mechanism and function

which is considered a marker of reactive gliosis. Notably, in retinas from old/caloric restricted mice gliosis is abrogated in conjunction with reduced retinal damage induced by transient retinal ischemia (Kim et al., 2004). Guo et al. (2016) showed that 7 weeks of every other day fasting suppresses retinal degeneration and ameliorates visual impairment in a mouse model of NTG. More recently, our group has shown that 48 h of fasting prevents RGC loss following an ischemic insult induced by transient elevation of IOP (Russo et al., 2018). In our setting, the neuroprotection afforded by fasting was associated with a reduced activation of the proteolytic activity of the calcium-dependent enzyme calpains (personal communication) and the activation autophagy (Russo et al., 2018). Interestingly, a retrospective cohort study showed that the risk of developing POAG was reduced in diabetic patient taking the hypoglycemic drug metformin, a caloric restriction mimetic (Lin et al., 2015).

5 Autophagy: Mechanism and function Autophagy is an evolutionarily conserved catabolic process by which cellular components are degraded through the lysosomes with the aim to maintain a correct balance in type, amount and size of cytoplasmic constituents (Frake et al., 2015). Autophagy is basically considered a pro-survival stress-response though intensive autophagy may end up in the so called programmed cell death type II (e.g. autophagy-associated apoptosis) (Clarke and Puyal, 2012; Fulda and Kogel, 2015). The latter process, contrary to programmed cell death type I (the classical apoptosis), is caspase-independent and requires the increase of lysosomal enzyme activity (Bialik et al., 2018). Based on the mechanism responsible for the delivery of the substrates to the lysosomes, three forms of autophagy can be distinguished: microautophagy, chaperone mediated autophagy (CMA) and macroautophagy (Li et al., 2012; Parzych and Klionsky, 2014; Xilouri and Stefanis, 2015). In microautophagy, lysosomes are responsible for the sequestration, internalization and degradation of the cytoplasmic cargo throughout a direct invagination of their membrane (Li et al., 2012). CMA, a selective form of autophagy, involves the formation of complexes between proteins bearing a CMA targeting motif (a pentapeptide sequence similar to KFERQ) and chaperones of the Hsp70 family (Cuervo, 2010). These complexes are transported and recognized by the lysosome-associated membrane protein type2A (Lamp2a) at the lysosomal membrane where the substrate proteins unfold, translocate into or to the lumen and are degraded by lysosomal hydrolase (Dice, 2007). Macroautophagy is the most widely characterized form of autophagy and it requires the formation of a double membrane structure that recognizes and engulfs cytoplasmic fragments, proteins and organelles ending in the formation of a vesicle called autophagosome. Mature autophagosomes fuse with lysosomes where their

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internal membranes are degraded together with the cargo and the products are released and recycled into the cytoplasm (Parzych and Klionsky, 2014). A detailed description of the molecular mechanism underlying these pathways is beyond the aim of this work and the authors refer the reader to more appropriated reviews (Yu et al., 2018). Nutritional stress, hypoxia and oxidative stress activate both macroautophagy and CMA, while their activity declines with age (Bejarano and Cuervo, 2010; Kiffin et al., 2004). Evidence supporting a reciprocal interplay between macroautophagy and CMA (so that changes in the activity of one pathway will affect the other) has been reported in cell culture models and whole organisms (Chava et al., 2017; Kaushik et al., 2008; Schneider et al., 2015). Furthermore, in several experimental systems, a sequential, rather than a concomitant activation of these two forms of autophagy can be observed. For instance, under starvation, macroautophagy is rapidly upregulated in liver and cultured fibroblast during the first hours of nutritional stress and reaches the maximum activity in 6 h, while longer starvation period are needed to induce CMA (Cuervo et al., 1995; Massey et al., 2006). Inversely, in presence of misfolded proteins, CMA is activated before macroautophagy (Iwata et al., 2005; Ravikumar et al., 2002). Neurons depend on autophagy for preventing the accumulation of toxic proteins and protein aggregates, which are pathological features of neurodegeneration and aging (Currais et al., 2017; Sweeney et al., 2017). Indeed, abrogation of autophagy triggers proteotoxicity and neuronal death (Boland et al., 2018; Metcalf et al., 2012). Dysfunctional autophagy has been associated with chronic (Nilsson and Saido, 2014; Tanik et al., 2013; Winslow et al., 2010) and acute (Sarkar et al., 2020; Zhang et al., 2013) neurodegenerative conditions and, more recently, alterations of the autophagy pathway have been linked to the pathogenic process leading to RGC death in optic neuropathies (Adornetto et al., 2020). Glaucoma is an age-related disease and the expression of autophagy-related genes and lysosomal function decrease with aging (Hansen et al., 2018); it is conceivable, therefore, that the decline of autophagy efficacy, and the consequent alteration of proteostasis, may play a role in the development and progression of the neuropathy.

6 Autophagy and glaucoma Modulation of autophagy has been observed in several experimental models of glaucoma (Russo et al., 2015). Accumulation of autophagosomal structures and impairment of autophagic flux have been reported in the retina of rats and mice exposed to transient elevation of IOP (Piras et al., 2011; Russo et al., 2011; Wei et al., 2015). In these same models, induction of autophagy by treatment with the mTOR inhibitor rapamycin or prolonged fasting reduced RGCs loss (Russo et al., 2018). Elevation of IOP by laser photocoagulation was associated with impairment of the autophagic flux in RGC axons of rats (Kitaoka et al., 2013) and increase of autophagy related

7 The effect of caloric restriction on autophagy

proteins (e.g. LC3II and beclin-1) and lysosomal activity in the retina of rhesus monkeys (Deng et al., 2013). In a chronic model of hypertensive glaucoma induced by episcleral veins cauterization (EVC), autophagy was significantly activated and its inhibition by 3-methyladenine exaggerated axonal damage (Park et al., 2012, 2018). Upregulation of beclin-1 and LC3II was described in isolated RGCs and whole retinas following optic nerve transection (Kim et al., 2008) and cytoprotective activation of autophagy was reported in axotomized retinas (Rodriguez-Muela et al., 2012). After optic nerve crush, Koch et al. (2010) showed that activation of autophagy in RGC axons participated to axonal degradation; conversely, in this same model Oku et al. (2019) reported an impairment of the autophagy process. In DBA/2J mice, a spontaneous ocular hypertensive model of glaucoma, alteration of mitophagy, a selective subtype of autophagy, was reported in myelinated optic nerve axons (Coughlin et al., 2015). In these same mice, a recent study monitored autophagy in the iridocorneal angle region and retina reporting an overall decline of autophagic flux (Hirt et al., 2018).

7 The effect of caloric restriction on autophagy Basal autophagy occurs in every cell type, regulates the balance between synthesis and degradation of macromolecules and can be further induced by several conditions (i.e. oxidative stress, presence of unfolded/misfolded proteins, infection etc.) (Murrow and Debnath, 2013). In particular, as a nutrient stress-response pathway, reduced availability of nutrients or starvation set a higher adaptive level of autophagy allowing cells to cope with and eventually survive under unfavorable conditions (He et al., 2018). Therefore, caloric restriction and fasting are the most effective, non-genetic and non-pharmacologic, triggers of autophagy and, in several experimental settings, inhibition of autophagy attenuates or prevents the beneficial effect of caloric restriction suggesting that autophagy mediates some of the beneficial effects of restricted dietary regimens (Morselli et al., 2010; Rubinsztein et al., 2011). As a physiological trigger, stimulation of autophagy by caloric restriction is effective in several organs and tissues. However, the autophagic response is not uniform but, rather, organ and cell-specific. It was initially believed that fasting might not be able to induce an autophagy response in the brain (Mizushima et al., 2004) since this relies, under condition of limited nutrient availability, on glucose and ketone bodies supplied by the catabolism activated in peripheral organs (Boland and Nixon, 2006). However, this concept has been reverted by studies reporting evidence of autophagy upregulation in the brain and retina of food-restricted mice (Alirezaei et al., 2010; Chen et al., 2015; Esteban-Martinez and Boya, 2015; Ferreira-Marques et al., 2016; Russo et al., 2018; Yang et al., 2014; Zhou et al., 2015). Caloric restriction and fasting modulate molecular players involved in the regulation and execution of autophagy.

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Upregulation of several autophagy-related modulators was detected in humans following long-term caloric restriction; down regulation of Phosphoinositide 3-kinases (PI3K) and Akt/protein kinase B, upregulation of the pro-autophagic transcriptional factors FOXO and some downstream transcripts inducing macroautophagy (i.e. beclin-1 and LC3) were also observed (Mercken et al., 2013; Yang et al., 2016). Caloric restriction, by increasing the AMP/ATP ratio, activates the AMPactivated kinase (AMPK) (Canto and Auwerx, 2011) which is also the target of several known caloric restriction mimetic drugs (i.e. metformin, resveratrol, curcumin) (Madeo et al., 2019). AMPK promotes autophagy through inhibition of the mammalian target of rapamycin (mTOR) and direct activation of ULK1, a critical kinase governing the cascade of events triggering autophagy (Alers et al., 2012; Egan et al., 2011; Kim et al., 2011). Furthermore, AMPK promotes lysosomal biogenesis via increased transcription factor EB (TFEB) activity (Phillipson, 2017) and activation of FOXO3-mediated transcription of proteins involved in macroautophagy (Mihaylova and Shaw, 2011). The serine/threonine kinase mTOR is the master negative regulator of autophagy and the converging point of several autophagy modulators (i.e. AMPK, PI3K/Akt) (Jung et al., 2009). Inhibition of the mTOR complex 1 (mTORC1) is involved in the induction of autophagy through caloric restriction (Blagosklonny, 2010) and it is key for the enhanced longevity and reduced senescence reported in cellular and animal models exposed to reduced nutrient availability (Pani, 2011; Xu et al., 2014). TORC1 inhibits autophagy by preventing the formation of the autophagosome through the hyperphosphorylation of the autophagy related genes Atg13 and ULK1 (Meijer et al., 2015). Also, TORC1 phosphorylates TFEB (a master regulator of lysosome biogenesis) on the lysosomal membrane preventing its translocation to the nucleus (Martina et al., 2012). Therefore, mTORC1 inhibition by nutrient deprivation reduces TFEB phosphorylation and promotes the expression of lysosomal genes (Settembre and Ballabio, 2011; Settembre et al., 2012). Sirtuins (SIRTs) are nicotinamide adenine dinucleotide (NAD+)-dependent lysine deacetylase playing a central role in autophagy and aging (Satoh et al., 2017). SIRTs have been identified as the most ubiquitous target of caloric restriction in all animal models, suggesting that these enzymes play a major adaptive role (Cohen et al., 2004; Guarente, 2013; Qiu et al., 2010). The mammalian sirtuin family comprises seven members (SIRT1-7) with different localization and function (Houtkooper et al., 2012). Nutrient depletion increases the level of SIRT1 (Cohen et al., 2004); SIRT1 deacetylates essential components of the autophagy machinery, including Atg6, Atg7 and Atg8 (LC3) inducing autophagy (Lee et al., 2008). In particular, deacetylation of nuclear LC3 drives autophagy induction under starvation (Huang et al., 2015). SIRT1 also regulates the acetylation status and transcriptional activity of FOXOs, which in turn modulate the transcription of autophagy-related genes like RAB7, a GTPase crucial for autophagosome maturation (Hariharan et al., 2010). Furthermore SIRT1 may indirectly induce autophagy by activation of AMPK and inhibition of mTOR pathway (Guo et al., 2011). SIRT1 has been

References

shown to play a key role in the neuroprotection mediated by caloric restriction (Chen et al., 2008) and to exert neuroprotective effects on RGCs (Kim et al., 2016). Indeed, overexpression of SIRT1 or oral treatment with resveratrol, a SIRT1 activator, prevented RGCs loss in an optic nerve crush injury model (Zuo et al., 2013).

8 Conclusion Several evidence suggest that maintaining an appropriate level of autophagy is key in the mitigation of age-related pathologies. Caloric restriction is the most effective, non-genetic, trigger of autophagy and an expanding body of data indicates that restricted diet regimens exert neuroprotective effects. Although the role of autophagy in the degeneration associated with glaucomatous neuropathy is still controversial, modulation of this catabolic pathway is a recurring response in insulted RGCs. Furthermore, the data produced so far suggest that caloric restriction exerts neuroprotective effects in experimental models of glaucoma. This concept is further supported by the RGCs neuroprotection afforded by several caloric mimetic drugs (i.e. resveratrol, rapamycin, metformin, curcumin, spermidin etc.). Beside autophagy, improving metabolic factors and mitochondrial function, activating sirtuins and reducing inflammation are other mechanisms likely playing a role in neuroprotection observed in the retina under restricted caloric regimens. Therefore, although further research is needed, caloric restriction might represent a potential, supportive, intervention for neuronal survival in retinal neurodegenerative disorders like glaucoma, where currently available therapies are not sufficient to halt or delay the progression of the disease.

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Is stagnant cerebrospinal fluid involved in the pathophysiology of normal tension glaucoma

9

Hanspeter Esriel Killera,b,* a

Department of Ophthalmology, Kantonsspital Aarau, Aarau, Switzerland b Center for Biomedicine University of Basel, Basel, Switzerland *Corresponding author: Tel.: +41-79-5600011, e-mail address: [email protected]

Abstract Current concepts of the pathophysiology of normal tension glaucoma (NTG) include intraocular pressure, vascular dysregulation and the concept of a translaminar pressure gradient. Studies on NTG performed with cisternography demonstrated an impaired cerebrospinal fluid (CSF) dynamics in the subarachnoid space of the optic nerve sheath, most pronounced behind the lamina cribrosa. Stagnant CSF might be another risk factor for NTG.

Keywords Normal tension glaucoma, Cerebrospinal fluid, Optic nerve sheath compartment syndrome

Glaucoma is the most frequent disease of the optic nerve worldwide (Thylefors and Negrel, 1994). It is characterized by optic disk excavation (which is considered specific), visual field defects and loss of visual acuity. Elevated intraocular pressure (IOP) is an established risk factor for this potentially blinding disease. Intriguingly, however, larger studies showed that IOP is not necessarily elevated in all patients with a typical glaucomatous optic disk morphology and corresponding visual field defects. This is the case in up to 40% of glaucoma patients in the Western hemisphere und for more than 90% in the Eastern hemisphere (Cho and Kee, 2014; Klein et al., 1992; Sommer, 1999). Alternative mechanisms leading to glaucomatous optic nerve damage have therefore been investigated and discussed in the literature. Among them range vascular dysregulation (Flammer et al., 2002), autoimmune processes (Pache and Flammer, 2006), translaminar pressure gradient related (Jonas et al., 2016) and

Progress in Brain Research, Volume 256, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2020.06.004 © 2020 Elsevier B.V. All rights reserved.

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most recently a disturbed cerebrospinal fluid (CSF) dynamics in the setting of the optic nerve sheath compartment syndrome (Killer and Subramanian, 2014; Killer et al., 2012; Hao et al., 2020). Several diseases of the central nervous system (CNS) that have already been linked to CSF malfunction, among dem Alzheimer’s disease, Parkinson’s disease and normal tension hydrocephalus (Giorgio et al., 2018; Gupta and Y€ucel, 2007; Lai et al., 2017; Minosse et al., 2019; Silverberg et al., 2003). Panta rhei, everything flows. Flow indeed is essential for all biological processes. There is virtually no live without flow. Blood flow may be the best example to illustrate this point. Stagnation of blood flow leads to thrombosis, stroke, heart attack and anterior and posterior ischemic optic neuropathy. In the same way as blood that transports oxygen, proteins and minerals to tissue, cerebrospinal fluid (CSF) is a transport medium that supplies proteins, peptides, glucose and minerals to the central nervous system (CNS), the brain spinal cord and the optic nerve, the later which anatomically and functionally represents a white matter tract of the brain. CSF further functions as an important clearing pathway for metabolic waste products from the CNS and thereby helps to maintain metabolic homeostasis within the entire CNS, including the spinal cord and the optic nerve (Davson et al., 1987; Sakka et al., 2011). In order to accomplish its multiple function, CSF like blood, needs to flow. Only in a dynamic mode CSF can supply nutrition to neurons, axons and glia cells. And only when in flow it can serve as a sewage system for metabolic waste, thereby cleaning the brain—and the optic nerve—from toxic metabolites. Davson therefore considered the CSF to be a “sink” that removes solutes from the CNS (Davson et al., 1987). CSF is a clear transparent fluid with a total volume of around 124–150 mL that are recycled three to five times within 24 h (Liu et al., 2020). The main site of production is considered to be the choroid plexus in the lateral, third and fourth ventricles. Newer research demonstrated that up to 30% of the CSF stems from the ependymal surface. From the lateral and the third ventricle it flows via the Sylvian aqueduct into the fourth ventricle, the cisterns and the subarachnoid cranial spaces of the brain and the optic nerve (Liu et al., 2020). Absorption of CSF was thought for a long time to take place mainly in the arachnoid granulations. More recent research demonstrated that there is also a strong involvement of lymphatics in CSF drainage (Boulton et al., 1998; Brinker et al., 2014; Johnston, 2003; Johnston et al., 2004; Koh et al., 2005; Zakharov et al., 2003). The optic nerve is a white matter tract of the brain and as such surrounded by CSF as well. CSF enters the subarachnoid space (SAS) of the optic nerve from the suprasellar cistern via the optic canal. The SAS of the optic nerve resembles a cull the sac that ends blind behind the lamina cribrosa. The optic nerve can be divided into the canalicular, the intra orbital and the retrolaminar (bulbar) portion (Killer et al., 2003). The optic nerve—like the brain and the spinal cord—is covered by a meningeal layer, the dura, arachnoid and pia mater. The arachnoid and the pia layers are covered by a layer of meningothelial cells (MECs) that are in direct contact with CSF and they form a barrier between CSF and tissue (Li et al., 2013; Zeleny et al., 2017).

Stagnant cerebrospinal fluid in normal tension glaucoma

The SAS is far from being empty as suggested on MRI images. It comprises a variety of trabeculae, pillars, septae and velum like structures that show different morphological characteristics in the different optic nerve portions (Killer et al., 2003). The amount of trabeculae and septae in the SAS of the ON is variable according to their location. In areas with very large numbers of trabeculae and septae they can form small compartments within the SAS itself. Just as the arachnoid and the pia layer, the trabeculae and septae are covered by (MECs) (Figs. 1 and 2).

FIG. 1 Scanning electron microscopy of two different regions in the subarachnoid space of human optic nerves. (A) Narrow and heavy trabeculated area close to the optic canal. (B) Subarachnoid space close to the lamina cribrosa.

FIG. 2 (A) Scanning electron microscopic image of trabecel in the subarachnoid space covered by meningothelial cells. (B) Transverse transmission electronic microscopy of trabecel. Note menigothelial cell cover. Inner part of the trabecel displays collagen fibrills.

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Next to their structural mechanical function, MECs are involved in important physiological functions (Fan et al., 2012; Li et al., 2013; Royer et al., 2013; Zeleny et al., 2017). In vitro studies demonstrated that MECs are involved in phagozytosis of bacteria and apoptotic cells bodies (Royer et al., 2013). In addition, they exercise a secretory function demonstrated among others by their interleukin-6, CXCL10 and CCL5 secretion (Fan et al., 2012; Royer et al., 2013). MECs demonstrate remarkable quality to react to mechanical changes in their environment which is demonstrated by their ability to react with growth and proliferation to an increase of the surrounding fluid pressure (Xin et al., 2011). CSF movement and flow within and around the brain is still only poorly understood. CSF movement can basically be categorized in bulk flow and pulsatile flow (Brinker et al., 2014; Liu et al., 2020). Bulk flow is considered unidirectional and is depending on the amount of newly produced CSF, while pulsatile flow is connected to the cardiac cycle and pulmonary action it is considered to have bidirectional qualities (Brinker et al., 2014; Greitz et al., 1991; Milohart, 1972). As a result of the volume gradient between the intracranial and the CSF volume and the volume in the SAS of the ON, CSF moves from the optic canal in the direction of the lamina cribrosa. A reversal of the direction of flow against the volume gradient of seems unlikely for bulk flow. This raises the question about how CSF can be recycled within this anatomical cull the sac under this condition? The obvious answer is that there must exist an outflow pathway for CSF out of the SAS. Histological studies in humans and sheep demonstrated lymphatic vessels within the dura of the meninges (Killer et al., 1999). Some of these lymphatics show a direct contact with the SAS (Fig. 3). Dural lymphatics therefore seem to be a good candidate for an CSF outflow pathway from the SAS of the optic nerve. In order for CSF dynamics to be functional, inflow and outflow need to be in balance. If influx exceeds outflux in the optic nerve SAS, the nerve sheath distends

FIG. 3 (A) Dura mater of optic nerve sampled behind the lamina cribrosa. Tracer injected into the subarachnoid space presents in lymphatic intradural vessels. (B) Dye filling up the subarachnoid space and enters lymphatic vessels.

Stagnant cerebrospinal fluid in normal tension glaucoma

according to the compliance of the optic nerve sheath, thereby most likely compressing the lymphatic vessels that do not have a muscular support to prevent their collapse. Unfortunately, in such a setting lymphatics may cease to function as a necessary outflow system for CSF, and thus facilitate the development of an optic nerve compartment syndrome. Increased pressure in the SAS results in compression of axoplasmic flow that manifests in the back of the eye as papilledema (Hayreh and Hayreh, 1977a,b). According to the traditional understanding CSF is considered to be homogeneous in pressure and content throughout all CSF spaces, e.g., ventricles, cisterns and subarachnoid spaces. This concept has been challenged by clinical observations such as interhemispheric pressure gradients in patients with severe head trauma reported by Mindermann (Mindermann, 1999; Mindermann and Gratzl, 1998). In 1991 Kelman et al. reported a series of patients that presented with papilledema despite a normal intracranial pressure (ICP) measured by lumbar puncture (Kelman et al., 1999). But not only pressure may vary in different locations in the CSF system, as described in patients with arachnoid cysts (Berle et al., 2013). Such findings seriously question the concept of a homogenous CSF pressure and content. In analogy to a surgical condition that occurs typically in the lower limb (compartment syndrome), this condition is now called optic nerve compartment syndrome (ONCS) (Killer and Subramanian, 2014). Such conditions have probably been reported before, but under different names. In 1918 Bane described a patient with a “cyst” of the dural sheath of the optic nerve (Bane, 1968). Garrity published a paper on 13 patients with “optic nerve sheath meningoceles” (Garrity et al., 1990). Slamovits published a bilateral case that he called orbital cysts (Slamovits et al., 1989). The common finding in all these cases was the enlargement of the optic nerve sheath. In some of these patients, optic nerve sheath decompression was performed and a “gush” of “crystal clear” fluid was observed exiting the fistula that was surgically created, thus suggesting an elevated “opening pressure” (Garrity et al., 1990). Probably cysts of the dural sheath, optic nerve sheath menigoceles and the optic nerve sheath compartment syndrome are all features of the same underlying process, optic nerve sheath compartmentation (Garrity et al., 1990; Hao et al., 2020; Jaggi et al., 2007; Killer and Subramanian, 2014; Slamovits et al., 1989). The space associated neuro-ocular syndrome (SANS) that can develop in astronauts during and after prolonged space flight is the most recent example in which optic nerve compartmentation is considered to be involved (Lee et al., 2020; Mader et al., 2011). Astronauts with SANS may present with disk edema, choroidal folds, cotton wool spots, nerve fiber layer thickening on OCT, globe flattening and hyperopic shift (Mader et al., 2011). Interestingly papilledema was reported to have persisted up to 21 month in these astronauts even after the ICP measured with lumbar puncture was found to be back to normal (Mader et al., 2015). The pathophysiological process that leads to compartmentation is not yet fully understood. Three components however have been identified that seem to play a role

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in the development of the optic nerve compartment syndrome. First an increased intracranial pressure, either chronic or intermittent. Intracranial mass lesions, inflammatory processes and sinus venous stasis and thrombosis are examples of chronic processes, while Valsalva maneuvers are a typical example of intermittent CSF pressure spikes. Second a preexisting narrow optic canal can be a risk factors for the development of an ONCS. Studies in patients with normal tension glaucoma demonstrated a narrow optic canal on CT reconstructions, compared to a cohort of normals (Pircher et al., 2017). The third component are the menigothelial cells. If exposed to an increased ambient pressure they react with growth and proliferation (Xin et al., 2011). As MECs are ubiquitous in the SAS their growth and proliferation can narrow the patent space, turning it into compartments which in turn will influence CSF flow characteristics. A histological study on optic nerves in glaucoma patients demonstrated proliferation of MECs in the subarachnoid space (Killer et al., 2012; Pache and Flammer, 2006; Pache and Meyer, 2006). Growth and proliferation of MECs caused by chronic or intermittent pressure elevation can narrow the optic canal which than becomes a critical “bottle neck” for CSF (Pircher et al., 2017). MEC proliferation in this “narrow from begin with” region will lead to an increased resistance to CSF in and outflux, turning the SAS into a CSF compartment with a reduced CSF turnover. Such compartmentation has been demonstrated in a cohort of patients with normal tension glaucoma (Killer et al., 2012). All patients that were included in the study demonstrated progressive loss of visual field in spite of repeated normal IOP measurements. Because of progressive visual field loss, imaging of the orbit and brain was performed with computer tomography assisted cisternography. After spinal injection of a contrast agent (Iopamidol, molecular weight 778 Da) the concentration of the contrast agent was measured intracranially and in the subarachnoid space along the optic nerve. The suprasellar cistern and the retrobulbar portion of the SAS served as reference points of interest. Further the optic nerve sheath diameter was measured at its widest site in the bulbar region behind the lamina cribrosa (Jaggi et al., 2012). In all patients examined the distribution of contrast loaded CSF between intracranial and within the optic nerve itself demonstrated a gradient of contrast agent concentration with the lowest concentration of contrast in the bulbar region of the subarachnoid space, thus suggesting the slowest CSF turnover at this specific location (Fig. 4). Further the optic nerve sheath diameter in the retrobulbar region was enlarged in all patients in this cohort, just as measured in patients with elevated pressure (Killer et al., 2012). Both findings are suggestive for a severe disturbance of CSF dynamics caused by optic nerve sheath compartmentation. In addition to computer assisted cisternography, indications for disturbed CSF dynamics in NTG patients were recently demonstrated with a diffusion magnetic resonance imaging sequence that reported on flow ratios of CSF velocity within the parenchyma of the brain, the intracranial subarachnoid space and the subarachnoid space of the optic nerves (Boye et al., 2018).

Stagnant cerebrospinal fluid in normal tension glaucoma

FIG. 4 (A) T2 weighted MRI of patient with normal tension glaucoma. Note “even”distribution of fluid in the suprasellar cistern and in the subarachnoid space of both optic nerves. Both subarachnoid spaces are distended. (B) Computer tomography assisted cisternography in the same patient. Note stop of contrast agent in posterior portion of both optic nerves.

Interestingly the flow ratios of CSF flow was reduced in the SAS of the glaucoma group compared to a sex and age correlated control group of normal. The finding of optic nerve sheath compartmentation is not limited to patients with NTG and papilledema, but has recently also been reported in patients with a history of meningitis, arachnoiditis and spinal disk surgery (Hao et al., 2020). This finding suggest that inflammatory changes in CSF might have caused adhesions within the SAS, thus leading to a partial occlusion most pronounced within the optic canal, finally leading to an optic nerve compartment syndrome. A reduction of CSF flow will result in a deficiency of important nutrients on one hand and in an accumulation of potentially toxic proteins on the other hand. Studies on betatrace protein (L-PGDS)—one of the most abundant proteins in CSF—have demonstrated that an elevated concentration of L-PGDS inhibits proliferation of astrocytes in vitro (Xin et al., 2009). Another study demonstrated a reduction of ATPproduction following an increased concentration of L-PGDS. Further, elevated L-PGDS was shown to contribute to PMA-induced apoptosis (Link and Olsson, 1972; Maesaka et al., 2013; Ragolia et al., 2003). L-PDGS on the other hand was shown to have beneficial effects when functioning as a chaperon (Kanekiyo et al., 2007). CSF sampled during optic nerve sheath fenestration (ONSF) in patients with papilledema and with normal tension glaucoma and compartment syndrome measured significantly elevated L-PGDS concentrations in the CSF of perioptic space of the optic nerve compared to CSF sampled during spinal tap (Killer et al., 2006). Experimental optic nerve sheath compartmentation in sheep resulted in axon destruction most pronounced right behind the lamina cribrosa (Jaggi et al., 2010). Interestingly the axons at the site of where the ligature was placed showed only minimal damage while axons in the bulbar segment where they lack a myelin sheath were most affected. The axons behind the lamina cribrosa display a high metabolic activity

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demonstrated by ATP-ase staining and might therefore be the most vulnerable portion of the optic nerve (Andrews et al., 1999; Bristow et al., 2002). It is therefore conceivable that components of stagnant CSF could have been involved in the axon destruction at this delicate location. There are two principal explanations for elevated concentration of L-PGDS in the compartmented perioptic CSF. A. Impaired recycling and outflow and B. local upregulation of L-PGDS production. In the second case the upregulation might represent the necessity of a chaperon in stagnant CSF with higher concentrations of potentially toxic proteins and peptides. The target proteins itself is not yet identified, but the high concentrations of the “remedy” is an indicator of its existence. Low concentration of the contrast agent in the subarachnoid space is also an indicator of low CSF flow velocity. Velocity was demonstrated to impact protein expression of MECs as they react to the flow characteristics of their surrounding fluid (Neutzner et al., 2019). Studies with MECs in bioreactors were used to demonstrate the mechanosensitivity of MECs to flow velocities. Interestingly RNA sequencing following a reduction of flow velocity demonstrated an upregulation of gap junction proteins, proteins for extracellular matrix. Further proteins involved in endo-lysosomal processes. Among ECM organization proteins were collagens (Type III, IV, XVIII) and laminin components (laminin, LAMB1, LAMA) but also integrins (integrin α). Within the endo-lysosomal pathway upregulated genes belonged to members of the protease (cathepsins A, L and F), galactosidase (β-galactosidase) and mannosidase (α-mannosidase and β-mannosidase) families. An enrichment of downregulated genes was found in the mitochondrial energy metabolic pathway. This finding suggests that a reduced fluid velocity that is related to diminished CSF clearing is a trigger for MECs to express gap junction proteins which strengthen the CSF brain barrier, thereby protecting the nerve tissue from toxic proteins. The important role of MECs also becomes evident in a new study (submitted) on MECs that demonstrate their phagocytotic capacity to remove amyloid beta and alfa-synuclein from their surroundings. Open questions. Compartmentation of the subarachnoid space has been demonstrated in a variety of optic nerve disease such as papilledema, optic atrophy following meningitis and spinal disk herniation, SANS syndrome and normal tension glaucoma. In some patients the optic nerve head is swollen (papilledema) while in normal tension glaucoma it is excavated. In some patients, visual field loss and loss of visual acuity is modest, in some it is severe. At the time being we do not have an explanation for this obvious discrepancies.

1 Summary Conclusion: Normal tension glaucoma is an optic nerve disease that still lacks a conclusive pathophysiological explanation. The focus of CSF on brain and optic nerve is foremost on the effect of pressure. There is growing evidence that not only CSF

References

pressure but also CSF content might be involved in the pathophysiology of NTG (Wostyn et al., 2014). Stagnant CSF might not only play a role in normal tension glaucoma but also in other neurodegenerative disease, such as Alzheimer’s disease and normal tension hydrocephalus (Silverberg et al., 2003). Further research on CSF dynamics and content, not only in the subarachnoid space of the optic nerve, but also in the brain need to be performed to gain deeper insight.

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